A Kalman Filter Method Based on Adaptive Thermal Model for Online Junction Temperature Estimation of SiC MOSFET

Junction temperature (Tj) estimation is critical for the health status and reliable operation of SiC MOSFET. Thermal sensitivity electrical parameter (TSEP) method will affect the accuracy of the estimation results due to the measurement conditions, while thermal model method can cause large deviation in the estimation results due to the aging effect of SiC MOSFET. In this paper, a Kalman filter method based on adaptive thermal model is proposed for online (Tj) estimation of SiC MOSFET. This method proposes the principle of updating the thermal model after device aging, and corrects the model parameter change of SiC MOSFET due to aging in real time by continuously updating the thermal model, and then estimates (Tj) by combining the TSEP method and the Kalman filter finally. The method not only has the advantages of the TSEP method and the thermal model method, but also can monitor the aging of the device, eliminate the estimation errors generated by the measurement process and inaccurate thermal model, and effectively improve the accuracy and reliability of the online (Tj) estimation. The experimental results verify the effectiveness of the proposed method.