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Homogeneous charge compression ignition (HCCI) is one of the alternatives to reduce significantly diesel engine emissions for the future emissions regulations. This new alternative combustion process is mainly controlled by chemical kinetics, unlike conventional combustion in internal combustion engines. To satisfy the different modes of operation, the tuning of HCCI engines requires a large number of tests which are time-consuming and very expensive. To reduce the number of tests, a model with a very short computational time to simulate the engine in the whole operating range is needed; therefore the goal of this study is to provide the engine manufacturers with a simple physical combustion model to assist engine tuning and engine management system optimization, with the aim of predicting in-cylinder pressure evolutions and mean effective pressure (IMEP).

Direct injection (DI) of natural gas (NG) at high pressure conditions has emerged as a high-potential strategy for improving SI engine performance. Besides, DI allows an increase in the fuel economy, due to the possibility of a significant engine dethrottling at partial load. The high-pressure gas injection can also increase the turbulence level of mixture and thus the overall fuel-air mixing. Since direct NG injection is an emerging technology, there is a lack of experience on the optimum configuration of the injection system and the associated combustion chamber design. In the last few years, some numerical investigations of gas injection have been made, mainly oriented at the development of reliable numerical investigation tools. The present paper is concerned with the development and application of a numerical Star-CD based model for the investigation of the direct NG injection process from a poppet-valve injector into a bowl-piston engine combustion chamber.

A real-time approach has been developed and assessed to control BMEP (brake mean effective pressure) and MFB50 (crank angle at which 50% of fuel mass has burnt) in a Euro 6 1.6L GM diesel engine. The approach is based on the use of feed-forward ANNs (artificial neural networks), which have been trained using virtual tests simulated by a previously developed low-throughput physical engine model. The latter is capable of predicting the heat release and the in-cylinder pressure, as well as the related metrics (MFB50, IMEP - indicated mean effective pressure) on the basis of an improved version of the accumulated fuel mass approach. BMEP is obtained from IMEP taking into account friction losses. The low-throughput physical model does not require high calibration effort and is also suitable for control-oriented applications. However, control tasks characterized by stricter demands in terms of computational time may require a modeling approach characterized by a further lower throughput.

The main objective of this study is to determine the appropriate boundary conditions for the distribution of droplet sizes, speed of the fuel settling at the nozzle of the injector and droplet penetration by numerical simulation using STARCD for a 3-holes injector of ULC-GE. In this study, the Eulerian- Lagrangian approach has been used to model the multiphase domain. A new strategy has been adapted to model droplet initial conditions using the Rosin-Rammler distribution, which is determined by measurement of the Sauter Mean Diameter D₃₂ and the De Brouckere Mean Diameter D₄₃ by the MALVERN method. Further, these droplets undergo the phenomenon of atomization by secondary break-up method and evaporation in the Eulerian domain. The numerical model has been used to evaluate the effects of different initial condition of droplets by changing the discharge coefficient of the nozzle, and the initial droplet size distribution at the nozzle tip.

This paper presents the results of part of the research activity carried out by the Politecnico di Torino and AVL List GmbH as part of the European Community InGAS Collaborative Project. The work was aimed at developing a combustion system for a mono-fuel turbocharged CNG engine, with specific focus on performance, fuel economy and emissions. A numerical and experimental analysis of the jet development and mixture formation in an optically accessible, single cylinder engine is presented in the paper. The experimental investigations were performed at the AVL laboratories by means of the planar laser-induced fluorescence technique, and revealed a cycle-to-cycle jet shape variability that depended, amongst others, on the injector characteristics and in-cylinder backpressure. Moreover, the mixing mechanism had to be optimized over a wide range of operating conditions, under both stratified lean and homogeneous stoichiometric modes.

New methodologies have been developed to optimize EGR rate and injection timing in diesel engines, with the aim of minimizing fuel consumption (FC) and NOx engine-out emissions. The approach entails the application of a recently developed control-oriented engine model, which includes the simulation of the heat release rate, of the in-cylinder pressure and brake torque, as well as of the NOx emission levels. The engine model was coupled with a C-class vehicle model, in order to derive the engine speed and torque demand for several driving cycles, including the NEDC, FTP, AUDC, ARDC and AMDC. The optimization process was based on the minimization of a target function, which takes into account FC and NOx emission levels. The selected control variables of the problem are the injection timing of the main pulse and the position of the EGR valve, which have been considered as the most influential engine parameters on both fuel consumption and NOx emissions.

The present work has the aim of developing a fast approach for the predictive calculation of in-cylinder combustion temperatures and NOx formation in diesel engines, under steady state and transient conditions. The model has been tested on a PC, and found to require very little computational time, thus suggesting it could be implemented in the ECU (Engine Control Unit) of engines for model-based control tasks. The method starts with the low-throughput predictive combustion model that was previously developed by the authors, which allows the predictive estimation of the heat-release rate and of the in-cylinder pressure trace to be made on the basis of the injection parameters and of a few quantities measured by the ECU, such as the intake manifold pressure and temperature.

An investigation has been carried out on the spray penetration and soot formation processes in a research diesel engine by means of a quasi-dimensional multizone combustion model. The model integrates a predictive non stationary 1D spray model developed by the Sandia National Laboratory, with a diagnostic multizone thermodynamic model, and is capable of predicting the spray formation, combustion and soot formation processes in the combustion chamber. The multizone model was used to analyze three operating conditions, i.e., a zero load point (BMEP = 0 bar at 1000 rpm), a medium load point (BMEP = 5 bar at 2000 rpm) and a medium-high load point (BMEP = 10 bar at 2000 rpm). These conditions were experimentally tested in an optical single cylinder engine with the combustion system configuration of a 2.0L Euro4 GM diesel engine for passenger car applications.

In this study, different designs of intake ports for two-stroke Ultra Low Cost Gasoline Direct Injection Engine (ULC-GE) has been analyzed to conclude on best design using steady state analysis in STAR-CD. The four types of intake ports design with two cylinders, each having fourteen ports, have been studied. The basic differences in designs are horizontal inlet entry (perpendicular to cylinder axis) and vertical inlet entry (in-line with cylinder axis) having rotation of flow clockwise and anticlockwise. Each type is further differentiated in eight cases with varying distances between axis of two-cylinder as 85mm, 88mm, 91 mm, 94 mm, 97 mm, 100 mm, 105 mm and 112 mm. These designs are analyzed for four different pressure drops as 10 mbar, 50 mbar, 100 mbar and 150 mbar.

Nowadays, green hydrogen can play a crucial role in a successful clean energy transition, thus reaching net zero emissions in the transport sector. Moreover, hydrogen exploitation in internal combustion engines is favoured by its suitable combustion properties and quasi-zero harmful emissions. High flame speeds enable a lean combustion approach, which provides high efficiency and reduces NOx emissions. However, high air flow rates are required to achieve the load levels typical of heavy-duty applications. In this framework, the present study aims to investigate the required boosting system of a 6-cylinder, 13-liter heavy-duty spark ignition engine through 1D numerical simulation. A comparison among various architectures of the turbocharging system and the size of each component is presented, thus highlighting limitations and potentialities of each architecture and providing important insights for the selection of the best turbocharging system.

An innovative 0D predictive combustion model for the simulation of the HRR (heat release rate) in DI diesel engines was assessed and implemented in a 1D fluid-dynamic commercial code for the simulation of a Fiat heavy duty diesel engine equipped with a Variable Geometry Turbocharger system, in the frame of the CORE (CO2 reduction for long distance transport) Collaborative Project of the European Community, VII FP. The 0D combustion approach starts from the calculation of the injection rate profile on the basis of the injected fuel quantities and on the injection parameters, such as the start of injection and the energizing time, taking the injector opening and closure delays into account. The injection rate profile in turn allows the released chemical energy to be estimated. The approach assumes that HRR is proportional to the energy associated with the accumulated fuel mass in the combustion chamber.

Combustion in any engine starts with the injection of fuel into the combustion chamber. Atomization of fuel and its mixing plays a vital role in determining the suitable air-fuel (A/F) ratio. Appropriate A/F ratio determines the amount of energy release and pollutant formation for standard engines. Thus an accurate prediction of these processes is required to perform reliable combustion and pollutant formation simulations. In this study, the Eulerian-Lagrangian Spray Atomization (ELSA) model is implemented as a Computational Fluid Dynamics (CFD) tool for the prediction of spray behavior. Past studies performed on diesel fuel suggest good agreement between experiment and simulation indicating the model’s capability. The study aims to validate the ELSA model for gasoline fuel against the test results obtained from Renault and against the pure Lagrangian spray model. The simulations have been performed using CONVERGE CFD v2.4.18.