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Applications of artificial neural network based battery management systems: A literature review
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 …
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
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 …
become one of the most important energy storage sources for many applications. Battery …
Semi-supervised learning for explainable few-shot battery lifetime prediction
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 …
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 …
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
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 …
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
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 …
management. However, poor generalization, lack of labeled data, and unused …
Electric vehicle battery capacity degradation and health estimation using machine-learning techniques: A review
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 …
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 …
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
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 …
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
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 …
towards achieving energy saving and emission reduction in the transportation sector. The …