Heuristic Methods for EV Charging Scheduling in Fast Charging Stations with Modular Architecture: A Comparative Analysis

The DC ultra-fast charging technology holds significant potential for mitigating range anxiety, a key barrier to the widespread adoption of electric vehicles (EVs). To enhance the efficiency, scalability, and flexibility of the charging infrastructure, several EV supply equipment manufacturers are transitioning to a modular architecture for fast charging stations (FCSs). This design incorporates discrete, independent, low-power DC/DC converter modules alongside multiple charging ports for EV connection and charging. Each charging port can be assigned multiple modules to increase the power delivery capacity, thereby presenting a charging scheduling problem related to module-to-port allocation. Furthermore, incorporation of the non-linear charging power characteristics of EVs, represented by the charge curve, is essential when scheduling the charging power in FCSs. While heuristic charge curve-aware methods such as first-come-first-served (FCFS), uniform policy (UP), and proportional policy (PP) have been proposed for EV charging scheduling in traditional FCSs with continuous power allocation, these methods are not directly applicable to the modular FCS setting where decision making is discrete. In this work, extensions of these heuristic methods are proposed, namely mFCFS, mUP, and mPP, tailored for the modular FCSs. Through various case studies, quality-of-service and charge fairness are evaluated and compared across the considered EV charging scheduling methods using performance metrics based on charging time.