A Novel DC-DC Converter Design for Electric Vehicles Based on PID Control Optimized by a Hybrid Grey Wolf-Cuckoo Search Algorithm

Electric Vehicles (EVs) have emerged as a key solution for sustainable transportation, particularly with advancements in smart and fast energy storage systems. A critical component of these systems is the rechargeable lithiumion battery, which requires efficient charging to ensure optimal performance and longevity. In this context, this paper proposes an enhanced charging system based on a hybrid PID-controlled DC-DC converter optimized using the Grey Wolf Optimizer (GWO) and Cuckoo Search (CS) algorithms. The optimized PID controller improves converter performance by minimizing overshoot, reducing response time, and enhancing system stability, ultimately leading to increased inverter efficiency and extended battery life. The feasibility of the proposed system is validated through MATLAB/Simulink simulations, demonstrating significant improvements in efficiency and safety over conventional PID controllers. Simulation results indicate that the GWOCS-optimized PID controller effectively reduces power loss, thermal stress, and voltage overshoot, thereby enhancing the reliability and lifespan of both the converter and the battery. Additionally, the hybrid controller reduces total harmonic distortion (THD) from 162 (with conventional PID control) to 112, significantly improving power quality. This approach presents a promising step toward the development of a cost-effective and environmentally friendly EV charging infrastructure.