Model predictive control for quad active bridge DC-DC converter for more electric aircraft applications

dc.contributor.authorAdam, Ahmed Hamed Ahmed
dc.contributor.authorChen, Jiawei
dc.contributor.authorXu, Minghan
dc.contributor.authorKamel, Salah
dc.contributor.authorAli, Guma
dc.date.accessioned2025-12-17T13:15:17Z
dc.date.available2025-12-17T13:15:17Z
dc.date.issued2025-04-21
dc.descriptionThis paper presents a moving-discretized control-set model predictive control strategy for quad active-bridge converters used to connect multiple power sources and loads with different voltage levels. The approach overcomes the limitations of traditional controllers by eliminating voltage overshoot, undershoot, and steady-state errors while improving dynamic response robustness and computational efficiency. Validation through simulation and hardware-in-the-loop experiments confirms reliable, high-performance control. The study supports SDG 7 (affordable and clean energy), SDG 9 (industry, innovation, and infrastructure), and SDG 13 (climate action). It also aligns with the aspirations of Uganda's National Development Plan IV for digital transformation, energy security, resilient infrastructure, and human capital development.
dc.description.abstractThe isolated multi-port converters quad-active bridge (QAB) presents a unique opportunity to connect multiple sources and loads operating at different power and voltage levels, offering galvanic isolation and shared magnetics as advantages. However, the high number of modulation variables, dynamic response, and overall modeling complexity of QAB converters pose challenges to controller design. Traditional linear controllers often struggle with voltage overshooting and undershooting under abrupt load changes and exhibit limited dynamic performance and coupling among different ports. To address these challenges, this paper introduces a moving discretized control set-model predictive control (MDCS-MPC) strategy for QAB converters. The developed approach predicts phase shift values through the converter model, ensuring fast dynamic performance and eliminating steady-state errors in control variables. The prediction model’s embedded circuit parameters and operating modes enhance performance across various power and terminal voltage ranges. An adaptive step is implemented for quick transitions, significantly reducing computational demands. These analytical findings and the MDCS-MPC strategy are verified through Matlab simulation results and experimental results obtained from the Hardware-in-the-Loop (HIL) real-time Typhoon 602 platform. Both experimental and simulation results demonstrate the effectiveness of the developed strategy, showing superior dynamic response, robustness, and reduced computational requirements. Furthermore, the voltage achieves a very fast dynamic response and exhibits no significant voltage overshoot or undershoot.
dc.identifier.citationAdam, A. H. A., Chen, J., Xu, M., Kamel, S., & Ali, G. (2025). Model predictive control for quad active bridge DC-DC converter for more electric aircraft applications. Scientific Reports, 15(1), 13653.
dc.identifier.issn2045-2322
dc.identifier.urihttps://dir.muni.ac.ug/handle/20.500.12260/828
dc.language.isoen
dc.publisherSpringer Nature
dc.subjectQuad
dc.subjectActive bridge
dc.subjectLinear controllers
dc.subjectDynamic performance
dc.subjectMoving discretized control set
dc.subjectModel predictive control
dc.subjectHardware-in-the-loop (HIL)
dc.subjectTyphoon 602 platform
dc.titleModel predictive control for quad active bridge DC-DC converter for more electric aircraft applications
dc.typeArticle

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