Abstract
In this study, response surface methodology (RSM)-based prediction model was prepared for specific fuel consumption (SFC) as a response. A regression model was designed to predict SFC using RSM with central composite rotatable design (CCRD). In the development of regression models, injection timing, compression ratio, injection pressure, and engine load were considered as controlled variables. Injection pressure and compression ratio were observed as the most influencing variables for the SFC. The predicted SFC values and the succeeding verification experiments under the optimal conditions established the validity of the regression model.
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Patel, S.C., Brahmbhatt, P.K. (2017). Mathematical Modeling of Specific Fuel Consumption Using Response Surface Methodology for CI Engine Fueled with Tyre Pyrolysis Oil and Diesel Blend. In: Satapathy, S., Bhateja, V., Udgata, S., Pattnaik, P. (eds) Proceedings of the 5th International Conference on Frontiers in Intelligent Computing: Theory and Applications . Advances in Intelligent Systems and Computing, vol 515. Springer, Singapore. https://doi.org/10.1007/978-981-10-3153-3_2
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DOI: https://doi.org/10.1007/978-981-10-3153-3_2
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