Multi-objective Optimization Based Design of High Efficiency DC-DC Switching Converters - Angelo Ambrisi; Massimiliano de Magistris; Raffaele Fresa (International Journal of Power Electronics and Drive Systems (IJPEDS), 2016)
In this paper we explore the feasibility of applying multi objective stochastic optimization algorithms to the optimal design of switching DC-DC converters, in this way allowing the direct determination of the Pareto optimal front of the problem. This approach provides the designer, at affordable computational cost, a complete optimal set of choices, and a more general insight in the objectives and parameters space, as compared to other design procedures. As simple but significant study case we consider a low power DC-DC hybrid control buck converter. Its optimal design is fully analyzed basing on a Matlab public domain implementations for the considered algorithms, the GODLIKE package implementing Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Simulated Annealing (SA). In this way, in a unique optimization environment, three different optimization approaches are easily implemented and compared. Basic assumptions for the Matlab model of the converter are briefly discussed, and the optimal design choice is validated “a-posteriori” with SPICE simulations.