Fatigue estimation device, remaining life estimation system, and fatigue estimation method

Abstract

To provide a fatigue estimation device capable of precisely calculating fatigue variable values even when the storage space for the data representing the values of the stress variables is limited.SOLUTION: A CPU 22 performs sampling of the current each time when the inverter 16 outputs, and updates a temporary storage area 26a. When detecting the start of vehicle VC, the CPU 22 calculates time series data of the torque by using all the currents stored in the temporary storage area 26a at that time, and stores the same in a storage area 26b. When the vehicle VC is running, the CPU 22 calculates the torque from the sampling value of the current each time, and stores the same in the storage area 26b. When the amount of data stored in the storage area 26b reaches a predetermined amount, the CPU 22 calculates fatigue variable values of a power transmission device 12 by the rain flow method.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a fatigue estimation device, a remaining life estimation system, and a fatigue estimation method. [Background technology]

[0002] For example, Patent Document 1 below describes a device for calculating the fatigue damage level of a vehicle fatigue diagnosis target. This device cumulatively stores detection values ​​of a sensor that detects strain applied to the diagnosis target, and calculates the fatigue damage level of the diagnosis target based on the stored detection values. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2013-79920 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, the larger the maximum value of the strain, the greater the degree of fatigue damage is likely to be. Therefore, if the transition of the magnitude of strain around the maximum value of the strain cannot be stored sufficiently, the accuracy of the calculation of the degree of fatigue damage may be reduced. On the other hand, when the detection values ​​are stored cumulatively as in the above device, the storage device has a finite storage area, and therefore, discontinuities occur in the time series data of the detection values. As a result, the transition of the magnitude of strain around the maximum value cannot be stored sufficiently, and the accuracy of the calculation of the degree of fatigue damage may be reduced. [Means for solving the problem]

[0005] Means for solving the above problems and their effects will be described below. 1. A system including an execution device and a storage device, the execution device executing an acquisition process, an activation detection process, a stress variable storage process, a fatigue variable calculation process, and a fatigue variable storage process, the acquisition process being a process of repeatedly acquiring a value of a stress variable, the stress variable being a variable indicating a stress of a power transmission device to which power from a drive source is transmitted, the activation detection process being a process of detecting the activation of the drive source, the stress variable storage process being a process of storing in the storage device each of the values ​​of the stress variables acquired each time by the acquisition process, and the fatigue variable calculation process being a process of newly recording in the storage device. a fatigue estimation device in which the fatigue variable storage process is a process of calculating a value of a fatigue variable based on a predetermined amount of time series data each time the time series data of the stored stress variable reaches a predetermined amount, the fatigue variable being a variable indicating fatigue of the power transmission device, the fatigue variable storage process is a process of storing fatigue variable data corresponding to the value of the fatigue variable in the storage device, and the stress variable storage process is a process of starting to overwrite a new value of the stress variable in a memory area in which the value of the stress variable is already stored each time the predetermined amount is exceeded and each time the startup is detected by the startup detection process.

[0006] In the above configuration, each time the amount of data stored in the storage area that stores the value of the stress variable that is the input of the fatigue variable calculation process reaches a predetermined amount, the data in the storage area is overwritten. Therefore, the input of the fatigue variable calculation process does not necessarily include all data near the maximum value of the stress variable. Here, in the above configuration, each time a start is detected, the amount of data stored in the storage area that stores the value of the stress variable that is the input of the fatigue variable calculation process is overwritten. This allows a sufficient amount of data indicating the value of the stress variable from the start to be stored in the storage area. In particular, since the value of the stress variable at the start is likely to be large, the value of the fatigue variable can be calculated with high accuracy when the fatigue of the power transmission device becomes noticeable. Therefore, in the above configuration, the value of the fatigue variable can be calculated with high accuracy in grasping the degree of deterioration of the power transmission device, compared to a case where the amount of data indicating the value of the stress variable from the start can be small.

[0007] 2. The execution device is a fatigue estimation device described in 1 above, which executes a stop detection process to detect a stop of the driving source, and the fatigue variable calculation process includes a process of calculating a value of the fatigue variable based on the time series data newly stored in the memory device until the stop is detected by the stop detection process.

[0008] In the above configuration, the value of the fatigue variable is calculated when a stop is detected, so that even if the memory area is overwritten when starting up after the stop, the value of the fatigue variable can be calculated using the data stored in the memory area before the stop.

[0009] 3. The fatigue estimation device according to claim 1 or 2, wherein the fatigue variable calculation process is a process of calculating the value of the fatigue variable based on a maximum value and a minimum value of the stress variable. The fatigue variable calculation process calculates the value of the fatigue variable based on the maximum and minimum values ​​of the stress variable. Here, if the memory area that stores the stress variable value is overwritten, the maximum or minimum value may not be identified with high accuracy. In particular, when the maximum value tends to be large, such as at startup, if the maximum and minimum values ​​cannot be identified with high accuracy, the fatigue variable value may not be calculated with high accuracy. For this reason, it is particularly effective to start overwriting the memory area at the time startup is detected.

[0010] 4. A fatigue estimation device as described in any one of claims 1 to 3 above, wherein the fatigue variable storage process is a process of classifying the value of the fatigue variable calculated by the fatigue variable calculation process according to the magnitude of the value of the fatigue variable, counting the number of times the value is classified into each magnitude, and storing the counted values ​​in the storage device as the fatigue variable data.

[0011] In the above-described configuration, by storing the frequency classified according to the magnitude of the fatigue variable, it is possible to store accurate information regarding the degree of fatigue of the power transmission device with a small data storage capacity.

[0012] 5. The fatigue estimation device according to any one of 1 to 4 above, wherein the drive source is a device that generates thrust for a vehicle, and the power transmission device is a device that transmits the power of the drive source to drive wheels of the vehicle.

[0013] When the device generating the thrust of the vehicle is started, the stress applied to the power transmission device is particularly large in order to transition the vehicle from a stationary state to a running state. Therefore, it is particularly effective in determining the degree of deterioration of the power transmission device with high accuracy to calculate the value of the fatigue variable by continuously using the value of the stress variable near the start-up.

[0014] 6. A fatigue estimation device as described in above 5, wherein the start-up detection process is a process for detecting the start of the vehicle, and the acquisition process includes a standby detection process, a specified amount storage process, and a stress variable calculation process, and the standby detection process is a process for determining that the vehicle is in a standby state when the shift position of the vehicle is in a driving range, the specified amount storage process is a process for storing each time value for either the value of the stress variable or the value of the stress correlation variable in the storage device, and each time the amount of stored data reaches a specified amount, starting to overwrite the each time value in the storage area in which the each time value is already stored, the stress correlation variable is a variable for calculating the value of the stress variable and is a variable indicating the state of the driving source, the stress variable calculation process is a process for calculating the value of the stress variable based on the value of the stress correlation variable, and the data overwritten in the storage area when the start-up is detected includes data based on the value for the one stored by the specified amount storage process before the start-up was detected, and the specified amount is smaller than the predetermined amount.

[0015] In the above configuration, when a standby state is detected, one of the two values, the stress variable value or the stress correlation variable value used to calculate the stress variable value, is stored in the storage device. Then, when a start of the vehicle is detected, the stress variable value corresponding to the one value stored before the start of the vehicle is overwritten in the storage area. Therefore, time series data of the stress variable value near the start of the vehicle can be stored in detail in the storage area.

[0016] 7. The execution device is the fatigue estimation device according to claim 5 or 6, which executes an output process for outputting data according to a calculation result of the value of the fatigue variable by the fatigue variable calculation process to the outside of the vehicle.

[0017] In the above configuration, by outputting data corresponding to the calculation results of the fatigue variable value to the outside of the vehicle, the remaining life of the power transmission device, etc. can be determined outside the vehicle based on the data, and the information can be utilized.

[0018] 8. A remaining life estimation system comprising the fatigue estimation device according to 7 above, and a remaining life estimation device that estimates a remaining life of the power transmission device based on a value of the fatigue variable. Since the value of the remaining life variable is easier to understand the state of the power transmission device compared to the value of the fatigue variable, according to the above configuration, the state of the power transmission device can be easily understood by calculating the value of the remaining life variable.

[0019] 9. A fatigue estimation method, comprising the steps of executing each of the processes in the fatigue estimation device according to any one of 1 to 7 above, by a computer. [Brief description of the drawings]

[0020] [Figure 1] FIG. 1 is a block diagram showing a configuration of a remaining life estimation system according to an embodiment. [Diagram 2] 4 is a flowchart showing the procedure of a process executed by the fatigue estimation device according to the embodiment. [Diagram 3] FIG. 4 is a diagram illustrating classification data according to the embodiment. [Figure 4]4A and 4B are flowcharts showing the procedure of a process executed by the remaining life estimation system according to the embodiment. [Diagram 5] 6A and 6B are diagrams showing the effect of the embodiment; DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0021] Hereinafter, an embodiment will be described with reference to the drawings. Fig. 1 shows a remaining life estimation system according to this embodiment. As shown in Fig. 1, a vehicle VC is equipped with a motor generator 10 as a thrust generating device for the vehicle VC. The motor generator 10 is mechanically connected to driving wheels 14 via a power transmission device 12. The power transmission device 12 is equipped with a differential gear. The output voltage of an inverter 16 is applied to the terminals of the motor generator 10.

[0022] The fatigue estimation device 20 is a device that executes a process for estimating the degree of fatigue of the power transmission device 12. The fatigue estimation device 20 may be configured by a control device that controls the control amount of the vehicle VC as a control target. When estimating the degree of fatigue, the fatigue estimation device 20 refers to currents iu, iv, and iw that are output currents of the inverter 16 detected by a current sensor 30. The fatigue estimation device 20 also refers to an output signal Sm of a rotation angle sensor 32 that detects the rotation angle of the motor generator 10. The fatigue estimation device 20 also refers to a shift variable Vsft that is a variable indicating a shift position detected by a shift position sensor 34. The shift variable Vsft indicates brake, parking, drive, reverse, etc.

[0023] The fatigue estimation device 20 includes a CPU 22, a ROM 24, a RAM 26, a storage device 27, and an external interface 28, which are capable of communicating with each other via a local network 29. The storage device 27 is an electrically rewritable non-volatile device. The external interface 28 is an output device that outputs data to the outside of the fatigue estimation device 20 by at least one of wireless communication and wired communication.

[0024] The remaining life estimation device 50 is a device that imports data from the vehicle VC and estimates the remaining life of the power transmission device 12 based on the imported data. The remaining life estimation device 50 is equipped with a CPU 52, a ROM 54, a storage device 57, and an external interface 58, which are capable of communicating with each other via a local network 59. The external interface 58 is an input device into which data from outside the remaining life estimation device 50 is input via at least one of wireless communication and wired communication.

[0025] Fig. 2 shows the procedure of the process executed by the fatigue estimation device 20. The process shown in Fig. 2 is realized by the CPU 22 repeatedly executing a program stored in the ROM 24, for example, at a predetermined interval. Note that, hereinafter, the step number of each process is represented by a number preceded by "S."

[0026] In the series of processes shown in FIG. 2, the CPU 22 first determines whether or not the range is a driving range (S10). The CPU 22 determines that the range is a driving range when the value of the shift variable Vsft is not a value indicating either the parking or neutral range. When the CPU 22 determines that the range is a driving range (S10: YES), the CPU 22 samples the currents id and iq of the dq axes (S12). This process includes a process of sampling the currents iu, iv, and iw and performing a dq conversion on the sampled values. Next, the CPU 22 updates the data stored in the temporary storage area 26a of the ROM 24 shown in FIG. 1 with the newly sampled currents id and iq (S14). Here, the CPU 22 sequentially stores the time series data of the currents id and iq according to the predetermined addresses of the temporary storage area 26a. Then, the CPU 22 determines whether or not the amount of data updated by the process of S14 has reached a specified amount (S16). The specified amount is the amount of data that can be stored in the temporary storage area 26a. Therefore, the specified amount is equal to the update amount at the time when the data is updated from the first to the last of the above-mentioned predetermined addresses. When the CPU 22 determines that the specified amount has been reached (S16: YES), it initializes the update address of the temporary storage area 26a (S18). As a result, in the next process of S14, the data of the first address among the above-mentioned predetermined addresses is updated.

[0027] When the process of S18 is completed or when a negative determination is made in the process of S16, the CPU 22 determines whether or not the flag F is "1" (S20). The flag F is "1" when the vehicle VC is in a running state, and is "0" when the vehicle VC is in a stopped state. When the CPU 22 determines that the flag F is "0" (S20: NO), the CPU 22 determines whether or not the vehicle VC has started moving (S22). When the rotation speed Nm of the motor generator 10 is equal to or higher than a start determination value Nstart, the CPU 22 determines that the vehicle VC has started moving. The rotation speed Nm is calculated by the CPU 22 using the output signal Sm as an input.

[0028] When it is determined that the vehicle has started moving (S22: YES), the CPU 22 assigns "1" to the flag F (S24). Next, the CPU 22 calculates the torque Trq of the motor generator 10 from each pair of the currents id, iq stored in the temporary storage area 26a (S26). Next, the CPU 22 updates the data stored in the recording area 26b of the RAM 26 shown in FIG. 1 with the calculated torque Trq (S28). Here, the CPU 22 sequentially stores the time series data of the torque Trq according to a predetermined address in the recording area 26b.

[0029] Then, the CPU 22 judges whether the amount of data updated by the process of S28 has reached a predetermined amount (S30). The predetermined amount is the amount of data that can be stored in the recording area 26b. Therefore, the predetermined amount coincides with the amount of data updated when data is updated from the beginning to the end of a predetermined address in the recording area 26b. The predetermined amount is an amount larger than the above-mentioned specified amount. If the CPU 22 judges that the predetermined amount has been reached (S30: YES), it initializes the update address of the recording area 26b (S32). As a result, in the next process of S28, the data at the first address of the predetermined addresses in the recording area 26b will be updated.

[0030] On the other hand, when the CPU 22 determines that the flag F is "1" (S20: YES), the CPU 22 determines whether the vehicle VC has stopped (S46). The CPU 22 determines that the vehicle VC has stopped when the rotation speed Nm of the motor generator 10 is equal to or lower than a stop determination value Nstop. The stop determination value Nstop is set to a value smaller than the start determination value Nstart.

[0031] When the CPU 22 determines that the motor is not stopped (S46: NO), the CPU 22 proceeds to the process of S26. In this case, in the process of S26, the CPU 22 calculates one torque Trq from one pair of the currents id and iq newly updated in the process of S14. In this case, the newly updated data in the process of S28 is also only the data of one torque Trq.

[0032] On the other hand, if the CPU 22 determines that the operation has stopped (S46: YES), the CPU 22 sets the flag F to "0" (S48). Then, the CPU 22 proceeds to the process of S32. When the CPU 22 completes the process of S32, it executes rainflow processing based on the time series data of the torque Trq stored in the recording area 26b (S34). Then, the CPU 22 classifies the value of the fatigue variable Vf calculated by the rainflow processing according to its magnitude, and stores it in the storage device 27 shown in FIG. 1 (S36). Here, the fatigue variable Vf is a variable indicating the degree of deterioration of the power transmission device 12. The degree of deterioration is quantified according to the hysteresis loop of the stress grasped by the rainflow processing. Classifying the fatigue variable Vf is an act of determining which of a plurality of regions, which are divided in advance according to the magnitude of the fatigue variable Vf, the variable Vf falls into. The storage device 27 stores classification data 27a, which is data indicating the number of times the variable Vf falls into each of the plurality of regions.

[0033] An example of the classification data 27a is shown in Fig. 3. Fig. 3 shows that the magnitude of the fatigue variable Vf is classified into a range of "0 to 20", a range of "20 to 40", a range of "40 to 60", etc.

[0034] In the process of S36, the CPU 22 classifies each of the values ​​of the fatigue variable Vf newly calculated in the process of S34, and counts the number of values ​​that fall into each range. Then, the CPU 22 updates the classification data 27a stored in the storage device 27 with the counted values.

[0035] When the CPU 22 completes the process of S36, the CPU 22 temporarily ends the series of processes shown in FIG. Fig. 4 shows the procedure of the calculation process of the remaining life variable Vrl using the classification data 27a. The process shown in Fig. 4(a) is realized by the CPU 22 repeatedly executing a program stored in the ROM 24 of the fatigue estimation device 20, for example, at a predetermined cycle. The process shown in Fig. 4(b) is realized by the CPU 52 repeatedly executing a program stored in the ROM 54 of the remaining life estimation device 50, for example, at a predetermined cycle.

[0036] 4(a), the CPU 22 first determines whether or not there is a request to output the classification data 27a (S40). For example, if the external interface 28 includes a device that outputs the classification data 27a via wireless communication, the request may be generated when a predetermined amount of time has elapsed since the process of S42 was executed. Also, for example, if the external interface 28 includes a device that outputs the classification data 27a via wired communication, the request may be generated when a member external to the vehicle VC is connected to the external interface 28.

[0037] When the CPU 22 determines that a request has been made (S40: YES), it outputs the classified data 27a to the outside via the external interface 28 (S42). When the CPU 22 completes the process of S42 or when the process of S40 makes a negative determination, it temporarily ends the series of processes shown in FIG. 4(a).

[0038] 4(b), the CPU 52 acquires the classified data 27a (S50). Here, for example, if the classified data 27a is transmitted to the remaining life estimation device 50 by wireless communication in the process of S42, the process of S50 may be a process of receiving the transmitted classified data 27a. Also, for example, if the classified data 27a is output by wired communication in the process of S42, the process may be a process of receiving the classified data 27a transmitted by wireless communication from the device that imported the classified data 27a. Alternatively, a storage medium that stores the output classified data 27a may be connected to the external interface 58, and the classified data 27a may be acquired by wired communication.

[0039] Next, the CPU 52 calculates the value of the remaining life variable Vrl for each component of the power transmission device 12 based on the classification data 27a (S52). The remaining life variable Vrl is a variable that indicates the remaining life of the object whose remaining life is to be estimated. The remaining life variable is quantified as a value obtained by subtracting the current degree of deterioration from the upper limit value of the degree of deterioration. The degree of deterioration is calculated by the CPU 52 using the classification data 27a as an input.

[0040] Specifically, for example, the following may be performed. That is, the CPU 52 calculates a classified damage degree as a variable indicating the degree of deterioration based on the number of times in each area in the classification data 27a. The CPU 52 then calculates a cumulative fatigue damage degree, which is the sum of the classified damage degrees of each of the multiple areas. The difference between this cumulative fatigue damage degree and "1" is proportional to the remaining life. Therefore, the CPU 52 calculates the value of the remaining life variable Vrl by multiplying a value obtained by subtracting the cumulative fatigue damage degree from "1" by a value indicating a predetermined life.

[0041] Here, the relationship between the number of times in each region and the classified damage level is set separately for each component constituting the power transmission device 12. This is because the degree of fatigue relative to the magnitude of the fatigue variable Vf differs for each component.

[0042] Next, the CPU 52 stores remaining life data 57a in the storage device 27 shown in Fig. 1 (S54). If remaining life data 57a for the target power transmission device 12 has already been stored in the storage device 27, the process of S42 updates the already stored remaining life data 57a with the data newly generated by the process of S50. The remaining life data 57a is a variable that indicates the value of the remaining life variable Vrl for each component.

[0043] When the CPU 52 completes the process of S54, it temporarily ends the series of processes shown in FIG. Here, the operation and effects of this embodiment will be described.

[0044] The CPU 22 periodically samples the currents id and iq output by the inverter 16 and stores them in a predetermined order in the temporary storage area 26a of the RAM 26. Since the data capacity of the temporary storage area 26a is a specified amount, the CPU 22 initializes the address in the temporary storage area 26a where the currents id and iq should be stored next each time the amount of data of the currents id and iq stored in the temporary storage area 26a reaches the specified amount. This causes the temporary storage area 26a to be overwritten each time the specified amount of data is written.

[0045] When the rotation speed Nm of the motor generator 10 becomes equal to or greater than the start determination value Nstart and thus the CPU 22 detects a start, it calculates the torque Trq from the currents id and iq stored in the temporary storage area 26a at that time, and stores the torque Trq in the recording area 26b. As a result, time series data of the torque Trq calculated from the specified amount of data of the currents id and iq is stored in the recording area 26b. Furthermore, after the vehicle VC starts, the CPU 22 calculates the torque Trq based on the currents id and iq sampled periodically, and stores the torque Trq in the recording area 26b. As a result, the time series data of the torque Trq from immediately before the vehicle VC starts is stored in the recording area 26b.

[0046] When the amount of data stored in the recording area 26b reaches a predetermined amount, the CPU 22 calculates the value of the fatigue variable Vf by rainflow processing using the time-series data of the torque Trq stored in the recording area 26b.

[0047] Here, the stress applied to the power transmission device 12 tends to be particularly large when the vehicle VC starts moving. One of the reasons for this is that the coefficient of static friction between the drive wheels 14 and the road surface is greater than the coefficient of kinetic friction. Here, deterioration of the power transmission device 12 becomes noticeable when the stress is large. In particular, when the magnitude of the stress is large, deterioration is accelerated exponentially.

[0048] On the other hand, according to the rainflow process, the magnitude of the stress is grasped according to the difference between the maximum and minimum values ​​of the time series data of the torque Trq, which has a positive correlation with the stress. Therefore, by continuously using the time series data of the torque Trq before and after the start, the stress at the time of starting can be grasped with high accuracy.

[0049] FIG. 5(a) illustrates an example of the time series data of the torque Trq according to this embodiment. In FIG. 5(a), the CPU 22 detects a start at time t2, and stores the time series data Trq of the torque Trq from time t1 onward in the storage area 26b. Then, when the CPU 22 detects a stop of the vehicle at time t3, it calculates the value of the fatigue variable Vf by rainflow processing using the time series data of the torque Trq from time t1 to t3. The CPU 22 also detects a start at time t5, and stores the time series data Trq of the torque Trq from time t4 onward in the storage area 26b. Then, when the CPU 22 detects a stop of the vehicle VC at time t6, it calculates the value of the fatigue variable Vf by rainflow processing using the time series data of the torque Trq from time t4 to t6.

[0050] Here, the rainflow process based on the time series data of the torque Trq in the period from time t4 to t6 is as follows. That is, point P1 which is the minimum value, point P2 which is the maximum value, and point P3 which is the minimum value are extracted from the time series data, and point P1 is set as the start point and point P3 is set as the end point.

[0051] Consider the case where raindrops flow from point P1 with the left side of FIG. 5 as the upper side. The raindrops that flow to point P2 continue to flow to point P3 because point P3, which is the next minimum value of point P2, is greater than point P1. Next, the raindrops that flow to point P3 continue to flow in the horizontal direction in the figure because point P4, which is the next maximum value of point P3, is smaller than point P2, and when they reach point P3a, they flow to point P5. As a result, points P1, P3, P3a, and P5 determine one strain width. There are other strain widths that are determined at times t4 to t6 by the rainflow process, but the above is the maximum. Other strain widths do not affect the following discussion, so their explanation is omitted.

[0052] In contrast, Fig. 5(b) illustrates a case in which the detection of starting and stopping is not used to start and stop recording the time series data of the torque Trq in the recording area 26b. Note that the torque waveforms in Fig. 5(b) and Fig. 5(a) are the same.

[0053] FIG. 5(b) shows an example in which the time series data of the torque Trq from time 11 onward is recorded in the recording area 26b, and the amount of data recorded in the recording area 26b reaches a predetermined amount at time t12. In this case, it is not possible to record the continuous time series data of the torque Trq from time t4 to t6 shown in FIG. 5(a). Therefore, one strain width is determined by points P1, P2, and P6. Therefore, the maximum value of the stress applied to the power transmission device 12 due to the start immediately after time t4 is underestimated.

[0054] According to the present embodiment described above, the following actions and effects can be obtained. (1) When the CPU 22 detects the stop of the vehicle VC, it initializes the address in the recording area 26b where data should be recorded next even if the amount of data stored in the recording area 26b does not reach a predetermined amount. Then, when the CPU 22 detects the stop of the vehicle VC, it calculates the value of the fatigue variable Vf based on the time series data of the torque Trq stored in the recording area 26b. As a result, while storing the time series data of the torque Trq from the address at the start of writing in the recording area 26b when the vehicle VC starts after stopping, it is possible to calculate the value of the fatigue variable Vf using the stress applied until the vehicle VC stops. Here, when the vehicle VC stops, the stress applied to the power transmission device 12 tends to be small. Therefore, according to this embodiment, it is possible to calculate the stress applied until the vehicle VC stops and the stress after the vehicle starts without omission. Therefore, it is possible to calculate the value of the fatigue variable Vf with high accuracy.

[0055] (2) The value of the fatigue variable Vf was calculated by rainflow processing using the time series data of the torque Trq. In the rainflow processing, the amount of time series data used to calculate one strain width varies depending on the magnitude of adjacent maximum values ​​and adjacent minimum values. If the time series data is cut off midway, there is a risk that the time series data that should be used to calculate one strain width cannot be used. For this reason, the above setting, which can store time series data from immediately before the vehicle VC starts to the upper limit of the data capacity of the recording area 26b, is particularly useful.

[0056] (3) The CPU 22 stores the number of times the fatigue variable Vf is classified according to the magnitude as the classification data 27a, which makes it possible to store information about the value of the fatigue variable Vf using a small data storage capacity.

[0057] (4) The fatigue variable Vf is calculated for the power transmission device 12 of the vehicle VC. When the device that generates the thrust of the vehicle VC starts moving, the vehicle VC is transitioned from a stationary state to a running state, and therefore the stress applied to the power transmission device 12 is particularly large. Therefore, calculating the value of the fatigue variable Vf by continuously using the time series data of the torque Trq around the time of starting is particularly effective in calculating the value of the fatigue variable Vf with high accuracy.

[0058] (5) When the CPU 22 detects the start of the vehicle VC, it generates time-series data of the torque Trq using all of the currents id and iq stored in the temporary storage area 26a and stores the time-series data in the recording area 26b. This makes it possible to store in the recording area 26b the time-series data of the torque Trq from before the start of the vehicle VC is detected.

[0059] In particular, in this embodiment, since the start is detected based on the rotation speed Nm of the motor generator 10, the stress applied to the power transmission device 12 increases before the start is detected. Therefore, by storing time series data from before the start is detected, it is possible to store in the recording area 26b the time series data of the torque Trq during the period when the stress applied to the power transmission device 12 increases.

[0060] (7) The CPU 22 outputs the classification data 27a to the outside of the vehicle VC. This allows the remaining life estimation device 50 to calculate the value of the remaining life variable Vrl. Then, the information on the remaining life obtained from the value of the remaining life variable Vrl can be utilized. That is, for example, if the remaining life estimation device 50 is owned by the manufacturer of the vehicle VC or by a business that provides data to the manufacturer, the manufacturer can utilize the remaining life data 57a in developing a new vehicle, etc. Also, for example, if the remaining life estimation device 50 is owned by a business that reuses vehicle parts or a business that provides information to the same business, the reuse business can utilize the remaining life data 57a.

[0061] <Correspondence> The correspondence between the matters in the above embodiment and the matters described in the above "Means for solving the problem" column is as follows. In the following, the correspondence is shown for each number of the means for solving the problem described in the "Means for solving the problem" column. [1,5] The execution device corresponds to the CPU 22 and the ROM 24. The storage device corresponds to the RAM 26. The acquisition process corresponds to the process of S26. The stress correlation sensor corresponds to the current sensor 30. The driving source corresponds to the motor generator 10. The power transmission device corresponds to the power transmission device 12. The start detection process corresponds to the process of S22. The stress variable storage process corresponds to the process of S28. The stress variable corresponds to the torque Trq. The fatigue variable calculation process corresponds to the process of S34. The fatigue variable corresponds to the fatigue variable Vf. [2] The stop detection process corresponds to the process of S46. [3] In the process of S34, the value of the fatigue variable Vf is calculated by the rainflow method. [4] The fatigue variable storage process corresponds to the process of S36. [6] The standby detection process corresponds to the process of S10. The specified amount storage process corresponds to the processes of S14 to S18. The stress variable calculation process corresponds to the process of S26. [7] The output process corresponds to the process of S42. [8] The remaining life estimation system corresponds to the fatigue estimation device 20 and the remaining life estimation device 50. [9] The computer corresponds to the CPU 22.

[0062] <Other embodiments> This embodiment can be modified as follows: This embodiment and the following modifications can be combined with each other to the extent that no technical contradiction occurs.

[0063] "About startup detection process" In the above embodiment, in the process of S22, it is determined that the vehicle has started when the rotation speed Nm of the motor generator 10 is equal to or greater than the start determination value Nstart, but this is not limiting. In other words, the start of the motor generator 10 as a drive source is detected when the rotation speed Nm is equal to or greater than the start determination value Nstart, but this is not limiting. For example, the start of the motor generator 10 may be detected when the absolute value of the torque command value for the motor generator 10 switches from zero to a value greater than zero.

[0064] "Regarding the specified amount memory processing" In the above embodiment, the currents id and iq are stored in the process of S12, but this is not limiting. For example, the torque Trq calculated from the currents id and iq may be stored.

[0065] It is not essential that the temporary storage area 26a and the recording area 26b are separate areas. For example, a part of the recording area 26b may be used as the temporary storage area 26a when the flag F is "0". In that case, when the flag F is "1", the process of S14 is not performed.

[0066] "On memory processing of stress variables" In the above embodiment, when a positive determination is made in the process of S22, the torque Trq is calculated based on the data stored in the process of S14 before that and stored in the storage area 26b, but this is not limited to the above. For example, as described in the section "Regarding the start-up detection process," when detecting a point in time when the torque command value for the motor generator 10 becomes greater than zero, the torque Trq from that point in time may be stored.

[0067] When the flag F is "1", the torque Trq calculated from the currents id and iq may be stored in the recording area 26b without storing the sampled values ​​of the currents id and iq in the temporary storage area 26a.

[0068] "About stress correlation variables" For example, as described in the section "Regarding the device that generates thrust for a vehicle," if the device that generates thrust for a vehicle is an internal combustion engine, the stress correlation variable may be the injection amount from a fuel injection valve, etc. Also, if the device that generates thrust is an internal combustion engine and a motor generator, the stress correlation variable may be a pair of the injection amount of the internal combustion engine and the current flowing through the motor generator.

[0069] The stress correlation variables are not limited to variables that indicate the state of the drive source, such as the current of the motor generator. For example, they may be variables for estimating the torque applied to the drive wheels. These are composed of a set of factors such as the friction coefficient of the road surface, the vehicle speed, and the vehicle acceleration.

[0070] "About fatigue variable calculation process" In the above embodiment, the fatigue variable Vf is used as a variable for calculating the differential damage level. However, the present invention is not limited to this. For example, the differential damage level itself may be used.

[0071] In the above embodiment, the values ​​of fatigue variables are calculated using the rainflow method, but the present invention is not limited to this. For example, a range pair method that counts equal pairs of rising and falling ranges of stress or strain may be used. Also, for example, a range method that counts the range of change in stress or strain may be used. Also, for example, a peak method that counts the maximum and minimum values ​​of stress or strain may be used.

[0072] "About stop detection processing" In the above embodiment, it is determined that the motor generator 10 has stopped when the rotation speed Nm of the motor generator 10 becomes equal to or less than the stop determination value Nstop, but this is not limited to the above. For example, it may be determined that the motor generator 10 has stopped when the logical product of the rotation speed Nm becoming equal to or less than the stop determination value Nstop and the torque command value for the motor generator 10 becoming zero is true.

[0073] "About remaining life variables" In the above embodiment, the remaining life variable Vrl is a variable that has a larger value as the remaining life is longer, but this is not limited to the above. For example, the remaining life may be a variable that has a larger value as the remaining life is shorter. In other words, the variable may be a variable that has a larger value when the degree of fatigue deterioration is large than when the degree of fatigue deterioration is small.

[0074] "About output processing" The fatigue variable data that is output to the outside of the vehicle VC is not limited to the classification data 27a. For example, each time the process of S34 is executed, a positive determination is made in the process of S40, and one or more values ​​of the fatigue variables Vf calculated in one process of S34 may be transmitted to the outside.

[0075] For example, the processes of S40 and S42 may be deleted if the process of S52 is executed by the fatigue estimation device 20. In other words, the output process is not essential. "About the use of remaining life variables" The use of the remaining life variable of the power transmission device 12 is not limited to the one exemplified in the above embodiment. For example, the variable may be used by a distributor of the vehicle VC to grasp the condition of the vehicle VC.

[0076] "About the device that generates thrust for the vehicle" In the above embodiment, the motor generator 10 is exemplified as a device that generates thrust for the vehicle, but this is not limiting. For example, an internal combustion engine may be used. Furthermore, for example, the vehicle may be a hybrid vehicle, and the device that generates thrust may be a motor generator and an internal combustion engine. In this case, the torque input to the power transmission device that is used to calculate the stress applied to the power transmission device may be the torque transmitted to the drive wheels.

[0077] "About the driving source" The driving source is not limited to a device that generates thrust for the vehicle. For example, it may be an electric motor that drives a machine tool.

[0078] "About the execution device" The execution device is not limited to one equipped with a CPU 22 and a ROM 24 and executing software processing. For example, it may be equipped with a dedicated hardware circuit such as an ASIC that performs hardware processing of at least a part of what was processed by software in the above embodiment. That is, the execution device may have any of the following configurations (a) to (c). (a) It comprises a processing device that executes all of the above processing according to a program, and a program storage device such as a ROM that stores the program. (b) It comprises a processing device and a program storage device that executes a part of the above processing according to a program, and a dedicated hardware circuit that executes the remaining processing. (c) It comprises a dedicated hardware circuit that executes all of the above processing. Here, there may be multiple software execution devices equipped with a processing device and a program storage device, and multiple dedicated hardware circuits.

[0079] "About storage devices" In the above embodiment, the currents id, iq and the torque Trq are stored in the RAM 26. However, this is not limiting. For example, they may be stored in the storage device 27.

[0080] The temporary storage area 26a and the recording area 26b do not necessarily have to be different storage areas in the same storage device. "About Computers" 2 is not necessarily executed by a single computer. For example, the process of S36 may be executed by the CPU 52 of the remaining life estimation device 50. This can be realized by executing the output process each time the process of S34 is executed, as described in the section "Regarding output process."

[0081] In addition, even when multiple computers located at separate locations cooperate to execute the software process, it is not essential that the computers have a CPU and ROM to execute the software process. Each of the computers may have any of the configurations of the execution device described in the "Execution Device" section above. [Explanation of symbols]

[0082] 10...Motor generator 12...Power transmission device 14…Drive wheel 16…Inverter 20...Fatigue estimation device 27…Storage device 50...Remaining life estimation device 59…Local network

Claims

1. An execution device and a storage device, The execution device executes an acquisition process, a start-up detection process, a stress variable storage process, and a fatigue variable calculation process, The acquisition process is a process of repeatedly acquiring values ​​of stress variables, The stress variable is a variable indicating a stress of a power transmission device to which power from a drive source is transmitted, the start-up detection process is a process of detecting the start-up of the driving source, the stress variable storage process is a process of storing in the storage device each of the stress variable values ​​acquired by the acquisition process, the fatigue variable calculation process is a process of calculating a value of a fatigue variable based on a predetermined amount of time-series data of the stress variable newly stored in the storage device each time the predetermined amount of time-series data is reached; the fatigue variable is a variable indicative of fatigue of the power transmission device, The stress variable storage process of the fatigue estimation device includes a process of starting to overwrite a new value of the stress variable into a memory area in which the value of the stress variable is already stored each time the stress variable exceeds the predetermined amount and each time the startup is detected by the startup detection process.

2. the execution device executes a stop detection process for detecting a stop of the driving source; The fatigue estimation device according to claim 1 , wherein the fatigue variable calculation process includes, when a stop is detected by the stop detection process, a process of calculating a value of the fatigue variable based on the time series data newly stored in the storage device until the stop is detected.

3. 3. The fatigue estimation device according to claim 1, wherein the fatigue variable calculation process calculates the value of the fatigue variable based on a maximum value and a minimum value of the stress variable.

4. The execution device executes a fatigue variable storage process; The fatigue estimation device according to any one of claims 1 to 3, wherein the fatigue variable storage process is a process of classifying the value of the fatigue variable calculated by the fatigue variable calculation process according to the magnitude of the value of the fatigue variable, counting the number of times the value is classified into each magnitude, and storing the counted values ​​in the storage device.

5. The drive source is a device that generates thrust for the vehicle, 5. The fatigue estimation device according to claim 1, wherein the power transmission device is a device that transmits the power of the drive source to drive wheels of the vehicle.

6. The start detection process is a process of detecting a start of the vehicle, The acquisition process includes a standby detection process, a specified amount storage process, and a stress variable calculation process, the standby detection process is a process of determining that the vehicle is in a standby state when a shift position of the vehicle is in a driving range, the specified amount storage process is a process of storing in the storage device each time a value for either one of the two values, the stress variable or the stress correlation variable, and starting to overwrite the storage area in which the value for each time has already been stored with a new value for each time every time the amount of stored data reaches a specified amount; the stress correlation variable is a variable for calculating a value of the stress variable and is a variable indicating a state of the driving source, the stress variable calculation process is a process of calculating a value of the stress variable based on a value of the stress correlation variable, The data overwritten in the storage area when the start-up is detected includes data based on the value related to the one stored by the specified amount storage process before the start-up is detected; The fatigue estimation device according to claim 5 , wherein the specified amount is smaller than the predetermined amount.

7. 7. The fatigue estimation device according to claim 5, wherein the execution unit executes an output process for outputting data corresponding to a result of the calculation of the value of the fatigue variable by the fatigue variable calculation process to an outside of the vehicle.

8. The fatigue estimation device according to claim 7 ; and a remaining life estimation device that estimates a remaining life of the power transmission device based on a value of the fatigue variable.

9. A fatigue estimation method, comprising the steps of executing each of the processes in the fatigue estimation device according to any one of claims 1 to 7, by a computer.

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