The objective of this investigation is to optimize light-duty diesel engine operating parameters using Adaptive Injection Strategies (AIS) for optimal fuel preparation. A multi-dimensional Computational Fluid Dynamics (CFD) code with detailed chemistry, the KIVA-CHEMKIN code, is employed and a Multi-Objective Genetic Algorithm (MOGA) is used to study a Two-Stage Combustion (TSC) concept. The combustion process is considered at a light load operating condition (nominal IMEP of 5.5 bar and high speed (2000 rev/min)), and two combustion modes are combined in this concept. The first stage is ideally Homogeneous Charge Compression Ignition (HCCI) combustion and the second stage is diffusion combustion under high temperature and low oxygen concentration conditions. Available experimental data on a 1.9L single-cylinder research engine is used for model validation. The results show that the computations are able to adequately predict the emissions trends and quantities over an injection timing sweep for the Partially Premixed Compression Ignition (PCCI) cases investigated. A preliminary investigation was performed to gain an understanding of two-stage combustion in the light duty engine. At this condition it was found that pure HCCI combustion could yield very low engine out emissions, but extreme pressure rise rates would lead to excessive combustion noise. A multi-dimensional optimization code, NSGAII, was used for optimization of six objectives (NOx, soot, CO, HC, ISFC, and peak PRR) by adjusting four parameters (boost pressure, EGR rate, fraction of premixed fuel, and start of late injection timing). The optimization has shown that two-stage combustion is a feasible concept for noise reduction while maintaining reasonable emissions and fuel consumption. A Pareto solution yielding a peak pressure rise rate of 4.3 bar/deg was found using a high EGR rate (54%), relatively low IVC pressure (1.74 bar), premixing 36% of the total fuel, and injecting the remainder of the fuel at 2.9 degrees after TDC.
