Realisation of Optimal Parameters of PEM Fuel Cell Using Simple Genetic Algorithm (SGA) and Simulink Modeling
R Raajiv Menon1, Vijay Kumar2, Jitendra K Pandey3

1R Raajiv Menon, Research Scholar, Department of Research and Development, University of Petroleum & Energy Studies, Dehradun, India.
2Vijay Kumar, Department of Ocean Engineering, Indian Institute of Technology (IIT), Chennai, India.
3Jitendra Kumar Pandey, Department of Research & Development, University of Petroleum and Energy Studies, Dehradun, India.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 1542-1548 | Volume-8 Issue-6, August 2019. | Retrieval Number: F8157088619/2019©BEIESP | DOI: 10.35940/ijeat.F8157.088619
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: A methodology to solve parameter extraction of PEM Fuel cell by an optimisation process using simple genetic algorithm and Simulink is proposed. The results are validated using the traditional curve fitting method where in the initial values are compared with the existing curve for its convergence and exactitude. In this work the modelling and extensive simulation of the PEM Fuel cell has been undertaken using MATLAB-SIMULINK. The steps have been elaborated further in order to explain the incorporation and efficacy of Genetic algorithm codes in FC model. Simple Genetic Algorithm (SGA) is a reliable methodology towards optimisation of fuel cell parameters. It is inferred from the simulated results that the process is precise and absolute error is generated to showcase the subtleness of the algorithm. The proposed model can be utilised to study and develop steady state performances of PEMFC stacks.
Keywords: Simple Genetic Algorithm (SGA), PEM fuel cell, Optimisation, Simulink modeling.