The hybrid powertrain is a promising concept to contribute to the future CO2-targets. Besides the dimensioning of the internal combustion engine and the electric components, the operating strategy of the hybrid powertrain is of particular importance to optimise the vehicles fuel consumption. A combination of start/stop operation, downspeeding, load-point shifting and pure electric driving can provide substantial fuel savings compared to conventional powertrains. Due to the fact that numerous parameters have to be optimised, a numerical approach is useful to define the operating strategies efficiently. A numerical simulation model of a powertrain with mild hybridization was set up at the Institute for Powertrains and Automotive Technology at the Vienna University of Technology with the goal to minimise the fuel consumption for the New European Driving Cycle. The 6-cylinder SI engine, the electric components and the vehicle were modelled in accordance with a close-to-series powertrain. The battery, the electric motor and the SI engine were characterised with maps to provide fast simulation times. In addition to previous investigations, a new and sophisticated approach with a numerical optimiser based on several heuristic methods was developed. With this method, up to 18 parameters were investigated and optimised in parallel. The results of this optimization were compared to the fuel consumption of the conventional powertrain and a simpler optimization approach with the Design-of-Experiment method. Generally, it became obvious that long phases of electric driving combined with aggressive load point shifting to balance the battery's state of charge are most favourable in terms of efficiency. The strategies were verified on an Engine-in-the-Loop test bench. In order to obtain a strategy for arbitrary driving cycles and real-life cycles, a more general formulation of the driving parameters and criteria has to be provided for optimisation what will be a future target.


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    Title :

    Optimisation of hybrid strategies with heuristic algorithms


    Contributors:


    Publication date :

    2012


    Size :

    16 Seiten, 10 Bilder, 1 Tabelle, 13 Quellen


    Type of media :

    Conference paper


    Type of material :

    Storage medium


    Language :

    English




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