Parameter Estimation of Permanent Magnet Synchronous Machines reviews estimation techniques of the parameters of PMSMs, introducing basic models and techniques, as well as issues and solutions in parameter estimation challenges, including rank deficiency, inverter nonlinearity, and magnetic saturation. This book is supported by theories, experiments, and simulation examples for each technique covered.
Topics explored in this book include: - Electrical and mechanical parameter estimation techniques, including those based on current/voltage injection and position offset injection, under constant or variable speed and load for sensored or sensorless controlled PMSMs, accounting for magnetic saturation, cross-coupling, inverter nonlinearity, temperature effects, and more - Recursive least squares, the Kalman filter, model reference adaptive systems, Adaline neural networks, gradient-based methods, particle swarm optimization, and genetic algorithms - Applications of parameter estimation techniques for improvement of control performance, sensorless control, thermal condition monitoring, and fault diagnosis
Parameter Estimation of Permanent Magnet Synchronous Machines, is an essential reference for professionals working on the control and design of electrical machines, researchers studying electric vehicles, wind power generators, aerospace, industrial drives, automation systems, robots, and domestic appliances, as well as advanced undergraduate and graduate students in related programs of study.
Table of Contents
AUTHORS
PREFACE
LIST OF ABBREVIATIONS
LIST OF SYMBOLS
CHAPTER 1 GENERAL INTRODUCTION
1.1 Introduction
1.2 Permanent Magnet Machines
1.3 Basic Equations and Machine Parameters
1.3.1 Fundamental mathematical model for PMSMs
1.3.2 Mathematical model considering magnetic saturation, thermal effect, and iron loss
1.4 Drives and Control Strategies
1.4.1 Drive system of PMSM
1.4.2 Space vector pulse width modulation
1.5 Outline of Parameter Estimation Techniques
1.5.1 Offline parameter estimation
1.5.2 Online parameter estimation
1.6 Scope of This Book
References
CHAPTER 2 CRITICAL ISSUES WITH ONLINE PARAMETER ESTIMATION
2.1 Rank-deficient Problem
2.1.1 Rank-deficient issue
2.1.2 Experimental analysis and results
2.2 Nonlinearity of Voltage Source Inverter
2.2.1 Modelling of VSI nonlinearity
2.2.2 VSI nonlinearity estimation and compensation
2.2.3 Influences of VSI nonlinearity on parameter estimation
2.3 Ill-conditioned Problem
2.4 Summary
References
CHAPTER 3 ONLINE ESTIMATION OF ROTOR FLUX LINKAGE WITH AID OF THERMOCOUPLES IN STATOR WINDINGS
3.1 Introduction
3.2 Online Estimation of Rotor flux Linkage with Aid of Thermocouples in Stator Windings
3.2.1 Online estimation of rotor flux linkage
3.2.2 Thermal condition monitoring of rotor PM
3.3 Summary
References
CHAPTER 4 ONLINE PARAMETER ESTIMATION BASED ON CURRENT INJECTIONS
4.1 Introduction
4.2 Multi-parameter Estimation Based on Current Injection and Error Analysis
4.2.1 Designed parameter estimation scheme
4.2.2 Error analysis
4.2.3 Experimental results
4.3 Winding Resistance and Rotor Flux Linkage Estimation Based on Current Injection under Constant Torque/Speed Control
4.3.1 Designed parameter estimation scheme
4.3.2 Error analysis and experimental validation
4.4 Summary
References
CHAPTER 5 ONLINE PARAMETER ESTIMATION BASED ON POSITION OFFSET INJECTION
5.1 Introduction
5.2 Phasor Analysis of Rotor Position Offset in PMSMs
5.3 Position Offset-based Estimation with under Constant Torque/Speed Control
5.3.1 Designed estimation method
5.3.2 Experimental and FEA results
5.4 Position Offset-based Estimation with under Constant Torque/Variable Speed Control
5.4.1 Designed estimation method
5.4.2 Experimental and FEA results
5.5 Position Offset-based Estimation with id≠0 under Constant Torque/Speed Control
5.5.1 Designed estimation method
5.5.2 Experimental and FEA results
5.6 Position Offset-based Estimation with & id≠0 under Constant and Variable Speed Control
5.6.1 Designed estimation method
5.6.2 Experimental and FEA results
5.7 Analysis of Amplitude of Position Offset Injection
5.8 Summary
References
CHAPTER 6 ONLINE PARAMETER ESTIMATION UNDER VARIABLE SPEED CONTROL
6.1 Introduction
6.2 Estimation of Stator Resistance, Inductances, and Rotor PM Flux Linkage
6.2.1 Identifiability analysis and influence of VSI nonlinearity
6.2.2 Improved estimation scheme
6.2.3 Experimental results
6.3 Estimation of dq-axis Flux Linkage Maps with Uncertainties of Circuit Resistance and Inverter Nonlinearity
6.3.1 Modelling of penalty functions for identification of flux linkages
6.3.2 Minimisation of penalty functions
6.3.3 Experimental results
6.4 Summary
References
CHAPTER 7 ESTIMATION OF MAGNETIC SATURATION AND CROSS-COUPLING BASED ON HIGH-FREQUENCY SIGNAL INJECTION
7.1 Introduction
7.2 Magnetic Saturation Modelling and Time Delay Effect in High-frequency Signal Injection
7.2.1 Fundamental mathematical model
7.2.2 Time delay effect in high-frequency signal injection methods
7.3 High-frequency Rotating Voltage Injection Method
7.4 High-frequency Pulsating Voltage Injection Method
7.4.1 With aid of position estimator
7.4.2 Without aid of position estimator
7.5 Combined High-frequency Rotating and Pulsating Voltage Injection Method
7.6 Experimental Results
7.6.1 Evaluation of estimation performance
7.6.2 Comparison with FE results
7.6.3 Selection of injected voltage
7.7 Summary
References
CHAPTER 8 OFFLINE AND MULTI-STEP PARAMETER ESTIMATION METHODS
8.1 Introduction
8.2 Parameter Estimation at Standstill by Square Voltage Injection
8.3 Parameter Estimation at Standstill by High-frequency Current Injection
8.3.1 Estimation based on current variations
8.3.2 Estimation based on zero-crossing detection
8.4 Multi-step Parameter Estimation
8.4.1 Two-step estimation method
8.4.2 Three-step estimation method
8.5 Summary
References
CHAPTER 9 ESTIMATION OF MECHANICAL PARAMETERS
9.1 Introduction
9.2 Mechanical Parameter Estimation Methods
9.2.1 Acceleration/deceleration-based method
9.2.2 MRAS observer-based method
9.2.3 Fundamental motion equation-based estimation method
9.2.4 Critical issue of torque prediction
9.3 Experimental Results
9.3.1 Comparison between scheme I and sScheme III
9.3.2 Comparison between scheme II and scheme III
9.3.3 Influence of variation of rotor PM flux linkage
9.3.4 Sensitivity analysis of sinusoidal perturbation signal
9.4 Design of PI Speed Regulator
9.5 Summary
References
CHAPTER 10 MODERN CONTROL AND OPTIMISATION THEORY BASED PARAMETER ESTIMATION ALGORITHMS
10.1 Introduction
10.2 Designed Parameter Estimation Scheme
10.3 Recursive Least Squares (RLS)
10.3.1 Basic principle
10.3.2 Application to parameter estimation for PMSMs
10.4 Kalman Filter (KF)
10.4.1 Basic principle
10.4.2 Application to parameter estimation for PMSMs
10.5 Model Reference Adaptive System (MRAS)
10.5.1 Basic principle
10.5.2 Application to parameter estimation for PMSMs
10.6 Adaline Neural Network (ANN)
10.6.1 Basic principle
10.6.2 Application to parameter estimation for PMSMs
10.7 Gradient-based Methods
10.7.1 Basic principle
10.7.2 Application to parameter estimation for PMSMs
10.8 Particle Swarm Optimisation (PSO)
10.8.1 Basic principle
10.8.2 Application to parameter estimation for PMSMs
10.9 Genetic Algorithm (GA)
10.9.1 Basic principle
10.9.2 Application to parameter estimation for PMSMs
10.10 Summary
References
CHAPTER 11 APPLICATIONS OF PARAMETER ESTIMATION
11.1 Introduction
11.2 Improvement in Control Performance
11.2.1 Design of PI regulators for field-oriented control
11.2.2 Determination of MTPA current trajectory
11.3 Improvement in Sensorless Control
11.3.1 Improvement in sensorless control performance
11.3.2 Application of parameter estimation under sensorless control
11.4 Precise Torque Estimation
11.4.1 HF square wave voltage injection considering cross-coupling effect
11.4.2 Torque estimation based on estimated HF inductances
11.5 Thermal Condition Monitoring
11.6 Fault Diagnosis
11.6.1 Interturn short-circuit fault
11.6.2 Demagnetisation fault
11.7 Summary
References
APPENDIX A FINITE ELEMENT CALCULATION OF WINDING INDUCTANCES
APPENDIX B SPECIFICATIONS OF PROTOTYPE MACHINES AND EXPERIMENTAL PLATFORMS
