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For most car manufacturers, wind noise from the greenhouse region has become the dominant high frequency noise contributor at highway speeds. Addressing this wind noise issue using experimental procedures involves 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 use of a reliable numerical prediction capability early in the vehicle design process. Previously, a computational approach that couples an unsteady computational fluid dynamics solver (based on a Lattice Boltzmann method) to a Statistical Energy Analysis (SEA) solver had been validated for predicting the noise contribution from the side mirrors. This paper presents the use of this computational approach to predict the vehicle interior noise from the windshield wipers, so that different wiper placement options can be evaluated early in the design process before the surface is frozen.

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.

Flow generated acoustic sources are of significant import for automotive applications since perception of noise is a critical customer satisfaction issue. High temperature acoustic sources known as thermo-acoustics such as those occurring inside an exhaust system of a vehicle, an important subset of acoustic sources, is the subject of the investigation. In this article, we study a Rijke tube configuration that consists of a vertical and hollow cylindrical tube open at both ends where sound is generated by buoyancy driven flow as a result of a heated wire gauze placed in the bottom half of the tube. This configuration captures the essence of the thermo-acoustic phenomena and was investigated both numerically and experimentally and good agreement was observed between the two.

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.

Car manufacturers put large efforts into reducing wind noise to improve the comfort level of their cars. Each component of the vehicle is designed to meet its individual noise target to ensure the wind noise passenger comfort level inside the vehicle is met. Sunroof designs are tested to meet low-frequency buffeting (also known as boom) targets and broadband noise targets for the fully open sunroof with deflector and for the sunroof in vent position. Experimentally testing designs and making changes to meet these design targets typically involves 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 use of a reliable numerical prediction capability early in the vehicle design process.

Unusual noises during vehicle acceleration often reflect poorly on customer perception of product quality and must be removed in the product development process. Flow simulation can be a valuable tool in identifying root causes of exhaust noises created due to tailpipe openings surrounded by fascia structure. This paper describes a case study where an unsteady Computational Fluid Dynamics (CFD) simulation of the combined flow and acoustic radiation from an exhaust opening through fascia components provided valuable insight into the cause of an annoying flow noise. Simulation results from a coupled thermal/acoustic analysis of detailed tailpipe opening geometry were first validated with off-axis microphone spectra under wide open throttle acceleration. After studying the visualizations of unsteady flow velocity and pressure from the CFD, a problem that had proved difficult to solve by traditional “cut and try” methods was corrected rapidly.

A computational design study, performed in conjunction with experiments, to reduce the howl noise caused by the roof rack crossbars of a production automobile is presented. This goals were to obtain insight into the flow phenomenon causing the noise, and to do a design iteration study that would lead to a small number of cross-section recommendations for crossbars that would be tested in the wind tunnel. The flow condition for this study is 0 yaw at 30 mph inlet speed, which experimentally gives the strongest roof rack howl for the vehicle considered for this study. The numerical results have been obtained using the commercial CFD/CAA software PowerFLOW. The simulation kernel of this software is based on the numerical scheme known as the Lattice Boltzmann Method (LBM), combined with a two-equation RNG turbulence model.

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.

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 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. This paper presents a computational approach that can be used to predict the vehicle interior noise from the greenhouse wind noise sources, during the early stages of the vehicle developmental process so that design changes can be made to improve the wind noise performance of the vehicle.

Statistical Energy Analysis (SEA) models are routinely being adopted in up-front automotive sound package design. SEA models serve two important functions. First they provide a means of assessing noise and vibration performance relative to absolute targets. Secondly, they are used to assess various alternative designs or changes required to meet targets. This paper addresses how to objectively evaluate both the absolute and relative predictive capability of SEA models. The absolute prediction is assessed using a hypothesis test to determine membership of the analytical prediction relative to a set of test data. The relative prediction is assessed using hardware-designed experiments to estimate design sensitivities. Both have been found useful to drive model improvement efforts. Being able to objectively document model capability also improves the credibility of SEA model predictions and the design information they deliver.

This paper reports on a case study involving the use of SEA methods in the acoustic design of an advanced design luxury sedan. The power of the analytical method was used to advantage in a case of a vehicle with very challenging NVH targets. Three practical issues are highlighted; review of a method to handle adding components that contribute acoustic absorption, presentation of data to aid vehicle content decisions, and design sensitivity analysis. This effort demonstrates an example in which SEA modeling provided relevant and timely input to the vehicle design team to aid decision making for sound package content.

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.

Autonomous vehicles need to be able to detect and react to the approach of emergency vehicles, such as fire trucks and ambulances. Exterior acoustic sensors may be deployed to “listen” for sirens of these emergency vehicles. Unfortunately, wind noise from turbulence at cruising conditions can greatly interfere with these exterior sensors. Early assessment of wind noise at alternative sensor locations enables engineers to make design changes to reduce that wind noise, either by choosing quieter sensor locations or by changing the source of interfering turbulence. A computational approach to evaluate the wind noise due to exterior shape at acoustic sensor locations is demonstrated in this paper. By comparing simulated spectra of wind noise at each proposed sensor location to that from a nearby siren signal, designers can rank sensor locations for acoustic detection in different frequency bands.

Statistical energy analysis (SEA) has recently emerged as an effective tool for design assessment in the automotive industry. Automotive OEM companies develop vehicle models to aid design of body and chassis systems. The tire and wheel suppliers develop and supply component models to OEM companies in the engineering stage. In the model development process, some information on the vehicle side or component side is necessary for model development and correlation. A suitable termination representation of the vehicle characteristics on the tire/wheel model is required. This termination should account for the dissipation of energy on vehicle body and chassis side, otherwise the component model will overestimate the vibration responses and energy levels. On the vehicle model side, a representative simplified tire/wheel model may be sufficient for full vehicle road noise simulation.

Statistical Energy Analysis (SEA) models of passenger vehicles may involve 400-500 subsystems to characterize the vehicle structure and sound package. Full sized models are often difficult to describe and some results may be awkward to present. A more intuitively comprehensible model size would involve 30-50 subsystems, which is typical of an experimental SEA approach. A methodology is described for processing full SEA model results in condensed form including major structural components and acoustic spaces. The approach is based on the experimental SEA methodology in which power injection and response predictions are carried out for 30-50 condensed subsystems. Full matrix inversion and weak coupling assumptions were investigated. Differences between condensed and full SEA model predictions are observed when the subsystem connectivity is limited.

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.

Off-highway equipment operates in residential communities and must meet their radiated noise targets to be compliant with noise regulations and to be competitive in the marketplace. Traditional find and fix noise testing of late-stage prototype designs may cause launch delays, with intense time pressures that often result in missed opportunities to create excellent products with good value. Accurate simulation of noise from these machines allows noise targets to be assessed at each stage of product development, giving engineers time to develop low noise products without adding excessive manufacturing cost. Simulation of an early prototype of a new vacuum excavator showed excessive levels of radiated noise in two different frequency ranges. Further investigation of the simulation results of these two spectrum ranges indicated different noise mechanisms producing the excessive noise levels.

The ability to assess noise transmitted through seals to cabin interiors early in the design process is very important for automotive manufacturers. When a seal design is inadequate, the noise transmitted can dominate the interior noise, making the wind noise performance of the vehicle unacceptable. This can cause launch delays, increasing costs and risking loss of sales. Designing seals using conventional experimental processes is challenging, since the location and strength of flow noise sources are not known when the seal design is planned. Making changes to the seal system after the tooling stage is expensive for manufacturers as tooling and redesign costs can be considerable. Deliberate overdesign by adding multiple layers of seals in a wide range of locations also can reduce profit by unnecessarily raising part and manufacturing costs.

Thermoacoustic heat engines convert heat into useful energy by generating acoustic waves from a heat source that can then be extracted as useful work. These engines are inexpensive, robust, versatile, and capable of extracting energy from a wide variety of heat sources ranging from waste heat from power plants to exhaust heat of vehicles. In this article, our investigation focuses on using simulation workflows to improve the performance of thermoacoustic engines. We begin with validating the workflows with published data for both traveling wave and standing wave thermoacoustic engines. Following that, we investigate the effect of changing the working fluid and the operating pressure to increase acoustic power. This study uses a coupled PowerFLOW™ and PowerTHERM™ methodology to simulate the buoyancy-driven flows that generate acoustic pressure waves. Good correlations were observed for both traveling and standing wave thermoacoustic engines.

Traditionally vehicles are designed for wind noise under ideal steady wind conditions. But, passenger comfort is affected by high modulation of cabin noise while cruising in traffic due to variations of instantaneous wind speed and direction from driving through large-scale turbulence. In consequence, designing a vehicle for the best performance in a low-turbulence wind tunnel may lead to issues during on-road conditions. To predict the interior noise corresponding to on-road turbulence, a simulation approach is proposed combining an upstream turbulence flow simulation with an SEA vehicle model. This work is an extension of existing well validated procedures for steady wind conditions. Time-segmented transient loads on panels and steady-state structural acoustics transfer functions are combined, producing interior noise results for a series of overlapping time segments.