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Inverse numerical acoustics is a method which reconstructs the source surface normal velocity from the sound measured in the near-field around the source. This is of particular interest when the source is rotating or moving, too light or too hot to be instrumented by accelerometers. The use of laser vibrometers is often of no remedy due to the complex shape of the source. The Inverse Numerical Acoustics technique is based on the inversion of transfer relations (Acoustic Transfer Vectors) using truncated Singular Value Decomposition (SVD). Most of the time the system is underdetermined which results in a non unique solution. The solution obtained by the truncated SVD is the minimal solution in the RMS sense. This paper is investigating the impact of non homogeneities in the mesh density (local mesh refinement) on the retrieved solution for underdetermined systems. It will be shown that if transfer quantities are inverted as such, big elements get a higher weight in the inversion.

For a numerical model of vibro-acoustic coupling analysis, such as a vehicle noise and vibration, both structural and acoustical dynamic characteristics are necessary to replicate the physical phenomenon. The accuracy of the analysis is not enough for substituting a prototype phase with a digital phase in the product development phases. One of the reasons is the difficulty of addressing the interior acoustical characteristics due to the complexity of the acoustical transfer paths, which are a duct and a small hole of trim parts in a vehicle. Those complex features affect on the nodal locations and the body coupling surface of acoustic mode shapes. In order to improve the accuracy of the analysis, the physical mechanisms of those features need to be extracted from experimental testing.

It is essential to include uncertainties in the simulation process in order to perform reliable vibroacoustic predictions in the early design phase. In this contribution, uncertainties are quantified using the generalized Polynomial Chaos (gPC) expansion in combination with a Finite Element (FE) model of a vehicle body in white. It is the objective to particularly investigate the applicability of the gPC method in the industrial context with a high number of uncertain parameters and computationally expensive models. A non-intrusive gPC expansion of first and second order is implemented and the approximation of a stochastic response process is compared to a Latin Hypercube sampling based reference solution with special regard to accuracy and computational efficiency. Furthermore, the method is examined for other input distributions and transferred to another FE model in order to verify the applicability of the gPC method in practical applications.

During the last decades, big steps have been taken towards a realistic simulation of NVH (Noise Vibration Harshness) behavior of vehicles using the Finite Element (FE) method. The quality of these computation models has been substantially increased and the accessible frequency range has been widened. Nevertheless, to perform a reliable prediction of the vehicle vibroacoustic behavior, the consideration of uncertainties is crucial. With this approach there are many challenges on the way to valid and useful simulation models and they can be divided into three areas: the input uncertainties, the propagation of uncertainties through the FE model and finally the statistical output quantities. Each of them must be investigated to choose sufficient methods for a valid and fast prediction of vehicle body vibroacoustics. It can be shown by rough estimation that dimensionality of the corresponding random space for different types of uncertainty is tremendously high.

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.

The adoption of electric vehicles (EVs) has been announced worldwide with the aim of reducing CO2 emissions. However, a significant increase in electricity demand by EVs might impact the stable operation of the existing power grid. Meanwhile, EV charging is acceptable to most users if it is completed by the time of the next driving event. From the viewpoint of power grid operators, flexibility for shifting the timing of EV charging would be advantageous, including making effective use of renewable energy. In this work, an EV model and simulation tool were developed to make clear how the total charging demand of all EVs in use will be influenced by future EV specifications (e.g., charge power) and installation of charging infrastructure. Among the most influential factors, EV charging behavior according to use cases and regional characteristics were statistically analyzed based on the real-world usage data of over 14, 000 EVs and incorporated in the simulation tool.

The thermal fatigue resistance of engine exhaust system parts has conventionally been evaluated in thermal fatigue tests conducted with a restrained specimen. However, the test results have not always been consistent with data obtained in engine endurance tests. Two new evaluation methods have been developed to overcome this problem. One is a method of predicting thermal fatigue life on the basis of nonlinear elastic and plastic thermal analyses performed with a finite element model and the ABAQUS program. The other is a method of evaluating exhaust system parts using an exhaust system simulator. This paper describes the concepts underlying the two methods and their relative advantages.

Since interior noise has a strong effect on vehicle salability, it is particularly important to be able to estimate noise levels accurately by means of simulation at the design stage. The use of sensitivity analysis makes it easy to determine how the analytical model should be modified or the structure optimized for the purpose of reducting vibration and noise of the structural-acoustic systems. The present work focused on a structural-acoustic coupling problem. As the coefficient matrices of a coupled structural-acoustic system are not symmetrical, the conventional orthogonality conditions obtained in structural dynamics generally do not hold true for the coupled system. To overcome this problem, the orthogonality and normalization conditions of a coupled system were derived by us. In this paper, our sensitivity analysis methods are applied to an interior noise problem of a cabin model.

This study focused on European NCAP activities of introducing a new head protection evaluation procedure, as proposed by BASt (Federal Highway Research Institute - GERMANY). Various kinds of E-bikes are available in the market, ranging from E-bikes that have a small motor to assist the rider’s pedal-power i.e., pedelecs to somewhat more powerful E-bikes which is similar to a moped-style scooter. This paper focused on identifying the factors influencing bicyclist head kinematics during bicycle vs. passenger vehicle (PV) collisions at the intersection. Two AM50 bicyclist FE models are developed using i) GHBMC Human Body Model (HBM) and ii) WorldSID (WS) side impact dummy. Head kinematics of bicyclists of pedal-assist E-bike and normal bike were compared using CAE simulation. It is found that the vehicle’s impact velocity, type of bicycle, the mass of E-bike and bicycle traveling speed will influence the head kinematics.

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 four methodologies for modeling gear mesh excitations in simple and compound planetary gear sets. The gear mesh excitations use simplified representations of the gear mesh contact phenomenon so that they can be implemented in a numerically efficient manner. This allows the gear mesh excitations to be included in transmission system-level, multibody dynamic models for the assessment of operating noise and vibration levels. After presenting the four approaches, a description is made regarding how they have been implemented in software. Finally, example models are used to do a comparison between the methods

The work presented in this paper outlines the design and development of a compliant sprocket for balancer drives in an effort to reduce the noise levels related to chain-sprocket meshing. An experimental observation of a severe chain noise around a resonant engine speed with the Dual-Mass Flywheel (DMF) and standard build solid (fixed) balancer drive sprocket. Torsional oscillation at the crankshaft nose at full load is induced by uneven running of crankshaft with a dual-mass flywheel system. This results in an increase of the undesirable impact noise caused by the meshing between the chain-links and the engagement/disengagement regions of sprockets, and the clatter noise from the interaction between the vibrating chain and the guides. This paper evaluates and discusses the benefits that the compliant sprocket design provided. A multi-body dynamics system (MBS) model of the balancer chain drive has been developed, validated, and used to investigate the chain noise.

Achieving a multi-cylinder engine with excellent noise/vibration character sties and low friction at the main bearings requires an optimal design not only for the crankshaft construction but also for the bearing support system of the cylinder block. To accomplish that, it is necessary to understand crankshaft system behavior and the bearing load distribution for each of the main bearings. Crankshaft system behavior has traditionally been evaluated experimentally because of the difficulty in performing calculations to predict resonance behavior over the entire engine speed range. A coupled crankshaft-block analysis method has been developed to calculate crankshaft system behavior by treating vibration and lubrication in a systematic manner. This method has the feature that the coupled behavior of the crankshaft and the cylinder block is analyzed by means of main bearing lubrication calculations. This paper presents the results obtained with this method.

Many studies have been reported concerning fundamental tribological research aimed at reducing the severe valve train wear that occurs in internal combustion engines. In this paper, cam follower wear was theoretically and experimentally analyzed at the material development stage. Statistical methods have been applied to practical use in determining the material properties quantitatively. Based on the results, a method for predicting cam follower wear has been derived which has made it possible to develop new valve train systems more efficiently. Further, a guideline for developing new wear resistant materials was also clarified. Finally, the precision high chrominum cast iron rocker arm is described, along with its application to a new NISSAN high-performance 4-cylinder DOHC engine, as an example of the use of this method to develop new wear-resistant materials.

Engines that not only produce less noise but also provide good sound quality have been in increasing demand recently. Discomforting noise can sometimes be heard, however, during acceleration as the engine reaches higher levels of power and speed. This paper presents the results of a study into the bending vibration of the crankshaft-flywheel system, which clarify the mechanism producing discomforting noise during acceleration. Based on that study, a flexible flywheel has been developed which effectively reduces crankshaft bending vibration that is closely related to the frequency range of the discomforting noise. As a result, acceleration sound quality is greatly improved.

With SUVs and minivans accounting for a larger share of the US market in the past decade, rollover accidents have drawn greater attention, leading to more active research from different perspectives. This ranges from investigations for elucidating the basic causes and mechanisms of rollover accidents to studies of more advanced occupant protection measures. As the phenomenon of a rollover accident is longer in duration than frontal, side or rear impacts, it is relatively difficult [1] to simulate such accidents for experimental verification and also for proper evaluation of occupant restraint system performance. In this work, we focused on the trip-over type, which occurs most frequently, and performed simulations to reproduce real-world rollover accidents by combining PC-Crash and FEA.

Recently, it has been very important to reduce the noise, especially the Squeak and Rattle noise, for improving customer appeal of passenger vehicles. The Squeak and Rattle noise occurring inside the car cabin during vehicle operation is an especially large problem. This paper describes a newly developed measurement technology that uses the developed signal processing using the Beam-forming method and vibration sensor to identify the Squeak and Rattle noise sources, making it possible to determine effective countermeasures quickly. This new technology is used to identify all Squeak and Rattle noises at a time among many different noises, for example Wind noise, Engine noise and Road noise occurring during vehicle operation, and is expected to shorten substantially the time needed for noise analysis and contribute to quality improvements.

The probability or risk of traffic accidents must be estimated quantitatively in order to implement effective traffic safety measures. In this study, various statistical data and probability theory were used to examine a method for predicting the risk of crossing-collisions, representing a typical type of accident at intersections in Japan. Crossing-collisions are caused by a variety of factors, including the road geometry and traffic environment at intersections and the awareness and intentions of the drivers of the striking and struck vehicles. Bayes' theorem was applied to find the accident probability of each factor separately. Specifically, the probability of various factors being present at the time of a crossing-collision was estimated on the basis of traffic accident data and observation survey data.

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.