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Nonlinear modeling for switched reluctance motor by measuring flux linkage curves

  • Yan Cai*
  • , Qingxin Yang
  • , Lihua Su
  • , Yanbin Wen
  • , Yiming You
  • *Corresponding author for this work
  • Tiangong University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Two kinds of modeling methods are studied based on measuring flux linkage curves for switched reluctance motor (SRM) which the machine geometry is unknowable. A simplified model of SRM is presented for general switched reluctance drive (SRD), which is easy to be built and its accuracy has been improved compared with the quasi-linear model. To get an accurate model, the BP Neural Network (BPNN) nonlinear model of SRM is developed based on Levenberg-Marquardt algorithm by measuring flux linkage characteristics. Compared with measured data of flux linkage and torque, the BPNN model of SRM is proved accurate and meet high performance SRD. Both kinds of the modeling methods are suitable for SRD with different control performance requirement respectively.

Original languageEnglish
Title of host publicationICCET 2010 - 2010 International Conference on Computer Engineering and Technology, Proceedings
PagesV647-V651
DOIs
StatePublished - 2010
Externally publishedYes
Event2010 2nd International Conference on Computer Engineering and Technology, ICCET 2010 - Chengdu, China
Duration: 16 Apr 201018 Apr 2010

Publication series

NameICCET 2010 - 2010 International Conference on Computer Engineering and Technology, Proceedings
Volume6

Conference

Conference2010 2nd International Conference on Computer Engineering and Technology, ICCET 2010
Country/TerritoryChina
CityChengdu
Period16/04/1018/04/10

Keywords

  • BP Neural Network
  • Nonlinear model
  • Simplified model
  • Switched reluctance motor (SRM)

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