Multiloop Stability Analysis of Input Voltage Balancing Control in Dual-Active-Bridge-Based Input-Series Output-Parallel Converters

Modeling and stability analysis of the input voltage balancing control (IVBC) loops in input-series output-parallel (ISOP) converters have been widely studied in the existing literature, where stability of the IVBC loops was analyzed in single-loop form and guaranteed by possessing desired stability margins of the open-loop gain. Nonetheless, the analyzed results can be less effective or even ineffective when submodules are nonidentical, due to aggravated coupling effects among the IVBC loops by mismatch of parameters. By selecting dual-active-bridge-based ISOP converters applied with a general control strategy for the case study, this article initially develops a Kirchhoff's Voltage Law (KVL)-based straightforward model, which allows for predicting loop instability of the IVBC in a multiloop form for cases where submodules are not identical, with its limitations revealed. To further overcome the limitations, a model using implicit control targets of the IVBC exposed by a rearranged input circuitry of the converter is proposed, which enables accurate prediction of the loop instability and its main oscillation frequency regardless of whether submodules are identical or not. The effectiveness and accuracy of the proposed model are comprehensively validated in comparison with the KVL-based straightforward model through the simulation and experiments conducted on a laboratory prototype.

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Publication Details

Journal
IEEE Transactions on Power Electronics
Published
2025-02-07
DOI
https://doi.org/10.1109/tpel.2025.3539774
Citations
2
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
2.43

Funders

Controls
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article

Multiloop Stability Analysis of Input Voltage Balancing Control in Dual-Active-Bridge-Based Input-Series Output-Parallel Converters

Patrick Wheeler, Giampaolo Buticchi, Sandro Günter, Marco Liserre et al.
2 citations
IEEE Transactions on Power Electronics
Microgrid Control and Optimization
2.43
article

Multiloop Stability Analysis of Input Voltage Balancing Control in Dual-Active-Bridge-Based Input-Series Output-Parallel Converters

Patrick Wheeler, Giampaolo Buticchi, Sandro Günter, Marco Liserre, Chunyang Gu, Jiajun Yang
article en
2 citations

Abstract

Modeling and stability analysis of the input voltage balancing control (IVBC) loops in input-series output-parallel (ISOP) converters have been widely studied in the existing literature, where stability of the IVBC loops was analyzed in single-loop form and guaranteed by possessing desired stability margins of the open-loop gain. Nonetheless, the analyzed results can be less effective or even ineffective when submodules are nonidentical, due to aggravated coupling effects among the IVBC loops by mismatch of parameters. By selecting dual-active-bridge-based ISOP converters applied with a general control strategy for the case study, this article initially develops a Kirchhoff's Voltage Law (KVL)-based straightforward model, which allows for predicting loop instability of the IVBC in a multiloop form for cases where submodules are not identical, with its limitations revealed. To further overcome the limitations, a model using implicit control targets of the IVBC exposed by a rearranged input circuitry of the converter is proposed, which enables accurate prediction of the loop instability and its main oscillation frequency regardless of whether submodules are identical or not. The effectiveness and accuracy of the proposed model are comprehensively validated in comparison with the KVL-based straightforward model through the simulation and experiments conducted on a laboratory prototype.

IEEE Transactions on Power ElectronicsVol. 40(6)
University of Nottingham Ningbo China (CN), University of Nottingham (GB), Christian-Albrechts-Universität zu Kiel (DE)
National Natural Science Foundation of China, Ningbo Municipal Bureau of Science and Technology
Affordable and clean energy
Openalex Percentile: Top 13%
Microgrid Control and Optimization
2.43
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