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.

我们解决了在城市交通网络中部署无线充电站（WCS）引起的网络设计问题。众所周知，尽管可以使用电动汽车的常规充电设施，但电动汽车的行驶距离相对较短（由于电池能量密度低）和电池充电时间长（统称为“范围焦虑”现象） ）仍然是阻碍电动汽车普及的主要因素。因此，在这项研究中，我们研究了一种经济有效的WCS部署网络设计，该设计可通过减轻这两个主要的反采用因素来促进电动汽车的采用。

我们以城市作为决策者的角度考虑问题，其目标是以包括安装和充电成本在内的最低成本满足城市交通网络中所有电动汽车的充电需求。为此，我们建议一种新的数学模型，以策略性地在网络中部署WCS，以确保没有EV在到达目的地之前耗尽能量。为了解决该模型，我们设计了组合经典组合的Benders分解方法，并通过使用代理约束和上限启发式算法进一步提高了效率。我们提供的计算结果说明了我们方法的算法效率，以及对变化的系统和新技术相关参数（即