Chang-Ying Liu

Physics-Informed Transfer Learning for Cross-Condition State of Health Prediction of Lithium-Ion Batteries

Estimating lithium-ion battery state of health (SOH) across operating conditions is challenging because operating profiles, measurement characteristics, and degradation trajectories differ among domains. This study proposes a physics-informed transfer learning (PITL) framework that combines a common health descriptor s...