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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:

State of health prediction for li-ion batteries with end-to-end deep learning
Chunxiang Zhu, Mingyu Gao, Zhiwei He, et al.
Journal of Energy Storage (2023) Vol. 65, pp. 107218-107218
Closed Access | Times Cited: 21

Showing 21 citing articles:

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
Comprehensive Review of Machine Learning, Deep Learning, and Digital Twin Data-Driven Approaches in Battery Health Prediction of Electric Vehicles
A. Pravin Renold, Neeraj Singh Kathayat
IEEE Access (2024) Vol. 12, pp. 43984-43999
Open Access | Times Cited: 11
A novel hybrid neural network-based SOH and RUL estimation method for lithium-ion batteries
Baoliang Chen, Yonggui Liu, Bin Xiao
Journal of Energy Storage (2024) Vol. 98, pp. 113074-113074
Closed Access | Times Cited: 9
Enhanced battery health monitoring in electric vehicles: A novel hybrid HBA-HGBR model
Wenjun Liao, Zilong Chen, Pingfei Li, et al.
Journal of Energy Storage (2025) Vol. 110, pp. 115316-115316
Closed Access | Times Cited: 1
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
Vibration-based anomaly pattern mining for remaining useful life (RUL) prediction in bearings
Pooja Kamat, Satish Kumar, Rekha Sugandhi
Journal of the Brazilian Society of Mechanical Sciences and Engineering (2024) Vol. 46, Iss. 5
Closed Access | Times Cited: 6
SOH and RUL prediction of lithium batteries based on fusions of RLOESS filtered electrochemical and thermal features by bidirectional gated recurrent unit network
Fei Xia, Yun Yu, Jiajun Chen
Journal of Energy Storage (2024) Vol. 102, pp. 114134-114134
Closed Access | Times Cited: 6
State of Health Estimation of Lithium-Ion Batteries Based on Hybrid Neural Networks with Residual Connections
Xugang Zhang, Ze Wang, Qingshan Gong, et al.
Journal of The Electrochemical Society (2025) Vol. 172, Iss. 2, pp. 020503-020503
Open 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
Research Progress on Data-Driven Methods for Battery States Estimation of Electric Buses
Dengfeng Zhao, Haiyang Li, Fang Zhou, et al.
World Electric Vehicle Journal (2023) Vol. 14, Iss. 6, pp. 145-145
Open Access | Times Cited: 12
Li-ion battery state-of-health estimation based on the combination of statistical and geometric features of the constant-voltage charging stage
Sizhe Chen, Zikang Liang, Haoliang Yuan, et al.
Journal of Energy Storage (2023) Vol. 72, pp. 108647-108647
Closed Access | Times Cited: 10
Lithium-ion battery state of health monitoring based on an adaptive variable fractional order multivariate grey model
Zhicun Xu, Naiming Xie, Huakang Diao
Energy (2023) Vol. 283, pp. 129167-129167
Closed Access | Times Cited: 9
Physical knowledge guided state of health estimation of lithium-ion battery with limited segment data
Fujin Wang, Ziqian Wu, Zhibin Zhao, et al.
Reliability Engineering & System Safety (2024) Vol. 251, pp. 110325-110325
Closed Access | Times Cited: 3
A Feature Extraction and Analysis Method for Battery Health Monitoring
Jilun Tian, Jiusi Zhang, Hao Luo, et al.
(2024), pp. 1-6
Closed Access | Times Cited: 1
Lithium Battery State-of-Health Estimation Based on Sample Data Generation and Temporal Convolutional Neural Network
Fang Guo, Guangshan Huang, Wencan Zhang, et al.
Energies (2023) Vol. 16, Iss. 24, pp. 8010-8010
Open Access | Times Cited: 4
Advancing Lithium-Ion Battery Health Assessment: A Novel Approach Through Multi-Feature Fusion and Swin-Transformer Modeling
Simin Yang, Xiaojun Tan, Jiagen Li, et al.
(2024)
Closed Access
Remaining Useful Life Prediction of Lithium-ion Batteries Based on DBO-CNN-DSformer
Congbo Yin, Xiaoyu Shen, Chengbin Wang, et al.
Electrochimica Acta (2024) Vol. 508, pp. 145123-145123
Closed Access
Improving electric vehicles sustainability: Accurate forecasting of lithium-ion battery health using machine learning models
Chao Yang, Zhihao Ye, Xin Xiong, et al.
Journal of Energy Storage (2024) Vol. 103, pp. 114280-114280
Closed Access
A unified GPR model based on transfer learning for SOH prediction of lithium-ion batteries
Li Cai
Journal of Process Control (2024) Vol. 144, pp. 103337-103337
Closed Access
Prediction of remaining service life of lithium battery based on VMD-MC-BiLSTM
Meng Guangxiong, Liang Zhongnan, Mou Zhongyi
Frontiers in Energy Research (2024) Vol. 12
Open Access
Enhanced prediction of end-point carbon content in electric arc furnaces using Bayesian optimised fully connected neural networks with early stopping
Hong‐Chun Zhu, Hongbin Lu, Zhouhua Jiang, et al.
Ironmaking & Steelmaking Processes Products and Applications (2024)
Closed Access
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