Parameterisation of a Maxwell model for transient tyre force by means of an extended firefly algorithm

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Abstract

Developing functions for advanced driver assistance systems requires very accurate tyre models, especially for the simulation of transient conditions. In the past, parametrisation of a given tyre model based on measurement data showed shortcomings, and the globally optimal solution obtained did not appear to be plausible. In this article, an optimisation strategy is presented, which is able to find plausible and physically feasible solutions by detecting many local outcomes. The firefly algorithm mimics the natural behaviour of fireflies, which use a kind of flashing light to communicate with
other members. An algorithm simulating the intensity of the light of a single firefly, diminishing with increasing distances, is implicitly able to detect local solutions on its way to the best solution in the search space. This implicit clustering feature is stressed by an additional explicit clustering step, where local solutions are stored and terminally processed to
obtain a large number of possible solutions. The enhanced firefly algorithm will be first applied to the well-known Rastrigin functions and then to the tyre parametrisation problem. It is shown that the firefly algorithm is qualified to find a high number of optimisation solutions, which is required for plausible parametrisation for the given tyre model.
LanguageEnglish
Number of pages11
JournalAdvances in Mechanical Engineering
VolumeVol. 9(1)
StatusPublished - 10 Jan 2017

Keywords

    Cite this

    @article{23ca63abd30149db8ec8fe8f3275af34,
    title = "Parameterisation of a Maxwell model for transient tyre force by means of an extended firefly algorithm",
    abstract = "Developing functions for advanced driver assistance systems requires very accurate tyre models, especially for the simulation of transient conditions. In the past, parametrisation of a given tyre model based on measurement data showed shortcomings, and the globally optimal solution obtained did not appear to be plausible. In this article, an optimisation strategy is presented, which is able to find plausible and physically feasible solutions by detecting many local outcomes. The firefly algorithm mimics the natural behaviour of fireflies, which use a kind of flashing light to communicate withother members. An algorithm simulating the intensity of the light of a single firefly, diminishing with increasing distances, is implicitly able to detect local solutions on its way to the best solution in the search space. This implicit clustering feature is stressed by an additional explicit clustering step, where local solutions are stored and terminally processed toobtain a large number of possible solutions. The enhanced firefly algorithm will be first applied to the well-known Rastrigin functions and then to the tyre parametrisation problem. It is shown that the firefly algorithm is qualified to find a high number of optimisation solutions, which is required for plausible parametrisation for the given tyre model.",
    keywords = "Vehicle Dynamics, Tyre Dynamics Modelling, Semi-Physical Tyre Model, Parameter Optimisation, Swarm Optimisation, Firefly Algorithm, Clustering, Experimental Validation",
    author = "Andreas Hackl and Wolfgang Hirschberg and Cornelia Lex and Christian Magele",
    year = "2017",
    month = "1",
    day = "10",
    language = "English",
    volume = "Vol. 9(1)",
    journal = "Advances in Mechanical Engineering",
    issn = "1687-8140",
    publisher = "Hindawi Publishing Corporation",

    }

    TY - JOUR

    T1 - Parameterisation of a Maxwell model for transient tyre force by means of an extended firefly algorithm

    AU - Hackl, Andreas

    AU - Hirschberg, Wolfgang

    AU - Lex, Cornelia

    AU - Magele, Christian

    PY - 2017/1/10

    Y1 - 2017/1/10

    N2 - Developing functions for advanced driver assistance systems requires very accurate tyre models, especially for the simulation of transient conditions. In the past, parametrisation of a given tyre model based on measurement data showed shortcomings, and the globally optimal solution obtained did not appear to be plausible. In this article, an optimisation strategy is presented, which is able to find plausible and physically feasible solutions by detecting many local outcomes. The firefly algorithm mimics the natural behaviour of fireflies, which use a kind of flashing light to communicate withother members. An algorithm simulating the intensity of the light of a single firefly, diminishing with increasing distances, is implicitly able to detect local solutions on its way to the best solution in the search space. This implicit clustering feature is stressed by an additional explicit clustering step, where local solutions are stored and terminally processed toobtain a large number of possible solutions. The enhanced firefly algorithm will be first applied to the well-known Rastrigin functions and then to the tyre parametrisation problem. It is shown that the firefly algorithm is qualified to find a high number of optimisation solutions, which is required for plausible parametrisation for the given tyre model.

    AB - Developing functions for advanced driver assistance systems requires very accurate tyre models, especially for the simulation of transient conditions. In the past, parametrisation of a given tyre model based on measurement data showed shortcomings, and the globally optimal solution obtained did not appear to be plausible. In this article, an optimisation strategy is presented, which is able to find plausible and physically feasible solutions by detecting many local outcomes. The firefly algorithm mimics the natural behaviour of fireflies, which use a kind of flashing light to communicate withother members. An algorithm simulating the intensity of the light of a single firefly, diminishing with increasing distances, is implicitly able to detect local solutions on its way to the best solution in the search space. This implicit clustering feature is stressed by an additional explicit clustering step, where local solutions are stored and terminally processed toobtain a large number of possible solutions. The enhanced firefly algorithm will be first applied to the well-known Rastrigin functions and then to the tyre parametrisation problem. It is shown that the firefly algorithm is qualified to find a high number of optimisation solutions, which is required for plausible parametrisation for the given tyre model.

    KW - Vehicle Dynamics

    KW - Tyre Dynamics Modelling

    KW - Semi-Physical Tyre Model

    KW - Parameter Optimisation

    KW - Swarm Optimisation

    KW - Firefly Algorithm

    KW - Clustering

    KW - Experimental Validation

    M3 - Article

    VL - Vol. 9(1)

    JO - Advances in Mechanical Engineering

    T2 - Advances in Mechanical Engineering

    JF - Advances in Mechanical Engineering

    SN - 1687-8140

    ER -