• DocumentCode
    723985
  • Title

    Multi-objective optimization design of permanent magnet drive based on Kriging model

  • Author

    Li Zhao ; Wang Dazhi ; Liu Zhen

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
  • fYear
    2015
  • fDate
    23-25 May 2015
  • Firstpage
    847
  • Lastpage
    851
  • Abstract
    Permanent magnet drive (PMD) design problems are studied and a multi-objective optimization design approach based on Kriging approximate model is put forward, which takes a variety of structural parameters and performance parameters (such as thickness of permanent magnets, air gap, etc.) as design variables and the minimum eddy current loss and maximum out torque as double optimization goals. Firstly initial sampling data is obtained with the orthogonal experiment design and finite element method (FEM); then the approximate model between the structrual parameters and the eddy current loss and out torque are set up with Kriging method; finally the structure parameters of PMD is optimized by using multi-objective particle swarm algorithm(MOPSO). In the finite element simulation experiment, the magnetic braking force and eddy current density distributions before and after the improvement are compared, the results prove that the parameter optimization method is feasible and has realized the optimization of PMD structrual parameters configuration, and improved working efficiency of the system.
  • Keywords
    current density; eddy current braking; eddy current losses; finite element analysis; motor drives; particle swarm optimisation; permanent magnet motors; statistical analysis; FEM; Kriging approximate model; PMD multiobjective optimization design approach; eddy current density distribution; finite element method; finite element simulation; magnetic braking force; maximum out torque; minimum eddy current loss; multiobjective particle swarm algorithm; parameter optimization method; permanent magnet motor drive multiobjective optimization design; structrual parameters; Atmospheric modeling; Eddy currents; Finite element analysis; Optimization; Particle swarm optimization; Permanent magnets; Torque; Kriging model; Permanent magnet drive (PMD); finite element method (FEM); multi-objective particle swarm (MOPSO);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2015 27th Chinese
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4799-7016-2
  • Type

    conf

  • DOI
    10.1109/CCDC.2015.7162037
  • Filename
    7162037