基于GABP-NSGA-Ⅱ的开关磁阻电机系统级多目标优化设计OA
A System-Level Multi-Objective Optimization Design for Switched Reluctance Motors Based on GABP-NSGA-Ⅱ
为提升开关磁阻电机(SRM)的系统驱动性能,提出一种基于遗传算法(GA)优化反向传播(BP)神经网络和非支配排序遗传算法(NSGA-Ⅱ)相结合的多目标优化设计方法,旨在降低其转矩脉动、提高其平均转矩和效率.通过灵敏度分析,选择对开关磁阻电机优化目标影响较大的 3 个本体参数(匝数、转子极弧系数、气隙)和两个控制参数(开通角、关断角)作为决策变量,采用有限元分析、GA-BP法建模和NSGA-Ⅱ算法进行多目标寻优,得到最优解.仿真结果表明,运用GA-…查看全部>>
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 …查看全部>>
陈刚;邓琪
湖南工业大学 电气与信息工程学院,湖南 株洲 412007湖南工业大学 电气与信息工程学院,湖南 株洲 412007
动力与电气工程
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)
switched reluctance motorsystem-level multi-objective optimizationgenetic algorithm optimized backpropagation neural networknon-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)
《湖南工业大学学报》 2024 (3)
32-37,6
国家自然科学基金资助项目(62173136)
评论