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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

State of health estimation of lithium-ion batteries based on fine-tuning or rebuilding transfer learning strategies combined with new features mining
Kai Huang, Kaixin Yao, Yongfang Guo, et al.
Energy (2023) Vol. 282, pp. 128739-128739
Closed Access | Times Cited: 24

Showing 24 citing articles:

Semi-supervised adversarial deep learning for capacity estimation of battery energy storage systems
Jiachi Yao, Zhonghao Chang, Te Han, et al.
Energy (2024) Vol. 294, pp. 130882-130882
Closed Access | Times Cited: 28
Machine learning for battery systems applications: Progress, challenges, and opportunities
Zahra Nozarijouybari, Hosam K. Fathy
Journal of Power Sources (2024) Vol. 601, pp. 234272-234272
Closed Access | Times Cited: 27
Progress in estimating the state of health using transfer learning–based electrochemical impedance spectroscopy of lithium-ion batteries
Guangheng Qi, Guangwen Du, Kai Wang
Ionics (2025) Vol. 31, Iss. 3, pp. 2337-2349
Closed Access | Times Cited: 1
State of the Art in Electric Batteries’ State-of-Health (SoH) Estimation with Machine Learning: A Review
Giovane Ronei Sylvestrin, Joylan Nunes Maciel, Márcio Luís Munhoz Amorim, et al.
Energies (2025) Vol. 18, Iss. 3, pp. 746-746
Open Access | Times Cited: 1
Technologies for Energy Storage Power Stations Safety Operation: Battery State Evaluation Survey and a Critical Analysis
Xiangyang Xia, J.T. Yue, Yuan Guo, et al.
IEEE Access (2024) Vol. 12, pp. 31334-31356
Open Access | Times Cited: 5
State-of-Health Prediction of Lithium-Ion Batteries Using Feature Fusion and a Hybrid Neural Network Model
Yang Li, Guoqiang Gao, Kui Chen, et al.
Energy (2025), pp. 135163-135163
Closed Access
Physics-constrained transfer learning: Open-circuit voltage curve reconstruction and degradation mode estimation of lithium-ion batteries
Tobias Hofmann, Jacob Hamar, Bastian Mager, et al.
Energy and AI (2025), pp. 100493-100493
Open Access
Fine-Tuned Transfer Learning and Deep Gated Recurrent Unit Methods for State-of-Health Estimation of the Whole Life-Cycle of Lithium-Ion Batteries
Zhenglin Guo, Jian Wang, Qiang Fu, et al.
International Journal of Electrochemical Science (2025), pp. 100931-100931
Open Access
A Hybrid Technique for Estimating the State of Health of Lithium‐Ion Batteries
Manjunatha Babu Pattabhi, Ozwin Dominic Dsouza, G. Shilpa
Optimal Control Applications and Methods (2025)
Closed Access
Accurate and adaptive state of health estimation for lithium-ion battery based on patch learning framework
Yuyao Li, Xiangwen Zhang, Ziyang Li, et al.
Measurement (2025), pp. 117083-117083
Closed Access
Multi-source self-supervised domain adaptation network for VRLA battery anomaly detection of data center under non-ideal conditions
Mengqi Miao, Pu Yang, Yue Shang, et al.
Energy (2024) Vol. 299, pp. 131392-131392
Closed Access | Times Cited: 3
A general multi-source ensemble transfer learning framework for health prognostic of lithium-ion batteries
Xianghui Qiu, Wentao Yan, Shuangfeng Wang, et al.
Applied Energy (2024) Vol. 376, pp. 124245-124245
Closed Access | Times Cited: 2
State of health estimation joint improved grey wolf optimization algorithm and LSTM using partial discharging health features for lithium-ion batteries
Simin Peng, Yujian Wang, Aihua Tang, et al.
Energy (2024), pp. 134293-134293
Closed Access | Times Cited: 2
A Novel Method for State of Health Estimation of Lithium-Ion Batteries Based on Deep Learning Neural Network and Transfer Learning
Zhong Ren, Changqing Du, Yi‐Fang Zhao
Batteries (2023) Vol. 9, Iss. 12, pp. 585-585
Open Access | Times Cited: 5
Towards Real-World State of Health Estimation: Part 2, System Level Method Using Electric Vehicle Field Data
Yufang Lu, Dongxu Guo, Gengang Xiong, et al.
eTransportation (2024) Vol. 22, pp. 100361-100361
Closed Access | Times Cited: 1
Robust lithium-ion battery state of health estimation based on recursive feature elimination-deep Bidirectional long short-term memory model using partial charging data
Fengxun Tian, Shuwen Chen, Xin Ji, et al.
International Journal of Electrochemical Science (2024), pp. 100891-100891
Open Access | Times Cited: 1
A novel unsupervised domain adaptation-based method for lithium-ion batteries state of health prognostic
Xianghui Qiu, Yu Bai, Shuangfeng Wang
Journal of Energy Storage (2023) Vol. 75, pp. 109358-109358
Closed Access | Times Cited: 3
Towards Real-World State of Health Estimation: Part 2, System Level Method Using Electric Vehicle Field Data
Yufang Lu, Dongxu Guo, Gengang Xiong, et al.
(2024)
Closed Access
Rapid Estimation of Static Capacity Based on Machine Learning: A Time-Efficient Approach
Younggill Son, Woongchul Choi
Batteries (2024) Vol. 10, Iss. 6, pp. 191-191
Open Access
A Meta-Learning Method for Few-Shot Multi-Domain State of Health Estimation of Lithium-ion Batteries
Xiaoyu Zhao, Zuolu Wang, Te Han, et al.
IEEE Transactions on Transportation Electrification (2024) Vol. 11, Iss. 1, pp. 4830-4840
Closed Access
Degradation modeling of serial space lithium-ion battery pack based on online inconsistency representation parameters
Yuhang Du, Yuchen Song, Datong Liu
Journal of Power Sources (2024) Vol. 624, pp. 235608-235608
Closed Access
BMSFormer: An efficient deep learning model for online state-of-health estimation of lithium-ion batteries under high-frequency early SOC data with strong correlated single health indicator
Xiaopeng Li, Minghang Zhao, Shisheng Zhong, et al.
Energy (2024), pp. 134030-134030
Closed Access
Multiple measurement health factors extraction and transfer learning with convolutional-BiLSTM algorithm for state-of-health evaluation of energy storage batteries
Zinan Shi, Chenyu Zhu, Huishi Liang, et al.
Ionics (2024)
Closed Access
Lithium-ion Battery Health State Prediction based on Adaptive Fine-tuning Learning Approach
Lei Yao, Changsheng Zhao, Guangzhen Cui, et al.
2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI) (2024), pp. 1-6
Closed Access
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