A parametric investigation of HCCI combustion to reduce emissions and improve efficiency using a CFD model approach

Abstract

Homogeneous charge compression ignition (HCCI) combustion process is a promising method to decrease NOx and Soot emissions with low fuel consumption. In the present study, a sample CI engine was simulated by CFD model through AVL Fire software. After validating the simulated results by comparing with experimental data, the compression ignition was changed into HCCI. The purpose of the study was to examine the effect of various operation variables of the HCCI engine. Firstly, the HCCI engine was simulated and the simulation results were compared to the experimental data. The comparison showed the numerical data had a good accordance with experimental data. After that, influences of various important parameters such as injection timing, air–fuel equivalence ratio, injection rate shape and EGR on HCCI combustion were analyzed. The early injection can create homogeneous air and fuel mixture and advance the changing of fuel to lower hydrocarbons. Also poor and rich fuel was injected in the cylinder and their combustions were compared. It was found that the ignition timing and air–fuel equivalence ratio could control low and high temperature reactions. To have of the best combustion, fuel was injected by various injection rate shapes and it was revealed injection rate shape was effective in combustion temperature and emission quantity. Then it concentrated on the effects of cooled external exhaust gas recirculation on the combustion and pollution performance of the HCCI combustion. Cooled external EGR can delay the start of combustion (SOC) effectively, which is very useful for diesel HCCI because these fuels can be easily self-ignited and make the SOC earlier. Results showed it is possible to gain the less pollution and better performance and optimize the HCCI combustion by changing various parameters. The qualitative trends observed in the parametric variation study match well with experimental data in literature.