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The Injection Rate Shaping consists in a novel injection strategy to control air-fuel mixing quality via a suitable variation of injection timing that affects the injection rate profile. This strategy has already provided to be useful to increase combustion efficiency and reduce pollutant emissions in the modern compression ignition engines fed with fossil Diesel fuel. But nowadays, the ever more rigorous emission targets are enhancing a search for alternative fuels and/or new blends to replace conventional ones, leading, in turn, a change in the air-fuel mixture formation. In this work, a 1D model of spray injection aims to investigate the combined effects of both Injection Rate Shaping and alternative fuels on the air-fuel mixture formation in a compression ignition engine. In a first step, a ready-made model for conventional injection strategies has been set up for the Injection Rate Shaping.

The analysis of a spray behavior is confined to study the fluid dynamic parameters such as axial and radial velocity of the droplets, size distribution of the droplets, and geometrical aspect as the penetration length. In this paper, the spray is considered like a dynamic system and consequently it can be described by a number of parameters that characterize its dynamic behavior. The parameter chosen to describe the dynamic behavior is the external cone angle. This parameter has been detected by using an experimental injection chamber, a multi-hole (8 holes) injector for GDI applications and recorded by a high-speed C-Mos camera. The images have been elaborated by a fuzzy logic and neural network algorithm and are processed by using a chaos deterministic theory. This procedure carries out a map distribution of the working point of the spray and determines the stable (signature of the spray) and instable behavior.

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.

This paper reports the study of the effects of alternative diesel fuel and the impact for the air-fuel mixture preparation. The injection process characterization has been carried out in a non-evaporative high-density environment in order to measure the fuel injection rate and the spatial and temporal distribution of the fuel. The injection and vaporization processes have been characterized in an optically accessible single cylinder Common Rail diesel engine representing evaporative conditions similar to the real engine. The tests have been performed by means of a Bosch second generation common rail solenoid-driven fuel injection system with a 7-holes nozzle, flow number 440 cc/30s @100bar, 148deg cone opening angle (minisac type). Double injection strategy (pilot+main) has been implemented on the ECUs corresponding to operative running conditions of the commercial EURO 5 diesel engine.

In the present paper the status of development of diesel combustion and pollutants formation modelling at Diesel Engines and Fuels Research Division of Istituto Motori is pointed out. The main features and performances of the model are discussed comparing the numerical results with some experimental data. For the experiments a single cylinder direct injection diesel engine was used. In the head of the engine two small quartz windows have been mounted, in order to obtain pictures of the injection and combustion processes by high speed cinematography, and to apply the two colour technique for soot temperature and soot loading measurements. The soot loading was measured by the two colour technique and the a priori and the experimental uncertainties of the measurement technique were carefully evaluated. In addition, the engine may be also equipped with a second head, in which a fast acting valve allows the direct sampling of the combustion products.

The present paper reports 1D and 3D CFD analyses of the air-filter box of a turbocharged VVA engine, aiming to predict and improve the gas-dynamic noise emissions through a partial re-design of the device. First of all, the gas-dynamic noise at the intake mouth is measured during a dedicated experimental campaign. The developed 1D and 3D models are then validated at full load operation, based on experimental data. In particular, 1D model provides a preliminary evaluation of the radiated noise and simultaneously gives reliable boundary conditions for the unsteady 3D CFD simulations. The latter indeed allow to better take into account the geometrical details of the air-filter and guarantee a more accurate gas-dynamic noise prediction. 3D CFD analyses put in evidence that sound emission mainly occur within a frequency range of 350 to 450 Hz.

In the present paper, two different methodologies are adopted and critically integrated to analyze the knock behavior of a last generation small size spark ignition (SI) turbocharged VVA engine. Particularly, two full load operating points are selected, exhibiting relevant differences in terms of knock proximity. On one side, a knock investigation is carried out by means of an Auto-Regressive technique (AR model) to process experimental in-cylinder pressure signals. This mathematical procedure is used to estimate the statistical distribution of knocking cycles and provide a validation of the following 1D-3D knock investigations. On the other side, an integrated numerical approach is set up, based on the synergic use of 1D and 3D simulation tools. The 1D engine model is developed within the commercial software GT-Power™. It is used to provide time-varying boundary conditions (BCs) for the 3D code, Star-CD™.

The diesel particulate filters (DPF) are considered the most robust technologies for particle emission reduction both in terms of mass and number. On the other hand, the increase of the backpressure in the exhaust system due to the accumulation of the particles in the filter walls leads to an increase of the engine fuel consumption and engine power reduction. To limit the filter loading, and the backpressure, a periodical regeneration is needed. Because of the growing interest about particle emission both in terms of mass, number and size, it appears important to monitor the evolution of the particle mass and number concentrations and size distribution during the regeneration of the DPFs. For this matter, in the presented work the regeneration of a catalyzed filter was fully analyzed. Particular attention was dedicated to the dynamic evolution both of the thermodynamic parameters and particle emissions.

The use of lean or ultra-lean ratios is an efficient and proven strategy to reduce fuel consumption and pollutant emissions. However, the lower fuel concentration in the cylinder hinders the mixture ignition, requiring greater energy to start the combustion. The prechamber is an efficient method to provide high energy favoring the ignition process. It presents the potential to reduce the emission levels and the fuel consumption, operating with lean burn mixtures and expressive combustion stability. In this paper the analysis of the combustion process of SI engines equipped with an innovative architecture and operating in different injection modes was described. In particular, the effect of the prechamber ignition on the engine stability and the efficiency was investigated in stoichiometric and lean-burn operation conditions. The activity was carried out in two parts.

This paper is based on a Research Project of the Department of Mechanical Engineering (DiME) in collaboration with Aprilia, the Italian motorbike manufacturer. In an attempt to simulate the functioning of the cooling plant of the Aprilia RSV-4 motorbike a numerical model was constructed using mono-dimensional and three-dimensional simulation codes. Our ultimate aim was to create a simulation model which could be of assistance to engine designers to improve cooling plant performance, thereby reducing research and development costs. The model allows to simulate the running conditions of the whole cooling circuit upon variations in environmental and running conditions. In particular, the centrifugal pump of the cooling plant was simulated by a 3D commercial software, while the whole circuit was built by a 1D commercial code which allows simulation of all the thermal exchanges and pressure drops in the cooling circuit.

The growing concerns on the emission of particles smaller than 23 nm, which are harmful to human health, lead to the necessity of introducing a regulation for these particles not yet included in the current emission standards. Considering that measurements of concentration of sub-23 nm particles are particularly sensitive to the sampling conditions, it is important to identify an effective assessment procedure. Aim of this paper is the characterization of the effect of the sampling conditions on sub-23 nm particles, emitted by PFI (port fuel injection) and DI (direct injection) spark ignition engines fueled with gasoline, ethanol and a mixture of ethanol and gasoline (E30). The experimental activity was carried out on a 250 cm3 displacement four stroke GDI and PFI single cylinder engines. The tests were conducted at 2000 rpm and 4000 rpm full load, representative of the homologation urban driving cycle.

The application of more efficient compression ignition combustion concepts requires advancement in terms of fuel injection technologies. The injector nozzle is the most critical component of the whole injection system for its impact on the combustion process. It is characterized by the number of holes, diameter, internal shape, and opening angle. The reduction of the nozzle hole diameter seems the simplest way to promote the atomization process but the number of holes must be increased to keep constant the injected fuel mass. This logic has been applied to the development of a new generation of injectors. First, the tendency to increase the nozzle number and to reduce the diameter has led to the replacement of the nozzle with a circular plate. The vertical movement of the needle generates an annulus area for the fuel delivery on 360 degrees, so controlling the atomization as a function of the vertical plate position.

Application of more and more complex control strategies in spark ignition (SI) engines is required for ensuring high conversion efficiency and effective emissions reduction. Closed loop fuel injection is being implemented on an ever wider scale in small size SI units that generally feature single cylinder architecture. For such systems the readings from the exhaust gas oxygen sensor are essential for controlling air-fuel ratio and indirectly combustion. The present study looked at the influence of pressure oscillations on the values given by the sensor, for different equivalence ratio settings in wide open throttle conditions for an experimental SI unit. As expected, the readings were found to be influenced by pressure oscillations in the exhaust line during lean operation, while with stoichiometric and rich fueling the effects were minimal. Fuel type was also found to be an important aspect.

The introduction of new light-duty vehicle emission limits to comply under real driving conditions (RDE) is pushing the diesel engine manufacturers to identify and improve the technologies and strategies for further emission reduction. The latest technology advancements on the after-treatment systems have permitted to achieve very low emission conformity factors over the RDE, and therefore, the biggest challenge of the diesel engine development is maintaining its competitiveness in the trade-off “CO2-system cost” in comparison to other propulsion systems. In this regard, diesel engines can continue to play an important role, in the short-medium term, to enable cost-effective compliance of CO2-fleet emission targets, either in conventional or hybrid propulsion systems configuration. This is especially true for large-size cars, SUVs and light commercial vehicles.

The increasing diffusion of gasoline direct injection (GDI) engines requires a more detailed and reliable description of the phenomena occurring during the fuel injection process. As well known the thermal and fluid-dynamic conditions present in the combustion chamber greatly influence the air-fuel mixture process deriving from GDI injectors. GDI fuel sprays typically evolve in wide range of ambient pressure and temperatures depending on the engine load. In some particular injection conditions, when in-cylinder pressure is relatively low, flash evaporation might occur significantly affecting the fuel-air mixing process. In some other particular injection conditions spray impingement on the piston wall might occur, causing high unburned hydrocarbons and soot emissions, so currently representing one of the main drawbacks of GDI engines.

The numerical reconstruction of the liquid jet generated by a multi-hole injector, operating in flash-boiling conditions, has been developed by means of a Eulerian- Lagrangian CFD code and validated thanks to experimental data collected with schlieren and Mie scattering imaging techniques. The model has been tested with different injection parameters in order to recreate various possible engine thermodynamic conditions. The work carried out is framed in the growing interest present around the gasoline direct-injection systems (GDI). Such technology has been recognized as an effective way to achieve better engine performance and reduced pollutant emissions. High-pressure injectors operating in flashing conditions are demonstrating many advantages in the applications for GDI engines providing a better fuel atomization, a better mixing with the air, a consequent more efficient combustion and, finally, reduced tailpipe emissions.

The recent interest in alternative non-fossil fuels has led researchers to evaluate several alcohol-based formulations. However, one of the main requirements for innovative fuels is to be compatible with existing units’ hardware, so that full replacement or smart flexible-fuel strategies can be smoothly adopted. n-Butanol is considered as a promising candidate to replace commercial gasoline, given its ease of production from bio-mass and its main physical and chemical properties similar to those of Gasoline. The compared behavior of n-butanol and gasoline was analyzed in an optically-accessible DISI engine in a previous paper [1]. CFD simulations explained the main outcomes of the experimental campaign in terms of combustion behavior for two operating conditions. In particular, the first-order role of the slower evaporation rate of n-butanol compared to gasoline was highlighted when the two fuels were operated under the same injection phasing.

Data decomposition techniques have become a standard approach for the analysis of 2D imaging data originating from optically accessible internal combustion engines. In particular, the method of Proper Orthogonal Decomposition (POD) has proven to be a valuable tool for the evaluation of cycle-to-cycle variability based on luminous combustion imaging and particle image velocimetry (PIV) measurements. POD basically permits to characterize the dominant structures of the process under consideration. Recently, an alternative procedure based on Independent Component Analysis (ICA) has been introduced in the engine field. Unlike POD, the method of ICA identifies the patterns corresponding to physical processes that are statistically independent. In this work, a Group-ICA approach is applied to 2D cycle-resolved images of the luminosity emitted by the combustion process. The analysis is meant to characterize cyclic variability of a port fuel injection spark ignition (PFI SI) engine.

The paper reports an innovative method of analysis based on an advanced statistical techniques applied to images captured by a high-speed camera that allows highlighting phenomena and anomalies hardly detectable by conventional optical diagnostic techniques. The images, previously elaborated by neural network tools in order for clearly identifying the contours, have been analyzed in their time evolution as pseudo-chaotic variables that may have internal periodic components. In addition to the Fourier analysis, tools as Lyapunov and Hurst exponents and average Kω permitted to detect the chaos level of the signals. The use of this technique has permitted to distinguish periodic oscillations from chaotic variations and to detect those parameters that actually determine the spray behavior.

In the last years, even more attention was paid to the alternative fuels which can allow both reducing the fuel consumption and the pollutant emissions. Among gaseous fuels, methane is considered one of the most interesting in terms of engine application. It represents an immediate advantage over other hydrocarbon fuels leading to lower CO₂ emissions; if compared to gasoline, CH₄ has wider flammable limits and better anti-knock properties, but lower flame speed. The addition of H₂ to CH₄ can improve the already good qualities of methane and compensate its weak points. In this paper a comparison was carried out between CH₄ and different CH₄/H₂ mixtures. The measurements were carried out in an optically accessible small single-cylinder, Port Fuel Injection spark ignition (PFI SI), four-stroke engine. It was equipped with the cylinder head of a commercial 250 cc motorcycle engine representative of the most popular two-wheel vehicles in Europe.