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Computational fluid dynamics (CFD) model has been widely applied in internal combustion (IC) engine research. The integration of chemical kinetic model with CFD provides an opportunity for researchers to investigate the detailed chemical reactions for better understanding the combustion process of IC engines. However, the simulation using CFD has generally focused on the examination of primary parameters, such as temperature and species distributions. The detailed investigation on chemical reactions is limited. This paper presents the development of a post-processing tool capable of calculating the rate of production (ROP) of interested species with the known temperature, pressure, and concentration of each species in each cell simulated using CONVERGE-SAGE CFD model.

A 3-D DNS (Three-Dimensional Direct Numerical Simulation) study with detailed chemical kinetic mechanism of methane has been performed to investigate the characteristics of turbulent premixed oxy-fuel combustion in the condition relevant to Spark Ignition (SI) engines. First, 1-D (one-dimensional) laminar freely propagating premixed flame is examined to show a consistent combustion temperature for different dilution cases, such that 73% H2O and 66% CO2 dilution ratios are adopted in the following 3-D DNS cases. Four 3-D DNS cases with various turbulence intensities are conducted. It is found that dilution agents can reduce the overall flame temperature but with an enhancement of density weighted flame speed. CO2 dilution case shows the lowest flame speed both in turbulent and laminar cases.

The range-extended electric vehicle (REEV) is a complex nonlinear system powered by internal combustion engine and electricity stored in battery. This research proposed a Multiple Operation Points (MOP) control strategy of REVV based on operation features of REEV and the universal characteristic curve of the engine. The switching logic rules of MOP strategy are designed for the desired transition of the operation mode, which makes the engine running at high efficiency region. A Genetic algorithm (GA) is adapted to search the optimal solution. The fuel consumption is defined as the target cost function. The demand power of engine is defined as optimal variable. The state of charge (SOC) and vehicle speed are selected as the state variables. The dynamic performance of vehicle and cycling life of battery is set as the constraints. The optimal switching parameters are obtained based on this control strategy. Finally, a dynamic simulation model of REEV is developed in Matlab/Simulink.