Cost-competitiveness analysis of mobile chargers in an electric vehicle parking and charging system

Abstract

Currently, mobile chargers (MCs) are gaining popularity owing to their flexibility and the potential to solve the widespread issue of chargers being occupied after the charging process has finished, due to delayed departures of electric vehicles (EVs). In this study, we investigate the adoption of MCs in the EV parking and charging system (EVPCS) and demonstrate its cost-competitiveness through comparison with fixed chargers (FCs). First, we propose a modified M/M/n/K queueing model with two-phase services to capture the EVs’ dwell-after-charging behavior. Then we present the steady-state analysis with a matrix analytical method to analyze the properties of the proposed models. To evaluate and compare the performances of these two types of charging facilities, several key measures like blocking probability, average queue length and delay, and chargers’ utilization rate are derived, and extensive experiments exploring diverse scenarios are obtained. Numerical results uncover that: (1) the EVPCS configuration and EVs’ arrival and service rates have distinct impacts on the performance metrics of different types of chargers; (2) the MC may lose its competitiveness if the EV arrival rate is relatively low along with a high charging service rate or when the charger proportion approaches 1 in a small-sized EVPCS; only when the system is overloaded would the MC have a higher level of service than the FC; (3) in terms of cost efficiency, MCs demonstrate better competitiveness than the low-powered FCs considering the equivalent service with higher consumer surplus, while competing with moderately to high-powered FCs, MCs have little superiority; MCs are more profitable to the operator when competing with either low or high-powered FCs, but not for moderately-powered FCs; yet, the MC’s charging powers is required to be at an acceptably moderate level to demonstrate its cost-competitiveness. Furthermore, analytical formulas have been developed to approximate the two-phase queueing model under certain scenarios, and their accuracy has been compared with the customized two-phase queueing model.