Efficient Conceptual Tire Model and Parameter Identification for NVH Applications
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- Provide download link
- Format
- Price
- Non-members (tax incl.):¥6,600 Members (tax incl.):¥5,280
- Paper/Info type
- SAE Paper
No.2021-01-0937
- Pages
- 1-10(Total 10 p)
- Date of publication
- Apr 2021
- Publisher
- SAE International
- Language
- English
- Event
- SAE WCX Digital Summit 2021
Detailed Information
Author(E) | 1) Domenico Minervini, 2) Marc Brughmans |
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Affiliation(E) | 1) Siemens Digital Industries Software, 2) Siemens Digital Industries Software |
Abstract(E) | With the advent of the electrification era, rolling noise is set to become a dominant source of noise for electric vehicles due to the phasing out of the internal combustion engine. The vibrations generated by tire-road interaction are transferred through the wheel center to the knuckle and subsequently through the vehicle cabin. With the advance of the simulation techniques, the description of tire operational phenomena has improved. However, some limitations are present. These include low computational efficiency in a full-vehicle simulation and absence of direct validation with the real tire in the same operational conditions. Siemens Digital Industries Software currently offers a lightweight combined test and model-based solution for tire NVH for the assessment of structure-borne noise. The aim of this paper is to demonstrate the potential of a pragmatic approach able to capture the static tire dynamic behavior up to 300 Hz. Initially, a consolidated process is able to generate a conceptual twin of the target tire in few seconds for improved physical representation. An automated optimization process easily adapts tire parameters considering both the wave propagation and transfer from the road to knuckle, in view of full-vehicle integration. Effectiveness of the parameter identification procedure is granted by the improved description of the tread-sidewall interaction, the presence of flexible parametric rim and the inclusion of the dispersion plot as a time-saving solution for modal visualization and classification. Finally, the focus moves towards the description of rolling phenomena without using extensive time domain simulation. |