改进遗传蚁群算法及其在电机结构优化中的研究  

Improved genetic ant colony algorithm and research on motor structure optimization

作　　者：谢颖[1] 李吉兴[1] 杨忠学[2] 张岩[1] 

机构地区：[1]哈尔滨理工大学电气与电子工程学院,黑龙江哈尔滨150080 [2]东北石油大学电气信息工程学院,黑龙江大庆163318

出　　处：《电机与控制学报》2015年第10期64-70,共7页Electric Machines and Control

基　　金：国家自然科学基金(51107022);黑龙江省博士后科研启动项目(LBH-Q12061);黑龙江省普通高等学校新世纪优秀人才培养计划(1252-NCET-015);黑龙江省自然科学基金(E201443);哈尔滨市科技创新人才研究专项资金(青年后备人才)项目(RC2014QN007005);人社部留学人员科技活动项目择优资助项目

摘　　要：针对电机的优化设计问题,采用一种改进的二进制遗传蚁群算法,对一台4极7.5k W的自起动永磁同步电动机的结构参数进行优化,该算法结合遗传算法和蚁群算法各自的优点,并且能解决连续空间优化问题。介绍了改进二进制遗传蚁群算法的基本思想及其特点,重点论述该算法在电机优化设计中的具体实现方法。采用编程语言实现该算法,通过大量的仿真计算验证算法的全局收敛能力。利用有限元方法对优化后的电磁设计方案进行仿真,结果表明该算法可以使自起动永磁同步电动机得到较好的优化,有可能提高电机的起动性能和运行性能。To optimize the structural parameters of the 4-pole 7. 5 kW line-start permanent magnet synchro-nous motor, an improved binary genetic ant colony algorithm which combined the advantages of genetic al-gorithm with ant colony algorithm and solved the problem of continuous space optimization was used. The basic idea of binary genetic ant colony algorithm and its features were presented, and the specific imple-mentation method of binary genetic ant colony algorithm in motor optimization design was mainly discussed. Language was used to realize the algorithm and results of simulation and calculation were obtained to prove its global convergence property. Finite element method was used to simulate the optimized electromagnetic design. The result slows that the optimization design of motor based on improved binary genetic ant colony algorithm may effectively improve the starting and running performance of the motor.

关 键 词：算法 二进制 遗传蚁群 优化 永磁同步 

分 类 号：TM351[电气工程—电机]