Firefly Algorithm-based Optimization of Control Parameters in DC Conversion Systems - Le, Thanh-Lam (Engineering, Technology & Applied Science Research, 2025)
Sustainable energy and electric vehicles require DC-DC converters in renewable energy systems, EV charging, and smart grids. In this context, buck converters are crucial, providing efficient voltage regulation and reliable performance in these advanced energy systems. While Proportional-Integral (PI) controllers are widely adopted for their simplicity and dependability, they often rely on manual parameter tuning, limiting their adaptability and responsiveness. To address this limitation, this research introduces a digital control strategy that optimizes the PI parameters using the Firefly Algorithm (FA). This optimization significantly enhances the stability and reduces the oscillations in the DC-DC buck converter. A MATLAB/Simulink simulation model is utilized to validate the proposed approach, and the results demonstrate that the FA-optimized control parameters substantially improve the converter's performance, making it highly suitable for high-demand applications in advanced energy systems.