Application of Response Surface Methodology for Optimization of Fuel Injection Parameters of a Dual Fuel Engine Fuelled with Producer Gas-Biodiesel blends

The present work reports the development of a mathematical model to establish a correlation between controllable engine input parameters and their dependent responses over a varied range of engine loadings. Brake thermal efficiency (BTE), peak combustion pressure, and exhaust gas temperature (EGT) are chosen as a response while engine load, pilot fuel injection timing (FIT), and pilot fuel injection pressure (FIP) are taken as controllable input. The response surface methodology (RSM) has been used for the model development based on multilinear regression analysis and the design of experiments techniques. The experimental data for model development was collected through lab-based experiments carried out using diesel engines in dual-fuel mode. The dual-fuel engine was powered with producer gas as the main fuel and waste cooking oil biodiesel as pilot fuel. The best possible combination of input parameters optimized by RSM helps in the improved and stable operation of the dual-fuel engine. Furthermore, the developed model can predict the output responses very close to experimental results. The model robustness is verified with high values of correlation coefficients R-2 for all three response variables.

Automated summary

This study developed a mathematical model to establish a correlation between controllable engine input parameters and their dependent responses. Experimental data showed that the model can predict output responses very close to experimental results.