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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.

In scooter/motorbike engines coherent and stable tumble motion generation is still considered an effective mean in order to both reduce engine emissions and promote higher levels of combustion efficiency. The scientific research also assessed that squish motion is an effective mean for speeding up the combustion in a combustion process already fast. In a previous technical paper the authors demonstrated that for an engine having a high C/D ratio the squish motion is not only not necessary but also detrimental for the stability of the tumble motion itself, because there is a strong interaction between these two motions with the consequent formation of secondary vortices, which in turn penalizes the tumble breakdown and the turbulent kinetic energy production.

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.

In the last years the automotive industry has been involved in the development and implementation of CO2 reducing concepts such as the engines downsizing, stop/start systems as well as more costly full hybrid solutions and, more recently, waste heat recovery technologies. These latter include ThermoElectric Generator (TEG), Rankine cycle and Electric Turbo Compound (ETC) that have been practically implemented on few heavy-duty application but have not been proved yet as effective and affordable solutions for the automotive industry. The paper deals with the analysis of opportunities and challenges of the Electric Turbo Compound for automotive light-duty engines. In the ETC concept the turbine-compressor shaft is connected to an electric machine, which can work either as generator or motor. In the former case the power can satisfy the vehicle electrical demand to drive the auxiliaries or stored in the batteries.

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.

To accurately evaluate the energy consumption benefits provided by connected and automated vehicles (CAV), it is necessary to establish a reasonable baseline virtual driver, against which the improvements are quantified before field testing. Virtual driver models have been developed that mimic the real-world driver, predicting a longitudinal vehicle speed profile based on the route information and the presence of a lead vehicle. The Intelligent Driver Model (IDM) is a well-known virtual driver model which is also used in the microscopic traffic simulator, SUMO. The Enhanced Driver Model (EDM) has emerged as a notable improvement of the IDM. The EDM has been shown to accurately forecast the driver response of a passenger vehicle to urban and highway driving conditions, including the special case of approaching a signalized intersection with varying signal phases and timing. However, most of the efforts in the literature to calibrate driver models have focused on passenger vehicles.

The software design of this new engine control unit is based on a unique and homogenous torque structure. All input signals are converted into torque equivalents and a torque coordinator determines their influence on the final torque delivered to the powertrain. The basic torque structure is independent on the type of fuel and can be used for gasoline, diesel, or CNG injection systems. This allows better use of custom specific algorithms and facilitates reusability, which is supported by the graphical design tool that creates all modules using automatic code generation. Injection specific algorithms can be linked to the software by simply setting a software switch.

Over the last decade, many methods have been proposed for estimating the in-cylinder combustion pressure or the torque from instantaneous crankshaft speed measurements. However, such approaches are typically computationally expensive. In this paper, an entirely different approach is presented to allow the real-time estimation of the in-cylinder pressures based on crankshaft speed measurements. The technical implementation of the method will be presented, as well as extensive results obtained for a V-6 S.I. engine while varying spark timing, engine speed, engine load and EGR. The method allows to estimate the in-cylinder pressure with an average estimation error of the order of 1 to 2% of the peak pressure. It is very general in its formulation, is statistically robust in the presence of noise, and computationally inexpensive.

Nowadays, an automotive DI Diesel engine is demanded to provide an adequate power output together with limit-complying NOx and soot emissions so that the development of a specific combustion concept is the result of a trade-off between conflicting objectives. In other words, the development of a low-emission DI diesel combustion concept could be mathematically represented as a multi-objective optimization problem. In recent years, genetic algorithm and CFD simulations were successfully applied to this kind of problem. However, combining GA optimization with actual CFD-3D combustion simulations can be too onerous since a large number of simulations is usually required, resulting in a high computational cost and, thus, limiting the suitability of this method for industrial processes.

Fuels are formulated by a variety of different components characterized by chemical and physical properties spanning a wide range of values. Changing the ratio between the mixture component molar fractions, it is possible to fulfill different requirements. One of the main properties that can be strongly affected by mixture composition is the volatility that represents the fuel tendency to vaporize. For example, changing the mixture ratio between alcohols and hydrocarbons, it is possible to vary the mixture saturation pressure, therefore the fuel vaporization ratio during the injection process. This paper presents a 1D numerical model to simulate the superheated injection process of a gasoline-ethanol mixture through real nozzle geometries. In order to test the influence of the mixture properties on flash atomization and flash evaporation, the simulation is repeated for different mixtures characterized by different gasoline-ethanol ratio.

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.

In power-split configuration, the input power is split into two parts, one of which is transmitted from the internal combustion engine through one or more planetary gear(s) to the wheels. The other part is generated as electricity and passes through an electrical variator to assist the driving torque. The latter has the characteristic of poor efficiency. In this simulation study, a comparison among the input power-split, compound power-split, and two mode power-split are discussed. Output power-split is not mentioned in this paper due to its limited applicability in specific vehicles. The idea of selection of the electrical machines is explained: the speed and torque of electrical machines was taken into consideration for the required transmission ratios spread.

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.

The combination of geometrically variable compression (VCR) and early intake valve closure (EIVC) proved to offer high potential for increasing efficiency of gasoline engines. While early intake valve closure reduces pumping losses, it is detrimental to combustion quality and residual gas tolerance due to a loss of temperature and turbulence. Large geometric compression ratio at part load compensates for the negative temperature effect of EIVC with further improving efficiency. By optimizing the stroke/bore ratio, the reduction in valve cross section at part load can result in greater charge motion and therefore in turbulence. Turbocharging means the basis to enable an increase in stroke/bore ratio, called β in the following, because the drawbacks at full load resulting from smaller valves can be only compensated by additional boosting pressure level.

In the field of passenger car engines, recent research advances have proven the effectiveness of downsized, turbocharged and direct injection concepts, applied to gasoline combustion systems, to reduce the overall fuel consumption while respecting particularly stringent exhaust emissions limits. Knock and turbocharger control are two of the most critical factors that influence the achievement of maximum efficiency and satisfactory drivability, for this new generation of engines. The sound emitted from an engine encloses many information related to its operating condition. In particular, the turbocharger whistle and the knock clink are unmistakable sounds. This paper presents the development of real-time control functions, based on direct measurement of the engine acoustic emission, captured by an innovative and low cost acoustic sensor, implemented on a platform suitable for on-board application.

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.

Standard compressor and turbine maps obtained from steady-state test bench measurements are not sufficient for assessing transient turbocharger behavior. This also makes them inappropriate for gauging combustion-engine response and fuel consumption. Nor do they allow for the widely differing operating conditions which, apart from aerodynamics, have a major influence on heat transfer and turbocharger efficiency. This paper looks at a more complex approach of modeling the turbocharger as well developing appropriate measurement methods (“advanced turbocharger model”). This includes non-destructive measurements under various heat transfer conditions to define the turbocharger's adiabatic behavior needed to describe charge-air pressure increase in the compressor and engine exhaust gas backpressure from the turbine for transient engine operation.