Name: Physics Informed Neural Network—Estimated Circuit Parameter Adaptive Modulation of DAB
Keywords: Signal Processing (eess.SP), FOS: Computer and information sciences, FOS: Electrical engineering, electronic engineering, information engineering, Computer Science - Neural and Evolutionary Computing, Neural and Evolutionary Computing (cs.NE), Systems and Control (eess.SY), Electrical Engineering and Systems Science - Signal Processing, Electrical Engineering and Systems Science - Systems and Control

descriptionPublicationkeyboard_double_arrow_right Article , Preprint 01 Oct 2025Embargo end date: 01 Jan 2025Publisher:Institute of Electrical and Electronics Engineers (IEEE)Journal:IEEE Transactions on Power Electronics, volume 40, pages 14,821-14,841 (issn: 0885-8993, eissn: 1941-0107,

Authors: Saikat Dey; Ayan Mallik;

doi: 10.1109/tpel.2025.3574873 , 10.48550/arxiv.2502.17452

arXiv: http://arxiv.org/abs/2502.17452

Physics Informed Neural Network—Estimated Circuit Parameter Adaptive Modulation of DAB

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Abstract

This article presents the development, implementation, and validation of a loss-optimized and circuit parameter-sensitive TPS modulation scheme for a dual-active-bridge DC-DC converter. The proposed approach dynamically adjusts control parameters based on circuit parameters estimated using a physics-informed neural network.

21 pages, 24 figures

Related Organizations

Arizona State University
United States

Keywords

Signal Processing (eess.SP), FOS: Computer and information sciences, FOS: Electrical engineering, electronic engineering, information engineering, Computer Science - Neural and Evolutionary Computing, Neural and Evolutionary Computing (cs.NE), Systems and Control (eess.SY), Electrical Engineering and Systems Science - Signal Processing, Electrical Engineering and Systems Science - Systems and Control

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