Easing range anxiety through user-specific patterns of transportation with simulations (ERUPTS) for electric vehicle transition

Abstract

Many internal combustion engine (ICE) vehicle drivers would consider transitioning to an electric vehicle (EV), but they have not had practical experience driving an EV. Many current ICE and even EV drivers have what has been termed range anxiety, which is the concern that they will run out of charge before reaching a suitable place to recharge their vehicle. We utilize DIMO driving data at macro scale to demonstrate that the vast majority of driving would be satisfied by charging at individual drivers’ primary anchor locations (e.g. a home charging station) and the existing charging infrastructure by simulating EV ownership for current ICE drivers. 15 to 30% of drivers would never need to charge away from home, and 75 to 80% of all driving would be satisfied with only home charging. This simulation utilizes observed driver behavior in order to determine user-specific compatibility with different EV ownership scenarios and presents users with detailed and customized analyses as to how their operation of an EV would require visiting public chargers and charging capacity at their primary anchor. This information can be presented to drivers in order to demonstrate their objective compatibility with an EV as well as predict future needs for the EV charging network and the power grid. We utilize these simulations to discover locations where charging stations may not satisfy the needs of drivers as more ICE drivers transition to EVs. We further utilize current EV driving behavior to discover where the charging network is not meeting drivers’ needs.