System model and simulation for optimal parameter design of dynamic wireless charging EVs

In this paper, we provide the numerical analysis of the charging states for the dynamic wireless charging (DWC) electric vehicles (EVs), or simply called DWC-EVs, which charge the their batteries from the power source embedded under the road while the vehicles are in motion. The previous studies suggested the optimal allocation of the wireless power source called power track and economic size of the battery. However, these studies used the assumption that the vehicles are driving with a predetermined speed. This study relaxes the nominal speed assumption and instead assumes that the uncertainty in the vehicle speed. The goal of this study is to understand the how the uncertainty in driving causes the performance of the charging and operation of the vehicles for the DWC-EV based public transportation system. In this study, we used the operation data collected from the KAIST On-line Electric Vehicle (OLEV) currently operating in a Gumi City in South Korea, which is one of the first commercialized DWC-EVs. With the data, energy states are generated from the Markov-based energy consumption simulation model. The simulation results indicate that there is significant risk of running out of battery if the power tracks are allocated and battery size is selected with the nominal speed assumption.