battery health estimation 1contextual learning 1interpretability 1symbolic distillation 1trustworthy AI 1
From the 1 of 2 linked papers with an AI index.
2 papers
cs.LG2026
TIDE: Trustworthy and Interpretable Battery Degradation Estimation with Contextual Learning and Symbolic Distillation
Wen Yang Tan, Jiawei Li, Fang Liu +4
The paper introduces TIDE, a machine‑learning system that combines battery domain knowledge with operational data to estimate battery health accurately while providing trustworthy…
eess.SP2026
Interpretable Battery Aging without Extra Tests via Neural-Assisted Physics-based Modelling
Yuan Qiu, Wei Li, Wei Zhang +4
State of health (SoH) is widely used for battery management, but it is a single scalar and offers limited interpretability. Two batteries with similar SoH can exhibit very differen…