IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i2p189-d89741.html
   My bibliography  Save this article

On-Line Junction Temperature Monitoring of Switching Devices with Dynamic Compact Thermal Models Extracted with Model Order Reduction

Author

Listed:
  • Fabio Di Napoli

    (Department of Electrical Engineering and Information Technology, University Federico II, via Claudio 21, 80125 Naples, Italy)

  • Alessandro Magnani

    (Department of Electrical Engineering and Information Technology, University Federico II, via Claudio 21, 80125 Naples, Italy)

  • Marino Coppola

    (Department of Electrical Engineering and Information Technology, University Federico II, via Claudio 21, 80125 Naples, Italy)

  • Pierluigi Guerriero

    (Department of Electrical Engineering and Information Technology, University Federico II, via Claudio 21, 80125 Naples, Italy)

  • Vincenzo D’Alessandro

    (Department of Electrical Engineering and Information Technology, University Federico II, via Claudio 21, 80125 Naples, Italy)

  • Lorenzo Codecasa

    (Department of Electronics, Information, and Bioengineering, Politecnico di Milano, 20133 Milan, Italy)

  • Pietro Tricoli

    (School of Electronic, Electrical and Systems Engineering, University of Birmingham, Birmingham B15 2TT, UK)

  • Santolo Daliento

    (Department of Electrical Engineering and Information Technology, University Federico II, via Claudio 21, 80125 Naples, Italy)

Abstract

Residual lifetime estimation has gained a key point among the techniques that improve the reliability and the efficiency of power converters. The main cause of failures are the junction temperature cycles exhibited by switching devices during their normal operation; therefore, reliable power converter lifetime estimation requires the knowledge of the junction temperature time profile. Since on-line dynamic temperature measurements are extremely difficult, in this work an innovative real-time monitoring strategy is proposed, which is capable of estimating the junction temperature profile from the measurement of the dissipated powers through an accurate and compact thermal model of the whole power module. The equations of this model can be easily implemented inside a FPGA, exploiting the control architecture already present in modern power converters. Experimental results on an IGBT power module demonstrate the reliability of the proposed method.

Suggested Citation

  • Fabio Di Napoli & Alessandro Magnani & Marino Coppola & Pierluigi Guerriero & Vincenzo D’Alessandro & Lorenzo Codecasa & Pietro Tricoli & Santolo Daliento, 2017. "On-Line Junction Temperature Monitoring of Switching Devices with Dynamic Compact Thermal Models Extracted with Model Order Reduction," Energies, MDPI, vol. 10(2), pages 1-14, February.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:2:p:189-:d:89741
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/2/189/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/10/2/189/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. d'Alessandro, Vincenzo & Di Napoli, Fabio & Guerriero, Pierluigi & Daliento, Santolo, 2015. "An automated high-granularity tool for a fast evaluation of the yield of PV plants accounting for shading effects," Renewable Energy, Elsevier, vol. 83(C), pages 294-304.
    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. Issam A. Smadi & Saher Albatran & Hamzeh J. Ahmad, 2018. "On the Performance Optimization of Two-Level Three-Phase Grid-Feeding Voltage-Source Inverters," Energies, MDPI, vol. 11(2), pages 1-17, February.
    2. Krzysztof Górecki, 2021. "Influence of the Semiconductor Devices Cooling Conditions on Characteristics of Selected DC–DC Converters," Energies, MDPI, vol. 14(6), pages 1-16, March.
    3. Adrian Plesca, 2019. "Thermal Analysis of Power Semiconductor Device in Steady-State Conditions," Energies, MDPI, vol. 13(1), pages 1-18, December.
    4. Michał Szulborski & Sebastian Łapczyński & Łukasz Kolimas & Daniel Zalewski, 2021. "Transient Thermal Analysis of the Circuit Breaker Current Path with the Use of FEA Simulation," Energies, MDPI, vol. 14(9), pages 1-24, April.
    5. Michał Szulborski & Sebastian Łapczyński & Łukasz Kolimas & Łukasz Kozarek & Desire Dauphin Rasolomampionona & Tomasz Żelaziński & Adam Smolarczyk, 2021. "Transient Thermal Analysis of NH000 gG 100A Fuse Link Employing Finite Element Method," Energies, MDPI, vol. 14(5), pages 1-18, March.
    6. Michał Szulborski & Sebastian Łapczyński & Łukasz Kolimas, 2021. "Thermal Analysis of Heat Distribution in Busbars during Rated Current Flow in Low-Voltage Industrial Switchgear," Energies, MDPI, vol. 14(9), pages 1-23, April.

    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. Jayesh Thaker & Robert Höller, 2022. "A Comparative Study of Time Series Forecasting of Solar Energy Based on Irradiance Classification," Energies, MDPI, vol. 15(8), pages 1-26, April.
    2. Alonso Gutiérrez Galeano & Michael Bressan & Fernando Jiménez Vargas & Corinne Alonso, 2018. "Shading Ratio Impact on Photovoltaic Modules and Correlation with Shading Patterns," Energies, MDPI, vol. 11(4), pages 1-26, April.
    3. Rico Espinosa, Alejandro & Bressan, Michael & Giraldo, Luis Felipe, 2020. "Failure signature classification in solar photovoltaic plants using RGB images and convolutional neural networks," Renewable Energy, Elsevier, vol. 162(C), pages 249-256.
    4. Bressan, M. & Gutierrez, A. & Garcia Gutierrez, L. & Alonso, C., 2018. "Development of a real-time hot-spot prevention using an emulator of partially shaded PV systems," Renewable Energy, Elsevier, vol. 127(C), pages 334-343.
    5. Arias-Rosales, Andrés & LeDuc, Philip R., 2020. "Comparing View Factor modeling frameworks for the estimation of incident solar energy," Applied Energy, Elsevier, vol. 277(C).
    6. Gonçalves, Juliana E. & van Hooff, Twan & Saelens, Dirk, 2021. "Simulating building integrated photovoltaic facades: Comparison to experimental data and evaluation of modelling complexity," Applied Energy, Elsevier, vol. 281(C).
    7. Alfredo Nespoli & Emanuele Ogliari & Sonia Leva & Alessandro Massi Pavan & Adel Mellit & Vanni Lughi & Alberto Dolara, 2019. "Day-Ahead Photovoltaic Forecasting: A Comparison of the Most Effective Techniques," Energies, MDPI, vol. 12(9), pages 1-15, April.
    8. Rehman, Naveed ur & Uzair, Muhammad & Allauddin, Usman, 2020. "An optical-energy model for optimizing the geometrical layout of solar photovoltaic arrays in a constrained field," Renewable Energy, Elsevier, vol. 149(C), pages 55-65.
    9. Rehman, Naveed ur & Uzair, Muhammad, 2020. "Optimizing the inclined field for solar photovoltaic arrays," Renewable Energy, Elsevier, vol. 153(C), pages 280-289.

    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:10:y:2017:i:2:p:189-:d:89741. 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.