Remaining Useful Life Prediction of Power MOSFETs Using Model-Based and Data-Driven Methods

Prognostics and health management has become an advanced engineering technology in avionics systems which can implement condition monitoring and reduce unnecessary downtime. A prognostic application to power MOSFETs is developed in this paper. Firstly, failure mechanism of the power MOSFETs under power cycling aging tests is analyzed. Then, the drain-source on-state resistance is considered as a leading precursor of failure as it exhibits a decaying trend. Finally, a degradation model is established to predict the remaining useful life based on Kalman filter and LS-SVM, respectively. Several results are analyzed to demonstrate the feasibility and effectiveness of these methods.