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The capability to drive NVH quality into vehicle frame design is often compromised by the lack of available predictive tools that can be developed and applied within the timeframe during which key architectural design decisions are required. To address this need, a new parametric frame modeling approach was developed and is presented in this paper. This fully parameterized model is capable of fast modal, static stiffness & weight assessments, as well as DSA/optimization for frame design changes. This tool has been proven to be effective in improving speed, quality and impact of NVH hardware decisions.

Vehicle wind noise testing is usually done at elaborate tunnel facilities with minimal tunnel background noise, Techniques to reduce the tunnel noise, such as acoustic panels or improved fan systems, translate into higher costs for wind noise testing. We introduce an innovative procedure using an adaptive filtering algorithm to separate the tunnel noise from the wind noise inside the cabin of the vehicle. This new technique is capable of artificially reducing the tunnel background noise at low frequencies. Such a procedure has the potential to dramatically improve the wind noise testing capability of any wind tunnel, without the need for costly acoustic treatments.