• DocumentCode
    157205
  • Title

    Model prediction based instantaneous torque control of switched reluctance motor

  • Author

    Goto, Hiromi ; Ichinokura, Osamu

  • Author_Institution
    Dept. of Electr. Enginnering, Tohoku Univ., Sendai, Japan
  • fYear
    2014
  • fDate
    2-5 Sept. 2014
  • Firstpage
    810
  • Lastpage
    815
  • Abstract
    Switched reluctance (SR) motors have many advantages such as simple and solid construction, low-cost on manufacturing, excellent reliability at high temperatures, and large torque density. However, the higher torque ripple from magnetic saliency is a serious problem preventing its applications from being expanded. Several torque control methods have been already proposed. In practical use, a controller must decide gate signals considering some limitations such as inductance, control period, and so on. However SR motor is often operated in magnetic saturation region. So, it is too difficult to consider the limitations. Then, we notice at flux can be easily estimated by integrating the phase voltage. In the paper, a new torque control method based on model prediction to reduce torque ripple is proposed. The proposed method is confirmed through simulations. Then our new method can reduce torque ripple in wide speed range and provides high efficiency drive.
  • Keywords
    machine control; predictive control; reluctance motors; torque control; SR motors; control period; gate signals; inductance; magnetic saliency; magnetic saturation region; model prediction based instantaneous torque control; phase voltage; switched reluctance motors; torque density; torque ripple reduction; Inductance; Logic gates; Reluctance motors; Torque; Torque control; Velocity control; Windings; Electric Vehicle; Model Predictive Control; Switched Reluctance Motor; Torque Control; Torque Ripple;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Machines (ICEM), 2014 International Conference on
  • Conference_Location
    Berlin
  • Type

    conf

  • DOI
    10.1109/ICELMACH.2014.6960274
  • Filename
    6960274