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Active prechamber combustion systems for SI engines represent a feasible and effective solution in reducing fuel consumption and pollutant emissions for both marine and ground heavy-duty engines. However, reliable and low-cost numerical approaches need to be developed to support and speed-up their industrial design considering their geometry complexity and the involved multiple flow length scales. This work presents a CFD methodology based on the RANS approach for the simulation of active prechamber spark-ignition engines. To reduce the computational time, the gas exchange process is computed only in the prechamber region to correctly describe the flow and mixture distributions, while the whole cylinder geometry is considered only for the power-cycle (compression, combustion and expansion). Outside the prechamber the in-cylinder flow field at IVC is estimated from the measured swirl ratio.

An advanced catalytic exhaust after-treatment system addresses the problem of NOX emissions from heavy-duty diesel trucks, relying on real-time catalyst modelling. The system consists of de-NOX catalysts, a device for injection of a reducing agent (diesel fuel) upstream the catalysts, and computer programmes to control the injection of the reducing agent and to model the engine and catalysts in real time. Experiments with 5 different air-assisted injectors were performed to determine the effect of injector design on the distribution of the injected diesel in the exhaust gas stream. A two-injector set-up was investigated to determine whether system efficiency could be increased without increasing the amount of catalyst or the amount of reducing agent necessary for the desired outcome. The results were verified by performing European standard transient cycle tests as well as stationary tests.

In the truck industry there is a continuous demand to increase the efficiency and to decrease the emissions. To acknowledge both these issues a waste heat recovery system (WHR) is combined with a partially premixed combustion (PPC) engine to deliver an efficient engine system. Over the past decades numerous attempts to increase the thermal efficiency of the diesel engine has been made. One such attempt is the PPC concept that has demonstrated potential for substantially increased thermal efficiency combined with much reduced emission levels. So far most work on increasing engine efficiency has been focused on improving the thermal efficiency of the engine while WHR, which has an excellent potential for another 1-5 % fuel consumption reduction, has not been researched that much yet. In this paper a WHR system using a Rankine cycle has been developed in a modeling environment using IPSEpro.

Emissions and in-cylinder pressure traces are used to compare the relative importance of soot formation and soot oxidation in a heavy-duty diesel engine. The equivalence ratio at the lift-off length is estimated with an empirical correlation and an idealized model of diesel spray. No correlation is found between the equivalence ratio at lift-off and the soot emissions. This confirms that trends in soot emissions cannot be directly understood by the soot formation process. The coupling between soot emission levels and late heat release after end of injection is also studied. A regression model describing soot emissions as function of global engine parameters influencing soot oxidation is proposed. Overall, the results of this analysis indicate that soot emissions can be understood in terms of the efficiency of the oxidation process.

The present work describes the numerical modeling of medium-speed marine engines, operating in a fumigated dual-fuel mode, i.e. with the second fuel injected in the ports. This engine technology allows reducing engine-out emissions while maintaining the engine efficiency and can be fairly easily retrofitted from current diesel engines. The main premixed fuel that is added can be a low-carbon one and can additionally be of a renewable nature, thereby reducing or even completely removing the global warming impact. To fully optimize the operational parameters of such a large marine engine, computational fluid dynamics can be very helpful. Accurately describing the combustion process in such an engine is key, as the prediction of the heat release and the pollutant formation is crucial. Auto-ignition of the diesel fuel needs to be captured, followed by the combustion and flame propagation of the premixed fuel.

Increased research is being driven by the automotive industry facing challenges, requiring to comply with both current and future emissions legislation, and to lower the fuel consumption. The reason for this legislation is to restrict the harmful pollution which every year causes 3.3 million premature deaths worldwide [1]. One factor that causes this pollution is NOx emissions. NOx emission legislation has been reduced from 8 g/kWh (Euro I) down to 0.4 g/kWh (Euro VI) and recently new legislation for ammonia slip which increase the challenge of exhaust aftertreatment with a SCR system. In order to achieve a good NOx conversion together with a low slip of ammonia, small droplets of Urea solution needs to be injected which can be rapidly evaporated and mixed into the flow of exhaust gases.

In the automotive industry, the piezo-based in-cylinder pressure sensor is getting commercialized and used in production vehicles. For example, the pressure sensor offers the opportunity to design algorithms for estimation of engine emissions, such as soot and NO , during a combustion cycle. In this paper a zero-dimensional NO model for a diesel engine is implemented that will be used in real time. The model is based on the thermal NO formation and the Zeldovich mechanism using two non-geometrical zones: burned and unburned zone. The influence of EGR on combustion temperature was modeled using a well-known thermodynamic identity where specific heat at constant pressure is included. Specific heat will vary with temperature and the gas composition. The model was implemented in LabVIEW using tools specific for an FPGA (Field-Programmable Gate Array).

The focus on engine thermal management is rapidly increasing due to the significant effect of heat losses on fuel consumption, engine performance and emissions. This work presents a time resolved, high resolution 3D engine heat balance model, including all relevant components. Notably, the model calculates the conjugated heat transfer between the solid engine components, the coolant and the oil. Both coolant and oil circuits are simultaneously resolved with a CFD solver in the same finite volume model as the entire engine solid parts. The model includes external convection and radiation. The necessary boundary conditions of the thermodynamic cycle (gas side) are mapped from a calibrated 1D gas exchange model of the same engine. The boundary conditions for the coolant and at the oil circuits are estimated with 1D models of the systems. The model is calibrated and verified with measurement data from the same engine as modeled.

As the number of actuators and sensors increases in modern combustion engines, the task of optimizing engine performance becomes increasingly complex. Efficient information processing techniques are therefore important, both for off-line calibration of engine maps, and on-line adjustments based on sensor data. In-cylinder pressure sensors are slowly spreading from laboratory use to production engines, thus making data with high temporal resolution of the combustion process available. The standard way of using the cylinder pressure data for control and diagnostics is to focus on a few important physical features extracted from the pressure trace, such as the combustion phasing CA50, the indicated mean effective pressure IMEP, and the ignition delay. These features give important information on the combustion process, but much information is lost as the information from the high-resolution pressure trace is condensed into a few key parameters.

While striving for more fuel-efficient vehicles, all possible measures are considered to increase the efficiency of the combustion engine powertrain. 48V mild hybrid technology is one such measure, SIDI (Spark Ignited Direct Injection) engines with Miller technology are another, while recovering energy from the engine’s waste heat (WHR) is yet another option. In this paper, results will be published from an advanced engineering project at Volvo Cars including all of these components. An ethanol based Organic Rankine Cycle (ORC) WHR-system was successfully built around a 4-cylinder, 2.0 litre SIDI-engine, including 48V mild hybrid technology, with vehicle packaging considered. A dedicated control system was also developed for the ORC system including communication between it and the engine. The ORC system uses the engine exhaust as the heat source, for which a purpose-built evaporator was designed and built to fit in the vehicle tunnel.

The combustion timing in internal combustion engines affects the fuel consumption, in-cylinder peak pressure, engine noise and emission levels. The combination of an in-cylinder pressure sensor together with a direct injection fuel system lends itself well for cycle-to-cycle control of the combustion timing. This paper presents a method of controlling the combustion timing by the use of a cycle-to-cycle injection-timing algorithm. At each cycle the currently estimated heat-release rate is used to predict the in-cylinder pressure change due to a combustion-timing shift. The prediction is then used to obtain a cycle-to-cycle model that relates combustion timing to gross indicated mean effective pressure, max pressure and max pressure derivative. Then the injection timing that controls the combustion timing is decided by solving an optimization problem involving the model obtained.

In this paper, computation fluid dynamics (CFD) simulations are employed to describe the effect of flow parameters on the formation of soot and NOx in a heavy duty engine under low load and high load. The complexity of diesel combustion, specially when soot, NOx and other emissions are of interest, requires using a detailed chemical mechanism to have a correct estimation of temperature and species distribution. In this work, Multiple Representative Interactive Flamelets (MRIF) method is employed to describe the chemical reactions, ignition, flame propagation and emissions in the engine. A phenomenological model for soot formation, including soot nucleation, coagulation and oxidation with O2 and OH is incorporated into the flamelet combustion model. Different strategies for modelling NOx are chosen to take into account the longer time scale for NOx formation. The numerical results are compared with experimental data to show the validity of the model for the cases under study.

A previously presented robust and fast diagnostic NOx model was modified into a predictive model. This was done by using simple yet physically-based models for fuel injection, ignition delay, premixed heat release rate and diffusion combustion heat release rate. The model can be used both for traditional high temperature combustion and for high-EGR low temperature combustion. It was possible to maintain a high accuracy and calculation speed of the NOx model itself. The root mean square of the relative model error is 16 % and the calculation speed is around one second on a PC. Combustion characteristics such as ignition delay, CA50 and the general shape of the heat release rate are well predicted by the combustion model. The model is aimed at real time NOx calculation and optimization in a vehicle on the road.

Volvo Car Corporation has developed a Reference Architecture for PAG1 Infotainment Systems. A Reference Architecture is an architecture scoping over more than a single system, i.e. an architecture aimed for a family of systems. The Infotainment Reference Architecture has since 2001 been successfully applied for the PAG family which so far covers the infotainment systems of Volvo XC90, Volvo S40/V50, Jaguar XK, Aston Martin DB9 and the brand new Volvo S80. In 1999, the system design departments started up with the clear objective to develop a system solution aiming for the PAG infotainment system family. The work was carried out according to the established development process at Volvo Cars. A year later a discouraging design review was performed. The number of involved functions, the level of function interaction and the distribution of functionalities between ECUs resulted in a non-manageable system solution.

The use of Selective Catalytic Reduction (SCR) is becoming increasingly more popular as a way of reducing NOx emissions from heavy duty vehicles while maintaining competitive operating costs. In order to make efficient use of these systems, it's important to have a complete system approach when it comes to calibration of the engine and aftertreatment system. This paper presents a simplified model of a heavy duty SCR catalyst, primarily intended for use in combination with an engine-out emissions model to perform model based offline optimization of the complete system. The traditional way of modelling catalysts using a dense discretization of the catalyst channels and non-linear differential equation solvers to solve the heat and mass balance equations, requires too much computational power in this application. The presented model is also useful in other applications such as model based control.

The development and implementation of a new structure for data-driven models for NOX and soot emissions is described. The model structure is a linear regression model, where physically relevant input signals are used as regressors, and all the regression parameters are defined as grid-maps in the engine speed/injected fuel domain. The method of using grid-maps in the engine speed/injected fuel domain for all the regression parameters enables the models to be valid for changes in physical parameters that affect the emissions, without having to include these parameters as input signals to the models. This is possible for parameters that are dependent only on the engine speed and the amount of injected fuel. This means that models can handle changes for different parameters in the complete working range of the engine, without having to include all signals that actually effect the emissions into the models.

Analysis of pressure pulsations in ducts is an active research field within the automotive industry. The fluid dynamics and the wave transmission properties of internal combustion (IC) engine intake and exhaust systems contribute to the energy efficiency of the engines and are hence important for the final amount of CO₂ that is emitted from the vehicles. Sound waves, originating from the pressure pulses caused by the in- and outflow at the engine valves, are transmitted through the intake and exhaust system and are an important cause of noise pollution from road traffic at low speeds. Reliable prediction methods are of major importance to enable effective optimization of gas exchange systems. The use of nonlinear one-dimensional (1D) gas dynamics simulation software packages is widespread within the automotive industry. These time-domain codes are mainly used to predict engine performance parameters such as output torque and power but can also give estimates of radiated orifice noise.

The emission control in heavy-duty vehicles today is based on predefined injection strategies and after-treatment systems such as SCR (selective catalytic reduction) and DPF (diesel particulate filter). State-of-the-art engine control is presently based on cycle-to-cycle resolution. The introduction of the crank angle resolved pressure measurement, from a piezo-based pressure sensor, enables the possibility to control the fuel injection based on combustion feedback while the combustion is occurring. In this paper a study is presented on the possibility to control NOx (nitrogen oxides) formation with a crank angle resolved NOx estimator as feedback. The estimator and the injection control are implemented on an FPGA (Field-Programmable Gate Array) to manage the inherent time constraints. The FPGA is integrated with the rest of the engine control system for injection control and measurement.

In recent years, stricter regulations on emissions and higher demands for more fuel efficient vehicles have led to a greater focus on increasing the efficiency of the internal combustion engine. Nowadays, there is increasing interest in the recovery of waste heat from different engine sources such as the coolant and exhaust gases using, for example, a Rankine cycle. In diesel engines 15% to 30% of the energy from the fuel can be lost to the coolant and hence, does not contribute to producing work on the piston. This paper looks at reducing the heat losses to the coolant by increasing coolant temperatures within a single cylinder Scania D13 engine and studying the effects of this on the energy balance within the engine as well as the combustion characteristics. To do this, a GT Power model was first validated against experimental data from the engine.

An acoustic one-dimensional compressor model has been developed. This model is based on compressor map information and it is able to predict how the pressure waves are transmitted and reflected by the compressor. This is later on necessary to predict radiated noise at the intake orifice. The fluid-dynamic behavior of the compressor has been reproduced by simplifying the real geometry in zero-dimensional and one-dimensional elements with acoustic purposes. These elements are responsible for attenuating or reflecting the pressure pulses generated by the engine. In order to compensate the effect of these elements in the mean flow variables, the model uses a corrected compressor map. Despite of the fact that the compressor model was developed originally as a part of the OpenWAM™ software, it can be exported to other commercial wave action models. An example is provided of exporting the described model to GT-Power™.