基于遗传粒子群的永磁低速直线电机优化研究

本文以改善电机效率和降低永磁低速直线电机制造成本为优化设计目标,把单台电机造价和电机电磁推力的比值作为目标函数,由于目标函数的优化变量多,参数间相互约束,目标函数复杂等特点,因此本文采用遗传粒子群算法对永磁低速直线电机进行优化设计,通过对两种设计仿真结果对比证明了该算法在提高电机电磁性能,降低制造成本方面有明显的优越性。

Study on low speed permanent magnet linear motor is optimized based on genetic particle swarm optimization

The goal of the paper is to improve efficiency and reduce manufacturing cost of the low-speed permanent magnet motor, regarding the single motor＇s costs and motor electromagnetic thrust ratio as the objective function. As the character of function contains too many optimization variables, complex parameters,so this paper uses genetic particle swarm algorithm to design low-speed permanent magnet linear motor. By comparing two simulation results, it shows that this new algorithm has obvious advantage in term of proving motor＇s electromagnetic and reducing manufacturing cost.