The main challenge of medium-frequency transformers is the high number of design parameters, constraints and objectives, and the difficulty of handling them on a particular design. This paper presents a novel computer-aided optimal design for MF transformers using a multiobjective genetic algorithm, in particular the Non-dominated Sorting Genetic Algorithm II (NSGA-II). 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. The proposed methodology and the optimal solutions are validated with the design and the development of two 10 kVA / 500 V transformers considering two different topologies. Finally, some experimental measurements are presented so as to demonstrate the proposed models and the performance of built transformers.

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This study is focused on modulation strategies and soft-switching techniques of the isolated dual-active-bridge (DAB) converter for power-electronics applications, where wide input/output voltage and power ranges are required. The aim of this work is to study the different operation modes and to propose a modulation schema combining five operation modes. The objective of the proposed control strategy is to reduce the switching losses of semiconductors and to improve the overall converter efficiency. Thanks to the use of the single-active-bridge modulation, the zero-voltage-switching (ZVS) region of the DAB topology is extended, achieving high-efficiency levels in a wide operation range, even with output voltages close to zero. New analytical expressions are presented in this study to model accurately the behaviour of the DAB converter operation in this extended ZVS region. The influence of non-dissipative snubbers is also studied including experimental measurements with an insulated gate bipolar transistor-based 10 kW prototype for the validation of the theoretical study.

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