IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i7p1793-d156872.html
   My bibliography  Save this article

Induction Motor Drive Direct Torque Control and Predictive Torque Control Comparison Based on Switching Pattern Analysis

Author

Listed:
  • Pavel Karlovsky

    (Department of Electric Drives and Traction, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, 16627, Czech Republic)

  • Jiri Lettl

    (Department of Electric Drives and Traction, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, 16627, Czech Republic)

Abstract

This paper describes a switching pattern generated in case of induction motor drive predictive torque control (PTC) compared to a switching pattern of direct torque control (DTC). PTC is a modern control method for electric drives based on model predictive control (MPC). DTC is a very powerful method and is today an industrial standard for controlling an induction motor drive. Its usage is wide-spread, mainly in high-power applications. However, the method suffers from a few disadvantages. One of the causes of the control method’s problematic behavior is choosing the switching combinations in the flux sector. Another inconvenience is the common selection table not including all voltage vectors in given sector. By these factors, the ripples of flux vector trajectory and torque waveforms are influenced. The longer the sample time is, the more significant the influence of factors becomes, because only a few steps occur within one turn of the magnetic flux vector. Based on the detailed analysis, the reasons of the different performance of both systems are explained. The analysis performed by simulation in Matlab Simulink environment has proved that, while DTC might choose voltage vector that pushes system away from the reference values, the MPC always chooses the most proper vector. The experimental results measured on the real drive confirm the appropriate vector selection, just in case of the predictive control method.

Suggested Citation

  • Pavel Karlovsky & Jiri Lettl, 2018. "Induction Motor Drive Direct Torque Control and Predictive Torque Control Comparison Based on Switching Pattern Analysis," Energies, MDPI, vol. 11(7), pages 1-14, July.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:7:p:1793-:d:156872
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/7/1793/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/7/1793/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fengxiang Wang & Zhenbin Zhang & Xuezhu Mei & José Rodríguez & Ralph Kennel, 2018. "Advanced Control Strategies of Induction Machine: Field Oriented Control, Direct Torque Control and Model Predictive Control," Energies, MDPI, vol. 11(1), pages 1-13, January.
    2. Milutin Petronijević & Nebojša Mitrović & Vojkan Kostić & Bojan Banković, 2017. "An Improved Scheme for Voltage Sag Override in Direct Torque Controlled Induction Motor Drives," Energies, MDPI, vol. 10(5), pages 1-16, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sergey Goolak & Viktor Tkachenko & Svitlana Sapronova & Vaidas Lukoševičius & Robertas Keršys & Rolandas Makaras & Artūras Keršys & Borys Liubarskyi, 2022. "Synthesis of the Current Controller of the Vector Control System for Asynchronous Traction Drive of Electric Locomotives," Energies, MDPI, vol. 15(7), pages 1-19, March.
    2. Sergey Goolak & Borys Liubarskyi & Ievgen Riabov & Vaidas Lukoševičius & Artūras Keršys & Sigitas Kilikevičius, 2023. "Analysis of the Efficiency of Traction Drive Control Systems of Electric Locomotives with Asynchronous Traction Motors," Energies, MDPI, vol. 16(9), pages 1-30, April.
    3. Chaymae Fahassa & Yassine Zahraoui & Mohammed Akherraz & Mohammed Kharrich & Ehab E. Elattar & Salah Kamel, 2022. "Induction Motor DTC Performance Improvement by Inserting Fuzzy Logic Controllers and Twelve-Sector Neural Network Switching Table," Mathematics, MDPI, vol. 10(9), pages 1-14, April.
    4. Mingmao Hu & Feng Yang & Yi Liu & Liang Wu, 2022. "Finite Control Set Model-Free Predictive Current Control of a Permanent Magnet Synchronous Motor," Energies, MDPI, vol. 15(3), pages 1-18, January.
    5. Bowei Zou & Yougui Guo & Xi Xiao & Bowen Yang & Xiao Wang & Mingzhang Shi & Yulin Tu, 2020. "Performance Improvement of Matrix Converter Direct Torque Control System," Energies, MDPI, vol. 13(12), pages 1-17, June.
    6. Alessandro Benevieri & Gianmarco Maragliano & Mario Marchesoni & Massimiliano Passalacqua & Luis Vaccaro, 2021. "Induction Motor Direct Torque Control with Synchronous PWM," Energies, MDPI, vol. 14(16), pages 1-17, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sofiane Bacha & Ramzi Saadi & Mohamed Yacine Ayad & Mohamed Sahraoui & Khaled Laadjal & Antonio J. Marques Cardoso, 2023. "Autonomous Electric-Vehicle Control Using Speed Planning Algorithm and Back-Stepping Approach," Energies, MDPI, vol. 16(5), pages 1-26, March.
    2. Kodkin Vladimir & Anikin Alexander, 2021. "On the Physical Nature of Frequency Control Problems of Induction Motor Drives," Energies, MDPI, vol. 14(14), pages 1-15, July.
    3. Ahmed G. Mahmoud A. Aziz & Almoataz Y. Abdelaziz & Ziad M. Ali & Ahmed A. Zaki Diab, 2023. "A Comprehensive Examination of Vector-Controlled Induction Motor Drive Techniques," Energies, MDPI, vol. 16(6), pages 1-32, March.
    4. 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.
    5. Zhanqing Zhou & Xin Gu & Zhiqiang Wang & Guozheng Zhang & Qiang Geng, 2019. "An Improved Torque Control Strategy of PMSM Drive Considering On-Line MTPA Operation," Energies, MDPI, vol. 12(15), pages 1-17, July.
    6. Tadeusz Białoń & Roman Niestrój & Jarosław Michalak & Marian Pasko, 2021. "Induction Motor PI Observer with Reduced-Order Integrating Unit," Energies, MDPI, vol. 14(16), pages 1-12, August.
    7. 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.
    8. Yuzhe Zhang & Xiaodong Liu & Haitao Li & Zhenbin Zhang, 2023. "A Model Independent Predictive Control of PMSG Wind Turbine Systems with a New Mechanism to Update Variables," Energies, MDPI, vol. 16(9), pages 1-15, April.
    9. Chaymae Fahassa & Yassine Zahraoui & Mohammed Akherraz & Mohammed Kharrich & Ehab E. Elattar & Salah Kamel, 2022. "Induction Motor DTC Performance Improvement by Inserting Fuzzy Logic Controllers and Twelve-Sector Neural Network Switching Table," Mathematics, MDPI, vol. 10(9), pages 1-14, April.
    10. Tadeusz Białoń & Marian Pasko & Roman Niestrój, 2020. "Developing Induction Motor State Observers with Increased Robustness," Energies, MDPI, vol. 13(20), pages 1-24, October.
    11. Camila Paes Salomon & Wilson Cesar Sant’Ana & Germano Lambert-Torres & Luiz Eduardo Borges da Silva & Erik Leandro Bonaldi & Levy Ely de Lacerda De Oliveira, 2018. "Comparison among Methods for Induction Motor Low-Intrusive Efficiency Evaluation Including a New AGT Approach with a Modified Stator Resistance," Energies, MDPI, vol. 11(4), pages 1-21, March.
    12. Habib Benbouhenni & Nicu Bizon, 2021. "Improved Rotor Flux and Torque Control Based on the Third-Order Sliding Mode Scheme Applied to the Asynchronous Generator for the Single-Rotor Wind Turbine," Mathematics, MDPI, vol. 9(18), pages 1-16, September.
    13. Yanis Hamoudi & Hocine Amimeur & Djamal Aouzellag & Maher G. M. Abdolrasol & Taha Selim Ustun, 2023. "Hyperparameter Bayesian Optimization of Gaussian Process Regression Applied in Speed-Sensorless Predictive Torque Control of an Autonomous Wind Energy Conversion System," Energies, MDPI, vol. 16(12), pages 1-19, June.
    14. Mostafa Ahmed & Ibrahim Harbi & Ralph Kennel & José Rodríguez & Mohamed Abdelrahem, 2022. "Evaluation of the Main Control Strategies for Grid-Connected PV Systems," Sustainability, MDPI, vol. 14(18), pages 1-20, September.
    15. Mohamed Derbeli & Cristian Napole & Oscar Barambones & Jesus Sanchez & Isidro Calvo & Pablo Fernández-Bustamante, 2021. "Maximum Power Point Tracking Techniques for Photovoltaic Panel: A Review and Experimental Applications," Energies, MDPI, vol. 14(22), pages 1-31, November.
    16. Thyago Estrabis & Gabriel Gentil & Raymundo Cordero, 2021. "Development of a Resolver-to-Digital Converter Based on Second-Order Difference Generalized Predictive Control," Energies, MDPI, vol. 14(2), pages 1-22, January.
    17. Ondrej Lipcak & Filip Baum & Jan Bauer, 2021. "Influence of Selected Non-Ideal Aspects on Active and Reactive Power MRAS for Stator and Rotor Resistance Estimation," Energies, MDPI, vol. 14(20), pages 1-19, October.
    18. Andrzej Chudzikiewicz & Igor Maciejewski & Tomasz Krzyżyński & Andrzej Krzyszkowski & Anna Stelmach, 2022. "Electric Drive Solution for Low-Floor City Transport Trams," Energies, MDPI, vol. 15(13), pages 1-18, June.
    19. Chaoying Xia & Xiaoxin Hou & Feng Chen, 2018. "Flux-Angle-Difference Feedback Control for the Brushless Doubly Fed Machine," Energies, MDPI, vol. 11(1), pages 1-16, January.
    20. Farya Golesorkhie & Fuwen Yang & Ljubo Vlacic & Geoff Tansley, 2020. "Field Oriented Control-Based Reduction of the Vibration and Power Consumption of a Blood Pump," Energies, MDPI, vol. 13(15), pages 1-18, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:11:y:2018:i:7:p:1793-:d:156872. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.