Multi-objective Design Optimization of Switched Reluctance Motor Drive Systems (Hardcover)

This book presents the design optimization method for switched reluctance motors (SRMs) and drive systems. It covers an in-depth literature review on the status and potential trend of design optimization techniques for SRMs, including design theory, modeling methods, topologies, control methods, and techniques for optimization efficiency and effects. Readers will discover new design methods based on the specific nonlinear characteristics of SRMs, and multi-objective optimization methods for the design of high-quality switched reluctance drive systems without or with the consideration of uncertainties, i.e., the deterministic and robust approaches. Multi-mode design optimization method regarding SRMs is investigated and some examples are presented. In addition, some essential trends in design optimization development are presented and highlighted as future perspectives. This book benefits students, researchers, engineers, and companies in the field of electrical drive design and manufacturing.

The focuses of this book are different from those of the published books. The advanced optimization methods including deterministic optimization, robust optimization, and system-level optimization are not discussed in these books. Besides, new design method based on the nonlinear characteristic and multi-mode optimization combined with specific application will be introduced to the design of high-performance of switched reluctance machines.

Xiaodong Sun received the B.Sc. degree in electrical engineering, and the M.Sc. and Ph.D. degrees in control engineering from Jiangsu University, Zhenjiang, China, in 2004, 2008, and 2011, respectively.

Since 2004, he has been with Jiangsu University, where he is currently Professor in Vehicle Engineering with the Automotive Engineering Research Institute. From 2014 to 2015, he was Visiting Professor with the School of Electrical, Mechanical, and Mechatronic Systems, University of Technology Sydney, Sydney, Australia. His current teaching and research interests include electrified vehicles, electrical machines, electrical drives, and energy management. He is Associate Editor of the IEEE Transactions on Industrial Electronics, Associate Editor of the IEEE Transactions on Transportation Electrification, and Editor of the IEEE Transactions on Energy Conversion.

Kaikai Diao received the B.S. degree in vehicle engineering from Jiangsu University, Zhenjiang, China, in 2017, and he is currently working toward the Ph.D. degree in vehicle engineering at Jiangsu University, Zhenjiang, China.

His current research interests include design, optimization, magnetic equivalent circuits modeling, control, and loss analysis of switched reluctance motors for automobile application.

Gang Lei received the B.S. degree in mathematics from Huanggang Normal University, China, in 2003, the M.S. degree in mathematics and Ph.D. degree in electrical engineering from Huazhong University of Science and Technology, China, in 2006 and 2009,respectively. He is currently Senior Lecturer with the School of Electrical and Data Engineering, University of Technology Sydney (UTS), Sydney, NSW, Australia. He currently serves as Associate/Guest Editors for several international journals, including Associate Editor of the IEEE Transactions on Industrial Electronics and Guest Editor of the IEEE Transactions on Energy Conversion for a special section on robust design and analysis of electrical machines and drives.

Jianguo Zhu (Senior Member, IEEE) received the Ph.D. degree in electrical engineering from the University of Technology Sydney (UTS), NSW, Australia, in 1995. He was promoted to a Full Professor in 2004 and a Distinguished Professor of electrical engineering in 2017, UTS. He joined as a Full Professor and the Head of the School of Electrical and Computer Engineering, The University of Sydney, NSW, Australia, in 2018. His research interests include electromagnetics, magnetic properties, electrical machines and drives, and power electronics.