期刊
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
卷 357, 期 18, 页码 13816-13833出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jfranklin.2020.10.010
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资金
- Spanish national project DOVELAR (MINECO/FEDER) [RTI2018-096001-B-C32]
- Spanish State Research Agency through the Maria de Maeztu Seal of Excellence to IRI [MDM-2016-0656]
- AGAUR of Generalitat de Catalunya through the Advanced Control Systems (SAC) group grant [2017 SGR 482]
The aim of this work is to deploy and experimentally validate a model-based strategy to estimate unmeasurable variables in a proton exchange membrane (PEM) fuel cell. First, a nonlinear PEM fuel cell dynamical model is implemented and calibrated using an optimisation approach that takes real measurement data as input. Then, an advanced observation approach is developed to retrieve non -measurable data from the fuel cell. Two states are estimated in this work: the fuel cell temperature and the internal liquid water fraction. To achieve this, a model-based high-order sliding mode observer (HOSM) with chattering-free capabilities is deployed. The fuel cell temperature is measured in real time to drive the estimation error to zero in a finite amount of time. Finally, the methodology is validated using experimental data stemming from a laboratory test station, comparing the the HOSM observer with and without chattering-free gain. (c) 2020 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
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