Entwicklung eines integrierten Kraftstoffverbrauchs- und Fahrtenkettenmodells des Straßengüterverkehrs am Beispiel schwerer Nutzfahrzeuge

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Germany's climate protection goals are increasingly challenged by rising greenhouse gas emissions from the transport sector, particularly heavy-duty vehicles predominantly powered by diesel engines. This situation necessitates not only technical solutions, such as improved energy efficiency and alternative drive technologies, but also immediate behavioral changes, like reducing maximum speeds on motorways. Policymakers and stakeholders in road freight transport must investigate these measures. This thesis integrates a fuel consumption model with a trip chain model to assess the impacts holistically. Initially, simulations using a MATLAB/Simulink-based fuel consumption model determine average fuel consumption (l/100 km) and velocity (km/h) resulting from speed reduction measures. These variables are then expressed as payload-dependent functions for each vehicle class, representing 91% of diesel consumption and GHG emissions from heavy-duty vehicles in Germany as of 2010. The study also analyzes how reduced average velocity affects trip sequences throughout the year using a discrete-event simulation model based on Excel-VBA. The findings indicate increased trip times inversely proportional to velocity, potentially necessitating rescheduling of trips. The analysis includes calculating the delay time compared to baseline conditions and evaluating the rise in personnel costs against fuel savings to determine the economic efficiency