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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.

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.

Acoustics comfort is a key point for the ground transportation market and in particular in the automotive area. A significant contributor to the noise levels in the cabin in the range 200Hz to 3000Hz is the HVAC (Heating, Ventilating, and Air Conditioning) system, consisting of sub-systems such as the air intake duct, thermal mixing unit, blower, ducts, and outlet vents. The noise produced by an HVAC system is mainly due to aeroacoustics mechanisms related to the flow fluctuations induced by the blower rotation. The structure borne noise related to the surface induced vibrations and to the noise transmission through the dash or plastic panels may also contribute but is not considered in this study. This study presents a digital approach for HVAC aeroacoustics noise predictions related to the ducts and outlet vents. In order to validate the numerical method flow and acoustics measurements are performed on production HVAC systems placed in an anechoic room.

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.

Nowadays vehicle quality is rated for noise and vibration and the interior sound levels have become a major target of automotive companies. Strides have been made in reducing power train, tire and external wind noise over the years. However, HVAC and blower fan flow-induced noise reaches the interior cabin without any sound isolation and can strongly impact customer comfort. In the early stage of vehicle design, it is experimentally difficult to get an estimate of the flow pattern and sound levels. The goal of this study is to develop and validate a numerical noise prediction tool for complete HVAC systems noise, defined as the arrangement of sub-systems such as air intake duct, thermal mixing unit, blower, ducts and outlet vents. This tool can then be used during the development of vehicles to evaluate and optimize the aeroacoustics performances of the system without additional or belated experiments.