IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i3p595-d135334.html
   My bibliography  Save this article

A High-Precision Adaptive Thermal Network Model for Monitoring of Temperature Variations in Insulated Gate Bipolar Transistor (IGBT) Modules

Author

Listed:
  • Ning An

    (Tianjin Key Laboratory of Control Theory & Applications in Complicated System, Tianjin University of Technology, Tianjin 300384, China)

  • Mingxing Du

    (Tianjin Key Laboratory of Control Theory & Applications in Complicated System, Tianjin University of Technology, Tianjin 300384, China)

  • Zhen Hu

    (School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China)

  • Kexin Wei

    (Tianjin Key Laboratory of Control Theory & Applications in Complicated System, Tianjin University of Technology, Tianjin 300384, China)

Abstract

This paper proposes a novel method for optimizing the Cauer-type thermal network model considering both the temperature influence on the extraction of parameters and the errors caused by the physical structure. In terms of prediction of the transient junction temperature and the steady-state junction temperature, the conventional Cauer-type parameters are modified, and the general method for estimating junction temperature is studied by using the adaptive thermal network model. The results show that junction temperature estimated by our adaptive Cauer-type thermal network model is more accurate than that of the conventional model.

Suggested Citation

  • Ning An & Mingxing Du & Zhen Hu & Kexin Wei, 2018. "A High-Precision Adaptive Thermal Network Model for Monitoring of Temperature Variations in Insulated Gate Bipolar Transistor (IGBT) Modules," Energies, MDPI, vol. 11(3), pages 1-16, March.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:3:p:595-:d:135334
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/3/595/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/3/595/
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Khaled Itani & Alexandre De Bernardinis, 2022. "Electrothermal Multicriteria Comparative Analysis of Two Competitive Powertrains Applied to a Two Front Wheel Driven Electric Vehicle during Extreme Regenerative Braking Operations," Energies, MDPI, vol. 15(22), pages 1-27, November.
    2. Cui, Peng & Zhu, Wenbo & Ji, Hongjun & Chen, Hongtao & Hang, Chunjin & Li, Mingyu, 2022. "Analysis and optimization of induction heating processes by focusing the inner magnetism of the coil," Applied Energy, Elsevier, vol. 321(C).

    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:3:p:595-:d:135334. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.