2009-01-1039

Development of an Engine-in-the-loop Vehicle Simulation System in Engine
Dynamometer Test Cell
Shugang Jiang, Michael H. Smith and James Kitchen
A&D Technology Inc.

Atsushi Ogawa
A&D Co. Ltd.
Copyright © 2009 SAE International

ABSTRACTTo meet the ever increasing requirements for engines
and vehicles in the areas of performance, fuel economy,
emission, and meanwhile reduce product development
time,
Hardware-in-the-loop(HIL)
simulationisincreasingly used in automotive control systemdevelopment.
Engine-in-the-loop(EIL)
vehiclesimulation, which is a specific form of HIL simulation, is
an approach in which a physical engine (together with its
control unit) is coupled to virtual vehicle and drivermodels through a high power, low inertia engine
dynamometer in the engine test cell environment. EIL
can be used to perform powertrain control development,
as well as engine and vehicle performance evaluation.
Because of its advantages in repeatability and flexibility
etc., especially for transient operating mode study, EIL
has become a powerful tool and will be more widelyused in the near future.
Design and implementation of an EIL vehicle simulation
system is described. Driver and vehicle simulation
models are developed and executed in real time on ahigh-speed system controller. A highly responsive
permanent magnet AC engine dynamometer and avehicle acceleration pedal are controlled such that the
dynamometer loads the connected engine as a realvehicle would and the simulated vehicle speed trace
follows the targeted driving cycle. With this system,
developers can perform transient engine control
development before whole vehicle integration isavailable. Vehicle parameters, including driveline
configurations can be easily modified and the effect onengine and vehicle performance can be studied. An
application example of simulating a 10-15 modeemission test cycle is given. The result verifies theeffective performance of the system in simulating vehicle
dynamics and shows its great potential in engine andvehicle system development.

INTRODUCTION
The ever increasing requirements for engine and vehicle
performance, fuel economy, and especially the pressure
for fulfilling stringent emission regulations have pushed
OEMs and suppliers to continually put forward newconcepts and implement new technologies. At the sametime, fierce market competition has driven OEMs tocontinually shorten the product development time. Undersuch
circumstances,
Hardware-in-the-loop(HIL)
simulation is increasingly used in automotive control
system prototyping, calibration, and validation. For the
traditional HIL simulation concept, the control unit is thephysical hardware. The engine, or the engine together
with driveline and vehicle body, is simulated in the realtime platform and interacts with the control unit throughproper interface [1-4]. This type of “controller-in-the-loop”[5] simulation is the most commonly used format in
automotive industry. However, in a much broader sense,
HIL simulation can be defined as “the operation of realcomponent in connection with real-time simulated
component” [6]. It is a setup that “emulates a system by
immersing faithful physical replicas of some of its
subsystems within a closed-loop virtual simulation of theremaining subsystems” [5]. HIL basically realizes
synergistic combination of the real and virtual

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components, which facilitates system development andgreatly reduces development time and cost. In thissense, the “hardware” that is “in the loop” does notnecessarily need to be the control unit.
In Engine-in-the-loop (EIL) vehicle simulation, the “realcomponent”, or the “faithful physical replicas”, is theengine control hardware and software together with aphysical engine; while the “real-time simulated
component”, or the “virtual simulation”, is the vehicle anddriver. The interaction between the engine and thevehicle system, which includes the driveline, tire androad interface, and vehicle body etc., is replaced by theengine and a transient dynamometer that emulates areal vehicle [5, 7-10]. There are specific reasons why
such a combination is used. There have been manystudies in which both the engine and the vehicle system
are modeled [11-13]. However, high fidelity modeling ofengine emission, especially in transient operating mode
has been very challenging. For an EIL system, since aphysical engine is in the setup, there is no need to makean effort in emission modeling. Moreover, such a system
has many other advantages for powertrain control
development, as well as engine and vehicle
performance evaluation, which are evident by looking
into the role of EIL in the whole process of the systemdevelopment cycle.
Figure 1 shows the V-cycle which is widely adopted in
automotive control system development, especially inpowertrain control development. This cycle includes all
the activities from determination of system requirement
to system validation and approval. The horizontal axis
represents time, thus a narrower “V” means a shorter
development time. The vertical axis basicallycorresponds to the hardware platform on which various
activities of the development process are performed,
with the higher position referring more to a system leveland vehicle level hardware platform, and the lower
position to a subsystem level and component level
hardware platform. The left half of the cycle mainly
covers the design and prototyping activities, while theright half covers verification, calibration, and validation
activities.

Figure 1.

V-Cycle for System Development Process

Usually model-based development methodology isadopted for the design and prototyping portion of thecycle. With this approach, after the system requirements
are studied, new algorithms are designed and specified
in a high-level graphical language. Then with the aid of
an automatic code generation tool, the algorithms areconverted and compiled into executables to be
implemented and tested on real-time hardware.
In the verification and calibration portion of the V-cycle,
various levels of HIL testing may be performed before
the system is calibrated and validated at the vehicle
level. These HIL tests can be component oriented,
subsystem oriented, or function oriented, and are usually
started out at the component level and moved on to thesystem level, i.e., after sufficient confidence is obtained
for the component and subsystem functionalities, more
system level verification and calibration is performed.
During this process, the environment is closer and closer
to the reality. EIL is the HIL testing stage in which thephysical engine is already in the setup. Moreover, theenvironment makes it possible that the vehicle anddriver behaviors are simulated. It is obvious this systemlevel verification and calibration approach can help not
only the overall engine control function verification, butalso engine calibration and performance evaluation,
especially for transient operations. As increasingemphasis is being placed on engine control performancein transient operating mode to improve fuel economy
and emission, an EIL platform shows many advantages.
Some of the benefits are as follows:• EIL provides a platform to rapidly and efficiently
evaluate, verify and debug engine control software,find and correct function errors in the early stages ofthe design process• Using EIL, developers can perform transient engine
control development before whole vehicle integration
is available• EIL can support performance-assured controller
design. With its help, developers can perform
preliminary calibration targeting driveline and vehicle
system with specific parameter values.
• An EIL system is very flexible in that the vehicle
system parameters can be easily modified such that
their impact on engine performance can be studied.
• An EIL platform provides better monitoring of engine
behavior and good repeatability of the test runs. It
ensures a reliable and consistent process.
Development activities normally executed in highlyvariable vehicle environment are carried out incontrolled engine test cell settings which significantly
improve the repeatability.
In summary, with an EIL system, developers cancomplete as much work as possible for engine control
development and performance evaluation in the engine
test cell environment, before having to perform at thevehicle level. Because of its numerous advantages, EIL
has become a powerful tool and is expected to be more
widely used in the near future.

This paper presents the effort of setting up such anenvironment. ADX simulation and control platform of
A&D Co. Ltd. is used in the system, serving as a modelbased dynamometer and acceleration pedal controllerthat includes vehicle and driver models to realize realtime simulation of an actual vehicle. A high power low
inertia permanent magnet AC dynamometer is used toload the engine. Application results of simulating a 10-15
mode driving cycle are given.
The paper is organized into four parts. Section I gives an
overview of the design and configuration of the EIL
system. System hardware including ADX controller is
described. Section II provides detailed description of thevehicle and driver models, and the dynamometer control
and acceleration pedal control. An application example
of using the system to simulate a 10-15 mode driving
cycle is presented in Section III. The last section
summarizes the paper.

SYSTEM OVERVIEW
Figure 2 shows the overall structure of the EIL system.
The engine used in this setup is a 2.4 liter inline 4cylinder gasoline engine. It has electronic throttle control
system ― the acceleration pedal position signal is readby the Engine Control Unit (ECU), and the desired
throttle opening is consequently determined and set.
The engine is coupled to a 265 KW AC dynamometer
which uses a synchronous motor with permanent
magnet rotor. The dynamometer has a constantmotoring and absorbing torque of 506 Nm to 5000 rpm.
2
It has a very low moment of inertia of 0.128 Kg-m ,which makes it highly responsive and especially suitable

for transient testing. The low moment of inertia also
makes its impact on the engine perceived load minimal.
Vehicle and driver models, as well as dynamometer andacceleration pedal control algorithms are executed inreal time on the ADX controller. The ADX reads in the
speed and torque feedback information, and sends out
speed or torque setpoint command, which is the result of
the driver and vehicle models, to the dynamometer drive
through Profibus and consequently controls theoperation of the dynamometer. The ADX also sends out
acceleration pedal control command to an actuator tocontrol the operation of the pedal. It can be seen that byintegrating the virtual system (which includes the drivermodel, the vehicle model and the control algorithms for
dynamometer and acceleration pedal) with the physicalhardware (which includes the engine and ECU, speed
and torque sensors, dynamometer and drive, andacceleration pedal actuator), the created EIL system
makes the dynamometer emulate a vehicle to theconnected engine.
The ADX high-speed system controller, which runs thesimulation models and controls the dynamometer andacceleration pedal is the central part of the EIL system.
Figure 3 shows the hardware framework of thiscontroller. It has a dual CPU architecture, using an Intel
PentiumM processor for high-speed simulation andcontrol, and a Renesas SH4 processor for running thehuman-machine interface, including color touch-screen
LCD, function keys, and Ethernet communication withthe host PC. A bus controller on the active back plane
handles the data transfer between the interface boards
and the CPUs. Various function boards can be selected
and integrated in the controller to realize the required

Figure 2. Overall Structure of the EIL System

functions. For the EIL application, analog input andoutput function boards are integrated in the ADX
controller for acceleration pedal control. An encoder
board is used for the dynamometer speed and torquefeedback. Communication between the controller andthe dynamometer drive is fulfilled through a Profibus
board.

Simulation
Processor
Communication Renesas SH-4
Processor
200 MHz

Figure 3. Hardware Architecture of the ADX
Real-time Controller
The ADX sends out control commands to the
dynamometer drive and pedal actuator at a rate of
1000Hz. Vehicle and driver models, as well as
dynamometer and acceleration pedal control algorithms
aredeveloped
using
MATHWORKS
products
MATLAB®/Simulink®/Stateflow® in the form of model
block diagrams on the host PC. The S-functions for

system hardware and function modules are developedand integrated in the block diagram. Real-TimeWorkshop® converts the block diagram into C code,
which is then compiled, linked, and downloaded
automatically to the ADX hardware for real-time
execution under the RT-Linux operating system.
VirtualConsole software provides the graphical userinterface to the controller enabling the arrangement ofvarious screen elements on the host PC and on thecolor touch-screen LCD. These screen elements areassociated with the variables or parameters of the
Simulink® model, enabling real-time parameter setting
and signal monitoring.

SIMULATION MODELS AND CONTROLSEIL simulation of vehicles equipped with automatictransmission (AT) and manual transmission (MT) isdifferent in both the vehicle and driver models. For
brevity, this paper only discuss the AT scenario. Figure 4
shows the structure of the virtual system and therelationship among its components. For a given driving
cycle, the driver model recognizes the difference
between the targeted and calculated vehicle speeds andsends out the target acceleration pedal position value or
brake command accordingly. The acceleration pedal
control algorithm will subsequently control the action of
the acceleration pedal actuator based on the target
position value and the position feedback value. The
brake command is a virtual command which is sent tothe vehicle model, rather than any physical hardware.

Figure 4. Simulation and Control Model StructureAs to controlling the dynamometer to emulate the engine
load, based on different approaches in establishing theconnection causality between the physical portion andthe virtual portion of the system, two types of simulationand control implementation can be chosen for realizing
the setup. The first implementation uses torque control
mode of the dynamometer, with which the engine load
torque is commanded by the vehicle model, while theengine speed is the result of the torque imbalance
between the engine and the dynamometer (Figure 4(a)).
An alternative implementation is configured to use thespeed control mode of the dynamometer such that thevehicle model commands the dynamometer speed while
the engine torque is measured through the
dynamometer (Figure 4(b)). Roughly speaking, the first
implementation involves higher order control comparedwith the second and is more challenging [5, 8]. In thispaper the first implementation is adopted. For thisapproach, the engine will generate a specific amount of
torque under the engine speed and throttle opening. The
engine speed information is read by the vehicle model
which calculates the updated vehicle speed. The model
also calculates and sends out a dynamometer torquecommand to the drive to control the operation of the
dynamometer.
More details of the driver and vehicle models, which are
the most important parts in the EIL system integration,
are as follows. A driver model should reflect the humancontrol behavior, which can be very complicated if suchfactors as response time delay, cognition, preview,
adaptive control and learning etc. are all considered [14].
However, since the main focus is vehicle longitudinal
dynamics when simulating a vehicle to follow a specificdriving cycle, the driver model adopted is very much
simplified and only partially mimics human driver control
behavior.
Figure 5 shows the longitudinal driver model used forthis implementation, which allows the simulated vehicle
speed to follow a prescribed schedule. The major
function of the model is to calculate the target
acceleration pedal position value and brake command
value based on the difference between the driving cycle
to be realized and the simulated vehicle speed from thevehicle model. A feed-forward algorithm is included in
the model which gives a base acceleration pedal
position value based on the driving cycle. This feed-

forward mechanism basically reflects the driver’s
understanding of the engine and the vehicle., i.e., for the
combination of the engine and the simulated vehicle
system, to realize the target speed set by the driving
cycle, how much the acceleration pedal needs to bepressed. This base acceleration pedal position value issubsequently adjusted by a PID control algorithm withpreview action that uses the information of the target
speed profile and the simulated vehicle speed. The
resultant value might be positive or negative, indicating
whether controlling the acceleration pedal alone issufficient to realize the speed target, or braking need beapplied. Finally the value will be processed by someacceleration/braking logic and a target acceleration
pedal position value and a brake command value will beobtained and sent to the vehicle model.
The basic function of a vehicle model is to calculate thesimulated vehicle speed and the dynamometer setpoint,either target torque value, or target speed value.
Complexity and fidelity of the vehicle model can vary
greatly in different application scenarios. Per [15], avehicle model should be “simultaneously accurateenough to capture key powertrain transients and fastenough to run in real time”. Since a major purpose of theEIL system is to develop engine control and evaluate
engine and vehicle performance in transient operating
mode, the vehicle model should be complex enough toreflect the driveline and vehicle dynamics. Because of
the powerful calculation capability and abundantresources, the ADX controller can run very complicatedvehicle models in real time, such as Mechanical®
Simulation Corporation’s Carsim . For this study, vehicle
model which is very much simplified but still fulfills therequirement of effectively reflecting vehicle longitudinal
dynamics is developed and used.
Figure 6 shows the vehicle model, which consists of
torque converter, automatic transmission, shafts anddifferential, tire and road, and vehicle body etc. Since
torque mode is used for dynamometer control, thetorque converter model has target dynamometer torqueas output, which further dictates that it uses transmission
torque as input, measured engine speed as input, andoutputs transmission speed as an input for thetransmission model. Input and output relationships of thesubsystems following the torque converter are as welldetermined. Each subsystem is briefly discussed below.

Figure 5. Driver ModelFigure 6. Vehicle ModelTORQUE CONVERTER - A quasi-steady state model isused for the torque converter. The inputs to the model
are the measured engine speed (impeller speed) andtransmission input shaft torque. A capacity factor is usedwhich is a function of the speed ratio between thetransmission input shaft speed (turbine speed) and theengine speed:ω
K C = fC ( t )ωewhere ωt(1)

is transmission input shaft speed,ωeTe = (

KC

)2

is

(2)

Torque multiplication ratio is also obtained as a functionof the speed ratio:

KT = fT (

ωt
)
ωe

(3)

Turbine torque is obtained by multiplying the engine load
torque with the torque multiplication ratio:
TT = KT Te(4)
The transmission input shaft speed is calculated using
the relationship among the turbine torque, transmission
input shaft torque, and the turbine moment of inertia:

TT − Tti = J T (

dωt
)
dt

Tto = η gTti Rg(7)

where ω s is transmission output shaft speed, which isalso speed of the drive shaft connected to it. Rg is theengine speed. Load torque on the engine is calculatedusing the capacity factor and engine speed:ωeUsually speed reduction is calculated considering gear
ratio only, while the torque multiplication also takes into
consideration the efficiency factors:(6)ω s = ω t / Rg

(5)

where Tti is the transmission input shaft torque, J T is
the turbine moment of inertia.
AUTOMATIC TRANSMISSION - An automatictransmission model basically takes care of the shift logic,
gear ratio, speed reduction, torque multiplication, andtransfer efficiency etc. Shift logic is established based onsuch input information as vehicle speed and acceleration
pedal position etc. After the gear position is determined
and the gear ratio value obtained, the speed reduction
and torque multiplication are calculated subsequently.

gear ratio, Tto is the transmission output shaft torque,η g is the efficiency factor, which is a function of the gear
ratio etc. Effect of moment of inertia of the gear sets is
integrated in the model:

Tto − Tsi = J t (

dω s
)
dt

(8)

where Tsi is the drive shaft input torque, J t is thetransmission moment of inertia reflected at its output
side.
SHAFTS AND DIFFERENTIAL - Similar to thetransmission model, the shafts and differential modeltakes care of speed reduction and torque multiplication,
as well as transfer efficiency. Such influences as
moment of inertias etc. are integrated in the model. For
this implementation only the vehicle longitudinal
dynamics is considered and there is no difference
between the left and right driving wheels.
ωw = ωs / Rd
(9)

Tso = η sTsi Rd(10)where ω w is the wheel speed, Rd is the final drive gear
ratio, Tso is the output torque at the wheel end, η s is theefficiency factor. Effect of moment of inertia of the shafts
and differential components is integrated in the model:

Tso − Tw = J s (

dω w
)
dt

(11)

where Tw is the wheel torque, J s is the shafts anddifferential moment of inertia reflected at its wheel side.
TIRE AND ROAD - The tire and road model mainly
takes care of the longitudinal force (driving or braking)between the tire and road interface which eventually
determines the behavior of the vehicle acceleration,
deceleration, and speed. The longitudinal force iscalculated based on the wheel slip. It is restricted by thetire normal force and the friction coefficient between thetire and road interface:(12)
Fx = f X ( s, Fy )where s is wheel slip, Fy is the tire vertical load force.
The wheel slip is defined by:s=

Rrωw − VV(13)

where Rr is the rolling radius of tire, V is vehicle
longitudinal speed.
The brake command from the driver model, and also
such factors as whether the vehicle is equipped with anantilock braking system (ABS) and traction control
system (TCS) etc. need be taken into consideration formodeling the switching between the driving and braking
actions. Dynamics of the tire is integrated in the modelas:Tw − TB − Tr − Fx Rr = J w (

dω w
)
dt

(14)

where TB is the braking torque on the wheel, Tr is therolling resistance moment, J w is the moment of inertiaof the wheel and tire.
VEHICLE BODY - The vehicle body model includes
such components as road grade effect and aerodynamic
drag etc. It can be as simple as a point mass model, oras complex as a detailed multi-body dynamics model.
The simplified model adopted for the implementation is:

dV
(15)
)
dt
where m is vehicle mass, Fs is the slope resistanceFx − Fs − Fa = m(defined by:

Fs = mg sin θ(16)with θ to be the slope angle. Fa is air resistance:

1(17)
Fa = Cd ρV 2 A
2where Cd is the air drag coefficient, ρ is air density,
A is the vehicle frontal projection area.
Above are the vehicle subsystem models. In short, thedegree of complexity of a vehicle model might vary
greatly. Proper modeling of a vehicle should satisfy the
purpose of the EIL settings and meanwhile fulfill the realtime requirement.

Finally, the acceleration pedal control and dynamometer
control are briefly discussed. After the target values forthe acceleration pedal position and dynamometer torqueare obtained from the driver and vehicle models, PID
controls are implemented using the measured
acceleration pedal position and measured dynamometer
torque values for feedback. Necessary filtering of themeasured signals and tuning of control gains need to be
performed. Setting of proper model parameters that
represent the vehicle and driveline characteristics is
critical for good simulation results. Validation of the EIL
vehicle simulation needs to be performed by comparing
the simulation results against the test data collected onreal vehicle during chassis dynamometer testing or roadtesting.

APPLICATION EXAMPLEThe EIL setup can be a very powerful tool in powertrain
control development, function verification, calibrationand validation, especially for emission evaluation intransient operating mode. Detailed usage of the systemin these areas will be covered by separate papers. Herethe application results of simulating a Japanese 10-15
mode test cycle are given, which serve as a verificationof the system performance in simulating vehicle
dynamics.
The 10-15 mode emission test cycle is currently used inJapan for emission certification and fuel economy
evaluation for light duty vehicles. The entire cycle
includes a sequence of warm-up, idle, and multiple 10mode and 15-mode segments. Emissions are measured
over the final duration which consists of three 10-mode
and one 15-mode segments. In this application apassenger car with a curb weight of 1400 kg andequipped with a 5 speed automatic transmission issimulated. For brevity, the following figures only show
the results of the time duration approaching the end of
the test cycle, which includes one 10-mode segment andone 15-mode segment. Figure 7 shows the driving cycle
speed (target) and the simulated vehicle speed. It is
obvious the simulated vehicle speed follows the target
very well. Figure 8 demonstrates the commanded andmeasured dynamometer torque, which serves as theengine load torque. It can be seen both motoring andabsorbing modes are incurred during the process,reflecting the interaction between the engine and thedriveline in transient operations. Figure 9 shows theengine speed and the automatic transmission gear
position in the simulation process. In Figure 10 theacceleration pedal control behavior and the brakecommand are shown. It is clear the acceleration pedal
follows its commanded position well and the accelerationcommand and brake command are in coordination.
The application example indicates the EIL setup fulfills
the design requirement of reflecting the vehicle
dynamics in real time and can be used for powertrain
control development in transient operating mode.

80

Target Speed
Simulated Speed

60

Vehicle Speed (km/h)

Acceleration Pedal
Position (%)

40

70

50
40

Commanded Acceleration Pedal Position
Measured Acceleration Pedal Position

30
20
10
0

0

50

100

150

200

250

300

350

400

350

400

30

10
0
0

50

Figure 7.

100

150

200
Time (Sec)

250

300

350

400

Brake Command (%)

15

20

Brake Command
10

5

0

Target and Simulated Vehicle Speed

0

50

100

150

200
Time (Sec)

250

300

Figure 10. Acceleration Pedal Control and Brake
Command250
Measured Dynamometer TorqueCommanded Dynamometer Torque200

CONCLUSION
Torque (Nm)

150

100

50

0

-50

0

50

100

150

200
250
Time (Sec)

300

350

400

4000
Engine Speed

3000
2000
1000
0

Gear Position

Engine Speed (rpm)Figure 8. Commanded and Measured Dynamometer
Torque

0

50

100

6
5
4

150

200

250

300

350

400

200
250
Time (Sec)

300

350

400

Gear Position

3
2
1
0

0

50

100

150

Figure 9. Engine Speed and AutomaticTransmission Gear Position

HIL simulation has become an indispensable method in
automotive system development. As a system level
verification, calibration and validation tool, EIL vehicle
simulation couples physical engine to virtual vehicle anddriver models through a high power, low inertia engine
dynamometer in the engine test cell environment. Sucha setup has many advantages including repeatability
and flexibility, especially for transient operating mode
study. Development of such a system centered on ADX
high-speed system controller is described. Driver andvehicle simulation models are developed and executedin real time on the controller. A highly responsive
permanent magnet AC engine dynamometer and avehicle acceleration pedal are controlled such that the
dynamometer loads the connected engine as a realvehicle does and the simulated vehicle speed trace
follows the targeted driving cycle. An application
example of simulating a 10-15 mode driving cycle
indicates the EIL setup fulfills the design requirement ofreflecting the vehicle dynamics in real time and can beused for powertrain control development in transient
operating mode. Future work includes development andintegration of more comprehensive and higher fidelity
vehicle and driver models to obtain simulation resultsthat demonstrate more detailed information of vehicle
dynamics effects. Advanced application of the system inpowertrain control development, transient operation
calibration and validation, and engine and vehicle
emission performance evaluation etc. will be reported infuture papers.

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CONTACT
Dr. Shugang Jiang
Technical Specialist
A&D Technology Inc.
4622 Runway Blvd., Ann Arbor, MI 48108 USA
Email: sjiang@aanddtech.com