In a co-simulation, subsystems are coupled via their in- and outputs to simulate
the overall system behaviour. The subsystems are modelled in their domain specfic
simulation tools. The task changes if one coupled subsystem represents a real-time system.
A real-time system which has to guarantees hard-real-time conditions influences the
co-simulation concept: now the co-simulation also has to fulfill hard-real-time conditions.
This type of co-simulation is called real-time co-simulation. The most important difference
to a non-real-time co-simulation is the time correct overall simulation speed with respect
to the involved real-time systems. To achieve this, all subsystems in form of non-real-time
systems have to be synchronised to the involved real-time systems. The focus of this work
lies on the problems that occur in a real-time co-simulation environment compared to a
classical one. A concept to handle the additional problems is outlined and tested on an
example real-time co-simulation

Benedikt, M.

Stettinger, G.

Thek, N.

Zehetner, J.

English

UPCommons. Portal del coneixement obert de la UPC

On the difficulties of real-time co-simulationV International Conference on Computational Methods for Coupled Problems in Science and EngineeringCOUPLED PROBLEMS 2013S. Idelsohn, M. Papadrakakis and B. Schrefler (Eds)ON THE DIFFICULITIES OF REAL-TIMECO-SIMULATIONG. STETTINGER∗, M. BENEDIKT†, N. THEK† AND J. ZEHETNER†∗Alpen-Adria Universität KlagenfurtInstitute of Smart System TechnologiesUniversitätsstrasse 65-67, 9020 Klagenfurt, Austriae-mail: georg.stettinger@aau.atweb page: http://www.uni-klu.ac.at/tewi/ict/sst/me/index.html†Virtual Vehicle Research CenterArea E - Electrics/Electronics and SoftwareInffeldgasse 21/A/2, 8010 Graz, Austriae-mail: martin.benedikt@v2c2.at, norbert.thek@v2c2.at, josef.zehetner@v2c2.atweb page: http://www.v2c2.atKey words: Co-Simulation, Real-Time, Extrapolation, Coupling Types, Dead-TimeAbstract. In a co-simulation, subsystems are coupled via their in- and outputs to sim-ulate the overall system behaviour. The subsystems are modelled in their domain specficsimulation tools. The task changes if one coupled subsystem represents a real-time sys-tem. A real-time system which has to guarantees hard-real-time conditions influences theco-simulation concept: now the co-simulation also has to fulfill hard-real-time conditions.This type of co-simulation is called real-time co-simulation. The most important differenceto a non-real-time co-simulation is the time correct overall simulation speed with respectto the involved real-time systems. To achieve this, all subsystems in form of non-real-timesystems have to be synchronised to the involved real-time systems. The focus of this worklies on the problems that occur in a real-time co-simulation environment compared to aclassical one. A concept to handle the additional problems is outlined and tested on anexample real-time co-simulation.1 INTRODUCTIONThe co-simulation concept is often used in a modern vehicle development process inthe field of the automotive industry [3, 5, 6]. Different subsystems are modelled in theirdomain specific simulation tools. To get an overall simulation result all subsystems haveto be combined via their specific in- and outputs. The correct coupling of these signals isthe main task of a so called co-simulation platform. The co-simulation concept has the big1989G. Stettinger, M. Benedikt, N. Thek and J. Zehetneradvantage that all subsystems can use their domain specific solvers and no adaptations inthe existing simulations are necessary [1]. Often the classical co-simulation concept is notenough to solve all occuring problems in the vehicle development process. One extensionis the integration of hard-real-time systems in the co-simulation. This is the case whenat least one modelled subsystem gets replaced by real hardware, e.g. HiL (Hardwarein the Loop) systems or test benches. In this case the co-simulation is called real-timeco-simulation and now the typical hard real-time conditions must hold during the sim-ulation [3, 8]. The main difference compared to a classical co-simulation is the correctcoupling with respect to the wall-clock-time. The involved real-time systems which fulfillthe hard-real-time conditions run with the so called wall-clock-time.The paper is organised as follows: Chapter 2 discusses the difficulties of a classicalco-simulation. Chapter 3 describes the additional problems occuring in a real-time co-simulation. Chapter 4 shortly illustrates the structure of a real-time co-simulation. Inchapter 5 an example real-time co-simulation is presented. The difficulties are shown andpossible approaches to solve these problems are outlined.The presented work is part of the ongoing research project ACoRTA (Advanced Co-Simulation Methods for Real-Time Applications1) at the Virtual Vehicle CompetenceCenter in Graz, Austria. All techniques to handle the real-time co-simulation problemare implemented in the ICOS Real-Time Framework (ICOS RT).2 DIFFICULITIES OF A CO-SIMULATIONTypically co-simulation problems are handled with the help of so called co-simulationplatforms, which offer specific interfacing capabilities of the simulation tools and performthe data exchange between involved subsystems. The main requirements of such classicalco-simulation problems are [7, 9, 10]:• Proper choice of the coupling time instants• Selection of an extrapolation method• Definition of the subsystem scheduling2.1 Choice of the coupling time instants (macro-time-step)To distinguish between the step sizes of domain specific numerical solvers of the in-volved subsystems and the step sizes between two coupling instants, the micro- (δT ) andmacro-time-steps (∆T ) are introduced (see Fig. 1). Every domain specific simulationtool typically has it’s own micro-time-step which doesn’t get influenced during the co-simulation. For a co-simulation only the macro-time-step has to be defined by the user.The involved subsystems get synchronised at every macro-time-step (which may be fixedor adaptive) [2, 4]. The coupling data exchange is done with the help of a co-simulation1http://acorta.info2990G. Stettinger, M. Benedikt, N. Thek and J. ZehetnerFigure 1: Micro- and macro-time-steps, polynomial extrapoltion techniques [9]platform (e.g. the ICOS2, Independent Co-Simulation Framework). The choice of themacro-time-step is very important for the quality of the overall simulation result becauseoften a trade-off between the overall simulation time and the desired accuracy of the sim-ulation results. In conclusion, smaller macro-time-steps lead to more accurate simulationresults but with the drawback of longer simulation times [7, 10].2.2 Signal-based extrapolation techniquesIn the case of two interdependent subsystems, which are connected via their in- andoutputs, at least one input has to be extrapolated to solve the coupled system [7]. Ina classical co-simulation typically polynomial extrapolation techniques of low order areused to solve this problem [4, 5]. Fig. 1 shows the most commonly used polynomialextrapolation techniques such as zero-order extrapolation (zero-order hold, ZOH), first-order extrapolation (first-order hold, FOH) and second-order extrapolation (second-orderhold, SOH). Due to the fact that every extrapolation technique is a prediction of the futurecoupling signal an error gets introduced [7]. This coupling error influences the overallsimulation result and thus, this error must be as small as possible. Another importantproblem is the introduction of dead-times due to the used polynomial extrapolation. Thisdead-times can lead to instability in closed loop systems. The introduced dead-timesmainly depend on the chosen macro-time-step (see Fig. 2) [7, 9].2.3 Simulation tool schedulingIn principle, there are two different ways of subsystem scheduling: parallel and se-quential. In the parallel case all inputs of the coupled subsystems has to be extrapolated2http://www.v2c2.at/icos3991G. Stettinger, M. Benedikt, N. Thek and J. Zehetner100 120 140 160 180 200 220 240 260 280 300202530354045Time [s]Coupling Signal [−] phase shift → ←coupling signalextrapolated signaldelayed signalFigure 2: Introduced dead-time due to ZOH-extrapolation [9]which lead to shorter simulation times, with the drawback of more extrapolation errors.Sequential scheduling requires less extrapolation effort with the the disadvantageous factof longer simulation times. Additionally the execution sequence influences the entiresystem behavior [6, 7].3 COMMENTS ON REAL-TIME CO-SIMULATIONFor real-time co-simulation basically the same problems as for classical non-real-timeco-simulation occur. One important aspect for a real-time co-simulation are hard real-timeconditions which have to be fullfilled during a real-time co-simulation which is responsiblefor the following problems [9]:1. Requirements for coupleable subsystems2. Synchronisation of the involved subsystems3. Handling of dead-times4. Extrapolation of noisy coupling signalsThese additional difficulties are discussed in detail in the following sections.3.1 Requirements for coupleable subsystemsTo fulfill the required hard-real-time conditions a time correct exchange of coupling datawith respect to the wall-clock-time is necessary. This is only possible if the involved non-real-time systems, which do not guarantee hard-real-time conditions, have a simulationtime which is faster than the wall-clock-time. Otherwise no synchronisation between theinvolved real-time and non-real-time systems is possible [9].3.2 Synchronisation of the involved subsystemsThe main task of the real-time co-simulation problem is the time correct exchange ofcoupling data with respect to the wall-clock-time. The synchronisation is typically realised4992G. Stettinger, M. Benedikt, N. Thek and J. Zehetnervia a slow down mechanism for the non-real-time systems. The simulation speed of thesesystems is faster than the wall-clock time and so these systems have to slow down untilboth system types run with the wall-clock time to perform a time correct synchronisation.So the involved non-real-time systems get paused to realise this slow down effect [9].3.3 Handling of dead-timesTo guarantee hard-real-time conditions a time correct coupling is mandatory as dis-cussed in 3.2. So the communication delays due to the communication medium betweencoupled systems play an important role. These dead-times influence the stability of theclosed loop system and can violate the hard-real-time conditions when the synchronisa-tion fails. The coupling mechanism between the coupled systems split the communciationdead-times into sending and receiving dead-times (see Fig. 3). To guarantee the requiredhard-real-time conditions an approximate compensation of the sending and receiving dead-times is required [9].Figure 3: Sending and receiving dead-time due to the data transfer [9]3.4 Extrapolation of noisy coupling signalsAs discussed before, extrapolation is necessary to solve the co-simulation problem [9]. Ifreal-time systems enter the co-simulation several coupling signals are typically measuredwith sensors and are often corrupted by noise. Signal-based extrapolation techniques,which are typically used for extrapolation, amplify the noisy measurements and so theycannot provide reliable coupling signals. So extrapolation methods which are robustagainst noisy measurements are required. To satisfy this requirement e.g. model-basedextrapolation methods can be used [9].4 STRUCTURE OF A REAL-TIME CO-SIMULATIONThe focus of this work lies on the coupling of real-time and non-real-time systems. Thesynchronisation of the involved real-time and non-real-time sytems is done via ICOS RT(see Fig. 4). ICOS RT is responsible for the time correct communication between theinvolved subsystems. So the slow down mechanism is the most important task of ICOS5993G. Stettinger, M. Benedikt, N. Thek and J. ZehetnerRT to perform a correct synchronisation between the real-time and non-real-time systems.Two additional coupling types which are not part of this work are handled by ICOS RT:Figure 4: Coupling of real-time and non real-time systems [9]The coupling of real-time systems and the coupling of tasks on one real-time system [9].5 EXAMPLE: MILD HYBRIDThe following example demonstrates the synchronisation mechanism of a real-timeco-simulation.5.1 Model descriptionThe used example represents a hybrid vehicle which consists of seven subsystems (seeFig. 5). These involved subsystems are modelled in different simulations tools (MAT-LAB/SIMULINK 3, KULI 4 and AVL CRUISE 5):• Vehicle (AVL CRUISE):The vehicle model includes the power train of a parallel hybrid vehicle. This subsys-tem interacts with 17 inputs and 8 outputs with the other involved subsystems. Themicro- and macro-time-steps are set to δT = 0.001s and ∆T = 0.05s, respectively.• Thermal Network (KULI ):The thermal network model includes the cooling circuit of the vehicle.Inputs: 9; Outputs: 12; δT = 1s; ∆T = 1s.• Cockpit (MATLAB/SIMULINK ):The cockpit model describes the driver of the hybrid car. So this system defines thevelocity profile and the gear selection.Inputs: 1; Outputs: 7; δT = 0.01s; ∆T = 0.05s.• Hybrid Module (MATLAB/SIMULINK ):The hyrid module includes the parallel hybrid structure of the vehicle. So the3http://www.mathworks.com4http://www.kuli.at5http://www.avl.com/cruise16994G. Stettinger, M. Benedikt, N. Thek and J. ZehetnerFigure 5: Subsystems of the hybrid vehiclerecuperation of the brake energy and the partition of the desired driving torque tothe combustion and electric engine are the main tasks of this subsystem.Inputs: 7; Outputs: 5; δT = 0.01s; ∆T = 0.05s.• Energy Management System (MATLAB/SIMULINK ):This subsystem includes the energy management of the hybrid vehicle. Especiallythe energy exchange between the super cap, the electric motor and the Li-Ion batteryis represented herein.Inputs: 8; Outputs: 6; δT = 0.01s; ∆T = 0.05s.• Super Cap (MATLAB/SIMULINK ):The super cap subsystem modells the behaviour of the super cap.Inputs: 1; Outputs: 4; δT = 0.01s; ∆T = 0.05s.• Li-Ion Battery (MATLAB/SIMULINK ):The Li-Ion battery subsystem modells the behaviour of the Li-Ion battery.Inputs: 2; Outputs: 5; δT = 0.01s; ∆T = 0.05s.7995G. Stettinger, M. Benedikt, N. Thek and J. Zehetner5.2 Real-time co-simulation configurationFor this example the four involved MATLAB/SIMULINK modells are compiled andrun on an ETAS real-time system (see Fig. 6). The non-real-time part includes the KULI,one MATLAB/SIMULINK and the AVL CRUISE modell. The subsystems of the non-real-time part are coupled via the ICOS Co-Simulation framework to achieve a correctinteraction of these subsystems. The essential part of the real-time co-simulation is thesynchronisation of the real-time and non-real-time part. This synchronisation mechanismslows down the non-real-time part such that a time correct interaction between the real-time- and non-real-time part is performed. The macro-time-step, where coupling databetween the real-time- and non-real-time system gets exchanged, is set to ∆T = 200ms.The overall real-time co-simulation, consisting of the real-time and non-real-time part,use a parallel scheduling while the subsystems in the non-real-time part are sequentialscheduled.Figure 6: Configuration of the real-time co-simulation5.3 Simulation resultsFig. 7 shows the simulation results of the real-time co-simulation compared to a non-real-time realisation of the same system. In the case of the non-real-time co-simulationall subsystems are simulated using the co-simulation platform ICOS. The two simulationresults are nearly the same over the simulation time. This means that a subsystem of thenon-real-time co-simulation, which runs faster than the wall-clock time, can be replacedby a real-time system with the same functionality and the simulation result is still reli-able. The small deviations between the simulation results stem from the communicationmedium between the real-time- and non-real-time part of the real-time co-simualtion. Es-pecially the introduced dead-times influence the overall simulation result. Fig. 8 showsthe synchronisation effect of the time correct coupling: All involved subsystems have asimulation speed which is close to the wall-clock time due to the slow down mechanism.8996G. Stettinger, M. Benedikt, N. Thek and J. ZehetnerFigure 7: Real-time co-simulation resultFigure 8: Synchronization of the involved online and offline systemsSo a correct interaction between the real-time and non-real-time systems is possible. Fig.9 shows the slow down effect of the real-time co-simulation compared to the non-real-time9997G. Stettinger, M. Benedikt, N. Thek and J. Zehetnerrealisation. In the non-real-time case the whole simulation is done via ICOS where allinvolved subsystems have a simulation speed which is faster than the wall-clock time.With the help of ICOS RT the non-real-time systems slow down and a synchronisationwith the real-time system is possible.Figure 9: Slow down effect of the coupling element6 CONCLUSIONS & OUTLOOKThe integration of hard real-time systems into co-simulation frameworks faces severalchallenges. The presented approach shows that a real-time co-simulation is handable if thenon-real-time systems run faster than the wall-clock time. The required synchronisationwith respect to the wall-clock time is realised via the discussed slow down mechanism.Future activities will concentrate on dead-time handling due to the involved communi-cation medium and on extrapolation techniques which are robust against noisy coulplingsignals. These difficulties are focused in the ongoing research project ACoRTA at ViF,together with Porsche, AVL and Uni Klagenfurt. By solving these problems co-simulationunder hard-real-time conditions will be possible.REFERENCES[1] Geimler, M.; Krüger, T.; Linsel, P.: ”Co-Simulation, gekoppelte Simulation oderSimulatorkopplung? Ein Versuch der Begriffsvereinheitlichung”, O+P Zeitschrift fürFluidtechnik (50), 2006, 572-576.10998G. Stettinger, M. Benedikt, N. Thek and J. Zehetner[2] Benedikt, M.; Stippel, H.; Watzenig, D.: ”An adaptive Coupling Methodology forFast Time-Domain Distributed Heterogeneous Co-Simulation”, SAE International,2009, 1-10.[3] Dronka, S.: ”Die Simulation gekoppelter Mehrkörper- und Hydraulik-Modelle mitErweiterung für Echtzeitsimulation”, PhD Thesis, Technische Universität Dresden,2004.[4] Arnold, M.: ”Multi-Rate Time Integration for Large Scale Multibody System Mod-els”, IUTAM Bookseries, 2007, 1-10.[5] Gonzales, F.; Naya, M.; Luaces, M.; Gonzales, M.: ”On the effect of multirate co-simulation techniques in the efficiency and accuracy of multibody system dynamics”,Multibody System Dynamics, 2011, 461-483.[6] Puntigam, W.: ”Independent Co-Simulation Platform for transient coupling of indi-vidual submodels to establish an efficient energy management for the entire vehicle- taking thermal management as an example”, PhD Thesis, Technische UniversitätGraz, 2007.[7] Benedikt, M.; Zehetner, J.; Watzenig, D.; Bernasch, J.: ”Modern coupling strategies- is co-simulation controllable?”, NAFEMS Seminar: The Role of CAE in SystemSimulation, Wiesbaden, Germany, 2011.[8] Hermann Kopetz. 1997. Real-Time Systems: Design Principles for Distributed Em-bedded Applications (1st ed.). Kluwer Academic Publishers, Norwell, MA, USA.[9] Stettinger, G.; Benedikt, M.; Thek, N.; Zehetner, J.: ”Extending Co-Simulation tothe Real-Time domain”, SAE International, 2013, 1-8.[10] Benedikt, M.; Watzenig, D.; Zehetner, J.; Hofer, A.: ”Macro-Step-Size Selection andMonitoring of the Coupling Error for Weak Coupled Subsystems in the FrequencyDomain”, V International Conference on Computational Methods for Coupled Prob-lems in Science and Engineering, Ibiza, Spain, 2013.11999

On the difficulities of real-time co-simulation

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On the difficulities of real-time co-simulation

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