2020/09/08 by Duc Minh Nguyen, Nguyen, Duc Minh, Mustafa A. Kishk +3
Engineering · #Advanced Battery Technologies Research #Applications (stat.AP) #Electric Vehicles and Infrastructure #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #Probability (math.PR) #Signal Processing (eess.SP) #Transportation and Mobility Innovations #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2009.03726
openalex publication_date 2020/09/08 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
With the increasing demand for greener and more energy efficient\ntransportation solutions, electric vehicles (EVs) have emerged to be the future\nof transportation across the globe. However, currently, one of the biggest\nbottlenecks of EVs is the battery. Small batteries limit the EVs driving range,\nwhile big batteries are expensive and not environmentally friendly. One\npotential solution to this challenge is the deployment of charging roads, i.e.,\ndynamic wireless charging systems installed under the roads that enable EVs to\nbe charged while driving. In this paper, we use tools from stochastic geometry\nto establish a framework that enables evaluating the performance of charging\nroads deployment in metropolitan cities. We first present the course of actions\nthat a driver should take when driving from a random source to a random\ndestination in order to maximize dynamic charging during the trip. Next, we\nanalyze the distribution of the distance to the nearest charging road. This\ndistribution is vital for studying multiple performance metrics such as the\ntrip efficiency, which we define as the fraction of the total trip spent on\ncharging roads. Next, we derive the probability that a given trip passes\nthrough at least one charging road. The derived probability distributions can\nbe used to assist urban planners and policy makers in designing the deployment\nplans of dynamic wireless charging systems. In addition, they can also be used\nby drivers and automobile manufacturers in choosing the best driving routes\ngiven the road conditions and level of energy of EV battery.\n