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

The regression analysis method is used in this study work to examine the ideal engine operating parameters, including engine load, palm biodiesel content, and ethanol %. A single-cylinder, four-stroke diesel engine with various engine loads and constant speed was used for the study. Utilizing Minitab software (Version 17), a general full factorial design was created for three distinct input factors with varied values. The engine load and percentages of palm biodiesel and ethanol in ternary blends of diesel, biodiesel, and ethanol are optimized using test findings based on the regression model. At a 95% confidence level, the analysis of variance (ANOVA) showed that all three factors had a substantial impact on the performance and emission metrics. According to the regression investigation, the ideal engine load, palm biodiesel content, and ethanol share were found to be 43.43%, 11.06%, and 5%, respectively, for brake thermal efficiency (BTE), nitrogen oxide (NOx), carbon monoxide (CO), and unburned hydrocarbon (UHC) emissions. The results of this study can be applied to improve pollution and engine performance. Future studies on optimizing engine performance and emission parameters can use the regression analysis method given in this paper as a tool.