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Tracer-based PLIF temperature diagnostics have been used to study the distribution and evolution of naturally occurring thermal stratification (TS) in an HCCI engine under fired and motored operation. PLIF measurements, performed with two excitation wavelengths (277, 308 nm) and 3-pentanone as a tracer, allowed investigation of TS development under relevant fired conditions. Two-line PLIF measurements of temperature and composition were first performed to track the mixing of the fresh charge and hot residuals during intake and early compression strokes. Results showed that mixing occurs rapidly with no measureable mixture stratification remaining by early compression (220°CA aTDC), confirming that the residual mixing is not a leading cause of thermal stratification for low-residual (4-6%) engines with conventional valve timing.

Soot and fuel distributions have been studied in an optically accessible direct-injection diesel engine of the “heavy-duty” size class. Laser-induced incandescence (LII) was used to study the effects of changes in the engine speed on the in-cylinder soot distribution, and elastic (Mie) scattering and laser-induced fluorescence (LIF) were used to examine the fuel distribution. The investigation showed that, in this engine, soot is distributed throughout the cross section of the combusting region of the fuel jet for engine speeds ranging from 600 to 1800 rpm. No indication was found that soot occurs preferentially around the periphery of the plume. The LII images showed that the soot concentration decreases with increasing engine speed and injection pressure, and that the soot distribution extends much further upstream (toward the injector) at the lower engine speeds than at higher speeds.

This work investigates the potential of in-cylinder thermal stratification for reducing the pressure-rise rate in HCCI engines, and the coupling between thermal stratification and combustion-phasing retard. A combination of computational and experimental results is employed. The computations were conducted using both a custom multi-zone version and the standard single-zone version of the Senkin application of the CHEMKIN III kinetics-rate code, and kinetic mechanisms for iso-octane. This study shows that the potential for extending the high-load operating limit by adjusting the thermal stratification is very large. With appropriate stratification, even a stoichiometric charge can be combusted with low pressure-rise rates, giving an output of 16 bar IMEPg for naturally aspirated operation. For more typical HCCI fueling rates (ϕ = 0.38 - 0.45), the optimal charge-temperature distribution is found to depend on both the amount of fuel and the combustion phasing.

This study presents estimates for measurement uncertainties for a Homogenous Charge Compression Ignition (HCCI)/Low-Temperature Gasoline Combustion (LTGC) engine testing facility. A previously presented framework for quantifying those uncertainties developed uncertainty estimates based on the transducers manufacturers’ published tolerances. The present work utilizes the framework with improved uncertainty estimates in order to more accurately represent the actual uncertainties of the data acquired in the HCCI/LTGC laboratory, which ultimately results in a reduction in the uncertainty from 30 to less than 1 kPa during the intake and exhaust strokes. Details of laboratory calibration techniques and commissioning runs are used to constrain the sensitivities of the transducers relative to manufacturer supplied values.

Refinements were made to a post-processing technique, termed the Thermal Stratification Analysis (TSA), that couples the mass fraction burned data to ignition timing predictions from the autoignition integral to calculate an apparent temperature distribution from an experimental HCCI data point. Specifically, the analysis is expanded to include all of the mass in the cylinder by fitting the unburned mass with an exponential function, characteristic of the wall-affected region. The analysis-derived temperature distributions are then validated in two ways. First, the output data from CFD simulations are processed with the Thermal Stratification Analysis and the calculated temperature distributions are compared to the known CFD distributions.