用于飞轮储能系统的轴向分相电机的电磁分析与优化设计

针对轴向分相电机参数优化问题，在分析电机基本电磁特性的基础上，探究一种关键结构参数提取及其优化设计方法。首先，通过有限元分析探究电机悬浮及转矩性能与结构参数间的一般规律，并基于所得各结构参数的变化曲线进行敏感度分析，获取待优化的关键结构参数。其次结合极限学习机学习速度快、建模精度高的优点，构建多目标统一优化模型。然后以改善平均悬浮力及转矩性能为优化目标，利用粒子群算法进行全局寻优以获得最优参数配置。有限元仿真结果表明，优化后电机的悬浮力和平均转矩分别提高了10.07%和6.67%，验证了所述优化方法的有效性。

Electromagnetic Analysis and Optimization Design of Axial Split-Phase Machine for Flywheel Energy Storage System

For the parameter design problem of axial split-phase machine, based on the analysis of the basic electromagnetic characteristics, the extraction and design method of key structural parameters was studied. First, the general laws between motor suspension force, torque and structural parameters were studied by finite element analysis. Based on the sensitivity analysis of electromagnetic structure parameters, the key parameters to be optimized were obtained. Secondly, a multi-objective unified optimization model was established which combines the advantages of the extreme learning machine with fast learning speed and high modeling accuracy. Then, to improve performance indicators such as average levitation force and average torque, particle swarm optimization was used to perform global optimization to obtain the optimal parameter configuration. The results show that the suspension force and average torque of the machine after optimization are increased by 10.07% and 6.67%, respectively, which verifies the effectiveness of the optimization method.