Using the powerful techniques of neural networks and genetic algorithms, a brake system controller is designed. First, the problem of blending auxiliary brakes, foundation brakes and gear for high mean speed in down hill cruising situations is investigated. An optimization problem with constraints such as vehicle speed and disc temperature is formulated and solved, resulting in a well performing controller even compared to experienced drivers. It is shown that the mean speed can be improved by controlling the whole brake system. Second, the issue of distributing a required force between auxiliary and foundation brakes in order to minimize wear cost of pad, disc, and tyres is investigated. The neural network controllers obtained from the optimization procedure significantly outperform the traditional strategy of using non-wear auxiliary brakes in order to minimize pad and disc wear cost.


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    Title :

    Integrated retardation control using neural networks with genetic algorithms


    Additional title:

    Integrierte Verzögerungssteuerung mit Hilfe eines neuronalen Netzwerkes und einem genetischen Algorithmus


    Contributors:
    Lingman, P. (author) / Wahde, M. (author)


    Publication date :

    2002


    Size :

    6 Seiten, 10 Bilder, 4 Quellen


    Type of media :

    Conference paper


    Type of material :

    Storage medium


    Language :

    English






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