Optimization Of Boron-Based Nanolubricant For Diesel Engine

Wear and friction are unavoidable in engineering application nowadays. One of common solution to overcome these problems is by using lubricant which can reduce this friction and wear to a minimum level for promising to a better efficiency. The purposes of this study were to investigate the effect of boron based nanolubricant on the tribological mechanism and engine performance. Design of Experiment (DOE) was constructed using the Taguchi method, which consists of L9 orthogonal arrays. The optimal design parameters were determined and indicated which of these design parameters are statistically significant for obtaining a low Coefficient of Friction (COF) with hexagonal boron nitride (hBN) and/or alumina (Al2O3) nanoparticles, dispersed in conventional diesel engine oil (SAE 15W40) as optimized nano-oil. Tribological testing was conducted using a four-ball tester according to ASTM standard D4172 procedures. The optimized nano-oil was physco-chemical characterised and the effect of dilution by biodiesel (B100) were tested before undergo for engine performance test. The optimized nano-oil was tested using AIRMAN YANMAH YX2500CXA single cylinder diesel engine which coupled with 20 horse power eddy current dynamometer. The engine performance, emission and fuel consumption testing were conducted and recorded by using DynoMite 2010 software parallel with emission analyser and fuel measurement. 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). The optimized nano-oil shown an improvement in viscosity index where it showed a 3% better VI (Viscosity Index) reading compared to the conventional engine oil in advanced the COF obtained by 20% diluted nano-oil is still maintained in lower condition compared to diluted conventional engine oil which indicated that, dilution of optimized nano-oil did not affect the detergency of the lubricant. Result of engine performance shows that, the torque and power of conventional engine oil containing hBN nanoparticle are improved approximately 12.86% and 9.1% compared with conventional engine oil. The Brake Specific Fuel Consumption (B.S.F.C) shows significant efficiency approximately 13~32% and the gas emission of CO2 and HC reduce approximately 27.5% and 5.27%. As conclusion the damage of the material due to adhesive wear type with intensive plastic deformation was less pronounced tested by optimized nano-oil

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)

Optimization On The Nanoparticles Stability In Liquid Phased Condition By Using Taguchi Analysis

The problem arises from the application of nanofluid is that the nanoparticles tend to agglomerate and sedimentation which affect the stability of nanofluid. The aim of the study is to investigate the effect of different surfactant agents and homogenize time on the stability of nanoparticle (SAE 15W 40). In this study, the Nano-oil was prepared by dispersing the nanoparticles with an optimal composition of 0.5 vol.% 70 nm graphite, Al2O3 and ZrO2 in conventional engine oil (SAE 15W 40) grade by using ultrasonic homogenizer for 10-30 minutes. In order to determine the stability of the dispersion, Oleic Acid, SDBS Salt and Sodium chloride were utilized as a surfactant agent with an optimal composition of 0.3 vol. %. The stability test was conducted by using UV-spectrophotometer as quantitative test and observation of sedimentation by using the traditional method as a qualitative test. The collected data were analysed by using the Taguchi method to determine the optimum value of nanoparticle stability. The results of Taguchi analysis show that zirconia nanoparticle with SDBS agent is more stable compared with another sample. Unfortunately, Taguchi analysis analysed on the alumina nanoparticle with an oleic acid agent is a less stable sample

Stability of nano-oil by pH control in stationary conditions

The purpose of this study is to investigate the stability of nano-oil by pH control in stationary conditions. The nano-oil was prepared by dispersing an optimal composition of 0.5 vol.% 70 nm hexagonal boron nitride (hBN) nanoparticles in SAE 15W-40 diesel engine oil by sonication technique. Hydrochloric (HCl) acid and Sodium Hydroxide (NaOH) were used as a dispersing agent to determine the stability of the dispersion. The dispersion stability was evaluated by using the sedimentation method with the help of Ultra Violet-Visible (UV-Vis) spectrophotometer. It was demonstrated that the suspension in the alkaline region with a pH value of 11 to 13 was stable over the period of 60 days

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

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

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