Analysis of Potential Crash Hazards of Recalled Battery Electric Vehicles Using Risk Tree and Grey Correlation Theory

During the operation of new energy vehicles (NEVs), accidents such as out of control, collision and fire often occur, and many countries have recalled vehicles with potential risk. The various risk information disclosed in the vehicle recall bulletin truly reveals the current situation and serious harm of the hidden risks of NEVs. At present, the special theoretical research on the crash hazard information of recalled vehicles has not been reported yet. This paper excavates and summarizes the crash hazard information in the 2018–2021 BEV recall Bulletin of the Chinese government, adopts the method of logical deduction, analyzes the basic influencing factors, influence levels and logical causality of crash risk, creates the crash risk tree of BEVs, which reveals the path of risk factors spreading the crash and the characteristics of the crash risk. Referring to the weights of recalled vehicles, the crash risk rate of the risk factor is given, and the structural function of the crash risk tree is established by using Boolean algebra algorithm, and the key importance model of the risk rate is deduced theoretically. Using the grey correlation theory, the crash risk characteristic matrix and the mode vector to be tested are established to explore the grey correlation degree of risk factors. Identify the strength, weight and priority sequence of the impact of each risk factor on the crash, and identify the weakest link of the system, so as to provide a theoretical basis to resolve the crash risk.