Key points are not available for this paper at this time.
This paper proposes an electric vehicle (EV) scheduling algorithm with fuzzy logic control in smart charging network in order to improve the charging performance of the network significantly. The fuzzy logic control helps that the EV scheduling algorithm determines the proper pair of charging station (CS) and EV logically. The fuzzy inference system determines a weight value by reflecting the multiple charging requirements such as distance between EV and CS, charging time, and charging speed. The weight value describes an EV charging priority, and is used in the scheduling algorithm. The proposed scheduling algorithm focuses on avoiding EV congestion at the CS by reducing the waiting time for charging and balancing charging request rate, which shows how the EV is distributed to the CS with balancing the number of available charging pads. In order to compare the performance of the proposed scheduling algorithm with that of conventional algorithms, the random and max weight scheduling algorithm are also considered. The simulation results show that the proposed scheduling algorithm can improve the performance of the smart charging network in view of waiting time for charging and balancing of charging request rate.
Park et al. (Tue,) studied this question.