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The present paper describes the first results of a cooperative research project between GM Powertrain Europe and Istituto Motori of CNR aimed at studying the impact of Fatty-Acid Methyl Esters (FAME) and gas-to-liquid (GTL) fuel blends on the performance, emissions and fuel consumption of modern automotive diesel engines. The tests were performed on the architecture of GM 1.9L Euro4 diesel engine for passenger car application, both on optical single-cylinder and on production four-cylinder engines, sharing the same combustion system configuration. Various blends of biodiesels as well as reference diesel fuel were tested. The experimental activity on the single-cylinder engine was devoted to an in-depth investigation of the combustion process and pollutant formation, by means of different optical diagnostics techniques, based on imaging multiwavelength spectroscopy.

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.

An innovative quasi-dimensional multizone combustion model for the spray formation, combustion and emission formation analysis in DI diesel engines was assessed and applied to an optical single cylinder engine. The model, which has been recently presented by the authors, integrates a predictive non stationary 1D spray model developed by the Sandia National Laboratory, with a diagnostic multizone thermodynamic model. The 1D spray model is capable of predicting the equivalence ratio of the fuel during the mixing process, as well as the spray penetration. The multizone approach is based on the application of the mass and energy conservation laws to several homogeneous zones identified in the combustion chamber. A specific submodel is also implemented to simulate the dilution of the burned gases. Soot formation is modeled by an expression which derives from Kitamura et al.'s results, in which an explicit dependence on the local equivalence ratio is considered.

In this study, experiments were carried out in an optical single-cylinder Direct Injection Spark Ignition engine fuelled with n-butanol and gasoline, alternatively. The engine is equipped with the head of a commercial turbocharged engine with similar geometrical specifications (bore, stroke, compression ratio). The head has four valves and a centrally located spark device with surface charge ignition. A conventional elongated hollow Bowditch piston is used and an optical crown, accommodating fused-silica window, is screwed onto it. The injector is side mounted and features 6 holes oriented to guide the jets towards the piston crown. During the experimental activity, the injection pressure was maintained at 100 bar for all conditions; the injection timing and the number of injections were adjusted to investigate their influence on combustion and emissions.

In view of the new emission regulations seeking to lower the particle cut-off size down to the current 23 nm, an extensive comprehension on the nature of sub-23 nm particles is crucial. In this regard, a new challenge lies ahead considering an even more massive use of biofuels. The objective of this research study was to characterize the sub-23 nm particles and to evaluate their volatile organic fraction (VOF) from a high performance, 1.8 L gasoline direct injection (GDI) engine under the Worldwide harmonized Light vehicles Test Cycle (WLTC). Particle emissions were measured through an Engine Exhaust Particle Sizer (EEPS) capable of particle sizing and counting in the range 5.6 - 560 nm. The sampling and conditioning were performed by both a single diluter and the Dekati Engine Exhaust Diluter (DEED) a Particle Measurement Programme (PMP) compliant sample conditioning system.

Many aspects of battery electric vehicles are very challenging from the engineering point of view in terms of safety, weight, range, and drivability. Commercial vehicle engines are often subjected to high loads even at low speeds and this can lead to an intense increment of the battery pack temperature and stress of the cooling system. For these reasons the optimal design of the battery pack and the relative cooling system is essential. The present study deals with the challenge of designing a battery pack that satisfies both the conditions of lowest weight and efficient temperature control. The trade-off between the battery pack size and the electrical stress on the cells is considered. The electric system has the aim to substitute a 3.0 liters compression ignition engine mainly for commercial vehicles.

Methane supply in diesel engines operating in dual fuel mode has demonstrated to be effective for the reduction of particulate matter and nitric oxides emissions from this type of engine. In particular, methane is injected into the intake manifold to form a premixed charge with air, while a reduced amount of diesel oil is still directly injected to ignite the mixture inside the cylinder. As a matter of fact, the liquid fuel burns following the usual diffusive combustion, so activating the gaseous fuel oxidation in a premixed flame. Clearly, the whole combustion process appears to be more complex to be described in a CFD simulation, mainly because it is not always possible to select in the 3-dimensional codes a different combustion model for each fuel and, also, because other issues arise from the interaction of the two fuels.

Nowadays internal combustion engines can operate under lean combustion conditions to maximize efficiency, as long as combustion stability is guaranteed. The robustness of combustion initiation is one of the main issues of actual spark-ignition engines, especially at high level of excess-air or dilution. The enhancement of the in-cylinder global motion and local turbulence is an effective way to increase the flame velocity. During the ignition process, the excessive charge motion can hinder the spark discharge and eventually cause a misfire. In this perspective, the interaction between the igniter and the flow field is a fundamental aspect which still needs to be explored in more detail to understand how the combustion originates and develops. In this work, a combined experimental and numerical study is carried out to investigate the flow field around the spark gap, and its effect on the spark discharge evolution.

A growing number of electric vehicles (EV) and hybrid electric vehicles (HEV) in the present market depicts the rapid growing demand for energy storage systems. The battery’s main peculiarities must be the power density and reliability over time. The temperature strongly affects battery performance for low and high intensity. In particular, the management of the heat generated by the battery itself is one of the main aspects to handle to preserve the performance over time. The objective of this paper is to compare the surface temperature of the lithium-ion polymer battery at different discharging rates by infrared thermography. Thermal imaging is performed to detect the battery surface temperature distribution, focusing on its variation over time and the local inhomogeneity. Temperature measurements are then used to estimate the contributions of the different heat transfer mechanisms for the dissipation of the heat generated by the battery.

The electrochemical performance of a lithium-ion battery is strongly affected by the temperature. During charge and discharge cycles, batteries are subjected to an increment of temperature that can accelerate aging and loss of efficiency if critical values are reached. Knowing the thermal parameters that affect the heat exchange between the battery surface and the surrounding environment (air, cooling fins, plates, etc…) is fundamental to their thermal management. In this work, thermal imaging is applied to a laminated lithium-polymers battery as a non-invasive temperature-indication method. Measurements are taken during the discharge phase and the following cooling down until the battery reaches the ambient temperature. The 2d images are used to analyze the homogeneity of the temperature distribution on the battery surface. Then, experimental results are coupled with mathematical correlations.

Growing concerns about the emissions of internal combustion engines have forced the adoption of aftertreatment devices to reduce the adverse impact of diesel engines on health and environment. Diesel particulate filters are considered as an effective means to reduce the particle emissions and comply with the regulations. Research activity in this field focuses on filter configuration, materials and aging, on understanding the variation of soot layer properties during time, on defining of the optimal strategy of DPF management for on-board control applications. A model was implemented in order to simulate the filtration and regeneration processes of a wall-flow particulate filter, taking into account the emission characteristic of the engine, whose architecture and operating conditions deeply affect the size distribution of soot particles.

The common realization of the necessity to reduce the use of mineral sources is promoting the use of alternative fuels. Big efforts are being made to replace petroleum derivatives in the internal combustion engines (ICEs). For this purpose it is mandatory to evaluate the behavior of non-conventional fuels in the ICEs. The optical diagnostics have proven to be a powerful tool to analyze the processes that take place inside the engine. In particular, 2d imaging in the infrared range can reveal new details about the effect of the fuel properties since this technique is still not very common. In this work, a comparison between commercial diesel fuel and two non-conventional fuels has been made in an optically accessible diesel engine. The non-conventional fuels are: the first generation biofuel Rapeseed Methyl Ester (RME) and an experimental blend of diesel and a fuel with high glycerol content (HG).

An investigation has been carried out on the spray penetration and soot formation processes in a research diesel engine by means of a quasi-dimensional multizone combustion model. The model integrates a predictive non stationary 1D spray model developed by the Sandia National Laboratory, with a diagnostic multizone thermodynamic model, and is capable of predicting the spray formation, combustion and soot formation processes in the combustion chamber. The multizone model was used to analyze three operating conditions, i.e., a zero load point (BMEP = 0 bar at 1000 rpm), a medium load point (BMEP = 5 bar at 2000 rpm) and a medium-high load point (BMEP = 10 bar at 2000 rpm). These conditions were experimentally tested in an optical single cylinder engine with the combustion system configuration of a 2.0L Euro4 GM diesel engine for passenger car applications.

A plasma ignition system was tested in a GDI engine with the target of combustion efficiency improvement without modifying engine configuration. The plasma was generated by spark discharge and successively sustained to enhance its duration up to 4 ms. The innovative ignition system was tested in an optically accessible single-cylinder DISI engine to investigate the effects of plasma on kernel stability and flame front propagation under low loads and lean mixture (λ≅1.3). The engine was equipped with the head of a commercial turbocharged engine with similar geometrical specifications (bore, stroke, compression ratio). All experiments were performed at 2000 rpm and 100 bar injection pressure. UV-visible 2D chemiluminescence was applied in order to study the flame front inception and propagation with particular interest in the early combustion stages. A bandpass filter allowed selecting luminous signal due to OH radicals.

The increasing limitations in engine emissions and fuel consumption have led researchers to the need to accurately predict combustion and related events in gasoline engines. In particular, knock is one of the most limiting factors for modern SI units, severely hindering thermal efficiency improvements. Modern CFD simulations are becoming an affordable instrument to support experimental practice from the early design to the detailed calibration stage. To this aim, combustion and knock models in RANS formalism provide good time-to-solution trade-off allowing to simulate mean flame front propagation and flame brush geometry, as well as “ensemble average” knock tendency in end-gases. Still, the level of confidence in the use of CFD tools strongly relies on the possibility to validate models and methodologies against experimental measurements.

Engine knock is one of the most limiting factors for modern Spark-Ignition (SI) engines to achieve high efficiency targets. The stochastic nature of knock in SI units hinders the predictive capability of RANS knock models, which are based on ensemble averaged quantities. To this aim, a knock model grounded in statistics was recently developed in the RANS formalism. The model is able to infer a presumed log-normal distribution of knocking cycles from a single RANS simulation by means of transport equations for variances and turbulence-derived probability density functions (PDFs) for physical quantities. As a main advantage, the model is able to estimate the earliest knock severity experienced when moving the operating condition into the knocking regime.

The occurrence of knock is the most limiting hindrance for modern Spark-Ignition (SI) engines. In order to understand its origin and move the operating condition as close as possible to onset of this potentially harmful phenomenon, a joint experimental and numerical investigation is the most recommended approach. A preliminary experimental activity was carried out at IM-CNR on a 0.4 liter GDI unit, equipped with a flat transparent piston. The analysis of flame front morphology allowed to correlate high levels of flame front wrinkling and negative curvature to knock prone operating conditions, such as increased spark timings or high levels of exhaust back-pressure. In this study a detailed CFD analysis is carried out for the same engine and operating point as the experiments. The aim of this activity is to deeper investigate the reasons behind the main outcomes of the experimental campaign.

With the aim of identifying technical solutions to lower the particulate matter emissions, the engine research community made a consistent effort to investigate the root causes leading to soot formation. Nowadays, the computational power increase allows the use of advanced soot emissions models in 3D-CFD turbulent reacting flows simulations. However, the adaptation of soot models originally developed for Diesel applications to gasoline direct injection engines is still an ongoing process. A limited number of studies in literature attempted to model soot produced by gasoline direct injection engines, obtaining a qualitative agreement with the experiments. To the authors’ best knowledge, none of the previous studies provided a methodology to quantitatively match particulate matter, particulate number and particle size distribution function measured at the exhaust without a case-by-case soot model tuning.

The present paper describes the results of a cooperative research project between GM Powertrain Europe and Istituto Motori - CNR aimed at studying the impact of both fresh and highly oxidized RME at two levels of blending on spray formation and combustion in modern automotive diesel engines. The tests were performed on an optical single-cylinder engine sharing combustion system configuration with the 2.0L Euro5 GM diesel engine for passenger car application. Two blends (B50 and B100) blending were tested for both fresh and aged RME and compared with commercial diesel fuel in two different operating points typical of NEDC (1500rpm/2bar BMEP and 2000rpm/5bar BMEP). The experimental activity was devoted to an in-depth investigation of the spray density, breakup and penetration, mixture formation, combustion and soot formation, by means of optical techniques.

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.