Transfer Learning for State of Charge Estimation across Batteries and Chemistries: A Lightweight, Physics-Guided LSTM with Regime-Aware Temporal Attention and Staged Adaptation

Transfer Learning for State of Charge Estimation across Batteries and Chemistries: A Lightweight, Physics-Guided LSTM with Regime-Aware Temporal Attention and Staged Adaptation

A cross-battery, cross-chemistry method for state-of-charge (SOC) estimation under domain shift is introduced. The approach employs a lightweight sequence model—two stacked LSTMs with temporal attention—augmented by regime-aware cues and physics-guided regularization. Inputs compri...