Ducted fuel injection (DFI) is a novel combustion strategy that has been shown to significantly attenuate soot formation in diesel engines. While previous studies have used optical diagnostics and optical filter smoke number methods to show that DFI reduces in-cylinder soot formation and engine-out soot emissions, respectively, this is the first study to measure solid particle number (PN) emissions in addition to particle mass (PM). Furthermore, this study quantitatively evaluates the use of transient particle instruments for measuring particles from skip-fired operation in an optical single cylinder research engine (SCRE). Engine-out PN was measured using an engine exhaust particle sizer following a catalytic stripper, and PM was measured using a photoacoustic analyzer. The study improves on earlier preliminary emissions studies by clearly showing that DFI reduces overall PM by 76%–79% and PN for particles larger than 23 nm by 77% relative to conventional diesel combustion at a 1200-rpm, 13.3-bar gross indicated mean effective pressure operating condition. The degree of engine-out PM reduction with DFI was similar across both particulate measurement instruments used in the work. Through the use of bimodal distribution fitting, DFI was also shown to reduce the geometric mean diameter of accumulation mode particles by 26%, similar to the effects of increased injection pressure in conventional diesel combustion systems. This work clearly shows the significant solid particulate matter reductions enabled by DFI while also demonstrating that engine-out PN can be accurately measured from an optical SCRE operating in a skip-fired mode. Based on these results, it is believed that DFI has the potential to enable fuel savings when implemented in multi-cylinder engines, both by lowering the required frequency of active diesel particulate filter regeneration, and by reducing the backpressure imposed by exhaust filtration systems.

No abstract

No abstract

In this work, a stochastic reactor model (SRM) is presented that bridges the gap between multi-dimensional computational fluid dynamics (CFD) models and zero-dimensional models for simulating spark-ignited internal combustion engines. The quasi-dimensional approach calculates spatial temperature and composition of stochastic “particles” in the combustion chamber without defining their spatial position, thus allowing for mixture stratification while keeping computational costs low. The SRM simulates flame propagation using a three-zone combustion model consisting of burned gas, flame front, and unburned gas. This “flame brush” approach assumes a hemispherical flame front that propagates through the cylinder based on estimated turbulent flame speed. Cycle-averaged turbulence intensity (u’) is used in the model, calibrated using experimental data. Through the use of a kinetic mechanism, the model predicts key emissions such as CO, CO2, NO, NO2, and HC from both port fuel injection (PFI) and gasoline direct injection (GDI) engines, the latter through the implementation of a simplified spray model. Experimental data from three engines, two GDI and one PFI, were used to validate the model and calibrate cycle-averaged u’. Across all engines, the model was able to produce pressure curves that matched the experimental data. In terms of emissions, the simplified chemical kinetics mechanism matched trends of the experimental data, with the PFI results having higher accuracy. Pressure, burned fraction, and engine-out emissions predictions show that the SRM can reliably match experimental results in certain operating ranges, thus providing a viable alternative to complex CFD and single zone models.