Electrical engineering & Electromechanics (Nov 2022)

On modeling and real-time simulation of a robust adaptive controller applied to a multicellular power converter

  • R. Hamdi,
  • A. Hadri Hamida,
  • O. Bennis

DOI
https://doi.org/10.20998/2074-272X.2022.6.08
Journal volume & issue
no. 6
pp. 48 – 52

Abstract

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Introduction. This paper describes the simulation and the robustness assessment of a DC-DC power converter designed to interface a dual-battery conversion system. The adopted converter is a Buck unidirectional and non-isolated converter, composed of three cells interconnected in parallel and operating in continuous conduction mode. Purpose. In order to address the growing challenges of high switching frequencies, a more stable, efficient, and fixed-frequency-operating power system is desired. Originality. Conventional sliding mode controller suffers from high-frequency oscillation caused by practical limitations of system components and switching frequency variation. So, we have explored a soft-switching technology to deal with interface problems and switching losses, and we developed a procedure to choose the high-pass filter parameters in a sliding mode-controlled multicell converter. Methods. We suggest that the sliding mode is controlled by hysteresis bands as the excesses of the band. This delay in state exchanges gives a signal to control the switching frequency of the converter, which, in turn, produces a controlled trajectory. We are seeking an adaptive current control solution to address this issue and adapt a variable-bandwidth of the hysteresis modulation to mitigate nonlinearity in conventional sliding mode control, which struggles to set the switching frequency. Chatter problems are therefore avoided. A boundary layer-based control scheme allows multicell converters to operate with a fixed-switching-frequency. Practical value. Simulation studies in the MATLAB / Simulink environment are performed to analyze system performance and assess its robustness and stability. Thus, our converter is more efficient and able to cope with parametric variation.

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