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The global trend toward a more sustainable future, based on economics and societal behavior, have assisted in making electric vehicles (EV) more attractive to consumers. New technology implemented in EVs continuously improves their range, charging time, and battery capacity. Therefore, the number of EV sales increased significantly within the last few years. In order to handle the demand from the growth in EV sales, the development of a user-orientated distribution of charging stations is needed which requires substantial knowledge about user patterns in charging behavior. Understanding real data from existing charging stations that is analyzed with rigorous statistical methods gives valuable insight for the development of empirical models of charging behavior. In order to initiate this work, a case study approach of public Level-2 charging stations in Rhode Island (RI) were analyzed. Research questions range from how charging stations are being used to which kind of areas influence this behavior and what patterns exist toward calendar dependence. After processing the data, single charging stations were classified into functional areas followed by statistical analysis performed with descriptive statistics, visualizing data, hypothesis testing, clustering, regressive models, and forecasting. Based on the data, there is a strong connection between the total duration of charging events, actual charging time, and the amount of charging events. Not only are chargers utilized differently based on frequency and location, many users use charging stations as parking spots. This pattern exists regardless of charging fees. The charging behavior varies greatly between the different functional areas. Geographical areas seem to have less influence on charging behavior, seemingly more like a mixture of functional areas. Approximately, only about one third of the RI EV drivers are using RI charging stations. There is mainly a decreasing median amount of charges per user, which speaks to either more home charging or larger battery capacity. Areas in which people are working have less charging events on weekends and have a strong peak of charging events in the morning. Areas in which people are spending their free time have the same amount or more charges on weekends and do not have peak times. Timeseries forecasting models found that, both currently and in the near future, there are enough charging stations in RI. However, this does not imply that all the charging stations are in the correct locations, just that the volume of plugs available in RI is sufficient for the current EV charging population. Knowing how people charge their EVs is vital to understanding and implementing a new sustainable transportation infrastructure at a critical time when the monumental paradigm shift has relatively just begun.

Electric Vehicle Charging Behavior in Existing Infrastructures: A Rhode Island Case Study