AI RESEARCH
BatteryMFormer: Multi-level Learning for Battery Degradation Trajectory Forecasting
arXiv CS.AI
•
ArXi:2605.27044v1 Announce Type: new Early battery degradation trajectory forecasting (BDTF), which predicts the full-life state-of-health trajectory from early operational data, is critical for battery optimization, manufacturing, and deployment. Battery degradation data exhibit two key characteristics. First, degradation data present a multi-level structure, including regularities shared within aging conditions and trajectory patterns shared across batteries. Second, degradation-related variations in voltage-current profiles are often localized to specific state-of-charge (SOC) intervals.