AlpeDHues – Aging Analysis and Performance Optimization of Fuel Cells in Highly Dynamic Operation
Project Description
Overview
The use of green hydrogen in electric vehicles through fuel cells is of great interest due to numerous advantages, including the elimination of CO₂ emissions, high efficiency, long driving range, and short refueling times. At the same time, fuel cells are sensitive to the dynamic load profiles typical for vehicle applications, which accelerate degradation and lead to performance losses and reduced lifetime.
In this project, model-based concepts for monitoring and control were developed to guide transient phases in a damage-minimizing way. High-resolution simulation models, real-time capable performance models, and fuel cell test benches were employed. This enabled the identification of potentially harmful operating conditions, the implementation of control strategies in real time, and the validation of methods using experimental data.
Goals and Challenges
A central goal was the development of virtual sensors that provide insights into the internal processes of the fuel cell. By means of state observers, unmeasurable variables and parameters were to be derived from a limited set of available measurements. In parallel, control concepts were pursued that enable efficient and low-degradation operation under highly dynamic conditions. A key challenge was the reliable detection of critical operating states and their integration into the applied control algorithms.
Figure: Overview of the Project Goals
Results and Insights
A developed state-of-health observer allows the effects of degradation during operation to be captured without the need for additional sensors. By differentiating specific degradation parameters, various aging processes in the components can be estimated with precision. This provides a virtual window into the fuel cell, enabling detailed analysis of degradation and early diagnosis.
To prevent local damage, distributed-parameter observers were applied. These allow the reconstruction of internal state distributions, such as humidity or temperature, based on spatially resolved models and a limited number of measurements. Building on this, model-based control concepts were developed that not only capture internal states but also actively influence them to slow down local aging mechanisms.
For precise gas conditioning under transient conditions, as encountered in automotive applications, a control approach was implemented that decouples mass flow and pressure in the cathode channel and was validated on a real test bench. This enables highly dynamic experiments on fuel cell test benches that support both realistic operating scenarios and targeted aging tests and diagnostic procedures.
Highlights
- Achieved deeper insights into fuel cell degradation and efficiency
- Successful development of advanced monitoring and control strategies, including the implementation of dynamic gas conditioning at a test bench
- Result-oriented collaboration between research and industry partners
- Comprehensive dissemination activities: 1 patent application, 8 scientific articles in peer-reviewed journals, 17 contributions to national and international conferences
Key findings
- Internal cell states can be monitored in real time and manipulated in a way that slows down local aging mechanisms.
- Advanced control strategies enable highly dynamic operation with real-time gas conditioning while avoiding harmful operating conditions.
- Methods from modeling and control theory (e.g., model reduction, model predictive control, differential flatness) provide precise and efficient monitoring and control of complex systems.
- The developed concepts deliver not only new scientific insights but also strong potential for more economical use of fuel cells in vehicle applications.
Publications
Bartlechner, Johanna, Christoph Hametner, and Stefan Jakubek. "Health-conscious MPC for PEM fuel cells considering main degradation mechanisms of cathode catalyst, opens an external URL in a new window." IFAC-PapersOnLine 59, no. 5 (2025): 73-78.
Fuchs, Benjamin, Florian Altmann, Martin Vrlić, Stefan Braun, Martin Kozek, Christoph Hametner, and Stefan Jakubek. "Nonlinear distributed-parameter observer design for efficient estimation of internal temperature profiles in polymer electrolyte membrane fuel cells., opens an external URL in a new window" Nonlinear Dynamics (2025): 1-25.
Fuchs, Benjamin, Christoph Hametner, and Stefan Jakubek. "Model predictive humidity distribution control for polymer electrolyte membrane fuel cells., opens an external URL in a new window" In 2024 IEEE Vehicle Power and Propulsion Conference (VPPC), pp. 1-6. IEEE, 2024.
Bartlechner, Johanna, Martin Vrlić, Christoph Hametner, and Stefan Jakubek. "State-of-Health observer for PEM fuel cells—A novel approach for real-time online analysis, opens an external URL in a new window." International Journal of Hydrogen Energy (2024).
Vrlić, Martin, Dominik Pernsteiner, Alexander Schirrer, Christoph Hametner, and Stefan Jakubek. "Reduced-dimensionality nonlinear distributed-parameter observer for fuel cell systems., opens an external URL in a new window" Energy Reports 10 (2023): 1-14.
Cooperation Partner
Duration
- January 2022 - June 2025
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