Simulation Modelling Practice and Theory

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1 Simulation Modelling Practice and Theory 21 (212) Contents lists available at SciVerse ScienceDirect Simulation Modelling Practice and Theory journal homepage: Actuator-based hardware-in-the-loop testing of a jet engine fuel control unit in flight conditions M. Montazeri-Gh, M. Nasiri, M. Rajabi, M. Jamshidfard Systems Simulation and Control Laboratory, Department of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran article info abstract Article history: Received 8 February 211 Received in revised form 18 July 211 Accepted 21 September 211 Available online 15 November 211 Keywords: Flight Turbojet engine Hardware-in-the-loop Fuel control unit Electro-hydraulic An actuator-based hardware-in-the-loop (HIL) simulation for testing of a jet engine fuel control unit (FCU) is presented. In this approach, the FCU operates dynamically as the hardware in connection with an integrated flight and propulsion numerical simulation. The simulator is built based on a state-of-the-art hydraulic test bench which experimentally simulates hydraulic loads imposed on the FCU in flight conditions. For this purpose, an electric motor is employed to drive the FCU gear-typed fuel pump using the reference shaft speed signal that comes from the simulation. The HIL simulator developed in this study is finally used to test the FCU and to investigate the interaction between the FCU and overall aircraft performance. The results of HIL simulation demonstrate the functionality of the proposed HIL simulation during flight maneuvers. Ó 211 Elsevier B.V. All rights reserved. 1. Introduction Hardware-in-the-loop (HIL) simulation enables the operation and testing of actual components of a system along with virtual computer-based simulation models of the rest of the system in real time [1,2]. In a typical HIL test, the hardware component consists of a box of electronic components which can communicate with the software models via electrical signals exchanged using a data acquisition card [3]. Several studies have been reported for the use of HIL simulation approach for rapid prototyping of electronic control unit (ECU) of turbojet [4 6] and turbofan engines [7 9]. Recently, the use of HIL simulation to test the mechanical and other components has been attracted. Such simulations which have significant power flows between the real hardware and simulation make their design more challenging. This kind of HIL simulation is often called actuator-based HIL simulation or dynamic substructuring. Gawthrop et al. [3,1] presented an overview to the topic of real-time dynamic substructuring in variety of applications. In the field of aerospace engineering, several researches have been undertaken to employ the concept of the HIL simulation to examine the performance of aircraft vehicle components within a closed loop virtual simulation of the remaining subsystems. For instance, the authors in [11] have presented the development of an HIL simulation for testing of vision based control systems for unmanned aircraft vehicles (UAVs). The authors have explained how to integrate a camera-in-the-loop simulation with the model aircraft in a wind tunnel. In addition, the study reported in [12] has addressed the testing of electro-hydraulic actuators and their interactions with the representative environment by emulating the aerodynamic loads caused by the aircraft control surfaces. In [13], a study of the performance of a fuel-cell-powered UAV using an HIL simulation of the aircraft in flight has been presented. The authors of [14,15] have presented an integrated flight control development to implement and test the flight controllers on small unmanned aircraft vehicle systems. However, the use of HIL simulation for testing of jet engine fuel control unit (FCU) in flight condition has not been studied. Corresponding author. Tel.: address: m_nasiri@iust.ac.ir (M. Nasiri) X/$ - see front matter Ó 211 Elsevier B.V. All rights reserved. doi:1.116/j.simpat

2 66 M. Montazeri-Gh et al. / Simulation Modelling Practice and Theory 21 (212) The dynamic performance of an electro-hydraulic FCU can be influenced by changes in the characteristics of the operating environment and by changes in the system parameters. Therefore, it is desired to verify the correct operation of electrohydraulic FCU experimentally using real hardware. In addition, since this hydraulic actuator is an integral part of the flight control loop, actuator faults can influence the handling quality of the aircraft and limits its overall maneuverability. Hydraulic actuator faults, such as loss of supply pressure or nonlinearities arising from the servo valve orifice port shapes or flows and operation under control valve saturation can impair the dynamic response of the hydraulic system and decrease the functionality of the process in which the actuator is embedded. HIL simulation is a way to shorten the design cycle and improve the reliability and robustness of the FCU, when detailed field testing is not feasible. Accordingly, The FCU can be experimentally tested under operating conditions that resemble, more closely, the intended application without the need to operate the real process. Moreover, the availability of an HIL simulation environment allows the effects of hydraulic actuator faults on the performance of the overall system to be studied in a safe and controlled fashion. In this paper, an actuator-based HIL simulation framework is developed for testing of jet engine FCU in flight conditions. The HIL simulator is based on a state-of-the-art hydraulic test bench that has the ability to experimentally simulate hydraulic loads. The goal of this novel HIL simulation is to test the engine FCU and to investigate, for the first time, the complex interaction between the FCU hardware and overall aircraft performance. This paper presents a functional overview of the HIL simulator and demonstrates the applicability of the developed experimental framework towards meeting these objectives. To the authors knowledge, this work presents the first development of HIL simulation framework for jet engine fuel control system that incorporates electro-hydraulic FCU hardware within the real-time integrated flight and propulsion simulation. The reminder of the paper is organized as follows. The next section describes the configuration and operation of the FCU. The detailed structure of HIL simulation, the software and hardware framework and interfaces are presented in Section 3. Section 4 describes the software simulation including the flight, turbojet engine and ECU models. Interfacing the simulation to hardware is presented in Section 5. In Section 6, the hydraulic test bench for testing of the FCU is explained. The emulator of pump driver and its control system is described in Section 7. Finally, the results of the simulation with the simulated FCU and actual FCU are compared in Section 8. Some concluding remarks are presented in Section Fuel control unit description Basic components of the proposed electro-hydraulic FCU are shown in Fig. 1. A gear-type fuel pump, which is driven in a fraction of the engine shaft speed, supplies fuel to the system. The unit employs a pressure balanced metering valve, which Fig. 1. Fuel control unit (FCU).

3 M. Montazeri-Gh et al. / Simulation Modelling Practice and Theory 21 (212) consists of a plunger and barrel with longitudinal slits, to control fuel flow rate. Depending on the position of the plunger exposing the slits in the barrel and assurance constant differential pressure, the fuel flow rate to the engine would be proportional to the flow area. The spool type bypass valve is used to keep the differential pressure across the metering valve constant by spilling back the excess fuel flow delivered by the pump to the tank. This causes the metering valve operation becomes linear with respect to the flow area. A servo motor is employed to operate on the metering valve plunger and a screw is used to convert servo motor rotational motion to linear movement. Also a spring maintains the connection between the barrel and shaft during retraction. A restriction orifice is used to prevent bypass valve spool fluctuation by the eventual pump flow impulses. Finally, the fuel nozzle is connected at the output part of the FCU. Fig. 2. Fuel control system block diagram. Fig. 3. HIL simulation framework.

4 68 M. Montazeri-Gh et al. / Simulation Modelling Practice and Theory 21 (212) Fig. 4. Simulation platform (1: host PC, 2: target IPC, 3: PC for speed control of AC motor, 4: target PC interface, 5: interface for speed control of AC motor, 6: flowmeter, 7: FCU, 8: AC motor, 9: variable frequency drive for AC motor, 1: booster pump, 11: tank, 12: pressure gage, 13: voltage to PWM converter, 14: graphics display). 3. HIL setup A schematic of the HIL simulation framework for testing of the FCU is presented in Fig. 2. As shown in this figure, the jet engine and its ECU are numerically simulated within a flight simulator and the FCU is immersed within the HIL simulation as the hardware. The Matlab/Simulink is selected as the base software used in this study. The toolbox of real-time workshop (RTW) is also used to generate the C-code directly from the Simulink model. The xpc-target is then selected as an HIL simulation platform which can be employed to make a real-time system with the host and target PCs. It provides a high-performance host-target prototyping environment to connect with the physical systems, and then execute them in real time on PC-compatible hardware. The xpc target also provides some input/output (I/O) interface blocks for system engineer to add them into the Simulink model on the host PC, and then to automatically generate code with real-time workshop which can be uploaded to the target PC for running real-time applications. The host PC is operated under Microsoft Windows operation system like a general PC. The target PC runs the simulation programs with the xpc operating system for speeding up the computation, and hence, to realize the real-time simulation. In addition, a TCP/IP network connection is used as the connection between the host and target PCs. The HIL simulator consists of a host computer (PC1), target computer (PC2), Ethernet network card, network cable and an I/O device. The block diagram of this HIL system is shown in Fig. 3. An industrial personal computer, PC2, is used as the target computer. A compact disc carries xpc target real-time kernel is used for starting the target computer. After starting the target computer, the application files of flight, jet engine and ECU models are uploaded from the host computer to the target computer via TCP/IP protocol. An Ethernet local area network (LAN) and an NE2 network card are used for connecting the host and target computers. In order to connect the target computer and FCU hardware, the Advantech PCL-812PG I/O card is employed as an interface between the software and FCU. A desktop computer, PC3, serves as a processor to control the experimental AC motor shaft speed via a software coded control law. The commanded speed of the motor is computed by the target PC2, for transmission to the speed controller computer over a data acquisition card. The speed command and the measured motor speed are communicated back to PC3. The final computer, PC4, is employed to run a graphics engine to render the aircraft motion. A photograph of the HIL test facility and an overview of the HIL simulator architecture are shown in Fig Software simulation 4.1. Flight model The flight model developed for use in the HIL simulation environment is based on a 6 DOF nonlinear model of aircraft presented in [16]. Based on the assumption of the flat earth, the generic equation of translational motion is given in Eq. (1) where the resultant applied force F b is in the body frame. F b þ½dcmš 1 mg ¼ mð _ V b þ x b V b Þþ _mv b where m is the mass of the aircraft, V is the aircraft velocity, g is the gravity vector in the inertial axis system and DCM is the directive cosine matrix and can be calculated according to Euler angles. Subscript b denotes the body-axis system. ð1þ

5 M. Montazeri-Gh et al. / Simulation Modelling Practice and Theory 21 (212) The rotational dynamics of the body defined in body-axis is given in Eq. (2). T B ¼ I _x B þ x B ðix B Þ where T is the resultant moment applied to the aircraft in the body-axes system, x is the aircraft angular velocity and I is the inertia tensor with respect to the body origin. The force and moment vectors in Eqs. (1) and (2) include the effects of aerodynamic and propulsion. Aerodynamic forces and moments are obtained using stability and control derivatives and are obtained from the extensive theoretical works and given in the format of a numerical look-up table. Aerodynamic forces in terms of lift, drag, and side-force are most conveniently expressed in the stability-axis system and are transformed into the body-axis using DCM matrix. The contribution of the engine to the force vector in Eq. (1) is based on a thermodynamic model of the engine through thrust value and will be represented in greater detail in the next section. Moreover, the positioning dynamics of the actuators are described in the flight model as first-order lags. The aircraft position (x) in earth centered inertial reference frame is calculated as follows. _x ¼ DCM T V b Moreover, an autopilot is implemented in the simulation to drive the aircraft aileron and elevator actuators. The controlled flight variables are the aircraft body axis roll and glide angles. The graphics engine selected for use in the HIL simulation environment is the 3DSTATE package [17]. The C++ programming language and object oriented principles are utilized as a platform to use 3DSTATE package for graphical 3D rendering process. To interface the flight model to the 3DSTATE graphics engine, an RS232 protocol has been used Turbojet engine model The process considered is a single spool turbojet engine with a convergent nozzle, without bypass and bleed flow. The assumptions in the model presented here are that, there does not exist any heat transfer between the control volumes and the gas is perfectly mixed in each control volume. These assumptions imply that only two gas states per control volume are necessary to determine the condition there. Jet engine model has been composed of two parts. The first one refers to a system of Algebraic nonlinear equations that describe the thermodynamic relations in compressor, turbine and nozzle [18,19]. The second refers to dynamic nonlinear equations that describe transient processes. It has been assumed that the processes of accumulating the enthalpy and the mass of working medium take place only in combustion chamber and nozzle. Similar progress in the inlet duct, the compressor and the turbine has been neglected. Disregard of the turbine duct volume has resulted from the fact that it is a single stage turbine. In addition, the compressor duct has been modeled as a control volume together with the combustion chamber. The transient equations due to combustion chamber volume are as follows [19,2]: ð2þ ð3þ dt b dt ¼ 1 ½ _m 3 ðct 3 T b Þþ _m 4 ðt b ct 4 Þþ _m f g m b H f Š b dp b dt ¼ð_m 3 _m 4 Þ RT b þ P b dt b T b dt V b And the following relations show transient equations due to nozzle volume: dt n dt ¼ 1 ½ _m 5 ðct 5 T n Þþ _m e ðt n ct e ÞŠ m n dp n dt ¼ð_m 5 _m e Þ RT n þ P n dt n T n dt V n ð4þ ð5þ ð6þ ð7þ Moreover, the Euler equation due to the rotational motion of the shaft is given by: _N ¼ _m tc ph JN ðt 4 T 5 Þ _m cc pc JN ðt 3 T 2 Þ ð8þ The parameters used in Eqs. (4) (8) are defined in Fig. 5 and Table 1. Physical modeling of turbojet engine results in systems of differential and algebraic equations (DAEs). This model includes seven algebraic equations and five ordinary differential equations (ODEs). The ODEs are solved using the fourth order Runge Kutta method. The steady state values of variables at the starting time of simulation are given by solving a set of nonlinear algebraic equations using Newton Raphson method [6]. In addition, the engine is equipped with some pressure transducer, thermocouples, flowmeter and a magnetic toothed wheel to measure the operating parameters of the engine in the test. Moreover, a PC/14 embedded computer is employed to receive the signals from the measurement devices at a desired rate. Furthermore, the fuel flow is changed by a PLA (power lever angle) manually where the servo angle is varied according to the PLA command. Fig. 6 shows comparison of error between the engine thermodynamic model and test response due to fuel flow variations. These results show a good agreement between the model and test responses that support the model used in this study.

6 7 M. Montazeri-Gh et al. / Simulation Modelling Practice and Theory 21 (212) Fig. 5. Turbojet engine. Table 1 Symbol of parameters for jet engine model. Symbol c g _m T P N H c ph, c pc Subscripts c t n b f Parameter Ratio of specific heats Efficiency Mass flow rate Temperature Pressure Rotor speed Heating value Specific heat of hot/cold air at constant pressure Compressor Turbine Nozzle Combustion chamber Fuel 1.95 Rotor speed (Normalized) Experimental Simulation time (sec) Fig. 6. Engine shaft speed. The interesting parameter during flight simulation is the net thrust. To calculate the net thrust, the aircraft s mach (M) and altitude (H) are required. In this study, the gross thrust of the jet engine during flight is calculated by use of a lookup table. Moreover, the aircraft angle of attack (a) and side-slip (b) affect the engine performance Electronic control unit model The pilot is usually not interested in getting a specific net thrust value from the aircraft engine. What the pilot usually wants to achieve is to get the engine to deliver a certain percentage of the thrust that is available at the current flight conditions. Since thrust itself is not measurable in flight, the relative thrust command given by the power lever angle

7 M. Montazeri-Gh et al. / Simulation Modelling Practice and Theory 21 (212) Table 2 Specification of target computer. Component Specification CPU Intel Core 2 due, 2.4 GHz RAM 2 GB COM Ports 2 Slots 4 ISA, 6 PCI LAN 1 onboard HDD SATA (PLA) setting must be translated into a command change of a measured variable. The relative thrust corresponds very well to the engine pressure ratio. Therefore the engine pressure ratio is used for thrust modulation in controller design. In this study, the min max fuel controller employed in the ECU is simulated according to Ref. [21]. Using this control algorithm, four control loops are defined for calculation of fuel flow. Three of the fuel control loops are limiting control loops which include maximum shaft speed limitation, maximum acceleration limiting, maximum deceleration limiting and thrust modulation for satisfying the pilot demands [22]. The first three limiting loops organize a bounded safe zone for transient fuel selection and the safe physical operation of the engine will be attained. The fuel flow corresponding to each control loops are named _m nmax ; _m dec ; _m acc and _m pla respectively. Then the engine transient fuel flow is calculated using the following min max selection algorithm. _m f ¼ minðminðmaxð _m dec ; _m pla Þ; _m nmax Þ; _m acc Þ ð9þ 5. Simulation to hardware interface As shown in Fig. 3, the HIL simulation environment consists of four computers. Two computers named PC1 and PC2 are employed as host and target computers respectively and the third computer named PC3 is used for AC motor rotor speed controller. The final computer, PC4, is also employed to run a graphics engine to render the aircraft motions AC motor controller interface The connection between the AC motor speed controller (PC3) and the test setup has been done via Advantech data acquisition card of PCI The card reads the signals that come from the target PC and tachometer as the reference and feedback signals respectively and sends the control signal to the driver of the AC motor Target PC interface An industrial PC with specifications shown in Table 2 is used as the target computer for jet engine and flight simulations. This computer is equipped by the ISA card of Advantech PCL-812PG. This card has two analog output channels. These channels are used for exporting servomotor driving signal and shaft speed as the outputs of the jet engine simulation. Moreover, an analog input channel of the card is used for reading the flowmeter signal Voltage to PWM converter For voltage to PWM converter, the analog output part of the Advantech PCL-812 PG data acquisition card, installed on the target PC, is connected to the analog input port of the AVR microcontroller employed in the converter. The PWM pulse signal generated by the microcontroller is used to drive the servomotor of the FCU. The spool of the FCU control valve is controlled by a cam installed on a servo motor shaft. 6. Hydraulic test bench A schematic of the hydraulic circuit implemented on the hydraulic test bench is shown in Fig. 7. This setup is a mechatronic collection which includes mechanical design, discharge and pressure sensors, tachometer, control unit and piping systems. Fuel control unit has two distinct parts. The first part is a hydraulic block and the second is a control block. The hydraulic block consists of a miniature gear type liquid fuel pump and a filter to provide flow and to overcome working pressure of the system. The control block includes a servomotor and a spool valve. In order to test the control and hydraulic blocks simultaneously, the blocks working conditions must be similar to the engine working conditions. The installed pump on the FCU, receives its motive force from the shaft of the engine. The components of this test bench are described based on Fig. 7. Booster pump (1) sucks fluid from the atmospheric reservoir and transfers it to entrance of the FCU. Fluid pressure in the pump entrance is measured by means of a pressure gage (2). Controlled flow is directed to the nozzle and its pressure is also recorded by a pressure gage sensor (3). The fluid flow is

8 72 M. Montazeri-Gh et al. / Simulation Modelling Practice and Theory 21 (212) Fig. 7. Hydraulic test bench. measured by the flowmeter (4). The fuel returns to the tank after passing through the nozzle orifice (5). In this test stand, the fuel is replaced by a kind of white oil which is safe and non-flammable and its viscosity and density are similar to the jet engine fuel. 7. Jet engine shaft speed emulator To drive the hydraulic pump of the FCU, an AC motor with a variable frequency drive is used. The AC motor speed is controlled by a PI controller with an optical tachometer. In this paper, the model structure used for the AC motor modeling is as follows. height (m) x y(m) 1 2 x(m) Fig. 8. Trajectory of the aircraft. 3 2 Elevator deflection Aileron deflection 1 δe, δa (deg) time (sec) Fig. 9. Deflections of elevator (de) and aileron (da) control surfaces.

9 M. Montazeri-Gh et al. / Simulation Modelling Practice and Theory 21 (212) K GðsÞ ¼ ½ðT w sþ 2 þð2nt w Þs þ 1ŠðT p s þ 1Þ ð1þ The method of iterative prediction error minimization (PEM) is employed to Estimate model parameters that minimizes the prediction errors to obtain maximum likelihood estimates. The response of the transfer system G(s) is measured experimentally by applying a square wave speed set point to the system; and the corresponding speed is measured. The model obtained from the identification stage was used to replace the real system within simulated environment in order to design the suitable controller. In this paper, a conventional PI controller is applied due to its simplicity. The result of applying the controller is also presented in Fig. 16 which shows that the controller is successful in following the desired speed. The experiment setup for control of the motor includes a desktop computer with an Advantech data acquisition card of PCI In this application, the frequency command is generated from the target PC and the actual frequency is read from the tachometer by the analog input channel of the card. 8. HIL simulation experimental results The HIL simulation setup is run for a flight maneuver. In the flight maneuver, a typical roll and glide angles controls are performed using conventional controllers, activated in the longitudinal and lateral channels of the flight control system. The aircraft is trimmed for steady flight at 3 km altitude and 21 m/s airspeed. A 1 glide angle and 3 roll angle are Fig. 1. Aircraft angle of attack (a) and sideslip (b) responses. Fig. 11. Input power lever angle (PLA).

10 74 M. Montazeri-Gh et al. / Simulation Modelling Practice and Theory 21 (212) compressor discharge pressure cdp (Normalized) MIL simulation HIL simulation time(sec) Fig. 12. Compressor discharge pressure. 1. engine rotor speed (Normalized) MIL simulation HIL simulation time(sec) Fig. 13. Jet engine shaft speed..8 MIL simulation HIL simulation servo angle (Normalized) time(sec) Fig. 14. Servomotor angle.

11 M. Montazeri-Gh et al. / Simulation Modelling Practice and Theory 21 (212) commanded and held for 7 s. Fig. 8 shows the resulting aircraft trajectory of the aircraft in the maneuver. The deflections of elevator (de) and aileron (da) control surfaces are shown in Fig. 9. Moreover, Fig. 1 shows the aircraft angle of attack (a) and sideslip (b) responses. In this HIL simulation, the ECU algorithm performed using a min max controller previously developed in [22]. The engine is simulated in flight conditions and control surfaces with fuel flow rate are varied during the simulation. In order to achieve the goal of real-time simulation, the fourth-order Runge Kutta method with a fixed-step time is chosen that provides accurate results at a step size enlarged to 5 ms and the integration still remains stable. Note that although the integration step size can be more enlarged, the ECU of the engine is operated at a sampling period of 56 ms, and the simulation code must provide feedback information at a period of 56 ms. Hence the largest integration step size that can be used is 56 ms. In order to compare the response of the simulated and the actual FCU responses, the same type of input test is attempted. In the flight simulation, the flight control inputs (elevator, aileron and PLA) are commanded by an autopilot implemented in the simulation. Fig. 11 shows the time history of the PLA input applied by the autopilot with simulated and experimental FCU. In the ECU, the PLA command is transformed into compressor pressure ratio (CPR) demand and the controlled engine follows this demand using min max controller. Fig. 12 shows the performance of the controller in following the demand. The agreement between the PLA and CPR validates that the min max controller operates successfully. Similar results are achieved using the same PLA input applying to the simulation with simulated FCU. Comparison of the results for FCU Model-In-the-Loop (MIL) and experimental FCU in the loop (HIL) has been shown in Figs After going through the results, it becomes clear that the HIL simulation results match with those of MIL simulation. The similarity between the two traces, with simulated and experimental FCU, indicates that the modeled FCU employed in the integrated flight and propulsion.4 fuel flow rate (Normalized) time(sec) Fig. 15. Fuel flow rate forward velocity (m/sec) MIL simulation HIL simulation time(sec) Fig. 16. Forward velocity of the aircraft.

12 76 M. Montazeri-Gh et al. / Simulation Modelling Practice and Theory 21 (212) thrust (Normalized) MIL simulation HIL simulation.1 time(sec) Fig. 17. Jet engine thrust..25 AC motor speed (Normalized) Command speed Actual speed time (sec) Fig. 18. AC motor speed..8.7 MIL simulation HIL simulation HIL simulation with const. rotor speed servo angle (Normalized) time(sec) Fig. 19. Effect of shaft speed emulator on performance of the experimental FCU.

13 M. Montazeri-Gh et al. / Simulation Modelling Practice and Theory 21 (212) simulation, is accurate. The HIL test results verify proper functionality of the FCU and its ability to provide the fuel required for performing the maneuver. The difference between the two results is mainly due to hardware uncertainties. Although a clear lag between the MIL and HIL simulation are unavoidable because of the sensor delays and the emulator transfer system dynamics. The effect of transfer system dynamics can be mitigated by the methods presented in [3]. Fig. 16 shows how the experimental FCU influences the forward velocity of the aircraft for the tested flight condition. As shown in Fig. 17, changing the thrust produced by the engine alters the forward velocity. The efficacy of the dynamic jet engine shaft speed emulator to accurately replicate the commanded shaft speed is verified in Fig. 18. The result of applying the speed controller shows that the controller tries to track the desired speed for a wide variety of loads. In the HIL simulator, two tests are carried out to illustrate how the performance of the experimental FCU can change when it is operated under shaft speed emulator. In the first experiment, the FCU is operated with constant shaft speed and then, the experiment is repeated with shaft speed emulator. The consequences of the speed emulator on the performance of the experimental FCU are also illustrated in Fig Conclusion This paper describes the details of a hardware-in-the-loop (HIL) simulation environment that has been developed to support the research activities on the design and verification of an electro-hydraulic fuel control unit (FCU). The simulator is built around a state-of-the-art hydraulic test bench that can experimentally simulate several systems affecting the performance of the FCU. The experimental hardware is employed within the environment of the numerical real-time simulation of a turbojet engine in flight conditions. An AC motor is also used to emulate the fuel pump driver of the FCU. In the real engine, the pump is driven mechanically by a gear from the jet engine main shaft. Thus, the actuator-based HIL simulator allows the FCU performance to be tested under operating conditions that are similar to those found in a real jet engine application. In order to meet the requirement for real-time simulation, a host-target architecture is employed over an Ethernet network. A high speed industrial PC is used as a master processor to real-time integrated flight and propulsion simulation to perform the numerical integration of flight and jet engine dynamic equations. Finally, the results of the HIL experiment are presented to demonstrate the overall functionality of the simulator and emphasize the relevance of the simulation framework toward development and testing of FCU. References [1] H.K. Fathy, Review of hardware-in-the-loop simulation and its prospect in the automotive area, Society of Photo-optical Instrumentation Engineers, Proceedings of SPIE 6228 (26). [2] R. Isermann, J. Schaffnit, S. Sinsel, Hardware-in-the-loop simulation for the design and testing of engine-control systems, Control Engineering Practice 7 (1999) [3] P.J. Gawthrop, D.W. Virden, S.A. Neild, D.J. Wagg, Emulator-based control for actuator-based hardware-in-the-loop testing, Control Engineering Practice 16 (8) (28) [4] T. Cheng, Hardware in the loop simulation of mini type turbojet engine digital control regulator, Journal of Aerospace Power 19 (3) (24) [5] A. Watanabe, S.M. Ölçmen, R.P. Leland, K.W. Whitaker, L.C. Trevino, C. 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14 ID Title Pages Actuator-based hardware-in-the-loop testing of a jet engine fuel control unit in flight conditions