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Adaptive Model Predictive Control for DAB Converter Switching Losses Reduction

Author

Listed:
  • Adriano Nardoto

    (Electrical Engineering Department, Federal Institute of Espírito Santo (IFES), BR101 Km 58, São Mateus 29932-540, Brazil)

  • Arthur Amorim

    (Electrical Engineering Department, Federal Institute of Espírito Santo (IFES), BR101 Km 58, São Mateus 29932-540, Brazil)

  • Nelson Santana

    (Electrical Engineering Department, Federal Institute of Espírito Santo (IFES), BR101 Km 58, São Mateus 29932-540, Brazil)

  • Emilio Bueno

    (Department of Electronics, Alcalá University (UAH), Plaza San Diego S/N, 28801 Madrid, Spain)

  • Lucas Encarnação

    (Department of Electrical Engineering, Federal University of Espírito Santo (UFES), Av. Fernando Ferrari, 514, Vitória 29075-910, Brazil)

  • Walbermark Santos

    (Department of Electrical Engineering, Federal University of Espírito Santo (UFES), Av. Fernando Ferrari, 514, Vitória 29075-910, Brazil)

Abstract

The solid-state transformer is the enabling technology for the future of electric power systems. The increasing relevance of this equipment demands higher standards for efficiency and losses reduction. The dual active bridge (DAB) topology is the most usual DC-DC converter used in the solid-state transformer, and is responsible for part of its switching losses. The traditional phase-shift modulation used on DAB converters presents significant switching losses during the operation with reduced loads. The alternative Triangular and Trapezoidal Modulations have been proposed in recent literature; however, there are limitations on the maximum power these techniques can deal with. This paper presents an adaptive model predictive control to select among these three techniques, according to the converter model, the one that minimizes the switching losses and allows the current demanded by the load. Moreover, an alternative cost function is proposed, including the output voltage and current. Through real-time simulation, using a 1000 V/600 V 12 kW DAB converter, it is shown that the proposed control is able to reduce the losses on the converter. Furthermore, the proposed control presents fast and accurate response, and precise transition between the modulation techniques.

Suggested Citation

  • Adriano Nardoto & Arthur Amorim & Nelson Santana & Emilio Bueno & Lucas Encarnação & Walbermark Santos, 2022. "Adaptive Model Predictive Control for DAB Converter Switching Losses Reduction," Energies, MDPI, vol. 15(18), pages 1-24, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:18:p:6628-:d:911746
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    References listed on IDEAS

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    1. Renner Sartório Camargo & Daniel Santamargarita Mayor & Alvar Mayor Miguel & Emilio José Bueno & Lucas Frizera Encarnação, 2020. "A Novel Cascaded Multilevel Converter Topology Based on Three-Phase Cells—CHB-SDC," Energies, MDPI, vol. 13(18), pages 1-25, September.
    2. Pierpaolo Dini & Sergio Saponara, 2020. "Design of Adaptive Controller Exploiting Learning Concepts Applied to a BLDC-Based Drive System," Energies, MDPI, vol. 13(10), pages 1-20, May.
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    Cited by:

    1. Nguyen Ngoc Nam & Sung Hyun Kim, 2022. "Robust Tracking Control of Dual-Active-Bridge DC–DC Converters with Parameter Uncertainties and Input Saturation," Mathematics, MDPI, vol. 10(24), pages 1-19, December.

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