• DocumentCode
    40583
  • Title

    Robust Optimization Considering Probabilistic Magnetic Degradation

  • Author

    Hidaka, Yuki ; Furui, Shintaro ; Igarashi, Hajime

  • Author_Institution
    Grad. Sch. of Inf. Sci. & Technol., Hokkaido Univ., Sapporo, Japan
  • Volume
    51
  • Issue
    3
  • fYear
    2015
  • fDate
    Mar-15
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This paper presents robust topology optimization of electromagnetic machines by considering the magnetic degradation caused by mechanical and thermal stresses in punching, shrinking fitting, and other manufacturing processes. The topology optimization is performed using two methods: one is the robust genetic algorithm in which random noises are added to the magnetic characteristic parameters and the other takes the deviations in the objective and constraint functions due to the degradation into account. These methods are applied to optimization of the flux barrier shapes in an interior permanent magnetic motor to find that one can successfully realize robust design.
  • Keywords
    genetic algorithms; permanent magnet motors; thermal stresses; wear; constraint functions; electromagnetic machines; flux barrier shapes optimization; interior permanent magnetic motor; magnetic characteristic parameters; manufacturing processes; mechanical stresses; objective functions; probabilistic magnetic degradation; punching; random noises; robust genetic algorithm; robust topology optimization; shrinking fitting; thermal stresses; Degradation; Genetic algorithms; Magnetomechanical effects; Magnetostatic waves; Magnetostatics; Optimization; Robustness; Finite element method (FEM); magnetic degradation; robust optimization; topology optimization;
  • fLanguage
    English
  • Journal_Title
    Magnetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9464
  • Type

    jour

  • DOI
    10.1109/TMAG.2014.2353653
  • Filename
    7093444