• DocumentCode
    2344187
  • Title

    Optimization of Switched Reluctance Motor for Efficiency Improvement Using Response Surface Model and Kriging Model

  • Author

    Song, Xueguan ; Park, Youngchul ; Li, Jian ; Lee, Joonho

  • Author_Institution
    Dept. of Mech. Eng., Dong-A Univ., Busan, South Korea
  • fYear
    2011
  • fDate
    15-19 April 2011
  • Firstpage
    259
  • Lastpage
    260
  • Abstract
    This paper presented an optimization of switched reluctance motor for higher efficiency. The motor in this study was designed based on the magnetic energy conversion loop according to the power requirements of application system. It´s found that besides the width of air gap, the stack length and turns of winding influenced the electric and magnetic excitation greatly. Hence, in this study, the stack length, turns of winding and width of air gap were optimized as the design variables, surrogate models including response surface model and kriging model are employed to formulate the objective i.e. the efficiency, in which optimal Latin hypercube sampling and sequential sampling are implemented. Dynamic FEM analysis coupling with external circuit is utilized to conduct computer experiments of the various models. The results demonstrate the capability and potential of this approach in solving the efficiency design of reluctance motors.
  • Keywords
    air gaps; finite element analysis; machine windings; optimisation; reluctance motors; Latin hypercube sampling; air gap; dynamic FEM analysis coupling; electric excitation; external circuit; kriging model; magnetic energy conversion loop; magnetic excitation; optimization; power requirements; response surface model; sequential sampling; switched reluctance motor; windings; Atmospheric modeling; Computational modeling; Computers; Mathematical model; Optimization; Reluctance motors; Response surface methodology; Kriging Model; RSM; optimziation; switched reluctance motor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Sciences and Optimization (CSO), 2011 Fourth International Joint Conference on
  • Conference_Location
    Yunnan
  • Print_ISBN
    978-1-4244-9712-6
  • Electronic_ISBN
    978-0-7695-4335-2
  • Type

    conf

  • DOI
    10.1109/CSO.2011.194
  • Filename
    5957655