EP3398092A1 - Procédé de configuration d'une cosimulation pour un système complet - Google Patents

Procédé de configuration d'une cosimulation pour un système complet

Info

Publication number
EP3398092A1
EP3398092A1 EP16819948.7A EP16819948A EP3398092A1 EP 3398092 A1 EP3398092 A1 EP 3398092A1 EP 16819948 A EP16819948 A EP 16819948A EP 3398092 A1 EP3398092 A1 EP 3398092A1
Authority
EP
European Patent Office
Prior art keywords
subsystem
parameter
simulation
output
macro
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP16819948.7A
Other languages
German (de)
English (en)
Inventor
Martin Benedikt
Jost Bernasch
Franz Holzinger
Daniel Watzenig
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Virtual Vehicle Research GmbH
Original Assignee
Kompetenzzentrum das Virtuelle Fahrzeug Forchungs GmbH
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Kompetenzzentrum das Virtuelle Fahrzeug Forchungs GmbH filed Critical Kompetenzzentrum das Virtuelle Fahrzeug Forchungs GmbH
Publication of EP3398092A1 publication Critical patent/EP3398092A1/fr
Pending legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/30—Circuit design
    • G06F30/32—Circuit design at the digital level
    • G06F30/33—Design verification, e.g. functional simulation or model checking
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2117/00—Details relating to the type or aim of the circuit design
    • G06F2117/08—HW-SW co-design, e.g. HW-SW partitioning

Definitions

  • the present invention relates to a method and apparatus for configuring a co-simulation for an overall system.
  • Co-simulation provides a way to bring together the distributed modeled and distributed simulated models.
  • the coupling quantities are exchanged at defined times, after so-called macro-time steps, during the simulation.
  • Characteristics of the models determine which coupling algorithm can be used. Allowing simulation tools or simulated models (e.g., FMI) to repeat a computational step, iterative (implicit) approaches (strong coupling) may be used. Usually, however, a required resetting of the simulation tools and
  • the resulting error can be kept negligible by suitable configuration of the co-simulation, but is to be made manually by the user of the co-simulation according to the prior art. This is time consuming and usually, due to the prevailing complexity of co-simulation, by the user of co-simulation manually not feasible.
  • AT 509930 A2 entitled "Model-based methodology and method for quantifying the quality of the results of co-simulations” describes a method for evaluating the quality of the co-simulated overall system.
  • Execution orders as static meta-information are used in addition to the modeled coupling uncertainties introduced by extrapolation to predict the quality in advance, i. H . before the co-simulation starts.
  • Subsystems represent algebraic and / or differential
  • each subsystem is solved or simulated independently of other subsystems via a macro-time step by means of its own numerical solution algorithm.
  • Solution algorithms are typically selected by the user on the basis of the present and to be solved equation system.
  • solver special numerical solution algorithm
  • Network internal loops create data dependencies between the involved subsystems, so that - depending on the execution order - parallel or sequential - more or less coupling quantities (input parameters) must be "estimated" by extrapolation methods over the macro-time step to be solved.This extrapolation is necessary to solve the prevailing problem of causality and inevitably leads to a necessary error.
  • This error which is inevitably introduced by the coupling, in part significantly influences the physical behavior of the distributed system. If, for example, a force acts as a coupling variable in such a co-simulation, then the coupling error has a direct effect on the overall system behavior, for example by a faulty acceleration of an inertia.
  • This object can be achieved by a method for configuring a co-simulation for an overall system and with an apparatus for configuring a co-simulation for an overall system according to the independent ones
  • a method for configuring a co-simulation for an entire system or a
  • Total simulation with at least a first subsystem and a second subsystem.
  • the first subsystem has at least a first one
  • Parameter input and at least a first parameter output wherein based on the first parameter input by means of a first
  • the first parameter output can be determined, and wherein the second subsystem has at least one second parameter input and at least one second parameter output. Based on the second parameter input, the second parameter output can be determined by means of a second solution algorithm.
  • connection network is determined which couples the first subsystem and the second subsystem to a coupling and determines which of the first and second parameter outputs is
  • Coupling size for the corresponding first and second parameter inputs are determined.
  • first and second parameter outputs of the corresponding first and second subsystems are determined as coupling size for the corresponding first and second parameter inputs of other subsystems (eg the other first and second subsystems) are supported by the user of the co-simulation (possibly automated, e.g.
  • the determination of the resulting connection network designates the information-technological recording of the physical relationships in the real world within the co-simulation network, eg via a directed graph consisting of all subsystems (the so-called). Nodes), their parameter inputs and parameter outputs and the specified connections of the inputs and outputs (the so-called edges).
  • first subsystem information eg direct access, input / output dynamics, instantaneous frequency, simulation times, etc.
  • second subsystem information of the second subsystem are determined.
  • An input or output dynamics describes between a
  • Parameter output can the corresponding dynamics or the input or
  • An instantaneous frequency describes the frequency content of a coupling signal at a specific time. Different physical effects can lead to different instantaneous frequencies.
  • a wheel of a vehicle turns at a constant
  • Determining the subsystem information includes obtaining pre-available information, e.g. the connectivity network and / or direct pass-through, and information generated at runtime.
  • Information generated at runtime is determined by a subsystem analysis, where the current simulation times of the subsystems are recorded, the input / output dynamics by methods from the system identification (eg via recursive least squares, finite differences) and the instantaneous frequencies by methods from the signal processing ( eg Hilbert Huang Transformation), and "direct penetration" through direct input-output relationships (eg a linear or nonlinear
  • an execution order is selected by means of which it is determined in which order the first parameter output and the second parameter output are determined (and thus determines which first and / or second parameter inputs must be extrapolated for solving the causality problem).
  • a force represents a first parameter input of a first subsystem representing a mechanical inertia and a resulting position change of the mass is available on the first parameter output configured as a second parameter input of a second subsystem and that position change in the second subsystem
  • Parameter output leads and this second parameter output is again configured as the first parameter input, so the execution order can influence the physical behavior of the co-simulation.
  • connection in the second subsystem a proportionally amplified error at the second parameter output or the force.
  • the order of execution is therefore crucial for a qualitative, high-quality, overall physical system behavior.
  • extrapolation methods are determined by which the first and second parameter inputs are input during a macro-step size (i.e.
  • the macro step size is determined, which specifies the coupling times at which an exchange of the corresponding first and second
  • Input parameters and the first and second output parameters between the first and second subsystems is performed, and which determines the extrapolation of first and second input parameters.
  • the coupling of the first and second subsystems is configured based on the interconnection network, the first subsystem information, and second subsystem information, the execution order, the
  • a subsystem has a sub model that depicts a real model (eg, a component itself or a flow model of a component, etc.).
  • a model describes the behavior of a subsystem via algebraic and / or differential relationships. This submodel is created by means of a
  • Simulation tools produced and simulated (eg a CAD program). To model and simulate an overall system and thus a
  • the entire system is built up of several subsystems. Each subsystem solves a specific system area
  • Input parameters are those parameters which the solution algorithm requires as input in order to derive the simulation result or the result
  • the input parameters are z. B.
  • the solution algorithm performs the desired simulation in a subsystem.
  • Solution algorithms can be the same or different.
  • individual solution algorithms of the subsystems can use different fixed or variable step sizes for solving the individual subsystems
  • the solution algorithm represents a numerical method with which the output parameters can be determined from the input parameters and the modeled subsystems.
  • the output parameters of the subsystems are specific values which are calculated and simulated by means of associated solution algorithms.
  • these can be geometric values for forming a geometric model, for example, if a dynamic deformation behavior, modeled using differential equations, is to be simulated in a subsystem.
  • the input parameter I can be calculated in another subsystem and is the corresponding one there
  • the interconnection network determines how and which subsystems should be coupled together.
  • the interconnection network forms a coupling between two subsystems and determines which of the first and second parameter outputs are intended as a coupling variable for the corresponding first and second parameter inputs.
  • a parameter output of a subsystem can be assigned to several parameter inputs of other subsystems.
  • the coupling can be wired or wireless to exchange the
  • the subsystem information represents information of a subsystem that characterizes the subsystem. If necessary, the subsystem information can be controlled and adapted or influenced by the coupling with other subsystems.
  • the subsystem information is, as described in more detail below, e.g. a direct penetration, input-output dynamics, instantaneous frequency and / or simulation times.
  • Subsystem information such as "direct pass-through” or “input / output dynamics,” may be pre-available or known to individual subsystems.
  • this information could be provided by the subsystem manufacturer (eg the
  • the execution order is selected, by means of which it is determined in which order to one another the first parameter output and the second parameter output are determined. In other words, it is determined when which subsystem is executed (ie simulated over the defined macro-time step). For example, in the case of mutually influencing subsystems, it is advantageous first of all to carry out a specific subsystem in advance and to use the resulting output parameters for a following subsystem, assuming identical macro time steps, without extrapolation of the input parameters (sequential execution).
  • the execution order may be predetermined by the user and / or adapted in the configuring step.
  • extrapolation methods are determined, by means of which the first and second parameter inputs during a macro step size (eg.
  • first and second input parameters different extrapolation methods can be used. If no parameter inputs are available, especially for the current macro-time step, these values must be extrapolated (estimated) and interpolated accordingly to calculate the output parameters. For example, for certain
  • the coupling of the first and second subsystems is configured based on the interconnection network, the first subsystem information, and second subsystem information, the execution order, the
  • Execution order, the connection network, etc.) and the configuration of the subsystems themselves can be set or improved. Furthermore, the duration of the overall simulation and the consumption of resources can be reduced, in particular by means of adapted and improved coupling.
  • Configuration defines the user e.g. the execution order of
  • Subsystems and for a plurality of coupling signals are the extrapolation approaches as well as the
  • the configuration is improved by taking into account in particular the subsystem information, the connection network, the execution order, the extrapolation method and the macro step width in the configuration.
  • the co-simulation is ended or the co-simulation is performed again.
  • the simulation results, the subsystem information determined (eg direct penetration, input-output dynamics, instantaneous frequency, simulation times, etc.) and the interconnection network, and the configuration can be used to run the next simulation the execution order, the
  • Macro-time step at coupling time as part of a subsystem analysis, an analysis of coupling events (for example, discrete events, high
  • Input and output parameters of the submodel are, for example, in a separate component to
  • Input parameters and first output parameters of the first subsystem and between second input parameters and second output parameters of the second subsystem.
  • the "input / output dynamics" of the subsystems are the dynamic properties of the subsystems between all available input / output combinations of the individual subsystems.
  • a subsystem between an input and an output may have a different input / output dynamics than with respect to a further input and a further output of the subsystem or a further subsystem.
  • These input / output dynamics of the subsystems can be determined by methods for data-based system identification of MIMO (multiple-input multiple-output) systems or input / output specifically, by SISO (single-input single-output). The dynamics of this subsystem decisively determine which kind of MIMO (multiple-input multiple-output) systems or input / output specifically, by SISO (single-input single-output). The dynamics of this subsystem decisively determine which kind of MIMO (multiple-input multiple-output) systems or input / output specifically, by SISO (single-input single-output). The dynamics of this subsystem decisively determine which kind of MIMO (multiple-input multiple-output) systems or input / output specifically, by SISO (single-input single-output). The dynamics of this sub
  • the input / output dynamics of the subsystems will be used to select the execution order and individual extrapolation methods.
  • Subsystem information on a simulation time of the first subsystem and / or the second subsystem For example, a first subsystem may have a different simulation time than the second subsystem (eg, by using different macro-increments). Based on the individual simulation time of the subsystems, for example, the macro step size or the execution order
  • a real-time co-simulation requires that the subsystems can be simulated in real time and thus the first and second
  • Parameter outputs can be determined in real time and thus at defined times, the coupling times, based on the real time (e.g.
  • Wall clock for further use (eg extrapolation).
  • Subsystem information on the required calculation times for performing the simulation of the individual subsystems for the respective macro-time steps so that by means of reference to the calculation time required by the subsystems with the respective macro-time steps of the subsystems Adjustments in the temporal behavior for the implementation of the co-simulation are carried out in real time at the respective coupling times.
  • Coupling times can thus bottlenecks in the temporal behavior for an execution of the co-simulation are recognized in real time, which by an advantageous configuration of the co-simulation during the term
  • Computation time (as subsystem information) needed as a macro-time step (which, for example, is defined in real-time).
  • the execution order of the subsystems can be adapted or free
  • Subsystem information on an instantaneous frequency of the first and / or second input parameters and / or the first and / or second output parameters are included in Subsystem information on an instantaneous frequency of the first and / or second input parameters and / or the first and / or second output parameters.
  • Subsystem information on a direct access of the first and / or second input parameters to the first and / or second output parameters of the subsystems refers to a system property where a change at an input of a system directly and without delay leads to a change (effect) at the output of the system.
  • the integration of subsystems with "direct penetration” leads to algebraic loops and thus to difficulties during the co-simulation or the superordinate solution process Therefore, the knowledge of whether the input and output quantities of subsystems is direct Penetration is of great interest and will therefore be used subsequently for the method of automatically configuring the co-simulation.
  • the step of determining the macro-step size comprises determining a first macro-step width of the first sub-system and determining a second macro-step width of the second subsystem.
  • the first macro step size predetermines first coupling times at which the first output parameter can be determined in each case, wherein the second macro step size specifies second coupling times at which the second output parameter can be determined in each case.
  • the step of determining the extrapolation methods comprises determining first
  • Extrapolations Kunststoffe the first subsystem by means of which the first parameter inputs during the first macro-step size (and between the coupling times) are determinable, and a determination of second
  • Extrapolations Kunststoff the second subsystem by means of which the second parameter inputs during the second macro-step size (and between the coupling times) can be determined on. For individual first and second input parameters, different extrapolation methods can be used.
  • the first subsystem has at least one first parameter input and at least one first parameter output, wherein the first parameter output can be determined based on the first parameter input by means of a first solution algorithm.
  • the second subsystem has at least one second parameter input and at least one second
  • Parameter output based on the second parameter input by means of a second solution algorithm, the second parameter output can be determined.
  • the device has a connection unit for determining a
  • Connection network which is the first subsystem and the second
  • Subsystem coupled to a coupling and determines which of the first and second parameter outputs are determined as a coupling size for the corresponding first and second parameter inputs on.
  • the apparatus further comprises a determining unit for determining first subsystem information (direct penetration, input-output dynamics, instantaneous frequency, simulation times, computation time of the subsystems and discrete events) of the first subsystem and of second ones
  • the apparatus further comprises a selection unit for selecting an execution order, by means of which it is determined in which order in relation to one another the first parameter output and the second parameter output are determined.
  • the apparatus further comprises an extrapolation unit for determining the extrapolation method, by means of which the first and second
  • the apparatus further comprises a step size unit for determining a macro step size or the macro step sizes, which specifies coupling times to which a
  • the apparatus further includes a configurator for configuring the
  • Connection network the first subsystem information and second
  • connection unit the different units, in particular connection unit,
  • Selection unit, extrapolation unit, step size unit, and configurator etc. of the device may each be realized as a processor. It is also possible to design any combination or plurality of these or other units as a common processor. All units can also be realized as a common processor. According to another exemplary embodiment, a
  • a computer-readable storage medium is described in which a program for configuring a co-simulation for an entire system is stored, which program, when executed by a processor, executes or controls the method described above.
  • a program element for configuring a co-simulation for an entire system is described, which program element, when executed by a processor, executes or controls the method described above.
  • the present invention describes a method for the automated configuration of co-simulation.
  • Coupling signals must be extrapolated; Extrapolation errors increase with increasing macro-step size in non-iterative co-simulation; and extrapolation methods are suitable for coupling depending on the application.
  • non-visible subsystems are combined to form an overall system by connecting the subsystem inputs and outputs.
  • required information is thus i .A the user. inaccessible .
  • the interconnection network represents available information and describes which subsystem inputs with which subsystem output are connected .
  • this method analyzes the involved subsystems at runtime and thus provides further information for an automated network
  • the method according to the invention additionally builds on detailed knowledge of the extrapolation methods used. Especially will be on here
  • a co-simulation consists of at least two interacting subsystems.
  • Coupling signals in the couplings over the defined macro time steps be extrapolated. If, in contrast, the first subsystem is calculated before the second subsystem and then the third subsystem, then only the coupling signal in the second coupling between the third subsystem and the second subsystem must be extrapolated in each co-simulation step.
  • Transfer function of the individual coupling can be determined.
  • Subsystems can have different dynamics and also have different dynamics.
  • Embodiments of the present invention may be implemented both by means of a computer program, that is to say a software, and by means of one or more special electrical circuits, that is to say in hardware (eg FPGA or ASIC), or in any hybrid form, that is to say by means of software. Components and hardware components, be realized.
  • the subsystems can z. B. locally on a computer (also distributed on different computing cores) or topologically network-distributed on different computers to be simulated. It should be noted that the embodiments described herein represent only a limited selection of possible embodiments of the invention. So it is possible the characteristics of individual
  • Embodiments suitably combine with each other, so that a variety of different embodiments are to be regarded as obvious to those skilled in the art with the explicit embodiment variants here.
  • some embodiments of the invention are with
  • Fig. 1 is a schematic representation of a co-simulation for a
  • Fig. 2 is a schematic representation of a sequence of the frame according to an exemplary representation of the method according to the invention
  • Fig. 3 is a schematic representation of an exemplary embodiment of the present invention.
  • Fig. 4 shows a schematic representation of an extrapolation between two coupling times.
  • Fig. 1 shows a schematic representation of a co-simulation for a
  • FIG. 1 a co-simulation of a first submodel 110, a second submodel 120, and a third submodel 130 is constructed.
  • the first subsystem 110 has at least a first one
  • the second subsystem 120 has at least one second parameter input 121 and at least one second parameter output 122, wherein, based on the second parameter input 121, by means of a second parameter input 121
  • the third subsystem 130 has at least one third parameter input 131 and at least one third parameter output 132, based on on the third parameter input 131 by means of a third
  • a subsystem 110, 120, 130 each has a submodel which depicts a real model (eg, a component itself or a flow model of a component, etc.).
  • a model describes the behavior of a subsystem 110, 120, 130 via algebraic and / or differential relationships.
  • This submodel is produced and simulated by means of a simulation tool 113, 123, 133 (eg a CAD program). To an entire system 100 too
  • the overall system 100 is constructed from a plurality of subsystems 110, 120, 130. Each subsystem 110, 120, 130 solves a particular system area
  • the subsystems 110, 120, 130 can be simulated locally on a computer (also distributed on different processor cores) or topologically network-distributed on different computers.
  • the input parameters 111, 121, 131 are those parameters which the solution algorithm 114, 124, 134 needs as input in order to use the simulation result or the output parameters 112, 122, 132
  • the input parameters 111, 121, 131 are z. Temperature, geometric data, strengths, force, speed, environmental parameters (eg, outside temperature), flow, etc. required by the solution algorithm.
  • the solution algorithm (solver) 114, 124, 134 performs the desired
  • Solution algorithm 114 or second solution algorithm 124 may be the same or different.
  • individual solution algorithm 114 or second solution algorithm 124 may be the same or different.
  • Solution algorithms of the subsystems use different fixed or variable increments to solve the individual subsystems.
  • the solution algorithm 114, 124, 134 represents a numerical method with which the output parameters 112, 122, 132 can be determined from the input parameters 111, 121, 131 and the modeled subsystems 110, 120, 130.
  • the output parameters 112, 122, 132 in the subsystems 110, 120, 130 are specific values which are calculated and simulated by the solution algorithm 114, 124, 134. During a macro-time step, also several values of the output parameters 112, 122, 132 can be determined.
  • the first coupling 101 takes place.
  • the first parameter outputs or output parameters 112 are obtained from the first subsystem 110 and used as second parameter inputs or
  • Input parameters 121 are provided to the second subsystem 120.
  • the second output parameter of the second subsystem 120 is provided as the third input parameter 131 in the third subsystem 130.
  • a subsystem may, for example, also have a plurality of input parameters 121, which are obtained from different submodels 110, 130.
  • a third party for example, a third party
  • Input parameters 121 are provided to the second subsystem 120.
  • the first output parameter 112 is provided to the subsystem 120 via the first coupling 101 as a further second input parameter 121.
  • FIG. 2 shows, in conjunction with the co-simulation of FIG. 1 on
  • subsystem information 201 is first determined.
  • first subsystem information eg direct access, input / output dynamics, instantaneous frequency, simulation times
  • second subsystem information of the second subsystem 120 are determined.
  • This subsystem information 201 is in an initial step from a database or via default of the user to the configuration
  • the subsystem information determined in previous runs of the method may be used. Subsequent to repeatedly performing the method, the subsystem information determined in previous runs of the method may be used.
  • connection network 202 is determined, which is the first
  • Subsystem 110 and the second subsystem 120 (or a plurality of further subsystems) coupled to couplings 101, 102, 103 and determines which of the first and second parameter outputs 112, 122 are determined as coupling size for the corresponding first and second parameter inputs 111, 121.
  • an execution order 203 is selected, by means of which it is determined in which order to each other the first parameter output 112 and the second parameter output 122 are determined to us determines which first and / or second parameter inputs 121, 131 need to be extrapolated to solve the causality problem.
  • extrapolation methods 204 are determined by means of which the first and second parameter inputs 112, 122 can be determined during a macro-step width (and between the coupling times).
  • a macro step size 205 which specifies coupling times at which an exchange of the corresponding first and second
  • Subsystem 110, 120 configured based on the interconnect network (202), the first subsystem information, and second
  • Extrapolation method (204), the macro-step size (205), and the co-simulation over the Marko time step.
  • Information can be from z. B. the execution order 203 are set. On this basis and the information available, then, in a further step, appropriate
  • Extrapolation method 204 determined.
  • suitable macro-step sizes 205 are selected so that the
  • Configuration 206 of the co-simulation for a pending macro-time step is certain in the co-simulation.
  • this simulation step 207, d. H . at the next coupling time there is a subsystem analysis 208 and updating the previously collected subsystem information 201. Is after the
  • FIG. 3 describes a possible technical implementation of the method for automated configuration during (t ⁇ t en d) of the co-simulation.
  • Two subsystems 110, 120 are connected via a coupling 101 to a co-simulation.
  • a next simulation step 207 and a renewed subsystem analysis 208 takes place a next simulation step 207 and a renewed subsystem analysis 208.
  • the subsystems 110, 120, 130 based on the coupling data (the input parameters 111, 121, 131 and output parameters 112, 122, 132) analyzed and relevant information, such as a direct pass-through 302, an input / output dynamics 304, an instantaneous frequency 305 and / or
  • Simulation times 303 extracted or determined for configuration. From this database and along with other available information, such as the connection network 202 and the individual
  • Solution algorithms 301 (114, 124, 134) of the corresponding subsystems 110, 120, 130, the selection of the execution order 203, the choice of extrapolation 204 and the choice of the macro-time increments 205.
  • Fig. 3 shows a possible implementation for storing the information which serves as a database for an automated configuration of the co-simulation.
  • the available data is stored in different matrices (e.g., 202, 301, 302, 303, 304, 305). Describe by way of example
  • connection network 202 different matrices the connection of the inputs and outputs of all involved subsystems 110, 120, 130 and the connection network 202, existing "direct passages" 302 of the subsystems 110, 120, 130, input / output dynamics 304 of the subsystems 110, 120, 130, the
  • Instantaneous frequencies 305 of the coupling signals (for example, in couplings 101, 102, 103), if available subordinate solution algorithms 301 and / or the current simulation times 303 of the individual subsystems 110, 120, 130. This information is at runtime and / or following the simulation extracted.
  • the columns form the parameter inputs of the subsystems 110, 120, 130 and the rows the parameter outputs of
  • the proposed method analyzes local (eg subsystem analysis) and global (e.g., interconnection network) information and uses it to globally configure the co-simulation.
  • local e.g subsystem analysis
  • global e.g., interconnection network
  • Fig. 4 shows an extrapolation between two coupling times.
  • the subsystems 110, 120, 130 involved are solved exactly once over each defined macro-time step.
  • Execution order 203 the type of extrapolation 204 and the choice of the macro time step size 205 must be determined before the calculation, at the time of the coupling. Occur during this macro-time step z. For example, if there is a discrete event or high system dynamics, the co-simulation for this step has not been configured according to system behavior. This situation is shown graphically in FIG. Fig. 4 shows a coupling signal 401 which corresponds to the micro-time steps of the
  • Solution algorithm 114, 124, 134 of the subsystem 110, 120, 130 is defined.
  • the coupling signal 401 is extrapolated over the Marko time step to be calculated until the next coupling time 403 via extrapolation 1 st order 404.
  • extrapolation the last two values from the history of the coupling signal 401 before
  • Coupling time 402 used.
  • an event 405 now occurs at a time t e in a subsystem 110, 120, 130, which leads to a sharp change of the coupling signal 401 at the time of the event 405 and thus also to a large one

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Abstract

La présente invention concerne un procédé de configuration d'une co-simulation destiné à un système complet (ou simulation totale) comprenant au moins un premier sous-système et un deuxième sous-système. Selon le procédé, on définit un réseau de connexion qui définit le premier sous-système et le second sous-système et les couple à un couplage. En outre, on définit des premières informations du premier sous-système et des deuxièmes informations du deuxième sous-système. De plus, on sélectionne un ordre d'exécution avec lequel on définit dans quel ordre sont définies la première sortie de paramètres et la deuxième sortie de paramètres. En outre, on définit un procédé d'extrapolation au moyen duquel les première et deuxième entrées de paramètre peuvent être définies au cours d'un macro-incrément (par exemple entre les instants de couplage). On définit le macro-incrément qui spécifie les instants de couplage auxquels est effectué un échange des premier et deuxième paramètres d'entrée correspondants et des premier et deuxième paramètres de sortie entre les premier et deuxième sous-systèmes. Le couplage des premier et deuxième sous-systèmes est réalisé en étant configuré sur la base du réseau de connexion, des premières informations de sous-système et des deuxièmes d'informations de sous-système, de l'ordre d'exécution et des procédés d'extrapolation et du macro-incrément et la co-simulation.
EP16819948.7A 2015-12-30 2016-12-29 Procédé de configuration d'une cosimulation pour un système complet Pending EP3398092A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EP15203199.3A EP3188053A1 (fr) 2015-12-30 2015-12-30 Procede de configuration d'une co-simulation pour systeme entier
PCT/EP2016/082809 WO2017114883A1 (fr) 2015-12-30 2016-12-29 Procédé de configuration d'une cosimulation pour un système complet

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EP3398092A1 true EP3398092A1 (fr) 2018-11-07

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EP3454234A1 (fr) * 2017-09-06 2019-03-13 dSPACE digital signal processing and control engineering GmbH Procédé de fourniture d'une simulation en temps réel pour le développement des appareils de commande et dispositif de simulation pour le développement des appareils de commande
CN108319752B (zh) * 2017-12-25 2021-09-17 博格华纳汽车零部件(宁波)有限公司 湿式双离合器及液压控制系统的物理仿真试验方法
EP3518216A1 (fr) 2018-01-30 2019-07-31 Volvo Car Corporation Système de cosimulation présentant une compensation de retard et procédé de commande de système de cosimulation
DE102018205924A1 (de) * 2018-04-18 2019-10-24 Robert Bosch Gmbh Kopplungseinrichtung zur Kopplung eines ersten Simulators mit wenigstens einem zweiten Simulator und Betriebsverfahren hierfür
US11940978B2 (en) 2018-09-19 2024-03-26 International Business Machines Corporation Distributed platform for computation and trusted validation
US11032063B2 (en) 2018-09-19 2021-06-08 International Business Machines Corporation Distributed platform for computation and trusted validation
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AT509930A2 (de) 2010-06-01 2011-12-15 Kompetenzzentrum Das Virtuelle Fahrzeug Forschungsgmbh Modellbasiertes verfahren zur quantifizierung der qualität der resultate von co-simulationen
AT511272A1 (de) * 2010-10-15 2012-10-15 Kompetenzzentrum Das Virtuelle Fahrzeug Forschungsgmbh Kopplungsmethodik für nicht-iterative co-simulation
US20120197617A1 (en) 2011-01-31 2012-08-02 Muris Mujagic Co-Simulation with Peer Negotiated Time Steps
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JP2019507405A (ja) 2019-03-14
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US11720730B2 (en) 2023-08-08
US20190018916A1 (en) 2019-01-17

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