基于遗传算法的双余度无刷直流电机优化设计

针对航空电作动系统用双余度无刷直流电机的方案寻优问题,提出了一种基于遗传算法的优化设计方法.通过分析航空作动系统的特点和性能要求得出电机优化设计的目标函数和约束条件.建立电机的电磁和热路模型,得到目标函数和约束条件的解析方程.其中,在电磁模型的建立过程中,采用解析方法得到气隙磁密和反电势系数表达式;在热路模型的建立过程中,采用Bertotti分立铁耗法计算铁心损耗,并利用热路法求解电机各部分的温升.通过遗传算法对电机重量全局寻优.计算结果表明:在满足性能要求的前提下,优化设计方案合理,电机重量减小了13.3%,验证了该优化设计和建模方法的有效性. 

Genetic algorithm based optimal design for dual-redundancy brushless DC motor

A genetic algorithm (GA) based global optimization for a dual-redundancy brushless DC motor (DR-BLDCM) used in aviation actuators was presented. The aim of the optimal design is to reduce the weight of the motor. First, the objective function was established based on the electromagnetic and thermal models. The electromagnetic models include the flux density and the back-electromotive force coefficient expressed by the analytical method. The thermal models were established by the thermal circuit method, in which an accurate estimation for the iron loss was considered. Then the structural parameters of the dual-redundancy brushless DC motor were optimized by using the GA and taking account of the electromagnetic and thermal characteristic constrains. The result of the optimization shows that the weight of the motor had been reduced by 13.3%. This method can be used as a reference for other motor optimal design.