Machine Learning Approach for Modeling and Control of a Commercial Heliocentris FC50 PEM Fuel Cell System

نویسندگان

چکیده

In recent years, machine learning (ML) has received growing attention and it been used in a wide range of applications. However, the ML application renewable energies systems such as fuel cells is still limited. this paper, prognostic framework based on artificial neural network (ANN) designed to predict performance proton exchange membrane (PEM) cell system, aiming investigate effect temperature humidity stack characteristics tracking control improvements. A large part experimental database for various operating conditions training operation achieve an accurate model. Extensive tests with ANN parameters number neurons, hidden layers, selection dataset, etc., are performed obtain best fit terms prediction accuracy. The predicted model investigated compared ones obtained from real-time experiments. design keep point at adequate power stage high-performance tracking. Experimental results have demonstrated effectiveness proposed improvements PEM system.

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ژورنال

عنوان ژورنال: Mathematics

سال: 2021

ISSN: ['2227-7390']

DOI: https://doi.org/10.3390/math9172068