3 papers
eess.SP2025
Chemistry-aware battery degradation prediction under simulated real-world cyclic protocols
Yuqi Li, Han Zhang, Xiaofan Gui +10
Battery degradation is governed by complex and randomized cyclic conditions, yet existing modeling and prediction frameworks usually rely on rigid, unchanging protocols that fail t…
eess.SP2023
Accurate battery lifetime prediction across diverse aging conditions with deep learning
Han Zhang, Yuqi Li, Shun Zheng +4
Accurately predicting the lifetime of battery cells in early cycles holds tremendous value for battery research and development as well as numerous downstream applications. This ta…
cs.LG2023
BatteryML:An Open-source platform for Machine Learning on Battery Degradation
Han Zhang, Xiaofan Gui, Shun Zheng +3
Battery degradation remains a pivotal concern in the energy storage domain, with machine learning emerging as a potent tool to drive forward insights and solutions. However, this i…