基于混沌蚁群算法的鱼雷集成电机推进器电机优化设计

王 鼎; 谢顺依; 连军强

doi:10.11993/j.issn.1673-1948.2011.04.014

基于混沌蚁群算法的鱼雷集成电机推进器电机优化设计

doi: 10.11993/j.issn.1673-1948.2011.04.014

海军工程大学兵器工程系, 湖北武汉, 430033

详细信息

作者简介:
王鼎(1983-), 男, 在读博士, 研究方向为电动力推进技术.

中图分类号: TJ631.2; TM301.3
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- 被引次数: 0
出版历程
- 收稿日期: 2010-11-03
- 修回日期: 2010-12-03
- 刊出日期: 2011-08-31

Optimization Design of Motor for Torpedo Integrated Motor Propulsor Based on Chaos Ant Colony Algorithm

Department of Weaponry Engineering, Naval University of Engineering, Wuhan 430033, China

摘要

摘要: 针对集成电机推进器(IMP)一体化结构要求电机功率密度大, 效率高的特点, 采用将混沌优化算法嵌入蚁群算法的混合智能优化算法——混沌蚁群算法(CACA)对集成电机推进器特种电机设计方案进行优化, 该方法充分利用以上2种优化算法的优点, 即蚁群算法的高精度和混沌算法的快速性。优化结果显示, 优化后的设计方案使电机效率提高了1.6%, 有效体积缩小了5.6%, 使电机能更好地适应高启动场合要求, 优化效果良好, 可为鱼雷IMP特种电机的设计提供参考。
- 电动力鱼雷 /
- 集成电机推进器 /
- 混沌蚁群算法 /
- 特种无刷直流电机
Abstract: To enhance power density and work efficiency of the special brushless DC motor for integrated motor propulsor (IMP) of torpedo, a hybrid optimum intelligent algorithm, named chaos ant colony algorithm (CACA), is presented. This method embeds chaos optimization algorithm into ant colony algorithm. The special brushless DC motor is optimized by making use of the high accuracy of the ant colony algorithm and the rapidness of the chaos optimization algorithm. The optimization results of the motor show that the efficiency is enhanced by 1.6% and the volume is reduced by 5.6%. The proposed chaos ant colony algorithm may become a tool for the design of special brushless DC motor of torpedo IMP.
- electric power torpedo /
- integrated motor propulsor(IMP) /
- chaos ant colony algorithm(CACA) /
- special brushless DC motor

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参考文献(9)

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