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Fatty Acid Methyl Ester (FAME) products derived from vegetable oils and animal fats are now widely used in European diesel fuels and their use will increase in order to meet mandated targets for the use of renewable products in road fuels. As more FAME enters the diesel pool, understanding the impact of higher FAME levels on the performance and emissions of modern light-duty diesel vehicles is increasingly important. Of special significance to Well-to-Wheels (WTW) calculations is the potential impact that higher FAME levels may have on the vehicle's volumetric fuel consumption. The primary objective of this study was to generate statistically robust fuel consumption data on three light-duty diesel vehicles complying with Euro 4 emissions regulations. These vehicles were evaluated on a chassis dynamometer using four fuels: a hydrocarbon-only diesel fuel and three FAME/diesel fuel blends containing up to 50% v/v FAME. One FAME type, a Rapeseed Methyl Ester (RME), was used throughout.

To meet future stringent emission regulations such as Euro6, the design and control of diesel exhaust after-treatment systems will become more complex in order to ensure their optimum operation over time. Moreover, because of the strong pressure for CO₂ emissions reduction, the average exhaust temperature is expected to decrease, posing significant challenges on exhaust after-treatment. Diesel Oxidation Catalysts (DOCs) are already widely used to reduce CO and hydrocarbons (HC) from diesel engine emissions. In addition, DOC is also used to control the NO₂/NOx ratio and to generate the exothermic reactions necessary for the thermal regeneration of Diesel Particulate Filter (DPF) and NOx Storage and Reduction catalysts (NSR). The expected temperature decrease of diesel exhaust will adversely affect the CO and unburned hydrocarbons (UHC) conversion efficiency of the catalysts. Therefore, the development cost for the design and control of new DOCs is increasing.

It is commonly accepted that future powertrains will be based to a large extent on hybrid architectures, in order to optimize fuel efficiency and reduce CO₂ emissions. Hybrid operation is typically achieved with frequent engine start-and-stops during real-world as well as during the legislated driving cycles. The cooling of the exhaust system during engine stop may pose problems if the substrate temperature drops below the light-off temperature. Therefore, the design and thermal management of after-treatment systems for hybrid applications should consider the 3-dimensional heat transfer problem carefully. On the other hand, the after-treatment system calculation in the concept design phase is closely linked with engine calibration, taking into account the hybridization strategy. Therefore, there is a strong need to couple engine simulation with 3d aftertreatment predictions.

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.

Efforts to develop a sensor for on-board diagnostics (OBD) of diesel vehicles are intensive as diesel particulate filters (DPFs) have become widespread around the world. This study presents a novel sensor that has been successfully tested for OBD diagnosis of damaged DPFs. The sensor is based on the "escaping current" technique. Based on this, a sample of exhaust gas is charged by a corona-ionized flow and is pumped by an ejector dilutor built in the sensor's construction. While the majority of ions return to the grounded sensor's body, a small quantity is lost with the charged particles exiting the sensor. This "escaping current" is a measurement of the particle concentration in the exhaust gas. Such a sensor has been developed and tested in real-exhaust of a diesel car and a diesel engine. The sensor provides high resolution (1 Hz, 0.3 s response time) and high sensitivity superseding OBD requirements. The sensor was used on an engine to monitor the efficiency of damaged DPFs.

The pressure for compact and efficient deNO systems has led to increased interest of incorporating SCR coatings in the DPF walls. This technology could be very attractive especially if high amounts of washcoat loadings could be impregnated in the DPF porous walls, which is only possible with high porosity filters. To counterbalance the filtration and backpressure drawbacks from such high porosity applications, the layered wall technology has already been proposed towards minimizing soot penetration in the wall and maximizing filtration efficiency. In order to deal with the understanding of the complex interactions in such advanced systems and assist their design optimization, this paper presents an advanced modeling framework and selected results from simulation studies trying to illustrate the governing phenomena affecting deNO performance and passive DPF regeneration in the above combined systems.

The successful design and especially the control of the SCR system is a challenging process that can be supported by the application of simulation tools. As a first step, we employ physico-chemically informed ‘off-line’ models that are calibrated with the help of targeted small- and full-scale tests. Despite their high level of sophistication, this SCR model is able to be integrated in a control-oriented simulation software platform and connected to other powertrain simulation blocks. The target is to use this simulation platform as a virtual environment for the development and optimization of SCR control strategies. The above process is demonstrated in the case of a passenger car SCR. The model is calibrated at both fresh and aged catalyst condition and validated using experimental data from the engine bench under a wide variety of operating conditions. Next, the calibrated model was coupled with embedded control models, developed for Euro 6 passenger car powertrains.

This paper presents an overview of the results on heavy duty engines collected in the “PARTICULATES” project, which aimed at the characterization of exhaust particle emissions from road vehicles. The same exhaust gas sampling and measurement system as employed for the measurements on light duty vehicles [1] was used. Measurements were made in three labs to evaluate a wide range of particulate properties with a range of heavy duty engines and fuels. The measured properties included particle number, with focus separately on nucleation mode and solid particles, particle active surface and total mass. The sample consisted of 10 engines, ranging from Euro-I to prototype Euro-V technologies. The same core diesel fuels were used as in the light duty programme, mainly differentiated with respect to their sulphur content. Additional fuels were tested by some partners to extend the knowledge base.

This paper presents an overview of the results on light duty vehicles collected in the “PARTICULATES” project which aimed at the characterization of exhaust particle emissions from road vehicles. A novel measurement protocol, developed to promote the production of nucleation mode particles over transient cycles, has been successfully employed in several labs to evaluate a wide range of particulate properties with a range of light duty vehicles and fuels. The measured properties included particle number, with focus separately on nucleation mode and solid particles, particle active surface and total mass. The vehicle sample consisted of 22 cars, including conventional diesels, particle filter equipped diesels, port fuel injected and direct injection spark ignition cars. Four diesel and three gasoline fuels were used, mainly differentiated with respect to their sulfur content which was ranging from 300 to below 10 mg/kg.

The effect of “Start & Stop” and “Gear Shift Indicator” - two widespread fuel saving technologies - on fuel consumption and particle emissions of a Euro 5 passenger car is evaluated in this paper. The vehicle was subjected to a series of different driving cycles, including the current (NEDC) and future (WLTC) cycles implemented in the European type approval procedure at cold and hot start condition and particle number was measured with an AVL Particle Counter. In addition, we have utilized two Pegasor Particle Sensor units positioned in different locations along the sampling line to assess the impact of the sampling location on the particle characteristics measured during highly transient events. The results showed that the particle number emission levels over the WLTC were comparable to the NEDC ones, whereas NOx emissions were more than twofold higher. Both fuel saving technologies can lead to reduced fuel consumption and, subsequently CO2 emissions, in the order of 5%.

The accurate prediction of pollutant emissions generated by IC engines is a key aspect to guarantee the respect of the emission regulation legislation. This paper describes the approach followed by the authors to achieve a strict numerical coupling of two different 1D modeling tools in a co-simulation environment, aiming at a reliable calculation of engine-out and tailpipe emissions. The main idea is to allow an accurate 1D simulation of the unsteady flows and wave motion inside the intake and exhaust systems, without resorting to an over-simplified geometrical discretization, and to rely on advanced thermodynamic combustion models and kinetic sub-models for the calculation of cylinder-out emissions. A specific fluid dynamic approach is then used to track the chemical composition along the exhaust duct-system, in order to evaluate the conversion efficiency of after-treatment devices, such as TWC, GPF, DPF, DOC, SCR and so on.

Cyclic combustion variability (CCV) is an undesirable characteristic of spark ignition (SI) engines, and originates from variations in gas motion and turbulence, as well as from differences in mixture composition and homogeneity in each cycle. In this work, the cycle to cycle variability on combustion and emissions is experimentally investigated on a high-speed, port fuel injected, spark ignition engine. Fast response analyzers were placed at the exhaust manifold, directly downstream of the exhaust valve of one cylinder, for the determination of the cycle-resolved carbon monoxide (CO) and nitric oxide (NO) emissions. A piezoelectric transducer, integrated in the spark-plug, was also used for cylinder pressure measurement. The impact of engine operating parameters, namely engine speed, load, equivalence ratio and ignition timing on combustion and emissions variability, was evaluated.