Special Estimation Analysis for the Position of Switched Reluctance Machine using Sinusoidal Inductance Model

Yan Tai Cheng, K. W.E. Cheng

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Fourier modelings of the inductance of switched reluctance machines have been extensively investigated extensively in the past, but the skills are restricted to the construction of the inductance profile model at a known motor position. This paper gives a presentation of a novel sensorless position estimation method based on online sinusoidal modeling of relative inductance for switched reluctance motors at startup. The background of this method is based on sinusoidal fitting and only very few data points are needed. It is numerically efficient and can provide accurate position information for each phase. There is no special requirement on the inductance profile of the machine, and the magnetic characteristics of the machine are not required. The method is simple and easy to implement. Experimental results have confirmed its validity.

Original languageEnglish
Title of host publicationProceedings of the 9th International Conference on Power Electronics Systems and Applications, PESA 2022
EditorsKa-wai Eric Cheng
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665486682
DOIs
Publication statusPublished - Sept 2022
Event9th International Conference on Power Electronics Systems and Applications, PESA 2022 - Hong Kong, Hong Kong
Duration: 20 Sept 202222 Sept 2022

Publication series

NameProceedings of the 9th International Conference on Power Electronics Systems and Applications, PESA 2022

Conference

Conference9th International Conference on Power Electronics Systems and Applications, PESA 2022
Country/TerritoryHong Kong
CityHong Kong
Period20/09/2222/09/22

Keywords

  • Estimation
  • Position Sensorless
  • SR machine
  • Startup
  • Switched Reluctance Motor

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Optimization
  • Energy Engineering and Power Technology

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