Enhancing Efficiency in Bidirectional DC-DC Converters through PSO-Based Optimization

Efficiency is paramount in the design of a DC-DC converter, mainly in electric vehicle applications. This study focuses on minimizing power losses in bidirectional DC-DC converters, which is crucial for optimizing efficiency. The Particle Swarm Optimization (PSO) method minimizes losses under thermal, electrical, and magnetic constraints. Simulation results demonstrate a significant reduction in power losses to 16.84 watts, achieving an impressive efficiency of 93.05. The success of the PSO optimization algorithm in enhancing power converter efficiency is affirmed, making it a suitable choice for such applications. Additionally, the study delves into the integral integration of renewable energy sources and energy storage, emphasizing the pivotal role of bidirectional DC-DC converters in managing fluctuations. It explores the Dual Active Bridge (DAB) converter, offering insights into its structure, characteristics, and applications. The paper introduces a novel contribution using the PSO method for bidirectional DC-DC converter optimization, considering various constraints. The comprehensive exploration covers the bidirectional DC-DC converter structure, losses in each component, formulation of the optimization problem, and the PSO optimization process. The study concludes by summarizing contributions, highlighting the significance of PSO in enhancing bidirectional DC-DC converter performance, and suggesting future research avenues. This work provides a valuable foundation for further exploration in the field.