Data processing method and device for steering stability test of steering wheel central area

Abstract

The present application relates to a data processing method and device for the handling stability test of the center area of a steering wheel, belonging to the technical field of vehicle testing. The method includes the following steps: monitoring a preset target vehicle at a plurality of preset test points, integrating the stability-related parameters under the same working condition to obtain a first parameter curve graph; splitting the peaks and valleys in the first parameter curve graph into an increasing curve graph and a decreasing curve graph; obtaining an average data hysteresis loop based on the increasing curve graph and the decreasing curve graph; obtaining an increasing interval variable fitting region and a decreasing interval variable fitting region of different influencing factor parameters based on the average data hysteresis loop. The present application integrates, splits, reorganizes, and averages the collected time-domain data to obtain an average hysteresis loop, and obtains the slope through a variable fitting interval linear fitting method, so as to meet the requirements of the handling stability test work in the center area of the steering wheel.

Description

Technical Field

[0001] This application relates to the technical field of vehicle testing, and particularly to a data processing method and device for the handling stability test of the steering wheel center area. Background Art

[0002] In the vehicle performance test, the handling stability test of the steering wheel center area is an important part of the vehicle performance test. In the traditional method of the handling stability test of the steering wheel center area, data processing is an extremely important link and an important aspect to ensure the validity of the test results.

[0003] In the traditional data processing method, the specific process is as follows:

[0004] First, carefully analyze the time history of the listed variables, especially the steering wheel angle, steering wheel angular velocity, vehicle longitudinal speed, and vehicle lateral acceleration. At least four cycles with good control indicators should be selected for data analysis.

[0005] Second, plot the data in a rectangular coordinate system. The graph is a set of loops formed by superimposing multiple hysteresis loops, and the number of loops is equal to the number of cycles selected.

[0006] Furthermore, the set of loops should be averaged in an appropriate manner. The recommended method is polynomial fitting, and the fitting order value is 3. When processing data, first determine the abscissa interval of the data. In this interval, select an interval at a certain ratio. When selecting, ensure that the interval is large enough to cover the data area of concern, but avoid the influence of the hysteresis effect at both ends. The recommended ratio of the interval occupying the abscissa interval is 50% - 70%.

[0007] Finally, it is recommended to perform linear fitting on the fitting polynomial in the data area of concern to estimate the slope. Among them, the average slope should be fitted in the specified area. For transient efficiency, it should be fitted in a small area near the concern point. The typical area value is the range corresponding to the positive and negative changes in lateral acceleration of 0.1 m / s². Each hysteresis loop can be analyzed separately, and the characteristic parameters of each loop are averaged to obtain the final result. Finally, through the polynomial fitting of the set of hysteresis loops, the vertical hysteresis area, the horizontal hysteresis area, and the slope are obtained.

[0008] Therefore, how to provide a more convenient data processing technology to meet the handling stability test work of the steering wheel center area is a technical problem that urgently needs to be solved at present. Summary of the Invention

[0009] The present application provides a data processing method and device for the handling stability test of the steering wheel center area. By integrating, splitting, reorganizing, and averaging the collected time-domain data, an average hysteresis loop is obtained, and the slope is obtained through a variable fitting interval linear fitting method, so as to conveniently and quickly process the data of the handling stability test of the steering wheel center area and meet the requirements of the handling stability test of the steering wheel center area.

[0010] To achieve the above object, the present application provides the following solutions.

[0011] In a first aspect, the present application provides a data processing method for the handling stability test of the steering wheel center area, and the method includes the following steps:

[0012] Monitor a preset target vehicle at a plurality of preset test points, integrate the stability-related parameters obtained by monitoring under the same working condition, and obtain a first parameter curve graph;

[0013] Split the peaks and valleys in the first parameter curve graph into an increasing curve graph and a decreasing curve graph;

[0014] Based on the increasing curve graph and the decreasing curve graph, obtain an average data hysteresis loop corresponding to the influencing factor parameters that affect the stability-related parameters;

[0015] Based on the average data hysteresis loop, obtain an increasing interval variable fitting region and a decreasing interval variable fitting region corresponding to different influencing factor parameters of the stability-related parameters; wherein,

[0016] The stability-related parameters include steering wheel angle, steering wheel angular velocity, vehicle longitudinal velocity, and vehicle lateral acceleration;

[0017] The influencing factor parameters corresponding to the steering wheel angle include torque, yaw angular velocity, and lateral acceleration.

[0018] Specifically, in the step of splitting the peaks and valleys in the first parameter curve graph into an increasing curve graph and a decreasing curve graph, the following steps are included:

[0019] Identify the peaks and valleys in the first parameter curve graph, and split the first parameter curve graph into an increasing curve graph and a decreasing curve graph according to the valley-to-peak and peak-to-valley.

[0020] Specifically, in the step of obtaining an average data hysteresis loop corresponding to the influencing factor parameters that affect the stability-related parameters based on the increasing curve graph and the decreasing curve graph, the following steps are included:

[0021] Based on the increasing curve graph and the decreasing curve graph, obtain the average data curve graph of the increasing interval and the average data curve graph of the decreasing interval corresponding to the influencing factor parameters that affect the stability-related parameters, and then obtain the corresponding average data hysteresis loop.

[0022] Specifically, the steps of identifying the peaks and valleys in the first parameter curve graph and splitting the first parameter curve graph into an increasing curve graph and a decreasing curve graph according to the valleys to peaks and peaks to valleys include the following:

[0023] Identify the peaks and valleys in the first parameter curve graph, and split to obtain multiple curve segments from peaks to valleys and curve segments from valleys to peaks;

[0024] Integrate the curve segments from peaks to valleys obtained according to the first parameter curve graph to obtain the increasing curve graph;

[0025] Integrate the curve segments from valleys to peaks obtained according to the first parameter curve graph to obtain the decreasing curve graph.

[0026] Specifically, the steps of obtaining the average data curve graph of the increasing interval and the average data curve graph of the decreasing interval corresponding to the influencing factor parameters that affect the stability-related parameters based on the increasing curve graph and the decreasing curve graph, and then obtaining the corresponding average data hysteresis loop include the following:

[0027] Set an analysis minimum unit based on the types of the stability-related parameters;

[0028] Based on the analysis minimum unit, obtain the corresponding analysis parameter positions on the increasing curve graph and the decreasing curve graph;

[0029] Based on each of the analysis parameter positions, obtain the average values of the influencing factor parameters corresponding to different test points, and then obtain the average data curve graph of the increasing interval and the average data curve graph of the decreasing interval corresponding to the influencing factor parameters;

[0030] Perform linear fitting on the average data curve graph of the increasing interval and the average data curve graph of the decreasing interval to obtain the corresponding average data hysteresis loop.

[0031] In a second aspect, the present application provides a data processing device for a steering wheel center area handling stability test, and the device includes:

[0032] A data collection module, which is used to monitor a preset target vehicle at a plurality of preset test points, integrate the stability-related parameters obtained by monitoring under the same working condition, and obtain a first parameter curve graph;

[0033] A data splitting module, which is used to split the peaks and valleys in the first parameter curve graph into an increasing curve graph and a decreasing curve graph;

[0034] A data analysis module, which is used to obtain an average data hysteresis loop corresponding to the influencing factor parameters that affect the stability-related parameters based on the increasing curve graph and the decreasing curve graph;

[0035] A data fitting module, which is used to obtain an increasing interval variable fitting region and a decreasing interval variable fitting region corresponding to different influencing factor parameters of the stability-related parameters based on the average data hysteresis loop; wherein,

[0036] The stability-related parameters include steering wheel angle, steering wheel angular velocity, vehicle longitudinal speed, and vehicle lateral acceleration;

[0037] The influencing factor parameters corresponding to the steering wheel angle include torque, yaw angular velocity, and lateral acceleration.

[0038] Further, the data splitting module is also used to identify the peaks and valleys in the first parameter curve graph, and split the first parameter curve graph into an increasing curve graph and a decreasing curve graph according to from valley to peak and from peak to valley.

[0039] Further, the data analysis module is also used to obtain an increasing interval average data curve graph and a decreasing interval average data curve graph corresponding to the influencing factor parameters that affect the stability-related parameters based on the increasing curve graph and the decreasing curve graph, and then obtain the corresponding average data hysteresis loop.

[0040] Further, the data splitting module is also used to identify the peaks and valleys in the first parameter curve graph, and split to obtain a plurality of peak-to-valley curve segments and valley-to-peak curve segments;

[0041] The data splitting module is also used to integrate the peak-to-valley curve segments obtained according to the first parameter curve graph to obtain the increasing curve graph;

[0042] The data splitting module is also used to integrate the valley-to-peak curve segments obtained according to the first parameter curve graph to obtain the decreasing curve graph.

[0043] Further, the data analysis module is also used to set an analysis minimum unit based on the types of the stability-related parameters;

[0044] The data analysis module is also used to obtain the corresponding analysis parameter positions on the increasing curve graph and the decreasing curve graph based on the analysis minimum unit;

[0045] The data analysis module is further configured to obtain the average values of the influencing factor parameters corresponding to different test points based on the positions of the analysis parameters, and further obtain the average data curve graph of the increasing interval and the average data curve graph of the decreasing interval corresponding to the influencing factor parameters;

[0046] The data analysis module is further configured to perform linear fitting on the average data curve graph of the increasing interval and the average data curve graph of the decreasing interval to obtain the corresponding average data hysteresis loop.

[0047] The beneficial effects brought by the technical solution provided by this application include:

[0048] This application integrates, splits, reorganizes, and averages the collected time-domain data to obtain an average hysteresis loop, and obtains the slope through a variable fitting interval linear fitting method, so as to conveniently and quickly process the handling stability test data in the center area of the steering wheel and meet the handling stability test work in the center area of the steering wheel. Description of the Drawings

[0049] In order to more clearly illustrate the technical solutions in the embodiments of this application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of this application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0050] Figure 1 It is a flowchart of the steps of the data processing method for the handling stability test in the center area of the steering wheel provided in the embodiments of this application;

[0051] Figure 2 It is a curve graph corresponding to five groups of steering wheel angle data in the data processing method for the handling stability test in the center area of the steering wheel provided in the embodiments of this application;

[0052] Figure 3 It is a curve graph corresponding to the integrated steering wheel angle data in the data processing method for the handling stability test in the center area of the steering wheel provided in the embodiments of this application;

[0053] Figure 4 It is a curve graph obtained after splitting the steering wheel angle data in the data processing method for the handling stability test in the center area of the steering wheel provided in the embodiments of this application;

[0054] Figure 5 It is a curve graph corresponding to the data in the increasing area in the data processing method for the handling stability test in the center area of the steering wheel provided in the embodiments of this application;

[0055] Figure 6It is a curve graph corresponding to the data in the decreasing area in the data processing method for the steering wheel center area handling stability test provided in the embodiments of the present application;

[0056] Figure 7 It is a schematic diagram corresponding to the average data of each measurement point at each steering wheel angle position obtained with the smallest unit in the data processing method for the steering wheel center area handling stability test provided in the embodiments of the present application;

[0057] Figure 8 It is a curve graph corresponding to the average hysteresis loop of the steering wheel angle vs. yaw rate in the data processing method for the steering wheel center area handling stability test provided in the embodiments of the present application;

[0058] Figure 9 It is a schematic diagram corresponding to the variable set area of the increasing interval of the steering wheel angle vs. yaw rate in the data processing method for the steering wheel center area handling stability test provided in the embodiments of the present application;

[0059] Figure 10 It is a structural block diagram of the data processing device for the steering wheel center area handling stability test provided in the embodiments of the present application. Detailed implementation manners

[0060] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0061] The following further elaborates on the embodiments of the present application with reference to the accompanying drawings.

[0062] The embodiments of the present application provide a data processing method and device for the steering wheel center area handling stability test. By integrating, splitting, reorganizing, and averaging the collected time-domain data, an average hysteresis loop is obtained, and the slope is obtained through a variable fitting interval linear fitting method, so that the data of the steering wheel center area handling stability test can be processed conveniently and quickly, meeting the requirements of the steering wheel center area operation stability test work.

[0063] To achieve the above technical effects, the overall idea of the present application is as follows:

[0064] A data processing method for the steering wheel center area handling stability test, the method includes the following steps:

[0065] S1. Monitor a preset target vehicle at a plurality of preset test points, integrate the stability-related parameters obtained from the monitoring under the same working condition, and obtain a first parameter curve graph;

[0066] S2. Split the peaks and valleys in the first parameter curve graph into an increasing curve graph and a decreasing curve graph;

[0067] S3. Based on the increasing curve graph and the decreasing curve graph, obtain the average data hysteresis loop corresponding to the influencing factor parameters that affect the stability-related parameters;

[0068] S4. Based on the average data hysteresis loop, obtain the variable fitting regions in the increasing intervals and the variable fitting regions in the decreasing intervals of the stability-related parameters corresponding to different influencing factor parameters; wherein,

[0069] The stability-related parameters include steering wheel angle, steering wheel angular velocity, vehicle longitudinal velocity, and vehicle lateral acceleration;

[0070] The influencing factor parameters corresponding to the steering wheel angle include torque, yaw angular velocity, and lateral acceleration.

[0071] The following further elaborates on the embodiments of the present application with reference to the accompanying drawings.

[0072] See Figures 1-9 As shown, the embodiments of the present application provide a data processing method for the steering wheel center area handling stability test. The method includes the following steps:

[0073] S1. Monitor a preset target vehicle at a plurality of preset test points, integrate the stability-related parameters obtained from the monitoring under the same working condition, and obtain a first parameter curve graph;

[0074] S2. Split the peaks and valleys in the first parameter curve graph into an increasing curve graph and a decreasing curve graph;

[0075] S3. Based on the increasing curve graph and the decreasing curve graph, obtain the average data hysteresis loop corresponding to the influencing factor parameters that affect the stability-related parameters;

[0076] S4. Based on the average data hysteresis loop, obtain the variable fitting regions in the increasing intervals and the variable fitting regions in the decreasing intervals of the stability-related parameters corresponding to different influencing factor parameters; wherein,

[0077] The stability-related parameters include steering wheel angle, steering wheel angular velocity, vehicle longitudinal velocity, and vehicle lateral acceleration;

[0078] The influencing factor parameters corresponding to the steering wheel angle include torque, yaw angular velocity, and lateral acceleration.

[0079] In the embodiments of the present application, by integrating, splitting, reorganizing, and averaging the collected time-domain data, an average hysteresis loop is obtained, and the slope is obtained by a variable fitting interval linear fitting method, so that the handling stability test data of the steering wheel center area can be processed conveniently and quickly, meeting the requirements of the handling stability test of the steering wheel center area.

[0080] Specifically, in step S2, when splitting the peaks and valleys in the first parameter curve graph into an increasing curve graph and a decreasing curve graph, the following steps are included:

[0081] Identify the peaks and valleys in the first parameter curve graph, and split the first parameter curve graph into an increasing curve graph and a decreasing curve graph according to from valley to peak and from peak to valley.

[0082] Specifically, in step S3, when obtaining the average data hysteresis loop corresponding to the influencing factor parameters of the stability-related parameters based on the increasing curve graph and the decreasing curve graph, the following steps are included:

[0083] Based on the increasing curve graph and the decreasing curve graph, obtain the increasing interval average data curve graph and the decreasing interval average data curve graph corresponding to the influencing factor parameters of the stability-related parameters, and then obtain the corresponding average data hysteresis loop.

[0084] Specifically, when identifying the peaks and valleys in the first parameter curve graph and splitting the first parameter curve graph into an increasing curve graph and a decreasing curve graph according to from valley to peak and from peak to valley, the following steps are included:

[0085] Identify the peaks and valleys in the first parameter curve graph, and split to obtain multiple peak-to-valley curve segments and valley-to-peak curve segments;

[0086] Integrate the peak-to-valley curve segments obtained according to the first parameter curve graph to obtain the increasing curve graph;

[0087] Integrate the valley-to-peak curve segments obtained according to the first parameter curve graph to obtain the decreasing curve graph.

[0088] Specifically, when obtaining the increasing interval average data curve graph and the decreasing interval average data curve graph corresponding to the influencing factor parameters of the stability-related parameters based on the increasing curve graph and the decreasing curve graph, and then obtaining the corresponding average data hysteresis loop, the following steps are included:

[0089] Based on the types of the stability-related parameters, set an analysis minimum unit;

[0090] Based on the minimum analysis unit, obtain the corresponding analysis parameter positions on the increasing curve graph and the decreasing curve graph;

[0091] Based on each of the analysis parameter positions, obtain the average values of the influencing factor parameters corresponding to different test points, and further obtain the average data curve graph of the increasing interval and the average data curve graph of the decreasing interval corresponding to the influencing factor parameters;

[0092] Perform linear fitting on the average data curve graph of the increasing interval and the average data curve graph of the decreasing interval to obtain the corresponding average data hysteresis loop.

[0093] Based on the technical solution of the embodiment of the present application, a practical implementation process is given as follows:

[0094] Premise of this technical solution: Monitor the visually inspected vehicle based on multiple test points.

[0095] The first step is the grouping operation. Group the stability-related parameters obtained from the monitoring according to the same working conditions; where

[0096] Same working conditions means that the vehicle speed and vehicle acceleration in the working conditions are equal at the same time.

[0097] It should be noted that the stability-related parameters include the steering wheel angle, steering wheel angular velocity, vehicle longitudinal speed, and vehicle lateral acceleration. The following operation process takes the steering wheel angle as the stability-related parameter as an example for detailed description.

[0098] The second step is the integration operation. Among the stability-related parameters after grouping, take the steering wheel angle data as the standard, find the steering wheel angle data, specifically sine or quasi-sine curve data, and identify all the peak and valley positions therein, record the first and last valley positions, and splice all the stability-related parameters of each file under the same working conditions according to the measurement points to obtain a set of integrated data; where

[0099] All the stability-related parameters of each file refer to that the monitoring data obtained from different monitoring points are stored in their respective corresponding files. Therefore, it is necessary to integrate the monitoring data of different monitoring points, that is, all the stability-related parameters of each file.

[0100] As shown in the accompanying drawings Figure 2 and Figure 3 shown, Figure 2 are the starting valley positions corresponding to five groups of steering wheel angle data, while Figure 3 is the integrated steering wheel angle data.

[0101] Step 3: Splitting operation. After integration, there is only one set of data for each working condition, that is, each working condition can be regarded as having data from only one file, and there is also only one piece of data for each measuring point. Taking the steering wheel angle as the standard, find the sine or sine-like curve data in the steering wheel angle data, that is, the positions of all wave troughs and wave peaks, and split them according to continuous data wave trough - wave peak and wave peak - wave trough;

[0102] As shown in the accompanying drawings of the specification Figure 4 shown, it is a curve graph obtained after splitting the steering wheel angle data.

[0103] Step 4: Recombination operation. Recombine the steering wheel data in an increasing and decreasing manner, that is, wave trough - wave peak and wave peak - wave trough, so that there are two groups after recombination: increasing area data and decreasing area data;

[0104] As shown in the accompanying drawings of the specification Figure 5 and Figure 6 shown, Figure 5 is a schematic diagram of the increasing area data, while Figure 6 is a schematic diagram of the decreasing area data.

[0105] Step 5: Calculating the average value. After splitting and recombination, each working condition obtains two sets of data, namely increasing area data and decreasing area data. Taking the steering wheel angle as the standard, with every 0.1° of the steering wheel angle data as the minimum unit, find the corresponding actual position of the steering wheel angle, that is, set the minimum analysis unit to 0.1°. Based on this position, find the accurate data of each segment of data corresponding to different measuring points in its original file, and then calculate the average value of all segmented different measuring points based on the points of each steering wheel angle value after segmentation. Finally, obtain the average data. Each working condition has two sets of data, namely the average data in the increasing interval (left turn) and the average data in the decreasing interval (right turn);

[0106] Taking the steering wheel angle position of 1.5° in the increasing interval (left turn) as an example, find the accurate data of torque, yaw rate, and lateral acceleration at this position. As Figure 7 shown, taking the yaw rate as an example, its accurate data at the steering wheel angle position of 1.5° is Y1, Y2, Y3, Y4, Y5, Y6, and the average data is (Y1 + Y2 + Y3 + Y4 + Y5 + Y6) / 6 = (0.22 + 0.3 + 0.22 + 0.21 + 0.15 + 0.05) / 6 = 0.19.

[0107] As shown in the accompanying drawings of the specification Figure 7 and Figure 8 shown, taking 0.1° as the minimum unit to find the average data of each measuring point at each steering wheel angle position, and obtain the average hysteresis loop between different measuring points. Figure 8 is the average hysteresis loop of steering wheel angle vs yaw rate;

[0108] Figure 7 The curves in it correspond to steering angle, torque, yaw rate, and lateral acceleration from top to bottom in sequence;

[0109] Figure 8 The curves in it correspond to right turn - monotonically decreasing and left turn - monotonically increasing from top to bottom respectively.

[0110] The sixth step is linear fitting. The principle for selecting the variable fitting region is as follows:

[0111] Count the number n of steering wheel angle positions with a minimum unit of 0.1° in the increasing interval or decreasing interval of the statistical average hysteresis loop, then the variable fitting region is the number of 0.1n steering wheel angle positions, that is, select 0.1n data points for linear fitting;

[0112] Taking the average hysteresis loop of steering wheel angle vs yaw rate as an example, the number of steering wheel angle positions with a minimum unit of 0.1° in its increasing interval is 230, then the variable fitting region is the number of 23 steering wheel angle positions, that is, select 23 data points for linear fitting, as Figure 9 shown; among them,

[0113] Figure 9 The curves in it correspond to right turn - monotonically decreasing and left turn - monotonically increasing from top to bottom respectively.

[0114] Based on the above operations, data processing is performed on the original data. According to this method, the data is integrated, split, reorganized, averaged, the variable fitting region is determined, and index calculation is performed. The test result processing meets the requirements of engineering applications;

[0115] It has the advantages of meeting the standard requirements, simple method, reliable data, beautiful curves, good test repeatability, and wide application.

[0116] See Figure 10 As shown, based on the same inventive concept as the method real - time example, the embodiment of the present application provides a data processing device for the steering wheel center area handling stability test. The device includes:

[0117] A data collection module, which is used to monitor a preset target vehicle at a preset plurality of test points, integrate the stability - related parameters obtained from the monitoring under the same working condition, and obtain a first parameter curve graph;

[0118] A data splitting module, which is used to split the peaks and valleys in the first parameter curve graph into an increasing curve graph and a decreasing curve graph;

[0119] A data analysis module, which is used to obtain the average data hysteresis loop corresponding to the influencing factor parameters affecting the stability - related parameters based on the increasing curve graph and the decreasing curve graph;

[0120] A data fitting module, which is used to obtain a variable fitting region for the increasing interval and a variable fitting region for the decreasing interval of the stability-related parameters corresponding to different influencing factor parameters based on the average data hysteresis loop; wherein,

[0121] The stability-related parameters include steering wheel angle, steering wheel angular velocity, vehicle longitudinal speed, and vehicle lateral acceleration;

[0122] The influencing factor parameters corresponding to the steering wheel angle include torque, yaw angular velocity, and lateral acceleration.

[0123] In the embodiments of the present application, by integrating, splitting, reorganizing, and averaging the collected time-domain data to obtain an average hysteresis loop, and obtaining the slope through a variable fitting interval linear fitting method, the handling stability test data of the steering wheel center area can be processed conveniently and quickly, meeting the requirements of the steering wheel center area handling stability test work.

[0124] Further, the data splitting module is further used to identify the peaks and valleys in the first parameter curve graph, and split the first parameter curve graph into an increasing curve graph and a decreasing curve graph according to the valleys to peaks and peaks to valleys.

[0125] Further, the data analysis module is further used to obtain an increasing interval average data curve graph and a decreasing interval average data curve graph of the influencing factor parameters affecting the stability-related parameters based on the increasing curve graph and the decreasing curve graph, and then obtain the corresponding average data hysteresis loop.

[0126] Further, the data splitting module is further used to identify the peaks and valleys in the first parameter curve graph, and split to obtain multiple peak-to-valley curve segments and valley-to-peak curve segments;

[0127] The data splitting module is further used to integrate the peak-to-valley curve segments obtained according to the first parameter curve graph to obtain the increasing curve graph;

[0128] The data splitting module is further used to integrate the valley-to-peak curve segments obtained according to the first parameter curve graph to obtain the decreasing curve graph.

[0129] Further, the data analysis module is further used to set an analysis minimum unit based on the types of the stability-related parameters;

[0130] The data analysis module is further used to obtain the corresponding analysis parameter positions on the increasing curve graph and the decreasing curve graph based on the analysis minimum unit;

[0131] The data analysis module is further configured to obtain the average values of the influencing factor parameters corresponding to different test points based on the positions of the analysis parameters, and further obtain the average data curve graph of the increasing interval and the average data curve graph of the decreasing interval corresponding to the influencing factor parameters;

[0132] The data analysis module is further configured to perform linear fitting on the average data curve graph of the increasing interval and the average data curve graph of the decreasing interval to obtain the corresponding average data hysteresis loop.

[0133] It should be noted that the data processing device for the steering wheel center area handling stability test provided in the embodiments of the present application has corresponding technical problems, technical means, and technical effects, which are similar in principle to those of the data processing method for the steering wheel center area handling stability test.

[0134] It should be noted that in the present application, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the element.

[0135] The above are only specific embodiments of the present application, enabling those skilled in the art to understand or implement the present application. Various modifications to these embodiments will be obvious 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 these embodiments shown herein, but will be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A data processing method for the handling stability test of the disk center area, characterized in that, the method comprises the following steps: Monitoring a preset target vehicle at a plurality of preset test points, integrating the stability-related parameters obtained from the monitoring under the same working condition, and obtaining a first parameter curve graph; Splitting the peaks and valleys in the first parameter curve graph into an increasing curve graph and a decreasing curve graph; Based on the increasing curve graph and the decreasing curve graph, obtaining an average data hysteresis loop corresponding to the influencing factor parameters that affect the stability-related parameters; Based on the average data hysteresis loop, obtaining an increasing interval variable fitting region and a decreasing interval variable fitting region corresponding to different influencing factor parameters of the stability-related parameters; wherein, the stability-related parameters include steering wheel angle, steering wheel angular velocity, vehicle longitudinal velocity, and vehicle lateral acceleration; the influencing factor parameters corresponding to the steering wheel angle include torque, yaw angular velocity, and lateral acceleration.

2. The data processing method for the handling stability test of the disk center area according to claim 1, characterized in that, in the step of splitting the peaks and valleys in the first parameter curve graph into an increasing curve graph and a decreasing curve graph, the following steps are included: Identifying the peaks and valleys in the first parameter curve graph, and splitting the first parameter curve graph into an increasing curve graph and a decreasing curve graph according to valley-to-peak and peak-to-valley.

3. The data processing method for the handling stability test of the disk center area according to claim 1, characterized in that, in the step of obtaining an average data hysteresis loop corresponding to the influencing factor parameters that affect the stability-related parameters based on the increasing curve graph and the decreasing curve graph, the following steps are included: Based on the increasing curve graph and the decreasing curve graph, obtaining an increasing interval average data curve graph and a decreasing interval average data curve graph corresponding to the influencing factor parameters that affect the stability-related parameters, and further obtaining the corresponding average data hysteresis loop.

4. The data processing method for the handling stability test of the disk center area according to claim 2, characterized in that, in the step of identifying the peaks and valleys in the first parameter curve graph, and splitting the first parameter curve graph into an increasing curve graph and a decreasing curve graph according to valley-to-peak and peak-to-valley, the following steps are included: Identifying the peaks and valleys in the first parameter curve graph, and splitting to obtain a plurality of peak-to-valley curve segments and valley-to-peak curve segments; Integrating the peak-to-valley curve segments obtained according to the first parameter curve graph to obtain the increasing curve graph; Integrating the valley-to-peak curve segments obtained according to the first parameter curve graph to obtain the decreasing curve graph.

5. The data processing method for the handling stability test of the disk center area according to claim 3, characterized in that, in the step of obtaining an increasing interval average data curve graph and a decreasing interval average data curve graph corresponding to the influencing factor parameters that affect the stability-related parameters based on the increasing curve graph and the decreasing curve graph, and further obtaining the corresponding average data hysteresis loop, the following steps are included: Set an analysis minimum unit based on the types of the stability-related parameters; Based on the analysis minimum unit, obtain the corresponding analysis parameter positions on the increasing curve graph and the decreasing curve graph; Based on each of the analysis parameter positions, obtain the average values of the influencing factor parameters corresponding to different test points, and further obtain the average data curve graph of the increasing interval and the average data curve graph of the decreasing interval corresponding to the influencing factor parameters; Perform linear fitting on the average data curve graph of the increasing interval and the average data curve graph of the decreasing interval to obtain the corresponding average data hysteresis loop.

6. A data processing device for the handling stability test of the center area of the disc, characterized in that the device includes: A data collection module, which is used to monitor a preset target vehicle at a plurality of preset test points, integrate the stability-related parameters obtained from the monitoring under the same working condition, and obtain a first parameter curve graph; A data splitting module, which is used to split the peaks and valleys in the first parameter curve graph into an increasing curve graph and a decreasing curve graph; A data analysis module, which is used to obtain the average data hysteresis loop corresponding to the influencing factor parameters that affect the stability-related parameters based on the increasing curve graph and the decreasing curve graph; A data fitting module, which is used to obtain an increasing interval variable fitting area and a decreasing interval variable fitting area of the stability-related parameters corresponding to different influencing factor parameters based on the average data hysteresis loop; wherein, the stability-related parameters include steering wheel angle, steering wheel angular velocity, vehicle longitudinal speed, and vehicle lateral acceleration; the influencing factor parameters corresponding to the steering wheel angle include torque, yaw angular velocity, and lateral acceleration.

7. The data processing device for the handling stability test of the center area of the disc according to claim 6, characterized in that: The data splitting module is further used to identify the peaks and valleys in the first parameter curve graph, and split the first parameter curve graph into an increasing curve graph and a decreasing curve graph according to the valleys to peaks and peaks to valleys.

8. The data processing device for the handling stability test of the center area of the disc according to claim 6, characterized in that: The data analysis module is further used to obtain the average data curve graph of the increasing interval and the average data curve graph of the decreasing interval corresponding to the influencing factor parameters that affect the stability-related parameters based on the increasing curve graph and the decreasing curve graph, and further obtain the corresponding average data hysteresis loop.

9. The data processing device for the handling stability test of the center area of the disc according to claim 6, characterized in that: The data splitting module is further used to identify the peaks and valleys in the first parameter curve graph, and split to obtain a plurality of peak-to-valley curve segments and valley-to-peak curve segments; The data splitting module is further used to integrate the peak-to-valley curve segments obtained according to the first parameter curve graph to obtain the increasing curve graph; The data splitting module is further used to integrate the valley-to-peak curve segments obtained according to the first parameter curve graph to obtain the decreasing curve graph.

10. The data processing device for the handling stability test of the disc center area as described in claim 6, characterized in that: the data analysis module is further configured to set an analysis minimum unit based on the types of the stability-related parameters; the data analysis module is further configured to obtain the positions of the analysis parameters corresponding to the increasing curve graph and the decreasing curve graph based on the analysis minimum unit; the data analysis module is further configured to obtain the average values of the influence factor parameters corresponding to different test points based on the positions of the respective analysis parameters, and further obtain the average data curve graph of the increasing interval and the average data curve graph of the decreasing interval corresponding to the influence factor parameters; the data analysis module is further configured to perform linear fitting on the average data curve graph of the increasing interval and the average data curve graph of the decreasing interval to obtain the corresponding average data hysteresis loop.

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