Instruments and Systems: Monitoring, Control, and Diagnostics Annotation << Back Monitoring and Prediction of Critical Operating Modes of Hydrogen Fuel Cells During Operation Based on Artificial Neural Networks E.S. DENISOV, N.R. GAISIN, T.P. NIKISHIN, N.F. ADIUTANTOV The article considers the issue of creating a model of a hydrogen fuel cell battery based on artificial neural networks. The selection of the most statistically significant features was carried out to obtain high accuracy of the neural network model. It is shown that the proposed neural network model allows predicting the voltage of a hydrogen fuel cell battery for 10 seconds. The obtained results can be used in promising systems for diagnosing and predicting the operating modes of power plant systems based on hydrogen fuel cells. Keywords: fuel cell, fuel cell battery, solid polymer electrolyte, relaxation process, diagnostics, neural network, prediction. DOI: 10.25791/pribor.12.2021.1308 Pp. 11-16.