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Cycle-To-Cycle Variability (CCV) must be properly considered when modeling the ignition process in SI engines operating with ultra-lean mixtures. In this work, a strategy to model the impact of the ignition type on the CCV was developed using the RANS approach for turbulence modelling, performing multi-cycle simulations for the power-cycle only. The spark-discharge was modelled through a set of Lagrangian particles, introduced along the sparkgap and interacting with the surrounding Eulerian gas flow. Then, at each discharge event, the velocity of each particle was modified with a zero-divergence perturbation of the velocity field with respect to average conditions. Finally, the particles velocity was evolved according to the Simplified Langevin Model (SLM), which keeps memory of the initial perturbation and applies a Wiener process to simulate the stochastic interaction of each channel particle with the surrounding gas flow.

The thorough understanding of the effects due to the fuel direct injection process in modern gasoline direct injection engines has become a mandatory task to meet the most demanding regulations in terms of pollutant emissions. Within this context, computational fluid dynamics proves to be a powerful tool to investigate how the in-cylinder spray evolution influences the mixture distribution, the soot formation and the wall impingement. In this work, the authors proposed a comprehensive methodology to simulate the air-fuel mixture formation into a gasoline direct injection engine under multiple operating conditions. At first, a suitable set of spray sub-models, implemented into an open-source code, was tested on the Engine Combustion Network Spray G injector operating into a static vessel chamber. Such configuration was chosen as it represents a typical gasoline multi-hole injector, extensively used in modern gasoline direct injection engines.

Today, Direct-Injection systems are widely used on Spark-Ignition engines in combination with turbo-charging to reduce the fuel-consumption and the knock risks. In particular, the spread of Gasoline Direct Injection (GDI) systems is mainly related to the use of new generations of multi-hole, high-pressure injectors whose characteristics are quite different with respect to the hollow-cone, low-pressure injectors adopted in the last decade. This paper presents the results of an experimental campaign conducted on the spray produced by a GDI six-holes injector into a constant volume vessel with optical access. The vessel was filled with air at atmospheric pressure. Different operating conditions were considered for an injection pressure ranging from 3 to 20 MPa. For each operating condition, spray images were acquired by a CCD camera and then post processed to evaluate the spray penetration and cone angles.

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.

An important paradigm for the modelling of naturally aspirated (NA) spark ignition (SI) engines for control purposes is the Mean Value Engine Model (MVEM). Such models have a time resolution which is just sufficient to capture the main details of the dynamic performance of NA SI engines but not the cycle-by-cycle behavior. In principle such models are also physically based, are very compact in a mathematical sense but nevertheless can have reasonable prediction accuracy. Presently no MVEMs have been constructed for intercooled turbocharged SI engines because their complexity confounds the simple physical understanding and description of such engines. This paper presents a newly constructed MVEM for a turbocharged SI engine which contains the details of the compressor and turbine characteristics in a compact way. The model has been tested against the responses of an experimental engine and has reasonable accuracy for realistic operating scenarios.

Long term control of the AFR (Air/Fuel Ratio) of spark ignition engines is currently accomplished with a selvoscillating PI control loop. Because of the intake/exhaust time delay, the oscillation frequency and hence bandwidth of this loop is small. This paper describes a new approach to the design of this control loop using a novel observer system. In this way the bandwidth of this important loop is increased by a factor of 2 - 6 times, leading to more accurate overall AFR control. Moreover the observer approach is so robust and allows such feedback levels that it reduces significantly the accuracy required in the calibration of the base fuel control system with which it is be used. It can be used with either conventional- or advanced observer based- base fuel strategies.

This paper exploits the possibilities of achieving an efficient performance optimization methodology to be applied to different spark ignition engine configurations. The objective of the task described here is to determine the combination of parameters which provides the highest volumetric efficiency and effective torque. The definition of general strategy requires first the identification and grouping of the geometric and operating variables to be optimized (duct diameters and lengths, valve timing, spark advance, etc…). The high number of possibilities entails critical choices to reduce, from an engineering design point of view before than from a mathematical point of view, the required computational time. Once proper thermo-fluid dynamic decisions are taken, the most efficient optimization methodology is required. The application of Design of Experiments techniques allows to screen the design space and give a first estimation of the optimal point.

Mean value engine models (MVEMs) seek to predict dynamically the mean values of important SI engine variables such as the crank shaft speed, the manifold pressure and the theoretical air/fuel ratio (lambda). Previous work also shows that such models can be made quite accurate, both for stationary and transient operating modes. Because these models can be made mathematically simple and compact, they are also tractable for direct mathematical and physical analysis. In this paper an analysis of a mean value engine model is carried out which reveals the underlying structure of the problems which face engine control system designers. In particular it is shown that an SI engine is extremely nonlinear and time dependent. Because of this, conventional control strategies using conventional sensors cannot be made to operate correctly in the transient regime. An “ideal” nonlinear compensator is also described for the fueling dynamics which works over a wide operating range.

Experimental investigations have been conducted with two identical small scale SI gas engines gen-sets operating on biomass producer gas from thermal gasification of wood. The engines where operated with two different compression ratios, one with the original compression ratio for natural gas operation 9.5:1, and the second with a compression ratio of 18.5:1. It was shown that high compression ratio SI engine operation was possible when operating on biomass producer gas from a TwoStage gasifier. The results showed an increase in the electrical efficiency from 31% to 35% when the compression ratio was increased. The influence of ignition timing on emissions was investigated during high compression ratio operation. It was shown that for λ=1.4 the NOx emission decreases by almost a factor 3, when the timing is retarded from 13° to 7° before top dead center.

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.

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.

A correct prediction of the initial stages of the combustion process in SI engines is of great importance to understand how local flow conditions, fuel properties, mixture stratification and ignition affect the in-cylinder pressure development and pollutant formation. However, flame kernel growth is governed by many interacting processes including energy transfer from the electrical circuit to the gas phase, interaction between the plasma channel and the flow field, transition between different combustion regimes and gas expansion at very high temperatures. In this work, the authors intend to present a comprehensive, multi-dimensional model that can be used to predict the initial combustion stages in SI engines. In particular, the spark channel is represented by a set of Lagrangian particles where each one of them acts as a single flame kernel.

The liquefied natural gas (LNG)-fueled ships were provisioned to meet the strict emission legislation in the marine application since 2000. However, the scientific approach of burning the low-emission natural gas in lean combustion uncovered that the engine suffers from high methane slip emission. Serious questions are raised about the quantity of methane slip during marine conditions when the load varies in multiple frequencies and amplitudes. Previous studies by these authors explained how methane slip increases during load oscillation. This paper examined several practical methods to reach stable combustion in transient conditions to reduce the methane slip. Employing Proportional-Integral-Derivative (PID) controllers in a closed loop, implementing open-loop lookup tables, model predictive controller (MPC), and an innovated solenoid method are performed in a high-fidelity medium-speed natural gas spark-ignition (SI) engine model.

One of the most important operating modes for SI engines is in the idle speed region. This is because SI engines spend a large part of their time operating in this mode. Moreover, a large measure of operator satisfaction is dependent on an engine operating smoothly and reliably in and around idle. In particular the operator expects that the idle speed will remain constant in spite of the engine loads due to power steering pumps and air conditioning compressors. In the idle speed region an SI engine is thought to be quite nonlinear because the engine loading can be quite significant, thus forcing the engine to be driven through a reasonably large portion of its lower operating range. Many of the earlier studies of idle speed control systems have dealt with linearized models which in principle have limited validity for the problem at hand. In order to improve this situation, it is necessary to deal with the more general nonlinear control problem.

Mean Value Engine Models (MVEMs) are dynamic models which describe dynamic engine variable (or state) responses as mean rather than instantaneous values on time scales slightly longer than an engine event. Such engine variables are the independent variables in nonlinear differential (or state) equations which can be quite compact but nevertheless quite accurate. One of the most important of the differential equations for a spark ignition (SI) engine is the intake manifold filling (often manifold pressure) state equation. This equation is commonly used to estimate the air mass flow to an SI engine during fast throttle angle transients to insure proper engine fueling. The purpose of this paper is to derive a modified manifold pressure state equation which is simpler and more physical than those currently found in the literature. This new formulation makes it easier to calibrate a MVEM for different engines and provides new insights into dynamic SI engine operation.

In general most engine models for control applications have been constructed using regressions fitting and measured engine data. Such techniques have also been used to model the dynamic performance of engines. Unfortunately regression equation models are very complex and do not show directly the physical reality from which they emerge. This has for example made it impossible to write down explicitly the dymanic equations for, for example, the air exchange process in an SI engine in any form other than as the manifold pressure state equation. In recent a publication a Mean Value Engine Model (MVEM) has been constructed for an SI engine which is physically based and which has a simple physical form which can be immediately understood and manipulated.

Aim of this work is to present and discuss the possibility and the limits of two zone models for spark-ignition engines using a detailed kinetic scheme for the characterization of the evolution of the air-fuel mixture, while an equilibrium approach is used for the burnt zone. Simple experimental measurements of knocking tendency of different fuels in ideal reactors, such as rapid compression machines and shock tube reactors, cannot be directly used for the analysis of octane numbers and sensitivity of hydrocarbon mixtures. Thus a careful investigation is very useful, not only of the combustion chamber behavior, including the modelling of the turbulent flame front propagation, but also of the fluid dynamic behavior of the intake and exhaust system, accounting for the volumetric efficiency of the engine.

The continuous pursuit of higher combustion efficiencies, as well as the possible usage of synthetic fuels with different properties than fossil-ones, require reliable and low-cost numerical approaches to support and speed-up engines industrial design. In this context, SI engines operated with homogeneous ultra-lean mixtures both characterized by a classical ignition configuration or equipped with an active prechamber represent the most promising solutions. In this work, for the classical ignition arrangement, a 3DCFD strategy to model the impact of the ignition system type on the CCV is developed using the RANS approach for turbulence modelling. The spark-discharge is modelled through a set of Lagrangian particles, whose velocity is modified with a zero-divergence perturbation at each discharge event, then evolved according to the Simplified Langevin Model (SLM) to simulate stochastic interactions with the surrounding gas flow.

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.

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.