Strategic network design and analysis for in-motion wireless charging of electric vehicles

We address a network design problem arising in the deployment of wireless charging stations (WCSs) within an urban transportation network. It is widely acknowledged that, despite the availability of EV conventional charging facilities, the relatively short driving range of EVs (due to low energy density of the batteries) and the long battery charging times (collectively leading to a phenomenon known as range anxiety) remain the major factors that hamper EV adoption. Thus, in this research, we study a cost-effective WCS deployment network design that facilitates EV adoption by alleviating these two major anti-adoption factors. We consider the problem from the perspective of a city as the decision maker whose aim is to satisfy the charging demands of all EVs in its urban traffic network at the minimum cost including installation and charging costs. For this purpose, we suggest a new mathematical model to strategically deploy WCSs in the network in such a way that no EV runs out of energy before reaching its destination. To solve the proposed model, we devise a combined combinatorial classical Benders Decomposition approach and further enhance its efficiency via employing surrogate constraints and an upper bound heuristic. We present computational results illustrating the algorithmic efficiency of our approach as well as an analysis of the effect of varying system and new technology related parameters (i.e., product design) on the resulting network design based on a case study with urban network data from Chicago, IL.

Automated summary

The study focuses on designing a cost-effective wireless charging station deployment network to facilitate EV adoption by addressing range anxiety and long charging times issues. By proposing a new mathematical model and algorithm, it aims to satisfy the charging demands of all EVs in urban traffic networks and provides an analysis on the impact of various parameters on network design.