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Random incidence sound absorption measurements of automotive components such as floor carpets, seats, headliners and hoodliners are important during the design and development of noise control treatments in a vehicle. Small volume reverberation rooms [1]1 have been widely used in practice to determine the absorption properties of those components. The SAE Acoustical Materials Committee has organized a task force to develop a standard procedure for measuring random incidence sound absorption properties of flat samples, as well as automotive components in small reverberation rooms. Statistical analysis and correlation study between large reverberation rooms and small reverberation rooms of flat samples using data acquired from a recent round robin study were reported in SAE Paper 2005-01-2284 [2, 3].

This paper describes the work carried out to assess the structure-borne and airborne contributions in the Rieter APAMAT II testing machine. The APAMAT II system was designed to measure the effectiveness of various trim and barrier treatments in automotive interior applications. The individual structure-borne and airborne contributions from the ball impact on the treated panel cannot be obtained directly from the sound pressure level measurements in the receiver chamber of the system. A hybrid modeling technique is proposed that incorporates finite element (FE) and statistical energy analysis (SEA) methods to develop vibro-acoustic models across the entire frequency range for analyzing transmission characteristics of various trim configurations. This provides an analytical model that can adequately predict the vibro-acoustic response under structure-borne loads at low to mid frequencies.

Sound transmission loss and sound absorption measurements are conducted to characterize acoustical performance of noise control materials and components used in vehicles. These measured data are often used to select materials and define acoustical targets. It is imperative to have accurate and repeatable data. Process variability is often monitored using measurement data collected over time. A certain amount of variability due to random causes is always expected. Acoustical measurements have inherent variability from different operators, equipment, test setup, environment etc. When variation in the measurements is due to random causes the measurements are in-control and measured data are considered “good”. However, special cause variations in the measured data such as operator error or setup error must be identified and corrected. Control chart is a popular statistical tool for monitoring process variability and improving quality.

In the early stages of a vehicle program, sound package design is significantly complicated by numerous competing requirements including cost, weight, acoustical targets and packaging space. The problem is further convoluted due to a limited definition of the vehicle at this time. In this article, a Statistical Energy Analysis (SEA) model of the vehicle is created based on a gross description of the vehicle architecture. A large material database of commonly used sound package configurations is then linked to the SEA model. Genetic Algorithms (GA) are finally applied to optimize the sound package design to satisfy cost, weight, acoustical targets and packaging requirements in the vehicle design.

System Engineering has increasingly been applied in the automotive industry to develop quality vehicles efficiently and effectively. It is particularly important to use System Engineering methods in the early stages of vehicle development when all requirements such as performance, package space, cost and weight are actively defined and balanced, and when decisions are made that have substantial downstream design consequences. To achieve effective balance, decisions have to be data driven to complement engineering experience and judgment. Analytical tools (CAE) have been developed in the industry to evaluate and synthesize designs. However, there are limited examples and discussions in the literature on how the “upfront” CAE can be implemented to integrate cross-functional requirements into the component design. Statistical Energy Analysis (SEA) method is the CAE tool used in sound package development.

Small reverberation rooms are used in common practice for determining random incidence sound absorption properties of flat materials and finished parts. Based on current small reverberation room usage in the automotive industry, there is a need for standardization that would bring about an appropriate level of consistency and repeatability. To respond to this need, a feasibility study is being pursued by an SAE task force, under the direction of the Acoustical Materials Committee, to develop a small volume reverberation room test method for conducting random incidence sound absorption tests. In addition to an accepted test method for small reverberation rooms, a data driven correlation that relates full size reverberation room absorption testing to small size reverberation room testing would be beneficial in understanding the usage of both. A Round Robin study has been underway for more than three years and will be completed in 2005.

Lightweighting of vehicle panels enclosing vehicle cabin causes NVH degradation since engine, road, and wind noise acoustic sources propagate to the vehicle interior through these panels. In order to reduce this NVH degradation, there is a need to develop new NVH sound package materials and designs for use in lightweight vehicle design. Statistical Energy Analysis (SEA) model can be an effective CAE design tool to develop NVH sound packages for use in lightweight vehicle design. Using SEA can help engineers recover the NVH deficiency created due to sheet metal lightweighting actions. Full vehicle SEA model was developed to evaluate the high frequency NVH performance of “Vehicle A” in the frequency range from 200 Hz to 10 kHz. This correlated SEA model was used for the vehicle sound package optimization studies. Full vehicle level NVH laboratory tests for engine and tire patch noise reduction were also conducted to demonstrate the performance of sound package designs on “Vehicle A”.

SAE acoustics materials committee published updates of SAE J1400 Standard - Laboratory Measurement of the Airborne Sound Barrier Performance of Flat Materials and Assemblies in 2017. In the standard, a control sample is defined with a specific construction to determine the suitability of the test suite. A set of measured sound transmission loss data of the control sample are included in the published updated standard. Autoneum North America Acoustics Laboratory constructed a control sample based on the design in the standard. Sound transmission loss (STL) measurement of this control sample was performed and results are consistent with published data below 2000 Hz. Above 2000 Hz, STL results are above published limits. Sound intensity measurement and flanking noise paths measurements confirmed the measured STL values of the control sample.

The Multi Material Lightweight Vehicle (MMLV) developed by Magna International and Ford Motor Company is a result of a US Department of Energy project DE-EE0005574. The project demonstrates the lightweighting potential of a five passenger sedan, while maintaining vehicle performance and occupant safety. Prototype vehicles were manufactured and limited full vehicle testing was conducted. The Mach-1 vehicle design, comprised of commercially available materials and production processes, achieved a 364 kg (23.5%) full vehicle mass reduction, enabling the application of a 1-liter 3-cylinder engine resulting in a significant environmental benefit and fuel reduction. This paper includes details associated with the noise, vibration and harshness (NVH) sound package design and testing. Lightweight design actions on radiating panels enclosing the vehicle cabin typically cause vehicle interior acoustic degradation due to the reduction of panel surface mass.