Multi-objective optimization of power converters using genetic algorithms

Abstract

In this paper an application of the multi-objective genetic algorithm NSGA-II to synthesize a power electronic converter is described. The formal approach and the routines for synthesis are developed. As an example, a flyback converter is synthesized for minimum diode and transistor losses. The results are compared with brute-force simulation and show an exact match, but with 2.5 less simulation time. The bottlenecks of the optimization process are explored and acceleration techniques are introduced