Search Results

Accurately predicting the evolution of soot mass and soot particle numbers under engine conditions is critical to advanced engine design. A detailed soot-chemistry model that can capture soot under gasoline and diesel conditions without tuning is necessary for such predictions. Building confidence in the predictive usage of the chemistry in engine simulations requires validating the soot kinetics over a wide range of operating conditions and fuels, using data from different experimental techniques, and using sources from laboratory flames to engines. This validation study focuses on a soot-chemistry model that considers multiple nucleation, growth, and oxidation reaction pathways. It involves 14 gas-phase precursors and considers the effect of different soot-particle surface sites.

Aromatics constitute a significant portion of refinery fuels. Characterizing the impact of various aromatic components on combustion and emissions facilitates formulation of surrogate fuels for engine simulations. The impact of blending aromatics in fuel surrogates is usually nonlinear for ignition characteristics responsible for knocking in spark engines and for combustion phasing in diesel engines. In this work, we have characterized the behavior of nine aromatics components under engine-relevant conditions. A self-consistent and validated detailed kinetics mechanism has been developed for gasoline and diesel surrogates that contains toluene, ethylbenzene, n-propylbenzene, n-butylbenzene, isomers of xylene, 1,2,4-trimethylbenzene, and 1-methylnaphthalene. Numerical experiments using 0-D and 1-D models have been performed to study the relative behavior of these aromatics for different reacting conditions.

Emissions from Diesel engines have been a major concern for many years, particularly with regards to the impact of NOx and particulate matter on human health. Exhaust gas re-circulation (EGR) is a widely used method in diesel engines for controlling NOx production. While EGR rates can be varied to ensure engine performance and reduce NOx emissions, EGR also influences the ignition delay, reduces the peak combustion temperature and increases particulate emissions. Moreover, the injection timing directly affects NOx and particulate emissions under the broad and highly variable operating conditions. An effective CFD-based design tool for diesel engines must therefore include robust and accurate predictive capabilities for combustion and pollutant formation, to address the complex design tradeoffs. The objective of the present study is to evaluate CFD modeling of diesel engine combustion and emissions for various combinations of EGR rates and injection timings.

Gasoline Direct Injection (GDI) is a key technology in the automotive industry for improving fuel economy and performance of gasoline internal combustion engines. GDI engine performance and emission characteristics are mainly determined by the complex interaction of in-cylinder flow, mixture formation and subsequent combustion processes. In a GDI engine, mixture formation depends on spray characteristics. Spray evolution and mixture formation is critical to GDI engine operation. In this work, a multi-component surrogate fuel blend was used to represent the chemical and physical properties of the gasoline employed in the experimental engine tests. Multi-component spray models were also validated in this study against experimental spray injection measurements in a chamber. The spray-chamber data include spray-penetration lengths, transient spray velocities and droplet Sauter mean diameter (SMD) at different axial and radial distances from the spray tip, obtained using a PDPA system.

A multi-component fuel model is used to represent gasoline in computational fluid dynamics (CFD) simulations of a dual-fuel engine that combines premixed gasoline injection with diesel direct injection. The simulations employ detailed-kinetics mechanisms for both the gasoline and diesel surrogate fuels, through use of an advanced and efficient chemistry solver. The objective of this work is to elucidate kinetics effects of dual-fuel usage in Reactivity Controlled Compression Ignition (RCCI) combustion. The model is applied to simulate recent experiments on highly efficient RCCI engines. These engine experiments used a dual-fuel RCCI strategy with port-fuel-injection of gasoline and early-cycle, multiple injections of diesel fuel with a conventional diesel injector. The experiments showed that the US 2010 heavy-duty NO and soot emissions regulations were easily met without aftertreatment, while achieving greater than 50% net indicated thermal efficiency.

At temperatures below 1100 K, the oxidation of nitric oxide (NO) impacts the oxidation of hydrocarbons, causing a sensitization effect in fuel combustion. This effect can be important in engine operations, especially those involving high levels of exhaust-gas recirculation (EGR). Many researchers have observed this NO sensitization for the oxidation of hydrocarbons in HCCI engines as well as stirred reactors. They used several model-fuel components relevant to gasoline, such as n-heptane, iso-octane, and toluene. As found in stirred reactor experiments, NO tends to increase the extent of oxidation for high-octane fuel components, such as isooctane and toluene. However, for the low-octane component n-heptane, NO has an inhibiting effect on hydrocarbon oxidation, particularly at low temperatures corresponding to the negative temperature coefficient (NTC) region.

Surrogate fuels used in simulations need to capture the physical, combustion and emission characteristics of the real diesel and gasoline fuels they represent. This requirement can result in complex surrogate fuels that are blends of components representing several chemical classes, such as normal-, cyclo- and iso-alkanes, alkenes and aromatics. With a palette of around 20 potential surrogate-fuel components we can identify a blend to represent the most important physical and chemical properties of a particular real fuel. However, a detailed chemical kinetics mechanism is required to use such a surrogate in a model of the in-cylinder combustion processes. The detailed mechanism must capture the relevant kinetic pathways for all of the surrogate-fuel components. To this end, we have assembled a large comprehensive kinetic mechanism that includes several thousands of species to represent the combustion behavior of a wide range of surrogate fuels for gasoline and diesel.

While gasoline surrogate development has progressed in the areas of more complex surrogate mixtures and in kinetic modeling tools and mechanism development, it is generally recognized that further development is still needed. This paper represents a small step in supporting this development by providing comparisons between experimental engine data and surrogate-based kinetic models. In our case, the HCCI engine data comes from a port-injected, single-cylinder research engine with intake-air heating for combustion phasing control. Timing sweeps were run at constant fuel rate for three market gasolines and five surrogate mixtures. Modeling was done using the CHEMKIN software with a gasoline mechanism set containing 1440 species and 6572 reactions. Five pure compounds were selected for the surrogate blends and include iso-octane, n-heptane, toluene, methylcyclohexane, and 1-hexene.

Automated mechanism reduction is important in enabling the use of kinetics data in engineering design. In this work, we report on a mechanism-reduction technique that serves as a practical tool for automated mechanism reduction when applied to engine-simulation, with particular focus on compression-ignition engines. For this application, a multi-zone engine model has been developed, which can capture the stratification in the engine due to crevice and boundary-layer cooling effects. The multi-zone model serves as the workhorse for the mechanism-reduction algorithm. The reduction process is designed to operate on model-solution data from a parametric matrix of runs, in which the multi-zone model is run under different conditions. A more accurate reduction can therefore be achieved while accounting for spatial variations in the engine, temporal variations over the compression cycle, and variations in operating conditions.

The heavy-duty diesel engine industry is required to meet stringent emission standards. There is also the demand for more fuel efficient engines by the customer. In a previous study on an engine with variable intake valve closure timing, the authors found that an early single injection and accompanying premixed charge compression ignition (PCCI) combustion provides advantages in emissions and fuel economy; however, unacceptably high peak pressures and rates of pressure-rise impose a severe operating constraint. The use of a Pressure Reactive Piston assembly (PRP) as a means to limit peak pressures is explored in the present work. The concept is applied to a heavy-duty diesel engine and genetic algorithms (GA) are used in conjunction with the multi-dimensional engine simulation code KIVA-3V to provide an optimized set of operating variables.