Torque Quality Enhancement Design of an Interior Permanent Magnet Synchronous Motor by Reluctance-Network-Based Topology Optimization

Interior permanent magnet synchronous motor (IPMSM) obtains wide application in electric vehicles (EVs). The torque quality of this kind of motor is closely related to the rotor design. In this article, a novel topology optimization (TO) approach is proposed to autonomously design the structure of the IPMSM achieving the improvement of torque and suspension of torque ripple. The key of this study is to establish a mesh-based reluctance network (RN) model for the proposed TO. It can rapidly calculate torque characteristics of generated motors with arbitrary rotor structures during the optimization. Meanwhile, the mesh of RN can be shared with the spatial algorithm of TO, which contributes to the improvement of optimization efficiency. To verify the effectiveness of the proposed method, an existing 36-slots/eight-pole V-type IPMSM is selected as an initial design example. The processes of corresponding RN construction and TO implementation are specifically clarified. After optimization, the torque characteristics including cogging torque and output torque are analyzed in detail. Finally, a prototype of the optimized motor is manufactured and the performance is compared with that of the initial prototype to further verify the effectiveness of the proposed optimization method.

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Publication Details

Journal
IEEE Transactions on Transportation Electrification
Published
2024-10-25
DOI
https://doi.org/10.1109/tte.2024.3486447
Citations
5
Primary Topic
Topology Optimization in Engineering
Type
article
Field-Weighted Citation Impact
1.30

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article

Torque Quality Enhancement Design of an Interior Permanent Magnet Synchronous Motor by Reluctance-Network-Based Topology Optimization

Yunyun Chen, Jiqi Wu, Zixuan Xiang, Xiaoyong Zhu et al.
5 citations
IEEE Transactions on Transportation Electrification
Topology Optimization in Engineering
1.30
article

Torque Quality Enhancement Design of an Interior Permanent Magnet Synchronous Motor by Reluctance-Network-Based Topology Optimization

Yunyun Chen, Jiqi Wu, Zixuan Xiang, Xiaoyong Zhu, Li Quan, Zhangwei Yang
article en
5 citations

Abstract

Interior permanent magnet synchronous motor (IPMSM) obtains wide application in electric vehicles (EVs). The torque quality of this kind of motor is closely related to the rotor design. In this article, a novel topology optimization (TO) approach is proposed to autonomously design the structure of the IPMSM achieving the improvement of torque and suspension of torque ripple. The key of this study is to establish a mesh-based reluctance network (RN) model for the proposed TO. It can rapidly calculate torque characteristics of generated motors with arbitrary rotor structures during the optimization. Meanwhile, the mesh of RN can be shared with the spatial algorithm of TO, which contributes to the improvement of optimization efficiency. To verify the effectiveness of the proposed method, an existing 36-slots/eight-pole V-type IPMSM is selected as an initial design example. The processes of corresponding RN construction and TO implementation are specifically clarified. After optimization, the torque characteristics including cogging torque and output torque are analyzed in detail. Finally, a prototype of the optimized motor is manufactured and the performance is compared with that of the initial prototype to further verify the effectiveness of the proposed optimization method.

IEEE Transactions on Transportation ElectrificationVol. 11(2)
Jiangsu University (CN), Yangzhou University (CN)
Major International Joint Research Programme, National Key Research and Development Program of China
Affordable and clean energy
Openalex Percentile: Top 22%
Topology Optimization in Engineering
1.30
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Torque Quality Enhancement Design of an Interior Permanent Magnet Synchronous Motor by Reluctance-Network-Based Topology Optimization — Yunyun Chen, Jiqi Wu, et al. · IEEE Transactions on Transportation Electrification (2024) | TGRS Research Map | TGRS