[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 …

Artificial Neural Networks, Gradient Boosting and Support Vector Machines for electric vehicle battery state estimation: A review

A Manoharan, KM Begam, VR Aparow… - Journal of Energy …, 2022 - Elsevier
Abstract In recent years, Artificial Intelligence has been widely used for determining the
current state of Li-ion batteries used for Electric Vehicle applications. It is crucial to have an …

Key challenges for a large-scale development of battery electric vehicles: A comprehensive review

BE Lebrouhi, Y Khattari, B Lamrani, M Maaroufi… - Journal of Energy …, 2021 - Elsevier
Nowadays, several countries have adopted an energy transition policy to achieve carbon
targets and decarbonize transport while improving their electricity mixes. Electric vehicles …

Advanced battery management strategies for a sustainable energy future: Multilayer design concepts and research trends

H Dai, B Jiang, X Hu, X Lin, X Wei, M Pecht - Renewable and Sustainable …, 2021 - Elsevier
Lithium-ion batteries are promising energy storage devices for electric vehicles and
renewable energy systems. However, due to complex electrochemical processes, potential …

[HTML][HTML] Digital twin for battery systems: Cloud battery management system with online state-of-charge and state-of-health estimation

W Li, M Rentemeister, J Badeda, D Jöst… - Journal of energy …, 2020 - Elsevier
Battery management is critical to enhancing the safety, reliability, and performance of the
battery systems. This paper presents a cloud battery management system for battery …

Overview of model-based online state-of-charge estimation using Kalman filter family for lithium-ion batteries

P Shrivastava, TK Soon, MYIB Idris… - … and Sustainable Energy …, 2019 - Elsevier
Carbon impression and the growing reliance on fossil fuels are two unique concerns for
world emission regulatory agencies. These issues have placed electric vehicles (EVs) …

Deep convolutional neural networks with ensemble learning and transfer learning for capacity estimation of lithium-ion batteries

S Shen, M Sadoughi, M Li, Z Wang, C Hu - Applied Energy, 2020 - Elsevier
It is often difficult for a machine learning model trained based on a small size of
charge/discharge cycling data to produce satisfactory accuracy in the capacity estimation of …

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

R Xiong, 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 …

A review of state of health and remaining useful life estimation methods for lithium-ion battery in electric vehicles: Challenges and recommendations

MSH Lipu, MA Hannan, A Hussain, MM Hoque… - Journal of cleaner …, 2018 - Elsevier
Electric vehicles (EVs) have become increasingly popular due to zero carbon emission,
reduction of fossil fuel reserve, comfortable and light transport. However, EVs employing …

Co-estimation of state-of-charge and state-of-health for lithium-ion batteries using an enhanced electrochemical model

Y Gao, K Liu, C Zhu, X Zhang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Real-time electrochemical state information of lithium-ion batteries attributes to a high-fidelity
estimation of state-of-charge (SOC) and state-of-health (SOH) in advanced battery …