In this work, a Genetic Algorithm (GA) approach was utilized to optimize a chemical kinetic mechanism for propane, targeting autoignition (i.e. knock) predictions in a high compression ratio, boosted, long-stroke SI engine. The overall objective of this DOE funded project was to design a high-efficiency LPG fueled engine with Diesel-like efficiency.
Here, engine operating conditions exhibiting pre-spark heat release (PSHR) were modeled using various literature kinetic mechanisms for gasoline surrogate fuels to evaluate end-gas thermodynamic state and composition leading up to autoigniting (knocking) conditions. Shortcomings in literature mechanisms with respect to low-temperature chemistry predictions were observed.
Several research efforts have been conducted using a custom-built GT-Power model of the CFR engine validated against experimental engine data from Argonne National Laboratory, including defining the thermal and compositional boundary conditions under RON and MON test conditions, and investigating the feasibility of a Boosted Octane Number test.