Health state prognostic of fuel cell based on wavelet neural network and cuckoo search algorithm
This paper proposes a novel degradation prognosis of Proton Exchange Membrane Fuel Cell (PEMFC) based on Wavelet Neural Network (WNN) and Cuckoo Search Algorithm (CSA). The proposed method considering the main operating conditions of PEMFC can be applied to the health state prognostic of PEMFC under...
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| Published in | ISA transactions Vol. 113; pp. 175 - 184 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Elsevier Ltd
01.07.2021
Elsevier |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0019-0578 1879-2022 1879-2022 |
| DOI | 10.1016/j.isatra.2020.03.012 |
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| Abstract | This paper proposes a novel degradation prognosis of Proton Exchange Membrane Fuel Cell (PEMFC) based on Wavelet Neural Network (WNN) and Cuckoo Search Algorithm (CSA). The proposed method considering the main operating conditions of PEMFC can be applied to the health state prognostic of PEMFC under different conditions. First, the operating data of PEMFC are reconstructed by the locally weighted scatterplot smoothing method to filter noise. Then, the WNN that can analyze the degradation characteristics of PEMFC (global degradation trend and reversible phenomena) is adopted to build the degradation model of PEMFC. Finally, the structure and parameters of WNN are optimized by CSA to improve the accuracy for the degradation prognosis of PEMFC. The optimized degradation prognosis method is used to predict the remaining useful life of PEMFC. The proposed prognostic method is validated by 3 degradation tests of PEMFC under different conditions. The results show that CSA can greatly improve the degradation prognosis accuracy of PEMFC based on WNN. The proposed CSA-WNN can achieve higher precision than other traditional prognostic methods. |
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| AbstractList | This paper proposes a novel degradation prognosis of Proton Exchange Membrane Fuel Cell (PEMFC) based on Wavelet Neural Network (WNN) and Cuckoo Search Algorithm (CSA). The proposed method considering the main operating conditions of PEMFC can be applied to the health state prognostic of PEMFC under different conditions. First, the operating data of PEMFC are reconstructed by the locally weighted scatterplot smoothing method to filter noise. Then, the WNN that can analyze the degradation characteristics of PEMFC (global degradation trend and reversible phenomena) is adopted to build the degradation model of PEMFC. Finally, the structure and parameters of WNN are optimized by CSA to improve the accuracy for the degradation prognosis of PEMFC. The optimized degradation prognosis method is used to predict the remaining useful life of PEMFC. The proposed prognostic method is validated by 3 degradation tests of PEMFC under different conditions. The results show that CSA can greatly improve the degradation prognosis accuracy of PEMFC based on WNN. The proposed CSA-WNN can achieve higher precision than other traditional prognostic methods.This paper proposes a novel degradation prognosis of Proton Exchange Membrane Fuel Cell (PEMFC) based on Wavelet Neural Network (WNN) and Cuckoo Search Algorithm (CSA). The proposed method considering the main operating conditions of PEMFC can be applied to the health state prognostic of PEMFC under different conditions. First, the operating data of PEMFC are reconstructed by the locally weighted scatterplot smoothing method to filter noise. Then, the WNN that can analyze the degradation characteristics of PEMFC (global degradation trend and reversible phenomena) is adopted to build the degradation model of PEMFC. Finally, the structure and parameters of WNN are optimized by CSA to improve the accuracy for the degradation prognosis of PEMFC. The optimized degradation prognosis method is used to predict the remaining useful life of PEMFC. The proposed prognostic method is validated by 3 degradation tests of PEMFC under different conditions. The results show that CSA can greatly improve the degradation prognosis accuracy of PEMFC based on WNN. The proposed CSA-WNN can achieve higher precision than other traditional prognostic methods. This paper proposes a novel degradation prognosis of Proton Exchange Membrane Fuel Cell (PEMFC) based on Wavelet Neural Network (WNN) and Cuckoo Search Algorithm (CSA). The proposed method considering the main operating conditions of PEMFC can be applied to the health state prognostic of PEMFC under different conditions. First, the operating data of PEMFC are reconstructed by the locally weighted scatterplot smoothing method to filter noise. Then, the WNN that can analyze the degradation characteristics of PEMFC (global degradation trend and reversible phenomena) is adopted to build the degradation model of PEMFC. Finally, the structure and parameters of WNN are optimized by CSA to improve the accuracy for the degradation prognosis of PEMFC. The optimized degradation prognosis method is used to predict the remaining useful life of PEMFC. The proposed prognostic method is validated by 3 degradation tests of PEMFC under different conditions. The results show that CSA can greatly improve the degradation prognosis accuracy of PEMFC based on WNN. The proposed CSA-WNN can achieve higher precision than other traditional prognostic methods. |
| Author | Chen, Kui Laghrouche, Salah Djerdir, Abdesslem |
| Author_xml | – sequence: 1 givenname: Kui surname: Chen fullname: Chen, Kui email: kui.chen@utbm.fr – sequence: 2 givenname: Salah surname: Laghrouche fullname: Laghrouche, Salah email: salah.laghrouche@utbm.fr – sequence: 3 givenname: Abdesslem surname: Djerdir fullname: Djerdir, Abdesslem email: abdesslem.djerdir@utbm.fr |
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| Keywords | Degradation prognosis Proton exchange membrane fuel cell Cuckoo search algorithm Remaining useful life Wavelet neural network |
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| Snippet | This paper proposes a novel degradation prognosis of Proton Exchange Membrane Fuel Cell (PEMFC) based on Wavelet Neural Network (WNN) and Cuckoo Search... |
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| SubjectTerms | Automatic Cuckoo search algorithm Degradation prognosis Electric power Engineering Sciences Fluid mechanics Mechanics Physics Proton exchange membrane fuel cell Remaining useful life Thermics Wavelet neural network |
| Title | Health state prognostic of fuel cell based on wavelet neural network and cuckoo search algorithm |
| URI | https://dx.doi.org/10.1016/j.isatra.2020.03.012 https://www.ncbi.nlm.nih.gov/pubmed/32173038 https://www.proquest.com/docview/2377683918 https://hal.science/hal-03359941 |
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