Improving engine oil lubrication in light-duty vehicles by using of dispersing MWCNT and ZnO nanoparticles in 5W50 as viscosity index improvers (VII)

The objective of this study is to offer a suitable nano-lubricant (engine oils containing nanoparticles) to use in light-duty automotive industries in order to reach a higher ability and efficient oil in comparison to ordinary engine oils, in order to reduce cold start engine damages. Therefore, in present study a feasibility study of using a new nano-engine oil containing a combination of MWCNT (multi wall carbon nanotubes)-ZnO nanoparticles with the ratio of 30-70% has been arranged. Results of experimental study show a considerable decrease in viscosity of nano-engine oil (in comparison to viscosity of pure 5W50 oil) after adding 0.05% and 0.1% nano particles to 5W50. This viscosity reduction, reduces the damage caused by starting up the engine in cold start condition. In order to predict the viscosity of this applied nano-engine oil (obtained from experimental studies), the efficiency of using a mathematical correlation using response surface methods (RSM) was investigated for viscosity prediction. For the proposed correlation, R-2 is equal to 0.9715 that shows its acceptable accuracy. An artificial neural network has also been used as the second method to predict viscosity in the range of 5 degrees C-55 degrees C and in solid volume fractions of 0.05%-1%. Selected structure of Artificial Neural Network with R = 9.999e-01 is the most optimal and precise structure among 100 studied structures.