IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i5p1822-d761991.html
   My bibliography  Save this article

Influence of the Placement Accuracy of the Brushless DC Motor Hall Sensor on Inverter Transistor Losses

Author

Listed:
  • Krzysztof Kolano

    (Department of Electrical Drives and Machines, Lublin University of Technology, Nadbystrzycka 38a, 20-618 Lublin, Poland)

  • Artur Jan Moradewicz

    (The Łukasiewicz Research Network-Institute of Electrical Engineering—Headquater Mieczysława Pożaryskiego St. 28, 04-703 Warsaw, Poland)

  • Bartosz Drzymała

    (Department of Electrical Drives and Machines, Lublin University of Technology, Nadbystrzycka 38a, 20-618 Lublin, Poland)

  • Jakub Gęca

    (Doctoral School, Lublin University of Technology, Nadbystrzycka 38a, 20-618 Lublin, Poland)

Abstract

Low-power BLDC motors are often and willingly used in many drive devices due to their functional advantages. They are also used in advanced positioning systems, where their good dynamic performance parameters are used. The control systems use shaft position sensors mounted on motors, the structure of which is based on magnetic elements and Hall sensors. The aim of this article was to investigate the influence of the BLDC motor quality on the correct operation of the control semiconductor system. The article presents the effect of BLDC motor shaft observation system’s inaccuracies on the friction and current amplitudes of individual inverter keys. Waveforms of the controller phase currents are considered and recorded on a test bench that allows precise sensor position changes. In addition, the effect of sensor misalignment on power losses in individual inverter transistors is investigated. The article shows a significant influence of the motor shaft observation system’s assembly accuracy on the current amplitudes of individual driver transistors and their power losses, which makes it necessary to consider these parameters when constructing power electronic systems.

Suggested Citation

  • Krzysztof Kolano & Artur Jan Moradewicz & Bartosz Drzymała & Jakub Gęca, 2022. "Influence of the Placement Accuracy of the Brushless DC Motor Hall Sensor on Inverter Transistor Losses," Energies, MDPI, vol. 15(5), pages 1-13, March.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:5:p:1822-:d:761991
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/5/1822/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/5/1822/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Krzysztof Kolano & Bartosz Drzymała & Jakub Gęca, 2021. "Sinusoidal Control of a Brushless DC Motor with Misalignment of Hall Sensors," Energies, MDPI, vol. 14(13), pages 1-13, June.
    2. Ho-Jin Kim & Hyung-Seok Park & Jang-Mok Kim, 2020. "Expansion of Operating Speed Range of High-Speed BLDC Motor Using Hybrid PWM Switching Method Considering Dead Time," Energies, MDPI, vol. 13(19), pages 1-13, October.
    3. Krzysztof Kolano, 2020. "Determining the Position of the Brushless DC Motor Rotor," Energies, MDPI, vol. 13(7), pages 1-9, April.
    4. Karolina Kudelina & Bilal Asad & Toomas Vaimann & Anton Rassõlkin & Ants Kallaste & Huynh Van Khang, 2021. "Methods of Condition Monitoring and Fault Detection for Electrical Machines," Energies, MDPI, vol. 14(22), pages 1-20, November.
    Full references (including those not matched with items on IDEAS)

    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. Vadim Carev & Jan Roháč & Martin Šipoš & Michal Schmirler, 2021. "A Multilayer Brushless DC Motor for Heavy Lift Drones," Energies, MDPI, vol. 14(9), pages 1-19, April.
    2. Krzysztof Kolano & Bartosz Drzymała & Jakub Gęca, 2021. "Sinusoidal Control of a Brushless DC Motor with Misalignment of Hall Sensors," Energies, MDPI, vol. 14(13), pages 1-13, June.
    3. Tong Wu & Jing Li & Xuan Qin, 2021. "Braking performance oriented multi–objective optimal design of electro–mechanical brake parameters," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-31, May.
    4. Toomas Vaimann & Jose Alfonso Antonino-Daviu & Anton Rassõlkin, 2023. "Novel Approaches to Electrical Machine Fault Diagnosis," Energies, MDPI, vol. 16(15), pages 1-4, July.
    5. Viktor Rjabtšikov & Anton Rassõlkin & Karolina Kudelina & Ants Kallaste & Toomas Vaimann, 2023. "Review of Electric Vehicle Testing Procedures for Digital Twin Development: A Comprehensive Analysis," Energies, MDPI, vol. 16(19), pages 1-17, October.
    6. Jose R. Huerta-Rosales & David Granados-Lieberman & Juan P. Amezquita-Sanchez & Arturo Garcia-Perez & Maximiliano Bueno-Lopez & Martin Valtierra-Rodriguez, 2022. "Contrast Estimation in Vibroacoustic Signals for Diagnosing Early Faults of Short-Circuited Turns in Transformers under Different Load Conditions," Energies, MDPI, vol. 15(22), pages 1-15, November.
    7. Sebastian Berhausen & Tomasz Jarek, 2022. "Analysis of Impact of Design Solutions of an Electric Machine with Permanent Magnets for Bearing Voltages with Inverter Power Supply," Energies, MDPI, vol. 15(12), pages 1-19, June.
    8. Mikko Tahkola & Áron Szücs & Jari Halme & Akhtar Zeb & Janne Keränen, 2022. "A Novel Machine Learning-Based Approach for Induction Machine Fault Classifier Development—A Broken Rotor Bar Case Study," Energies, MDPI, vol. 15(9), pages 1-23, May.
    9. Hadi Ashraf Raja & Karolina Kudelina & Bilal Asad & Toomas Vaimann & Ants Kallaste & Anton Rassõlkin & Huynh Van Khang, 2022. "Signal Spectrum-Based Machine Learning Approach for Fault Prediction and Maintenance of Electrical Machines," Energies, MDPI, vol. 15(24), pages 1-16, December.
    10. Ying Zhou & Zuyu Wu & Yutong Wu, 2021. "Intelligent Permanent Magnet Motor-Based Servo Drive System Used for Automated Tuning of Piano," Energies, MDPI, vol. 14(20), pages 1-23, October.
    11. Hoffstaedt, J.P. & Truijen, D.P.K. & Fahlbeck, J. & Gans, L.H.A. & Qudaih, M. & Laguna, A.J. & De Kooning, J.D.M. & Stockman, K. & Nilsson, H. & Storli, P.-T. & Engel, B. & Marence, M. & Bricker, J.D., 2022. "Low-head pumped hydro storage: A review of applicable technologies for design, grid integration, control and modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    12. Ahmed Belkhadir & Remus Pusca & Driss Belkhayat & Raphaël Romary & Youssef Zidani, 2023. "Analytical Modeling, Analysis and Diagnosis of External Rotor PMSM with Stator Winding Unbalance Fault," Energies, MDPI, vol. 16(7), pages 1-23, April.
    13. Muhammad Usman Sardar & Toomas Vaimann & Lauri Kütt & Ants Kallaste & Bilal Asad & Siddique Akbar & Karolina Kudelina, 2023. "Inverter-Fed Motor Drive System: A Systematic Analysis of Condition Monitoring and Practical Diagnostic Techniques," Energies, MDPI, vol. 16(15), pages 1-41, 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:15:y:2022:i:5:p:1822-:d:761991. 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.