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.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Multiobjective NSGA 11-based control optimization of hydraulic and electric hybrid propulsion systems with respect to their dynamic behavior in time domain


    Additional title:

    Mehrkriterienoptimierte NSGA II-basierte Optimierung hydraulischer und elektrischer Hybridantriebssysteme hinsichtlich ihres dynamischen Verhaltens im Zeitbereich


    Contributors:
    Karbaschian, M.A. (author) / Marx, M. (author) / Moulik, B. (author) / Söffker, D. (author)


    Publication date :

    2013


    Size :

    17 Seiten, 7 Bilder, 15 Quellen



    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    NSGA-II multi-objectives optimization algorithm for energy management control of hybrid electric vehicle

    Deng, Tao / Lin, Chunsong / Luo, Junlin et al. | SAGE Publications | 2019


    TORQUE BALANCING FOR HYBRID ELECTRIC PROPULSION SYSTEMS AND AIRCRAFT UTILIZING HYBRID ELECTRIC PROPULSION SYSTEMS

    THOMASSIN JEAN / BENGEA SORIN / PEKOVIC TATJANA | European Patent Office | 2020

    Free access

    TORQUE BALANCING FOR HYBRID ELECTRIC PROPULSION SYSTEMS AND AIRCRAFT UTILIZING HYBRID ELECTRIC PROPULSION SYSTEMS

    THOMASSIN JEAN / BENGEA SORIN / PEKOVIC TATJANA | European Patent Office | 2020

    Free access

    TORQUE BALANCING FOR HYBRID ELECTRIC PROPULSION SYSTEMS AND AIRCRAFT UTILIZING HYBRID ELECTRIC PROPULSION SYSTEMS

    THOMASSIN JEAN / BENGEA SORIN / PEKOVIC TATJANA | European Patent Office | 2022

    Free access

    TORQUE BALANCING FOR HYBRID ELECTRIC PROPULSION SYSTEMS AND AIRCRAFT UTILIZING HYBRID ELECTRIC PROPULSION SYSTEMS

    THOMASSIN JEAN / BENGEA SORIN / PEKOVIC TATJANA | European Patent Office | 2020

    Free access