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The integration of fuel cell systems as an independent energy source (Auxiliary Power Unit, APU) requires enhanced aircraft cooling architectures. New environmental control systems and systems with an increased cooling demand are investigated in various research projects. Cooling system architectures can be designed which benefit from similar requirements, e.g. by using the same cooling loops. Additionally, an increased cooling demand makes the investigation of alternative heat sinks necessary. For detailed system investigations simulation studies are used. A model library has been created in Dymola/Modelica containing the necessary component models to simulate cooling systems. The used modeling approaches and main model information are presented in this article. In order to understand the basic system behavior a Design of Experiment (DOE) is useful. If only two or three parameters are considered, simulation studies can be performed for each possible parameter combination.

This paper presents a methodology to develop, optimize and evaluate fuel cell system architectures. The main focus is placed on the sizing and optimization process which uses the simulation tool Matlab/Simscape. A model library is introduced which contains parametric behavior models. The benefit of this is that the size of the components is not fixed by the parameters. The size of the components is driven by the energy and mass flows of each component. Thus the implicit sizing and optimization process is easy to handle and numerically robust. Illustrative results are shown for a fuel cell system.

This paper presents a model-based design and verification approach, which is used to develop a complex state-based fuel cell control system. The architecture of the control system is organized in a hierarchical manner with one supervisory controller and several system controllers. The used development approach considers the systematic design of this hierarchical concept and enables the integration of requirements. The single modules of the control system are modeled as Statecharts. During the design process a method based on Petri Nets is used to analyze and verify the state-based structure of the supervisory controller. The verification of the control system functionalities is finally realized by a black box test approach. The required test sequences are systematically specified on the basis of the state transition graph of the supervisory controller.