IET Power Electronics (Aug 2023)

Optimal transformer design of DAB converters in solid‐state transformers for maximum power efficiency

  • Eun S. Lee,
  • Seung H. Song,
  • Jin H. Park,
  • Myung R. Kim

DOI
https://doi.org/10.1049/pel2.12418
Journal volume & issue
Vol. 16, no. 10
pp. 1625 – 1639

Abstract

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Abstract Solid‐state transformers (SST) are a viable solution to replace the conventional low‐frequency transformer in railway vehicles. In the SST, high frequency transformers in dual‐active‐bridge (DAB) converters are essentially used for electrical insulation. Thus, the high‐frequency transformer design becomes so important to increase the high efficiency operation with electrical insulation. Here, an optimal transformer design methodology, which provides a maximum power efficiency operation of the transformer for DAB converters, is proposed. Considering the core loss and copper loss of the transformer, the optimal number of turns for the transformer in a DAB converter N1,op and N2,op can be determined so that the maximum power efficiency for the transformer is achieved at a normal operating point of the DAB converter. To derive the major loss parameters, a finite‐element‐method based simulation was performed for resistive and magnetic loss analysis, which eventually provided the optimal number of turns under the given physical size of ferrite core. The 20 W prototype for a DAB converter with EER2828 and EER3019 of ferrite core shapes were fabricated and verified by simulations and experiments. The results showed that the optimum number of turns N1,op were selected as 12 and 8 turns for two ferrite core models, respectively, which are most highest efficiencies with regard to the different winding turns. To apply the proposed methodology to the SST power level in railway vehicles, 125 kW transformers with inductor set for the SST applications has been fabricated and experimentally verified. As a result, 99.6% of highest efficiency with thermal stable operation was obtained by the proposed transformer design methodology.