The minimization of friction losses in internal combustion engines is a goal of primary importance for the automotive industry, both to improve performance and to comply with increasingly stringent legislative requirements. It is therefore necessary to provide designers with tools for the effective estimation of friction losses from the earliest stages of design. We present a code for the estimation of friction losses in piston assembly that uses semianalytical models that require only strictly necessary geometric and functional inputs for the representation of components. This feature renders the code particularly suitable for the preliminary design phase. Furthermore, models ensure reduced computation times while maintaining excellent predictive capabilities, as demonstrated by the numerical-experimental comparison.

A Minimal Input Engine Friction Model for Power Loss Prediction / Delprete, Cristiana; Gastaldi, Chiara; Giorio, Lorenzo. - In: LUBRICANTS. - ISSN 2075-4442. - 10:5(2022), p. 94. [10.3390/lubricants10050094]

A Minimal Input Engine Friction Model for Power Loss Prediction

CRISTIANA DELPRETE;Chiara Gastaldi;Lorenzo Giorio
2022

Abstract

The minimization of friction losses in internal combustion engines is a goal of primary importance for the automotive industry, both to improve performance and to comply with increasingly stringent legislative requirements. It is therefore necessary to provide designers with tools for the effective estimation of friction losses from the earliest stages of design. We present a code for the estimation of friction losses in piston assembly that uses semianalytical models that require only strictly necessary geometric and functional inputs for the representation of components. This feature renders the code particularly suitable for the preliminary design phase. Furthermore, models ensure reduced computation times while maintaining excellent predictive capabilities, as demonstrated by the numerical-experimental comparison.
2022
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2972534