Planning Ahead for EV: Total Travel Time Optimization for Electric Vehicles

Abstract

Travelling long distances with electric vehicles is becoming more viable today. Nevertheless, recharging is still necessary on long trips. As of now, the charging infrastructure is not yet ubiquitous and can be very heterogeneous in terms of charging power. Thus, appropriate route planning is needed, which is still an open research problem. We present an approach to optimize the total travel time for electric vehicles by selecting charging stations and routes, respectively, between origin and destinaton and the charging stations. We also take the possibility into account that driving below the speed limit helps to save energy. In particular, we use a multi-criterion shortest-path search to find the best compromise between the fastest and most economic route. In our approach, we use a non-linear charging model that supports CC-CV and CP-CV charging protocols used for lithium-ion batteries. To achieve acceptable speed for the multi-criterion shortest-path search, we combine contraction hierarchies with precomputation of shortest-path trees. By exploiting the fact that most routes are queried between the known locations of the charging stations, we were able to accelerate these queries by about two orders of magnitude. We compare our proposed adaptive charging and routing strategy to other strategies often cited in the literature. Our results clearly show that we are able to achieve a lower total travel time.