TY  - JOUR
PY  - 2022//
TI  - Analysis on electric vehicle accidents based on data mining and site investigation
JO  - China safety science journal (CSSJ)
A1  - Liang, X.
A1  - Xiao, L.
A1  - Wang, P.
A1  - Dong, H.
A1  - Qu, X.
A1  - Liu, C.
SP  - 180
EP  - 187
VL  - 32
IS  - 1
N2  - In order to study the causes of electric vehicles' spontaneous combustion accidents due to batteries' thermal runaway, and to reduce such accidents, new energy vehicle fire accidents in 2020 was summarized. Then, based on the failure mechanism of power batteries and vehicle operating data, a multidimensional accident analysis method was put forward, which integrated safety parameter correlation analysis of accident stages, site investigation and full life cycle cell variation analysis. Finally, this method was employed to analyze an electric vehicle spontaneous combustion accident. The results show that the proposed method can identify evolution process from failure to accident, and therefore trace the cause of accidents by exploring damage of accident vehicle and change characteristics of operating data. © 2022, Editorial Department of China Safety Science Journal. All rights reserved.<p /> <p>Language: zh</p>
LA  - zh
SN  - 1003-3033
UR  - http://dx.doi.org/10.16265/j.cnki.issn1003-3033.2022.01.024
ID  - ref1
ER  -