Tracking and managing real world electric vehicle power usage and supply

In this paper the tracking and analytical infrastructure necessary to adequately manage the power demands of a fleet of electric vehicles is considered. The data from a 230 day trial of 15 vehicles has been used to simulate a single day with over 3000 vehicles on the road within the North East of England. Current analytical approaches are considered and possible future avenues are addressed. A general model for predicting the probability of vehicle charging is proposed. The comparative charging rates between morning and evening and the spatial distribution of the charging are all considered. It is found that although the evening charging has the greater number of charging events across the region it is the morning charges which pose the most risk for local power management as the morning charges tend to be concentrated within a smaller spatial extent. In more general terms the use of individual vehicle tracking systems is found to be an ideal system for determining the current and future state of power consumption for electric vehicles.