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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:

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: 17

Showing 17 citing articles:

A review of data-driven whole-life state of health prediction for lithium-ion batteries: Data preprocessing, aging characteristics, algorithms, and future challenges
Yanxin Xie, Shunli Wang, Gexiang Zhang, et al.
Journal of Energy Chemistry (2024) Vol. 97, pp. 630-649
Closed Access | Times Cited: 25
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
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
State-of-health estimation for fast-charging lithium-ion batteries based on a short charge curve using graph convolutional and long short-term memory networks
Yvxin He, Zhongwei Deng, Jue Chen, et al.
Journal of Energy Chemistry (2024) Vol. 98, pp. 1-11
Closed Access | Times Cited: 11
Big field data-driven battery pack health estimation for electric vehicles: A deep-fusion transfer learning approach
Hongao Liu, Zhongwei Deng, Yunhong Che, et al.
Mechanical Systems and Signal Processing (2024) Vol. 218, pp. 111585-111585
Closed Access | Times Cited: 9
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
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
Multi-modal framework for battery state of health evaluation using open-source electric vehicle data
Hongao Liu, Chang Li, Xiaosong Hu, et al.
Nature Communications (2025) Vol. 16, Iss. 1
Open Access
Early prediction of battery knee interval before capacity degradation
Y.Y. Yu, Shunfeng Yang, Gucheng Wang, et al.
Journal of Power Sources (2025) Vol. 633, pp. 236438-236438
Closed Access
TELL-Me: a time-series-decomposition-based ensembled lightweight learning model for diverse battery prognosis and diagnosis
Kopin Liu, Tingting Wang, Bobo Zou, et al.
Journal of Energy Chemistry (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
Flexible bidirectional pulse charging regulation achieving long-life lithium-ion batteries
Xiaodong Xu, Shengjin Tang, Xuebing Han, et al.
Journal of Energy Chemistry (2024) Vol. 96, pp. 59-71
Closed Access | Times Cited: 3
A Data Augmentation Method for Lithium‐Ion Battery Capacity Estimation Based on Wassertein Time Generative Adversarial Network
Yin‐Yi Soo, Yujie Wang, Haoxiang Xiang, et al.
Energy Technology (2024)
Closed Access | Times Cited: 3
State‐of‐health estimation of lithium‐ion batteries: A comprehensive literature review from cell to pack levels
Lingzhi Su, Yan Xu, Zhaoyang Dong
Energy Conversion and Economics (2024) Vol. 5, Iss. 4, pp. 224-242
Open Access | Times Cited: 3
State of Health Estimations for Lithium-Ion Batteries Based on MSCNN
J. L. Wang, Hao Li, Chunling Wu, et al.
Energies (2024) Vol. 17, Iss. 17, pp. 4220-4220
Open Access | Times Cited: 2
Capacity estimation of lithium-ion battery through interpretation of electrochemical impedance spectroscopy combined with machine learning
Yan Li, Min Ye, Qiao Wang, et al.
Measurement (2024), pp. 116374-116374
Closed Access | Times Cited: 2
An IoT-based predictive model for improved battery management system using advanced LSTM model
Gopal Krishna, Rajesh Singh, Anita Gehlot, et al.
Journal of Energy Storage (2024) Vol. 101, pp. 113694-113694
Closed Access | Times Cited: 1
State of Charge Estimation of Lithium‐Ion Batteries with Adaptive Square Root Central Difference Kalman Filter
Hongbo Du, Yuan Yuan, Wei Zheng, et al.
Advanced Theory and Simulations (2024) Vol. 7, Iss. 11
Open Access
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