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With the current use of bio-renewable fuel, the application of Ethanol in Flex-Fuel vehicles presents a very low CO2 emission alternative when the complete cycle, from plantation, fuel production, till vehicle use, is considered. In Brazil more than 80% of the car production is composed of Flex-Fuel vehicles. Due to the lower heating content of the Ethanol, more aggressive combustion calibrations are used to obtain the same engine power than when burning gasoline. Such Ethanol demands, associated with the continuous increase of engine specific power has lead to thermo-mechanical loads which challenges the tribology of piston rings. The ethanol use brings also some specific tribological differences not very well understood like fuel dilution in the lube oil, especially on cold start, corrosive environment etc. Under specific driving conditions, incipient failures like spalling on nitrided steel top rings have been observed.

Motivated by the demand for the reduction of fuel consumption, in particular to meet the engine energy efficiency goals of the Brazilian incentives legislation (INOVAR AUTO), this paper proposes a method to identify potential for energy efficiency and exemplifies it through three engines of the Brazilian market. The proposed method consists in identify the engine losses in different operating points (speed x load) through combustion mapping and the basic formulations which describe the energy/losses share. These data are grouped into 12 map sections, allowing the identification of the ones with more improvement potential. The baseline engine is 1.6 l naturally aspirated, port injection and was tested with E100 fuel (100% Ethanol). Engine #2 is similar to the baseline but with 4 valves per cylinder and a lower viscosity oil. The engine #3 is a more advanced engine: turbo charged, direct fuel injection, variable valve train and piloted pumps.

In the last years, sophisticated analyses and control of topography parameters have been introduced to study engine bore cylinders. Such surface characteristics have impact on friction and wear of the engine, with effects on fuel consumption and durability. Among such characteristics, folded metal blocking the honing grooves has received much attention, but its quantification and actual impact on engine performance is still under discussion, both in the academia and in the industry. In this work, a methodology was developed to mathematically quantify the folded metal present in engine bores. The method is compared to others described in the literature and in use by some European automotive manufacturers. The quantification method, based on topography measurements, was also compared with other analyses, such as optical and scanning electron microscopy. The necessary resolution of the topography measurement and some recommendations for the analysis are given.

Many countries are introducing fuel economy regulations in order to reduce the average emissions of light duty vehicles, since fuel consumption of vehicles is an important factor in air pollution. The lubricant has a significant role in reducing friction losses hence the fuel consumption, but the impact depends on the engine operation regime and the manner in which the lubricant components work together to change frictional properties. Different driving cycles are used by different countries and organizations to measure fuel consumption. The most common driving cycles are the European NEDC and the North American FTP-75 vehicle transient cycles. Fuel economy at full load and BSFC (Brake Specific Fuel consumption) are also common methods of measuring engine fuel economy.

On urban and emission homologation cycles, engines operate predominantly at low speeds and part loads where engine friction losses represent around 10% of the consumed fuel energy but would account for 25% of the fuel consumption once combustion efficiency is taken into account. Under such mild conditions, engine and engine oil temperatures are also lower than ideal. The influence of oil viscosity on friction losses are significant. By reducing lubricant viscosity, engine friction, fuel consumption and emissions are reduced. Tribological and machine learning models were investigated to predict the effect of oil viscosity on fuel consumption during the FTP75 emission cycle with the use of detailed actual emission test measurements. Oil viscosity was calculated with the measured oil temperature. As the same vehicle transient is followed in the cold and hot phases, the models were evaluated by comparing their prediction of fuel consumption in the hot phase versus the measured value.