• DocumentCode
    1716583
  • Title

    The use of a genetic algorithm in the design optimisation of a brushless DC permanent magnet machine rotor

  • Author

    Wrobel, Rafal ; Mellor, Phil H.

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Bristol Univ., UK
  • Volume
    2
  • fYear
    2004
  • Firstpage
    823
  • Abstract
    The paper describes the use of a genetic algorithm in the design optimisation of a surface magnet brushless DC machine. The method combines a two-dimensional magnetostatic finite element model (FEM) with a genetic algorithm (GA) to investigate the influence of the shape of the permanent magnets and their direction of magnetisation. The objective function used in the optimisation procedure is based on maximising torque for a given volume of permanent magnet, assuming the electrical loading of the machine remains unchanged. Compared to a standard radial magnetisation, the optimised rotor designs yield a significant improvement in output torque. To confirm the GA technique a gradient descent optimisation is also applied to the problem.
  • Keywords
    brushless DC motors; finite element analysis; genetic algorithms; gradient methods; load (electric); magnetisation; magnetostatics; permanent magnet motors; rotors; torque; FEM; GA; Halbach magnetisation; design optimisation; electrical loading; finite element model; genetic algorithm; gradient descent optimisation; maximising torque; permanent magnet machine; rotor designs; standard radial magnetisation; surface magnet brushless DC machine; torque improvement; two-dimensional magnetostatic;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Power Electronics, Machines and Drives, 2004. (PEMD 2004). Second International Conference on (Conf. Publ. No. 498)
  • Conference_Location
    Edinburgh, UK
  • ISSN
    0537-9989
  • Print_ISBN
    0-86341-383-8
  • Type

    conf

  • DOI
    10.1049/cp:20040395
  • Filename
    1350130