Abstract:With the development of the electric vehicle industry, the charging demand for electric vehicles is also increasing. To meet the diverse charging demand of electric vehicle users and improve the utilization rate of charging facilities, this paper proposes a mixed integer linear programming model considering three influencing parameters: travel distance, charging price and charging station queuing. It then presents a multi-factor electric vehicle charging path planning method based on the topology of road network to plan the charging path and station selection for users. Firstly, we uses Dijkstra algorithm for charging guidance under the premise of energy consumption constraint, and introduces the concept of information entropy to determine the weight of each parameter for solving the multi-objective optimization. Secondly, to address the variability of users′ charging demand, three planning methods with different objectives are proposed to reduce users′ charging costs. Additionally, this paper constructs a stochastic charging service queue model and conducts sensitivity analysis to investigate the impact of station service capacity on charging cost. Finally, the proposed method is applied to an actual road network for simulation, the results demonstrate that the proposed method can effectively reduce the users′ charging travel cost and reasonably plan the travel path and has certain decision-making significance for charging selection and station configuration.
