Automotive Science and Engineering

In this study the performance and emissions characteristics of a heavy-duty, direct injection, Compression ignition (CI) engine which is specialized in agriculture, have been investigated experimentally. For this aim, the influence of injection timing, load, engine speed on power, brake specific fuel consumption (BSFC), peak pressure (PP), nitrogen oxides (NOx), carbon dioxide (CO2), Carbon monoxide (CO), hydrocarbon (HC) and Soot emissions has been considered. The tests were performed at various injection timings, loads and speeds. It is used artificial neural network (ANN) for predicting and modeling the engine performance and emission. Multi-objective optimization with respect to engine emissions level and engine power was used in order to deter mine the optimum load, speed and injection timing. For this goal, a fast and elitist non-dominated sorting genetic algorithm II (NSGA II) was applied to obtain maximum engine power with minimum total exhaust emissions as a two objective functions.

Cooled exhaust gas recirculation is emerging as a promising technology to address the increasing demand for fuel economy without compromising performance in turbocharged spark injection engines. The objectives of this study are to quantify the increase in knock resistance and to decrease the enrichment and emission at high load. For this purpose four stroke turbo charged Spark Ignition engine (EF7-TC) including its different systems such as inlet and exhaust manifold, exhaust pipe and engine geometry are modeled using GT Power Software. As predicted, using cooled EGR at high load enabled operation at lambda near to one with the same serial engine performances, which offers substantial advantages Such As BSFC reduction (up to 14%), and emission reduction (CO, NOx).