State of power prediction joint fisher optimal segmentation and PO-BP neural network for a parallel battery pack considering cell inconsistency

S Peng, S Chen, Y Liu, Q Yu, J Kan, R Li - Applied Energy, 2025 - Elsevier
Accurate state of power (SOP) of battery is critical for efficient control and stable operation of
electric vehicles. Due to cell inconsistency and even varying degrees of discrepancy …

Innovative multiscale fusion–Antinoise extended long short-term memory neural network modeling for high precision state of health estimation of lithium-ion batteries

J Tao, S Wang, W Cao, Y Cui, C Fernandez… - Energy, 2024 - Elsevier
An accurate assessment of lithium-ion (Li-ion) batteries' state of health (SOH) is essential for
the safe operation of new energy systems and extended battery life. Health factors were …

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 …

AM-MFF: A multi-feature fusion framework based on attention mechanism for robust and interpretable lithium-ion battery state of health estimation

SZ Chen, J Liu, H Yuan, Y Tao, F Xu, L Yang - Applied Energy, 2025 - Elsevier
State of health (SOH) is a crucial parameter in a battery management system (BMS). Using
multiple sources of data effectively improves the end-to-end SOH estimation performance …

Joint estimation of SOC and peak power capability for series reused battery pack based on screening process method

Y Zhang, B Liu, H Zhang, R Kuang, Y Xu, J Zhang… - Energy, 2024 - Elsevier
Lithium-ion battery disposal is becoming an increasingly important issue with the rapid
growth of Electric Vehicles (EVs) regarding resource conservation and environmental …

Early perception of Lithium-ion battery degradation trajectory with graphical features and deep learning

H Zhao, J Meng, Q Peng - Applied Energy, 2025 - Elsevier
Capturing the degradation path of lithium-ion battery (LIB) at the early stage is critical to
managing the whole lifespan of the battery energy storage systems (BESS), while recent …

State of health estimation joint improved grey wolf optimization algorithm and LSTM using partial discharging health features for lithium-ion batteries

S Peng, Y Wang, A Tang, Y Jiang, J Kan, M Pecht - Energy, 2025 - Elsevier
Accurate estimation of the state of health (SOH) of lithium-ion batteries is crucial for the
safety and operation of electric vehicles. The accuracy and efficiency of SOH estimation are …

State of health estimation of lithium-ion batteries based on feature optimization and data-driven models

G Mu, Q Wei, Y Xu, J Li, H Zhang, F Yang, J Zhang… - Energy, 2025 - Elsevier
With the widespread application of lithium-ion batteries in electric vehicles, accurately
estimating their state of health (SOH) has become a key focus of research. This paper …

An innovative multitask learning-Long short-term memory neural network for the online anti-aging state of charge estimation of lithium-ion batteries adaptive to varying …

J Tao, S Wang, W Cao, C Fernandez, F Blaabjerg… - Energy, 2025 - Elsevier
As the new industrial revolution accelerates, new energy storage systems are becoming
increasingly vital to the industrial chain. The overall performance of the battery management …

State-of-Health Prediction of Lithium-Ion Batteries Using Feature Fusion and a Hybrid Neural Network Model

Y Li, G Gao, K Chen, S He, K Liu, D **n, Y Luo, Z Long… - Energy, 2025 - Elsevier
With their high energy density and long cycle life, lithium-ion batteries are vital components
of energy storage systems. However, accurate State of Health (SOH) prediction remains …