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Article

Efficient Two-Step Parametrization of a Control-Oriented Zero-Dimensional Polymer Electrolyte Membrane Fuel Cell Model Based on Measured Stack Data

1
Institute of Mechanics and Mechatronics, Technische Universität Wien, Getreidemarkt 9, 1060 Vienna, Austria
2
Institute of Powertrains and Automotive Technology, Technische Universität Wien, Getreidemarkt 9, 1060 Vienna, Austria
*
Author to whom correspondence should be addressed.
Academic Editor: Alessandro D’ Adamo
Processes 2021, 9(4), 713; https://doi.org/10.3390/pr9040713
Received: 23 March 2021 / Revised: 12 April 2021 / Accepted: 15 April 2021 / Published: 18 April 2021
(This article belongs to the Special Issue Experimental Analysis and Numerical Simulation of Fuel Cells)
This paper proposes a new efficient two-step method for parametrizing control-oriented zero-dimensional physical polymer electrolyte membrane fuel cell (PEMFC) models with measured stack data. Parametrizations of these models are computationally intensive due to the numerous unknown parameters and the typically nonlinear, stiff model properties. This work reduces an existing model to decrease its stiffness for accelerated numerical simulations. Subdividing the parametrization into two consecutive subproblems (thermodynamic and electrochemical ones) reduces the solution space significantly. A parameter sensitivity analysis further reduces each sub-solution space by excluding non-significant parameters. The method results in an efficient parametrization process. The two-step approach minimizes each sub-solution space’s dimension by two-thirds, respectively three-fourths, compared to the global one. An achieved R2 value between simulation and measurement of 91% on average provides the required accuracy for control-oriented models. View Full-Text
Keywords: polymer electrolyte membrane fuel cell; control-oriented model; grey-box modeling; analytical differentiability; model reduction; parameter sensitivity analysis; fisher information; efficient parameterization; data-driven identification; transient operation measurement data polymer electrolyte membrane fuel cell; control-oriented model; grey-box modeling; analytical differentiability; model reduction; parameter sensitivity analysis; fisher information; efficient parameterization; data-driven identification; transient operation measurement data
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MDPI and ACS Style

Du, Z.P.; Steindl, C.; Jakubek, S. Efficient Two-Step Parametrization of a Control-Oriented Zero-Dimensional Polymer Electrolyte Membrane Fuel Cell Model Based on Measured Stack Data. Processes 2021, 9, 713. https://doi.org/10.3390/pr9040713

AMA Style

Du ZP, Steindl C, Jakubek S. Efficient Two-Step Parametrization of a Control-Oriented Zero-Dimensional Polymer Electrolyte Membrane Fuel Cell Model Based on Measured Stack Data. Processes. 2021; 9(4):713. https://doi.org/10.3390/pr9040713

Chicago/Turabian Style

Du, Zhang P., Christoph Steindl, and Stefan Jakubek. 2021. "Efficient Two-Step Parametrization of a Control-Oriented Zero-Dimensional Polymer Electrolyte Membrane Fuel Cell Model Based on Measured Stack Data" Processes 9, no. 4: 713. https://doi.org/10.3390/pr9040713

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