Uncovering the charging behaviors and preferences of electric taxis: A case study of Shenzhen

Abstract

The rapid development of electric vehicle (EV) has driven the electrification of taxis in several major cities, which also brings a challenge to the charging infrastructure planning. Understanding the drivers’ charging behavior is crucial for optimizing infrastructure planning and improving charging efficiency. In this paper, we analyze the charging behavior characteristics of a fully electrified taxi fleet in Shenzhen, China, based on taxi GPS data and public station data. Specifically, we classify stations into commercial stations dedicated to taxi services and public stations available for all vehicles. By leveraging the trajectory and the station data, we identify charging activities and estimate the real charged energy, thereby constructing the state-of-charge (SOC) trajectories. Our results reveal that charging at commercial stations and at public stations exhibits different spatiotemporal characteristics. Although partial charging occurs at both types of stations, it is more often observed at public stations. Besides, taxis operate with battery levels above 50% for most of the time. We further classify charging stations based on their nearby POI and uncover several classes of charging stations that are more appealing to drivers. These findings provide valuable insights into charging infrastructure planning aiming at efficient utilization of charging resources.