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A Modulated Model Predictive Current Controller for Interior Permanent-Magnet Synchronous Motors

Author

Listed:
  • Crestian Almazan Agustin

    (Department of Electrical Engineering, National Taiwan Ocean University, Keelung City 202, Taiwan)

  • Jen-te Yu

    (Department of Electrical Engineering, Chung Yuan Christian University, Taoyuan City 32023, Taiwan)

  • Cheng-Kai Lin

    (Department of Electrical Engineering, National Taiwan Ocean University, Keelung City 202, Taiwan)

  • Xiang-Yong Fu

    (Department of Electrical Engineering, National Taiwan Ocean University, Keelung City 202, Taiwan)

Abstract

Model predictive current controllers (MPCCs) are widely applied in motor drive control and operations. To date, however, the presence of large current errors in conventional predictive current control remains a significant predicament, due to harmonic distortions and current ripples. Naturally, noticeable current estimation inaccuracies lead to poor performance. To improve the above situation, a modulated model predictive current controller (MMPCC) is proposed for interior permanent-magnet synchronous motors (IPMSMs) in this paper. Two successive voltage vectors will be applied in a sampling period to greatly boost the number of candidate switching modes from seven to thirteen. A cost function, which is defined as the quadratic sum of current prediction errors, is employed to find an optimal switching mode and an optimized duty ratio to be applied in the next sampling period, such that the cost value is minimal. The effectiveness of the proposed method is verified through eight experiments using a TMS320F28379D microcontroller, and performance comparisons are made against an existing MPCC. In terms of quantitative improvements made to the MPCC, the proposed MMPCC reduces its current ripple and total harmonic distortion (THD) by, on average, 27.17% and 21.84%, respectively.

Suggested Citation

  • Crestian Almazan Agustin & Jen-te Yu & Cheng-Kai Lin & Xiang-Yong Fu, 2019. "A Modulated Model Predictive Current Controller for Interior Permanent-Magnet Synchronous Motors," Energies, MDPI, vol. 12(15), pages 1-20, July.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:15:p:2885-:d:252034
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    References listed on IDEAS

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    1. Xiaoliang Yang & Guorong Liu & Anping Li & Le Van Dai, 2017. "A Predictive Power Control Strategy for DFIGs Based on a Wind Energy Converter System," Energies, MDPI, vol. 10(8), pages 1-24, July.
    2. Cheng-Kai Lin & Jen-te Yu & Hao-Qun Huang & Jyun-Ting Wang & Hsing-Cheng Yu & Yen-Shin Lai, 2018. "A Dual-Voltage-Vector Model-Free Predictive Current Controller for Synchronous Reluctance Motor Drive Systems," Energies, MDPI, vol. 11(7), pages 1-29, July.
    3. Zhi Wu & Jiawei Chu & Wei Gu & Qiang Huang & Liang Chen & Xiaodong Yuan, 2018. "Hybrid Modulated Model Predictive Control in a Modular Multilevel Converter for Multi-Terminal Direct Current Systems," Energies, MDPI, vol. 11(7), pages 1-17, July.
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    Cited by:

    1. Karol Wróbel & Piotr Serkies & Krzysztof Szabat, 2020. "Model Predictive Base Direct Speed Control of Induction Motor Drive—Continuous and Finite Set Approaches," Energies, MDPI, vol. 13(5), pages 1-15, March.
    2. Chi Zhang & Binyue Xu & Jasronita Jasni & Mohd Amran Mohd Radzi & Norhafiz Azis & Qi Zhang, 2023. "Three Voltage Vector Duty Cycle Optimization Strategy of the Permanent Magnet Synchronous Motor Driving System for New Energy Electric Vehicles Based on Finite Set Model Predictive Control," Energies, MDPI, vol. 16(6), pages 1-18, March.
    3. Jaime A. Rohten & David N. Dewar & Pericle Zanchetta & Andrea Formentini & Javier A. Muñoz & Carlos R. Baier & José J. Silva, 2021. "Multivariable Deadbeat Control of Power Electronics Converters with Fast Dynamic Response and Fixed Switching Frequency," Energies, MDPI, vol. 14(2), pages 1-16, January.
    4. Xingliang Liu & Guiyun Tian & Yu Chen & Haoze Luo & Jian Zhang & Wuhua Li, 2020. "Non-Contact Degradation Evaluation for IGBT Modules Using Eddy Current Pulsed Thermography Approach," Energies, MDPI, vol. 13(10), pages 1-14, May.

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