H Radical Sensitivity-Assisted Automatic Chemical Kinetic Model Reduction for Laminar Flame Chemistry Retaining: A Case Study of Gasoline–DME Mixture under Engine Conditions

Flame
propagation commonly exists in a wide range of engine operating
modes. In chemical kinetic model reduction, the prediction of flame
speeds must be targeted when engines involve flame propagation. However,
the time-consuming nature of 1-D flame code running largely limits
the feasibility of trial-and-error type reduction approaches. In this
study, an improved automatic reduction scheme is proposed by adding
a normalized H radical sensitivity with rate constants. By comparison
with flame speed sensitivity, the combination of H radical and flame
speed sensitivity can be more accurate to construct the species group
relevant to laminar flame chemistry. Then, the newly proposed reduction
methodology is applied for the spark ignition-controlled autoignition
hybrid combustion (SCHC) with dimethyl ether (DME) as the pilot injection
into gasoline, which proves promising in the engine performance by
flexible controlling and stabilizing the combustion process. By constructing
a new detailed chemical kinetic model for PRF–DME mixtures
(348 species), a 143-species skeletal model is developed by considering
both ignition and laminar flame. 3D-CFD simulations of experimental
SCHC cases show that the detailed and skeletal models can capture
the engine phenomena accurately. The results of a 103-species skeletal
model reduced without flame speed target indicate that the flame propagation
must be emphasized in the SCHC mode.