Experimental Investigation of Additive Effects of Nano Particles on Diesel and Biofuel Powered Compression Ignition Engine

Abstract

Energy demand in India is increasing in the transportation, agricultural, industrial, and residential sectors. The main energy sources are coal, gas, fossil fuels, solar and wind energy. Due to the shortage of petroleum, India has become dependent on oil-rich countries for fossil fuel imports. The extensive use of fossil fuels in transportation has contributed to increasing pollution. Exhaust emissions from engines have polluted the environment with pollutants such as carbon monoxide (CO), unburnt hydrocarbons (UHC), carbon dioxide (CO2) and NOx. It has become inevitable to address the problems associated with pollution and reconsider the dependence on imported fossil fuels. newlineThe literature review shows that renewable energy is a solution to the energy and environmental crisis and that there is a huge potential of non-edible oil crops that can be used to produce biodiesel, which is renewable in nature. newlineThe properties of biodiesel are comparable to those of conventional diesel fuel, and its emission characteristics support its use in various sectors. Various research studies have shown that the quality of biodiesel can be further improved by blending some additives. Nanoparticles as additives have improved both the performance and emission characteristics of biodiesel. newlineConsidering the above points, the objectives of the present study were established. Karanja oilseed was selected as the main source because of its availability in the nearby area and other favourable properties. Karanja oil was extracted using a conventional mechanical oil expeller. The conventional transesterification method was used to produce karanja biodiesel. Addition of different concentrations of nanoparticles to different diesel-biodiesel blends was carried out and the engine was tested with different compression ratios. newlineThe results of the study indicate that biodiesel blend KB20 with addition of nanoparticles (Aluminium oxide 100 ppm) has exhibited potential improvement over other combinations and can be accepted as a potential alternative for use in various applications. newlineSince the problem at hand is a multi-objective, multivariate problem, the Response Surface Methodology (RSM) was used to build a polynomial regression model to predict the effects of various process parameters on the engine output responses. Thus, a second order quadratic model was formulated to predict the response of the engine. The validity and accuracy of the constructed model was measured using various statistical methods. The response values and the prediction of the input parameters were determined. newlineThe predicted values obtained from the model showed very good fitness when the results were compared with experimental data. When validated with the experimental test setup, the optimization results showed a good level of acceptance. The model was found to have a high level of accuracy and the results were found to be consistent with the results of the research work. newline newline