Health prognostics for lithium-ion batteries: mechanisms, methods, and prospects

Y Che, X Hu, X Lin, J Guo, R Teodorescu - Energy & Environmental …, 2023 - pubs.rsc.org
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 …

A comprehensive review of lithium-ion batteries modeling, and state of health and remaining useful lifetime prediction

M Elmahallawy, T Elfouly, A Alouani… - Ieee …, 2022 - ieeexplore.ieee.org
According to the United States environmental protection agency (EPA), every burned gallon
of gasoline generates 8.87 Kg of CO2. The pollution created by vehicles' fuel consumption …

A deep feature learning method for remaining useful life prediction of drilling pumps

J Guo, JL Wan, Y Yang, L Dai, A Tang, B Huang… - Energy, 2023 - Elsevier
Abstract Remaining Useful Life (RUL) prediction of drilling pumps, pivotal components in
fossil energy production, is essential for efficient maintenance and safe operation of such …

Data efficient health prognostic for batteries based on sequential information-driven probabilistic neural network

Y Che, Y Zheng, Y Wu, X Sui, P Bharadwaj, DI Stroe… - Applied Energy, 2022 - Elsevier
Accurate and reliable prediction of the battery capacity degradation is vital for predictive
health management. This paper proposes a novel framework to improve the accuracy and …

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 …

[HTML][HTML] Review of “grey box” lifetime modeling for lithium-ion battery: Combining physics and data-driven methods

W Guo, Z Sun, SB Vilsen, J Meng, DI Stroe - Journal of Energy Storage, 2022 - Elsevier
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 …

Augmented model-based framework for battery remaining useful life prediction

A Thelen, M Li, C Hu, E Bekyarova, S Kalinin… - Applied Energy, 2022 - Elsevier
Traditional, model-based approaches for predicting the remaining useful life (RUL) of a
rechargeable battery cell simply update and extrapolate a mathematical model which …

A Review of Expert Hybrid and Co-Estimation Techniques for SOH and RUL Estimation in Battery Management System with Electric Vehicle Application

T Alsuwian, S Ansari, MAAM Zainuri, A Ayob… - Expert Systems with …, 2024 - Elsevier
To improve the functionality and efficiency of electric vehicles (EVs), the smart battery
management system (BMS) is essential. The accurate estimation of the state of health (SOH) …

Artificial intelligence-based data-driven prognostics in industry: A survey

MA El-Brawany, DA Ibrahim, HK Elminir… - Computers & Industrial …, 2023 - Elsevier
In the age of Industry 5.0, prognostics and health management (PHM) is very important for
proactive and scheduled maintenance in industrial processes. The target of prognosis is the …

Parallel state fusion LSTM-based early-cycle stage lithium-ion battery RUL prediction under Lebesgue sampling framework

G Lyu, H Zhang, Q Miao - Reliability Engineering & System Safety, 2023 - Elsevier
Remaining useful life (RUL) prediction for lithium-ion batteries in early-cycle stage is of great
significance for improving battery performance and reducing losses caused by accidental …