Multi-Objective Optimization Algorithm and Verification for Electromagnetic Vibration and Noise of Direct-Drive Motors in Mobile Robots

WU Huawei; DU Yuxing; ZHANG Ning; LIU Ling; LI Lang

doi:10.7652/xjtuxb202610005

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Multi-Objective Optimization Algorithm and Verification for Electromagnetic Vibration and Noise of Direct-Drive Motors in Mobile Robots

Special Topic Embodied Intelligent Robot | 更新时间：2026-09-29

- Multi-Objective Optimization Algorithm and Verification for Electromagnetic Vibration and Noise of Direct-Drive Motors in Mobile Robots
- Journal of Xi'an Jiaotong University Vol. 60, Issue 10, Pages: 56-68(2026)
- 作者机构：
  
  湖北文理学院湖北隆中实验室，441053，湖北襄阳
  湖北文理学院纯电动车动力系统设计与测试湖北省重点实验室，441053，湖北襄阳
  东南大学机械工程学院，211189，南京
  西安交通大学电气工程学院，710049，西安
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb202610005
  CLC： TP242
- Received：16 December 2025，
  
  Online First：03 March 2026，
  
  Published：10 October 2026
- 稿件说明：
移动端阅览
WU Huawei, DU Yuxing, ZHANG Ning, et al. Multi-Objective Optimization Algorithm and Verification for Electromagnetic Vibration and Noise of Direct-Drive Motors in Mobile Robots[J/OL]. Journal of Xi'an Jiaotong University,2026,60 (10):56-68. https://doi.org/10.7652/xjtuxb202610005.
DOI：

WU Huawei, DU Yuxing, ZHANG Ning, et al. Multi-Objective Optimization Algorithm and Verification for Electromagnetic Vibration and Noise of Direct-Drive Motors in Mobile Robots[J/OL]. Journal of Xi'an Jiaotong University,2026,60 (10):56-68. https://doi.org/10.7652/xjtuxb202610005. DOI：

摘要

针对移动机器人轮式直驱电机运行中由电磁振动噪声引发的环境舒适性与定位感知干扰问题，提出了一种基于改进多目标蜉蝣算法（IMOMA）与参数扫描法（PSM）的协同优化策略。以外径为355.6mm的外转子永磁同步轮式直驱电机为对象，通过定子开辅助槽、转子分段斜极的多目标结构优化设计，验证该策略的工程应用价值。通过引入双层轮盘选择与动态维度变换机制，增强IMOMA算法的全局搜索能力与Pareto前沿覆盖均匀性，结合PSM法构建辅助槽宽度、深度、旋转角度和分段斜极参数的多目标性能数据库，实现高效协同优化。基于多物理场耦合仿真模型验证优化方案的有效性，结果表明：优化后，机壳端盖振动加速度均值在转速为600、1200r/min时分别降低了39.35、41.78mm/s

；机壳-定子接触面与空气域1m处的等效辐射功率分别减少9.2、9.0dB；噪声传播均匀性显著提升；当转速为1200r/min时，A计权声压级降低3.913dB，噪声等级从70dB级削弱至60dB级，有效改善了噪声尖锐感与电机舒适性。该研究可为直驱电机低噪声设计提供理论依据。

Abstract

To address the issues of environmental comfort degradation and positioning interference caused by electromagnetic vibration and noise in wheel direct-drive motors of mobile robots during operation

a collaborative optimization strategy based on an improved multi-objective mayfly algorithm (IMOMA) and a parameter scanning method (PSM) was proposed. Taking an outer-rotor permanent magnet synchronous wheel direct-drive motor with an outer diameter of 355.6mm as the research object

the engineering application value of this strategy was verified through the multi-objective structural optimization design of auxiliary stator slots and a st

ep-skewed rotor. By introducing a dual-layer roulette wheel selection and dynamic dimension transformation mechanism

the global search capability and the uniformity ofPareto front coverage of the IMOMA algorithm were enhanced. The approach combined with a PSM-constructed multi-objective performance database for auxiliary slot parameters (width

depth

rotation angle) and step-skewing parameters achieved efficient collaborative optimization. The effectiveness of the optimized solution was verified through a multi-physics coupled simulation model. The results show that the optimized motor exhibits the following: the average housing end-cap vibration acceleration was reduced by 39.35mm/s

at 600r/min and 41.78mm/s

at 1200r/min; the equivalent radiated power was reduced by 9.2dB at the stator-housing interface and by 9.0dB at a distance of 1min the air domain; and noise propagation uniformity was significantly improved

with a 3.913dB reduction in A-weighted sound pressure level at 1200r/min. This effectively lowered the noise level from the 70dB range to the 60dB range

mitigating noise harshness and enhancing motor comfort. This study provides a theoretical basis for the low-noise design of direct-drive motors.

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