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Using adaptive neuro-fuzzy inference system (ANFIS) for proton exchange membrane fuel cell (PEMFC) performance modeling

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Abstract

In this paper, an adaptive neuro-fuzzy inference system (ANFIS) is used for modeling proton exchange membrane fuel cell (PEMFC) performance using some numerically investigated and compared with those to experimental results for training and test data. In this way, current density I (A/cm2) is modeled to the variation of pressure at the cathode side PC (atm), voltage V (V), membrane thickness (mm), Anode transfer coefficient αan, relative humidity of inlet fuel RHa and relative humidity of inlet air RHc which are defined as input (design) variables. Then, we divided these data into train and test sections to do modeling. We instructed ANFIS network by 80% of numerical-validated data. 20% of primary data which had been considered for testing the appropriateness of the models was entered ANFIS network models and results were compared by three statistical criterions. Considering the results, it is obvious that our proposed modeling by ANFIS is efficient and valid and it can be expanded for more general states.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Faculty of Engineering, Urmia University, Urmia, Iran

    S. Rezazadeh & I. Mirzaee

  2. Department of Mechanical and Aeronautical Engineering, University of Pretoria Pretoria, Pretoria, South Africa

    M. Mehrabi

  3. Department of Mechanical Engineering, Faculty of Engineering, Elm-o-Fan University, Urmia, Iran

    T. Pashaee

Authors
  1. S. Rezazadeh
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  2. M. Mehrabi
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  3. T. Pashaee
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  4. I. Mirzaee
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Correspondence to S. Rezazadeh.

Additional information

Recommended by Associate Editor Yong Tae Kim

Sajad Rezazadeh was born in Urmia in 1984. He passed entrance exam of Technical University of Urmia in mechanical course in 2002. Immediately after finishing B.S, he was accepted in Master Degree of the same course (Energy conversion field). He finished his M.sc degree with his thesis about computational fluid dynamics modeling of proton exchange membrane Fuel cell. He was accepted in PhD and now he is studying in second year. During this nearly 8 years, he has presented several articles in internal and international seminars about main mechanical topics such as fuel cells and heat exchangers.

Mehdi Mehrabi is from Iran. He passed entrance exam of Technical University of Urmia in mechanical course in 2007. He finished his M.sc degree in mechanical engineering (energy conversion field).

Tuhid Pashaee was born in Urmia in 1985. He passed entrance exam of Technical University of Urmia in mechanical course in 2002. Immediately after finishing B.S, he was accepted in Master Degree of the same course (energy conversion field). He finished his M.sc degree with his thesis about computational fluid dynamics modeling of helical heat exchangers.

Iraj Mirzaee was born in 1960 in Ahar city in Iran. He received BS degree in Mechanical Engineering in Mashhad University in 1986. He started Msc. degree in mechanical engineering (energy conversion field) in Esfehan University in Iran and finally he received his Ph.D degree in mechanical engineering (energy conversion field) in 1997 at the Bath University in England. He is an associated professor in the mechanical engineering department at faculty of engineering of Urmia University. His professional interests are in the field of CFD, turbulent, fluid flow, energy conversion problems and turbine gas.

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Rezazadeh, S., Mehrabi, M., Pashaee, T. et al. Using adaptive neuro-fuzzy inference system (ANFIS) for proton exchange membrane fuel cell (PEMFC) performance modeling. J Mech Sci Technol 26, 3701–3709 (2012). https://doi.org/10.1007/s12206-012-0844-2

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  • DOI: https://doi.org/10.1007/s12206-012-0844-2

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