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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.

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.

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 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.

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.

In order to satisfy environmental regulations while maintaining strong performance and excellent fuel economy, advanced diesel engines are employing sophisticated air breathing systems. These include high pressure and low pressure EGR (Hybrid EGR), intake and exhaust throttling, and variable turbine geometry systems. In order to optimize the performance of these sub-systems, system level controls are necessary. This paper presents the design, benefits and test results of a model-based air system controller applied to an automotive diesel engine.

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.

Knock control systems based on engine block vibrations analysis are widely adopted in passenger car engines, but such approach shows its main limits at high engine speeds, since knock intensity measurement becomes less reliable due to the increased background mechanical noise. For small two wheelers engines, knock has not been historically considered a crucial issue, mainly due to small-sized combustion chambers and mixture enrichment. Due to more stringent emission regulations and in search of reduced CO2 emissions, an effective on-board knock controller acquires today greater importance also for motorcycle applications, since it could protect the engine when different fuel types are used, and it could significantly reduce fuel consumption (by avoiding lambda enrichment and/or allowing higher compression ratios to be adopted). These types of engines typically work at high rotational speeds and the reduced signal to noise ratio makes knock onset difficult to identify.

The increasing environmental concern is leading to the need for innovation in the field of internal combustion engines, in order to reduce the carbon footprint. In this context, hydrogen is a possible mid-term solution to be used both in conventional-like internal combustion engines and in fuel cells (for hybridization purposes), thus, hydrogen combustion characteristics must be considered. In particular, the flame of a hydrogen combustion is less subjected to the quenching effect caused by the engine walls in the combustion chamber. Thus, the significant heating up of the thin lubricant layer upon the cylinder liner may lead to its evaporation, possibly and negatively affecting the combustion process, soot production. The authors propose an analysis which aims to address the behavior of different typical engine oils, (SAE0W30, SAE5W30, SAE5W40) under engine thermo-physical conditions considering a large hydrogen-fuelled engine.

A practical Gasoline Compression Ignition (GCI) concept is presented that works on standard European 95 RON E10 gasoline over the whole speed/load range. A spark is employed to assist the gasoline autoignition at low loads; this avoids the requirement of a complex cam profile to control the local mixture temperature for reliable autoignition. The combustion phasing is controlled by the injection pattern and timing, and a sufficient degree of stratification is needed to control the maximum rate of pressure rise and prevent knock. With active control of the swirl level, the combustion system is found to be relatively robust against variability in charge motion, and subtle differences in fuel reactivity. Results show that the new concept can achieve very low fuel consumption over a significant portion of the speed/load map, equivalent to diesel efficiency. The efficiency is worse than an equivalent diesel engine only at low load where the combustion assistance operates.

Combustion phasing is crucial to achieve high performance and efficiency: for gasoline engines control variables such as Spark Advance (SA), Air-to-Fuel Ratio (AFR), Variable Valve Timing (VVT), Exhaust Gas Recirculation (EGR), Tumble Flaps (TF) can influence the way heat is released. The optimal control setting can be chosen taking into account performance indicators, such as Indicated Mean Effective Pressure (IMEP), Brake Specific Fuel Consumption (BSFC), pollutant emissions, or other indexes inherent to reliability issues, such as exhaust gas temperature, or knock intensity. Given the high number of actuations, the calibration of control parameters is becoming challenging.

The recent advance in the development of various hybrid vehicle technologies comes along with the need of establishing optimal energy management strategies, in order to minimize both fuel economy and pollutant emissions, while taking into account an increasing number of state and control variables, depending on the adopted hybrid architecture. One of the objectives of this research was to establish benchmarking performance, in terms of fuel economy, for real time on-board management strategies, such as ECMS (Equivalent Consumption Minimization Strategy), whose structure has been implemented in a SIMULINK model for different hybrid vehicle concepts.

Advanced Diesel combustion strategies with the focus on the reduction of NOx and PM emission as well as fuel consumption need an increase of the EGR rate and therefore improved boost concepts. The suppression of the nitrogen oxide build up requires changes in the charge condition (charge temperature, EGR rate), which have to be realized by the gas exchange system. The gas exchange system of IAV's ADCS test engine was dimensioned with the help of the engine process simulation software THEMOS®. This paper shows simulation and test bench results of the potential to increase the EGR rate and the charge density at stationary and transient operation. The increase of both EGR rate and boost pressure, as well as the need for a better control of transient operation leads to greater requirements for the engine control system. The potential of the engine and its control system for an application to a demo vehicle will be assessed.

Recent years have witnessed a dramatic increase in global ethanol production, while cellulosic feedstock or the algae-based production approach make more sustainable ethanol production foreseeable in many countries. The ethanol produced will increasingly penetrate the markets not only as blending component, but also as main fuel component, boosting demand for flex-fuel vehicles. One of the main challenges for flex-fuel vehicles is the cold start due to the poor vapor pressure of ethanol. This is detrimental to starting capability in DISI engines in particular, with increased cylinder wall wetting causing higher oil dilution. The most efficient solution for DISI engines is a smart injection strategy, enabling fuel vaporization during injection in the compression stroke. But this requires optimum injection parameters such as injection timing, split ratio and rail pressure.

A detailed analysis of knocking events can help improving engine performance and diagnosis strategies. The paper aim is a better understanding of the phenomena involved in knocking combustions through the combination of CFD and signals analysis tools. CFD simulations have been used in order to reproduce knock effect on the in-cylinder pressure trace. In fact, the in-cylinder pressure signal holds information about waves propagation and heat losses: for the sake of the diagnosis it is important to relate knock severity to knock indexes values. For this purpose, a CFD model has been implemented, able to predict the combustion evolution with respect to Spark Advance, from non-knocking up to heavy knocking conditions. The CFD model validation phase is crucial for a correct representation of both regular and knocking combustions: the operation has been carried out by means of an accurate statistical analysis of experimental in-cylinder pressure data.

This paper presents an optimization algorithm, based on discrete dynamic programming, that aims to find the optimal control inputs both for energy and thermal management control strategies of a Plug-in Hybrid Electric Vehicle, in order to minimize the energy consumption over a given driving mission. The chosen vehicle has a complex P1-P4 architecture, with two electrical machines on the front axle and an additional one directly coupled with the engine, on the rear axle. In the first section, the algorithm structure is presented, including the cost-function definition, the disturbances, the state variables and the control variables chosen for the optimal control problem formulation. The second section reports the simplified quasi-static analytical model of the powertrain, which has been used for backward optimization. For this purpose, only the vehicle longitudinal dynamics have been considered.