Prepared by: Team Leader: Dr. H. B. Vo/E.G.Delgado 7/23/2010. Submitted: Reviewed: Revised: Approved: Team Member: A. M. Espinal Mena 7/23/2010

Transcription

1 HASP Program Flight Readiness Review Document for the Attitude Determination System (ADS) Experiment by Experiments with Quality United In Science (EQUIS) Prepared by: Team Leader: Dr. H. B. Vo/E.G.Delgado 7/23/2010 Team Member: A. M. Espinal Mena 7/23/2010 Team Member: F. O. Rivera Vélez 7/23/2010 Team Member: E.M. Portilla Matías 7/23/2010 Submitted: Reviewed: Revised: Approved: Team Member: J. I. Espinosa Acevedo 7/23/2010 Dr. Greg Guzik 7/23/2010 Institution Signoff Date HASP Signoff Date Team EQUIS i FRR v1.0

2 Change Information Page Title: FRR Document for ADS Experiment Date: 07/23/2010 List of Effected Pages Page Number Issue Date Team EQUIS ii FRR v1.0

3 Status of TBDs TBD Number Section Description Date Created Date Resolved Team EQUIS iii FRR v1.0

4 Table of Contents Experiment by... i Change Information Page... ii Status of TBDs...iii Table of Contents... iv List of Figures... vi List of Tables...viii 1.0 Document Purpose Document Scope Change Control and Update Procedures Reference Documents Goals, Objectives, Requirements Mission Goal Objectives Science Background and Requirements Technical Background and Requirements Payload Design Principle of Operation System Design Electrical Design Software Design Thermal Design Mechanical Design Payload Development Plan Payload Construction Plan Hardware Fabrication and Testing Integration Plan Software Implementation and Verification Flight Certification Testing Mission Operations Pre-Launch Requirements and Operations Flight Requirements, Operations and Recovery Data Acquisition and Analysis Plan Project Management Team EQUIS iv FRR v1.0

5 8.1 Organization and Responsibilities Configuration Management Plan Interface Control Master Schedule Work Breakdown Structure (WBS) Staffing Plan Timeline and Milestones Master Budget Expenditure Plan Risk Management and Contingency Glossary Appendix Appendix A Appendix B Sensors Subsystem Schematic and PCB design Appendix C RTC (DS1306) pseudo code Magnetometer (MicroMag3) pseudo code Accelerometer (SCA3000-D01) pseudo code SD card pseudo code Pre-flight software During flight software Appendix D Team EQUIS v FRR v1.0

6 List of Figures Figure 1: Three axis center mass reference frame and their rotational change definition Figure 2: Accelerometer average values Figure 3: Accelerometer maximum values Figure 4: Gyroscope basic structure and operation Figure 5: Earth's Magnetic Field Figure 6: Magnitude of the earth s magnetic field Figure 7: Parameters of the magnetic field Figure 8: Vector's example of the magnetic field Figure 9: Vector s example of the magnetic field Figure 10: Angles of interest Figure 11: HASP 2006 flight profile Figure 12: Payload trajectory dynamics Figure 13: Angle of translation determination Figure 14: Angle of translation determination Figure 15 Beamwidth shade diameter determination Figure 16: Determining position accuracy Figure 17: Determining position accuracy with orbit decay Figure 18: Plot of typical orbit decay Figure 19: Temperature variation during flight Figure 20: Accelerometers basic principal of operation Figure 21: Gyroscopes basic principal of operation Figure 22: Simplified representation of magnetometer basic operations Figure 23: The DS18B20 Digital temperature sensor Figure 24: DS18B20 Digital Temperature Sensor Diagram (From the DS18B20 datasheet).. 28 Figure 25: Determination of sampling rate by maximum angular velocity Figure 26: ADS System Design Figure 27: Arduino Pro V/8MHz schematic Figure 28: Three Axis Accelerometer schematic Figure 29: Three Axis Magnetometer schematic Figure 30: Three Axis Gyroscope schematic Figure 31: Digital Temperature Sensor schematic Figure 32: MicroSD board schematic Figure 33: Real-Time Clock schematic Figure 34: 9V DC to DC Converter schematic Figure 35: 3.3V Voltage Regulator schematic Figure 36: 5V Voltage Regulator schematic Figure 37: Electrical Design Subsystems Figure 38: Electrical Subsystem Figure 39: Accelerometer Sensor Figure 40: SCA3000 Three axis accelerometer pins Figure 41: Gyroscope Sensor Figure 42: Three Axis Magnetometer Figure 43: Digital Temperature Sensor Figure 44: Real Time Clock Team EQUIS vi FRR v1.0

7 Figure 45: ADS PCB Design Figure 46: Power System Diagram Figure 47: Power Budget Analysis Figure 48: Flight software control flow chart Figure 49:Payload s Top Cover Figure 50: Internal View of the External Structure Figure 51: External Structure Drawing Figure 52: Finite Element Analysis View Figure 53 Finite Element Analysis View Figure 54: Detail drawings of payload Figure 55: Top view payload structure Figure 56: View of punctures on structures Figure 57: Internal Structure Drawing Figure 58: EDAC pin layout Figure 59 Psi Vacuum chamber Figure 60 Chamber where temperature test was taken Figure 61: Shock Test Figure 62 Helmholtz coils Figure 63: Helmholtz coil (X) vs MM3 (Y) Figure 64: Linear Fit Figure 65: WBS- Work Breakdown Schedule Figure 66: Risk Management Cycle Figure 68: Heat Loss Analysis Figure 69: External Convention Team EQUIS vii FRR v1.0

8 List of Tables Table 1: Traceability Matrix Table 2: Pins for the Pro Table 3: Power Requirements Table 4: Bytes Description Table 5: SPCR bit specification Table 6: RTC registers and address map Table 7: Axis Select Table 8: SCA3000 registers Table 9: Electronic temperature limits Table 10: Effects of the surface treatment in the emisivity Table 11: Alloy Selection Table 12 Polyester Properties Table 13: Mass Budget Table 14: EDAC 516 pins function and color code Table 15 Example of raw data from the MM Table 16: Calibration values Table 17: Equations to correct offset Table 18: Quadrant determination Table 19: DS18B20 versus HOBO temperature measures Table 20: Materials Acquirement & Costs Table 21: Risk Management & Contingency Team EQUIS viii FRR v1.0

9 1.0 Document Purpose This document describes the final designs for the Attitude Determination System (A.D.S.) experiment by Team EQUIS for the HASP Program. It fulfills part of the HASP Project requirements for the Flight Readiness Review (FRR) to be held July 23, Document Scope This FRR document specifies the scientific purpose and requirements for the A.D.S. experiment and provides a guideline for the development, operation, and cost of this payload under the HASP Project. The document includes details of the payload design, fabrication, integration, testing, flight operation, and data analysis. In addition, project management, timelines, work breakdown, expenditures, and risk management is discussed. Finally, the designs and plans presented here are preliminary. 1.2 Change Control and Update Procedures Changes to this FRR document shall only be made after approval by designated representatives from Team EQUIS and the HASP Institution Representative. Document modification requests should be sent to Team members, the HASP Institution Representative and the HASP Project. 2.0 Reference Documents The following websites are references for relevant scientific information as well as sources of electronic components, their specifications, part numbers, products availability, and prices. Bibliography: [1] (USRA), R. N. (2002, November 25). Astronomy Picture of the Day. Retrieved May 24, 2010, from Astronomy Picture of the Day Web site: [2] Analog Devices Corporate Headquarters. (2008, September). Analog Devices. Retrieved May 24, 2010, from Analog Devices Web site: [3] Arduino Pro. (2010). Retrieved March 28, 2010, from Arduino:Blog: March 28, 2010 [4] Biology Blog. (n.d.). Retrieved May 24, 2010, from Biology Blog Web Site: [5] Field Code. (2008). Retrieved February 3, 2010, from Whatis?com Web site: [6] kowoma.de. (2009, April 19). Retrieved May 24, 2010, from kowoma.de Web site: Team EQUIS 9 FRR v1.0

10 [7] Metrolab Instruments. (2006, October). Metrolab Instruments. Retrieved May 24, 2010, from MetroLab Manufactures of MRI systems: [8] Mystery Class. (2008). Retrieved May 24, 2010, from Mystery Class Journy North Web site: [9] Ritter, M. E. (2009). The Physical Environment an Introduction to Physical Geography. Retrieved May 24, 2010, from seasons.html [10] Sparkfun. (2003). Retrieved May 24, 2010, from Sparkfun website: [11] Wikipedia (DC-to-DC Converters). (2010). Retrieved April 4, 2010, from Wikipedia Web site: [12]Anderson, B. J., editor, and R. E. Smith, compiler, Natural Orbital Environment Guidelines for Use in Aerospace Vehicle Development, NASA TM 4527, chapters 6 and 9, June [13] T Williams & P Collins, 1997, "Orbital Considerations in Kankoh-Maru Rendezvous Operations", Proceedings of 7th ISCOPS, AAS Vol 96, pp Team EQUIS 10 FRR v1.0

11 3.0 Goals, Objectives, Requirements 3.1 Mission Goal The goal of this project is to develop an attitude determination systems (ADS) prototype, by improving the robustness and accuracy of a previous design (ABITA; Tiger team) in order to obtain relevant data and hands-on experience for a future satellite attitude control and determination system (ADCS). The designing, developing and testing will serve as a stepping stone for a future CubeSat project with the objective to transmit to a ground station the measurement data that has been applied for the terrestrial gamma ray flashes (TGF). Previous CubeSat data will help as a base point for this design. 3.2 Objectives Science Objectives There are four science objectives related to this ADS experiment which are the following: 1. To determine translation and attitude motion of the payload during flight. 2. To obtain the platform s body frame orientation with respect to the body fixed reference frame 3. To measure the Earth s gravitational and magnetic field and the angular momentum of the payload such that the data can be used to determine the orientation of the payload. 4. To measure the heat transfer characteristic during flight and its potential impact on internal and structural components. This attitude information will demonstrate the robustness and effectiveness expected from the proposed requirements for the payload described in this document for tracking purposes. Post processing of this data will confirm the assumption presented in this work to design similar ADS for future small satellite missions Technical Objectives There are technical objectives that are required to learn during this experience. These objectives will be completed during the development of the attitude determination system: 1. Design and connect the sensors such that they can be located in the body frame of the payload to fully determine the attitude motion of the payload. 2. Use different attitude determination algorithms used to determine the attitude motion of the payload such as the Kalman Filter, QUEST and TRIAD to be used as the algorithms to determine the attitude motion 3. Develop graphs and charts related to the translation and orientation of the vehicle as well as the heat transfer in it 4. Reduce the attitude pointing knowledge of the payload to less than 10 degrees of error. Team EQUIS 11 FRR v1.0

12 These objectives provide the desire knowledge to learn how the attitude determination system can be used in an actual mission. 3.3 Science Background and Requirements Science Background The design of the attitude determination system (ADS) for this payload is a midpoint development for a future CubeSat project with the purpose of communicating data about measurements for science missions such as a terrestrial gamma ray flashes (short blasts of gamma rays, which are discharged from the uppermost part of the atmosphere into space 1 ) or other similar science objectives. The intended requirements must be those needed for an effective and almost error free communication of the ADS data for the CubeSat that will be navigating at a height above the Earth s surface as well as the design of the communication system with a suitable main lobe beamwidth. The A.D.S. project will give the opportunity to enhance the chosen technology as well as determine the minimum adjustments that it might need to meet the goal, which is to develop an attitude determination system prototype. The attitude of a spacecraft is its orientation in space. The motion of a rigid spacecraft is specified by its position, velocity, attitude, and attitude motion. The position, acceleration, and velocity quantities describe the translational motion of the center of mass of the spacecraft and can be determined from previously defined spatial frames such as the magnetic field of the Earth and the moment of inertia of the body itself. Moreover, attitude determination is used to change the spacecraft s direction and maintain the spacecraft on-course (Attitude Control System). Attitude analysis can be classified in three types: attitude determination, prediction, and control. Attitude determination is a process of calculating the orientation of an object relative to an inertial reference frame. Attitude prediction is the process of anticipating the future course of the object through the analysis of dynamic models to extrapolate the attitude history. Attitude control is the method of controlling the orientation of the object based on a predetermined data from the sensors; it consists of two areas of control, attitude stabilization and maneuver control, for example a CubeSat project. The orientation of the payload will be determined by comparing its actual three axis body frame (three dimensional orthogonal axes at the payload center of mass) with those of three external vector fields: the Earth s gravitational field, the payload angular momentum, and the Earth s magnetic field. The gravitational field will serve as a reference frame to measure the change of position, velocity and acceleration of the payload. The gravitational field has a constant direction (towards the Earth s center) which allows its use as a trusted reference frame. The change of the payload s center of mass with respect to the Earth s gravitational frame is done by determining the yaw, pitch, and roll of the payload when its acceleration is determined with 1 The gamma rays are presumed to be released by electrons traveling at the speed of light when they scatter off of atoms and decelerate. The mechanism in which the electrons produce TGFs is uncertain; although, it probably involves the build-up of electric charge at the tops of clouds due to lightning discharge. This results in a powerful electric field between the top of the clouds and the ionosphere. (Tim Stephens, UC at Santa Cruz,2005) Team EQUIS 12 FRR v1.0

13 respect to the gravitational field. A single integration of the acceleration will have a result of the payload s velocity (a vector) and a double integration will result in the payload s position with respect to a previous measured point (previous state or reference starting point). Figure 1: Three axis center mass reference frame and their rotational change definition Figure 1 illustrates the rotational movements (roll, pitch, and yaw), which are described in reference to a plane. The movement described is a combination of two-axis (2 dimensional) area and a missing combination of a pair of axis (pitch) is portrayed in the z y plane. The acceleration with respect to the gravitational field will determine the proper acceleration, which is the acceleration detected by the payload within the reference gravitational field. For example, the gravitational field strength is 1g; the proper acceleration of the payload must be obtained by subtracting this 1g to that acceleration sensed. If the velocity is constant the proper acceleration is zero (0). The ABITA project (2008), determined the balloon dynamics during flight by doing the following: comparing acceleration vs. altitude, rotational rate, and translational movement of the payload. The ABITA payload used the gravitational field to determine its acceleration. A known disadvantage of using the aforementioned is that it needs another frame to initialize the spatial model (such as data from a GPS). As a brief description of its basic operation, to measure acceleration is to determine the vibration, or acceleration of motion of a structure. Team EQUIS 13 FRR v1.0

14 Figure 2: Accelerometer average values As it is observed from Figure 2 the average maximum and minimum acceleration that was achieved by the ABITA was approximately 1.6g and -1.2g, respectively. The values shown on Figure 3, repeat at 3g, thus it is considered the maximum average. Figure 3: Accelerometer maximum values In conjunction with measuring the acceleration, the measurement of the moment of inertia is used to determine accurately the attitude of the payload. The angular momentum of the payload and its rate of change, with respect to time, provide information of the payload s orientation state in a repetitive measured time frame. There is an equivalence between the angular momentum at a specific distance from the center of a spinning body (r), the moment of inertia (I), the angular speed ( ), and linear momentum (p) that a body experiments when moving in a straight line at a known velocity (v). The moment of inertia is defined as the resistance of a body to an angular acceleration applied to it. The resistance to the angular acceleration, on any of the 3 rotational axes, can be measured to determine when the body is rotating due to an external applied force. The result of the integral of an angular acceleration Team EQUIS 14 FRR v1.0

15 is the velocity and position of the body. The initial position is obtained by using other reference information, such as that obtained from a Global Positioning System. A gyroscope is a device used to measure the orientation of an object in space, based on the principles of conservation of angular momentum. The simplest way to explain the gyroscope function is to consider the mechanical gyroscope which is essentially a spinning wheel or disk whose axle is mounted on a metal frame and that is free to take any orientation. The metal frame consists of three rings called gimbals. A diagram of this device is illustrated in Figure 4. If the wheel in the center of the frame is not rotating the gyroscope behaves like any other object with respect to gravity, but if the wheel is spinning this behavior changes. When the wheel spins an angular momentum (L) is created with a direction collineal to the axis of rotation. Because of the presence of the angular momentum a resistive force is created. The resistive force resists the changes in the direction of the wheel s rotational axis if the gyroscope is tilted or rotated. If a gyroscope is tipped, the gimbals will try to reorient to keep the spin axis of the rotor in the same direction. If released in this orientation, the gyroscope will rotate maintainig the direction of the rotational axis (i.e. the direction of the angular momentum), this behaivor is known as precession. Precession is a change in the orientation of the rotation axis of a rotating body but without changing the direction of the axis. Figure 4: Gyroscope basic structure and operation The gyroscope commonly selected for payload projects are micro electrical mechanical system (MEMS) gyroscopes, which detect rotational rate about the X (roll), Y (pitch), and Z (yaw) axes. When the gyros are rotated about any of the sense axes, the Coriolis Effect causes a deflection that is detected by a capacitive pickoff. The resulting signal is amplified, demodulated, and filtered to produce a voltage that is proportional to the angular rate. The Coriolis Effect is an inertial force that appears in bodies that possesses two types of motion; a rotational motion and a linear motion. The interaction between the linear and rotational movement produce a linear acceleration of the body in a different direction and that is known as the Coriolis acceleration. The use of an accelerometer and a gyroscope is essential to obtain a more precise data of the inertial reference frame because they provide linear and rotational attitude information. Pure gyroscopic data is used for rotation detection (angular velocity within the inertial frame) with high resolution and quick response. Pure accelerometer data can be used for application for fixed reference frame from gravity as well as linear or tilt movement, constrained to initial position determination. Moreover, the data received from the accelerometer can be processed (mathematically integrated) to obtain the velocity and position of the body from this Team EQUIS 15 FRR v1.0

16 previously reference starting point. Having both gyroscopes and accelerometers we can obtain the motion processing solution of linear movement and rotation at the same time. By tracking both the current angular velocity of the system and the current linear acceleration of the body it is possible to determine the overall attitude, position, and velocity of the body provided by a starting reference point in time (for example, determined periodically from a GPS). The starting point provided by the reference mechanism (GPS) provides for the minimization of the cumulative errors inherent of a sensors system with no external reference frame used when integration is used. The Earth s magnetic field is used as a reference frame for the payload in order to determine attitude. The magnetic field exists due to the movement inside the Earth s liquid in the outer core (mostly compound by iron) that produces an electric current. A dynamo effect is created and it converts the Earth to a very large bar magnet with a magnetic field that goes from the North Pole to the South Pole associated to it. Figure 5 presents a not-to-scale representation of the magnetic field. The HASP mainframe should rise at about 120,000 feet or approximately 36 km navigating through the magnetic field. Figure 5: Earth's Magnetic Field Earth has a magnetic field tilted at about 23.5º with respect to the rotational (physical) axis. The common sensor used to detect this magnetic field reference frame is the magnetometer. The magnetometer that will be used for the A.D.S. project consists of three axes (x, y, and z) that will provide a vector component. The data obtained from this device will be the magnetic field intensity vs. typical values of the Earth s magnetic field that goes from 30,000 nt (in the equator) towards 60,000 nt (in the Poles). Typical values of a magnetometer suitable for this payload are approximately ±1,000,000 nt and ±15 nt of resolution. The magnetic field vector will be obtained by the combination of the measurements of each axis and thus can be projected with respect to the Earth s magnetic field to determine the payload s orientation. In attitude determination systems magnetometers are used because of vector sensing capabilities. They can provide both direction and magnitude of the magnetic field. Team EQUIS 16 FRR v1.0

17 Figure 6: Magnitude of the earth s magnetic field The Earth's magnetic field can be described, at any point and time by a direction and intensity which can be measured. The Earth s magnetic field is a vector field in which at least three components are necessary to represent the field. Commonly the components of the geomagnetic field that are measured are the north (X) and east (Y) components of the horizontal intensity and the vertical intensity (Z). From these elements, all other parameter of the magnetic field can be calculated. A figure that illustrates these parameters is the following: Figure 7: Parameters of the magnetic field The magnetic field s direction is described by the declination (D) and the inclination (I). These two parameters (i.e. D and I), are measured in units of degrees. The declination angle is form between the magnetic north (i.e. x in the plot), and the horizontal intensity or true north. The inclination angle is form between the horizontal intensity and the total intensity field vector. The parameters that describe the field intensity are the total intensity (F), horizontal component (H), vertical component (Z), and the north (X) and east (Y) components of the horizontal intensity. These parameters are normally expressed in units of nanotesla or gauss. The magnetic field parameters measured are used to determine the payload s orientation with respect to the axis directions of the Earth s magnetic field. (i.e. Northward Eastward and Downward in the figure #). To explain the procedure performed to interpret the magnetometer data in order to define the payload s orientation let s consider the following example: Team EQUIS 17 FRR v1.0

18 If the magnetic field measurement obtained at one instant of time during the payload s flight is x=35,000nt, y=-3314nt and z=38,000nt and the data obtained for the standard value of the magnetic field in that earth s region is x = nT, y = nT and z = nT, what is the payload s orientation? p = E = = Figure 8: Vector's example of the magnetic field In this problem the angles formed between the two systems of coordinate axis is what is desired to be determined, since, these angles will define the payload s orientation with respect to the reference frame of the Earth s magnetic field. Considering only the angle formed between the axis z and z it s found out that the angle can be define taking in to account the projection of the component of the magnetic field in the z direction onto the z axis. This procedure is illustrated in the following figure: b z = b z cos Θ z Θ z = cos -1 (b z /b z ) Figure 9: Vector s example of the magnetic field As illustrated above the angle between axes can be determined just by considering the projection of the component with respect to the desired axis. This procedure is repeated until all the axes with respect to one component are considered. To completely define the payload s orientation the angles formed in each axis by each component must be determined. These angles can be determined since the values of the component of the magnetic field intensity are known in both coordinate systems. The angles between the coordinate system that are needed to determine the payloads orientation with respect to the Earth s magnetic field ar shown on Figure 10. Team EQUIS 18 FRR v1.0

19 Figure 10: Angles of interest Therefore three equations are necessary to completely define the payload s orientations since three angle are needed to define the payload s attitude. These equations are: Θ z = cos -1 (b z /b z ) Θ y = cos -1 (b y /b y ) Θ x = cos -1 (b x /b x ) The value of the earth s magnetic field in a certain region of the earth will be provided by simulation software available in the International Geomagnetic Reference Field (IGRF) web page. This simulator only request values of altitude, latitude and longitude to estimate the magnitude and direction of the earth s magnetic field. The latitude, longitude and altitude information will be provided by the GPS on board the HASP platform to perform the analysis post flight. Post processing of the received data might include the use of mathematical and statistical algorithms such as the Kalman Filter, to decrease substantially inherent noise in the data. This allows predicting the real position and orientation of the payload at any moment during flight. The Kalman Filter determines the next state estimation by using average weighted matrices that combines the present state, a mathematical model of the measurement systems and the noise inherent to both, the system and the measurement devices. The position and direction of movement will be obtained by determining the payload s current position, velocity, and acceleration. The x(t), y(t), and z(t)) will be recorded periodically in a pre-defined time rate for the whole flight trajectory (creating a vector matrix of its position, x(t+nt), y(t+nt), z(t+nt), where i stands for the predefined time slot and n stands for a counter with a limit). X x0( t) x1(2t ) x2(3t ) x3(4t)... xn ( t nt) Y y0( t) y1(2t ) y2(3t ) y3(4t)... yn( t nt) Z z0( t) z1(2t) z2(3t ) z3(4t)... zn( t nt) Team EQUIS 19 FRR v1.0

20 A matrix is constructed with the x-y-z axes. Noise suppressor and position predictor algorithms are used with matrix base mathematical operations to recover the real position from the raw data (typical from the sensing elements inaccuracies) and a 3-dimensional trajectory diagram. According to the flight operation plan provided in the HASP website; the platform will launch at a rate of about 1000 feet per minute. Thus, with this ascent velocity is expected that the payload reach the float altitude (i.e. 120,000 feet) in approximately 1 ½ to 2 hours. The actual flight profile for the 2006 HASP flight is shown in Figure 11. Figure 11 is a comparison between a HASP flight (blue curve) and the profile for typical latex, sounding balloon flight (red curve). The vehicle will stay at an altitude (i.e. at the stratosphere) for about 5 to 15 hours before the flight must be terminated to parachute HASP into a safe landing zone. The trajectory expected for the HASP payload, considering Figure 11, can be divided in two phases: that of a turbulent launch and that of a steady and slow dynamic Figure 11: HASP 2006 flight profile behavior. Figure 12 illustrates the payload s trajectory, when the payload ascends up to 120,000 feet in two approximately 2 hours and when it reaches a near constant altitude for a time greater than 15 hours but no more than 18 hours. The first phase data will be used to determine the gradient of temperature in the physical structure of the payload and the possible impact it may have in the performance of the internal electronic components and subsystems. A typical communication link for a small satellite, in LEO (Low Earth Orbit), with an antenna Figure 12: Payload trajectory dynamics beamwidth of 30, a height of 700 km, and an average speed of 7,500 km/s will need an approximate time of 22 minutes to pass over the ground station communication. Team EQUIS 20 FRR v1.0

21 This is justified by developing the following analysis. For an average Earth radius plus the height of the satellite of 7,078 km (6,378 km km) and at the speed of 7,500 km/s the linear displacement in orbit in 1 minute will be of: 7,500m / s 60s 1 1min s 125,000m / min Figure 13: Angle of translation determination In the preceding calculation s stands for a segment of the circumference that the satellite will travel in one (1) minute. Then, the angle of translation is determined as follows (s is approximate as a line but it is really a segment of a circumference): sin s r sin 1 125, ,078,000 Then, at the speed of 7,500 km, the satellite will travel about 1. Figure 14: Angle of translation determination Since the downlink antenna beamwidth chosen is about 30 degrees the angle from the maximum power density center of the mainlobe and the -3 db (half of power density) is 15. In order to assure a robust communication link a 20 angle is chosen. Then the needed minimum accuracy for orientation used will be 10. The downlink antenna beamwidth chosen can also be employ to determine the accuracy of the position desired for this project. To define the position s accuracy two important cases must be considered. One is the movement of a cube sat along its orbit and the second is the effect of the orbit decay in the strength of the downlink communication signal. In order to define correctly the accuracy of the position the most Figure 15 Beamwidth shade diameter determination limiting case for the downlink communication must be examined. This limiting case occurs when the satellite is pointing Team EQUIS 21 FRR v1.0

22 directly downward, because is in this orientation where the signal covers less distance in comparison with other types of orientations. If a height of 400 km out of the earth s atmosphere is considered for the cubesat s orbit and a beamwidth of 30 0, the distance covered by that situation is of 214 km. The visualization and procedure follow to determine this distance is shown in the following figure: Figure 16: Determining position accuracy This implies that if a 3db of power density don t want to be lost in the communication link at least an accuracy of a 100 km should be used for the position. If the effect of orbit decay in the strength of the downlink communication signal is examined considering that at least 100 km have been lost it s found that the 214 km of covered distance from the previous case (i.e 400 km of height), have been reduce to approximately 160 km. This means that the second case suggests a smaller value of position accuracy do to the effect of the cubesat s orbit decay, therefore it can be concluded that the lost in altitude will be the limiting factor to establish the accuracy of the position. Figure 17: Determining position accuracy with orbit decay An examination of previous data must be employ to completely define the accuracy of the position considering the phenomena of orbit decay. That is why data of orbit decay is retrieved from the Department of Industry Tourism and Resources to complete this task. This data is illustrated in the following figure: Team EQUIS 22 FRR v1.0

23 Figure 18: Plot of typical orbit decay Figure 18 illustrates that the satellite starts a rapid descend at the time the satellite reaches an altitude above the earth s atmosphere of approximately 300 km. Therefore from this plot it can be inferred that this height will establish the limits of distance covered by the downlink communication signal which is this case of 160 km. Thus, it can be concluded that in terms of communication the accuracy required should be at least of 80 km. As described in the Science Objectives section it is also of interest the behavior of the temperature as well as the response of the physical metallic enclosure of the payload under the same temperature changes. The temperature of the atmosphere varies as a function of height and as a function of the rotational position of the Earth. The temperature gradient can be obtained when at least two temperature sensors (one inside the payload and the second outside of its physical structure). The change of temperature from one point to the other presents the flow of energy (in heat form) from the hotter point to the cooler. This is known as conduction when it happens between the particle of a material (better in metals where metallic bonding is stronger) and radiation when it happens through empty space. The temperature gradient will help determine the influence on the internal components of the payload and as well as determine the effectiveness or behavior of the external physical structure. As described in the Science Objectives section it is also of interest the behavior of the temperature as well as the response of the physical metallic enclosure of the payload under the same temperature changes. The temperature of the atmosphere varies as a function of height and as a function of the rotational position of the Earth. The temperature gradient can be obtained when at least two temperature sensors (one inside the payload and the second outside of its physical structure). The change of temperature from one point to the other presents the flow of energy (in heat form) from the hotter point to the cooler. This is known as conduction when it happens between the particle of a material (better in metals where metallic bonding is stronger) and radiation when it happens through empty space. The temperature gradient will help determine the influence on the internal components of the payload and as well as determine the effectiveness or behavior of the external physical structure. The temperature changes significantly while it is ascending in the atmosphere. Figure 19 demonstrates the HASP payload during its ascending and floating time as it was exposed to a Team EQUIS 23 FRR v1.0

24 very extreme environment that consists of very low and high temperatures at a very low pressure (i.e millibars). Figure 19 illustrates the lowest temperature that was found on the platform s top was of C and could be lower due to the form of the curve. The highest temperature encountered during the 2006 HASP flight was of approximately 40 0 C. The exposure to these environmental conditions is what makes necessary the design of a thermal control system so that the electronic equipment inside the payload can be kept working at its optimal temperature range. The description of the ADS above, including the chosen attitude determination reference frames are intended for a robust and precise control of satellite for ground station contact. In order to test the proposed operation of the ADS, the collection of data needs to be done with adequate technology. The data collected will determine the attitude of the payload within the abovementioned reference frames. Proper design and programming of hardware components and sub-systems are intended to record the relevant data that will be post-processed to determine the tracking of the payload during the whole test flight Science Requirements Figure 19: Temperature variation during flight To accomplish the development of a robust ADS prototype that would be used to determine the orientation of a satellite, it is necessary to define the requirements that are needed to obtain the orientation, position and heat characteristics of the payload throughout the flight. These requirements are: 1. Determine the payload position within accuracy of 80 km. 2. Determine the heat transfer rate into or out of the payload. 3. Verify the orientation of the payload by comparing an external reference magnetic field and the International Geomagnetic Reference Field (IGRF) model of the year Use and verify the position accuracy of the Inertial Measurement Unit (IMU) with respect to the position GPS data. 5. Use the obtained data to gather knowledge about the attitude motion of the payload and provide recommendations for future HASP and CubeSat projects. 6. Complete final science report post flight. Team EQUIS 24 FRR v1.0

25 3.4 Technical Background and Requirements Technical Background The ADS developed in this project consists of several sensors and a data processing unit used to collect and store the measurements needed to determine the payload s position and orientation at intervals of time during the flight. The ADS is use to determine the payload s attitude, using different reference frames that will be established by the following equipment: Accelerometer For application with space and weight limitations there are three different kinds of accelerometers commonly used which are the piezoelectric micro-accelerometer, capacitive micro-accelerometer and the tunneling current micro-accelerometer. The type of accelerometer selected for this application is the piezoelectric microaccelerometer. It has been selected because its measures are not affected by parasitic capacitance or electromagnetic interference (EMI) which is disadvantages of capacitive accelerometers. In addition piezoelectric accelerometers don t require a high voltage like the tunneling current accelerometer. The piezoelectric accelerometer selected is an electromechanical device that obtains acceleration using the relation that exists between a piezoelectric deformation and the rate of change of the velocity in the body. When the body of the system accelerates a force is created and this force produce a deformation in the small piezoelectric that form part of the sensor. The principle of operation of these devices is presented in the following Figure 17. Figure 20: Accelerometers basic principal of operation As the body moves the mass in the sensor due to its inertia moves in the vertical direction producing a deformation in the beam. The piezoelectric is embedded in the location of the beam s maximum deflection and is that deformation which affects the piezoelectric producing a change in the piezoelectric structure. This piezoelectric deformation causes a change in the piezoelectric resistance that consequently will alter the output voltage of the piezoelectric of the specific axis where this inertial change occurs. This amount will permit us to determine the linear acceleration of the payload during the flight. This device will allow us to understand the payload behavior better, thus allowing better knowledge of payload s motion. An average sensitivity of 10mV/g is commonly encountered in this type of sensors. Team EQUIS 25 FRR v1.0

26 Gyroscope The three-axis gyroscope is a device for measuring the payload s degree of rotation. The types of gyroscopes commonly used for applications with space limitations are the Micro Electrical Mechanical System (MEMS) gyro. These types of gyroscopes are compose by miniature mechanical elements that vibrates and electronic components used to process the data produced by the mechanical elements. The vibration of the mechanical element is affected every time the payloads rotate due to the Coriolis effect (see section #), which produce a vibration in direction different to direction of the initial vibration. This resultant vibration is directly related to the angular velocity of the payload s rotation. This second vibration is sensed and processed by the electronic equipment in the gyroscope to finally determine the payload s angular velocity readings. To illustrate the principal of operation of these devices consider the following figure: Figure 21: Gyroscopes basic principal of operation The gyroscope readings will provide information about the payload s rotation on each one of the axes. The gyroscope and accelerometer data can be combined to acquire a more precise measure of the payload s orientation. Three-axis magnetometer The ADS system of the payload will take measurements of the strength of the Earth s magnetic field. These measurements will be used to obtain the position of the payload during the complete flight. The magnetometer detects the magnitude of the earth s magnetic field on each axis, in this case; X, Y and Z. To obtain the magnetic field the magnetometer works by measuring the magnetic filed through magneto inductance by using a circuit that is magneto inductive (which consist of a coil around a ferromagnetic core). A relaxation oscillator connected to this magnetic circuit works by gradually building up charge in the circuit and discharging rapidly, this cycle repeats itself. As the strength of the magnetic field varies so does the frequency of oscillation in the coil that is perpendicular to field. The output of the magnetometer is in form of a square wave signal that can be read as a digital signal. This output Team EQUIS 26 FRR v1.0

27 represents the magnitude of the magnetic field on a specific axis; having three magnitudes will allow the calculation of the earth magnetic field vector. B component along coil axis B Figure 22: Simplified representation of magnetometer basic operations The magnetic field is directly related to the cosine of the angle; as a result, when the angle changes, the magnetic field will change will result in a change of voltage at the output of the sensor. The following equation represents the relationship between the magnetic field and the angle at different times. Where and is the magnetic constant field. Note that the output of the magnetometer is measured in volts depending directly on the strength of the field along the axis. Three different circuits as described above would be needed if three dimensional frame detection is desired. Temperature sensor Different kinds of temperature sensors have been develop in the present to meet diverse kind of requirements that can appear in a variety of applications. These sensors differ in their ranges of measurements, sensitivity, accuracy, and mode of sensing. The different kinds of temperature sensor that exist today can be classified as thermocouples, thermistors, RTD s, or solid state sensors. For this application the temperature device considered is solid state sensor. An illustration of this type of sensor is presented in the following figure: Team EQUIS 27 FRR v1.0

28 Figure 23: The DS18B20 Digital temperature sensor A DS18B20 digital temperature sensor will gather the internal temperature measurement. The measurement range of the digital temperature sensor is from -55ºC to +125ºC. Once the temperature reading has been realized, the DS18B20 converts the temperature into 12-bit digital word. The communication between the microcontroller and the digital temperature sensor is through 1-wire bus that requires only one data line (by definition). The data obtained by the DS18B20 will remain when the device is powered down, since an EEPROM is included in the DS18B20 temperature sensor. The user can configure the resolution of the temperature sensor. Figure 24: DS18B20 Digital Temperature Sensor Diagram (From the DS18B20 datasheet) Figure 21 shows an example to power the DS18B20 temperature sensor that is shown in the datasheet. An external power supply can be used to power the DS18B20 temperature sensor in the pin. The DS18B20 has the feature of receiving power from the data line (power supply range is from 3.0V to 5.5V); however, the advantage of power the DS18B20 by an external power supply is that the MOSFET pullup is not required, and the 1-Wire bus is free to carry other traffic during the temperature conversion time. Sampling rate The sampling rate is the pace of taking measurements at a specific amount of time. The selected sampling rate for this project is 10 s and applies for the entire data acquisition sequence. This rate is necessary to obtain the data needed for orientation Team EQUIS 28 FRR v1.0

29 and position within a specific accuracy and, at the same time, to calculate the amount of storage needed for it. This rate was determined as follows. A video from the HASP 2007 project, where a balloon payload dynamics were recorded, it was observed that the platform was moving at an approximately maximum angular velocity of 90 in approximately 90 minutes, that is, 1 degree per second. For an accuracy of 10, as determined above for the communication link constrain, a minimum sampling rate of 10 seconds is chosen so the system knowledge for proper attitude determination updated for a maximum of angular change of that angle. is This 10 accuracy determine also the linear trajectory of the payload when changes its position to a 55 meters per second. This value is obtained from the fact that the payload moves approximately 300 km in 15 hours which is equal to 5.55 m/s Technical Requirements The requirements about the technology needed to accomplish them to determine the orientation, position, and heat characteristics of the payload are: General: 1. To develop a payload that requires less than 30V at 0.5Amps, provided by HASP, and as well to meet the CubeSat power requirements. 2. Develop a mechanical structure that can withstand all the stresses during the payload s flight. 3. Maintain the internal temperature in the range of -10 o C to 60 o C. 4. Obtain the data at a sampling rate of 10 s. Specific: Figure 25: Determination of sampling rate by maximum angular velocity 1. Employ a three axis accelerometer with an accuracy ± 2% to determine the position of the payload within 55 meters. 2. Determine the orientation by employing accelerometers with an accuracy of ± 2% and gyroscope with an accuracy of 0.01 o /hr (angular velocity) to develop an Inertial Navigation System. 3. The rate of heat transfer is to be determined by using a pair of temperature sensor (internal and external) with a size of no bigger than 4 mm (because of space contraints) and an accuracy of ± 1 o C. 4. Determine orientation with a 3 axis magnetometer with accuracy of 10 o Team EQUIS 29 FRR v1.0

30 5. Determine position from a three axis accelerometer that has an accuracy of ± 2% and a reference Global Positioning System sensor. 6. Develop an integrated system of sensor such as magnetometer (10 o accuracy) accelerometer (± 2% ) and gyroscope (0.01 o /hr) at a sample rate of 10s. 4.0 Payload Design The ADS experiment has a sensor subsystem of five main sensors that will take measurements to study the balloon platform dynamics. The design arrangement for the experiment consist of rotational sensor, acceleration sensor, magnetic field sensor, and internal temperature sensor to acquire data at different positions to get exact information about the Attitude of the payload. 4.1 Principle of Operation The ADS experiment will take a variety of measurements, such as acceleration, orientation, temperature, position, and magnetic field. A three axis accelerometer sensor will be use to obtain the acceleration data which in the post analysis will be used to obtain velocity and position and will be compare to the GPS data. The magnetic field concentration will be determined by a three axis magnetometer to obtain the orientation of the payload. Also the orientation will be determined by a combination of the gyroscope and accelerometer to obtain robustness. The internal temperature data will be obtained by an internal temperature sensor used to monitor the payload s internal environment to see when the temperature limits of the devices are reached. 4.2 System Design Mechanical System Legend SD Card Memory Data from Clock Data from the Sensors Three Axis Accelerometer Real Time Clock Payload Structure Transmission of Data Three Axis Gyroscope Flight Control System Microcontroller Digital Temperature Sensor Three Axis Magnetometer Figure 26: ADS System Design Team EQUIS 30 FRR v1.0

31 The system design (Figure 23) shows the elements of the ADS system. The clear blue connections designate the data exchange between the flight control and the sensors that will be in the payload. The green line represents communication between the Microcontroller and the Real Time Clock to obtain time and day data. The data obtained from the sensors will be saved in the SD card; this communication is represented by the red line. The light gray line and the mechanical system box represent the ADS payload structure. The temperature sensor box represents the internal temperature sensor. The power subsystem is explained in more detail in the sections power supply and power budget. Arduino Pro 328 An Arduino Pro 328 version 3.3V/8MHz will be used as the flight control computer for the ADS experiment. Figure 4 shows 328 provides 3.3V and 40 ma on each of the I/O pins. The clock speed for the 3.3V version is 8 MHz. The has both SPI and I2C interface; as a result sensors with SPI and I2C protocol can communicate with the Pro 328. As mentioned above, the accelerometer and the magnetometer sensors have SPI interface. Both sensors have a unique pin for their slave select; therefore, the Pro 328 can send the instruction via the developed program to the sensor that is assigned to read once the data is available. The gyroscope sensor can communicate with the Pro 328 using the I2C protocol. SCA-3000-D01 The schematic for the SCA-3000D01 three axis accelerometer sensor is shown in Figure 28. The SCA D01 has a measurement range of + 2g and has an SPI digital interface. The SEN Breakout board includes an SCA3000 and provides 8 pins in this board. The pins are as follows; VIN, RST, INT, MOSI, MISO, SCK, CSB and GND. As mentioned in previous section Flight Software, for SPI interface the data transfer consist of a 4 wire interface; MOSI, MISO, SCK and CSB. The MOSI and MISO pins stand for master out slave in and master in slave out respectively. In addition, the SCK stand for serial clock and is used to synchronize all the devices. Finally, in Figure 27: Arduino Pro V/8MHz schematic Figure 28: Three Axis Accelerometer schematic order to select this sensor to communicate with the microcontroller instead of the other slaves, the SCA-3000-D01 includes a CSB chip select that will be activated by the Pro 328 microcontroller when the Pro 328 sends a signal through this pin. The CSB pin is low active. Team EQUIS 31 FRR v1.0

32 MicroMag3 Figure 29 shows the schematic for the MicroMag3 three axis magnetometer. The MicroMag3 provides a measurement range of +1100µT ( +11 Gauss). The MicroMag3 has a total of 14 pins; however, from pin 8 to 11 and pin 13 are not connected pins. Therefore, the pins that will be used are 1 through 7, 12 and 14. The functions of these pins are SCLK, MISO, MOSI, SS, DRDY, RESET, GND, VDD and GND respectively. The MicroMag3 has an SPI digital interface; therefore, the pins MISO, MOSI, SCLK and SS are SPI pins. SCLK and SS pins are the serial clock and the slave select respectively. The RESET pin is usually low and can be used by the Pro 328 during the program testing to reset the sensor and run the program. The DRDY stand for data ready and is recommended that once the data is available it is clocked out of the MicroMag3; however, this pin is not used since the sampling rate for the ADS experiment will be different from the rates mentioned in the MicroMag3 datasheet. Three Axis Gyroscope Figure 29: Three Axis Magnetometer schematic The ITG-3200 is a three axis gyroscope, it consist of seven; these pins are VCC, SCL, SDA, VLO, INT, CLK and GND. Both the INT and CLK are not used these are an interrupt pin and a pin for an external clock, CLK needs to be grounded if it is not used. In Figure pin 6 and 7 are I 2 C these pin are connected to the digital pins on the Pro 328, these pins require pull up resistors to VDD. The VLO in generally it is connected to the pin 1. Notice that C1 and C2 are used as decoupling capacitors to allow a clearer signal. Figure 30: Three Axis Gyroscope schematic Digital Temperature Sensor The DS18D20 is a one wire digital thermometer with 3 pins in a TO92 package, the pins are GND, VDD and DQ. In Figure it is illustrated that pin 2 needs a pull-up resistor of 4.7kΩ. Pin 3 Figure 31: Digital Temperature Sensor schematic is supplied with 3.3V with a series capacitor to reduce noise. This sensor is connected to digital pin 13 in the Pro 328. Team EQUIS 32 FRR v1.0

33 Micro SD Transflash CD: Card detect DO: Data output GND: Ground SCK: Clock VCC: Supply Voltage DI: Data Input CS: Chip Select In Figure 32 is demonstrated the Schematic of the SD Card transflash board with the connections to the microcontroller. This device has 7 pins CD, DO, GND, SCK, VCC DI and CS. The serial peripheral interface (SPI) pins are DI, DO, SCK and CS. As with previous sensors the capacitor C6 will reduce noise and allow a clearer signal. Pin 7 is not used when using SPI mode, pin 7 is mostly used in SD mode. Figure 32: MicroSD board schematic Serial Alarm Real Time Clock (RTC) Figure 33 demonstrates the schematic and pin configuration use for this experiment. This RTC is a DS1306 and it is use to obtain a time stamp. The pins used will allow to obtain the time without using any alarm features. Pins 3 and 4 are use for the crystal; the recommended crystal is a kHz Quartz crystal with a series resistance of 45kΩ and a capacitance of 6pF. Pin 10 Figure 33: Real-Time Clock schematic through 13 are use for SPI. Pin 16, 14 and 9 needs to be connected to the source, the capacitor C7 allows a clear input signal. A lithium 3V cell is used as a backup battery in pin 2. In this configuration Vcc2 is connected to pin 8 and GND. This device is connected to the digital pins in the Pro 328 for SPI. 9V DC to DC Converter Connected to the 9V DC to DC converter is the power supplied by HASP which is 500mA as shown in Figure: through pins 1 and 2. A 3A diode is used to Figure 34: 9V DC to DC Converter schematic Team EQUIS 33 FRR v1.0

34 avoid any damage to the devices if a wrong connection is done. The C8 through C11 and C14 is to reduce noise and to guarantee the full parametric performance over the full line and load range. The 9V output will supply the Pro 328 and the Linear Voltage Regulator. This device has an efficiency of 80%. Linear Voltage Regulators Each one of the sensor and the SD card memory that will be used for the ADS experiment will be powered by 3.3V. The ADS instruments will receive power from the HASP platform, which deliver 30V at 0.5 Amps. A 9V DC to DC converter will transform the 30V provided by the platform into 9V to power the Pro 328. Since the ADS electronics (with the exception of the Pro 328 and the DC to DC converter) will be powered by 3.3V, an UA78M33IKCS 3.3V linear voltage regulator is required to reduce the 9V delivered by the DC to DC converter. Figure 35: 3.3V Voltage Regulator schematic The 3.3V linear voltage regulator will remove the excess voltage and it will turn it into heat to provide the 3.3V. This device is a linear voltage regulator capable of providing 5V output for the Real Time Clock since it requires that the input voltage be higher than 3.2, the device did not work with a input voltage of 3.3V. The power of the regulator is obtained from the 9V DC to DC converter. Figure 36: 5V Voltage Regulator schematic Functional Components 1. Power Subsystem: VDC will be provided by the HASP platform during the entire flight. A power budget analysis is required to ensure that this power will be sufficient for the instruments of the ADS experiment for the entire period of flight. 2. Microcontroller: The Arduino Pro 328 microcontroller, which is connected to all the instruments, is in charge of collecting the measurements from all the sensors and stores it to the memory. 3. SD Card Memory: The SD card memory module will be added to the Arduino were the measurements of the sensors will be stored here as digital quantities. 4. Three Axes Accelerometer: The accelerometer will take the acceleration measurements of the payload. Each one of it axes will perform measurements related to the payload response on that axis. 5. Three Axes Gyroscope: The gyroscope is in charge to determine the orientation of the ADS payload by sensing the platform rotation during flight. 6. Three Axes Magnetometer: The magnetometer will measure the earth s magnetic field intensity. 7. Internal Temperature Sensor: The internal temperature will be monitored by the flight control computer using an internal temperature sensor. The internal temperature Team EQUIS 34 FRR v1.0

35 readings will be compared with a particular temperature value set in the program of the microcontroller to identify at what time the maximum temperature is reached. 8. GPS Data: Will provide the position and altitude information of the platform obtained through HASP website. 9. Mechanical System: The mechanical system is the enclosure of the subsystem components for the experiment. An aluminum 2014-T4 alloy will be use to construct the mechanical system to isolate the circuit components and protect them from the temperature. 10. Thermal Subsystem: The main purpose of the thermal system is to maintain the internal temperature of the payload within the operating temperature range of the sensors and the components at the same time protect them from any impact that can damage it. 11. Data Gathering and Analysis: The Pro 328 has to execute the flight software to gather the sensors measurements and stored it in the SD card. Once the data is extracted from the SD card several plots will be made to analyze the data and develop new recommendations V DC to DC Converter: The purpose of this device is to transform the high level voltage of 30V to 9V to supply the Pro 328 and the linear regulator V Linear Voltage Regulator: To supply the sensor with the voltage level of 3.3V it necessary to use the regulator do to it efficiency with low voltages V Linear Voltage Regulator: To supply the real time clock with the voltage level of 5V it is necessary to use this regulator Component Interfaces The Attitude Determination System will be composed of the following interfaces. The Pro 328 is going to be connected with each one of the sensors output which are digital pins its interface will be composed of the necessary traces on the PCB. The power subsystem will have connection with the sensors subsystem and with the Pro 328 to deliver power to both subsystems, thus permitting for each sensor to receive the power necessary to operate within the specifications by the use of a 9V DC to DC converter and 3.3V Linear Voltage Regulator. Also decoupling capacitors will be use to allow a power clearer signal by reducing noise from the power system. In sections to is an explanation in greater detail of the power interfaces and consumption. The interface between the Magnetometer, Accelerometer and Gyroscope is a direct connection to the digital pins of the Pro 328. A direct connection interface with the SD card memory module is used to receive the information that will be stored. To store the data in micro SD card it is necessary to use a time reference, having the need for a RTC and its interface is a SPI trace throughout the board. Team EQUIS 35 FRR v1.0

36 4.2.3 Traceability Table 1 below shows the traceability matrix for the ADS experiment. Main Mission Goal Objectives Requirements Implementation Determine the payload position within accuracy of 10 meters. The goal of this project is to develop an attitude determination systems (ADS) prototype, by improving the robustness and accuracy of a previous design (ABITA; Tiger team) in order to obtain relevant data and hands-on experience for a future satellite attitude control and determination system (ADCS). The designing, developing and testing will serve as a stepping stone for a future CubeSat project with the objective to transmit to a ground station the measurement data that has been applied for the terrestrial gamma ray flashes (TGF). Previous CubeSat data will help as a basepoint for this design. To determine translation and attitude motion of the payload during flight To obtain the platform s body frame orientation with respect to the body fixed reference frame To measure the Earth s gravitational and magnetic field and the angular momentum of the payload such that the data can be used to determine the orientation of the payload. Determine the heat transfer characteristic during flight and its potential impact on internal and structural components. Determine the acceleration with an accuracy of ± 2% and the angular velocity with an accuracy of 0.01 o /hr Determine the magnetic field with an accuracy of 10 o Determine the gravitational field with an accuracy of ± 2% Determine the angular momentum with an accuracy of 0.01 o /hr Determine the temperature in the range of -10 to 60 o C and a accuracy of 0.5% Table 1: Traceability Matrix Combining the acceleration and movements in pitch, yaw and roll data from the accelerometer and gyroscope Employing an accelerometer with a resolution of 0.002g and a gyroscope with a sensitivity of LSB/dps Develop an integrated system with a magnetometer with a resolution of 15nT Develop an integrated system with an accelerometer with a resolution of 0.002g Develop an integrated system with a gyroscope with a sensitivity of LSB/dps Use a small signal diode that can operate from -30 to -90 o C Team EQUIS 36 FRR v1.0

37 4.3 Electrical Design Legend Sensors Digital Outputs HASP VDC Power 3-Axis Magnetometer Sensors Subsystem 3-Axis Accelerometer Internal Temperature 3-Axis Gyroscope Flight Control Subsystem Atmega 1280 Arduino SD Card Memory Real Time Clock Digital Outputs Digital Inputs Figure 37: Electrical Design Subsystems As shown in Figure 37 the electrical design consists of three main subsystems; the power subsystem (HASP), the flight control subsystem and the sensor subsystem. The power subsystem consists of the power provided by HASP, the DC to DC converter and the linear voltage regulator. The sensor subsystem is composed of digital devices; therefore these signal outputs from the sensors will be received by the Pro 328 as shown in Figure 37. The flight control subsystem will gather data from all instruments. The sensors subsystem consists of four sensors; a three axis accelerometer, a three axis gyroscope, a three axis magnetometer, and an internal temperature sensor Sensors Subsystem Legend Sensors Digital Outputs Sensors Subsystem 3-Axis Magnetometer 3-Axis Accelerometer 3-Axis Gyroscope Internal Temperature Flight Control Subsystem Digital Inputs Digital Outputs Arduino Pro 328 Analog Inputs Analog Outputs Figure 38: Electrical Subsystem Team EQUIS 37 FRR v1.0

38 The electrical subsystem is shown in Figure 38 above which allows observing a general view of how the electrical connections will be done. The sensor subsystem is represented in the left box and Pro 328 is represented by the right box. The interface between the Pro 328 and each one of the sensors is represented with the lines with ends. The line ends points at the direction that the information will be flowing, which is from the sensors to the Pro 328 through the SPI pins for Magnetometer and the Accelerometer, I 2 C for the Gyroscope and a digital pins for the Internal Temperature sensor. The SCA3000 is a digital three axis accelerometer with an acceleration range of +2 g. The digital I/O voltage of the SCA3000 is from 1.7 V up to 3.6 V. The digital outputs range of the SCA3000 accelerometer is from 2.35 V up to 3.6 V. The sensing element of the SCA3000 three axis accelerometer consists of three acceleration sensitive masses. A capacitance change will occur due to acceleration and will be converted into a voltage change in the signal conditioning ASIC. The element s measurement coordinates are rotated 45º compared to the conventional orthogonal X, Y, Z coordinate system, due to its mechanical construction. Figure 39: Accelerometer Sensor The sensing element is interfaced via a capacitance-tovoltage (CV) converter. The SCA3000 includes an internal oscillator, reference and non-volatile memory that enable the sensor s autonomous operation within a system. The SCA3000 includes a temperature sensor; therefore, temperature stability can be reached by using the temperature information from this sensor. The Figure 40 shows the pins for the SCA3000. The accelerometer can receive instructions from the Arduino microcontroller by connecting an output pin to the accelerometer Master Output Slave Input (MOSI) pin. The Pro 328 represents the Master and the accelerometer the slave. The SCA3000 can be set to operate at low power to save system level power consumption by using the Motion Detection (MD) mode. When the Free- Fall Detection (FFD) is enabled normal acceleration is available. Figure 40: SCA3000 Three axis accelerometer pins The EQUIS team selected the ITG-3200 three axis gyroscope for the ADS experiment. As mentioned in previous sections, the ITG-3200 is a three axis gyroscope with digital outputs. The full scale range of the ITG-3200 three axis gyroscope is º/s. The ITG-3200 has digital (I 2 C) outputs. The operating voltage range of the gyroscope is from 2.1 V up to 3.6 V. Team EQUIS 38 FRR v1.0

39 The pins to receive the digital instructions are shown in Figure 29. The ITG-3200 is a three independent vibratory Micro-electro-mechanical System (MEMs) gyroscope sensitive to Coriolis forces. The ITG-3200 can detect rotational rate in three axis; the X (roll), Y (pitch), and Z (yaw). Figure 41: Gyroscope Sensor A rotation about any of the sense axes of the gyro must be induced to create a Coriolis Effect, which causes a deflection that is detected by a capacitive pickoff. The MEMs device applies the following process to the detected signal; amplification, demodulation and filtering that produce a voltage that is digitalized with an internal ADC. The converted voltage is proportional to the angular rate. The ADC output rate is capable from 3.8 up to a maximum 8,000 sample per seconds, while allowing a wide range of cut off frequencies due to its capability of a user selectable pass filter. A MicroMag3 three axis magnetometer has been selected for the earth s magnetic field measurements of the ADS experiment. The three axis magnetometer sensor operates as an oscillator circuit composed of the internal sensors, bias, resistors, digital gates and a comparator. Only one sensor can be measured at the time. The user sends a command byte to the MicroMag3 through the SPI port specifying the sensor axis to be measured. A model of the MicroMag3 is shown in Figure 42. Figure 42: Three Axis Magnetometer The micromag3 three axis magnetometer has a low power: draws < 500 µa at 3 VDC and have a field measurement range (3 VDC at Rb = 43Ω) of µt. The micromag3 has a fully digital interface: SPI protocol at 3V, it can also be powered at 3.3V. Figure 43: Digital Temperature Sensor A DS18B20 will be the internal temperature sensor for the ADS experiment. The master (the Pro 328) must issue a convert T [44h] command in order to initiate a temperature measurement. The DS18B20 stores the temperature measurement in the 2-byte temperature register in the scratchpad memory, and then the DS18B20 will return to its idle state. Team EQUIS 39 FRR v1.0

40 The time during flight will be provided by the circuit of an RTC-Real Time Clock shown in Figure 44. The specific model will be the DS1306, which can withstand a temperature range of -40ºC to 85ºC. This device is reliable due to the fact that it allows to have a backup battery, which in this experiment it will be a +3V Lithium battery additional to the constant source, which is 5V. In addition, this device requires a crystal of khz, 6 pf and a resistance of 45 kω Sensor Interfacing Figure 44: Real Time Clock The sensor connections with the Arduino are as shows the following table; Sensors Sensors Pins Arduino Pro Pins Gyroscope (I2C) SCL A4 (I2C) SDA Accelerometer RST 2 A5 SS ACC 3 Magnetometer SS MAG 4 DRDY MAG 5 RESET MAG 6 Digital Temp DQ 7 SD Card SS SD 8 Real Time Clock SS RTC 9 Accelerometer Magnetometer (SPI) MOSI 10 (SPI) MISO 11 (SPI) SCK 12 Not Connected TBA 13 Not Connected TBA 14 Table 2: Pins for the Pro 328 All the sensors will have an interface between each one of the outputs and the Pro 328. All the sensors for the ADS experiment are digital sensors; therefore, they do not require any additional components besides a decoupling capacitor to allow a clearer signal. Team EQUIS 40 FRR v1.0

41 Figure 45: ADS PCB Design Figure 45 shows the Print Circuit Board (PCB) design for the ADS experiment. Each one of the components is represented with yellow lines with its actual size and the corresponding name. The holes that are required for the PCB to place the components and connect traces were also realized using the actual size of the leads of each component and are represented with red circles. The complete schematic design was linked to the PCB design to enable a tool of the Express PCB software that indicates the pins that need to be connected according to the schematic. Several traces were designed on the PCB to realize the required connection between the components. The green and red lines represent the traces that connect the components in the PCB. The red lines are the connection traces designed in the top copper layer and the green lines are the connection traces in the bottom copper layer. When a trace is made in both copper layers (top and bottom) to make a connection between two components, pass through a hole to allow connection. Finally, the yellow square that surrounds all the components, holes and traces represent the actual dimension of the PCB, which is 4 x 4 inches. Team EQUIS 41 FRR v1.0

42 4.3.4 Power Supply HASP 0.5 Amps at 30 VDC 30V 3.3V 3.3V Three Axis Magnetometer Three Axis Accelerometer FUSE Box 30V 3.3V Three Axis Gyroscope 9V DC to DC Converter 9V 3.3V Linear Voltage Regulator 3.3V Real Time Clock 9V 3.3V SD Card Arduino Pro 328 5V Linear Voltage Regulator 5V Digital Internal Temperature Sensor Figure 46: Power System Diagram The power subsystem for the ADS experiment is shown in Figure 46. The HASP platform will be the power source for the ADS experiment and will deliver 30V at 0.5 Amps to the ADS payload. The fuse shown in the figure 33 is included in the power subsystem to isolate the ADS electronics from the HASP platform as a safety precaution. As mentioned in the section 4.2 System Design, a 9V DC to DC Converter will transform the power from the platform to power the Pro 328. Also a suitable supply of 3.3V is being delivered through a Linear Voltage Regulator that is represented in the Figure 33 to power the Micro SD board and all the sensors. Also a 5V voltage converter is used to supply the 5V required for the RTC. The Pro 328 has an input voltage range from 3.35V to 12 V; however, the voltage regulator of the Pro 328 Board may overheat and damage the board when is using more than 12 V and if the supplied voltage is less than 7 V, the 5 V pin may supply less voltages on the pins and the board may be unstable [Ref. 14]. Therefore, the Pro 328 will receive 9 V from a DC to DC converter as shown in Figure 46. Team EQUIS 42 FRR v1.0

43 4.3.5 Power Budget The HASP- High Altitude Student Platform provides power for small and large payloads. For small payloads the supplied voltage that HASP platform provides is VDC. Sensor and Devices Three Axis Gyroscope ITG3200 Three Axis Accelerometer SCA3000 Three Axis Magnetometer Micromag3 Digital Temperature Sensor DS18B20 Required Voltage (V) Required Current Amperes (A) Power Consumption Watts (W) mA 21.45mW uA 21.45uW uA 1.65uW mA 4.95mW Arduino Pro mA 1800mW Real Time Clock DS1306 5V 1.28mA 6.4mW SD card circuit 3.3 Max consumption of sensors and devices 100mA(max) 40-60mA(Typical) 330mW Power Source (after HASP) 3.3V Linear Regulator 3.3V Linear Regulator 3.3V Linear Regulator 3.3V Linear Regulator 9V DC to DC Converter 5V Linear Regulator 3.3V Linear Regulator mW -- Table 3: Power Requirements Table 3 demonstrates the current, voltage required, power source and power consumption for each of the electronic sensors without the power devices as the linear Regulator and DC to DC converter. Note that the current consumed by the SD card is a maximum value and that the typical value is in the range of 40mA to 60mA depending on brands. The total power consumption was obtained through a mathematical analysis that can be observe in Figure 47, first all the current of the sensors is sum, then multiplied by the voltage supplied to obtain the power. This current consumed by the sensor is also consumed by the linear voltage regulator; to obtain the power dissipated by the regulators, the current consumed is multiplied by the voltage drop of 5.7V in the 3.3V regulator, and this procedure is also done with the 5V regulator. The 108mA consumed by the 3.3V regulator, the 1.28mA consumed by the 5V regulator and the 200mA of the Pro 328 are added to obtain the total current consumed before the 9V converter; this is defined by Kirchhoff Current Law. This current of 309mA and the voltage of 9V are used to obtain the power consumed which is mW. The DC to DC converter need to supply what is required for the components to work, the converter has an efficiency of 80%. To obtain the total power consumption of the value power is divided by the efficiency (0.80) thus obtaining the consumption of the ADS system which is 3479mW. This power value is divided by the 30V supplied by HASP, thus obtaining the total current and power consumption. The difference between the powers before and after of the converter will provide the power dissipation of the device. To verify that the Team EQUIS 43 FRR v1.0

44 calculation is correct that total power consumption must be equal to sum of the individual power consumption of all the devices in the ADS system. Therefore: Total Power = DC to DC Power + Pro328 Power + Regulator Power + Sensor and Devices Power 3479mW 696mW+ 1800mW mW mW+5.12mW+6.4mW HASP Power 500mA 30V 116mA 3479mW DC to DC Converter 80% efficiency 9V mA mW 200 ma Arduino Pro 328 9V 200 ma 1800mW 696 mw 108 ma 3.3V Linear Voltage Regulator 615.6mW Sensors and Devices 3.3V 108mA 356.4mW 1.28 ma 5V Linear Voltage Regulator Real Time Clock 5V 1.28mA 6.4mW 5.12 mw Figure 47: Power Budget Analysis 4.4 Software Design The data will be retrieved from the sensors and thus the software will be designed to store the data in the SD card Data Format & Storage The total bytes required for the flight is determined by the quantity of the sensors and the total bytes of the measurement of the sensor times the hours the payload may remain in flight. The system has four sensors; three axis magnetometer, three axis gyroscope, three axis accelerometer, and one for the internal temperature sensor. Each sensor with three axes will have a total of six bytes and the internal temperature sensor will have a total of two bytes. The time stamp consists of four bytes, one byte for the hours, one byte for the minutes, one byte for the seconds, and one byte for the date. In total we have 24 bytes for the whole system. The sample rate will be of approximately 3 seconds. The data will be received 20 times each minute. The total bytes for the whole flight will be of about 576,000 bytes. Team EQUIS 44 FRR v1.0

45 The total bytes required for the system are: Byte Description 1-4 Time Stamp 5-6 Accelerometer: X axis 7-8 Accelerometer: Y axis 9-10 Accelerometer: Z axis Gyroscope: X axis Gyroscope: Y axis Gyroscope: Z axis Magnetometer: X axis Magnetometer: Y axis Magnetometer: Z axis Internal Temperature Sensor Table 4: Bytes Description The data will be saved in the SD card. The SD card will be formatted FAT 16 before use. The program will use the SDFat library to create an object to access Fat16 files in SD cards. The data will be saved as a comma separated values (CSV) format Flight Software To run the code on the Arduino, the code must have two main functions: Void setup() o Will run once, when the Arduino starts o The pins are set (input or output) Void loop() o Is an infinite loop, starts running when setup function finishes o Runs the rest of the code The magnetometer, accelerometer, SD card, and the real-time clock use the serial peripheral interface (SPI) to communicate with the microcontroller. SPI is a synchronous serial communication with one microcontroller (master) and several devices (slaves). The master provides the clock signal and activates which device (slave) to receive data from. The SPI uses 4 lines, the slave select line to activate the device, the serial clock line to synchronize the data communication, the master-in-slave-out (MISO) line to send data from the slave to the master, and the master-out-slave-in (MOSI) line to send data from the master to the device. The SPI communication uses the Atmega s SPI internal registers. The following are the registers that will be used: SPDR - SPI data register SPCR SPI control register SPSR SPI status register SPIF SPI interrupt flag Team EQUIS 45 FRR v1.0

46 The control register (SPCR) has 8 bits, each bit is a command. Bit 7 Bit 6 Bit 5 Bit 4 Bit 3 Bit 2 Bit 1 Bit 0 SPIE SPE DORD MSTR CPOL CPHA SPR1 SPR0 Enables If bit = 1 Sets SPI Sets SPI SPI sends speed speed Enables interrupts LSB first, if bit = 0 sends MSB first If bit = 1 sets master mode, if bit = 0 sets slave mode Sets clock polarity Table 5: SPCR bit specification Sets clock phase EQUIS software uses SPI mode 0 for the accelerometer and for the SD card and mode 1 for the real-time clock. In mode 0 the CPOL and CPHA are set as 0; therefore, the leading edge of the clock uses a sample on the rising edge (signal low to high) and the trailing edge of the clock uses a setup on the falling edge (signal high to low) of the clock. The SPR1 and SPR0 are set to 1, this sets the clock frequency to 62.5 KHz, because the oscillator frequency is divided by 128 and the ArduinoPro 328 (3.3v) is of 8MHz. The real-time clock operates on SPI mode 1 where CPHA is set to 1 and CPOL is set to 0, this makes the leading edge of the clock use a setup on the rising edge (signal low to high) and the trailing edge of the clock sample on the falling edge (signal high to low). The SPR1 and SPR 0 are set to 0 setting the clock frequency to 2MHz. The magnetometer uses another method, bit-banging, instead of setting the SPCR. Bit-banging uses software to transmit bits (high and low), the magnetometer recognizes the bits as commands. The pre-flight software sets the RTC by sending the seconds, minutes, hours, day, and date, month, and year to the corresponding RTC s internal registers (code on Appendix C). During flight the software will read from the RTC s internal registers to receive the timestamp. Table 6 illustrates the RTC s registers that will be used to determine their addresses to read data from and write data to. Table 6: RTC registers and address map Team EQUIS 46 FRR v1.0

47 The software contains a function called spi_transfer it is used to start the transmission. Sets the data sent to the data transmission register, waits for transmission to complete, and returns the data from the data transmission register. For example, when reading from the RTC register, the registers address is sent first to the spi_transfer, so that the RTC can prepare the register, followed by 0 and the device will send the registers value. The magnetic field will be measured using a magnetometer, a MicroMag3. The MicroMag3 data sheet suggests following these steps to communicate with magnetometer: 1. Slave select is brought low. 2. Reset the MicroMag3 before each measurement. Reset must be toggled from lowhigh-low. 3. Data is clocked in on the MOSI line. Once eight bits are read in, the MicroMag3 will execute the command. 4. The MicroMag3 will make the measurement. 5. At the end of the measurement, the data ready line is set to high indicating that the data is ready. As stated in the MicroMag3 data sheet, the axes are chosen by setting the appropriate bits in the 0 and 1 bit position in the commanding byte as shown on Table 7. The pseudo code for the MicroMag3 is shown on Appendix C. Function BIT 1 (from the commanding byte) BIT 0 (from the commanding byte) X axis 0 1 Y axis 1 0 Z axis 1 1 Table 7: Axis Select The accelerometer that will be used in the ADS experiment is the SCA 3000-D01. The readings for each axis are divided into two registers, most significant byte (MSB) and the least significant byte (LSB) as shown on Table 8. The data has a total of two bytes. Table 8: SCA3000 registers The register is shifted 2 bits to the left making the last 2 bits 0 s thus indicating the registers are being read. The data consists of the MSB and the LSB by shifting the MSB to the upper 8 bits and using bitwise OR to check which bits are 1 s and the LSB is computed by using a bitwise AND with F8 hex ( b) then the result will be divided by 8. The pseudo code for the SCA3000-D01 is shown on Appendix C. The gyroscope (ITG 3200) uses I 2 C to communicate with the microcontroller using two lines the serial data line (SDA) and the serial clock (SCK). The commands from the microcontroller Team EQUIS 47 FRR v1.0

48 and the data sent use the same line, SDA. The Arduino has a library called Wire to setup the communication with I 2 C devices. The software will use the following Wire library functions: Wire.begin() initializes the I 2 C communication (SDA and SCK lines) as a master Wire.beginTransmission(device address) selects the device and starts the communication with the selected device from the bus Wire.send(value) sends a value to the device, can be a register number or the data if the register will be written Wire.endTransmission() ends the communication with the device, deselects the device Wire.requestFrom(device address, quantity) requests the quantity of bytes that will be received from the device Wire.available() determines if the requested bytes are available to be read Wire.receive() the master receives the data from the device and stores it on the variable, e.g. data = Wire.receive(); The temperature will be measured using a One-Wire digital thermometer (DS18B20). One- Wire is how the device communicates with the master, using one wire for data and power. The master sends pulses to the bus to receive the device address; the address is used to choose the device when multiple one-wire devices are connected on the same bus. Following the address, the microcontroller sends the register for the command for the device. Two of the commands that will be given to the DS18B20 are the convert T, this command converts the temperature and stores the data in the scratchpad memory, and the read scratchpad, transfer the data from the scratchpad memory to the microcontroller. The DS18B20 has a default resolution of 12 bits and an increment of o C. The program calculates the temperature by adding first byte (LSB) and the second byte (MSB). The total of both bytes is checked if the MSB bit has the value of 1 by using the bitwise AND with a WORD (16 bits). If the total is negative the total will be computed as two s complement by XORing the total with a WORD of values all 1 (FFFFh) and adding 1 to the result; the result is used twice, it will be multiplied by 6 and it will be added with the result of the multiplication, and then divided by 4. The value is given as an integer, and to separate the integer with the fraction is calculated by dividing the total with 100 (integer) and using MOD (modulus) to have the residual of the division. The SDFat library has three classes: Sd2Card has raw access to SD flash memory cards, some of its functions are: o errorcode() returns the error code if any error was triggered o errordata() returns the data error o init() initializes an SD flash memory card SdVolume has access to Fat16 and Fat32 volumes on SD cards, some of its functions are: o init() - initializes the SD card s Fat volume SdFile has access to Fat 16 and Fat 32 files on an SD card, some of its functions are: o openroot() opens a volume s root directory o print() (used like the Arduino s print) prints the data to the file o open() opens a file or directory by the file name Team EQUIS 48 FRR v1.0

49 o isopen() indicates if the file can be created or not o writeerror() indicates if there were errors writing to the file o sync() causes modified data to be written to the SD card A file will be created at start-up and when the file closes the software will create a new file. The file names will be EQUIS in addition to three numbers from , with each file creation the numbers will increment, e.g. EQUIS000, EQUIS001, and so on. The pseudo code for the SD card is shown on Appendix C. The flowchart explained briefly (complete code on Appendix C): INPUT Receive time stamp Receive data from sensors Magnetometer Gyroscope Accelerometer Internal temperature OUTPUT Save to SD card Figure 48: Flight software control flow chart Team EQUIS 49 FRR v1.0

50 4.5 Thermal Design In order to maintain the electronic components inside the payload in their operative optimal temperature ranges and to reduce any measure errors (i.e. bias) that could appear due to temperature changes, a thermal control system will be adapted inside the payload. During this experiment the payload will be submitted mostly to the stratosphere thermal environment. This environment can reach temperature as low as -80 C and as high as 90 0 C and winds that fluctuate between 20mph to 100mph. These are the atmospheric conditions that would lead to drastic changes in the environment surrounding the equipment, producing damage in these devices. The thermal operating ranges of the main components inside the payload are presented in the following table: Electronic equipment Arduino Gyroscope Accelerometer Magnetometer Digital Temp. Sensor Real Time Clock -40 to 85( 0 C) -40 to 85( 0 C) -40 to 85( 0 C) -20 to 70( 0 C) -55 to125( 0 C) -40 to 85( 0 C) Table 9: Electronic temperature limits The table illustrates that the device that will limit the temperature parameter inside the payload is the magnetometer. Considering the temperature range of the magnetometer, a temperature of 10 0 C is selected as the lowest temperature allowed for the medium inside the payload. An evaluation of the overall thermal dissipation from the inside to the external environment was made to have an idea of the amount of thermal energy that is lost in the payload used for this application. The worst case scenario was considered in the analysis and the structure is study at 100,000ft above sea level. In addition is important to mention that the materials and their dimensions were determined before the analysis. This analysis was performed considering steady state conditions (i.e. no change at a point with time) and the coldest environment that the equipment can experience. The assumption of steady state conditions helps to solve the heat transfer problem without involving any differential equations or temperature distribution and permits the use of the thermal resistance concept. The concept of thermal resistance is used mainly for the case of steady heat conduction through walls or any solid material. Thermal resistances for the analysis of convection and radiation had been developed considering Newton s law of cooling and the Stefan-Boltzmann law, and the expressions obtained can be applied only at the boundary of the solid material where conduction occurs. The expressions that define the thermal resistances of the different heat transfer mechanism are the following: Conduction: Convection: Radiation: R cond = L/kAs R conv =1/h conv As R rad =1/h rad As To simplify even more the heat transfer analysis performed the overall heat transfer coefficient term is used so that the heat loss by the inner space can be expressed using only one expression instead of considering each heat transfer mechanism separately. This expression is analogous to Newton s law of cooling and has the following form: Team EQUIS 50 FRR v1.0

51 Q=UA T where: U = overall heat transfer coefficient UA = 1/R total Is important to mention that convection was examined in this analysis so that all the possible heat transfer mechanism that could occurred in the stratosphere can be considered. The stratosphere contains very dry air which is the medium that allows the presence of convection in that layer of the earth atmosphere (National Center for Atmospheric Research, 2009,. 4). Natural convection was considered in the payloads inside, but at the outside forced convection is the mean of heat transfer considered. For the analysis of natural convection at the payloads inside the following terms were determined: β = (1/T) ideal gas Gr L = Pr = Nu = represents the variation of the density of a fluid with temperature at a constant pressure. represents the ratio of the buoyancy force to the viscous force acting on the fluid. (Grashof number) represents the ratio between the velocity boundary layer and the thermal boundary layer form in the contact surface between a fluid and a solid surface. (Prandtl number) Dimensionless convection heat transfer convection (Nusselt number) For the analysis of external forced convection at the payloads outside the following terms were determined: Nu = Re = represents the enhancement of heat transfer through a fluid layer as a result of convection relative to conduction across the same fluid layer. represents the ratio between the inertial forces and the viscous forces. Used to determine the fluid flow regime. (Reynolds number) The terms used in the convection analysis are mainly used to define the convection heat transfer coefficient h which can be determine for different cases once the Nusselt number had been evaluated. The radiation in this analysis is only considered in the payloads inside and this is because the structure in this analysis is examined in the coldest environment that can occur only during night. For the evaluation of radiation in the payload the following equation was used: Team EQUIS 51 FRR v1.0

52 Q rad eq = є FR4 σa eq (Ts 4 - T in 4 ) A summary of the analysis performed is presented in the appendix. The results obtained show that for this application 5 W of heat are lost from the payload s inside. This were the results obtained from the analysis of the coldest environment that the payload can experience. The other case that was considered was the worst warm case that the payload can experiment. The measures considered to protect the payload for this case involve the use of reflective material in the walls of the payload s external structure to reflect a considerable portion of the sun rays received and also the walls of the external structure in its inside will be polished to improve the emissivity of the material so that the rate of heat transfer that moves from the inside to the outside can be increased. A table that illustrates how this surface treatment can change the emissivity of the material is the following: Aluminum 0 C Emissivity Unoxidized Commercial Sheet Roughly Polished Mechanical Design Table 10: Effects of the surface treatment in the emisivity The first step in the mechanical design was to determine which type of aluminum alloy was the appropriate for this application. This alloy was selected considering that the structures have to withstand thermal and mechanical loads during the various mission phases. Weight was another important parameter considered for the material selection, since there is a maximum value of mass that can t be exceeded in this project (i.e. 3kg). The materials examined are presented in the following table: Aluminum ρ (Mg/m³) (Mpa) (Mpa) K ( /m 6066-T T T Table 11: Alloy Selection The aluminum 6061-T6 was the alloy selected for this application because of its advantages compared with the other materials. As can be observed from the table this material posses the best combination of thermal and mechanical properties necessary for this application. In addition Polystyrene Foam was the insulating material selected for this project. Polyester foam was selected because of its low cost and low conductivity (i.e. 0.08W/mK). These characteristics are what make this material a good option for heat transfer problems, specifically for applications with weight limitation. The payloads geometry selected is basically a cube; this symmetrical geometry facilitates the structural and thermal analysis of the payload as well as the computation of any unknown dimension. The cube structure made Team EQUIS 52 FRR v1.0

53 of aluminum will be form using assembling methods that basically consist of joining aluminum square pieces using l shape brackets. This structure was selected considering the maintenance of the structural stresses within a considerable range during the payload s ascent and descent External Structure The external structure is basically a cube used to provide the first thermal and mechanical protection to the equipment inside the payload. It s a box built with polystyrene insulation in its core and aluminum skin at its outside. The external aluminum structure is constituted of four sides that are made using the aluminum alloy 6061 which is a common type of alloy used for space applications where the weight and resistance of the materials are important factors. The top cover of the external structure is also made from aluminum and is attached to the rest of the structure using brackets. The bottom cover is provided by HASP personnel and is attached to the rest of the structure using the same type of brackets used for the sides and top parts of the payload s structure. An illustration of the payload s wall is provided in the following figure: Figure 49:Payload s Top Cover The previous figures is used to illustrate the basic components of the payload structure. As can be observed from the figure the payload s walls will be painted with a reflective color at its outside surface and at the inside surface will be treated to increase the emissivity of the aluminum so that the payload s heat transfer rate from the inside can be increased. These features will help to prevent any overheating of the internal components due to the stratosphere s environment. A complete illustration of the payloads external structure is shown in the following figure: Team EQUIS 53 FRR v1.0

54 Figure 50: Internal View of the External Structure The mounting plate will be attached to the payload s external structure using L-shape brackets. The following figure is used to illustrate this feature. Figure 51: External Structure Drawing As can be observed from the previous figure four L-shape brackets will be used to secure the payload to the mounting plate. This amount of couplers will create a strong bond between the mounting plate and the payload s structure, which is required for the structure, since the payload will be exposed to a 10 g vertical and 5 g horizontal shock. An analysis was made using two different software (i.e. Solidworks and ANSYS) to determine the stresses develop during the payload flight whit the purpose of verifying that the structure is capable enough to resist the stresses developed in its components during its flight. Figures that illustrate the results obtained from these analyses are the following: Team EQUIS 54 FRR v1.0

55 Figure 52: Finite Element Analysis View 1 Figure 53 Finite Element Analysis View 2 The payload s walls were analyze separately considering the correspond load of each wall, that is a vertical shock of approximately 2.5 g and a horizontal shock of 5 g. The 2.5 g of vertical load comes from the fact that there will be 4 walls that act like columns supporting the 10 g of vertical shock. By inspection of the counter plots shown in the figures above it can be appreciated that as expected there will be a stress concentration in the regions near the holes for the bolts due to the area discontinuities in that section (i.e. less area supporting the stress). However, both contour plots show that the payload s walls are capable of withstanding the stresses developed during the payload s flight and this can be observe because the dominant color in both plots is blue, which represent in the plot s scale the lower values of stress. The complete external structure with its dimensions is presented in the following figure: Team EQUIS 55 FRR v1.0

56 Figure 54: Detail drawings of payload Internal Structure The internal case is used to provide thermal and structural support for the internal components which are in this case electronic devices. The internal case is basically a box build using polyester foam. The foam will be utilized as an insulation and also as a damper for any impact that the electronic components could experience during the payload s flight. The internal case has the same geometry and building concept used in the external structure, but with a difference in building materials and dimensions used. An example of how the payload should look from the its top is illustrated in the following figure: External Structure Insulation Electronic Components L-shape Brackets Figure 55: Top view payload structure Team EQUIS 56 FRR v1.0

57 Is important to mention that a set of holes will be made in the internal structure to route the electrical cables to the payload s inside. These cables are necessary for the electrical and data connections. The polyester foam used for the internal case is a material commonly used for payloads missions. The following table contain a list of important properties of the polyester foam: Polyester Foam Properties Density Thermal Specific Heat Young Modulus Tensile Strength Conductivity 1050 kg/m W/(m-K) 1.3 kj/kg.k 3000 MPa 46-60MPa Table 12 Polyester Properties The figure # contains a complete description of the payload s inside structure with all the dimensions and necessary views: Figure 56: View of punctures on structures The internal structure will be protected by the external structure which withstand all the loads directly and by the insulation material that enclose this part of the payload. All the important dimensions and drawing views of the external structure are provided in the following figure: Figure 57: Internal Structure Drawing Team EQUIS 57 FRR v1.0

58 4.6.3 Mass Budget In this project the maximum mass allowed for a small payload is 3kg. The approximate value of the total mass of our payload is g. This total mass was determined using values obtained from the Solidworks (CAD software) mass properties feature and considering approximated values for the PCBs and microcontroller (i.e. Arduino). The masses obtained directly from the software were the insulation, the external structure and the internal structure. The value of the PCBs were base in past experiment of this kind. To eliminate any bias introduced by the presumed mass values of the PCBs and to work in conservative range of values, the mass value of the PCBs observed in previous experiment was increased from 95g to 100g for each board. Also the mass value of the microcontroller board was approximated to 100g. The following table is used to show the payload s main components and their masses. Component Mass (grams) External Structure Internal Structure Insulation Two PCB (approximately) 200 Arduino 100 Total Mass Table 13: Mass Budget It can be observed considering the total mass value, that even with the increment of mass in the PCB values we still have g that can be used for any component that is not considered in this moment. 5.0 Payload Development Plan Prior to the payload fabrication in the development phase various task should accomplished such as verifying calculations, designs, prototyping and testing. This is done to resolve issues that can only be fulfilled through testing results made to the prototype. The areas that will be mostly focused on will be software, electrical and mechanical. On the software, tests and measurements will be obtained to identify the size of files developed when storing data to the SD card. It is necessary to establish the processing time of the program which is obtained by prototyping. Verify that all interfaces, connections, and programming will work as plan, otherwise apply the suitable contingency plan previously develop. Simulate or develop a model to ensure that the microcontroller can communicate through proper connections that will be used for telemetry purpose. The electrical section will involve prototyping the signal conditional for the external temperature sensor and the sun sensor to verify the output response and perform calibrations. Develop the complete design of the print circuit board and develop a prototype. Perform the prototyping and calibration for the temperature sensor. Proving that the degrees calculated with the sun sensor data are approximately identical to the sun positioning measured. Team EQUIS 58 FRR v1.0

59 Mechanical prototyping will be performed to ensure optimal quality in the payload s structure. Test will be performed to ensure the thermal characteristics calculated are similar to the characteristics and behavior physically. For the prototyping parts are necessary to be order with a degree of urgency thus requiring a organize list of parts with sequence. The order the part must be order is: 1. Arduino 2. Magnetometer 3. Gyroscope 4. Accelerometer 5. Slot and SD Memory Card SDHC compatible 6. Payload Structure materials More detail on order or purchase of parts can be observe in the table in section Payload Construction Plan When we have the component dimensions we will start sketching for a box that meets the size and making an estimate of the weight. After the sketching we will start making possible real size models and testing then. When we finish with the result we will make the final box and test it with all of the components. 6.1 Hardware Fabrication and Testing The hardware fabrication will be worked in parallel since the measurement of the payload enclosure is known, allowing the members to start their respective sections. There will be various tests done in the mechanical section such as thermal, impact, stress, strain and vibration. On the electrical part there will be test in current and power dissipation, verifying that circuits work properly. In the software development there will be a test of all sensors to make sure it is giving and storing the proper data. The parts and components will be ordered as soon as possible to prevent shipping delays. If a delay were to happen the team will work on other areas accordingly until the parts are received to reduce downtime. 6.2 Integration Plan A mechanical interface mounting plate will be provided to for the payload. The thickness of the mechanical interface mounting plate is ¼ PVC. The payload will be enough attached to the mounting plate that can handle 10g vertical and 5g horizontal shock. The mounting plate includes an EDAC connector for power. The EDAC connector will be the power interface between the payload and the HASP platform. Team EQUIS 59 FRR v1.0

60 Figure 58: EDAC pin layout The EDAC 516 for HASP has twenty pins as shows Figure 54. The pins function and the color code for the wires of the EDAC 516 are explained in the Table 13. Function EDAC Pins Wire Color 30VDC A, B, C, D White with red stripe Power Ground W, T, U, X White with black stripe Analog 1 K Blue Analog 2 M Red Signal Return L, R Black Discrete 1 F Brown Discrete 2 N Green Discrete 3 H Red with white stripe Discrete 4 P Black with white stripe Table 14: EDAC 516 pins function and color code As shows Table 1, the +30VDC delivered power from the HASP platform can be received through the pin A, B, C and D of the EDAC 516 interface and the ground can be provided by the pins W, T, U and X. 6.3 Software Implementation and Verification The first step is to design the program to meet the Pro 328 needs and run it for testing purposes. The sensor code will be develop separately and tested to verify proper functionality, then the code structure will be develop to join all the different sensor code and tests with the complete code. If errors and problems appear they will be verified for electrical errors, if no electrical errors code will be corrected. This phase will be executed as follow: Determine the required bytes Flowchart analysis Sensor calibration Display sensor data during testing Verify Arduino s processing time Team EQUIS 60 FRR v1.0

61 6.4 Flight Certification Testing To certify that the ADS payload is ready for flight it is necessary to reproduce test with conditions that could occur during flight, such as pressure, temperature changes and impact test when the payload is lands. By doing this prevents possible failures that can occur, such electrical failure due to any of the different conditions just mentioned. The following tests were concluded: Vacuum Test The testing will be done by: Styrofoam to hold the sensors in place Full system test o Payload shock testing o Payload temperature o Payload vacuum testing Electrical system testing o PCB board continuity test o Cable connection testing o Electronic components test (IC- integrated circuit testing) System Testing Procedures Vacuum Test The vacuum test was performed with in a vacuum chamber with the capability of (35psi) in the physics and astronomy department as shown in Figure 59. Figure 59 Psi Vacuum chamber The payload was placed in the chamber, sealed and the test was initiated. The test was fulfilled by raising the pressure by a factor of 10 up to 30psi, for each pressure the payload was left for 10 min as the pressure raised and as it went down to cero. Temperature Test This test requires placing the payload in four different temperatures stages, starting from the highest to the lowest temperature and then at the same rate reducing the temperature to the lowest. First it was placed outside at ambient temperature for 10min then it was placed at room temperature 25 o C, then it was place in a freezer for 10mins and then it will be place in a Team EQUIS 61 FRR v1.0

62 box with dry ice. Then the same procedure will be performed until the temperature is finally ambient temperature. Figure 60 shows the box where it was placed with dry ice. Shock test Figure 60 Chamber where temperature test was taken The shock test consist of dropping the payload while fully functional and talking data, from a height of approximately 10 feet as shown in Figure 61. Figure 61: Shock Test Team EQUIS 62 FRR v1.0

63 6.4.2 System Testing Results Vacuum Test During the time payload was tested it operated correctly during the complete test, the values obtained will be shown in the Table in Appendix D. The complete test the payload successfully kept gathering data and function properly... The values of the sensor remained throughout the test the same. In the result analysis after the calibration the data will be plotted and explained in detail. It is important to identify that the output is raw data, later it will be converted to significant values for each sensor. Temperature Test Throughout the temperature test the payload was being exposed to different temperatures for a determined period of time. The results of the data will be in Appendix D, the results should show that the all the components function properly during the complete test. The data that will have change will be the temperature; this data will be plotted as a temperature vs time analysis. Also plots of sensor data vs. temperature will be completed. Shock Test For the shock test the result showed that the payload is capable of a withstanding the impact while taking data from the sensor without failure. In Appendix D the table shown has the values obtained during this test. By observing the values it can be observed the electrical components and the structure is capable of passing the impact test. 7.0 Mission Operations Equipment final checkup Complete system integration Place the equipment on the launch site Ground platform tracking Data analysis o Data retrieval o Data conversion o Data plots o Plot analysis 7.1 Pre-Launch Requirements and Operations A successful flight testing in simulated environment (similar to that were the payload is going to be, such as vacuum and thermal testing) will be done to make sure that the sensors are working as expected. The Arduino also needs to boot up and run the pre-flight software to ensure the memory will be clean, in other words with 0 data in the SD card Calibrations Proper sensor calibration, with the recommended procedure suggested by the manufacturer, needs to be done to all of the sensors in the ADS payload. Team EQUIS 63 FRR v1.0

64 Magnetometer Calibration Calibration of the MicroMag3 is necessary to comprehend the raw data obtained by the attitude determination system, to obtain orientation. Calibration will be made by using a Helmholtz Coil shown in Figure 62, this payload is centered with two large coils (Helmholtz coils) to receive a uniform magnetic field. MM3 Figure 62 Helmholtz coils By placing the ADS payload in the center of the coil it is possible to compare the values of the magnetometer with the calculated values of the field in the Helmholtz. The field in the Helmholtz is calculated with the following equation: Where B= Magnetic filed in Teslas µ 0 = Magnetic permeability of vacuum in N/A 2 N= number of turns I = current in Amperes R= radius of the coil in meters The Helmholtz has an N of 70 turns and a radius for the coils of 26.4cm; with the power supply it is possible to find the magnetic field by knowing the current. The following equation is a simplified form of the previous equation to obtain the field magnitude with a controlled current. This test was done with the MM3 without ADS payload, the result obtained when the current was cero was approximately 400counts and with a current of 1A the output was approx on the positive x-axis similar, the count of the magnetic field was 8000counts. By applying the following we obtained a gain of 33.58counts/µT, this values is similar to the gain on the datasheet of 31.24counts/ µt. Team EQUIS 64 FRR v1.0

65 Notice on Table 14 the x-axis has values much larger than the other axis, because this is the concerning one at this instant. X Y Z Table 15 Example of raw data from the MM3 To convert the raw data all that needs to be done is to multiply the counts of the axis and multiply it by the gain calculated for that axis. For the each axis the same procedure must be done. The calibration values based on the data obtained at each axis both on the positive side and negative side can be obtained with the equations in Table 15. X offset = X max + X min Y offset = Y max + Y min Calculates the Offset Z offset = Z max + Z min X range = X max - X min Y range = Y max - Y min Z range = Z max - Z min Table 16: Calibration values Calculates the Range Where X max & X min are the maximum and minimum values obtained in the X-axis Y max & Y min are the maximum and minimum values obtained in the Y-axis Z max & Z min are the maximum and minimum values obtained in the X-axis To correct the offset the following equations in Table 16 must be applied to the values of the magnetometer. X value = Xraw - X Offset Y value = Yraw - Y Offset Z value = Zraw - Z Offset Table 17: Equations to correct offset Note that if the values of the X range are greater than the Y range it is necessary to match the gain by using the following equation: Since tan -1 results is only in the range of 0 to 90 it is important to note the sign of the X and Y to determine the proper quadrant and to add the correct padding to determine it direction, this is assisted by using the values in Table 17. X value Y value Formula Quadrant D= Ө +X +Y 0-90 D=180 - Ө -X +Y Team EQUIS 65 FRR v1.0

66 D=180+Ө -X -Y D=360 - Ө +X -Y Table 18: Quadrant determination To obtain the calibration equations the values obtained from the magnetometer are plotted and compared with the known magnetic field of the Helmholtz as in Figure 63. Figure 63: Helmholtz coil (X) vs MM3 (Y) With figure # it can be observe the a linear fit for the set data will allow a calibration equation which is F=0.9624(DCounts) Where F = Helmholtz field DC= Digital Counts (raw data) Digital Temperature Sensor (DS18B20) As mentioned in Section Technical Background and Sensors Subsystem, the internal temperature of the payload will be gathered using a DS18B20 Digital Temperature Sensor. The DS18B20 will be calibrated by placing this sensor with a calibrated temperature sensor (HOBO) inside the payload and exposing the payload to a temperature profile. These measurements will be stored during the temperature profile to develop a graph with both measures and compare the readings of the DS18B20 with the reading of the calibrated temperature sensor. A plot can be generated using both measurements to obtain an equation to adjust the output of the DS18B20 and calibrate the data obtained from this sensor; as a result, the data of the DS18B20 will be calibrated in the post flight analysis phase using the gathered equation to realize some adjustments to the output of the DS18B20. Team EQUIS 66 FRR v1.0

67 The temperature profile consists of the following environments; ambient temperature outside the building, ambient temperature inside the building, inside the fridge and inside the freezer. The payload will be on each environment for approximately 30 minutes. In addition, after the payload complete 10 minutes in the freezer it will return to the fridge for 10 minutes and to the other environments that it was previously exposed to complete a temperature profile. The calibrated temperature sensor that will be use is a HOBO, which is an indoor data logger that can measure and record temperature measurements. The temperature readings of the HOBO can be obtained using the software of the HOBO data logger and generate a plot of the temperature profile that the payload will be expose. In addition, the readings of the DS18B20 will be plotted to study the response of this instrument. The DS18B20 has a 1 wire interface and requires one port pin for communication. Through this pin data can be obtained and the Pro 328 can be send pulses to the DS18B20. The Pro 328 can be programmed to adjust the output of the DS18B20 sensor from the DQ pin after the payload has been retrieved and the data has been downloaded from the micro SD memory. A transaction sequence is required to establish communication with the DS18B20, which is explained in detail in the DS18B20 datasheet. The DS18B20 has the following temperature register format; LS BYTE BIT 7 BIT 6 BIT 5 BIT 4 BIT 3 BIT 2 BIT 1 BIT 0 BIT 15 BIT 14 BIT 13 BIT 12 BIT 11 BIT 10 BIT 9 BIT 8 MS BYTE S S S S S Where; S = Sign LS BYTE = Least significant Byte MS BYTE = Most significant Byte The Pro 328 will read the temperature measures of the DS18B20 during flight; the raw data is in digital format using both least significant byte and the most significant byte as shows the Table above. The DS18B20 will measure temperature in digital format. BIT 11 is will indicate the sign of the reading to determine if the measured temperature is a negative or a positive value. When S = 0 the value is positive and for negative values S = 1. The subsequent equations are required to shift the data from two bytes into a word and to convert the measures from digital quantities into physical quantities. The data shifting is realized using the following equation; Where; MSB = the Most Significant Byte LSB = the Least Significant Byte For a positive number (When S = 0) the temperature reading from the DS18B20 in digital format can be converted into a temperature value using the following equation; Team EQUIS 67 FRR v1.0

68 For a negative number (When S = 1) the temperature reading from the DS18B20 in digital format can be converted into a temperature value using the following equation; The temperature measurements are placed from BIT 4 to BIT 11; however, the code for the DS18B20 will shift 16 bit number, so that the measure will start at BIT 0 instead of BIT 4; as a result, the measurement value will be from BIT 0 to BIT 7. HOBO data ( C) DS18B20 data ( C) Table 19: DS18B20 versus HOBO temperature measures The Table 18 shows simulated measurements obtained from both; the DS18B20 temperature sensor and the HOBO during the temperature profile. Both sensors were inside the payload during the temperature profile. For the temperature profile the payload remained on each of the five different environments; ambient temperature outside the building, ambient temperature inside the building, the fridge, the freezer and the dry ice for approximately 10 minutes. Team EQUIS 68 FRR v1.0

69 Figure 64: Linear Fit Figure 64 shows the temperature measurements from both sensors; the DS18B20 and the HOBO temperature sensor. This graph was developed using the Graphical Analysis 3.2 software. Note that there is a small difference between the temperature measures of the DS18B20 and the HOBO measures; therefore, an equation is required to make fine adjustments to the change the output values from the sensor into a calibrated response. The subsequent equation is required to convert the measures from digital quantities into physical quantities. This equation was obtained using the data and the Graphical Analysis software; Where; The temperature measured by the DS18B20 The raw data of the DS18B20 The gain The Offset Accelerometer Calibration The SCA3000 Three axis accelerometer sensor will have an output response when a capacitance change occurs due to acceleration. Once the accelerometer sensor arrives the prototype for the accelerometer sensor will be implemented to perform the required tests. The accelerometer prototype will be exposed to at least three different acceleration positions on each one of its axes to determine the output response of the sensor at that particular acceleration. The next step is to assign a digital value to each one of the selected outputs response of the accelerometer to obtain a linear equation that will relate the outputs with the digital values. Gyroscope Calibration Team EQUIS 69 FRR v1.0

70 The ITG-3200 Three axis gyroscope sensor will measure the rate of rotation; as a result, the sensor will have an output response when sense a change in rotation in each one of the axis. Each axis will be rotated at approximately the same rate of rotation to have a similar calibration for each axis. After rotating each axis at a particular rate of rotation and obtain the output response, a linear equation can be created to relate the digital values with the gyroscope output response Pre-Launch Checklist Make sure all the instruments are working properly Realize a final check of the prototype comparing it with the schematics and the simulations Revise the list of test, such as thermal and vacuum test to ensure that all the testing has been accomplish Run all the program and make sure are working properly Bring all the necessary equipment for any emergency 7.2 Flight Requirements, Operations and Recovery The payload will ascend up to an altitude of 120,000 ft for approximately 2 hours and remain there for 16 hours total. The payload and components will have to support temperature conditions of an expected -40 degree of temperature. The system needs the sensors to read all the time to get all the data during the flight. The batteries must be able to support the flight with the minimum required power. If the batteries are not in the minimum required power then the circuit would be in equilibrium with the sensor voltage required for them to work. The experiment needs a GPS or any radiofrequency tracking device of high power so we can track the altitude in which the payload is located and to track the retrieval of the payload in the landing site. 7.3 Data Acquisition and Analysis Plan The Arduino Pro requires an SD card memory module for the storage of the data during the flight then we going to download the data using an Arduino Pro and a serial/usb cable in which is going to be connected from the payload to the computer software but to process the receiving data we need to convert the measurement in ADC counts requiring some equations for the convection of ADC to physical values then we analyze the data of the atmosphere and flight of the payload Ground Software The ground software requires the following components; a microcontroller (Atmega 328), a serial/usb cable, the code to download the data and a computer to process the information and download the data from the payload. Graphical analysis 3.2 for plot the data will also be needed Data Analysis Plan Team EQUIS 70 FRR v1.0

71 The first step on the ground station after the land will be to use the post flight program to take the data from the payload. The software will be prepared using the Arduino IDE. We will implement some software for the calibration of the sensors. The data will be store using ADC counts to represent the measurements from the sensors. In the process of receiving the data, the ADC will convert the measurements into ADC counts that will be stored in the SD card. This requires some equations to convert from ADC counts to physical values. Some uncertainties during the launch are expected as well as in the balloon cut off and in the landing. Expecting those irregularities, make some extra calibrations looking for the most precise measurements. 8.0 Project Management To ensure documentation version control a single team member (A.M. Espinal Mena) will be the team member that will have the latest version of all the documentation. It has been agreed that when a team member do a modification in the PDR, CDR and FRR they have to send an of the modification to this team member, so she can add it to the proper document and send a notification to the rest of the team so they can now which parts has been updated. In addition to the days of class regular meetings in the week to monitor the progress of the project will be scheduled. 8.1 Organization and Responsibilities The EQUIS Team consists of three students of the Inter American University of Puerto Rico, Bayamón Campus. The responsibilities of these students are to work on the following part of their experiment; the electrical/mechanical designs, prototype development, fabrication, integration and testing of the payload that will be launch with a balloon. The name of the students of the EQUIS Team and their tasks are as follows: A. M. Espinal Mena, anaespinal@gmail.com, Electrical Design, Prototype and Calibration E. M. Portilla Matías, marsarf@gmail.com, Software Design and Implementation F. O. Rivera Vélez, felix.omar@yahoo.com, Mechanical and Thermal Design J. I. Espinosa Acevedo, j.23.espinosa.13@gmail.com, Prototype and Calibrstion, Risks and Management plan 8.2 Configuration Management Plan Every time a design is made we consult with the team member so we can make a decision of the design and to analyze de advantage and disadvantage of the design before getting approved. 8.3 Interface Control Interface control allows us to maintain a constant monitoring of the Flight Readiness Review (FRR) document at all times. It was established in a group meeting to assign one person in charge of the FRR, this person will be in charge of constantly adding new information to the document and uploading its final version, this way every member will allow access to the file. Also an online group section was established where all document will be uploaded. It was notified to the members that every time a document is uploaded or any change will be made to Team EQUIS 71 FRR v1.0

72 notify Ana Espinal through a call, which is the person in charge of the FRR, doing so she will be aware of any modifications. Finally a group meeting will be held to verified the complete document and ensure it is the final version before submitting. 9.0 Master Schedule We establish to divide the tasks into different member of the team but some task will be in parallel with the other task, because this will makes us to meet the experiment goal. The amount of days assigned to each task is shown in the Figure 62. Following the work breakdown schedule is essential to realize the mission of this experiment. 9.1 Work Breakdown Structure (WBS) Figure 65: WBS- Work Breakdown Schedule Figure 65 shows the WBS of the EQUIS team to complete the EQUIS payload and instruments on time. 9.2 Staffing Plan A. M. Espinal Mena- Electrical design, Prototype and Calibration E. M. Portilla Matías- Software Design and Implementation F. O. Rivera Vélez- Mechanical and Thermal Design J. I. Espinosa Acevedo- Prototype and Calibrstion, Risks and Management plan Advisor: Dr. H. B. VO/ E. G. Delgado Team EQUIS 72 FRR v1.0

73 9.3 Timeline and Milestones The PDR, CDR and FRR documents have to be submitted by the following deadlines: PDR- Preliminary Design Review due March 5, 2010 PDR Revision- Preliminary Design Review Revision due April 12, 2010 PDR Defense- Preliminary Design Review Defense June 4, 2010 CDR- Critical Design Review due July 1, 2010 FRR- Flight Readiness Review due July 23, Master Budget The maximum capital cost budget required for this project is $5,000. It is also required to have a reserve contingency fund of 10%, which is $500 in this case; therefore, the capital cost budget is $4, Expenditure Plan Integrating the instruments for the ADS experiment requires several components. Table 13 shows the list of electronic components necessary to integrate the instruments, their price and delivery status. Lead time Sensors Part Sales Quantity Status Price ($) Number Company 1 Three Axis Accelerometer SCA3000 Sparkfun 2 - $89.98 ($44.99 each) 1 Three Axis Gyroscope 1 Three Axis Magnetometer ITG-3200 Sparkfun 2 - $99.90 ($49.95 each) Micromag3 Sparkfun 2 - $ ($59.95 each) 1 Digital Temperature Sensor DS18B20 Sparkfun 2 - $8.50 ($4.25each) 1 Level Shift Converter 8745 Sparkfun 10 - $19.50 ($1.95 each) 1 San Disk 4 GB SDSDB- Amazon 2 - $17.98 ($8.99) 004GA14F 1 Arduino Pro DEV Sparkfun 2 - $39.90 ($19.95 each) 1 microsd BOB Sparkfun 2 - $29.90 ($14.95 each) transflash 1 Material for housing - $500 Team EQUIS 73 FRR v1.0

74 1 Extra PCB board - $300 1 Real Time Clock DS1306 Maxim 2 - $12.72 ($6.36 each) -- Total Cost: - $ Risk Management and Contingency Risk Type Electrical Mechanical Software Risk Exceed component s temperature Faulty connection between cables Impact Severity Assessment of Risk Likelihood Probability Detention Difficulty HIGH HIGH MEDIUM HIGH HIGH MEDIUM Short circuit HIGH MEDIUM MEDIUM SD card failure HIGH LOW MEDIUM Temperature Leakage into payload HIGH MEDIUM MEDIUM Structure Failure HIGH LOW MEDIUM Loosening of nuts and bolts due to vibration Fall into wet terrain MEDIUM LOW LOW HIGH MEDIUM LOW Data Corruption HIGH HIGH HIGH Loss of Data due to Overwriting Improper Logic Programming Table 20: Materials Acquirement & Costs HIGH HIGH MEDIUM HIGH MEDIUM HIGH Risk Control Measures Provide a heating system Ensure connections and strap cable to prevent movement Review the PCB population process Transmit through Telemetry Pressure and temperature testing Minimize apertures, use alloy 2014 and mono-block design Use pressure bolts Ensure proper sealing of Payload Store Data in SD memory card Divide SD in sectors of 512bytes Test program before flight Team EQUIS 74 FRR v1.0

75 Scheduling Insufficient memory storage Not meeting FRR deadline HIGH HIGH LOW HIGH MEDIUM MEDIUM Errors in FRR HIGH MEDIUM MEDIUM Table 21: Risk Management & Contingency Obtain memory card with greater storage Getting more hours of work and more days in the lab Review document various time Through a risk management it is possible to reduce the likelihood of unexpected events. By having a contingency plan it is possible to reduce costs and severity of a risk. This is done by identifying, assessing and developing a strategy to response for each risk, while monitoring for additional risks as shown in Figure 66. Table 14shows the potential risks that the EQUIS experiment may encounter and the contingency plan that the ADS team has for each of these risks. As illustrated in the Table 14, the potential risks have several categories. It is important to keep constant cycle of risk management in order to control possible variables that may affect project performance. Figure 66: Risk Management Cycle Team EQUIS 75 FRR v1.0

76 12.0 Glossary CDR Critical Design Review FRR Flight Readiness Review PDR Preliminary Design Review TBD To be determined TBS To be supplied WBS Work breakdown structure HASP High Altitude Student Platform ITS Internal Temperature Sensor ADS Attitude Determination System EQUIS Experiment with Quality United In Science NEU North-East-Up MRI Magnetic Resonance Imaging GPS Global Positioning Satellite SD Secure Digital USB Universal Serial Bus EEPROM Electrically Erasable Programmable Read-Only Memory ADC Analog to Digital Converter FET Field Effect Transistor IC Integrated Circuits PCB Printed Circuit Board LSB Least significant byte MSB Most significant byte Team EQUIS 76 FRR v1.0

77 Appendix Appendix A I. Data. T out = C Q emt eq = 1W (computed) T in = 0 0 C (design parameter) k alm = 134W/m 0 C k ins = 0.12 W/m 0 C L alm = m L ins = 0.005m σ = 5.67X10-8W/m 2 K 4 (Stefan-Boltzmann const.) є FR4 = 0.8 є Alm = 0.07 (rough surface) ѵ air@100000ft = 8.012X10 4 m 2 /s ρ air@100000ft = 1.841X10-2 kg/m 3 II. Find Q loss =? III. Diagrams V mean@100000ft = 26.82m/s μ air@100000ft = 1.475X10-5 kg/m s Figure 67: Heat Loss Analysis Team EQUIS 77 FRR v1.0