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

Du, Zhang Peng; Steindl, Christoph; Jakubek, Stefan

doi:10.3390/pr9040713

Cited by 9 publications

(12 citation statements)

References 32 publications

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“…The measurement data used in this work were obtained using a dedicated test stand equipped with a commercial 30 kW fuel cell stack, the associated balance-of-plant components and a specifically designed measurement and control system. As the test stand has also been used for measurements in other publications and to avoid redundancy with other articles, the authors refer the reader to the work in [25,45] for a more detailed presentation of the test stand setup.…”

Section: Resultsmentioning

confidence: 99%

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Parameter Identification of a Quasi-3D PEM Fuel Cell Model by Numerical Optimization

2021

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Polymer electrolyte membrane fuel cells (PEMFCs) supplied with green hydrogen from renewable sources are a promising technology for carbon dioxide-free energy conversion. Many mathematical models to describe and understand the internal processes have been developed to design more powerful and efficient PEMFCs. Parameterizing such models is challenging, but indispensable to predict the species transport and electrochemical conversion accurately. Many material parameters are unknown, or the measurement methods required to determine their values are expensive, time-consuming, and destructive. This work shows the parameterization of a quasi-3D PEMFC model using measurements from a stack test stand and numerical optimization algorithms. Differential evolution and the Nelder–Mead simplex algorithm were used to optimize eight material parameters of the membrane, cathode catalyst layer (CCL), and gas diffusion layer (GDL). Measurements with different operating temperatures and gas inlet pressures were available for optimization and validation. Due to the low operating temperature of the stack, special attention was paid to the temperature dependent terms in the governing equations. Simulations with optimized parameters predicted the steady-state and transient behavior of the stack well. Therefore, valuable data for the characterization of the membrane, the CCL and GDL was created that can be used for more detailed CFD simulations in the future.

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Section: Resultsmentioning

confidence: 99%

“…A very comprehensive review of available material data in the scientific literature can be found in [21]. Recently, some authors used the data-driven parameterization [25][26][27]. Goshtasbi et al [28] created a framework on efficient parameterization based on the extended local sensitivity analysis from in [29].…”

Section: Introductionmentioning

confidence: 99%

Parameter Identification of a Quasi-3D PEM Fuel Cell Model by Numerical Optimization

2021

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“…Furthermore, the battery simulator supplied the electric power generated by the FC stack during operation into the electric grid, and an additional power supply system fed the balance of plant components with energy. A more detailed description of the test bench and the experimental conditions is available in [18].…”

Section: Methodsmentioning

confidence: 99%

“…The sampled signal was necessary for the parametrization, and n k is the number of sampling instants. The objective function J considers the weighted squared errors between the measured y * (t k ) and simulated output signals y(t k , Θ) [18,39]:…”

Section: Parametrizationmentioning

confidence: 99%

Physically Motivated Water Modeling in Control-Oriented Polymer Electrolyte Membrane Fuel Cell Stack Models

Kravos

Steindl

et al. 2021

Energies

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Polymer electrolyte membrane fuel cells (PEMFCs) are prone to membrane dehydration and liquid water flooding, negatively impacting their performance and lifetime. Therefore, PEMFCs require appropriate water management, which makes accurate water modeling indispensable. Unfortunately, available control-oriented models only replicate individual water-related aspects or use oversimplistic approximations. This paper resolves this challenge by proposing, for the first time, a control-oriented PEMFC stack model focusing on physically motivated water modeling, which covers phase change, liquid water removal, membrane water uptake, and water flooding effects on the electrochemical reaction. Parametrizing the resulting model with measurement data yielded the fitted model. The parameterized model delivers valuable insight into the water mechanisms, which were thoroughly analyzed. In summary, the proposed model enables the derivation of advanced control strategies for efficient water management and mitigation of the degradation phenomena of PEMFCs. Additionally, the model provides the required accuracy for control applications while maintaining the necessary computational efficiency.

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“…, n θ } denotes a tunable parameter, and n θ is the number of parameters. As in [19] and [21], ξ i is obtained by solving the following first-order ordinary differential equation, which is a total derivative of the FC model (1):…”

Section: ) Design Of Experimentsmentioning

confidence: 99%

Concentration Estimation for Fuel Cells: Design of Experiments, Nonlinear Identification, and Observer Design With Experimental Validation

Steindl

Jakubek

et al. 2023

IEEE Access

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Fuel cells (FCs) are promising eco-friendly power sources. Nevertheless, there are challenges to overcome if they are to be widely deployed in areas such as degradation avoidance and control, where the knowledge of the unavailable concentrations is crucial. In this respect, observers can provide unavailable quantities based on an estimation algorithm and available measurements. This paper presents an FC concentration observer design workflow, covering the model-based design of experiments (DOE), their execution, systematic nonlinear identification, and measurement-based validation. The model-based DOE and the validation with a mass spectrometer, including dynamic operation, are unique for PEMFC observers. The workflow is demonstrated with a constrained extended Kalman filter observer on a 30 kW polymer electrolyte membrane FC (PEMFC) test stand. A control-oriented model serves as the workflow basis, and the DOE is based on optimizing the parameter sensitivity. The test stand delivers the measurements, the parametrization comprises a sensitivity analysis, and the experimentally validated observer yields outstanding concentration estimation performance.INDEX TERMS Design of experiments, design workflow, experimental validation, fuel cells, Kalman filter, mass spectrometer, observer, parameter sensitivity analysis, parametrization, PEMFC.

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

Cited by 9 publications

References 32 publications

Parameter Identification of a Quasi-3D PEM Fuel Cell Model by Numerical Optimization

Parameter Identification of a Quasi-3D PEM Fuel Cell Model by Numerical Optimization

Physically Motivated Water Modeling in Control-Oriented Polymer Electrolyte Membrane Fuel Cell Stack Models

Concentration Estimation for Fuel Cells: Design of Experiments, Nonlinear Identification, and Observer Design With Experimental Validation

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