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Modulated Predictive Control to Improve the Steady-State Performance of NSI-Based Electrification Systems

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  • Mustafa Gokdag

    (Department of Electrical-Electronics Engineering, Karabuk University, Karabuk 78050, Turkey)

Abstract

This paper presents a modulated model predictive control (M 2 PC) strategy for a nine-switch inverter (NSI) based electrification system to improve the steady-state performance. The model predictive control method has gained significant interest due to its straightforward structure. However, the traditional finite control set model predictive control (FCS-MPC) imposes a high computational burden that is problematic in practical applications. This prevents reaching the high sampling frequencies due to an excessive increase in algorithm run-time. Selecting a low sampling frequency causes an unpleasant distortion in the control variable or poor power quality. An M 2 PC method for the NSI is proposed in this work to remove this trade-off. One zero vector and two active vectors are selected by evaluating a cost function for each allowed switching state of the NSI. The duty cycles of these vectors are calculated by assessing the cost function employing current error terms. An optimized sequence of these vectors is applied to the system that operates with the fixed-modulation frequency. Thus, an improvement in power quality (reduced harmonics with a better spectral content) with a lower sampling frequency is achieved. The computational burden rate (CBR) on the processor is reduced. These enhancements were proved by simulation and experimental studies. The comparison work was conducted to highlight the advantages of the proposed method over the other techniques reported in the literature. The proposed M 2 PC method was verified on a lab-scale NSI prototype driving two induction machines. The machine torques and speeds are well regulated, and the quality of the stator current is improved.

Suggested Citation

  • Mustafa Gokdag, 2022. "Modulated Predictive Control to Improve the Steady-State Performance of NSI-Based Electrification Systems," Energies, MDPI, vol. 15(6), pages 1-19, March.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:6:p:2043-:d:768558
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    References listed on IDEAS

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    1. Guan-Jhu Chen & Yi-Hua Liu & Yu-Shan Cheng & Hung-Yu Pai, 2021. "A Novel Optimal Charging Algorithm for Lithium-Ion Batteries Based on Model Predictive Control," Energies, MDPI, vol. 14(8), pages 1-18, April.
    2. Mariusz Jabłoński & Piotr Borkowski, 2022. "Correction Mechanism for Balancing Driving Torques in an Opencast Mining Stacker with an Induction Motor and Converter Drive System," Energies, MDPI, vol. 15(4), pages 1-16, February.
    3. Deepa Sankar & Lakshmi Syamala & Babu Chembathu Ayyappan & Mathew Kallarackal, 2021. "FPGA-Based Cost-Effective and Resource Optimized Solution of Predictive Direct Current Control for Power Converters," Energies, MDPI, vol. 14(22), pages 1-26, November.
    4. Antonio José Calderón & Francisco José Vivas & Francisca Segura & José Manuel Andújar, 2020. "Integration of a Multi-Stack Fuel Cell System in Microgrids: A Solution Based on Model Predictive Control," Energies, MDPI, vol. 13(18), pages 1-24, September.
    5. Victor Daniel Reyes Dreke & Mircea Lazar, 2022. "Long-Horizon Nonlinear Model Predictive Control of Modular Multilevel Converters," Energies, MDPI, vol. 15(4), pages 1-22, February.
    6. Jagabar Sathik & Shady H. E. Abdel Aleem & Rasoul Shalchi Alishah & Dhafer Almakhles & Kent Bertilsson & Mahajan Sagar Bhaskar & George Fernandez Savier & Karthikeyan Dhandapani, 2021. "A Multilevel Inverter Topology Using Diode Half-Bridge Circuit with Reduced Power Component," Energies, MDPI, vol. 14(21), pages 1-21, November.
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    Cited by:

    1. Levon Gevorkov & José Luis Domínguez-García & Anton Rassõlkin & Toomas Vaimann, 2022. "Comparative Simulation Study of Pump System Efficiency Driven by Induction and Synchronous Reluctance Motors," Energies, MDPI, vol. 15(11), pages 1-12, June.
    2. Roberto O. Ramírez & Carlos R. Baier & Felipe Villarroel & Eduardo Espinosa & Mauricio Arevalo & Jose R. Espinoza, 2023. "Reduction of DC Capacitor Size in Three-Phase Input/Single-Phase Output Power Cells of Multi-Cell Converters through Resonant and Predictive Control: A Characterization of Its Impact on the Operating ," Mathematics, MDPI, vol. 11(14), pages 1-19, July.

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