Oil Transport Simulation and Oil Consumption Prediction with a Physics-Based and Data-Driven Digital Twin Model for Internal Combustion Engines
Name
lubricants-13-00463.pdf
Description
Published version
Size
2.65 MB
Format
Adobe PDF
Checksum (MD5)
b200505f8b4cbca0371af92326b56777
Author(s)
Zhong, Xinlin
Tian, Tian
Date Issued
October 21, 2025
Journal
Lubricants
Publisher
Multidisciplinary Digital Publishing Institute
Citation
Zhong, X., & Tian, T. (2025). Oil Transport Simulation and Oil Consumption Prediction with a Physics-Based and Data-Driven Digital Twin Model for Internal Combustion Engines. Lubricants, 13(10), 463.
Version
Final published version
Abstract
Lubrication oil consumption (LOC) is one of the major sources of emissions from internal combustion (IC) engines; yet, analyzing and predicting it through modeling is challenging due to its multi-physics nature, which spans different time and length scales. In this work, a digital twin model is developed to simulate oil transport in the piston ring pack of IC engines and predict the resulting oil consumption with all major physical mechanisms considered. Three main contributors to LOC, namely, top ring up-scraping, oil vaporization on the liner, and reverse gas flows through the top ring gap, are included in the model. It was found that their behaviors are heavily dependent on the arrangement of the piston ring gaps. Therefore, with the ring rotation behavior still not resolved, the current model can predict the LOC range of a given engine profile. Results show that the predicted range can well encapsulate the experimentally measured LOC value.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.3390/lubricants13100463
