A Simplified ANN Based Power Decoupling Method of MAB Converters

Rongxin Qiu; Chunyang Gu; Jing Li; Jiajun Yang

doi:10.1109/CIEEC64805.2025.11116139

A Simplified ANN Based Power Decoupling Method of MAB Converters

Rongxin Qiu
, Chunyang Gu
, Jing Li
, Jiajun Yang

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

To deal with the decoupling control problem between ports of multiple active bridge (MAB) converters, This paper proposes a simplified artificial neural networks (ANN) based power decoupling method for MAB converters. Using the ANN model, the computational complexity and training data requirements of the model are reduced compared to iterative optimization algorithms. The parameter sensitivity is low, and it can accept output errors of less than 2% under 30% voltage fluctuations, improving output accuracy and achieving complete power decoupling, simplifying the complexity of MAB control.

Original language	English
Title of host publication	2025 IEEE 8th International Electrical and Energy Conference, CIEEC 2025
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2438-2443
Number of pages	6
ISBN (Electronic)	9798331542979
DOIs	https://doi.org/10.1109/CIEEC64805.2025.11116139
Publication status	Published - 2025
Event	8th IEEE International Electrical and Energy Conference, CIEEC 2025 - Changsha, China Duration: 16 May 2025 → 18 May 2025

Publication series

Name	2025 IEEE 8th International Electrical and Energy Conference, CIEEC 2025

Conference

Conference	8th IEEE International Electrical and Energy Conference, CIEEC 2025
Country/Territory	China
City	Changsha
Period	16/05/25 → 18/05/25

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Free Keywords

artificial neural networks (ANN)
multiple active bridge (MAB)
power decoupling
simplified

ASJC Scopus subject areas

Energy Engineering and Power Technology
Renewable Energy, Sustainability and the Environment
Electrical and Electronic Engineering
Biomaterials
Electronic, Optical and Magnetic Materials
Polymers and Plastics

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10.1109/CIEEC64805.2025.11116139

Cite this

Qiu, R., Gu, C., Li, J., & Yang, J. (2025). A Simplified ANN Based Power Decoupling Method of MAB Converters. In 2025 IEEE 8th International Electrical and Energy Conference, CIEEC 2025 (pp. 2438-2443). (2025 IEEE 8th International Electrical and Energy Conference, CIEEC 2025). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CIEEC64805.2025.11116139

@inproceedings{48b7372598c845fca8288f4f90a93175,

title = "A Simplified ANN Based Power Decoupling Method of MAB Converters",

abstract = "To deal with the decoupling control problem between ports of multiple active bridge (MAB) converters, This paper proposes a simplified artificial neural networks (ANN) based power decoupling method for MAB converters. Using the ANN model, the computational complexity and training data requirements of the model are reduced compared to iterative optimization algorithms. The parameter sensitivity is low, and it can accept output errors of less than 2\% under 30\% voltage fluctuations, improving output accuracy and achieving complete power decoupling, simplifying the complexity of MAB control.",

keywords = "artificial neural networks (ANN), multiple active bridge (MAB), power decoupling, simplified",

author = "Rongxin Qiu and Chunyang Gu and Jing Li and Jiajun Yang",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 8th IEEE International Electrical and Energy Conference, CIEEC 2025 ; Conference date: 16-05-2025 Through 18-05-2025",

year = "2025",

doi = "10.1109/CIEEC64805.2025.11116139",

language = "English",

series = "2025 IEEE 8th International Electrical and Energy Conference, CIEEC 2025",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "2438--2443",

booktitle = "2025 IEEE 8th International Electrical and Energy Conference, CIEEC 2025",

address = "United States",

}

Qiu, R, Gu, C , Li, J & Yang, J 2025, A Simplified ANN Based Power Decoupling Method of MAB Converters. in 2025 IEEE 8th International Electrical and Energy Conference, CIEEC 2025. 2025 IEEE 8th International Electrical and Energy Conference, CIEEC 2025, Institute of Electrical and Electronics Engineers Inc., pp. 2438-2443, 8th IEEE International Electrical and Energy Conference, CIEEC 2025, Changsha, China, 16/05/25. https://doi.org/10.1109/CIEEC64805.2025.11116139

A Simplified ANN Based Power Decoupling Method of MAB Converters. / Qiu, Rongxin; Gu, Chunyang ; Li, Jing et al.
2025 IEEE 8th International Electrical and Energy Conference, CIEEC 2025. Institute of Electrical and Electronics Engineers Inc., 2025. p. 2438-2443 (2025 IEEE 8th International Electrical and Energy Conference, CIEEC 2025).

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A Simplified ANN Based Power Decoupling Method of MAB Converters

AU - Qiu, Rongxin

AU - Gu, Chunyang

AU - Li, Jing

AU - Yang, Jiajun

PY - 2025

Y1 - 2025

N2 - To deal with the decoupling control problem between ports of multiple active bridge (MAB) converters, This paper proposes a simplified artificial neural networks (ANN) based power decoupling method for MAB converters. Using the ANN model, the computational complexity and training data requirements of the model are reduced compared to iterative optimization algorithms. The parameter sensitivity is low, and it can accept output errors of less than 2% under 30% voltage fluctuations, improving output accuracy and achieving complete power decoupling, simplifying the complexity of MAB control.

AB - To deal with the decoupling control problem between ports of multiple active bridge (MAB) converters, This paper proposes a simplified artificial neural networks (ANN) based power decoupling method for MAB converters. Using the ANN model, the computational complexity and training data requirements of the model are reduced compared to iterative optimization algorithms. The parameter sensitivity is low, and it can accept output errors of less than 2% under 30% voltage fluctuations, improving output accuracy and achieving complete power decoupling, simplifying the complexity of MAB control.

KW - artificial neural networks (ANN)

KW - multiple active bridge (MAB)

KW - power decoupling

KW - simplified

UR - https://www.scopus.com/pages/publications/105015664165

U2 - 10.1109/CIEEC64805.2025.11116139

DO - 10.1109/CIEEC64805.2025.11116139

M3 - Conference contribution

AN - SCOPUS:105015664165

T3 - 2025 IEEE 8th International Electrical and Energy Conference, CIEEC 2025

SP - 2438

EP - 2443

BT - 2025 IEEE 8th International Electrical and Energy Conference, CIEEC 2025

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 8th IEEE International Electrical and Energy Conference, CIEEC 2025

Y2 - 16 May 2025 through 18 May 2025

ER -

A Simplified ANN Based Power Decoupling Method of MAB Converters

Abstract

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UN SDGs

Free Keywords

ASJC Scopus subject areas

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