Predicting the operating characteristics of a diesel engine running on a ternary fuel blend of alcohol, hybrid biodiesel and diesel with nanoparticles: Experimental analysis and response surface methodology
Bala Divya Potnuru, Indra Kiran NVN, Jaikumar Sagari
Abstract
The main objective of the present study is to evaluate the performance, combustion and emission characteristics of a diesel engine running on a ternary fuel blend of TiO 2 nanoparticles using a Response Surface Methodology (RSM) model. The hybrid biodiesel was synthesised from two different feedstocks, Cassia fistula and Ricinus communis . In addition, three different alcohols were added to the biodiesel blend, namely iso-butanol, iso-propanol and n-butanol, each at a volume concentration of 5%. In addition, a concentration of 75 ppm TiO 2 was added to the ternary fuel along with the surfactant sodium dodecyl sulphate (SDS) to increase stability. The performance, combustion and emission levels of the engine were evaluated at different load and compression ratios. The ternary fuel blend resulted in a slight reduction in brake specific fuel consumption (BSFC) and a modest improvement in thermal efficiency (BTE). In addition, combustion characteristics such as combustion pressure (CP) and net heat release rate (NHRR) were improved. Carbon monoxide (CO), unburnt hydrocarbons (UHC), and smoke emissions also decreased, while nitrogen oxides (NO x ) emissions increased. The addition of TiO 2 nanoparticles to the ternary fuel blend improved performance and combustion characteristics while reducing emissions, including NOx. The BTE was 26.91% and the BSFC was 0.173 kg/kWh. The CP was 68.12 bar and the NHRR was 70.14 J/°CA. The minimum values for CO, UHC, NO x , and smoke were 0.051%, 31 ppm, 1245 ppm and 32.63% for the fuel blend of B20+n-butanol 5%+NPs 75 ppm. The ternary fuel combination showed favourable operating characteristics when the nanoparticles were uniformly distributed. The correlation coefficient (R 2 ) obtained using RSM ranged from 0.92 to 0.99 for all output parameters. The remarkable range of results shows a robust relationship between the experimental data and the predicted results.