3 papers
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…
cs.LG2026
When Smaller Wins: Dual-Stage Distillation and Pareto-Guided Compression of Liquid Neural Networks for Edge Battery Prognostics
Dhivya Dharshini Kannan, Wei Li, Wei Zhang +3
Battery management systems increasingly require accurate battery health prognostics under strict on-device constraints. This paper presents DLNet, a practical framework with dual-s…
cond-mat.mtrl-sci2022
Machine Learning for a Sustainable Energy Future
Zhenpeng Yao, Yanwei Lum, Andrew Johnston +6
Transitioning from fossil fuels to renewable energy sources is a critical global challenge; it demands advances at the levels of materials, devices, and systems for the efficient h…