Spatiotemporal Distribution of Electric Vehicle State of Charge Based on Travel Chains and Gravity Model

The rapid increase in electric vehicle usage has turned the establishment of charging stations into a pressing issue. Accurately estimating the demand load for these vehicles is vital for determining optimal station locations and their capacities. Load estimation is important both for research and practical purposes, especially for advancing sustainable practices in electric vehicles. This study utilizes travel chain concepts and a gravity model to investigate how the state of charge (SOC) of electric vehicles is distributed over time and space. By scrutinizing the travel patterns of private EVs in the road network, we can forecast the demand on the network. Furthermore, the gravity model is applied to enhance the process of selecting charging station sites, indicating their appeal to potential users.