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  4. Multiobjective Optimization of Medium-Frequency Transformers for Isolated Soft-Switching Converters Using a Genetic Algorithm
 
research article

Multiobjective Optimization of Medium-Frequency Transformers for Isolated Soft-Switching Converters Using a Genetic Algorithm

Garcia-Bediaga, Asier
•
Villar, Irma
•
Rujas, Alejandro
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2017
IEEE Transactions on Power Electronics

The main challenge of medium-frequency transformers is the 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 nondominated sorting genetic algorithm 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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Type
research article
DOI
10.1109/Tpel.2016.2574499
Web of Science ID

WOS:000395480400046

Author(s)
Garcia-Bediaga, Asier
Villar, Irma
Rujas, Alejandro
Mir, Luis
Rufer, Alfred  
Date Issued

2017

Publisher

Ieee-Inst Electrical Electronics Engineers Inc

Published in
IEEE Transactions on Power Electronics
Volume

32

Issue

4

Start page

2995

End page

3006

Subjects

Genetic algorithm (GA)

•

medium frequency (MF)

•

soft-switching

•

transformers

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LEI  
Available on Infoscience
March 27, 2017
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/135824
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