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A 2007 Cummins ISL 8.9L direct-injection common rail diesel engine rated at 272 kW (365 hp) was used to load the filter to 2.2 g/L and passively oxidize particulate matter (PM) within a 2007 OEM aftertreatment system consisting of a diesel oxidation catalyst (DOC) and catalyzed particulate filter (CPF). Having a better understanding of the passive NO2 oxidation kinetics of PM within the CPF allows for reducing the frequency of active regenerations (hydrocarbon injection) and the associated fuel penalties. Being able to model the passive oxidation of accumulated PM in the CPF is critical to creating accurate state estimation strategies. The MTU 1-D CPF model will be used to simulate data collected from this study to examine differences in the PM oxidation kinetics when soy methyl ester (SME) biodiesel is used as the source of fuel for the engine.

Flow noise produced by the turbulent motion of the exhaust gases is one of the main contributions to the noise generation for a heavy-duty vehicle. The exhaust system has therefore to be optimized since the early stages of the design to improve the engine’s Noise Vibration Harshness (NVH) performance and to comply with legislation noise limits. In this context, the availability of reliable Computational Aero-Acoustics (CAA) methodologies is crucial to assess the noise mitigation potential of different exhaust system designs. In the present work, a characterization of the sound generation in a heavy-duty exhaust system was carried out evaluating the noise attenuation potential of a design modification, by means of a hybrid CAA methodology.

Worldwide regulations concerning noise emissions of road vehicles are constantly demanding further reductions of acoustic emissions, which are considered a major environmental health concern in several countries. Among the different sources contributing to noise generation in vehicles equipped with internal combustion engines, exhaust flow noise is one of the most significant, being generated by turbulence development in the exhaust gases, and robust and reliable numerical methodologies for its prediction in early design phases are currently still needed. To this extent, Computational Aero-Acoustics (CAA) can be considered a valuable approach to characterize the physical mechanisms leading to flow noise generation and its propagation, and it could therefore be used to support exhaust system development prior to the execution of experimental testing campaigns.

The turbulent flow field inside the cylinder plays a major role in spark ignition (SI) engines. Multiple phenomena that occur during the high pressure part of the engine cycle, such as early flame kernel development, flame propagation and gas-to-wall heat transfer, are influenced by in-cylinder turbulence. Turbulence inside the cylinder is primarily generated via high shear flows that occur during the intake process, via high velocity injection sprays and by the destruction of macro-scale motions produced by tumbling and/or swirling structures close to top dead center (TDC) . Understanding such complex flow phenomena typically requires detailed 3D-CFD simulations. Such calculations are computationally very expensive and are typically carried out for a limited number of operating conditions. On the other hand, quasi-dimensional simulations, which provide a limited description of the in-cylinder processes, are computationally inexpensive.

The selection and tuning of the Fuel Injection System (FIS) are among the most critical tasks for the automotive diesel engine design engineers. In fact, the injection strongly affects the combustion phenomena through which controlling a wide range of related issues such as pollutant emissions, combustion noise and fuel efficiency becomes feasible. In the scope of the engine design optimization, the simulation is an efficient tool in order to both predict the key performance parameters of the FIS, and to reduce the amount of experiments needed to reach the final product configuration. In this work a complete characterization of a solenoid ballistic injector for a Light-Duty Common Rail system was therefore implemented in a commercially available one-dimensional computational software called GT-SUITE. The main phenomena governing the injector operation were simulated by means of three sub-models (electro-magnetic, hydraulic and mechanical).

One of the key technologies for the improvement of the diesel engine thermal efficiency is the reduction of the engine heat transfer through the thermal insulation of the combustion chamber. This paper presents a numerical investigation on the effects of the combustion chamber insulation on the heat transfer, thermal efficiency and exhaust temperatures of a 1.6 l passenger car, turbo-charged diesel engine. First, the complete insulation of the engine components, like pistons, liner, firedeck and valves, has been simulated. This analysis has showed that the piston is the component with the greatest potential for the in-cylinder heat transfer reduction and for Brake Specific Fuel Consumption (BSFC) reduction, followed by firedeck, liner and valves. Afterwards, the study has been focused on the impact of different piston Thermal Barrier Coatings (TBCs) on heat transfer, performance and wall temperatures.

Nowadays, injection rate shaping and multi-pilot events can help to improve fuel efficiency, combustion noise and pollutant emissions in diesel engine, providing high flexibility in the shape of the injection that allows combustion process control. Different strategies can be used in order to obtain the required flexibility in the rate, such as very close pilot injections with almost zero Dwell Time or boot shaped injections with optional pilot injections. Modern Common-Rail Fuel Injection Systems (FIS) should be able to provide these innovative patterns to control the combustion phases intensity for optimal tradeoff between fuel consumption and emission levels.

The fuel injection plays a crucial role in determining the mixture formation process in Gasoline Direct Injection (GDI) engines. Pollutant emissions, and soot emissions in particular, as well as phenomena affecting engine reliability, such as oil dilution and injector coking, are deeply influenced by the injection system features, such as injector geometric characteristics (such as injector type, injector position and targeting within the combustion chamber) and operating characteristics (such as injection pressure, injection phasing, etc.). In this paper, a new CFD methodology is presented, allowing a preliminary assessment of the mixture formation quality in terms of expected soot emissions, oil dilution and injector coking risks for different injection systems (such as for instance multihole or swirl injectors) and different injection strategies, from the early stages of a new engine design.

The aim of this work is the assessment of the predictive capabilities of fast running models, obtained through an appropriate reduction and simplification process from detailed 1D fluid-dynamic models, for a turbocharged s.i. engine under highly transient operating conditions. Simulations results have been compared with experimental data for different types of models, ranging from fully detailed 1D fluid-dynamic models to map-based models, quantifying the degradation of the model accuracy and the reduction in the computational time for different kinds of driving cycles, from moderately transient such as the NEDC to highly dynamic such as the US06.

Development trends in modern common rail fuel injection systems (FIS) show dramatically increasing capabilities in terms of optimization of the fuel injection strategy through a constantly increasing number of injection events per engine cycle as well as through the modulation and shaping of the injection rate. In order to fully exploit the potential of the abovementioned fuel injection strategy optimization, numerical simulation can play a fundamental role by allowing the creation of a kind of a virtual test rig, where the input is the fuel injection rate and the optimization targets are the combustion outputs, such as the burn rate, the pollutant emissions, and the combustion noise (CN).

In the framework of an increasing demand for a more sustainable mobility, where the fuel consumption reduction is a key driver for the development of innovative internal combustion engines, Turbulent Jet Ignition (TJI) represents one of the most promising solutions to improve the thermal efficiency. However, details concerning turbulent jet assisted combustion are still to be fully captured, and therefore the design and the calibration of efficient TJI systems require the support of reliable simulation tools that can provide additional information not accessible through experiments. To this aim, an experimental investigation combined with a 3D-CFD study was performed to analyze the TJI combustion characteristics in a single-cylinder spark-ignition (SI) engine. Firstly, the model was validated against experiments considering stoichiometric mixture at 3000 rpm, wide open throttle operating conditions.

Experimental work was carried out on a small displacement Euro 5 automotive diesel engine alternatively fuelled with ultra low sulphur diesel (ULSD) and with two blends (30% vol.) of ULSD and of two different fatty acid methyl esters (FAME) obtained from both rapeseed methyl ester (RME) and jatropha methyl ester (JME) in order to evaluate the effects of different fuel compositions on particle number (PN) emissions. Particulate matter (PM) emissions for each fuel were characterized in terms of number and mass size distributions by means of two stage dilutions system coupled with a scanning mobility particle sizer (SMPS). Measurements were performed at three different sampling points along the exhaust system: at engine-out, downstream of the diesel oxidation catalyst (DOC) and downstream of the diesel particulate filter (DPF). Thus, it was possible to evaluate both the effects of combustion and after-treatment efficiencies on each of the tested fuels.

This paper presents the modeling of the transient phase of catalyst heating on a high-performance turbocharged spark ignition engine with the aim to accurately predict the exhaust thermal energy available at the catalyst inlet and to provide a “virtual test rig” to assess different design and calibration options. The entire transient phase, starting from the engine cranking until the catalyst warm-up is completed, was taken into account in the simulation, and the model was validated using a wide data-set of experimental tests. The first step of the modeling activity was the combustion analysis during the transient phase: the burn rate was evaluated on the basis of experimental in-cylinder pressure data, considering both cycle-to-cycle and cylinder-to-cylinder variations.

The need for achieving a fast warm up of the exhaust system has raised in the recent years a growing interest in the adoption of Variable Valve Actuation (VVA) technology for automotive diesel engines. As a matter of fact, different measures can be adopted through VVA to accelerate the warm up of the exhaust system, such as using hot internal Exhaust Gas Recirculation (iEGR) to heat the intake charge, especially at part load, or adopting early Exhaust Valve Opening (eEVO) timing during the expansion stroke, so to increase the exhaust gas temperature during blowdown. In this paper a simulation study is presented evaluating the impact of VVA on the exhaust temperature of a modern light duty 4-cylinder diesel engine, 1.6 liters, equipped with a Variable Geometry Turbine (VGT).

In Motorsports the understanding of the real engine performance within a complete circuit lap is a crucial topic. On the basis of the telemetry data the engineers are able to monitor this performance and try to adapt the engine to the vehicle's and race track's characteristics and driver's needs. However, quite often the telemetry is the sole analysis instrument for the Engine-Vehicle-Driver (EVD) system and it has no prediction capability. The engine optimization for best lap-time or best fuel economy is therefore a topic which is not trivial to solve, without the aid of suitable, reliable and predictive engineering tools. A complete EVD model was therefore built in a GT-SUITE™ environment for a Motorsport racing car (STCC-VW-Scirocco) equipped with a Compressed Natural Gas (CNG) turbocharged S.I. engine and calibrated on the basis of telemetry and test bench data.

Currently, two consolidated aftertreatment technologies are available for the reduction of NOx emissions from diesel engines: Urea SCR (Selective Catalytic Reduction) systems and LNT (Lean NOx Trap) systems. Urea SCR technology, which has been widely used for many years at stationary sources, is becoming nowadays an attractive alternative also for light-duty diesel applications. However, SCR systems are much more effective in NOx reduction efficiency at high load operating conditions than light load condition, characterized by lower exhaust gas temperatures.

Particulate Matter (PM) particles number and size distribution emitted from a small displacement automotive Common-Rail Diesel engine were analyzed in order to evaluate the impact of different engine operating parameters, such as engine load, EGR rate and injection pattern during DPF regeneration. The engine was equipped with a close coupled aftertreatment system, featuring a Diesel Oxidation Catalyst (DOC) and a Diesel Particulate Filter (DPF) integrated in a single canning. The pollutant emissions were sampled at two locations along the exhaust system: at the engine outlet and downstream of the diesel oxidation catalyst, in order to characterize particles entering the DOC and the DPF respectively. Particle size distributions were measured by means of a two stage dilution system coupled with a downstream Scanning Mobility Particle Sizer (SMPS).

Three different ceramic substrate materials (Silicon Carbide, Cordierite and Aluminum Titanate) for a Diesel Particulate Filter (DPF) for a European passenger car diesel engine have been experimentally investigated in this work. The filters were soot loaded under real world operating conditions on the road and then regenerated in two different ways that simulate the urban driving conditions, which are the most severe for DPF regeneration, since the low exhaust flow has a limited capability to absorb the heat generated by the soot combustion. The tests showed higher temperature peaks, at the same soot loading, for Cordierite and Aluminum Titanate compared to the Silicon Carbide, thus leading to a lower soot mass limit, which in turn required for these components a higher regeneration frequency with draw backs in terms of fuel consumption and lube oil dilution.

In this work, a methodology for building and calibrating the kinetic scheme for the 1D CFD model of a zone-coated automotive Diesel Oxidation Catalyst (DOC) by means of a Genetic Algorithm (GA) approach is presented. The methodology consists of a preliminary experimental activity followed by a modelling, optimization and validation process. The tested aftertreatment component presents zone coating, with the front brick side covered with Zeolites in order to ensure hydrocarbons trapping at low temperature, and Platinum Group Metal (PGM), while the rear brick side presents an alumina washcoat with a different PGM loading. Reactor scale samples representative of each coating zone were tested on a Synthetic Gas Bench (SGB), to fully characterize the component’s behavior in terms of Light-off and hydrocarbons (HC) storage for a wide range of inlet feed compositions and temperatures, representative of engine-out conditions.

The increasingly demanding targets in terms of CO2 reduction lead to the adoption of engine technologies left so far for innovation. In diesel engines, some of the primary interests in adopting an advanced air management system, as Variable Valve Actuation (VVA), are related to Miller cycle enabling, and valve timing optimization. In this context, a numerical study was carried out in order to evaluate the impact of VVA on passenger car 4-cylinder diesel engine, 1.6 liters. The engine model, developed in GT-SUITE, features a predictive combustion model (DIPulse) and it is coupled with a fully predictive fuel injector model for the simulation of complex injection patterns. 3 different VVA techniques were evaluated, all targeting CO2 reduction: Late Exhaust Valve Opening (LEVO), Exhaust Phasing, and Late Inlet Valve Closure (LIVC) for enabling Miller cycle.