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There is substantial research interest in how future fleets ofbattery-electric vehicles will interact with the power sector. To this end,various types of energy models depend on meaningful input parameters, inparticular time series of vehicle mobility, driving electricity consumption,grid availability, or grid electricity demand. As the availability of such datais highly limited, we introduce the open-source tool emobpy. Based on mobilitystatistics, physical properties of vehicles, and other customizableassumptions, it derives time series data that can readily be used in a widerange of model applications. For an illustration, we create and characterize200 battery-electric vehicle profiles for Germany. Depending on the hour of theday, a fleet of one million vehicles has a median grid availability between 5and 7 gigawatts, as vehicles are parking most of the time. Four exemplary gridelectricity demand time series illustrate the smoothing effect of balancedcharging strategies.

An open tool for creating battery-electric vehicle time series from empirical data -- emobpy