基于粒子群优化算法的永磁直流电动机设计  

Design of permanent magnet direct current motors based ona particle swarm optimization algorithm

作　　者：韩力[1] 辛懋[1] 罗辞勇[1] 

机构地区：[1]重庆大学输配电装备及系统安全与新技术国家重点实验室,重庆400030

出　　处：《重庆大学学报（自然科学版）》2009年第5期535-538,共4页Journal of Chongqing University

基　　金：重庆市自然科学基金计划资助项目(CSTC;2008BB6163)

摘　　要：在介绍粒子群优化算法并利用Shubert函数对其有效性进行数值验证的基础上,将其应用于永磁直流电动机的优化设计,分析了优化目标、优化变量和约束条件,在此基础上研发了相应的优化设计软件,并分别以高效率和低成本为目标,应用粒子群优化算法对1台2 kW的永磁直流电动机进行了优化设计,使其效率提高了2.04%、材料成本降低了7.85%。结果表明,粒子群优化算法对永磁直流电动机优化设计是实用有效的,可为其产品设计提供一种良好的新方法。We introduce a particle swarm optimization （PSO） algorithm and verified it using the Shubert function. The PSO algorithm is applied to design optimization of permanent magnet DC motors （PMDCMs）. The optimal objects, decision variables and restricted conditions of PMDCMs are analyzed and given. Furthermore, a set of software is developed to increase the efficiency and decrease the cost of PMDCMs. As an example, the efficiency of a 2 kW PMDCM is improved by 2.04% and its cost is reduced by 7. 85% via the optimization algorithm. The results show that the PSO algorithm is a practical and effective method for optimal design of PMDCMs.

关 键 词：粒子群优化 永磁 直流电动机 电机设计 

分 类 号：TM351[电气工程—电机]