Open AccessRealisation of Optimal Parameters of PEM Fuel Cell Using Simple Genetic Algorithm (SGA) and Simulink Modeling
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.f8157.088619
Subject(s) - proton exchange membrane fuel cell , genetic algorithm , computer science , convergence (economics) , matlab , algorithm , process (computing) , simple (philosophy) , mathematical optimization , fuel cells , engineering , mathematics , machine learning , philosophy , epistemology , chemical engineering , economics , operating system , economic growth
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