JP2013079920A - System for diagnosing fatigue damage degree of vehicle - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a system for diagnosing a fatigue damage degree of a vehicle, configured to estimate a fatigue damage degree of a member or a portion of a vehicle so as to properly maintain the member or the portion of the vehicle.SOLUTION: The system for diagnosing a fatigue damage degree of a vehicle includes: detection means 5 for detecting an input correlation value I correlated to the magnitude of input to be applied to a traveling vehicle 1; cumulative storage means 110 for cumulatively storing the input correlation value I detected by the detection means 5 as a cumulative value; a database 120 for storing the correspondence 122, 124 between a fatigue lifetime of an object 2a to be diagnosed in the vehicle 1 and the cumulative value stored in the cumulative storage means 110; and calculation means 130a for calculating a fatigue damage degree D of the object 2a, on the basis of the cumulative value and the correspondence 122, 124 recorded in the database 120.

Description

  The present invention relates to a system for diagnosing the degree of fatigue damage of a vehicle.

In vehicles such as automobiles, maintenance of various members (including parts) and parts (hereinafter also referred to as members) is necessary. Depending on the member or the like, the member is periodically replaced, or the degree of deterioration is determined from the appearance and tactile sensation of the member or the like during vehicle maintenance.
When exchanging members and the like regularly, it is common to determine the replacement time according to the travel distance and elapsed time of the vehicle since the previous replacement.

However, since the degree of deterioration of the vehicle members and the like varies depending on the usage history, if the vehicle is uniquely replaced based on the distance traveled from the previous replacement or the elapsed time, the replacement time may not be appropriate. .
Skilled techniques are required to determine the degree of deterioration from the appearance and tactile sensation of a member, etc., and it is difficult to examine the degree of deterioration by looking at or touching depending on the member. There is no way to rely on this method.

In this regard, Patent Document 1 discloses a technique for quantitatively determining the deterioration state (degree) of an internal combustion engine and a transmission, although the main purpose is not vehicle maintenance.
Although the technique of Patent Document 1 also describes application to vehicle maintenance, the main purpose is to appropriately perform purchase assessment and sales price setting in the used car market in accordance with the state of the vehicle. The load state is detected by, for example, a torque sensor, an acceleration sensor, a vehicle speed sensor, etc., and the accumulated time when the detected load value is larger than a pre-stored threshold value or the load value is stored in advance. The degree of deterioration of the engine or the like is quantitatively determined from the cumulative number of times when the time longer than the threshold is longer than the predetermined time.

JP 2004-243924 A

However, although the technology of Patent Document 1 can be applied to the evaluation of the deterioration degree of the engine or transmission and the evaluation of the price corresponding to the vehicle state, the application to vehicle maintenance is not specifically described, and the vehicle It is not possible to evaluate the life of a member or the like and specify the replacement time of the member or the like.
Patent Document 1 is a technique for evaluating the degree of deterioration of an engine or transmission, and pays attention to a load on the engine or transmission, that is, a load of a drive system. The deterioration is considered to depend on the input received from the road surface or the like when the vehicle travels rather than the load on the drive system.

  The present invention was devised in view of such a problem, and estimates the degree of fatigue damage of a vehicle member or part, and allows the vehicle member or part to be properly maintained. An object is to provide a diagnostic system.

  In order to achieve the above object, a vehicle fatigue damage degree diagnosis system according to the present invention has a detection means for detecting an input correlation value that correlates with a magnitude of an input applied to the vehicle during traveling, and is detected by the detection means. A cumulative storage unit that cumulatively stores the input correlation value as a cumulative value; a database in which a correspondence relationship between a fatigue life related to a fatigue diagnosis target of the vehicle and the cumulative value stored in the cumulative storage unit; And calculating means for calculating a fatigue damage degree of the fatigue diagnosis target based on the cumulative value and the correspondence relationship recorded in the database.

Further, the detection means detects distortion of the main part of the vehicle as the input correlation value, acceleration detection means detects the acceleration of the main part of the vehicle as the input correlation value, and the input correlation value As at least one of load detection means for detecting a load applied to a main part of the vehicle, and the database includes, as the correspondence, the input correlation value detected by the detection means and the fatigue first and correspondence that associates the stress amplitude S _k applied to the diagnostic object, the repetition number of inputs N _Lim fatigue diagnostic stress amplitude applied to the subject S _k and the stress amplitude S _k and (S _k) and fatigue life second correspondence relationship and are recorded is SN characteristics showing the relationship the calculation means, the number of occurrences of the stress amplitude S _k corresponding to the input correlation values obtained by using the first relationship N And (S _k), the repetition number of inputs N _Lim (S _k) from the equation of the stress amplitude S _k obtained by using the second relationship (1), calculates the fatigue damage degree D It is preferable. That is, the fatigue damage degree D is calculated the ratio of the repeating input count N _Lim stress amplitude S _k fatigue diagnosis target is a number which leads to fatigue life stress amplitude for (S _k) S _k of occurrences N (S _k) To do.
D = Σ {N (S _k ) / N _Lim (S _k )} (1)

  The main part of the vehicle is a main part of a suspension (for example, a suspension arm) or a vehicle body (for example, a member such as a side member or a front cross member) of the vehicle. It is preferably a member or part of a suspension (for example, a suspension arm) or a vehicle body (for example, a member such as a side member or a cross member).

  Further, a display means for displaying the fatigue damage degree D in response to a display request, a data output means for outputting data of the fatigue damage degree D in response to an output request, and the fatigue diagnosis based on the fatigue damage degree D It is preferable to provide warning means for warning that the life of the object is near or that the replacement time has come.

  The cumulative storage means cumulatively stores the input correlation value together with the vehicle running state data (for example, the state of the transmission such as the selected gear stage, engine torque, and engine speed), and the input correlation. When the value is greater than or equal to a preset value, it is stored as large input data, and in response to a display request, the display means stores cumulative data that is the value of the cumulatively stored traveling state data. Displayed in association with the degree of fatigue damage, displays the large input data, and the data output means outputs the accumulated data in association with the degree of fatigue damage in response to an output request, and outputs the large input data It is preferable.

  According to the vehicle fatigue damage diagnosis system of the present invention, based on the correspondence relationship between the cumulative value of the input correlation values recorded in the database and the fatigue life of the fatigue diagnosis target, for example, vehicle fatigue such as a vehicle member or part. The degree of fatigue damage for the diagnosis target can be calculated. Thereby, based on the calculated fatigue damage degree, replacement of the fatigue diagnosis target can be performed at an appropriate timing, and the fatigue diagnosis target can be appropriately maintained.

  Further, as an input correlation value correlated with an input applied to the vehicle during traveling, each detection means such as a distortion detection means, an acceleration detection means, and a load detection means is used if at least one of distortion, acceleration, and load of the main part of the vehicle is used. Thus, the input correlation value can be reliably detected.

The database, first and correspondence that associates the stress amplitude S by the input of the input correlation value and applied to the fatigue diagnosed, the stress amplitude S _k and the stress amplitude S _k of repetitions input count N _Lim (S _k) if the second corresponding relationship between fatigue life is SN characteristic showing the relationship are recorded, it is determined stress amplitude S _k fatigue diagnosed in accordance with the input correlation value using the first corresponding relationship It is possible to obtain the number of repeated inputs N _Lim (S _k ) reaching the fatigue life by repeatedly inputting the obtained stress amplitude S _k using the second correspondence relationship.

Then, by _obtaining the number N (S _k ) of occurrences of the stress amplitude S _k for each input, the fatigue damage degree D of a fatigue diagnosis target such as a vehicle member or part can be obtained from the equation (1).
According to the equation (1), the fatigue damage degree D is calculated accurately by weighting and accumulating the number of occurrences N (S _k ) of the stress amplitude S _k corresponding to the input correlation value. The degree of fatigue damage of a fatigue diagnosis target such as a vehicle member or part can be accurately estimated based on the lifetime.

  In addition, if a first correspondence or a second correspondence is prepared for the main part of the vehicle that is the detection target by the detection means and the fatigue diagnosis target such as a member or part of each vehicle, the specific vehicle The fatigue damage degree D of various fatigue diagnosis targets (vehicle members and parts) can be calculated from the input correlation value detected in the main part.

  Further, if the display means for displaying the fatigue damage degree D according to the display request is provided, the fatigue damage degree D can be displayed according to the display request, and the fatigue of the fatigue diagnosis target can be displayed to the maintenance worker or the driver. The degree of damage D can be recognized.

  If data output means for outputting fatigue damage degree D data in response to an output request is provided, for example, data on fatigue damage degree D is output during vehicle maintenance, and fatigue diagnosis targets such as vehicle members or parts are appropriately maintained. can do. In addition, the maintenance operator, the driver, and the like can recognize the fatigue damage degree D of the fatigue diagnosis target.

  If a warning means for warning that the life of the fatigue diagnosis target is near or the replacement time is coming based on the fatigue damage degree D is provided, for example, the life of the fatigue diagnosis target is near to the vehicle driver or the replacement time Can warn you are coming. As a result, it is possible to promote replacement or repair of the fatigue diagnosis target and prevent damage.

  The cumulative storage means cumulatively stores the input correlation value together with vehicle running state data (for example, the state of the transmission such as the selected gear stage, engine torque, and engine speed), and the input correlation value is preset. If it is greater than or equal to the calculated value, if it is stored as large input data, the large input data as a damage factor other than damage due to fatigue is combined with the fatigue damage degree D associated with the cumulative data that is the vehicle running state data. Can be displayed or output. As a result, it is possible to provide maintenance judgment materials for other vehicle members or parts as well as fatigue diagnosis targets, and promote appropriate maintenance and replacement of members and the like.

1 is a side view showing a vehicle to which a fatigue damage degree diagnosis system according to an embodiment of the present invention is applied, and vehicle ECU related functions are shown as functional block diagrams. 1 is a top view showing a vehicle to which a fatigue damage degree diagnosis system according to an embodiment of the present invention is applied, and vehicle ECU related functions are shown as functional block diagrams. It is a perspective view which shows the lower arm which is a member of the suspension apparatus of the vehicle to which the fatigue damage degree diagnostic system concerning one Embodiment of this invention is applied. It is a figure which shows the time change of the input correlation value of the fatigue damage degree diagnostic system of the vehicle concerning one Embodiment of this invention. It is a figure explaining the IS characteristic which is a correspondence of the input correlation value and stress amplitude of the fatigue damage degree diagnostic system of vehicles concerning one embodiment of the present invention, and (a) shows the 1st example and (b) ) Shows a second example. In view showing the SN characteristic is the relationship between an exemplary stress amplitude applied to the vehicle fatigue damage degree diagnostic system according to the S _k and repeat input count stress amplitude N _Lim (S _k) and fatigue diagnosed life of the present invention is there. It is a flowchart which shows the diagnosis flow of the fatigue damage degree by the fatigue damage degree diagnosis system of the vehicle concerning one Embodiment of this invention.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
[One Embodiment]
1 to 7 illustrate a fatigue damage level diagnosis system for a vehicle according to an embodiment of the present invention. FIG. 1 is a side view showing the vehicle, FIG. 2 is a top view showing the vehicle, and FIG. Is a perspective view showing a lower arm of the suspension device of the vehicle, FIG. 4 is a diagram showing a time change of the input correlation value, FIG. 5 is a diagram showing an IS characteristic defining a correspondence relationship between the input correlation value and the stress amplitude, and FIG. Is a diagram showing SN characteristics used for calculation of the fatigue damage degree, and FIG. 7 is a flowchart for explaining a fatigue damage degree diagnosis system for a vehicle.

〔Constitution〕
First, the configuration of a vehicle to which the fatigue damage degree diagnosis system according to the present embodiment is applied will be described with reference to FIGS. 1 and 2. Here, the vehicle according to the present embodiment will be described using an automobile as an example. The directions indicated by arrows in FIGS. 1 and 2 are based on the traveling direction as the front, F is forward, R is backward, T is upward, B is downward, RS is right, and LS is left. .

  The vehicle 1 has wheels 3 and a vehicle body 2 having a panel structure or a frame structure on the front, rear, left and right in the traveling direction. The vehicle body 2 includes members such as a front side member 2a and a cross member 2b. The vehicle body 2 is connected to wheels 3 via a suspension device, and various components and members such as an engine and a transmission are disposed. The

  The front side member 2a is a metal member (usually a steel member) that extends in the front-rear direction to the front portion of the vehicle body 2 and ensures the strength of the vehicle body 2 in the front-rear direction. The cross member 2b is a metal member (usually a steel member) that extends in front of the front wheels 3 and 3 in the left-right direction of the vehicle body 2 and ensures strength in the left-right direction of the vehicle body 2.

  The suspension device is interposed between the vehicle body 2 and the front, rear, left and right wheels 3 to relieve input from the road surface to the vehicle body 2, and has a structure such as a lower arm (suspension arm) 4 and a link (also called a rod). It has a shock absorbing member such as a member, a spring, a rubber bush or a shock absorber.

As shown in FIG. 3, the lower arm 4 has a swing axis C _B on the vehicle body 2 side and a swing axis C _W on the wheel 3 side. The lower arm 4, the shaft C _B is connected is inserted an appropriate pin member body 2 and swingably, the axis C _W are connected is inserted appropriate pin member wheel 3 and swingably The 3 illustrates an example of the lower arm 4 disposed on the left rear side that connects the left rear wheel 3 and the vehicle body 2. However, the lower arm 4 disposed on the right rear side is similar to the left rear and the left and right objects. Each of the lower arms 4 arranged in the right front and left front is different in shape but has the same function.

  The lower arm 4 is a member that is interposed between the wheel 3 that contacts the road surface and the vehicle body 2. For this reason, the lower arm 4 receives an input (road surface reaction force) from the road surface through the wheel 3 when the vehicle travels, and transmits this input to the vehicle body 2. Such input from the road surface acts so as to cause stress (or stress change) to each part of the lower arm 4. This action varies depending on the position of the lower arm 4.

Areas 4 a, 4 b, and 4 c indicated by hatching in the vicinity of the axes C _W and C _B are areas where a large stress is generated due to the shape discontinuity or the like, and among the lower arms 4 in accordance with the input to the wheel 3. This is a region where a large force acts. Since stress and strain are correlated, the regions 4a, 4b, and 4c in the vicinity of the axes C _W and C _B are likely to be distorted. Therefore, it can be said that the regions 4a, 4b, and 4c are regions where distortion is easily detected.

  A sensor (detection means) 5 is attached to at least one of the regions 4a, 4b, and 4c where these distortions are easily detected. The sensor 5 is a distortion sensor (distortion detection means) that detects distortion that is an input correlation value I that correlates with an input from the road surface to the vehicle 1.

  In addition, since the stress state of a part having a member correlates with a force (load) or acceleration applied to the part, the sensor 5 includes an acceleration sensor (acceleration detecting means) or a load that detects acceleration in addition to a strain sensor. A load sensor (load detection means) for detecting the above can also be applied, and any of these sensors or a combination of these sensors may be used. The mounting location of the acceleration sensor may be at least one of the regions 4a, 4b, and 4c where the input correlation value I is easily detected, and the mounting location similar to that of the strain sensor can be applied. The load sensor can be attached between a strut attached to an impact absorbing member (not shown) and the lower arm 4.

  That is, each sensor 5 detects an input correlation value I applied to each lower arm 4. Specifically, sensors 5 are respectively attached to the lower arms 4 connected to the front, rear, left, and right wheels 3, and each input correlation value I correlated with the force applied to the vehicle 1 by the input to each wheel 3 is detected. The

In the vehicle fatigue damage diagnosis system of the present embodiment, a portion for detecting distortion as the input correlation value I is provided in a part of the region 4a, 4b, 4c where the large stress of the lower arm 4 is generated. The part for detecting the input correlation value I according to the present invention may be any part (main part) of the vehicle in which the input correlation value I can be easily detected. For example, various members (including parts) and parts of the vehicle 1 can be set.
Each sensor 5 is connected to the vehicle ECU 100, and the input correlation value I detected by each sensor 5 is input to the vehicle ECU 100.

  When each sensor 5 is a combination of a plurality of types of strain sensors, acceleration sensors, and load sensors, the vehicle ECU 100 weights each of the strain, acceleration, and load detected by the plurality of types of sensors constituting each sensor 5. Thus, each input correlation value I is calculated.

  By the way, materials such as members and parts of the vehicle 1 are eventually damaged when a force is repeatedly applied. That is, materials such as members and parts of the vehicle 1 have a characteristic that, when a repeated force is input, the damage degree (fatigue damage degree D) due to accumulated fatigue increases and breaks (becomes a life). Such characteristics are remarkable in metal materials, particularly steel materials. Other materials such as resin materials have such characteristics.

  In the vehicle fatigue damage diagnosis system according to the present embodiment, a target for monitoring the fatigue damage degree D is referred to as a fatigue diagnosis target member (fatigue diagnosis target). Although any member or part of the vehicle 1 can be set as the fatigue diagnosis target member, in the present embodiment, the front side member 2a will be described as a fatigue diagnosis target member.

[Configuration of vehicle ECU]
The vehicle ECU 100 is a computer including a CPU, a ROM, a RAM, an input / output circuit, and the like, and calculates a fatigue damage degree D based on an input correlation value I detected by each sensor 5.
The vehicle ECU 100 includes a memory (cumulative storage means) 110, a database 120 in which IS characteristics (first correspondence) 122 and SN characteristics (second correspondence) 124 are recorded, and a fatigue damage degree calculation unit (calculation means). ) 130a.

The memory 110 cumulatively stores the input correlation value I detected by each sensor 5.
An example of a cumulative storage method of the input correlation value I will be described with reference to FIG.
FIG. 4 shows the trajectory (time change) of the input correlation value I, with the input correlation value I on the vertical axis and time t on the horizontal axis. Level values I _k (= I ₁ , I ₂ , I ₃ , I ₄ ...) Described on the vertical axis in FIG. 4 are preset to be used for leveling the magnitude of the input correlation value I. There, the level value I _{k is, I 1, I 2, I} 3, are set I ₄ ... in ascending order at regular intervals. In FIG. 4, the equilevel value line for each level value I _k is indicated by a broken line.

As shown in FIG. 4, the input correlation value I detected by the sensor 5 is increased or decreased with time, while the increase (slope positive), the input correlation value I reaches one of level values I _k (equal level Each location (which intersects the value line) is indicated by a point (hereinafter also referred to as an intersection) P _N. The input correlation value I at the location indicated by these points _PN is one of the level values I _k divided into levels. Input correlation value I of these points P _N is stored in the cumulative memory 110 is selected by a so-called level cross method.

That is, it is assumed that the input correlation value I at the point P _N at a certain time t _N is the level value I _i , and the level value I above the level value I _i of the input correlation value I at the point P _N after that time t _{N. If the} input correlation value I decreases below the level value I _i without reaching _{i + 1,} the generation of the level value I _i at this time is counted and the count value of the level value I _i stored in the memory 110 is incremented. .

In other words, when crossed with any of the level value I _k increases from the minimum value in the input correlation value I to up to the maximum value, the maximum level value I _k of the crossed level values I _{k ' Is} counted and the count value of the level value I _{k ′} stored in the memory 110 is incremented. Here, since attention is paid to the increase, the input correlation value I from this maximum value to the next minimum value is not stored, and the above condition is applied to the input correlation value from the next minimum value to the next maximum value. fill count the occurrence of the maximum level value I _k', again increments the count value of the maximum level value I _k'stored in the memory 110.

Thus, in other words more, of the intersection P _N in increasing the input correlation value I, a just before the intersection P _N'the maximum value of the input correlation value I, and the input correlation value I of the immediately following maxima of when the input correlation value I by the reduction is smaller than the level value I _k'of this intersection P _N', it counts the level value I _k'of this intersection P _N', and can be said.

For example, if the input correlation value I is changed as shown in FIG. 4, focusing in the increase of the input correlation value I, the input correlation value I time t ₁ is, t _2, t _3, · · ·, in t ₁₀ , Each of which intersects with an equal level value line of any level value I _k . Each time point _{t 1, t 2, t 3} , ···, intersection points inputted correlation value I intersects an equal level contours at _{t 10 P 1, P 2,} P 3, ···, when the P ₁₀ for the intersection _{P 3, P 5, P 10} , then takes the maximum value never reach the level value I _{i + 1} above the level value I _i of each intersection _{P 3, P 5, P 10} , Since the input correlation value I has decreased below the level value I _i , all of the level values I _k of P ₃ , P ₅ and P ₁₀ are counted and the count value of the level value I _k stored in the memory 110 is counted. Is incremented. On the other hand, for the other intersections P ₁ , P ₂ , P ₄ , P ₆ , P ₇ , P ₈ , P ₉ , the input correlation value I increases thereafter, and each intersection P ₁ , P ₂ , P ₄ , P 9 _Since the level value I _{i + 1 is} higher than the level value I _{i of 6} , P ₇ , P ₈ , and P ₉ , none of them is counted.

The intersection P ₄ takes the maximum value and the minimum value by the subsequent increase / decrease in the input correlation value I, but the input correlation value I does not intersect any level value I _k until the intersection P ₅ is reached. That is, reaching the level value I ₅ above the level values I ₄ inputs the correlation value I of the point P ₄ at a time t ₄ later, the level value I ₄ intersection P ₄ is not counted. In this case, the level value I ₅ higher than the level value I ₄ of the input correlation value I at the point P ₄ is reached at the intersection P ₅ at the time point t ₅ .

In this example, the count value N (I _k ) of the level value I _k stored cumulatively in the memory 110 is equal to the count value N (I ₄ ) of the level value I _{4 at} the time point t _{3 in} the example shown in FIG. Once, the count value N (I ₅ ) of the level value I ₅ is twice at time t ₅ and time t ₁₀ .
That is, the memory 110, by counting the number of times for each level of the value I _k (size), cumulatively stores the level value I _k based on the input correlation value I.

FIG. 4 illustrates the case where the detected input correlation value I is positive, but when the input correlation value I is negative, the input correlation value I at the point P _N at a certain time t _N is the level value. and a I _-i, the input correlation value level values below the level value I _-i of I I at the time t _N later point P _{N - (i + 1)} input correlation value level values without reaching when increased larger than I _-i, it counts the occurrence of level values I _-i this time, increments the count value of the level value I _-i stored in the memory 110 N (I _-i). The memory 110 cumulatively stores the count value N (I _k ) of the level value I _k corresponding to the level value I _−i stored in this way.

In the case of the present embodiment, the input correlation value I detected by the sensor 5 provided in each of the lower arm 4 corresponding to the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel is a level value according to the storage method described above. I _k of the count value N (I _k) is stored, it is cumulatively stored in the memory 110.

In addition, the memory 110 cumulatively stores the traveling state of the vehicle 1 together with each level value I _k as accumulated data. What is stored in the accumulated data is, for example, the state of transmission of the selected gear stage, the running state data of the vehicle 1 such as the engine torque and the engine speed, and the level value I _k and the accumulated data are associated in time series. Is remembered.
The IS characteristic 122 records the correspondence between the level value I _k stored in the memory 110 and the stress amplitude (stress magnitude) S _k applied to the front side member 2a.

As shown in FIG. 5A, the IS characteristic 122 stores a stress amplitude S _k corresponding to, for example, the level value I _k stored in the memory 110. This memory is performed beforehand experimentally and empirically.
Therefore, the stress amplitude S _k acting on the front side member 2a can be _obtained based on each level value I _k .

Considering the coupling of four wheels, as shown in FIG. 5B, the input correlation value I detected by the sensor 5 provided on the lower arm 4 corresponding to the left front wheel is selected as the IS characteristic 122. The first level value I _1k , the second level value I _{2k obtained} by selecting the input correlation value I detected by the sensor 5 provided on the lower arm 4 corresponding to the right front wheel, and the lower arm 4 corresponding to the left rear wheel The third level value I _{3k obtained} by selecting the input correlation value I detected by the detected sensor 5 and the fourth level value obtained by selecting the input correlation value I detected by the sensor 5 provided in the lower arm 4 corresponding to the right rear wheel. Based on the level value I _4k , an IS characteristic in which a correspondence relationship between a set of level values of the first _to fourth level values I _{1k to 4k} and the stress amplitude S _k may be used. In this case, the memory 110 cumulatively stores a set of level values I _{1k to 4k} of the first _to fourth level values I _{1k to 4k} .

The SN characteristic 124 indicates that the stress amplitude S _k applied to the front side member 2a and the number of times N _Lim (S _k ) that is broken (reach the life) when this stress amplitude S _k is repeatedly input are fatigued. The correspondence relationship with the lifetime is stored, and the SN characteristic 124 will be described below with reference to FIG.

FIG. 6 shows the stress amplitude S on the vertical axis, the horizontal axis on the logarithmic scale, and the repeated input number N _Lim of the stress amplitude S. The solid line or the broken line shown in FIG. This is a fatigue life line L1 indicating the fatigue life of the member subjected to fatigue diagnosis, and the one-dot chain line is a life warning line indicating that the life of the member subjected to fatigue diagnosis such as the front side member 2a is near the end or the replacement time has come. L2.

In the fatigue life line L1, if the stress amplitude S is larger than the predetermined stress amplitude S _L , the stress amplitude S at which the fatigue diagnosis target member reaches the fatigue life decreases as the number of repeated inputs N _Lim increases. Show. That is, when the stress amplitude S is large, the fatigue life is reached with a small number of repeated inputs N _Lim , and when the stress amplitude S is relatively small, the fatigue life is reached with a relatively large number of repeated inputs N _Lim .

The predetermined stress amplitude S _L is an upper limit of the stress amplitude S that does not lead to breakage even if the number N of repeated inputs of the stress amplitude S is increased, and it is known that such a stress amplitude S exists. That is, it is indicated by the fatigue life line L1 that the stress diagnosis target member does not reach breakage when the stress amplitude S is equal to or less than the predetermined stress amplitude S _L even if the number N of repeated inputs of the stress amplitude S is increased.
The fatigue diagnosis target member having such SN characteristics will be damaged in the damaged region indicated by hatching in the lower left direction.

However, in an actual fatigue phenomenon, a stress amplitude S equal to or lower than a predetermined stress amplitude S _L may affect the damage, and a member having SN characteristics that does not have the predetermined stress amplitude S _L is also known. As shown, the fatigue diagnosis of the front side member 2a, for example, has the characteristic of the fatigue life line L1 that does not have the stress amplitude S _L and has a stress amplitude S that reaches the fatigue life as the number of repeated inputs N increases. There are many target members.
The fatigue diagnosis target member having such SN characteristics will be damaged in a damaged region indicated by hatching in the lower right direction.

The life warning line L2 is a line shifted so as to reduce the number of repeated inputs N _Lim corresponding to the stress amplitude S of the fatigue life line L1, and the life of the fatigue diagnosis target member is near or has come to be replaced. It is a set of threshold values indicating that. In FIG. 6, the life warning line L2 is exemplified by an apparent shift of the number N _Lim of repeated inputs of the fatigue life line L1, but is shifted by decreasing the number of repeat inputs N _Lim of the fatigue life line L1 by a certain amount. Alternatively, it may be shifted by a constant rate. Further, the shift amount and the shift ratio are preferably changed depending on the fatigue diagnosis target member.

In the present embodiment, the SN characteristic 124 having no stress amplitude S _L and having a fatigue life line L 1 in which the stress amplitude S _k reaching the fatigue life decreases as the number of repeated inputs N _Lim increases is used. This SN characteristic 124 is set experimentally and empirically in advance.

Therefore, the SN characteristic 124 stores the fatigue life line L1 for the front side member 2a, in which the stress amplitude S _k that reaches the fatigue life decreases as the number of repeated inputs N _Lim (S _k ) increases. life warning line number N is shifted so as to reduce the repetition number of inputs N _Lim corresponding to the stress amplitude S _k of fatigue life line L1 indicating that it or replacement time is near fatigue life come him to increase L2 is stored.

In the SN characteristic 124, the damage (fatigue life) when the stress amplitude S _k is inputted to the front side member 2a by the number of repetitions N _Lim (S _k ) is experimentally and empirically set and stored. Therefore, N _Lim (S _k ) is 1 at the position of the vertical axis intercept, which is the intersection of the fatigue life line L1 and the vertical axis where the stress amplitude S is defined, and this neighborhood is in the region where fatigue is evaluated. Absent. However, since this section stress amplitude S exceeds _a stress amplitude S may damage the front side members 2a, vehicle ECU100 is the stress amplitude S _k obtained using IS characteristics 122 intercept stress amplitude S _a higher In some cases, the level value I _k corresponding to the stress amplitude S _k greater than the intercept stress amplitude S _a is stored in the memory 110 as large input data.

Fatigue degree calculating unit 130a, using the IS characteristics 122 obtains the stress amplitude S _k by the input applied from the level value I _k stored by the memory 110 to the front side members 2a, determined using the SN characteristics 124 Stress repeated input count N _Lim amplitude S _k (S _k), to calculate the fatigue damage degree D by the following equation (1) by using the stress amplitude S _k of actual input generation count N (S _k).
D = Σ {N (S _k ) / N _Lim (S _k )} (1)

That is, fatigue damage calculation unit 130a, the value of the stress amplitude S repetition number of inputs corresponding to the size of _k N _Lim stress amplitude for (S _k) S _k of occurrences N (S _k), i.e., the degree of damage ( = N (S _k ) / N _Lim (S _k )) is accumulated to calculate the fatigue damage degree D of the front side member 2a.
For example, a fatigue diagnosis target member is damaged when the fatigue damage degree D becomes 1 when any same stress amplitude S _k is input by the number of times of input N _Lim (S _k ) corresponding to the stress amplitude S _k . In other words, the damage degree per input of an arbitrary stress amplitude S _k can be treated as 1 / N _Lim (S _k ).

In this way, the fatigue damage degree calculation unit 130a calculates N (S _k ) / N _Lim (S _k ), which is the damage degree due to the number of occurrences N (S _k ) of arbitrary different stress amplitudes S _k , The damage degree N (S _k ) / N _Lim (S _k ) weighted for each stress amplitude S _k is cumulatively added, and the fatigue damage degree D of the member subjected to fatigue diagnosis is calculated using a so-called cumulative damage law. calculate.
The fatigue life line L1 corresponds to the case where the fatigue damage degree D is 1, and the life warning line L2 corresponds to the case where the fatigue damage degree L is smaller than 1, for example, 0.9 or 0.7.

  Note that the value of the fatigue damage degree D corresponding to the life warning line L2 is set in advance for each fatigue damage target member based on the material, dimensions, shape, and the like. For example, in the case where a metal member (for example, a steel member) that easily accumulates fatigue with a characteristic according to the fatigue life line L1 in the SN characteristic 124 is used as a fatigue diagnosis target member, a value close to 1 and less than 1 such as 0.9. When a member such as a resin that accumulates fatigue with varying characteristics is used as a member for fatigue diagnosis, a relatively small value such as 0.7 can be taken.

The vehicle 1 includes display requesting means (not shown) that can request display of the fatigue damage degree D. As this display request means, for example, a display switch that can be operated by a maintenance worker or a driver provided in an instrument panel or the like can be applied.
The vehicle ECU 100 is connected to a display (display unit) 10, a data output unit (data output unit) 20, and a warning device (warning unit) 30.

  The display 10 is disposed in the vehicle 1 and displays the fatigue damage degree D in response to a display request for the fatigue damage degree D. As the display 10, a display unit such as a liquid crystal, an organic EL, or a cathode ray tube provided in the vehicle interior can be applied. For example, if there is a display for displaying a car navigation screen or the like on the vehicle, this display is displayed on the display 10. It may be used as a dual purpose or diverted.

The display 10 displays the fatigue damage degree D in response to a display request of the fatigue damage degree D by a maintenance worker, a driver, or the like, and displays the accumulated data of the vehicle running state in association with the fatigue damage degree D. The display 10 displays the accumulated data of the vehicle running state and the fatigue damage degree D that are related in time series, such as displaying the accumulated data of the vehicle running state and the fatigue damage degree D at the same time, for example.
Further, the display 10 displays large input data that is a level value I _k corresponding to a stress amplitude S _k that is greater than or equal to the intercept stress amplitude S _a , together with the accumulated data of the vehicle running state and the fatigue damage degree D.

The data output unit 20 outputs the calculated fatigue damage degree D in response to an output request from a maintenance worker, a driver, or the like, and outputs the accumulated data of the vehicle running state in association with the fatigue damage degree D. For example, the accumulated data of the vehicle running state and the fatigue damage degree D, which are correlated in time series, such as outputting the accumulated data of the vehicle running state at the same time and the fatigue damage degree D, are output.
The data output unit 20, together with the accumulated data, and fatigue damage degree D of a vehicle running state, and outputs a large input data with the level value I _k corresponding to sections stress amplitude S _a more stress amplitude S _k.

  As the data output unit 20, an interface capable of communicating the fatigue damage degree D with the outside of the vehicle 1 can be applied, and a wired or wireless one can be applied. Data output unit 20 may be arranged integrally with vehicle ECU 100.

Based on the calculated fatigue damage degree D, the warning device 30 warns that the life of the front side member 2a is near or that the replacement time is approaching. The warning by the warning device 20 is made by, for example, making a sound or warning display to the driver when a predetermined warning threshold value _Dth is exceeded.
The warning threshold value D _th corresponds to the life warning line L2 of the SN characteristic 124, and is based on the characteristics of the front side member 2a in advance as a threshold value at which the life of the front side member 2a is approaching or the replacement time is approaching. Set experimentally and empirically.

[Action / Effect]
Since the vehicle fatigue damage degree diagnosis system according to the embodiment of the present invention is configured as described above, for example, the vehicle ECU 100 performs the diagnosis of the fatigue damage degree D as shown in FIG. This diagnosis flow is performed periodically every several tens of milliseconds, for example, when the vehicle is operating, that is, when the key switch is on.

When the diagnosis flow is started, the process proceeds to step S10, and sensor information (information of the input correlation value I) detected by each sensor 5 attached to the front, rear, left, and right lower arms 4 is collected.
In step S20, an input correlation value I is calculated. If each sensor 5 is a combination of a plurality of types of sensors such as a strain sensor, an acceleration sensor, and a load sensor, an input correlation value I obtained by weighting each detection value by each type of sensor is calculated. If there is one type of sensor 5, the input correlation value I detected by each sensor 5 can be used as it is, and this step S20 may be omitted. Then, the process proceeds to step S21.

In step S21, the level value I _k selected by the above storage method based on the input correlation value I calculated in step S20 is cumulatively stored in the memory 110. This level value I _k is cumulatively stored in the memory 110 as the level value I _k for each of the input correlation values I detected by the sensors 5 provided on the lower arms 4 of the front, rear, left and right wheels 3. Then, the process proceeds to step S22.
In step S22, by applying the level value I _k stored in the memory 110 to the IS characteristics 122 reads the stress amplitude S _k of the corresponding front side member 2a to the level value I _k. Then, the process proceeds to step S24.

In step S24, by applying a stress amplitude S _k read in step S22 to the SN characteristics 124 reads the number N _Lim (S _k) in damage to the front side members 2a repeated stress amplitude S _k input. Then, the process proceeds to step S30.
In step S30, the fatigue damage calculation unit 130a, occurrence frequency N (S number N _Lim (S _k) and the stress amplitude S _k be damaged repeatedly inputting the stress amplitude S _k read in step S22 and step S24 _k )), the fatigue damage degree D is calculated by the following equation (1). Then, the process proceeds to step S40.
D = ΣN (S _k ) / N _Lim (S _k ) (1)

In step S40, the calculated fatigue damage degree D is stored in the memory 110. Thereby, in step S30 of the diagnostic flow of the next cycle, if the damage degree N (S _k ) / N _Lim (S _k ) per cycle of the next control flow is calculated, the fatigue damage degree D of the current cycle is calculated. The accumulated fatigue damage degree D can be calculated by reading and adding from the memory 110.
In step S50, it is determined whether or not there is a request for displaying the fatigue damage degree D. If there is a display request, the process proceeds to step S55, and if there is no display request, the process proceeds to step S60.

In step S55, the fatigue damage degree D is displayed on the display 10 in association with the running state data (cumulative data) of the vehicle 1. In this case, if there is large input data, it is displayed together with the fatigue damage degree D. Then, the process proceeds to step S60.
In step S60, it is determined whether or not there is a request for output of the fatigue damage degree D. If there is an output request, the process proceeds to step S65, and if there is no output request, the process proceeds to step S70.

  In step S <b> 65, the fatigue damage degree D is output by associating the driving state data (cumulative data) of the vehicle 1 with the data output unit 20. In this case, if there is large input data, it is output together with the fatigue damage degree D. Then, the process proceeds to step S70.

In step S70, it is determined whether the fatigue damage degree D is larger than the warning threshold value _Dth . If the fatigue damage degree D is greater than the warning threshold D _th proceeds to step S75, the fatigue damage D is returns equal to or smaller than the warning threshold D _th.
In step S75, for example, a sound or a warning display is issued to warn the driver that the life of the front side member 2a is near or that the replacement time is approaching. Then return.

Therefore, according to the fatigue damage level diagnosis system for a vehicle of this embodiment, the IS value 122 and the SN property 124 recorded in the database 120 are used to determine the cumulative value of the level value I _k and the fatigue life of the front side member 2a. The fatigue damage degree D for the front side member 2a can be calculated based on the corresponding relationship. Thereby, based on the calculated fatigue damage degree D, the front side member 2a can be replaced at an appropriate timing, and the front side member 2a can be appropriately maintained.

  Further, as the input correlation value I correlated with the input applied to the vehicle 1 during traveling, at least one of the distortion, acceleration, and load of the lower arm 4 is used. Therefore, the sensor 5 such as a distortion detection sensor, an acceleration detection sensor, or a load detection sensor. The input correlation value I can be reliably detected.

The database 120, and IS characteristics 122 and stress amplitude S _k by an input applied to level values I _k and the front side member 2a is made to correspond, stress amplitude S _k and the stress fatigue life and amplitude S _k is repeatedly input Since the SN characteristic 124 indicating the relationship with the number of times N _Lim (S _k ) is recorded, the IS amplitude 122 is used to determine the stress amplitude S _k of the front side member 2a according to the level value I _k. The number of repeated inputs N _Lim (S _k ) of the stress amplitude S _k obtained using the IS characteristic 122 can be obtained using the SN characteristic 124. Repeat for each input number of inputs N _Lim (S _k) stress amplitude for S _k of occurrences N of (S _k) by calculating from the equation (1) can be obtained fatigue damage degree D of the front side member 2a.

According to the equation (1), the fatigue damage degree D is accurately calculated because the fatigue damage degree D is calculated by weighting and accumulating the number of occurrences N (S _k ) of the stress amplitude S _k corresponding to the level value I _k. And the fatigue damage degree D of the front side member 2a can be accurately estimated based on the life of the front side member 2a.

  Further, since the vehicle 1 includes the display 10 that displays the fatigue damage degree D in response to the display request, the vehicle 1 can display the fatigue damage degree D in response to the display request. The fatigue damage degree D of 2a can be recognized.

  Since the data output unit 20 that outputs the data of the fatigue damage degree D in response to the output request is provided, for example, the data of the fatigue damage degree D can be output during vehicle maintenance, and the front side member 2a can be appropriately maintained. In addition, the maintenance worker, the driver, and the like can recognize the fatigue damage degree D of the front side member 2a.

  Since the warning device 30 that warns that the life of the front side member 2a is near to the end or the replacement time is coming based on the fatigue damage degree D is provided, for example, the life of the front side member 2a is close to the driver of the vehicle 1 Or it can warn that it is time to replace. Thereby, replacement and repair of the front side member 2a can be promoted, and damage can be prevented in advance.

Further, the memory 110 cumulatively stores the level value I _k together with the driving state data of the vehicle 1 (for example, the state of the transmission such as the selected gear, the engine torque, and the engine speed), and uses the IS characteristic 122. stress amplitude S _k obtained Te is the case where the intercept stress amplitude S _a or stores the level value I _k corresponding to the section stress amplitude S _a more stress amplitude S _k in the memory 110 as a large input data Therefore, large input data as damage factors other than damage due to fatigue can be displayed or output together with the fatigue damage degree D associated with the running state data of the vehicle 1. Thereby, not only the front side member 2a but also other vehicle members or parts can be determined for maintenance, and appropriate maintenance and replacement of members and the like can be promoted.

[Others]
Although the embodiments of the present invention have been described above, the present invention is not limited to the above-described embodiments, and various modifications can be made without departing from the spirit of the present invention.
In the above-described embodiment, the front side member 2a has been described as a fatigue diagnosis target member. However, the fatigue diagnosis target member is not limited to this, and other vehicle body members such as the cross member 2b and suspension devices such as suspension arms. Arbitrary members or parts of the vehicle 1 such as members or welded parts of the members can be set. In this case, IS characteristics and SN characteristics corresponding to an arbitrary member or part of the vehicle 1 set as a fatigue diagnosis target member are set in advance, and the fatigue damage degree D is calculated.

  In the above-described embodiment, the lower arm 4 is set as the main part of the vehicle. However, the main part of the vehicle is not limited to this, and the members of the vehicle body 2 that are members such as the front side member 2a and the cross member 2b An arbitrary member or part of the vehicle 1 exemplified as a member or part of a suspension device such as a suspension arm can be set. In this case, the fatigue damage degree D is calculated by presetting IS characteristics and SN characteristics corresponding to an arbitrary member or part of the vehicle 1 set as a main part of the vehicle.

That is, any member or part of a vehicle can be set in the fatigue diagnosis target member and the main part of the vehicle. In this case, the IS characteristic corresponding to the main part of the vehicle and the fatigue diagnosis target member are supported. SN characteristics are set in advance. According to this, the fatigue damage degree D of various members to be subjected to fatigue diagnosis can be calculated from the input correlation value I detected in the main part of an arbitrary vehicle.
Further, in the above-described embodiment, the configuration of the vehicle 1 of the independent suspension system including the lower arm 4 is illustrated, but an axle suspension system such as a leaf spring type or a coil spring type may be adopted.

  In the above-described embodiment, the input correlation value I is cumulatively stored in the memory 110, the input correlation value I is read from the memory 110, and the IS and SN characteristics are sequentially applied to calculate the fatigue damage degree D. Although shown, the fatigue damage degree D may be calculated every time the input correlation value I is detected without storing the input correlation value I in the memory, and the fatigue damage degree D may be stored cumulatively in the memory 110.

  In the above-described embodiment, the input correlation value I is selected by the so-called level cross method and stored cumulatively. However, the present invention is not limited to this, and the rain flow method, the peak count method, the range count method, etc. A frequency analysis method may be applied.

In the above embodiments have been described to be stored in the memory 110 the level value I _k corresponding to sections stress amplitude S _a more stress amplitude S _k as large input data, preset value I _th or level values I _k of may be stored in the memory 110 as a large input data. As this preset value I _th , a level value I _k corresponding to a stress amplitude S _k greater than or equal to the intercept stress amplitude S _a is preset.

  The vehicle fatigue damage level diagnosis system of the present invention can be applied not only to automobiles but also to various vehicles such as motorcycles and railways.

1 Vehicle 2 Body 2a Front side member (fatigue diagnosis target)
2b Cross member 4 Lower arm (main part of vehicle)
5 Sensor (detection means)
10 Display (display means)
20 Data output section (data output means)
30 Warning device (Warning means)
110 memory (cumulative storage means)
120 Database 122 IS characteristics (first correspondence)
124 SN characteristics (second correspondence)
130a Cumulative damage degree calculation part (calculation means)

Claims (5)

Detection means for detecting an input correlation value correlated with the magnitude of input applied to the vehicle during traveling;
Cumulative storage means for cumulatively storing the input correlation values detected by the detection means as cumulative values;
A database in which a correspondence relationship between a fatigue life related to a fatigue diagnosis target of the vehicle and the cumulative value stored in the cumulative storage means is recorded;
A vehicle fatigue damage degree diagnosis system comprising: a calculation unit that calculates a fatigue damage degree of the fatigue diagnosis target based on the cumulative value and the correspondence relationship recorded in the database. The detection means is a distortion detection means for detecting distortion of the main part of the vehicle as the input correlation value, an acceleration detection means for detecting acceleration of the main part of the vehicle as the input correlation value, and the input correlation value as the input correlation value At least one of load detection means for detecting a load applied to a main part of the vehicle,
In the database, as the correspondence relationship, a first correspondence relationship in which the input correlation value detected by the detection unit and the stress amplitude S applied to the fatigue diagnosis target are associated with each other, and a stress applied to the fatigue diagnosis target. A second correspondence relationship, which is an SN characteristic indicating the relationship between the amplitude S and the number of repeated inputs N of the stress amplitude S and the fatigue life, is recorded,
The calculation means is obtained using the number of occurrences N (S _k ) of the stress amplitude S _k corresponding to the input correlation value obtained using the first correspondence and the second correspondence. 2. The fatigue damage degree diagnosis for a vehicle according to claim 1, wherein the fatigue damage degree D is calculated from the repeated input number N _Lim (S _k ) of the stress amplitude S _{k by} the following equation (1). system.
D = Σ {N (S _k ) / N _Lim (S _k )} (1) The main part of the vehicle is a main part of the suspension or the vehicle body of the vehicle,
3. The vehicle fatigue damage diagnosis system according to claim 2, wherein the fatigue diagnosis target is a suspension or a vehicle body member or part of the vehicle. Display means for displaying the fatigue damage degree D in response to a display request;
Data output means for outputting the fatigue damage degree D data in response to an output request;
The warning means which warns that the lifetime of the said fatigue diagnosis object is near based on the said fatigue damage degree D, or the replacement time has come, The any one of Claims 1-3 characterized by the above-mentioned. The vehicle fatigue damage degree diagnosis system according to Item 1. The cumulative storage means cumulatively stores the input correlation value together with the driving state data of the vehicle, and stores the input correlation value as large input data when the input correlation value is equal to or greater than a preset value.
In response to a display request, the display means displays cumulative data that is the value of the cumulatively stored running state data in association with the fatigue damage degree, displays the large input data,
5. The vehicle fatigue damage level diagnosis according to claim 4, wherein the data output means outputs the accumulated data in association with the fatigue damage level and outputs the large input data in response to an output request. system.

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