Fault Feature Recognition of Electric Vehicle Charging Infrastructure

With the rapid development of electric vehicles, vehicle charging infrastructure, an essential device for fast charging process, plays an important role in connecting vehicles to charge supply. Due to short time of application, it takes time and effort to diagnose faults and repair devices, so it is necessary to build a whole theory and do technical research in this area. More importantly, it is required to establish a fault diagnosis knowledge base and set up an expert system to improve diagnose efficiency. To this end, the expert system could assist maintenance personnel to recognize the fault feature quickly and accurately. Further, this paper proposes a fault-tree based analysis method, which contains the build process, qualitative analysis and quantitative analysis. Then we apply the aforementioned results into the expert system which is specifically realized via ACCESS database. Simulation results show that the proposed system meets the functional requirements of direct current (DC) charging infrastructure fault diagnosis. Future work will focus on fault prediction by monitoring operating status and obtaining performance evaluation based on sensors.