Optimization of reactivity-controlled compression ignition combustion fueled with diesel and hydrous ethanol using response surface methodology. (15th November 2015) - Fang, Wei; Kittelson, David B.; Northrop, William F.
Highlights: 80% of total fuel energy can be replaced with hydrous ethanol in a RCCI engine. Engine emissions from RCCI combustion can be significantly reduced using RSM. RSM can be used to elucidate effects of engine parameters on dual-fuel combustion. Abstract: Anhydrous ethanol has been widely investigated as an alternative fuel for internal combustion engines. The use of high water content hydrous ethanol in engines has the potential to significantly improve life-cycle energy use and CO2 emissions of bio-ethanol. Our previous work showed that dual-fuel reactivity-controlled compression ignition (RCCI) combustion is a promising combustion strategy replacing up to 80% of the total fuel energy with hydrous ethanol yielding simultaneously high thermal efficiency and low engine-out NO X and soot emissions. In this work, we use response surface methodology (RSM) to experimentally optimize several key engine engine-out emissions parameters at high and low engine load with data from a single-cylinder research engine. Efficient experimental designs were developed that allowed identification of statistically significant operating parameters for optimizing emissions. Following the optimization path generated by the RSM, NO X and soot emissions were reduced by 79% and 50% at the low load condition, and by 72% and 27% at the high load condition, compared to the starting points. Indicated thermal efficiency was compromised along the optimization path due to delayed combustion phasing for both load conditions. The study also shows that different operating parameters are significant for RCCI emissions at different engine loads. A trade-off between HC and CO emissions was observed at the lower load condition, while HC and CO were both lower after the optimization process at the higher load condition. Overall, this work shows that RSM can be effectively used to elucidate interactions among multiple engine operating parameters with reduced experimentation to optimize complex dual-fuel RCCI combustion modes.