Optimization of Tribological Performance of hBN/AL2O3 Nanoparticles as Engine Oil Additives

The purpose of this study is to determine the optimal design parameters, and indicate which of these design parameters are statistically significant for obtaining a low Coefficient of Friction (COF) with hexagonal boron nitride (hBN) and alumina (Al2O3) nanoparticles, dispersed in conventional diesel engine oil (SAE 15W40). Design of Experiment (DOE) was constructed using the Taguchi method, which consists of L9 orthogonal arrays. Tribological testing was conducted using a four-ball tester according to ASTM standard D4172 procedures. From analysis of Signal-to-Noise (S/N) ratio and Analysis of Variance (ANOVA), COF and wear scar diameter reduced significantly by dispersing several concentrations of hBN nanoparticles in conventional diesel engine oil, compared to without nanoparticles and with Al2O3 nanoparticle additive. Contribution of 0.5 vol.% of hBN and 0.3 vol.% of oleic acid, as a surfactant, can be an optimal composition additive in conventional diesel engine oil, to obtain a lower COF. In addition, the predicted value of COF by utilizing the levels of the optimal design parameters (0.5 vol.% hBN, 0.3 vol.% surfactant), as made by the Taguchi optimization method, was consistent with the confirmation test (average value of COF = 0.07215), which fell within a 95% Confidence Interval (CI)

Optimized Nanolubricant for Friction Reduction

In Malaysia, capability of nanoparticles as lubricating oil additive to improve the performance of diesel engine oil has not yet been studied extensively. Therefore, this paper presents the experimental results for conventional diesel engine oil enriched with optimized nanoparticle

Preliminary Study - Analytical Approach in Experimental Rig of Automotive Flexible Wiper System

In this study, experimental rig of automotive wiper System is designed and analyzed using numerical tool. Generally, this rig utilizes different types of electric motor as a power assist. In addition, a suitable dimension and material for each part was chose for the rig. There are two main considerations in order to design the experimental rig. The first consideration is the selection of power assist (electric motor) and the second is the consideration made pertaining to the criteria the design method. In research methodology, the design and materials used in this study is needed to be structurally analyzed using analytical calculation. After the calculation is complete and the desired results is obtained, then only the experimental rig of automotive wiper system can be fabricated and tested. The platform of the rig was analyzed to identify the external forces acting on the rig. Structural finite element analysis is conducted on the completed a best design. It is to ensure the rig has a safety factor during the experiment going on

Tribological effects of nano-based engine oil diluted with biodiesel fuel

The aim of this study was to investigate the tribological effects of nano-based engine oil diluted with biodiesel fuel. The nano-oil was prepared by disperse an optimal composition 0.5 vol.% of 70 nm hexagonal boron nitride (hBN) nanoparticles in diesel engine oil using sonication technique. Sample was diluted by difference percentages of B100 biodiesel fuel in range of 5-20 vol.%. The tribological test was performed using a four-ball tribometer. It was found that the addition of biodiesel fuel increases the coefficient of friction (COF) and seizure wears as compared with nano-oil. However, there is no significant effect on the extreme pressure (EP) properties, where the seizure for all tested samples starts to occur at 981 N

Drive to Greener Future: Tribological and Engine Performances of Nano-Oil

This paper presents the experimental study on the tribological and engine performances of nano-oil. In this study, the nano-oil was prepared by dispersing an optimal composition (0.5 vol.%) of 70nm hexagonal boron nitride (hBN) nanoparticles in conventional diesel engine oil by sonication technique. The tribological study was performed using a four-ball tribometer, while the single cylinder diesel engine performance test was conducted using 20 hp, air cooled type, eddy current dynamometer. By comparing with conventional diesel engine oil, it was found that the nano-oil is effective in reducing the coefficient of friction and enhancing the engine performance, simultaneously reduces frictional wear on the contact surfaces of engine components. The results presented here may facilitate improvements in the energy efficiency of tribological systems towards a sustainable future for green technology advancement

The hBN Nanoparticles as an Effective Additive in Engine Oil to Enhance the Durability and Performance of a Small Diesel Engine

With the increase in the number of vehicles, the problems with fuel consumption and environmental pollution are becoming more prominent. The use of an energy-conserving and emission-reducing automotive engine oil additive would have a great impact on energy conservation and environment protection. However, such an additive would need to enhance, or at least maintain the key lubrication properties. Thus, in this work, the potential of hexagonal boron nitride (hBN) nanoparticles as effective additive in SAE 15W40 diesel engine oil, to enhance the engine performance and simultaneously reduce frictional wear on the contact surfaces was studied

Effect of hBN/Al2O3 Nanoparticle Additives on the Tribological Performance of Engine Oil

Nanotechnology currently has an important role in reducing engine wear and improving fuel efficiency within engines using nanoparticle additives in engine oil. In this work, the effect of hexagonal boron nitride (hBN) and alumina (Al2O3) nanoparticle additives, on the tribological performance of SAE 15W40 diesel engine oil, was studied. A tribological test was conducted using a four-ball tribotester. The results show that the coefficient of friction (COF) and wear rate of the ball reduced significantly by dispersing hBN nanoparticle additives in SAE 15W40 diesel engine oil; compared to without or with Al2O3 nanoparticle additives. This is in accordance with the significant reduction of wear scar diameter and smoother worn surfaces observed on the balls

Effect of hBN/Al2O3 Nanoparticle Additives on the Tribological Performance of Engine Oil

Nanotechnology currently has an important role in reducing engine wear and improving fuel efficiency within engines using nanoparticle additives in engine oil. In this work, the effect of hexagonal boron nitride (hBN) and alumina (Al2O3) nanoparticle additives, on the tribological performance of SAE 15W40 diesel engine oil, was studied. A tribological test was conducted using a four-ball tribotester. The results show that the coefficient of friction (COF) and wear rate of the ball reduced significantly by dispersing hBN nanoparticle additives in SAE 15W40 diesel engine oil; compared to without or with Al2O3 nanoparticle additives. This is in accordance with the significant reduction of wear scar diameter and smoother worn surfaces observed on the balls

Optimization of Tribological Performance of hBN/AL2O3 Nanoparticles as Engine Oil Additives

The purpose of this study is to determine the optimal design parameters, and indicate which of these design parameters are statistically significant for obtaining a low Coefficient of Friction (COF) with hexagonal boron nitride (hBN) and alumina (Al2O3) nanoparticles, dispersed in conventional diesel engine oil (SAE 15W40). Design of Experiment (DOE) was constructed using the Taguchi method, which consists of L9 orthogonal arrays. Tribological testing was conducted using a four-ball tester according to ASTM standard D4172 procedures. From analysis of Signal-to-Noise (S/N) ratio and Analysis of Variance (ANOVA), COF and wear scar diameter reduced significantly by dispersing several concentrations of hBN nanoparticles in conventional diesel engine oil, compared to without nanoparticles and with Al2O3 nanoparticle additive. Contribution of 0.5 vol.% of hBN and 0.3 vol.% of oleic acid, as a surfactant, can be an optimal composition additive in conventional diesel engine oil, to obtain a lower COF. In addition, the predicted value of COF by utilizing the levels of the optimal design parameters (0.5 vol.% hBN, 0.3 vol.% surfactant), as made by the Taguchi optimization method, was consistent with the confirmation test (average value of COF = 0.07215), which fell within a 95% Confidence Interval (CI)