Reliability evaluation of switched reluctance motor drive system in electric vehicle based on Bayesian network

Hao Chen, Feng Dong, Shuai Xu, Jian Yang, C. C. Chan

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

1 Citation (Scopus)

Abstract

The reliability evaluation on switched reluctance motor (SRM) system can effectively reveal the weaken links and then develop the powerful strategies to extend the lifetime of electric vehicles. This paper introduces the Bayesian Network to quantitatively evaluate the reliability of SRM system. First, the modeling process and corresponding solving principle are clearly illustrated. Next, according to the evaluation results, the Bayesian Network owns superior performance than commonly used reliability block diagram and fault tree models. Finally, the simulation and experimental results validate the reliability analysis results with Bayesian Network.

Original languageEnglish
Title of host publication2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728112497
DOIs
Publication statusPublished - Oct 2019
Externally publishedYes
Event2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Hanoi, Viet Nam
Duration: 14 Oct 201917 Oct 2019

Publication series

Name2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings

Conference

Conference2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019
Country/TerritoryViet Nam
CityHanoi
Period14/10/1917/10/19

Keywords

  • Bayesian Network
  • Reliability evaluation
  • SRM

ASJC Scopus subject areas

  • Control and Optimization
  • Modelling and Simulation
  • Artificial Intelligence
  • Transportation
  • Energy Engineering and Power Technology
  • Fuel Technology
  • Automotive Engineering
  • Electrical and Electronic Engineering

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