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The University of Southampton
University of Southampton Malaysia

Research project: The design of lubricant and surface interaction for reduced boundary friction and wear

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Funded by Exploratory Research Grant Scheme (ERGS) 2013/Phase 1, Ministry of Education, Malaysia

In typical automotive internal combustion (IC) engines, the total energy from fuel available at driven wheels is approximately 12%. Mechanical losses account for 15% of total energy loss in an IC engine where 45% of these losses result from friction of piston-ring assembly. An increase in mechanical efficiency of 10% could lead to improved fuel consumption of 1.5%. Taking into account the amount of vehicles on the road (21.25 million as given by the Malaysian Automotive Association in 2011) and fuel consumption of 20km/litre, this would accrue to approximated savings of RM484.5 million/annum, which is substantial to Malaysia’s economy. These show the dire need to increase mechanical efficiency of not only IC engines but also typical engineering applications through improved understanding of mechanisms underlying friction and wear along the contact.

Friction and wear in IC engine components are mainly influenced by boundary interactions between opposite features of sliding surfaces. Low shear strength adsorbed thin films are often formed by boundary active lubricant species. They act as a last barrier to prevent direct surface-to-surface interaction. The mechanism is not fundamentally understood but is critical to boundary friction. Boundary lubrication (prevailing in diminishing gaps at nano-scale) is governed by 1) shearing of thin adsorbed boundary film, 2) adhesion and plastic deformation of approaching surface asperities that could lead to material wear when ploughed. However, the amount of these additives (known as friction modifiers) in a lubricant blend is formulated empirically, having limited theoretical input/understanding.

To optimize boundary lubrication, the study proposes a statistical mechanics model coupled with a multi-scale surface characterization to predict friction and wear of rough surfaces. The model combines lubricant-surface interaction as a single system, with different concentration of boundary-active molecules. This can lead to a surface-optimized lubricant blend through fundamentals rather than by an empirical approach.

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