Biofuel powered engine characteristics improvement through split injection parameter multivariate optimization with titanium based nano-particle additives

A combined approach of injection parameter optimization using multivariate analysis along with titanium oxide (TiO2) nanoparticles as a fuel additive for pine oil is presented in this work. The novelty of the study lies in the strategic technique for the calibration of split injection parameters with the application of multivariate and interaction analysis between operating parameters. To facilitate this, multivariate effect and response surface methodology (RSM) are employed to reduce engine testing time while calibrating the engine under a full pedal position at 20% pine oil biofuel (POB)-diesel blend. Compared to diesel, improved pine oil combustion resulted in 34.3%, 39%, and 58% reduction of carbon monoxide (CO), hydrocarbon (HC), and smoke respectively. These emissions are affected by air-fuel homogeneity controlled by the interaction of engine load (EL), dwell time (DT) and pilot mass (PM). Furthermore, oxides of nitrogen (NOx) emissions are reduced by 21.4% on the fine-tuning PM parameter for POB. From the study, it is found that the lower calorific value of POB causes thermal efficiencies and fuel consumption to deteriorate even after the injection parameter optimization. Hence, to improve the performance output, titanium nanoparticles are used as an additive and blended with POB under two different concentrations of 50 and 100 ppm through the nano-emulsion technique. For optimized injection parameters, the nanoparticles are added with POB-diesel blends exhibits better efficiency and fuel consumption. This is due to the catalytic effect of titanium nanoparticles along with a micro explosion of water molecules in the pine oil with the nanoparticle.