Predicting Emissions from HCCI Engines using LIF Imaging

This paper proposes a method for quantitatively predicting emissions from a homogeneous-charge compression-ignition (HCCI) engine using laser-induced fluorescence (LIF) imaging of the in-cylinder fuel distribution. The prediction scheme, which is applied to stratified operation, is based on the premise that local fuel-air packets at a given equivalence ratio burn as if in an isolated homogeneous mixture at the same equivalence ratio. Insofar as the premise holds true, the emissions produced by each packet can be predicted using a look-up table of exhaust emission values measured during homogeneous operation. LIF images of fuel distribution during stratified operation are reduced to probability density functions (PDF) that, together with the look-up tables, allow prediction of engine-out emissions. Despite the simplifications associated with the prediction scheme, predicted values of CO₂, CO and HC emissions each agree to within 15% of total fuel carbon for low-load operation.