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Premixed Charge Compression Ignition (PCCI), a Low Temperature Combustion (LTC) strategy for diesel engines is of increasing interest due to its potential to simultaneously reduce soot and NOx emissions. However, the influence of mixture preparation on combustion phasing and heat release rate in LTC is not fully understood. In the present study, the influence of injection timing on mixture preparation, combustion and emissions in PCCI mode is investigated by experimental and computational methods. A sequential coupling approach of 3D CFD with a Stochastic Reactor Model (SRM) is used to simulate the PCCI engine. The SRM accounts for detailed chemical kinetics, convective heat transfer and turbulent micro-mixing. In this integrated approach, the temperature-equivalence ratio statistics obtained using KIVA 3V are mapped onto the stochastic particle ensemble used in the SRM.

Analyzing the combustion characteristics, engine performance, and emissions pathways of the internal combustion (IC) engine requires management of complex and an increasing quantity of data. With this in mind, effective management to deliver increased knowledge from these data over shorter timescales is a priority for development engineers. This paper describes how this can be achieved by combining conventional engine research methods with the latest developments in process informatics and statistical analysis. Process informatics enables engineers to combine data, instrumental and application models to carry out automated model development including optimization and validation against large data repositories of experimental data.

This paper builds upon recent publication (SAE Technical Paper 2011-01-1388, 2011, doi:10.4271/2011-01-1388) and outlines the on-going development of an advanced simulator for virtual engine mapping and optimization of engine performance, combustion and emissions characteristics. The model is further advanced through development of new sub-models for turbulent mixing, multiple injection events, variable injection pressures, engine breathing and gas exchange, as well as particulates formation and oxidation. The result is a simulator which offers engine design and performance data typically associated with 1D thermodynamic engine cycle simulations but with the "physics-based" model robustness usually associated with 3D CFD methods. This combination then enables efficient optimization of engine design with respect to engine performance, combustion characteristics and exhaust gas emissions.