Electric Vehicle Charging Behavior Modeling and Simulation Based on Energy-Constrained Traffic Equilibrium

Abstract

In cyber-physical energy systems (CPES), electric vehicles (EVs) have emerged as a critical coupling interface between transportation and power distribution networks. Their growing penetration intensifies charging demand, while existing studies often overlook traffic dynamics in charging behavior analysis. This paper therefore develops an improved dynamic user equilibrium (IDUE) model for EV charging behavior analysis. The main contributions of this paper are as follows. First, a traffic equilibrium model for mixed vehicle categories is constructed by comprehensively considering road congestion, charging time cost, and electric vehicle state of charge (SOC) constraints during route selection. This achieves a unified description of traffic flow evolution and energy state changes. Second, an EV feasible path screening model is established, incorporating an energy constrained feasible path search and charging station selection mechanism to enhance the model's representation of real-world charging behavior. Finally, a modified flow-swapping algorithm is proposed to solve the equilibrium model. Through collaborative computation involving dynamic network loading (DNL) and path flow updating, the locations and SOC information of EVs under equilibrium conditions are obtained. The model is validated using Nanjing's transportation network as a case study. Simulation results demonstrate that the proposed method provides decision support for coordinated scheduling of traffic-energy coupled systems and optimization of charging infrastructure.