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OpenAlex Citation Counts

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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:

An improved CNN-LSTM model-based state-of-health estimation approach for lithium-ion batteries
Huanwei Xu, Lingfeng Wu, Shizhe Xiong, et al.
Energy (2023) Vol. 276, pp. 127585-127585
Closed Access | Times Cited: 125

Showing 1-25 of 125 citing articles:

State of health estimation of lithium-ion batteries based on Mixers-bidirectional temporal convolutional neural network
Jingyi Gao, Dongfang Yang, Shi Wang, et al.
Journal of Energy Storage (2023) Vol. 73, pp. 109248-109248
Closed Access | Times Cited: 78
State of health estimation of lithium-ion batteries based on modified flower pollination algorithm-temporal convolutional network
Hao Zhang, Jingyi Gao, Le Kang, et al.
Energy (2023) Vol. 283, pp. 128742-128742
Closed Access | Times Cited: 50
Enhancing real-time degradation prediction of lithium-ion battery: A digital twin framework with CNN-LSTM-attention model
Wei Li, Yongsheng Li, Akhil Garg, et al.
Energy (2023) Vol. 286, pp. 129681-129681
Closed Access | Times Cited: 40
A review of expert hybrid and co-estimation techniques for SOH and RUL estimation in battery management system with electric vehicle application
Turki Alsuwian, Shaheer Ansari, Muhammad Ammirrul Atiqi Mohd Zainuri, et al.
Expert Systems with Applications (2024) Vol. 246, pp. 123123-123123
Closed Access | Times Cited: 34
State of Health (SoH) estimation methods for second life lithium-ion battery—Review and challenges
S Vignesh, Hang Seng, Jeyraj Selvaraj, et al.
Applied Energy (2024) Vol. 369, pp. 123542-123542
Closed Access | Times Cited: 32
Flexible method for estimating the state of health of lithium-ion batteries using partial charging segments
Chaolong Zhang, Laijin Luo, Yang Zhong, et al.
Energy (2024) Vol. 295, pp. 131009-131009
Closed Access | Times Cited: 29
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: 27
A self-attention-based CNN-Bi-LSTM model for accurate state-of-charge estimation of lithium-ion batteries
Zeinab Sherkatghanad, Amin Ghazanfari, Vladimir Makarenkov
Journal of Energy Storage (2024) Vol. 88, pp. 111524-111524
Open Access | Times Cited: 20
Recent advancement of remaining useful life prediction of lithium-ion battery in electric vehicle applications: A review of modelling mechanisms, network configurations, factors, and outstanding issues
M. S. Reza, M. Mannan, Muhamad Mansor, et al.
Energy Reports (2024) Vol. 11, pp. 4824-4848
Open Access | Times Cited: 20
Integrating mechanism and machine learning based capacity estimation for LiFePO4 batteries under slight overcharge cycling
Meng Wei, Min Ye, Chuanwei Zhang, et al.
Energy (2024) Vol. 296, pp. 131208-131208
Closed Access | Times Cited: 18
Time Series Stock Price Forecasting Based on Genetic Algorithm (GA)-Long Short-Term Memory Network (LSTM) Optimization
Xinye Sha
Advances in Economics Management and Political Sciences (2024) Vol. 91, Iss. 1, pp. 142-149
Open Access | Times Cited: 16
State of health estimation for Lithium-ion batteries based on novel feature extraction and BiGRU-Attention model
Sun Rongli, Junsheng Chen, Benchuan Li, et al.
Energy (2025), pp. 134756-134756
Closed Access | Times Cited: 1
Improved LSTM based state of health estimation using random segments of the charging curves for lithium-ion batteries
Liang Zhang, Junyu Zhang, Tian Gao, et al.
Journal of Energy Storage (2023) Vol. 74, pp. 109370-109370
Open Access | Times Cited: 35
A novel integrated SOC–SOH estimation framework for whole-life-cycle lithium-ion batteries
Haichi Huang, Chong Bian, Mengdan Wu, et al.
Energy (2023) Vol. 288, pp. 129801-129801
Closed Access | Times Cited: 26
State-of-health and remaining-useful-life estimations of lithium-ion battery based on temporal convolutional network-long short-term memory
Chaoran Li, Xianjie Han, Qiang Zhang, et al.
Journal of Energy Storage (2023) Vol. 74, pp. 109498-109498
Closed Access | Times Cited: 21
Battery health diagnostics: Bridging the gap between academia and industry
Zhenghong Wang, Dapai Shi, Jingyuan Zhao, et al.
eTransportation (2023) Vol. 19, pp. 100309-100309
Closed Access | Times Cited: 21
Battery State-of-Health Estimation: A Step towards Battery Digital Twins
Vahid Safavi, Najmeh Bazmohammadi, Juan C. Vásquez, et al.
Electronics (2024) Vol. 13, Iss. 3, pp. 587-587
Open Access | Times Cited: 14
An end-cloud collaboration approach for online state-of-health estimation of lithium-ion batteries based on multi-feature and transformer
Wentao Wang, Kaiyi Yang, Lisheng Zhang, et al.
Journal of Power Sources (2024) Vol. 608, pp. 234669-234669
Closed Access | Times Cited: 12
Accurate Capacity Prediction and Evaluation with Advanced SSA-CNN-BiLSTM Framework for Lithium-Ion Batteries
Chunsong Lin, Xianguo Tuo, Longxing Wu, et al.
Batteries (2024) Vol. 10, Iss. 3, pp. 71-71
Open Access | Times Cited: 11
Capacity estimation of lithium-ion batteries with uncertainty quantification based on temporal convolutional network and Gaussian process regression
R. Zhang, Chunhui Ji, Xing Zhou, et al.
Energy (2024) Vol. 297, pp. 131154-131154
Closed Access | Times Cited: 11
Quantification of uncertainty in robot pose errors and calibration of reliable compensation values
Teng Zhang, Fangyu Peng, Rong Yan, et al.
Robotics and Computer-Integrated Manufacturing (2024) Vol. 89, pp. 102765-102765
Closed Access | Times Cited: 10
Electro-hydraulic SBW fault diagnosis method based on novel 1DCNN-LSTM with attention mechanisms and transfer learning
Senhao Zhang, Weihe Liang, Wanzhong Zhao, et al.
Mechanical Systems and Signal Processing (2024) Vol. 220, pp. 111644-111644
Closed Access | Times Cited: 10
Early-stage degradation trajectory prediction for lithium-ion batteries: A generalized method across diverse operational conditions
Xianbin Yang, Haicheng Xie, Lisheng Zhang, et al.
Journal of Power Sources (2024) Vol. 612, pp. 234808-234808
Closed Access | Times Cited: 9
SOH estimation of lithium-ion batteries based on multi-feature deep fusion and XGBoost
Jing Sun, Chaoqun Fan, huiyi yan
Energy (2024) Vol. 306, pp. 132429-132429
Closed Access | Times Cited: 9
A Data-Fusion-Model Method for State of Health Estimation of Li-Ion Battery Packs Based on Partial Charging Curve
Xingzi Qiang, Wenting Liu, Zhiqiang Lyu, et al.
Green Energy and Intelligent Transportation (2024) Vol. 3, Iss. 5, pp. 100169-100169
Open Access | Times Cited: 8
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