An Adaptive BOA-Tuned PI Controller for DC-Link Voltage Regulation and Bidirectional Power Flow Control in EV Charging Applications
This paper presents an advanced grid-connected electric vehicle (EV) charging system incorporating bidirectional battery energy storage and an Adaptive Butterfly Optimization Algorithm (ABOA)-tuned PI controller for DClink voltage regulation and bidirectional power-flow control. The proposed architecture consists of a PWM rectifier for AC/DC conversion with near-unity power factor and reduced input current harmonics. A highfrequency inverter and isolation transformer provide compact and efficient isolated power transfer for EV charging applications. The major contribution of this work is the implementation of an Adaptive BOA-tuned PI controller that dynamically optimizes PI gains to maintain stable DC-link voltage under varying load conditions and battery operating states. The adaptive optimization process minimizes voltage error, overshoot, settling time, and ripple, thereby improving transient response and converter performance. MATLAB/Simulink simulation results demonstrate that the proposed controller achieves superior performance compared with conventional PI, PID, FLC, ANN, PSO, GA, SMC, and MPC-based control methods, achieving a settling time of 0.089 s, conversion efficiency of 98.5%, and THD of 0.6%. Hardware implementation using dsPIC30F4011 digital controllers validates the practical feasibility of the proposed system, showing close agreement between simulation and experimental results in terms of DC-link stability, bidirectional energy management, and EV charging performance. Overall, the proposed Adaptive BOA-tuned PI controller provides a computationally efficient and cost-effective solution for next-generation smart EV charging infrastructures with improved dynamic stability, power quality, and energy efficiency.