Study on Modeling and Simulation of a Flight Simulator Engine System

Haiguo Xiong, Qitao Huang, Hongzhou Jiang and Junwei Han School of Mechatronics Engineering

Harbin Institute of Technology Harbin, Heilongjiang Province, China

haiguox@163.com Abstract –The accurate aero-engine simulation of the flight simulator is very difficult. To establish the perfect models of aero-engine, the study on modeling method and simulation of turbofan engine system are carried out in this paper. Based on the engine operating principle, control law, logical relation of individual components and vast test data, the engine performance models and function models are developed using Integrated Modeling method. Then the application of 3D/2D interpolation algorithm, alterable coefficient method and modularization modeling method in engine modeling is investigated and the simulation of engine performance in various working conditions is realized. The simulation results show that the established models can satisfy the tolerance of acceleration and deceleration of flight simulator engine system. They also show that the Integrated Modeling method has the advantages in resolving the contradiction between Real-time characteristic and precision of simulation. Index Terms - aero-engine, Integrated Modeling method, interpolation algorithm, alterable coefficient method

I. INTRODUCTION

The aero-engine simulation is an important part of flight simulator, but the complex working conditions and various working environments of the aero-engine make the modeling of flight simulator engine system become very complicated and difficult. Presently, the Overall Modeling method and the Component Level Modeling method are widely used in the engine system modeling. The Overall Modeling method regards the entire engine as a "black-box"; it simulates the primary performance of Input and Output [1] and develops the corresponding connection model between thrust level position and rotor speed using the engine test data as data table. The developed model does not describe the working conditions of components. In this case, the engine internal aerothermodynamics are not of primary interest and the engine model is usually simplified to achieve the required computing speed [2~5]. This method has good Real-time characteristic, but in the process of modeling, it needs much data which are obtained from various engine trial run and test flight conditions to satisfy the requirements of simulating accuracy. The Component Level Modeling method regards each component as a "black-box"; it develops the mathematical models of the performance of individual component, then determines the performance of engine according to the working characteristic of individual component. The developed models do not describe the

internal working condition of each component. This method needs to calculate lots of Component Level Models (CLM), so the Real-time characteristic is poor. But this method has many advantages, such as simulating many working conditions, outputting many state parameters, having high precision and so on. In this paper, Integrated Modeling method is used in the turbofan engine simulation which is "Overall modeling method + Component Level Modeling method". It develops the engine steady state and dynamic state performance simulation models using Overall Modeling method and develops the engine control system function and logic simulation models using Component Level Modeling method.

II. ENGINE SYSTEM MODELING

The engine system used in flight simulator is a complex Real-time Digital Simulation system. It consists of two parts, engine performance simulation and control system function simulation. Engine performance simulation calculates the engine steady state and dynamic state mathematical models. It makes the output characteristics of engine system basically same as the true aero-engine throughout the process of the flight envelope and from start-up to maximum-state of the thrust level. Control system function simulation simulates the function and logic of engine control system and its sub-systems to make sure that the engine system can normally work in the different working states and flight conditions. Engine system simulation model consists of engine performance models and control system function models, as shown in figure 1.

Fig.1 Engine system model structure

A. Engine System Performance Model 1) Engine Steady state Performance Model

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Proceedings of the 2007 IEEEInternational Conference on Integration Technology

March 20 - 24, 2007, Shenzhen, China

Engine steady state models are developed using the Similarity Theory. Synthetical characteristic of the turbofan engine is simulated by steady state models which include rotor speed characteristic, altitude characteristic and velocity characteristic. Because the major thrust of high bypass ratio turbofan engine is provided by the outer duct fan, the low pressure rotor speed 1N will represent engine thrust more directly [6]. We develop the steady state model of modified low pressure rotor speed with the known steady state point data and 3D interpolation method, and then the modified low pressure rotor speed can be calculated by

( )AltitudeMachTLAfN Lcorr ,,= (1) Where LcorrN is modified low pressure rotor speed, TLA is thrust level angle, Mach is flight Mach number, Altitude is flight altitude. Using the modified low pressure rotor speed, flight Mach number and 2D interpolation method, we develop the steady state mathematical models of typical parameters. The models include modified high pressure rotor speed, modified gross thrust and modified fuel flow and so on. Individual parameters can be calculated by

),( MachNfN LcorrHcorr = (2) ( )MachNfFF Lcorrcorr ,= (3) ( )MachNfGT Lcorrcorr ,= (4)

Where HcorrN is modified high pressure rotor speed, corrFF is fuel flow, corrGT is gross thrust. The modified engine mathematical models mentioned above just consider the change of state parameters with the change of flight altitude, flight velocity and thrust level position. But they don’t consider the effects produced by ambient temperature and engine fan inlet pressure to the state parameters. So the redefined standard models with the ambient temperature and the engine fan inlet pressure can be expressed as

( )0

21T

MachTNN amb

LcorrL∗+∗

∗=α

(5)

( )0

21T

MachTNN amb

HcorrH∗+∗

∗=α

(6)

( )t

ambcorr P

TMachT

FFFF Δ∗∗+∗

∗=0

21 α (7)

amb

tcorr P

PGTGT ∗= (8)

Where LN is standard low pressure rotor speed, HN is standard high pressure rotor speed, FF is standard fuel flow, GT is standard gross thrust, ambT is ambient temperature, 0T

is sea level temperature, α is coefficient, tPΔ is engine fan Inlet total pressure ratio, tP is engine fan inlet total pressure,

ambP is ambient pressure.

The engine steady state mathematical models which are developed by using the interpolation table well meet the Real-time requirements of flight simulator engine system, and the mathematical models have good readability and maintainability.

2) Engine Dynamic State Performance Model Engine transition state includes start, shutdown, acceleration and deceleration [7]. The dynamic state performance simulation mainly simulates the transition process of one steady working state rapidly and safely transferring to another steady working state. So, the start point parameters of dynamic state process should use the data include original test data, test flight data or the state parameters calculated by the steady state models. In the specific modeling process, aiming at different engine working states, colligating the factors affect the engine state parameters such as compressor bleed, engine anti-ice, fault and so on, adopting the alterable coefficient establish the engine dynamic state models to simulate the engine inertia. The established dynamic state models can be written as

( ) ( ) tkNN nltLtL Δ∗±=+1 (9)

( ) ( ) tkNN nhtHtH Δ∗±=+1 (10)

( ) ( ) tkFFFF fftt Δ∗±=+1 (11)

Where ( )1+tLN , ( )1+tHN and ( )1+tFF are next moment low pressure rotor speed, high pressure rotor speed and fuel flow.

( )tLN , ( )tHN and ( )tFF are current moment low pressure

rotor speed, high pressure rotor speed and fuel flow. nlk , nhk and ffk are low pressure rotor speed coefficient, high

pressure rotor speed coefficient and fuel flow coefficient. tΔ is step.

Alterable coefficient model is the product of all effect factors,

ni kkkkk ��21=β (12) Where βk is state parameter coefficient, β can be nl , nh or

ff , ik is the number of i effect factor coefficient. Almost all the thrust of turbofan engine is provided by the low pressure rotor. So, the engine gross thrust dynamic state mathematical model is the function of the low pressure rotor speed. The dynamic change of gross thrust will be carried out by the dynamic change of modified low pressure rotor speed. The gross thrust dynamic state mathematical model can be written as

( ) ( ) tkNN nlcorrtLcorrtLcorr Δ∗±=+1 (13)

( )( )MachNfGT tLcorrdyncorr ,1+= (14)

Where ( )1+tLcorrN is next moment modified low pressure

rotor speed, ( )tLcorrN is current moment modified low

pressure rotor speed, nlcorrk is modified low pressure rotor speed coefficient, dyncorrGT is dynamic state gross thrust.

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EEC Power Unit

Ignition Control

Channel A Cross Channel Data

Link

Thrust Reverser Interlock Solenoid

Starter Air Valve

L and R Ignition Syatems

VSVVBV HPTACC

LPTACCTBV

EHSVSFMV

HPSOV

Oil Filter Clog

12T 2525 / PT 3T CCT 5.49T 12SP 3SP LN HN

Channel B

EEC

Fuel Filter Clog

Fuel Flow

DMS Detector

Start Switch

Start Lever

TRA

Fire Handle Switch

DEU

Oil Pressure

Oil Tempreture

Fuel

HMU

ElectronicFuel FlowArinc429

Engine system dynamic state performance mainly lies on the rapidity of transient response. For example, through measuring the total time which is from the moment of beginning of moving the throttle to the moment of the response value of typical parameters reaching 10% can reflect the engine accelerating ability. The engine dynamic state mathematical model which is established using the alterable coefficient method loses some calculating accuracy, but it improves the computing speed effectively and satisfies the dynamic state performance of the engine commendably.

B. Engine System Function Model Engine system of flight simulator is an important part of flight simulator, the accuracy of its models and the extent of simulation has a direct impact on the fidelity of the flight simulator. Engine system function simulation is another vital component of engine system simulation. In this paper, the turbofan engine control is Full Authority Digital Electronic

Control (FADEC), which uses Electronic engine control (EEC) as its centre. EEC works together with engine fuel system, oil system, start system, thrust reverser system, engine sensor, air system etc to supply the control of engine in the entire flight envelope and to carry out steady-state performance and dynamic state performance. The engine control system of flight simulator needs to simulate almost all the functions and logic of aero-engine control system. The interface of engine control system of flight simulator is very complex, as shown in figure 2.Engine control system receives the discrete signals of switches from cockpit and analog signals of thrust lever. By calculating and processing the input signals on the basis of flight condition and aircraft attitude, the control system provides thrust for flight system, rotor speed for sound system, fuel flow for fuel system, oil pressure and temperature for oil system and indicative information for correlative instruments and lights.

Engine control system simulates the following functions of aero-engine system. The simulation of control function of engine gas generator includes fuel flow control simulation, VSV, VBV and TBV control simulation and turbine clearance control simulation. Engine limitation protection function simulation includes engine fan speed ( LN ) and engine core speed ( HN ) over speed protection and engine exhaust temperature (EGT) monitoring. Engine power management simulation includes engine thrust automatic control and using LN as the given parameter to calculating the limited thrust value. Engine start function simulation includes starter valve on/off logic simulation, high pressure shutoff valve logic simulation and ignition on/off logic simulation.

Thrust reverser control function logic simulation includes thrust reverser deploy and stow logic and thrust reverser power control. Engine parameters cockpit indication simulation includes low pressure rotor speed, high pressure rotor speed, exhaust temperature, fuel flow, oil temperature, oil pressure, fuel quantity, thrust reverser, engine fail, start valve open, oil filter bypass, low oil pressure and engine vibration indications, etc. Based on the analysis of function and logic of aero-engine control system and interface parameters of engine system, it develops the engine function models with modularization modeling method. The structure of function models as shown in figure 3.

Fig.2 Engine control system interface

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Fig.3 Engine control system function models structure

III. SIMULATION AND ANALYSIS OF RESULTS

According to the established mathematical models, it develops the simulating program of turbofan engine using the Matlab/Simulink tools, and then simulates the process of acceleration and deceleration of the engine. The simulating results are shown in Fig.4 to Fig.9.

0 2 4 6 8 1020

40

60

80

100

120

Time(t)

N1(

%)

Fig.4 Low pressure rotor speed during acceleration

0 2 4 6 8 1070

75

80

85

90

95

100

Time(s)

N2(

%)

Fig.5 High pressure rotor speed during acceleration

0 2 4 6 8 100

0.5

1

1.5

2x 10

4

Time(s)

Thr

ust(lb

s)

Fig.6 Thrust during acceleration

15 20 25 30 35 400

20

40

60

80

100

120

Time(s)

N1(

%)

Fig.7 Low pressure rotor speed during deceleration

15 20 25 30 35 4050

60

70

80

90

100

110

Time(s)

N2(

%)

Fig.8High pressure rotor speed during deceleration

15 20 25 30 35 400

0.5

1

1.5

2

2.5

3x 10

4

Time(s)

Thr

ust(

lbs)

Fig.9 Thrust during deceleration

After contrasting the simulating data with the real flight data, it indicates that the acceleration time and deceleration time are in the tolerance defined by the Airplane Simulator Qualification. It also improved that the real time characteristic and the precision of the simulation satisfies the requirement of the engine system of flight simulator in practical application.

IV. CONCLUSION

In this paper, it develops the models of engine system using the Integrated Modeling method. After simulating with the models and contrasting the results with the real data, we can improve that the models can satisfy the tolerance of acceleration and deceleration of engine of flight simulator and it accurately reflects the actual working situation of engine. It also improves that the Integrated Modeling method commendably resolves the contradiction between Real-time characteristic and precision of simulation of engine. Modeling method study is an essential and vital step for study of engine simulation in flight simulator. The Integrated Modeling method has resolved some issues mentioned in the paper, but there still have some other unsolved issues to be studied in the future.

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