Health prognostics for lithium-ion batteries: mechanisms, methods, and prospects
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 …
significance for a smart battery management system to ensure safe and optimal use of the …
[HTML][HTML] The development of machine learning-based remaining useful life prediction for lithium-ion batteries
X Li, D Yu, VS Byg, SD Ioan - Journal of Energy Chemistry, 2023 - Elsevier
Lithium-ion batteries are the most widely used energy storage devices, for which the
accurate prediction of the remaining useful life (RUL) is crucial to their reliable operation and …
accurate prediction of the remaining useful life (RUL) is crucial to their reliable operation and …
Specialized deep neural networks for battery health prognostics: Opportunities and challenges
Lithium-ion batteries are key drivers of the renewable energy revolution, bolstered by
progress in battery design, modelling, and management. Yet, achieving high-performance …
progress in battery design, modelling, and management. Yet, achieving high-performance …
Bayesian deep-learning for RUL prediction: An active learning perspective
Deep learning (DL) has been intensively exploited for remaining useful life (RUL) prediction
in the recent decade. Although with high precision and flexibility, DL methods need sufficient …
in the recent decade. Although with high precision and flexibility, DL methods need sufficient …
Battery prognostics and health management from a machine learning perspective
Transportation electrification is gaining prominence as a significant pathway for reducing
emissions and enhancing environmental sustainability. Central to this shift are lithium-ion …
emissions and enhancing environmental sustainability. Central to this shift are lithium-ion …
[HTML][HTML] Battery safety: Machine learning-based prognostics
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 …
devices to large-scale electrified transportation systems and grid-scale energy storage …
Battery health management using physics-informed machine learning: Online degradation modeling and remaining useful life prediction
Lithium-ion batteries have been extensively used to power portable electronics, electric
vehicles, and unmanned aerial vehicles over the past decade. Aging decreases the capacity …
vehicles, and unmanned aerial vehicles over the past decade. Aging decreases the capacity …
[HTML][HTML] Review of “grey box” lifetime modeling for lithium-ion battery: Combining physics and data-driven methods
Lithium-ion batteries are a popular choice for a wide range of energy storage system
applications. The current motivation to improve the robustness of lithium-ion battery …
applications. The current motivation to improve the robustness of lithium-ion battery …
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 …
depends on the battery's operation during charging, discharging, and rest phases. Mapping …
Prognostics and remaining useful life prediction of machinery: advances, opportunities and challenges
As the fundamental and key technique to ensure the safe and reliable operation of vital
systems, prognostics with an emphasis on the remaining useful life (RUL) prediction has …
systems, prognostics with an emphasis on the remaining useful life (RUL) prediction has …