基于模糊推理田口法的IPMSM多目标优化设计

内置式永磁同步电机（IPMSM）已广泛应用在电动汽车、城市轨道交通等领域，高转矩密度、宽调速范围和低振动噪声等是IPMSM设计时需要兼顾的重要性能指标。提出基于模糊推理田口法的IPMSM多目标优化设计，以解决平均转矩、转矩脉动和弱磁扩速范围多个优化目标之间的制约和冲突问题。在田口正交实验设计的基础上，利用模糊推理将多个优化目标转化为单一目标，从而获得电机的最优设计参数组合。有限元仿真表明，所提出的优化设计方案与优化前和传统田口法比较，各性能指标均得到较大的提升，验证了模糊推理田口法的有效性和先进性。

Multi-objective Optimization Design for IPMSM based on Fuzzy Inference Taguchi Method

The interior permanent magnet synchronous motor (IPMSM) is widely used in electric vehicles, urban rail trains, and other fields. High torque density, wide range of speed, and low vibration and noise are important performances that need to be considered in the design of IPMSM. Multi-objective optimization design for IPMSM based on Fuzzy Inference Taguchi Method (FITM) is proposed to solve the problem of conditionality and conflict between objectives such as high average torque, low torque ripple, and wide flux-weakening speed range. On the basis of the orthogonal design of experiments established by Taguchi method, the fuzzy inference system was introduced to translate the multiple optimization targets to a single target, so as to obtain the best combination of motor design parameters. The finite element simulation shows that the performance of the proposed optimization scheme is greatly improved compared with the initial design and the traditional Taguchi method, and the validity and superiority of FITM are verified.