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

doi:10.1109/VPPC46532.2019.8952523

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 proceeding › Conference article published in proceeding or book › Academic research › peer-review

3 Citations (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 language	English
Title of host publication	2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728112497
DOIs	https://doi.org/10.1109/VPPC46532.2019.8952523
Publication status	Published - Oct 2019
Externally published	Yes
Event	2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Hanoi, Viet Nam Duration: 14 Oct 2019 → 17 Oct 2019

Publication series

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

Conference

Conference	2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019
Country/Territory	Viet Nam
City	Hanoi
Period	14/10/19 → 17/10/19

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

More information

10.1109/VPPC46532.2019.8952523

Cite this

Chen, H., Dong, F., Xu, S., Yang, J., & Chan, C. C. (2019). Reliability evaluation of switched reluctance motor drive system in electric vehicle based on Bayesian network. In 2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings Article 8952523 (2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VPPC46532.2019.8952523

Chen, Hao ; Dong, Feng ; Xu, Shuai et al. / Reliability evaluation of switched reluctance motor drive system in electric vehicle based on Bayesian network. 2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings).

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title = "Reliability evaluation of switched reluctance motor drive system in electric vehicle based on Bayesian network",

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.",

keywords = "Bayesian Network, Reliability evaluation, SRM",

author = "Hao Chen and Feng Dong and Shuai Xu and Jian Yang and Chan, {C. C.}",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 ; Conference date: 14-10-2019 Through 17-10-2019",

year = "2019",

month = oct,

doi = "10.1109/VPPC46532.2019.8952523",

language = "English",

series = "2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Chen, H, Dong, F, Xu, S, Yang, J & Chan, CC 2019, Reliability evaluation of switched reluctance motor drive system in electric vehicle based on Bayesian network. in 2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings., 8952523, 2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019, Hanoi, Viet Nam, 14/10/19. https://doi.org/10.1109/VPPC46532.2019.8952523

Reliability evaluation of switched reluctance motor drive system in electric vehicle based on Bayesian network. / Chen, Hao; Dong, Feng; Xu, Shuai et al.
2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. 8952523 (2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

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AU - Chen, Hao

AU - Dong, Feng

AU - Xu, Shuai

AU - Yang, Jian

AU - Chan, C. C.

PY - 2019/10

Y1 - 2019/10

N2 - 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.

AB - 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.

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KW - Reliability evaluation

KW - SRM

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U2 - 10.1109/VPPC46532.2019.8952523

DO - 10.1109/VPPC46532.2019.8952523

M3 - Conference article published in proceeding or book

AN - SCOPUS:85078727551

T3 - 2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings

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

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019

Y2 - 14 October 2019 through 17 October 2019

ER -

Chen H, Dong F, Xu S, Yang J, Chan CC. Reliability evaluation of switched reluctance motor drive system in electric vehicle based on Bayesian network. In 2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. 8952523. (2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings). doi: 10.1109/VPPC46532.2019.8952523

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

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

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