5 papers
PhyMamba: Physics-Modulated Mamba for Robust Battery Health Prognostics
Sara Sameer, Yunyi Zhao, Wei Zhang +4
Battery health prognostics is a core function in battery management systems (BMSs), yet long-horizon health forecasting from BMS signals remains challenging due to operating-condit…
TIDE: Trustworthy and Interpretable Battery Degradation Estimation with Contextual Learning and Symbolic Distillation
Wen Yang Tan, Jiawei Li, Fang Liu +4
Battery health estimation is fundamental for battery management in battery-powered systems, where inaccurate health states may affect control, maintenance, and service life. It bec…
Pace: Physics-Aware Attentive Temporal Convolutional Network for Battery Health Estimation
Sara Sameer, Wei Zhang, Dhivya Dharshini Kannan +4
Batteries are critical components in modern energy systems such as electric vehicles and power grid energy storage. Effective battery health management is essential for battery sys…
EntroLnn: Entropy-Guided Liquid Neural Networks for Operando Refinement of Battery Capacity Fade Trajectories
Wei Li, Wei Zhang, Qingyu Yan
Battery capacity degradation prediction has long been a central topic in battery health analytics, and most studies focus on state of health (SoH) estimation and end of life (EoL)…
GiNet: Integrating Sequential and Context-Aware Learning for Battery Capacity Prediction
Sara Sameer, Wei Zhang, Xin Lou +3
The surging demand for batteries requires advanced battery management systems, where battery capacity modelling is a key functionality. In this paper, we aim to achieve accurate ba…