Fault Tree Analysis Method of Electric Vehicle Charging Based on Binary Decision Diagram

Electric vehicle (EV) charging safety risk factors are numerous and complex, and using fault trees can explore the key possible causes of EV charging faults. However, the traditional fault tree analysis method to solve the minimum cut set is quite complicated and lengthy. Based on the binary decision diagram (BDD), the fault tree can be solved across the cut set, and the minimum cut set can be obtained directly by traversing the BDD, which can achieve fast analysis of faults. However, the sorting of the basic events seriously affects the structure of the BDD and directly impacts the spatial and temporal complexity of the BDD. In this paper, the appropriate sorting rule for EV charging risk analysis is proposed and combined with the if-then-else algorithm to convert the fault tree into an optimal structure of BDD, which can quickly complete the analysis of the EV charging fault tree. The results show that the method proposed in this paper can reduce the number of nodes of the BDD.