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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.

A computational process for early stage vehicle shape assessment for automotive front window buffeting and greenhouse wind noise is presented. It is a challenging problem in an experimental process as the vehicle geometry is not always finalized. For example, the buffeting behavior typically worsens during the vehicle development process as the vehicle gets tighter, leading to expensive late counter measures. We present a solution using previously validated CFD/CAA software based on the Lattice Boltzmann Method (LBM). A CAD model with realistic automotive geometry was chosen to simultaneously study the potential of different side mirror geometries to influence the front window buffeting and greenhouse wind noise phenomena. A glass mounted mirror and a door mounted mirror were used for this comparative study. Interior noise is investigated for the two phenomena studied. The unsteady flow is visualized and changes in the buffeting and wind noise behavior are explored.

Acoustic comfort of automotive cabins has progressively become one of the key attributes of passenger comfort within vehicle design. Wind noise and the heating, ventilation, and air conditioning (HVAC) system noise are two of the key contributors to noise levels heard inside the car. The increasing prevalence of hybrid technologies and electrification has an associated reduction in powertrain noise levels. As such, the industry has seen an increasing focus on understanding and minimizing HVAC noise, as it is a main source of noise in the cabin particularly when the vehicle is stationary. The complex turbulent flow path through the ducts, combined with acoustic resonances can potentially lead to significant noise generation, both broadband and tonal.

A computational approach to evaluate rear-view mirror performance on wind noise in cars is presented in this paper. As a comfort metric at high speeds, wind noise needs to be addressed, for it dominates interior noise at mid-high frequencies. The impetus on rear-view mirror design arises from its crucial role in the flow field and the resulting pressure fluctuations on the greenhouse panels. The motivation to adopt a computational approach arises from the need to evaluate mirror designs early in vehicle design process and thus in conjunction with different vehicle shapes. The current study uses a Lattice Boltzmann method (LBM) based computational fluid dynamics(CFD) solver to predict the transient flow field and a statistical energy analysis(SEA) solver to predict interior noise contribution from the greenhouse panels. The accuracy of this computational procedure has been validated and published in the past.

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.

Wind noise has become an important indicator for passenger automobile quality. Several transmission paths can be related to different parts of the vehicle exterior. While the greenhouse (side glasses, windshield, seals & others) often dominates the interior noise level above 500 Hz, the contribution coming from the underbody area usually dominates the interior noise spectrum at lower frequencies. This paper describes a framework of numerical tools which is capable of determining realistic underbody turbulent and acoustic loads being generated for typical driving conditions, as well as performing the noise transmission through underbody panels and the propagation of sound to the drivers ear location.

Developing a low interior noise level of vehicles is a big challenge - even a greater one if one thinks about aeroacoustics. Aeroacoustic noise and its origins are usually identified with the help of prototypes when exterior design changes or the replacement of exterior parts like side mirrors are very limited. However, computational aeroacoustic (CAA) methods in virtual project phases offer more design options for the vehicle's geometric shape. The early consideration of aeroacoustic relevant design changes helps to keep project costs low by avoiding tool changes. This paper describes MAGNA STEYR's virtual aeroacoustic process starting from standardized model generation and simulation of wind noise, including the validation of computational results via comparison with measurement data gathered in an acoustic wind tunnel. The simulations are carried out using the commercial CAA code “PowerFLOW” (Exa) based on the Lattice-Boltzmann method.

Design of HVAC system plays an important role in acoustic comfort for passengers. With automotive world moving towards electrical vehicles where powertrain noise is low, designing low noise HVAC system is becoming more important. For an automobile manufacturer, ability to predict the production vehicle cabin noise at the early design stage is important as it allows more freedom for design changes, which can be incorporated in the vehicle at lower cost. Although HVAC prototype and system level testing at early design stage is possible for noise estimation but flow field is not visible in test that makes difficult to improve design. CFD simulation can provide detailed information on flow field, noise source strength and location. But in such a simulation, accurate prediction has been a challenge due to the inability of CFD tools to model acoustic absorptive characteristics of interior walls of cabin.

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.