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
arXiv:2607. 23482v1 Announce Type: new Abstract: Accurate State-of-Health estimation is essential for safe battery operation and cost-effective maintenance.
By Huy Hoang Le, Kim-Anh Nguyen
arXiv:2608. 14637v1 Announce Type: new Abstract: Long-duration stationary energy storage requires batteries whose degradation can be detected before substantial capacity loss has accumulated.
By Suyang Zhuang, Zekun Jiang, Tianhang Zhou
arXiv:2606. 23725v1 Announce Type: cross Abstract: Machine-learning screens for battery materials are trained and judged almost entirely against computed reference voltages, and those references carry their own systematic errors.
By Krishna Teja Vepa
arXiv:2605. 27044v2 Announce Type: replace Abstract: Early battery degradation trajectory forecasting (BDTF), which predicts the full-life state-of-health trajectory from early operational data, is critical for battery optimization, manufacturing, and deployment.
By Ruifeng Tan, Jintao Dong, Weixiang Hong, Jia Li, Jiaqiang Huang, Tong-Yi Zhang
arXiv:2607. 09762v1 Announce Type: new Abstract: Public battery aging datasets are a critical asset for advanced health management, but their practical use is often limited by inconsistent formats, unclear schemas, and metadata scattered across repositories and publications.
By Tianwen Zhu, Hao Wang, Yonggang Wen