• DocumentCode
    729413
  • Title

    Position estimation at zero speed for PMSM using probabilistic neural network

  • Author

    Urbanski, Konrad

  • Author_Institution
    Inst. of Control & Inf. Eng., Poznan Univ. of Technol., Poznan, Poland
  • fYear
    2015
  • fDate
    24-26 June 2015
  • Firstpage
    427
  • Lastpage
    432
  • Abstract
    The paper presents a method for estimating the shaft position of a synchronous motor with permanent magnets (PMSM) for the zero and very low speed range. The method is based on the analysis of the high frequency currents, which are induced by the additional test voltage in a stationary coordinate system associated with the stator. Although this method involves the identification of currents hodograph, the method does not need to calculate the current ellipse position. Presented method involves a comparison of obtained shape to the reference pattern using probabilistic neural network (PNN). The method can achieve satisfactory accuracy in a case the high asymmetry of the inductance, as well as in the case of small values of the inductance asymmetry ratio, also in the case of a high level of noise.
  • Keywords
    estimation theory; inductance; neural nets; permanent magnet motors; power engineering computing; probability; shafts; synchronous motors; PMSM; PNN; current ellipse position; current hodograph identification; inductance asymmetry; permanent magnet synchronous motor; probabilistic neural network; shaft position estimation; zero speed; Estimation; Frequency measurement; Inductance; Noise; Rotors; Shafts; Shape; artificial neural network; estimation; permanent magnets synchronous motor; probabilistic neural network; sensorless control; zero speed;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cybernetics (CYBCONF), 2015 IEEE 2nd International Conference on
  • Conference_Location
    Gdynia
  • Print_ISBN
    978-1-4799-8320-9
  • Type

    conf

  • DOI
    10.1109/CYBConf.2015.7175972
  • Filename
    7175972