Sensorless Position Estimation in Fault-Tolerant Permanent Magnet AC Motor Drives with Redundancy

Transcription

1 Sensorless Position Estimation in Fault-Tolerant Permanent Magnet AC Motor Drives with Redundancy Jae Sam An Thesis submitted for the degree of Doctor of Philosophy The School of Electrical & Electronic Engineering Faculty of Engineering Computer & Mathematical Sciences The University of Adelaide Australia September 2010

2 Copyright 2010 Jae Sam An All Rights Reserved.

3 Table of Contents Table of Contents.i Abstract....v Declaration vii Acknowledgements....ix List of Figures. xi List of Tables. xv Symbols and Abbreviations...xvii Chapter 1 Introduction Overview Literature Review Objectives Outline of Thesis.8 Chapter 2 The Fault-Tolerant Motor Drive Topology and Control Principles Introduction The Motor and Inverter The Brushless PM Motor Modules Three-Phase H-Bridge Inverter Sinusoidal Current Excitation Current and Torque Control Current Control Torque Control Conclusion 21 Chapter 3 Survey of Sensorless Position Estimation Methods in PMAC Motors i

4 3.1 Introduction Sensorless Position Estimation Methods in Trapezoidal PMAC Motors Techniques Based on the Back EMF Detection Techniques Based on the Stator Third Harmonic Voltage Techniques Based on Conducting States of Free-Wheeling Diodes Sensorless Position Estimation Methods in Sinusoidal PMAC Motors Techniques Based on the Flux Linkages Techniques Based on Kalman Filters Techniques Based on State Observers Techniques Based on Magnetic Saliencies Starting Techniques Conclusions Chapter 4 Mathematical Modeling and Simulation of the Motor Drive Introduction Modeling of the Fault-Tolerant Three-Phase PMAC Motors with Redundancy Simulation of the Fault-Tolerant Motor Drive Simulink Model for the Steady State Operation Simulation Model for the Dynamic State Operations Simulation Results Steady State Results Dynamic State Results Conclusions Chapter 5 Principles and Simulation of Fault-Tolerant Sensorless Position Estimation Methods Introduction ii

5 5.2 Principles of the Fault-Tolerant Three-Phase Position Estimation Method Rotor Position Estimation Based on Flux Linkage Increment A Single Final Rotor Position Estimate Principles of the Fault-Tolerant Two-Phase Sensorless Position Estimation Method The Modified Flux Linkage Incremental Algorithm Estimation of a Final Rotor Position Computer Simulation of the Fault-Tolerant Sensorless Position Estimation Methods Simulation Results Steady State Operation and Position Estimation Simulation Studies to Investigate the Dynamic Operation Operation Under Faults Conclusions...97 Chapter 6 Analysis of the Position Estimators using the Real Time Off-Line Data Introduction The System Hardware of the Motor Drive Data Acquisition and Data Processing Data Acquisition System Principles of the Real-Time Data Processing iii

6 for Position Estimation Experimental Results Steady-State Test Results Dynamic-State Operation Operations under Faults Conclusions.135 Chapter 7 General Conclusions and Suggestions for the Future Study Summary of Thesis Key Results Suggestions for Future Research Publications References iv

7 Abstract Safety critical applications are heavily dependent on fault-tolerant motor drives being capable of continuing to operate satisfactorily under faults. This research utilizes a fault-tolerant PMAC motor drive with redundancy involving dual drives to provide parallel redundancy where each drive has electrically magnetically thermally and physically independent phases to improve its fault-tolerant capabilities. PMAC motor drives can offer high power and torque densities which are essential in high performance applications for example more-electric airplanes. In this thesis two sensorless algorithms are proposed to estimate the rotor position in a fault-tolerant three-phase surface-mounted sinusoidal PMAC motor drive with redundancy under normal and faulted operating conditions. The key aims are to improve the reliability by eliminating the use of a position sensor which is one of major sources of failures as well as by offering fault-tolerant position estimation. The algorithms utilize measurements of the winding currents and phase voltages to compute flux linkage increments without integration hence producing the predicted position values. Estimation errors due to parameter variations and inaccurate measurements are compensated for by a modified phase-locked loop technique which forces the predicted positions to track the flux linkage increments finally generating the rotor position estimate. The fault-tolerant three-phase sensorless position estimation method utilizes the measured data from the three phase windings in each drive consequently obtaining a total of two position estimates. However the fault-tolerant two-phase sensorless position estimation method uses measurements from pairs of phases and produces three position estimates for each drive. Therefore six position estimates are available in the dual drive system. In normal operation all of these position estimates can be averaged to achieve a final rotor angle estimate in both schemes. Under faulted operating conditions on the other hand a final position estimate should be achieved by averaging position estimates obtained with measurements from healthy phases since unacceptable estimation errors can be created by making use of measured values from phases with failures. v

8 In order to validate the effectiveness of the proposed fault-tolerant sensorless position estimation schemes the algorithms were tested using both simulated data and offline measured data from an experimental fault-tolerant PMAC motor drive system. In the healthy condition both techniques presented good performance with acceptable accuracies under low and high steady-state speeds starting from standstill and step load changes. In addition they had robustness against parameter variations and measurement errors as well as the ability to recover quickly from large incorrect initial position information. Under faulted operating conditions such as sensor failures however the two-phase sensorless method was more reliable than the threephase sensorless method since it could operate even with a faulty phase. vi

9 Declaration This work contains no material which has been accepted for the award of any other degree or diploma in any university or other tertiary institution to Jae Sam An and to the best of my knowledge and belief contains no material previously published or written by another person except where due reference has been made in the text. I give consent to this copy of my thesis when deposited in the University Library being made available for loan and photocopying subject to the provisions of the Copyright Act I also give permission for the digital version of my thesis to be made available on the web via the University s digital research repository the Library catalogue the Australasian Digital Theses Program (ADTP) and also through web search engines unless permission has been granted by the University to restrict access for a period of time. Signed: Date: vii

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11 Acknowledgements I wish to thank my supervisor Associate Professor Nesimi Ertugrul for his advice guidance idea support motivation and kindness during this research. I am also happy to thank my co-supervisor Dr. Wen L. Soong for his warmth smile direction encouragement knowledge assistance and suggestion. I would like to thank all colleagues in my laboratory for their support encouragement and friendship. In particular my thanks are going to Dr. Jingwei Zhu for his help in my experimental works by providing a fault-tolerant PMAC motor drive system and its control. Dr. Ameen Gargoom has given a lot of kind assistance for my LabVIEW programming tasks as well. I am pleased to thank members of the School of Electrical and Electronic Engineering for their administrative assistance computing support technical help and friendship. I also thank staff of the international student centre of the University of Adelaide for their assistance in student VISA matters. This thesis would not have been possible without my wife s endless love encouragement and support. I am also grateful to my cute son for his birth during my study in Australia. I thank my family and relatives in Korea for their help. Jae Sam An September 2010 Adelaide Australia. ix

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13 List of Figures 2.1 Block diagram of a prototype of the fault-tolerant three-phase surfacemounted sinusoidal PMAC motor drive system with redundancy (a) Conventional winding arrangement [28] (b) fault-tolerant winding arrangement [29] for a three-phase surface-mounted PMAC motor Schematic diagrams of a conventional three-phase inverter for a conventional PMAC motor with Y-type winding configuration (a) and a three-phase H-bridge inverter utilized in a fault-tolerant three-phase motor (b) The schematic diagram of the hysteresis current control for the three-phase windings a b and c The principles of the operation of a hysteresis controller for one motor phase (a) Inverter schematic diagram (b) typical waveforms of the inverter based on the bipolar voltage PWM switching modulation scheme The schematic diagram of the torque control in the fault-tolerant three-phase PMAC motor drive The equivalent circuit of the fault-tolerant three-phase surface-mounted sinusoidal PMAC motor with redundancy A Simulink model of the torque control of the fault-tolerant motor drive with redundancy for steady-state operation (a) A Simulink model of the fault-tolerant three-phase surface-mounted sinusoidal PMAC motor drive 1 xi

14 (b) a schematic block diagram of one phase of the drive The dynamic model of the entire drive (a) schematic block diagram (b) Simulink model Simulation results of the motor drive under a steady-state mechanical rotor speed of 31.4/s with no phase advance or delay angle Simulation results of the fault-tolerant three-phase surface-mounted sinusoidal PMAC motor drive with redundancy under a steady-state constant mechanical rotor speed of /s with no phase advance or delay angle Simulation results of the motor drive under a steady-state constant mechanical rotor speed of /s and at the phase advance angle of π Simulation results under dynamic operation while the motor starts from standstill Block diagram of the fault-tolerant three-phase sensorless rotor position estimation method for the motor drive module The block diagram of the position estimation method given for a pair of phases Simulink models of (a) the fault-tolerant three-phase sensorless position estimation method for the fault-tolerant PMAC motor drive 1 and (b) the fault-tolerant two-phase sensorless position estimation method (for a pair of phases A and B of the motor module 1) Steady state performance of the fault-tolerant PMAC motor drive 1 at low speed operation (300 rpm) Steady- state performance of the motor drive 1 at a high speed operation of 2100 rpm. 80 xii

15 5.6 Steady-state performance of the motor drive 1 at an operating speed of 2100 rpm (high speed) and with an incorrect initial position The position errors in the motor drive 1 at a speed of 2100 rpm and under the parameter variations: Blue trace ( ε ) Purple trace ( ε 3 ph ) The position errors in the motor drive 1 at a speed of 2100 rpm and under 2 ph the measurement errors: Blue trace ( ε ) Purple trace ( ε 3 ph ) Starting performance of the motor drive 1. (a) phase currents and voltages (b) actual and estimated rotor positions (c) 3ph position estimate 2 ph and estimation errors Starting performance of the motor drive 1 with an incorrect initial position Dynamic operation performance of the motor drive 1 under step load changes Characteristic waveforms of the motor drive 1 under an open-winding fault in the phase C Performance of the position estimators in the motor drive 1 under (a) a current sensor fault (with 10 times greater gain) in phase A (b) a voltage sensor fault (with 10 times greater than the original gain) in phase A A photo of the fault-tolerant motor drive hardware The principal block diagram of the torque control of the fault-tolerant three-phase PMAC motor drive and the data acquisition system The photo of the data acquisition system (a) The block diagram and (b) the front panel of the LabVIEW-based data acquisition system used for the real time data capturing The block diagrams ((a) and (b)) and (c) the front panel of the custom xiii

16 LabVIEW VIs of the two-phase and the three-phase position estimation methods Steady-state test results of the motor drive 1 at a low speed of 300 rpm Steady-state performance of the motor drive 1 at high speed operation (2100 rpm) Steady-state Pperformance of the motor drive 1 at 2100 rpm while starting with an different incorrect initial rotor position Steady-state performance of the position estimators at 2100 rpm for the different motor parameters: ε ε 3 ph Steady-state test results at 2100 rpm and under measurement errors. 2 ph From the top: ε ε 3 ph for each test case ph 6.11 Starting performance of the motor drive Starting performance of the motor drive 1 with an initial position error of Dynamic performance of the motor drive 1 with a step load change (deceleration test) Dynamic performance of the motor drive 1 with a step load change (acceleration test) Performance of the position estimators under an open-winding fault in the phase A Operation performance of the motor drive 1 under (a) a current sensor fault in Phase A and (b) a voltage sensor fault in Phase A xiv

17 List of Tables 2.1 Operation modes of the hysteresis current regulated H-bridge type inverter based on the bipolar voltage switching method in winding phase A of the motor drive Parameters of the motor modules used in the simulation studies Summary of the available rotor position estimates with and without faults Summary of the available rotor position estimates with and without faults in the motor drive RMS position estimation error under steady-state operation RMS position estimation error under parameter variations RMS position estimation error under inaccurate measurements RMS position estimation errors under a current or a voltage sensor fault in Phase A (introducing a gain that is 10 times greater compared to its original value The motor parameters of the motor modules RMS position estimation error in computer simulation and offline tests under low and high speed steady-state operation RMS position estimation error in computer simulation and offline tests under parameter variations RMS position estimation error in computer simulation and offline tests under inaccurate measurements RMS position estimation error in computer simulation and offline tests under a current or voltage sensor fault in Phase A xv

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19 Symbols and Abbreviations B damping coefficient of the motor and mechanical load Nm//s h hysteresis bandwidth A i a i u i b i v i c i w phase current increments between samples A ψ amplitude of the flux linkage increments Wb ψ b ψ c ψ a ψ v ψ w ψ u phase flux linkage increments between samples Wb t sampling time s θb θc θ a θ u θv θw estimated electrical rotor position increments of corresponding phases between samples θ ab θbc θ uv θvw θca θwu δθ ab δθ bc δθ ca δθ uv δθ vw δθ wu rotor position increments obtained by utilizing pairs of phases A-B B-C C-A U-V V-W and W-U in the fault-tolerant PMAC motor modules 1 and 2 phase differences between the flux linkage increments and the back EMF functions with respect to the predicted rotor position for pairs of phases A-B B-C C-A U-V V-W and W-U in the motor modules 1 and 2 θ rotor position increments in the motor modules 1 2 θ 1 and 2 δθ 1 δθ 2 phase differences between the phase angles of the flux linkage increments and the predicted rotor positions e a e b e c phase back EMF voltages V xvii

20 e u e v e w e ( ) e ( ) e ( ) 1 θ 2 θ 3 θ phase back EMF functions e ( ) e ( ) e ( ) 4 θ 5 θ i a i b i c i u i v i w 6 θ phase currents A i a (0) initial value of winding current in phase A A * i a i * i * b c reference phase currents for the stator windings of the motor module 1 A I amplitude of the excitation current command A m J inertia of the motor and connected load kgm 2 K gain of the phase detector k ( k 1) integers representing the k -th and ( k 1)-th sampling instants k Back-EMF constant V//s e K p K i proportional and integral gains of the PI controller L phase inductance H p number of pole pairs ω mechanical angular speed of the rotor /s r 1 integrator s R phase resistance Ω T net electromagnetic torque Nm e T ea T eb T ec T eu T ev T ew phase electromagnetic torques Nm T e1 e2 T electromagnetic torques generated by the motor modules 1 and 2 Nm xviii

21 θ electrical rotor position θ ab θ bc θ ca * * θ ( k) θ ( k) ab bc * * θ ( k) θ ( k) ca uv * * θ ( k) θ ( k) vw wu θ ( k 1) θ ( k 1) ab bc θ ( k 1) θ ( k 1) ca uv θ ( k 1) θ ( k 1) vw wu electrical rotor position estimates obtained between phases A-B B-C and C-A predicted rotor position values rotor position estimates at the previous sampling instant ( k 1) ε ab θ actual electrical rotor position of the fault-tolerant act PMAC motor drive ε bc ε position estimation errors given from phases A-B ca B-C and C-A θ θ phase angles of the flux linkage increments 2 f 1 f θ ( ) θ ( ) rotor position estimates of the motor 1 k 2 k modules 1 and 2 * * θ ( ) θ ( ) predicted electrical rotor position values of the 1 k 2 k θ 3 ph 3 ph 2 ph motor modules 1 and 2 ε electrical rotor position estimate and position estimation error of the motor module 1 obtained by the three-phase position estimator θ ε averaged electrical rotor position estimate and the 2 ph averaged electrical position estimation error of the motor module 1 obtained by the two-phase position estimator θ ( k 1) θ ( k 1) previous electrical rotor position estimates 1 2 obtained at the ( k 1)-th instant θ mechanical rotor position r xix

22 T load torque Nm l v a v b v c phase voltages V v u v v v w v AN v terminal voltage drop between the point A and the AB point B v terminal voltages at the points A and B with BN respect to the earthed negative DC power supply V V rail respectively V dc DC link input power supply voltage for the conventional three-phase inverter V V V DC link power supply voltages for the three-phase 2 dc1 dc H-bridge inverter sets 1 and 2 V A (or a) B (or b) phases of the motor modules 1 and 2 C (or c) U (or u) V (or v) W (or w) AC A/D BLDC CPU CT d-axis DIO DC DC Supply 1 alternating current analog to digital brushless direct current central processing unit current transducer direct axis digital input and output direct current DC input power supplies DC Supply 2 D1 D2 D3 D4 freewheeling diodes d-q direct-quadrature xx

23 (d-axis or q-axis) DSP EKF EMF FDI GUI H-inverter H/W E INFORM I/O IPM IPMSM K MOSFET MS MSPS P rail N rail (direct-axis or quadrature-axis) digital signal processor extended Kalman filter electromotive force fault detection and isolation graphical user interface H-bridge type inverter hardware incremental encoder indirect flux detection by on-line reactance measurement input and output interior permanent magnet interior permanent magnet synchronous motor kilo metal-oxide-semiconductor field-effect transistor mega samples mega samples per second positive and negative DC power supply rails of the inverter N P north and south magnetic poles of permanent magnets mounted on the rotor PC PI PLL PM PMAC PMSM personal computer proportional integral phase-locked loop permanent magnet permanent magnet alternating current permanent magnet synchronous motor xxi

24 PPR PWM q-axis QEI RMS rpm RTSI SMPM SNR pulses per revolution pulse width modulation quadrature axis quadrature encoder interface root mean square revolutions per minute real-time system integration bus surface-mounted permanent magnet signal-to-noise ratio S1 S2 S3 S4 power switches SPM SPMSM SRM S/W UART VI ZOH surface-mounted permanent magnet surface permanent magnet synchronous motor switched reluctance motor software universal asynchronous receiver/transmitter virtual Instruments zero order hold xxii