Remaining useful life prediction of PEMFC systems based on the multi-input echo state network

Citations

Cited by:

1. Jiao, Jieran & Chen, Fengxiang, 2022. "Humidity estimation of vehicle proton exchange membrane fuel cell under variable operating temperature based on adaptive sliding mode observation," Applied Energy, Elsevier, vol. 313(C).
2. Zhang, Caizhi & Zhang, Yuqi & Wang, Lei & Deng, Xiaozhi & Liu, Yang & Zhang, Jiujun, 2023. "A health management review of proton exchange membrane fuel cell for electric vehicles: Failure mechanisms, diagnosis techniques and mitigation measures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
3. 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).
4. 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).
5. Huang, Ruike & Zhang, Xuexia & Dong, Sidi & Huang, Lei & Li, Yuan, 2025. "Degradation prediction of PEM fuel cell using LSTM based on Gini gamma correlation coefficient and improved sand cat swarm optimization under dynamic operating conditions," Applied Energy, Elsevier, vol. 392(C).
6. Bai, Fan & Quan, Hong-Bing & Yin, Ren-Jie & Zhang, Zhuo & Jin, Shu-Qi & He, Pu & Mu, Yu-Tong & Gong, Xiao-Ming & Tao, Wen-Quan, 2022. "Three-dimensional multi-field digital twin technology for proton exchange membrane fuel cells," Applied Energy, Elsevier, vol. 324(C).
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. 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.
9. Li, Qi & Wang, Tianhong & Li, Shihan & Chen, Weirong & Liu, Hong & Breaz, Elena & Gao, Fei, 2021. "Online extremum seeking-based optimized energy management strategy for hybrid electric tram considering fuel cell degradation," Applied Energy, Elsevier, vol. 285(C).
10. 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).
11. 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).
12. Zhan, Yuling & Kong, Ziqian & Wang, Ziqi & Jin, Xiaohang & Xu, Zhengguo, 2024. "Remaining useful life prediction with uncertainty quantification based on multi-distribution fusion structure," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
13. 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.
14. 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.
15. 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).
16. Qian, Zhang & Hongwei, Wang & Chunlei, Liu & Yi, An, 2024. "Establishment and identification of MIMO fractional Hammerstein model with colored noise for PEMFC system," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
17. 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.
18. 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).
19. Yang, Jibin & Chen, Li & Zhang, Bo & Zhang, Han & Chen, Bo & Wu, Xiaohua & Deng, Pengyi & Xu, Xiaohui, 2025. "Remaining useful life prediction for vehicle-oriented PEMFCs based on organic gray neural network considering the influence of dual energy source synergy," Energy, Elsevier, vol. 322(C).
20. 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).
21. Gao, Qinxiang & Lei, Tao & Yao, Wenli & Zhang, Xingyu & Zhang, Xiaobin, 2023. "A health-aware energy management strategy for fuel cell hybrid electric UAVs based on safe reinforcement learning," Energy, Elsevier, vol. 283(C).
22. Zhang, Tian & Hou, Zhengmeng & Li, Xiaoqin & Chen, Qianjun & Wang, Qichen & Lüddeke, Christian & Wu, Lin & Wu, Xuning & Sun, Wei, 2025. "A novel multivariable prognostic approach for PEMFC degradation and remaining useful life prediction using random forest and temporal convolutional network," Applied Energy, Elsevier, vol. 385(C).
23. Tian, Lei & Gao, Yan & Yang, Haiyu & Wang, Renkang, 2025. "Multi-scenario long-term degradation prediction of PEMFC based on generative inference informer model," Applied Energy, Elsevier, vol. 377(PA).
24. Hou, Yanzhu & Yin, Cong & Sheng, Xia & Xu, Dechao & Chen, Junxiong & Tang, Hao, 2025. "Automotive fuel cell performance degradation prediction using Multi-Agent Cooperative Advantage Actor-Critic model," Energy, Elsevier, vol. 318(C).
25. Zhang, Pulin & Qiu, Diankai & Peng, Linfa, 2025. "Prediction of non-uniform reactions in PEMFC based on the multi-physics quantity fusion graph auto-encoder network," Applied Energy, Elsevier, vol. 383(C).
26. 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).
27. 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).
28. Jinrong Yang & Yichun Wu & Xingyang Liu, 2023. "Proton Exchange Membrane Fuel Cell Power Prediction Based on Ridge Regression and Convolutional Neural Network Data-Driven Model," Sustainability, MDPI, vol. 15(14), pages 1-31, July.
29. 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).
30. Ko, Taehwan & Kim, Dukyong & Park, Jaewoong & Lee, Seung Hwan, 2025. "Physics-informed neural network for long-term prognostics of proton exchange membrane fuel cells," Applied Energy, Elsevier, vol. 382(C).
31. 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).
32. Wu, Jinglai & Zhang, Yunqing & Ruan, Jiageng & Liang, Zhaowen & Liu, Kai, 2023. "Rule and optimization combined real-time energy management strategy for minimizing cost of fuel cell hybrid electric vehicles," Energy, Elsevier, vol. 285(C).