Channel/rib patterns optimization of a proton exchange membrane fuel cell by combining down-the-channel performance model and genetic algorithm

Author(s):  
Zihan Zhou ◽  
Diankai Qiu ◽  
Linfa Peng ◽  
Xinmin Lai
2021 ◽  
Vol 7 ◽  
pp. 1374-1384 ◽  
Author(s):  
Taiming Huang ◽  
Wei Wang ◽  
Yao Yuan ◽  
Jie Huang ◽  
Xi Chen ◽  
...  

Author(s):  
Mehdi Mehrabi ◽  
Sajad Rezazadeh ◽  
Mohsen Sharifpur ◽  
Josua P. Meyer

In the present study, a genetic algorithm-polynomial neural network (GA-PNN) was used for modeling proton exchange membrane fuel cell (PEMFC) performance, based on some numerical results which were correlated with experimental data. Thus, the current density was modeled in respect of input (design) variables, i.e., the variation of pressure at the cathode side, voltage, membrane thickness, anode transfer coefficient, relative humidity of inlet fuel and relative humidity of inlet air. The numerical data set for the modeling was divided into train and test sections. The GA-PNN model was introduced with 80% of the numerically-validated data and the remaining data was used for testing the appropriateness of the GA-PNN model by means of two statistical criteria.


2019 ◽  
Vol 35 (4) ◽  
pp. 1021-1041 ◽  
Author(s):  
Tian Erlin ◽  
Abdol Ghaffar Ebadi ◽  
Dinesh Mavaluru ◽  
Mohammed Alshehri ◽  
Ahmed Abo‐Bakr Mohamed ◽  
...  

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