Research on Site Selection Technology of Electric Vehicle Charging Stations in Large Cities Considering User Behavior Patterns

Abstract

This paper conducts an in-depth study on the site selection technology of electric vehicle charging stations in large cities considering user behavior patterns from a professional and technical perspective. Firstly, it expounds the significance of user behavior patterns in
site selection, including their impact on station operation efficiency, spatial coverage accuracy, resource allocation balance, and sustainability.
Then, it analyzes the existing problems in current site selection, such as the mismatch between station distribution and users’ daily activity
areas, failure to match users’ charging time rules, neglect of users’ driving route characteristics, and failure to respond to differences in users’
charging demand intensity, as well as the consequences. Finally, it proposes specific site selection technologies such as user activity hotspot
analysis, charging time prediction model, path trajectory mining, and demand grading response. The research shows that the site selection
technology combined with user behavior patterns can improve the rationality and utilization efficiency of charging station layout, providing
technical support for the sustainable development of urban transportation.