• DocumentCode
    2365792
  • Title

    On-Line Identification of Induction Motors using Discrete Models for Sinusoidal Signals

  • Author

    Prado, Alcindodo, Jr. ; De Sousa, Antonio Heronaldo ; Ferrari, Sandro Mauro

  • Author_Institution
    Santa Catarina State Univ.
  • fYear
    2006
  • fDate
    6-10 Nov. 2006
  • Firstpage
    811
  • Lastpage
    816
  • Abstract
    In this work are developed two on-line identification methods for induction motors based on discrete models obtained when we consider continuous systems excited by sinusoidal signals. The first method uses the discrete model of the homopolar machine in the stationary frame to estimate the stator resistance and the stator leakage inductance and the discrete model of the linear system existent among the stator flux and stator current in the rotor frame to estimate all the electric parameters of the motor. The second method, besides this last model, presupposes to estimate the stator resistance with DC excitation added to the supply voltage of the motor and the knowledge of the motor class, in order to estimate the other electric parameters through classical methods of least squares parameters estimation. Simulation and experimental results illustrate the proposed methods
  • Keywords
    continuous systems; induction motors; least squares approximations; magnetic flux; parameter estimation; rotors; stators; DC excitation; continuous systems; discrete models; homopolar machine; induction motors; least squares parameters estimation; linear system; online identification; rotor frame; sinusoidal signals; stator current; stator flux; stator leakage inductance; stator resistance; Continuous time systems; DC motors; Electric resistance; Homopolar machines; Inductance; Induction motors; Linear systems; Rotors; Signal processing; Stators;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    IEEE Industrial Electronics, IECON 2006 - 32nd Annual Conference on
  • Conference_Location
    Paris
  • ISSN
    1553-572X
  • Print_ISBN
    1-4244-0390-1
  • Type

    conf

  • DOI
    10.1109/IECON.2006.347339
  • Filename
    4153097