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Lean burn natural gas engines have high potential in terms of efficiency and NOx emissions in comparison with stoichiometric natural gas engines, and much lower particulate emissions than diesel engines. They are a promising solution to meet the increasingly stringent exhaust emission targets for both light and heavy-duty engines. Partially Stratified-Charge (PSC) is a novel concept which was conceived by prof. Evans (University of British Columbia, Vancouver). This technique allows to further limit pollutant emissions and improve efficiency of an otherwise standard spark-ignition engine fuelled by natural gas, operating with lean air-fuel ratio. The potential of the PSC technique lies in the control of load without throttling by further extending the lean flammability limit.

Emission control efficiency and limited fuel consumption penalty and are the main design factors driving the development of engine-after-treatment exhaust systems according to both ACEA/DOE targets and continental regulations. The particulate-filter is certainly a critical technology to this aim as usually presents very high pm reduction efficiencies (even more than 90% on a mass basis depending on soot loading) leading however to a back pressure increase and eventually to an appreciable fuel consumption penalty. Nevertheless, it is in general discussion that health hazard related to particulate depends primarily on total number of emitted particles rather than on mass. The partial-flow-filter has been recently developed presenting lower reduction efficiencies on a mass basis but also a reduced penalty on fuel consumption.

Gasoline Full Hybrid Electric Vehicles (FHEVs) are considered among good candidates as cost-effective solution to comply with upcoming emissions legislation. However, several studies have highlighted that frequent start-and-stops worsen the hydrocarbon tailpipe emissions, especially when the light-off temperature of the three-way catalyst (TWC) has not been reached. In fact, strategies only addressing the minimization of fuel consumption tend to delay engine activation and hence TWC warming, especially during urban driving. Goal of the present research is therefore to develop an on-line powertrain management strategy accounting also for TWC temperature, in order to reduce the time needed to reach TWC light-off temperature. A catalyst model is incorporated into the model of the powertrain where torque-split is performed by an adaptive equivalent consumption minimization strategy (a-ECMS).

The assessment of tighter and tighter emission targets, and the increase of efficiency of Diesel engines is pushing towards the need of oxidation catalysts capable of high conversion performance at very low temperatures. These capabilities can be achieved only by the adoption of very high noble metal loadings (up to 140 g/ft3), which lead to very high costs. Washcoat distribution may play a key role in this context. In this paper the influence of washcoat distribution on light-off behaviour of a Diesel Oxidation Catalyst has been then investigated by means of a 3D numerical model. The model is capable of representing the coupling among flow, washcoat diffusion and detailed surface chemistry. Results state that the adoption of an optimized washcoat distribution may roughly lead to cost-savings of the order 30-40% in terms of noble metal loading.

Particulate Matter (PM) filters are becoming a standard component of Diesel engines exhaust aftertreatment devices to comply with the forthcoming engine emission regulations. However, cost reduction and durability are still critical issues in particular for the integration of the PM-filter with other components of the after-treatment system (e.g. pre-turbo-catalyst, close-coupled-catalyst, PM-filter, SCR). To respect functional (available temperature and gas composition) and space restraints, very complex shapes may result from the design causing tortuous flow patterns and influencing the flow distribution into the PM-filter. Uneven soot distributions in the filter may cause a non-homogeneous development of filter regeneration, leading to failures, for example due to the occurrence of large temperature gradients during the oxidation of soot deposits.

The design of compact and efficient Diesel Oxidation Catalysts (DOC) is primarily important to comply with emission regulations not increasing engine fuel consumption at the same time. To design DOCs, Sherwood number correlations are typically used to calculate mass transfer by varying operating conditions in terms of catalyst volume, active area and mass flow rate. To that aim, Sherwood number trend over channel length has been extensively studied during last decades. However, Sherwood number correlations are highly dependent on channel geometry, and on the possible presence of special structures (such as blades, fins or bumps). These modifications, which characterize the latest developments in substrate technology, allow to improve mass transfer performance and require a special characterization.

Conversion from diesel to dual fuel (diesel and natural gas) operation may represent an attractive retrofit technique to get a better PM-NOx trade-off in a diesel engine, with no major modifications of the original design. In the proposed paper, an Euro 2 heavy duty diesel engine, converted for dual fuelling, has been studied and tested to reduce pollutant emissions. Throttled stoichiometric with EGR and lean burn technologies have been selected as control strategies. A mixed experimental-numerical approach has been utilized to analyze the engine behavior by varying key operating conditions such as throttling, natural gas/diesel oil percentage and EGR. The model, based on a 3D approach, has been used mainly to understand the evolution of the distribution of the most important parameters in the combustion chamber.

Computational Fluid Dynamics (CFD) surely has played a fundamental role in the design of the bodies and shapes of both commercial and racing vehicles in the last decades. This circumstance was mainly due to the connected substantial improvement in the design timings and to the possibility of producing numerous flow field and surface data that are difficult to obtain from a physical experimental method. Such a local analysis leads to a further understanding of the interactions of components with the overall aerodynamics. The development of wing performances, with respect to racing vehicles, has to deal with very short times but also with a very detailed description of the physics occurring. Starting from these constraints, a coupling procedure was developed by the joining of a CFD code with a Finite Element Method (FEM) structural code to better evaluate the aerodynamic performance of the wing deformed under the fluid dynamic loads.

The development of catalytic converter systems for automotive applications is, to a great extent, related to monolith catalyst support materials and design. In this paper improvements of converter channels fluid-dynamics aiming to enhance pollutant conversion in all the engine operating conditions are investigated with respect to the role of channel cross-section shape on mass and heat transfer processes. The performances of different channel sections, characteristic of ceramic and metallic monoliths, have been compared by two strategies (respectively equal cell density and equal hydraulic diameter). The results have been examined in terms of mass conversion efficiency, thermal behavior and single channel backpressure for coated and non coated single channels. 3D numerical simulations have been used as an analysis tool to give a detailed insight of in-channel phenomena. Classical shapes have been analyzed and their relative performances are reported.

Metal based Diesel Particulate Filters (PM-TRAPs) could represent a short time solution to face with particulate (and NOx) emissions with a small influence on CO2 emission. In fact, the operation principle of the PM-TRAP, based on fluid dynamical behavior of exhaust flow in “ad hoc” shaped geometries, allows to separate the particle content of exhaust-gases but needs to be carefully assessed to optimize filter performances. In this paper a mixed numerical and experimental procedure has been developed; it allows to finely tune the design parameters which can be used to achieve pre-defined targets in terms of particulate matter and fuel consumption. By adopting the previously declared procedure, a PM-TRAP “optimal” geometry has been chosen. Its performance has been verified with respect to experimental data. Results are encouraging and suggest further development of the system.

A Large Eddy Simulation (LES) numerical study of the Partially Stratified Charge (PSC) combustion process is here proposed, carried out with the open Source code OpenFOAM, in a Constant Volume Combustion Chamber (CVCC). The solver has already been validated in previous papers versus experimental data under a limited range of operating conditions. The operating conditions domain for the model validation is extended in this paper, mostly by varying equivalence ratio, to better highlight the influence of turbulence on flame front propagation. Effects of grid sizing are also shown, to better emphasize the trade-off between the level of accuracy of turbulent vortex description, and their impact on the kinematics of flame propagation. Results show the validity of the approach that is evident by comparing numerical and experimental data.

Using natural gas in internal combustion engines (ICEs) is emerging as a promising strategy to improve thermal efficiency and reduce exhaust emissions. One of the main benefits related to the use of this fuel is that the engine can be run with lean mixtures without compromising its performances. However, as the mixture is leaned out beyond the Lean Misfire Limit (LML), several technical problems are more likely to occur. The flame propagation speed gradually decreases, leading to a slower heat release and a low combustion quality, thus increasing the occurrence of misfiring and incomplete combustions. This in turn results in a sharp increment in CO and UHC emissions, as well as in cycle-to-cycle variability. In order to limit the above-mentioned problems, different solutions have been proposed over the last decade.

Diesel Particulate Filters (DPFs) are well assessed exhaust aftertreatment devices currently equipping almost every modern diesel engine to comply with the most stringent emission standards. However, an accurate estimation of soot content (loading) is critical to managing the regeneration of DPFs in order to attain optimal behavior of the whole engine-after-treatment assembly, and minimize fuel consumption. Real-time models can be used to address challenges posed by advanced control systems, such as the integration of the DPF with the engine or other critical aftertreatment components or to develop model-based OBD sensors. One of the major hurdles in such applications is the accurate estimation of engine Particulate Matter (PM) emissions as a function of time. Such data would be required as input data for any kind of accurate models. The most accurate way consists of employing soot sensors to gather the real transient soot emissions signal, which will serve as an input to the model.

In 2011-2013, regulations will be tightened for non-road vehicles, via the application of Stage III-B standards in Europe. With state-of-the-art technology (high pressure common rail, cooled EGR), non-road diesel engines will require DPFs to control PM, as 90% reduction is requested with respect to STAGE III-A standards. Additional challenges may also foresee the obtainment of STAGE III-B standards with STAGE III-A engine technology, by means of retrofit systems for PM control. In that case, retrofit systems must furthermore guarantee simple control systems, and must be robust especially in terms of limited back pressure increase during normal operation. Moreover, retrofit systems must offer flexibility from the design point of view, in order to be correctly operated with several engines of same class, possibly characterized by totally different PM flow rates, temperature, NOx and O₂ availability.

An increasing concern has been growing in the last years toward health effects due to Particulate Matter (PM) emissions. This triggered the widespread diffusion of Diesel Particulate Filters (DPFs), which equip almost every Diesel car and truck on the market, allowing to get large reduction (in the order of 95% and more) in terms of PM mass. However, PM health effects are believed to be more related to particle number rather than to particle mass. This gave rise in Europe to new regulations for passenger cars on total particle number, that will be introduced from EURO6 on. Engine/Exhaust-System assembly is therefore under investigation, to better understand the effectiveness of aftertreatment components toward particle number reduction, especially by varying engine and exhaust-system design/operating conditions, and to compare particle number emissions to particle mass emissions.

Diesel particulate filters (DPFs) are recognized as the most efficient technology for particulate matter (PM) reduction, with filtration efficiencies in excess of 90%. Design guidelines for DPFs typically are: high removal efficiency, low pressure drop, high durability and capacity to resist high temperature excursions during regeneration events. The collected mass inside the trap needs to be periodically oxidized to regenerate the DPF. Thus, an in-depth understanding of filtration and regeneration mechanisms, together with the ability of predicting actual DPF conditions, could play a key role in optimizing the duration and number of regeneration events in case of active DPFs. Thus, the correct estimation of soot loading during operation is imperative for effectively controlling the whole engine-DPF assembly and simultaneously avoidingany system failure due to a malfunctioning DPF. A viable way to solve this problem is to use DPF models.

The use of biodiesel has been widely accepted as an effective solution to reduce greenhouse emissions. The high potential of biodiesel in terms of PM emission reduction may represent an additional motivation for its wide use. This potential is related to the oxygenated nature of biodiesel, as well as its lower PAH and S, which leads, in general, to lower PM emissions as well as equal or slightly higher NOx emissions. According to these observations a different behavior of the Aftertreatment System (AS), especially as far as control issues of the Diesel Particulate Filter are concerned is also expected. The competition with the food sector is currently under debate, thus, besides second generation biofuels (e.g. from algae), the transesterification of Waste Cooking Oil (WCO) is another option, however needing further insight.

The use of biodiesels is an effective way to limit greenhouse emissions and partly limit the dependence on fossil primary sources. Biodiesel fuels also show interesting features in terms of PM-NOx emissions trade-off that appears more favorable toward an optimized control of the Diesel Particulate Filter (DPF). In fact, the DPF, which is the assessed aftertreatment technology to reduce PM emissions below the limits, suffers from fuel consumption penalization or excessive exhaust system backpressure, as a function of the frequency of the regeneration process. On the other side, issues such as the impact of the higher ash content of biodiesel on the DPF performance have also to be better understood. In the given scenario, an experimental study on a DEUTZ 4L off-road Diesel engine coupled to a DOC-DPF (Diesel Oxidation Catalyst-Diesel Particulate Filter) system is proposed in this paper.

According to European Union strategies, hydrogen technologies have a significant potential for the decarbonization of the automotive sector. Fuel Cells are considered a highly sustainable alternative to internal combustion engines for hybrid powertrain solutions. Since experimental tests on real prototypes are extremely costly in terms of time and resources, they represent a limit to the development rapidity of such complex vehicles. Consequently, simulation models are gaining further importance for their intrinsic time- and cost-saving characteristics, while their predictive capability is crucial. Accordingly, the development of the so-called “digital twins” able to accurately represent the real-time digital counterpart of a physical system has become an important research issue.

The international community is making significant efforts to face climate changes related to substantial greenhouse gas (GHG) emissions. Among all the sectors, transport is responsible for almost a quarter of global GHG emissions, 72% of which is imputable to road vehicles. It’s also expected that, without significant measures, these emissions may grow at a faster rate than other sectors. Furthermore, rising fuel costs and availability concerns have made the electrification of road transportation an attractive option to reduce oil dependency. However, this solution produces an electricity demand increase, causing significant overload conditions that could affect the reliability of the distribution sector.