Data-Driven Control of a PEM Electrolyzer

Yeyson A. Becerra-Mora, Yeyson A. Becerra-Mora, Juan Manuel Escaño, José Ángel Acosta

2025

Abstract

Green hydrogen production has gained significant relevance in recent years to substitute fossil fuels in the coming years. One of the most promising technologies for attaining such a milestone is the PEM electrolyzer; nevertheless, some considerations related to controlling its temperature must be addressed, such as avoiding high temperatures to extend its useful life and improve its efficiency. Therefore, this study proposes a data-driven control strategy based on Gaussian Process Regression (GPR) and Nonlinear Model Predictive Control (NMPC). GPR is used to identify the system, while NMPC is used to regulate the output temperature of the PEM electrolyzer with the identified model. Simulations show a clear resemblance between the Gaussian Process model and the phenomenological model, as well as the effectiveness of the controller. Furthermore, error metrics and computational time are presented.

Paper Citation

in Harvard Style

Becerra-Mora Y., Escaño J. and Acosta J. (2025). Data-Driven Control of a PEM Electrolyzer. In Proceedings of the 22nd International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-770-2, SciTePress, pages 267-273. DOI: 10.5220/0013738800003982

in Bibtex Style

@conference{icinco25,
author={Yeyson Becerra-Mora and Juan Escaño and José Acosta},
title={Data-Driven Control of a PEM Electrolyzer},
booktitle={Proceedings of the 22nd International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2025},
pages={267-273},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013738800003982},
isbn={978-989-758-770-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 22nd International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - Data-Driven Control of a PEM Electrolyzer
SN - 978-989-758-770-2
AU - Becerra-Mora Y.
AU - Escaño J.
AU - Acosta J.
PY - 2025
SP - 267
EP - 273
DO - 10.5220/0013738800003982
PB - SciTePress