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Patterns-Based Coating of Piston Skirt for Added Benefits during Hydrodynamic Lubrication in Internal Combustion Engines
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab. Department of Mechanical Engineering, COMSATS University Islamabad, Wah Cantt, Islamabad, 47040, Pakistan.ORCID iD: 0000-0002-2686-534X
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.ORCID iD: 0000-0003-4029-6574
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.ORCID iD: 0000-0001-7029-1112
School of Mechanical Engineering, Kyungpook National University, Daegu, 41566, Korea.
2022 (English)In: International Journal of Automotive Technology, ISSN 1229-9138, E-ISSN 1976-3832, Vol. 23, no 4, p. 1099-1107Article in journal (Refereed) Published
Abstract [en]

Friction has been a significant research concern for decades. Most of the energy input into an internal combustion (IC) engine is wasted because it is used to overcome friction. Scientific developments have been made to reduce friction, including surface coatings and surface textures, which have emerged as potential solutions to reducing friction throughout the lubricating regimes. This study combines surface texturing with the coating approach to investigate the frictional response. Realistic tribo-dynamics (secondary motion of the piston skirt) are considered during actual engine-like conditions to explore the effects of pattern-based coating on friction in hydrodynamic lubrication. Results show a remarkable reduction in friction and encourage the pattern-based development of surface coatings to extend the benefit across lubricating regimes. Consequently, the surface coated with optimized patterns had 7.98 ± 0.34 % reduced energy loss per engine cycle as compared with the surface coated without a pattern.

Place, publisher, year, edition, pages
Springer Nature, 2022. Vol. 23, no 4, p. 1099-1107
Keywords [en]
Tribological performance, Surface coatings, Surface texture, piston skirt, Secondary motion
National Category
Manufacturing, Surface and Joining Technology Applied Mechanics
Research subject
Machine Elements; Machine Learning
Identifiers
URN: urn:nbn:se:ltu:diva-92614DOI: 10.1007/s12239-022-0096-9ISI: 000838678900019Scopus ID: 2-s2.0-85135745130OAI: oai:DiVA.org:ltu-92614DiVA, id: diva2:1689233
Funder
The Kempe FoundationsSwedish Research Council, 2019-04293
Note

Validerad;2022;Nivå 2;2022-08-22 (hanlid);

Funder: National Research Foundation of Korea (2020R1A2B5B02002512 and 2020R1A4A1018652)

Available from: 2022-08-22 Created: 2022-08-22 Last updated: 2022-08-23Bibliographically approved

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Usman, AliLiwicki, MarcusAlmqvist, Andreas

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