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Wind noise is a significant source of interior noise in automobiles at cruising conditions, potentially creating dissatisfaction with vehicle quality. While wind noise contributions at higher frequencies usually originate with transmission through greenhouse panels and sealing, the contribution coming from the underbody area often dominates the interior noise spectrum at lower frequencies. Continued pressure to reduce fuel consumption in new designs is causing more emphasis on aerodynamic performance, to reduce drag by careful management of underbody airflow at cruise. Simulation of this airflow by Computational Fluid Dynamics (CFD) tools allows early optimization of underbody shapes before expensive hardware prototypes are feasible. By combining unsteady CFD-predicted loads on the underbody panels with a structural acoustic model of the vehicle, underbody wind noise transmission could be considered in the early design phases.

Exhaust and muffler noise is a challenging problem in the transport industry. While the main purpose of the system is to reduce the intensity of the acoustic pulses originating from the engine exhaust valves, the back pressure induced by these systems must be kept to a minimum to guarantee maximum performance of the engine. Emitted noise levels have to ensure comfort of the passengers and must respect community noise regulations. In addition, the exhaust noise plays an important role in the brand image of vehicles, especially with sports car where it must be tuned to be “musical”. However, to achieve such performances, muffler and exhaust designs have become quite complex, often leading to the rise of undesired self-induced noise. Traditional purely acoustic solvers, like Boundary Element Methods (BEM), have been applied quite successfully to achieve the required acoustic tuning.

A numerical investigation of automobile sunroof buffeting on a prototype sport utility vehicle (SUV) is presented, including experimental validation. Buffeting is an unpleasant low frequency booming caused by flow-excited Helmholtz resonance of the interior cabin. Accurate prediction of this phenomenon requires accounting for the bi-directional coupling between the transient shear layer aerodynamics (vortex shedding) and the acoustic response of the cabin. Numerical simulations were performed using the PowerFLOW code, a CFD/CAA software package from Exa Corporation based on the Lattice Boltzmann Method (LBM). The well established LBM approach provides the time-dependent solution to the compressible Navier-Stokes equations, and directly captures both turbulent and acoustic pressure fluctuations over a wide range of scales given adequate computational grid resolution.

The efficiency of a gap-type of deflector for suppressing vehicle sunroof buffeting is studied in this work. Buffeting is an unpleasant low frequency booming caused by flow-excited Helmholtz resonance of the interior cabin. Accurate prediction of this phenomenon requires accounting for the bi-directional coupling between the transient shear layer aerodynamics (vortex shedding) and the acoustic response of the cabin. Numerical simulations were performed using a CFD/CAA numerical method based on the Lattice Boltzmann Method (LBM). The well established LBM approach provides the time-dependent solution to the compressible Navier-Stokes equations, and directly captures both turbulent and acoustic pressure fluctuations over a wide range of scales given adequate computational grid resolution. In this study the same gap-type deflector configuration is installed on two different types of vehicles, a SUV and a sedan.

For most car manufacturers, aerodynamic noise is becoming the dominant high frequency noise source (> 500 Hz) at highway speeds. Design optimization and early detection of issues related to aeroacoustics remain mainly an experimental art implying high cost prototypes, expensive wind tunnel sessions, and potentially late design changes. To reduce the associated costs as well as development times, there is strong motivation for the development of a reliable numerical prediction capability. The goal of this paper is to present a computational approach developed to predict the greenhouse windnoise contribution to the interior noise heard by the vehicle passengers. This method is based on coupling an unsteady Computational Fluid Dynamics (CFD) solver for the windnoise excitation to a Statistical Energy Analysis (SEA) solver for the structural acoustic behavior.

Over the past decades, interior noise from wind noise or engine noise have been significantly reduced by leveraging improvements of both the overall vehicle design and of sound package. Consequently, noise sources originating from HVAC systems (Heat Ventilation and Air Conditioning), fans or exhaust systems are becoming more relevant for perceived quality and passenger comfort. This study focuses on HVAC systems and discusses a Flow-Induced Noise Detection Contributions (FIND Contributions) numerical method enabling the identification of the flow-induced noise sources inside and around HVAC systems. This methodology is based on the post-processing of unsteady flow results obtained using Lattice Boltzmann based Method (LBM) Computational Fluid Dynamics (CFD) simulations combined with LBM-simulated Acoustic Transfer Functions (ATF) between the position of the sources inside the system and the passenger’s ears.