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SiC MOSFET Junction Temperature Estimation based on
the Principal Component Regression Model


Mr. Jinghan Lin (M.Phil. candidate)

Department of Mechanical Engineering

The University of Hong Kong

Date & Time

Wednesday, 29 March 2023

2:00 am


Room 7-34, Haking Wong Building, HKU


The junction temperature estimation enables online health management and performance optimisation of SiC power modules. A multitude of temperature sensitive electrical parameters (TSEPs) is gaining increased attention due to their non-invasive nature for online measurements, but they are conventionally focused on certain individual TSEPs, which lack accuracy and robustness given the dynamic variations of operational conditions. This work proposed a fusion method by combining theprincipal component analysis (PCA) and multiple linear regression (MLR) to estimate the junction temperature from a TSEP data set. The presented fusion method predicts temperature with better accuracy and higher noise immunisation compared with the single TSEP estimation method.

Research Areas:

Contact for


Dr. P. Lu

+(852) 3910 2548

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