Electric Vehicle Fire Risk Assessment Based on WBS-RBS and Fuzzy BN Coupling
(1) Background: In recent years, electric vehicle fire accidents have occurred frequently. Studying the risk factors leading to electric vehicle fire can take corresponding safety measures to reduce the occurrence of electric vehicle fire accidents. (2) Methods: The Work Breakdown Structure (WBS) wa...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-10-01
|
| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/10/20/3799 |
| _version_ | 1827649074879266816 |
|---|---|
| author | Jianhong Chen Kai Li Shan Yang |
| author_facet | Jianhong Chen Kai Li Shan Yang |
| author_sort | Jianhong Chen |
| collection | DOAJ |
| description | (1) Background: In recent years, electric vehicle fire accidents have occurred frequently. Studying the risk factors leading to electric vehicle fire can take corresponding safety measures to reduce the occurrence of electric vehicle fire accidents. (2) Methods: The Work Breakdown Structure (WBS) was constructed to decompose the electric vehicle system, the Risk Breakdown Structure (RBS) was constructed to decompose the risk of electric vehicle fire accidents, a WBS-RBS coupling matrix was built to identify the risk factors that lead to electric vehicle fire accidents in the electric vehicle system, and the fuzzy Bayesian network was used to evaluate the risk of electric vehicle fire accidents. (3) Results: In this study, the electric vehicle was divided into four systems, and 15 risk factors leading to electric vehicle fire were found. The first risk factor was external collision ignition, followed by battery failure, artificial modification, battery-pack flooding, and charging equipment failure, and safety measures were proposed; (4) Conclusions: The results show that the WBS-RBS and fuzzy BN coupling research method can identify the risk factors leading to an electric vehicle fire, and the risk factors were ranked, providing a reference for the safety protection of electric vehicles. |
| first_indexed | 2024-03-09T19:51:50Z |
| format | Article |
| id | doaj.art-0d2559602c1642beb8e4294e8444710b |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-09T19:51:50Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-0d2559602c1642beb8e4294e8444710b2023-11-24T01:07:10ZengMDPI AGMathematics2227-73902022-10-011020379910.3390/math10203799Electric Vehicle Fire Risk Assessment Based on WBS-RBS and Fuzzy BN CouplingJianhong Chen0Kai Li1Shan Yang2School of Resources and Safety Engineering, Central South University, Changsha 410083, ChinaSchool of Resources and Safety Engineering, Central South University, Changsha 410083, ChinaSchool of Resources and Safety Engineering, Central South University, Changsha 410083, China(1) Background: In recent years, electric vehicle fire accidents have occurred frequently. Studying the risk factors leading to electric vehicle fire can take corresponding safety measures to reduce the occurrence of electric vehicle fire accidents. (2) Methods: The Work Breakdown Structure (WBS) was constructed to decompose the electric vehicle system, the Risk Breakdown Structure (RBS) was constructed to decompose the risk of electric vehicle fire accidents, a WBS-RBS coupling matrix was built to identify the risk factors that lead to electric vehicle fire accidents in the electric vehicle system, and the fuzzy Bayesian network was used to evaluate the risk of electric vehicle fire accidents. (3) Results: In this study, the electric vehicle was divided into four systems, and 15 risk factors leading to electric vehicle fire were found. The first risk factor was external collision ignition, followed by battery failure, artificial modification, battery-pack flooding, and charging equipment failure, and safety measures were proposed; (4) Conclusions: The results show that the WBS-RBS and fuzzy BN coupling research method can identify the risk factors leading to an electric vehicle fire, and the risk factors were ranked, providing a reference for the safety protection of electric vehicles.https://www.mdpi.com/2227-7390/10/20/3799electric vehiclefireWBS-RBSBNrisk evaluation |
| spellingShingle | Jianhong Chen Kai Li Shan Yang Electric Vehicle Fire Risk Assessment Based on WBS-RBS and Fuzzy BN Coupling Mathematics electric vehicle fire WBS-RBS BN risk evaluation |
| title | Electric Vehicle Fire Risk Assessment Based on WBS-RBS and Fuzzy BN Coupling |
| title_full | Electric Vehicle Fire Risk Assessment Based on WBS-RBS and Fuzzy BN Coupling |
| title_fullStr | Electric Vehicle Fire Risk Assessment Based on WBS-RBS and Fuzzy BN Coupling |
| title_full_unstemmed | Electric Vehicle Fire Risk Assessment Based on WBS-RBS and Fuzzy BN Coupling |
| title_short | Electric Vehicle Fire Risk Assessment Based on WBS-RBS and Fuzzy BN Coupling |
| title_sort | electric vehicle fire risk assessment based on wbs rbs and fuzzy bn coupling |
| topic | electric vehicle fire WBS-RBS BN risk evaluation |
| url | https://www.mdpi.com/2227-7390/10/20/3799 |
| work_keys_str_mv | AT jianhongchen electricvehiclefireriskassessmentbasedonwbsrbsandfuzzybncoupling AT kaili electricvehiclefireriskassessmentbasedonwbsrbsandfuzzybncoupling AT shanyang electricvehiclefireriskassessmentbasedonwbsrbsandfuzzybncoupling |