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During the last ten years, there is a significant tendency in automotive design to use lower aspect ratio tires and meanwhile also more and more run-flat tires. In appropriate publications, the influences of these tire types on the dynamic loads - transferred from the road passing wheel center into the car - have been investigated pretty well, including comparative wheel force transducer measurements as well as simulation results. It could be shown that the fatigue input into the vehicle tends to increase when using low aspect ratio tires and particularly when using run-flat tires. But which influences do we get for the loading and fatigue behavior of the respective rims? While the influences on the vehicle are relatively easy to detect by using wheel force transducers, the local forces acting on the rim flange (when for example passing a high obstacle) are much more difficult to detect (in measurement as well as in simulation).

Active suspension systems aim at increasing safety by improving vehicle ride and handling performance while ensuring superior passenger comfort. Good control of this active system can only be achieved by providing the control algorithm with reliable and accurate signals for the required quantities. This paper presents the design and development of a state estimator that accurately provides the information required by a sky-hook controller, using a minimum of sensors. The vehicle inertial parameters are estimated by an algorithm based on Monte Carlo simulations and anthropometric data. All state updating is performed using Kalman filters. The resulting performance enhancement has been proven during test drives.

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.

Friction-induced vibration is a serious problem in many industrial applications containing systems with rotating and/or sliding parts. Brake noise is a typical example. The critical element in the noise generation process is the combination of friction-induced loads with the dynamics of the braking system. In the present paper, a detailed experimental and numerical study of a specific low-frequency brake squeal problem is made on a simplified brake noise test rig. First, the signal and spatial characteristics of the noise were analyzed by spectral and acoustic holography techniques. A parametric study of influence factors as brake pressure, rotation speed, etc. was made. Operational deformation analysis during squeal confirms the dominant modal behavior of the components, implying the critical role of the assembly structural dynamics.

The need of weight reduction for fuel reduction and CO₂ regulations enforces the use of light-weight materials for structural parts also. The importance of reinforced composites will grow in this area. While the structural behavior and the simulation up to high strain-rate processes for those materials have been in the focus of investigation for many years, nowadays the simulation of high cycle fatigue behavior is getting important as well. Efficient fatigue analysis for metals was developed by understanding the microscopic behavior (crack nucleation and initiation) and bringing it to the macroscopic level by combining it with the matching test data (SN curves, etc.). Similar approaches can be applied to composite materials as well.

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.

Traditionally, vibration analysis in operating conditions (on the road or on a bench) had to be combined with experimental modal analysis in controlled laboratory conditions in order to understand the modal behaviour of the structure. This requires additional measurements, costs and time. However, in many applications, the real operating conditions may differ significantly from those applied during the modal test and hence the vibration modes from the modal test might not be representative for the active modes in operation conditions. The need for a capability of doing a modal analysis on data from operating conditions is obvious. Over the last years, several modal parameter estimation techniques have been proposed and studied for modal parameter extraction from output-only data. Each method needs to make a number of assumptions and has some limitations.

Traditionally, vibration analysis in operating conditions (on the road or on a bench) had to be combined with experimental modal analysis in controlled laboratory conditions in order to understand the modal behaviour of the structure. This requires additional measurements, costs and time. However, in many applications, the real operating conditions may differ significantly from those applied during the modal test and hence the vibration modes from the modal test might not be representative for the active modes in operation conditions. The need for a capability of doing a modal analysis on data from operating conditions is obvious. Over the last years, several modal parameter estimation techniques have been proposed and studied for modal parameter extraction from output-only data. Each method needs to make a number of assumptions and has some limitations.

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.

This paper presents a new time-domain source contribution analysis method for in-room pass-by noise. The core of the method is a frequency-domain ASQ model (Airborne Source Quantification) representing each noise generating component (engine, exhaust, left and right tyres, etc.) by a number of acoustic sources. The ASQ model requires the measurement of local FRF's and acoustic noise transfer functions to identify the operational loads from nearby pressure indicator responses and propagate the loads to the various target microphones on the sides of the vehicle. Once a good ASQ model is obtained, FIR filters are constructed, allowing a time-domain synthesis of the various source contributions to each target microphone. The synthesized target response signals are finally recombined into a pass-by sound by taking into account the speed profile of the vehicle.

While CAE methods allow improving nominal product design using virtual prototypes, uncertainty and variability in properties and manufacturing processes lead to scatter in actual performances. Uncertainty must hence be incorporated in the CAE process to guarantee the robustness and reliability of the design. This paper presents an overview of uncertainty-based design in automotive and aerospace engineering. Fuzzy methods take uncertainty into account, whereas reliability analysis and a reliability-based design optimization framework can deal with variability. Key enabling technologies to alleviate the computational burden, such as workflow automation, substructuring and design of experiments, are discussed, and industrial applications are presented.

Wing Anti-Icing Systems (WAIS) are integral part of a wing design. Their presence ensures safety in all-weather conditions. In standard designs, the WAIS are fitted in the slat internal structure and runs throughout its span in between the ribs. Given its critical function, such a system has to pass qualification test. The test specification is dictated by international standards. In the case discussed in this article, the standard adopted is the RTCA DO-160G “Environmental Conditions and Test Procedures for Airborne Equipment”. In particular, the work presented here concerns with the Vibration environmental test. The standard prescribes a number of dynamic tests to be carried out on the AIS: random, shock and sine excitation tests have to be performed in order to study their effect on the parts composing the Anti-Icing System. The standard prescribes vibration levels at the attachment locations of the AIS to the wings' ribs.