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<p>To enhance the design efficiency of axial-field flux-switching permanent magnet (AF-FSPM) machines, this paper proposes a multi-objective optimization method based on a quasi-three-dimensional (quasi-3D) harmonic modulation model. By combining magnetic field modulation theory with three-dimensional equivalent analysis, a multi-layer quasi-3D harmonic modulation model is developed to determine the optimal number of layers by analyzing the variation in magnetic flux linkage. In addition, the model also reveals relationships between key structural parameters (including inner diameter and stator/rotor tooth height ratio) and torque, thus providing valuable guidance for the initial design stage. Subsequently, structural parameters of each layer are classified into two levels by a sensitivity analysis and then optimized with the objectives of maximizing average torque and minimizing torque ripple. Finite element analysis and experimental results verify the method’s effectiveness, achieving a 17.1% torque increase while constraining torque ripple at 5.31% within only 19 hours. The proposed optimization method is also applicable to conventional axial flux permanent magnet machines; however, further analysis of the optimal number of layers is required due to differences in magnetic circuit topology and harmonic characteristics.</p>

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Optimization of axial-field flux-switching permanent magnet machine by quasi-3D harmonic modulation model

  • 期刊论文

  • 发表日期：

    2025年8月18日

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  • Peng Su,
  • Zeyu Xu,
  • Yongjian Li,
  • Yiwei Wang,
  • Tianli Liu

摘要

To enhance the design efficiency of axial-field flux-switching permanent magnet (AF-FSPM) machines, this paper proposes a multi-objective optimization method based on a quasi-three-dimensional (quasi-3D) harmonic modulation model. By combining magnetic field modulation theory with three-dimensional equivalent analysis, a multi-layer quasi-3D harmonic modulation model is developed to determine the optimal number of layers by analyzing the variation in magnetic flux linkage. In addition, the model also reveals relationships between key structural parameters (including inner diameter and stator/rotor tooth height ratio) and torque, thus providing valuable guidance for the initial design stage. Subsequently, structural parameters of each layer are classified into two levels by a sensitivity analysis and then optimized with the objectives of maximizing average torque and minimizing torque ripple. Finite element analysis and experimental results verify the method’s effectiveness, achieving a 17.1% torque increase while constraining torque ripple at 5.31% within only 19 hours. The proposed optimization method is also applicable to conventional axial flux permanent magnet machines; however, further analysis of the optimal number of layers is required due to differences in magnetic circuit topology and harmonic characteristics.