Abstract:For the safe and stable operation of electric vehicle DC charging piles, this paper proposes a charging pile fault prediction algorithm based on improved support vector machine. The algorithm first performs preprocessing such as missing value filling and normalization in the operating parameters of the charging pile; then the preprocessed data is input into the support vector machine model for training, and then the firefly algorithm is introduced for improving the sparrow algorithm to search for the parameters for the support vector machine model. The optimal model is obtained; finally, the obtained optimal model is using to predict and diagnose the operation state for the charging pile to do judge whether the charging pile is faulty. The experimental results show that the prediction accuracy of the prediction algorithm in this paper could reach 94.68%, which is much higher than 72.34% of the traditional support vector machine model.

Abstract:Aiming at the problem of fuzzy load model of plug-in electric vehicle charging pile load increasing gradually in power grid, a data fuzzification process based on linear re projection algorithm is designed. Multi column deep convolution fuzzy neural network is used to analyze the data, and the inverse function of linear re projection algorithm is used to solve the data fuzzification. Finally, the input data in 24 h time sequence is used to push forward 24 h for high precision Degree prediction and estimation. The results show that the model effectively improves the management efficiency of electric vehicle charging grid, and is suitable for load management of plug-in vehicle charging pile.

Abstract:In order to calibrate DC power metering modules in the electric vehicle charging pile in the field, developed a field detection device based on source and meter integration design. In the device, the power source module and the standard power metering module shared a set of transducer. In the device, voltage was measured by precise resistance voltage divider, current was measured by zero flux current transformer. In the zero flux current transformer, measuring sensitive parameter for feedback regulation was second harmonic component, which was extracted by secondorder filter and 2 stage amplifier. Designed a distributed synchronous traceability scheme. Evaluated uncertainty of calibration result. The results of calibration and evaluation indicate that the measurement accuracy is most high in the typical charging condition, and satisfy demand in the other charging condition.