可追溯性
过程(计算)
电动汽车
预警系统
断层(地质)
汽车工程
工程类
计算机科学
可靠性工程
电信
功率(物理)
物理
量子力学
地震学
地质学
软件工程
操作系统
作者
Anyue Zhang,Hui Gao,Haowei Duan
出处
期刊:Journal of physics
[IOP Publishing]
日期:2021-04-01
卷期号:1848 (1): 012135-012135
被引量:1
标识
DOI:10.1088/1742-6596/1848/1/012135
摘要
Abstract With the large-scale development of electric vehicles, in order to reduce the potential safety hazards in the charging process of electric vehicles, in this paper, through analyzing the characteristics of the faults in the charging process of electric vehicles and the charging and discharging fault location of electric vehicles based on artificial intelligence, a fault location method based on theoretical information fusion is proposed. The fault location method mainly includes three key modules which is fault data acquisition, address label analysis and information reverse traceability. Through the analysis of the hidden dangers of the electric vehicle charging process, the corresponding early warning process is analyzed by the established integrated safety protection model for electric vehicle charging. In this way, the structured design of the early warning system and the construction of the integrated charging and discharging safety early warning process for electric vehicles can effectively improve the charging safety of electric vehicles and promote the healthy development of electric vehicles.
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