Electric vehicle (EV) charging infrastructure is present all over the United States, but charging prices vary greatly, both in amount and in the methods by which they are assessed. For this paper, we interpret and analyze charging price information from PlugShare, a crowd-sourced EV charging data platform. Because prices in these data exist in a semi-structured textual format, an ad hoc text mining approach is used to extract quantitative price information. Descriptive analytics of the processed dataset demonstrate how the prices of EV charging vary with charging level (Direct Current Fast Charging versus Level 2), geographic location, network provider, and location type. Our research indicates that a great deal of diversity and flexibility exists in structuring the prices of EV charging to enable incentives for shaping charging behaviors, but that it has yet to be widely standardized or utilized. Comparisons with estimates of the levelized cost of EV charging illustrate some of the challenges associated with operating and using these stations.

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The Plug-In Hybrid Medium-Duty Truck Demonstration and Evaluation Program was sponsored by the United States Department of Energy (DOE) using American Recovery and Reinvestment Act of 2009 (ARRA) funding as well as the South Coast Air Quality Management District (AQMD). The purpose of the program was to develop a path to mitigate plug-in hybrid vehicle technology to medium-duty vehicles by demonstrating and evaluating in diverse applications. The program allows the fleets to develop interest in the technology. The 62 participants have deployed these vehicles into the field with their operators to achieve real-life experience with the vehicles in 23 different states. A total of 296 vehicles were delivered to the field prior to July 2015. This paper provides the results from the analysis of the data generated by these vehicles.