Artificial Neural Network Aided Analysis of Performance and Emission Paramets of 4S CI Engine

Abstract

The continuous rise in consumption of petroleum products is an issue of great apprehension for India. The enormous newlineoutpouring of foreign exchange on one fold and rise in the price of petroleum products on the other fold have significant effect on economic development of India. In addition to this, environmental pollution and related health hazards, global warming, depletion of newlinefossil fuels have driven alternative energy sources and associated technologies at the top of national agenda. The utilization of diesel is almost six times more than that of gasoline in India and even a few percentage of substitution for diesel will hoard a substantial amount of foreign exchange. Biodiesel is one such possible potential substitute to fossil fuels that promises proficient energy newlinesource. However, biodiesel can only substitute 20-25% of fossil fuel. Thus there is a challenge to the researchers universally to utilize the available petroleum reserves more sensibly with reduced emissions by varying design and operating parameters of diesel engines. Hence, it is proposed to conduct experiments on a diesel engine by varying design and operating parameters, viz. newlinecompression ratio (15, 16.5, 18, 19), injection pressure (180 bar, 200 bar, 220 bar and 240 bar), injection timing (220, 240, 260 and 280 BTDC), and load (0, 20, 40, 60 and 80% of full load). The effect newlineof above said parameters on performance (brake specific fuel consumption, brake specific energy consumption, brake thermal newlineefficiency and exhaust gas temperature), combustion (ignition delay, combustion duration, peak pressure and heat release) and emission (CO, NOx and HC) characteristics are studied by drawing newlinecharacteristic plots.