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Data-driven proton exchange membrane fuel cell degradation predication through deep learning method

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  1. Desantes, J.M. & Novella, R. & Pla, B. & Lopez-Juarez, M., 2022. "A modeling framework for predicting the effect of the operating conditions and component sizing on fuel cell degradation and performance for automotive applications," Applied Energy, Elsevier, vol. 317(C).
  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. Song, Ke & Huang, Xing & Huang, Pengyu & Sun, Hui & Chen, Yuhui & Huang, Dongya, 2024. "Data-driven health state estimation and remaining useful life prediction of fuel cells," Renewable Energy, Elsevier, vol. 227(C).
  4. Zhang, Ruiyuan & Min, Ting & Chen, Li & Kang, Qinjun & He, Ya-Ling & Tao, Wen-Quan, 2019. "Pore-scale and multiscale study of effects of Pt degradation on reactive transport processes in proton exchange membrane fuel cells," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
  5. Zhou, Yang & Ravey, Alexandre & Péra, Marie-Cecile, 2020. "Multi-mode predictive energy management for fuel cell hybrid electric vehicles using Markov driving pattern recognizer," Applied Energy, Elsevier, vol. 258(C).
  6. 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).
  7. Tianxiang Wang & Hongliang Zhou & Chengwei Zhu, 2022. "A Short-Term and Long-Term Prognostic Method for PEM Fuel Cells Based on Gaussian Process Regression," Energies, MDPI, vol. 15(13), pages 1-17, July.
  8. Wu, Kangcheng & Du, Qing & Zu, Bingfeng & Wang, Yupeng & Cai, Jun & Gu, Xin & Xuan, Jin & Jiao, Kui, 2021. "Enabling real-time optimization of dynamic processes of proton exchange membrane fuel cell: Data-driven approach with semi-recurrent sliding window method," Applied Energy, Elsevier, vol. 303(C).
  9. Zou, Wei & Froning, Dieter & Shi, Yan & Lehnert, Werner, 2020. "A least-squares support vector machine method for modeling transient voltage in polymer electrolyte fuel cells," Applied Energy, Elsevier, vol. 271(C).
  10. Wen, Kai & Jiao, Jianfeng & Zhao, Kang & Yin, Xiong & Liu, Yuan & Gong, Jing & Li, Cuicui & Hong, Bingyuan, 2023. "Rapid transient operation control method of natural gas pipeline networks based on user demand prediction," Energy, Elsevier, vol. 264(C).
  11. Li, Jianwei & Yan, Chonghao & Yang, Qingqing & Hao, Dong & Zou, Weitao & Gao, Lei & Zhao, Xuan, 2023. "Quantitative diagnosis of PEMFC membrane humidity with a vector-distance based characteristic mapping approach," Applied Energy, Elsevier, vol. 335(C).
  12. Zou, Wei & Froning, Dieter & Shi, Yan & Lehnert, Werner, 2021. "An online adaptive model for the nonlinear dynamics of fuel cell voltage," Applied Energy, Elsevier, vol. 288(C).
  13. Huu-Linh Nguyen & Sang-Min Lee & Sangseok Yu, 2023. "A Comprehensive Review of Degradation Prediction Methods for an Automotive Proton Exchange Membrane Fuel Cell," Energies, MDPI, vol. 16(12), pages 1-32, June.
  14. Chen, Kui & Laghrouche, Salah & Djerdir, Abdesslem, 2019. "Degradation model of proton exchange membrane fuel cell based on a novel hybrid method," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
  15. Mezzi, Rania & Yousfi-Steiner, Nadia & Péra, Marie Cécile & Hissel, Daniel & Larger, Laurent, 2021. "An Echo State Network for fuel cell lifetime prediction under a dynamic micro-cogeneration load profile," Applied Energy, Elsevier, vol. 283(C).
  16. Li, Haolong & Chen, Qihong & Zhang, Liyan & Liu, Li & Xiao, Peng, 2023. "Degradation prediction of proton exchange membrane fuel cell based on the multi-inputs Bi-directional long short-term memory," Applied Energy, Elsevier, vol. 344(C).
  17. Aihua Tang & Yuanhang Yang & Quanqing Yu & Zhigang Zhang & Lin Yang, 2022. "A Review of Life Prediction Methods for PEMFCs in Electric Vehicles," Sustainability, MDPI, vol. 14(16), pages 1-18, August.
  18. Tiancai Ma & Jianmiao Xu & Ruitao Li & Naiyuan Yao & Yanbo Yang, 2021. "Online Short-Term Remaining Useful Life Prediction of Fuel Cell Vehicles Based on Cloud System," Energies, MDPI, vol. 14(10), pages 1-17, May.
  19. 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).
  20. Huaqin Zhang & Jichao Hong & Zhezhe Wang & Guodong Wu, 2022. "State-Partial Accurate Voltage Fault Prognosis for Lithium-Ion Batteries Based on Self-Attention Networks," Energies, MDPI, vol. 15(22), pages 1-14, November.
  21. Zuo, Jian & Lv, Hong & Zhou, Daming & Xue, Qiong & Jin, Liming & Zhou, Wei & Yang, Daijun & Zhang, Cunman, 2021. "Deep learning based prognostic framework towards proton exchange membrane fuel cell for automotive application," Applied Energy, Elsevier, vol. 281(C).
  22. 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.
  23. Kregar, Ambrož & Tavčar, Gregor & Kravos, Andraž & Katrašnik, Tomaž, 2020. "Predictive system-level modeling framework for transient operation and cathode platinum degradation of high temperature proton exchange membrane fuel cells☆," Applied Energy, Elsevier, vol. 263(C).
  24. Tai, Xin Yee & Xing, Lei & Christie, Steve D.R. & Xuan, Jin, 2023. "Deep learning design of functionally graded porous electrode of proton exchange membrane fuel cells," Energy, Elsevier, vol. 283(C).
  25. 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).
  26. Deng, Zhihua & Chen, Qihong & Zhang, Liyan & Zong, Yi & Zhou, Keliang & Fu, Zhichao, 2020. "Control oriented data driven linear parameter varying model for proton exchange membrane fuel cell systems," Applied Energy, Elsevier, vol. 277(C).
  27. 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).
  28. Wang, Xuechao & Chen, Jinzhou & Quan, Shengwei & Wang, Ya-Xiong & He, Hongwen, 2020. "Hierarchical model predictive control via deep learning vehicle speed predictions for oxygen stoichiometry regulation of fuel cells," Applied Energy, Elsevier, vol. 276(C).
  29. Guarino, Antonio & Trinchero, Riccardo & Canavero, Flavio & Spagnuolo, Giovanni, 2022. "A fast fuel cell parametric identification approach based on machine learning inverse models," Energy, Elsevier, vol. 239(PC).
  30. 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.
  31. 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.
  32. Wang, Chu & Li, Zhongliang & Outbib, Rachid & Dou, Manfeng & Zhao, Dongdong, 2022. "Symbolic deep learning based prognostics for dynamic operating proton exchange membrane fuel cells," Applied Energy, Elsevier, vol. 305(C).
  33. Li, Shuangqi & He, Hongwen & Su, Chang & Zhao, Pengfei, 2020. "Data driven battery modeling and management method with aging phenomenon considered," Applied Energy, Elsevier, vol. 275(C).
  34. Jinquan, Guo & Hongwen, He & Jianwei, Li & Qingwu, Liu, 2022. "Driving information process system-based real-time energy management for the fuel cell bus to minimize fuel cell engine aging and energy consumption," Energy, Elsevier, vol. 248(C).
  35. Yang, Yang & Yu, Xiaoran & Zhu, Wenchao & Xie, Changjun & Zhao, Bo & Zhang, Leiqi & Shi, Ying & Huang, Liang & Zhang, Ruiming, 2023. "Degradation prediction of proton exchange membrane fuel cells with model uncertainty quantification," Renewable Energy, Elsevier, vol. 219(P2).
  36. Zhou, Yanting & Wang, Yanan & Wang, Kai & Kang, Le & Peng, Fei & Wang, Licheng & Pang, Jinbo, 2020. "Hybrid genetic algorithm method for efficient and robust evaluation of remaining useful life of supercapacitors," Applied Energy, Elsevier, vol. 260(C).
  37. Xuexia Zhang & Zixuan Yu & Weirong Chen, 2019. "Life Prediction Based on D-S ELM for PEMFC," Energies, MDPI, vol. 12(19), pages 1-15, September.
  38. Dan Wang & Haitao Min & Honghui Zhao & Weiyi Sun & Bin Zeng & Qun Ma, 2024. "A Data-Driven Prediction Method for Proton Exchange Membrane Fuel Cell Degradation," Energies, MDPI, vol. 17(4), pages 1-17, February.
  39. Mumin Rao & Li Wang & Chuangting Chen & Kai Xiong & Mingfei Li & Zhengpeng Chen & Jiangbo Dong & Junli Xu & Xi Li, 2022. "Data-Driven State Prediction and Analysis of SOFC System Based on Deep Learning Method," Energies, MDPI, vol. 15(9), pages 1-15, April.
  40. Chen, Hong & Zhan, Zhigang & Jiang, Panxing & Sun, Yahao & Liao, Liwen & Wan, Xiongbiao & Du, Qing & Chen, Xiaosong & Song, Hao & Zhu, Ruijie & Shu, Zhanhong & Li, Shang & Pan, Mu, 2022. "Whole life cycle performance degradation test and RUL prediction research of fuel cell MEA," Applied Energy, Elsevier, vol. 310(C).
  41. Niu, Zhiqiang & Bao, Zhiming & Wu, Jingtian & Wang, Yun & Jiao, Kui, 2018. "Two-phase flow in the mixed-wettability gas diffusion layer of proton exchange membrane fuel cells," Applied Energy, Elsevier, vol. 232(C), pages 443-450.
  42. Jingxuan Peng & Dongqi Zhao & Yuanwu Xu & Xiaolong Wu & Xi Li, 2023. "Comprehensive Analysis of Solid Oxide Fuel Cell Performance Degradation Mechanism, Prediction, and Optimization Studies," Energies, MDPI, vol. 16(2), pages 1-23, January.
  43. Ren, Tao & Modest, Michael F. & Fateev, Alexander & Sutton, Gavin & Zhao, Weijie & Rusu, Florin, 2019. "Machine learning applied to retrieval of temperature and concentration distributions from infrared emission measurements," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
  44. 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).
  45. Song, Ke & Ding, Yuhang & Hu, Xiao & Xu, Hongjie & Wang, Yimin & Cao, Jing, 2021. "Degradation adaptive energy management strategy using fuel cell state-of-health for fuel economy improvement of hybrid electric vehicle," Applied Energy, Elsevier, vol. 285(C).
  46. Liu, Hao & Chen, Jian & Hissel, Daniel & Lu, Jianguo & Hou, Ming & Shao, Zhigang, 2020. "Prognostics methods and degradation indexes of proton exchange membrane fuel cells: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 123(C).
  47. Liu, Di & Wang, Shaoping & Cui, Xiaoyu, 2022. "An artificial neural network supported Wiener process based reliability estimation method considering individual difference and measurement error," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
  48. Nguyen, Khanh T.P. & Medjaher, Kamal, 2019. "A new dynamic predictive maintenance framework using deep learning for failure prognostics," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 251-262.
  49. 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.
  50. 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).
  51. Hua, Zhiguang & Zheng, Zhixue & Péra, Marie-Cécile & Gao, Fei, 2020. "Remaining useful life prediction of PEMFC systems based on the multi-input echo state network," Applied Energy, Elsevier, vol. 265(C).
  52. Liu, Hao & Chen, Jian & Hissel, Daniel & Su, Hongye, 2019. "Remaining useful life estimation for proton exchange membrane fuel cells using a hybrid method," Applied Energy, Elsevier, vol. 237(C), pages 910-919.
  53. Zhou, Yang & Chen, Bo & Xu, Xianfeng & Zhang, Zhen & Ravey, Alexandre & Péra, Marie-Cécile & Ma, Ruiqing, 2024. "Data-driven cost-optimal energy management of postal-delivery fuel cell electric vehicle with intelligent dual-loop battery state-of-charge planner," Energy, Elsevier, vol. 290(C).
  54. Tang, Xingwang & Zhang, Yujia & Xu, Sichuan, 2023. "Experimental study of PEM fuel cell temperature characteristic and corresponding automated optimal temperature calibration model," Energy, Elsevier, vol. 283(C).
  55. Wu, Xiao-long & Xu, Yuan-Wu & Xue, Tao & Zhao, Dong-qi & Jiang, Jianhua & Deng, Zhonghua & Fu, Xiaowei & Li, Xi, 2019. "Health state prediction and analysis of SOFC system based on the data-driven entire stage experiment," Applied Energy, Elsevier, vol. 248(C), pages 126-140.
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