Utility Maximization Framework for Opportunistic Wireless Electric Vehicle Charging

236 + Text: 5432 + References: 737 + 4 tables/figures: 1000 = 7405 words Submission date: August 1, 2017 Khan, Chowdhury, Khan, Safro, Ushijima-Mwesigwa ABSTRACT The advancements in Electric Vehicle (EV) wireless charging technology have initiated substantial research on the optimal deployment of Wireless Charging Units (WCU) for dynamic charging or Charging While Driving (CWD) applications. This study presents a novel framework, named as the Simulation-based Utility Maximization of Wireless Charging (SUMWC), which aims to maximize the utility of WCUs for EV charging through the optimal WCU deployment using the concept of opportunistic CWD at signalized intersections. At first, a calibrated traffic micro-simulation network of the area of interest is required for this framework. The calibrated traffic network is used to create the utility function and control delay function for each selected lane at the selected intersections of the road network. The lanes are selected based on their potential to charge EVs. An optimization problem is formulated using the utility and control delay functions, where the objective is to maximize the utility of WCUs, and the decision variables are location and length of WCUs and traffic signal timing. The constraints of the optimization formulation are budget, locations, minimum green signal times and acceptable Level of Service (LOS). A global solution is achieved for this optimization problem using the Genetic Algorithm. The optimized utility is compared with other deployment schemes, such as deployment following betweenness centrality and placement at lane with the highest traffic volume. SUM-WC framework achieves at least 1.5 times more utility per hour than these other deployment schemes.The advancements in Electric Vehicle (EV) wireless charging technology have initiated substantial research on the optimal deployment of Wireless Charging Units (WCU) for dynamic charging or Charging While Driving (CWD) applications. This study presents a novel framework, named as the Simulation-based Utility Maximization of Wireless Charging (SUMWC), which aims to maximize the utility of WCUs for EV charging through the optimal WCU deployment using the concept of opportunistic CWD at signalized intersections. At first, a calibrated traffic micro-simulation network of the area of interest is required for this framework. The calibrated traffic network is used to create the utility function and control delay function for each selected lane at the selected intersections of the road network. The lanes are selected based on their potential to charge EVs. An optimization problem is formulated using the utility and control delay functions, where the objective is to maximize the utility of WCUs, and the decision variables are location and length of WCUs and traffic signal timing. The constraints of the optimization formulation are budget, locations, minimum green signal times and acceptable Level of Service (LOS). A global solution is achieved for this optimization problem using the Genetic Algorithm. The optimized utility is compared with other deployment schemes, such as deployment following betweenness centrality and placement at lane with the highest traffic volume. SUM-WC framework achieves at least 1.5 times more utility per hour than these other deployment schemes.