Remaining useful life prediction of electric vehicle drive system using physics-informed machine learning methods with uncertainty quantification
An innovative physics-informed machine learning framework for RUL prediction and uncertainty quantification in EVDS is proposed, which effectively integrates physical information with deep learning algorithms, yielding a more concentrated probability density distribution of RUL predictions with higher accuracy, and enh...