Multiple-objective optimization of heavy-duty compression ignition engine fueled by gasoline/hydrogenated catalytic biodiesel blends at low loads

Abstract

Multiple-objective optimization of a heavy-duty compression ignition engine fueled by gasoline/hydrogenated catalytic biodiesel (HCB) blends at low loads was performed by employing the KIVA-3V code and genetic algorithm. In addition, the mechanism of multiple-injection and sensitivity of operating parameters on engine performance of the optimal cases were also explored. The results indicated that efficient combustions for G70H30 (70% gasoline and 30% HCB) and G100 (pure gasoline) with ultra-low nitrogen oxides (NO_x) and soot emissions could be obtained after optimization. As HCB fraction increases, the ranges of operating parameters become more extensive, and the required initial temperature for optimal cases can be effectively reduced. When the main injection occurs after the ignition caused by pilot injection, main injection moderates the heat release rate (HRR) by creating concentration and temperature stratifications in the spray area simultaneously, and the exhaust gas recirculation (EGR) rate, pilot, and main start of injections and pilot fraction play dominant roles on engine performance. Moreover, when main injection is much more advanced than the ignition timing, main injection controls the HRR only through the concentration stratification in the reaction zone, and the EGR rate, initial temperature, and pilot faction have dominated effects on engine performance.