Lithium-ion battery management system for electric vehicles: constraints, challenges, and recommendations

AKMA Habib, MK Hasan, GF Issa, D Singh, S Islam… - Batteries, 2023 - mdpi.com
Flexible, manageable, and more efficient energy storage solutions have increased the
demand for electric vehicles. A powerful battery pack would power the driving motor of …

Deep feature extraction in lifetime prognostics of lithium-ion batteries: Advances, challenges and perspectives

C Li, H Zhang, P Ding, S Yang, Y Bai - Renewable and Sustainable Energy …, 2023 - Elsevier
The wide application of lithium-ion batteries makes their lifecycle prognosis a challenging
and hot topic in the battery management research field. Feature extraction is a key step for …

Application of electrochemical impedance spectroscopy to degradation and aging research of lithium-ion batteries

W Hu, Y Peng, Y Wei, Y Yang - The Journal of Physical Chemistry …, 2023 - ACS Publications
An in-depth understanding of battery degradation and aging in-Operando not only plays a
vital role in the design of battery managing systems but also helps to ensure safe use and …

Flexible battery state of health and state of charge estimation using partial charging data and deep learning

J Tian, R **ong, W Shen, J Lu, F Sun - Energy Storage Materials, 2022 - Elsevier
Accurately monitoring battery states over battery life plays a central role in building
intelligent battery management systems. This study proposes a flexible method using only …

State of health estimation for lithium-ion batteries based on hybrid attention and deep learning

H Zhao, Z Chen, X Shu, J Shen, Z Lei… - Reliability Engineering & …, 2023 - Elsevier
Accurate state of health estimation of lithium-ion batteries is imperative for reliable and safe
operations of electric vehicles. This study presents a hybrid attention and deep learning …

Convolutional autoencoder-based SOH estimation of lithium-ion batteries using electrochemical impedance spectroscopy

J Obregon, YR Han, CW Ho, D Mouraliraman… - Journal of Energy …, 2023 - Elsevier
The advancement of consumer electronics and electric vehicles requires heavy use of
energy sources, particularly in the form of rechargeable batteries. Although lithium-ion …

Machine learning for battery research

Z Wei, Q He, Y Zhao - Journal of Power Sources, 2022 - Elsevier
Batteries are vital energy storage carriers in industry and in our daily life. There is continued
interest in the developments of batteries with excellent service performance and safety …

State of health estimation for lithium-ion battery based on energy features

D Gong, Y Gao, Y Kou, Y Wang - Energy, 2022 - Elsevier
There is a recognized need to forecast lithium-ion batteries' state of health (SOH) to
guarantee their safety and reliability. However, the selected health indicators highly …

A novel back propagation neural network-dual extended Kalman filter method for state-of-charge and state-of-health co-estimation of lithium-ion batteries based on …

C Wang, S Wang, J Zhou, J Qiao, X Yang… - Journal of Energy Storage, 2023 - Elsevier
Abstract State-of-charge (SOC) and state-of-health (SOH) play a key role in the safety and
reliability of batteries. To improve the real-time estimation accuracy of battery state, a novel …

Data-driven-aided strategies in battery lifecycle management: prediction, monitoring, and optimization

L Xu, F Wu, R Chen, L Li - Energy Storage Materials, 2023 - Elsevier
Predicting, monitoring, and optimizing the performance and health of a battery system
entails a variety of complex variables as well as unpredictability in given conditions. Data …