Fatigue calculation device

Abstract

To suppress data from being dropped that contributes to the fatigue degree of components on one hand and reduce a data volume on the other hand.SOLUTION: Provided is a fatigue degree computing device that selects a representative value from stresses occurring to a component and acquired in plurality in a prescribed period or stress parameters as physical quantities associated with the stresses, computes, from the time series data of the selected representative values, the amplitude of stress parameters and the number of times of occurrence per amplitude by a rain flow method, and computes the fatigue degree of the component using a set amplitude and the number of times of occurrence. A stress parameter whose absolute value is largest among the plurality of stress parameters within a prescribed time is selected as the representative value.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present invention relates to a fatigue degree calculation device, and more particularly to a fatigue degree calculation device that calculates the fatigue degree of components.

Background Art

[0002] Conventionally, as this type of fatigue degree calculation device, a device that calculates the fatigue degree (fatigue damage degree) of components constituting a vehicle has been proposed (see, for example, Patent Document 1). In this device, data on acceleration amplitude is acquired for each unit travel distance of the vehicle, and only data within a predetermined range in which the acceleration amplitude contributes to the fatigue degree of the component is extracted from the time-series data obtained by arranging the acquired data in time series, and the fatigue degree of the component is calculated by the rainflow method using the extracted data. Without extracting data whose acceleration amplitude is outside the predetermined range from the acquired time-series data, the amount of data is reduced.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the above-described fatigue degree calculation device, depending on the value (acceleration amplitude) of the time-series data, the amount of data cannot be reduced. For example, when all the values of the time-series data are within the predetermined range, the amount of data cannot be reduced. As a method of reducing the amount of data, a method of increasing the time interval for acquiring the time-series data can be considered, but with this method, the possibility of not being able to extract data contributing to the fatigue degree of the component becomes high.

[0005] The main object of the fatigue degree calculation device of the present invention is to reduce the amount of data while suppressing the loss of data contributing to the fatigue degree of the component.

Means for Solving the Problems

[0006] The fatigue degree calculation device of the present invention has adopted the following means to achieve the above main object.

[0007] The fatigue degree calculation device of the present invention selects a representative value from the stress generated in a component acquired a plurality of times within the predetermined period or a stress parameter as a physical quantity related to the stress every predetermined period, calculates the amplitude of the stress parameter and the number of occurrences for each amplitude from the time series data of the selected representative value by the rainflow method, and calculates the fatigue degree of the component using the set amplitude and the number of occurrences. A fatigue degree calculation device, selects, as the representative value, the stress parameter having the largest absolute value among the plurality of stress parameters within the predetermined time. This is the gist.

[0008] In this fatigue degree calculation device of the present invention, a representative value is selected from the stress generated in a component acquired a plurality of times within a predetermined period or a stress parameter as a physical quantity related to the stress every predetermined period. The amplitude of the stress parameter and the number of occurrences for each amplitude are calculated from the time series data of the selected representative value by the rainflow method, and the fatigue degree of the component is calculated using the set amplitude and the number of occurrences. As the representative value, the stress parameter having the largest absolute value among the plurality of stress parameters within the predetermined time is selected. The stress parameter having the largest absolute value among the plurality of stress parameters within the predetermined time contributes the most to the fatigue degree of the component. Therefore, by selecting, as the representative value, the stress parameter having the largest absolute value among the plurality of stress parameters within the predetermined time, it is possible to suppress dropping data contributing to the fatigue degree of the component. Further, since the stress parameter having the largest absolute value among the plurality of stress parameters within the predetermined time is selected as the representative value, it is possible to reduce the data amount as compared with selecting all of the plurality of stress parameters within the predetermined time. As a result, it is possible to reduce the data amount while suppressing dropping data contributing to the fatigue degree of the component.

[0009] In such a fatigue degree calculation device of the present invention, the motor is controlled to be driven by a torque command, stress is generated in the component as the motor rotates, and the stress parameter may be the torque command of the motor. By doing so, when calculating the fatigue degree of a component in which stress is generated as the motor rotates, it is possible to reduce the data amount while suppressing the omission of data contributing to the fatigue degree of the component.

Brief Description of the Drawings

[0010]

Figure 1

Figure 2

Figure 3

Figure 4

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Figure 6

Embodiments for Carrying Out the Invention

[0011] Next, embodiments for carrying out the present invention will be described using examples.

Examples

[0012] FIG. 1 is a configuration diagram showing an outline of the configuration of an electric vehicle 20 equipped with a fatigue degree calculation device as an embodiment of the present invention. As shown in the figure, the electric vehicle 20 of the embodiment includes a driving motor 32, an inverter 34, a battery 40, and a vehicle electronic control unit (hereinafter referred to as "vehicle ECU") 60. As the fatigue degree calculation device of the embodiment, the vehicle ECU 60 mainly corresponds.

[0013] The motor 32 is configured as, for example, a synchronous generator motor, and the rotor of the motor 32 is connected to a drive shaft 26 that is connected to the drive wheels 22 via a differential gear 24. The inverter 34 is connected to the motor 32 and also connected to the power line 36. The motor 32 is rotationally driven by switching control of a plurality of switching elements (not shown) of the inverter 34 by the vehicle ECU 60.

[0014] The battery 40 is configured as, for example, a lithium-ion secondary battery and is connected to the power line 36.

[0015] The vehicle ECU 60 includes, although not shown, a microprocessor having a CPU, ROM, RAM, flash memory, input / output ports, and communication ports.

[0016] Signals from various sensors are input to the vehicle ECU 60 via the input ports. Examples of the signals input to the vehicle ECU 60 include the rotational position θm of the rotor of the motor 32 from a rotational position sensor (e.g., resolver) that detects the rotational position of the rotor of the motor 32, the voltage Vb of the battery 40 from a voltage sensor 40a attached between the terminals of the battery 40, and the current Ib of the battery 40 from a current sensor 40b attached to the output terminal of the battery 40. Note that since the vehicle ECU 60 also functions as a drive control device for the vehicle, the vehicle ECU 60 may also include the shift position from a shift position sensor that detects the operation position of the shift lever, the accelerator opening from an accelerator pedal position sensor that detects the depression amount of the accelerator pedal, the brake pedal position BP from a brake pedal position sensor that detects the depression amount of the brake pedal, and the vehicle speed from a vehicle speed sensor.

[0017] Various control signals are output from the vehicle ECU 60 via the output ports. Examples of the signals output from the vehicle ECU 60 include control signals to the plurality of switching elements of the inverter 34.

[0018] In the electric vehicle 20 of the embodiment configured in this way, the vehicle ECU 60 sets the required torque Td* required for running based on the accelerator opening degree from the accelerator pedal position sensor and the vehicle speed, and sets the torque command Tm* of the motor 32 so that the vehicle runs at the required torque Td*. Then, a plurality of switching elements (not shown) of the inverter 34 are switched and controlled so that the motor 32 is driven by the torque command Tm*. Thereby, the vehicle is caused to run at the required torque Td* by the power from the motor 32.

[0019] Next, the operation of the electric vehicle 20 of the embodiment configured in this way, particularly the operation when calculating the degree of deterioration (fatigue degree) of the components in which stress is generated along with the driving of the motor 32 will be described. Examples of the components in which stress is generated along with the driving of the motor 32 include the drive shaft 26 and the differential gear 24.

[0020] FIG. 2 is a flowchart showing an example of a processing routine executed by the vehicle ECU 60. This routine is executed every predetermined time titr (for example, several msec) when the motor 32 is being driven.

[0021] When this routine is executed, a CPU (not shown) of the vehicle ECU 60 executes a process of inputting the torque command Tm* (step S100), and stores the input torque command Tm* in a RAM (not shown) of the vehicle ECU 60 (step S110). Then, it is determined whether or not the number Nd of data of the torque command Tm* stored in the RAM is equal to or greater than a threshold value Nth (step S120). The threshold value Nth is a threshold value for determining whether or not the data of the torque command Tm* for a predetermined time tref has been stored in the RAM. The predetermined time tref is set based on the predetermined time titr as the repetition time of this routine, as the time when the ratio of the storage capacity consumed for storing the torque command Tm* to the total storage capacity of the RAM becomes large (for example, the ratio of the storage capacity consumed for storing the torque command Tm* to the total storage capacity of the RAM becomes 0.01, 0.1, etc.).

[0022] When the number Nd is less than the threshold value Nth in step S120, this routine ends. When the number Nd is greater than or equal to the threshold value Nth in step S120, among the data of the torque command Tm* stored in the RAM, the one with the largest absolute value is set as the representative value Dty(n) (step S130), "n" is incremented by 1 (step S140), the data of the torque command Tm* stored in the RAM is cleared (step S150), and this routine ends. Here, "n" is a natural number, and the value 1 is set as the initial value.

[0023] When the representative value Dty(n) is set in this way, a representative time-series waveform is created as time-series data in which the representative value Dty(n) is arranged in time series at intervals of a predetermined time tref, and is stored in the RAM. FIG. 3 is an explanatory diagram showing an example of the time change of the data of the torque command Tm*. In FIG. 3, the circles indicate the data of the torque command Tm*. The solid black circles indicate the data selected as the representative value Dty(n). The hollow circles indicate the data of the torque command Tm* not selected as the representative value Dty(n). FIG. 4 is an explanatory diagram showing an example of the representative time-series waveform. The solid black circles indicate the representative value Dty(n).

[0024] As shown in FIG. 3, within a predetermined time tref, the torque command Tm* is repeatedly input every predetermined time titr in step S100 of the processing routine in FIG. 2, and one of them is selected as the representative value Dty(n). As shown in FIG. 4, the representative time-series waveform is created such that the representative value Dty(n) is located at the center of each section of the predetermined time tref. Since the representative time-series waveform is created and stored in the RAM in this way, it is possible to reduce the amount of data in the RAM compared to storing all the torque commands Tm* in time series. Also, since the one with the largest absolute value among the plurality of torque commands Tm* within a predetermined time tref contributes the most to the fatigue degree of the component, the representative time-series waveform can be created without losing the data that contributes significantly to the fatigue degree of the component.

[0025] When the representative time series waveform is created in this way, the stress amplitude σa, the mean stress σm, and the number of cycles (corresponding to the number of occurrences (frequency) for each stress amplitude σa) are calculated from the representative time series waveform as the time series data of the representative value Dty(n) by the rainflow method. Fig. 5 shows an example of the calculated stress amplitude σa, mean stress σm, and number of cycles.

[0026] Subsequently, the equivalent stress amplitude σr is calculated for each interval of the time tref using the modified Goodman line from each stress amplitude σa and mean stress σm according to the following equation (1). In Equation (1), “σwb” is the y-coordinate of the y-intercept in the modified Goodman line diagram (fatigue limit diagram) where the x-axis (horizontal axis) is the mean stress σm and the y-axis (vertical axis) is the stress amplitude σa. “σB” is the tensile strength and is the x-coordinate of the x-intercept in the modified Goodman line diagram (fatigue limit diagram).

[0027] σr = σa +σwb / σB + |σm | ···(1)

[0028] Then, for each interval Tn (n is a natural number) of the equivalent stress amplitude σr within a predetermined range, the frequency (number of times) Gtn (n is a natural number) is calculated. When the frequency Gtn for each interval Tn is calculated, the degradation degree D is calculated from the guaranteed value Htn (n is a natural number) and the frequency Gtn in the interval Tn using the following equation (2). Fig. 6 is an explanatory diagram showing an example of the frequency Gtn and the guaranteed value Htn for each interval Tn. The guaranteed value Htn is the upper limit of the number of occurrences of the equivalent stress amplitude σr set in advance by experiments, analysis, etc. so that no fatigue damage occurs to the component when the equivalent stress amplitude σr corresponding to each interval Tn repeatedly occurs in the component. In this way, since the degradation degree D is calculated using the representative time series waveform, the calculation load can be reduced compared to a method that stores all the torque commands Tm* in time series and calculates the degradation degree D using the stored torque commands Tm*.

[0029]

Equation

[0030] According to the electric vehicle 20 equipped with the fatigue degree calculation device of the embodiment described above, as the representative value Dty(n), the torque command Tm* with the largest absolute value among the data of the torque command Tm* stored in the RAM within the predetermined time tref is selected. Therefore, it is possible to reduce the data amount while suppressing the omission of data contributing to the fatigue degree of the parts.

[0031] In the electric vehicle 20 equipped with the fatigue degree calculation device of the embodiment, the torque command Tm* is input every predetermined time titr, and as the representative value Dty(n), the torque command Tm* with the largest absolute value among the data of the torque command Tm* stored in the RAM within the predetermined time tref is selected. However, as the data to be input, any physical quantity related to the stress generated in the parts accompanying the driving of the motor 32, for example, the torque output from the motor 32, the current Ib of the battery 40, etc. may be used.

[0032] In the electric vehicle 20 equipped with the fatigue degree calculation device of the embodiment, the deterioration degree (fatigue degree) of the parts where stress is generated accompanying the driving of the motor 32 is calculated. However, the parts targeted for the calculation of the deterioration degree are not limited to those where stress is generated accompanying the driving of the motor 32, and any parts mounted on the vehicle where stress is generated during the running of the vehicle, such as the piston chamber where stress is generated accompanying the operation of the hydraulic clutch, may be used.

[0033] In the embodiment, the case where the present invention is applied to the electric vehicle 20 is illustrated. However, the present invention may be applied to other devices equipped with a motor, such as an electric drill, a cyclone type vacuum cleaner, a washing machine, or other devices that do not have a motor but generate some stress during operation.

[0034] The correspondence relationship between the main elements of the embodiment and the main elements of the invention described in the column of the means for solving the problems will be described. In the embodiment, the vehicle ECU 60 corresponds to the "fatigue degree calculation device".

[0035] Note that the correspondence between the main elements of the embodiments and the main elements of the invention described in the column of means for solving the problems is an example for specifically explaining the form for implementing the invention described in the column of means for solving the problems in the embodiments, and thus does not limit the elements of the invention described in the column of means for solving the problems. That is, the interpretation of the invention described in the column of means for solving the problems should be made based on the description in that column, and the embodiments are merely specific examples of the invention described in the column of means for solving the problems.

[0036] As described above, the embodiments have been used to explain the forms for implementing the present invention. However, the present invention is not limited to such embodiments, and it goes without saying that the present invention can be implemented in various forms without departing from the gist of the present invention.

Industrial Applicability

[0037] The present invention can be used in the manufacturing industry of fatigue degree calculation devices and the like.

Explanation of Reference Numerals

[0038] 20 Electric vehicle, 22 Driving wheel, 24 Differential gear, 26 Driveshaft, 32 Motor, 34 Inverter, 36 Power line, 40 Battery, 40a Voltage sensor, 40b Current sensor, 60 Vehicle ECU.

Claims

【Claim 1】 Select a representative value from stress or stress parameters as physical quantities related to stress generated in a plurality of components acquired within the predetermined time at each predetermined time, Calculate the amplitude of the stress parameter and the number of occurrences for each amplitude from the time-series data of the selected representative value by the rainflow method, Calculate the fatigue degree of the component using the set amplitude and the number of occurrences, A fatigue degree calculation device, As the representative value, select the stress parameter having the largest absolute value among the plurality of stress parameters within the predetermined time, Stress is generated in the component along with the drive of a motor controlled to be driven by a torque command, The stress parameter is the torque command, A fatigue degree calculation device.

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