Comparative assessment of vehicle powertrain concepts in the early development phase

In recent years vehicle powertrains show a growing trend towards diversification. This helps to mitigate inevitable conflicts between objectives, but vastly expands and complicates the concept solution space. The fair optimization and assessment across a number of distinct powertrain structures poses a considerable challenge for vehicle concept teams in the early development phase. Previous work fails to derive a realistic and holistic approach to tackle this challenge, which is still viable under tight time constraints. The solution presented in this thesis is based on novel combination of state-of-the-art concepts. Flexible powertrain definition is achieved with graph theory and parametric component models. Important secondary mass decompounding effects are considered. A vectorized quasi-static backward simulation approach and derived meta-models guarantee high computational performance. Fair dynamic assessment is realized consistently with global optimal control. Component sizing uses closed-loop optimization. The implementation of the methodology is applied for five technical vehicle criteria and to 10 powertrain structures as an example. For each structure two criteria are simultaneously optimized and depicted as a Pareto front. Concurrent visualization of the respective components' characteristics provides transparent insight on the relation between objective and decision space. Families of Pareto fronts allow comparative graphical decision making. The methodology presented here contributes to advanced vehicle systems engineering and its application in a practical development context.