• DocumentCode
    1210223
  • Title

    Switched reluctance machine model using inverse inductance characterization

  • Author

    Loop, Benjamin P. ; Sudhoff, Scott D.

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Purdue Univ., West Lafayette, IN, USA
  • Volume
    39
  • Issue
    3
  • fYear
    2003
  • Firstpage
    743
  • Lastpage
    751
  • Abstract
    This paper sets forth a new switched reluctance machine model based on a current-dependent inverse inductance representation of the flux linkage versus current and position characteristic. This form permits a particularly simple mathematical description. Based on this relationship, a complete state model is derived. The resulting model is easy to implement and computationally efficient. In addition, both manual and genetic-algorithm-based methods of parameter identification are set forth. The accuracy of the model is tested via comparison to laboratory measurements of the machine´s steady-state voltage and current waveforms as well as torque-speed characteristics. The proposed model is shown to be quite accurate.
  • Keywords
    genetic algorithms; inductance; machine theory; magnetic flux; parameter estimation; reluctance motors; torque; complete state model; current characteristic; current-dependent inverse inductance; flux linkage; genetic-algorithm-based methods; inverse inductance characterization; parameter identification; position characteristic; reluctance motors; steady-state current waveforms; steady-state voltage waveforms; switched reluctance machine model; torque-speed characteristics; Couplings; Current measurement; Inductance; Inverse problems; Laboratories; Parameter estimation; Reluctance machines; Steady-state; Testing; Torque measurement;
  • fLanguage
    English
  • Journal_Title
    Industry Applications, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0093-9994
  • Type

    jour

  • DOI
    10.1109/TIA.2003.811785
  • Filename
    1201542