arXiv:2609.22843v1 Announce Type: cross
Abstract: Accurate and timely detection of degradation in lithium-ion batteries is crucial to ensure safety, reliability, and longevity in high-demand applicat...
By Amir Madmolilvand, Farzaneh Abdollahi
Accurate and timely detection of degradation in lithium-ion batteries is crucial to ensure safety, reliability, and longevity in high-demand applications such as electric vehicles and energy storage s...
The paper introduces Relative Discharge Stage (RDS), a battery‑management indicator that classifies remaining discharge condition into five interpretable classes—Normal, Good, Moderate, Low, and Recharge Required—without needing future load information. It combines physics‑based SOC estimation with a lightweight temporal convolutional network that processes measured current, voltage, temperature, and SOC over a sliding window. Experiments on two public lithium‑ion datasets show RDS classification accuracy above 80% across varied load and thermal conditions.
By Khoa Tran, Tri Le, Hung-Cuong Trinh, Hung Tran-Nam
Accurate remaining discharge time (RDT) prediction is challenging in real-world battery applications because future load profiles are unknown and highly dynamic. To address the uncertainty of continuo...
Laboratory battery tests provide the main empirical basis for battery performance and degradation studies, but their operating patterns do not directly represent field duty profiles. This paper quantifies the gap by comparing six accessible evidence sources covering controlled cycling, drive-cycle testing, dynamic cycling, NMC811 laboratory ageing, a real electric-vehicle charging trace, and fleet-scale electric-vehicle state-of-health (SOH) data.
arXiv:2608. 16212v1 Announce Type: new Abstract: Laboratory battery tests provide the main empirical basis for battery performance and degradation studies, but their operating patterns do not directly represent field duty profiles.
By Chunyang Zhao, Chresten Tr{\ae}holt