RSM based parameter optimization of CI engine fuelled with nickel oxide dosed Azadirachta indica methyl ester

The usage of metal oxide nanoparticles in biodiesel-diesel blends has grown drastically. The current experimental and statistical study highlights the usage of possible levels of NiO in Neem Biodiesel blend with proper engine parameters such as Compression ratio, Injection pressure, and Static fuel injection timing for maximum performance and least emissions using response surface methodology. The NiO nanoparticles were used in different concentrations of 25, 50, and 75 ppm in a blend of Neem biodiesel and diesel (25%: 75% by volume). The prepared nanoparticles were subjected to various studies like XRD, FESEM, and EDS to determine the presence of nickel oxide. A L29 array of DOE was used in the analysis. Response Surface optimizer was used to predict the engine predictors, which were 26.998 degrees bTDC (SIT), 227.86 bar (IOP), 17.2585 (CR), and 25.0003 ppm of NiO Nanoparticle with a desirability function value of 0.6198. The modeling of engine responses were in quadratic nature and was found to be statistically fit, with good confidence levels. The predicted responses and experimental response validation of RSM predictors were having a low error range of 0.7%-4.64% for various engine characteristics. (C) 2021 Elsevier Ltd. All rights reserved.

Automated summary

The study focuses on using NiO nanoparticles in Neem biodiesel blend to optimize performance and minimize emissions, finding suitable engine parameters through response surface methodology. The predicted engine responses and experimental response validation show a low error range and high confidence level in the model.