Abstract
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.
| Sprache | englisch |
|---|---|
| Seitenumfang | 11 |
| Fachzeitschrift | Advances in Mechanical Engineering |
| Jahrgang | Vol. 9(1) |
| Status | Veröffentlicht - 10 Jan 2017 |
Schlagwörter
- Vehicle Dynamics
- Tyre Dynamics Modelling
- Semi-Physical Tyre Model
- Parameter Optimisation
- Swarm Optimisation
- Firefly Algorithm
- Clustering
- Experimental Validation
Dies zitieren
Parameterisation of a Maxwell model for transient tyre force by means of an extended firefly algorithm. / Hackl, Andreas; Hirschberg, Wolfgang; Lex, Cornelia; Magele, Christian.
in: Advances in Mechanical Engineering, Jahrgang Vol. 9(1), 10.01.2017.Publikation: Beitrag in einer Fachzeitschrift › Artikel › Forschung › Begutachtung
}
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 -