Prediction and optimization of CI engine performance fuelled with Calophyllum inophyllum diesel blend using response surface methodology (RSM)

Abstract

The transportation demand in India is increasing tremendously, which arouses the energy consumption by 4.1 to 6.1% increases each year from 2010 to 2050. In addition, the private vehicle ownership keeps on increasing almost 10% per year during the last decade and reaches 213 million tons of oil consumption in 2016. Thus, this makes India the third largest importer of crude oil in the world. Because of this problem, there is a need of promoting the alternative fuels (biodiesel) which are from different feedstocks for the transportation. This alternative fuel has better emission characteristics compared to neat diesel, hence the biodiesel can be used as direct alternative for diesel and it can also be blended with diesel to get better performance. However, the effect of compression ratio, injection timing, injection pressure, composition-blend ratio and air-fuel ratio, and the shape of the cylinder may affect the performance and emission characteristics of the diesel engine. This article deals with the effect of compression ratio in the performance of the engine while using Honne oil diesel blend and also to find out the optimum compression ratio. So the experimentations are conducted using Honne oil diesel blend-fueled CI engine at variable load conditions and at constant speed operations. In order to find out the optimum compression ratio, experiments are carried out on a single-cylinder, four-stroke variable compression ratio diesel engine, and it is found that 18:1 compression ratio gives better performance than the lower compression ratios. Engine performance tests were carried out at different compression ratio values. Using experimental data, regression model was developed and the values were predicted using response surface methodology. Then the predicted values were validated with the experimental results and a maximum error percentage of 6.057 with an average percentage of error as 3.57 were obtained. The optimum numeric factors for different responses were also selected using RSM.

Developing a smart fuel using artificial neural network for compression ignition engine fueled with Calophyllum inophyllum diesel blend at various compression ratio

“…Similarly, 34.49% reduced CO, 19.48% reduced HC, and 6.16% increased NO emissions are other performance values when fueled with CIME20 compared to the diesel as fuel. The CIB25 gives a better engine performance at 18:1 compression ratio (CR) than the lower CR 17 . From the above studies, 17 it is understood that C. inophyllum biodiesel with less blend ratio gives better performance due to its low viscosity, high calorific value, and better fuel atomization compared to blend ratio higher than 25%.…”

“…The CIB25 gives a better engine performance at 18:1 compression ratio (CR) than the lower CR 17 . From the above studies, 17 it is understood that C. inophyllum biodiesel with less blend ratio gives better performance due to its low viscosity, high calorific value, and better fuel atomization compared to blend ratio higher than 25%. The CIME biodiesel can be used as alternative fuels since it gives marginally lower brake thermal efficiency (BTE), reduced HC, and CO emissions with extra NO x emissions compared with the diesel 18 .…”

“…Even though the LSSVM and ANN is the new tool for predicting the output parameters for a different scenario, the above study clearly suggests that ANN proves to be a great tool to use as a prediction algorithm for the CIM25 biodiesel and diesel‐fueled CI engine. Also, most researchers reveal that the C. inophyllum diesel blend 16‐19 gives promising results compared to the diesel fuel.…”

An intelligent novel approach for diesel engine life monitoring using infrared image processing technic

“…19 The cetane number has a significant effect the ignition quality of the fuel. 20 Generally, pyrolysis oil possesses high density and viscosity along with lower cetane number than base line fuel. 11 This is because of high viscous and oxygenated characteristics nature of bio-fuels.…”

Analytical characterization of the Aegle marmelos pyrolysis products and investigation on the suitability of bio‐oil as a third generation bio‐fuel for C.I engine

“…At peak loading conditions, BTE for A10, A15, A20 and diesel was 25.18%, 26.62%, 29.67%, and 20.64% respectively. The high oxygen contention bio‐fuel enhance the combustion process which leads to lower fuel consumption to attain the necessary power output which in turn increases the BTE (%) .…”