Closed-Loop Control for Autonomous EV Charging Infrastructure

Abstract

Closed-Loop Control Architectures for Autonomous EV Charging Infrastructure Abstract Autonomous EV charging infrastructure is increasingly functioning as a feedback-controlled cyber-physical system in which charger state, queue condition, and power demand must be measured and corrected continuously. Existing studies have examined charging behavior, adaptive charging strategies, model predictive control, coordinated charging, and data-driven decision making, showing that intelligent regulation is becoming central to EV charging systems. However, much of the literature still emphasizes optimization more than the full closed-loop architecture linking sensing, control error, autonomous adjustment, and disturbance rejection. To address this issue, this article presents a closed-loop control architecture for autonomous EV charging infrastructure based on continuous state sensing, feedback-error evaluation, predictive support, autonomous actuation, and disturbance-rejection logic. The results show improved setpoint tracking, lower regulation error, stronger disturbance rejection, and better charging stability than open-loop and weak-feedback strategies. Overall, the study demonstrates that closed-loop feedback regulation provides a practical foundation for autonomous EV charging infrastructure.