湖南工业大学学报2026，Vol.40Issue(3)：17-23,7.DOI:10.20271/j.cnki.1673-9833.2026.3003
GA-SVM结合NSGA-Ⅲ对开关磁阻电机多目标优化设计
Multi-Objective Optimization Design of Switched Reluctance Motor Based on GA-SVM Combined with NSGA-Ⅲ
摘要
Abstract
In view of the flaw of significant performance fluctuations and low efficiency found in switched reluctance motor drives,a multi-objective optimization strategy,which combines a prediction model optimized using support vector machines(GA-SVM)with the third-generation non-dominated genetic algorithm(NSGA-Ⅲ),has thus been proposed.The simulation results show that the proposed method can significantly improve the average torque and efficiency of switched reluctance motors,with its torque ripple reduced.By establishing a simulation model of a switched reluctance motor,and using sensitivity analysis to select parameters with high influence factors as decision variables,the switched reluctance motor is sampled using hyper-Latin square sampling.The response values are calculated using finite element analysis,with the GA-SVM and NSGA-Ⅲ algorithms combined to perform multi-objective optimization on the motor.The optimized data is weighted with weight coefficients,thus obtaining the optimal solution.The effectiveness of the proposed method can be verified by the simulation results.关键词
开关磁阻电机/灵敏度分析/支持向量机/多目标寻优/第三代非支配排序遗传算法Key words
switched reluctance motor/sensitivity analysis/support vector machine(SVM)/multi-objective optimization/third-generation non-dominated sorting genetic algorithm(NSGA-Ⅲ)分类
信息技术与安全科学引用本文复制引用
周程涛,陈刚,邓琪,柏恋凡..GA-SVM结合NSGA-Ⅲ对开关磁阻电机多目标优化设计[J].湖南工业大学学报,2026,40(3):17-23,7.基金项目
国家自然科学基金资助项目(62173136) （62173136）
国家重点研发计划基金资助项目(2024YFE0111100) （2024YFE0111100）
