DelVescovo, D., Kokjohn, S., and Reitz, R., "The Development of an Ignition Delay Correlation for PRF Fuel Blends from PRF0 (n-Heptane) to PRF100 (iso-Octane)," SAE Int. J. Engines 9(1):520-535, 2016, https://doi.org/10.4271/2016-01-0551. Erratum published in SAE Int. J. Engines 10(3):1383, 2017, http://doi.org/10.4271/2016-01-0551.01.
A correlation was developed to predict the ignition delay of PRF blends at a wide range of engine-relevant operating conditions. Constant volume simulations were performed using Cantera coupled with a reduced reaction mechanism at a range of initial temperatures from 570-1860K, initial pressures from 10-100atm, oxygen mole percent from 12.6% to 21%, equivalence ratios from 0.30-1.5, and PRF blends from PRF0 to PRF100. In total, 6,480 independent ignition delay simulations were performed.The correlation utilizes the traditional Arrhenius formulation; with equivalence ratio (φ), pressure (p), and oxygen mole percentage (xo2) dependencies. The exponents α, β, and γ were fitted to a third order polynomial with respect to temperature with an exponential roll-off to a constant value at low temperatures to capture the behavior expressed by the reaction mechanism. The location and rate of the roll-off functions were modified by linear functions of PRF. The activation energy term, λ is expressed as a combination of a third and second order polynomial with respect to temperature with an exponential roll-off function whose location and rate varied with a second order function with respect to PRF to capture the differences between PRF blends in the NTC region. The resulting correlation contains 41 constants with an average standard deviation of ±24% compared to the reaction mechanism values in the range of interest to engine applications.Auto-ignition predictions were calculated using the Livengood-Wu auto-ignition integral and compared to experimental HCCI heavy-duty engine data. The predictions were calculated using two different methods, the first utilized the ignition delay correlation developed in this work, and the second method utilized linear interpolation between relevant points in a large matrix populated by 58,443 ignition delay values. Both predictions showed good agreement (±1.5 °CA) with the start of combustion from the HCCI engine data under the operating conditions tested.