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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.

In the paper at hand a model-based development approach for a diagnostic system for a multifunctional fuel cell system architecture will be presented. The approach consists primarily of four parts. The first part is a description of general steps needed to build an accurate component-based model of the system using a state of the art model-based diagnostic reasoning tool. As a first result there will be a static simulation model for nominal system behavior. The second part of the approach deals with the identification of safety critical failure conditions (SCFC) at a system level, e.g. low Power. The SCFCs are then mapped into the model. This means that categorized physical quantities and monitoring executives are chosen, that are appropriate for representing the specific SCFCs, e.g. low voltage at outlet of DC-DC converter module. According to step two there will be conflicts, meaning discrepancies between the simulated nominal and the mapped behavior.

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.