Performance Investigation of Electric Vehicle Charging Network Using FES and SOS Service Mechanism

The article presents an advanced queueing framework for electric vehicle (EV) charging infrastructures that integrate second-optional services (SOS), such as cleaning and maintenance, with first-essential services (FES), namely battery charging and battery swapping. Through the process of employing the matrix method and Chapman-Kolmogorov differential-difference equations, the investigation establishes a thorough statistical framework to address the increasing complexity of the EV charging network. Several measures, such as expected system and queue length, anticipated waiting times, and overall system throughput, are envisaged for evaluating system performance. The model includes critical operational characteristics, including arrival rates, service completion times, and the likelihood of individuals acquiring optional services following the completion of essential services. Through computational analysis, we demonstrate the significant impact of system design parameters on system performance and resource utilization. The outcomes indicate that overall system performance can be significantly improved by controlling the proportion between essential and optional services and optimizing service procedures.