An Analysis of Travel Patterns and Charging Behaviors of Battery Energy Vehicles Owners Using Real-World Data

By collecting real-world data of 2,500 battery energy vehicles (BEVs) in Shanghai, China, this paper presents the distributions of summary metrics describing the travel patterns and charging behavior among large-scale electric vehicle owners. It adopts a cluster approach DBSCAN to identify owners with heterogeneous usage of BEVs in terms of six metrics and segments them into three types. It is found that: (1) majority of single travel distance are short and possible range anxiety exits; (2) the majority of BEVs owners spend 2 or 3 h on single charge while part of them spend significantly more time at charging than required, which suggest the waste of charging facilities and resources to some degree; (3) three types of owners can be identified according to their heterogeneous usage of BEVs—that is, ride-hailing drivers, commuters, and other-related drivers; (4) the result would suggest a coupling relationship between travel patterns and charging behaviors—that is, shorter single stay time, more number of stay events, and higher travel distance in peak period correspond to earlier start time of charging and more number of charging events; and (5) the proportion of ride-hailing drivers is 44.07%, which is relatively high among BEVs owners, which can be explained by the new regulations published in Shanghai and the lower marginal cost of BEVs in ride-hailing services.