Torque ripple reduction of brushless DC motor with convex arc‐type permanent magnets based on robust optimization design

Abstract

The mass production of the motors causes tolerance of shape and dimension, deviation of permanent magnet remanence and rotor eccentricity error, which affect the cogging torque and torque ripple amplitude and performance consistency. In order to reduce the torque ripple of the motor in the actual condition, the robustness optimization is performed in the paper. Firstly, an improving convex arc type permanent magnet structure is adopted to improve air gap flux density and suppress the cogging torque. Secondly, the structure parameters of the magnetic pole are selected as optimization variables, and the magnetization angle, remanence and position of the permanent magnet, static and dynamic rotor eccentricity are considered as noise factors. To improve the overall robustness of the motor under different operating conditions, the dynamic Taguchi method is used to optimize the robustness of the motor, and the test data is processed through the relation analysis method to obtain the optimal combination of control factors. Finally, the prototype is manufactured for the experiment. Compared with the single-operating conditions robust optimization results, the robust optimization method improves the robustness of the motor. The cogging torque amplitude is reduced by 39.2%. The torque ripple is 38.4% lower than that before optimization.