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Extended Kalman Filter for prognostic of Proton Exchange Membrane Fuel Cell

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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. Jouin, Marine & Bressel, Mathieu & Morando, Simon & Gouriveau, Rafael & Hissel, Daniel & Péra, Marie-Cécile & Zerhouni, Noureddine & Jemei, Samir & Hilairet, Mickael & Ould Bouamama, Belkacem, 2016. "Estimating the end-of-life of PEM fuel cells: Guidelines and metrics," Applied Energy, Elsevier, vol. 177(C), pages 87-97.
  3. Wang, Yiwei & Gogu, Christian & Kim, Nam H. & Haftka, Raphael T. & Binaud, Nicolas & Bes, Christian, 2019. "Noise-dependent ranking of prognostics algorithms based on discrepancy without true damage information," Reliability Engineering and System Safety, Elsevier, vol. 184(C), pages 86-100.
  4. Yuan, Hao & Dai, Haifeng & Wei, Xuezhe & Ming, Pingwen, 2020. "A novel model-based internal state observer of a fuel cell system for electric vehicles using improved Kalman filter approach," Applied Energy, Elsevier, vol. 268(C).
  5. Zhang, Caizhi & Yu, Xingzi & Rubel, Hossain Md & Li, Qi & Sun, Yuhui & Jiang, Shangfeng & Wang, Gucheng, 2025. "Fault-tolerant method of open-cathode PEMFC based on adaptive strong tracking Kalman filter combined with Hampel algorithm," Applied Energy, Elsevier, vol. 388(C).
  6. 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).
  7. Pei, Pucheng & Chen, Dongfang & Wu, Ziyao & Ren, Peng, 2019. "Nonlinear methods for evaluating and online predicting the lifetime of fuel cells," Applied Energy, Elsevier, vol. 254(C).
  8. Li, Changzhi & Lin, Wei & Wu, Hangyu & Li, Yang & Zhu, Wenchao & Xie, Changjun & Gooi, Hoay Beng & Zhao, Bo & Zhang, Leiqi, 2023. "Performance degradation decomposition-ensemble prediction of PEMFC using CEEMDAN and dual data-driven model," Renewable Energy, Elsevier, vol. 215(C).
  9. Pei, Pucheng & Fan, Tengbo & Ren, Peng & Wang, Mingkai & Chen, Dongfang & Meng, Yining & Tan, Mingbo & Shen, Hailin & Zhou, Wenping, 2025. "Fuel cell current degradation law and I-V performance prediction," Applied Energy, Elsevier, vol. 381(C).
  10. Qiu, Xiaoyan & Zhang, Hang & Qiu, Yiwei & Zhou, Yi & Zang, Tianlei & Zhou, Buxiang & Qi, Ruomei & Lin, Jin & Wang, Jiepeng, 2023. "Dynamic parameter estimation of the alkaline electrolysis system combining Bayesian inference and adaptive polynomial surrogate models," Applied Energy, Elsevier, vol. 348(C).
  11. Huu Linh Nguyen & Jaesu Han & Hoang Nghia Vu & Sangseok Yu, 2022. "Investigation of Multiple Degradation Mechanisms of a Proton Exchange Membrane Fuel Cell under Dynamic Operation," Energies, MDPI, vol. 15(24), pages 1-21, December.
  12. 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).
  13. 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.
  14. Ma, Yangyang & Li, Songting & Zhou, Shulin & Wang, Xueyuan & Yuan, Hao & Chang, Guofeng & Zhu, Jiangong & Dai, Haifeng & Wei, Xuezhe, 2025. "Performance degradation prediction of proton exchange membrane fuel cells based on CNN-LSTM network with squeeze-and-excitation attention mechanism," Energy, Elsevier, vol. 335(C).
  15. E. Skordilis & R. Moghaddass, 2017. "A condition monitoring approach for real-time monitoring of degrading systems using Kalman filter and logistic regression," International Journal of Production Research, Taylor & Francis Journals, vol. 55(19), pages 5579-5596, October.
  16. Wei, Ya & Stanford, Russell J., 2019. "Parameter identification of solid oxide fuel cell by Chaotic Binary Shark Smell Optimization method," Energy, Elsevier, vol. 188(C).
  17. 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).
  18. Barzegari, Mohammad M. & Dardel, Morteza & Alizadeh, Ebrahim & Ramiar, Abas, 2016. "Dynamic modeling and validation studies of dead-end cascade H2/O2 PEM fuel cell stack with integrated humidifier and separator," Applied Energy, Elsevier, vol. 177(C), pages 298-308.
  19. 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.
  20. 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.
  21. 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.
  22. 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).
  23. 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).
  24. 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.
  25. Chen, Kui & Laghrouche, Salah & Djerdir, Abdesslem, 2021. "Prognosis of fuel cell degradation under different applications using wavelet analysis and nonlinear autoregressive exogenous neural network," Renewable Energy, Elsevier, vol. 179(C), pages 802-814.
  26. Li, Jianwei & Zou, Weitao & He, Hongwen & Zhang, Chenyu & Zhai, Shuang & Wan, Xinming & Mao, Zhanxing, 2025. "Fuel cell health state estimation based on a novel dynamic degradation model under non-fixed dynamic vehicle working conditions," Applied Energy, Elsevier, vol. 391(C).
  27. Shan-Jen Cheng & Wen-Ken Li & Te-Jen Chang & Chang-Hung Hsu, 2021. "Data-Driven Prognostics of the SOFC System Based on Dynamic Neural Network Models," Energies, MDPI, vol. 14(18), pages 1-17, September.
  28. 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.
  29. Guo, Xinru & Zhang, Houcheng & Wang, Jiatang & Zhao, Jiapei & Wang, Fu & Miao, He & Yuan, Jinliang & Hou, Shujin, 2020. "A new hybrid system composed of high-temperature proton exchange fuel cell and two-stage thermoelectric generator with Thomson effect: Energy and exergy analyses," Energy, Elsevier, vol. 195(C).
  30. Abdenour Soualhi & Mourad Lamraoui & Bilal Elyousfi & Hubert Razik, 2022. "PHM SURVEY: Implementation of Prognostic Methods for Monitoring Industrial Systems," Energies, MDPI, vol. 15(19), pages 1-24, September.
  31. 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).
  32. Chen, Li & Yang, Jibin & Wu, Xiaohua & Deng, Pengyi & Xu, Xiaohui & Peng, Yiqiang, 2025. "Remaining useful life prediction of PEMFCs based on mode decomposition and hybrid method under real-world traffic conditions," Energy, Elsevier, vol. 314(C).
  33. 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).
  34. 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.
  35. Chuang Sheng & Yi Zheng & Rui Tian & Qian Xiang & Zhonghua Deng & Xiaowei Fu & Xi Li, 2023. "A Comparative Study of the Kalman Filter and the LSTM Network for the Remaining Useful Life Prediction of SOFC," Energies, MDPI, vol. 16(9), pages 1-16, April.
  36. Dong, Zhe & Liu, Miao & Guo, Zhiwu & Huang, Xiaojin & Zhang, Yajun & Zhang, Zuoyi, 2019. "Adaptive state-observer for monitoring flexible nuclear reactors," Energy, Elsevier, vol. 171(C), pages 893-909.
  37. 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).
  38. Zhu, Li & Chen, Junghui, 2018. "Prognostics of PEM fuel cells based on Gaussian process state space models," Energy, Elsevier, vol. 149(C), pages 63-73.
  39. 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).
  40. Qiang Liu & Weihong Zang & Wentao Zhang & Yang Zhang & Yuqi Tong & Yanbiao Feng, 2025. "Steady-State Model Enabled Dynamic PEMFC Performance Degradation Prediction via Recurrent Neural Network," Energies, MDPI, vol. 18(10), pages 1-20, May.
  41. 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).
  42. Chuanxue Song & Yulong Shao & Shixin Song & Silun Peng & Fang Zhou & Cheng Chang & Da Wang, 2017. "Insulation Resistance Monitoring Algorithm for Battery Pack in Electric Vehicle Based on Extended Kalman Filtering," Energies, MDPI, vol. 10(5), pages 1-13, May.
  43. 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).
  44. Zhu, Yunlong & Dong, Zhe & Cheng, Zhonghua & Huang, Xiaojin & Dong, Yujie & Zhang, Zuoyi, 2023. "Neural network extended state-observer for energy system monitoring," Energy, Elsevier, vol. 263(PA).
  45. Zuo, Jian & Steiner, Nadia Yousfi & Li, Zhongliang & Hissel, Daniel, 2025. "Degradation root cause analysis of PEM fuel cells using distribution of relaxation times," Applied Energy, Elsevier, vol. 378(PA).
  46. Ke Song & Yimin Wang & Xiao Hu & Jing Cao, 2020. "Online Prediction of Vehicular Fuel Cell Residual Lifetime Based on Adaptive Extended Kalman Filter," Energies, MDPI, vol. 13(23), pages 1-21, November.
  47. 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).
  48. 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).
  49. Ma, Rui & Yang, Tao & Breaz, Elena & Li, Zhongliang & Briois, Pascal & Gao, Fei, 2018. "Data-driven proton exchange membrane fuel cell degradation predication through deep learning method," Applied Energy, Elsevier, vol. 231(C), pages 102-115.
  50. 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).
  51. 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).
  52. 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).
  53. 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.
  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).
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