This work defines and implements a technique to predict water activity in proton exchange membrane fuel cell. This technique is based on the electrochemical impedance spectroscopy (EIS) as sensor and adaptive neuro-fuzzy inference system (ANFIS) as estimator. For this purpose, a proton exchange membrane fuel cell (PEMFC) model has been proposed to study the performances of the fuel cell for different operating conditions where the simulation model for water activity behavior is in the proposed structure. The technique based on ANFIS predicts the PEM fuel cell relative humidity (RH) from the EIS. For creation of ANFIS training and checking database, a new method based on factorial design of experimental is used. To check the proposed technique, the ANFIS estimator will be compared with the output humidity relative observation.
Application of Adaptive Neuro-Fuzzy Inference System Techniques to Predict Water Activity in Proton Exchange Membrane Fuel Cell
Manuscript received November 12, 2017; final manuscript received April 18, 2018; published online May 9, 2018. Assoc. Editor: Matthew Mench.
- Views Icon Views
- Share Icon Share
- Cite Icon Cite
- Search Site
Mammar, K., and Laribi, S. (May 9, 2018). "Application of Adaptive Neuro-Fuzzy Inference System Techniques to Predict Water Activity in Proton Exchange Membrane Fuel Cell." ASME. J. Electrochem. En. Conv. Stor. November 2018; 15(4): 041009. https://doi.org/10.1115/1.4040058
Download citation file:
- Ris (Zotero)
- Reference Manager