Electric Vehicle Charging Guidance Strategy Based on Markov Decision Model

The charging station malfunction may deny the charging service for the electric vehicles at the station. As a result, the affected owners have two options of leaving or continuing to wait. The owner's leave / stay selection is modeled as a two-state Markov decision model. Then, based on the objective factors such as the state of charge (SOC) and queuing order of electric vehicles, a fuzzy inference algorithm is proposed to solve the state transition matrix of Markov decision model. And then the owner's choice result is obtained. Furthermore, the charging guidance strategy based on Markov decision model and weighted complex network model is designed for owners who choose to leave. Subsequently, the owner's charging satisfaction index is defined to evaluate the charging guidance results. Finally, the feasibility of Markov decision model in describing the charging choice of vehicle owners is verified by simulation experiments, and the superiority of the scheduling strategy is verified by comparative experiments.