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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:

A data-driven method for multi-step-ahead prediction and long-term prognostics of proton exchange membrane fuel cell
Khaled Benaggoune, Meiling Yue, Samir Jemeï, et al.
Applied Energy (2022) Vol. 313, pp. 118835-118835
Closed Access | Times Cited: 75

Showing 1-25 of 75 citing articles:

A performance degradation prediction model for PEMFC based on bi-directional long short-term memory and multi-head self-attention mechanism
Chunchun Jia, Hongwen He, Jiaming Zhou, et al.
International Journal of Hydrogen Energy (2024) Vol. 60, pp. 133-146
Closed Access | Times Cited: 55
The Degradation Prediction of Proton Exchange Membrane Fuel Cell Performance Based on a Transformer Model
Xuan Meng, Jian Mei, Xingwang Tang, et al.
Energies (2024) Vol. 17, Iss. 12, pp. 3050-3050
Open Access | Times Cited: 17
Short-term performance degradation prediction of a commercial vehicle fuel cell system based on CNN and LSTM hybrid neural network
Bei Sun, Xudong Liu, Jiayuan Wang, et al.
International Journal of Hydrogen Energy (2022) Vol. 48, Iss. 23, pp. 8613-8628
Closed Access | Times Cited: 59
Emerging technologies in prognostics for fuel cells including direct hydrocarbon fuel cells
Samuel Jun Hoong Ong, Amani Al–Othman, Muhammad Tawalbeh
Energy (2023) Vol. 277, pp. 127721-127721
Closed Access | Times Cited: 30
Progress in prediction of remaining useful life of hydrogen fuel cells based on deep learning
Wenbin He, Ting Liu, Wuyi Ming, et al.
Renewable and Sustainable Energy Reviews (2023) Vol. 192, pp. 114193-114193
Closed Access | Times Cited: 27
Comparative study of data-driven and model-driven approaches in prediction of nuclear power plants operating parameters
Houde Song, Xiaojing Liu, Meiqi Song
Applied Energy (2023) Vol. 341, pp. 121077-121077
Closed Access | Times Cited: 24
Performance degradation prediction method of PEM fuel cells using bidirectional long short-term memory neural network based on Bayesian optimization
Dongfang Chen, Wenlong Wu, Kuanyu Chang, et al.
Energy (2023) Vol. 285, pp. 129469-129469
Closed Access | Times Cited: 23
Health state monitoring and predicting of proton exchange membrane fuel cells: A review
K. J. Li, Jichao Hong, Chi Zhang, et al.
Journal of Power Sources (2024) Vol. 612, pp. 234828-234828
Closed Access | Times Cited: 13
Fuel cell life prediction considering the recovery phenomenon of reversible voltage loss
Xuan Meng, Chuanyu Sun, Jian Mei, et al.
Journal of Power Sources (2024) Vol. 625, pp. 235634-235634
Closed Access | Times Cited: 13
Health management review for fuel cells: Focus on action phase
Jian Zuo, Nadia Yousfi Steiner, Zhongliang Li, et al.
Renewable and Sustainable Energy Reviews (2024) Vol. 201, pp. 114613-114613
Open Access | Times Cited: 11
Bearing faults classification using a new approach of signal processing combined with machine learning algorithms
Fawzi Gougam, Adel Afia, Abdenour Soualhi, et al.
Journal of the Brazilian Society of Mechanical Sciences and Engineering (2024) Vol. 46, Iss. 2
Closed Access | Times Cited: 9
A numerical study on heat transfer for serpentine-type cooling channels in a PEM fuel cell stack
Laura González-Morán, Christian Suárez, Alfredo Iranzo, et al.
Energy (2024) Vol. 307, pp. 132634-132634
Open Access | Times Cited: 8
Adaptive optimization strategy of air supply for automotive polymer electrolyte membrane fuel cell in life cycle
Zhichao Gong, Bowen Wang, Yifan Xu, et al.
Applied Energy (2022) Vol. 325, pp. 119839-119839
Closed Access | Times Cited: 31
An evolutionary stacked generalization model based on deep learning and improved grasshopper optimization algorithm for predicting the remaining useful life of PEMFC
Chu Zhang, Haowen Hu, Jie Ji, et al.
Applied Energy (2022) Vol. 330, pp. 120333-120333
Closed Access | Times Cited: 31
Model-assisted analysis and prediction of activity degradation in PEM-fuel cell cathodes
David Bernhard, Thomas Kadyk, Sebastian Kirsch, et al.
Journal of Power Sources (2023) Vol. 562, pp. 232771-232771
Closed Access | Times Cited: 20
Transformer Based Long-Term Prognostics for Dynamic Operating PEM Fuel Cells
Jianfeng Lv, Zhongliang Yu, Haochuan Zhang, et al.
IEEE Transactions on Transportation Electrification (2023) Vol. 10, Iss. 1, pp. 1747-1757
Closed Access | Times Cited: 20
Accurate long-term prognostics of proton exchange membrane fuel cells using recurrent and convolutional neural networks
Kartik Sahajpal, K.P.S. Rana, Vineet Kumar
International Journal of Hydrogen Energy (2023) Vol. 48, Iss. 78, pp. 30532-30555
Closed Access | Times Cited: 19
An interpretable data-driven method for degradation prediction of proton exchange membrane fuel cells based on temporal fusion transformer and covariates
Hong-Wei Li, Bin-Xin Qiao, Zhicheng Hou, et al.
International Journal of Hydrogen Energy (2023) Vol. 48, Iss. 66, pp. 25958-25971
Closed Access | Times Cited: 16
Generative adversarial networks for stack voltage degradation and RUL estimation in PEMFCs under static and dynamic loads
Tamilarasan Sathesh, Chong-Kai Wang, Shih-Cheng Hu, et al.
International Journal of Hydrogen Energy (2024) Vol. 89, pp. 66-83
Closed Access | Times Cited: 5
Physics-informed neural network for long-term prognostics of proton exchange membrane fuel cells
Taehwan Ko, Dukyong Kim, Jong-Seong Park, et al.
Applied Energy (2025) Vol. 382, pp. 125318-125318
Closed Access
Long-term degradation prediction method for proton exchange membrane fuel cells based on hybrid transfer learning
Zhe Li, Xiaofang Yuan, Chen Zhang, et al.
International Journal of Hydrogen Energy (2025) Vol. 106, pp. 781-789
Closed Access
A hybrid method combining degradation mechanisms and deep learning for lifetime prediction of proton exchange membrane fuel cells under dynamic load cycle conditions
Chang Ke, Kai Han, Yongzhen Wang
Journal of Power Sources (2025) Vol. 633, pp. 236464-236464
Closed Access
A novel multivariable prognostic approach for PEMFC degradation and remaining useful life prediction using random forest and temporal convolutional network
Tian Zhang, Zhengmeng Hou, LI Xiao-qin, et al.
Applied Energy (2025) Vol. 385, pp. 125569-125569
Open Access
A review of hybrid methods based remaining useful life prediction framework and SWOT analysis for energy storage systems in electric vehicle application
Turki Alsuwian, Shaheer Ansari, Muhammad Ammirrul Atiqi Mohd Zainuri, et al.
Journal of Energy Storage (2025) Vol. 117, pp. 116152-116152
Closed Access
Investigation of nonlinear accelerated degradation mechanism in fuel cell stack under dynamic driving cycles from polarization processes
Xuexia Zhang, Lei Huang, Yu Jiang, et al.
Applied Energy (2023) Vol. 355, pp. 122286-122286
Closed Access | Times Cited: 14
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