针对传统NSGA-Ⅱ在永磁辅助开关磁阻电机的多目标优化中局部搜索能力较弱的问题，提出一种基于NSGA-Ⅱ的局部范围搜索算法（RLS-NSGA-Ⅱ），利用改进的交叉算子与变异算子增强算法的搜索能力，在局部区域内搜索最优解集，并通过标准多目标问题验证算法的有效性。针对优化算法对决策变量的优化精度过高的问题，对决策变量进行有效单位保留，并以此提出一种最小单位优化变异方法。对电机转矩脉动、效率和平均转矩进行多目标优化，并与传统NSGA-Ⅱ进行优化效果和仿真的对比验证，结果表明本算法得出的最优解更有优势。

Aiming at the problem that the traditional NSGA-Ⅱ has weak regional local search ability in multi-objective optimization of permanent magnet (PM) assisted switched reluctance motors, a regional local search algorithm based on NSGA-Ⅱ (RLS-NSGA-Ⅱ) is proposed. The improved crossover operator and mutation operator are used to enhance the search capability of the algorithm and search for the optimal solution set in the local area. The effectiveness of the algorithm is verified through standard multi-objective problems. Aiming at the problem that the optimization algorithm′s optimization precision of decision variables is too high, effective units for decision variables are reserved, and a minimum unit optimization mutation method is proposed. The multi-objective optimization of motor torque ripple, efficiency and average torque is performed using the proposed algorithm and the traditianal NSGA-Ⅱ. After optimization effect comparison and simulation, it is verified that the optimal solution derived from the proposed algorithm is more advantageous.

国家自然科学基金项目（52167005）