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 …

A review on state of health estimations and remaining useful life prognostics of lithium-ion batteries

MF Ge, Y Liu, X Jiang, J Liu - Measurement, 2021 - Elsevier
Lithium-ion batteries have been generally used in industrial applications. In order to ensure
the safety of the power system and reduce the operation cost, it is particularly important to …

Transformer network for remaining useful life prediction of lithium-ion batteries

D Chen, W Hong, X Zhou - Ieee Access, 2022 - ieeexplore.ieee.org
Accurately predicting the Remaining Useful Life (RUL) of a Li-ion battery plays an important
role in managing the health and estimating the state of a battery. With the rapid development …

A review of the state of health for lithium-ion batteries: Research status and suggestions

H Tian, P Qin, K Li, Z Zhao - Journal of Cleaner Production, 2020 - Elsevier
Lithium-ion batteries (LIBs) have become the mainstream power source for battery electric
vehicles (BEVs) with relatively superior performance. However, LIBs experience battery …

[HTML][HTML] Nonlinear health evaluation for lithium-ion battery within full-lifespan

H You, J Zhu, X Wang, B Jiang, H Sun, X Liu… - Journal of Energy …, 2022 - Elsevier
Abstract Lithium-ion batteries (LIBs), as the first choice for green batteries, have been widely
used in energy storage, electric vehicles, 3C devices, and other related fields, and will have …

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 …

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 …

Remaining useful life estimation for prognostics of lithium-ion batteries based on recurrent neural network

M Catelani, L Ciani, R Fantacci… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Prognostic and condition-based maintenance of lithium-ion batteries is a fundamental topic,
which is rapidly expanding since a long battery lifetime is required to ensure economic …

[HTML][HTML] Degradation of lithium-ion batteries in an electric transport complex

NI Shchurov, SI Dedov, BV Malozyomov, AA Shtang… - Energies, 2021 - mdpi.com
The article provides an overview and comparative analysis of various types of batteries,
including the most modern type—lithium-ion batteries. Currently, lithium-ion batteries (LIB) …

Forecasting state-of-health of lithium-ion batteries using variational long short-term memory with transfer learning

S Kim, YY Choi, KJ Kim, JI Choi - Journal of Energy Storage, 2021 - Elsevier
Accurate forecasting of state-of-health and remaining useful life of Li-ion batteries ensure
their safe and reliable operation. Most previous data-driven prediction methods assume the …