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<p>High-speed switched reluctance motors generate vibration during operation, which can adversely affect. By analyzing the principles of vibration, it is determined that the main influencing factors in terms of electromagnetism are torque ripple and radial electromagnetic force. To optimize torque ripple and radial force while ensuring that the average torque does not decrease, semicircular grooves are excavated on both sides of the rotor teeth, and circular holes are opened in the rotor yoke. To accurately and efficiently identify the optimal optimization parameters, a multi-objective optimization approach is employed, combining response surface optimization with the particle swarm algorithm (PSO). The results indicate that both torque ripple and radial force are significantly reduced without compromising the average torque. Finally, based on the optimal parameters identified, a post-optimization prototype is manufactured and experimentally compared with the pre-optimization prototype. The results demonstrate that vibration acceleration and vibration is significantly reduced, which in turn leads to a substantial decrease in vibration noise. Additionally, the motor experienced a notable weight reduction, thereby validating the accuracy of the optimization process.</p>

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A novel rotor design for mitigating vibration noise in high-speed switched reluctance motors

  • 期刊论文

  • 发表日期：

    2025年6月28日

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  • Li Li,
  • Zhipeng Li,
  • Jianfeng Mao,
  • Baisong Pan,
  • Yingjie Xu,
  • Rongsheng Jia,
  • Chunhui Ye,
  • Weigang Wang

摘要

High-speed switched reluctance motors generate vibration during operation, which can adversely affect. By analyzing the principles of vibration, it is determined that the main influencing factors in terms of electromagnetism are torque ripple and radial electromagnetic force. To optimize torque ripple and radial force while ensuring that the average torque does not decrease, semicircular grooves are excavated on both sides of the rotor teeth, and circular holes are opened in the rotor yoke. To accurately and efficiently identify the optimal optimization parameters, a multi-objective optimization approach is employed, combining response surface optimization with the particle swarm algorithm (PSO). The results indicate that both torque ripple and radial force are significantly reduced without compromising the average torque. Finally, based on the optimal parameters identified, a post-optimization prototype is manufactured and experimentally compared with the pre-optimization prototype. The results demonstrate that vibration acceleration and vibration is significantly reduced, which in turn leads to a substantial decrease in vibration noise. Additionally, the motor experienced a notable weight reduction, thereby validating the accuracy of the optimization process.