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10.1109_access.2023.3264013.pdf (4.51 MB)

An Adaptive Sliding Mode Control for a Dual Active Bridge Converter With Extended Phase Shift Modulation

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submitted on 2024-02-12, 09:11 and posted on 2024-02-12, 09:12 authored by Farzaneh Bagheri, Naki Guler, Hasan Komurcugil, Sertac Bayhan

This paper introduces an adaptive super-twisting sliding mode control (ASTSMC) approach for controlling a dual active bridge (DAB) converter with an extended phase shift (EPS) modulation. The conventional single-phase shift (SPS) modulation-based DAB converter is known to be inefficient. Hence, an optimization algorithm based on the Lagrange multiplier method (LMM) is proposed to minimize both backflow power and inductor current stress simultaneously. Unlike the conventional schemes that use an offline optimization (OFFO) method to derive the phase shift ratios, this paper proposes an online optimization method and an ASTSMC method for generating the inner and outer phase shift ratio respectively. Initially, a generalized average modeling (GAM) for the DAB converter under EPS modulation is derived, and then the proposed ASTSMC is introduced according to this model. The conventional STSMC with constant gains suffers from low performance under disturbances such as load current perturbations, input voltage variations, and output voltage reference variations. Additionally, it requires an overestimated gain under steady-state conditions. To address these issues, a variable gain-based STSMC scheme is proposed to enhance the performance of the converter under all operating conditions. The effectiveness of the proposed method is verified through simulation and experimental results, which are compared with the results of the conventional STSMC method.

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Published in: IEEE Access
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Open Access funding provided by the Qatar National Library.



  • English



Publication Year

  • 2023

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License

Institution affiliated with

  • Hamad Bin Khalifa University
  • Qatar Environment and Energy Research Institute - HBKU