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Previous research has shown that elevating fuel injection pressure results in better air-fuel mixture formation, allowing for a further increase in maximum exhaust gas recirculation (EGR) rate while consequently reducing NOx emissions. The aim of this paper is to find out whether there is an optimum injection pressure for lowest soot-NOx emissions at a given boost pressure in high-speed diesel engines. Experiments are carried out on a single-cylinder research engine with a prototype common-rail system, capable of more than 200 MPa injection pressure. The effect of injection pressure on soot-NOx formation is investigated for a variety of boost conditions, representing the conditions of single to multi-stage turbocharger systems. Analysis of the data is performed at the application relevant soot to NOx ratio of approximately 1:10. It is observed that above a critical injection pressure, soot-NOx emissions are not reduced any further.

The introduction of CO₂-reduction technologies like Start-Stop or the Hybrid-Powertrain and the future emission legislation require a detailed optimization of the engine start-up. The combustion concept development as well as the calibration of the ECU makes an explicit thermodynamic analysis of the combustion process during the start-up necessary. Initially, the well-known thermodynamic analysis of in-cylinder pressure at stationary condition was transmitted to the highly non-stationary engine start-up. There, the current models for calculation of the transient wall heat fluxes were found to be misleading. Therefore, adaptations to the start-up conditions of the known models by Woschni, Hohenberg and Bargende were introduced for calculation of the wall heat transfer coefficient in SI engines with gasoline direct injection. This paper shows how the indicated values can be measured during the engine start-up.

The subject of this work is 3D numerical simulations of combustion and soot emissions for a passenger car diesel engine. The CFD code STAR-CD version 3.26 [1] is used to resolve the flowfield. Soot is modeled using a detailed kinetic soot model described by Mauss [2]. The model includes a detailed description of the formation of polyaromatic hydrocarbons. The coupling between the turbulent flowfield and the soot model is achieved through a flamelet library approach, with transport of the moments of the soot particle size distribution function as outlined by Wenzel et al. [3]. In this work we extended this approach by considering acetylene feedback between the soot model and the combustion model. The model was further improved by using new gas-phase kinetics and new fitting procedures for the flamelet soot library.

Combination of an NOx storage and reduction catalyst (NSRC, called also lean NOx trap, LNT) and a catalyst for the selective catalytic reduction of NOx by NH₃ (NH₃-SCR) offers a potential to significantly increase the efficiency of NSRC-based exhaust gas aftertreatment systems. Under most situations the SCR catalyst is able to adsorb the NH₃ peaks generated in the NSRC during the regeneration and utilize it for additional NOx reduction in the course of the consequent lean phase. This synergy becomes more important with the aged NSRC, where generally lower NOx conversions and higher NH₃ yields in wider range of operating temperatures are observed (in comparison with the fresh or de-greened NSRC). In this paper we present global kinetic models for the NSRC (Pt/Ba/Ce/gγ-Al₂O₃ catalyst type) and NH₃-SCR (Fe-ZSM5 catalyst type).

Due to the increasingly stricter emission legislation and growing demands for lower fuel consumption, there have been significant efforts to improve combustion efficiency while satisfying the emission requirements. Homogeneous Charge Compression Ignition (HCCI) combined with turbo/supercharging on gasoline engines provides a particularly promising and, at the same time, a challenging approach. Naturally aspirated (n.a.) HCCI has already shown a considerable potential of about 14% in the New European Driving Cycle (NEDC) compared with a conventional 4-cylinder 2.0 liter gasoline Port Fuel Injection (PFI) engine without any advanced valve-train technology. The HCCI n.a. operation range is air breathing limited due to the hot residuals required for the self-ignition and to slow down reaction kinetics, and therefore is limited to a part-load operation area.

Regarding the strongly growing two-wheeler market fuel economy, price and emission legislations are in focus of current development work. Fuel economy as well as emissions can be improved by introduction of engine management systems (EMS). In order to provide the benefits of an EMS for low cost motorcycles, efforts are being made at BOSCH to reduce the costs of a port fuel injection (PFI) system. The present paper describes a method of how to reduce the number of sensors of a PFI system by the use of sophisticated software functions based on high-resolution engine speed evaluation. In order to improve the performance of a system working without a MAP-sensor (manifold air pressure sensor) an air charge feature (ACFn) based on engine speed is introduced. It is shown by an experiment that ACFn allows to detect and adapt changes in manifold air pressure. Cross-influences on ACFn are analyzed by simulations and engine test bench measurements.

Fuel economy of two-wheelers is an important factor influencing the purchasing psychology of the consumer within the emerging markets. Additionally, air pollution being a major environmental topic, there is a rising concern about vehicle emissions, especially in the big cities and their metropolitan areas. Potentially, the relatively expensive engine management systems are providing more features and value in comparison to the carburettor counterpart. The combustion system analysis is carried out on a 125 cm3 motorcycle engine and the subsequent numerical simulation comparing the carburettor and the Electronic (Port) Fuel Injection which provides a basis to establish the fuel consumption benefit for the electronic injection systems [1].

Due to the diversity of Heavy Duty Vehicles (HDV), the European CO2 and fuel consumption monitoring methodology for HDVs will be based on a combination of component testing and vehicle simulation. In this context, one of the key input parameters that need to be accurately defined for achieving a representative and accurate fuel consumption simulation is the vehicle's aerodynamic drag. A highly repeatable, accurate and sensitive measurement methodology was needed, in order to capture small differences in the aerodynamic characteristics of different vehicle bodies. A measurement methodology is proposed which is based on constant speed measurements on a test track, the use of torque measurement systems and wind speed measurement. In order to support the development and evaluation of the proposed approach, a series of experiments were conducted on 2 different trucks, a Daimler 40 ton truck with a semi-trailer and a DAF 18 ton rigid truck.

The spray-guided combustion process offers a high potential for fuel savings in gasoline engines in the part load range. In this connection, the injector and spark plug are arranged in close proximity to one another, as a result of which mixture formation is primarily shaped by the dynamics of the fuel spray. The mixture formation time is very short, so that at the time of ignition the velocity of flow is high and the fuel is still largely present in liquid form. The quality of mixture formation thus constitutes a key aspect of reliable ignition. In this article, the spray characteristics of an outward-opening piezo injector are examined using optical testing methods under pressure chamber conditions and the results obtained are correlated with ignition behaviour in-engine. The global spray formation is examined using high-speed visualisation methods, particularly with regard to cyclical fluctuations.

Equipping low cost two-wheelers with engine management systems (EMS) enables not only a reduction of emissions but also an improvement in fuel consumption and system robustness. These benefits are accompanied by initially higher system costs compared to carburetor systems. Therefore, intelligent software solutions are developed by Bosch, which enable a reduction of the necessary sensors for a port fuel injection system (PFI) and furthermore provide new possibilities for combustion control. One example for these intelligent software solutions is a model based evaluation of the engine speed. By use of the information contained in the engine speed signal, characteristic features like air charge, indicated mean effective pressure (imep) and combustion phasing are derivable. The present paper illustrates how these features could be used to reduce the system costs and to improve fuel consumption and system robustness.

Cost reduction of engine management systems (EMS) for two-wheeler applications is the key to utilize their potentials compared to carburetor bikes regarding emissions, fuel economy and system robustness. In order to reduce the costs of a system with port fuel injection (PFI) Bosch is developing an EMS without a manifold air pressure (MAP) sensor. The pressure sensor is usually used to compensate for different influences on the air mass, which cannot be detected via the throttle position sensor (TPS) and mean engine speed. Such influences are different leakage rates of the throttle body and changing ambient conditions like air pressure. Bosch has shown in the past that a virtual sensor relying on model based evaluation of engine speed can be used for a detection of leakage air mass in idling to improve the pre-control of the air-fuel ratio. This provides a functionality which so far was only possible with an intake pressure sensor.

This paper describes the possibility to resolve aeroacoustic feedback with a commercial 2nd/3rd order finite volume CFD code [1]. After a first comparison to a NACA 0012 test case, tonal noise components of a realistic automotive side view mirror are validated with in-house wind tunnel measurements. A zonal RANS/LES approach is used to ensure a realistic flow around the exterior side mirror mounted on a Mercedes-Benz passenger car. The provided compressible large eddy simulations are using non-reflecting boundary conditions in combination with a sponge zone approach to reduce hydrodynamic fluctuations and are in great accordance to measurements. The possibility of localizing and investigating the underlying feedback mechanism enables the chance for a targeted design of different appropriate remedies, which are finally confirmed by means of experimental comparison.

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.

With the reduction of engine and road noise, wind has become an important source of interior noise when cruising at highway speed. The challenges of weight reduction, performance improvement and reduced development time call for stronger support of the development process by numerical methods. Computational Fluid Dynamics (CFD) and finite element (FE) vibroacoustic computations have reached a level of maturity that makes it possible and meaningful to combine these methods for wind noise prediction. This paper presents a method used for coupling time domain CFD computations with a finite element vibroacoustic model of a vehicle for the prediction of low-frequency wind noise below 500 Hz. The procedure is based on time segmentation of the excitation load and transformation into the frequency domain for the vibroacoustic computations. It requires simple signal processing and preserves the random character as well as the spatial correlation of the excitation signal.

Aero-vibro-acoustic prediction of interior noise associated with exterior flow requires accurate predictions of both fluctuating surface pressures across the exterior of a vehicle and efficient models of the vibro-acoustic transmission of these surface pressures to the interior of a vehicle. The simulation strategy used in this paper combines both CFD and vibro-acoustic methods. An accurate excitation field (which accounts for both hydrodynamic and acoustic pressure fluctuations) is calculated with a hybrid CAA approach based on an incompressible unsteady flow field with an additional acoustic wave equation. To obtain the interior noise level at the driver's ears a vibro-acoustic model is used to calculate the response of the structure and interior cavities. The aero-vibro-acoustic simulation strategy is demonstrated for a Mercedes-Benz S-class and the predictions are compared to experimental wind tunnel measurements.

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.

A physically based model to predict the amount of snow which is entering the air intake of an automobile is extremely important for the automotive industry. It allows to improve the air intake system in the development state so that new vehicles can be developed in a shorter time. Using an Eulerian/Lagrangian approach within a commercial CFD-software we set up a model and calculated the snow ingress into an air intake of an automobile. In our numerical investigations we considered different particle shapes when calculating the drag coefficient, different coefficients of restitution and different particle sizes. Furthermore two-way coupling was considered. To obtain key parameters for the simulation, we measured the size of snow particles in the Daimler climatic wind tunnel in Sindelfingen by using a microscope and a measuring device from Malvern. Besides we used mechanical snow traps to determine the snow mass flux in the climatic wind tunnel and on a test area in Sweden.

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 future emission regulation (BS V) in India is expected to create new challenges to meet the particulate matter (PM) limit for diesel cars. The upcoming emission norms will bring down the limit of PM by 80 % when compared to BS IV emission norms. The diesel particulate filter (DPF) is one of the promising technologies to achieve this emission target. The implementation of DPF system into Indian market poses challenges against fuel quality, driving cycles and warranty. Hence, it is necessary to do a detailed on-road evaluation of the DPF system with commercially available fuel under country specific drive cycles. Therefore, we conducted full vehicle durability testing with DPF system which is available in the European market to evaluate its robustness and reliability with BS III fuel (≤350ppm sulfur) & BS IV (≤50ppm sulfur) fuel under real Indian driving conditions.

A simulation approach to predict the amount of snow which is penetrating into the air filter of the vehicle’s engine is important for the automotive industry. The objective of our work was to predict the snow ingress based on an Eulerian/Lagrangian approach within a commercial CFD-software and to compare the simulation results to measurements in order to confirm our simulation approach. An additional objective was to use the simulation approach to improve the air intake system of an automobile. The measurements were performed on two test sites. On the one hand we made measurements on a natural test area in Sweden to reproduce real driving scenarios and thereby confirm our simulation approach. On the other hand the simulation results of the improved air intake system were compared to measurements, which were carried out in a climatic wind tunnel in Stuttgart.