重庆大学学报2017，Vol.40Issue(8)：1-8,8.DOI:10.11835/j.issn.1000-582X.2017.08.001
量子遗传算法在永磁同步轮毂电机优化设计中的应用
Application of quantum genetic algorithm to the optimum design of permanent magnet synchronous in-wheel motor
摘要
Abstract
Quantum genetic algorithm (QGA) has advantages of small population size with good algorithm performance,fast convergent rate and powerful ability of global search.In order to acquire high power density and low cost in-wheel motor of electric vehicle,based on the quantum genetic algorithm,a designed outer-rotor permanent magnet synchronous in-wheel motor model with 8 designed variables and 5 constraints was built to optimize the effective quality,material cost and power consumption.The results show that the effective quality,material cost and power consumption of the motor are decreased and the efficiency of the motor is improved.The results of finite element analysis are close to those calculated by quantum genetic algorithm,which can satisfy the using requirements of driving in-wheel motor electric vehicle.Therefore,the QGA is an effective and feasible algorithm in optimization design of in-wheel motor.关键词
量子遗传算法/永磁同步轮毂电机/优化设计Key words
quantum genetic algorithm/permanent magnet synchronous in-wheel motor/optimization design分类
信息技术与安全科学引用本文复制引用
张羽,邓兆祥,张河山,陶胜超,唐蓓..量子遗传算法在永磁同步轮毂电机优化设计中的应用[J].重庆大学学报,2017,40(8):1-8,8.基金项目
国家高技术研究发展计划(“863”计划)项目(2012AA111803) （“863”计划）
重庆市科委攻关项目(CSTC,2010AA6039) （CSTC,2010AA6039）
重庆市研究生科研创新项目资助(CYS15034).Supported by The National High Technology Research and Development Program of China (863 Program)(2012AA111803),ChongqingKey Technology Program (CSTC,2010AA6039) and 2015 Chongqing University Postgraduates' Innovation Project (CYS15034). （CYS15034）
