A comprehensive review of battery-based power service applications considering degradation: Research status and model integration

SW Park, JU Yu, JW Lee, SY Son - Applied Energy, 2024 - Elsevier
Battery-based resources, such as electric vehicles and energy storage systems, are widely
used in various power service applications (PSAs). Battery degradation management is …

Recent Advances in Thermal Management Strategies for Lithium-Ion Batteries: A Comprehensive Review

Y Ortiz, P Arévalo, D Peña, F Jurado - Batteries, 2024 - mdpi.com
Effective thermal management is essential for ensuring the safety, performance, and
longevity of lithium-ion batteries across diverse applications, from electric vehicles to energy …

[HTML][HTML] IIP-Mixer: Intra–Inter-Patch Mixing Architecture for Battery Remaining Useful Life Prediction

G Ye, L Feng, J Guo, Y Chen - Energies, 2024 - mdpi.com
Accurately estimating the Remaining Useful Life (RUL) of lithium-ion batteries is crucial for
maintaining the safe and stable operation of rechargeable battery management systems …

Capacity Estimation for Lithium-ion Batteries Based on Impedance Spectral Dynamics and Deep Gaussian Process

S Zhang, W Yuan, Y Wang, S Cheng… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The charging and discharging processes of lithiumion batteries are accompanied by
complex electrochemical behaviors that have long-lasting and irreversible effects on the …

Joint prediction of state of health and remaining useful life for lithium-ion batteries based on health features optimization and multi-model fusion

D Zheng, S Man, X Guo, Y Ning - Ionics, 2024 - Springer
Accurate prediction of the state of health (SOH) and remaining useful life (RUL) of batteries
is essential for ensuring their safe and stable operation. Given the strong correlation …

Adaptive control of electric vehicle drives through neural network ensembles

T Singla, P Sruthi - MATEC Web of Conferences, 2024 - matec-conferences.org
This study examines the use of neural network ensembles in adaptive control for electric
vehicle (EV) propulsion systems, using simulated data to evaluate their efficacy. The …

Estimating the battery life of an electric train using the ANFIS model

Y Darvishpour, GSM Mousavi - 2023 - sid.ir
Batteries as a power source for Electric Train s have been considered due to a number of
advantages, including flexibility, reduced air and noise pollution, and lower operating costs …

Joint Prediction of Capacity and Rul for Lithium-Ion Batteries Based on Ceemdan-Sos-Vmd-Lstm

Q Zhang, S Feng, J Liu, J Xie, Y Chen - Available at SSRN 4845113 - papers.ssrn.com
Accurately predicting the capacity and remaining service life of lithium-ion batteries is crucial
for Battery Management Systems (BMS). However, during the aging process of batteries …

A Lithium-Ion Battery Energy Estimation Method Based on Deep Learning and Magnetic Field Effects

G Ruan, Z Liu, S Chen, S Liu, Y Guo… - Available at SSRN … - papers.ssrn.com
This paper proposes a deep learning model merging an enhanced Informer with LSTM to
estimate lithium-ion battery SOE amidst varying magnetic fields. The improved decoder …

Online Estimation of Lithium-Ion Battery Health Status Based on Transfer Learning and Deep Neural Network

Y Chen, Y Tang, J Lin, H Tang - Available at SSRN 4886799 - papers.ssrn.com
The health status (State of Health, SOH) of lithium-ion batteries is crucial for ensuring their
safety and efficiency. With the rapid development of big data technology, traditional offline …