Advances in piston engine technology, coupled with high costs of turbine engines have led many general aviation manufacturers to explore the use of piston engines in their smaller vehicles. However, very few engine models are available to analyze piston engine performance. Consequently, designers using vehicle synthesis programs are unable to accurately predict vehicle performance when piston engines are used. This thesis documents the development of a comprehensive, thermodynamics based performance model that meets that need.
The first part of this thesis details the basics of piston engine operation, including component geometry and the four stroke engine cycle. Next, the author analyzes the critical components of engine performance, including engine work and power. In developing the engine performance model the Ideal Engine Cycles are discussed. The cold air and fuel-air working fluid models are discussed, along with the types of combustion models, including the Otto Cycle, Diesel Cycle, and the Dual Cycle.
Two performance models are generated using the Constant Volume Ideal Engine Cycle: an Ideal Gas Standard Cycle, and a Fuel-Air Cycle. The Ideal Gas Standard Cycle is useful for parametric analysis but lacks the accuracy required for performance calculations. The Fuel-Air Cycle, however, more accurately models the engine cycle and is selected as the basis for the computer program.
In developing the computer program the thermodynamic charts used in the Fuel-Air Cycle calculations must be reproduced. To accomplish this, the NASA Chemical Equilibrium Application (CEA) program is integrated into a parent VBA based computer code to provide thermodynamic state point data. Finally, the computer program is correlated to the performance of an existing aviation engine to validate the model.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/5146 |
| Date | 02 April 2004 |
| Creators | Highley, Justin L. |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
| Format | 3121967 bytes, application/pdf |
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