A review of data-driven whole-life state of health prediction for lithium-ion batteries: Data preprocessing, aging characteristics, algorithms, and future challenges

Y **e, S Wang, G Zhang, P Takyi-Aninakwa… - Journal of Energy …, 2024 - Elsevier
Lithium-ion batteries are the preferred green energy storage method and are equipped with
intelligent battery management systems (BMSs) that efficiently manage the batteries. This …

Advancing state of charge management in electric vehicles with machine learning: A technological review

A Mousaei, Y Naderi, IS Bayram - IEEE Access, 2024 - ieeexplore.ieee.org
As the share of electric vehicles increases, electric vehicles are exposed to broader of
driving conditions (eg, extreme weather), which reduce the performance and driving ranges …

Closed-loop state of charge estimation of Li-ion batteries based on deep learning and robust adaptive Kalman filter

W Qi, W Qin, Z Yun - Energy, 2024 - Elsevier
The state of charge (SOC) is among the most crucial monitoring states in battery
management systems. To accurately and robustly estimate the battery SOC, a closed-loop …

Industrial expert systems review: A comprehensive analysis of typical applications

X Yang, C Zhu - IEEE Access, 2024 - ieeexplore.ieee.org
As a branch of artificial intelligence (AI), expert systems are well-known for interpreting and
deducing solutions to problems based on the rules contained within a knowledge base …

Recent advances in thermal management strategies for lithium-ion batteries: a comprehensive review

Y Ortiz, P Arévalo, D Peña, F Jurado - Batteries, 2024 - mdpi.com
Effective thermal management is essential for ensuring the safety, performance, and
longevity of lithium-ion batteries across diverse applications, from electric vehicles to energy …

[HTML][HTML] Integration of electric vehicle power supply systems—case study analysis of the impact on a selected urban network in Türkiye

W Lewicki, HH Coban, J Wróbel - Energies, 2024 - mdpi.com
Undoubtedly, the transition to electromobility with several million new, efficient charging
points will have consequences for the energy industry, and in particular for network …

Progress of machine learning-based biosensors for the monitoring of food safety: A review

MM Hassan, X Yi, J Sayada, M Zareef, M Shoaib… - Biosensors and …, 2024 - Elsevier
Rapid urbanization and growing food demand caused people to be concerned about food
safety. Biosensors have gained considerable attention for assessing food safety due to …

Graphene-Based 2D Materials for Rechargeable Batteries, Hydrogen Production and Storage-A Critical Review

CS Bongu, S Tasleem, MR Krishnan… - Sustainable Energy & …, 2024 - pubs.rsc.org
Batteries and hydrogen energy devices are considered the most critical technologies for
achieving zero carbon dioxide emissions. However, they still suffer from several limitations …

Advances of machine learning-assisted small extracellular vesicles detection strategy

Q Zhang, T Ren, K Cao, Z Xu - Biosensors and Bioelectronics, 2024 - Elsevier
Detection of extracellular vesicles (EVs), particularly small EVs (sEVs), is of great
significance in exploring their physiological characteristics and clinical applications. The …

Survey on task-centric robot battery management: A neural network framework

Z Lin, Z Huang, S Yang, C Wu, S Fang, Z Liu… - Journal of Power …, 2024 - Elsevier
The surge in autonomous robotic applications across various sectors highlights the crucial
need for effective robot battery management to ensure robots perform their tasks …