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The introduction of real driving emissions cycles and increasingly restrictive emissions regulations force the automotive industry to develop new and more efficient solutions for emission reductions. In particular, the cold start and catalyst heating conditions are crucial for modern cars because is when most of the emissions are produced. One interesting strategy to reduce the time required for catalyst heating is post-oxidation. It consists in operating the engine with a rich in-cylinder mixture and completing the oxidation of fuel inside the exhaust manifold. The result is an increase in temperature and enthalpy of the gases in the exhaust, therefore heating the three-way-catalyst. The following investigation focuses on the implementation of post-oxidation by means of scavenging in a four-cylinder, turbocharged, direct injection spark ignition engine. The investigation is based on detailed measurements that are carried out at the test-bench.

As a consequence of reduced fuel consumption, direct injection gasoline engines have already prevailed against port fuel injection. However, in-cylinder fuel homogenization strongly depends on charge motion and injection strategies and can be challenging due to the reduced available time for mixture formation. An insufficient homogenization has generally a negative impact on the combustion and therefore also on efficiency and emissions. In order to reach the targets of the intensified CO2 emission reduction, further increase in efficiency of SI engines is essential. In this connection, 0D/1D simulation is a fundamental tool due to its application area in an early stage of development and its relatively low computational costs. Certainly, inhomogeneities are still not considered in quasi dimensional combustion models because the prediction of mixture formation is not included in the state of the art 0D/1D simulation.

For the cylinder-selective monitoring of combustion cycles in spark-ignition engines, the dynamic exhaust-gas pressure is analyzed. A time domain based diagnostic system for misfire detection has been developed and tested on data measured in a BMW 750i, V-12 engine. It uses features of the suitable low-pass-filtered exhaust-gas pressure signal by calculating differences of the locally determined extrema. For the detection and localization of all misfire combinations a simple inference system in the form of linguistic rules is used. It is shown that even within the operating areas of high engine speeds and low loads on engines with a high number of cylinders good classification rates can be obtained.

This paper provides a method that corrects errors induced by the empty-tunnel pressure distribution in the aerodynamic forces and moments measured on an automobile in a wind tunnel. The errors are a result of wake distortion caused by the gradient in pressure over the wake. The method is applicable to open-jet and closed-wall wind tunnels. However, the primary focus is on the open tunnel because its short test-section length commonly results in this wake interference. The work is a continuation of a previous paper [4] that treated drag only at zero yaw angle. The current paper extends the correction to the remaining forces, moments and model surface pressures at all yaw angles. It is shown that the use of a second measurement in the wind tunnel, made with a perturbed pressure distribution, provides sufficient information for an accurate correction. The perturbation in pressure distribution can be achieved by extending flaps into the collector flow.

Test of autonomous systems is mostly brute force and ad-hoc thus being neither efficient nor transparent. Though requirements invite for a situational transparency, a framework is missing to judge quality of requirements and derived test-cases. Practical challenges are state explosion, difficulty to derive corner cases, no systematic safety of the intended functionality as specified, lack of accepted KPI, etc. Maintaining a valid safety case is hardly possible with such adaptive systems and continuous software updates. To achieve trusted autonomous vehicles, test cases must be generated automatically while at same time providing coverage (e.g., indicating progress with KPI), efficiency (e.g., limiting the amount of regression testing) and transparency (e.g., showing how specific corner cases are tested in case of accidents). This paper provides a method for automatically generating test cases for AI-based autonomous systems and compares it with existing testing methods.

In the automotive industry, there is a continued need to improve the development process and handle the increasing complexity of the overall vehicle system. One major step in this process is a comprehensive and complementary approach to both simulation and testing. Knowledge of the overall dynamic vehicle behavior is becoming increasingly important for the development of new control concepts such as integrated vehicle dynamics control aiming to improve handling quality and ride comfort. However, with current well-established test systems, only separated and isolated aspects of vehicle dynamics can be evaluated. To address these challenges and further merge the link between simulation and testing, the Institute of Internal Combustion Engines and Automotive Engineering (IVK), University of Stuttgart is introducing a new Handling Roadway (HRW) Test System in cooperation with The Research Institute of Automotive Engineering and Vehicle Engines Stuttgart (FKFS) and MTS Systems Corporation.

Synthetic fuels for internal combustion engines offer CO2-neutral mobility if produced in a closed carbon cycle using renewable energies. C1-based synthetic fuels can offer high knock resistance as well as soot free combustion due to their molecular structure containing oxygen and no direct C-C bonds. Such fuels as, for example, dimethyl carbonate (DMC) and methyl formate (MeFo) have great potential to replace gasoline in spark-ignition (SI) engines. In this study, a mixture of 65% DMC and 35% MeFo (C65F35) was used in a single-cylinder research engine to determine friction losses in the piston group using the floating-liner method. The results were benchmarked against gasoline (G100). Compared to gasoline, the density of C65F35 is almost 40% higher, but its mass-based lower heating value (LHV) is 2.8 times lower. Hence, more fuel must be injected to reach the same engine load as in a conventional gasoline engine, leading to an increased cooling effect.

The influence of internal mixture formation oil hydrogen combustion in a SI engine was investigated using high speed Schlieren photography. To this end a computer controlled high pressure injection system for direct injection of gaseous hydrogen was developed. The injection system for hydrogen direct injection consists of an electronic control unit, a solenoid valve and a purpose developed injector. The timing and the duration of the hydrogen injection are controlled by an electronic unit. The fuel-air ratio was varied by adjusting the opening time of the solenoid valve. The hydrogen was fed into the combustion chamber of the engine with a pressure of 6.0 MPa. With this injection system and injection pressure it, is possible to inject the hydrogen into the combustion chamber of the engine even during hydrogen combustion. In order to compare the results of internal mixture formation, experiments with external mixture formation were also performed.

Increasing demand for utilities like navigation systems or user-defined electronic phonebooks on one hand and sophisticated engine and gear controls on the other hand leads to growing bus load between distributed local control units. This paper shows the benefits and the characteristics of various state of the art data-compression algorithms and their impact on typical automotive multiplex dataclasses. The evaluation and optimization of promising algorithms can be done via a proposed “communications prototyping”-approach. The hardware/software components of such a rapid prototyping package are outlined. Finally, first performance results of suitable data-compression measures are presented.

For development of new engines a ‘general purpose ECU’ for spark ignition engines with up to 12 cylinders has been developed. As part of this ECU a DSP (Digital Signal Processor)-based measurement unit for high frequency combustion analysis has been integrated. In this paper, details about this signal processing platform are given. The DSP-unit has 24 analog input channels. 12 channels are used for cylinder pressure measurement; the other 12 channels are general purpose ones. For example, they can be used for ionic current analysis. Additional digital inputs allow measurement of crank speed and crank speed variations. This is an important topic for misfire detection as part of the OBD regulations.

To meet the requirements of strict CO2 emission regulations in the future, internal combustion engines must have excellent efficiencies for a wide operating range. In order to achieve this goal, various technologies must be applied. Additionally, fuels other than gasoline should also be considered. In order to investigate the potential of the efficiency improvement, a SI engine was designed and optimized using 0D/1D methods. Some of the advanced features of this engine model include: High stroke-to-bore-ratio, variable valve timings with Miller cycle, EGR, cylinder deactivation, high turbulence concept, variable compression ratio and extreme downsizing. The fuel of choice was gasoline. With the proper application of technologies, the fuel consumption at the most relevant operating window could be decreased by approximately 10% in comparison to a state-of-the-art spark-ignited direct-injection four-cylinder passenger car engine.

Knocking is one of today’s main limitations in the ongoing efforts to increase efficiency and reduce emissions of spark-ignition engines. Especially for synthetic fuels or any alternative fuel type in general with a much steeper increase of the knock frequency at the KLSA, such as hydrogen, precise knock prediction is crucial to exploit their full potential. This paper therefore proposes a post-processing tool enabling further investigations to continuously gain better understanding of the knocking phenomenon. In this context, evaluation of local auto-ignitions preceding knock is crucial to improve knowledge about the stochastic occurrence of knock but also identify critical engine design to further optimize the geometry. In contrast to 0D simulations, 3D CFD simulations provide the possibility to investigate local parameters in the cylinder during the combustion.

In this paper we present an advanced knock detection approach. The detection concept consists of a two-level feature extraction step followed by neural network detector. A knock tendency index is estimated that takes into account the statistical behavior of the knock phenomena. The configuration of the neural network is based on a signal database that was acquired under almost ‘on-road’ conditions. The experimental set-up consisted of several measurement sessions in a special vehicle test cell. In order to achieve a most realistic knock database the test engine was mounted on an in-production car.

Although hydrogen ICE engines have existed in one sort or another for many years, the testing of fuel consumption by way of exhaust emissions is not yet a proven method. The current consumption method for gasoline- and diesel-fueled vehicles is called the Carbon-Balance method, and it works by testing the vehicle exhaust for all carbon-containing components. Through conservation of mass, the carbon that comes out as exhaust must have gone in as fuel. Just like the Carbon-Balance method for gas and diesel engines, the new Hydrogen-Balance equation works on the principle that what goes into the engine must come out as exhaust components. This allows for fuel consumption measurements without direct contact with the fuel. This means increased accuracy and simplicity. This new method requires some modifications to the testing procedures and CVS (Constant Volume Sampling) system.

In the present work we investigated experimentally and computationally the unsteady flow around a BMW car model including wheels*. This simulation yields mean flow and turbulence fields, enabling the study aerodynamic coefficients (drag and lift coefficients, three-dimensional/spatial wall-pressure distribution) as well as some unsteady flow phenomena in the car wake (analysis of the vortex shedding frequency). Comparisons with experimental findings are presented. The computational approach used is based on solving the complete transient Reynolds-Averaged Navier-Stokes (TRANS) equations. Special attention is devoted to turbulence modelling and the near-wall treatment of turbulence. The flow calculations were performed using a robust, eddy-viscosity-based ζ - ƒ turbulence model in the framework of the elliptic relaxation concept and in conjunction with the universal wall treatment, combining integration up to the wall and wall functions.

In this paper, the differences between a production car of the 2018 A-class and an early stage vehicle model with a mostly similar outer skin are examined experimentally and numerically. The aerodynamic development of vehicles at Mercedes-Benz is divided into several phases. When comparing force coefficients differences can be observed between these distinct hardware stages as well as when comparing steady state simulations to wind tunnel measurements. In early phases when prototype vehicles are not yet available, so-called aero foam models are used. These are well-defined full-sized vehicle models, as the outer skin is milled from Polyurethane. Important aerodynamic characteristics such as a motor compartment with a cooling module, deflecting axles with rotatable wheels and underbody covers are represented.

The reduction of engine-out emissions and increase of the total efficiency is a fundamental approach to reduce the fuel consumption and thus emissions of vehicles driven by combustion engines. Conventional passenger cars are operated mainly in lower part loads for most of their lifetime. Under these conditions, oil temperatures are far below the maximum temperature allowed and dominate inside the journal bearings. Therefore, the objective of this research was to investigate possible potentials of friction reduction by optimizing the combustion engine’s thermal management of the oil circuit. Within the engine investigations, it was shown that especially the friction of the main and connecting rod bearings could be reduced with an increase of the oil supply temperature. Furthermore, on a journal bearing test rig, it was shown that no excessive wear of the bearings is to be expected in case of load increase and simultaneous supply of cooler oil.

The increasing complexity of communication protocols for asynchronous multiplex systems requires the use of simulation during the optimisation of these protocols or the integration of other control units. Consideration of realistic communication behaviour of the connected control units is essential for performance analysis of multiplex systems. For a first pass, the use of simple statistical distributions (e.g. Poisson distribution) is suitable to get some simulation results. A better way to get realistic results is the approximation of empirical communication data through the use of more complex statistical distribution (e.g. mixed Erlang distributions). In this paper several approaches for the approximation of empirical data are presented. Beside simple statistical distributions (with one parameter), the use of more complex statistical distributions is discussed and methods for the identification of their parameters are presented.

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.

There is a growing need for low-emissions concepts due to stricter emission regulations, more stringent homologation cycles, and the possibility of a ban on new engines by 2035. Of particular concern are the conditions during a cold start, when the Three-Way Catalyst is not yet heated to its light-off temperature. During this period, the catalyst remains inactive, thereby failing to convert pollutants. Reducing the time needed to reach this temperature is crucial to comply with the more stringent emissions standards. The post oxidation by means of secondary air injection, illustrated in this work, is a possible solution to reduce the time needed to reach the above-mentioned temperature. The strategy consists of injecting air into the exhaust manifold via secondary air injectors to oxidize unburned fuel that comes from a rich combustion within the cylinder.