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Deep learning based prognostic framework towards proton exchange membrane fuel cell for automotive application

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  1. Zhang, Chu & Hu, Haowen & Ji, Jie & Liu, Kang & Xia, Xin & Nazir, Muhammad Shahzad & Peng, Tian, 2023. "An evolutionary stacked generalization model based on deep learning and improved grasshopper optimization algorithm for predicting the remaining useful life of PEMFC," Applied Energy, Elsevier, vol. 330(PA).
  2. Deng, Zhihua & Chan, Siew Hwa & Chen, Qihong & Liu, Hao & Zhang, Liyan & Zhou, Keliang & Tong, Sirui & Fu, Zhichao, 2023. "Efficient degradation prediction of PEMFCs using ELM-AE based on fuzzy extension broad learning system," Applied Energy, Elsevier, vol. 331(C).
  3. Theissler, Andreas & Pérez-Velázquez, Judith & Kettelgerdes, Marcel & Elger, Gordon, 2021. "Predictive maintenance enabled by machine learning: Use cases and challenges in the automotive industry," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
  4. Zhang, Kefei & Cao, Hua & Thé, Jesse & Yu, Hesheng, 2022. "A hybrid model for multi-step coal price forecasting using decomposition technique and deep learning algorithms," Applied Energy, Elsevier, vol. 306(PA).
  5. Xuan Meng & Jian Mei & Xingwang Tang & Jinhai Jiang & Chuanyu Sun & Kai Song, 2024. "The Degradation Prediction of Proton Exchange Membrane Fuel Cell Performance Based on a Transformer Model," Energies, MDPI, vol. 17(12), pages 1-13, June.
  6. Mojgan Fayyazi & Paramjotsingh Sardar & Sumit Infent Thomas & Roonak Daghigh & Ali Jamali & Thomas Esch & Hans Kemper & Reza Langari & Hamid Khayyam, 2023. "Artificial Intelligence/Machine Learning in Energy Management Systems, Control, and Optimization of Hydrogen Fuel Cell Vehicles," Sustainability, MDPI, vol. 15(6), pages 1-38, March.
  7. He, Wenbin & Liu, Ting & Ming, Wuyi & Li, Zongze & Du, Jinguang & Li, Xiaoke & Guo, Xudong & Sun, Peiyan, 2024. "Progress in prediction of remaining useful life of hydrogen fuel cells based on deep learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
  8. Tao, Zihan & Zhang, Chu & Xiong, Jinlin & Hu, Haowen & Ji, Jie & Peng, Tian & Nazir, Muhammad Shahzad, 2023. "Evolutionary gate recurrent unit coupling convolutional neural network and improved manta ray foraging optimization algorithm for performance degradation prediction of PEMFC," Applied Energy, Elsevier, vol. 336(C).
  9. Li, Da & Zhang, Zhaosheng & Zhou, Litao & Liu, Peng & Wang, Zhenpo & Deng, Junjun, 2022. "Multi-time-step and multi-parameter prediction for real-world proton exchange membrane fuel cell vehicles (PEMFCVs) toward fault prognosis and energy consumption prediction," Applied Energy, Elsevier, vol. 325(C).
  10. Liu, Ze & Xu, Sichuan & Zhao, Honghui & Wang, Yupeng, 2022. "Durability estimation and short-term voltage degradation forecasting of vehicle PEMFC system: Development and evaluation of machine learning models," Applied Energy, Elsevier, vol. 326(C).
  11. Yue, Meiling & Jemei, Samir & Zerhouni, Noureddine & Gouriveau, Rafael, 2021. "Proton exchange membrane fuel cell system prognostics and decision-making: Current status and perspectives," Renewable Energy, Elsevier, vol. 179(C), pages 2277-2294.
  12. Chen, Dongfang & Wu, Wenlong & Chang, Kuanyu & Li, Yuehua & Pei, Pucheng & Xu, Xiaoming, 2023. "Performance degradation prediction method of PEM fuel cells using bidirectional long short-term memory neural network based on Bayesian optimization," Energy, Elsevier, vol. 285(C).
  13. Deng, Huiwen & Hu, Weihao & Cao, Di & Chen, Weirong & Huang, Qi & Chen, Zhe & Blaabjerg, Frede, 2022. "Degradation trajectories prognosis for PEM fuel cell systems based on Gaussian process regression," Energy, Elsevier, vol. 244(PA).
  14. Daeichian, Abolghasem & Ghaderi, Razieh & Kandidayeni, Mohsen & Soleymani, Mehdi & Trovão, João P. & Boulon, Loïc, 2021. "Online characteristics estimation of a fuel cell stack through covariance intersection data fusion," Applied Energy, Elsevier, vol. 292(C).
  15. Zhang, Zhendong & Wang, Ya-Xiong & He, Hongwen & Sun, Fengchun, 2021. "A short- and long-term prognostic associating with remaining useful life estimation for proton exchange membrane fuel cell," Applied Energy, Elsevier, vol. 304(C).
  16. Benaggoune, Khaled & Yue, Meiling & Jemei, Samir & Zerhouni, Noureddine, 2022. "A data-driven method for multi-step-ahead prediction and long-term prognostics of proton exchange membrane fuel cell," Applied Energy, Elsevier, vol. 313(C).
  17. Zhuang Tian & Zheng Wei & Jinhui Wang & Yinxiang Wang & Yuwei Lei & Ping Hu & S. M. Muyeen & Daming Zhou, 2023. "Research Progress on Aging Prediction Methods for Fuel Cells: Mechanism, Methods, and Evaluation Criteria," Energies, MDPI, vol. 16(23), pages 1-21, November.
  18. Lei Pan & Tong Zhang & Yuan Gao, 2023. "Real-Time Control of Gas Supply System for a PEMFC Cold-Start Based on the MADDPG Algorithm," Energies, MDPI, vol. 16(12), pages 1-20, June.
  19. Lv, Jianfeng & Shen, Xiaoning & Gao, Yabin & Liu, Jianxing & Sun, Guanghui, 2024. "The seasonal-trend disentangle based prognostic framework for PEM fuel cells," Renewable Energy, Elsevier, vol. 228(C).
  20. Mukhtar Sani & Maxime Piffard & Vincent Heiries, 2023. "Fault Detection for PEM Fuel Cells via Analytical Redundancy: A Critical Review and Prospects," Energies, MDPI, vol. 16(14), pages 1-16, July.
  21. Zhang, Zhendong & He, Hongwen & Wang, Yaxiong & Quan, Shengwei & Chen, Jinzhou & Han, Ruoyan, 2024. "A novel generalized prognostic method of proton exchange membrane fuel cell using multi-point estimation under various operating conditions," Applied Energy, Elsevier, vol. 357(C).
  22. Wang, Shunli & Wu, Fan & Takyi-Aninakwa, Paul & Fernandez, Carlos & Stroe, Daniel-Ioan & Huang, Qi, 2023. "Improved singular filtering-Gaussian process regression-long short-term memory model for whole-life-cycle remaining capacity estimation of lithium-ion batteries adaptive to fast aging and multi-curren," Energy, Elsevier, vol. 284(C).
  23. Wang, Chu & Dou, Manfeng & Li, Zhongliang & Outbib, Rachid & Zhao, Dongdong & Zuo, Jian & Wang, Yuanlin & Liang, Bin & Wang, Peng, 2023. "Data-driven prognostics based on time-frequency analysis and symbolic recurrent neural network for fuel cells under dynamic load," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
  24. Yu, Yang & Yu, Qinghua & Luo, RunSen & Chen, Sheng & Yang, Jiebo & Yan, Fuwu, 2024. "Degradation and polarization curve prediction of proton exchange membrane fuel cells: An interpretable model perspective," Applied Energy, Elsevier, vol. 365(C).
  25. Zuo, Jian & Steiner, Nadia Yousfi & Li, Zhongliang & Hissel, Daniel, 2024. "Health management review for fuel cells: Focus on action phase," Renewable and Sustainable Energy Reviews, Elsevier, vol. 201(C).
  26. Danqi Su & Jiayang Zheng & Junjie Ma & Zizhe Dong & Zhangjie Chen & Yanzhou Qin, 2023. "Application of Machine Learning in Fuel Cell Research," Energies, MDPI, vol. 16(11), pages 1-32, May.
  27. Chen, Kui & Badji, Abderrezak & Laghrouche, Salah & Djerdir, Abdesslem, 2022. "Polymer electrolyte membrane fuel cells degradation prediction using multi-kernel relevance vector regression and whale optimization algorithm," Applied Energy, Elsevier, vol. 318(C).
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