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<p>This research carries out the optimization design and analysis experiment of the existing design of the IPM motor. In this paper, three optimization methods are designed for the torque ripple value: the Taguchi method, the fuzzy Taguchi method, and the reaction surface method, and the reaction surface method has the highest optimization rate. Ripple optimization results: The optimization rates are 84.58% and 38.47%, respectively. Finally, a single-layer magnet IPM motor with a high optimization rate and low production cost is selected to make a prototype, and the verification and comparison between the physical and the simulation are carried out. The error values between the load and no-load measurement results and the simulation results are 4.35% and 3.95% for average torque, 14.49% and 75.98% for torque ripple, and 17.21% and 15.07% for efficiency. The load test’s measurement results show that the prototype’s torque ripple value is better than the original design, so it is verified that the above optimization and simulation methods are suitable for torque ripple optimization.</p>

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Enhanced design and optimization of torque ripple in interior permanent magnet motors via Taguchi and response surface methodologies

  • 期刊论文

  • 发表日期：

    2025年3月12日

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  • Yu-Hsun Chen,
  • Hao-Run Chang,
  • Guan-Chen Chen

摘要

This research carries out the optimization design and analysis experiment of the existing design of the IPM motor. In this paper, three optimization methods are designed for the torque ripple value: the Taguchi method, the fuzzy Taguchi method, and the reaction surface method, and the reaction surface method has the highest optimization rate. Ripple optimization results: The optimization rates are 84.58% and 38.47%, respectively. Finally, a single-layer magnet IPM motor with a high optimization rate and low production cost is selected to make a prototype, and the verification and comparison between the physical and the simulation are carried out. The error values between the load and no-load measurement results and the simulation results are 4.35% and 3.95% for average torque, 14.49% and 75.98% for torque ripple, and 17.21% and 15.07% for efficiency. The load test’s measurement results show that the prototype’s torque ripple value is better than the original design, so it is verified that the above optimization and simulation methods are suitable for torque ripple optimization.