An Improved Position Sensor Fault Detection and Algorithm Transition Using Adaptive Threshold for Sensorless Control of IPMSM

Dongwoo Lee, Kan Akatsu

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

Abstract

This paper proposes an improved position sensor fault detection based on back-electromotive force (back-EMF) estimation in an interior permanent magnet synchronous motor (IPMSM). The threshold value in order to detect the position sensor fault of rotor is one of the most important things in IPMSM drive system. This threshold value should be designed by a higher value than the maximum overshoot of estimated angle error caused by acceleration or deceleration of motor as well as steady state error. In this paper, the fast fault detection method using adaptive threshold design is determined and proposed method is verified in transient state such as acceleration and deceleration by simulation and experimental results.

Original languageEnglish
Title of host publicationProceedings
Subtitle of host publicationIECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society
PublisherIEEE Computer Society
Pages910-915
Number of pages6
ISBN (Electronic)9781728148786
DOIs
Publication statusPublished - 2019 Oct
Event45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019 - Lisbon, Portugal
Duration: 2019 Oct 142019 Oct 17

Publication series

NameIECON Proceedings (Industrial Electronics Conference)
Volume2019-October

Conference

Conference45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019
CountryPortugal
CityLisbon
Period19/10/1419/10/17

Keywords

  • adaptive threshold
  • extended-EMF
  • interior permanent magnet synchronous motor
  • sensorless control

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'An Improved Position Sensor Fault Detection and Algorithm Transition Using Adaptive Threshold for Sensorless Control of IPMSM'. Together they form a unique fingerprint.

Cite this