Battery electric vehicles (BEVs) are becoming more prevalent as improvements in battery technology and energy management continue to be made. As the number of electric vehicles grows, the demand for fast-charging stations is expected to increase dramatically. Thus, building new charging station infrastructure efficiently will be key to reducing upfront costs while meeting consumer demands. In this work, we propose a method for choosing a set of charging station locations that are optimized based on a set of given common vehicle demand points. As part of this solution, we also offer a novel abstraction of the road network on which energy-efficient paths that account for charge-time delays may be found. The current algorithm chooses the optimal charging locations for a single agent which has a route objective specified using temporal logic. To demonstrate the proposed method, the running example shows how a charging station could be chosen for an electric delivery vehicle. Simulations were run on sample road networks with a given set of demand points to service and potential charging station locations to compare. The method is shown to successfully rank potential charging stations in terms of their expected average charging time cost.
|Original language||English (US)|
|Number of pages||8|
|State||Published - 2020|
|Event||31st IEEE Intelligent Vehicles Symposium, IV 2020 - Virtual, Las Vegas, United States|
Duration: Oct 19 2020 → Nov 13 2020
|Conference||31st IEEE Intelligent Vehicles Symposium, IV 2020|
|City||Virtual, Las Vegas|
|Period||10/19/20 → 11/13/20|
Bibliographical noteFunding Information:
Further investigation was supported by the connected vehicles group from the T. E. Murphy Engine Research Lab at the University of Minnesota, Twin Cities, including Pengyue Wang.
© 2020 IEEE.
- charger placement
- connected vehicles