Abstract：The double permanent-magnet vernier motor operates based on the bi-directional magnetic field modulation effect principle. With the improvement of torque density, there is a problem of significant motor loss. By taking the rated point as the optimization object, the traditional optimization method can only improve the performance of the rated operating point, but has difficulty in efficiently operating multiple working points under the actual operation condition of the motor. Therefore, this paper designs a low-loss modular dual permanent-magnet vernier motor and proposes a multi-operating points optimization method considering operation condition. The representative working points and their weights are extracted using the K-clustering method. To make the optimization procedure more efficient, the sensitivity analysis method is used to qualitatively optimize the variables to reduce the design space. The optimal global solution of susceptible parameters is determined by combining the response surface method and high-convergence multi-objective differential evolution with a ranking-based mutation operator (MODE-RMO). And then, an efficient and accurate motor parameter optimization under operation condition is realized. The proposed method is verified by simulation and experiment.
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2022, Vol. 37 
