Novel Multiobjective Optimization of MF Transformers for Soft-Switching Converters using a Genetic Algorithm

This paper presents a novel computer-aided multiobjective optimal design for medium-frequency (MF) transformers using NSGA genetic algorithm. The proposed methodology has the aim of reaching the best MF transformer for a given power converter topology, by optimizing transformer efficiency, weight, and also, transformer leakage and magnetizing inductances at the same time. Moreover, this work provides some practices for a correct formulation of complex power-electronic design problems and the selection of the optimization algorithm. The proposed methodology and the optimal solutions are validated with the design and the development of two different 10 kVA/500V transformers and some experimental measurements are presented.