Electric hybridisation of vehicles aims at reducing fuel consumption but increases production costs. Hence, automobile manufacturers are confronted with the multi-objective optimisation problem of sizing the drive-train components. In this paper, we evaluated Particle Swarm Optimisation (PSO) for solving this problem. The results showed that PSO performs significantly better than competing methods. Parameter sensitivities indicated that the optimal solution, the vehicle performance constraints, and the preference between fuel consumption and production cost are intimately coupled. Finally, a Pareto analysis confirmed that a relatively small increase in cost accounts for a majority of the total fuel saving potential.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Particle swarm optimisation for hybrid electric drive-train sizing


    Weitere Titelangaben:

    PSO-Verfahren zur Auslegung der Antriebsstrangkomponenten von Hybridfahrzeugen


    Beteiligte:
    Ebbesen, Soren (Autor:in) / Dönitz, Christian (Autor:in) / Guzzella, Lino (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2012


    Format / Umfang :

    19 Seiten, 8 Bilder, 4 Tabellen, 20 Quellen




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch