A suspension system is a set of mechanical elements whose functions can be summarized as isolate the passenger and the structure from vibrations and ensure the vehicle stability under different travel condition. A semiactive suspension system is defined as set of mechanical and electric devices that includes semiactive or active elements whose parameters could be controlled by a system, although they cannot introduce forces into the system. An option of devices that can be used in semiactive suspension system could be elements which their mechanical properties can be controlled by an external stimulus, such capability is produced by the so-called “Smart Materials”. This work analyses the application of a kind of those materials which can modify their mechanical properties by the influence of a magnetic field, that category is called magnetorheologic materials. Those allow through the intensity of a magnetic field tune their behavior in terms of their viscoelastic properties. The control of this devices requires a sensing and actuator systems and the response between them requires a so small delay process, otherwise the suspension system does not achieve its objective, but also is considered unsafe. Therefore, a more efficient model using artificial intelligence techniques such Fuzzy Logic and Artificial Neural Network is developed to simulate and keep the system response updated through the time due to variations on the elements behavior such wear or another factors. Furthermore, the optimization of the response and the element design is complex because of the high non-linear system and the large number of degrees of freedom that the system have, therefore the application of Genetic Algorithm to improve the time of calculus and design process. This article presents a short introduction of smart materials focused on Magnetorheological materials such fluids and elastomer, also a modeling of suspension devices based on this technology are modeled. These elements are introduced in a vehicle model to evaluate the ...


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    Titel :

    Hybrid fuzzy neural network: genetic algorithm applied to the control of magnetorheological and smart material vehicle semiactive suspensions



    Erscheinungsdatum :

    2023-11-02



    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Schlagwörter :

    Klassifikation :

    DDC:    620 / 629





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