WO2018065223A1 - Procédé et dispositif pour déterminer un état de détérioration d'un composant d'un véhicule - Google Patents

Procédé et dispositif pour déterminer un état de détérioration d'un composant d'un véhicule Download PDF

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Publication number
WO2018065223A1
WO2018065223A1 PCT/EP2017/073852 EP2017073852W WO2018065223A1 WO 2018065223 A1 WO2018065223 A1 WO 2018065223A1 EP 2017073852 W EP2017073852 W EP 2017073852W WO 2018065223 A1 WO2018065223 A1 WO 2018065223A1
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WO
WIPO (PCT)
Prior art keywords
variable
determined
component
behavioral
influencing
Prior art date
Application number
PCT/EP2017/073852
Other languages
German (de)
English (en)
Inventor
Liv Proenneke
Stephan Rittler
Original Assignee
Robert Bosch 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 Robert Bosch Gmbh filed Critical Robert Bosch Gmbh
Publication of WO2018065223A1 publication Critical patent/WO2018065223A1/fr

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Classifications

    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D41/00—Electrical control of supply of combustible mixture or its constituents
    • F02D41/22—Safety or indicating devices for abnormal conditions
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D41/00—Electrical control of supply of combustible mixture or its constituents
    • F02D41/02—Circuit arrangements for generating control signals
    • F02D41/14—Introducing closed-loop corrections
    • F02D41/1401—Introducing closed-loop corrections characterised by the control or regulation method
    • F02D2041/1412—Introducing closed-loop corrections characterised by the control or regulation method using a predictive controller
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D41/00—Electrical control of supply of combustible mixture or its constituents
    • F02D41/22—Safety or indicating devices for abnormal conditions
    • F02D2041/224—Diagnosis of the fuel system
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D41/00—Electrical control of supply of combustible mixture or its constituents
    • F02D41/24—Electrical control of supply of combustible mixture or its constituents characterised by the use of digital means
    • F02D41/26—Electrical control of supply of combustible mixture or its constituents characterised by the use of digital means using computer, e.g. microprocessor
    • F02D41/28—Interface circuits
    • F02D2041/286—Interface circuits comprising means for signal processing
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D2200/00—Input parameters for engine control
    • F02D2200/02—Input parameters for engine control the parameters being related to the engine
    • F02D2200/06—Fuel or fuel supply system parameters
    • F02D2200/0602—Fuel pressure
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D2200/00—Input parameters for engine control
    • F02D2200/02—Input parameters for engine control the parameters being related to the engine
    • F02D2200/06—Fuel or fuel supply system parameters
    • F02D2200/0606—Fuel temperature
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D41/00—Electrical control of supply of combustible mixture or its constituents
    • F02D41/30—Controlling fuel injection
    • F02D41/38—Controlling fuel injection of the high pressure type
    • F02D41/3809—Common rail control systems
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/10—Internal combustion engine [ICE] based vehicles
    • Y02T10/40—Engine management systems

Definitions

  • the invention relates to a method for determining a damage state of a component of a vehicle, and to a computer program and a control and / or regulating device for carrying out the method and to a machine-readable storage medium on which the computer program is stored.
  • the method with the features of independent claim 1 has the advantage that a forecast of an error can be made very reliable.
  • the invention in a first aspect, relates to a method for determining a damage state of a component, in particular of a vehicle, in which at least one behavioral quantity of the component, ie a parameter characterizing the behavior of the component, is determined and in which at least one influencing variable of the behavioral variable, ie a the behavior of
  • Component influencing size is determined, and is determined depending on a change in the at least one behavioral variable compared to a reference value of the at least one behavioral variable as a function of the influencing variable of the damage state.
  • the term "as a function of the influencing variable” here means that all other influencing variables are kept constant within specifiable limits, or that only those measured values are selected in which all other influencing variables lie within predefinable limits This is a particularly simple implementation
  • the damage state is determined as a function of whether the change in at least one of the modifications is determined by a change value Behavioral size for preferably all, in particular all determined, values of the influencing variable above an influence variable threshold value exceeds the predefinable change threshold value.
  • This method becomes particularly accurate if the damage state is determined as a function of whether the change in the at least one behavior variable for preferably all, in particular all, determined values of each of the relevant influencing variables above the influencing variable threshold value exceeds the predefinable change threshold value.
  • the respectively remaining relevant influencing variables are kept constant for each of the relevant influencing variables in order to further improve the reliability of the method.
  • Constant means in particular that each of these other relevant influencing variables is kept constant within specifiable limits, or that only those measured values are selected in which each of these other influencing factors lies within specifiable limits.
  • the damage state is determined to be "defective at risk” if the absolute value of the change exceeds the predefinable change threshold, in particular then it can be provided that a warning message is issued. If a defect is diagnosed, a graded warning can be issued that enables adequate countermeasures to be taken.
  • the reference value is a determined new value of the at least one behavior variable, wherein the new value of the at least one behavior variable is determined before a mileage of the vehicle has exceeded a predefinable mileage threshold. Since the determination of the damage state is therefore based not on a theoretical nominal value but on an actual initial value of the relevant specimen of the component, the process becomes particularly accurate.
  • the component is decided that the component is defective if the at least one behavioral variable of the component is outside predefinable limits, in particular by a nominal value of the behavioral variable. In this way, gross errors of the component can be detected particularly easily reliable.
  • a pin-pointing over a temporal reference is possible
  • the damage state of the component is also determined as a function of a number of activations, that is to say in particular activations, of the component.
  • the damage state of the component is determined as a function of whether the number of actuations is greater than a predefinable actuation number threshold value.
  • the method can be implemented in software or hardware or in a hybrid of software and hardware. It can be implemented in a control device, for example in the vehicle, or else on an external device, for example as an app on a smartphone that communicates with a control device of the vehicle, or on a server that communicates with the control device.
  • FIG. 1 shows schematically a vehicle in which the method can be used
  • FIG. 2 shows a flow chart of a possible sequence of the method
  • FIG. 3 shows an illustration of the dependencies of behavioral parameters, influencing variable and reference values
  • FIG. 4 shows an illustration of measurements of a behavior variable as a function of influencing variables
  • FIG. 5 shows an illustration of measurements of a behavior variable as a function of an influencing variable.
  • FIG. 1 shows a motor vehicle 1 with a component, in the concrete example an electric intake valve 30 on a high pressure chamber of a common rail injection system.
  • An array of sensors 20 determines measurements of behavioral quantities, such as an on-time of the suction valve 30.
  • a controller 70 receives this measurement.
  • the method according to the invention can be implemented on the control unit 70, for example as a computer program that is stored on a machine-readable storage medium 71.
  • FIG. 2 shows a flow chart of this method, wherein steps 100, 200 and 300 can take place before a first-time execution of the method and are therefore only optional part of the method.
  • the injection valve is measured or simulatively examined (100).
  • a nominal characteristic Nl and a lower limit Bl and an upper limit B2 are determined (200) and stored in the software (300).
  • the nominal characteristic is determined as a function of factors I, II, III, IV, i. Measuring points are determined, and for each measuring point both the influencing variable and the behavioral variable are determined.
  • the determination of the influencing variables can likewise be effected via the sensor array 20.
  • the behavior of the nominal characteristic N1, an upper limit B2 and a lower limit B1 is illustrated as a function of an influencing variable I1 in FIG.
  • the behavior variables are designated below by the reference symbols A, B, C.
  • an elasticity of a spring can also be determined. It is also possible that the influencing variable is determined by calculation, for example a delivery start angle of the common rail system.
  • the influencing variable is determined by calculation, for example a delivery start angle of the common rail system.
  • an amount of relevant influencing variables I, II, III, IV is defined, as a function of which the behavioral variable A, B, C is determined. This is illustrated in FIG.
  • the relevant influencing variables for the behavioral variable A are the influencing variables I, II, III (FIGS. 3a)
  • the relevant influencing factors for the behavioral variable B are the influencing variables I, II (FIG. 3b)
  • the relevant influencing variables for the behavioral variable C are the influencing variables II, IV ( Figure 3c).
  • the storage of the relationships between behavioral variable A, B, C and relevant parameters I, I I, I I I, IV can be done, for example, in multi-dimensional arrays. It is possible for the characteristic curves N1, B1, B2 to be interpolated by interpolation or by a mathematical fitting method.
  • a behavioral variable A, B, C can be determined, or several.
  • this variable determines how much fuel is delivered to the rail of the common rail system at each stroke of the high-pressure pump.
  • the delivery start angle is u.a. depending on the location of an upper camshaft dead center and is nominally determined for a mid-mounted camshaft.
  • New values N2 of the behavioral variables A, B, C are determined (400) as a function of the respectively relevant influencing variables I, II, II, IV, either directly at the first start of the motor vehicle 1 or after an operating hours limit (eg 50 h), see also FIGS deposited on the storage medium 71 (500).
  • the determination can take place during a regular operation of the motor vehicle 1. It is also possible for the motor vehicle 1 to be operated in a diagnostic mode in order to ensure that the relevant influencing variables I, I I, I I, IV are explored as completely as possible, i. that over the entire possible range of these influencing variables I, I I, II I, IV data points are detected.
  • the characteristic curve N2 is interpolated by interpolation or by a mathematical fitting method.
  • the delivery start angle can be determined for example by means of a high-pressure regulator, namely as the delivery start angle, which fits for this common rail system to a required amount of fuel.
  • Limit B2 lies, and all other measurement points Ml, ... M6, M8, MIO below the upper limit B2.
  • step 1500 follows.
  • step 1000 further measuring points M11, M12, M19 of the behavioral variables A, B, C and the respective relevant influencing variables I, II, III, IV are determined, and the respective deviations Aist of the measuring points from the curve N2 of the new values are determined, specifically separately of each of the relevant influencing variables, see FIG. 5.
  • step 700 it is optionally possible, in addition to the further processing, to branch back to step 700 and to carry out the monitoring there using the further measuring points M11,..., M19 determined in step 1000 instead of the measuring points M1, MIO.
  • step 1200 follows.
  • Step 1200 may also follow, for example, if a behavior as illustrated in FIG. 5 exists for one or each cutting plane SE, for which values of the influencing variable I II above (or alternatively below) an influencing variable threshold value S the deviations Alst leave the specifiable limits ,
  • step 1200 can either take place if the described criteria for one of the relevant influencing variables (in the example of the behavior variable B: I, I II) are fulfilled, but it can also take place only if it is suitable for all of the relevant influencing variables I, III are met.
  • step 1200 it is checked whether the currently determined behavioral variables A, B, C are within the determined limits Bl, B2. If so, step 1300 follows, identifying that component 30 may fail and issuing a corresponding warning to the driver.
  • step 1400 the determined measured values of a data preparation, for example a trend analysis, eg. B. with exponential smoothing. Subsequently, branch back to step 1000.
  • step 1500 it is decided that the respective component 30 is defective and deposits a corresponding entry in a fault memory and / or activates a corresponding drive strategy in order not to load the defective component 30 in a "limp-home" mode.
  • each component 30 associated with the conspicuous behavioral quantity can be identified. Goes from step 1200 to step 1500 branches, but it is also possible to identify the component on the basis of the influencing variables in whose dependence the conspicuous behavior has been shown.
  • the behavioral variable A of the ascertained delivery start angle of the common rail system is associated with the component "electric intake valve”, and the behavior variable C is also the determined delivery start angle, but with the component "chain of the common rail system”. Systems "is associated.
  • step 700 Upon leaving the predetermined limits Bl, B2 will monitor for both components, the monitoring in step 700.
  • the behavioral quantity A is associated with the relevant parameters of fuel temperature (I), rail pressure (II) and the volume flow (III) to be delivered to the rail
  • the monitoring will branch to step 1200 in step 1100 only if the behavioral quantity A is related is conspicuous to these relevant influencing factors.
  • the behavioral quantity C depends on the relevant influencing variables of rail pressure (II) and the position of the upper camshaft dead center (IV), so that the monitoring in step 1100 will branch to step 1200 only if the behavioral quantity C is conspicuous with respect to these relevant influencing variables.
  • branching through steps 1100, 1200 to step 1500 differential determination of the defective component is possible.
  • defect messages of different components are determined in step 1500 and, in addition, the respective number of actuations of the components whose damage state was determined to be “defective.” Depending on the number of these actuations and optionally on a respectively definable actuation threshold value the components whose damage state has been determined to be "defective”, the component whose actual defect is assumed to be the most probable, are selected.
  • This may be, for example, that component whose number of actuations is the lowest, or that component whose quotient of the number of actuations and actuation threshold value is the lowest. This ends the procedure.
  • the presented functionality can be used differently. In systems where the components always have to work safely and are to be replaced after a predefined number of operating hours, this function can help prevent this from occurring and detect a premature failure. In other cases, it can be used to delay component replacement, thereby saving costs. If a component damage is detected, it is possible to switch automatically to an emergency driving function.
  • the presented method is ideally suited for the calculation in a cloud, since in principle only the data per measuring point must be observed and transmitted.
  • the calculation does not have to be time-synchronized and only requires a low sampling rate ("ls to 10 s).
  • the method can continuously observe the behavior of the system or of individual components on the basis of behavior variables and influencing variables and does not require any separately triggered test cycles. Furthermore, trend data can be stored at predetermined time intervals, from which a lifetime characteristic curve can be generated. Therefore, a permanent assessment of damage occurring is possible.
  • the lifetime characteristic curve generated in a cloud of several vehicles with the same component can also be used to be stored in future systems as a nominal characteristic N 1. Therefore, the presented method is suitable for long-term observation.

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  • Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Mechanical Engineering (AREA)
  • General Engineering & Computer Science (AREA)
  • Combined Controls Of Internal Combustion Engines (AREA)

Abstract

L'invention concerne un procédé pour déterminer un état de détérioration d'un composant (30), consistant à déterminer au moins une grandeur de comportement (A, B, C) du composant (30), et à déterminer en outre au moins une grandeur d'influence (I, II, III, IV) de cette grandeur de comportement (A, B, C) et, en fonction d'une variation (ΔIst) de la ou des grandeur(s) de comportement (A, B, C) par rapport à une valeur de référence (N1, N2) de la ou des grandeur(s) de comportement (A, B, C), à déterminer l'état de détérioration en fonction de la grandeur d'influence (I, II, III, IV).
PCT/EP2017/073852 2016-10-07 2017-09-21 Procédé et dispositif pour déterminer un état de détérioration d'un composant d'un véhicule WO2018065223A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102016219479.8 2016-10-07
DE102016219479.8A DE102016219479A1 (de) 2016-10-07 2016-10-07 Verfahren und Vorrichtung zum Ermitteln eines Schädigungszustands einer Komponente eines Fahrzeugs

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2020074115A1 (fr) * 2018-10-10 2020-04-16 Deutz Aktiengesellschaft Procédé pour la détection et la prédiction de l'encrassement d'un refroidisseur ecr dans un moteur diesel à combustion interne

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0860600A2 (fr) * 1997-02-21 1998-08-26 Toyota Jidosha Kabushiki Kaisha Système d'injection de combustible pour moteur à combustion interne
DE102005008180A1 (de) * 2005-02-23 2006-08-31 Robert Bosch Gmbh Verfahren und Vorrichtung zur Überwachung einer Einspritzvorrichtung einer Brennkraftmaschine
US20080109144A1 (en) * 2005-01-31 2008-05-08 Carl-Eike Hofmeister Method for Monitoring the Operability of a Fuel Injection System
US20080209990A1 (en) * 2007-03-01 2008-09-04 Isuzu Motors Limited Fuel pressure sensor diagnosing device and method
DE102014211896A1 (de) 2014-06-20 2015-12-24 Robert Bosch Gmbh Verfahren zur Überwachung einer Fahrzeugsteuerung
US20160138544A1 (en) * 2013-07-11 2016-05-19 Scania Cv Ab Method at fuel injection

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE10010847C1 (de) * 2000-03-06 2001-09-20 Siemens Ag Verfahren zum Überwachen der Kraftstoffeinspritzung bei einer Brennkraftmaschine
DE102007028900B4 (de) * 2007-06-22 2013-06-27 Continental Automotive Gmbh Verfahren und Vorrichtung zur Diagnose eines mit einer Kraftstoffverteilerleiste in Verbindung stehenden Einspritzventils einer Brennkraftmaschine

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0860600A2 (fr) * 1997-02-21 1998-08-26 Toyota Jidosha Kabushiki Kaisha Système d'injection de combustible pour moteur à combustion interne
US20080109144A1 (en) * 2005-01-31 2008-05-08 Carl-Eike Hofmeister Method for Monitoring the Operability of a Fuel Injection System
DE102005008180A1 (de) * 2005-02-23 2006-08-31 Robert Bosch Gmbh Verfahren und Vorrichtung zur Überwachung einer Einspritzvorrichtung einer Brennkraftmaschine
US20080209990A1 (en) * 2007-03-01 2008-09-04 Isuzu Motors Limited Fuel pressure sensor diagnosing device and method
US20160138544A1 (en) * 2013-07-11 2016-05-19 Scania Cv Ab Method at fuel injection
DE102014211896A1 (de) 2014-06-20 2015-12-24 Robert Bosch Gmbh Verfahren zur Überwachung einer Fahrzeugsteuerung

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2020074115A1 (fr) * 2018-10-10 2020-04-16 Deutz Aktiengesellschaft Procédé pour la détection et la prédiction de l'encrassement d'un refroidisseur ecr dans un moteur diesel à combustion interne

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