Computational optimizations of dual-fuel reactivity controlled compression ignition combustion and gasoline compression ignition combustion were performed using a novel adaptive dual-fuel injector capable of direct injecting both gasoline and diesel fuel in a single cycle. Optimization used the Engine Research Center KIVA code coupled with a multiobjective genetic algorithm. Model validation was performed by comparing simulation results to conventional diesel, reactivity controlled compression ignition, and gasoline compression ignition combustion, and the validated model was used to develop an optimum reactivity controlled compression ignition-gasoline compression ignition combustion strategy. The reactivity controlled compression ignition optimization results showed that by direct injecting gasoline and diesel fuel, the gasoline quantity can be held at a high percentage across the range of loads considered. In this study, the mode weighted gasoline percentage was 91%. At the lightest load point, direct injecting the gasoline gave optimum results, whereas for the other load points, premixing the gasoline yielded the optimum results. The optimized results were compared with conventional diesel combustion, and it was seen that reactivity controlled compression ignition combustion gives a cycle-averaged improvement of 33% in gross indicated efficiency over conventional diesel combustion. The cycle-averaged NOx and soot emissions were reduced by 95% and 75%, respectively. To demonstrate operation over the entire operating map, an optimization was performed at a high-speed-high-load (16 bar, 2500 r/min) condition. Optimization results showed that a gross indicated efficiency of 46.4% with near zero NOx and soot emissions could be achieved using gasoline compression ignition at this load point.


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    Title :

    Blending the benefits of reactivity controlled compression ignition and gasoline compression ignition combustion using an adaptive fuel injection system




    Publication date :

    2016



    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English



    Classification :

    BKL:    52.35 / 52.35 Kolbenkraftmaschinen