Health prognostics for lithium-ion batteries: mechanisms, methods, and prospects

Y Che, X Hu, X Lin, J Guo, R Teodorescu - Energy & Environmental …, 2023 - pubs.rsc.org
Lithium-ion battery aging mechanism analysis and health prognostics are of great
significance for a smart battery management system to ensure safe and optimal use of the …

Towards long lifetime battery: AI-based manufacturing and management

K Liu, Z Wei, C Zhang, Y Shang… - IEEE/CAA Journal of …, 2022 - ieeexplore.ieee.org
Technologies that accelerate the delivery of reliable battery-based energy storage will not
only contribute to decarbonization such as transportation electrification, smart grid, but also …

A comparative study of different features extracted from electrochemical impedance spectroscopy in state of health estimation for lithium-ion batteries

B Jiang, J Zhu, X Wang, X Wei, W Shang, H Dai - Applied Energy, 2022 - Elsevier
Battery state of health (SOH) estimation is a critical but challenging demand in advanced
battery management technologies. As an essential parameter, battery impedance contains …

[HTML][HTML] Transfer learning for battery smarter state estimation and ageing prognostics: Recent progress, challenges, and prospects

K Liu, Q Peng, Y Che, Y Zheng, K Li… - Advances in Applied …, 2023 - Elsevier
With the advent of sustainable and clean energy transitions, lithium-ion batteries have
become one of the most important energy storage sources for many applications. Battery …

[HTML][HTML] Battery safety: Machine learning-based prognostics

J Zhao, X Feng, Q Pang, M Fowler, Y Lian… - Progress in Energy and …, 2024 - Elsevier
Lithium-ion batteries play a pivotal role in a wide range of applications, from electronic
devices to large-scale electrified transportation systems and grid-scale energy storage …

A review on methods for state of health forecasting of lithium-ion batteries applicable in real-world operational conditions

F von Bülow, T Meisen - Journal of Energy Storage, 2023 - Elsevier
The ageing of Lithium-ion batteries can be described as change of state of health (∆ SOH). It
depends on the battery's operation during charging, discharging, and rest phases. Mapping …

Lithium-ion battery degradation trajectory early prediction with synthetic dataset and deep learning

M Lin, Y You, J Meng, W Wang, J Wu… - Journal of Energy …, 2023 - Elsevier
Knowing the long-term degradation trajectory of Lithium-ion (Li-ion) battery in its early usage
stage is critical for the maintenance of the battery energy storage system (BESS) in reality …

[HTML][HTML] Interpretable machine learning for battery capacities prediction and coating parameters analysis

K Liu, MF Niri, G Apachitei, M Lain… - Control Engineering …, 2022 - Elsevier
Battery manufacturing plays a direct and pivotal role in determining battery performance,
which, in turn, significantly affects the applications of battery-related energy storage systems …

Semi-supervised self-learning-based lifetime prediction for batteries

Y Che, DI Stroe, X Hu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Accurate and reliable degradation and lifetime prediction for lithium-ion batteries is the main
challenge for smart prognostic and health management. This article proposes a novel semi …

Multi-level data-driven battery management: From internal sensing to big data utilization

Z Wei, K Liu, X Liu, Y Li, L Du… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
A battery management system (BMS) is essential for the safety and longevity of lithium-ion
battery (LIB) utilization. With the rapid development of new sensing techniques, artificial …