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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:

Specialized deep neural networks for battery health prognostics: Opportunities and challenges
Jingyuan Zhao, Xuebing Han, Minggao Ouyang, et al.
Journal of Energy Chemistry (2023) Vol. 87, pp. 416-438
Closed Access | Times Cited: 57

Showing 1-25 of 57 citing articles:

Battery safety: Machine learning-based prognostics
Jingyuan Zhao, Xuning Feng, Quanquan Pang, et al.
Progress in Energy and Combustion Science (2024) Vol. 102, pp. 101142-101142
Open Access | Times Cited: 53
Battery safety: Fault diagnosis from laboratory to real world
Jingyuan Zhao, Xuning Feng, Manh‐Kien Tran, et al.
Journal of Power Sources (2024) Vol. 598, pp. 234111-234111
Open Access | Times Cited: 48
Battery fault diagnosis and failure prognosis for electric vehicles using spatio-temporal transformer networks
Jingyuan Zhao, Xuning Feng, Junbin Wang, et al.
Applied Energy (2023) Vol. 352, pp. 121949-121949
Closed Access | Times Cited: 42
Rapid health estimation of in-service battery packs based on limited labels and domain adaptation
Zhongwei Deng, Le Xu, Hongao Liu, et al.
Journal of Energy Chemistry (2023) Vol. 89, pp. 345-354
Closed Access | Times Cited: 41
Insights and reviews on battery lifetime prediction from research to practice
Xudong Qu, Dapai Shi, Jingyuan Zhao, et al.
Journal of Energy Chemistry (2024) Vol. 94, pp. 716-739
Closed Access | Times Cited: 24
Battery pack capacity estimation for electric vehicles based on enhanced machine learning and field data
Qingguang Qi, Wenxue Liu, Zhongwei Deng, et al.
Journal of Energy Chemistry (2024) Vol. 92, pp. 605-618
Closed Access | Times Cited: 18
A Comparative Analysis of Generative Artificial Intelligence Tools for Natural Language Processing
Aamo Iorliam, Joseph Abunimye Ingio
Journal of Computing Theories and Applications (2024) Vol. 1, Iss. 3, pp. 311-325
Open Access | Times Cited: 18
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
Fault prognosis of Li-ion batteries in electric vehicles: Recent progress, challenges and prospects
Heng Li, Muaaz Bin Kaleem, Kailong Liu, et al.
Journal of Energy Storage (2025) Vol. 116, pp. 116002-116002
Closed Access | Times Cited: 1
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
Exploring impedance spectrum for lithium-ion batteries diagnosis and prognosis: A comprehensive review
Xinghao Du, Jinhao Meng, Yassine Amirat, et al.
Journal of Energy Chemistry (2024) Vol. 95, pp. 464-483
Open Access | Times Cited: 13
Artificial intelligence-driven real-world battery diagnostics
Jingyuan Zhao, Xudong Qu, Yuyan Wu, et al.
Energy and AI (2024) Vol. 18, pp. 100419-100419
Open Access | Times Cited: 11
Deep machine learning approaches for battery health monitoring
Sanjeev Kumar Singh, P. R. Budarapu
Energy (2024) Vol. 300, pp. 131540-131540
Closed Access | Times Cited: 10
Specialized Convolutional Transformer Networks for Estimating Battery Health via Transfer Learning
Jingyuan Zhao, Zhenghong Wang
Energy storage materials (2024) Vol. 71, pp. 103668-103668
Closed Access | Times Cited: 10
Recent Progress of Deep Learning Methods for Health Monitoring of Lithium-Ion Batteries
Seyed Saeed Madani, Carlos Ziebert, Parisa Vahdatkhah, et al.
Batteries (2024) Vol. 10, Iss. 6, pp. 204-204
Open Access | Times Cited: 8
AI and machine learning in climate change research: A review of predictive models and environmental impact
Ahmad Hamdan, Kenneth Ifeanyi Ibekwe, Emmanuel Augustine Etukudoh, et al.
World Journal of Advanced Research and Reviews (2024) Vol. 21, Iss. 1, pp. 1999-2008
Open Access | Times Cited: 7
Vehicle-cloud-collaborated prognosis and health management for lithium-ion batteries: framework, technics and perspective
Sida Zhou, Gao Zichao, Honglei Dong, et al.
Energy storage materials (2024) Vol. 70, pp. 103531-103531
Closed Access | Times Cited: 7
Vehicle choice modeling for emerging zero-emission light-duty vehicle markets in California
Andrew Burke, Jingyuan Zhao, Marshall R. Miller, et al.
Heliyon (2024) Vol. 10, Iss. 12, pp. e32823-e32823
Open Access | Times Cited: 7
Optimized XGBoost modeling for accurate battery capacity degradation prediction
Sadiqa Jafari, Ji-Hyeok Yang, Yung-Cheol Byun
Results in Engineering (2024), pp. 102786-102786
Open Access | Times Cited: 7
Battery Engineering Safety Technologies (BEST): Mechanisms, Modes, Metrics, Modelling and Mitigation
Jingyuan Zhao, Zhilong Lv, Di Li, et al.
eTransportation (2024), pp. 100364-100364
Closed Access | Times Cited: 6
A generic fusion framework integrating deep learning and Kalman filter for state of charge estimation of lithium-ion batteries: Analysis and comparison
Hanqing Yu, He Lu, Zhengjie Zhang, et al.
Journal of Power Sources (2024) Vol. 623, pp. 235493-235493
Closed Access | Times Cited: 5
A semi-supervised learning strategy for lithium-ion battery capacity estimation with limited impedance data
Yan Li, Zi He, Min Ye, et al.
Energy (2025), pp. 135129-135129
Closed Access
Artificial Intelligence in Gas Sensing: A Review
M. Arshad Zahangir Chowdhury, Matthew A. Oehlschlaeger
ACS Sensors (2025)
Closed Access
Battery pack capacity prediction using deep learning and data compression technique: a method for real-world vehicles
Yi Yang, Jibin Yang, Xiaohua Wu, et al.
Journal of Energy Chemistry (2025)
Closed Access
A comprehensive review of the dairy pasteurization process using machine learning models
Poornima Singh, Surabhi Pandey, Subhadip Manik
Food Control (2024) Vol. 164, pp. 110574-110574
Closed Access | Times Cited: 4
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