Computational optimization of engine emissions and performance of a CI engine powered with biogas and NiO nanoparticles doped diesel

To counter the concern of the future availability of fossil fuel due to ever-increasing energy demand and the emission generated due to its utilization, alternative renewable fuels, such as biogas and fuel additives in the form of nanoparticles emerge as viable alternative fuels. To date, no research has been carried out on the optimization of the co-addition rate of nanoparticles and biogas. In this study, engine load (0.7-3.5 kW), Nickel oxide (NiO) Nanoparticles doped rate (NDR, 0-50 ppm), and Biogas Flow Rate (BFR, 0.5-1 kg/h) were selected as independent input variables to optimize compression ignition (CI) engine emission and performance outputs through the response surface methodology (RSM) approach. The F-value of the RSM model indicates that the engine load variable has the greatest impact on engine output responses, with the BFR and NDR variables following in importance. At 2.54 kW engine load, 47.48 ppm NDR, and 0.747 kg/h BFR, the best engine output response was seen when the RSM model including the desirability function was optimized. Based on the optimization results, an assertion can be made that the use of nanoparticles in conjunction with biogas has a substantial impact on the emissions and efficiency of CI engines.