A methodology for an efficient failure prediction of automotive steel wheels during fatigue experimental tests is proposed. The strategy joins the CDTire simulative package effectiveness to a specific wheel finite element model in order to deeply monitor the stress distribution among the component to predict damage. The numerical model acts as a Software-in-the-loop and it is calibrated with experimental data. The developed tool, called VirtualWheel, can be applied for the optimisation of design reducing prototyping and experimental test costs in the development phase. In the first section, the failure criterion is selected. In the second one, the conversion of hardware test-rig into virtual model is described in detail by focusing on critical aspects of finite element modelling. In conclusion, failure prediction is compared with experimental test results.
A Methodology for Automotive Steel Wheel Life Assessment / Rovarino, D.; Actis Comino, L.; Bonisoli, E.; Rosso, C.; Venturini, S.; Velardocchia, M.; Baecker, M.; Gallrein, A.. - In: SAE TECHNICAL PAPER. - ISSN 0148-7191. - STAMPA. - 2020-:April(2020). [10.4271/2020-01-1240]
A Methodology for Automotive Steel Wheel Life Assessment
Bonisoli E.;Rosso C.;Venturini S.;Velardocchia M.;
2020
Abstract
A methodology for an efficient failure prediction of automotive steel wheels during fatigue experimental tests is proposed. The strategy joins the CDTire simulative package effectiveness to a specific wheel finite element model in order to deeply monitor the stress distribution among the component to predict damage. The numerical model acts as a Software-in-the-loop and it is calibrated with experimental data. The developed tool, called VirtualWheel, can be applied for the optimisation of design reducing prototyping and experimental test costs in the development phase. In the first section, the failure criterion is selected. In the second one, the conversion of hardware test-rig into virtual model is described in detail by focusing on critical aspects of finite element modelling. In conclusion, failure prediction is compared with experimental test results.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2818958