SOH early prediction of Lithium-ion batteries based on voltage interval selection and features fusion

S Peng, J Zhu, T Wu, A Tang, J Kan, M Pecht - Energy, 2024 - Elsevier
Accurate state of health (SOH) of batteries is a crucial prerequisite for ensuring the safety
and stable operation of electric vehicles. However, existing conventional prediction methods …

A novel fractional system grey prediction model with dynamic delay effect for evaluating the state of health of lithium battery

S Wang, X **ao, Q Ding - Energy, 2024 - Elsevier
Accurately predicting the state of health (SOH) of lithium batteries is critical to improving the
energy storage technology of batteries. However, most research focuses solely on the …

[HTML][HTML] Accurate and efficient remaining useful life prediction of batteries enabled by physics-informed machine learning

L Ma, J Tian, T Zhang, Q Guo, C Hu - Journal of Energy Chemistry, 2024 - Elsevier
The safe and reliable operation of lithium-ion batteries necessitates the accurate prediction
of remaining useful life (RUL). However, this task is challenging due to the diverse ageing …

SOH estimation of lithium-ion batteries based on multi-feature deep fusion and XGBoost

J Sun, C Fan, H Yan - Energy, 2024 - Elsevier
State of Health (SOH) is a crucial metric for battery management systems, and accurate
estimation of battery SOH is essential for the underlying management and maintenance of …

Comparative analysis of data-driven electric vehicle battery health models across different operating conditions

R Kumar, K Das, A Krishna - Energy, 2024 - Elsevier
The work covers the development of a data-driven algorithm and computes the performance
of learning models for lithium-ion battery state of health (SOH) estimation. A wide range of …

Enhanced multi-constraint dung beetle optimization-kernel extreme learning machine for lithium-ion battery state of health estimation with adaptive enhancement …

D Mo, S Wang, Y Fan, P Takyi-Aninakwa, M Zhang… - Energy, 2024 - Elsevier
Accurately estimating the state of health (SOH) of lithium batteries is a critical and
challenging task in battery management systems. Data-driven models are widely used for …

State of health prediction of lithium-ion batteries using particle swarm optimization with Levy flight and generalized opposition-based learning

B Zhang, W Liu, Y Cai, Z Zhou, L Wang, Q Liao… - Journal of Energy …, 2024 - Elsevier
As an important energy storage device, accurate prediction of the state of health (SOH) in
lithium-ion batteries is necessary to ensure their safe and stable operation. While current …

BMSFormer: An efficient deep learning model for online state-of-health estimation of lithium-ion batteries under high-frequency early SOC data with strong correlated …

X Li, M Zhao, S Zhong, J Li, S Fu, Z Yan - Energy, 2024 - Elsevier
The efficient and accurate state-of-health (SOH) estimation is crucial for reducing risks and
ensuring effective application in battery management systems (BMS) of resource-limited …

A decade of machine learning in lithium-ion battery state estimation: a systematic review

Z Al-Hashimi, T Khamis, M Al Kouzbary, N Arifin… - Ionics, 2025 - Springer
Lithium-ion batteries are central to contemporary energy storage systems, yet the precise
estimation of critical states—state of charge (SOC), state of health (SOH), and remaining …

Improved PSO-TCN model for SOH estimation based on accelerated aging test for large capacity energy storage batteries

P Yu, C Zhou, Y Yu, Z Chang, X Li, K Huang, J Yu… - Journal of Energy …, 2025 - Elsevier
The accurate estimation of the state of health (SOH) of lithium-ion batteries is crucial for
enhancing the reliability and safety of battery systems. However, the current SOH estimation …