Search Results

This paper describes a novel approach for modeling an automotive HVAC unit. The model consists of black-box models trained with experimental data from a self-developed measurement setup. It is capable of predicting the temperature and mass flow of the air entering the vehicle cabin at the various air vents. A combination of temperature and velocity sensors is the basis of the measurement setup. A measurement fault analysis is conducted to validate the accuracy of the measurement system. As the data collection is done under fluctuating ambient conditions, a review of the impact of various ambient conditions on the HVAC unit is performed. Correction models that account for the different ambient conditions incorporate these results. Numerous types of black-box models are compared to identify the best-suited type for this approach. Moreover, the accuracy of the model is validated using test drive data.

Highly automated driving (HAD) is under rapid development and will be available for customers within the next years. However the evidence that HAD is at least as safe as human driving has still not been produced. The challenge is to drive hundreds of millions of test kilometers without incidents to show that statistically HAD is significantly safer. One approach is to let a HAD function run in parallel with human drivers in customer cars to utilize a fraction of the billions of kilometers driven every year. To guarantee safety, the function under test (FUT) has access to sensors but its output is not executed, which results in an open loop problem. To overcome this shortcoming, the proposed method consists of four steps to close the loop for the FUT. First, sensor data from real driving scenarios is fused in a world model and enhanced by incorporating future time steps into original measurements.

Impact noise, inside a car, due to tire-launched gravel on the road can lead to loss of quality perception. Gravel noise is mainly caused by small-sized particles which are too small to be seen on the road by the driver. The investigation focuses on the identification of the mechanisms of excitation and transfer. The spatial distribution of the particles flying from a tire is determined, as well as the probable impact locations on the vehicle body-panels. Finally the relative noise contributions of the body-panels are estimated by adding the panel-to-ear transfer functions. This form of Transfer-Path-Analysis allows vehicle optimization and target setting on the level of the tires, exterior panel treatment and isolation.

The firewall design of a BMW1 is optimized for interior noise and weight using a Hybrid Interior Noise Synthesis (HINS) approach. This method associates a virtual firewall with a test based body model. A vibro-acoustic model of the firewall panel, including trim elements and full vehicle boundary conditions, is used for predictions in the 40 Hz - 400 Hz range. The short calculation time of this set-up allows multiple design iterations. The firewall noise is reduced by 0.9 dB and its mass by 5.1% through structural changes. Crashworthiness is maintained at its initial level using advanced steel processing. The total interior noise shows improvement in the 90 Hz - 140 Hz range.

This paper describes a practical approach to extract the global static stiffness of a body in white (BIW) from dynamic measurements in free-free conditions. Based on a limited set of measured frequency response functions (FRF), the torsional and bending stiffness values are calculated using an FRF based substructuring approach in combination with inverse force identification. A second approach consists of a modal approach whereby the static car body stiffness is deduced from a full free-free modal identification including residual stiffness estimation at the clamping and load positions. As an extra important result this approach allows for evaluating the modal contribution of the flexible car body modes to the global static stiffness values. The methods have been extensively investigated using finite element modeling data and verified on a series of body in white measurements.

A joint study was conducted between BMW and Goodyear with the objective of analysing the cause and identifying methods to reduce the structure-borne interior noise in a vehicle driving on rough road surfaces. A vibro-acoustic characterization of the car was performed by measuring the car vibro-acoustic transfer functions and by using a transfer path analysis technique to identify the main suspension parts affecting the interior noise at target frequencies. The vibration transmissibility characteristics of the tire were measured and also simulated by Finite Element in [1-200Hz] frequency range. The vibro-acoustic interaction between the tire and car sub-systems was examined. A Finite Element sensitivity analysis was used to define and build new prototype tires. A 3dB(A) interior noise improvement was obtained with these new tires at target frequencies.

The use of numerical models as basis to assemble or modify all kind of new structures is increasing over the last years. This has as benefit that it reduces the number of expensive, physical prototypes. These numerical models however must be verified and validated against measured data. Updating is generally needed to guarantee accurate correspondence with reality. This paper focuses on an exhaust. It describes the different steps of the complete process from the acquisition till the updating. On the measurement side, some typical acquisition measures and an efficient approach to handle (slightly) inconsistent data sets is explained. On the numerical side, it is investigated how to achieve the final updated exhaust with physical relevant characteristics.

One of the scientific fields where, for already more than 20 years, system identification plays a crucial role is this of structural dynamics and vibro-acoustic system optimization. The experimental approach is based on the “Modal Analysis” concept. The present paper reviews the test procedure and system identification principles of this approach. The main focus though is on the real problems with which engineers, performing modal analysis on complex structures on a daily basis, are currently confronted. The added value of several new testing approaches (laser methods, smart transducers…) and identification algorithms (spatial domain, subspace, maximum likelihood,..) for solving these problems is shown. The discussed elements are illustrated with a number of industrial case studies.

Source identification applied to a truck engine and using inverse numerical acoustics is presented. The approach is based on acoustic transfer vectors (ATV) and truncated singular value decomposition (SVD). Acoustic transfer vectors are arrays of transfer functions between surface normal velocity and acoustic pressure at response points. They can be computed using boundary element methods (indirect, direct or multi-domain direct formulations) or finite element methods (in physical or modal coordinates). Regularization techniques such as the so-called L-curve approach are used to identify the optimum SVD truncation. To increase the reliability of the source identification, the approach can use velocity measurements on the boundary surface as well as the standard nearfield pressure measurements. It also allows for linear or spline interpolation of the acoustic transfer vectors in the frequency domain, to increase computational speed.

Over the past decades, interior noise from wind noise or engine noise have been significantly reduced by leveraging improvements of both the overall vehicle design and of sound package. Consequently, noise sources originating from HVAC systems (Heat Ventilation and Air Conditioning), fans or exhaust systems are becoming more relevant for perceived quality and passenger comfort. This study focuses on HVAC systems and discusses a Flow-Induced Noise Detection Contributions (FIND Contributions) numerical method enabling the identification of the flow-induced noise sources inside and around HVAC systems. This methodology is based on the post-processing of unsteady flow results obtained using Lattice Boltzmann based Method (LBM) Computational Fluid Dynamics (CFD) simulations combined with LBM-simulated Acoustic Transfer Functions (ATF) between the position of the sources inside the system and the passenger’s ears.

Tip-in/Tip-out of the accelerator pedal generates transient torque oscillations in the driveline. These oscillations may be amplified by P/T, suspension and body modes and will eventually be sensible at the receiver side in the vehicle, for example at the seat or at the steering-wheel. The forces that are active during this transient excitation are influenced by non-linear effects in both the suspension and the power train mounts. In order to understand the contribution of each of these forces to the total interior target response (e.g. seat rail vibration) a detailed investigation is performed. Traditional force identification methods are not suitable for low-frequent, transient phenomena like tip-in/tip-out. Mount stiffness method can not be used because of non-linear effects in the P/T and suspension mounts. Application of matrix inversion method based on trimmed body vibration transfer functions is not possible due to numerical condition problems.

Road-tire induced vibrations are in many vehicles determining the interior noise levels in (semi-) constant speed driving. The understanding of the noise contributions of different connections of the suspension systems to the vehicle is essential in improvement of the isolation capabilities of the suspension- and body-structure. To identify these noise contributions, both the forces acting at the suspension-to-body connections points and the vibro-acoustic transfers from the connection points to the interior microphones are required. In this paper different approaches to identify the forces are compared for their applicability to road noise analysis. First step for the force identification is the full vehicle operational measurement in which target responses (interior noise) and indicator responses (accelerations or other) are measured.

A key issue in noise emission studies of noise producing machinery concerns the identification and analysis of the noise sources and their interaction and radiation into the far field. This paper presents a new acoustic measurement technique for noise source identification in stationary applications. The core of the technology is a handheld measurement instrument combining a position and orientation tracking device with a 3D sound intensity probe. The technique allows an on-line 3D visualization of the sound field while moving the probe freely around the test object. By focusing on the areas of interest, troublesome areas can be identified that require further in-depth analysis. The measurement technique is flexible, interactive and widely applicable in industrial applications. This paper explains the working principle and characteristics of this new technology and positions it to existing methods like traditional sound intensity testing and array techniques.

Air conditioning acoustics have become of paramount importance in electric vehicles, where noise from electromechanical components is no longer masked by the presence of the internal combustion engine. In a car HVAC systems, the coolant compressor is one of the most important sources in terms of vibration and noise generation. The paper, the generated structural noise is studied in detail on a prototype installation, and the noise transmission and propagation mechanisms are analyzed and discussed. Through ”in situ” measurements and virtual point transformation, the rotor unbalance forces and torque acting within the component are identified. The dynamic properties of the rubber mounts, installed between the compressor and its support, are identified thanks to matrix inversion methods. To assess the quality of the proposed procedure, the synthesized sound pressure level is compared with experimental SPL measurements in different operational conditions.

It is particularly easy to get tunnel vision as a domain expert, and focus only on the improvements one could provide in their area of expertise. To make matters worse, many Original Equipment Manufacturers (OEMs) are silo-ed by domain of expertise, unconsciously promoting this single mindedness in design. Unfortunately, the successful and profitable development of a vehicle is dependent on the delicate balance of performance across many domains, involving multiple physics and departments. Taking for instance the design of a Heating, Ventilation & Air Conditioning (HVAC) system, the device’s primary function is to control the climate system in vehicle cabins, and more importantly to make sure that critical areas on the windshield can be defrosted in cold weather conditions within regulation time. With the advent of electric and autonomous vehicles, further importance is now also placed on the energy efficiency of the HVAC, and its noise.

Two models for the forecast of road traffic emissions, independently developed in parallel, are comparatively presented and assessed: EPROG developed by BMW and enlarged by VDA for a national application (Germany) and FOREMOVE, developed for application on European Community scale. The analysis of the methodological character of the two algorithms proves that the models are fundamentally similar with regard to the basic calculation schemes used for the emissions. The same holds true as far as the significant dependencies of the emission factors, and the recognition and incorporation of the fundamental framework referring to traffic important parameters (speeds, mileage and mileage distribution etc) are concerned.

The low frequency interior noise in cars is for a large part the result of structure borne excitation. The transfer of the structure borne sound involves a large number of components of the engine suspension, wheel suspension and chassis which are all potentially contributing to the overall noise level. This process can be analyzed through a combination of transfer function measurements with operational measurements under normal conditions. This technique, called transfer path analysis, requires large numbers of transfer function measurements with excitation of the body or cabin at the rubber mountings. Unfortunately, bad access to these crucial measurement locations causes either high instrumentation and measurement effort or less accurate measurement data. The practicality and quality of the measurements can be improved by using reciprocal measurements for the mechano-acoustic transfer of the body or cabin structure; a loudspeaker in the cavity is used for the reciprocal excitation.

This paper presents two applications of the RADSER model updating technique (ref. 1). The RADSER technique updates finite element model parameters by solution of a linearised set of equations that optimise the Reduced Analytical Dynamic Stiffness matrix based on Experimental Receptances. The first application deals with the identification of the dynamice characteristics of rubber mounts. The second application validates a coarse finite element model of a subframe of a Volvo 480.

This paper presents the measurement & analysis procedures and the results of a complete road noise identification and reduction project on a midsize passenger car. Operational interior noise signals and structural accelerations are measured for several test conditions. The operating data are decomposed into sets of mathematically independent phenomena by Principal Component Analysis. Operating Deflection Shape Analysis and Transfer Path Analysis are applied to each of these independent phenomena. Critical transfer paths are thus identified and quantified. The interior sound level is amplified when the frequency content of the transmitted energy coincides with structural resonances or standing waves of the interior car cavity. The vehicle is dynamically characterized by Experimental Structural Modal Analysis and by Acoustic Modal Analysis.

Low frequency noise from engine- and wheel-vibrations often dominates the interior noise spectrum in vehicles. For the optimization of vehicle bodies it is necessary to know the contribution of individual body panels to sound pressures at the passengers ear. An experimental approach is presented which makes use of reciprocal acoustic transfer function measurements and surface acceleration measurements in normal road operation. This method, called Airborne Source Quantification, has been applied as a diagnostic tool to the interior noise of a four cylinder diesel engined van.