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Modeling Control and Robustness Assessment of Multilevel Flying-Capacitor Converters

Author

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  • Roberto Zanasi

    (“Enzo Ferrari” Department of Engineering, University of Modena and Reggio Emilia, Via Pietro Vivarelli 10 Int. 1, 41125 Modena, Italy)

  • Davide Tebaldi

    (“Enzo Ferrari” Department of Engineering, University of Modena and Reggio Emilia, Via Pietro Vivarelli 10 Int. 1, 41125 Modena, Italy)

Abstract

When performing AC/DC-DC/AC power conversions, multilevel converters provide several advantages as compared to classical two-level converters. This paper deals with the dynamic modeling, control, and robustness assessment of multilevel flying-capacitor converters. The dynamic model is derived using the Power-Oriented Graphs modeling technique, which provides the user with block schemes that are directly implementable in the Matlab/Simulink environment by employing standard Simulink libraries. The performed robustness assessment has led to the proposal of a divergence index, which allows for evaluating the voltage balancing capability of the converter using different voltage vector configurations for the extended operation of the converter, namely when the number of output voltage levels is increased for a given number of capacitors. A new variable-step control algorithm is then proposed. The variable-step control algorithm safely enables the converter extended operation, which prevents voltage balancing issues, even under particularly unfavorable conditions, such as a constant desired output voltage or a sudden load change. The simulation results showing the good performances of the proposed variable-step control as compared to a classical minimum distance approach are finally provided and commented in detail.

Suggested Citation

  • Roberto Zanasi & Davide Tebaldi, 2021. "Modeling Control and Robustness Assessment of Multilevel Flying-Capacitor Converters," Energies, MDPI, vol. 14(7), pages 1-40, March.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:7:p:1903-:d:526677
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    References listed on IDEAS

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    1. Ming Liu & Zetao Li & Xiaoliu Yang, 2020. "A Universal Mathematical Model of Modular Multilevel Converter with Half-Bridge," Energies, MDPI, vol. 13(17), pages 1-18, August.
    2. Patricio Gaisse & Javier Muñoz & Ariel Villalón & Rodrigo Aliaga, 2020. "Improved Predictive Control for an Asymmetric Multilevel Converter for Photovoltaic Energy," Sustainability, MDPI, vol. 12(15), pages 1-22, August.
    3. Matias Diaz & Roberto Cardenas & Efrain Ibaceta & Andrés Mora & Matias Urrutia & Mauricio Espinoza & Felix Rojas & Patrick Wheeler, 2020. "An Overview of Modelling Techniques and Control Strategies for Modular Multilevel Matrix Converters," Energies, MDPI, vol. 13(18), pages 1-38, September.
    4. Gianluca Brando & Adolfo Dannier & Ivan Spina & Pietro Tricoli, 2017. "Integrated BMS-MMC Balancing Technique Highlighted by a Novel Space-Vector Based Approach for BEVs Application," Energies, MDPI, vol. 10(10), pages 1-14, October.
    5. Yantao Liao & Jun You & Jun Yang & Zuo Wang & Long Jin, 2018. "Disturbance-Observer-Based Model Predictive Control for Battery Energy Storage System Modular Multilevel Converters," Energies, MDPI, vol. 11(9), pages 1-19, August.
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    1. Jorge Lara & Lesedi Masisi & Concepcion Hernandez & Marco A. Arjona & Ambrish Chandra, 2021. "Novel Single-Phase Grid-Tied NPC Five-Level Converter with an Inherent DC-Link Voltage Balancing Strategy for Power Quality Improvement," Energies, MDPI, vol. 14(9), pages 1-22, May.

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