A comprehensive review on the state of charge estimation for lithium‐ion battery based on neural network

Z Cui, L Wang, Q Li, K Wang - International Journal of Energy …, 2022 - Wiley Online Library
Implementing carbon neutrality and emission peak policies requires a high‐level electric
vehicle field. Lithium‐ion batteries have been considered an essential component of electric …

[HTML][HTML] A review on online state of charge and state of health estimation for lithium-ion batteries in electric vehicles

Z Wang, G Feng, D Zhen, F Gu, A Ball - Energy Reports, 2021 - Elsevier
With electric vehicles (EVs) being widely accepted as a clean technology to solve carbon
emissions in modern transportation, lithium-ion batteries (LIBs) have emerged as the …

Lithium-ion battery aging mechanisms and diagnosis method for automotive applications: Recent advances and perspectives

R **ong, Y Pan, W Shen, H Li, F Sun - Renewable and Sustainable Energy …, 2020 - Elsevier
Lithium-ion batteries decay every time as it is used. Aging-induced degradation is unlikely to
be eliminated. The aging mechanisms of lithium-ion batteries are manifold and complicated …

A data-driven auto-CNN-LSTM prediction model for lithium-ion battery remaining useful life

L Ren, J Dong, X Wang, Z Meng… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Integration of each aspect of the manufacturing process with the new generation of
information technology such as the Internet of Things, big data, and cloud computing makes …

State estimation for advanced battery management: Key challenges and future trends

X Hu, F Feng, K Liu, L Zhang, J **e, B Liu - Renewable and Sustainable …, 2019 - Elsevier
Batteries are presently pervasive in portable electronics, electrified vehicles, and renewable
energy storage. These indispensable engineering applications are all safety-critical and …

Towards a smarter battery management system: A critical review on battery state of health monitoring methods

R **ong, L Li, J Tian - Journal of Power Sources, 2018 - Elsevier
To ensure the driving safety and avoid potential failures for electric vehicles, evaluating the
health state of the battery properly is of significant importance. This study aims to serve as a …

Long short-term memory recurrent neural network for remaining useful life prediction of lithium-ion batteries

Y Zhang, R **ong, H He… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Remaining useful life (RUL) prediction of lithium-ion batteries can assess the battery
reliability to determine the advent of failure and mitigate battery risk. The existing RUL …

State-of-the-art and energy management system of lithium-ion batteries in electric vehicle applications: Issues and recommendations

MA Hannan, MM Hoque, A Hussain, Y Yusof… - Ieee …, 2018 - ieeexplore.ieee.org
A variety of rechargeable batteries are now available in world markets for powering electric
vehicles (EVs). The lithium-ion (Li-ion) battery is considered the best among all battery types …

Critical review on the battery state of charge estimation methods for electric vehicles

R **ong, J Cao, Q Yu, H He, F Sun - Ieee Access, 2017 - ieeexplore.ieee.org
Battery technology is the bottleneck of the electric vehicles (EVs). It is important, both in
theory and practical application, to do research on the modeling and state estimation of …

An integrated method of the future capacity and RUL prediction for lithium-ion battery pack

C Zhang, S Zhao, Y He - IEEE Transactions on Vehicular …, 2021 - ieeexplore.ieee.org
Accurate prediction of remaining useful life (RUL) is of critical significance to the safety and
reliability of lithium-ion batteries, which can offer efficient early warning signals for failure …