Research on a Charging Pile Fault Prediction Method Based on Improved C4.5 Algorithm

Big data mining technology is used to predict the faults of EV charging piles, which can effectively solve the current problem of difficult maintenance and management of charging piles. In this paper, the fault prediction of charging pile is carried out by constructing C4.5 decision tree model. On the basis of the original calculation formula of C4.5 algorithm, the calculation formula of information gain rate is regenerated by simplifying the calculation formula and introducing the balance coefficient
$\lambda$
. Compared with the random forest algorithm and the original C4.5 algorithm, the advantages of the new algorithm in improving the prediction accuracy and reducing the model construction time are proved through daily monitoring data training and decision tree verification of a brand charging pile.