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  • 标题:Optimal Design of Switched Reluctance Motor Using PSO Based FEM-EMC Modeling
  • 其他标题:Optimal Design of Switched Reluctance Motor Using PSO Based FEM-EMC Modeling
  • 本地全文:下载
  • 作者:Mouellef Sihem ; Bentounsi Amar ; Benalla Hocine
  • 期刊名称:International Journal of Electrical and Computer Engineering
  • 电子版ISSN:2088-8708
  • 出版年度:2015
  • 卷号:5
  • 期号:5
  • 页码:887-895
  • DOI:10.11591/ijece.v5i5.pp887-895
  • 语种:English
  • 出版社:Institute of Advanced Engineering and Science (IAES)
  • 摘要:This paper aims to optimize the design of a prototype of a 6/4 Switched Reluctance Motor (SRM) using the Particle Swarm Optimization (PSO) algorithm. The geometrical parameters to optimize are the widths of the stator and rotor teeth due to their significant effects on the prototype design and the performances in terms of increased average torque and reduced torque ripple. The studied 3kW SRM is modeled using a numerical-analytical approach based on a coupled Finite Element Method with Equivalent Magnetic Circuit (FEM-EMC). The simulations are performed under MATLAB environment with user-friendly software. The optimal results found are discussed, compared against those obtained by the Genetic Algorithms (GA) and showed a significant improvement in average torque.
  • 其他摘要:This paper aims to optimize the design of a prototype of a 6/4 Switched Reluctance Motor (SRM) using the Particle Swarm Optimization (PSO) algorithm. The geometrical parameters to optimize are the widths of the stator and rotor teeth due to their significant effects on the prototype design and the performances in terms of increased average torque and reduced torque ripple. The studied 3kW SRM is modeled using a numerical-analytical approach based on a coupled Finite Element Method with Equivalent Magnetic Circuit (FEM-EMC). The simulations are performed under MATLAB environment with user-friendly software. The optimal results found are discussed, compared against those obtained by the Genetic Algorithms (GA) and showed a significant improvement in average torque.
  • 关键词:Electrical;Particle swarm optimization (PSO); Genetic algorithms (GA ); Equivalent magnetic circuits (EMC;); Average torque; Variable reluctance motor (VRM)
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