摘要：本文以单位永磁体功率最大为目标，提出利用遗传算法和粒子群优化算法对一台三相8对极轴向磁场定子无铁心永磁电机进行优化设计。在建立电机磁场分析模型的基础上，提取五个变量，优化目标的同时约束输出功率、电流密度等电机性能。文章阐述了两种算法在该电机优化中的性能差异，并运用有限元软件对优化结果进行比对分析。仿真结果表明两种算法优化效果均很明显，解析法与有限元分析结果吻合，证明了电磁分析模型的准确性。

关键词：轴向磁场；优化设计；遗传算法；粒子群；3D有限元
Abstract: The genetic algorithm (GA) and particle swarm optimization algorithm（PSO) was presented to optimize an three-phase axial flux permanent magnet (AFPM) motor with 8 pair poles. The maximizing of the motor power density was designed for the objective. Five variables were selected based on the magnetic field analysis model to optimize the objective while constraining the output power, current density and other motor performances. Discussed the difference of the two algorithms in this motor optimizations, then the optimization results were compared with the consequence of the finite element analysis (FEA). The simulation results indicated that both of the algorithms were effective and the results of the analytic method correspond to the FEA. The accuracy of the magnetic field analysis model was verified.

Key words: axial flux permanent-magnet；optimization design； GA； PSO； FEA