Multidisciplinary Design Optimization Methods for Electrical Machines and Drive Systems - Lei, Gang
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Présentation Multidisciplinary Design Optimization Methods For Electrical Machines And Drive Systems de Lei, Gang Format Broché
- Livre Technologie
Résumé :
This book presents various computationally efficient component- and system-level design optimization methods for advanced electrical machines and drive systems. Readers will discover novel design optimization concepts developed by the authors and other researchers in the last decade, including application-oriented, multi-disciplinary, multi-objective, multi-level, deterministic, and robust design optimization methods. A multi-disciplinary analysis includes various aspects of materials, electromagnetics, thermotics, mechanics, power electronics, applied mathematics, manufacturing technology, and quality control and management. This book will benefit both researchers and engineers in the field of motor and drive design and manufacturing, thus enabling the effective development of the high-quality production of innovative, high-performance drive systems for challenging applications, such as green energy systems and electric vehicles.
Biographie:
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 a Chancellor's Postdoctoral Research Fellow at School of Electrical, Mechanical and Mechatronic Systems, University of Technology, Sydney (UTS), Sydney, Australia. He is a core member of the Green Energy & Vehicle Innovation Centre (GEVIC) which is one of the Research Strengths at UTS. His current research interests include numerical analysis of electromagnetic field, design and optimization of advanced electrical drive systems for renewable energy systems and applications. Jianguo Zhu received the B.E. from the Jiangsu Institute of Technology, Zhenjiang, China, in 1982, the M.E. from Shanghai University of Technology, Shanghai, China, in 1987, and the Ph.D. from University of Technology Sydney (UTS), Sydney, Australia, in 1995. He is currently a Professor of Electrical Engineering and the Head of the School of Electrical, Mechanical and Mechatronic Systems, UTS. He is the co-director of the Green Energy & Vehicle Innovation Centre (GEVIC) which is one of the Research Strengths at UTS. His research interests include electromagnetics, magnetic properties of materials, electrical machines and drives, power electronics, renewable energy systems, and smart micro-grids. Youguang Guo received the B.E. from Huazhong University of Science and Technology (HUST), Wuhan, China, in 1985, the M.E. from Zhejiang University, Zhejiang, China, in 1988, and the Ph.D. from University of Technology Sydney (UTS), Sydney, Australia in 2004, all in Electrical Engineering. From 1988 to 1998, he lectured in the Department of Electric Power Engineering, HUST. From March 1998 to July 2008, he was a Visiting Research Fellow, Ph.D. candidate, Postdoctoral Fellow, and Research Fellow in the Center for Electrical Machines and Power Electronics, Faculty of Engineering, UTS. He is currently an Associate Professor at the School of Electrical, Mechanical and Mechatronic Systems, UTS. He is a core member of the Green Energy & Vehicle Innovation Centre (GEVIC) which is one of the Research Strengths at UTS. His research fields include measurement and modeling of magnetic properties of magnetic materials, numerical analysis of electromagnetic field, electrical machine design and optimization, power electronic drives and control....
Sommaire:
Introduction.- Design fundamentals of electrical machines and drive systems.- Optimization methods.- Design optimization methods for electrical machines.- Design optimization methods for electrical drive systems.- Design optimization for high quality mass production.- Application-oriented design optimization methods for electrical machines.- Conclusion and future works.
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