Electric vehicle user charging mode selection method combining individual heterogeneity and bounded rationality behavior modeling

Abstract

The invention relates to an electric vehicle user charging mode selection method combining individual heterogeneity and bounded rationality behavior modeling, and belongs to the field of electric vehicles. The method comprises the steps that the current battery charge state of an electric vehicle is detected, and when the current battery charge state is lower than a threshold value, it is judged that the electric vehicle needs to be charged; obtaining a personal social economic characteristic variable, a personal travel characteristic variable and a charging characteristic variable of an electric vehicle user, and constructing a charging mode set in the service area; in the charging mode selection of the electric vehicle users, a hybrid Logit model is adopted to carry out modeling on charging prices and waiting time, and individual heterogeneity of the charging prices and the waiting time on different electric vehicle users in charging mode selection is captured; and setting a threshold-greedy finite rationality decision-making mechanism, and correcting the random selection behavior of the electric vehicle user when the selection probabilities of the plurality of charging modes are similar. According to the method, the highway scene charging demand prediction precision can be improved, the facility layout is optimized, and the prediction is closer to the real electric vehicle user behavior.

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