Propulsion directorate/control and engine health management (CEHM): real-time turbofan engine simulation

2005 ◽  
Author(s):  
T. Curry ◽  
A. Behbahani
Keyword(s):  
Real Time ◽  
Health Management ◽  
Turbofan Engine ◽  
Engine Simulation

Real-Time Execution of a High Fidelity Aero-Thermodynamic Turbofan Engine Simulation

2012 ◽  
Vol 134 (5) ◽  
Author(s):  
Igor Fuksman ◽  
Steven Sirica
Keyword(s):  
Real Time ◽  
Thermodynamic Simulation ◽  
High Fidelity ◽  
Time Model ◽  
Turbofan Engine ◽  
Engine Simulation ◽  
Thermodynamic Simulations ◽  
Execution Speed ◽  
Asme Turbo Expo ◽  
Function Models

In the past, a typical way of executing simulations in a real-time environment had been to use transfer function models, state-variable models, or reduced-order aero-thermodynamic models. These models are typically not as accurate as the conventional full-fidelity aero-thermodynamic simulations used as a basis for the generation of real-time models. Also, there is a cost associated with the creation and maintenance of these derived real-time models. The ultimate goal is to use the high fidelity aero-thermodynamic simulation as the real-time model. However, execution of the high fidelity aero-thermodynamic simulation in a real-time environment is a challenging objective since accuracy of the simulation cannot be sacrificed to optimize execution speed, yet execution speed still has to be limited by some means to fit into real-time constraint. This paper discusses the methodology used to resolve this challenge, thereby enabling use of a contemporary turbofan engine high fidelity aero-thermodynamic simulation in real-time environments. This publication reflects the work that was initially presented at the ASME Turbo Expo 2011 (Fuksman and Sirica, 2011, “Real-Time Execution of a High Fidelity Aero-Thermodynamic Turbofan Engine Simulation,” ASME Turbo Expo, Jun. 6-10, Vancouver, Canada, Paper No. GT2011-46661).

scholarly journals Benchmarking Gas Path Diagnostic Methods: A Public Approach

2008 ◽  
Author(s):  
Donald L. Simon ◽  
Jeff Bird ◽  
Craig Davison ◽  
Al Volponi ◽  
R. Eugene Iverson
Keyword(s):  
Power Systems ◽  
Health Management ◽  
Diagnostic Methods ◽  
Fault Detection And Isolation ◽  
Benchmark Problem ◽  
Noise Levels ◽  
Turbofan Engine ◽  
Engine Simulation ◽  
Component Faults ◽  
New Algorithms

Recent technology reviews have identified the need for objective assessments of engine health management (EHM) technology. The need is two-fold: technology developers require relevant data and problems to design and validate new algorithms and techniques while engine system integrators and operators need practical tools to direct development and then evaluate the effectiveness of proposed solutions. This paper presents a publicly available gas path diagnostic benchmark problem that has been developed by the Propulsion and Power Systems Panel of The Technical Cooperation Program (TTCP) to help address these needs. The problem is coded in Matlab™ and coupled with a non-linear turbofan engine simulation to produce “snap-shot” measurements, with relevant noise levels, as if collected from a fleet of engines over their lifetime of use. Each engine within the fleet will experience unique operating and deterioration profiles, and may encounter randomly occurring relevant gas path faults including sensor, actuator and component faults. The challenge to the EHM community is to develop gas path diagnostic algorithms to reliably perform fault detection and isolation. An example solution to the benchmark problem is provided along with associated evaluation metrics. A plan is presented to disseminate this benchmark problem to the engine health management technical community and invite technology solutions.

Real-Time Execution of a High Fidelity Aero-Thermodynamic Turbofan Engine Simulation

2011 ◽  
Author(s):  
Igor Fuksman ◽  
Steven Sirica
Keyword(s):  
Real Time ◽  
Thermodynamic Simulation ◽  
High Fidelity ◽  
Time Model ◽  
Turbofan Engine ◽  
The Real ◽  
Engine Simulation ◽  
Thermodynamic Simulations ◽  
Execution Speed ◽  
Function Models

In the past, a typical way of executing simulations in the real-time environment had been to use transfer function models, state-variable models or reduced-order aero-thermodynamic models. These models are typically not as accurate as the conventional full-fidelity aero-thermodynamic simulations used as basis for generation of the real-time models. Also, there is a cost associated with creation and maintenance of these derived real-time models. The ultimate goal is to use the high fidelity aero-thermodynamic simulation as the real-time model. However, execution of the high fidelity aero-thermodynamic simulation in a real-time environment is a challenging objective since accuracy of the simulation cannot be sacrificed to optimize execution speed, yet execution speed still has to be limited by some means to fit into real-time constraint. This paper discusses the methodology used to resolve this challenge, thereby enabling use of a contemporary turbofan engine high fidelity aero-thermodynamic simulation in the real-time environments.

Real-Time Transient Three Spool Turbofan Engine Simulation: A Hybrid Approach

2009 ◽  
Vol 131 (5) ◽  
Author(s):  
Naveed U. Rahman ◽  
James F. Whidborne
Keyword(s):  
Iterative Method ◽  
Real Time ◽  
State Vector ◽  
Hybrid Approach ◽  
Test Case ◽  
Turbofan Engine ◽  
Engine Simulation ◽  
Engine Model ◽  
Pass Through ◽  
Volume Method

This paper presents a transient three-spool turbofan engine simulation model that uses a combination of intercomponent volume and iterative techniques. The engine model runs in real time and has been implemented in MATLAB/SIMULINK environment. The main advantage of this hybrid approach is that it preserves the accuracy of the iterative method while maintaining the simplicity of the intercomponent volume method. The iterative approach is applied at each engine subsystem to solve algebraic thermodynamic equations for exit enthalpy, entropy, and temperature, whereas the intercomponent volume method is used to calculate pressures derivatives and hence pressures at corresponding engine stations. This allows the engine state vector to be updated at each pass through the engine calculations. This technique was applied as a test case on the Rolls Royce Trent 500 three-spool turbofan engine, and the results were compared with an iterative method. As the engine state vector is updated during each cycle, the model lends itself for easy integration into nonlinear aircraft simulations, real-time engine diagnostics/prognostics, and jet engine control applications.

Turbofan Engine Robust H-∞ Dynamical Output Feedback Control Design Based on LMI Method

2005 ◽  
Author(s):  
Xi Wang ◽  
Daoliang Tan ◽  
Tiejun Zheng
Keyword(s):  
Output Feedback ◽  
Linear Models ◽  
Nonlinear Models ◽  
Design Method ◽  
State Space Model ◽  
Output Feedback Control ◽  
Linear Matrix ◽  
Turbofan Engine ◽  
Engine Simulation ◽  
Linear State

This paper presents an approach to turbofan engine dynamical output feedback controller (DOFC) design in the framework of LMI (Linear Matrix Inequality)-based H∞ control. In combination with loop shaping and internal model principle, the linear state space model of a turbofan engine is converted into that of some augmented plant, which is used to establish the LMI formulations of the standard H∞ control problem with respect to this augmented plant. Furthermore, by solving optimal H∞ controller for the augmented plant, we indirectly obtain the H∞ DOFC of turbofan engine which successfully achieves the tracking of reference instructions and effective constraints on control inputs. This design method is applied to the H∞ DOFC design for the linear models of an advanced multivariate turbofan engine. The obtained H∞ DOFC is only in control of the steady state of this turbofan engine. Simulation results from the linear and nonlinear models of this turbofan engine show that the resulting controller has such properties as good tracking performance, strong disturbance rejection, and satisfying robustness.

Real-Time Marine Diesel Engine Simulation for Fault Diagnosis

2002 ◽  
Vol 39 (01) ◽  
pp. 21-28
Author(s):  
Kevin Logan ◽  
Bahadir Inozu ◽  
Philippe Roy ◽  
Jean-Francçois Hetet ◽  
Pascal Chesse ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Real Time ◽  
Learning System ◽  
Cerebellar Model Articulation Controller ◽  
Diagnostic Systems ◽  
Efficient Manner ◽  
Engine Simulation ◽  
Intelligent Software ◽  
Marine Diesel ◽  
Cost Efficient

Automated monitoring systems are now the standard on most large vessels; however, few are equipped with diagnostic systems. This paper presents new developments in the area of fault diagnosis based on intelligent software agents. The research objective was to design an agent capable of continuous real-time machine learning by using an artificial neural network known as the cerebellar model articulation controller (CMAC). An engine simulator that can model both normal and faulty engine operations was used to develop the learning system controller in a flexible and cost-efficient manner. This paper provides a description of the selected CMAC, a brief overview of the real-time engine simulator and its integration with the learning system as well as a few results.

Approximate Nonlinear Modeling and Feedback Linearization Control for Aeroengines

2011 ◽  
Vol 133 (11) ◽  
Author(s):  
Hui Zhao ◽  
Jinfu Liu ◽  
Daren Yu
Keyword(s):  
Feedback Linearization ◽  
Nonlinear Modeling ◽  
Loop System ◽  
Control Technique ◽  
Input Output ◽  
Close Loop System ◽  
Identification Procedure ◽  
Turbofan Engine ◽  
Engine Simulation ◽  
Feedback Linearization Control

This paper aims to develop an applicable nonlinear control technique for aeroengines. An approximate nonlinear model is presented and a rational identification procedure is given. Exact input-output feedback linearization can be easily performed on this model. The controller derived can approximately linearize the plant such that the close-loop system exhibits linear input-output dynamics locally. Modeling and controlling are exemplified and validated by a small turbofan engine. Simulation results illustrate that the modeling accuracy is good and linear close-loop system dynamics are achieved.

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