基于量子遗传算法电机优化策略及参数选择

吴 凇; 陈 钢

doi:10.11993/j.issn.1673-1948.2015.02.008

基于量子遗传算法电机优化策略及参数选择

doi: 10.11993/j.issn.1673-1948.2015.02.008

吴凇,
陈钢

中国船舶重工集团公司第705研究所昆明分部, 云南昆明, 650118

详细信息

作者简介:
吴凇(1984-), 男, 在读硕士, 主要研究方向为水下航行器推进电机设计

中图分类号: TJ630.32; TM302
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出版历程
- 收稿日期: 2015-01-22
- 修回日期: 2015-01-30
- 刊出日期: 2015-04-20

Strategy and Parameter Selection for Motor Optimization Based on Quantum Genetic Algorithm

WU Song,
CHEN Gang

Kunming Branch of the 705 Research Institute, China Shipbuilding Industry Corporation, Kunming 650118, China

摘要

摘要: 使用量子遗传算法对电机结构进行优化设计需对相关策略和参数进行妥善设置这对使用者的使用经验有一定要求。以某外转子磁系统永磁无刷双转电机为原型讨论了旋转角调整策略及收敛判据的选择方法分析了不同量子交叉、量子变异概率对寻优效果的影响并介绍了种群规模、优化变量个数的设置思路。归纳总结出使用量子遗传算法解决电机结构优化问题的算法设置方案可作为解决其同类问题的参考。
- 量子遗传算法 /
- 电机优化 /
- 永磁无刷双转电机
Abstract: When the quantum genetic algorithm is applied to optimization design of motor structure, it is necessary to deal with the relative strategies and parameters properly, which needs more user′s experience. In this study, taking a permanent magnet brushless DC double-rotor motor with an outer rotating magnetic system for example, the selection of rotation angle adjusting strategy and convergence criterion is discussed, the effects of different quantum crossover probabilities and quantum mutation probabilities on optimization result are analyzed, and the setting idea of population size and number of optimization variables is introduced. As a result, a scheme for applying quantum genetic algorithm to motor structure optimization is obtained. This scheme can also be adopted for solving other similar problems
- quantum genetic algorithm /
- motor optimization /
- permanent magnet brushless DC double-rotor motor

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参考文献(7)

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