Exploring Charging Infrastructure and Charging Patterns in Real Urban Environments

With the widespread adoption of electric vehicles (EVs) as a sustainable transportation solution, there is an increasing demand for efficient charging infrastructure. To address the existing charging infrastructure, this study ethically collected real driving data from registered EVs in Hefei, solely relying on vehicle-side data. The study explored the positions and quantities of charging stations and charging piles, with a particular focus on fast charging stations (FCSs). The proposed solutions were partially validated using actual data. Moreover, we divided a week into five time periods and employed Geographic Information Systems (GIS) and a grid-based approach to analyze the temporal variations in charging demand within the Hefei region, providing insights for the power grid. Finally, a comprehensive analysis of the charging behavior of 1000 electric vehicles was conducted, including the proportion of fast charging versus slow charging and usage patterns. This research enhances the understanding of electric vehicle charging behavior and contributes to the planning of sustainable and intelligent charging station networks within future intelligent transportation systems.