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

Authors

  • 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

DOI:

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

Keywords:

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

Abstract

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.

Downloads

Download data is not yet available.

Author Biographies

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

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.

Cheng Liu, School of Electrical Engineering China University of Mining and Technology, Xuzhou 221116, China

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.

Xing Wang, Shenzhen Research Institute China University of Mining and Technology, Shenzhen 515100, China

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.

Shudong Hou, Nexus Intelligent Equipment (Zhejiang) Co. Ltd. Zhejiang, China

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.

Antonino Musolino, Department of Energy, System, Territory and Construction Engineering (DESTEC) University of Pisa, 56122 Pisa, Italy

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.

Nurkhat Zhakiyev, Department of Science and Innovation Astana IT University, Astana, Kazakhstan

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.

References

H. Chen, R. Nie, and X. Li, “A transverse-flux single-phase tubular switched reluctance linear machine with 4 poles,” IEEE Transactions on Applied Superconductivity, vol. 31, no. 8, pp. 1-4, Nov. 2021.

G. Zhang, R. Nie, J. Si, C. Gan, and Y. Hu, “Optimal design of a novel double-stator linear-rotary flux-switching permanent-magnet generator for offshore wind-wave energy conversion,” in 2021 IEEE Energy Conversion Congress and Exposition, Vancouver, BC, Canada, pp. 4300-4305, 2021.

R. Nie, J. Si, P. Wang, Z. Li, J. Liang, and C. Gan, “Optimization design of a novel permanent magnet linear-rotary generator for offshore wind-wave combined energy conversion based on multi-attribute decision making,” IEEE Transactions on Energy Conversion, pp. 1-17, Feb. 2024.

W. Ding, H. Fu, and Y. Hu, “Characteristics assessment and comparative study of a segmented-stator permanent-magnet hybrid-excitation SRM drive with high-torque capability,” IEEE Transactions on Power Electronics, vol. 33, no. 1, pp. 482-500, Jan. 2018.

R. Nie, J. Si, Y. Jia, P. Wang, S. Xu, J. Liang, and C. Gan, “Comprehensive comparison of mover-PM and stator-PM linear-rotary generators for wind-wave combined energy conversion system,” IEEE Transactions on Industry Applications, pp. 1-14, May 2024.

J. Zhang, J. Liu, and L. Gei, “Multi-objective optimization of switched reluctance motor based on Gaussian process regression model,” in 2024 IEEE 10th International Power Electronics and Motion Control Conference, Chengdu, China, pp. 4020-4025, 2024.

O. Zayed, M. Omar, M. Bakr, M. Narimani, A. Emadi, and B. Bilgin, “Switched reluctance motor design for an EV propulsion application,” in IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society, Toronto, ON, Canada, pp. 1-6, 2021.

Z. Xu, Q. Yu, H. Wang, Y. Zhang, and T. Yi, “Optimal design of hybrid stator pole type bearingless switched reluctance motor with simulated annealing particle swarm optimization algorithm,” in 2022 IEEE 5th International Electrical and Energy Conference, Nanjing, China, pp. 3422-3427, 2022.

Y. Geng, C. Huang, H. Yuan, and Y. Wu, “Optimization of a permanent magnet-assisted switching reluctance motor based on the iterative optimization strategy of NSGA-III,” in 2023 IEEE 6th International Electrical and Energy Conference, Hefei, China, pp. 3733-3738, 2023.

T. Sharifi, V. M. Khales, and M. Mirsalim, “Torque ripple minimization for a switch reluctance motor using the Ant Lion Optimization algorithm,” in 2022 13th Power Electronics, Drive Systems, and Technologies Conference, Tehran, Islamic Republic of Iran, pp. 207-211, 2022.

M. Abdalmagid, M. H. Bakr, and A. Emadi, “A linesearch-based algorithm for topology and generative optimization of switched reluctance machines,” IEEE Transactions on Transportation Electrification, vol. 9, no. 3, pp. 3849-3866, Sep. 2023.

S. E. M. Mohammadi, P. Chen, M. Moallem, B. Fahimi, and M. Kiani, “An alternate rotor geometry for switched reluctance machine with reduced torque ripple,” IEEE Transactions on Energy Conversion, vol. 38, no. 2, pp. 939-947, June 2023.

M. Pourkarimi, U. Demı

r, and M. C. Akuner, “Neural network approach for E-motor development,” in 2022 8th International Conference on Control, Decision and Information Technologies, Istanbul, Turkey, pp. 1091-1095, 2022.

W. Yan, W. Wang, H. Li, H. Chen, F. Yu, D. Zhao, and H. Yang, “Performance analysis of a novel axial radial flux segmental rotor switched reluctance motor,” IEEE Transactions on Transportation Electrification, vol. 10, no. 1, pp. 1031-1042, Mar. 2024.

S.-I. Kim, J.-Y. Lee, Y.-K. Kim, J.-P. Hong, Y. Hur, and Y.-H. Jung, “Optimization for reduction of torque ripple in interior permanent magnet motor by using the Taguchi method,” IEEE Transactions on Magnetics, vol. 41, no. 5, pp. 1796-1799, May 2005.

X. Jia and G. Lu, “An improved random Taguchi’s method based on swarm intelligence and dynamic reduced rate for electromagnetic optimization,” IEEE Antennas and Wireless Propagation Letters, vol. 18, no. 9, pp. 1878-1881, Sep. 2019.

X. Dong, Z. Q. Zhu, D. Liang, L. Mao, X. Qiu, S. Li, and L. Zheng, “Taguchi-based preprocess strategy for fast evaluating worst case cogging torque due to PM tolerance interactions,” IEEE Transactions on Transportation Electrification, vol. 11, no. 1, pp. 4097-4110, Feb. 2025.

J. Yang, J. Chen, Z. Cai, W. Yan, W. Liu, J. Zhang, J. Qiao, G. Yang, and C. Zhang, “Design and optimization of a novel permanent magnet linear motor with the same number of poles and slots,” IEEE Transactions on Industry Applications, vol. 61, no. 1, pp. 16-24, Jan.-Feb. 2025.

J. Chen, K. Liu, Z.-Q. Zhu, H. Cai, S. Zhou, D. Wei, Y. Chen, and D. Zhang, “Torque improvement of interior permanent magnet synchronous machine by axial-assisted magnets,” IEEE Transactions on Transportation Electrification, vol. 11, no. 1, pp. 3480-3490, Feb. 2025.

S. Jiang, J. Wang, B. Zhou, Y. Zhao, M. Gao, S. Miao, L. Xu, and X. Xu, “Design and electromagnetic–thermal analysis of doubly salient electromagnetic machine for more electric engine based on excitation compensation,” IEEE Transactions on Transportation Electrification, vol. 11, no. 1, pp. 3311-3322, Feb. 2025.

Y. Wang, M. Zhao, Y. Huang, X. Jia, and M. Lu, “Torque performance optimization of a novel hybrid PMSM with eccentric Halbach based on improved Taguchi method,” IEEE Transactions on Instrumentation and Measurement, vol. 73, pp. 1-12, 2024.

M. T. B. Tarek, A. W. Bandarkar, and Y. Sozer, “Design, optimization, and development of an axial flux interior permanent magnet motor with a novel flux barrier,” IEEE Transactions on Industry Applications, vol. 60, no. 4, pp. 6103-6112, July-Aug. 2024.

F. Siddique, S. Shastri, and B. Singh, “Computational investigation of modeling coupled optimization techniques for MCSRM driving EV,” IEEE Transactions on Energy Conversion, vol. 39, no. 3, pp. 1793-1803, Sep. 2024.

F. Liu, X. Wang, and H. Wei, “Electromagnetic performance analysis, prediction, and multiobjective optimization for U-type IPMSM,” IEEE Transactions on Industrial Electronics, vol. 71, no. 9, pp. 10322-10334, Sep. 2024.

Downloads

Published

2025-09-30

How to Cite

[1]
H. . Chen, C. . Liu, X. . Wang, S. . Hou, A. . Musolino, and N. . Zhakiyev, “Multi-objective Optimization Design of Modular Linear Rotary Switched Reluctance Machine Based on the Taguchi Method”, ACES Journal, vol. 40, no. 09, pp. 800–809, Sep. 2025.

Issue

2025: Vol 40 Iss 9

Section

Advances in Analysis, Design and Control of Switched Reluctance Machines

Categories