Automotive Systems

Control Engineering Practice 11 (2003) 179190

Modelling and simulation for mechatronic design inautomotive systems

T. Bertram, F. Bekes, R. Greul, O. Hanke, C. Ha, J. Hilgert, M. Hiller*, O. .Ottgen,P. Opgen-Rhein, M. Torlo, D. Ward

Faculty of Engineering Sciences, Gerhard Mercator University of Duisburg, Institute for Mechatronics and System Dynamics,

Mechatronics Laboratory, Lotharstr. 1, D-47057 Duisburg, Germany

Received 19 October 2001; accepted 17 January 2002

Abstract

This paper gives an overview of current industry based projects in the eld of vehicle modelling and simulation for the

mechatronic design of automotive systems. It shows the wide range of applications for analysis and synthesis during the

development process, including vehicle systems, vehicle dynamics, occupant safety, adaptive cruise control, hardware-in-the-loop

and fault tolerant real-time systems. r 2003 Elsevier Science Ltd. All rights reserved.

Keywords: Modelling; Simulation; Control of multibody kinematics and dynamics; Active and passive safety in automotive systems

1. Introduction

Something historic is happening in the automobilebusiness. It will affect the transportation world in thesame way that the invention of the internal combustionengine affected personal transportation. The process ishappening overnight and is inuencing the wholeindustry. It involves an entirely new automobile devel-opment and manufacturing process, and requires afundamental shift in thinking. From thinking of thecar as a mechanical device that carries some electroniccontrols to thinking of the car as a mechatronic device(Fig. 1). This means a device where the mechanical,electrical, and software parts are fully integrated(Dickinson, 1996; DesJardin, 1996).The main driving forces for this shift in thinking are the

expectations of the consumer. Consumers already expectthe same things from their automobiles as they do fromtheir other consumer electronics products. They expectsafety, security, reliability, ease of operation, comfort,entertainment, and value for money. Furthermore theyexpect what they can get elsewhere, for example, in their

home or in their ofce, to be available in theirautomobiles. The automobile in the mind of the youngergeneration is no more than a powerful computer. It isimportant to keep in perspective the fact that auto-mobiles are primarily mechanical products with me-chanical functionality. Electrical assemblies and theembedded software are only enabling technologies, andnot the critical vehicle functions themselves. However,sophisticated functions such as engine management,traction control, and active vehicle dynamics can only beimplemented today by the judicious combination ofmechatronic technologies.Among the various current developments in the

electronics eld, the trend towards networking existingand newly developed systems is playing a prominentrole. While linking control systems for active safety hasalready been employed for some years, the next step inthis evolution is the integration of systems, aimed at theusers wish for increased safety, improved securitysystems, reduced power consumption, responsible eco-logical friendliness, comfort, and growing multimediacapabilities. Thus, electronic systems that were up untilnow essentially autonomous are now growing together.This process is mainly driven by demand for improvedfunctionality and the need to limit costs. Extendedsystem interaction helps to make more intelligent use ofwhat is already installed and can even simplify present

*Corresponding author. Tel.: +49-203-379-2199; fax: +49-203-379-

4143.

E-mail address: [email protected] (M. Hiller).

0967-0661/03/$ - see front matter r 2003 Elsevier Science Ltd. All rights reserved.

PII: S 0 9 6 7 - 0 6 6 1 ( 0 2 ) 0 0 0 7 6 - X

installations. The traditional example of interaction inthe area of active safety is the link between the tractioncontrol and engine management systems for torquecontrol.The engineering of such a new, interconnected system

poses great challengesin particular for guarantying itsreliability, safety, and acceptance by the car user. Thenetwork has to be set up systematically to achieveadvantages going beyond the sum of the components,and to avoid mutual disturbance. On top of that, eachnetwork component must be able to work in a widevariety of congurations where varying contributionsfrom different sources come together. Therefore, thecomplete network must be scalable from a low level offunctionality and cost, via numerous customer-orientedvariants, up to the future state-of-the-art in automotiveelectronics. To deal with these challenges, and the longand complex supply chain associated with them, theautomotive industry has been converging on develop-ment processes where systematic modelling and simula-tion play a major role.This contribution is divided into nine main sec-

tions. Section 2 briey describes modelling vehicles inFasim C++, and how they are modelled as mecha-tronic systems, incorporating multibody kinematics anddynamics, hydraulics, controllers, sensors, data manage-ment systems, and environmental conditions. Fasim C++is the multibody vehicle simulation package used (anddeveloped) in the Mechatronics Laboratory at theUniversity of Duisburg (Hiller, Schuster, & Adamski,1997). The next six sections illustrate application ofcomplex vehicle dynamics simulation control (Section3), rollover simulation (Section 4), crosswind compensa-tion (Section 5), dynamic headlamp levelling control(Section 6), semi-autonomous driving (Section 7) andhardware-in-the-loop simulation with the complexvehicle model (Section 8) and makes some remarks withregard to the fault tolerant integration of a decoupledcontrol system into the vehicle. Section 9 presents someconclusions.

2. Vehicle dynamics

Development of vehicle controllers requires anappropriate model of the vehicle dynamics built into aversatile simulation environment. This simulation en-vironment has to be able to simulate different vehicletypes or models without any recompilation. The vehiclemodel has to have a modular form so that singlecomponent of the vehicle may be exchanged, dependingon the simulation task. Thus, models of the vehicledynamics with differing levels of complexity can bedened covering correspondent physical effects with thedesired accuracy. The modular structure of a vehiclemodel in Fasim C++ is shown in Fig. 2 using theexample of a passenger car.The structure presented does not show the construc-

tion details of the modules, e.g. which kind of frontsuspension is used. During initialization this is notimportant, because the required information for gen-erating the equations of motion is part of the modulesand only at the beginning of simulation is it evaluated.The topology of the vehicle, which describes thekinematic topology of the individual modules, is shownin Fig. 3. For reasons of clarity the modules enginehydraulics (braking system), driver and environment arenot shown. Using this modelling technique it is possibleto decide during runtime which conguration of a

Fig. 1. The automobile as a mechatronic device.

Car Body / Chassis

Front Suspension

Rear Suspension

Driver

wheel wheel

wheelwheel

Engine

Drive Train Hydraulics

Fig. 2. Modular structure of a passenger car in Fasim C++.

T. Bertram et al. / Control Engineering Practice 11 (2003) 179190180

vehicle is used without any recompilation of theprogram.Fasim C++ contains a large library of different

vehicle modules such as suspensions, tire models, drivetrains, engines, engine mounts, controllers, sensors,elasticities, a rigid or exible car body, several hydraulicbraking systems, a driver and an environment model.The structure of the modules makes it easy to expandthe library by adding new modules. The equations ofmotion are based on DAlemberts principle:

XnB

i1

mi.rSi Fi drSi

HSi xi xi HSixi TSi d/i 0; 1

where nB is the number of mass-endowed bodies, mi; HSiare the mass and inertia tensor of body i, .rSi theacceleration of c.o.g., Fi;TSi the applied force andtorque, and drSi ; dui are the virtual linear and angulardisplacement.Due to the constraints in the system, the virtual

displacements are not independent. To generate theequations of motion in minimal coordinates the choiceof f independent generalized coordinates q1; q2;y; qf ; isnecessary, corresponding to the number of degrees offreedom in the system. The equations of motion of themechanical system in minimal coordinates can then bewritten as:

Mq.q bq; q Qq; q; t; 2

where M is the generalized mass matrix, b the general-ized gyroscopic forces, q the generalized coordinates,and Q the generalized applied forces.Applying the principle of kinematic differentials, the

elements of the equations of motion are calculatedexpressing partial derivatives using kinematic terms.Due to the modular structure of the matrices andvectors, their elements can easily be calculated from thecorresponding modules. For this reason they aresubdivided into an inner sum, inside the module lconsidering all its bodies nB and in an outer sumconsidering all modules nM :

Mj; k XnM

l1

X

iAIl

mi#rji #r

ki #x

ji Hi #x

ki ;

bj XnM

l1

X

iAIl

mi#rji #.ri #x

ji Hi #xi xi Hixi;

Qj XnM

l1

X

iAIl

#rji Fi #x

ji Ti: 3

The pseudo velocities #rji ; #x

ji and pseudo accelera-

tions #.ri; #xi are dened as follows (Hiller & Kecske-m!ethy, 1989):

#rji

qriqqj

; #.ri Xf

j1

Xf

k1

q2riqqj qqk

qj qk;

#oji qoiq qj

; #oi Xf

j1

qJoiqqj

q qj ; Joi qoiqq

: 4

3. Control of vehicle dynamics

Numerous reforms have taken place in the sector ofelectronic control systems since their introduction in theeighties. The eld of active safety devices reaches fromthe classic antilock braking system (ABS) to complexvehicle dynamic controllers such as electronic stabilityprogram (ESP). The objective of vehicle control systemsis support in situations of non-linear and coupledoperations, which are difcult to handle for the driver.By means of interference in the acceleration, steeringand braking processes it is possible to maintain stabilityand control (Fig. 4).Simulation is an important tool for the design and

optimization of controllers. Due to its high adaptabilityFasim C++ ensures through its modular structurethe efcient realization and optimization of vehiclemodels. Interfaces on the basis of TCP/IP, CORBA andActiveX permit the integration of complex controlmodels, implemented in controller developmentsoftware such as Matlab/Simulink (as shown inFig. 5).

Fig. 3. Kinematic topology.

T. Bertram et al. / Control Engineering Practice 11 (2003) 179190 181

With the aid of the vehicles state variables

(a) wheel velocities,(b) lateral acceleration and(c) yaw angle

and the driver inputs

1. steering wheel angle,2. throttle opening and3. brake position

the brake booster or individual brake actuators can betriggered under the terms of the control strategy. InFig. 6 the simulation results of steering interference areshown. This open loop manoeuvre claries the possibi-lities of active chassis components.For this reason comprehensive examination of the

complete system is carried out to allow the implementa-tion of concepts with regard to the priorities of thecomponents.Validation of the simulation results can be obtained

by use of hardware-in-the-loop test benches as well asdriving trials.

4. Rollover simulation

An industrial application of Fasim C++ lies in theeld of passive vehicle safety. Featuring front airbags,side airbags, seat belt pretensioners and load limiters,existing restraint systems provide a high level ofprotection. Additionally so now that knee and headprotecting side airbags are starting to come onto themarket. For the activation of these protective devices,comprehensive sensor systems are required which canreact with the appropriate deployment of restraintsystems, taking into account any relevant accidentparameter. For this reason future sensor concepts mustsupply information about vehicle stability, approachingobstacles, vehicle interior conditions, accident type andcrash severity (Gr .osch et al., 1996).Computer simulation plays an important role in the

development of a rollover detection system (Hiller &Bardini, 1998). Vehicle dynamics simulation, for exam-ple, provides the possibility to test in advance varioussensors and algorithms for rollover detection. Further-more, occupant simulation can be used to establishtrigger times for rollover detection. For occupantsimulation the commercial simulation toolset MADY-MO (Lupker, 1996) is used. Fasim C++ and Madymohave been combined to form an application anddevelopment environment for the rollover detectionsystem from Robert Bosch GmbH (Mehler, Mattes,Henne, Lang, & Wottreng, 1998). Some special en-hancements have been made in Fasim C++ for con-ducting rollover simulations. Firstly the sensor,including the rollover detection algorithm, was imple-mented. Thus it was now possible to analyse thetriggering behaviour in any simulated manoeuvre.Furthermore, it was necessary to enhance the modellingof the environment. For the simulation of embankmentand ramp manoeuvres it is now possible to conguresurfaces such as those shown in Fig. 7.The simulation of an embankment rollover is used

here to illustrate the application of these modellingFig. 4. Effect of ESP.

Fig. 5. Control interface in Fasim C++.


techniques to the analysis of real world vehicleproblems. As leaving the road is statistically the mostlikely cause of a rollover situation, it is very importantthat this manoeuvre is detected by a rollover protectivesystem.Therefore, a full-scale rollover test with a middle class

car has been investigated in detail. As shown in Fig. 8,very good correlation between the simulation and thereal experiment has been achieved. Only when the carbody hits the ground does the simulation yield incorrectresults, as the contact interactions between the exteriorof the vehicle and the environment have not beenmodelled. Since this phase of the rollover is no longer ofimportance for rollover detection these errors have beenneglected. When the car body hits the ground rolloverdetection must have taken place long ago. The sensormodule that has been implemented in the vehicle is fed

with longitudinal and lateral acceleration and angularvelocity data during simulation by the chassis module,and returns the trigger signal for controlling the rolloverprotective devices. The instant of rollover detection isvisualized using a cone which has been added to theanimation and which appears above the vehicle bonnet(hood) when the sensor triggers (Fig. 8). With thevalidated model it is possible to perform parameterstudies in order to optimize the rollover sensing concept,and to establish trigger times for rollover protectivedevices such as seat belt pretensioners and windowairbags.As a second example the application of the vehicle

dynamics simulation software for the behaviour whendriving over a ramp is chosen. Typical ramps in realityare the beginning of crash barriers or amassments ofsoil. Fig. 9 shows exemplary a comparison of a middleclass vehicle driving with a velocity of v 20m/s one-sided over a ramp with a height of h 0:7m. For theparameters roll angle and roll rate good approx-imation of the real behaviour can be achieved.

5. Crosswind compensation

Automobiles react to crosswinds with reduced direc-tional stability and a change in their yaw motion. Inparticular sport utility vehicles (SUV), whose marketshare rose around 30% in 1999, are affected by thisproblem. With the help of Fasim C++ the dynamic

0 10 20 30 40 50 60 70 800

10

20

30

40

50

60

70

Interference of steering controller

with steering controller

without steering controller

X-coordinate [m]

Y-co

ordi

nate

[m]

vehicle (position and orientation)

v = 35 m/s = 0.1 radx

f

Fig. 6. Simulation results of active chassis management.

b X

Y

Z

=0.45

Street

h

B

H

Ramp

Embankment 2

Embankment 1

=0.8

Fig. 7. Example of surface contours used for rollover simulation.


behaviour of the vehicles under crosswind conditionscan be analysed.While driving, there is a component of the wind in x-

direction vDW due to the forward motion of the vehicleand a component of the wind in lateral direction, thecrosswind vCW : The addition of these wind vectors givesthe resulting wind velocity vr; which has an angle ofapproach t with respect to the vehicle. With asymmetrical airow over the vehicle (t 0) there is aresisting force (aerodynamic drag) Fx in the x-directionand a lifting force (aerodynamic lift) Fz in the z-direction. An asymmetrical airow over the vehicle(ta0) results in an additional lateral force Fy on thevehicle, a roll moment Mx and a yaw moment Mz: Theforces and torques due to airow over the vehicle can beseen in Fig. 10.A manoeuvre with the sudden appearance of cross-

wind on the highway is chosen. It is comparable todriving over a bridge or past a gap in the wind walls.The vehicle travels with a velocity of 160 km/h (open-loop manoeuvre). After 10m a crosswind springs upfrom the right-hand side, and acts on the vehicle for20m with a velocity vCW 100 km/h, which describes a

wind gust that can occur in Germany in autumn orwinter (Hucho, 1998). Fig. 11 displays this manoeuvregraphically.The resulting forces cause the car to alter its direction

and yaw to the left. For a typical lane width of 3.75mand a vehicle track width of approximately 1.55m, only1.1m is left on both sides of the vehicle before reachingthe edge of the lane. This is often bordered withkerbstones or crash barriers, or the vehicle could beput into the path of other road users.A controller has been systematically designed to

reduce the lateral offset of the vehicle. The controlconcept uses the lateral acceleration ay and the yaw ratec of the vehicle as inputs for a system that combines twoPI-controllers. These parameters are chosen since theyare already used in the ESP system, and are relativelyeasy to access. The output value of this combinedcontroller, the steering angle dL; is the sum of theoutputs of the two controllers.The comparison of the simulation results (with and

without crosswind compensation) can be seen in Fig. 12.The drivers reaction time (between 0.3 and 1.7 s, Bosch,1993) depends on age, tiredness and driving experience,

Fig. 8. Embankment test.

Fig. 9. Validation resultsRamp manoeuvre.


but 1 s after entering the crosswind area the vehiclewithout the controller has already reached the peripheryof the lane. The improvement in the vehicles behaviourobtained using the controller, in the form of a reduction

in the lateral offset, is obvious. With the controllerimplemented in the vehicle, the driver has more time toreact and avoid a potential accident by applying a smallsteering correction.

6. Dynamic headlamp levelling control

The approach dynamic headlamp levelling systemdeals with the control of the angle of vehicle headlamps.To guarantee safe driving in the dark as well, theheadlamp must maximize the illuminated area in frontof the car under every given condition. Along with theintroduction of xenon headlamps that produce a muchhigher light intensity than conventional halogen head-lamps, the development of the dynamic headlamplevelling system (HLS) has become more and moreimportant.Vehicles that are not equipped with a dynamic HLS

will dazzle oncoming trafc while accelerating and willhave a smaller illuminated eld, so that the drivers eldof vision is reduced, while braking. These effects can beseen in Fig. 13.The dynamic HLS regulates the motion of the

headlamps relative to the vehicle motion so that therange is maintained and oncoming trafc is not dazzled(Fig. 14). To control the headlights it is necessary toknow the dynamic pitch angle of the vehicle. Thisrepresents the disturbance variable. But the pitch angleis difcult to measure. One possibility is to work withinductive angle sensors (Thiemann, Stryschik, & Ho-bein, 1998) that measure the vertical distance betweenthe car body and the wheel carrier at the front and at theback axle, and to calculate the pitch angle over thedifference between these two distances and the wheel-base. This method detects the pitch angle reliably, but it

Fig. 10. Forces and torques due to airow over a vehicle.

yx

10 m 20 m

v = 100 km /hCW

v

1.1 m3.75 m

1.1 m

Fig. 11. Crosswind manoeuvre.

Fig. 12. Lateral offset with vDW 160km/h and vCW 100km/h,with and without control unit.


neglects the angle that results from tire deformation.Therefore, another possibility to calculate the pitchangle on the basis of an Luenberger observer wasinvestigated.The manoeuvre shown here represents acceleration

for a period of time, with subsequent braking. Fig. 15shows the change in velocity and acceleration withrespect to time for the manoeuvre, as well as the scaledaccelerator pedal position and the scaled brakingpressure.Fig. 16 shows the reference pitch angle curve calcu-

lated using Fasim C++ (Section 2). The pitch angle

decreases very strongly at the beginning of the accel-eration process. The gearshifts can be seen as spikes inthe curve. The pitch angle measurement method thatuses inductive angle sensors approximates the referenceangle very well. The deviations can be traced back to theneglected deformation of the tires. The pitch anglecalculated using the estimation method also approx-imates the reference angle very well. The curves are inthe area of the acceleration nearly congruent.The inuence of the spring and damper character-

istics, with differing compression and rebound values,on the dynamic behaviour of the pitch angle would beinteresting for further research. A more exact investiga-

Fig. 13. Vehicle without a dynamic HLS.

Fig. 14. Vehicle with a dynamic HLS.

Fig. 15. Characteristics of a simulated manoeuvre.

Fig. 16. Pitch angle calculated using the three different methods.


tion of both the stationary and the dynamic effects ofincorrect pitch angle detection on the whole dynamicHLS control loop should also be investigated.

7. Semi-autonomous driving

The road transport system (including automobiles,buses and trucks) has not yet made signicant use ofmodern electronic technologies to enhance systemoperations. However, the 21st century will makeincreasing demands on modern trafc and logisticstechnologies, especially in congested urban areas. Anintelligent transportation system (ITS) which contains awide range of systems that fully or partially take overthe tasks of driver by using intelligent systems built inthe vehicle, possibly in combination with control fromthe transport infrastructure (Fig. 17) is considered to bea promising development for the more efcient, reliable,safer and environmentally friendly use of the transportinfrastructure.Within the framework of this project, strategies and

concepts will be developed which enable the semi-autonomous driving of a vehicle as a part of an ITS.This semi-autonomous driving relates to the coordi-nated, autonomous, steering, acceleration and braking

of a vehicle in order to let it stably follow a given lane.The development of the vehicle controller will primarilyconcentrate on driving in small convoys or platoons.A necessary recommendation for the merging of vehiclesinto and out of the platoon is the development of amodel for the communication between the vehicle andthe platoon.Several mathematical tools and experiments will be

established, with the main emphasis on merging into andout of the platoon. In contrast to existing studies specialattention will be given to

* robustness of the merging process with regard tounexpected situations, disturbances, etc.,

* dynamic vehicle behaviour,* trajectory planning for emergency situations.

The trajectory planning is based on B!ezier-splines andcombined with a simplied vehicle model. Simulationsresults for an open-loop lane change manoeuvre ISO/TR 3888 can be seen in Fig. 18.The integration of this project into the project design

of an automated vehicle integrated control instrument(DAVINCI), a cooperative with the Delft University ofTechnology and the TNO Road-Vehicles ResearchInstitute, provides a vehicle model that includes acontroller for the semi-autonomous driving.

Fig. 17. ITS infrastructure and communications.


8. Hardware-in-the-loop real-time simulation

Real-time simulation is becoming more and moreimportant for testing of electronic control unit (ECU)software in complex mechatronic systems. Efcient andreliable test and release of ECU software for suchsystems cannot be achieved using expensive and timeconsuming in-vehicle testing only. Parallel applicationof in-vehicle tests, ofine simulation and real-timesimulation is essential for adequate software vericationwithin required cost and time frames (Fig. 19). In ourcase real-time simulation is used for testing safetysoftware in automotive ECUs. It continually checksinput and output signals for plausibility and consistency.A low cost real-time computer with comparatively lowcomputing power handles the complete I/O. It is basedon a VME bus system with a Motorola 68040 CPU, adedicated real-time operating system (OS9) and applica-tion specic I/O cards. In the real-time application theworkstation must be able to calculate one simulationstep Dt in less than or equal to real-time. In this case theworkstation is a DEC Alpha 600 5/333 workstation with333MHz clock speed. In order to model the dynamics ofthe mechanical subsystems of the vehicle with sufcientaccuracy integration steps of o1ms (and even as smallas 0.1ms for the hydraulic components) are required.A hardware-in-the-loop real-time simulation result of

a safety software test for the ESP is exemplary shown inFig. 20. The signals lateral acceleration, wheel speed andbaking pressure of the rear wheels are measured duringa braking in a turn manoeuvre. The real-time simulationis carried out with the same program as is used for the

ofine simulation. To ensure that the model is valid forthe complete range of operating conditions the modelhas been validated. This means that extensive in-vehiclemeasurements were performed and compared withsimulated data. For a rear wheel driven vehicle, thevehicle model consists of 41 rst-order differentialequations. In the ofine simulation models with up to70 rst order differential equations are available.Most innovations in the development of automotive

ECUs for modern cars are based on an iterative process.In this environment hardware-in-the-loop simulationoffers a wide range of function tests in the laboratoryunder close-to-real conditions. Furthermore, it ispossible to implement new algorithms and weight them

Fig. 18. Simulation results for lane change ISO/TR 3888.

Fig. 19. Hardware-in-the-loop concept.


correspondingly with very short development cycles.The function of an ECU can be examined often only inthe application environment with further controllersunder real-time conditions. Specically with drive-by-wire systems, which will increasingly replace themechanical and hydraulic systems in the car over thenext few years, it must be possible to guarantee at everytime that in the case of an error in one or morecomponents, safe stopping or control of the vehicleremains possible. Consequently, the complete systemmust have a fault tolerant design and have systems sothat individual controllers are able to diagnose an errorand to initiate the corresponding countermeasures. Inthis case, the communication between the individualmodules occurs via a bus system, which has an errorresistant, redundant design. If a serious disturbanceoccurs on the bus, the communications of all remainingparticipants must be able to be immediately transferredonto a backup system. In addition, the failed device(s)must be able to detach itself from the bus system.It must be checked continuously whether data

transmitted via the bus system is transmitted correctlyand is still valid during time-critical processes. Forexample, in the case of the brakes in a drive-by-wiresystem no delay in the resulting braking effect is allowedto occur because a defective ECU is disturbing thecommunications on the bus system. Consequently, everycommand has a limited, temporal validity in addition tothe recommendation that it is actually correct. Thecommunication of the individual components occurs ata tightly clocked frequency, which assigns a timewindow to every element in which communicatios mayoccur. One possible solution here is the time-triggered-protocol (TTP), which evaluates the temporal behaviourof the system components, as described, during each bus

cycle. A similar procedure is also used in the mobiledigital GSM communication systems (i.e. mobile cellu-lar telephones). The individual transmission channelstransmit the digital information in a time-multiplexedfashion in rmly assigned time slots.The ECUs in motor vehicles today are primarily

independent, and only transmit diagnostic functions orstatus information via a bus system to the outside world.To exclude a possible system failure through erroneouscommunications with the sensors and actuators, per-ipherals and controllers are often integrated into onecontrol unit (i.e. ABS and ESP). If a communicationsystem has the described features, the reuse of sensorsand actuators for functions of a similar type is alsoconceivable (Fig. 21). An ECU would consequently beable to be reduced to the actual micro controller and thecorresponding communication hardware. This wouldthen be similar to a distributed computer system where,in the case of the disturbance of single device, anotherundertakes its function, switching from a safetyirrelevant functions such as the air conditioning tocontrolling the brakes or some other important functionthat has failed.

9. Conclusions

This paper gives an overview of current industrybased projects in the eld of vehicle modelling andsimulation for the mechatronic design of automotivesystems. It shows the wide range of applications foranalysis and synthesis during the development process,including vehicle systems, vehicle dynamics, occupantsafety, semi-autonomous driving and hardware-in-the-loop and fault tolerant real-time systems.The object-oriented design of the simulation environ-

ment Fasim C++ allows easy adaptation of differentextensions of the vehicle model. On the one hand thisleads to a remarkable variety of the vehicles that can besimulated, while on the other hand, the extension of the

Fig. 21. Decoupled control system.

Fig. 20. Real-time simulation results.


modular vehicle model is easy to manage. Additionalmechanical or non-mechanical components (e.g. control-lers, sensors) can be easily appended. The vehicle modeldescribed has been implemented for the development of arollover protective system, vehicle dynamics controlsystems, and for hardware-in-the-loop simulation.

Acknowledgements

The work presented in this paper is supported byRobert Bosch GmbH, Stuttgart (Germany), Hella KGHueck & Co., Lippstadt (Germany) and Ford WerkeAG, Cologne (Germany).The project Semi-autonomous driving is supported

by the Ministry of Schools, Science and Research of thestate of Nordrhein-Westfalen (Germany).

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Modelling and simulation for mechatronic design in automotive systemsIntroductionVehicle dynamicsControl of vehicle dynamicsRollover simulationCrosswind compensationDynamic headlamp levelling controlSemi-autonomous drivingHardware-in-the-loop real-time simulationConclusionsAcknowledgementsReferences

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