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WO2018178196A1 - Procédé de détermination d'une incertitude de mesure d'endommagement d'un véhicule automobile - Google Patents

Procédé de détermination d'une incertitude de mesure d'endommagement d'un véhicule automobile Download PDF

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Publication number
WO2018178196A1
WO2018178196A1 PCT/EP2018/058009 EP2018058009W WO2018178196A1 WO 2018178196 A1 WO2018178196 A1 WO 2018178196A1 EP 2018058009 W EP2018058009 W EP 2018058009W WO 2018178196 A1 WO2018178196 A1 WO 2018178196A1
Authority
WO
WIPO (PCT)
Prior art keywords
uncertainty
damage
motor vehicle
determined
evaluation step
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.)
Ceased
Application number
PCT/EP2018/058009
Other languages
German (de)
English (en)
Inventor
Rafael Fietzek
Stéphane Foulard
Stephan Rinderknecht
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.)
Technische Universitaet Darmstadt
Original Assignee
Technische Universitaet Darmstadt
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 Technische Universitaet Darmstadt filed Critical Technische Universitaet Darmstadt
Priority to DE112018001704.4T priority Critical patent/DE112018001704A5/de
Publication of WO2018178196A1 publication Critical patent/WO2018178196A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Classifications

    • 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
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/20—Pc systems
    • G05B2219/26—Pc applications
    • G05B2219/2637—Vehicle, car, auto, wheelchair
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0243—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model
    • G05B23/0254—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model based on a quantitative model, e.g. mathematical relationships between inputs and outputs; functions: observer, Kalman filter, residual calculation, Neural Networks
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
    • G05B23/0283—Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL]

Definitions

  • the invention relates to a method for determining a damage degree uncertainty of a motor vehicle, wherein in a determining step during operation of the
  • Damage measure of the component is determined.
  • a first evaluation step one or more features that have a comparatively high correlation with a damage of the component (for example, so-called condition monitoring and / or condition prediction methods) are first determined in a first evaluation step. Subsequently, these features are processed in a further evaluation step with a previously determined mathematical model and determined in this way the damage measure.
  • the mathematical model is usually using appropriate
  • the vehicle parameters can either be determined directly in the determination step by suitable measuring devices or can be determined on the basis of mathematical models, for example between measurement information determined by different measuring devices.
  • Engine provided torque by a mathematical model in dependence on a metrologically detected engine speed and a predetermined by a control unit of the motor vehicle target injection quantity determine.
  • a mathematical model in dependence on a metrologically detected engine speed and a predetermined by a control unit of the motor vehicle target injection quantity determine.
  • Determining the degree of damage results, for example, from unavoidable manufacturing tolerances, inter alia due to fluctuating material quality and differences between the respective production equipment used in the production of the component.
  • An object of the invention is to provide a method for determining a damage measure uncertainty, which defines the damage measure uncertainty first and then continuously by the inclusion of further
  • This object is achieved in that based on predetermined parameter uncertainties
  • Damage measurement uncertainty represents a measure of the fact that the component has actually suffered a damage corresponding to the determined damage level.
  • the parameters directly influencing the operation of the motor vehicle are also variables which influence the operation of the motor vehicle, for example the respective ambient temperature and current weather data.
  • the determined value corresponds to the actual value or that the actual value lies in a certain value range around the determined value.
  • the uncertainty measures each bound a range of values within which the true value of the observed
  • Size such as a metric with a
  • the measure of uncertainty is a measure of whether the
  • the damage measurement uncertainty is determined by the
  • the measure of injury inaccuracy represents a measure, namely a measure of the probability of determining whether the damage identified is actually the case
  • the method according to the invention provides for the parameter uncertainty quantities and / or functions and / or the evaluation step uncertainty quantities and / or functions each by one
  • Probability density function is. With the aid of a probability density function, a probability can be determined by integration that the respectively determined motor vehicle parameter or the variable determined in the respective evaluation step actually corresponds to a corresponding real variable. On the basis of the known probability density functions can also be a common
  • Likelihood density function can be specified, in which the various uncertainties in the determination of the vehicle parameters and in the
  • Probability density functions can, for example, under the assumption of a normal distribution in the determination of the vehicle parameters and the variables determined in the respective evaluation steps by a
  • the invention provides that, starting from the damage measure and the Damage probability uncertainty a default probability for predefined points in time in the future of the component is determined, whereby the probability of failure for each time is a measure of the fact that the component will fail at this time. From the state of
  • a load collective is determined in a load collective evaluation step with the determined motor vehicle parameter.
  • a time profile of a torque load of a motor vehicle operation can be mapped in the load collective.
  • the invention provides that the damage measure in an accumulation evaluation step is determined by a linear damage accumulation using a Wöhler curve determined in advance for the component.
  • a dispersion of the Wöhler curve can be achieved by accumulation evaluation results and / or functions
  • uncertainty variables or functions used for the accumulation evaluation step in the determination of the damage uncertainty can be taken into account that a temporal course of load changes acting on the component is not taken into account when determining partial damages based on the Wöhler curve time course basically has an impact on the actual injury, but off
  • the invention provides that the determined damage measure and the
  • Damage measurement uncertainty in a diagnostic system for example, using condition monitoring and / or
  • the damage measurements and damage uncertainties determined from a damage calculation can be used particularly advantageously to determine a faulty or damaged component which has led to a detected fault condition in the context of an error detection on the basis of fault detection functions.
  • the invention provides that, when determining the probability of failure, results of a diagnostic system of the motor vehicle are taken into account.
  • Errors and causes of errors from a diagnostic system in the determination of the probability of failure can be taken into account certain events that are not taken into account when determining the damage uncertainty.
  • the invention provides that the determined damage dimensions and the associated
  • Automotive parameters and / or the load collectives are transmitted to a central database. According to the invention, it is provided that the parameter uncertainty variables and / or functions and / or the
  • Car fleet transmitted data centrally determined and subsequently transferred as required to individual vehicles.
  • the parameter uncertainty variables and / or functions and / or the evaluation step uncertainty variables and / or functions are determined and continuously minimized with the aid of machine learning algorithms.
  • the parameter uncertainty quantities and / or functions and / or the evaluation step uncertainty variables and / or functions can be processed and minimized particularly efficiently on the basis of the large data volumes transmitted to the database.
  • Automotive parameters and / or the load collectives are then transmitted to the central database if the associated component has failed unexpectedly or has caused an error or if the component is not
  • the data is then transmitted to the database if the probability of default for
  • Default probability limit is or if the
  • Failure probability limit is and the component has either failed or caused an error.
  • Figure 1 is a schematically illustrated flow of the
  • FIG. 1 schematically shows the sequence of a method 1 for determining a damage measure uncertainty
  • a transmission 5 of the motor vehicle 3 is determined acting torque continuously calculated. This continuously calculated
  • Torque represents a motor vehicle parameter 6.
  • a load collective 8 acting on the transmission is first of all calculated in a load collective evaluation step 7.
  • a damage measure 11 is determined by linear damage accumulation using a Wöhler curve 10 determined beforehand for the transmission.
  • a torque parameter uncertainty 13 determines that the determined torque actually a real on the
  • Torque parameter uncertainty 13 is particularly dependent on an absolute value of the torque, since the
  • Damage measure 11 a residual life or a
  • calculated failure time corresponds to a real failure time, a default probability determined.
  • Partial damage measurements AD (t) 20 determined. Amongst other things Due to measurement uncertainties relevant vehicle parameters (F) 21 for determining the Part collapsesrune not accurate, but for example with
  • Uncertainties of measurement are detected.
  • the respective measurement uncertainty is determined by a
  • This parameter uncertainty quantity or function (P (F (t)) 12 can narrow a range of values within which the true or actual value of the observed
  • Partial damage uncertainty (P (AD (t))) 22 can be determined. On the basis of the partial damage dimensions (AD (t)) 20 and the partial damage uncertainties (P (AD (t))) 22, the damage measure (D) 11 and a
  • data 23 of each vehicle under consideration is transmitted to a central database 24 where it is augmented with metadata 25 such as weather conditions at the different times (ti, t 2 , t) 19 at the locations where the respective vehicle is different Time points (ti, t 2 , t 3 ) 19 has found.
  • the method can advantageously be expanded in such a way that recorded, actual failures of a component based on the determined damage measure 11 and the damage uncertainty 18 are compared with the predicted failure of the component.
  • Self-learning algorithms 26 can use this information
  • the parameter uncertainty variables or functions (P (F (t)) 12 and also evaluation step uncertainty variables and / or functions and / or the damage uncertainty 18 and / or the partial damage uncertainties 22 are improved in such a way that a more accurate prognosis is made possible ,

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
  • Control Of Electric Motors In General (AREA)

Abstract

L'invention concerne un procédé (1) de détermination d'une incertitude (18) de mesure d'endommagement d'un composant d'un véhicule automobile (3). Dans une étape de détermination (2), les paramètres du véhicule automobile (6) sont déterminés en permanence à des intervalles de temps prédéterminés pendant le fonctionnement du véhicule (3) sur la base d'informations de capteur et d'état de conduite (4, 5) disponibles dans le véhicule automobile respectif (3). Les paramètres du véhicule automobile (6) sont ensuite traités dans une étape d'évaluation ou dans plusieurs étapes d'évaluation (7, 9), parallèles et/ou successives, et une mesure (11) d'endommagement du composant est déterminée. Une incertitude de mesure d'endommagement (18) est déterminée sur la base de grandeurs et/ou de fonctions d'incertitude de paramètre (12) prescrites qui représentent une mesure d'incertitude pour chaque paramètre de véhicule automobile (6) déterminé, le paramètre de véhicule automobile (6) déterminé correspondant à un paramètre de véhicule réel (6), et sur la base de grandeurs et/ou de fonctions d'incertitude d'étape d'évaluation (14, 15) prescrites, des grandeurs d'incertitude d'étape d'évaluation prises en compte dans l'étape d'évaluation respective et indépendante des paramètres de véhicule (6) correspondant aux grandeurs d'incertitude d'étape d'évaluation réelles. L'incertitude de mesure d'endommagement (18) représente une mesure pour laquelle le composant a effectivement subi un endommage correspondant à la mesure d'endommagement déterminé (11).
PCT/EP2018/058009 2017-03-30 2018-03-28 Procédé de détermination d'une incertitude de mesure d'endommagement d'un véhicule automobile Ceased WO2018178196A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
DE112018001704.4T DE112018001704A5 (de) 2017-03-30 2018-03-28 Verfahren zur Bestimmung einer Schädigungsmaßunsicherheit eines Kraftfahrzeugs

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102017106919.4A DE102017106919A1 (de) 2017-03-30 2017-03-30 Verfahren zur Bestimmung einer Schädigungsmaßunsicherheit eines Kraftfahrzeugs
DE102017106919.4 2017-03-30

Publications (1)

Publication Number Publication Date
WO2018178196A1 true WO2018178196A1 (fr) 2018-10-04

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PCT/EP2018/058009 Ceased WO2018178196A1 (fr) 2017-03-30 2018-03-28 Procédé de détermination d'une incertitude de mesure d'endommagement d'un véhicule automobile

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Country Link
DE (2) DE102017106919A1 (fr)
WO (1) WO2018178196A1 (fr)

Cited By (1)

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LU101181B1 (de) 2019-04-12 2020-10-12 Compredict Gmbh Verfahren zur Bestimmung einer Belastungsvorhersage für ein Bauteil eines Kraftfahrzeugs

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WO2022223565A1 (fr) * 2021-04-20 2022-10-27 Robert Bosch Gmbh Dispositif et procédé, en particulier procédé mis en œuvre par ordinateur, permettant de réaliser un test
DE102021205838A1 (de) 2021-06-10 2022-12-15 Robert Bosch Gesellschaft mit beschränkter Haftung Verfahren und Vorrichtung zur Abschätzung der Lebensdauer eines tribologisch beanspruchten Bauteils und Computerprogrammprodukt

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DE10215865A1 (de) * 2002-04-11 2003-11-06 Bosch Gmbh Robert Verfahren und Steuergerät zur Ermittlung der Ausfallwahrscheinlichkeit einer Kraftfahrzeugkomponente
US8725456B1 (en) * 2009-05-05 2014-05-13 The United States of America as represented by the Administrator of the National Aeronautics & Space Administration (NASA) Decomposition technique for remaining useful life prediction

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
LU101181B1 (de) 2019-04-12 2020-10-12 Compredict Gmbh Verfahren zur Bestimmung einer Belastungsvorhersage für ein Bauteil eines Kraftfahrzeugs
WO2020208182A1 (fr) 2019-04-12 2020-10-15 Compredict Gmbh Procédé de détermination d'une prédiction de charge pour un élément d'un véhicule à moteur
US12044598B2 (en) 2019-04-12 2024-07-23 Compredict Gmbh Method for determining a load prediction for a component of a vehicle

Also Published As

Publication number Publication date
DE102017106919A1 (de) 2018-10-04
DE112018001704A5 (de) 2019-12-19

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