Improved Multiple Point Nonlinear Genetic Algorithm Based Performance Adaptation Using Least Square Method
- 30 December 2011
- journal article
- Published by ASME International in Journal of Engineering for Gas Turbines and Power
- Vol. 134 (3)
- https://doi.org/10.1115/1.4004395
Abstract
At off-design conditions, engine performance model prediction accuracy depends largely on its component characteristic maps. With the absence of actual characteristic maps, performance adaptation needs to be done for good imitations of actual engine performance. A nonlinear multiple point genetic algorithm based performance adaptation developed earlier by the authors using a set of nonlinear scaling factor functions has been proven capable of making accurate performance predictions over a wide range of operating conditions. However, the success depends on searching the right range of scaling factor coefficients heuristically, in order to obtain the optimum scaling factor functions. Such search ranges may be difficult to obtain and in many off-design adaption cases, it may be very time consuming due to the nature of the trial and error process. In this paper, an improvement on the present adaptation method is presented using a least square method where the search range can be selected deterministically. In the new method, off-design adaptation is applied to individual off-design point first to obtain individual off-design point scaling factors. Then plots of the scaling factors against the off-design conditions are generated. Using the least square method, the relationship between each scaling factor and the off-design operating condition is generated. The regression coefficients are then used to determine the search range of the scaling factor coefficients before multiple off-design points performance adaptation is finally applied. The developed adaptation approach has been applied to a model single-spool turboshaft engine and demonstrated a simpler and faster way of obtaining the optimal scaling factor coefficients compared with the original off-design adaptation method.Keywords
This publication has 11 references indexed in Scilit:
- Nonlinear Multiple Points Gas Turbine Off-Design Performance Adaptation Using a Genetic AlgorithmJournal of Engineering for Gas Turbines and Power, 2011
- GA-based design-point performance adaptation and its comparison with ICM-based approachApplied Energy, 2010
- Compressor map generation using a feed-forward neural network and rig dataProceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 2009
- Multiple-Point Adaptive Performance Simulation Tuned to Aeroengine Test-Bed DataJournal of Propulsion and Power, 2009
- Components Map Generation of Gas Turbine Engine Using Genetic Algorithms and Engine Performance Deck DataJournal of Engineering for Gas Turbines and Power, 2006
- A Novel Boiler Ash Deposit Removal SystemPublished by ASME International ,2006
- An Adaptation Approach for Gas Turbine Design-Point Performance SimulationJournal of Engineering for Gas Turbines and Power, 2005
- A New Scaling Method for Component Maps of Gas Turbine Using System IdentificationJournal of Engineering for Gas Turbines and Power, 2003
- Adaptive modeling of jet engine performance with application to condition monitoringJournal of Propulsion and Power, 1994
- Adaptive Simulation of Gas Turbine PerformanceJournal of Engineering for Gas Turbines and Power, 1990