On-line torque estimation in a switched reluctance motor for torque ripple minimisation

Zhengyu Lin, Donald Shewan Reay, Barry Wayne Williams, Xiang Ning He

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

This paper considers torque ripple minimisation control for switched reluctance motors (SRMs) and presents a novel on-line approach to the estimation of instantaneous torque. An adaptive B-spline neural network is used to learn the nonlinear flux linkage and torque characteristics of an SRM. The training of the B-spline neural network is accomplished on-line in real-time. anid the system does not require a priori know-ledge of the SRM"s electromagnetic characteristics. The potential of the torque estimation method is demonstrated in simulation and experimentallx using a 550W 8/6 four-phase SRM operating in saturation, and it has been applied successfully to torque ripple minimisation. © 2004 IEEE.

Original languageEnglish
Title of host publication2004 IEEE International Symposium on Industrial Electronics
Pages981-985
Number of pages5
Volume2
DOIs
Publication statusPublished - 2004
Event2004 IEEE International Symposium on Industrial Electronics -
Duration: 4 May 20047 May 2004

Conference

Conference2004 IEEE International Symposium on Industrial Electronics
Abbreviated titleIEEE-ISlE
Period4/05/047/05/04

Keywords

  • Modeling
  • SRM
  • Torque estimation

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    Lin, Z., Reay, D. S., Williams, B. W., & He, X. N. (2004). On-line torque estimation in a switched reluctance motor for torque ripple minimisation. In 2004 IEEE International Symposium on Industrial Electronics (Vol. 2, pp. 981-985) https://doi.org/10.1109/ISIE.2004.1571947