Investigation of fuel property impacts on ignition and combustion characteristics in MCCI engines and CN measuring devices

Abstract

As efforts to decarbonize the transportation sector continue, the use of alternative fuels in compression ignition (CI) engines has received increased attention. These fuels often diverge from petroleum-derived fuels in physical and chemical properties, raising questions about the abilities of traditional fuel characterization methods, particularly the derived cetane number (DCN), for predicting combustion behavior. This work investigates the combustion behavior of two DCN-matched fuel blends, methanol-dibutyl ether and toluene-dibutyl ether, in both a single-cylinder optical CI engine and a constant-volume combustion chamber known as the Ignition Quality Tester (IQT). Despite matching derived cetane numbers (DCN), significant differences in ignition behavior were observed between the fuels under engine conditions. Further experiments in the IQT suggested that the standard definition of start of combustion used by the IQT may not accurately reflect the onset of sustained combustion. A revised start of combustion metric was developed to consistently identify the start of main ignition and a new correlation between DCN and ignition delay was developed using D613 reference fuels to improve fidelity and correlate the ignition delay with cetane number tests. Variations of temperature and equivalence ratio were conducted to isolate the effect of thermodynamic properties, termed enthalpy demand, on ignition delay. Results demonstrated that increased fuel mass led to chamber temperature depression and extended ignition delays were primarily attributed to enthalpy demand differences that varied across fuels. By applying a first-law-based enthalpy correction, ignition delays were shown to follow Arrhenius temperature dependence, as observed in simulation work. This work concludes that thermodynamic effects, especially enthalpy demand, may influence ignition delay in both the IQT and engine environments and the magnitude of impact in each platform may be different. The magnitude and significance of these effects need to be considered when using IQT data to predict engine-relevant behavior. A framework for identifying and correcting these discrepancies is proposed, with implications for the future design of fuel characterization protocols and CN testing platforms.