A Planning Method for Fast Charging Stations Based on the Deduction of Dynamic Traffic Flow

Nowadays, the substantial growth of charging demand has raised higher requirements for the infrastructure construction of highway fast-charging stations (FCSs). The flow of electric vehicles (EVs) in FCSs is always affected by the joint influence of the traffic flow on the road network and the results of users’ charging decisions, and to portray this characteristic, a highway fast charging station planning method based on the dynamic deduction of traffic flow is proposed. Firstly, the vehicle travel path is determined by allocating the traffic flow. Secondly, a charging decision-making model based on a fuzzy inference system is established to complete the in-station dynamic traffic flow deduction by simulating the users’ decision-making behavior of traveling to the FCS during their trip, considering the time-varying waiting time and the uncertainty of the users’ decision-making results. Finally, a multi-objective planning model that takes into account the investment of FCSs and the waiting time cost of users is established, and the NSGA-II algorithm is used to determine the number of charging piles in FCSs.