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The reduction of vehicle exhaust particle emissions is a success story of European legislation. Various particle number (PN) counters and calibration procedures serve as tools to enforce PN emission limits during vehicle type approval (VTA) or periodical technical inspection (PTI) of in-use vehicles. Although all devices and procedures apply to the same PN-metric, they were developed for different purposes, by different stakeholder groups and for different target costs and technical scopes. Furthermore, their calibration procedures were independently defined by different stakeholder communities. This frequently leads to comparability and interpretation issues. Systematic differences of stationary and mobile PN counters (PN-PEMS) are well-documented. New, low-cost PTI PN counters will aggravate this problem. Today, tools to directly compare different instruments are scarce.

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.

The reliability of electronic components is of increasing importance for further progress towards automated driving. Thermal aging processes such as electromigration is one factor that can negatively affect the reliability of electronics. The resulting failures depend on the thermal load of the components within the vehicle lifetime - called temperature collective - which is described by the temperature frequency distribution of the components. At present, endurance testing data are used to examine the temperature collective for electronic components in the late development stage. The use of numerical simulation tools within Vehicle Thermal Management (VTM) enables lifetime thermal prediction in the early development stage, but also represents challenges for the current VTM processes [1, 2]. Due to the changing focus from the underhood to numerous electronic compartments in vehicles, the number of simulation models has steadily increased.

Autonomous driving systems and connected mobility are the next big developments for the car manufacturers and their suppliers during the next decade. To achieve the high computing power needs and fulfill new upcoming requirements due to functional safety and security, heterogeneous processor architectures with a mixture of different core architectures and hardware accelerators are necessary. To tackle this new type of hardware complexity and nevertheless stay within monetary constraints, high performance computers, inspired by state of the art data center hardware, could be adapted in order to fulfill automotive quality requirements. The European Processor Initiative (EPI) research project tries to come along with that challenge for next generation semiconductors. To be as close as possible to series development needs for the next upcoming car generations, we present a hybrid semiconductor system-on-chip architecture for automotive.

In this paper a method for the identification of most significant vehicle parameters influencing the behavior of a lateral control system of autonomous car is presented. Requirements for the design stage of the controller need to consider many uncertainties in the plant. While most vehicle properties can be compensated by an appropriate tuning of the control parameters, other vehicle properties can change significantly during usage. The control system is evaluated based on performance measures. Analyzed parameters comprise functional tire characteristics, mass of the vehicle and position of its center of gravity. Since the parameters are correlated, but Sobol’ sensitivity analysis assumes decorrelated inputs, random variation yields no reasonable results. Furthermore, the variation of each parameter or set of parameters is not applicable since the numbers of required simulations is increased significantly according to input dimension.

The TOP TIERTM Diesel fuel standard was first established in 2017 to promote better fuel quality in marketplace to address the needs of diesel engines. It provides an automotive recommended fuel specification to be used in tandem with regional diesel fuel specifications or regulations. This fuel standard was developed by TOP TIERTM Diesel Original Equipment Manufacturer (OEM) sponsors made up of representatives of diesel auto and engine manufacturers. This performance specification developed after two years of discussions with various stakeholders such as individual OEMs, members of Truck and Engine Manufacturers Association (EMA), fuel additive companies, as well as fuel producers and marketers. This paper reviews the major aspects of the development of the TOP TIERTM Diesel program including implementation and market adoption challenges.

Since 2013 the new Daimler Aeroacoustic Wind Tunnel (AAWT) is in operation at the Mercedes-Benz Technology Center in Sindelfingen, Germany. This construction was the second stage of a wind tunnel center project, which was launched in 2007 and started with the climatic wind tunnels including workshop and office areas. The AAWT features a test facility for full-scale cars and vans with a nozzle exit area of 28 m2, a five-belt system, and underfloor balance to measure forces with best possible road simulation. With a remarkable low background noise level of the wind tunnel, vehicle acoustics can be investigated under excellent conditions using high-performance measurement systems. An overview is given about the building and the design features of the wind tunnel layout. The aerodynamic and aeroacoustic properties are summarized. During the first years of operation, further improvements regarding the wind tunnel background noise and vehicle handling were made.

From an acoustical point of view, the integration of seatbelt retractors in a vehicle is a real challenge that has to be met early in the vehicle development process. The buzz and rattle noise of seat belt retractors is a weak yet disturbing interior noise. Street irregularities excite the wheels and this excitation is transferred via the car body to the mounting location of the retractor. Ultimately, the inertia sensor of the locking mechanism is also excited. This excitation can be amplified by structural resonances and generate a characteristic impact noise. The objective of this paper is to describe a simulation method for an early development phase that predicts the noise-relevant low frequency local modes and consequently the contact of the retractor with the mounting panel of the car body via the finite element method.

Downsizing and direct injection in modern DISI engines can lead to fuel impinging on the cylinder walls. The interaction of liquid fuel and engine oil due to fuel impinging on the cylinder wall causes problems in both lubrication and combustion. To analyze this issue with temporal and spatial resolution, we developed a laser-induced fluorescence (LIF) system for simultaneous kHz-rate imaging of fuel and oil films on the cylinder wall. Engine oil was doped with traces of the laser dye pyrromethene 567, which fluoresces red after excitation by 532 nm laser radiation. Simultaneously, the liquid fuel was visualized by UV fluorescence of an aromatic “tracer” in a non-fluorescent surrogate fuel excited at 266 nm. Two combinations of fuel and tracer were investigated, iso-octane and toluene as well as a multi-component surrogate and anisole. The fluorescence from oil and fuel was spectrally separated and detected by two cameras.

The management of surface water flows driven from the wind screen by the action of wipers and aerodynamic shear is a growing challenge for automotive manufacturers. Pressure to remove traditional vehicle features, such as A-Pillar steps for aesthetic, aeroacoustic and aerodynamic reasons increases the likelihood that surface water may be convected over the A-Pillar and onto the front side glass where it can compromise drivers’ vision. The ability to predict where and under which conditions the A-Pillar will be breached is important for making correct design decisions. The use of numerical simulation in this context is desirable, as experimental testing relies on the use of aerodynamics test properties which will not be fully representative, or late-stage prototypes, making it difficult and costly to correct issues. This paper provides an update on the ability of simulation to predict A-Pillar overflow, comparing physical and numerical results for a test vehicle.

At SAIC-GM-Wuling (SGMW) the greenhouse wind noise performance of their vehicles has gained a lot of attention in the development process. In order to evaluate and improve the noise quality of a newly developed SUV a digital simulation based process has been employed during the early stage of the design. CFD simulation was used for obtaining the flow induced exterior noise sources. Performance metrics for the quality were based on interior noise levels which were calculated from the exterior sources using a SEA approach for the noise transmission through the glass panels and propagation to the driver’s or passenger’s head space. Detailed analysis of the CFD results allowed to identify noise sources and related flow structures. Based on this analysis, design modifications were then applied and tested in a sequential iterative process. As a result an improvement of more than 2 dB in overall sound pressure level could be achieved.

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.

Safety-critical embedded software has to satisfy stringent quality requirements. All contemporary safety standards require evidence that no data races and no critical run-time errors occur, such as invalid pointer accesses, buffer overflows, or arithmetic overflows. Such errors can cause software crashes, invalidate separation mechanisms in mixed-criticality software, and are a frequent cause of errors in concurrent and multi-core applications. The static analyzer Astrée has been extended to soundly and automatically analyze concurrent software. This novel extension employs a scalable abstraction which covers all possible thread interleavings, and reports all potential run-time errors, data races, deadlocks, and lock/unlock problems. When the analyzer does not report any alarm, the program is proven free from those classes of errors. Dedicated support for ARINC 653 and OSEK/AUTOSAR enables a fully automatic OS-aware analysis.

In order to offer a wide range of driving experiences to their customers, original equipment manufacturers implement different driving programs. The driver is capable of manually switching between these programs which alter drivability parameters in the engine control unit. As a result, acceleration forces and gradients are modified, changing the perceived driving experience. Nowadays, drivability is calibrated iteratively through road testing. Hence, the resulting set of parameters incorporated within the engine control unit is strongly dependent on the individual sentiments and decisions of the test engineers. It is shown, that implementing a set of objective criteria offers a way to reduce the influences of personal preferences and sentiments in the drivability calibration process. In combination with the expertise of the test engineers, the desired vehicle behavior can be formalized into a transient set point sequence to give final shape to the acceleration behavior.

The validation of vehicle aerodynamic simulation results to wind tunnel test results and simulation accuracy improvement attract considerable attention of many automotive manufacturers. In order to improve the simulation accuracy, a simulation model of the ground effects simulation system of the aerodynamic wind tunnel of the Shanghai Automotive Wind Tunnel Center was built. The model includes the scoop, the distributed suction, the tangential blowing, the moving belt and the wheel belts. The simulated boundary layer profile and the pressure distribution agree well with test results. The baseline model and multiple design changes of the new Buick Excelle GT are simulated. The simulation results agree very well with test results.

Side window clarity and its effect on side mirror visibility plays a major role in driver comfort. Driving in inclement weather conditions such as rain can be stressful, and having optimal visibility under these conditions is ideal. However, extreme conditions can overwhelm exterior water management devices, resulting in rivulets of water flowing over the a-pillar and onto the vehicle’s side glass. Once on the side glass, these rivulets and the pooling of water they feed, can significantly impair the driver’s ability to see the side mirror and to see outwardly when in situations such as changing lanes. Designing exterior water management features of a vehicle is a challenging exercise, as traditionally, physical testing methods first require a full-scale vehicle for evaluations to be possible. Additionally, common water management devices such as grooves and channels often have undesirable aesthetic, drag, and wind noise implications.

A cooperation of several research partners supported by the German Federal Ministry of Research and Education proposes a new active matrix LED light source. A multi pixel flip chip LED array is directly mounted to an active driver IC. A total of 1024 pixel can be individually addressed through a serial data bus. Several of these units are integrated in a prototype headlamp to enable advanced light distribution patterns in an evaluation vehicle.

A local Gaussian process regression approach is presented, which allows to model nonlinearities of internal combustion engines more accurate than global Gaussian process regression. By building smaller models, the prediction of local system behavior improves significantly. In order to predict a value, the algorithm chooses the nearest training points. The number of chosen training points depends on the intensity of estimated nonlinearity. After determining the training points, a model is built, the prediction performed and the model discarded. The approach is demonstrated with a benchmark system and air charge test bed measurements. The measurements are taken from a turbocharged SI gasoline engine with both variable inlet valve lift and variable inlet and exhaust valve opening angle. The results show how local Gaussian process regression outmatches global Gaussian process regression concerning model quality and nonlinearities in particular.

Air charge calibration of turbocharged SI gasoline engines with both variable inlet valve lift and variable inlet and exhaust valve opening angle has to be very accurate and needs a high number of measurements. In particular, the modeling of the transition area from unthrottled, inlet valve controlled resp. throttled mode to turbocharged mode, suffers from small number of measurements (e.g. when applying Design of Experiments (DoE)). This is due to the strong impact of residual gas respectively scavenging dominating locally in this area. In this article, a virtual residual gas sensor in order to enable black-box-modeling of the air charge is presented. The sensor is a multilayer perceptron artificial neural network. Amongst others, the physically calculated air mass is used as training data for the artificial neural network.

Design and evaluation of construction equipments and vehicles in the construction industry constitute a very important but expensive and time consuming part of the engineering process on account of large number of variants of prototypes and low production volumes associated with each variant. In this article, we investigate an alternative approach to the hardware testing based design process by implementing a Computational Fluid Dynamics (CFD) simulation based methodology that has the potential to reduce the cost and time of the entire design process. The simulation results were compared with test data and good agreement was observed between test data and simulation.