Interpretable Multi-Feature Fusion for Lithium-Ion Battery State-of-Health Prediction Using ICEEMDAN-Autoformer-BiTCN
Accurate state-of-health (SOH) prediction is essential for the safe and cost-effective operation of lithium-ion battery systems. However, current data-driven methods still struggle to jointly extract multiscale degradation information, capture long-range dependencies, fuse heterogeneous health indicators, and provide t...