• DocumentCode
    2235573
  • Title

    A new approach for overcoming failure of current sensors in states estimation of an Induction motor

  • Author

    Tebianian, Hamed ; Moshiri, Behzad ; Nabavi, Mohammad Taghi

  • Author_Institution
    Dept. of Electr. Eng., Islamic Azad Univ., Shahrood, Iran
  • fYear
    2012
  • fDate
    19-21 March 2012
  • Firstpage
    725
  • Lastpage
    730
  • Abstract
    Failures and uncertainties of current sensors are key issues in states and parameters estimation of Induction motors. In this paper, an EKF equipped with Output Augmented Fusion method (OAF) is used to design a new observer for dominance over these challenges. The proposed observer has the ability of speed estimation in a wide range with less sensitivity to parameters´ variations and also failures and uncertainties of current sensors. An EKF is employed to estimate speed as a dynamic state variable over wide range of variation, using extension of states vector with equation of motion and other major parameters consisted of stator/rotor resistances and load torque. Moreover, using OAF algorithm, output matrices are extended to overcome failure probability and uncertainties of current sensors. The effectiveness of this approach is validated by simulation.
  • Keywords
    electric sensing devices; failure analysis; induction motors; observers; rotors; stators; EKF; OAF algorithm; current sensors failure; current sensors uncertainties; dynamic state variable; failure probability; induction motor; induction motor parameters estimation; induction motor states estimation; load torque; observer; output augmented fusion method; parameters estimation; speed estimation ability; stator-rotor resistances; Computer languages; Jacobian matrices;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Technology (ICIT), 2012 IEEE International Conference on
  • Conference_Location
    Athens
  • Print_ISBN
    978-1-4673-0340-8
  • Type

    conf

  • DOI
    10.1109/ICIT.2012.6210024
  • Filename
    6210024