Review of state estimation and remaining useful life prediction methods for lithium–ion batteries
J Zhao, Y Zhu, B Zhang, M Liu, J Wang, C Liu, X Hao - Sustainability, 2023 - mdpi.com
The accurate estimation of the state of charge, the state of health and the prediction of
remaining useful life of lithium–ion batteries is an important component of battery …
remaining useful life of lithium–ion batteries is an important component of battery …
A review of battery state of charge estimation and management systems: Models and future prospective
HM Hussein, A Aghmadi… - Wiley …, 2024 - Wiley Online Library
Batteries are considered critical elements in most applications nowadays due to their power
and energy density features. However, uncontrolled charging and discharging will …
and energy density features. However, uncontrolled charging and discharging will …
Optimized data-driven approach for remaining useful life prediction of Lithium-ion batteries based on sliding window and systematic sampling
The prediction of remaining useful life (RUL) in lithium-ion batteries (LIB) serves as a critical
health index for evaluating battery parameters, including efficiency, robustness, and …
health index for evaluating battery parameters, including efficiency, robustness, and …
Collaborative training of deep neural networks for the lithium-ion battery aging prediction with federated learning
T Kröger, A Belnarsch, P Bilfinger, W Ratzke… - eTransportation, 2023 - Elsevier
Accurate and reliable prediction of the future capacity degradation of lithium-ion batteries is
crucial for their application in electric vehicles. Recent publications have highlighted the …
crucial for their application in electric vehicles. Recent publications have highlighted the …
State of health estimation for lithium-ion batteries based on incremental capacity analysis and Transformer modeling
Z Xu, Z Chen, L Yang, S Zhang - Applied Soft Computing, 2024 - Elsevier
As an important performance indicator of battery management systems, lithium-ion battery
state of health (SOH) information is crucial to ensure battery safety and extend battery …
state of health (SOH) information is crucial to ensure battery safety and extend battery …
A CNN-GRU Approach to the Accurate Prediction of Batteries' Remaining Useful Life from Charging Profiles
Predicting the remaining useful life (RUL) is a pivotal step in ensuring the reliability of lithium-
ion batteries (LIBs). In order to enhance the precision and stability of battery RUL prediction …
ion batteries (LIBs). In order to enhance the precision and stability of battery RUL prediction …
Novel PI controller and ANN controllers-Based passive cell balancing for battery management system
The cycle life and efficiency of a battery pack get enhanced by employing an intelligent
supporting system with it called the Battery Management System (BMS). A novel …
supporting system with it called the Battery Management System (BMS). A novel …
Battery Energy Storage Systems: A Review of Energy Management Systems and Health Metrics
With increasing concerns about climate change, there is a transition from high-carbon-
emitting fuels to green energy resources in various applications including household …
emitting fuels to green energy resources in various applications including household …
Review on battery state estimation and management solutions for next-generation connected vehicles
The transport sector is tackling the challenge of reducing vehicle pollutant emissions and
carbon footprints by means of a shift to electrified powertrains, ie, battery electric vehicles …
carbon footprints by means of a shift to electrified powertrains, ie, battery electric vehicles …
[HTML][HTML] State of health prediction in electric vehicle batteries using a deep learning model
RM Alhazmi - World Electric Vehicle Journal, 2024 - mdpi.com
Accurately estimating the state of health (SOH) of lithium-ion batteries plays a significant role
in the safe operation of electric vehicles. Deep learning (DL)-based approaches for …
in the safe operation of electric vehicles. Deep learning (DL)-based approaches for …