The automotive industry is evolving towards Electrified Vehicles (EV) in the recent years. Compared to the traditional ICE vehicles, tire noise induced by the tire-road interaction, is no longer masked by the internal combustion engine, and therefore becomes one of the most dominant sources of noise within the cabin and acoustic emission perceived by by-standers.
Robust source characterization is one of the most important tasks for road noise prediction. The receiver-independent tire blocked forces are often used as ire-road source characteristics, which can be applied to any test-based or FE-based vehicle model to obtain the interior noise. They can be inversely identified from measurements on a tire test rig or on an in-situ vehicle. However, this inverse process needs to be repeated for different tires, roads and rolling speeds, which can become time-consuming and expensive.
In this paper, an alternative solution for the blocked force calculation is proposed: a direct simulation of blocked forces from measured road profile data. This approach consists of two major steps. The first step is a road envelopment module, which allows the user to reprocess a once measured road profile at any desired speed. This is done using a CAE based approach to get in an objective manner to the right envelopment settings for the given tire, thus avoiding dependency on experience-based tuning of envelopment functions. In a second step, the enveloped profile is applied to a test-driven, concept CAE tire model which enables to predict the blocked forces and moments. As the whole process is implemented in the frequency domain, this allows efficient integration with full vehicle NVH calculations for design optimization.
This paper gives a detailed description of the proposed direct or forward approach to get to the blocked forces, with a validation case to demonstrate the obtained results.