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To achieve global climate goals, greenhouse gas emissions must be drastically reduced. The energy and transportation sectors are responsible for about one third of the greenhouse gases emitted worldwide, and they often use internal combustion engines (ICE). One effective way to decarbonize ICEs may be to replace carbon-containing fossil fuels such as natural gas entirely, or at least partially, with hydrogen. Cost-effective development of sustainable combustion concepts for hydrogen and natural gas/hydrogen mixtures in ICEs requires the intensive use of fast and robust simulation tools for prediction. The key challenge is appropriate modeling of flame front propagation. This paper evaluates and applies different approaches to modeling laminar flame speeds from the literature. Both appropriate models and reaction kinetic calculations are considered.

To achieve high power output and good efficiency and to comply with increasingly stricter emission standards, modern combustion engines require a more complex engine design, which results in a higher number of control parameters. As the measurement effort and the number of sensors for engine development at the test bed continue to increase, it is becoming nearly impossible for the test bed engineer to manually check measurement data quality. As a result, automated methods for analysis and plausibility checks of measurement data are necessary in order to find faults as soon as they occur and to obtain test results of the highest possible quality. This paper presents a methodology for automated fault diagnosis on engine test beds. The methodology allows reliable detection of measurement faults as well as the identification of the root cause of faults.