Search Results

Turbocharging is playing today a fundamental role not only to improve automotive engine performance, but also to reduce fuel consumption and exhaust emissions for both Spark Ignition and Diesel engines. Dedicated experimental investigations on turbochargers are therefore necessary to assess a better understanding of its performance. The availability of experimental information on turbocharger steady flow performance is an essential requirement to optimize the engine-turbocharger matching, which is usually achieved by means of simulation models. This aspect is even more important when referred to the turbine efficiency, since its swallowing capacity can be accurately evaluated through the measurement of mass flow rate, inlet temperature and pressure ratio across the machine.

Direct-injection represents a consolidated technology to increase performance and efficiency in spark-ignition engines. It reduces the knock tendency and makes engine downsizing possible through the use of turbocharging. Better control of CO and HC emissions at cold-start is also ensured since there is no wall-impingement in the intake port. However, to take advantages of all the theoretical benefits derived from GDI technology, detailed investigations of both fuel-air mixing and combustion processes are necessary to extend the stratified charge operations in the engine map and to reduce soot emissions, that are now severely regulated by emission standards. In this work, the authors developed a CFD methodology to investigate and optimize the fuel-air mixing process in direct-injection, spark-ignition engines. The Eulerian-Lagrangian approach is used to model the evolution of the fuel spray emerging from a multi-hole injector.

In this work the 3Dcell method, a quasi3D approach developed by the Internal Combustion Engine Group at Politecnico di Milano, has been extended and applied to the fluid dynamic simulation of turbocharging devices for internal combustion engines, focusing on the compressor side. The 3Dcell is based on a pseudo-staggered leapfrog method applied to the governing equation of a 1D problem arbitrarily oriented in space. The system of equations is solved referring to the relative system in the rotating zone, whereas the absolute reference system has been used elsewhere. The vaneless diffuser has been modelled resorting to the conservation of the angular momentum of the flow stream in the tangential direction, combined with the solution of the momentum equation in the radial direction.

ELEVATE (European Low Emission V4 Automotive Two-stroke Engine) was a research project part funded by the European Commission to design and develop a compact and efficient gasoline two-stroke automotive engine. Five partners were involved in the project, IFP (Institut Français Du Pétrole) who were the project leaders, Lotus, Opcon (Autorotor and SEM), Politecnico di Milano and Queen's University Belfast. The general project targets were to achieve Euro 3 emissions compliance without DeNOx catalisation, and a power output of 120 kW at 5000 rev/min with maximum torque of 250 Nm at 2000 rev/min. Specific targets were a 15% reduction in fuel consumption compared to its four-stroke counterpart and a size and weight advantage over the four-stroke diesel with significant reduction in particulate and NOx emissions. This paper describes the design philosophy of the engine as well as the application of the various partner technologies used.

Tires will be protagonists in the new European regulations for safety and fuel economy: in 2012 a tire pressure monitoring system will be mandatory for all new vehicles, enabling as natural consequence the development of the so called “intelligent tire”, able to capture all the relevant information of the contact between the road surface and the rubber, a starting point for new functions development to improve safety and reduce fuel consumption of all vehicles. A description of the methodologies that can be used to extract features from the tires, based on the experience of the development of Cyber Tyre, a high performance sensorized tire, is included in this work; comparison with the same information gained thorough ordinary sensors are provided too. The paper also presents some interesting examples of how data, coming from Cyber Tyres, can be exploited to improve the safety margins of a vehicle, preventing the critical operating condition represented by hydroplaning.

Multiple injection strategies are commonly used in conventional Diesel engines due to the flexibility for optimizing heat-release timing with a consequent improvement in fuel economy and engine-out emissions. This is also desirable in low-temperature combustion (LTC) engines since it offers the potential to reduce unburned hydrocarbon and CO emissions. To better utilize these benefits and find optimal calibrations of split injection strategies, it is imperative that the fundamental processes of multiple injection combustion are understood and computational fluid dynamics models accurately describe the flow dynamics and combustion characteristics between different injection events. To this end, this work is dedicated to the identification of suitable methodologies to predict the multiple injection combustion process.

The Computational Chemistry Consortium (C3) is dedicated to leading the advancement of combustion and emissions modeling. The C3 cluster combines the expertise of different groups involved in combustion research aiming to refine existing chemistry models and to develop more efficient tools for the generation of surrogate and multi-fuel mechanisms, and suitable mechanisms for CFD applications. In addition to the development of more accurate kinetic models for different components of interest in real fuel surrogates and for pollutants formation (NOx, PAH, soot), the core activity of C3 is to develop a tool capable of merging high-fidelity kinetics from different partners, resulting in a high-fidelity model for a specific application. A core mechanism forms the basis of a gasoline surrogate model containing larger components including n-heptane, iso-octane, n-dodecane, toluene and other larger hydrocarbons.

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.

A detailed understanding of Gasoline Direct Injection (GDI) techniques applied to spark-ignition (SI) engines is necessary as they allow for many technical advantages such as increased power output, higher fuel efficiency and better cold start performances. Within this context, the extensive validation of multi-dimensional models against experimental data is a fundamental task in order to achieve an accurate reproduction of the physical phenomena characterizing the injected fuel spray. In this work, simulations of different Engine Combustion Network (ECN) Spray G conditions were performed with the Lib-ICE code, which is based on the open source OpenFOAM technology, by using a RANS Eulerian-Lagrangian approach to model the ambient gas-fuel spray interaction.

In this work, the possibility to perform a cold-flow simulation as a way to improve the accuracy of the starting conditions for a combustion simulation is examined. Specifically, a dual-fuel marine engine running on methanol/diesel and natural gas/diesel fueling conditions is investigated. Dual-fuel engines can provide a short-term solution to cope with the more stringent emission legislations in the maritime sector. Both natural gas and methanol appear to be interesting alternative fuels that can be used as main fuel in these dual-fuel engines. Nevertheless, it is observed that combustion problems occur at part load using these alternative fuels. Therefore, different methods to increase the combustion efficiency at part load are investigated. Numerical simulations prove to be very suitable hereto, as they are an efficient way to study the effect of different parameters on the combustion characteristics.

This work proposes a focus on the simulation of a rotative volumetric expander via a CFD code. A customized application of OpenFOAM® has been developed to handle the particular motion of the calculation grid. The model uses a mesh to mesh interpolation technique, switching from a calculation grid to the new one on the basis of mesh quality considerations performed on the fly. This particular approach allows to account for the presence of leakages occurring between the stator and blade tips and also occurring at the top and bottom of the vanes. The fluid considered is the refrigerant R245fa, whose particular properties have been determined resorting to the NIST database. Experimental data, measured at different conditions of mass flow and fluid temperature, are compared to calculation results. Moreover, the CFD analysis has allowed the estimation of the influence of the leakage mass flow occurring at the tip of the vanes on the overall machine performances.

A comprehensive model for sprays emerging from high pressure swirl injectors for GDI engine application has been developed. The primary and secondary atomization mechanism as well as the evaporation process both in standard and superheated conditions are taken into account. The spray modelling after the injection is based on the Liquid Instability Sheet Atomization (LISA) approach, modified to correctly predict the liquid sheet thickness at the breakup length. The effect of different values of the superheat degree on evaporation and impact on the spray distribution and fuel-air mixing is analyzed. Comparisons with experimental data show good agreements under atmospheric conditions and with different superheated degrees, while some discrepancies occur under higher ambient pressures.

Predictive combustion models are useful tools towards the development of clean and efficient engines operating with alternative fuels. This work intends to validate two different combustion models on compression-ignition engines fueled with Dimethyl Ether. Both approaches give a detailed characterization of the combustion kinetics, but they substantially differ in how the interaction between fluid-dynamics and chemistry is treated. The first one is single-flamelet Representative Interactive Flamelet, which considers turbulence-kinetic interaction but cannot correctly describe the stabilization of the flame. The second, named Tabulated Well Mixed, correctly accounts for local flow and mixture conditions but does not consider interaction between turbulence and chemistry. An experimental campaign was carried out on a heavy-duty truck engine running on DME at a constant load considering trade-off of EGR and SOI.

Computational fluid dynamics (CFD) modeling has many potentials for the design and calibration of modern and future engine concepts, including facilitating the exploration of operation conditions and casting light on the involved physical and chemical phenomena. As more attention is paid to the matching of different fuel types and combustion strategies, the use of detailed chemistry in characterizing auto-ignition, flame stabilization processes and the formation of pollutant emissions is becoming critical, yet computationally intensive. Therefore, there is much interest in using tabulated approaches to account for detailed chemistry with an affordable computational cost. In the present work, the tabulated flamelet progress variable approach (TFPV), based on flamelet assumptions, was investigated and validated by simulating constant-volume Diesel combustion with primary reference fuels - binary mixtures of n-heptane and iso-octane.

To improve the combustion and emission characteristics of the large-bore marine engines, the spray is usually designed as an inter-spray impingement to promote the fuel-air mixing process, which implies frequent droplet collisions. Properly describing the collision dynamics of liquid droplets has been of interest in the field of spray modeling for marine engine applications. In this context, this work attempts to develop an accurate and efficient methodology for modeling impinging sprays under engine-like conditions. Experimental validations in terms of spray penetration and morphology are initially carried out at different operating conditions considering the parametric variations of ambient temperature and pressure, where the measurements are performed on a large-scale constant volume chamber with two symmetrical injectors.

Gasoline, direct injection engines represent one of the most widely adopted powertrain for passenger cars. However, further development efforts are necessary to meet the future fuel consumption and emission standards imposing an efficiency increase and a reduction of particulate matter emissions. Within this context, computational fluid dynamics is nowadays a consolidated tool to support engine design; this work is focused on the development of a set of CFD models for the prediction of combustion in modern GDI engines. The one-equation Weller model coupled with a zero-dimensional approach to handle initial flame kernel growth was applied to predict flame propagation. To account for mixture fraction fluctuations which might lead to the presence of soot precursor species, burned gas chemical composition is computed using tabulated kinetics with a presumed probability density function.

The increasing diffusion of gasoline direct injection (GDI) engines requires a more detailed and reliable description of the phenomena occurring during the fuel injection process. As well known the thermal and fluid-dynamic conditions present in the combustion chamber greatly influence the air-fuel mixture process deriving from GDI injectors. GDI fuel sprays typically evolve in wide range of ambient pressure and temperatures depending on the engine load. In some particular injection conditions, when in-cylinder pressure is relatively low, flash evaporation might occur significantly affecting the fuel-air mixing process. In some other particular injection conditions spray impingement on the piston wall might occur, causing high unburned hydrocarbons and soot emissions, so currently representing one of the main drawbacks of GDI engines.

Prediction of in-cylinder flows and fuel-air mixing are two fundamental pre-requisites for a successful simulation of direct-injection engines. Over the years, many efforts were carried out in order to improve available turbulence and spray models. However, enhancements in physical modeling can be drastically affected by how the mesh is structured. Grid quality can negatively influence the prediction of organized charge motion structures, turbulence generation and interaction between in-cylinder flows and injected sprays. This is even more relevant for modern direct injection engines, where multiple injections and control of charge motions are employed in a large portion of the operating map. Currently, two different approaches for mesh generation exist: manual and automatic. The first makes generally possible to generate high-quality meshes but, at the same time, it is very time consuming and not completely free from user errors.

In the rapidly changing scenario of the energy transition, data-driven tools for kinetic mechanism development and testing can greatly support the evaluation of the combustion properties of new potential e-fuels. Despite the effectiveness of kinetic mechanism generation and optimization procedures and the increased availability of experimental data, integrated methodologies combining data analysis, kinetic simulations, chemical lumping, and kinetic mechanism optimization are still lacking. This paper presents an integrated workflow that combines recently developed automated tools for kinetic mechanism development and testing, from data collection to kinetic model reduction and optimization. The proposed methodology is applied to build a consistent, efficient, and well-performing kinetic mechanism for the combustion of oxymethylene ethers (OMEs), which are promising synthetic e-fuels for transportation.

Multiple injections and high EGR rates are now widely adopted for combustion and emissions control in passenger car diesel engines. In a wide range of operating conditions, fuel is provided through one to five separated injection events, and recirculated gas fractions between 0 to 30% are used. Within this context, fast and reliable multi-dimensional models are necessary to define suitable injection strategies for different operating points and reduce both the costs and time required for engine design and development. In this work, the authors have applied a modified version of the characteristic time-scale combustion model (CTC) to predict combustion and pollutant emissions in diesel engines using advanced injection strategies. The Shell auto-ignition model is used to predict auto-ignition, with a suitable set of coefficients that were tuned for diesel fuel.