EP2339318A1 - Diagnoseverfahren einer Störung eines Mechatroniksystems - Google Patents

Diagnoseverfahren einer Störung eines Mechatroniksystems Download PDF

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Publication number
EP2339318A1
EP2339318A1 EP10306490A EP10306490A EP2339318A1 EP 2339318 A1 EP2339318 A1 EP 2339318A1 EP 10306490 A EP10306490 A EP 10306490A EP 10306490 A EP10306490 A EP 10306490A EP 2339318 A1 EP2339318 A1 EP 2339318A1
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EP
European Patent Office
Prior art keywords
test
function
signal
malfunction
diagnostic
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EP10306490A
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English (en)
French (fr)
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EP2339318B1 (de
Inventor
Louise Trave-Massuyes
Hervé Ressencourt
Hervé Poulard
Jérôme Thomas
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Centre National de la Recherche Scientifique CNRS
Actia Automotive SA
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Centre National de la Recherche Scientifique CNRS
Actia Automotive SA
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    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
    • G07C5/00—Registering or indicating the working of vehicles
    • G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
    • G07C5/0808—Diagnosing performance data

Definitions

  • the present invention relates to a method for diagnosing a malfunction of a mechatronic system, a tool for carrying out this method, and a method for generating a signature table for implementing the method of diagnostic.
  • ECUs Electronic Control Units
  • a function is the set of resources (UEC, part of software, networks, electronic and mechanical components %) necessary for the realization of a service.
  • the maintenance of the vehicles, and in particular the fault diagnosis in the garage, has thus become a real problem.
  • the known diagnostic systems use methods based on the modeling of the physical components, which determine static values, to be compared with the measurement carried out during a test. These methods remain rather rudimentary so that today, in garages, the diagnosis of mechatronic systems based on these methods relies mainly on the knowledge of the mechanic or manually built diagnostic trees.
  • the present invention aims at providing a high-performance method for diagnosing a mechatronic system and a tool adapted to the implementation of this method.
  • the comparison made between a signal representing the evolution over time of an observable variable and a reference signal makes it possible, by the wealth of information that it brings into play, to report with a much greater relevance of a much greater number of malfunctions than the simple conventional comparison between the value taken at a given moment by this observable variable and a value, a range or a reference threshold.
  • a comparison according to the state of the art relates to a static value and ignores any transient or periodic regime.
  • Mechatronic systems such as motor vehicles, include electronic components associated with mechanical, and / or electromechanical, and / or hydraulic, and / or pneumatic components, etc., and more and more frequently to software components. The malfunction of such a mechatronic system is difficult to diagnose.
  • a function can be defined as the set of resources (UEC, part of software, networks, physical, electronic, mechanical, thermal components, etc.) needed to perform a service.
  • These resources are variables of the function that can take different configurations. By example, being a switch, it can be in the closed or open state.
  • the configuration of the function is the set consisting of the configuration of each resource.
  • observable or simply observable variables The variables of the mechatronics system that are likely to be observed and tested by the garage mechanic are hereinafter referred to as observable or simply observable variables.
  • the functional observables are the abstractions of a physical variable, directly apprehensible by the mechanic. For example, a speed of rotation of the wiper blades whose signal is a sinusoid can be translated into functional observation by a two-parameter information, namely the brushes are in motion, or the brushes are at the same time. stop.
  • the parameter-type observables are all the parameters that can be obtained directly by means of a diagnostic tool connected to a diagnostic socket of the vehicle.
  • observables of the physical quantities type are all the physical quantities that can be measured on a controlled system, that is to say on physical components. These physical measurements can for example be electrical, such as potential measurements, hydraulic measurements, pressure measurements, etc.
  • the diagnostic method according to the invention involves carrying out one or more tests on one or more observables of a function of which a malfunction has been detected.
  • a test is the observation of an observable in a configuration of the given function. It is therefore a couple (observable, configuration).
  • test Ti is initially chosen by the mechanic. The choice of this test to be performed may be left to the initiative of the garage owner, or be guided by an algorithm determining the relevance of a particular test based on previous functional observations.
  • a first test time signal corresponding to an observable O i in a configuration of the sensor is collected either by means of a diagnostic test, or by measurement of physical quantities, or by means of a functional observation. given system C i .
  • This test must be performed for a certain time. Its duration must be of the order of magnitude of twice the maximum period of periodic phenomena that exist in the system, and greater than the duration of all the transients.
  • This first test time signal is then compared to a set of reference time signals present in a table or matrix of signatures M, represented to the figure 1 .
  • These reference time signals which can be generated by simulation as described below, also have durations of the order of magnitude of twice the maximum period of periodic phenomena that exist in the system in order to be able to compare signals having substantially the same duration.
  • the signature table M or modality table, associates a signature with each of the modes of operation, namely the mode of good functioning and all the anticipated malfunction modes, the observables of the function studied in each of their different configurations. .
  • Each reference signal M ij is representative of an equivalence class, also called modality and also designated by the reference M ij, which groups by resemblance a certain number of individual signature time signals.
  • These individual signature signals are the true signatures of the different modes of operation of the observables in the different configurations of the function.
  • These individual signature signals are obtained preferably by simulation of the different functions to be diagnosed, according to a method which will be described below.
  • the same reference signal M 11 constitutes the signature of the operating mode F0 for the observable O1 in a configuration C0 and that of the operating mode F2 for the observable O1 in the same configuration C0.
  • an observable can have the same reference signal or equivalence class M ij, for several different operating modes in a given configuration.
  • the set of suspicious operating modes at a given moment of the diagnostic session that is to say the good functioning F0 or the malfunctions F1, F2 or F3 in the case of figure 1 .
  • all modes of operation are suspect. This is the set of total ambiguity.
  • test time signal collected during the test performed by the garage mechanic is compared with the reference signals contained in the signature table M for this test Ti to determine by resemblance to which equivalence class belongs this test signal.
  • This similarity determination can be made by an algorithm such as the Dynamic Time Warping (DTW) algorithm, or visually by the garage mechanic, as described hereinafter.
  • DTW Dynamic Time Warping
  • the selected reference signal corresponds to a class of equivalence specific to only one of the modes of operation of the observable in the tested configuration, said operating mode Fi is directly identified.
  • the selected test is T1 and the signal corresponds to the modality M12 the diagnosis stops because the set of ambiguity is only ⁇ F1 ⁇ . In the same way if the signal corresponds to M13, then the ambiguity set is ⁇ F3 ⁇ . And the diagnosis stops on this fault.
  • the equivalence class selected from the test signal is common to several modes of operation, a new test must be performed to determine which of these modes of operation is to be retained. More generally, when the ambiguity set contains more than one operating mode, other tests must be carried out. For example, as shown in figure 1a , if for the T1 test the reference signal selected corresponds to the equivalence class M 11 , the operating modes can be F0 and F2. The ambiguity set is then ⁇ F0, F2 ⁇ . The diagnosis must continue, it is then necessary to carry out a new test, different from the previous test.
  • This new test may relate to an observable different from that tested previously, or may relate to the same observable in a different configuration.
  • the choice of this new test to be carried out can be left to the initiative of the mechanic, or be guided by an algorithm determining the relevance of this or that test based on the previous test and results found.
  • a second test time signal T i representative of an observable of said function, is collected in a given configuration. This second time signal is then compared with the reference signals present in the signature table for the modes of operation of the observable in the configuration which is that of the test.
  • This resemblance determination can be made by an algorithm such as the DTW (Dynamic Time Warping) algorithm, or visually by the garage mechanic.
  • DTW Dynamic Time Warping
  • the ambiguity set is ⁇ F0, F2 ⁇ .
  • the T2 test of the same observable in the C1 configuration led to select the equivalence class M 23, then the ambiguity set is only ⁇ F2 ⁇ .
  • the sequence M 11, M 23 is specific to the F2 malfunction mode of the observable 01. A malfunction is identified, the diagnosis can stop.
  • the diagnostic method described above can be implemented by means of a diagnostic tool such as that shown in FIG. figure 2 .
  • this diagnostic tool 2 is in the form of a laptop, easily transportable by the garage to the vehicle on which it must intervene.
  • this diagnostic tool 2 comprises a computer 4 and at least one memory 6, in which the signature table M is stored. It further comprises man-machine interface means such as a keyboard 8 and display means 10.
  • the diagnostic tool 2 also comprises means 12 for acquiring variables of the mechatronic system of the vehicle, namely a circuit diagnostic electronics 14 having a diagnostic socket (not shown) that can be connected to a diagnostic socket complementary to a motor vehicle and an electronic circuit for measuring physical quantities 16, for example a voltage or a hydraulic pressure also provided with appropriate sensor means (not shown)
  • the diagnostic electronic circuit and the electronic measuring circuit are connected by connection means 18 appropriate to the computer 4.
  • the electronic diagnostic circuit 14 and the electronic measurement circuit 16 may physically separated from the computer or in the form of integrated electronic cards.
  • the computer 4 controls the acquisition means 12 to acquire the test time signal.
  • the computer 4 is adapted to allow simultaneous display, on the display means 10, on the one hand of the test time signal collected, and on the other hand of all the reference associated with this test given in the signatures table.
  • This simultaneous display allows the mechanic to visually compare these time signals and determine itself which reference signal has the greatest resemblance to the test signal collected. Because they correspond to equivalence classes, the reference signals are limited in number so that they are distinguished from each other by characteristic forms freed from certain singularities, which facilitates their comparison with the signal of test and ranking it in one of several equivalence classes.
  • the computer 4 is programmed to make the comparison of the first test time signal collected with the set of reference signals corresponding to said test in the signature table M, and to determine which equivalence class belongs to the first time signal of test.
  • the diagnostic tool 2 If the comparison between the first time signal and the reference signals results in an equivalence class specific to one of the malfunction modes associated with the test, the diagnostic tool 2 signals the operator by the display means 10 what is the malfunction is identified. Otherwise the tool signals the operator that a new test must be performed.
  • the new test may be chosen manually by the operator or proposed by the computer 4 by a calculation of local or overall optimization of the choice of the test.
  • the computer 4 can be advantageously programmed to determine what is the sequence of tests to be implemented to perform with a minimum cost the diagnosis of the system function. This determination can be made using an algorithm that uses the signature table as input, and also takes into account information such as intrinsic test costs, configuration change costs, instrumentation costs, or still the probabilities of malfunctions.
  • a local optimization of the choice of the test that is to say, decide which is the next best test, can be set up and updated after each test carried out by the mechanic.
  • a second solution may be the establishment of a graph forming a general tree of tests, and a search algorithm in this graph, for the overall optimization of the choice of tests.
  • the sequence of equivalence classes selected during the successive tests is updated and stored at least until a diagnosis is obtained.
  • a list of future tests in order of relevance may be presented to the garage on the display means 10, without the garage owner being forced into his choice. If the recommended test is a functional observation to be made by the garage, it can use the keyboard 8 to enter the calculator 4 the result observed visually.
  • the method for constructing, for a given function, the signature table or matrix by modeling and simulation of this function will now be described.
  • the construction of the signature table requires, first of all, a modeling of all the resources (UEC, networks, physical and electronic components) necessary for the realization of a function of the mechatronic system.
  • the principle of modeling consists of an approach based on models of the whole function. It breaks down into a controlled system and a control system.
  • Two types of modeling are implemented for a mechatronic system, a causal modeling of the control system and an acausal modeling of the controlled system.
  • the controlled system be it electronic, mechanical, hydraulic or thermal, for example, is modeled in an acausal way by the equations of the physics of the corresponding domain.
  • the acausal modeling takes into account two types of information, the structural knowledge of the controlled system, and the behavioral knowledge of each physical component of this controlled system, in the various modes of operation, both in a mode of good functioning and in a mode malfunction.
  • the components are interconnected with acausal ports.
  • these ports are the pins of the component.
  • the ports are the sharing points of the flow and effort variables, for example, for the electronics, the intensity of the current I which crosses the port and the potential U at the port level.
  • the equations of structure must be considered as equations shared between two dipoles, and the behavioral equations as equations specific to each dipole. In the present case, the modeling of a resistance results in four equations and four variables.
  • the two behavior equations correspond to a particular mode of operation, the proper functioning. It is also necessary to integrate the operation of the component for anticipated malfunction modes. At the same time, the structure equations remain the same for all modes of operation.
  • the behavior of each component is modeled by a hybrid two-level controller.
  • the first level corresponds to the mode of operation and the different modes of malfunction.
  • the transitions between the operating mode and a malfunction mode represent the expected failures for the component, for example a gate relay. In the modeling described, only the permanent malfunctions are considered, and the transitions from a malfunction mode to the operating mode are therefore not taken into account. At each transition is associated a condition, for example for the relay the intensity that exceeds a threshold.
  • the second level will describe each mode of the first level by an automaton.
  • a controlled switch will have a mode of operation that will be described by a two state machine, passing and blocked.
  • the transition condition between these two states is related to a control signal cmd.
  • the model of the switch can thus be represented by the figure 7 .
  • the signal cmd is a causal signal that determines the sub mode to use, closed or open.
  • a first malfunction Fi corresponds to the switch blocked in open circuit
  • a second malfunction Fii corresponds to the open switch in closed circuit.
  • the control system is modeled in a causal manner with, among other things, finite state machines for the software parts. In addition, it is taken into account that certain physical components of the controlled system may have a causal input.
  • the observables of this causal modeling will be variables accessible by the garage mechanic via the diagnostic socket of the vehicle.
  • the implementation of the obtained model is performed on a hybrid and multi-physics simulator.
  • This simulation can be based on the Modelica language, which can be found in the article P. Fritzson, "Principles of Object-Oriented Modeling and Simulation with Modelica” (Wiley-IEEE Computer Society Pr, 2003, ISBN 0471471631 ).
  • Such a simulator may be for example the Dymola environment (Dynasim company, Dassault Systèmes).
  • the construction of the signature table for a function involves simulating this function in the operating mode, and in the various malfunction modes anticipated, for all the possible configurations of the observable N o of the function.
  • N f is the number of anticipated malfunctions in the physical components and the control part
  • N c is the number of configurations different, and knowing that for each configuration it is also necessary to simulate the good functioning, it will be carried out a number of different simulations equal to (N f +1) x N c .
  • An individual signature time signal is generated for each given observable Oi in each of its given configurations Ci and each of its anticipated operating modes Fi, namely a mode of operation and one or more modes of malfunction.
  • the collected individual signature time signal can thus take the form of one of N f + 1 different curves.
  • Each simulation must be performed for a certain duration.
  • This duration must be of the order of magnitude of twice the maximum period of periodic phenomena that exist in the system, and greater than the duration of all the transients.
  • the duration is of the order of 20 seconds.
  • the individual signature time signals are compared with one another, advantageously by a signal resembling algorithm, and then these individual signature signals are grouped, according to their resemblance, into a plurality of equivalence classes or modalities each of which is represented by a reference signal.
  • a signal comparison algorithm determines the resemblance between two signals, and groups them together if the similarity is proven.
  • the DTW algorithm (Dynamic Time Warping) can be used.
  • this algorithm for information on this algorithm, for example, in the article of H. Sakoe and S. Chiba, "Dynamic Programming Algorithm Optimization for Spoken Word Recognition” (IEEE Trans. Acoust., Speech, Signal Processing, Vol 26, No. 1, pp 43-49, Feb 1978 ), or in the article of L. Rabiner and BH Juang, "Fundamentals of Speech Recognition” (Prentice Hall, Upper Saddle River, New Jersey 07458, 1993 ).
  • a reference signal or equivalence class Mij is associated with each of the anticipated modes of operation F i .
  • a reference time signal representative of a first equivalence class must be distinct from the reference temporal signal representative of a second equivalence class, in order to be visually distinguishable by the mechanic. It is the role of the comparison algorithm, which determines the equivalence classes translated into reference signals, to manage this notion of visual tolerance.
  • the modeling and simulation of a given function focuses on observables, that is to say variables that the garage owner or other operator can observe.
  • the signature table is constructed by repeating the simulation operations described above for each of the mechatronics system functions that are likely to be diagnosed.
  • the operating principle of this function is such that the user makes a request for rear wiping by means of a control lever, this request is transmitted to a computer associated with the passenger compartment of the vehicle via a network of CAN type information.
  • the vehicle computer manages the intermittent wiping behavior by applying tension to the wiper motor until information is obtained that the wiper has returned to its idle position. It then suspends the application of the voltage for a few seconds before starting a cycle again.
  • FIG. 3 A first level of modeling is illustrated at the figure 3 .
  • This figure shows the computer 31 associated with the control lever and the computer of the cockpit 32, interconnected by a CAN bus 33.
  • the computer dedicated to the passenger compartment 32 is connected to a power source 34, beam connectors 35, wires 36 and the rear wiper means 37 consisting of the engine and the mechanical part of the wiping of the rear window.
  • the figure 4 illustrates a second level of modeling, namely the model of the cabin calculator 32 mentioned above.
  • This figure shows the control software 41 of the rear wiping function, the power electronics elements 42, and the software 43 for testing the motor of the wiping means.
  • the power electronics elements include among others a fuse 44, a protection resistor 45 and a switch 46.
  • the modeling of the purely software control part 41 of the cabin computer 32 is illustrated in the form of a finite state machine at the figure 5 , on which the squares represent states and the bars of the transitions between these states.
  • the first state E0 corresponds to a state where the rear window wiper function can not be activated because the vehicle contact has not been closed by means of the ignition key.
  • the first transition T1 corresponds to the information that the ignition key has been rotated and the ignition of the vehicle closed.
  • the next state E1 corresponds to the state of closure of the contact by the ignition key.
  • the transition following T2 corresponds to a request for scanning the rear window at low speed made by the user of the vehicle.
  • the state E2 is the one in which there is scanning of the rear window at low speed.
  • the following transition T3 is representative of a "fixed stop" information provided by a sensor for detecting the angular position of the blade, to stop it when it has returned to its initial position.
  • the state E3 corresponds to the rest position of the blade after one go and a return of it on the window.
  • the transition T4 represents the information provided by a timer to go to the scanning state after the lapse of a predetermined time, for example 12 seconds.
  • the transition T4 leads to the input of the state E2 which is the scanning state.
  • the transition T5 connected to the output of the state E2 corresponds to a command provided by a timer in order to cut off the power supply of the electric scanning motor if the wiper blade has been in a sweeping state for more than 7 seconds.
  • the state E4 is a state of protection of the motor in which the latter is no longer electrically powered.
  • the transition T6 between the output of E4 and the input of E2 corresponds to a command delivered by a timer to trigger the scanning again after a determined time, for example 30 seconds, after the scanning engine has been found put in the state of protection E4.
  • the transition T7 between the output of the state E4 and the input of the state E1 corresponds to a command from the user to end the scanning at low speed.
  • transition T8 between the output of E2 and the input of E1 and the transition T9 between the output of E3 and the input of E1 also correspond to a command by the user to interrupt the scanning at low speed.
  • transition T10 between the output of E1 and the input of E0 corresponds to the breaking of the contact of the vehicle by the user by means of the ignition key.
  • the figure 6 is an example of global multi-acausal model of the electric motor part and linkage of the wiping function of the rear window, which incorporates electronic, electromechanical and mechanical components.
  • the electrical part of the motor is represented by an inductor 60 in parallel with a resistor 61 which represents the ohmic value of this inductance.
  • the inductor 60 is shown connected in series by one of its terminals with a resistor 62 and a wire 63 connected to an acausal port P3 representing a pole of a power supply.
  • the other terminal of the inductor 60 is connected to the port P2, which constitutes the other pole of the power source, via a component 64 constituting an "electrical-mechanical transformer", and a a fixed switch 65 controlled by a sensor (modeled by the component 68) which detects the return of the brush in the vicinity of its starting position.
  • the sensor closes the switch 65 whose terminal opposite to the port P2 is connected to a port P1 via a wire 66.
  • the current flow in the port loop P1, switch 65, wire 66, port P2 is detected by the cockpit computer 32 to interrupt the scanning as illustrated by the state E3 of the figure 5 .
  • the component 64 represents the transformation of a current that passes through a mechanical movement of continuous rotation.
  • the component 67 connected to the component 64 illustrates the reciprocating transformation of the continuous rotational movement at the output of the component 64.
  • This component 67 can be represented in the form of a two-state hybrid automaton and two transitions.
  • the component 68 corresponds to a modeling of the aforementioned mechanical sensor which detects the angle of rotation of the wiper blade and closes the switch 65 when its angular position relative to the rest position becomes lower than a given threshold. .
  • the component 69 represents a model of the insulator between the wires leading to the ports P2 and P3 and corresponds in normal operation to an open circuit, and to a closed circuit in the event of a short circuit.
  • the model of the rear screen wiper function is thus carried out in a hierarchical manner, the function is successively decomposed down to the elementary components.
  • an illustration of the modeling in graphical form not in the form of equations. But, of course, it is these equations available to those skilled in the art using modeling tools (Modelica) that make it possible to generate by simulation the temporal signals of individual signature of the observable variables.
  • results matrix of the figure 8 illustrates the temporary signals of individual signature that are obtained by simulation, thanks to the model which has just been described above with regard to Figures 3 to 6 , for the rear windscreen wiper function.
  • the lines V1, V2 and V3 of the matrix correspond to signals which are present at the terminals V1, V2 and V3 at the input of the wiping motor ( figure 3 ), for different modes of operation which will be detailed below.
  • the "stop-fixed" line corresponds to a parameter of the passenger compartment computer relating to the circulation or non-circulation of a current in the loop P1, 66, 65, P2 as described above with respect to the figure 6 .
  • this parameter will be read by the diagnostic tool using the diagnostic socket of the vehicle.
  • CMB_PV_AR is also a parameter that reflects the fact that the cockpit computer 31 controls or not the electric motor 37 of the windscreen wiper system.
  • the line "brush speed” shows as a time signal the speed of the brush or brooms in a number of operating modes. During a diagnosis, this observable corresponds to a functional observation made by the mechanic and returned by him in the diagnostic tool in the form of information.
  • the column I46.RC corresponds to a malfunction according to which the cockpit calculator sees the switch 46 of the figure 4 permanently closed, that is to say it remains glued.
  • the FIL 36 1 .CO column means that the wire 36 1 of the figure 3 is in open circuit.
  • the following column FIL 36 2 .CO corresponds to the malfunction according to which the wire 36 2 of the figure 3 is in open circuit.
  • the column 31.VR Cal corresponds to the situation in which the outgoing command of the computer 31 always remains in the state "true", that is to say a control state.
  • the matrix of the figure 8 shows at each intersection of a row and a column the individual signature time signal, generated by simulation using the appropriate equations, which is obtained for the relevant variable in the relevant operating mode.
  • a modality mo_ii is associated with each of the rows and columns of the matrix, the modalities being identical in the same row when the temporal signals of individual signatures obtained in the result matrix of the matrix. figure 8 have been considered sufficiently similar.
  • the realism of the reference signals generated by modeling and simulation depends on the degree of abstraction of the modeling of the function.
  • this abstraction the higher this abstraction, the more the shape of these signals is moving away from that of the real signals that can be found on the mechatronic system.
  • the "brush speed" signal in the BF mode of the matrix of the figure 8 corresponds to a relatively idealized modeling of the function.
  • it would be appropriate to introduce into the model as is well known to those skilled in the art, a certain number of components that make it possible to take into account additional phenomena of an electrical nature, mechanical or other such as, for example, inertia, friction, etc. of the set of brooms and linkage.
  • the choice of the degree of abstraction is a question of compromise between the complexity of the model and the minimum of realism of the signals considered necessary to allow the operator to implement the diagnosis.

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EP20100306490 2009-12-23 2010-12-22 Diagnoseverfahren einer Störung eines Mechatroniksystems Not-in-force EP2339318B1 (de)

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FR0959513A FR2954496B1 (fr) 2009-12-23 2009-12-23 Procede de diagnostic d'un disfonctionnement d'un systeme mecatronique

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Cited By (2)

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CN108153285A (zh) * 2017-12-28 2018-06-12 上汽通用五菱汽车股份有限公司 汽车安全监控方法、装置、存储介质及系统
DE102018121270A1 (de) * 2018-08-31 2020-03-05 Volkswagen Aktiengesellschaft Diagnoseverfahren, Diagnosesystem und Kraftfahrzeug

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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108153285A (zh) * 2017-12-28 2018-06-12 上汽通用五菱汽车股份有限公司 汽车安全监控方法、装置、存储介质及系统
CN108153285B (zh) * 2017-12-28 2020-12-15 上汽通用五菱汽车股份有限公司 汽车安全监控方法、装置、存储介质及系统
DE102018121270A1 (de) * 2018-08-31 2020-03-05 Volkswagen Aktiengesellschaft Diagnoseverfahren, Diagnosesystem und Kraftfahrzeug
US11354945B2 (en) 2018-08-31 2022-06-07 Volkswagen Aktiengesellschaft Diagnostic method, diagnostic system and motor vehicle
DE102018121270B4 (de) 2018-08-31 2023-12-21 Volkswagen Aktiengesellschaft Diagnoseverfahren, Diagnosesystem und Kraftfahrzeug

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EP2339318B1 (de) 2013-08-21
FR2954496A1 (fr) 2011-06-24

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