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During transients, engines tend to produce substantially higher peak emissions like soot - the main fraction of particular matter (PM) - which are the longer the more important as the steady state emissions are better controlled. While Diesel particulate filters are normally able to block them, preventing their occurrence would of course be more important. In order to achieve this goal, however, they must be measurable. While for most emissions commercial sensors of sufficient speed and performance are available, the same is not true for PMs, especially for production engines. Against this background, in the last years the possible use of a full stream 50Hz sensor based on Laser Induced Incandescence (LII) was investigated, and the results were very encouraging, showing that the sensor could recognize transient changes undetected by conventional measurement systems (like the AVL Opacimeter) but confirmed by the analysis of combustion.

Abatement and control of emissions from passenger car combustion engines have been in the focus for a long time. Nevertheless, to address upcoming real-world driving emission targets, knowledge of current engine emissions is crucial. Still, adequate sensors for transient emissions are seldom available in production engines. One way to target this issue is by applying virtual sensors which utilize available sensor information in an engine control unit (ECU) and provide estimates of the not measured emissions. For real-world application it is important that the virtual sensor has low complexity and works under varying conditions. Naturally, the choice of suitable inputs from all available candidates will have a strong impact on these factors. In this work a method to set up virtual sensors by means of design of experiments (DOE) and iterative identification of polynomial models is augmented with a novel input candidate selection strategy.

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.

Especially in view of more and more stringent emission legislation in passenger cars it is required to reduce the amount of pollutants. In the case of Diesel engines mainly NOx and PM are emitted during engine operation. The main influence factors for these pollutants are the in-cylinder oxygen concentration and the injected fuel amount. Typically the engine control task can be divided into two separate main parts, the fuel and the air system. Commonly air system control, consisting of a turbocharger and exhaust gas recirculation control, is used to provide the required amount of oxygen and address the emission targets, whereas the fuel is used to provide the desired torque. Especially in transient maneuvers the different time scales of both systems can lead to emission peaks which are not desired. Against this background in this work instead of the common way to address the air system, the fuel system is considered to reduce emission peaks during transients.

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.

Modern Diesel engines have become complex systems with a high number of available sensor information and degrees of freedom in control. Due to recent developments in production type in-cylinder pressure sensors, there is again an upcoming interest for in-cylinder pressure based applications. Besides the standard approaches, like to use it for closed loop combustion control, also estimation and on-board diagnostics have become important topics. Not surprising in general the trend is to utilize those sensors for as many tasks as possible. Consequently this work focuses on the estimation of the injection parameters based on the indicated pressure signal information which can be seen as first step of a combustion control based on desirable indicated pressure characteristics which may be utilized for e.g. the minimization of NOx emissions. Currently the acquisition of the cylinder pressure traces can be done in real-time by fast FPGA (Field Programmable Gate Array) based systems.

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.

Although SCR is a well established technology for many applications, it is still a field in which several new approaches and components are being tested. Control is a critical issue, as the conflicting requirements of NOx abatement and very small NH3 slip need to be met. Besides empirical solutions, model based controls have been proposed and are probably the technology of choice, also in view of the combination with monitoring functions. However, SCR models are typically based on First Principles (FP), i.e. on global chemical equations and reaction rate equations, and require precise calibration. Still, their performance for the control of dynamic processes is limited, or a high detail, much a priori information, e.g. on the actual SCR reaction rates, are needed. Frequently, this information is not available or reliable, and this is particularly true when components are changed or modified during the development process, so that typically a re-design is needed.

Although the application of cylinder pressure sensors to gain insight into the combustion process is not a novel topic itself, the recent availability of inexpensive in-cylinder pressure sensors has again prompted an upcoming interest for the utilization of the cylinder pressure signal within engine control and monitoring. Besides the use of the in-cylinder pressure signal for combustion analysis and control the information can also be used to determine related quantities in the exhaust or intake manifold. Within this work two different methods to estimate the pressure inside the exhaust manifold are proposed and compared. In contrary to first principle based approaches, which may require time extensive parameterization, alternative data driven approaches were pursued. In the first method a Principle Component Analysis (PCA) is applied to extract the cylinder pressure information and combined with a polynomial model approach.

In a typical diesel engine exhaust aftertreatment system consisting of a diesel oxidation catalyst (DOC), a diesel particulate filter (DPF) and a selective catalytic reduction (SCR) system the main purpose of the DOC, besides the oxidation of CO to CO₂, is the oxidation of NO to NO₂. The NO to NO₂ conversion is an essential contribution for the downstream SCR system because the fast SCR reaction which provides the highest conversion rates of NOx to H₂O and N₂ works well only under roughly equal concentrations of NO and NO₂. The typical amount of NO to NOx ratio produced by the engine is about 0.95, hence the DOC is necessary to decrease this coefficient close to 0.50. Due to the temperature dependency of the DOC reaction mechanism the oxidation of NO to NO₂ takes only place sufficiently if the temperature of the DOC is higher than 200°C, which, however, cannot be reached during low engine speed and low load situations.

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.

NOx and PM are the critical emissions to meet the legislation limits for diesel engines. Often a value for these emissions is needed online for on-board diagnostics, engine control, exhaust aftertreatment control, model-based controller design or model-in-the-loop simulations. Besides the obvious method of measuring these emissions, a sensible alternative is to estimate them with virtual sensors. A lot of literature can be found presenting different modeling approaches for NOx emissions. Some are very close to the physics and the chemical reactions taking place inside the combustion chamber, others are only given by adapting general functions to measurement data. Hence, generally speaking, there is not a certain method which is seen as the solution for modeling emissions. Finding the best model approach is not straightforward and depends on the model application, the available measurement channels and the available data set for calibration.

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.

Transient emission peaks have become an important fraction of the total emissions during the standardized test cycles for passenger car Diesel engines. To this end this paper is concerned with the challenge of measuring emissions during transients. The importance of this topic is increasing due to strict regulation on pollutant emissions. Hence, suitably accurate and fast measurement devices for PM emission detection are required. Thus, we present a comparison between different measurement techniques for Particulate matter (PM) emissions from a Diesel engine, in particular during transients. The compared equipments include AVL Micro soot sensor, AVL Opacimeter, Differential mobility spectrometer and Laser induced incandescence. The goal of this paper is to reveal the most accurate device in the sense of sensitivity and dynamics for fast measurements of PM from a Diesel engine.

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.

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.

Nitrogen oxide (NOx) sensing is required both for on-board diagnosis and optimal selective catalytic reduction (SCR)-catalyst control in heavy duty diesel engines. This can be accomplished either by physical solid-state sensors, or by so-called virtual sensors, which estimate the value of the target quantity using other states by means of a model. Both approaches have advantages and disadvantages. This paper resumes the derivation and the identification of a virtual sensor based on a polynomial structure and optimal experimental design methods and compares its performance to the one of a production physical solid state sensor. The virtual sensor is compared with a commercially available solid-state sensor in terms of accuracy (stationary as well as dynamic) and operation limits.

Complexity and nonlinearity of engines makes precise first principle engine models often difficult to obtain, as for instance for emissions. System identification is a well known possible alternative, successfully used in several automotive applications. In most cases system identification is concerned with the estimation of the unknown parameters of a known set of equations. Unfortunately, for many engine subsystems, there is no sufficiently precise or real time suitable model. This paper presents a sequential algorithm which allows to derive real time suitable models on line by a combination of model structure hypothesis of increasing complexity and an associated optimal input design and selection process. This paper introduces the method and shows its use both for a rather simple and a very difficult engine identification task, a dynamical model of the airpath of a Diesel engine and a dynamical model of nitrogen oxides and particulate matter.

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 for nitric oxides (NOx) and particulate matter (PM) emissions, by online optimization. It is based on a former work [1] in which alternative target quantities for engine control were proposed, namely in-cylinder oxygen concentrations before (O2,BC) and after combustion (O2,AC). A generic nonlinear optimization is applied to provide a systematic determination for the optimal trajectories of these oxygen target quantities during a transient torque maneuver. The proposed method was implemented on a dynamic engine test bed using a production passenger car Diesel engine for the objective function evaluation. Torque response could be maintained unchanged while NOx as well as PM emission peaks were reduced significantly.

Due to the advancements in passenger car Diesel engine design, the contribution of transient emission spikes has become an important fraction of the total emissions during the standardized test cycles, hence the interest of this work on dynamical engine operation, in particular on the improvement of NOX and PM emissions. This paper proposes to use a UEGO sensor (universal exhaust gas oxygen sensor) in the upstream of the turbine in combination with a Kalman filter to estimate the target quantities, namely in-cylinder oxygen concentration before and after combustion. This information is used to define the fuel injection as well as the values of the air path actuators. Test bench measurements with a production Diesel engine are presented, where the oxygen based approach is compared to the standard calibration during a fast load increase. It is shown that the torque response could be maintained while NOX as well as PM emission peaks were reduced significantly.