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Lookup NU author(s): Professor Cheng Chin
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The durability is a key factor of fuel cell in large-scale application of automobiles. It is great important to real the lifetime and health status of fuel cells, especially in vehicle driving conditions. Based on the experimental data, this paper used the model-based method and data-driven method to predict the life of fuel cells, respectively. The model-based method established the equivalent circuit model according to the mapping law of electrochemical impedance spectroscopy (EIS) and the parameters of the equivalent circuit model were identified by newly considering the phenomenon of voltage recovery, revealing the strong linear correlation between impedance and voltage. The data-driven method selected a combinatorial optimization PSO-LSSVM algorithm and compared it with the prediction results of MATLAB's time series toolbox. The results show the mean square error (MSE), End of Life (EOL) of the model-based method, the time series toolbox and PSO-LSSVM algorithm are 0.019, 8.2 × 10−3 and 4.42 × 10−5, the 260h, 438h and 427h, respectively. Comparing with the real EOL of 421h, the error of PSO-LSSVM algorithm is only 6 h, which means the remaining useful life can be predicted with high accurately. Thus this study provides a reference for fault identification and life prediction of fuel cell health management.
Author(s): Huang W, Liu M, Zhang C, Niu T, Fu Z, Ren X, Chin CS
Publication type: Article
Publication status: Published
Journal: International Journal of Hydrogen Energy
Year: 2024
Volume: 79
Pages: 364-376
Print publication date: 19/08/2024
Online publication date: 08/07/2024
Acceptance date: 03/07/2016
ISSN (print): 0360-3199
ISSN (electronic): 1879-3487
Publisher: Elsevier
URL: https://doi.org/10.1016/j.ijhydene.2024.07.029
DOI: 10.1016/j.ijhydene.2024.07.029
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