A brake system controller is designed using the powerful techniques of neural networks and genetic algorithms. First, the problem of coordinating auxiliary brakes, foundation brakes, and gear for high transport effectiveness 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. Second, the issue of distributing a required force between auxiliary and foundation brakes in order to minimize the maintenance cost 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. The performance of the brake system can be improved by controlling the whole brake system including gear.


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    Title :

    Transport and maintenance effective retardation control using neural networks with genetic algorithms


    Contributors:

    Published in:

    Vehicle System Dynamics ; 42 , 1-2 ; 89-107


    Publication date :

    2004


    Size :

    19 Seiten, 9 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English





    Transport and Maintenance Effective Retardation Control Using Neural Networks With Genetic Algorithms

    Lingman, P. / Wahde, M. / Society of Automotive Engineers of Japan et al. | British Library Conference Proceedings | 2004



    Transport and maintenance effective retardation control using neural networks with genetic algorithms

    Lingman,P. / Wahde,M. / Volvo,SE et al. | Automotive engineering | 2004