Modeling and Optimization of Trajectory-Based HCCI Combustion

点击翻译按钮获取中文摘要

This award supports the fundamental study of a new mode of operation for internal combustion engines, made possible through the use of a free piston engine. In a standard automobile engine, the piston positions are fixed by the crankshaft angle. In a free piston engine the piston motions are independently controlled. This control can be used to significantly improve engine efficiency and to accommodate a large variety of alternative fuels. This project could enable a modular, clean and highly efficient power source for hybrid vehicles, and enable the wide use of renewable fuels. Because transportation accounts for about thirty percent of the national energy consumption, these advances could have a major beneficial impact on energy independence and environmental quality. The research objective is to investigate the dynamics and the optimization of a new combustion mode: trajectory-based homogeneous charge compression ignition (HCCI) combustion enabled by the free piston engine. With a free piston engine, the piston motion can be controlled in real-time to actively regulate the cylinder volume, and thereby adjust the gas pressure-temperature history prior, during, and after the combustion event. This extra degree of freedom enables the in-cycle real-time optimization of the chemical reactivity and heat transfer processes of the HCCI combustion. To achieve the above objective, fundamental properties of the in-cylinder processes need to be investigated to gain insights of the influence of the unconstrained gas pressure-temperature history. Both chemical kinetics driven model and control oriented model will be developed to predict the effect of the piston trajectory on the efficiency and emissions of HCCI combustion. On this basis, optimization methods will be developed to achieve the maximum attainable fuel efficiency and emissions benefits by designing the optimal piston trajectory. Experimental work on a prototype free piston engine and a rapid compression and expansion machine will help to validate the modeling and optimization results.