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Wet-running multi-plate clutches and brakes are important components of modern powershift gearboxes and industrial powertrains. In the open stage, drag losses occur due to fluid shear. The identification of drag losses is possible by experiment or CFD-simulation. For the calculation of the complex fluid flow of an open clutch, CFD-approaches such as the volume of fluid (vof) method or the Singhal cavitation model are applicable. Every method has its own specific characteristics. This contribution sets up CFD-calculation models for different clutches with diverse groove designs. We present results of calculations in various operating conditions obtained from the Singhal cavitation model and the vof method. The usage of modern commercial CFD-Tools (Simerics MP+) results in short calculation times.

A reliable environment perception is a requirement for safe automated driving. For evaluating and demonstrating the reliability of the vehicle’s environment perception, field tests offer testing conditions that come closest to the vehicle’s driving environment. However, establishing a reference ground truth in field tests is time-consuming. This motivates the development of a procedure for learning the vehicle’s perception reliability from fleet data without the need for a ground truth, which would allow learning the perception reliability from fleet data. In Berk et al. (2019), a method based on Bayesian inference to determine the perception reliability of individual sensors without the need for a ground truth was proposed. The model utilizes the redundancy of sensors to learn the sensor’s perception reliability. The method was tested with simulated data.

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.

Electrified vehicles are particularly quiet, especially at low speeds due to the absence of combustion noises. This is why there are laws worldwide for artificial driving sounds to warn pedestrians. These sounds are generated using a so-called Acoustic Vehicle Alerting System (AVAS) which must maintain certain minimum sound pressure levels in specific frequency ranges at low speeds. The creation of the sound currently involves an iterative and sometimes time-consuming process that combines composing the sound on a computer with measuring the levels with a car on an outside noise test track. This continues until both the legal requirements and the subjective demands of vehicle manufacturers are met. To optimize this process and reduce the measurement effort on the outside noise test track, the goal is to replace the measurement with a simulation for a significant portion of the development.

Bicycle-drawn cargo trailers with an electric drive to enable the transportation of high cargo loads are used as part of the last-mile logistics. Depending on the load, the total mass of a trailer can vary between approx. 50 and 250 kg, potentially more than the mass of the towing bicycle. This can result in major changes in acceleration and braking behavior of the overall system. While existing systems are designed primarily to provide sufficient power, improvements are needed in the powertrain control system in terms of driver safety and comfort. Hence, we propose a novel prototype that allows measurement of the tensile force in the drawbar which can subsequently be used to design a superior control system. In this context, a sinusoidal force input from the cyclist to the trailer according to the cadence of the cyclist is observed. The novelty of this research is to analyze whether torque impulses of the cyclist can be reduced with the help of Model Predictive Control (MPC).

With the ever increasing amount of available software processing resources in a vehicle, more and more high-level algorithms are emerging to improve the existing systems in a car. Often these algorithms only need a platform with a bus connection and some resources such as processing power and memory space. These functions are predestined to be integrated into existing systems that have free resources. This paper will examine the role of time protection in these multi-algorithm systems and describe what timing protection means and why it is required. The processing time will be partitioned to the different processing levels like interrupts, services and tasks. The problems of timing protection will be illustrated as well as its limitations. The conflict between real-time requirements and timing protection will be shown. Finally Autosar will be examined with focus on timing protection and applicability in actual development projects.

The increasing complexity of automotive functions which are necessary for improved driving assistance systems and automated driving require a change of common vehicle architectures. This includes new concepts for E/E architectures such as a domain-oriented vehicle network based on powerful Domain Control Units (DCUs). These highly integrated controllers consolidate several applications on different safety levels on the same ECU. Hence, the functions depend on a strictly separated and isolated implementation to guarantee a correct behavior. This requires middleware layers which guarantee task isolation and Quality of Service (QoS) communication have to provide several new features, depending on the domain the corresponding control unit is used for. In a first step we identify requirements for a middleware in automotive DCUs. Our goal is to reuse legacy AUTOSAR based code in a multicore domain controller.

The large wind tunnel at the Technische Universität München was upgraded by integrating a modular single-belt system, which enables the simulation of moving ground conditions for ground vehicle testing. Central part of this system is its large belt that moves at a maximum speed of 50 m/s. This belt not only simulates the relative motion between the model vehicle under investigation and the floor, but also drives the model's wheels. Due to its size, the wind tunnel facility is suited for testing 40%-scaled models of typical passenger cars, which are held in place by a newly designed model support system consisting of five struts: One strut to support the body of the model and four struts to hold the model's wheels on top of the moving belt. Another crucial step in upgrading the wind tunnel was to install a boundary layer scoop system to reduce the thickness of the boundary layer approaching the moving belt.

Audi's new full scale aeroacoustic wind tunnel is under full operation now. The new facility is designed for full scale automotive testing of aerodynamics and aeroacoustics for vehicles up to 3 m2 frontal area at wind speeds up to 300 kph. The highlights are the unique ground simulation system with boundary layer suction and a 5-belt-system, and the extremely low background noise of only 60 dB(A) at 160 kph. First the background of the project is illustrated and the need for the special features of the tunnel is deduced form the industrial requirements. Then an overview of the facility design is given with a detailed description of the key technical components. The calibration of the self-correcting test section will be discussed and the physical background for it will be examined more closely. For the calibrated wind tunnel the results of two correlation tests including open jet as well as closed wall wind tunnels show a reasonable conformity.

Uncertainties play a major role in vibroacoustics - especially in car body design in the preliminary development because of the overall spread in the production that should be covered with one simulation model. Therefore, we use uncertain input parameters to determine the stochastically distributed admittance of the car body before each part of the car is fully designed. To gain a stochastic result - the stochastically distributed admittance curve - we calculate a deterministic finite element simulation several times with sets of stochastically distributed input parameter values. To reduce simulation time and cost of the car model with many million degrees of freedom we focus on the uncertain parameters that show a significant influence on the admittance curve. It is therefore necessary to be able to accurately estimate for each parameter if its influence on the admittance of the car body plays a major role for the noise vibration harshness simulation.

Optimization of ride comfort is becoming increasingly important in chassis development. Constantly rising traffic density and comfort-orientated customer preferences are mainly responsible for this. Comfort and its improvement are important, not only on bad road surfaces, but also on even surfaces. The complexity of analysis leads to a strong link between car testing and simulation. The testing itself is divided in to roadtests and test stands. It is of outstanding importance to analyze the vehicles vibrational behavior from road tests as it is a real life situation. In order to get meaningful results from the roadtest the vehicle has to be seen as a complete vibrational system. The vibrational behavior of a system is clearly defined by input and output of the system. Road tests are chosen in relation to the predicted car. The roads surface is the input of the system exciting the vibrational subsystems of a car. The ride tests are used for the evaluation of drive response behavior.

Deep neural network models have been widely used for environment perception of intelligent vehicles. However, due to models’ innate probabilistic property, the lack of transparency, and sensitivity to data, perception results have inevitable uncertainties. To compensate for the weakness of probabilistic models, many pieces of research have been proposed to analyze and quantify such uncertainties. For safety-critical intelligent vehicles, the uncertainty analysis of data and models for environment perception is especially important. Uncertainty estimation can be a way to quantify the risk of environment perception. In this regard, it is essential to deliver a comprehensive survey. This work presents a comprehensive overview of uncertainty estimation in deep neural networks for environment perception of intelligent vehicles.

To minimize the impact of global warming worldwide, net greenhouse-gas (GHG) emissions have to be reduced. The transportation sector is one main contributor to overall greenhouse gas emissions due to the fact that most of the current propulsion systems rely on fossil fuels. The gasoline engine powertrain is the most used system for passenger vehicles in the EU and worldwide. Besides emitting GHG, gasoline driven cars emit harmful pollutants, which can cause health issues for humans. Hybrid powertrains provide an available short-term solution to reduce fuel consumption and thus overall emissions. Therefore, an overview of the currently available technology and methodology of hybrid cars is provided in this paper as well as an overview of the performance of current HEV cars in real world testing. From the testing, it can be concluded that despite reducing harmful emissions, hybrid vehicles still emit pollutants and GHG when fueled with conventional gasoline.

The reference pressures are determined in automotive wind tunnels by measurement of pressures and pressure differences at upstream positions along the wind tunnel nozzle. For closed wall wind tunnels usually the so called nozzle method is used, where the volume flux is calculated from a pressure difference measured at the nozzle contour and a calibration factor determined in the empty test section. For open jet wind tunnels a choice is available between nozzle and plenum method. For the plenum method the reference static pressure is taken from the plenum chamber and the dynamic pressure also refers to the plenum conditions. The static reference pressure in closed wall tunnels is calculated by subtracting the dynamic pressure from the total pressure in the settling chamber. In this paper, the definitions and the differences between the two methods are discussed in detail.

The introduction of autonomous vehicles has gained significant attention due to its potential to revolutionize mobility and safety. A critical aspect underpinning the functionality of these autonomous vehicles is their sensor perception system. Demonstrating the reliability of the environment perception sensors and sensor fusion algorithms is, therefore, a necessary step in the development of automated vehicles. Field tests offer testing conditions that come closest to the environment of an automated vehicle in the future. However, a significant challenge in field tests is to obtain a reference truth of the surrounding environment. Here, we propose a pipeline to assess the sensor reliabilities without the need for a reference truth. The pipeline uses a model to estimate the reliability of redundant sensors. To do this, it relies on a binary representation of the surrounding area, which indicates either the presence or absence of an object.

Measurement techniques for piston ring rotation, engine oil emission and blow by have been implemented on a single-cylinder petrol engine. A novel method of analysis allows continuous and fast real-time identification of the piston ring rotation of the two compression rings, while the mass-spectrometric analysis of the exhaust gas delivers the cylinder oil emission instantly and with a high temporal resolution. Only minor modifications to the piston rings were made for the insertion of the γ-emitters, the rings rotate freely around the circumference of the piston. The idea of this setup is that through online observation at the test bench, instant feedback of the measured variables is available, making it possible to purposefully select and compare measurement points. The high time resolution of the measurement methods enables the analysis of dynamic effects. In this article, the measurement setup and evaluation method is described.

Longitudinal models are used to evaluate different vehicle-engine concepts with respect to driving behavior and emissions. The engine is generally map-based. An explicit calculation of both fluid dynamics inside the engine air path and cylinder combustion is not considered due to long computing times. Particularly for dynamic certification cycles (WLTC, US06 etc.), dynamic engine effects severely influence the quality of results. Hence, an evaluation of transient engine behavior with map-based engine models is restricted to a certain extent. The coupling of detailed 1D-engine models is an alternative, which rapidly increases the model computation time to approximately 300 times higher than that of real time. In many technical areas, the Fourier transformation (FT) method is applied, which makes it possible to represent superimposed oscillations by their sinusoidal harmonic oscillations of different orders.

In this study, a fully optically accessible single-cylinder research engine is the basis for the visualization and generation of extensive knowledge about the in-cylinder processes of mixture formation, ignition and combustion of oxygenated synthetic fuels. Previous measurements in an all-metal engine showed promising results by using a mixture of dimethyl carbonate and methyl formate as a fuel substitute in a DISI-engine. Lower THC and NOx emissions were observed along with a low PN-value, implying low-soot combustion. The flame luminosity transmitted via an optical piston was split in the optical path to simultaneously record the natural flame luminosity with an RGB high-speed camera. The second channel consisted of OH*-chemiluminescence recording, isolated by a bandpass filter via an intensified monochrome high-speed camera.

Time-resolved concentrations of formaldehyde and acetaldehyde in the exhaust gas have been investigated during transient motor operation, such as sudden change of speed and load, misfiring and switching off the fuel mixture control. To this purpose, a new laser mass spectrometer has been applied which is capable of measuring the concentrations of individual exhaust compounds with 1 ppm sensitivity at a sampling rate of 50 Hz corresponding to a sampling period of 20 ms. At sudden speed changes, high concentrations of aldehydes are observed, in particular during the phase of decreasing speed, i.e. after closing the throttle valve.

The classical theory of wind tunnel corrections calculated from potential flow theory is revisited. In this context a flow model uniformly valid for all types of test sections is developed for the correction of drag in automotive wind tunnels. To define and size the singularities setting up the flow model only geometrical properties of the model and measured force coefficients will be used. To achieve a correct representation of the flow about a vehicle body a number of improvements to the classical approach are proposed. Based on the uniformly valid flow model, correction formulae for closed wall, open jet and slotted wall test sections are given. For the open jet and slotted wall case it is shown, that the presented formulae are still incomplete, whereas for the closed wall case the correction is ready to use. The correction approach is validated step by step by comparison with appropriate experimental data.