• DocumentCode
    1541820
  • Title

    Determination of induction motor parameters by using neural network based on FEM results

  • Author

    Bae, Dongjin ; Kim, Dowan ; Jung, Hyun-Kyo ; Hahn, Song-Yop ; Koh, Chang Seop

  • Author_Institution
    Mechatronics Dev. Dept., Hyundai Heavy Ind. Co. Ltd., Kyunggi Do, South Korea
  • Volume
    33
  • Issue
    2
  • fYear
    1997
  • fDate
    3/1/1997 12:00:00 AM
  • Firstpage
    1924
  • Lastpage
    1927
  • Abstract
    A neural network (NN) is introduced for making model-building between design variables and equivalent circuit parameters in designing three phase induction motors. Some equivalent circuit parameters are calculated by finite element method (FEM) at each slip conditions and various design variables. From these results, a self-organized distributed network (SODN) is trained, then combined with per-phase equivalent circuit method. The use of the proposed method is evaluated from the results that a rapid execution time compared with original FEMs in design procedures. This method is useful for nonlinear problems and model-building problems such as parameter determination
  • Keywords
    electric machine analysis computing; equivalent circuits; finite element analysis; induction motors; learning (artificial intelligence); machine theory; neural nets; parameter estimation; slip (asynchronous machines); FEM results; computer simulation; design variables; equivalent circuit parameters; execution time; induction motor parameters determination; model-building; neural network; nonlinear problems; self-organized distributed network; three-phase; Computer networks; Equations; Equivalent circuits; Finite element methods; Induction motors; Magnetic analysis; Magnetic flux; Magnetic materials; Neural networks; Rotors;
  • fLanguage
    English
  • Journal_Title
    Magnetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9464
  • Type

    jour

  • DOI
    10.1109/20.582668
  • Filename
    582668