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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:

Combining empirical mode decomposition and deep recurrent neural networks for predictive maintenance of lithium-ion battery
James C. Chen, Tzu‐Li Chen, Weijun Liu, et al.
Advanced Engineering Informatics (2021) Vol. 50, pp. 101405-101405
Closed Access | Times Cited: 99

Showing 1-25 of 99 citing articles:

Improved anti-noise adaptive long short-term memory neural network modeling for the robust remaining useful life prediction of lithium-ion batteries
Shunli Wang, Yongcun Fan, Siyu Jin, et al.
Reliability Engineering & System Safety (2022) Vol. 230, pp. 108920-108920
Open Access | Times Cited: 336
Deep learning models for predictive maintenance: a survey, comparison, challenges and prospects
Oscar Serradilla, Ekhi Zugasti, Jon Rodriguez, et al.
Applied Intelligence (2022) Vol. 52, Iss. 10, pp. 10934-10964
Closed Access | Times Cited: 130
Multi-scale integrated deep self-attention network for predicting remaining useful life of aero-engine
Ke Zhao, Zhen Jia, Feng Jia, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 120, pp. 105860-105860
Closed Access | Times Cited: 128
A data-driven method for extracting aging features to accurately predict the battery health
Rui Xiong, Yue Sun, Chenxu Wang, et al.
Energy storage materials (2023) Vol. 57, pp. 460-470
Closed Access | Times Cited: 87
The development of machine learning-based remaining useful life prediction for lithium-ion batteries
Xingjun Li, Dan Yu, Søren Byg Vilsen, et al.
Journal of Energy Chemistry (2023) Vol. 82, pp. 103-121
Open Access | Times Cited: 85
An overview of data-driven battery health estimation technology for battery management system
Minzhi Chen, Guijun Ma, Weibo Liu, et al.
Neurocomputing (2023) Vol. 532, pp. 152-169
Closed Access | Times Cited: 73
Artificial Intelligence for Predictive Maintenance Applications: Key Components, Trustworthiness, and Future Trends
Ayşegül Uçar, Mehmet Karaköse, Necim Kırımça
Applied Sciences (2024) Vol. 14, Iss. 2, pp. 898-898
Open Access | Times Cited: 55
Research progress and application of deep learning in remaining useful life, state of health and battery thermal management of lithium batteries
Wenbin He, Zongze Li, Ting Liu, et al.
Journal of Energy Storage (2023) Vol. 70, pp. 107868-107868
Closed Access | Times Cited: 42
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
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
A hybrid method for prognostics of lithium-ion batteries capacity considering regeneration phenomena
Huixing Meng, Mengyao Geng, Jinduo Xing, et al.
Energy (2022) Vol. 261, pp. 125278-125278
Closed Access | Times Cited: 56
An ameliorated African vulture optimization algorithm to diagnose the rolling bearing defects
Govind Vashishtha, Sumika Chauhan, Anil Kumar, et al.
Measurement Science and Technology (2022) Vol. 33, Iss. 7, pp. 075013-075013
Closed Access | Times Cited: 41
Data-driven prognostics based on time-frequency analysis and symbolic recurrent neural network for fuel cells under dynamic load
Chu Wang, Manfeng Dou, Zhongliang Li, et al.
Reliability Engineering & System Safety (2023) Vol. 233, pp. 109123-109123
Open Access | Times Cited: 38
Advancements in Artificial Neural Networks for health management of energy storage lithium-ion batteries: A comprehensive review
Yuntao Zou, Zihui Lin, Dagang Li, et al.
Journal of Energy Storage (2023) Vol. 73, pp. 109069-109069
Closed Access | Times Cited: 37
Remaining useful life prediction via a deep adaptive transformer framework enhanced by graph attention network
Pengfei Liang, Ying Li, Bin Wang, et al.
International Journal of Fatigue (2023) Vol. 174, pp. 107722-107722
Closed Access | Times Cited: 36
Non-parametric Ensemble Empirical Mode Decomposition for extracting weak features to identify bearing defects
Anil Kumar, Yaakoub Berrouche, Radosław Zimroz, et al.
Measurement (2023) Vol. 211, pp. 112615-112615
Open Access | Times Cited: 35
Towards machine-learning driven prognostics and health management of Li-ion batteries. A comprehensive review
Sahar Khaleghi, Md Sazzad Hosen, Joeri Van Mierlo, et al.
Renewable and Sustainable Energy Reviews (2023) Vol. 192, pp. 114224-114224
Closed Access | Times Cited: 34
A Lithium-Ion Battery Degradation Prediction Model With Uncertainty Quantification for Its Predictive Maintenance
Chuang Chen, Guanye Tao, Jiantao Shi, et al.
IEEE Transactions on Industrial Electronics (2023) Vol. 71, Iss. 4, pp. 3650-3659
Closed Access | Times Cited: 28
A wiener-based remaining useful life prediction method with multiple degradation patterns
Yuxiong Li, Xianzhen Huang, Tianhong Gao, et al.
Advanced Engineering Informatics (2023) Vol. 57, pp. 102066-102066
Closed Access | Times Cited: 24
Open access dataset, code library and benchmarking deep learning approaches for state-of-health estimation of lithium-ion batteries
Fujin Wang, Zhi Zhai, Bingchen Liu, et al.
Journal of Energy Storage (2023) Vol. 77, pp. 109884-109884
Closed Access | Times Cited: 23
Data driven health and life prognosis management of supercapacitor and lithium-ion battery storage systems: Developments, implementation aspects, limitations, and future directions
Molla Shahadat Hossain Lipu, M. Rahman, Muhamad Mansor, et al.
Journal of Energy Storage (2024) Vol. 98, pp. 113172-113172
Closed Access | Times Cited: 11
Adaptive internal short-circuit fault detection for lithium-ion batteries of electric vehicles
Xiaoyong Zhang, Wenhao Yang, Lisen Yan, et al.
Journal of Energy Storage (2024) Vol. 84, pp. 110874-110874
Closed Access | Times Cited: 10
A survey of deep learning-driven architecture for predictive maintenance
Zhe Li, Qian He, Jingyue Li
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108285-108285
Open Access | Times Cited: 8
MST-GAT: A multi-perspective spatial-temporal graph attention network for multi-sensor equipment remaining useful life prediction
Liang Zhou, Huawei Wang
Information Fusion (2024) Vol. 110, pp. 102462-102462
Closed Access | Times Cited: 8
State‐of‐Health Prediction for Lithium‐Ion Batteries Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise‐Gate Recurrent Unit Fusion Model
Fei Xia, Kangan Wang, Jiajun Chen
Energy Technology (2022) Vol. 10, Iss. 4
Closed Access | Times Cited: 29
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