A Physics-Informed Bayesian Deep Learning Framework for Explainable and Probabilistic Lithium-Ion Battery Health Prognostics
To ensure the safety and efficiency of battery-powered applications, it is essential to accurately estimate the State of Health (SOH) and Remaining Useful Life (RUL) of the batteries. Although physics-based models are available to represent the degradation of the batteries, these models may have difficulties modeling t...