Zhang, Y.X.; Li, T.Y.; Li, B.; Zhang, J.; Wang, R.J.; Jiang, L.R., and Diao, X.H., 2020. Fault detection method of AC charging pile in coastal cities based on Kalman filtering algorithm. In: Guido Aldana, P.A. and Kantamaneni, K. (eds.), Advances in Water Resources, Coastal Management, and Marine Science Technology. Journal of Coastal Research, Special Issue No. 104, pp. 210–215. Coconut Creek (Florida), ISSN 0749-0208.
Aiming at the problems of AC charging pile fault detection, such as large amount of iterative calculation and low ability of fault classification, it is difficult to adapt to the practical application environment. The fault detection method of AC charging pile in coastal cities based on Kalman filter algorithm is studied. Through data fusion, algorithm fusion and other methods, the information related to the working state of AC charging pile is obtained from many aspects, and then integrated. The advantages of different fault diagnosis algorithms can improve the accuracy of fault diagnosis results; the fault tree analysis algorithm is introduced into Kalman filter algorithm to improve the modeling accuracy and efficiency of AC charging pile nonlinear model, and the relationship coefficient between the performance vector variation of the whole AC charging pile and its components is analyzed, so as to solve the problem of different times of the same model and different service life of the same AC charging pile. In order to improve the accuracy of component health parameter estimation results in hardware and software design, the fault detection of AC charging pile in coastal cities is realized. The simulation results show that the final output of the charging system is more scalable and the success rate of fault detection is higher. This method has good practical application effect in coastal cities and has strong applicability.