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

IF 1.7 4区工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

IET Power Electronics Pub Date : 2025-01-16 DOI:10.1049/pel2.12847

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

引用次数: 0

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.

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来源期刊

IET Power Electronics ENGINEERING, ELECTRICAL & ELECTRONIC-

CiteScore

5.50

自引率

10.00%

发文量

195

审稿时长

5.1 months

期刊介绍： IET Power Electronics aims to attract original research papers, short communications, review articles and power electronics related educational studies. The scope covers applications and technologies in the field of power electronics with special focus on cost-effective, efficient, power dense, environmental friendly and robust solutions, which includes: Applications: Electric drives/generators, renewable energy, industrial and consumable applications (including lighting, welding, heating, sub-sea applications, drilling and others), medical and military apparatus, utility applications, transport and space application, energy harvesting, telecommunications, energy storage management systems, home appliances. Technologies: Circuits: all type of converter topologies for low and high power applications including but not limited to: inverter, rectifier, dc/dc converter, power supplies, UPS, ac/ac converter, resonant converter, high frequency converter, hybrid converter, multilevel converter, power factor correction circuits and other advanced topologies. Components and Materials: switching devices and their control, inductors, sensors, transformers, capacitors, resistors, thermal management, filters, fuses and protection elements and other novel low-cost efficient components/materials. Control: techniques for controlling, analysing, modelling and/or simulation of power electronics circuits and complete power electronics systems. Design/Manufacturing/Testing: new multi-domain modelling, assembling and packaging technologies, advanced testing techniques. Environmental Impact: Electromagnetic Interference (EMI) reduction techniques, Electromagnetic Compatibility (EMC), limiting acoustic noise and vibration, recycling techniques, use of non-rare material. Education: teaching methods, programme and course design, use of technology in power electronics teaching, virtual laboratory and e-learning and fields within the scope of interest. Special Issues. Current Call for papers: Harmonic Mitigation Techniques and Grid Robustness in Power Electronic-Based Power Systems - https://digital-library.theiet.org/files/IET_PEL_CFP_HMTGRPEPS.pdf