Tire characteristic data processing method and tire characteristic data processing device

Abstract

This technology can reduce errors occurring in measured tire characteristic data. [Solution] In the tire characteristic data processing method, the data acquisition step involves taking either the slip ratio or slip angle of the tire as a variable and varying it within a predetermined range to acquire tire characteristic data by measuring the load generated on the tire. The first filtering step involves filtering the tire characteristic data to generate first filtered data. The data addition step involves inverting the endpoint of the first filtered data using the endpoint as a reference point and adding it to the first filtered data to generate added data. The second filtering step involves filtering the added data to generate second filtered data. The data removal step removes data outside the predetermined range of the second filtered data.

Description

Technical Field

[0001] The present invention relates to a tire characteristic data processing method and a tire characteristic data processing device for processing data obtained by a tire testing machine that measures forces acting on a tire.

Background Art

[0002] For example, tire characteristics such as the slip angle of a tire, the camber angle, and the lateral force of the tire with respect to the vertical load are measured by a tire testing machine, and a tire characteristic model represented by a Magic Formula model or the like is identified based on the measurement data. The tire characteristic model is incorporated into a kinematic model (dynamics model) of a vehicle and used for vehicle motion analysis and the like.

[0003] Patent Document 1 discloses a conventional device for estimating the wear state of a tire. In estimating the wear state of the tire, this conventional device calculates the slope of the slip ratio with respect to the driving force based on a large number of data sets of the slip ratio (slip rate) and the driving force.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] Patent Document 1 describes that filtering for removing measurement errors may be performed on the driving force and the slip ratio, but does not mention specifically what kind of filtering is appropriate.

[0006] In actual tire testing, which measures the three-axial forces and moments around the three axes acting on a tire, measurement errors occur due to noise, hysteresis, and vibration, depending on the set slip angle, etc. Measurement errors in the measured tire characteristic data are also dependent on the test environment, such as the drive mechanism and mechanical structure of the tire testing machine, making complete elimination difficult. Therefore, it was necessary to perform effective filtering or other processing on the tire characteristic data.

[0007] This invention has been made in view of the above circumstances, and its objective is to provide a tire characteristic data processing method and a tire characteristic data processing device that can reduce errors occurring in measured tire characteristic data. [Means for solving the problem]

[0008] One aspect of the present invention is a tire characteristic data processing method. The tire characteristic data processing method comprises: a data acquisition step of acquiring tire characteristic data by measuring the load generated on a tire, with at least one of the slip ratio and slip angle of the tire as variables and varying the variables within a predetermined range; a first filtering step of filtering the tire characteristic data acquired in the data acquisition step to generate first filtered data; a data addition step of inverting the first filtered data generated in the first filtering step with the endpoint of the predetermined range as a reference point and adding it to the first filtered data to generate added data; a second filtering step of filtering the added data generated in the data addition step to generate second filtered data; and a data removal step of removing data outside the predetermined range of the second filtered data generated in the second filtering step.

[0009] Another aspect of the present invention is a tire characteristic data processing device. The tire characteristic data processing device includes: a data acquisition unit that acquires tire characteristic data by measuring the load generated on a tire, with at least one of the slip ratio and slip angle of the tire as variables and varying the variables within a predetermined range; a first filter processing unit that filters the tire characteristic data acquired by the data acquisition unit to generate first filtered data; a data addition unit that inverts the first filtered data generated by the first filter processing unit using the endpoints of the predetermined range as reference points and adds it to the first filtered data to generate added data; a second filter processing unit that filters the added data generated by the data addition unit to generate second filtered data; and a data removal unit that removes data outside the predetermined range of the second filtered data generated by the second filter processing unit. [Effects of the Invention]

[0010] According to the present invention, it is possible to reduce errors occurring in the measured tire characteristic data. [Brief explanation of the drawing]

[0011] [Figure 1] This is a block diagram showing the functional configuration of a tire characteristic data processing device according to an embodiment. [Figure 2] This is a schematic diagram illustrating the processing performed by the data addition unit. [Figure 3] This flowchart shows the data processing procedure by the tire characteristics data processing device. [Figure 4] This graph shows an example of the first filtered data after processing by the first filtering unit. [Figure 5] This graph shows an example of sorted data after the first filtering process. [Figure 6] This graph shows an example of processed data after it has been added by the data addition unit. [Figure 7] This graph shows an example of resampled and processed data. [Figure 8] This graph shows an example of the second-filtered data after processing by the second filter processing unit. [Figure 9] This graph shows an example of tire characteristic data after processing. [Modes for carrying out the invention]

[0012] The present invention will be described below with reference to Figures 1 to 9, based on preferred embodiments. The same or equivalent components and members shown in each drawing will be denoted by the same reference numerals, and redundant explanations will be omitted as appropriate. Furthermore, the dimensions of the members in each drawing will be enlarged or reduced as appropriate for ease of understanding. In addition, some members that are not important for explaining the embodiments will be omitted from the drawings.

[0013] (Embodiment) Figure 1 is a block diagram showing the functional configuration of a tire characteristic data processing device 100 according to an embodiment. The tire characteristic data processing device 100 comprises a storage unit 10, an operation unit 20, a display unit 30, and an arithmetic processing unit 40. The tire characteristic data processing device 100 reduces errors contained in the tire characteristic data by performing processing such as a low-pass filter on the tire characteristic data measured by the tire testing machine 80.

[0014] The tire testing machine 80 includes, for example, a rotationally controlled drum drive mechanism and measuring devices for measuring the three-axial forces and moments around the three axes acting on the tire. The tire testing machine 80 rotates the tire placed on a flat belt at a speed corresponding to a predetermined travel speed, varies the slip ratio S and slip angle α within a predetermined range, and measures the forces and moments acting on the tire.

[0015] The tire tester 80 conducts a driving or cornering test to change the slip ratio S or slip angle α of the tire from one end point (lower limit value) R1 to the other end point (upper limit value) R2 within a predetermined range R, and measures the longitudinal force Fx or lateral force Fy acting on the tire. In the driving test, for example, the longitudinal force Fx is measured by changing from one end point R1 to the other end point R2, and then the longitudinal force Fx is measured by changing from the other end point R2 to one end point R1 to obtain tire characteristic data.

[0016] By starting from one end point R1 of the predetermined range R for the slip ratio S, reciprocally changing so as to turn back at the other end point R2 and return to one end point R1, tire characteristic data including hysteresis according to the direction of change of the slip ratio S and the slip rate change speed during measurement is obtained.

[0017] The tire characteristic data measured by the tire tester 80 is used for identification of a tire characteristic model represented by a Magic Formula model (hereinafter referred to as MF model) etc. after being filtered by the tire characteristic data processing device 100.

[0018] The MF model for which the parameter group has been identified is a function for calculating the longitudinal force Fx of the tire with respect to the slip ratio S of the tire, the lateral force Fy with respect to the slip angle α of the tire, the moment Mz about the vertical axis, etc., and is used, for example, in the motion analysis of a vehicle. The independent variables in the MF model are the slip ratio S and the slip angle α. The tire characteristic data is measured with the slip ratio S and the slip angle α variable within a predetermined range.

[0019] The MF model has a basic formula using coefficients B, C, D, E. The basic formula of the MF model is also called the basic Pacejka formula derived from the name of the inventor, and is described in a form including the following function. y = D sin[C arctan{B x - E(B x - arctan(B x))}] ···(1)

[0020] In equation (1), x on the right-hand side represents an independent variable, which is either the slip ratio S or the slip angle α itself, or a value added to either the slip ratio S or the slip angle α by adding or multiplying a coefficient or the like. In the right-hand side of equation (1), the slip ratio S and the slip angle α are treated as independent variables. Furthermore, the notation "B x" on the right-hand side of equation (1) represents the multiplication of B and x.

[0021] The basic equation of the MF model includes a term for y, represented by equation (1), and is independently defined for the longitudinal force Fx, lateral force Fy, and moment Mz of the tire. It is expressed by including terms that are further added to y and terms that are further multiplied by y. Coefficients are set for the terms that are further added to y and terms that are further multiplied by y in the basic equation of the MF model. The MF model depends, for example, on load conditions, camber angle conditions, and internal pressure conditions on the tire, and is identified by tire test data with these conditions varied. A characteristic of the basic equation of the MF model is that, by including calculations using sin and arctan functions, an empirical formula that fits well to tire characteristic data measured by the tire testing machine 80 can be obtained.

[0022] The tire characteristic data processing device 100 is an information processing device such as a PC (personal computer). Each part of the tire characteristic data processing device 100 can be implemented hardware-wise using electronic processing circuits and mechanical components, including the CPU of a computer, and software-wise using computer programs. Here, however, we are depicting functional blocks realized through the coordination of these components. Therefore, it will be understood by those skilled in the art that these functional blocks can be implemented in various forms through combinations of hardware and software.

[0023] The storage unit 10 is a storage device composed of, for example, an SSD (Solid State Drive), a hard disk, a CD-ROM, a DVD, etc. The storage unit 10 stores pre-processing tire characteristic data 11 measured by the tire testing machine 80, as well as first filtered data 12, additional processed data 13, second filtered data 14, and post-processing tire characteristic data 15 generated based on the processing of the arithmetic processing unit 40. The storage unit 10 also stores computer programs executed by the arithmetic processing unit 40, and data used to execute the computer programs.

[0024] The operation unit 20 has operable input devices such as a touch panel, switches, keyboard, and mouse device, and accepts user input. The operation unit 20 accepts user input related to filter settings in filtering processing, etc. The display unit 30 has a display device such as a liquid crystal display, and displays a screen for displaying graphs of tire characteristic data during the processing process and for accepting user input related to the processing of the calculation processing unit 40.

[0025] The arithmetic processing unit 40 includes a data acquisition unit 41, a first filter processing unit 42, a data addition unit 43, a second filter processing unit 44, and a data removal unit 45. The arithmetic processing unit 40 may also read and execute computer program modules from the storage unit 10 that perform processing in the data acquisition unit 41, the first filter processing unit 42, the data addition unit 43, the second filter processing unit 44, and the data removal unit 45.

[0026] The data acquisition unit 41 acquires tire characteristic data measured from the tire testing machine 80 and stores it in the storage unit 10 as pre-processed tire characteristic data 11. As described above, the pre-processed tire characteristic data 11 is data measured by changing the slip ratio S and slip angle α within a predetermined range, and includes measurement errors due to noise, hysteresis, vibration, etc.

[0027] The first filter processing unit 42 applies a low-pass filter to the pre-processed tire characteristic data 11 to remove high-frequency components and stores the data in the storage unit 10 as first filtered data 12. The first filter processing unit 42 may perform resampling after the low-pass filtering.

[0028] The data addition unit 43 generates processed data 13 by adding data outside the range of slip ratio S and slip angle α to the first filtered data 12 generated by the first filtering unit 42, and stores it in the storage unit 10. As a preprocessing step before adding data, the data addition unit 43 sorts the first filtered data 12 in order of slip ratio S and slip angle α.

[0029] The data addition unit 43 adds data to the first filtered data 12 that has been inverted using one endpoint R1 of the slip ratio S range in the first filtered data 12 as a reference point. The data addition unit 43 also adds data to the first filtered data 12 that has been inverted using the other endpoint R2 of the slip ratio S range as a reference point.

[0030] Figure 2 is a schematic diagram illustrating the processing performed by the data addition unit 43. In Figure 2, the horizontal axis represents the slip ratio S, the vertical axis represents the longitudinal force Fx of the tire, and the solid line represents the first filtered data 12 sorted by slip ratio S. The first filtered data 12 actually contains ripple due to measurement errors, but for the sake of simplicity in explanation, it is shown as a smooth solid line.

[0031] As shown in Figure 2, the data addition unit 43 inverts the first filtered data 12 with one endpoint R1 of a predetermined range R as the reference point, generates additional data represented by a dashed line outside the predetermined range R, and adds it to the first filtered data 12. The data addition unit 43 also inverts the first filtered data 12 with the other endpoint R2 of the predetermined range R as the reference point, generates additional data represented by a dashed line outside the predetermined range R, and adds it to the first filtered data 12. The data addition unit 43 generates processed data 13 with data added to the outside of both ends of the predetermined range R and stores it in the storage unit 10. The data addition unit 43 can similarly add additional data to tire characteristic data such as the lateral force Fy with respect to the slip angle α and the moment Mz about the vertical axis.

[0032] The second filter processing unit 44 applies a low-pass filter to the processed data 13 generated by the data addition unit 43 to remove high-frequency components and stores it in the storage unit 10 as second filtered data 14. Before applying the low-pass filter, the second filter processing unit 44 may resample the processed data 13 based on the slip ratio S and slip angle α as a pre-processing step.

[0033] The data removal unit 45 removes data from the second filtered data 14 generated by the second filtering unit 44 that is outside the range of slip ratio S and slip angle α before data addition by the data addition unit 43. The data removal unit 45 stores the data after the removal process as processed tire characteristic data 15 in the storage unit 10.

[0034] Next, the operation of the tire characteristic data processing device 100 will be explained. Figure 3 is a flowchart showing the data processing procedure by the tire characteristic data processing device 100. The data acquisition unit 41 of the tire characteristic data processing device 100 acquires tire characteristic data measured by the tire testing machine 80 and stores it in the storage unit 10 as pre-processed tire characteristic data 11 (S1). The following explanation will use as an example the case in which tire characteristic data A is obtained by measuring the longitudinal force Fx by changing the slip ratio S back and forth, starting from one endpoint R1 of a predetermined range R, turning back at the other endpoint R2, and returning to the first endpoint R1.

[0035] The first filter processing unit 42 performs a first filter processing by applying a low-pass filter to the pre-processed tire characteristic data 11 to remove high-frequency components, and stores the first filtered data 12 in the storage unit 10 (S2).

[0036] Figure 4 is a graph showing an example of the first filtered data 12 after processing by the first filter processing unit 42. In Figure 4, the horizontal axis represents the slip ratio S, and the vertical axis represents the longitudinal force Fx. The first filtered data 12 shown in Figure 4 is obtained by processing the above-mentioned tire characteristic data A with a Butterworth low-pass filter. The first filter processing unit 42 filters the tire characteristic data A with a Butterworth low-pass filter (5th order, cutoff frequency 0.5 Hz) and samples the data at a sampling frequency of 200 Hz using a double-sided filter. The tire characteristic data A is acquired as time-series data, and the filtered data is converted to the time axis based on the sweep rate of the slip ratio S.

[0037] As described above, since the slip ratio S is moved back and forth between one endpoint R1 and the other endpoint R2 within a predetermined range R to obtain tire characteristic data A, the graph of the first filtered data 12 shown in Figure 4 basically contains two curves.

[0038] The data addition unit 43 sorts the first filtered data 12 in order of slip ratio S and slip angle α as a preprocessing step before the data addition process (S3). Figure 5 is a graph showing an example of the sorted first filtered data 12. In Figure 5, the horizontal axis is the slip ratio S and the vertical axis is the forward / backward force Fx, and the graph shows the first filtered data 12 shown in Figure 4 sorted in order of slip ratio S.

[0039] The data addition unit 43 performs a data addition process on the first filtered data 12 sorted in step S3, adding data outside the range of slip ratio S and slip angle α, and stores the added data 13 in the storage unit 10 (S4).

[0040] Figure 6 is a graph showing an example of the processed data 13 after processing by the data addition unit 43. In Figure 6, the horizontal axis represents the slip ratio S, and the vertical axis represents the forward and backward force Fx. The graph shows the sorted first filtered data 12 shown in Figure 5 with data added to it. The data addition unit 43 adds data to the sorted first filtered data 12 by inverting it, using one endpoint R1 and the other endpoint R2 of the slip ratio S range as reference points.

[0041] The second filtering unit 44 resamples the processed data 13 on the axes of slip ratio S and slip angle α as a preprocessing step for the second filtering (S5). Figure 7 is a graph showing an example of the resampled processed data 13. In Figure 7, the horizontal axis is the slip ratio S and the vertical axis is the forward / backward force Fx, and the graph shows the processed data 13 shown in Figure 6 resampled, for example, at 1% intervals of the unit quantity of slip ratio S.

[0042] The second filter processing unit 44 performs a second filtering process by applying a low-pass filter to the resampled additional processing data 13 obtained in step S5 to remove high-frequency components, and stores the second filtered data 14 in the storage unit 10 (S6).

[0043] Figure 8 is a graph showing an example of the second filtered data 14 after processing by the second filtering unit 44. In Figure 8, the horizontal axis is the slip ratio S, and the vertical axis is the forward / backward force Fx. The second filtered data 14 shown in Figure 8 is obtained by processing the resampled and additionally processed data 13 shown in Figure 7 with a Butterworth low-pass filter. The second filtering unit 44 filters the data using, for example, a Butterworth low-pass filter (5th order, cutoff frequency 0.1 / %) and samples the data at a sampling frequency of 1 / % using a double-sided filter.

[0044] The data removal unit 45 removes data from the second filtered data 14 generated in step S6 that is outside the range of slip ratio S and slip angle α before data addition by the data addition unit 43 (S7). The data removal unit 45 stores the data after the removal process as processed tire characteristic data 15 in the storage unit 10 (S8), and terminates the process.

[0045] Figure 9 is a graph showing an example of processed tire characteristic data 15. In Figure 9, the horizontal axis is the slip ratio S, and the vertical axis is the longitudinal force Fx. The processed tire characteristic data 15 shown in Figure 9 is a graph obtained by removing data outside a predetermined range R from the second filtered data 14 shown in Figure 8. As shown in Figure 9, in the processed tire characteristic data 15, measurement errors such as hysteresis and ripple that occur during the back-and-forth motion between one endpoint R1 and the other endpoint R2 within the predetermined range R are reduced.

[0046] The tire characteristic data processing method in this embodiment comprises a data acquisition step, a first filtering step, a data addition step, a second filtering step, and a data removal step. The data acquisition step acquires pre-processed tire characteristic data 11 by measuring the load generated on the tire by changing at least one of the tire slip ratio S and slip angle α within a predetermined range. The first filtering step filters the tire characteristic data acquired in the data acquisition step to generate first filtered data 12. The data addition step adds the first filtered data 12 generated in the first filtering step to the first filtered data 12 by inverting it with the endpoints (R1, R2) of a predetermined range as reference points, thereby generating added data 13. The second filtering step filters the added data 13 generated in the data addition step to generate second filtered data 14. The data removal step removes data outside the predetermined range of the second filtered data 14 generated in the second filtering step and stores it in the storage unit 10 as processed tire characteristic data 15. This tire characteristic data processing method can reduce errors in the measured tire characteristic data.

[0047] The tire characteristic data processed by the tire characteristic data processing method is obtained by measuring the slip ratio S and slip angle α by making one round trip between the two endpoints of a predetermined range. The data addition step adds first filtered data 12, which corresponds to one round trip of the tire characteristic data, to the outside of one endpoint (R1) and the outside of the other endpoint (R2) of the predetermined range. As a result, the tire characteristic data processing method can reduce measurement errors in tire characteristic data that includes hysteresis that occurs when measuring by making one round trip between the two endpoints of a predetermined range.

[0048] The first filtering step of the tire characteristic data processing method filters the unprocessed tire characteristic data 11 using a low-pass filter. This allows the tire characteristic data processing method to reduce higher-order vibration components contained in the unprocessed tire characteristic data 11.

[0049] The second filtering step of the tire characteristic data processing method involves filtering the processed data 13 using a low-pass filter. This allows the tire characteristic data processing method to reduce higher-order vibration components contained in the processed data 13.

[0050] The second filtering step of the tire characteristic data processing method involves resampling the processed data 13 as a pre-processing step before filtering. The tire characteristic data processing method can also reduce higher-order vibration components contained in the processed data 13 by resampling.

[0051] The tire characteristic data processing device 100 in this embodiment includes a data acquisition unit 41, a first filter processing unit 42, a data addition unit 43, a second filter processing unit 44, and a data removal unit 45. The data acquisition unit 41 takes at least one of the tire slip ratio and slip angle as variables and acquires pre-processed tire characteristic data 11 by measuring the load generated on the tire by changing the variable within a predetermined range. The first filter processing unit 42 filters the pre-processed tire characteristic data 11 acquired by the data acquisition unit 41 to generate first filtered data 12. The data addition unit 43 inverts the first filtered data 12 generated by the first filter processing unit 42 using the endpoints (R1, R2) of a predetermined range as reference points and adds it to the first filtered data 12 to generate added data 13. The second filter processing unit 44 filters the added data 13 generated by the data addition unit 43 to generate second filtered data 14. The data removal unit 45 removes data outside a predetermined range of the second filtered data 14 generated by the second filter processing unit 44. This allows the tire characteristic data processing device 100 to reduce errors occurring in the measured tire characteristic data.

[0052] The embodiments of the present invention have been described above. These embodiments are illustrative, and it will be understood by those skilled in the art that various modifications and changes are possible within the scope of the claims of the present invention, and that such modifications and changes are also within the scope of the claims of the present invention. Accordingly, the descriptions and drawings herein should be treated as illustrative rather than limiting. [Explanation of Symbols]

[0053] 11. Pre-processed tire characteristic data, 12. First filtered data, 13 Additional processed data, 14 Second filtered data, 15 Processed tire characteristic data, 41 Data acquisition unit, 42 First filter processing unit, 43 Data addition unit, 44 Second filter processing unit, 45 Data removal unit, 100 Tire characteristic data processing device.

Claims

1. A data acquisition step involves obtaining tire characteristic data by measuring the load generated on the tire while varying at least one of the tire slip ratio and slip angle within a predetermined range, and using the aforementioned variables as variables. A first filtering step is performed to filter the tire characteristic data acquired in the data acquisition step to generate first filtered data, A data addition step is to generate added data by inverting the first filtered data generated in the first filtering step using the endpoints of the predetermined range as reference points and adding it to the first filtered data, A second filtering step is performed to filter the processed data generated by the data addition step to generate second filtered data, A data removal step which removes data outside the predetermined range of the second filtered data generated by the second filtering step, A tire characteristic data processing method comprising the following features.

2. The aforementioned tire characteristic data was measured by moving the variable back and forth once between the two endpoints of the predetermined range. The tire characteristic data processing method according to claim 1, wherein the data addition step adds the first filtered data, which corresponds to one round trip of the tire characteristic data, to the outside of one endpoint and the outside of the other endpoint of the predetermined range.

3. The tire characteristic data processing method according to claim 1, wherein the first filtering step is performed by a low-pass filter.

4. The tire characteristic data processing method according to claim 1, wherein the second filtering step is performed by a low-pass filter.

5. The tire characteristic data processing method according to claim 1, wherein the second filtering step is to resample the additionally processed data as a preprocessing step.

6. A data acquisition unit that acquires tire characteristic data by measuring the load generated on the tire while using at least one of the tire slip ratio and slip angle as variables and varying the said variable within a predetermined range, A first filter processing unit that filters the tire characteristic data acquired by the data acquisition unit to generate first filtered data, A data addition unit generates added data by inverting the first filtered data generated by the first filter processing unit using the endpoints of the predetermined range as reference points and adding it to the first filtered data, A second filter processing unit that filters the processed data generated by the data addition unit to generate second filtered data, A data removal unit removes data outside the predetermined range of the second filtered data generated by the second filtering unit, A tire characteristic data processing device equipped with the following features.

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