Grey wolf optimizer for the design optimization of a DC-DC boost converter

Abstract

Design optimization of a DC-DC boost converters for minimizing overall operational losses is the problem under study. The optimum design contains selecting the best value of circuit inductance, capacitance, and switching frequency for the continuous conduction mode (CCM) operation. The design constraints selected are the current ripple content, ripple content of voltage, and bandwidth for operation in CCM. Grey wolf optimizer (GWO) algorithm is implemented for the boost DC-DC converter’s optimal design. The comparative investigation of algorithms reveals that GWO outperforms other established optimization algorithms like the particle swarm optimization (PSO), moth flame optimization (MFO) algorithm, simulated annealing (SA) and firefly algorithm (FFA) in terms of convergence time, computational effort, and the minimized system losses while finding the most efficient design of the converter. Parametric study on statistical performance indicates that the GWO algorithm outperforms the rest of the optimization algorithms on comparing with previously reported results. The optimized results obtained in the current work provides and improved converter design with reduction in the power loss in the optimized design of the converter by over 15% from previously reported works.