• DocumentCode
    1507971
  • Title

    Parameter Identification of Induction Machine With a Starting No-Load Low-Voltage Test

  • Author

    Lin, Whei-Min ; Su, Tzu-Jung ; Wu, Rong-Ching

  • Author_Institution
    Dept. of Electr. Eng., Nat. Sun Yat-Sen Univ., Kaohsiung, Taiwan
  • Volume
    59
  • Issue
    1
  • fYear
    2012
  • Firstpage
    352
  • Lastpage
    360
  • Abstract
    This paper proposes the use of a steady-state model to identify the parameters of an induction motor. A time-varying impedance can be found with the time-varying voltages and currents under a starting no-load low-voltage test, where time-varying slip rates were also recorded. With a proper conversion, the variations of impedance versus slip rates could be acquired as sampled data for identification, and both electrical and mechanical parameters can be found. A least mean square (LMS) method was used with a particle swarm optimization method to solve the aforementioned problem. The method to find a good set of initial values for LMS is also described in this paper. Many tests were conducted to simulate the starting phases of an induction machine to compare with the existing data. From various tests, the practicability and accuracy of this method can be proven.
  • Keywords
    asynchronous machines; least mean squares methods; machine testing; particle swarm optimisation; induction machine; least mean square method; parameter identification; particle swarm optimization method; starting no-load low-voltage test; steady-state model; time-varying impedance; time-varying slip rates; Impedance; Induction machines; Least squares approximation; Resistance; Rotors; Stators; Steady-state; Induction machine; least mean square (LMS) method; parameter estimation; particle swarm optimization (PSO);
  • fLanguage
    English
  • Journal_Title
    Industrial Electronics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0046
  • Type

    jour

  • DOI
    10.1109/TIE.2011.2148674
  • Filename
    5759775