A hybrid battery equivalent circuit model, deep learning, and transfer learning for battery state monitoring

S Su, W Li, J Mou, A Garg, L Gao… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The accurate estimation of state of health (SOH) for lithium-ion batteries is significant to
improve the reliability and safety of batteries in operation. However, many existing studies …

Multiple health indicators fusion-based health prognostic for lithium-ion battery using transfer learning and hybrid deep learning method

Y Ma, C Shan, J Gao, H Chen - Reliability Engineering & System Safety, 2023 - Elsevier
Accurate state of health (SOH) estimation of lithium-ion battery provides a guarantee for the
safe driving of electric vehicles. Most SOH estimation methods based on the machine …

Robust State of Health estimation of lithium-ion batteries using convolutional neural network and random forest

N Yang, Z Song, H Hofmann, J Sun - Journal of Energy Storage, 2022 - Elsevier
Abstract The State of Health (SOH) of lithium-ion batteries is directly related to their safety
and efficiency, yet effective assessment of SOH remains challenging for real-world …

Integrating physics-based modeling and machine learning for degradation diagnostics of lithium-ion batteries

A Thelen, YH Lui, S Shen, S Laflamme, S Hu… - Energy Storage …, 2022 - Elsevier
Traditional lithium-ion (Li-ion) battery state of health (SOH) estimation methodologies that
focused on estimating present cell capacity do not provide sufficient information to determine …

Online state-of-health estimation of lithium-ion battery based on dynamic parameter identification at multi timescale and support vector regression

X Tan, D Zhan, P Lyu, J Rao, Y Fan - Journal of Power Sources, 2021 - Elsevier
Highlights•A proposed EKF-RLS-based dynamic parameter identification algorithm with
multi-timescale.•Establishment of an online SoH estimation and life assessing approach …

The capacity estimation and cycle life prediction of lithium-ion batteries using a new broad extreme learning machine approach

Y Ma, L Wu, Y Guan, Z Peng - Journal of Power Sources, 2020 - Elsevier
Lithium-ion batteries have become the main power source of many electronic devices.
Accurate capacity estimation and cycle life prediction of lithium-ion batteries are of great …

A comprehensive review of the lithium-ion battery state of health prognosis methods combining aging mechanism analysis

Y Xiao, J Wen, L Yao, J Zheng, Z Fang, Y Shen - Journal of Energy Storage, 2023 - Elsevier
In the field of new energy vehicles, lithium-ion batteries have become an inescapable
energy storage device. However, they still face significant challenges in practical use due to …

Deep learning methods and applications for electrical power systems: A comprehensive review

AK Ozcanli, F Yaprakdal… - International Journal of …, 2020 - Wiley Online Library
Over the past decades, electric power systems (EPSs) have undergone an evolution from an
ordinary bulk structure to intelligent flexible systems by way of advanced electronics and …

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 …

A survey on lithium-ion battery internal and external degradation modeling and state of health estimation

G Vennam, A Sahoo, S Ahmed - Journal of Energy Storage, 2022 - Elsevier
Battery management system (BMS) is an integral part of the Lithium-ion battery (LIB) for safe
operation and power management. The advanced BMSs also provide state of charge (SOC) …