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The door response to audio excitation contributes to the overall performance of the audio system on several items. First, acting as a cabinet, it influences the loudspeaker response. Second, due to the door trim inner panel radiation, the radiated power is disturbed. A third effect is the regular occurrence of squeak and rattle, that will not be considered at this stage. Design issues regarding these attributes are numerous, from the loudspeaker design to door structure and trim definition. Modeling then appears as an unavoidable tool to handle the acoustic response of the loudspeaker in its actual surrounding.

Structural damping is known as one of the most efficient design variable in order to reduce structure-borne noise. At medium frequencies (200 - 800 Hz) this damping can be obtained from various devices such as interior trim packages or viscoelastic layers. In order to improve car body design (cost, weight, performance, reliability), one must have a good understanding of ‘where’ and ‘how much’ damping must be specified. Because dissipative devices are usually localized, a single panel damping specification is more convenient than a global specification. The damping loss factor seems to be an appropriate indicator in the medium frequency range. The damping loss factor is the ratio of the dissipated power to the time derivative of the strain energy. Considering an isolated panel, the dissipated power is equal to the injected one.

This paper compares the application of a non-intrusive on-site component Transfer Path Analysis (TPA) method used to identify interface forces to a previously performed direct blocked forces measurement. The latter is the current practice for determining the load cases related to isolated vehicle components. Force transducers are placed between the investigated source component and a specific rigid measurement rig. The comparison presented aims to answer the question of whether the faster and cheaper TPA method can produce accurate enough interface forces. The TPA method used in this work calculates the force component contributions without disassembly of the interfaces and through the local stiffness of multiple indicator positions per interface combined with operational measurement. The method is based on the application of an inverse matrix model. This approach is applied to a vehicle road noise investigation carried out on a roller bench at different roller speeds.

This paper deals with the vibroacoustics of complex systems over a broad frequency band of analysis. The considered system is composed of a complex structure coupled with an internal acoustic cavity. The vibroacoustics model is represented by the usual global-displacements elastic modes associated with the main part, and by local elastic modes, associated with the preponderant vibrations of the flexible sub-parts. The main difficulty of the vibroacoustics analysis of complex system is the interweaving of the global displacements with the local displacements, which introduces an overlap of the usual three frequency domains (LF, MF and HF). A reduced-order computational vibroacoustic model constructed with a classical modal analysis is introduced. Nevertheless, the dimension of such reduced-order model (ROM) is still high when the frequency band of analysis overlaps for each frequency domain.

Car interior noise performances, such as booming noise and rolling noise, are usually computed in mid-low frequency range by multiplying vehicle vibroacoustic FRFs and the source (powertrain and chassis) blocked force spectrum. Unfortunately, during the early design stages, the cavity as well as some car body parts’ (like panels) are still subject to geometrical changes that do not allow a full vibrocoustic CAE analysis. Nevertheless, it has been shown that even in the low frequency range the vehicle response remains proportional to the mechanical injected power into the vehicle. The Power Frequency Response Functions was introduced in order to link the energy response of the vehicle to the injected power. Then, decreasing the injected power -without any consideration to the panels and cavity coupled responses- will ensure a noise reduction. The first part of this paper will introduce the injected power and power frequency response functions computation, using vibroacoustic FE models.

In order to improve the robustness of vibroacoustic numerical predictions, one introduces a model of random uncertainties. The random uncertainty modelling relies on a nonparametric approach providing random system realizations with a maximum entropy. This approach only requires a few uncertainty parameters but takes into account data errors as well as model errors. It appears to be well adapted to study the variability of structural-acoustic systems; the implementation of the method for this class of problem is presented here for the first time. Practically, the paper deals with a classical low frequency vibroacoustic modelling such as used for booming noise predictions. The application of the nonparametric approach to vehicle uncertainties modelling shows the sensitivity of the vibroacoustic frequency responses to structural and cavity uncertainties as well as coupling interface uncertainties. Flexible parts appear to be more sensitive to random uncertainties than stiff parts.

With electromobility, vehicles are becoming quieter due to the presence of electric motors that replace internal combustion engines. The interior cabin noise of electric vehicles is characterized by high-frequency components that can be annoying and unpleasant. Therefore, it is essential to analyse the NVH behaviour of e-powertrains early in the design-phase. However, this induces inherent uncertainties during the design process related to the operating conditions, geometrical parameters, measurement techniques, etc. that need to be quantified with fast and comprehensive stochastic models. In this work, we first present a deterministic framework to provide first-order estimations of the e-powertrain’s interior whining noises, combining both the airborne & structure-borne contribution with data-driven NVH transfers meta-models.

In the recent years, reduction of engine noise as well as aerodynamic noise makes vehicle road noise predominant in numerous operating conditions. Fortunately, experimental and numerical improvements now allow a better understanding of road noise generation and propagation. This paper will focus on two specifics improvements related to this matter. First, excitations are now extracted from the wheel blocking forces. As road noise is a random phenomenon, a component analysis is performed to extract a limited number of uncorrelated excitation patterns (magnitude and phase) at the five fixed Degrees of Freedom at the wheel center. The relevance of such excitations is proved when comparing computed blocking forces at the body-suspension interface to measurements. Implicitly, this comparison also validates the numerical model (Finite Elements) of the suspension.

Vehicle Acoustic Prototyping in the low to mid frequency range commonly relies on the knowledge of the excitation forces generated by the vibration sources like tires and powertrain. It is current practice to measure the excitation as blocked forces either on a component test bench or using an inverse method on the vehicle itself. In both cases, the measurements are performed with (pre)selected bushings. Since the bushing stiffness results of a trade-off with other performances, like handling and durability, it is most likely that the final bushing stiffness will differ in a later or final design from those used during source excitation testing. As a result, estimating the impact of bushing stiffness changes on the vehicle’s acoustic performance becomes a major challenge in the NVH design process. It is the aim of the presented Stiffness Injection method to provide the sensitivity of the bushings stiffness to the responses at the driver’s ears.

The door response to audio excitation contributes to the overall performance of a vehicle audio system on several items: acting as a cabinet, it influences the loudspeaker response, but it also radiates unwanted sound through the inner door panel. Associated design issues are numerous, from the loudspeaker design to door structure and inner panel definition. Modeling then appears as an unavoidable tool to handle the acoustic response of the loudspeaker in its actual surrounding as well as the door inner panel radiation. In the low frequency range (<300 Hz), the loudspeaker is conveniently modelled using the classical Thiele&Small 1 D model. The interaction with the door and the acoustic surroundings requires a more detailed Finite Element modeling considering the acoustic loads on both sides of the loudspeaker membrane and the force at the loudspeaker frame interface with the door structure.

The challenge of a NVH development is to define a link between the target of the OEMs expressed in terms of acoustic performance, weight and cost and the design of the optimized acoustic package reaching this target. The “Vehicle Acoustic Synthesis Method” (VASM) has been developed in order to create this link. The VASM method, which is an energy based hybrid simulation technique, calculates the Sound Pressure Level at ear location from the combination of sound power measurements and acoustic frequency response functions (FRF) panel/ear, either measured or simulated with Ray-Tracing Methods.

In the high frequency range, the SEA method has been applied to air borne path with success to predict both internal and external sound environment. Nevertheless, structure-borne prediction is still at issue -especially for cars, in the range 200 to 2000 Hz- as results are widely dependant on subsystem partition and validity of various assumptions required by SEA. Experimental SEA test technique (ESEA), applied to car bodies, has brought to the fore that SEA power balanced equations could robustly describe structure-borne noise. To make ESEA predictive, the database of measured FRF is simply replaced and enlarged by synthesized data generated from a finite element (FE) model and a selected observation grid of nodes. This technique, called Virtual SEA (VSEA), has been presented at SAE/NVC 2003.