APPLYING DATA FROM THE NEBRASKA TRACTOR TEST LABORATORY TO PREDICT BARE DIESEL ENGINE PERFORMANCE

摘要

The objective of this research was to demonstrate how tractor performance data from the Nebraska Tractor Test Laboratory (NTTL) and engine modeling techniques can be used to develop more wide-ranging performance maps for bare engines. Performance maps for industrial engines can greatly simplify the process of matching engines to their various applications in the most economical way. However, a common performance graph supplied by a manufacturer typically only includes a single performance curve across the range of an engine's operating speed, for one level of load. The single curve is good for some applications but lacks the needed performance detail at operating conditions other than shown on the performance curve. Extensive testing and resources are required to obtain performance curves at other load conditions. The application of engine performance modeling techniques can save much of the extensive amounts of time and resources that would normally be required to obtain this data through testing. Three modeling techniques were explored in this study (de Souza and Milanez, 1990; Jahns et al., 1990; Goering and Hansen, 2004). The results of this research showed that on average the models created by Goering and Hansen (2004) predicted engine performance with an average mean square error of less than 0.045 g kwh(-1). The next closest modeling technique averaged greater than 0.197 g kWh(-1). The Goering modeling technique outperformed the other techniques for all sets of data tested Goering's model was used to create performance maps for nine tractor models for which the necessary manufacturer information was available.