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.

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.

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.

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.

<div class="section abstract"><div class="htmlview paragraph">A promising approach for defossilization in the transport sector is using the polymer electrolyte membrane fuel cell (PEMFC) as an energy converter for propulsion in combination with green hydrogen. Furthermore, hybridization can bring an additional gain in efficiency. In a hybrid electric vehicle (HEV) powertrain, including FCHEV, at least two power sources (e.g., an FC system (FCS) with a hydrogen storage system and a high-voltage battery (HVB)) provide the required propulsion power. Thus, the powertrain topology and the energy management strategy (EMS) of an FCHEV are more complex than those of a conventional powertrain. To ensure a cost- and time-efficient development process, the FCHEV powertrain concept and its functions must be verified and evaluated early. To this end, this study presents the design and setup of an FC-in-the-Loop (FCiL) test platform as a tool for the systematic development of an FCHEV powertrain under realistic operating conditions. Hence, a medium size FCHEV is modeled with quasistatic sub-models of the powertrain components. The full-vehicle model is validated against measurement data of a commercially available FCHEV on a 4-wheel chassis dynamometer in a driving cycle. Based on the FCiL test methodology, the sizing of the FCS and HVB is demonstrated. It is found that for a low-load driving cycle such as the WLTC, a 110 kW FCS, and a 1.6 kWh HVB can achieve a good result regarding low hydrogen consumption. Furthermore, two different EMS schemes, the power follower strategy (PFS) and the equivalent consumption minimization strategy (ECMS), are implemented and evaluated. With the ECMS, hydrogen consumption can be reduced by 1.6 % compared to the PFS. Moreover, the trade-off behavior between minimum hydrogen consumption and reduced dynamics of the FCS is investigated. Reducing the dynamic operation of the FCS by one-third results in an additional hydrogen consumption of only about 0.8 %.</div></div>