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High-Frequency Non-Invasive Magnetic Field-Based Condition Monitoring of SiC Power MOSFET Modules

Author

Listed:
  • Javad Naghibi

    (School of Electronics Engineering and Computer Science, Queen Mary University of London, London E1 4NS, UK)

  • Kamyar Mehran

    (School of Electronics Engineering and Computer Science, Queen Mary University of London, London E1 4NS, UK)

  • Martin P. Foster

    (Department of Electronic and Electrical Engineering, The University of Sheffield, Sheffield S10 2TN, UK)

Abstract

Current distribution anomaly can be used to indicate the onset of package-related failures modes in Silicon Carbide power MOSFET modules. In this paper, we propose to obtain the wire bond’s magnetic field profile using an array of Tunnel Magneto-Resistance (TMR) sensors, and characterise the small changes in the current density distribution to find the onset of the wire bond degradation processes, including wire bond lift-off, wire bond cracking, and wire bond fracture. We propose a novel condition monitoring technique where a non-galvanic high-bandwidth sensing and a reliability model monitor the health of the power switches. We designed a dedicated calibration set-up to examine the sensor array and calibrated to demonstrate the adequate sensitivity to a minimum 5% current anomaly detection in a single wire bond of the switching devices operating with 50 kHz switching frequency. We use a hardware-in-the-loop (HIL) experimental set-up to replicate wire bond-related failures in a 1200 V/55 A SiC MOSFET power module of a DC/DC Boost converter. Signal conditioning circuits are further designed to amplify and buffer the sensor readings. Experimental results showed the proposed technique is able to detect a wide range of package-related failures.

Suggested Citation

  • Javad Naghibi & Kamyar Mehran & Martin P. Foster, 2021. "High-Frequency Non-Invasive Magnetic Field-Based Condition Monitoring of SiC Power MOSFET Modules," Energies, MDPI, vol. 14(20), pages 1-18, October.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:20:p:6720-:d:657647
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