In this contribution a technique for the optimization of hybrid hydraulic and hybrid electric power trains and related power management parameters is introduced. The optimization method uses the NSGA II algorithm (Non-dominated sorting genetic algorithm) which is connected with the dynamic system models of the power trains. The comparison shows the results of the two hybrid systems and therefore evaluates the effectiveness of the optimization algorithm. It becomes clear that the optimization leads to feasible solutions for both systems. The differences between the results of the two systems are due to the different dimensions and dynamics of the systems, the amount and density of the power which can be recaptured in both systems. The off-line optimization results can be used as benchmark such as dynamic programming results to evaluate global optimal solutions. Future steps will be the Integration of further system parameters to be optimized as well as further cost functions to be implemented. The usage of more sophisticated search algorithms will lead to a faster progress of the optimization algorithm. In this contribution the similarities and the differences of the power train concepts become clear. The usage of a common framework for the modeling, parameterization, and control optimization of hybrid hydraulic and hybrid electric power trains will lead to an easier comparability of the concepts.
Multiobjective NSGA 11-based control optimization of hydraulic and electric hybrid propulsion systems with respect to their dynamic behavior in time domain
Mehrkriterienoptimierte NSGA II-basierte Optimierung hydraulischer und elektrischer Hybridantriebssysteme hinsichtlich ihres dynamischen Verhaltens im Zeitbereich
ATK, Antriebstechnisches Kolloquium, 15 ; 641-657
2013
17 Seiten, 7 Bilder, 15 Quellen
Conference paper
English
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