ENHANCING PERFORMANCE AND EFFICIENCY OF DC-DC BOOST CONVERTER USING GOLDEN EAGLE OPTIMIZATION

Despite DC-DC converters are currently extensively utilized within power electronics for their effectiveness in generating a stable DC output with high efficiency, the fact that they are inherently nonlinear makes the selection of advanced converter components and control techniques indispensable for their improvement. In the context of overcoming the performance constraints of DC-DC boost converters, the purpose of the current research work is to use the concept of optimization, which targets the critical parameters of the continuous conduction mode. During the optimization procedure, the objective is to identify the best possible parameters for the inductor, the capacitor, as well as the frequency of switching. In addition to that, the adjustment of the parameters of the Proportional-Integral (PI) controller is carried out to improve the performance characteristics of the DC-DC boost converter circuit. The use of the Golden Eagle Optimization algorithm functions as the basis of the presented optimization approach. The validity of the current technique using the Golden Eagle Optimization algorithm for the design of the DC-DC boost converter circuit is demonstrated through a MATLAB/Simulink simulation. From the results, it can be seen that the proposed design using GEO outperforms various classical optimal techniques such as Grey Wolf Optimizer, Firefly Algorithm, Simulated Annealing, Particle Swarm Optimization, and Moth Flame Optimization. This proposed design using GEO results in a power loss reduction of over 6% and has 10% improvement in output voltage over the latest techniques proposed by Grey Wolf Optimizer. This again manifests the potential of GEO in developing boost converters in terms of power electronics and renewable energy sources