Modeling of specific fuel consumption for compression ignition engines fueled with polymer-based fuel: a response surface methodology approach

Abstract Background . Diesel engines play a crucial role in ensuring human comfort and well-being across residential, commercial, transportation, and emergency response sectors because of their reliability and versatility. However, identifying alternative fuels remains a significant challenge. Objective . This study aims to develop a comprehensive mathematical model using Response Surface Methodology (RSM) to optimize the performance of Compression Ignition (CI) engines utilizing different types of plastic pyrolysis oil. Methods . Through systematic data collection and analysis, this study examines the importance of design parameters, specifically injection pressure, compression ratio, engine load, and type of plastic pyrolysis oil, which are important for specific fuel consumption. A prediction model was developed to identify the complex correlations between these factors and the fuel use. Results . The developed model serves as an effective tool for optimizing the CI engine performance under diverse operational conditions. Experimental validation involved testing diesel engines with conventional diesel fuel and various plastic pyrolysis oils, followed by optimization using RSM to achieve optimal engine performance. The engine load was identified as the most significant parameter affecting the specific fuel consumption, followed by the fuel type, injection pressure, and compression ratio. The high R-squared (99.35%) and adjusted R-squared (98.02%) values indicate that the proposed model effectively fits the experimental data. Conclusion . The RSM-based model effectively optimizes CI engine performance under varied operational conditions. It significantly reduces the time and effort required to optimize engine design variables, thus enhancing engine performance and sustainability.

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Publication Details

Journal
Engineering Research Express
Published
2024-09-01
DOI
https://doi.org/10.1088/2631-8695/ad78ab
Citations
2
Primary Topic
Advanced Combustion Engine Technologies
Type
article
Field-Weighted Citation Impact
0.44
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article

Modeling of specific fuel consumption for compression ignition engines fueled with polymer-based fuel: a response surface methodology approach

Maulik A. Modi, Tushar M. Patel
2 citations
Engineering Research Express
Advanced Combustion Engine Technologies
0.44
article

Modeling of specific fuel consumption for compression ignition engines fueled with polymer-based fuel: a response surface methodology approach

Maulik A. Modi, Tushar M. Patel
article en
2 citations

Abstract

Abstract Background . Diesel engines play a crucial role in ensuring human comfort and well-being across residential, commercial, transportation, and emergency response sectors because of their reliability and versatility. However, identifying alternative fuels remains a significant challenge. Objective . This study aims to develop a comprehensive mathematical model using Response Surface Methodology (RSM) to optimize the performance of Compression Ignition (CI) engines utilizing different types of plastic pyrolysis oil. Methods . Through systematic data collection and analysis, this study examines the importance of design parameters, specifically injection pressure, compression ratio, engine load, and type of plastic pyrolysis oil, which are important for specific fuel consumption. A prediction model was developed to identify the complex correlations between these factors and the fuel use. Results . The developed model serves as an effective tool for optimizing the CI engine performance under diverse operational conditions. Experimental validation involved testing diesel engines with conventional diesel fuel and various plastic pyrolysis oils, followed by optimization using RSM to achieve optimal engine performance. The engine load was identified as the most significant parameter affecting the specific fuel consumption, followed by the fuel type, injection pressure, and compression ratio. The high R-squared (99.35%) and adjusted R-squared (98.02%) values indicate that the proposed model effectively fits the experimental data. Conclusion . The RSM-based model effectively optimizes CI engine performance under varied operational conditions. It significantly reduces the time and effort required to optimize engine design variables, thus enhancing engine performance and sustainability.

Engineering Research ExpressVol. 6(3)
Gujarat National Law University (IN), Kadi Sarva Vishwavidyalaya (IN)
Openalex Percentile: Top 45%
Advanced Combustion Engine Technologies
0.44
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