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Influence of Structural Temperature on Frictional Power Loss of Piston Ring-Cylinder Liner System
Technical Paper
2017-01-2421
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
With the enhancement of power density, the thermal load of internal combustion engine becomes an increasingly serious problem, the influence of heat load on the frictional power loss of piston ring is more prominent. A mixed lubrication model is established for the piston ring-cylinder liner system of a diesel engine, the influence of temperature change on the frictional power loss of piston ring-cylinder liner system is investigated. The maximum temperature ranges of the first ring, the second ring and the oil ring are 40 degrees Celsius independently, and the maximum temperature range of the cylinder liner is 20% of its temperature. The results show that: The temperature of cylinder liner has obviously influence on the oil film temperature, while the temperature of piston rings has little influence. The total frictional power loss of piston ring pack presents the characteristic of first decreasing and then increasing when the temperature of the first ring, the second ring, the oil ring and the cylinder liner is increased independently, so each case has a minimum frictional power loss point. The frictional power loss is large as the high oil viscosity at low temperature and the large thermal deformation at high temperature. In the calculated temperature range, when the temperatures of the first ring, the second ring, the oil ring and the cylinder liner are changed independently, the total frictional power losses of the piston ring pack are reduced by 5.92%, 4.87%, 6.44% and 47.39% compared with the maximum, respectively. Therefore, it is a feasible method to realize the low friction of piston ring by thermal management with more attention to cylinder liner thermal management strategy.
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Cheng, D. and Liu, X., "Influence of Structural Temperature on Frictional Power Loss of Piston Ring-Cylinder Liner System," SAE Technical Paper 2017-01-2421, 2017, https://doi.org/10.4271/2017-01-2421.Data Sets - Support Documents
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