A review of SOH prediction of Li-ion batteries based on data-driven algorithms

M Zhang, D Yang, J Du, H Sun, L Li, L Wang, K Wang - Energies, 2023 - mdpi.com
As an important energy storage device, lithium-ion batteries (LIBs) have been widely used in
various fields due to their remarkable advantages. The high level of precision in estimating …

Artificial Neural Networks, Gradient Boosting and Support Vector Machines for electric vehicle battery state estimation: A review

A Manoharan, KM Begam, VR Aparow… - Journal of Energy …, 2022 - Elsevier
Abstract In recent years, Artificial Intelligence has been widely used for determining the
current state of Li-ion batteries used for Electric Vehicle applications. It is crucial to have an …

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 …

Machine learning applied to electrified vehicle battery state of charge and state of health estimation: State-of-the-art

C Vidal, P Malysz, P Kollmeyer, A Emadi - Ieee Access, 2020 - ieeexplore.ieee.org
The growing interest and recent breakthroughs in artificial intelligence and machine learning
(ML) have actively contributed to an increase in research and development of new methods …

Advancements and challenges in machine learning: A comprehensive review of models, libraries, applications, and algorithms

S Tufail, H Riggs, M Tariq, AI Sarwat - Electronics, 2023 - mdpi.com
In the current world of the Internet of Things, cyberspace, mobile devices, businesses, social
media platforms, healthcare systems, etc., there is a lot of data online today. Machine …

Online estimations of Li-ion battery SOC and SOH applicable to partial charge/discharge

A Bavand, SA Khajehoddin… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Estimating the state of health (SOH) and state of charge (SOC) of lithium-ion batteries is
crucial for increasing the battery lifetime and performance. Many estimation methods are …

An adaptive data-driven approach for two-timescale dynamics prediction and remaining useful life estimation of Li-ion batteries

B Bhadriraju, JSI Kwon, F Khan - Computers & Chemical Engineering, 2023 - Elsevier
During the multi-cycle operation of a Li-ion battery, its process dynamics evolve in two
distinct timescales: slow degradation dynamics over multiple cycles and fast cycling …

Improvement of marine steam turbine conventional exergy analysis by neural network application

S Baressi Šegota, I Lorencin, N Anđelić… - Journal of Marine …, 2020 - mdpi.com
This article presented an improvement of marine steam turbine conventional exergy analysis
by application of neural networks. The conventional exergy analysis requires numerous …

Remaining useful life prediction of lithium-ion batteries by using a denoising transformer-based neural network

Y Han, C Li, L Zheng, G Lei, L Li - Energies, 2023 - mdpi.com
In this study, we introduce a novel denoising transformer-based neural network (DTNN)
model for predicting the remaining useful life (RUL) of lithium-ion batteries. The proposed …

[HTML][HTML] Investigation of the performance of direct forecasting strategy using machine learning in State-of-Charge prediction of Li-ion batteries exposed to dynamic …

A Dineva, B Csomós, SK Sz, I Vajda - Journal of Energy Storage, 2021 - Elsevier
On account of intense technological advances regarding Electric Vehicles, the state
evaluation and prediction issues of Li-ion cells have become increasingly important for …