Multiobjective Design Optimization of an IPMSM for EVs Based on Fuzzy Method and Sequential Taguchi Method

The Taguchi optimization method is an efficient method for motor design optimization. However, it is hard to handle the multiobjective motor optimization problem with big design space for the parameters. To deal with this problem, in this article, a fuzzy method and sequential Taguchi method to optimize an inter permanent magnet synchronous motor (IPMSM) is employed. The fuzzy inference system is introduced to convert the multiple objectives to a single-objective optimization problem. The sequential Taguchi method is used to optimize the structural parameters at multiple levels to improve the accuracy of optimization. After the optimal selection analysis, the best combination of motor structure factors is obtained. By comparing the optimization result of the proposed method with that of the conventional Taguchi optimization method, the effectiveness and superiority of the proposed method are verified.

Automated summary

In this article, a fuzzy method and sequential Taguchi method are employed to optimize an IPMSM motor, successfully converting multiple objectives to a single-objective problem and optimizing structural parameters at various levels to achieve the best combination of structure factors after optimal selection analysis. The proposed method's effectiveness and superiority are verified by comparing its optimization results with those of conventional Taguchi optimization method.