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Transfer path analyses of vehicle bodies are widely considered as an important tool in the noise, vibration and harshness design process, as they enable the identification of the dominating transfer paths in vibration problems. It is highly beneficial to model uncertain parameters in early development stages in order to account for possible variations on the final component design. Therefore, parameter studies are conducted in order to account for the sensitivities of the transfer paths with respect to the varying input parameters of the chassis components. To date, these studies are mainly conducted by performing sampling-based finite element simulations. In the scope of a sensitivity analysis or parameter studies, however, a large amount of large-scale finite element simulations is required, which leads to extremely high computational costs and time expenses. This contribution presents a method to drastically reduce the computational burden of typical sampling-based simulations.

Uncertainties play a major role in vibroacoustics - especially in car body design in the preliminary development because of the overall spread in the production that should be covered with one simulation model. Therefore, we use uncertain input parameters to determine the stochastically distributed admittance of the car body before each part of the car is fully designed. To gain a stochastic result - the stochastically distributed admittance curve - we calculate a deterministic finite element simulation several times with sets of stochastically distributed input parameter values. To reduce simulation time and cost of the car model with many million degrees of freedom we focus on the uncertain parameters that show a significant influence on the admittance curve. It is therefore necessary to be able to accurately estimate for each parameter if its influence on the admittance of the car body plays a major role for the noise vibration harshness simulation.

Underbody aerodynamics has become increasingly important over the last three decades because of its vital contribution to improving a vehicle's overall performance. This was the motivation for the research conducted by BMW Aerodynamics, concerning the determination of the overall pressure distribution on the underbody of a series-production vehicle. Static pressure measurements have been taken under various test conditions. Real on-road tests were carried out as well as wind tunnel experiments under application of different road simulation techniques. The analyzed vehicle configurations include wheel rim-tire and body modifications. The results presented include surface pressure data, drag and lift coefficients, ride heights, pitch and roll angles. The acquired data is used to examine the underbody flow topology and determine how the diverse attempts to represent the real on-road conditions affect its pressure distribution.

This study inquired into perceived attributes of car interior noise and correlating psychoacoustic parameters. Auditory assessments of a total of 29 vehicles were performed during cruise and acceleration in two independent road tests. Four perceptual dimensions were found to determine the sound evaluations: comfort/loudness, sportiness, harshness, and timbre. A regression model was used to predict comfort/loudness from sound level, roughness, sharpness and speech intelligibility (SVI). Instrumental assessments of engine roughness demonstrated to predict harshness to a large extent. Sportiness was substantially correlated with the increase of engine sound level due to load change. The latter finding was further examined in a third experiment, using sound synthesis in a test vehicle.

Engine management systems in modern motor vehicles are becoming increasingly extensive and complex. The functionality of the control units which are the central components of such systems is determined by the hardware and software. They are the result of a lengthy development and production process. Road testing of control units, together with testing them on the engine test bench, is very time consuming and costly. An alternative is to test control units away from their actual environment, in a virtual context. This involves operating the control unit on a Hardware-in-the-Loop test bench. The control unit's large number of individual and interlinked functions necessitates a structured, reproducible test procedure. These tests can, however, only be conducted once an engine prototype has been completed, as the parameters for the existing conventional models are determined from the data measured on the test bench.