TY - GEN
T1 - A General Pattern of Permanent Magnet Arrangement for Design Optimization of a Reluctance Magnetic Gear with Enhanced Torque Density for Electric Vehicles
AU - Bi, Yanding
AU - Fu, Weinong
AU - Niu, Shuangxia
AU - Huang, Jiahui
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2024/12
Y1 - 2024/12
N2 - A novel general pattern of permanent magnet (PM) arrangement for the optimal design of magnetic gears (MGs) is presented in this work. The proposed general pattern can generate six different types of PM arrangements. By using this optimization pattern, the PM arrangement with high torque and low torque ripple in MGs can be obtained within a short computing time. To demonstrate the effectiveness of this optimization approach, the proposed pattern is applied to a reluctance magnetic gear (RMG), a promising type of MG suitable for power transmission applications in lightweight electric vehicles (EVs). The transmission torque and torque ripple characteristics of the RMG model are evaluated using finite element analysis (FEA), while its design optimization is performed utilizing a non-dominated sorting genetic algorithm II (NSGA-II) method. The superiority of this general pattern is demonstrated through a comparative analysis between the proposed RMG and a conventional RMG model.
AB - A novel general pattern of permanent magnet (PM) arrangement for the optimal design of magnetic gears (MGs) is presented in this work. The proposed general pattern can generate six different types of PM arrangements. By using this optimization pattern, the PM arrangement with high torque and low torque ripple in MGs can be obtained within a short computing time. To demonstrate the effectiveness of this optimization approach, the proposed pattern is applied to a reluctance magnetic gear (RMG), a promising type of MG suitable for power transmission applications in lightweight electric vehicles (EVs). The transmission torque and torque ripple characteristics of the RMG model are evaluated using finite element analysis (FEA), while its design optimization is performed utilizing a non-dominated sorting genetic algorithm II (NSGA-II) method. The superiority of this general pattern is demonstrated through a comparative analysis between the proposed RMG and a conventional RMG model.
KW - Finite element analysis (FEA)
KW - magnetic flux density
KW - magnetic gear
KW - optimization
KW - permanent magnet (PM)
UR - https://www.scopus.com/pages/publications/85214106146
U2 - 10.1007/978-981-96-0232-2_12
DO - 10.1007/978-981-96-0232-2_12
M3 - Conference article published in proceeding or book
AN - SCOPUS:85214106146
SN - 9789819602315
T3 - Communications in Computer and Information Science
SP - 147
EP - 159
BT - Clean Energy Technology and Energy Storage Systems - 8th International Conference on Life System Modeling and Simulation, LSMS 2024 and 8th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024, Proceedings
A2 - Li, Kang
A2 - Liu, Kailong
A2 - Hu, Yukun
A2 - Tan, Mao
A2 - Zhang, Long
A2 - Yang, Zhile
PB - Springer Science and Business Media Deutschland GmbH
T2 - 8th International Conference on Life System Modeling and Simulation, LSMS 2024 and 8th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024
Y2 - 13 September 2024 through 15 September 2024
ER -