A stable machine learning based control for bidirectional interleaved DC/DC converter in battery systems

Ran Li, Ruigang Wang, Wendong Feng, Tianhao Qie, Yulin Liu, Tyrone Fernando, Herbert HoChing Iu, Xinan Zhang

Research output: Contribution to journalArticlepeer-review

Abstract

This paper proposes an innovative machine learning-based control algorithm for the bidirectional interleaved DC/DC converter in battery systems. It offers fast dynamics, gain tuning-free control design, and guaranteed closed-loop stability. Furthermore, compared to the other learning-based control methods, the proposed algorithm shows low computational complexity in both the neural network training and the online digital implementation. The efficacy of the proposed method is substantiated through experimental validation.

Original languageEnglish
Article numbere12847
Number of pages10
JournalIET Power Electronics
Volume18
Issue number1
DOIs
Publication statusPublished - 1 Jan 2025

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