A vehicle steering center region test data processing method, device and equipment

Abstract

The application discloses a vehicle steering center area test data processing method, device and equipment, which comprises the following steps: firstly, arranging target vehicle steering center area test data according to a preset channel and a preset format to obtain arranged data, and then automatically extracting the arranged data according to the preset channel and the preset format; secondly, performing Kalman filtering on the extracted data to obtain filtered data, and when the filtered data is determined to be reasonable data, performing periodic data interception on the filtered data, and dividing the intercepted data segment into left steering segmented data and right steering segmented data according to the positions of wave crests and wave troughs; then, the segmented data can be fitted by a six-level Fourier series, and the derivative and gradient curve are calculated, and relevant index parameter fitting calculation is performed to obtain a data processing result. Thus, the problems of low processing precision, multiple parameters and complex processing of target vehicle steering center area test data are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicles, in particular to a vehicle center region turning test data processing method, device and equipment. BACKGROUND

[0002] With the improvement of people's living standards and the rapid development of social economy, the use rate of automobiles is gradually increasing, and more and more automobiles have entered people's life, bringing great convenience to all aspects of people's life. Among them, how to improve the user's driving and riding experience, and ensure the safety and stability of vehicle driving is particularly important.

[0003] At present, the center region turning performance of the vehicle belongs to the user high perception working condition, which accounts for more than 90% of the daily road working condition, and its importance is self-evident. However, due to the steady-state characteristics of the data and the addition of the transient state, at least three cycles are required for a test, and the steering is repeated from left to right. Due to the nonlinear characteristics of the steering system and the tire system, the center region curve of the vehicle has obvious nonlinear characteristics, so the center region turning data of the vehicle has the characteristics of large fluctuation, periodicity, nonlinearity and certain dynamics, and belongs to the user high perception performance. Therefore, when processing the center region turning test data of the vehicle, how to ensure the rationality and fidelity of the data, and improve the effectiveness and accuracy of the processing result, so as to ensure that the turning design of the vehicle can meet the user's riding perception demand, improve the user experience and ensure the safety and stability of the vehicle driving is a problem to be solved at present. SUMMARY

[0004] The main purpose of the embodiment of the present application is to provide a vehicle center region turning test data processing method, device and equipment, which can effectively analyze and evaluate the vehicle center region turning test data, solve the problems of low processing precision, multiple parameters and complex processing of the vehicle center region turning test data, so as to ensure that the turning design of the vehicle can meet the user's riding perception demand, improve the user experience and ensure the safety and stability of the vehicle driving.

[0005] The embodiment of the present application provides a vehicle center region turning test data processing method, which comprises:

[0006] Obtaining target vehicle center region turning test data to be processed, and arranging the data according to a preset channel and a preset format to obtain arranged data;

[0007] According to the preset channel and the preset format, the arranged data is automatically extracted to obtain extracted data;

[0008] The extracted data is subjected to Kalman filtering to obtain filtered data;

[0009] When it is judged that the filtered data is reasonable data, according to the data characteristics of the target vehicle turning center area test data, the filtered data is periodically data-intercepted, and the intercepted data segment is divided into left turning segmented data and right turning segmented data according to the positions of wave peaks and wave troughs;

[0010] The left turning segmented data and the right turning segmented data are subjected to six-level Fourier series fitting, derivation and gradient curve calculation, and relevant index parameter fitting calculation, so as to obtain a data processing result.

[0011] In an alternative implementation, after the filtered data is obtained by performing Kalman filtering on the extracted data, the method further comprises:

[0012] The filtered data is compared with the extracted data, and it is judged whether the filtered data meets preset data accuracy and preset fitting requirements by using the comparison result.

[0013] In an alternative implementation, after the filtered data is obtained by performing Kalman filtering on the extracted data, the method further comprises:

[0014] The filtered data is subjected to signal-to-noise ratio calculation, so as to judge whether the filtered data is reasonable data after noise data is removed.

[0015] In an alternative implementation, the filtered data is periodically data-intercepted according to the data characteristics of the target vehicle turning center area test data, and the intercepted data segment is divided into left turning segmented data and right turning segmented data according to the positions of wave peaks and wave troughs, which comprises:

[0016] According to the data characteristics of the target vehicle turning center area test data, the first quarter data segment and the last quarter data segment of the filtered data are removed, and the remaining data is subjected to periodic data-interception, so as to obtain an intercepted data segment.

[0017] After each wave peak value and two wave trough values on both sides of the wave peak value are found from the intercepted data segment, the wave trough on the left side of the wave peak to the wave peak is divided into left turning segmented data, and the wave peak to the wave trough on the right side of the wave peak is divided into right turning segmented data.

[0018] In an alternative implementation, the method further comprises:

[0019] According to the subjective-objective consistency and the preset product positioning, an index evaluation and judgment are performed on the data processing result, so as to determine whether the vehicle model design of the target vehicle meets the preset design target.

[0020] Corresponding to the above vehicle steering center area test data processing method, the application provides a vehicle steering center area test data processing device, comprising:

[0021] An arrangement unit is configured to obtain target vehicle steering center area test data to be processed, and arrange the data according to a preset channel and a preset format to obtain arranged data.

[0022] An extraction unit is configured to automatically extract the arranged data according to the preset channel and the preset format to obtain extracted data.

[0023] A filtering unit is configured to perform Kalman filtering on the extracted data to obtain filtered data.

[0024] A division unit is configured to, when it is determined that the filtered data is reasonable data, perform periodic data cutting on the filtered data according to data characteristics of the target vehicle steering center area test data, and divide the cut data segment into left-turn segmented data and right-turn segmented data according to the positions of wave crests and wave troughs.

[0025] A fitting unit is configured to perform six-level Fourier series fitting on the left-turn segmented data and the right-turn segmented data, derive and gradient curve, and perform related index parameter fitting calculation to obtain a data processing result.

[0026] In an optional implementation, the device further comprises:

[0027] A comparison unit is configured to compare the filtered data with the extracted data, and use the comparison result to determine whether the filtered data meets preset data accuracy and preset fitting requirements.

[0028] In an optional implementation, the device further comprises:

[0029] A judgment unit is configured to perform signal-to-noise ratio calculation on the filtered data, so as to determine whether the filtered data is reasonable data after removing noise data.

[0030] In an optional implementation, the division unit comprises:

[0031] A removal subunit is configured to remove the first quarter data segment and the last quarter data segment of the filtered data according to data characteristics of the target vehicle steering center area test data, and perform periodic data cutting on the remaining data to obtain a cut data segment.

[0032] The dividing sub-unit is configured to divide the trough on the left side of the peak to the peak on the right side of the peak as left turning segmented data, and divide the peak to the trough on the right side of the peak as right turning segmented data after finding out each peak value and two trough values on both sides of the peak from the intercepted data segment.

[0033] In an optional implementation, the apparatus further includes:

[0034] The evaluation unit is configured to perform index evaluation and determination on the data processing result according to the subjective-objective consistency and the preset product positioning, to determine whether the vehicle model design of the target vehicle conforms to the preset design target.

[0035] Embodiments of the present application further provide a vehicle turning center area test data processing device, including: a processor, a memory, a system bus;

[0036] The processor and the memory are connected through the system bus;

[0037] The memory is configured to store one or more programs, the one or more programs including instructions that, when executed by the processor, cause the processor to perform any one of the implementation manners of the vehicle turning center area test data processing method.

[0038] Embodiments of the present application further provide a computer readable storage medium, the computer readable storage medium storing instructions, when the instructions run on a terminal device, causing the terminal device to perform any one of the implementation manners of the vehicle turning center area test data processing method.

[0039] Therefore, embodiments of the present application have the following beneficial effects:

[0040] The embodiment of the present application provides a vehicle steering center area test data processing method, device and equipment, first, target vehicle steering center area test data to be processed is acquired, and the data is arranged according to a preset channel and a preset format, to obtain arranged data, then, the arranged data is automatically extracted according to the preset channel and the preset format, to obtain extracted data; then, the extracted data is subjected to Kalman filtering, to obtain filtered data, and when it is judged that the filtered data is reasonable data, the filtered data is subjected to periodic data interception according to the data characteristics of the target vehicle steering center area test data, and the intercepted data segment is divided into left steering segmented data and right steering segmented data according to the positions of wave crests and wave troughs; further, the left steering segmented data and the right steering segmented data can be subjected to six-level Fourier series fitting, derivation and gradient curve calculation, and relevant index parameter fitting calculation, to obtain a data processing result. Therefore, effective data analysis on the target vehicle steering center area test data is realized, the problems of low processing precision, many parameters and complex processing of the target vehicle steering center area test data processing are solved, further, it is ensured that the steering design of the vehicle can meet the ride perception requirements of users, user experience is improved, and the safety and stability of vehicle driving are ensured. BRIEF DESCRIPTION OF DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0042] Figure 1 A flowchart of a vehicle steering center area test data processing method provided by the embodiment of the present application is provided.

[0043] Figure 2 A schematic diagram of the filtered data comparison provided by the embodiment of the present application is provided.

[0044] Figure 3 A schematic diagram of the intercepted data segment being divided into left steering segmented data and right steering segmented data according to the positions of wave crests and wave troughs provided by the embodiment of the present application is provided.

[0045] Figure 4 A data schematic diagram of the left steering segmented data and the right steering segmented data being subjected to six-level Fourier series fitting, derivation and gradient curve calculation, and relevant index parameter fitting calculation provided by the embodiment of the present application is provided.

[0046] Figure 5 A composition schematic diagram of a vehicle steering center area test data processing device provided by the embodiment of the present application is provided. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0048] As we all know, with the continuous advancement of high technologies such as cloud computing, artificial intelligence, modern sensing, information fusion, and communication, the future development of vehicles will accelerate, and people's perception and demand for vehicles are also gradually increasing. The steering performance of the vehicle's center area is a highly perceptible condition for users, and the data from this area exhibits characteristics such as large fluctuations, periodicity, nonlinearity, and a certain degree of dynamics. Therefore, ensuring the rationality and fidelity of the test data from the vehicle's steering center area when filtering it; improving the segmentation processing effect of left and right turn data within the period; and selecting appropriate data processing algorithms to improve the accuracy of the data processing results based on the overall requirements of gradient analysis for its evaluation index processing are all urgent problems to be solved.

[0049] Based on this, this application proposes a method, apparatus, and equipment for processing test data of the vehicle steering center area, which can effectively analyze and evaluate the test data of the vehicle steering center area, and solves the problems of low accuracy, many parameters, and complex processing of test data of the vehicle steering center area. This ensures that the vehicle steering design can meet the user's riding perception needs, improves the user experience, and ensures the safety and stability of vehicle driving.

[0050] The method for processing test data of the vehicle steering center area provided in this application will be described in detail below with reference to the accompanying drawings. See also Figure 1 The diagram illustrates a flowchart of an embodiment of a vehicle steering center area test data processing method provided in this application. This embodiment may include the following steps:

[0051] S101: Obtain the test data of the target vehicle's steering center area to be processed, and arrange the data according to the preset channel and preset format to obtain the arranged data.

[0052] In the embodiment, the steering center area test data of any vehicle using the method of the application for data processing is defined as target vehicle steering center area test data. In order to effectively process the target vehicle steering center area test data and solve the problems of low processing accuracy, many parameters and complex processing of the target vehicle steering center area test data, the application proposes that the target vehicle steering center area test data to be processed is first obtained, and the data is arranged according to the preset channel and the preset format to obtain arranged data, which is used to perform the subsequent step S102.

[0053] The vehicle identification code, the test working condition code, the data channel field name and the data format are defined as follows

[0054] Table 1 shows:

[0055]

[0056]

[0057] Table 1

[0058] S102: The arranged data is automatically extracted according to the preset channel and the preset format to obtain extracted data.

[0059] In the embodiment, in order to effectively analyze and evaluate the target vehicle steering center area test data, after the arranged data is obtained through step S101, the arranged data can be further automatically extracted according to the preset channel and the preset format to obtain extracted data, which is used to perform the subsequent step S103.

[0060] Specifically, after the arranged data is obtained, the test data file shown in Table 1 can be identified and extracted according to the preset naming format by applying the matlab function dir, for example, taking Test_Files = dir('*.tab') as an example, wherein the naming of *.tab has 9 bits, the first four bits represent the vehicle ID code, the 5th-7th bits represent the working condition code, and the 8th-9th bits represent the test number code, at this time, the vehicle working condition test round to be processed needs to be selected. Thus, after the corresponding relationship between the test data and the test round identification and the test working condition code is established, the automatic extraction of the test round identification code and the test working condition code is realized.

[0061] S103: The extracted data is subjected to Kalman filtering to obtain filtered data.

[0062] In this embodiment, after automatically extracting the arranged data according to the preset channel and preset format in step S102, the extracted data can be further subjected to Kalman filtering to obtain filtered data, which is then used to execute the subsequent step S104.

[0063] Specifically, the extracted data can be read sequentially according to the data channel encoding, and then Kalman filtered sequentially to obtain the filtered data, such as... Figure 2 As shown. The filtered data can then be compared with the extracted data, and the comparison results can be used to determine whether the filtered data meets the preset data accuracy and preset fitting requirements. Furthermore, the signal-to-noise ratio of the filtered data can be calculated to determine whether the filtered data is reasonable after removing noisy data. If so, the filtered data can be further segmented and fitted based on the characteristics of the experimental data. Specifically, when performing Kalman filtering on the extracted data, a low-parameter, high-performance robust model can be established (its model complexity can be automatically determined through data dependency) to address issues such as data noise and performance instability.

[0064] S104: When the filtered data is determined to be reasonable, the filtered data is periodically truncated according to the data characteristics of the test data of the target vehicle's steering center area, and the truncated data segments are divided into left steering segment data and right steering segment data according to the position of the peak and trough.

[0065] In this embodiment, after performing Kalman filtering on the extracted data in step S103 to obtain filtered data, when it is determined that the filtered data is reasonable, the filtered data can be periodically truncated according to the data characteristics of the test data of the target vehicle's steering center area, and the truncated data segments can be divided into left-turn segment data and right-turn segment data according to the position of the peak and trough, so as to execute the subsequent step S105.

[0066] Specifically, one possible implementation is, as follows: Figure 3 As shown, when the filtered data is determined to be reasonable, the first and second quarters of the filtered data are removed based on the characteristics of the test data in the target vehicle's steering center area. The remaining data is then subjected to periodic data truncation (at this time, the frequency of the periodic function under operating conditions is 0.2Hz, and the data segment is truncated starting from t>2.5s), resulting in the truncated data segments. Then, after identifying each peak value and its two trough values ​​on both sides from the truncated data segments, the trough to the left of the peak is divided into left-turn segment data, and the trough to the right of the peak is divided into right-turn segment data.

[0067] S105: Perform six-level Fourier series fitting on the left and right steering segment data, and derive and gradient curve, and perform related index parameter fitting calculation to obtain the data processing result.

[0068] In this embodiment, after obtaining the left and right steering segment data through step S104, further, in the case of judging the correctness of the data segmentation, the left and right steering segment data is fitted by using multi-level Fourier series, specifically, six-level Fourier series fitting is performed, the derivative and gradient curve is derived, and the related index parameter fitting calculation is performed, to obtain a data processing result with higher precision, to realize gradient analysis and processing of the target vehicle center area data, and the specific effect is as shown in Figure 4

[0069] Among them, the six-level Fourier series function formula is as follows:

[0070] y=a0+a1*cos(x*w)+b1*sin(x*w)+...

[0071] a2*cos(2*x*w)+b2*sin(2*x*w)+...

[0072] a3*cos(3*x*w)+b3*sin(3*x*w)+...

[0073] a4*cos(4*x*w)+b4*sin(4*x*w)+...

[0074] a5*cos(5*x*w)+b5*sin(5*x*w)+...

[0075] a6*cos(6*x*w)+b6*sin(6*x*w);

[0076] dy=-a1*w*sin(x*w)+b1*w*cos(x*w)...

[0077] -2*a2*w*sin(2*x*w)+2*b2*w*cos(2*x*w)...

[0078] -3*a3*w*sin(3*x*w)+3*b3*w*cos(3*x*w)...

[0079] -4*a4*w*sin(4*x*w)+4*b4*w*cos(4*x*w)...

[0080] -5*a5*w*sin(5*x*w)+5*b5*w*cos(5*x*w)...

[0081] ​- 6 * a6 * w * sin(6 * x * w) + 6 * b6 * w * cos(6 * x * w);

[0082] wherein, x and y represent the numerator and denominator of the gradient curve to be processed respectively; w represents the angular velocity of each term of the Fourier series, and the period of each Fourier is related to w as T = 2π / (nw); a1-a6 and b1-b6 represent Fourier coefficients respectively, and the trigonometric series Σ(an*cosnx+bn*sin nx) determined by the Fourier coefficients is called Fourier series, and n = 6 here, so it is called six-order Fourier series.

[0083] The function section is as follows:

[0084] ft_ = fittype('fourier6'); the function fitting form defined here is six-order Fourier series;

[0085] cf_ = fit(x, y, ft_); the fitting sub-function is defined here;

[0086] coeffvals = coeffvalues(cf_); wherein, coeffvals takes out the fitted Fourier coefficients a1-a6 and b1-b6.

[0087] Further, after obtaining the data processing result as shown in Figure 4 An optional implementation is that the data processing result obtained can be evaluated and judged according to the subjective-objective consistency and the preset product positioning to determine whether the vehicle model design of the target vehicle meets the preset design target.

[0088] For example, assuming that the center area steering gradient of a vehicle model after processing is 35.29 Nm / g, and the center area steering gradient target value is determined to be 34-38 Nm / g according to the market positioning and the input of this level vehicle model, it can be determined that this vehicle model meets the design target and can meet the user's ride perception demand.

[0089] In this way, by executing the above steps S101-S105, the vehicle identification and the working condition code definition and automatic extraction are performed in turn for the vehicle steering center area test data characteristics; the Kalman filtering processing of the discrete signal; the left and right turning segmentation processing of the data; the multi-level Fourier series fitting of the segmented data; the index evaluation and judgment according to the subjective-objective consistency and the product positioning, so as to effectively analyze and evaluate the vehicle steering center area test data, and solve the problems of low processing precision, multiple parameters and complex processing of the vehicle steering center area test data.

[0090] In summary, the vehicle turning center area test data processing method provided in the embodiment first acquires target vehicle turning center area test data to be processed, arranges the data according to a preset channel and a preset format to obtain arranged data, then automatically extracts the arranged data according to the preset channel and the preset format to obtain extracted data, next performs Kalman filtering on the extracted data to obtain filtered data, and when the filtered data is determined to be reasonable data, performs periodic data interception on the filtered data according to data characteristics of the target vehicle turning center area test data, and divides the intercepted data segment into left turning segmented data and right turning segmented data according to the positions of wave crests and wave troughs, and further performs six-level Fourier series fitting on the left turning segmented data and the right turning segmented data, derives and gradient curves, and performs relevant index parameter fitting calculation to obtain a data processing result. Thus, effective data analysis on the target vehicle turning center area test data is realized, the problems of low processing precision, multiple parameters, and complex processing of the target vehicle turning center area test data are solved, and thus the turning design of the vehicle can meet the ride perception requirements of users, the user experience is improved, and the safety and stability of vehicle driving are ensured.

[0091] Referring to Figure 5 The application also provides a vehicle turning center area test data processing device embodiment, which can include:

[0092] An arrangement unit 501 is configured to acquire target vehicle turning center area test data to be processed, and arrange the data according to a preset channel and a preset format to obtain arranged data.

[0093] An extraction unit 502 is configured to automatically extract the arranged data according to the preset channel and the preset format to obtain extracted data.

[0094] A filtering unit 503 is configured to perform Kalman filtering on the extracted data to obtain filtered data.

[0095] A division unit 504 is configured to, when the filtered data is determined to be reasonable data, perform periodic data interception on the filtered data according to data characteristics of the target vehicle turning center area test data, and divide the intercepted data segment into left turning segmented data and right turning segmented data according to the positions of wave crests and wave troughs.

[0096] A fitting unit 505 is configured to perform six-level Fourier series fitting on the left turning segmented data and the right turning segmented data, derive and gradient curves, and perform relevant index parameter fitting calculation to obtain a data processing result.

[0097] In some possible implementation manners of the present application, the apparatus further includes:

[0098] a comparison unit, configured to compare the filtered data with the extracted data, and determine whether the filtered data meets preset data accuracy and preset fitting requirements according to a comparison result.

[0099] In some possible implementation manners of the present application, the apparatus further includes:

[0100] a judgment unit, configured to perform signal-to-noise ratio calculation on the filtered data, so as to determine whether the filtered data is reasonable data after removing noise data.

[0101] In some possible implementation manners of the present application, the division unit 504 includes:

[0102] a removing subunit, configured to remove a first quarter data segment and a last quarter data segment of the filtered data according to data characteristics of the target vehicle turning center region test data, and perform periodic data interception on the remaining data to obtain an intercepted data segment;

[0103] a division subunit, configured to divide a trough on a left side of a wave crest to the wave crest as left turning segmented data, and divide the wave crest to a trough on a right side of the wave crest as right turning segmented data after finding out each wave crest and two troughs on both sides of the wave crest from the intercepted data segment.

[0104] In some possible implementation manners of the present application, the apparatus further includes:

[0105] an evaluation unit, configured to perform index evaluation and determination on the data processing result according to subjective-objective consistency and preset product positioning, so as to determine whether a vehicle model design of the target vehicle meets a preset design target.

[0106] As can be seen from the above embodiments, the vehicle turning center area test data processing device provided by the embodiments of the present application firstly acquires target vehicle turning center area test data to be processed, and arranges the data according to a preset channel and a preset format to obtain arranged data, then automatically extracts the arranged data according to the preset channel and the preset format to obtain extracted data; next, the extracted data is subjected to Kalman filtering to obtain filtered data, and when the filtered data is determined to be reasonable data, the filtered data is subjected to periodic data interception according to the data characteristics of the target vehicle turning center area test data, and the intercepted data segment is divided into left turning segmented data and right turning segmented data according to the positions of the wave crest and the wave trough; further, the left turning segmented data and the right turning segmented data can be subjected to six-level Fourier series fitting, derivation and gradient curve calculation, and relevant index parameter fitting calculation to obtain a data processing result. Thus, effective data analysis of the target vehicle turning center area test data is realized, the problems of low processing precision, multiple parameters and complex processing of the target vehicle turning center area test data are solved, and thus the turning design of the vehicle can meet the ride perception requirements of users, the user experience is improved, and the safety and stability of vehicle driving are ensured.

[0107] Further, the embodiments of the present application further provide a vehicle turning center area test data processing device, comprising: a processor, a memory, a system bus;

[0108] The processor and the memory are connected through the system bus;

[0109] The memory is used to store one or more programs, the one or more programs include instructions, the instructions make the processor execute any one of the implementation methods of the above vehicle turning center area test data processing method when executed by the processor.

[0110] Further, the embodiments of the present application further provide a computer readable storage medium, the computer readable storage medium stores instructions, when the instructions run on a terminal device, make the terminal device execute any one of the implementation methods of the above vehicle turning center area test data processing method.

[0111] Those skilled in the art can clearly understand that all or part of the steps of the above-mentioned method in the embodiments can be implemented by means of software and necessary universal hardware platforms, from the description of the above-mentioned embodiments. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product in essence or in the part of the prior art that makes contributions. The computer software product can be stored in a storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network communication device such as a media gateway, etc.) execute the method described in each embodiment or some part of the embodiments of the present application.

[0112] It should be noted that the various embodiments in the specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and the related parts can be referred to the method part.

[0113] It should also be noted that the terms such as first and second in the present document are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between the entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0114] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to the embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method of processing test data for a vehicle steering center region, characterized by, The method comprises the following steps: acquiring target vehicle turning center area test data to be processed, and arranging the data according to a preset channel and a preset format to obtain arranged data; automatically extracting the arranged data according to the preset channel and the preset format to obtain extracted data; performing Kalman filtering on the extracted data to obtain filtered data; when it is judged that the filtered data is reasonable data, performing periodic data cutting on the filtered data according to data characteristics of the target vehicle turning center area test data, and dividing the cut data segment into left turning segmented data and right turning segmented data according to the positions of wave crests and wave troughs; performing six-level Fourier series fitting on the left turning segmented data and the right turning segmented data, and performing derivation and gradient curve calculation, and performing relevant index parameter fitting calculation to obtain a data processing result.

2. The method of claim 1, wherein, After the step of performing Kalman filtering on the extracted data to obtain filtered data, the method further comprises the following steps: comparing the filtered data with the extracted data, and judging whether the filtered data meets preset data accuracy and preset fitting requirements by using the comparison result.

3. The method of claim 1, wherein, After the step of performing Kalman filtering on the extracted data to obtain filtered data, the method further comprises the following steps: performing signal-to-noise ratio calculation on the filtered data, so as to judge whether the filtered data is reasonable data after removing noise data.

4. The method of claim 1, wherein, The step of performing periodic data cutting on the filtered data according to data characteristics of the target vehicle turning center area test data, and dividing the cut data segment into left turning segmented data and right turning segmented data comprises the following steps: according to the data characteristics of the target vehicle turning center area test data, removing the first 1 / 4 data segment and the last 1 / 4 data segment of the filtered data, and performing periodic data cutting on the remaining data to obtain a cut data segment; after finding each wave crest value and two wave trough values on the left and right sides of the wave crest value from the cut data segment, dividing the wave trough on the left side of the wave crest to the wave crest as left turning segmented data, and dividing the wave crest to the wave trough on the right side of the wave crest as right turning segmented data.

5. The method of claim 1, wherein, The method further comprises the following steps: performing index evaluation and judgment on the data processing result according to subjective-objective consistency and a preset product positioning, so as to determine whether the vehicle model design of the target vehicle meets a preset design target.

6. A vehicle turning center region test data processing apparatus characterized by comprising: The method comprises the following steps: an arranging unit, configured to acquire target vehicle turning center area test data to be processed, and arrange the data according to a preset channel and a preset format to obtain arranged data; an extracting unit, configured to automatically extract the arranged data according to the preset channel and the preset format to obtain extracted data; a filtering unit, configured to perform Kalman filtering on the extracted data to obtain filtered data; The division unit is configured to, when it is determined that the filtered data is reasonable data, perform periodic data cutting on the filtered data according to data characteristics of the target vehicle turning center region test data, and divide the cut data segment into left turning segmented data and right turning segmented data according to positions of wave crests and wave troughs. The fitting unit is configured to perform six-level Fourier series fitting on the left turning segmented data and the right turning segmented data, derive and calculate gradient curves, and perform correlation index parameter fitting calculation to obtain a data processing result.

7. The apparatus of claim 6, wherein, The division unit includes: The elimination sub-unit is configured to eliminate a first quarter data segment and a last quarter data segment of the filtered data according to data characteristics of the target vehicle turning center region test data, and reserve the data for periodic data cutting to obtain a cut data segment. The division sub-unit is configured to, after finding each wave crest value and two wave trough values on both sides of the wave crest value from the cut data segment, divide the wave trough on the left side of the wave crest to the wave crest as left turning segmented data, and divide the wave crest to the wave trough on the right side of the wave crest as right turning segmented data.

8. The apparatus of claim 6, wherein, The device further includes: The evaluation unit is configured to perform index evaluation and determination on the data processing result according to subjective-objective consistency and a preset product positioning to determine whether a vehicle model design of the target vehicle meets a preset design target.

9. A vehicle turning center region test data processing apparatus characterized by comprising: The device includes: a processor, a memory, and a system bus; the processor and the memory are connected through the system bus; the memory is configured to store one or more programs, the one or more programs including instructions that, when executed by the processor, cause the processor to perform the method of any one of claims 1-5.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores instructions, and when the instructions run on the terminal device, the terminal device performs the method of any one of claims 1-5.

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