# Prediction of ethanol-gasoline blend fuelled spark ignition engine performance using dimensional analysis

Hatte, Prafulla and Bhalerao, Yogesh ORCID: https://orcid.org/0000-0002-0743-8633 (2021) Prediction of ethanol-gasoline blend fuelled spark ignition engine performance using dimensional analysis. Energy Sources Part A-Recovery Utilization and Environmental Effects. ISSN 1556-7230

## Abstract

Ethanol is blended with pure gasoline for use as a fuel in a gasoline engine. It is required to conduct physical tests on engines to observe the engine performance for these fuel blends. However, mathematical equations provide a quick, effective, and accurate alternate for physical tests. It may not be possible to develop the mathematical relations for the specific operating conditions of engine and fuel. It is possible to use dimensional analysis approach to develop mathematical model. Dimensional analysis approach is used in this research work for deriving the mathematical correlations of Indicated Mean Effective Pressure, Brake Power, Indicated Power, and Brake Specific Fuel Consumption as engine performance parameters. Their relations are established with engine speed, load on engine, calorific value of fuel fractions, and clearance volume of engine as independent parameters. Buckingham π theorem is used for formulating the relations having proportionality sign showing the possible relations of each dependent parameter with all four independent parameters. Regression analysis is used for eliminating proportionality signs from the equations developed. Mathematical relations developed by the dimensional analysis are accurate. Root Mean Square errors have noted a minimum of 4.19 for Brake Specific Fuel Consumption and a maximum 8.56 for Brake Power. The average percentage errors are less than 1%.

Item Type: Article buckingham π theorem,dimensional analysis,alternative fuel,engine performance,engine performance prediction model,regression analysis,renewable energy, sustainability and the environment,nuclear energy and engineering,fuel technology,energy engineering and power technology ,/dk/atira/pure/subjectarea/asjc/2100/2105 Faculty of Science > School of Engineering (former - to 2024) LivePure Connector 20 Aug 2021 00:07 06 Sep 2024 17:31 https://ueaeprints.uea.ac.uk/id/eprint/81155 10.1080/15567036.2021.1955044