Multi-objective Optimization Design of Modular Linear Rotary Switched Reluctance Machine Based on the Taguchi Method

作者

  • Hao Chen School of Electrical Engineering China University of Mining and Technology, Xuzhou 221116, China, Shenzhen Research Institute China University of Mining and Technology, Shenzhen 515100, China, Nexus Intelligent Equipment (Zhejiang) Co. Ltd. Zhejiang, China
  • Cheng Liu School of Electrical Engineering China University of Mining and Technology, Xuzhou 221116, China
  • Xing Wang Shenzhen Research Institute China University of Mining and Technology, Shenzhen 515100, China
  • Shudong Hou Nexus Intelligent Equipment (Zhejiang) Co. Ltd. Zhejiang, China
  • Antonino Musolino Department of Energy, System, Territory and Construction Engineering (DESTEC) University of Pisa, 56122 Pisa, Italy
  • Nurkhat Zhakiyev Department of Science and Innovation Astana IT University, Astana, Kazakhstan

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https://doi.org/10.13052/2024.ACES.J.400901

关键词:

Finite element analysis, modular linear rotary switched reluctance machine, structural optimization, Taguchi method

摘要

In order to combine the advantages of modularity for motor power density enhancement, this paper proposes a three-phase modular linear rotary switched reluctance machine (MLRSRM) with both segmented stator and rotor. In order to increase the torque characteristics of the motor, this paper proposes a multi-objective optimization design of MLRSRM based on the Taguchi method. The static average electromagnetic torque and electromagnetic thrust of the motor are taken as the optimization objectives, and the four ontological parameters (stator pole arc, rotor pole arc, rotor module radial depth and rotor module edge width) that have a greater impact on the MLRSRM optimization objectives are selected. The Taguchi method is used to optimize the motor, determine the optimized structural parameters and verify them by finite element analysis software. The finite element simulation results demonstrate the effectiveness of the described optimization method on the structural design of the MLRSRM. This paper has certain theoretical significance and reference value for the optimal design of MLRSRM.

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Hao Chen (SM’08) received the B.S. and Ph.D. degrees from the Department of Automatic Control, Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 1991 and 1996, respectively. In 1998, he became an Associate Professor with the School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, where he has been a Professor since 2001. From 2002 to 2003, he was a Visiting Professor at Kyungsung University, Busan, Korea. Since 2008, he is an Adjunct Professor at the University of Western Australia, Perth, Australia. He is the author of one book and has authored more than 190 papers. He is the holder of 14 US Patents, 23 Australian Patents, one Danish Patent, seven Canadian Patents, three South African Patents, 10 Russian Patents, 44 Chinese Invention Patents and six Chinese Utility Model Patents. His current research interests include motor control, linear launcher, electric vehicles, electric traction, servo drives and wind power generator control. Chen was the recipient of both the Prize of Science and Technology of Chinese Youth and the Prize of the Fok Ying Tong Education Foundation for Youth Teachers in both 2004. He was awarded the first prize in the Science and Technology advanced of Province and Ministry once, the second prize in the Science and Technology advanced of Province and Ministry seven times, and the third prize in the Science and Technology advanced of Province and Ministry 14 times. He became the Chinese New Century Hundred-Thousand Ten-Thousand Talents Engineering National Talent in 2007 and won the Government Especial Allowance of People’s Republic of China State Department in 2006.

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Cheng Liu received the B.S. degree in electrical engineering and automation from Hubei University of Technology, Wuhan, Hubei, China, in 2020, and the M.S. degree in electrical engineering from Hubei University of Technology, Wuhan, Hubei, in 2023. He is currently pursuing a Ph.D. degree in electrical engineering at China University of Mining and Technology, Xuzhou. His research interests include switched reluctance motor design control, ocean wave power generation, and electric vehicles.

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Xing Wang received the B.S. degree from China University of Mining and Technology, Xuzhou Jiangsu, China, in 1996, and M.S. degree from China University of Mining and Technology, Xuzhou Jiangsu, in 1999. In 2007, she became an Associate Professor with China University of Mining and Technology, Xuzhou. She is a holder of four US Patents, nine Australian Patents, two Canadian Patents, four Russian Patents, 12 Chinese Invention Patents, three Chinese Utility Model Patents, and has authored 15 papers.

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Shudong Hou founded Nanjing Enchuan New Energy Power System Co. Ltd. In September 2022, he won third prize in the high-level talent entrepreneurship competition in Zaozhuang, Shandong. In 2024, he founded Nexus Intelligent Equipment (Zhejiang) Co. Ltd. and serves as its chairman. He has presided over the research, development, production and sales of motor and controller systems for many years.

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Antonino Musolino received his Ph.D. degree in electrical engineering from the University of Pisa, Pisa, Italy, in 1994. He is currently a Full Professor of electrical machines at the University of Pisa. He has co-authored more than 130 papers published in international journals/conferences. He holds three international patents in the field of magnetorheological devices. His current research activities are focused on linear electromagnetic devices, motor drives for electric traction, and the development of analytical and numerical methods in electromagnetics. Musolino was involved in the organization of several international conferences, where he has served as the session chairman and an organizer, and as a member of the editorial board.

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Nurkhat Zhakiyev received the bachelor’s degree in physics and computer science in 2005, the master’s degree in applied mathematics from M. Utemisov West Kazakhstan State University, Kazakhstan, in 2007, and the Ph.D. degree in physics from L. N. Gumilyov Eurasian National University (ENU), in 2015. He is currently working at Astana IT University. His research interests include energy system modeling, smart grid and networks, smart city and optimization modeling.

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已出版

2025-09-30

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[1]
H. . Chen, C. . Liu, X. . Wang, S. . Hou, A. . Musolino, 和 N. . Zhakiyev, 《Multi-objective Optimization Design of Modular Linear Rotary Switched Reluctance Machine Based on the Taguchi Method》, ACES Journal, 卷 40, 期 09, 页 800–809, 9月 2025.

期

2025: Vol 40 Iss 9

栏目

Advances in Analysis, Design and Control of Switched Reluctance Machines

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