A Preference Multi-objective Optimization Method for Asymmetric External Rotor Switched Reluctance Motor

Abstract

To improve the performance (low torque ripple, high average torque, and high efficiency) of the external rotor switched reluctance motor (ERSRM), a preference multi-objective optimization framework for design and control of an ERSRM based on CD-NSGA-II (Chi-square distance fast nondominated sorting genetic algorithm) with gradient targets is investigated. Firstly, the structure of the ERSRM is introduced, and the comprehensive sensitive analysis that evaluates the influence of each design variable on optimization objectives is presented. Secondly, the initialization of population, crossmutation method, and sorting method of conventional NSGA-II are improved. Then, the practicability of this method was proved by standard test functions. Finally, the NSGA-II and CD-NSGA2-II are combined with the visual basic script (VBS) script to optimize the ERSRM, respectively. Finite-element analysis results confirmed the validity and superiority of the optimized design.