• DocumentCode
    2116247
  • Title

    Speed estimation of an induction motor drive using extended Kalman filter

  • Author

    Shi, K.L. ; Chan, T.F. ; Wong, Y.K. ; Ho, S.L.

  • Author_Institution
    Dept. of Electr. Eng., Hong Kong Polytech., Hung Hom, China
  • Volume
    1
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    243
  • Abstract
    This paper presents a detailed study of the extended Kalman filter (EKF) far estimating the rotor speed of an induction motor drive. The general structure of the Kalman filter is reviewed and the various system vectors and matrices are defined. By including the rotor speed as a state variable, the EKF equations are established from a discrete two-axis model of the three-phase induction motor. Using the software MATLAB/Simulink, simulation of the EKF speed estimation algorithm is carried out for an induction motor drive with constant V/Hz frequency control and an induction motor drive with direct self control. The investigations show that the EKF is capable of tracking the actual rotor speed provided that the elements of the covariance matrices are properly selected. Moreover, the performance of the EKF is satisfactory even in the presence of noise or when there are variations in the induction machine parameters
  • Keywords
    Kalman filters; covariance matrices; digital simulation; electric machine analysis computing; frequency control; induction motor drives; machine control; parameter estimation; rotors; MATLAB/Simulink software; constant V/Hz frequency control; covariance matrices; direct self control; discrete two-axis model; extended Kalman filter; induction motor drive; rotor speed estimation; three-phase induction motor; Equations; Frequency control; Frequency estimation; Induction motor drives; Induction motors; Kalman filters; MATLAB; Mathematical model; Rotors; Software algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering Society Winter Meeting, 2000. IEEE
  • Print_ISBN
    0-7803-5935-6
  • Type

    conf

  • DOI
    10.1109/PESW.2000.849963
  • Filename
    849963