5 papers
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)…
Knowledge-Aware Modeling with Frequency Adaptive Learning for Battery Health Prognostics
Vijay Babu Pamshetti, Wei Zhang, Sumei Sun +3
Battery health prognostics are critical for ensuring safety, efficiency, and sustainability in modern energy systems. However, it has been challenging to achieve accurate and robus…
Optimal Signal Decomposition-based Multi-Stage Learning for Battery Health Estimation
Vijay Babu Pamshetti, Wei Zhang, King Jet Tseng +2
Battery health estimation is fundamental to ensure battery safety and reduce cost. However, achieving accurate estimation has been challenging due to the batteries' complex nonline…
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…