• DocumentCode
    159087
  • Title

    Position estimation method for self-sensing electric machines based on the direct measurement of the current slope

  • Author

    Haarnoja, T. ; Halmeaho, Teemu ; Manninen, Antti ; Tammi, Kari

  • Author_Institution
    VTT Tech. Res. Centre of Finland, Espoo, Finland
  • fYear
    2014
  • fDate
    8-10 April 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In self-sensing machines, the rotor displacement or angle is recovered from the wave form of the winding current simplifying thus the structure and lowering the price of the machine. This paper introduces a new technique to enable sensorless operation of a magnetic bearing or other self-sensing Pulse-Width Modulation (PWM)-fed electric machines. The approach is based on the measurement of the rate of change of the winding current at the PWM frequency. The current slope along with the current and voltage measurements is used for estimating the winding inductance, which is a dynamic function of the rotor displacement and angle. The rotor state can then be deduced by matching the estimated inductance to the inductance model. The concept is tested in a setup in which the rotor of a Switched Reluctance Machine is levitated against the gravity using feedback from a displacement sensor. The actual displacement is then compared to the estimate given by the self-sensing algorithm. The estimate is found to be accurate, but sensitive to modeling error.
  • Keywords
    electric current measurement; machine control; magnetic bearings; reluctance machines; rotors; voltage measurement; PWM; current slope measurement; displacement sensor; inductance model; magnetic bearing; position estimation; rotor displacement; self-sensing electric machines; self-sensing pulse-width modulation fed electric machines; switched reluctance machine; voltage measurements; winding inductance;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Power Electronics, Machines and Drives (PEMD 2014), 7th IET International Conference on
  • Conference_Location
    Manchester
  • Electronic_ISBN
    978-1-84919-815-8
  • Type

    conf

  • DOI
    10.1049/cp.2014.0391
  • Filename
    6836880