arXiv:2607. 18860v1 Announce Type: cross Abstract: Thermal runaway in lithium-ion batteries poses a major safety risk to electric vehicles and energy storage systems.
By Syed Sajid Ullah, Muhammad Zunair Zamir, Salman Khan
The paper presents a two‑stage early‑warning system for detecting lithium‑ion battery thermal runaway under mechanical abuse. Stage I estimates localized thermal instability from infrared hotspot dynamics, achieving an ROC‑AUC of 0.945. Stage II fuses this instability score with mechanical, electrical, thermal, and image‑intensity features, reaching an ROC‑AUC of 0.908 and providing a 14.8‑frame mean lead time before voltage‑based detection.
By Syed Sajid Ullah, Salman Khan, Muhammad Zunair Zamir
arXiv:2607. 16864v1 Announce Type: new Abstract: Supercharging of lithium-ion batteries (LiBs) requires robust health monitoring to ensure durability, safety, and user confidence, particularly for emerging vehicle-to-grid applications with bidirectional energy flows.
By Wendi Guo, S{\o}ren Byg Vilsen, Daniel Ioan Stroe, Yaqi Li, Yicun Huang, Ashima Verma, Daniel Brandell
arXiv:2607. 29095v1 Announce Type: new Abstract: Accurate prediction of lithium-ion battery state of health (SOH) is essential for reliable energy storage operation.
By Zeping Chen, Ruda Jian, Sachin Sigdel, Guoping Xiong, Jian-Xun Wang, Tengfei Luo
arXiv:2608. 14764v1 Announce Type: new Abstract: With the increasing integration of renewable energy sources, energy storage systems have become essential, making the accurate estimation of their State of Health (SOH) and degradation behavior critical.
By Bego\~na Ispizua, Serio Gil-L\'opez, Leire Arrizabalaga, Ibai La\~na
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...