FE modelling of a motorcycle tyre for full-scale crash simulations
Daniele Barbani, Marco Pierini, Niccolò Baldanzini
Abstract
Daniele Barbani, Marco Pierini, Niccolò Baldanzini
Abstract
In finite-element (FE) simulations of motorcycle crashes, the tyre behaviour is of utmost importance since the front tyre is often the first component involved in the impact. For this reason, a typical approach used in car crashes analysis is not appropriated. In this paper, the state-of-the-art tyre FE models for crash/impact analysis will be presented and discussed. Two alternative tyre modelling approaches for full-scale virtual crash tests of motorcycles will be proposed and tested. A Design Of Experiment (DOE) analysis is performed to identify the main parameters that influence the model behaviour. The results are used to tune the models, based on experimental data. Finally, the models are compared and the one that results in the best compromise in terms of fidelity and computational efficiency is assessed in an additional set of configurations.
OpenAlex reports 20 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
In finite-element (FE) simulations of motorcycle crashes, the tyre behaviour is of utmost importance since the front tyre is often the first component involved in the impact. For this reason, a typical approach used in car crashes analysis is not appropriated. In this paper, the state-of-the-art tyre FE models for crash/impact analysis will be presented and discussed. Two alternative tyre modelling approaches for full-scale virtual crash tests of motorcycles will be proposed and tested. A Design Of Experiment (DOE) analysis is performed to identify the main parameters that influence the model behaviour. The results are used to tune the models, based on experimental data. Finally, the models are compared and the one that results in the best compromise in terms of fidelity and computational efficiency is assessed in an additional set of configurations.
Key concepts: Crash, Crashworthiness, Scale (ratio), Poison control, Automotive engineering, Engineering, Scale model, Crash test