湖南工业大学学报2024，Vol.38Issue(3)：32-37,6.DOI:10.3969/j.issn.1673-9833.2024.03.005
基于GABP-NSGA-Ⅱ的开关磁阻电机系统级多目标优化设计
A System-Level Multi-Objective Optimization Design for Switched Reluctance Motors Based on GABP-NSGA-Ⅱ
摘要
Abstract
In view of an improvement of the system driving performance of Switched Reluctance Motors(SRM),a multi-objective optimization design method has thus been proposed with a combination of a genetic algorithm(GA)optimized back propagation(BP)neural network and non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ),so as to reduce its torque ripple and improve its average torque and efficiency.Based on a sensitivity analysis,three ontology parameters(turns,rotor pole arc coefficient,air gap)and two control parameters(turn on angle,turn off angle),which have a significant impact on the optimization objectives of SRM(switched reluctance motors),are selected as decision variables,followed by an application of the finite element analysis,GA-BP modeling,and NSGA-Ⅱ algorithm for a multi-objective optimization to obtain the optimal solution.关键词
开关磁阻电机/多目标优化/遗传算法优化反向传播神经网络/非支配排序遗传算法(NSGA-Ⅱ)Key words
switched reluctance motor/system-level multi-objective optimization/genetic algorithm optimized backpropagation neural network/non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)分类
信息技术与安全科学引用本文复制引用
陈刚,邓琪..基于GABP-NSGA-Ⅱ的开关磁阻电机系统级多目标优化设计[J].湖南工业大学学报,2024,38(3):32-37,6.基金项目
国家自然科学基金资助项目(62173136) （62173136）
