Fast Modelling, Torque-Ripple-Reduction and
Fault-Detection Control of Switched Reluctance Motors
Author: Wei PENG
A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy in Engineering Science and Technology
“Docteur en Sciences de l’Ingénieur et Technologie” Academic year 2018-2019
Supervisor: Professor Johan GYSELINCK Electrical energy group Bio, Electro And Mechanical Systems Department
Thesis jury:
Université Libre de Bruxelles
École polytechnique de Bruxelles
Fast Modelling, Torque-Ripple-Reduction and
Fault-Detection Control of Switched Reluctance Motors
A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy
Wei PENG
Department of Bio, Electro And Mechanical Systems
Supervisor : Prof. Johan GYSELINCK
Copyright © 2019 by Wei Peng Printed April 2019
Acknowledgment
Firstly, I would like to address my respectful thank to my supervisor Prof. Gyselinck who gave me the chance of working in Université Libre de Bruxelles and supervised my work in the last five years. I appreciate his strictness and patience which helped me to improve my work significantly and his contributions of time, invaluable advice and constructive suggestions to make my PhD experience productive and stimulating. I had learned a lot from him, without his help I could not have finished my thesis successfully. Besides my supervisor I would like to thank the other members of my PhD committee Prof. Maun and Prof. Lataire for the insightful comments and questions about my work which encouraged me to widen my research from various perspectives.
My sincere thanks go to Prof. Lee and Prof. Ahn, who hosted me at the department of Mechatronics Engineering during my stay for the work in Chapter 4 in Kyungsung University, South Korea, and who gave access to their research facilities and helped me bring my theoretical ideas to experimental work. Without they precious support it would not be possible to achieve this research. Thanks also to the fellow researchers in Kyungsung University who welcomed me.
My deep thanks go to Prof. Martis from Technical University of Cluj-Napoca for insightful feedback on my research, the encouragement and warmth she extended to me for always making me feel so welcome. Thanks also to the fellow researchers in Technical University of Cluj-Napoca who welcomed me during my short stay there.
my personal and professional time at ULB. I am especially grateful for Ander, Ramon, Julien and Marcelo from whom I earned the most from the collaborations for work and great integration through lunch breaks and social events. The joy we had together was the light enters my life, even during tough times in my PhD pursuit. I would also like to thank my present or previous colleagues at BEAMS: Adrain, Yuxue, Dongmin, Xiang, Xavier, Thomas G., Thomas R., Yves, Shruti, Usman, Gilles, Benoît, Neriton, etc... for their help and the useful discussions that we had during these years. Moreover, I would like to thank other staff members from the BEAMS department. To Ariane for her homey help with both personal and work matters, to Pascal and Christophe for helping me with the technical work I needed to do.
This research was financially supported mainly in the frame of the ADvanced
Electric Powertrain Technology(ADEPT) project which is an European Union
funded Marie Curie ITN project, grant number 607361. Thanks to the fellow researchers: Andrii, Anton, Arkadiusz, Fabien, Georgios, Kesavan, Korawich, Mitrofan, Nenad, Pietro, Sabrina, Simon and Stjepan. I am lucky to have this oppor-tunity to meet all and proud of being a part of this great team. I also would like to acknowledge the funding Commission de classement des crédits internationaux de
l’Université libre de Bruxelles(CCCI) for supporting partly my stay in Kyungsung
University, and the prize Prix Van Buuren-Jaumotte-Demoulin for the financial support at the end of the study.
Contents
Copyrights . . . ii
Acknowledgment . . . iii
Abstract . . . ix
List of figures . . . xi
List of tables . . . xxiv
Abbreviations . . . xxvi
1
Introduction . . . 32
Fast Modelling of SRMs . . . 112.1 Introduction . . . 11
2.2 2D FE modelling of SRMs . . . 13
2.3 MEC modelling and combined MEC-FE modelling for SRMs . . . 16
2.3.1 MEC topology . . . 16
2.3.3 Airgap reluctance for MEC model . . . 18
2.3.4 Airgap reluctance for Combined MEC-FE model . . . 21
2.3.5 Resolution of system of equations . . . 26
2.4 Computation and comparison of flux-linkage and torque . . . 26
2.4.1 Different stator and rotor pole arcs . . . 26
2.4.2 Different stator and rotor yoke widths . . . 29
2.4.3 Different stator and rotor pole numbers . . . 29
2.4.4 Torque computation . . . 30
2.4.5 Experimental results . . . 32
2.5 Mutual coupling effects . . . 33
2.6 Discussion and conclusion . . . 42
3
Torque-Ripple Reduction Control of SRMs . . . 433.1 Introduction . . . 43
3.2 Optimal control strategy for FA control method . . . 47
3.2.1 Firing angle control . . . 47
3.2.2 Optimization based on different objective functions . . . 47
3.2.3 Simulation and experimental results . . . 51
3.3 Optimal control strategy for TSF control method . . . 55
3.3.1 Torque sharing function control . . . 55
3.3.2 Optimization based on different dwell periods for soft chopping method 58 3.3.3 Experimental results . . . 59
3.4 Simulation comparison of FA and TSF control methods . . . 64
3.5 PWM control for SRMs . . . 68
3.5.1 Back-EMF decoupling and gain scheduling . . . 68
3.6 Experimental results by using different control methods . . . 72
3.6.1 Fixed and adapted proportional gain with PWM control . . . 72
3.6.2 Hysteresis current control and PWM control . . . 76
3.6.3 Hard chopping and soft chopping with PWM control . . . 87
3.7 Discussion and conclusion . . . 89
4
Minimal Current Sensing Strategy Control . . . 914.1 Introduction . . . 91
4.2 The selection of current sensors . . . 93
4.3 Current reconstruction during single-phase conducing region . . 99
4.4 The selection of current regulation methods during commutation region - soft chopping . . . 101
4.4.2 Method 2: different chopping transistors . . . 108
4.5 The selection of current regulation methods during commutation region - adaptive current regulation method . . . 116
4.5.1 Method 3: hard chopping for outgoing phase and soft chopping for upcoming phase . . . 117
4.5.2 Method 4: hard chopping for outgoing and upcoming phases . . . 123
4.6 Comparison of the proposed and previous methods . . . 131
4.7 Fault detection results for the selected method . . . 133
4.7.1 Simulation verification . . . 133
4.7.2 Experimental results . . . 134
4.8 Discussion and conclusion . . . 139
5
Fault Detection of SRMs . . . 1415.1 Introduction . . . 141
5.2 Converter fault detection method . . . 143
5.2.1 Reference current fault detection method . . . 143
5.2.2 Simulation results . . . 144
5.3 Interturn short-circuit fault detection . . . 148
5.3.1 Interturn short-circuit fault of stator winding . . . 148
5.3.2 Interturn short-circuit fault diagnosis method . . . 149
5.3.3 Simulation and experimental results . . . 151
5.4 Discussion and conclusion . . . 168
6
Rotor Position Estimation of SRMs . . . 1696.1 Introduction . . . 169
6.2 Rotor position estimation method . . . 173
6.2.1 Phase selection for rotor position estimation . . . 173
6.2.2 Phase resistance correction . . . 176
6.3 Simulation and experimental results . . . 179
6.4 Discussion and conclusion . . . 197
7
Conclusions and Further Work . . . 1997.1 Conclusions . . . 199
7.2 Further work . . . 203
B
Airgap reluctance identification for MEC model . . . 211B.1 Piecewise analytical function . . . 211 B.2 Fitted analytical permeance function for different machines . . 212
Abstract
As the world moves towards a cleaner and greener future, electrical machines for various industrial purposes and transport applications have gained a lot of attention. Permanent magnet synchronous machines (PMSMs) are usually the solution for electric vehicle (EV) applications thanks to their high efficiency, compactness and high-power density. On the downside, although the price of rare-earth materials has recovered close to historical levels, concerns still remain and the questions on the environmental sustainability of these materials have also been raised, which has encouraged the researchers to consider rare-earth-free machines.
The switched reluctance machine (SRM) is one of the competitive alternatives, thanks to the simple and robust construction, high reliability and inherent fault tolerance capability. However, it has a bad reputation when it comes to torque ripple and acoustic noise. And the highly nonlinear characteristic brings much difficulty to routine design purposes and machine optimisation.
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