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A simulation method is presented for the analysis of combustion in spark ignition (SI) engines operated at elevated exhaust gas recirculation (EGR) level and employing multiple spark plug technology. The modeling is based on a zero-dimensional (0D) stochastic reactor model for SI engines (SI-SRM). The model is built on a probability density function (PDF) approach for turbulent reactive flows that enables for detailed chemistry consideration. Calculations were carried out for one, two, and three spark plugs. Capability of the SI-SRM to simulate engines with multiple spark plug (multiple ignitions) systems has been verified by comparison to the results from a three-dimensional (3D) computational fluid dynamics (CFD) model. Numerical simulations were carried for part load operating points with 12.5%, 20%, and 25% of EGR. At high load, the engine was operated at knock limit with 0%, and 20% of EGR and different inlet valve closure timing.

The laminar burning speed is an important intrinsic property of an air-fuel mixture determining key combustion characteristics such as turbulent flame propagation. It is a function of the mixture composition (mixture fraction and residual gas mass fraction) and of the thermodynamic conditions. Experimental measurements of Laminar Flame Speeds (LFS) are common in literature, but initial pressure and temperature are limited to low values due to the test conditions: typical pressure values for LFS detection are lower than 25 bar, and temperature rarely exceeds 550 K. Actual trends in spark ignition engines are to increase specific power output by downsizing and supercharging, thus the flame front involves even more higher pressure and temperature since the beginning of combustion.

The performance optimization of modern Spark Ignition engines is limited by knock occurrence: heavily downsized engines often are forced to work in the Knock-Limited Spark Advance (KLSA) range. Knock control systems monitor the combustion process, allowing to achieve a proper compromise between performance and reliability. Combustion monitoring is usually carried out by means of accelerometers or ion sensing systems, but recently the use of cylinder pressure sensors is also becoming frequent in motorsport applications. On the other hand, cylinder pressure signals are often available in the calibration stage, where SA feedback-control based on the pressure signal can be used to avoid damages to the engine during automatic calibration. A predictive real-time combustion model could help optimizing engine performance, without exceeding the allowed knock severity.

This paper presents a methodology for the 3D CFD simulation of the intake and compression processes of four stroke internal combustion engines.The main feature of this approach is to provide very accurate initial conditions by means of a cost-effective initialization step. Calculations are applied to a low stroke-to-bore SI engine, operated at full load and maximum engine speed. It is demonstrated that initial conditions for this kind of engines have an important influence on flow field development, particularly in terms of mean velocities close to the firing TDC. Simulation results are used to discuss the choice of a set of parameters for the flow field characterization of low stroke-to-bore engines, as well as to provide an insight into the flow patterns during the overlapping period.

As a consequence of reduced fuel consumption, direct injection gasoline engines have already prevailed against port fuel injection. However, in-cylinder fuel homogenization strongly depends on charge motion and injection strategies and can be challenging due to the reduced available time for mixture formation. An insufficient homogenization has generally a negative impact on the combustion and therefore also on efficiency and emissions. In order to reach the targets of the intensified CO2 emission reduction, further increase in efficiency of SI engines is essential. In this connection, 0D/1D simulation is a fundamental tool due to its application area in an early stage of development and its relatively low computational costs. Certainly, inhomogeneities are still not considered in quasi dimensional combustion models because the prediction of mixture formation is not included in the state of the art 0D/1D simulation.

Knocking combustions heavily limits the efficiency of Spark Ignition engines. The compression ratio is limited in the design stage of the engine development, letting to Spark Advance control the task of reducing the odds of abnormal combustions. A detailed analysis of knocking events can help improving engine performance and diagnosis strategies. An effective way is to use advanced 3D CFD (Computational Fluid Dynamics) simulation for the analysis and prediction of combustion performance. Standard 3D CFD approach is based on RANS (Reynolds Averaged Navier Stokes) equations and allows the analysis of the mean engine cycle. However knocking phenomenon is not deterministic and it is heavily affected by the cycle to cycle variation of engine combustions. A methodology for the evaluation of the effects of CCV (Cycle by Cycle Variability) on knocking combustions is here presented, based on both the use of Computation Fluid Dynamics (CFD) tools and experimental information.

Over the years numerous researchers have suggested that the ionization current signal carries within it combustion relevant information. The possibility of using this signal for diagnostics and control provides motivation for continued research in this area. To be able to use the ion current signal for feedback control a reliable estimate of some combustion related parameter is necessary and therein lies the difficulty. Given the nature of the ion current signal this is not a trivial task. Fei An et al. [1] employed PCA for feature extraction and then used these feature vectors to design a neural network based classifier for the estimation of air to fuel ratio (AFR). Although the classifier predicted AFR with sufficient reliability, a major draw back was that the ion current signals used for prediction were averaged signals thus precluding a cycle to cycle estimate of AFR.

In the near future, emissions legislation will become more and more restrictive for direct injection SI engines by adopting a stringent limitation of particulate number emissions in late 2017. In order to cope with the combustion system related challenges coming along with the introduction of this new standard, Hitachi Automotive Systems Ltd., Hitachi Europe GmbH and IAV GmbH work collaboratively on demonstrating technology that allows to satisfy EU6c emissions limitations by application of Hitachi components dedicated to high pressure injection (1). This paper sets out to describe both the capabilities of a new high pressure fuel system improving droplet atomization and consequently mixture homogeneity as well as the process of utilizing the technology during the development of a demonstrator vehicle called DemoCar. The Hitachi system consists of a fuel pump and injectors operating under a fuel pressure of 30 MPa.

Water injection is becoming a technology of increasing interest for SI engines development to comply with current and prospective regulations. To perform a rapid optimization of the main parameters involved by the water injection process, it is necessary to have reliable CFD methodologies capable of capturing the most important phenomena. In the present work, a methodology for the CFD simulation of combustion cycles of SI GDI turbocharged engines under water injection operation is proposed. The ECFM-3Z model adopted for combustion and knock simulations takes advantages by the adoption of correlations for the laminar flame speed, flame thickness and ignition delay times prediction obtained by a detailed chemistry calculation. The latter uses machine learning algorithms to reduce the time to generate the full database while still maintaining an even distribution along the variables of interest.

Charge motion is known to accelerate and stabilize combustion through its influence on turbulence intensity and flame propagation. The present work investigates the effect of charge motion generated by intake runner blockages on combustion characteristics and emissions under part-load conditions in SI engines. Firing experiments have been conducted on a DaimlerChrysler (DC) 2.4L 4-valve I4 engine, with spark range extending around the Maximum Brake Torque (MBT) timing. Three blockages with 20% open area are compared to the fully open baseline case under two operating conditions: 2.41 bar brake mean effective pressure (bmep) at 1600 rpm, and 0.78 bar bmep at 1200 rpm. The blocked areas are shaped to create different levels of swirl, tumble, and cross-tumble. Crank-angle resolved pressures have been acquired, including cylinders 1 and 4, intake runners 1 and 4 upstream and downstream of the blockage, and exhaust runners 1 and 4.

The mixture formation processes of methane and air in an optical access engine operating steadily at 200 RPM have been explored in order to study charge inhomogeneity in a natural gas powered spark ignition engine during transient engine cranking. Planar Laser Induced Fluorescence has been used to create fuel/air equivalence ratio maps as a function of injection timing for various image planes at intervals throughout the intake and compression strokes. The work has been done using a Honda VTEC-E engine head that features port injection, four valves per cylinder, a pentroof style combustion chamber for the generation of tumble motion, and one nearly deactivated intake valve to generate swirl motion at low engine speeds in order to enhance mixing.

During the last years the deep re-examination of the engine design for lowering engine emissions involved two-wheel vehicles too. The IC engine overall efficiency plays a fundamental role in determining final raw emissions. From this point of view, the optimization of the in-cylinder flow organization is mandatory. In detail, in SI engines the generation of a coherent tumble vortex having dimensions comparable to the engine stroke could be of primary importance to extend the engines' ignition limits toward the field of the dilute/lean mixtures. For motorbike and motor scooter applications, the optimization of the tumble generation is considered an effective way to improve the combustion system efficiency and to lower emissions, considering also that the two-wheels layout represents an obstacle in adopting the advanced post-treatment concepts designed for automotive applications.

A physics-based simulation program developed by IAV is used to calibrate the torque structure and cylinder charge calculation in the electronic control unit of SI engines. The model calculates both the charge cycle and combustion phase based on flow mechanics and a fractal combustion model. Once the air mass in the charge cycle has been computed, a fractal combustion model is used for the ongoing calculation of cylinder pressure and temperature. The progression of cylinder pressure over the high and low-pressure phases also provides information on engine torque. Following the engine-specific calibration of the model using elemental geometric information and reduced test bench measurements, the physical engine properties can be simulated over the operating cycle. The calibrated model allows simulations to be carried out at all operating points and the results to be treated as virtual test bench measurements.

The ported shroud casing treatment for turbocharger compressors offers a wider operating flow range, elevated boost pressures at low compressor mass flow rates, and reduced broadband whoosh noise in spark-ignition internal combustion engine applications. However, the casing treatment elevates tonal noise at the blade-pass frequency (BPF). Typical rotational speeds of compressors employed in practice push BPF noise to high frequencies, which then promote multi-dimensional acoustic wave propagation within the compressor ducting. As a result, in-duct acoustic measurements become sensitive to the angular location of pressure transducers on the duct wall. The present work utilizes a steady-flow turbocharger gas stand featuring a unique rotating compressor inlet duct to quantify the variation of noise measured around the duct at different angular positions.

Due to the ever increasingly stringent emission regulations for passenger vehicles, the efficiency and performance increase of Spark Ignition (SI) engines have been under the focus of the engine manufacturers. The quest for efficiency and performance increase has led to the development of increasingly complex powertrains and control strategies. The development process requires novel methods that feature a smooth transition between the real and the virtual prototypes. Furthermore, to reduce the development time and cost, developing an engine simulator with a low computational effort and good accuracy, which predicts the engine behavior on the entire operating range, plays a crucial role. This work proposes an Artificial Intelligence-based engine simulator for a Spark Ignition engine. The simulator relies on Neural Networks for the calculation of the main combustion metrics. In the first part of this paper, the data acquired at the engine test cell are analyzed.

This work focuses on the development and validation of a data-driven model capable of predicting the maximum in-cylinder pressure during the operation of an internal combustion engine, with the least possible computational effort. The model is based on two parameters, one that represents engine load and another one the combustion phase. Experimental data from four different gasoline engines, two turbocharged Gasoline Direct Injection Spark Ignition, a Naturally Aspirated SI and a Gasoline Compression Ignition engine, was used to calibrate and validate the model. Some of these engines were equipped with technologies such as Low-Pressure Exhaust Gas Recirculation and Water Injection or a compression ignition type of combustion in the case of the GCI engine. A vast amount of engine points were explored in order to cover as much as possible of the operating range when considering automotive applications and thus confirming the broad validity of the model.

In-cylinder charge motion is known to significantly increase turbulence intensity, accelerate combustion rate, and reduce cyclic variation. This, in turn, extends the tolerance to exhaust gas recirculation (EGR), while the introduction of EGR results in much lowered nitrogen oxide (NOx) emissions and reduced fuel consumption. The present study investigates the effect of charge motion in a spark ignition engine on fuel consumption, combustion, and engine-out emissions with stoichiometric and EGR-diluted mixtures under part-load operating conditions. Experiments have been performed with a Chrysler 2.4L 4-valve I4 engine under 2.41 bar brake mean effective pressure at 1600 rpm over a spark range around maximum brake torque timing. The primary intake runners are partially blocked to create different levels of tumble, swirl, and cross-tumble (swumble) motion in the cylinder before ignition.

Electronic throttle control is increasingly being considered as a viable alternative to conventional air management systems in modern spark-ignition engines. In such a scheme, driver throttle commands are interpreted by the powertrain control module together with many other inputs; rather than directly commanding throttle position, the driver is now simply requesting torque - a request that needs to be appropriately interpreted by the control module. Engine management under these conditions will require optimal control of the engine torque required by the various vehicle subsystems, ranging from HVAC, to electrical and hydraulic accessories, to the vehicle itself. In this context, the real-time estimation of engine and load torque can play a very important role, especially if this estimation can be performed using the same signals already available to the powertrain control module.

The modern spark ignition engines, due to the introduced strategies for limiting the consumption without reducing the power, are sensitive to both the detonation and the increase of the inlet turbine temperature. In order to reduce the risk of detonation, the use of dilution with the products of combustion (EGR) is an established practice that has recently improved with the use of water vapor obtained via direct or indirect injection. The application and optimization of these strategies cannot ignore the knowledge of physical quantities characterizing the combustion such as the laminar flame speed and the ignition delay, both are intrinsic property of the fuel and are function of the mixture composition (mixture fraction and dilution) and of its thermodynamic conditions. The experimental measurements of the laminar flame speed and the ignition delay available in literature, rarely report the effects of dilution by EGR or water vapor.

Specific shifting of load points is an important approach in order to reduce the fuel consumption of gasoline engines. A potential measure is cylinder deactivation, which is used as a study example. Currently CO2 savings of new concepts are evaluated by dynamic cycles simulations. The fuel consumption during driving cycles is calculated based on consumption-optimized steady-state engine maps. Discrete load point shifts occur as shifts within maps. For reasons of comfort shifts require neutral torque. The work of deactivated cylinders must be compensated by active cylinders within one working cycle. Due to the larger time constant of the air path the air charge must be increased or decreased in order to deactivate or activate cylinders without affecting the torque. A working-cycle-resolved, continuously variable parameter is prerequisite for process control. Manipulation of ignition timing enables a reduction of efficiency and gained work.