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The present contribution gives an overview of the use of different simulation tools for the optimization of injection parameters of a diesel engine. With a one-dimensional tool, the behavior of the mechanics and fluid dynamics of the entire injection system is calculated. This simulation provides information on the dynamic needle lift, injection rates, pressures, etc. The flow within the injector is simulated using a three-dimensional CFD tool. By use of a two-phase model, it is possible to analyze the cavitating flow inside the injector and to calculate the effective nozzle hole area as well as the exit flow characteristics. Mixture formation, combustion and pollutant formation simulation is performed adopting three-dimensional CFD. In order to provide the initial and boundary conditions for the engine CFD simulation and to optimize the engine cycle performance a one-dimensional tool is adopted.

A calibration and validation workflow will be presented in this paper, which utilizes common static global models for fuel consumption, NOx and soot. Due to the applicability for warm-up tests, e.g. New European Driving Cycle (NEDC), the models need to predict the temperature influence and will be fitted with measuring data from a conditioned engine test bed. The applied model structure consisting of a number of global data-based sub-models is configured especially for the requirements of multi-injection strategies of common rail systems. Additionally common global models for several constant coolant water temperature levels are generated and the workflow tool supports the combination and segmentation of global nominal map with temperature correction maps for seamless and direct ECU setting.

Eliminating toxic exhaust emissions, amongst them particulate matter (PM), is one of the driving factors behind the increasing use of electrified vehicles. However, it is frequently overseen that PM arise not only from combustion, but from non-exhaust traffic related causes as well; in particular from the vehicle brakes, tires and the road surface. Furthermore, as electrified vehicles weigh more and typically exhibit higher torques at low speeds, their non-exhaust emissions tend to be higher than for comparable conventional vehicles, especially those generated by tires. Fortunately, tire related emissions are directly related to tire wear, so that limiting tire wear can reduce these emissions as well. This can be accomplished by intelligently modulating the vehicle torque profile in real time, to limit the operation in conditions of higher tire wear.

The measurement of the particle number (PN) concentration of non-volatile particles ≻23 nm was introduced in the light-duty vehicles regulation; the heavy-duty regulation followed. Based on the findings of the Particle Measurement Program (PMP), heavy-duty inter-laboratory exercise, the PN concentration measurement can be conducted either from the full dilution tunnel with constant volume sampling (CVS) or from the partial flow dilution system (PFDS). However, there are no other studies that investigate whether the PN results from the two systems are equivalent. In addition, even the PMP study never investigated the uncertainty that is introduced at the final result from the extraction of a flow by a PN system from the PFDS. In this work we investigate the uncertainty for the three possible cases, i.e., considering a constant extracted flow from the PFDS, sending a signal with 1 Hz frequency to the PFDS, or feeding back the extracted flow to the PFDS.

This paper describes a method for optimization of engine settings in view of best total cost of operation fluids. Under specific legal NOX tailpipe emissions requirements the engine out NOX can be matched to the current achievable SCR NOX conversion efficiency. In view of a heavy duty long haul truck application various specific engine operation modes are defined. A heavy duty diesel engine was calibrated for all operation modes in an engine test cell. The characteristics of engine operation are demonstrated in different transient test cycles. Optimum engine operation mode (EOM) selection strategies between individual engine operation modes are discussed in view of legal test cycles and real world driving cycles which have been derived from on-road tests.

The reduction of particulate emissions limits requires new tools for the tuning of engines and exhaust aftertreatment systems. Time-resolved monitoring of low soot emissions is a key feature for such developments. The paper describes an improved photoacoustic soot sensor, and presents its applications for the characterization of transient exhaust soot emissions before and after Diesel emission after-treatment systems. The detection limit of the unit is around 5 μg/m3 soot, which is two orders of magnitude better than conventional time-resolved transmission measurement. Additionally, a wide dynamic range of four orders of magnitude can be achieved without range switching. The photoacoustic signal is proportional to the soot mass, no significant cross-sensitivities to gaseous absorbers were detected.

Future legislation, like EURO IV and EURO V or the US 2007 HD regulation will have massive reduction of particulate emission limits. For this beside improvement of engine combustion also exhaust aftertreatment systems are under investigation, like Diesel Particulate Filters (DPF), or Selective Catalytic Reduction (SCR) of Nitrogen Oxides. For all those tasks transient soot emission monitoring is one of the key features. To meet this demand a new device for the on-line measurement of soot emitted by combustion engines has been developed. Based on the photoacoustic principle, which has been optimized for automotive applications and easy use in test cells, the instrument shows a sensitivity of 5μg/m3, which is lower than current particulate immission standards in ambient air, and a time resolution of 1 sec. In the paper first the principles of measurement are shown, and then the specifications and results from measurements of very low soot concentration in the exhaust gas are presented.

Automotive embedded systems have become very complex, are strongly integrated, and the safety-criticality and real-time constraints of these systems raise new challenges. The OSEK/VDX standard provides an open-ended architecture for distributed real-time capable units in vehicles. This is supported by the OSEK Implementation Language (OIL), a language aiming at specifying the configuration of these real-time operating systems. The challenge, however, is to ensure consistency of the concept constraints and configurations along the entire product development. The contribution of this paper is to bridge the existing gap between model-driven systems engineering and software engineering for automotive real-time operating systems (RTOS). For this purpose a bidirectional tool bridge has been established based on OSEK OIL exchange format files.

Trends towards lower vehicle fuel consumption and smaller environmental impact will increase the share of Diesel hybrids and Diesel Range Extended Vehicles (REV). Because of the Diesel engine presence and the ever tightening soot particle emissions, these vehicles will still require soot particle emissions control systems. Ceramic wall-flow monoliths are currently the key players in the Diesel Particulate Filter (DPF) market, offering certain advantages compared to other DPF technologies such as the metal based DPFs. The latter had, in the past, issues with respect to filtration efficiency, available filtration area and, sometimes, their manufacturing cost, the latter factor making them less attractive for most of the conventional Diesel engine powered vehicles. Nevertheless, metal substrate DPFs may find a better position in vehicles like Diesel hybrids and REVs in which high instant power consumption is readily offered enabling electrical filter regeneration.

Current developments in automotive industry such as hybrid powertrains and the continuously increasing demands on emission control systems, are pushing complexity still further. Validation of such systems lead to a huge amount of test cases and hence extreme testing efforts on the road. At the same time the pressure to reduce costs and minimize development time is creating challenging boundaries on development teams. Therefore, it is of utmost importance to utilize testing and validation prototypes in the most efficient way. It is necessary to apply high levels of instrumentation and collect as much data as possible. And a streamlined data pipeline allows the fleet managers to get new insights from the raw data and control the validation vehicles as well as the development team in the most efficient way. In this paper we will demonstrate a data-driven approach for validation testing.