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Modern VVA systems offer new potentialities in improving the fuel consumption for spark-ignition engines at low and medium load, meanwhile they grant a higher volumetric efficiency and performance at high load. Recently introduced systems enhance this concept through the possibility of concurrently modifying the intake valve opening, closing and lift leading to the development of almost "throttle-less" engines. However, at very low loads, the control of the air-flow motion and the turbulence intensity inside the cylinder may require to select a proper combination of the butterfly throttling and the intake valve control, to get the highest BSFC (Brake Specific Fuel Consumption) reduction. Moreover, a low throttling, while improving the fuel consumption, may also produce an increased gas-dynamic noise at the intake mouth. In highly "downsized" engines, the intake valve control is also linked to the turbocharger operating point, which may be changed by acting on the waste-gate valve.

In the recent years, the interest in heavy-duty engines fueled with Compressed Natural Gas (CNG) is increasing due to the necessity to comply with the stringent CO2 limitation imposed by national and international regulations. Indeed, the reduced number of carbon atoms of the NG molecule allows to reduce the CO2 emissions compared to a conventional fuel. The possibility to produce synthetic methane from renewable energy sources, or bio-methane from agricultural biomass and/or animal waste, contributes to support the switch from conventional fuel to CNG. To drive the engine development and reduce the time-to-market, the employment of numerical analysis is mandatory. This requires a continuous improvement of the simulation models toward real predictive analyses able to reduce the experimental R&D efforts. In this framework, 1D numerical codes are fundamental tools for system design, energy management optimization, and so on.

In recent years, the increase of gasoline fuel injection pressure is a way to improve thermal efficiency and lower engine-out emissions in GDI homogenous combustion concept. The challenge of controlling particulate formation as well in mass and number concentrations imposed by emissions regulations can be pursued improving the mixture preparation process and avoiding mixture inhomogeneity with ultra-high injection pressure values up to 100 MPa. The increase of the fuel injection pressure in GDI homogeneous systems meets the demand for increased injector static flow, while simultaneously improves the spray atomization and mixing characteristics with consequent better combustion performance. Few studies quantify the effects of high injection pressure on transient gasoline spray evolution. The aim of this work was to simulate with OpenFOAM the spray morphology of a commercial gasoline injected in a constant volume vessel by a prototypal GDI injector.

In this paper, the results of an extensive experimental analysis regarding a twin-cylinder spark-ignition turbocharged engine are employed to build up an advanced 1D model, which includes the effects of cycle-by-cycle variations (CCVs) on the combustion process. Objective of the activity is to numerically estimate the CCV impact primarily on fuel consumption and knock behavior. To this aim, the engine is experimentally characterized in terms of average performance parameters and CCVs at high and low load operation. In particular, both a spark advance and an air-to-fuel ratio (α) sweep are actuated. Acquired pressure signals are processed to estimate the rate of heat release and the main combustion events. Moreover, the Coefficient of Variation of IMEP (CoVIMEP) and of in-cylinder peak pressure (CoVpmax) are evaluated to quantify the cyclic dispersion and identify its dependency on peak pressure position.

The modeling of fuel sprays under well-characterized conditions relevant for heavy-duty Diesel engine applications, allows for detailed analyses of individual phenomena aimed at improving emission formation and fuel consumption. However, the complexity of a reacting fuel spray under heavy-duty conditions currently prohibits direct simulation. Using a systematic approach, we extrapolate available spray models to the desired conditions without inclusion of chemical reactions. For validation, experimental techniques are utilized to characterize inert sprays of n-dodecane in a high-pressure, high-temperature (900 K) constant volume vessel with full optical access. The liquid fuel spray is studied using high-speed diffused back-illumination for conditions with different densities (22.8 and 40 kg/m3) and injection pressures (150, 80 and 160 MPa), using a 0.205-mm orifice diameter nozzle.

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

This paper is focused on the development and application of a CFD methodology that can be applied to predict the fuel-air mixing process in stratified charge, sparkignition engines. The Eulerian-Lagrangian approach was used to model the spray evolution together with a liquid film model that properly takes into account its effects on the fuel-air mixing process into account. However, numerical simulation of stratified combustion in SI engines is a very challenging task for CFD modeling, due to the complex interaction of different physical phenomena involving turbulent, reacting and multiphase flows evolving inside a moving geometry. Hence, for a proper assessment of the different sub-models involved a detailed set of experimental optical data is required. To this end, a large experimental database was built by the authors.

A numerical methodology to simulate the high pressure spray evolution and the fuel-air mixing in diesel engines is presented. Attention is focused on the employed atomization model, a modified version of the Huh and Gosman, on the definition of a turbulence length scale limiter and of an adaptive local mesh refinement technique to minimize the result grid dependency. All the discussed models were implemented into Lib-ICE, which is a set of libraries and solvers, specifically tailored for engine simulations, which runs under the open-source CFD technology OpenFOAM®. To provide a comprehensive assessment of the proposed methodology, the validation procedure consisted into simulating, with a unique and coherent setup of all models, two different sets of experiments: a non-evaporating diesel fuel spray in a constant-volume vessel with optical access and an evaporating non-reacting diesel fuel spray in an optical engine.

In this paper, a downsized twin-cylinder turbocharged spark-ignition engine is experimentally investigated at test-bench in order to verify the potential to estimate the peak pressure value and the related crank angle position, based on vibrational data acquired by an accelerometer sensor. Purpose of the activity is to provide the ECU of additional information to establish a closed-loop control of the spark timing, on a cycle-by-cycle basis. In this way, an optimal combustion phasing can be more properly accomplished in each engine operating condition. Engine behavior is firstly characterized in terms of average thermodynamic and performance parameters and cycle-by-cycle variations (CCVs) at high-load operation. In particular, both a spark advance and an A/F ratio sweep are actuated. In-cylinder pressure data are acquired by pressure sensors flush-mounted within the combustion chamber of both cylinders.

The scope of the work presented in this paper was to apply the latest open source CFD achievements to design a state of the art, direct-injection (DI), heavy-duty, natural gas-fueled engine. Within this context, an initial steady-state analysis of the in-cylinder flow was performed by simulating three different intake ducts geometries, each one with seven different valve lift values, chosen according to an estabilished methodology proposed by AVL. The discharge coefficient (Cd) and the Tumble Ratio (TR) were calculated in each case, and an optimal intake ports geometry configuration was assessed in terms of a compromise between the desired intensity of tumble in the chamber and the satisfaction of an adequate value of Cd. Subsequently, full-cycle, cold-flow simulations were performed for three different engine operating points, in order to evaluate the in-cylinder development of TR and turbulent kinetic energy (TKE) under transient conditions.

Extensive prior art within the Engine Combustion Network (ECN) using a Bosch single axial-hole injector called ‘Spray A’ in constant-volume vessels has provided a solid foundation from which to evaluate modeling tools relevant to spray combustion. In this paper, a new experiment using a Bosch three-hole nozzle called ‘Spray B’ mounted in a 2.34 L heavy-duty optical engine is compared to sector-mesh engine simulations. Two different approaches are employed to model combustion: the ‘well-mixed model’ considers every cell as a homogeneous reactor and employs multi-zone chemistry to reduce the computational time. The ‘flamelet’ approach represents combustion by an ensemble of laminar diffusion flames evolving in the mixture fraction space and can resolve the influence of mixing, or ‘turbulence-chemistry interactions,’ through the influence of the scalar dissipation rate on combustion.

In the paper a coupled Multi-Body and FEM-BEM methodology used to predict the noise radiated by a turbocharged 4-cylinder diesel engine prototype is described. A Multi-Body Dynamic Simulation (MBDS) of the engine has been carried out, simulating an engine speed sweep from 1500 to 4000 rpm, in order to determine the excitation force of the powertrain, and in particular to estimate the forces acting on the cylinder block. Thanks to the Multi-Body approach, the dynamics of the engine powertrain have been described taking into account both the effects of the burnt gas pressure during the combustion process and the inertia forces of the moving parts. Moreover to assess the real engine operating behaviour, both the crank and the block have been considered as flexible bodies.

Partially premixed compression ignition combustion is one of the low temperature combustion techniques which is being actively investigated. This approach provides a significant reduction of both soot and NOx emissions. Comparing to the homogeneous charge compression ignition mode, PPCI combustion provides better control on ignition timing and noise reduction through air-fuel mixture stratification which lowers heat release rate compared to other advanced combustion modes. In this work, CFD simulations were conducted for a low and a high air-fuel mixture stratification cases on a light-duty optical engine operating in PPCI mode. Such conditions for PRF70 as fuel were experimentally achieved by injection timing and spray targeting at similar thermodynamic conditions.

A three dimensional numerical simulation of the ECN “Spray A” is presented. Both primary and secondary breakup of the spray are included. The fuel is n-Dodecane. The n-Dodecane kinetic mechanism is modeled using a skeletal mechanism that consists of 103 species and 370 reactions [9]. The kinetic mechanism is computationally heavy when coupled with three dimensional numerical simulations. Multidimensional chemistry coordinate mapping (CCM) approach is used to speedup the simulation. CCM involves two-way mapping between CFD cells and a discretized multidimensional thermodynamic space, the so called multidimensional chemistry coordinate space. In the text, the cells in the discretized multidimensional thermodynamic space are called zone to discriminate them from the CFD cells. In this way, the CFD cells which are at the similar thermodynamic state are identified and grouped into a unique zone. The stiff ODEs operates only on the zones containing at least one CFD cell.

During the last years, a number of techniques aimed at the experimental identification of the knocking onset in Spark-Ignition (SI) Internal Combustion Engines have been proposed. Besides the traditional procedures based on the processing of in-cylinder pressure data in the frequency domain, in the present paper two innovative methods are developed and compared. The first one is based on the use of statistical analysis by applying an Auto Regressive Moving Average (ARMA) technique, coupled to a prediction algorithm. It is shown that such parametric model, applied to the instantaneous in-cylinder pressure measurements, is highly sensitive to knock occurrence and is able to identify soft or heavy knock presence in different engine operating conditions. An alternative, more expensive procedure is developed and compared to the previous one.

In the recent years, the interest in heavy-duty engines fueled with Compressed Natural Gas (CNG) is increasing due to the necessity to comply with the stringent CO2 limitation imposed by national and international regulations. Indeed, the reduced number of carbon atoms of the NG molecule allows to reduce the CO2 emissions compared to a conventional fuel. The possibility to produce synthetic methane from renewable energy sources, or bio-methane from agricultural biomass and/or animal waste, contributes to support the switch from conventional liquid fuels to CNG. To drive the engine development and reduce the time-to-market, the employment of numerical analysis is mandatory. This requires a continuous improvement of the simulation models toward real predictive analyses able to reduce the experimental R&D efforts. In this framework, 1D numerical codes are fundamental tools for system design, energy management optimization, and so on.

Dimethyl ether (DME) represents a promising fuel for heavy-duty engines thanks to its high cetane number, volatility, absence of aromatics, reduced tank-to-wheel CO2 emissions compared to Diesel fuel and the possibility to be produced from renewable energy sources. However, optimization of compression-ignition engines fueled with DME requires suitable computational tools to design dedicated injection and combustion systems: reduced injection pressures and increased nozzle diameters are expected compared to conventional Diesel engines, which influences both the air-fuel mixing and the combustion process. This work intends to evaluate the validity of two different combustion models for the prediction of performance and pollutant emissions in compression-ignition engines operating with DME. The first one is the Representative Interactive Flamelet while the second is the Approximated Diffusive Flamelet.

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.

Control of knock phenomenon is becoming more and more important in modern SI engine, due to the tendency to develop high boosted turbocharged engines (downsizing). To this aim, improved modeling and experimental techniques are required to precisely define the maximum allowable spark advance. On the experimental side, the knock limit is identified based on some indices derived by the analysis of the in-cylinder pressure traces or of the cylinder block vibrations. The threshold levels of the knock indices are usually defined following an heuristic approach. On the modeling side, in the 1D codes, the knock is usually described by simple correlation of the auto-ignition time of the unburned gas zone within the cylinders. In addition, the latter methodology commonly refers to ensemble-averaged pressure cycles and, for this reason, does not take into account the cycle-by-cycle variations.

In the present work, an Auto Regressive Moving Average (ARMA) model and a Discrete Wavelet Transform (DWT) are applied on vibrational signals, acquired by an accelerometer placed on the cylinder block of a Spark Ignition (SI) engine, for knock detection purposes. To the aim of tuning such procedures, the same analysis has been carried out by using the traditional MAPO (Maximum Amplitude of Pressure Oscillations) index and an Inverse Kinetic Model (IKM), both applied on the in-cylinder pressure signals. Vibrational and in-cylinder pressure signals have been collected on a four cylinder, four stroke engine, for different engine speeds, load conditions and spark advances. The results of the two vibrational based methods are compared and in depth discussed to the aim of highlighting the pros and cons of each methodology.