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Modern cars feature a variety of different driving assistance systems, which aim to improve driving comfort and safety as well as fuel consumption. Due to the technical advances and the possibility to consider vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication, cooperative adaptive cruise control (CACC) strategies have received significant attention from both research and industrial communities. The performance of such systems can be enhanced if the future velocity of the surrounding traffic can be predicted. Generally, human driving behavior is a complex process and influenced by several environmental impacts. In this work a stochastic model of the velocity of a preceding vehicle based on the incorporation of available information sources such as V2I, V2V and radar information is presented. The main influences on the velocity prediction considered in this approach are current and previous velocity measurements and traffic light signals.

At the moment, no equipment is available for fast measurements of particulate matter (PM) from production CI engines, especially during transients. Against this background, virtual sensors may be an option, provided their precision can be validated. This paper presents a new approach to estimate PM emission based only on in-cylinder pressure data. To this end, an in-cylinder pressure trace is measured with a high resolution (0.5 CAD) and every trace is divided into 8 segments according to critical cylinder events (e.g. opening of the valves or the beginning of injection). A piecewise principle component analysis (PCA) is used to compress the information. This information is then used for PM estimation via a second order polynomial model structure. The key element is the separate use of pressure trace information before and during the early stages of combustion. The model is parameterized by steady points and transient experiments which include parts of the FTP and the NEDC.

Virtual testing of advanced driver assistance systems (ADAS) using a simulation environment provides great potential in reducing real world testing and therefore currently much effort is spent on the development of such tools. This work proposes a simulation and hardware-in-the-loop (HIL) framework, which helps to create a virtual test environment for ADAS based on real world test drive. The idea is to reproduce environmental conditions obtained on a test drive within a simulation environment. For this purpose, a production standard BMW 320d is equipped with a radar sensor to capture surrounding traffic objects and used as vehicle for test drives. Post processing of recorded GPS raw data from the navigation system using an open source map service and the radar data allows an exact reproduction of the driven road including other traffic participants.

Transient emission peaks have become an important fraction of the total emissions during the standardized test cycles for passenger car Diesel engines. This paper is concerned with their reduction, in particular of nitric oxides (NOx) and particulate matter (PM) emissions, by online receding horizon optimal control. It is based on former works in which alternative target quantities for engine control were proposed, namely in-cylinder oxygen concentrations before (O2,BC) and after combustion (O2,AC). The actual work is concerned with testing an in-cylinder oxygen concentrations based control in simulation as well as by a real-time implementation on a turbocharged common rail passenger car production Diesel engine. The promising results confirm the choice of these concentrations as sensible control references and the feasibility of a real-time use in a model predictive control implementation.

Modeling the soot emissions of a Diesel engine is a challenge. Although it was part of many works before, it is still not a solved issue and has a substantial potential for improvement. A major problem is the presence of two competing effects during combustion, soot formation and soot oxidation, whereas only the cumulative difference of these effects can be measured in the exhaust. There is a wide consensus that it is sensible to design crank angle resolved models for both effects. Indeed, many authors propose crank angle based soot models which are mostly based on detailed first principles based structures, e.g. spray models, engine process calculations etc. Although these models are appealing from a theoretical point of view, they are all lacking of the required measurement information to validate all the complex model parts. Finally, most parts of the model remain at their assumed values and only a few parameters are used for calibration.

Measurements of transient emissions become more important due to the increasing contribution of transient operation to the total tail pipe emissions. While for many quantities measurement devices with response time in the range of few milliseconds exist, the same is not true for particulate matter(PM). Pulsed Laser Induced Incandescence (LII) is widely used in experimental setups and may offer a viable approach also for production engines, but the specific nature of LII raises doubts on the quantitative precision achievable by the method, especially in transient operation. Indeed, there are two main problems in particular for dynamic measurements. On one side, the emitted laser power must be high enough to excite a sufficiently large number of particles within the observed area, but not as high to destroy them, and varying engine operating conditions imply changes in the number and size distribution of the particles as well.

The Laser Induced Incandescence technique (LII) is a sensitive optical method for reliable spatially and temporally resolved measurement of particulate matter (PM) concentration. This technique appears to be suitable for measurement of fast transient PM emissions, from diesel engines, which forms the main fraction of total emissions during standardized test cycles. However, the existing commercial LII devices require modifications in the exhaust gas flow, dilution, sampling cell, or it measure only in a partial stream. This article presents the development of a laser based optical setup - LII for rapid in-situ measurement of PM concentrations during the combustion process of a diesel production engine. The presented LII setup is suitable for direct in-situ, full stream, measurements of soot emissions without needs of dilution or a sampling cell.

It is well known that driver behavior can affect fuel consumption to a large extent hence modifying it can lead to reasonable reduction in the magnitude of 10 to 20%. However, it is also known that effects of training are short lived and therefore many authors and companies suggest the use of monitoring systems, sometimes called eco-driver, which allow recognizing opportunities for reduction. V2V is an emerging technology which has been widely studied especially for safety applications. In terms of fuel consumption, there has also been a significant effort for methods directed to coordinate the movement of vehicles, especially of trucks, to improve fuel consumption by platooning [1].

This paper shows the potential of a multicalibration approach for reducing fuel consumption while keeping pollutant immissions. The paper demonstrates that the current engine control approach with a single fixed calibration involves important fuel penalties in areas with low vehicle densities where local pollution is not an issue, while the NOx emissions in urban areas are usually too high to fulfill air quality standards. The proposed strategy is based on using information about the vehicle location and the NOx concentrations in the ambient to choose a suitable calibration amongst a set of possibilities. To assess the potential of such a strategy experimental tests have been done with a state-of-art turbocharged Diesel engine. First, a design of experiments is used to obtain three different calibrations.

Pollutant immissions must be kept below some threshold values to prevent health and environmental damage. At the moment, the problem is usually met by constant emission limits for each vehicle independently from specific conditions - in particular, without any relation to the actual immission situation. This approach offers the advantage of simplicity, but offers no guarantee that the immission levels will be kept. New developments, in particular the expected diffusion of i2v methods, allows suggesting context specific emission levels so that the total emission roughly corresponding to the local immissions - can be limited to the target values. To meet this goal, emission-oriented control will be needed. This paper proposes a robust control system which allows tracking a time-varying NOx profile, based on the sliding mode concept.

Hybrid cars are a very interesting option for consumption and pollution reduction in urban areas, as they allow to reduce part load operation of the engine. The hybrid operation is based on the combination of two power sources, and it is well known that a sensible choice of the power split strategy can strongly influence the total consumption as well as the emissions. Therefore, control design is usually considered a critical issue. This paper, however, argues that it might be better not to fix a control structure, but to state the problem in terms of an optimization problem, without an a-priori control structure, and that this leads to better estimates of the achievable targets and in this way to better control results.

Adaptive cruise control (ACC) systems allow a safe and reliable driving by adapting the velocity of the vehicle to velocity setpoints and the distance from preceding vehicles. This substantially reduces the effort of the driver especially in heavy traffic conditions. However, standard ACC systems do not necessarily take in account comfort and fuel efficiency. Recently some work has been done of the latter aspect. This paper extends previous works for CI engines by incorporating a prediction model of the surrounding traffic and a simplified control law capable for real time use in experiments. The prediction model itself uses sinusoidal functions as the traffic measurements often show periodic behavior and is adapted in every sample instant with respect to the predecessor's velocity. Furthermore, the controlled vehicle is forced to stay within a specific inter-vehicle distance corridor to avoid collisions and ensure safe driving.

The emissions of modern Diesel engines, which are known to have various health effects, are beside the drivers torque demands and low fuel consumptions one of the most challenging issues for combustion and after treatment control. To comply with legal requirements, emission control for heavy duty engines is not feasible without additional hardware, usually consisting of a Diesel oxidation catalyst (DOC), a Diesel particulate filter (DPF) and a selective catalytic reduction (SCR) system. In contrast to other NOx reduction systems, e.g. lean NOx traps, the SCR system requires an additional ingredient, namely ammonia (NH3), to reduce the NOx emissions to non harmful components. Consequently, the correct amount of NH3 dosing in the SCR catalyst is one of the critical components to reach high conversion rates and avoid ammonia slip.

The focus in the development of modern exhaust after treatment systems, like the Diesel Oxidation Catalyst (DOC), the Diesel Particulate Filter (DPF) and Selective Catalytic Reduction (SCR), is to increase on one hand the oxidation rates of Carbon monoxide (CO), HC (Hydro Carbons) and NO (Nitrogen Oxide) and on the other hand the reduction rates of Particulate Matter (PM) and the NOx emissions to fulfill the more and more restricting requirements of the exhaust emission legislation. The simplest, practical most relevant way to obtain such a dosing strategy of a SCR system is the use of a nonlinear map, which has to be determined by extensive calibration efforts. This feedforward action has the advantage of not requiring a downstream NOx sensor and can achieve high conversion efficiency under steady-state operating conditions for nominal systems.

Computation of combustion, in particular of emissions over crank angle, relies on chemical oriented models. In some cases, chemical equilibrium can be assumed, as chemical reaction time scales tend to be fast compared to the crank rotation, so the rather complex reaction kinetics can be neglected. For engine process calculation based on the measured cylinder pressure chemical equilibrium concentrations are needed for every crank angle or calculation time step. On the one hand the equilibrium concentrations are necessary for estimating the thermodynamic properties of the working gas (internal energy and specific gas constant) which are needed for deriving the energy release (burn rate) and on the other hand the obtained concentrations are inputs for crank angle based soot and nitric oxygen emission models which depends also on the engine process calculation results.

This paper presents a detailed optical and thermodynamic analysis of effects which influences the soot formation and oxidation process during Diesel combustion. To measure the actual soot concentration over crank angle an optical sensor was installed on the engine. In combination with a thermodynamic engine process calculation, based on the measured cylinder pressure, several important effects are analyzed and described in detail. The main focus of the paper is to produce knowledge on how soot dynamics is influenced by changed engine control unit (ECU) calibration parameters. A modern 4 cylinder production car Diesel engine was used for the studies, which offers a lot of opportunities to influence combustion by varying injection timing and air path ECU parameters. As a consequence discussion is done on how the analyzed effects are treated by published 0-dimensional simulation models with focus on later control and optimization application.