Wipe quality of wiper systems is influenced not only by the definition of the wiper system, but also by the shape of the glass. In order to optimize the overall performance of the system, Valeo Wiper Systems has developed an optimization algorithm, which is based on geometrical criteria. The multi-criteria objective not only considers wipe quality but also constraints by glass feasibility and respect of optical standards. As the direct derivation of the objective functions is not available, a neural network approximation is used at the place of the real function. A neural network with several outputs enables the engineer to include his knowledge in the optimization loop by changing disciplinary weights.


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    Titel :

    Windshield Shape Optimization Using Neural Network


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Muradore, Fabien (Autor:in) / Jan, Sophie (Autor:in) / Dreher, Thomas (Autor:in)

    Kongress:

    SAE 2004 World Congress & Exhibition ; 2004



    Erscheinungsdatum :

    2004-03-08




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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