Abstract
Intelligent algorithms and surrogate models are commonly used in electromagnetic design of electrical machines. But they are rarely employed for other single-physics or multi-physics designs, such as that for electromagnetic vibration suppression. On the other hand, it is uncommon in existing literatures to compare the performances of different surrogate models for optimization. In this paper, the accuracies of three surrogate models are compared for different optimization objectives, and a 15-input 7-output problem involving electromagnetic vibration is solved through particle swarm optimization. After optimization, the motor electromagnetic vibrations at all dominant frequencies are significantly reduced and the torque performance is improved. The optimization result is verified with both finite element simulation and experimental measurement.
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