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

Suman Dey, Akhilendra Pratap Singh, Sameer Sheshrao Gajghate, Sagnik Pal, Bidyut Baran Saha (), Madhujit Deb and Pankaj Kumar Das
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Suman Dey: Department of Mechanical Engineering, Indian Institute of Technology (BHU), Varanasi 221005, Uttar Pradesh, India
Akhilendra Pratap Singh: Department of Mechanical Engineering, Indian Institute of Technology (BHU), Varanasi 221005, Uttar Pradesh, India
Sameer Sheshrao Gajghate: Department of Mechanical Engineering, G H Raisoni College of Engineering and Management, Pune 412207, Maharashtra, India
Sagnik Pal: Department of Mechanical Engineering, National Institute of Technology, Agartala 799046, Tripura, India
Bidyut Baran Saha: International Institute for Carbon-Neutral Energy Research (WPI-I2CNER), Kyushu University, Fukuoka 819-0385, Japan
Madhujit Deb: Department of Mechanical Engineering, National Institute of Technology, Agartala 799046, Tripura, India
Pankaj Kumar Das: Department of Mechanical Engineering, National Institute of Technology, Agartala 799046, Tripura, India

Sustainability, 2023, vol. 15, issue 20, 1-14

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 (NO x ), 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.

Keywords: optimization; CI engine; performance; emissions; alcohol–biodiesel blends; regression analysis; analysis of variance (ANOVA) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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