Open access
Oct 2026
A Probabilistic Data-Driven Ensemble Approach for Battery Remaining Useful Life (RUL) Prognostics
This study proposes a probabilistic data-driven ensemble framework for the remaining useful life (RUL) prognostics of lithium-ion batteries. This work addresses the limitations of single-model and deterministic methods by integrating Bayesian neural networks (BNNs), LSTM/Transformer architectures, Wiener process–based...
Guo-Zhu Zhi, Fahad Abul Kalam, Zhen-Bao Liu et al.
· Batteries · 0 citations