Design Optimization of a New Energy Vehicle Drive Motor Based on Genetic Algorithm and Taguchi Method

In order to enhance the electromagnetic characteristics for new energy vehicle (NEV) drive motors, an optimization design combining of the taguchi method and genetic algorithm is developed in this paper. The optimization concentrates on the rotor structure, and the variables are thickness of large and small magnets, angle of large and small magnets, and polar arc coefficients of large and small magnets. Employing a genetic algorithm with elite strategy, the quantities of torque ripple, line back EMF harmonic distortion, peak torque ripple, unit cost output torque, and electromagnetic force are solved. The taguchi method is used to uncover the sensitivity between variables and objectives, and the unique mutation operator for each variable is established. The best results are obtained through the selection of these mutation operators and selection operators. The research results demonstrate that, compared to the initial proposal, the optimized objective meets all technical specifications and effectively reduces noise. It confirms the feasibility and superiority of the current genetic algorithm, as well as its practical value in engineering.