The global proliferation of electric vehicles (EVs) has brought forth new challenges in electric vehicle (EV) charging infrastructure. This paper utilizes operational data from the 5G real-time system of EV and traffic platforms (5gRTS-ET) in China, encompassing 12,597,109 cases and 32,259 EVs. By employing frequency density analysis, a dynamic charging behavior model is devised to address the limitations of static models in accommodating the diverse roles of EV users. Analysis reveals distinct charging behavior preferences among three urban EV operation modes, paving the way for an adaptive model for integrating charging points into networked operations on the platform.

The current global utilization rate of electric vehicle (EV) charging stations ranges from approximately 20% to 40%. Despite numerous studies focusing on enhancing this utilization through single-variable approaches—such as optimizing charging point (CP) locations, analyzing charging behaviors, and adjusting pricing—low utilization rates persist. This paper examines the business model for EVs and charging stations integrated into the 5G Real-Time System for EVs and Transportation (5gRTS-ET) platform, which was operational in China in 2021. It establishes three distinct business models for EV users: the Government Subsidy Model, the Self-Operating Model without Government Subsidies, and the 5gRTS-ET Operating Model. Utilizing an integrated service modeling approach, the study constructs a dynamic business model for charging stations. Findings indicate that incorporating variables related to EV user roles significantly enhances the utilization rates of charging stations. Furthermore, onboarding EV CPs onto the 5gRTS-ET platform emerges as an effective strategy for ensuring their sustainable operation. This research offers a sustainable business model for EV charging stations in light of the evolving roles of EV users and serves as a reference for applying integrated business modeling methods in practical operational platforms.