DE102016219479A1 - Method and device for determining a damage state of a component of a vehicle - Google Patents

Abstract

Method for determining a damage state of a component (30), in which at least one behavior variable (A, B, C) of the component (30) is determined, and in which at least one influencing variable (I, II, III, IV) of the behavior variable ( A, B, C) and depending on a change (ΔIst) of the at least one behavioral variable (A, B, C) compared to a reference value (N1, N2) of the at least one behavioral variable (A, B, C) as a function of Influencing variable (I, II, III, IV) of the damage state is determined.

Description

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.

State of the art

In the DE 10 2014 211 896 A1 a method for monitoring a vehicle control is described. Correction values are determined by means of a correction function. The course of the correction values is recorded and extrapolated. Based on the extrapolated correction values, an error is predicted.

Advantages of the invention

The method with the features of independent claim 1 has the advantage that a forecast of an error can be made very reliable.

Advantageous developments are the subject of the dependent claims.

Disclosure of the invention

In a first aspect, the invention 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, i. a variable characterizing the behavior of the component is determined, and further comprising at least one factor influencing the behavior variable, i. a parameter influencing the behavior of the component is determined, and depending on a change in the at least one behavior variable relative to a reference value of the at least one behavior variable, the damage state is determined as a function of the influencing variable. 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 specifiable limits.

In a further aspect, it can be provided here that the damage state is determined as a function of whether an absolute value of the change exceeds a predefinable change threshold value. This is a particularly simple implementation.

In one development of this aspect, it may be provided that 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 the influencing variable above an influencing variable threshold value exceeds the predefinable change threshold value.

This can be done, in particular, by assigning a set of relevant influencing variables to the pair of behavioral variable and component, and determining the damage state depending on whether the change in the at least one behavioral variable is preferably all, ie in particular all, determined values of the relevant influencing variables above a threshold influencing this influencing variable, this behavior variable and this component individual influencing variable threshold value exceed the predefinable alteration threshold value.

This allows for predictive pin-pointing in troubleshooting. This overcomes the problem that the assignment of a signal curve of a behavior variable to a component is often only indirectly possible because direct information is not available. With this method, it is possible to enable this assignment via this clever combination of factors and behavioral variables.

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.

Alternatively or additionally, the respective remaining influencing variables are kept constant for each of the relevant influencing variables in order to further improve the reliability of the method. In this case, "constant" means in particular that each of these other relevant influencing variables is kept constant within predefinable limits, or that only those measured values are selected in which each of these other influencing variables lies within specifiable limits.

In a further aspect it can be provided that the damage state is determined as "defective at risk" if the absolute value of the change exceeds the predefinable change threshold value. In particular, it can then be provided that a warning message is issued. If defects in the levels "defective" and "defect is diagnosed" are diagnosed, this can be a stepped one Warning, which makes it possible to take appropriate countermeasures.

In order to take account of specimen spreads of the component particularly effectively, it may be provided that 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 method becomes particularly accurate.

In another aspect, it can be provided that it 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.

In another aspect, a pin-pointing over a temporal reference is possible. For this purpose, it may be provided that 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.

In this case, it can be provided, in particular, that 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.

Hereinafter, embodiments of the invention will be explained in more detail with reference to the accompanying drawings. In the drawings show:

1 schematically a vehicle in which the method can be used;

2 a flowchart of a possible procedure of the method;

3 an illustration of the dependencies of behavioral variables, influencing variables and reference values;

4 an illustration of measurements of a behavioral variable as a function of influencing variables;

5 an illustration of measurements of a behavioral variable as a function of an influencing variable.

1 shows a motor vehicle 1 with a component, in the concrete example an electric suction valve 30 at a high pressure chamber of a common rail injection system. An array of sensors 20 determines measured values of behavior variables, for example a switch-on time of the suction valve 30 , A control unit 70 receives this reading. The inventive method can on the control unit 70 be implemented, for example as a computer program, on a machine-readable storage medium 71 is stored.

2 shows a flowchart this procedure, taking the steps 100 . 200 and 300 can run before a first-time operation of the method and therefore are only optional part of the process.

First, the injection valve is measured or simulatively examined ( 100 ). For this purpose, a nominal characteristic N1 and a lower limit B1 and an upper limit B2 are determined ( 200 ) and stored in the software ( 300 ). The nominal characteristic curve is determined as a function of influencing variables I, II, III, IV, ie 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 also be done via the sensor array 20 respectively.

The behavior of the nominal characteristic N1, an upper limit B2 and a lower limit B1 is dependent on an influencing variable I is in 5 illustrated. The behavior variables are designated below by the reference symbols A, B, C.

As an influencing variable, 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.

Preferably, not all possible influencing variables are determined, but for each behavior variable A, B, C 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 in 3 illustrated. The relevant influencing variables for the behavioral quantity A are the Influencing factors I, II, III ( 3a ), the relevant influencing variables for the behavioral variable B are the influencing variables I, III ( 3b ), the relevant influencing variables for the behavioral quantity C are the influencing variables II, IV ( 3c ).

The storage of the relationships between behavioral variable A, B, C and relevant influencing variables I, II, III, IV can be done for example in multidimensional arrays. It is possible that the curves N1, B1, B2 are interpolated by interpolation or by a mathematical fitting method.

For a component 30 A behavioral variable A, B, C can be determined, or several.

Using the example of the delivery start angle as a behavioral variable, this can mean the following: 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.

Either immediately at the first start of the motor vehicle 1 or after an operating hour limit (eg 50 h) new values N2 of the behavioral variables A, B, C are determined as a function of the respective relevant influencing variables I, II, III, IV ( 400 ), see also 3 , and on the storage medium 71 deposited ( 500 ). The determination can in this case during regular operation of the motor vehicle 1 respectively. It is also possible that the motor vehicle 1 is operated in a diagnostic mode to ensure that the relevant influencing variables I, II, III, IV are explored as completely as possible, ie, that over the entire possible range of these influencing variables I, II, III, IV data points are detected.

It is possible that 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.

It will then be checked ( 700 ), whether the new values N2 are within the limits B1, B2. This is in 4 Based on the behavioral variable B with the relevant parameters I, III illustrated. Shown are measuring points M1, M2, ..., M10. In 4 The ratio of the measuring points M1, M2,..., M10 to the upper limit B2 is illustrated. Illustrated is the case that measuring point M7 is above the upper limit B2, and all other measuring points M1, ... M6, M8, ..., M10 below the upper limit B2.

If all measuring points lie within the limits B1, B2, follow step 1000 otherwise step follows 1500 ,

In 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 Δof the measuring points from the curve N2 of the new values are determined, specifically separate from each of the relevant influencing factors, see 5 ,

It is optionally possible that in addition to further processing to step 700 is branched back and the local monitoring with the in step 1000 determined further measuring points M11, ..., M19 instead of the measuring points M1, ..., M10 is performed.

This determination of the behavioral variable B as a function of the influencing variable III as in 5 illustrated is done on the basis of sectional planes SE, as in 4 is illustrated. Values of the other relevant influencing variables, influencing variable III in the concrete example, are then checked as to whether they lie in a predeterminable area (not shown) around the cutting plane SE. If this is the case, the data points in the in 5 shown depended on the influence size III. This determination can be made for each of the relevant parameters.

Subsequently ( 1100 ) checks whether the absolute values of the deviations Δist are within predeterminable limits as a function of the respective relevant influencing variable III. This may mean, for example, that the absolute value of the deviation lies within these limits for one or each of the sectional planes SE for all measured values.

If this is the case, further data is recorded ( 1000 ), otherwise step follows 1200 ,

step 1200 can also follow, for example, if for any or each cutting plane SE behaves like in 5 illustrated exists, for which values of the influencing variable III above (or alternatively: below) an influence variable threshold value S, the deviations ΔIst the predetermined limits.

The branch to step 1200 This can be done either if the described criteria for one of the relevant influencing variables (in the example of the behavioral parameter B: I, III) are fulfilled, but it can also only take place if they are fulfilled for all of the relevant parameters I, III.

In step 1200 it is checked whether the currently determined behavioral variables A, B, C are within the determined limits B1, B2. If this is the case, follow step 1300 in which it is recognized that the component 30 possibly fail, and a corresponding warning is issued to the driver. In the optional step 1400 the measured values determined will be subjected to data processing, for example a trend analysis, eg with exponential smoothing. Then, branch back to step 1000 ,

In step 1500 it is decided that the component concerned 30 is defective, and a corresponding entry is stored in a fault memory and / or a corresponding drive strategy is activated in order to operate in a "limp-home" mode the defective component 30 not to burden.

As a defective component 30 can any component 30 be identified, which is associated with the conspicuous behavioral size. Will from step 1200 to step 1500 However, it is also possible to identify the component based on the influencing variables in whose dependence the conspicuous behavior has been shown.

Thus, it is possible, for example, that the behavioral variable A of the determined 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 common rail Systems "is associated.

When leaving the predetermined limits B1, B2 will be monitoring for both components in step 700 attacks. However, since the behavioral variable A is associated with the relevant influencing variables fuel temperature (I), rail pressure (II) and the volume flow (III) to be delivered to the rail, the monitoring In step 1100 only to step 1200 branch if the behavioral quantity A is conspicuous in relation to these relevant parameters. On the other hand, the behavioral parameter C depends on the relevant parameters of rail pressure (II) and the position of the upper camshaft tundish (IV), so that the monitoring in step 1100 only to step 1200 will branch if the behavioral quantity C is conspicuous with respect to these relevant parameters. Thus, at branching over the steps 1100 . 1200 to step 1500 a differential determination of the defective component possible.

Additionally it is possible that in step 1500 Defect messages of different components are determined, and in addition the respective number of activations of the components, the damage state was determined as "defective". Depending on the number of these activations and optionally a respectively definable activation threshold value, it is possible to select from the components whose damage status was determined to be "defective", that component whose actual defect is assumed to be the most probable.

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.

As an extension of the connection with a mobile phone app is conceivable that informs the driver about the possible component failure.

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 (≈1s to 10s).

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 curve N1. Therefore, the presented method is suitable for long-term observation.

QUOTES INCLUDE IN THE DESCRIPTION

This list of the documents listed by the applicant has been generated automatically and is included solely for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions.

Cited patent literature

• DE 102014211896 A1 [0002]

Claims (14)

Method for determining a damage state of a component ( 30 ), in which at least one behavior variable (A, B, C) of the component ( 30 ), and in which at least one influencing variable (I, II, III, IV) of the behavioral variable (A, B, C) is determined, and depending on a change (ΔIst) of the at least one behavioral variable (A, B, C ) is determined relative to a reference value (N1, N2) of the at least one behavioral variable (A, B, C) as a function of the influencing variable (I, II, III, IV) of the damage state. The method of claim 1, wherein the damage condition is determined depending on whether an absolute value (ΔIst) of the change exceeds a predetermined change threshold. Method according to Claim 2, in which the state of damage is determined as a function of whether the change (ΔIst) of the at least one behavior variable (A, B, C) for values of the influencing variable (I, II, III, IV) is above an influencing variable threshold value (S). exceeds the predefinable change threshold. The method of claim 3, wherein the pair of behavioral variables (A, B, C) and component ( 30 ) is assigned a set of relevant influencing variables (I, II, III, IV), and in which the damage state is determined depending on whether the change (ΔIst) of the at least one behavioral variable (A, B, C) for values of one of the relevant influencing variables (I, II, III, IV) above one for this factor, this behavioral variable and this component ( 30 ) individual influencing variable threshold value (S) exceeds the predefinable change threshold value. Method according to claim 4, wherein the damage state is determined depending on whether the change (Δist) of the at least one behavior variable (A, B, C) for preferably all, in particular all, determined values of each of the relevant influencing variables (I, II, III, IV) above the influencing variable threshold value (SI) exceeds the predefinable change threshold value. The method of claim 4 or 5, wherein for each of the relevant influencing variables (II), the respective remaining relevant influencing variables (I, II, III, IV) are kept constant. Method according to one of claims 2 to 6, wherein the damage state is determined as "defective" if the absolute value (ΔIst) of the change exceeds the predefinable change threshold. Method according to one of the preceding claims, wherein the reference value (N1, N2) comprises a determined new value (N2) of the at least one behavior variable (A, B, C), wherein the new value (N2) of the at least one behavior variable (A, B, C ) is determined before a mileage of the vehicle has exceeded a predetermined mileage threshold. Method according to one of the preceding claims, wherein it is decided that the component ( 30 ) is defective, if the at least one behavioral variable (A, B, C) of the component ( 30 ) lies outside predefinable limits (B1, B2), in particular around a nominal value (N1) of the behavioral variable (A, B, C). Method according to one of the preceding claims, wherein the damage state of the component ( 30 ) also depends on a number of activations of the component ( 30 ) is determined. The method of claim 10, wherein the damage state of the component ( 30 ) is determined depending on whether the number of actuations is greater than a predeterminable number of actuation thresholds. Computer program configured to carry out the method according to one of Claims 1 to 11. Machine-readable storage medium ( 71 ) on which the computer program according to claim 12 is stored. Control and / or regulating device ( 70 ) arranged to carry out the method according to one of claims 1 to 11.

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