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The piston assembly is the major source of tribological inefficiencies among the engine components and is responsible for about 50% of the total engine friction losses, making such a system the main target element for developing low-friction technologies. Being a reciprocating system, the piston assembly can operate in boundary, mixed and hydrodynamic lubrication regimes. Computer simulations were used to investigate the synergistic effect between low viscosity oils and cylinder bore finishes on friction reduction of passenger car internal combustion engines. First, the Reynolds equation and the Greenwood & Tripp model were used to investigating the hydrodynamic and asperity contact pressures in the top piston ring. The classical Reynolds works well for barrel-shaped profiles and relatively thick oil film thickness but has limitations for predicting the lubrication behavior of flat parallel surfaces, such as those of Oil Control Ring (OCR) outer lands.

In the present work, a system approach to the tribological optimization of passenger car engines is demonstrated. Experimental data and simulation results are presented to demonstrate the role of surface specifications, ring pack, and lubricant on the piston/bore tribology. The importance of in-design “pairing” of low-viscosity motor oils with the ring pack and the cylinder bore characteristics in order to achieve maximum reduction in GHG emissions and improvement in fuel economy without sacrificing the endurance is elucidated. Earlier motored friction data for two different gasoline engines - Ford Duratec and Mercedes Benz M133 - using motor oils of different viscosity grades are now rationalized using AVL EXCITE® piston/bore tribology simulations. The main difference between the engines was the cylinder bore surface: honed cast iron vs thermally sprayed, and the valve train type: direct-acting mechanical bucket (DAMB) vs roller finger follower (RFF).

This paper is structured into two different parts: Firstly, it describes a methodology to evaluate wear conditions in internal combustion engines in order to go beyond the classical evaluation based on specified wear concentration limits provided by engine manufacturers or commercial oil laboratories. The proposed methodology uses spectrometric wear debris measurement data and typical maintenance data to obtain a more representative parameter of wear condition, defined as “compensated wear rate”, that takes into account particular engine operating conditions affecting wear concentration measurements. Later, an evaluation of this compensated wear rate is carried out using statistical criteria and considering individual engine characteristics such as engine age, type of service, engine metallurgy, environmental conditions of work etc.

Decreasing fuel consumption in Internal Combustion Engines (ICE) is a key target for engine developers in order to achieve the CO2 emissions limits during a standard cycle. In this context, reduction of engine friction could help meet those targets. The use of Low Viscosity Engine Oils (LVEOs), which is currently one of the avenues to achieve such reductions, was studied in this manuscript through a validated numerical simulation model that predicts the friction of the engine’s piston-cylinder unit, journal bearings and camshaft. These frictional power losses were obtained for four different lubricant formulations which differ in their viscosity grades and design. Results showed a maximum friction variation of up to 6% depending on the engine operating condition, where the major reductions came from hydrodynamic-dominated components such as journal bearings, despite an increase in friction in boundary-dominated components such as the piston-ring assembly.

This paper presents a study and review of the data collected in an Engine Fault Diagnosis System using oil analysis, used for diagnose different industrial vehicle engines (trucks, buses, road construction equipment, etc.). This system is being used since the beginning of the 1990s decade. The information acquired in this system has generated an important database that collects the information about the oil status at drain moment and further collateral information. Knowledge about oil properties (viscosity, TBN, detergency), and oil contamination, (insolubles content, soot from combustion, fuel dilution, and water) during engine operation, provide an important information about lubricants efficiency, optimal drain period and engine status that it has a direct influence on vehicles running cost. The study has been performed with a statistical tool which allows the characterisation of the main parameters of oil behaviour, in addition to the relationship between them.