• DocumentCode
    2513474
  • Title

    On-line estimation of stator resistance and mutual inductance of multiphase induction machines

  • Author

    Mengoni, M. ; Agarlita, S.C. ; Zarri, L. ; Casadei, D.

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Bologna, Bologna, Italy
  • fYear
    2012
  • fDate
    24-26 May 2012
  • Firstpage
    417
  • Lastpage
    423
  • Abstract
    Multiphase drives are receiving attention not only for medium and high power applications, but also for some low power applications, such as heavy electric vehicles. In the case of multiphase induction machines, the most widely adopted control technique is the field-oriented vector control, which provides high torque dynamics and can exploits all the degrees of freedom that this technology offers, but requires an adequate knowledge of the machine parameters. In this paper, a technique for the on-line estimation of the stator resistance and the magnetizing inductances is proposed. Under the assumption that the machine torque is produced by the fundamental component of the air-gap magnetic field, the proposed technique controls the higher harmonics in such a way to excite the machine and to estimate the unknown parameters. Experimental tests confirm the feasibility of the method described in the paper.
  • Keywords
    induction motor drives; machine vector control; parameter estimation; stators; air-gap magnetic field; control technique; degrees of freedom; field-oriented vector control; heavy electric vehicles; high torque dynamics; machine torque; magnetizing inductances; multiphase drives; multiphase induction machines; mutual inductance estimation; stator resistance online estimation; unknown parameter estimation; Harmonic analysis; Inductance; Magnetic fields; Rotors; Stator windings; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Optimization of Electrical and Electronic Equipment (OPTIM), 2012 13th International Conference on
  • Conference_Location
    Brasov
  • ISSN
    1842-0133
  • Print_ISBN
    978-1-4673-1650-7
  • Electronic_ISBN
    1842-0133
  • Type

    conf

  • DOI
    10.1109/OPTIM.2012.6231950
  • Filename
    6231950