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In order to meet the stricter and stricter emission regulations, cleaner combustion concepts for Diesel engines are being progressively introduced. These new combustion approaches often requires closed loop control systems with real time information about combustion quality. The most important parameter for the evaluation of combustion quality in internal combustion engines is the in-cylinder pressure, but its direct measurement is very expensive and involves an intrusive approach to the cylinder. Previous researches demonstrated the direct relationship existing between in-cylinder pressure and engine block vibration signal and several authors tried to reconstruct the pressure cycle on the basis of information coming from accelerometers mounted on engine block. This paper proposes a method, based on the analysis of the engine vibration signal, for the diagnosis of combustion process in a Diesel engine.

The use of oxygenated and renewable fuels is nowadays a widespread means to reduce regulated pollutant emissions produced by internal combustion engines, as well as to reduce the greenhouse impact of transportation. Besides PM, NOx and HC emissions, also the size distribution of particles emitted at the engine exhaust represent meaningful information, considering its adverse effects on the environment and human health. In this work, the results of a comprehensive investigation on the combustion characteristics and the exhaust emissions of a GDI high performance engine, fuelled with pure bio-ethanol and European gasoline, are shown. The engine is a 4-cylinder, 4-stroke, 1750 cm₃ displacement, and turbocharged. The engine was operated at different speed/load conditions and two fuel injection strategies were investigated: homogeneous charge mode and stratified charge mode.

Unregulated emissions of polycyclic aromatic hydrocarbons (PAHs), carbonylic compounds, benzene and particulate matter (PM) were quantified in exhausts of a vehicle fleet representative of in use gasoline cars. Emission factors were obtained during both cold and hot start driving cycles (from urban to motorway driving conditions). Carbonylic compounds were sampled by DNPH cartridges and analyzed by HPLC. Benzene and other light hydrocarbons were collected in bags and then analyzed by GC-FID. PAHs were trapped in XAD-2 cartridges and then analyzed by GC-MS. PM was sampled by using the gravimetric procedure required for diesel cars. The effect of technology is significant with respect to regulated and unregulated emissions but different emissive behavior was found by varying the driving cycles. Cold start has a major influence on hydrocarbon emissions (included unregulated ones). This experimental work was carried out within the framework of the EU Artemis project.

In the last years, increasing concerns about environmental pollution and fossil sources depletion led transport sectors research and development towards the study of new technologies capable to reduce vehicles emissions and fuel consumption. Direct-injection systems (DI) for internal combustion engines propose as an effective way to achieve these goals. This technology has already been adopted in Gasoline Direct Injection (GDI) engines and, lately, a great interest is growing for its use in natural gas fueling, so increasing efficiency with respect to port-fuel injection ones. Alone or in combination with other fuels, compressed natural gas (CNG) represents an attractive way to reduce exhaust emission (high H/C ratio), can be produced in renewable ways, and is more widespread and cheaper than gasoline or diesel fuels. Gas direct-injection process involves the occurrence of under-expanded jets in the combustion chamber.

Detailed experimental information on the early stages of spark ignition process represent a substantial part for guiding the development of engines with higher efficiencies and reduced pollutant emissions. Flame kernel formation influences strongly combustion development inside the cylinder, especially for a direct injection spark ignition engine. This study presents the analysis of the evolution of spark-ignited flame kernels with detailed view upon cycle-to-cycle variations. Experiments are performed in a SI optical engine equipped with the cylinder head and injection system of a commercial turbocharged engine. Blend of commercial gasoline and butanol (40% by volume) is tested at stoichiometric and lean mixture conditions. Experiments are carried out at 2000 rpm through conventional tests (based on in-cylinder pressure measurements and exhaust emission analysis) and through optical diagnostics. In particular, UV-visible digital imaging and natural emission spectroscopy are applied.

In this work, optical diagnostics were applied in a transparent DI diesel engine equipped with the head of Euro5 commercial engine and the last generation CR injection system. In order to realize the PCCI combustion the injection of neat bio-ethanol was performed in the intake manifold and European commercial diesel fuel was injected into the cylinder. Different amounts of bio-ethanol were injected in order to create PCCI combustion with high levels of pre-combustion mixing, and to ensure low equivalence ratio and low flame temperatures too. UV-Visible imaging and spectroscopic measurements were performed in the engine in order to investigate the autoignition of the charge and the combustion process, respectively. In particular, the detection of the species involved in the combustion, like OH, HCO, and CH, was performed. The relevance of the radicals and species on PCCI were evaluated and compared with the data from thermodynamic analysis.

Premixed charge compression ignition (PCCI) has been shown to be a promising strategy to simultaneously reduce emissions while realizing improved fuel economy. PCCI combustion uses high levels of pre-combustion mixing to lower both NOx and soot emissions by ensuring low equivalence ratio and low flame temperatures. The high level of pre-combustion mixing results in a primarily kinetics controlled combustion process. In this work, optical diagnostics have been applied in a transparent DI diesel engine equipped with the head of Euro5 commercial engine and the last generation CR injection system. In order to realize the PCCI combustion the injection of neat ethanol has been performed in the intake manifold. The engine run in continuous way at 1500 rpm engine speed and commercial diesel fuel has been injected into the cylinder. The PCCI combustion has been analyzed by means of UV- Visible digital imaging and the mixing process, the autoignition of the charge have been investigated.

Spectral flame emissivity and absorption measurements with high temporal and spatial resolution were performed in an optically accessible high-swirl divided-chamber Diesel system. Simultaneous determination of soot temperature, soot volume fraction and the OH radical concentration were made from the start to the end of the combustion in 153 locations equally distributed in the chamber. The engine was run at 2000 rpm and at fixed air-fuel ratio realizing 200 consecutive combustion cycles. To visualize the spatial and temporal spray and flame evolution, direct high-speed photographic sequences were taken at 8000 frames/s. The photographic sequences showed that the spray is strongly distorted and mixed by very high swirl resulting in a well premixed region where the combustion starts. The OH radicals were detected in the fuel reaction zone. Moreover OH concentration and soot volume fraction are well correlated with soot temperature.

Gasoline direct injection (GDI) engines are characterized by complex phenomena involving spray dynamics and possible spray-wall interaction. Control of mixture formation is indeed fundamental to achieve the desired equivalence ratio of the mixture, especially at the spark plug location at the time of ignition. Droplet impact on the piston or liner surfaces has also to be considered, as this may lead to gasoline accumulation in the liquid form as wallfilm. Wallfilms more slowly evaporate than free droplets, thus leading to local enrichment of the charge, hence to a route to diffusive flames, increased unburned hydrocarbons formation and particulate matter emissions at the exhaust. Local heat transfer at the wall obviously changes if a wallfilm is present, and the subtraction of the latent heat of vaporization necessary for secondary phase change is also an issue deserving a special attention.

This study aims at building efficient and robust artificial neural networks (ANN) able to reconstruct the in-cylinder pressure of Diesel engines and to identify engine conditions starting from the signal of a low-cost accelerometer placed on the engine block. The accelerometer is a perfect non-intrusive replacement for expensive probes and is prospectively suitable for production vehicles. In this view, the artificial neural network is meant to be efficient in terms of response time, i.e. fast enough for on-line use. In addition, robustness is sought in order to provide flexibility in terms of operation parameters. Here we consider a feed-forward neural network based on radial basis functions (RBF) for signal reconstruction, and a feed-forward multi-layer perceptron network with tan-sigmoid transfer function for signal classification. The networks are trained using measurements from a three-cylinder real engine for various operating conditions.

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 fuel 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.

A modified version of KIVA II code was used to perform three-dimensional calculations of combustion in a DI diesel engine. Both an ignition delay submodel and a different formulation of the fuel reaction rate were implemented and tested. The experiments were carried out on a single cylinder D.I. diesel of 0.75 I displacement equipped with sensors to detect injection characteristics and indicated pressure. A fast acting sampling valve was also installed in the combustion chamber to allow the measurement of main pollutants during the combustion cycle, by an ensemble average technique. Computational and experimental results are compared and the discrepancies are discussed. Today the demand for light duty engines that produce less emission and consume less fuel is increasing. Thus, if limits on CO2 emissions are established, the direct injection diesel engine for light duty applications will become an attractive option.

In the present work, an Auto Regressive Moving Average (ARMA) model and a Discrete Wavelet Transform (DWT) are applied on vibrational signals, acquired by an accelerometer placed on the cylinder block of a Spark Ignition (SI) engine, for knock detection purposes. To the aim of tuning such procedures, the same analysis has been carried out by using the traditional MAPO (Maximum Amplitude of Pressure Oscillations) index and an Inverse Kinetic Model (IKM), both applied on the in-cylinder pressure signals. Vibrational and in-cylinder pressure signals have been collected on a four cylinder, four stroke engine, for different engine speeds, load conditions and spark advances. The results of the two vibrational based methods are compared and in depth discussed to the aim of highlighting the pros and cons of each methodology.

The present paper describes the results of a cooperative research project between GM Powertrain Europe and Istituto Motori - CNR aimed at studying the capability of GM Combustion Closed-Loop Control (CLCC) in enabling seamless operation with high biodiesel blending levels in a modern diesel engine for passenger car applications. As a matter of fact, fuelling modern electronically-controlled diesel engines with high blends of biodiesel leads to a performance reduction of about 12-15% at rated power and up to 30% in the low-end torque, while increasing significantly the engine-out NOx emissions. These effects are both due to the interaction of the biodiesel properties with the control logic of the electronic control unit, which is calibrated for diesel operation. However, as the authors previously demonstrated, if engine calibration is re-tuned for biodiesel fuelling, the above mentioned drawbacks can be compensated and the biodiesel environmental inner qualities can be fully deployed.

The effect of different fuel parameters on emissions is difficult to understand, the response depending upon different engine technologies. In addition the isolation of some of the fuel variables is often very hard. The present paper discusses the main results obtained testing a matrix of 14 fuels designed for obtain large variations of cetane number, sulphur and aromatic contents of Diesel oil. The aromatic structure of fuels and its effect on particulate emissions was also investigated. A linear regression analysis was performed in order to isolate the main controlling factors on particulate emissions. Finally the influence of aromatic contents of fuel on unregulated emissions was also assessed.

With the advent of the KIVA-4 code which employs an unstructured mesh to represent the engine geometry, the gap in flexibility between commercial and research modeling software becomes more narrow. In this study, we tried to perform a full cycle simulation of a 4-stroke HD diesel engine represented by a highly boosted research IF (Isotta Fraschini) engine using the KIVA-4 code. The engine mesh including the combustion chamber, intake and exhaust valves and helical manifolds was constructed using optional O-Grids catching a complex geometry of the engine parts with the help of the ANSYS ICEM CFD software. The KIVA-4 mesh input was obtained by a homemade mesh converter which can read STAR-CD and CFX outputs. The simulations were performed on a full 360 deg mesh consisting of 300,000 unstructured hexahedral cells at BDC. The physical properties of the liquid fuel were taken corresponding to those of real diesel #2 oil.

The evaluation of vehicles real emissions circulating in urban areas is a basic activity for planning and management of implemented traffic measures aiming at emission control and air quality improvement. National, region, and city emission inventories require overall average emission estimation based on modeling technique with a few input parameters such as fleet composition and mission profile, represented by average speed. But in the field of emission modeling an important open issue is the very expensive costs of experimental campaigns needed to obtain driving cycle statistically representative of driving behavior, also if only in a specific link of a network. A possible approach to deal with this problem is represented by the use of traffic microscopic simulation models which are capable to simulate individual car motion on the basis of traffic conditions, road characteristics and management rules.

Internal combustion engines are characterized by high pressure and thermal loads on pistons and in cylinders. The heat generated by the combustion process is dissipated by means of water and oil cooling systems. For the best design and optimization of the engine components it is necessary to know the components temperature in order to estimate the thermal flows. The purpose of this work is to measure the piston sapphire window temperature in a research optically accessible engine by combining two different techniques: measurements with templugs and with thermography. The method is very simple and can provide a reliable value of temperature within a small interval. It fits well for applications inside the engine because of its low technical level requirements. It consists of application of temperature sensitive stickers on the target component that makes it a very robust method, not affected by piston movement.

Nowadays, the regulation regards only the particles larger than 23 nm. The attention is shifting towards the sub-23 nm particles because of their large presence at the exhaust of the modern engines and their negative impact on human health. The main challenge of the regulation of these particles is the definition of a proper procedure for their measure. The nature of the sub-23 nm particles is not well understood, and their measure is strongly affected by the sampling conditions leading to not reliable measure. The aim of this paper is to provide information on the emissions of sub-23 nm particles from GDI vehicles/engines. At the same time, the presence of volatiles, which mainly contribute to the formation of sub-23 nm particles, was evaluated and the effect of sampling conditions was investigated. The analysis was performed on a 1.8L GDI powered vehicle, widely used both in North America and Europe, and a 4-cylinder GDI engine, whose features are similar to those of the vehicle.

In the global scenario of encouraging the use of renewable sources, the bioethanol as fuel supply in the automotive sector is receiving increasing interest. In the present paper the results of a research activity aimed to study the impact of a bioethanol/biodiesel/mineral diesel blend on performance and emissions of an automotive diesel engine are reassumed. An experimental campaign has been devoted to characterize the engine fuelled by the ethanol based blend highlighting the advantages and issues related to the bioethanol use. Moreover, the effects of the most important injection settings on the engine performance have been detailed, applying a Design of Experiment (DoE) method, to identify the potentiality offered by a proper engine calibration to optimize the ethanol blend use.