Applications of artificial neural network based battery management systems: A literature review

M Kurucan, M Özbaltan, Z Yetgin, A Alkaya - Renewable and Sustainable …, 2024 - Elsevier
Lithium-ion batteries have gained significant prominence in various industries due to their
high energy density compared to other battery technologies. This has led to their …

[HTML][HTML] Transfer learning for battery smarter state estimation and ageing prognostics: Recent progress, challenges, and prospects

K Liu, Q Peng, Y Che, Y Zheng, K Li… - Advances in Applied …, 2023 - Elsevier
With the advent of sustainable and clean energy transitions, lithium-ion batteries have
become one of the most important energy storage sources for many applications. Battery …

Semi-supervised learning for explainable few-shot battery lifetime prediction

N Guo, S Chen, J Tao, Y Liu, J Wan, X Li - Joule, 2024 - cell.com
Accurate prediction of battery lifetime is critical for ensuring timely maintenance and safety of
batteries. Although data-driven methods have made significant progress, their model …

State of health estimation method for lithium-ion batteries based on multiple dynamic operating conditions

Q Yu, Y Nie, S Liu, J Li, A Tang - Journal of Power Sources, 2023 - Elsevier
Lithium-ion battery state of health estimation is an important task for electric vehicles.
However, the uncertainty and complexity of operating conditions pose significant challenges …

[HTML][HTML] Predictive health assessment for lithium-ion batteries with probabilistic degradation prediction and accelerating aging detection

Y Che, Y Zheng, FE Forest, X Sui, X Hu… - Reliability Engineering & …, 2024 - Elsevier
Predictive health assessment is of vital importance for smarter battery management to
ensure optimal and safe operations and thus make the most use of battery life. This paper …

[HTML][HTML] Boosting battery state of health estimation based on self-supervised learning

Y Che, Y Zheng, X Sui, R Teodorescu - Journal of Energy Chemistry, 2023 - Elsevier
State of health (SoH) estimation plays a key role in smart battery health prognostic and
management. However, poor generalization, lack of labeled data, and unused …

Electric vehicle battery capacity degradation and health estimation using machine-learning techniques: A review

K Das, R Kumar - Clean Energy, 2023 - academic.oup.com
Lithium-ion batteries have an essential characteristic in consumer electronics applications
and electric mobility. However, predicting their lifetime performance is a difficult task due to …

Three-dimensional electrochemical-magnetic-thermal coupling model for lithium-ion batteries and its application in battery health monitoring and fault diagnosis

X Bai, D Peng, Y Chen, C Ma, W Qu, S Liu, L Luo - Scientific Reports, 2024 - nature.com
Storage batteries with elevated energy density, superior safety and economic costs
continues to escalate. Batteries can pose safety hazards due to internal short circuits, open …

Optimizing battery RUL prediction of lithium-ion batteries based on Harris hawk optimization approach using random forest and LightGBM

S Jafari, YC Byun - IEEE Access, 2023 - ieeexplore.ieee.org
Predictive Maintenance (PdM) of lithium-ion batteries has garnered significant attention in
recent years due to their widespread application as energy supplies in various industrial …

AI enabled fast charging of lithium-ion batteries of electric vehicles during their life cycle: review, challenges and perspectives

D Sun, D Guo, Y Lu, J Chen, Y Lu, X Han… - Energy & …, 2024 - pubs.rsc.org
Gradually replacing conventional fuel vehicles with electric vehicles (EVs) is a crucial step
towards achieving energy saving and emission reduction in the transportation sector. The …