基于多目标遗传算法的增程器用外转子发电机的设计优化

Design Optimization of External Rotor Generator for Range Extender Based on Multi-Objective Genetic Algorithm

摘要: 增程器用外转子发电机的效率和转矩脉动等性能是电动汽车增程器系统的综合效率和振动的主要影响因素。本文研究用多目标遗传算法对某增程器用外转子发电机的主要结构参数进行分步优化，以改善其铁损、永磁体用量、转矩脉动和反电势波形等性能。首先，建立了目标外转子发电机的有限元仿真并进行电机模型的参数化。在此基础上，利用多目标遗传算法对定子结构尺寸、转子外径和斜极角度等结构参数进行分步优化，以最大化目标发电机的效率和转矩脉动等综合性能。研究结果表明，基于模型的多目标遗传算法优化后，目标发电机的最高效率达到了96%，高效率区域明显扩大，转矩脉动百分比为10.02%，反电势波形有明显改善。本文的研究可以为外转子永磁发电机的仿真分析和多目标优化提供重要的方法论指导。

Abstract: The efficiency and torque ripple of the external rotor generator for range extender are the main factors affecting the overall efficiency and vibration of the range extender system in electric vehicles. In this paper, multi-objective genetic algorithm is used to optimize the main structural parameters of a range extender external rotor generator step by step to improve its performance such as iron loss, permanent magnet consumption, torque ripple and back EMF waveform. First, the finite element simulation of the target external rotor generator is established and the motor model is parameterized. On this basis, the multi-objective genetic algorithm is used to optimize the structural parameters such as stator structure size, rotor outer diameter and oblique pole angle step by step to maximize the comprehensive performance of the target generator such as efficiency and torque ripple. The research results show that after the model-based multi-objective genetic algorithm optimization, the maximum efficiency of the target generator reaches 96%, the high-efficiency area is significantly expanded, the torque ripple percentage is 10.02%, and the back EMF waveform is significantly improved. The research in this paper can provide important methodological guidance for the simulation analysis and multi-objective optimization of the outer rotor permanent magnet generator.