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The use of early and late injection diesel Low Temperature Combustion (LTC) strategies in the low to mid load operating range are becoming increasingly popular options for production diesel engines to reduce oxides of nitrogen (NOx) and particulate matter (PM) emissions. Although opacity-based filter smoke number (FSN) PM measurements in these operating conditions have been reduced to near zero for many instruments (which are standard and very useful in most engine combustion research laboratories), significant changes can still be seen in the particle size and number measurements (such as a 2.5 - 4.5 fold variation in total particle number concentration, depending on engine operating condition). The current work presents particle size distribution measurements from early to late injection timing LTC, varying the start of injection (SOI) by three crank angle degrees (CAD) per data point, for two exhaust gas recirculation (EGR) rates, 45% and 50%.

The passive pre-chamber ignition concept has shown the potential of increasing the combustion efficiency at high load by allowing more advanced combustion phasing due to its rapid combustion. The optimization of the spark advance and the dilution rate is currently a challenging task that would allow these types of engines to maintain spark ignited (SI) engines pollutants with even higher combustion efficiencies than diesel engines. This paper is focused on the automatic calibration of a SI engine, when using the passive-chamber ignition concept. The sensitivity of the combustion efficiency to spark advance and dilution rate has been studied and an extremum seeking approach has been designed to optimize the control inputs by rejecting disturbances and maintaining certain limitations of cycle-to-cycle variability and misfires.

Most of the new Diesel combustion concepts are mainly based on reducing local combustion temperatures and enhancing the fuel/air mixing with the aim of simultaneously reducing soot and NOx emissions. In this framework, Premixed Charge Compression Ignition (PCCI) has revealed as one of the best options to combine both low emissions and good combustion controllability. During last years, PCCI strategy has been widely explored using high EGR levels and different early or late injection timings to extend the ignition delay. Recently, the use of lower cetane fuels is under investigation. Despite the great quantity of research work performed, there are still some aspects related to PCCI combustion that are not completely well known. In this paper an experimental and numerical study is carried out focused on understanding the mixing and auto-ignition processes in PCCI combustion conditions using Diesel and Gasoline fuels.

It is challenging to develop highly efficient and clean engines while meeting user expectations in terms of performance, comfort, and drivability. One of the critical aspects in this regard is combustion noise control. Combustion noise accounts for about 40 percent of the overall engine noise in typical turbocharged diesel engines. The experimental investigation of noise generation is difficult due to its inherent complexity and measurement limitations. Therefore, it is important to develop efficient numerical strategies in order to gain a better understanding of the combustion noise mechanisms. In this work, a novel methodology was developed, combining computational fluid dynamics (CFD) modeling and genetic algorithm (GA) technique to optimize the combustion system hardware design of a high-speed direct injection (HSDI) diesel engine, with respect to various emissions and performance targets including combustion noise.

The scope of this study is the analysis of the influence of boost pressure and injection pressure on combustion process and pollutant emissions. The influence of these parameters is investigated for different engine speeds. Fuel mass was kept constant for all the tests in order to avoid its influence on the analysis. A single cylinder research diesel engine, equipped with a common rail injection system capable of operating up to a maximum pressure of 150 MPa was used. Special attention was paid to NOx, smoke (which are the most important pollutants for legislation) and brake specific fuel consumption.

Partially Premixed Combustion (PPC) of fuels in the gasoline octane range has proven its potential to achieve simultaneous reduction in soot and NOX emissions, combined with high indicated efficiencies, while still retaining control over combustion phasing with the injection event. However, the octane range where the ignition properties of a given fuel are optimum depends on the engine running conditions. Thus, low octane fuels present problems for extending the ignition delay at medium to high engine loads; while too high octane fuels have ignition problems at low engine loads. Two-stroke engines arise as a promising solution to extend the load range of the PPC concept, since it intrinsically provides equivalent torque response with only half the IMEP required in a four-stroke engine.

Computational fluid dynamics (CFD) modeling has many potentials for the design and calibration of modern and future engine concepts, including facilitating the exploration of operation conditions and casting light on the involved physical and chemical phenomena. As more attention is paid to the matching of different fuel types and combustion strategies, the use of detailed chemistry in characterizing auto-ignition, flame stabilization processes and the formation of pollutant emissions is becoming critical, yet computationally intensive. Therefore, there is much interest in using tabulated approaches to account for detailed chemistry with an affordable computational cost. In the present work, the tabulated flamelet progress variable approach (TFPV), based on flamelet assumptions, was investigated and validated by simulating constant-volume Diesel combustion with primary reference fuels - binary mixtures of n-heptane and iso-octane.

A genetic algorithm (GA) optimization methodology is applied to the design of the combustion system of a heavy-duty (HD) Diesel engine fueled with dimethyl ether (DME). The study has two objectives, the optimization of a conventional diffusion-controlled combustion system aiming to achieve US2010 targets and the optimization of a stoichiometric combustion system coupled with a three way catalyst (TWC) to further control NOx emissions and achieve US2030 emission standards. These optimizations include the key combustion system related hardware, bowl geometry and injection nozzle design as input factors, together with the most relevant air management and injection settings. The GA was linked to the KIVA CFD code and an automated grid generation tool to perform a single-objective optimization. The target of the optimizations is to improve net indicated efficiency (NIE) while keeping NOx emissions, peak pressure and pressure rise rate under their corresponding target levels.

Despite recent advances towards powertrain electrification as a solution to mitigate pollutant emissions from road transport, synthetic fuels (especially e- fuels) still have a major role to play in applications where electrification will not be viable in short-medium term. Among e-fuels, oxymethylene ethers are getting serious interest within the scientific community and industry. Dimethoxy methane (OME1) is the smaller molecule among this group, which is of special interest due to its low soot formation. However, its application is still limited mainly due to its low lower heating value. In contrast, other fuel alternatives like hydrogenated vegetable oil (HVO) are considered as drop-in solutions thanks to their very similar properties and molecular composition to that of fossil diesel. However, their pollutant emission improvement is limited.