LAPSE:2023.9665
Published Article
LAPSE:2023.9665
Adaptive Model Predictive Control for DAB Converter Switching Losses Reduction
February 27, 2023
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.
Keywords
adaptive control, dual active bridge converter, Model Predictive Control, power electronics, switching losses
Suggested Citation
Nardoto A, Amorim A, Santana N, Bueno E, Encarnação L, Santos W. Adaptive Model Predictive Control for DAB Converter Switching Losses Reduction. (2023). LAPSE:2023.9665
Author Affiliations
Nardoto A: Electrical Engineering Department, Federal Institute of Espírito Santo (IFES), BR101 Km 58, São Mateus 29932-540, Brazil
Amorim A: Electrical Engineering Department, Federal Institute of Espírito Santo (IFES), BR101 Km 58, São Mateus 29932-540, Brazil [ORCID]
Santana N: Electrical Engineering Department, Federal Institute of Espírito Santo (IFES), BR101 Km 58, São Mateus 29932-540, Brazil [ORCID]
Bueno E: Department of Electronics, Alcalá University (UAH), Plaza San Diego S/N, 28801 Madrid, Spain [ORCID]
Encarnação L: Department of Electrical Engineering, Federal University of Espírito Santo (UFES), Av. Fernando Ferrari, 514, Vitória 29075-910, Brazil [ORCID]
Santos W: Department of Electrical Engineering, Federal University of Espírito Santo (UFES), Av. Fernando Ferrari, 514, Vitória 29075-910, Brazil [ORCID]
Journal Name
Energies
Volume
15
Issue
18
First Page
6628
Year
2022
Publication Date
2022-09-10
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en15186628, Publication Type: Journal Article
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LAPSE:2023.9665
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https://doi.org/10.3390/en15186628
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Feb 27, 2023
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