动圈式永磁直线直流电机的精英保留多种群遗传优化算法

为了实现陆基无人机电磁弹射器高机动性及其直线弹射电机的高功率密度,针对动圈式永磁直线直流电机,提出精英保留的多种群遗传算法(Multi-Population Genetic Algorithm with Elite Retention, MPGAER)的电机最大功率密度优化方法。以磁通密度和电流密度为约束条件,利用其搜索能力强、收敛速度快的特点优化电机的结构参数,并与磁路法初始设计结果和传统遗传算法优化结果进行比较。结果表明:与磁路法初始设计相比,MPGAER能使电机质量减少6.25%,功率密度提高10%,电机动态性能得到提高;MPGAER优化设计的电机功率密度高于遗传算法设计结果,所提方法有效地解决了在优化过程中出现易收敛于局部最优点和寻优效果差的问题。

Multi-population genetic optimization algorithm with elite retention for moving-armature permanent magnet linear direct current motor

In order to realize the high maneuverability of the electromagnetic catapult and the high power density of the linear catapult motor of the land-based unmanned aerial vehicle, a multi-population genetic algorithm with elite retention (MPGAER) was proposed to optimize the maximum power density of motor. It takes flux density and current density as constraints, and optimizes the structure parameters of the motor with its strong search ability and fast convergence speed, and compares with the initial scheme based on magnetic circuit method and the optimization results of traditional genetic algorithm. The results show that, compared with the initial scheme design, MPGAER can reduce the motor mass by 6.25%, increase the power density by 10%, and improve the dynamic performance of the motor; the motor power density of the MPGAER optimized design is higher than the genetic algorithm design result, which indicates that the proposed method effectively solves the problems of easy convergence to the local best advantage and poor optimization effect in the optimization process.