Machine learning in state of health and remaining useful life estimation: Theoretical and technological development in battery degradation modelling

H Rauf, M Khalid, N Arshad - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
Designing and deployment of state-of-the-art electric vehicles (EVs) in terms of low cost and
high driving range with appropriate reliability and security are identified as the key towards …

[HTML][HTML] A review of machine learning state-of-charge and state-of-health estimation algorithms for lithium-ion batteries

Z Ren, C Du - Energy Reports, 2023 - Elsevier
Vehicle electrification has been proven to be an efficient way to reduce carbon dioxide
emissions and solve the energy crisis. Lithium-ion batteries (LiBs) are considered 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 …

Remaining useful life assessment for lithium-ion batteries using CNN-LSTM-DNN hybrid method

B Zraibi, C Okar, H Chaoui… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The prediction of a Lithium-ion battery's lifetime is very important for ensuring safety and
reliability. In addition, it is utilized as an early warning system to prevent the battery's failure …

A comprehensive review of available battery datasets, RUL prediction approaches, and advanced battery management

SA Hasib, S Islam, RK Chakrabortty, MJ Ryan… - Ieee …, 2021 - ieeexplore.ieee.org
Battery ensures power solutions for many necessary portable devices such as electric
vehicles, mobiles, and laptops. Owing to the rapid growth of Li-ion battery users, unwanted …

Battery management strategies: An essential review for battery state of health monitoring techniques

SK Pradhan, B Chakraborty - Journal of energy storage, 2022 - Elsevier
To prevent probable battery failures and ensure safety, battery state of health evaluation is a
critical step. This study lays out a coherent literature review on battery health estimation …

Review on technological advancement of lithium-ion battery states estimation methods for electric vehicle applications

P Shrivastava, PA Naidu, S Sharma… - Journal of Energy …, 2023 - Elsevier
Due to the dynamic and non-linear behavior of lithium-ion battery (LIB) states, the accuracy
of state estimation proportionally impacts the performance of the battery management …

Aging mechanisms, prognostics and management for lithium-ion batteries: Recent advances

Y Wang, H Xiang, YY Soo, X Fan - Renewable and Sustainable Energy …, 2025 - Elsevier
In the rapidly evolving landscape of energy storage, lithium-ion batteries stand at the
forefront, powering a vast array of devices from mobile phones to electric vehicles and …

Online remaining useful life prediction of lithium-ion batteries using bidirectional long short-term memory with attention mechanism

FK Wang, ZE Amogne, JH Chou, C Tseng - Energy, 2022 - Elsevier
As battery management systems are widely used in industrial applications, it is important to
accurately predict the online remaining useful life (RUL) of batteries. Due to side reactions …

Towards machine-learning driven prognostics and health management of Li-ion batteries. A comprehensive review

S Khaleghi, MS Hosen, J Van Mierlo… - … and Sustainable Energy …, 2024 - Elsevier
Prognostics and health management (PHM) has emerged as a vital research discipline for
optimizing the maintenance of operating systems by detecting health degradation and …