电动汽车用内置式永磁同步电机气隙磁场解析建模与多目标优化

为提高电动汽车用内置式永磁同步电机气隙磁场解析计算精度和优化效率，利用混合解析法建立考虑转子铁心磁桥饱和效应的电机气隙磁场参数化解析模型。首先利用联合等效磁路法的子域法建立内置式永磁同步电机开路气隙磁场解析模型；然后利用同样方法建立转子磁桥虚拟磁场解析模型，从而得到考虑转子磁桥饱和效应的电枢反应磁场解析模型；最后通过叠加原理建立内置式永磁同步电机合成气隙磁场解析模型。通过有限元仿真和转矩测试验证内置式永磁同步电机气隙磁场解析模型的准确性。基于所建立的解析模型，以永磁体极弧宽度、定子槽口宽度和转子端部磁桥厚度为优化变量，以特定阶次频率的径向力波、转矩和效率为优化目标，利用带精英策略的非支配排序遗传算法，对一台电动汽车用内置式永磁同步电机样机进行多变量多目标优化。研究结果表明：与试验结果相比，解析计算误差小于5%,而计算时间较有限元仿真缩短90%以上；优化后，电机特定阶次频率的径向力波减小了9.2%,最大转矩提升了2.49%,最大效率提升了0.69%,高效区面积扩大了约54.46%;所提方法既解决了内置式永磁同步电机强非线性和高饱和的解析建模共性难点，又极大提高了电机多目标优化效率；研究可...

Analytical Modeling of Air-gap Magnetic Field and Multi-objective Optimization of Interior Permanent Magnet Synchronous Motor for Electric Vehicles

To improve the analytical calculation accuracy and optimization efficiency of the air-gap magnetic field of an interior permanent magnet synchronous motor (IPMSM) for electric vehicles, a parametric analytical model of the air-gap magnetic field considering the saturation effect of rotor core magnetic bridges was established using a hybrid analytical method. First, an analytical model of the open-circuit air-gap magnetic field of an IPMSM was established using the subdomain method combined with the equivalent magnetic circuit method. A virtual magnetic field analytical model of the rotor magnetic bridge was established by the same method. An armature reaction magnetic field analytical model considering the saturation effect of the rotor magnetic bridge was obtained, and an analytical model of the load air-gap magnetic field of the IPMSM was established by the superposition principle. The accuracy of the analytical model was verified using the finite element method and a torque test. Compared with the experimental results, the analytical calculation error is less than 5%. The calculation time is reduced by more than 90% compared with the finite element simulation. Based on the established analytical model, the optimization variables are the pole arc width of the permanent magnet, width of the stator slot, and thickness of the magnetic bridge at the end of the rotor. Taking the radial force wave of specific order frequency, torque, and efficiency as the optimization objectives, a multivariable and multi-objective optimization of an IPMSM prototype for electric vehicles was carried out using the non-dominated sorting genetic algorithm with elite strategy (NSGA-II). After optimization, the radial force wave of the specific-order frequency of the motor reduces by 9.2%, the maximum torque increases by 2.49%, the maximum efficiency increases by 0.69%, and the area of the high-efficiency zone increases by approximately 54.46%. The results show that the proposed method solves the common difficulties of analytical modeling of IPMSM with strong nonlinearity and high saturation and considerably improves motor multi-objective optimization efficiency. This research can provide a reference method for the optimization design of an IPMSM for electric vehicles.