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Quality and refinement are of paramount importance for luxury vehicles. The rapid electrification of the automotive industry has increased the contribution of aeroacoustics to the consumer perception of sound quality. The ability to predict whole vehicle aeroacoustic interior noise is essential in the development of vehicles with an extraordinary acoustic environment. This publication summarises the development of a process to combine lattice Boltzmann computational fluid dynamics simulations, with a whole vehicle statistical energy analysis model, to predict the aeroacoustic contribution from all relevant sources and paths. The ability to quantify the relative contribution of glazing panels and path modifications was also investigated. The whole vehicle aeroacoustic interior noise predictions developed, were found to be within 2dB(A) of comparable test vehicle wind tunnel measurements, across a broad frequency range (250-5000 Hz).

Wind noise is a major contributor to vehicle noise and a very common consumer complaint for overall vehicle quality [1]. The reduction of wind noise is becoming even more important as powertrain noise is reduced or eliminated (by conversion to hybrid and electric vehicles) and as the importance of quiet interior environment for hands-free device use and voice activation systems becomes more pronounced. In contrast to other noise sources such as tires, engine, intake, exhaust or other component noise whose acoustic loads may be measured in a direct and standardized way with the proper equipment, wind noise is very difficult to predict because the acoustic part of wind noise is a small component of overall fluctuating pressures. It is very challenging to either directly measure or to simulate the acoustic component of fluctuating exterior pressures using CFD (Computational Fluid Dynamics) without a great deal of specialized experience in this area.

This paper addresses the NVH design of a light rail vehicle whose maximum allowable interior SPL levels at certain speeds are regulated and may vary between countries, states, and cities. The objective of this study was to predict sound pressure levels (SPL) at several interior locations across a wide range of frequencies and estimate if the current design configuration will meet the noise level limits. Statistical Energy Analysis (SEA) was used to predict interior SPL and to understand and rank the various noise contribution paths and give a better understanding of the physics of transmission and what types of design changes are most effective to reduce the overall interior SPL to meet targets. A typical light rail vehicle is composed of a frame-like structure covered by lightweight panels and with interior panels that are increasingly made from composites, sandwich, laminated, or honeycomb materials or extruded panels.

The contribution of wind noise through the glasses into the vehicle cabin is a large source of customer concern. The wind noise sources generated by turbulent flow incident on the vehicle surfaces and the transmission mechanisms by which the noise is transmitted to the interior of the vehicle are complex and difficult to predict using conventional analysis techniques including Computational Fluid Dynamics (CFD) and acoustic analyses are complicated by the large differences between turbulent pressures and acoustic pressures. Testing in dedicated acoustic wind tunnel (AWT) facilities is often performed to evaluate the contribution of wind noise to the vehicle interior noise in the absence of any other noise sources. However, this testing is time-consuming and expensive and test hardware for the vehicle being developed is often not yet available at early stages of vehicle design.

For purposes of reducing development time, cost and risk, the majority of new vehicles are derived strongly or at least generally from a surrogate vehicle, often of the same general size or body style. Previous test data and lessons learned can be applied as a starting point for design of the new vehicle, especially at early phases of the design before definite design decisions have been finalized and before prototype of production test hardware is available. This is true as well of vehicle NVH development where most new vehicles being developed are variants of existing vehicles for which the main noise transfer paths from sources of interest are already understood via test results and existing targets. The NVH targets for new vehicles are defined via benchmarking, market considerations, and other higher-level decisions. The objective is then to bridge the gap between test data from surrogate vehicles to direct support of the NVH development of new vehicle programs.

Statistical Energy Analysis (SEA) is the standard analytical tool for predicting vehicle acoustic and vibration responses at high frequencies. SEA is commonly used to obtain the interior Sound Pressure Level (SPL) due to each individual noise or vibration source and to determine the contribution to the interior noise through each dominant transfer path. This supports cascading vehicle noise and vibration targets and early evaluation of the vehicle design to effectively meet NVH targets with optimized cost and weight. A common misconception is that SEA is only capable of predicting a general average interior SPL for the entire vehicle cabin and that the differences between different locations such as driver's ear, rear passenger's ear, lower interior points, etc., in the vehicle cannot be analytically determined by an SEA model.