[HTML][HTML] A review of non-probabilistic machine learning-based state of health estimation techniques for Lithium-ion battery

X Sui, S He, SB Vilsen, J Meng, R Teodorescu, DI Stroe - Applied Energy, 2021 - Elsevier
Lithium-ion batteries are used in a wide range of applications including energy storage
systems, electric transportations, and portable electronic devices. Accurately obtaining the …

Review on state-of-health of lithium-ion batteries: Characterizations, estimations and applications

S Yang, C Zhang, J Jiang, W Zhang, L Zhang… - Journal of Cleaner …, 2021 - Elsevier
Abstract State-of-health (SOH) monitoring of lithium-ion batteries plays a key role in the
reliable and safe operation of battery systems. Influenced by multiple factors, SOH is an …

Battery management strategies: An essential review for battery state of health monitoring techniques

SK Pradhan, B Chakraborty - Journal of energy storage, 2022 - Elsevier
To prevent probable battery failures and ensure safety, battery state of health evaluation is a
critical step. This study lays out a coherent literature review on battery health estimation …

A review of lithium-ion battery state of health estimation and prediction methods

L Yao, S Xu, A Tang, F Zhou, J Hou, Y Xiao… - World Electric Vehicle …, 2021 - mdpi.com
Lithium-ion power batteries have been widely used in transportation due to their advantages
of long life, high specific power, and energy. However, the safety problems caused by the …

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 …

Assessment and management of health status in full life cycle of echelon utilization for retired power lithium batteries

H Chen, T Zhang, Q Gao, Z Han, Y Jin, L Li… - Journal of Cleaner …, 2022 - Elsevier
In recent years, a significant increase in market share has occurred in the global electric
vehicle industry. These advancements will eventually lead to a large-scale …

Recovering large-scale battery aging dataset with machine learning

X Tang, K Liu, K Li, WD Widanage, E Kendrick, F Gao - Patterns, 2021 - cell.com
Batteries are crucial for building a clean and sustainable society, and their performance is
highly affected by aging status. Reliable battery health assessment, however, is currently …

State of health estimation of power batteries based on multi-feature fusion models using stacking algorithm

G Liu, X Zhang, Z Liu - Energy, 2022 - Elsevier
The data-driven method is used widely to estimate the state of health (SOH) of the battery,
but the selection of data features and the data training methods affect the estimation results …

An Immune Genetic Extended Kalman Particle Filter approach on state of charge estimation for lithium-ion battery

J Zhengxin, S Qin, W Yujiang, W Hanlin, G Bingzhao… - Energy, 2021 - Elsevier
In this paper, based on the lithium-ion battery parameter identification by Immune Genetic
Algorithm, An Extended Kalman Particle Filter approach is proposed to estimate the state of …

[HTML][HTML] Data-driven state of health modelling—A review of state of the art and reflections on applications for maritime battery systems

E Vanem, CB Salucci, A Bakdi… - Journal of Energy Storage, 2021 - Elsevier
Battery systems are becoming an increasingly attractive alternative for powering ocean
going ships, and the number of fully electric or hybrid ships relying on battery power for …