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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.

Increasingly stringent tailpipe emissions regulations have prompted renewed interest in catalyst heating technology – where an integrated device supplies supplemental heat to accelerate catalyst ‘light-off’. Bosch and Boysen, following a collaborative multi-year effort, have developed a Rapid Catalyst Heating System (RCH) for gasoline-fueled applications. The RCH system provides upwards of 25 kW of thermal power, greatly enhancing catalyst performance and robustness. Additional benefits include reduction of precious metal loading (versus a ‘PGM-only’ approach) and avoidance of near-engine catalyst placement (limiting the need for enrichment strategies). The following paper provides a technical overview of the Bosch/Boysen (BOB) Rapid Catalyst Heating system – including a detailed review of the system’s architecture, key performance characteristics, and the associated impact on vehicle-level emissions.

In the context of the energy transition, CO2-neutral solutions are of enormous importance for all sectors, but especially for the mobility sector. Hydrogen as an energy carrier has therefore been the focus of research and development for some time. However, the development of hydrogen combustion engines is in many respects still in the conception phase. Automotive system providers and engineering companies in the field of software development and simulation are showing great interest in the topic. In a joint project with the industrial partners Robert Bosch GmbH and AVL Germany, combustion in a H2-DI-engine for use in light-duty vehicles was methodically investigated using the CFD tool AVL FIRE®. The collaboration between Robert Bosch GmbH and the Institute for Mobile Systems (IMS) at Otto von Guericke University Magdeburg has produced a model study in which model approaches for the combustion of hydrogen can be analyzed.

Under the proposed Green Deal program, the European Union will aim to achieve zero net greenhouse gas (GHG) emissions by 2050. The interim target is to reduce GHG by 55% by 2030. In the current debate concerning CO2-neutral powertrains, bio-fuels and e-fuels could play an immediate and practical role in reducing lifecycle engine emissions. Hydrogen however, is one of the few practical fuels that can result in near zero CO2 emissions at the tailpipe, which is the main focus of current legislation. Compared to gasoline, hydrogen presents a higher laminar flame speed, a wider range of flammability and higher auto-ignition temperatures, making it among the most attractive of fuels for future engines. As a challenge, hydrogen requires a very low ignition energy. This may imply an increased susceptibility to Low Speed Pre-Ignition (LSPI), surface ignition and back-fire phenomena. In order to exploit hydrogen’s potential, the injection system plays an extremely important role.

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.

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.

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.

Model guided application (MGA) combining physico-chemical internal combustion engine simulation with advanced analytics offers a robust framework to develop and test particle number (PN) emissions reduction strategies. The digital engineering workflow presented in this paper integrates the kinetics & SRM Engine Suite with parameter estimation techniques applicable to the simulation of particle formation and dynamics in gasoline direct injection (GDI) spark ignition (SI) engines. The evolution of the particle population characteristics at engine-out and through the sampling system is investigated. The particle population balance model is extended beyond soot to include sulphates and soluble organic fractions (SOF). This particle model is coupled with the gas phase chemistry precursors and is solved using a sectional method. The combustion chamber is divided into a wall zone and a bulk zone and the fuel impingement on the cylinder wall is simulated.

Particulate emissions from Gasoline Direct Injection (GDI) engines have been an important topic of recent research interest due to their known environmental effects. This review paper will characterise the influence of different gasoline direct injection fuel systems on particle number (PN) emissions. The findings will be reviewed for engine and vehicle measurements with appropriate driving cycles (especially real driving cycles) to evaluate effects of the fuel injection systems on PN emissions. Recent technological developments alongside the trends of the influence of system pressure and nozzle design on injector tip wetting and deposits will be considered. Besides the engine and fuel system it is known that fuel composition will have an important effect on GDI engine PN emissions. The evaporation qualities of fuels have a substantial influence on mixture preparation, as does the composition of the fuel itself.

The success of model-based ECU-functions relies on precise and efficient modeling of the behavior of combustion engines. Due to the limited computing power, usually a combination of physical models and calibration parameters is preferred for engine modeling in ECU. The parameters can be scalars, 1 or 2-dimensional empirical models, such as look-up table for volumetric efficiency and effective area of the exhaust gas recirculation (EGR). A novel algorithm is proposed to automatically calibrate the look-up tables characterizing stationary functional relationships in ECU-function of the air system of a diesel engine with minimum calibration cost. The algorithm runs in the framework of online design of experiment (DoE), in which Gaussian process model (GPM) is adopted to approximate the relationships of interest.

A major source for soot particle formation in Gasoline-Direct-Injection (GDI) engines are fuel-rich zones near walls as a result of wall wetting during injection. To address this problem, a thorough understanding of the wall film formation and evaporation processes is necessary. The wall temperature before, during and after fuel impingement is an important parameter in this respect, but is not easily measured using conventional methods. In this work, a recently developed laser-based phosphor thermography technique is implemented for investigations of spray-induced surface cooling. This spatially and temporally resolved method can provide surface temperature measurements on the wetted side of the surface without being affected by the fuel-film. Zinc oxide (ZnO) particles, dispersed in a chemical binder, were deposited onto a thin steel plate obtaining a coating thickness of 17 μm after annealing.

This study presents a methodology to predict particle number (PN) generation on a naturally aspirated 4-cylinder gasoline engine with port fuel injection (PFI) from wall wetting, employing numerical CFD simulation and fuel film analysis. Various engine parameters concerning spray pattern, injection timing, intake valve timing, as well as engine load/speed were varied and their impact on wall film and PN was evaluated. The engine, which was driven at wide open throttle (WOT), was equipped with soot particle sampling technology and optical access to the combustion chamber of cylinder 1 in order to visualise non-premixed combustion. High-speed imaging revealed a notable presence of diffusion flames, which were typically initiated between the valve seats and cylinder head. Their size was found to match qualitatively with particulate number measurements. A validated CFD model was employed to simulate spray propagation, film transport and droplet impingement.

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 Side View Assist is the World’s first rider assistance system for two-wheelers. This is a Blind Spot Warning system, which uses four ultrasonic sensors to monitor the surrounding of the rider. Whenever there is a vehicle (i.e. a car, truck, or another motorbike) in the rider’s blind spot, the technology warns the rider with an optical signal close to the mirror. This will allow the rider to avoid a collision when changing lanes. In the current vehicle application, Side View Assist is active at speeds ranging from 25 to 80 kilometers per hour and supports riders whenever the difference in relative speed to other road users is small. The system helps to improve safety especially in cities, where heavy traffic makes it necessary to change lanes more often. Originally such systems have been developed for cars and different system solutions for cars have been in serial production for several years. The challenge was to adapt these systems so they would work for two-wheelers as well.

Many software functions currently available in the engine control units have been developed for several years (decades in some cases), reengineered or adapted due to new requirements, what may add to their inherent complexity an unnecessary complication. This paper deals with the study and implementation of a software reengineering strategy for the embedded domain, which is in transfer from research department to product development, here applied to improve maintainability of flex fuel functions. The strategy uses the SCODE “Essential Analysis”, an approach for the embedded system domain. The method allows to reduce the system complexity to the unavoidable inherent problem complexity, by decomposing the system into smaller sub problems based on its essential physics. A case study was carried out to redesign a function of fuel adaptation. The analysis was performed with the support of a tool, which covers all the phases of the method.

To satisfy future emission classes, e.g. EU6c, the particulate number (PN) of Direct-Injection Spark-Ignition (DISI) engines must be reduced. For these engines, different components influence the combustion process and thus also the formation of soot particles and deposits. Along with other engine components, the injector nozzle influences the particulate number and deposits in both fuel spray behavior and nozzle “tip wetting”. In case of non-optimized nozzle layouts, fuel may impinge on the piston and the liner in an unfavorable way, which implies low-oxygen diffusive combustion by retarded vaporizing wall films. For the tip wetting, wall films are present on the actual surface of the nozzle tip, which is also caused by unadapted nozzles. For non-optimized nozzles, the latter effect can become quite dominant. This paper deals with systematic nozzle development activities towards low-deposit nozzle tips and thus decreasing PN values.

The fuel-independent particulate emissions of a direct injection gasoline engine were investigated. This was done by running the engine with reference gasoline at four different loads and then switching to hydrogen or methane port fuel operation and comparing the resulting particulate emissions and their size distribution. Differences in the combustion characteristics of hydrogen and gasoline were accounted for by diluting the inlet air with nitrogen and matching the pressure or heat release traces to those of gasoline operation. Methane operation is expected to generate particulate emissions lower by several orders of magnitude compared to gasoline and hydrogen does not contribute to carbon soot formation because of the lack of carbon atoms in the molecule. Thus, any remaining particulate emissions at hydrogen gas operation must arise from non fuel related sources, e.g. from lubrication oil, metal abrasion or inlet air.

The spatial distribution of internal exhaust gas recirculation (EGR) is evaluated in an optically accessible direct injection spark ignition engine using near infrared laser absorption to visualize the distribution of the H2O molecule. The obtained overall internal exhaust gas recirculation compares well to gas-exchange cycle calculations and the spatial distributions are consistent with those measured with inverse LIF. The experimental procedures described in this report are designed to be simple and rapidly implemented without the need to resort to unusual optical components. The necessary spectral data of the selected absorption line is obtained from the HITEMP database and is validated with prior experiments carried out in a reference cell. Laser speckle in the images is effectively reduced using a ballistic diffuser.