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This study focuses on evaluation of various fuels within a conventional gasoline internal combustion engine (ICE) vehicle and the implementation of advanced emissions reduction technology. It shows the robustness of the implemented technology packages for achieving ultra-low tailpipe emissions to different market fuels and demonstrates the potential of future GHG neutral powertrains enabled by drop-in lower carbon fuels (LCF). An ultra-low emission (ULE) sedan vehicle was set up using state-of-the-art engine technology, with advanced vehicle control and exhaust gas aftertreatment system including a prototype rapid catalyst heating (RCH) unit. Currently regulated criteria pollutant emission species were measured at both engine-out and tailpipe locations. Vehicle was run on three different drive cycles at the chassis dynamometer: two standard cycles (WLTC and TfL) at 20°C, and a real driving emission (RDE) cycle at -7°C.

To meet emission targets, alternative fuels are increasingly vital in reducing exhaust emissions. One effective and cost-efficient method to achieve sustainable emission reductions is through hydrogen (H2) operated modern combustion engines. In line with the energy transformation, similar to Germany’s “Energiewende”, industries need CO2-neutral solutions, with special importance in the mobility sector. Hydrogen, as a carbon-free fuel, presents a viable alternative to conventional options and has been subject to extensive scientific research. The development of hydrogen combustion engines is still in the conceptualization phase. This study focuses on a direct-injection (DI) combustion engine from a commercial vehicle converted from diesel DI-compression ignition (CI) to hydrogen DI-spark ignition (SI) operation. The main objectives were to validate simulation models using 1D and 3D simulation software and to conduct a comprehensive analysis of engine operation.

X-Domain describes the merging of different domains (i.e., braking, steering, propulsion, suspension) into single functionalities. One example in this context is torque-vectoring. Different goals can be pursued by applying X-Domain features. On the one hand, savings in fuel consumption and an improved vehicle driving performance can be potentially accomplished. On the other hand, safety can be improved by taking over a failed or degraded functionality of one domain by other domains. The safety-aspect from the viewpoint of requirements is highlighted within this contribution. Every automotive system being developed and influencing the vehicle safety must fulfill certain safety objectives. These are top-level safety requirements (ISO 26262-1) specifying functionalities to avoid unreasonable risk. Every safety objective is associated with an Automotive Safety Integrity Level (ASIL) derived from a Hazard Analysis and Risk Assessment (HARA).

During cold start of natural gas engines, increased methane and formaldehyde emissions can be released due to flame quenching on cold cylinder walls, misfiring and the catalyst not being fully active at low temperatures. Euro 6 legislation does not regulate methane and formaldehyde emissions. New limits for these two pollutants have been proposed by CLOVE consortium for Euro 7 scenarios. These proposals indicate tougher requirements for aftertreatment systems of natural gas engines. In the present study, a zero-dimensional model for real-time engine-out emission prediction for transient engine cold start is presented. The model incorporates the stochastic reactor model for spark ignition engines and tabulated chemistry. The tabulated chemistry approach allows to account for the physical and chemical properties of natural gas fuels in detail by using a-priori generated laminar flame speed and combustion chemistry look-up tables.

Historically, whenever the automotive solutions’ state of art reaches a saturation level, the integration of new verticals of technology has always raised new opportunities to innovate, enhance and optimize automotive solutions. The predictive powertrain solutions using connectivity elements (e.g., navigation unit, e-Horizon or cloud-based services) are one of such areas of huge interest in automotive industry. The prior knowledge of trip destination and its route characteristics has potential to make prediction of powertrain modes or events in certain order and therefore it can add value in various application areas such as optimized energy management, lower fuel consumption, superior safety and comfort, etc.

Nowadays automobiles are getting smart and there is a growing need for the physical behavior to become part of its software. This behavior can be described in a compact form by differential equations obtained from modeling and simulation tools. In the offline simulation domain the Functional Mockup Interface (FMI) [3], a popular standard today supported by many tools, allows to integrate a model with solver (Co-Simulation FMU) into another simulation environment. These models cannot be directly integrated into embedded automotive software due to special restrictions with respect to hard real-time constraints and MISRA compliance. Another architectural restriction is organizing software components according to the AUTOSAR standard which is typically not supported by the physical modeling tools. On the other hand AUTOSAR generating tools do not have the required advanced symbolic and numerical features to process differential equations.

Software-in-the-Loop (SiL) test environments are the ideal virtual platforms for enabling continuous-development, -integration, -testing -delivery or -deployment commonly referred as Continuous-X (CX) of the complex functionalities in the current automotive industry. This trend especially is contributed by several factors such as the industry wide standardization of the model exchange formats, interfaces as well as architecture definitions. The approach of frontloading software testing with SiL test environments is predominantly advocated as well as already adopted by various Automotive OEMs, thereby the demand for innovating applicable methods is increasing. However, prominent usage of the existing monolithic architecture for interaction of various elements in the SiL environment, without regarding the separation between functional and non-functional test scope, is reducing the usability and thus limiting significantly the cost saving potential of CX with SiL.

To reduce exhaust emissions in commercial vehicles, hydrogen, as a carbon-free fuel, is a reasonable alternative to conventional fuels. In order to circumvent the current problem of hydrogen availability, the use of a gas engine for heavy duty vehicles (HDV), which is able to operate with pure compressed natural gas (CNG), pure hydrogen as well as any mixture of these both gases, is sensible. For this purpose, an operating concept for a gas engine was developed, which is able to operate with an arbitrary hydrogen-natural gas mixture ratio. Therefore, the mixture formation of a hydrogen-natural gas-air mixture was analyzed in a 3D CFD simulation. The results for pure hydrogen and pure CNG operation show a very good homogenization of the fuel distribution at the point of ignition when an outward-opening injector was used.

The tightening of the emission legislation and political and social demands for sustainable mobility are forcing the automotive industry to develop complex, high precision mechatronic drive systems. The increasing precision of mechatronic components generally leads to an increase in structural excitation and thus to a rise in noise. The so-called ticking of the fuel injection system has a rather low sound pressure level compared to the residual engine noise. Nevertheless, the impulsive and high frequency noise character leads to a decline concerning the perception of comfort and sound quality. In order to identify the sound quality of fuel injection systems as a frontloading measure, a system test bench has been developed which represents the structure-borne and airborne sound radiation of the stand-alone injection system in a close to series configuration.

Safety-critical embedded software has to satisfy stringent quality requirements. One such requirement, imposed by all contemporary safety standards, is that no critical run-time errors must occur. Runtime errors can be caused by undefined or unspecified behavior of the programming language; examples are buffer overflows or data races. They may cause erroneous or erratic behavior, induce system failures, and constitute security vulnerabilities. A sound static analyzer reports all such defects in the code, or proves their absence. Sound static program analysis is a verification technique recommended by ISO/FDIS 26262 for software unit verification and for the verification of software integration. In this article we propose an analysis methodology that has been implemented with the static analyzer Astrée. It supports quick turn-around times and gives highly precise whole-program results.

The introduction of new emission legislation and the demand of increased power for small two-wheelers lead to an increase of technical requirements. Especially for single cylinder engines with high compression ratio the transient behavior close to idling is challenging. The demand for two-wheeler specific responsiveness of the vehicle requires low overall rotational inertia as well as small intake manifold volumes. The combination with high compression ratio can lead to a stalling of the engine if the throttle opens and closes very quickly in idle operation. The fast opening and closing of the throttle is called a throttle blip. Fast, in this context, means that the blipping event can occur in one to two working cycles. Previous work was focused on the development of a procedure to apply reproducible blipping events to a vehicle in order to derive a deeper physical understanding of the stalling events.

External Exhaust Gas Recirculation (EGR) provides an opportunity to increase the efficiency of turbocharged spark-ignition engines. Of the competing technologies and configurations, Low-Pressure EGR (LP-EGR) is the most challenging in terms of its dynamic behavior. Only some of the stationary feasible potential can be used during dynamic engine operation. To guarantee fuel consumption-optimized engine operation with no instabilities, a load point-dependent limitation of the EGR rate or alternatively an adaptation of the operating point to the actual EGR rate is crucial. For this purpose, a precise knowledge of efficiency and combustion variance is necessary. Since the operating state includes the actual EGR rate, it has an additional dimension, which usually results in an immense measuring effort.

In the discussion on the reduction or complete avoidance of CO2-emissions and other pollutants in the transport sector, hydrogen as a carbon-free fuel, is an alternative to conventional fuels. The use of hydrogen in modern internal combustion engines offers a fast and cost-effective opportunity of decarbonisation of the transport sector. The utilisation of hydrogen as fuel in internal combustion engine systems is more challenging than using conventional fuels. Hydrogen is highly flammable, which affects the requirements of the ignition system and the design of the combustion chamber. In addition, due to the gaseous state of H2 the question, how the fuel should be delivered to the combustion chamber is of high importance by means of engine performance. There are two fundamentally different concepts for hydrogen injection. Hydrogen can be injected by a multi-point injection into intake manifold by external mixture-formation (MPI) or directly into the combustion chamber (DI).

Due to the new CO2 targets for vehicles, electrification of powertrains and operation strategies for electrified powertrains have drawn more attention. This article presents a predictive multi-objective operation strategy for hybrid electric vehicles (HEVs), which simultaneously minimizes the fuel consumption and the cycle aging of traction batteries. This proposed strategy shows better performance by using predictive information and high robustness to inaccuracy of predictive information. In this work, the benefits of the developed operation strategies are demonstrated in a strong hybrid electric vehicle (sHEV) with P2-configuration. For the cycle aging of a lithium-ion battery, an empirical model is built up with Gaussian processes based on experimental data.

The fuel spray behavior in the near nozzle region of a gasoline injector is challenging to predict due to existing pressure gradients and turbulences of the internal flow and in-nozzle cavitation. Therefore, statistical parameters for spray characterization through experiments must be considered. The characterization of spray velocity fields in the near-nozzle region is of particular importance as the velocity information is crucial in understanding the hydrodynamic processes which take place further downstream during fuel atomization and mixture formation. This knowledge is needed in order to optimize injector nozzles for future requirements. In this study, the results of three experimental approaches for determination of spray velocity in the near-nozzle region are presented. Two different injector nozzle types were measured through high-speed shadowgraph imaging, Laser Doppler Anemometry (LDA) and X-ray imaging.

The ongoing changes in the development of new power trains and the requirements due to driver assistance systems and autonomous driving could be the enabler for completely new brake system configurations. The shift in the brake load collective has to be included in the systems requirements for electric vehicles. Many alternative concepts for hydraulic brake systems, even for decentralized configurations, can be found in the literature. For a decentralized system with all state of the art safety functionalities included, four actuators are necessary. Therefore, the single brake module should be as cost-effective as possible. Previous papers introduced systems which are for example based on plunger-like concepts, which are very expensive and heavy due to the needed gearing and design. In this paper a comparison between a state of the art hydraulic brake system using an electromechanical brake booster, and a completely new decentralized hydraulic brake concept is presented.

Compressed Natural Gas (CNG) is a promising alternative fuel for internal combustion engines as its combustion is fuel-efficient and lean in carbon dioxide compared to gasoline. The high octane number of methane gives rise to significant increase of the thermodynamic efficiency due to higher possible compression ratios. In order to use this potential, new stratified mixture formation concepts for CNG are investigated by means of numerical fluid simulations. For decades RANS methods have been the industry standard to model three-dimensional flows. Indeed, there are well-known deficiencies of the widely used eddy viscosity turbulence models based on the applied Boussinesq hypothesis. Reynolds stress turbulence models as well as scale resolving simulation approaches can be appealing alternative choices since they offer higher accuracy. However, due to their large computing effort, they are still mostly impractical for the daily use in industrial product development processes.

A previous study by the authors has shown an efficiency benefit of up to Δηi = 10 % for stratified operation of a high pressure natural gas direct injection (DI) spark ignition (SI) engine compared to the homogeneous stoichiometric operation with port fuel injection (PFI). While best efficiencies appeared at extremely lean operation at λ = 3.2, minimum HC emissions were found at λ = 2. The increasing HC emissions and narrow ignition time frames in the extremely lean stratified operation have given the need for a detailed analysis. To further investigate the mixture formation and flame propagation und these conditions, an optically accessible single-cylinder engine was used. The mixture formation and the flame luminosity have been investigated in two perpendicular planes inside the combustion chamber.

As automobiles become increasingly smarter, the need to understand within the automotive software the physical behavior of its parts is growing as well. The laws of physics governing such behavior are mostly formulated as differential equations, which today are usually created or obtained from various modeling tools. For solving them, the tools offer several solvers to satisfy the requirements of different problems. E.g. simple and fast explicit low order solvers for non-stiff problems and more complex implicit solvers for stiff problems. Though the modeling and code generation features as available in such tools are desirable for embedded automotive software, they cannot be used directly due to special restrictions with respect to hard realtime constraints. One such restriction is the organization of automotive software in components complying with the AUTOSAR standard which is not widely supported by the modeling tools.

The introduction of stricter emission legislation and the demand of increased power for small two-wheelers lead to an increase of technical requirements. Especially the introduction of liquid-cooling over air-cooling allows the introduction of higher compression ratios, which improves power output as well as thermodynamic efficiencies and thereby fuel consumption. But an increase in compression ratio also introduces further challenges during transient behavior especially close to idling. In order to keep the two-wheeler specific responsiveness of the vehicle, the overall rotational inertia of the engine must be kept low. But the combination of low inertia and high compression ratio can lead to a stalling of the engine if the throttle is opened and closed very quickly in idle operation. The fast opening and closing of the throttle is called a throttle blip.