Artificial Neural Network based Multi-objective Optimization using Genetic Algorithm for Single Cylinder CI Engine Emission and Performance Parameters using Polanga Biodiesel

Abstract: In view of the limited accessibility and environmental concerns of diesel, biodiesel is one of the promising alternative fuels for CI engine. This research work investigates the influence of engine fuel injection pressure on the emissions and performance of a single cylinder 4-stroke CI engine using blended Polanga biodiesel (10, 20, 30, and 40 %) with diesel as a fuel. Experimental test was carried out using four different fuel injection pressure (160, 180, 200, 220 and 240) bars. The optimization using genetic algorithm in MATLAB software is carried out to optimize the chosen engine input parameters to achieve specified priorities. The study results show that the high fuel injection pressure improves emissions and performance parameters of CI engine, NOx, CO, smoke UBHC emissions, fuel consumption, brake thermal efficiency and exhaust gas temperature respectively. Keywords: biodiesel, performance, emission, CI engine, Multi-objective optimization.