A comprehensive review of the lithium-ion battery state of health prognosis methods combining aging mechanism analysis

Y Xiao, J Wen, L Yao, J Zheng, Z Fang, Y Shen - Journal of Energy Storage, 2023 - Elsevier
In the field of new energy vehicles, lithium-ion batteries have become an inescapable
energy storage device. However, they still face significant challenges in practical use due to …

Data-driven-aided strategies in battery lifecycle management: prediction, monitoring, and optimization

L Xu, F Wu, R Chen, L Li - Energy Storage Materials, 2023 - Elsevier
Predicting, monitoring, and optimizing the performance and health of a battery system
entails a variety of complex variables as well as unpredictability in given conditions. Data …

“Knees” in lithium-ion battery aging trajectories

PM Attia, A Bills, FB Planella, P Dechent… - Journal of The …, 2022 - iopscience.iop.org
Lithium-ion batteries can last many years but sometimes exhibit rapid, nonlinear
degradation that severely limits battery lifetime. In this work, we review prior work on" knees" …

Improving state-of-health estimation for lithium-ion batteries via unlabeled charging data

C Lin, J Xu, X Mei - Energy Storage Materials, 2023 - Elsevier
The state-of-health (SOH) estimation is an important and open issue in battery health
management. Most existing data driven SOH estimation methods are based on supervised …

Lithium-ion battery lifetime extension: A review of derating methods

H Ruan, JV Barreras, T Engstrom, Y Merla… - Journal of Power …, 2023 - Elsevier
Extending lithium-ion battery lifetime is essential for mainstream uptake of electric vehicles.
However, battery degradation is complex and involves coupling of underpinning …

Battery aging mode identification across NMC compositions and designs using machine learning

BR Chen, CM Walker, S Kim, MR Kunz, TR Tanim… - Joule, 2022 - cell.com
A comprehensive understanding of lithium-ion battery (LiB) lifespan is the key to designing
durable batteries and optimizing use protocols. Although battery lifetime prediction methods …

Li-ion battery degradation modes diagnosis via Convolutional Neural Networks

N Costa, L Sánchez, D Anseán, M Dubarry - Journal of Energy Storage, 2022 - Elsevier
Lithium-ion batteries are ubiquitous in modern society with a presence in storage systems,
electric cars, portable electronics, and many more applications. Consequently, to enable …

Data-driven direct diagnosis of Li-ion batteries connected to photovoltaics

M Dubarry, N Costa, D Matthews - Nature communications, 2023 - nature.com
Photovoltaics supply a growing share of power to the electric grid worldwide. To mitigate
resource intermittency issues, these systems are increasingly being paired with …

Developing extreme fast charge battery protocols–A review spanning materials to systems

EJ Dufek, DP Abraham, I Bloom, BR Chen… - Journal of Power …, 2022 - Elsevier
Extreme fast charging (XFC) has become a focal research point in the lithium-battery
community over the last several years. As adoption of electric vehicles increases, fast …

[HTML][HTML] Generalised diagnostic framework for rapid battery degradation quantification with deep learning

H Ruan, J Chen, W Ai, B Wu - Energy and AI, 2022 - Elsevier
Diagnosing lithium-ion battery degradation is challenging due to the complex, nonlinear,
and path-dependent nature of the problem. Here, we develop a generalised and rapid …