Ultra-fast model of the switched reluctance motor

  • T. J.E. Miller
  • , M. Glinka
  • , M. McGilp
  • , C. Cossar
  • , G. Gallegos-Lopez
  • , D. Ionel
  • , M. Olaru

Research output: Contribution to journalConference articlepeer-review

40 Scopus citations

Abstract

This paper describes a magnetic/electric circuit model of the switched reluctance motor that is especially well adapted for rapid computation or simulation. The model is based on a set of normalized `gage curves' of flux-linkage versus rotor position at constant current, which are used for the interpolation required to recover instantaneous current from the known rotor position and flux-linkage during a dynamic simulation. The particular structure of the gage curves is key not only to the speed of calculation, but also to their ability to represent all the main nonlinearities arising from the variable geometry, the variable saturation of overlapping pole corners, and the variable bulk saturation of poles and yokes. In addition, they have sufficient differentiability to ensure that there are no discontinuities in the computed instantaneous torque or its rate of change. For high accuracy the gage curve model needs to be calibrated and it is shown how this is done with great economy of effort by a very fast finite-element procedure developed specially for the purpose. The variable coefficients of the gage-curve model are related to identifiable physical phenomena in the machine in a strongly intuitive way, and it is shown that the accuracy of the finite-element calculations combined with the speed and intuitive clarity of the gage-curve model results in a set of analytical tools that surpasses what has been available before.

Original languageEnglish
Pages (from-to)319-326
Number of pages8
JournalConference Record - IAS Annual Meeting (IEEE Industry Applications Society)
Volume1
StatePublished - 1998
EventProceedings of the 1998 IEEE Industry Applications Conference. Part 1 (of 3) - St.Louis, MO, USA
Duration: Oct 12 1998Oct 15 1998

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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