Optimization of CI Engine Performance and Emissions Using Alcohol–Biodiesel Blends: A Regression Analysis Approach

Abstract

This research paper investigates the optimum engine operating parameters, namely engine load, palm biodiesel, and ethanol percentage, by using a regression analysis approach. The study was conducted on a single-cylinder, four-stroke diesel engine at varying engine loads and constant speed. A general full factorial design was established using Minitab software (Version 17) for three different input factors with their varying levels. The test results based on the regression model are used to optimize the engine load and percentages of palm biodiesel and ethanol in diesel–biodiesel–ethanol ternary blends. The analysis of variance (ANOVA) revealed a significant effect on performance and emission parameters for all three factors at a 95% confidence level. From the regression study, optimum brake thermal efficiency (BTE), nitrogen oxide (NOx), carbon monoxide (CO), and unburnt hydrocarbon (UHC) emissions were found to be 12.57%, 436.2 ppm, 0.03 vol.%, and 79.2 ppm, respectively, at 43.43% engine load, 11.06% palm biodiesel, and 5% ethanol share. The findings of this study can be used to optimize engine performance and emission characteristics. The regression analysis approach presented in this study can be used as a tool for future research on optimizing engine performance and emission parameters.