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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.

The adoption of the electronic controlled steering systems with new technologies has been extended in recent years. They have interactions with other complex vehicle subsystems and it is a hard task for the vehicle developer to find the best solution from huge number of the combination of parameter settings with track tests. In order to improve the efficiency of the steering system development, the authors had developed a steering bench test method for steering system using a Hardware-In-the-Loop Simulation (HILS). In the steering HILS system, vehicle dynamics simulation and the tie rod axial force calculation are required at the same time in the real-time simulation environment. The accuracy of the tie rod axial force calculation is one of the key factors to reproduce the vehicle driving condition. But the calculation cannot be realized by a commercial software for the vehicle dynamics simulation.

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.

Technologies for improving the fuel economy of gasoline engines have been vigorously developed in recent years for the purpose of reducing CO2 emissions. Increasing the compression ratio for improving thermal efficiency and downsizing the engine based on fuel-efficient operating conditions are good examples of technologies for enhancing gasoline engine fuel economy. A direct-injection system is adopted for most of these engines. Direct injection can prevent knocking by lowering the in-cylinder temperature through fuel evaporation in the cylinder. Therefore, direct injection is highly compatible with downsized engines that frequently operate under severe supercharging conditions for improving fuel economy as well as with high compression ratio engines for which susceptibility to knocking is a disadvantage.

Technologies for improving the fuel economy of gasoline engines have been vigorously developed in recent years for the purpose of reducing CO2 emissions. Increasing the compression ratio is an example of a technology for improving the thermal efficiency of gasoline engines. A significant issue of a high compression ratio engine for improving fuel economy and low-end torque is prevention of knocking under a low engine speed. Knocking is caused by autoignition of the air-fuel mixture in the cylinder and seems to be largely affected by heat transfer from the intake port and combustion chamber walls. In this study, the influence of heat transfer from the walls of each part was analyzed by the following three approaches using computational fluid dynamics (CFD) and experiments conducted with a multi-cooling engine system. First, the temperature rise of the air-fuel mixture by heat transfer from each part was analyzed.

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.

This study examined methods of machining a microsurface texture on the surface of the rolling elements of a toroidal continuously variable transmission (CVT) for improving the traction coefficient. The microsurface texture of the toroidal surfaces consists of tiny circumferential grooves (referred to here as micro grooves) and a mirror-like surface finish similar to the rolling surface of bearings. Hard turning with a cubic boron nitride (cBN) cutting tool, grinding with a cBN wheel and micro forming were applied to machine the micro grooves. The results made clear the practical potential of each method. A micro forming device was also developed for use in actual production. A mirror-like surface finish and micro crowning of the convex portions of the microsurface texture were simultaneously executed by superfinishing them with a fine-grained elastic superfinishing stone.

This paper describes the methods adopted to improve the image quality of the all-around view system. This system uses multiple vehicle-mounted cameras to capture images of the circumstances around the vehicle. The images undergo viewpoint transformation and are synthesized to create a single image seen from a virtual perspective overhead. The specific methods discussed here concern optimization of the design parameters for the camera orientation and a camera calibration method that does not involve physical movement of the cameras.

In the last decades the development time of vehicles has been drastically reduced due to the application of advanced numerical and experimental methods. Specifications concerning durability and other functional attributes for every new model improve for every vehicle. In particular, for machines and components under variable multiaxial loading, fatigue evaluation is one of the most important steps in the design process. Appropriate material testing and simulation is the key to efficient life prediction. However, the life of automotive components, power plants and other high-temperature facilities depends mostly on thermo-mechanical fatigue (TMF). This is due to the normally variable service conditions, which contain the phases of startup, full load, partial load and shut-down.

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 proposes a method of estimating road friction and tire slip angle in a cornering maneuver. The method can estimate front tire road friction accurately at low lateral acceleration because it is based on the tire self-aligning torque (SAT) that exhibits high sensitivity to road friction at low slip angles. Road friction and tire slip angle, which are mutually interdependent, are estimated simultaneously using an extended Kalman filter designed around a model describing the relationship between road friction and SAT and a vehicle lateral dynamic model. The front tire SAT is calculated with a mathematical model that describes the torque transmission characteristics from the electric power steering torque to SAT. Therefore, the proposed method is readily applicable to production vehicles. Results of an experimental study show that the change in road friction is instantaneously estimated at low lateral acceleration.

For diesel engine, lower compression ratio has been demanded to improve fuel consumption, exhaust emission and maximum power recently. However, low compression ratio engine might have combustion instability issues under cold temperature condition, especially just after engine started. As a first step of this study, cold temperature combustion was investigated by in-cylinder pressure analysis and it found out that higher heat release around top dead center, which was mainly contributed by pilot injection, was the key factor to improve engine speed fluctuation. For further understanding of combustion in cold condition, particularly mixture formation near a glow plug, 3D CFD simulation was applied. Specifically for this purpose, TI (Time-scale Interaction) combustion model has been developed for simulating combustion phenomena. This model was based on a reasonable combustion mode, taking into account the characteristic time scale of chemical reactions and turbulence eddy break-up.

A robotic driver has been designed on the basis of an analysis of a human driver's action in following a given driving schedule. The self-learning algorithm enables the robot to learn the vehicle characteristics without human intervention. Based on learned relationships, the robotic driver can determine an appropriate accelerator position and execute other operations through sophisticated calculations using the future scheduled vehicle speed and vehicle characteristics data. Compensation is also provided to minimize vehicle speed error. The robotic driver can reproduce the same types of exhaust emission and fuel economy data obtained with human drivers with good repeatability. It doesn't require long preparation time. Thereby making it possible to reduce experimentation work in the vehicle development process while providing good accuracy and reliability.

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.

Traction control systems (TCSs) serve to control brake pressure and engine torque, thereby reducing driving wheel spin for improved stability and handling. Systems are divided into two basic types by the brake control configuration. One type is a one-channel left-right common control system and the other is a two-channel individual control system. This paper presents an analysis of these two types of TCS configurations in terms of handling, acceleration, stability, yaw convergence and other performance parameters. The systems are compared with and without a limited-slip differential (LSD) under various road conditions, based on experimental data and computer simulations. As a result of this work, certain Nissan models are now equipped with a new Nissan Traction Control System with a rear viscous LSD (Nissan V-TCS), which provides both the advantages of a rear viscous LSD in a small slip region and a two-channel TCS in a large slip region.

The use of CAE software in developing plastic components has advanced rapidly in recent years. This progress has been supported by the development of practical analytical tools, based on the finite element and boundary element methods, and on the dramatic improvements seen in computer performance. Following the introduction of a flow analysis program in 1982, Nissan has developed and implemented advanced programs for use in developing plastic components and has integrated the programs into a unified in-house system. This system is being utilized at the design and manufacturing stages of interior and exterior trim parts and has produced concrete results in different phases of component development. Work is now proceeding on the development of a system that can simultaneously analyze both the component performance and the factors that need to be considered in the manufacturing process.