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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:

Health and lifespan prediction considering degradation patterns of lithium-ion batteries based on transferable attention neural network
Aihua Tang, Yihan Jiang, Yuwei Nie, et al.
Energy (2023) Vol. 279, pp. 128137-128137
Closed Access | Times Cited: 26

Showing 1-25 of 26 citing articles:

State of health prediction of lithium-ion batteries under early partial data based on IWOA-BiLSTM with single feature
Yan Ma, Jiaqi Li, Jinwu Gao, et al.
Energy (2024) Vol. 295, pp. 131085-131085
Closed Access | Times Cited: 23
Battery state of health estimation under dynamic operations with physics-driven deep learning
Aihua Tang, Yuchen Xu, Yuanzhi Hu, et al.
Applied Energy (2024) Vol. 370, pp. 123632-123632
Closed Access | Times Cited: 23
Data-physics-driven estimation of battery state of charge and capacity
Aihua Tang, Yukun Huang, Yuchen Xu, et al.
Energy (2024) Vol. 294, pp. 130776-130776
Closed Access | Times Cited: 21
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
Battery Remaining Useful Life Prediction Using Machine Learning Models: A Comparative Study
Vahid Safavi, Arash Mohammadi, Najmeh Bazmohammadi, et al.
Information (2024) Vol. 15, Iss. 3, pp. 124-124
Open Access | Times Cited: 9
Multiscale modeling for enhanced battery health analysis: Pathways to longevity
Kaiyi Yang, Lisheng Zhang, Wentao Wang, et al.
Carbon Neutralization (2024) Vol. 3, Iss. 3, pp. 348-385
Open Access | Times Cited: 7
Aging abnormality detection of lithium-ion batteries combining feature engineering and deep learning
Jingcai Du, Caiping Zhang, Shuowei Li, et al.
Energy (2024) Vol. 297, pp. 131276-131276
Closed Access | Times Cited: 5
A survey on few-shot learning for remaining useful life prediction
Renpeng Mo, Han Zhou, Hongpeng Yin, et al.
Reliability Engineering & System Safety (2025), pp. 110850-110850
Closed Access
Early prediction of battery lifetime for lithium-ion batteries based on a hybrid clustered CNN model
Jing Hou, Taian Su, Tian Gao, et al.
Energy (2025), pp. 134992-134992
Closed Access
Week-level early warning strategy for thermal runaway risk based on real-scenario operating data of electric vehicles
Aihua Tang, Zikang Wu, Tingting Xu, et al.
eTransportation (2023) Vol. 19, pp. 100308-100308
Closed Access | Times Cited: 13
State of health estimation based on inconsistent evolution for lithium-ion battery module
Aihua Tang, Xinyu Wu, Tingting Xu, et al.
Energy (2023) Vol. 286, pp. 129575-129575
Closed Access | Times Cited: 12
A critical review on prognostics for stochastic degrading systems under big data
Huiqin Li, Xiaosheng Si, Zhengxin Zhang, et al.
Fundamental Research (2024)
Open Access | Times Cited: 4
State of health estimation approach for Li-ion batteries based on mechanism feature empowerment
Lei Yao, Jishu Wen, Yanqiu Xiao, et al.
Journal of Energy Storage (2024) Vol. 84, pp. 110965-110965
Closed Access | Times Cited: 4
Efficacy assessment for multi-vehicle formations based on data augmentation considering reliability
Haoran Zhang, Ruohan Yang, Wei He
Advanced Engineering Informatics (2024) Vol. 61, pp. 102504-102504
Closed Access | Times Cited: 4
A Novel Online State-of-Health Estimation Method for Lithium-Ion Batteries with Multi-Input Metabolic Long Short-Term Memory Framework
Lin Chen, Deqian Chen, Manping He, et al.
Energies (2025) Vol. 18, Iss. 5, pp. 1037-1037
Open Access
Feature selection of battery capacity estimation method based on deep learning
Jiangtao Xu, Jie Qu, Haitao Xu
Journal of Power Sources (2025) Vol. 640, pp. 236809-236809
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
Enhancing lithium-ion battery lifespan early prediction using a multi-branch vision transformer model
Wanjie Zhao, Wei Ding, Shujing Zhang, et al.
Energy (2024) Vol. 302, pp. 131816-131816
Closed Access | Times Cited: 3
Future degradation trajectory prediction of lithium-ion battery based on a three-step similarity evaluation criterion for battery selection and transfer learning
Yongfang Guo, Yashuang Wang, P. Ding, et al.
Journal of Energy Storage (2023) Vol. 72, pp. 108763-108763
Closed Access | Times Cited: 8
Deep learning powered lifetime prediction for lithium-ion batteries based on small amounts of charging cycles
Yunpeng Liu, Moin Ahmed, Jiangtao Feng, et al.
IEEE Transactions on Transportation Electrification (2024) Vol. 11, Iss. 1, pp. 3078-3090
Closed Access | Times Cited: 2
State of Health Prediction of Lithium-Ion Batteries Under Early Partial Data Based on IWOA-BILSTM with Single Feature
Yan Ma, Jiaqi Li, Jinwu Gao, et al.
(2024)
Closed Access | Times Cited: 1
Toward understandable semi-supervised learning fault diagnosis of chemical processes based on long short-term memory ladder autoencoder (LSTM-LAE) and self-attention (SA)
Jing Yang, Xiaolong Ge, Botan Liu
Computers & Chemical Engineering (2024) Vol. 189, pp. 108817-108817
Closed Access | Times Cited: 1
Extracting Key Temporal and Cyclic Features from VIT Data to Predict Lithium-Ion Battery Knee Points Using Attention Mechanisms.
Jae‐Wook Lee, Seongmin Heo, Jay H. Lee
Computers & Chemical Engineering (2024), pp. 108931-108931
Closed Access | Times Cited: 1
Early Prediction of Battery Lifetime for Lithium-Ion Batteries Based on a Hybrid Clustered Cnn Model
Jing Hou, Taian Su, Tian Gao, et al.
(2024)
Closed Access
Remaining useful life prediction of lithium-ion batteries based on performance degradation mechanism analysis and improved Deep Extreme Learning Machine model
Renjun Feng, Shunli Wang, Chunmei Yu, et al.
Ionics (2024) Vol. 30, Iss. 9, pp. 5449-5471
Closed Access
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