Search Results

Biofuel usage is increasingly expanding thanks to its significant contribution to a well-to-wheel (WTW) reduction of greenhouse gas (GHG) emissions. In addition, stringent emission standards make mandatory the use of Diesel Particulate Filter (DPF) for the particulate emissions control. The different physical properties and chemical composition of biofuels impact the overall engine behaviour. In particular, the PM emissions and the related DPF regeneration strategy are clearly affected by biofuel usage due mainly to its higher oxygen content and lower low heating value (LHV). More specifically, the PM emissions and the related DPF regeneration strategy are clearly affected by biofuel usage due mainly to its higher oxygen content and lower low heating value, respectively. The particle emissions, in fact, are lower mainly because of the higher oxygen content. Subsequently less frequent regenerations are required.

The present paper describes some results of a research project aimed at studying the impact of alternative fuels blends on the emissions and fuel consumption of an Euro 5 automotive diesel engine. Two alternative fuels were chosen for the experiments: RME and GTL. The tests were done in the three most important operating conditions for the engine emission calibration. Moreover, the NOx-PM trade-off by means of EGR sweep was performed in the same operating conditions, in order to evaluate the engine EGR tolerability when burning low sooting fuels as the RME. The investigations put in evidence that the impact of the alternative fuels on modern diesel engines remains significant. This also depends on the interaction between the alternative fuel characteristics and the engine-management strategies, as described in detail in the paper.

Detailed chemistry and turbulence-chemistry interaction need to be properly taken into account for a realistic combustion simulation of IC engines where advanced combustion modes, multiple injections and stratified combustion involve a wide range of combustion regimes and require a proper description of several phenomena such as auto-ignition, flame stabilization, diffusive combustion and lean premixed flame propagation. To this end, different approaches are applied and the most used ones rely on the well-stirred reactor or flamelet assumption. However, well-mixed models do not describe correctly flame structure, while unsteady flamelet models cannot easily predict premixed flame propagation and triple flames. A possible alternative for them is represented by transported probability density functions (PDF) methods, which have been applied widely and effectively for modeling turbulent reacting flows under a wide range of combustion regimes.

Modeling combustion of transportation fuels remains a difficult task due to the extremely large number of species constituting commercial gasoline and diesel. However, for this purpose, multi-component surrogate fuel models with a reduced number of key species and dedicated reaction subsets can be used to reproduce the physical and chemical traits of diesel and gasoline, also allowing to perform CFD calculations. Recently, a detailed surrogate fuel kinetic model, named C3 mechanism, was developed by merging high-fidelity sub-mechanisms from different research groups, i.e. C0-C4 chemistry (NUI Galway), linear C6-C7 and iso-octane chemistry (Lawrence Livermore National Laboratory), and monocyclic aromatic hydrocarbons (MAHs) and polycyclic aromatic hydrocarbons (PAHs) (ITV-RWTH Aachen and CRECK modelling Lab-Politecnico di Milano).

In this study, tailpipe-sampling was used to sample the exhaust aerosol of a Stage IV tractor equipped with Diesel Oxidation Catalyst (DOC) and Selective Catalytic Reduction (SCR) aftertreatment systems. The particle emissions were characterized in terms of number concentration (particle size of > 2.5 nm), mass concentration (particle size of 6-612 nm) BC mass concentration and chemical composition (particle size of > 30 nm). The measurements were conducted on-road by setting a mobile laboratory on a trailer and pulling it with the tractor. In addition to driving, heavy-lift work cycles were tested, where separate lifts of a 1000 kg weight were conducted with the front fork of the tractor with two minutes of idling between consecutive lifts. Both a Porous Tube Diluter (PTD) with ambient temperature dilution air as well as an ejector diluter with hot dilution air were used to sample the exhaust aerosol.

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 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

Modern ‘DOC-cDPF’ systems for diesel exhaust are employing Pt-, Pd- as well as Pt/Pd alloy- based coatings to ensure high conversion efficiency of CO, HC even at low temperatures. Depending on the target application, these coatings should be also optimized towards NO2 generation which is involved in low temperature soot oxidation as well as in SCR-based deNOx. Zeolite materials are also frequently used to control cold-start HC emissions. Considering the wide variety of vehicles, engines and emission targets, there is no single optimum coating technology. The main target is therefore to maximize synergies rather than to optimize single components. At the same time, the system designer has nowadays a wide range of technologies to choose from, including PGM alloyed combinations (Pt/Pd), multiple layers and zones applicable to both DOCs and DPFs.

In this article we present a design of a new miniaturized sensor with the capacity to measure exhaust particle concentrations on board vehicles and engines. The sensor is characterized by ultra-fast response time, high sensitivity, and a wide dynamic range. In addition, the physical dimensions of the sensor enable its placement along the exhaust line. The concentration response and temporal performance of a prototype sensor are discussed and characterized with aerosol laboratory test measurements. The sensor performance was also tested with actual engine exhaust in both chassis and engine dynamometer measurements. These measurements demonstrate that the sensor has the potential to meet and even exceed any requirements around the world in terms of on-board diagnostic (OBD) sensitivity and frequency of monitoring.

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.

Very high pressures for injecting gasoline in internal combustion (i.c.) engines are recently explored for improving the air/fuel mixing process in order to control unburned hydrocarbons (UBHC) and particulate matter emissions such as for investigating new combustion concepts. The challenge remains the improvement of the spray parameters in terms of atomization, smaller droplets and their spread in the combustion chamber in order to enhance the combustion efficiency. In this framework, the raise of the injection pressure plays a key role in GDI engines for the trade-off of CO2 vs other pollutant emissions. This study aims contributing to the knowledge of the physical phenomena and mechanisms occurring when fuel is injected at ultra-high pressures for mapping and controlling the mixture formation.

A computational, three-dimensional approach to investigate the behavior of diesel soot particles in the micro-channels of wall-flow Diesel Particulate Filters is presented. The KIVA3V CFD code, already extended to solve the 2D conservation equations for porous media materials [1], has been enhanced to solve in 2-D and 3-D the governing equations for reacting and compressible flows through porous media in non axes-symmetric geometries. With respect to previous work [1], a different mathematical approach has been followed in the implementation of the numerical solver for porous media, in order to achieve a faster convergency as source terms were added to the governing equations. The Darcy pressure drop has been included in the Navier-Stokes equations and the energy equation has been extended to account for the thermal exchange between the gas flow and the porous wall.

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.

In the last ten years, the number of natural gas vehicles worldwide has grown rapidly with the biggest contribution coming from the Asia-Pacific and Latin America regions. As natural gas is the cleanest fossil fuel, the exhaust emissions from natural gas spark ignition vehicles are lower than those of gasoline powered vehicles. Moreover, natural gas is less affected by price fluctuations and its resources are more evenly widespread over the globe than to oil. However, as natural gas vehicles are usually bi-fuel gasoline and natural gas, the excellent knock resistant characteristics of natural gas cannot be completely exploited. This paper shows the results of an experimental activity performed on a passenger car fuelled alternatively by gasoline and compressed natural gas (CNG). The vehicle has been tested on a chassis dynamometer over standard (NEDC) and real driving cycles (Artemis CADC), allowing to investigate a wide range of operating conditions.

The Pegasor Particle Sensor (PPS) is a small and lightweight sensor that can be used directly in raw exhaust to provide the mass and number concentration of exhaust aerosol. Its operation principle is based on the electrical charging of exhaust aerosol and determination of particle concentration by measuring the charge accumulated on the particles. In this paper we have applied the PPS in a variety of vehicle exhaust configurations to evaluate its performance characteristics. First, the output signal of the instrument was calibrated with diesel exhaust to deliver either the mass or the number concentration of exhaust aerosol. Linear response with the soot mass concentration measured by a Photo Acoustic Soot Sensor and number concentration measured by an Electrical Low Pressure Impactor was established.

The Particle Measurement Programme (PMP) developed an exhaust particle number measurement protocol that has been adopted by current light duty vehicle emission regulations in Europe. This includes thermal treatment of the exhaust aerosol to isolate solid particles only and a number counting device with a lower cutpoint of 23 nm to avoid measurement of smaller particles that may affect the repeatability of the measurement. In this paper, we examine a potential alternative to the PMP system, where the thermal treatment is replaced by a catalytic stripper (CS). This offers oxidation and not just evaporation of the volatile components. Alternative sampling systems, either fulfilling the PMP recommendations or utilizing a CS, have been explored in terms of their volatile particle removal efficiency. Tests have been conducted on diesel exhaust, diesel equipped with DPF and gasoline direct injection emissions.

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

Modern diesel vehicles utilize two technologies, one fuel based and one hardware based, that have been motivated by recent European legislation: diesel fuel blends containing Fatty Acid Methyl Esters (FAME) and Diesel Particulate Filters (DPF). Oxygenates, like FAME, are known to reduce PM formation in the combustion chamber and reduce the amount of soot that must be filtered from the engine exhaust by the DPF. This effect is also expected to lengthen the time between DPF regenerations and reduce the fuel consumption penalty that is associated with soot loading and regeneration. This study investigated the effect of FAME content, up to 50% v/v (B50), in diesel fuel on the DPF regeneration frequency by repeatedly running a Euro 5 multi-cylinder bench engine over the European regulatory cycle (NEDC) until a specified soot loading limit had been reached.

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.

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.