摘要
提出了一种填充粒子群算法(FPSO),用以解决双次级永磁同步直线电机优化设计问题。在有限元分析的基础上,采用支持向量机拟合直线电机结构参数与运行性能参数之间的关系,建立用于优化计算的非参数模型;引入填充函数,对传统粒子群算法进行改进,并采用多峰值函数对算法进行测试,结果表明:FPSO具有良好的快速性和全局收敛性;采用FPSO对电机结构参数进行优化,得到一组最优的电机结构参数。仿真实验表明:采用该算法优化后的电机推力大、推力波动小且峰值电流小,符合电机的优化设计目标。
This article proposes a filled particle swarm optimization（FPSO） algorithm to study the double-secondary permanent magnent synchronous linear motor optimization design. This article uses support vector machine to build the model of structure parameters and output performances on the foundation of FEM analysis. The technology of filled functions was introduced to improve the traditional particle swarm optimization algorithm, the test function proves that the FPSO can be more frequent and accurate in global optimization. Finally FPSO is applied to optimize the linear motor model. The simulation experiment shows that the optimized PMLSM has an increased thrust, and smaller thrust ripple, low peak current, the motor can reach the goal of optimization design.
出处
《电气工程学报》
2015年第8期56-61,共6页
Journal of Electrical Engineering
基金
国家自然科学基金(51277002)资助项目
关键词
双次级永磁同步直线电机
支持向量机
填充函数
粒子群
全局优化
Double-secondary permanent magnent synchronous linear motor
support vector machine
filled functions
particle swarm
global optimi
