首页> 外文期刊>Compel >Multi-objective optimization of a spoke-type permanent magnet motor with fractional-slot concentrated windings for EVs
【24h】

Multi-objective optimization of a spoke-type permanent magnet motor with fractional-slot concentrated windings for EVs

机译:用于EVS的分数槽集中绕组的辐条型永磁电动机的多目标优化

获取原文
获取原文并翻译 | 示例
           

摘要

Purpose This paper aims to propose a spoke-type fractional-slot concentrated windings (FSCW) PM machine for EVs driving system to improve torque density. To further improve electromagnetic performance, the multi-objective optimization design is processed based on response surface (RS) model and simulated annealing cuckoo search (SA-CS) algorithm. Design/methodology/approach The spoke-type FSCW PM machine is designed and optimized to meet the requirement of EVs driving system. First, a spoke-type FSCW PM machine is designed and some of key parameters are obtained based on equivalent magnetic circuit (EMC) method. Then, the RS model and modified SA-CS algorithm are proposed to obtain higher torque, lower torque ripple and higher efficiency. Findings After verification by finite element method for no-load and load performance, the optimal machine has higher torque density, lower torque ripple and higher efficiency compared with initial machine. Finally, a 20 kW prototype is manufactured and tested to verify the validity of the proposed optimization design method. Originality/value This paper designs a high torque density spoke-type FSCW PM machine, which is superior for EVs driving system. Meanwhile, a novel modified SA-CS algorithm is applied to the field of electrical machine multi-objective optimal design.
机译:目的本文旨在提出一种用于EVS驱动系统的辐条型分数槽集中绕组(FSCW)PM机,以提高扭矩密度。为了进一步提高电磁性能,基于响应面(RS)模型和模拟退火覆盖杜鹃搜索(SA-CS)算法来处理多目标优化设计。设计/方法论/接近辐条型FSCW PM机器设计和优化,以满足EVS驱动系统的要求。首先,设计了一种辐条型FSCW PM机,基于等效磁路(EMC)方法获得了一些关键参数。然后,提出了RS模型和改进的SA-CS算法以获得更高的扭矩,更低的扭矩脉动和更高的效率。通过有限元方法进行验证后的调查结果,最佳机器具有较高的扭矩密度,扭矩纹波和较高效率与初始机器相比。最后,制造和测试了20 kW原型以验证所提出的优化设计方法的有效性。原创性/值本文设计了一个高扭矩密度辐条型FSCW PM机器,适用于EVS驱动系统。同时,新颖的修改SA-CS算法应用于电机多目标最佳设计领域。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号