Multiple measurement health factors extraction and transfer learning with convolutional-BiLSTM algorithm for state-of-health evaluation of energy storage batteries DOI

Zinan Shi,

Chenyu Zhu, Huishi Liang

et al.

Ionics, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 12, 2024

Language: Английский

Renewable energy integration with DC microgrids: Challenges and opportunities DOI
Md Shafiul Alam, Md. Alamgir Hossain, Md Shafiullah

et al.

Electric Power Systems Research, Journal Year: 2024, Volume and Issue: 234, P. 110548 - 110548

Published: June 12, 2024

Language: Английский

Citations

16
Deep learning and polarisation equilibrium based state of health estimation for lithium-ion battery using partial charging data DOI
Tong Wang, Yan Wu,

Keming Zhu

et al.

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 134564 - 134564

Published: Jan. 1, 2025

Language: Английский

Citations

3
Big data-driven prognostics and health management of lithium-ion batteries:A review DOI
Kui Chen, Yang Luo, Zhou Long

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2025, Volume and Issue: 214, P. 115522 - 115522

Published: Feb. 27, 2025

Language: Английский

Citations

1
Transfer learning from synthetic data for open-circuit voltage curve reconstruction and state of health estimation of lithium-ion batteries from partial charging segments DOI Creative Commons
Tobias Hofmann, Jacob Hamar,

Bastian Mager

et al.

Energy and AI, Journal Year: 2024, Volume and Issue: 17, P. 100382 - 100382

Published: June 7, 2024

Data-driven models for battery state estimation require extensive experimental training data, which may not be available or suitable specific tasks like open-circuit voltage (OCV) reconstruction and subsequent of health (SOH) estimation. This study addresses this issue by developing a transfer-learning-based OCV model using temporal convolutional long short-term memory (TCN-LSTM) network trained on synthetic data from an automotive nickel cobalt aluminium oxide (NCA) cell generated through mechanistic approach. The consists curves at constant temperature, C-rates between C/30 to 1C, SOH-range 70 % 100 %. is refined via Bayesian optimization then applied four use cases with reduced manganese (NMC) higher cases. TL models' performances are compared solely focusing different windows. results demonstrate that the mean absolute error (MAE) within average electric vehicle (BEV) home charging window (30 85 charge (SOC)) less than 22 mV first three across all C-rates. SOH estimated reconstructed exhibits percentage (MAPE) below 2.2 these further investigates impact source domain incorporating two additional datasets, lithium iron phosphate (LFP) entirely artificial, non-existing, cell, showing shifting scaling gradient changes in curve suffice transfer knowledge, even chemistries. A key limitation respect extrapolation capability identified evidenced our fourth case, where absence such comprehensive hindered process.

Language: Английский

Citations

8
Indirect health state prognosis of lithium-ion batteries based on VMD decomposition and neural network model DOI

Qinming Liu,

Fengze Yun,

Ming Dong

et al.

International Journal of Production Research, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 20

Published: Feb. 26, 2025

Language: Английский

Citations

0
Adaptive engineering-assisted deep learning for battery module health monitoring across dynamic operations DOI
Aihua Tang, Yuchen Xu, Jinpeng Tian

et al.

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 135332 - 135332

Published: March 1, 2025

Language: Английский

Citations

0
Physics-constrained transfer learning: Open-circuit voltage curve reconstruction and degradation mode estimation of lithium-ion batteries DOI Creative Commons
Tobias Hofmann, Jacob Hamar,

Bastian Mager

et al.

Energy and AI, Journal Year: 2025, Volume and Issue: unknown, P. 100493 - 100493

Published: March 1, 2025

Language: Английский

Citations

0
Estimating battery state of health using impedance spectrum geometric health indicators and recurrent deep sigma point process DOI
Shude Zhang, Weiru Yuan, Yingzhou Wang

et al.

Journal of Energy Storage, Journal Year: 2025, Volume and Issue: 119, P. 116117 - 116117

Published: March 23, 2025

Language: Английский

Citations

0
State Estimation of Lithium-Ion Batteries via Physics-Machine Learning Combined Methods: A Methodological Review and Future Perspectives DOI
Hanqing Yu, Hongcai Zhang, Zhengjie Zhang

et al.

eTransportation, Journal Year: 2025, Volume and Issue: unknown, P. 100420 - 100420

Published: April 1, 2025

Language: Английский

Citations

0
Trustworthy Battery State of Charge Estimation Enabled by Multi-task Deep Learning DOI Creative Commons
Liang Ma,

Yannan Li,

Tieling Zhang

et al.

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 136264 - 136264

Published: April 1, 2025

Language: Английский

Citations

0