Optimization of DC-DC Buck Converters Using ABC, GTO, and RIME Algorithms

Enhancing the design of a DC-DC converter is one of the most important topics studied in the field of power electronics given their widespread use of such converters in various applications. The ideal designing of the converter is based on many factors and variables to achieve the least amount of energy losses in the converter. This study focuses on optimizing the design of DC-DC buck converter by optimizing and choosing the optimal inductor value for minimizing the energy losses. For this, we used metaheuristic algorithms like Artificial Bee Colony (ABC), Gorilla Troops Optimizer (GTO) and RIME optimization algorithms to minimize power losses by introducing it as a cost function, which are inherently multiobjective algorithms for refining and finding the value for many variables adapting them to single-variable optimization. However, we applied the (ABC), (GTO) and RIME algorithms for only finding the optimal inductor value for DC-DC buck converter. Simulation and algorithm results demonstrate that the proposed methodology allowed for finding a superior inductor optimization and that is led to reducing energy losses for the studied converter.