A methodology to estimate mechanical losses and its distribution during a real driving cycle. (May 2020)

• Record Type: Journal Article
• Authors: Tormos, Bernardo; Martín, Jaime; Pla, Benjamín; Jiménez-Reyes, Antonio J.
• Is Part Of: Tribology international. Volume 145(2020)
• Publication Date: 2020-05
• Subjects: Driving cycles -- Friction model -- Mechanical losses distribution -- Numerical analysis; Tribology -- Periodicals; 621.89
• DOI: 10.1016/j.triboint.2020.106208
• Languages: English
• ISSNs: 0301-679X

Abstract

Abstract: Reducing mechanical losses in internal combustion engines has been a recurrent research topic over the past few decades. Despite mechanical losses are a key issue that should be carefully addressed to reduce fuel consumption and emissions, its distribution amongst engine elements is barely covered in literature. Recent work has shown the potential advantage of using low viscosity engine oils to reduce fuel consumption, however, there is reduced knowledge on mechanical losses distribution under transient conditions. In this work, a model is presented that predicts not only the total friction losses of an engine, but determines the amount of friction energy lost in piston-ring assembly, engine bearings, camshaft and engine auxiliaries in driving cycles representing a real driving route. The stationary mechanical losses engine maps can be used due to non-dependence on mechanical losses with temperature in warm driving cycle conditions. The final results of the simulation predicts, with 2% error, fuel consumption, energy expended by the driven wheel and mechanical losses of the engine. This methodology reduces the computational cost to estimate key engine parameters in a real driving cycle such as: mechanical losses and its distribution, fuel consumption... as the total calculation time is 10 s per cycle simulated. Highlights: A methodology to estimate mechanical losses during driving cycles, has been validated. The model predicts the mechanical losses from stationary test realized in a test bench. The minimal fuel consumption it does not implies the minimal engine mechanical losses. The model is a useful tool for future investigations to reduce CO 2 emissions.