Thermal Analysis of Steel and Aluminium Pistons for an HSDI Diesel Engine

Abstract

Chromium-molybdenum alloy steel pistons, which have been used in commercial vehicle applications for some time, have more recently been proposed as a means of improving thermal efficiency in lightduty applications. This work reports a comparison of the effects of geometrically similar aluminium and steel pistons on the combustion characteristics and energy flows on a single cylinder high-speed direct injection diesel research engine tested at two speed / load conditions (1500 rpm / 6.9 bar nIMEP and 2000 rpm / 25.8 bar nIMEP) both with and without EGR. The results indicate that changing to an alloy steel piston can provide a significant benefit in brake thermal efficiency at part-load and a reduced (but nonnegligible) benefit at the high-load condition and also a reduction in fuel consumption. These benefits were attributed primarily to a reduction in friction losses. In terms of energy transfer, switching to the steel piston design was shown to reduce heat transfer to the coolant, consistent with lower friction work and reduced conduction through the ring pack, and increase the energy transfer to the oil. Piston blowby was also greatly reduced. Ignition delay times and overall combustion durations were reduced with the steel piston design, possibly indicative of higher piston surface temperatures.

The Effect of an Active Thermal Coating on Efficiency and Emissions from a High Speed Direct Injection Diesel Engine

“…Increasing a coating's permeability has been shown to reduce thermal efficiency and increase heat losses as fuel/air mixture is trapped in the coating's pores as well as reducing the effective compression ratio [10,[14][15][16]. Furthermore, Kawaguchi et al [8] found that increased surface roughness results in reduced fuel spray penetration, which has been shown to lead to lower burn rates and reduced efficiency [17], although it must be noted that Kawaguchi et al did not model the combined effects of surface roughness and porosity.…”

Prediction of NOx Emissions for a Range of Engine Hardware Configurations Using Artificial Neural Networks

“…More specifically, different piston materials, cylinder heads, injector types, nozzle types and injection strategies were all tested using a combination of the above parameters. The experimental findings for these configurations are detailed in literature [26,27]. Table 2 shows the engine configurations that were tested in this work, along with the baseline configuration.…”

On the application of artificial neural networks for the prediction of NOx emissions from a high-speed direct injection diesel engine

“…The dataset includes 7 months of engine testing from the University of Oxford single-cylinder diesel research engine. The engine and its test cell have been designed to give the highest quality data, [21][22][23] and much of this dataset has already been published. 4,22,24 Overall the dataset consisted of 1108 individual experiments.…”