Optimization Of Boron-Based Nanolubricant For Diesel Engine

• المؤلف الرئيسي: Abdullah, Muhammad Ilman Hakimi Chua
• التنسيق: أطروحة
• اللغة: الإنجليزية; الإنجليزية
• منشور في: UTeM 2016
• الموضوعات: T Technology (General); TJ Mechanical engineering and machinery
• الوصول للمادة أونلاين: http://eprints.utem.edu.my/id/eprint/18517/; https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=100398; HF5351.M34 2016

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.