Method and system for detecting steering performance of electro-tricycle

Abstract

The invention discloses an electro-tricycle steering performance detection method and system, and belongs to the technical field of steering test.The method comprises the steps that multiple test detection road surfaces for conducting steering performance detection on an electro-tricycle are obtained, and driving characteristic data of a user on the multiple test detection road surfaces are collected; performing driving characteristic change degree analysis on the plurality of driving characteristic data; according to the multiple driving characteristic change degrees and the driving mileage of the user on the test detection road surface, the steering detection times are configured, and a steering performance test is conducted according to the test detection road surface and the driving characteristic data; according to the driving mileage, the driving characteristic change degree, the steering precision and the steering response speed, a steering performance detection result is obtained through calculation. The technical problem that the testing result cannot accurately reflect the steering performance of the electro-tricycle on different road surfaces and under different driving conditions due to the insufficiency of insufficient steering performance testing and lack of diversified driving behavior data in the prior art is solved.

Description

Technical Field

[0001] The invention relates to the technical field of steering test, and in particular to a method and system for detecting the steering performance of an electric tricycle. Background Art

[0002] The steering performance of electric tricycles directly affects the vehicle's handling and driving safety, which is closely related to characteristic parameters such as driving speed, steering speed, and steering torque. Most of the existing electric tricycle steering performance detection methods rely on a single test standard and experimental conditions, often ignoring the impact of the actual driving environment and different road conditions on the steering performance. In addition, most of the current detection methods rely on static measurements of steering accuracy and response speed, lacking a detailed analysis of dynamic changes during driving, resulting in insufficient accuracy and adaptability of the test results.

[0003] Therefore, there is an urgent need for an electric tricycle steering performance detection method that can comprehensively consider different driving behaviors, road environment and multi-dimensional performance indicators to improve the reliability and practicality of the detection results. Summary of the invention

[0004] The present application provides a method and system for detecting the steering performance of an electric tricycle, aiming to solve the technical problems in the prior art of insufficient steering performance testing and lack of diversified driving behavior data, resulting in the test results being unable to accurately reflect the steering performance of the electric tricycle under different road surfaces and driving conditions.

[0005] In view of the above problems, the present application provides a method and system for detecting the steering performance of an electric tricycle.

[0006] The first aspect disclosed in the present application provides a method for detecting the steering performance of an electric tricycle, the method comprising obtaining a plurality of test test roads for detecting the steering performance of the electric tricycle, collecting driving characteristic data of a user on the plurality of test test roads, wherein each driving characteristic data comprises a driving speed, a steering speed and a steering torque; performing driving characteristic variation degree analysis on the plurality of driving characteristic data to obtain a plurality of driving characteristic variation degrees; configuring a plurality of steering detection times according to the plurality of driving characteristic variation degrees and the driving mileage of the user on the plurality of test test roads, performing steering performance test tests according to the plurality of test test roads and the plurality of driving characteristic data to obtain a plurality of steering precisions and a plurality of steering response speeds; and calculating and obtaining the steering performance detection result of the electric tricycle according to the plurality of driving mileages, the plurality of driving characteristic variation degrees, the plurality of steering precisions and the plurality of steering response speeds.

[0007] Another aspect disclosed in the present application provides a steering performance detection system for an electric tricycle, the system comprising a feature data acquisition module for acquiring a plurality of test test roads for performing steering performance detection on an electric tricycle, and collecting driving feature data of a user on the plurality of test test roads, wherein each driving feature data comprises a driving speed, a steering speed and a steering torque; a variation degree acquisition module for performing driving feature variation degree analysis on a plurality of driving feature data, and obtaining a plurality of driving feature variation degrees; a performance test module for configuring a plurality of steering detection times according to a plurality of driving feature variation degrees and a driving mileage of the user on the plurality of test test roads, performing steering performance test tests according to the plurality of test test roads and a plurality of driving feature data, and obtaining a plurality of steering precisions and a plurality of steering response speeds; and a performance test result acquisition module for calculating and obtaining a steering performance detection result of the electric tricycle according to a plurality of driving mileages, a plurality of driving feature variation degrees, a plurality of steering precisions and a plurality of steering response speeds.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages: The technical solution of configuring the number of steering tests by combining multiple test road surfaces, multiple driving characteristic changes and multiple driving mileages solves the problem of insufficient steering performance testing and lack of diversified driving behavior data in the prior art, which results in the test results being unable to accurately reflect the steering performance of electric tricycles under different road surfaces and driving conditions. This solution ensures a comprehensive evaluation of steering performance by optimizing the configuration of the number of tests, and can obtain more accurate steering accuracy and response speed under variable road surfaces and driving conditions, ultimately achieving the technical effect of improving the adaptability and stability of the steering system.

[0009] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 A flow chart of a method for detecting the steering performance of an electric tricycle is provided for an embodiment of the present application.

[0011] Figure 2 A structural schematic diagram of a steering performance detection system for an electric tricycle is provided for an embodiment of the present application.

[0012] Explanation of the reference numerals: characteristic data acquisition module 11 , degree of change acquisition module 12 , performance test module 13 , performance test result acquisition module 14 . DETAILED DESCRIPTION

[0013] The overall idea of ​​the technical solution provided by this application is as follows: The embodiment of the present application provides a method and system for detecting the steering performance of an electric tricycle. By combining a variety of test test road surfaces, driving characteristic variability, and driving mileage, the number of steering performance tests is optimized. Specifically, the number of steering tests is reasonably allocated according to the driving characteristic variability and driving mileage of each test road surface, thereby ensuring that the test results under different driving conditions are more representative and accurate. Through this configuration, the steering accuracy and response speed of the electric tricycle under various road conditions can be comprehensively evaluated.

[0014] After introducing the basic principles of the present application, various non-limiting implementation methods of the present application will be specifically described below in conjunction with the drawings in the specification.

[0015] Embodiment 1, as Figure 1 As shown, the embodiment of the present application provides a method for detecting the steering performance of an electric tricycle, the method comprising: Step S100: Acquire a plurality of test test roads for testing the steering performance of the electric tricycle, and collect driving characteristic data of the user on the plurality of test test roads, wherein each driving characteristic data includes a driving speed, a steering speed and a steering torque.

[0016] Specifically, the test road surface refers to multiple different types of road environments designed for steering performance testing. These road environments simulate different road conditions, such as flat roads, bumpy roads, or roads with a certain slope. Different road environments can affect steering performance, so multiple road surfaces are required for comprehensive testing. Driving characteristic data refers to driving data recorded during the steering performance test, mainly including driving speed, steering speed and steering torque. It reflects the driver's driving behavior and operating methods in a specific environment, and is key data for evaluating steering performance. Steering torque refers to the torque applied by the driver to the steering system of the electric tricycle. The steering torque is related to the driver's control force and the feedback force of the steering system, and affects the vehicle's control feel and stability.

[0017] First, design and select multiple representative test roads that cover different driving scenarios. Then, on each test road, let the user drive the electric tricycle and collect driving characteristic data in real time, including driving speed, steering speed, and steering torque. These are obtained through sensors installed on the vehicle. Finally, integrate the collected data into the user's driving characteristic data set. These data sets reflect the performance of the electric tricycle steering system under different road surfaces and different driving conditions.

[0018] By testing on different test roads and collecting detailed driving characteristic data, we can fully understand the steering performance of electric tricycles under various actual road conditions. It can effectively reveal the response and accuracy of the electric tricycle steering system under different driving conditions, thus providing data support for subsequent steering performance optimization.

[0019] Step S200: performing driving characteristic variation degree analysis on a plurality of driving characteristic data to obtain a plurality of driving characteristic variation degrees.

[0020] Specifically, the driving characteristic variation is used to quantify the variation of driving characteristic data, describing the degree of deviation of the driver's driving behavior on a certain test road from the average driving behavior. The greater the variation, the greater the fluctuation of driving characteristics; the smaller the variation, the more stable the driving behavior.

[0021] First, the driving characteristic data are grouped according to the test road surface. For example, for flat roads, bumpy roads, sloped roads, etc., driving speed sets, steering speed sets, and steering torque sets are sorted out respectively. Then, for a specific test road surface, such as a flat road surface, multiple groups of driving speed data are randomly selected, and the deviation ratio between each group of data and the average driving speed of the road surface is calculated to obtain the speed characteristic variation. Similarly, for the steering speed and the average steering speed, the steering characteristic variation is calculated. According to the steering torque and the average steering torque, the torque characteristic variation is calculated. Finally, the speed characteristic variation, steering characteristic variation, and torque characteristic variation of each test road surface are weighted averaged to obtain the comprehensive driving characteristic variation of the test road surface.

[0022] By analyzing the variation of multiple driving characteristic data, the changes in the driver's driving behavior on different test roads can be quantified. Variation analysis can reveal the stability and regularity of driving behavior.

[0023] Step S300: According to a plurality of driving characteristic variation degrees and the user's driving mileage on a plurality of test roads, a plurality of steering detection times are configured, and a steering performance test is performed according to the plurality of test roads and a plurality of driving characteristic data to obtain a plurality of steering accuracies and a plurality of steering response speeds.

[0024] Specifically, the driving characteristic variation degree is a data indicator used to measure the degree of fluctuation of driving behavior, such as changes in driving speed, steering speed and steering torque. The greater the variation degree, the greater the change in the driver's driving behavior, and the smaller the variation degree, the more stable the driving behavior. The number of steering tests refers to the number of steering performance tests conducted on various test roads based on the configuration of driving characteristic variation degree and driving mileage. Steering accuracy refers to the accuracy of the steering system of the electric tricycle, usually expressed as the deviation of the steering angle. High steering accuracy means that the vehicle can accurately respond to the driver's steering operation. The steering response speed refers to the speed at which the steering system of the electric tricycle responds to the driver's steering operation, usually measured in the time of the steering angle change, indicating the speed of the vehicle's steering operation.

[0025] First, based on the driving characteristic data on multiple test roads, the driving characteristic variability of each road surface is calculated. The driving characteristic variability includes the degree of fluctuation of driving speed, steering speed and steering torque. For example, on a flat road, the driving speed variability is small, and the steering accuracy and response speed are relatively stable; on a bumpy road, the variability is large, resulting in a delayed or inaccurate response of the steering system. After analyzing the driving characteristic variability, the number of steering tests is configured based on the driving mileage of each test road surface. Roads with longer driving mileage require more tests to ensure more accurate and reliable steering performance data. In other words, a long driving test provides more opportunities for steering operations, which helps to more accurately evaluate the performance of the steering system on that road surface.

[0026] The number of steering tests is configured according to the driving characteristics variability and driving mileage of each road surface. For roads with large variability, more tests are required to fully evaluate the stability and responsiveness of the steering system. For roads with small variability and relatively stable driving behavior, the number of tests can be relatively reduced. The configured number of steering tests ensures comprehensive testing under different road conditions. Steering performance tests are carried out on each road surface to obtain multiple steering accuracy and steering response speed data. After each test, the steering accuracy and steering response speed are recorded and statistically analyzed. Steering accuracy can be calculated by measuring the difference between the actual steering angle of the vehicle and the target steering angle, and the steering response speed can be obtained by measuring the time it takes the vehicle to complete the steering operation. Specifically, on-board sensors (such as steering angle sensors, accelerometers, etc.) are used to collect steering accuracy and response speed data in real time.

[0027] By properly configuring the number of steering tests according to the driving characteristics and driving mileage, the accuracy and reliability of the steering performance test can be improved. On roads with large variations, increasing the number of tests can ensure that more steering accuracy and response speed fluctuations are captured, thereby optimizing the steering system design of the electric tricycle.

[0028] Step S400: Calculate and obtain the steering performance test result of the electric tricycle according to multiple driving mileages, multiple driving characteristic change degrees, multiple steering accuracies and multiple steering response speeds.

[0029] Specifically, the steering performance test result is a comprehensive performance score calculated based on multiple test road surfaces and driving characteristics data, reflecting the overall performance of the electric tricycle steering system under different driving conditions. The result includes steering accuracy and response speed, and is derived in combination with multiple influencing factors.

[0030] Collect driving mileage, driving characteristics variation, steering accuracy and steering response speed data on multiple test roads. Standardize different test data on each road surface to ensure that data on different roads can be directly compared. Each test data can be normalized (such as dividing each data by the maximum value) to unify the unit and magnitude of each data. Based on the collected multiple steering accuracy and steering response speed data, combined with multiple driving characteristics variation and driving mileage data, use weighted average and other methods to calculate the comprehensive steering performance test results. The scoring formula can comprehensively consider the effects of steering accuracy, response speed, driving mileage and variation to ensure that the steering performance score obtained can fully reflect the actual performance under various driving conditions.

[0031] By comprehensively calculating the driving mileage, driving characteristics variation, steering accuracy and steering response speed on multiple test roads, the steering system performance of the electric tricycle can be fully evaluated. This method can accurately reflect the performance of the vehicle under different road conditions, thus providing a reliable basis for the optimization of the steering system.

[0032] Furthermore, a variety of test test roads for testing the steering performance of electric tricycles are obtained, and driving characteristic data of users on the various test test roads are collected, including: obtaining a variety of test test roads for testing the steering performance of electric tricycles; based on the recorded data of users driving electric tricycles, collecting the driving speed, steering speed and steering torque of users on the various test test roads to obtain multiple driving speed sets, multiple steering speed sets and multiple steering torque sets; calculating the means of the multiple driving speed sets, multiple steering speed sets and multiple steering torque sets to obtain the average driving speed, average steering speed and average steering torque of the user on the various test test roads, and integrating them into multiple driving characteristic data.

[0033] Specifically, the test road surface is a different road environment used to test the steering performance of the electric tricycle, simulating different road conditions. The driving characteristic data includes three main elements: driving speed, steering speed and steering torque. Driving speed: vehicle speed, reflecting the driving speed of the electric tricycle. Steering speed: the speed at which the steering system rotates when the electric tricycle is steering. Steering torque: the torque applied by the driver to the steering system, reflecting the strength of the steering operation.

[0034] First, choose a variety of different road surfaces for testing. These roads can include flat urban roads, bumpy rural roads, and sloped mountain roads. Each road surface represents a different driving scenario encountered by the electric tricycle. For example, flat roads represent daily urban traffic conditions, bumpy roads simulate poor road conditions, and ramp tests involve steering performance when going uphill or downhill.

[0035] On various selected test roads, users drive electric tricycles and collect three main driving characteristic data through on-board sensors (such as speed sensors, steering angle sensors and torque sensors): driving speed; steering speed; steering torque. The driving data on each road is recorded in real time through sensors to form multiple data sets.

[0036] For each test road surface, the average of multiple driving speeds, steering speeds and steering torques on the road surface is first calculated. These averages reflect the average driving behavior of the user on this specific road surface. For example: assuming that the driving speeds on a flat road are 30km / h, 35km / h and 40km / h respectively, the average is 35km / h; the steering speeds on a bumpy road are 60 degrees, 50 degrees and 55 degrees per second respectively, the average is 55 degrees / second. The average values ​​of driving speeds, steering speeds and steering torques on each road surface are calculated and integrated into driving characteristic data. These data sets provide the basis for subsequent steering performance evaluation.

[0037] Through this step, the typical driving characteristics of users on different test roads can be obtained. It not only helps to quantify the driver's behavior under various road conditions, but also provides a scientific basis for the steering performance test of electric tricycles. By calculating the mean of each driving characteristic, accidental factors can be effectively eliminated and the representativeness of the test results can be improved.

[0038] Furthermore, a driving characteristic variation degree analysis is performed on multiple driving characteristic data to obtain multiple driving characteristic variation degrees, including: calculating a first speed characteristic variation degree of the first test test road surface based on a first driving speed set of the first test test road surface in the multiple driving speed sets and a first average driving speed; continuing to calculate a first steering characteristic variation degree and a first torque characteristic variation degree of the first test test road surface based on a first steering speed set and a first steering torque set; calculating a first driving characteristic variation degree of the first test test road surface based on the first speed characteristic variation degree, the first steering characteristic variation degree and the first torque characteristic variation degree; continuing to calculate multiple driving characteristic variation degrees based on multiple driving speed sets, multiple steering speed sets and multiple steering torque sets of other multiple test test road surfaces, in combination with multiple average driving speeds, multiple average steering speeds and multiple average steering torques.

[0039] Specifically, the speed characteristic variation is used to indicate the degree of deviation between the driving speed set and its average value, which is usually calculated as the difference between each driving speed and the average value, and the proportion of the change is obtained. The steering characteristic variation indicates the degree of deviation between the steering speed and its average value, which is usually quantified by calculating the fluctuation amplitude of the steering speed. The torque characteristic variation indicates the degree of deviation between the steering torque and its average value, which is usually used to evaluate the stability of the steering operation and the torque change applied by the driver.

[0040] First, the speed characteristic variation is calculated based on the set of driving speeds of the first test road (e.g., 30km / h, 35km / h, 40km / h) and the average driving speed of the road (e.g., 35km / h). The variation is calculated by quantifying the deviation between each collected driving speed and the average driving speed. Specifically, if a test speed is 40km / h, then its variation is: =14.3%; Continue to analyze the degree of change of the steering speed set and steering torque set of the first test road surface. For the steering speed, first calculate the average steering speed of the road surface, and then calculate the deviation ratio between each collected steering speed and the average steering speed. Similarly, calculate the degree of change of the steering torque and obtain the deviation ratio of each data point. Comprehensively calculate the speed characteristic change degree, steering characteristic change degree and torque characteristic change degree of the first test road surface, and finally obtain the overall driving characteristic change degree of the road surface.

[0041] Next, the variation of multiple driving speed sets, multiple steering speed sets, and multiple steering torque sets of other test test roads is calculated. For each road surface, the average driving speed, average steering speed, and average steering torque of the road surface are first calculated, and then the variation of speed, steering, and torque characteristics are calculated for each data set.

[0042] By analyzing the variation of multiple driving characteristic data, the steering performance of electric tricycles on different test roads can be effectively quantified. It can help identify the fluctuation of driving characteristics under different road conditions. It can identify the performance differences of the steering system of electric tricycles under different road conditions, and carry out targeted optimization design to improve the adaptability and safety of electric tricycles in complex driving environments.

[0043] Furthermore, based on the first driving speed set of the first test test road surface in the multiple driving speed sets and the first average driving speed, a first speed characteristic variation degree of the first test test road surface is calculated, including: randomly selecting multiple first driving speeds in the first driving speed set; calculating the driving speed deviation ratio between the average of the multiple randomly selected first driving speeds and the first average driving speed as the speed characteristic variation degree; and continuing to randomly select multiple groups of first driving speeds, calculating multiple speed characteristic variation degrees, and calculating the average as the first speed characteristic variation degree.

[0044] Specifically, the speed characteristic variation is an indicator used to quantify the fluctuation of data in the driving speed set, reflecting the degree of variation of driving speed under different test conditions. The greater the variation, the greater the fluctuation of driving speed, and vice versa, the driving speed is relatively stable. The driving speed deviation ratio is the degree of deviation between a set of driving speed data and the average driving speed, usually expressed by calculating the ratio of the difference value to the average value. The higher the deviation ratio, the greater the deviation of the data from the average value.

[0045] First, randomly select multiple driving speed data from the driving speed set of the first test road surface. For example, if the driving speed set is (30km / h, 35km / h, 40km / h, 45km / h, 50km / h), you can randomly select multiple speed values ​​such as 35km / h, 40km / h, and 45km / h. Through random selection, the representativeness of the sample can be guaranteed and the influence of a single data point on the calculation of the degree of variation can be avoided. For each set of randomly selected driving speed data, calculate their mean and compare them with the average driving speed of the road surface to obtain the deviation ratio. The mean of the deviation ratios of all randomly selected and calculated speed feature variation degrees is calculated. For example, if the degree of variation of the first group is 14.3%, the second group is 19.5%, and the third group is 12.0%, then the average speed feature variation degree is: = ; Through this step, the speed characteristic variation degree on the first test road surface can be quantified by randomly selecting multiple sets of driving speed data. This avoids the reliance on a single data point and provides a more comprehensive and reliable speed characteristic variation degree. By calculating the mean of multiple variation degrees, the speed stability of the electric tricycle on the test road surface can be better evaluated. This improves the adaptability and safety of the tricycle under different road conditions.

[0046] Furthermore, according to multiple driving characteristic variation degrees and the driving mileage of the user on multiple test road surfaces, multiple steering detection times are configured, and steering performance test tests are performed according to the multiple test road surfaces and multiple driving characteristic data to obtain multiple steering precisions and multiple steering response speeds, including: obtaining a preset test number for steering performance test of the electric tricycle; obtaining a plurality of driving mileages of the user on multiple test road surfaces according to the recorded data of the user driving the electric tricycle; calculating and configuring multiple steering detection times according to the multiple driving characteristic variation degrees and the multiple driving mileages, in combination with the preset test times; performing steering performance test tests of the electric tricycle according to the multiple steering detection times, using the multiple test road surfaces and multiple driving characteristic data, to obtain multiple test steering precision sets and multiple test steering response speed sets; respectively calculating the average of the multiple test steering precision sets and the multiple test steering response speed sets to obtain multiple steering precisions and multiple steering response speeds.

[0047] Specifically, the preset number of tests is the standard number of tests set before the steering performance test begins to ensure the accuracy and comprehensiveness of the test.

[0048] First, set the preset number of tests to ensure that the steering performance test can be fully tested on different test surfaces. The preset number of tests is usually determined based on the complexity of the vehicle's steering system, the type of test surface, and the accuracy of the required data. According to the user's driving record data on different test surfaces, the user's driving mileage on each surface is obtained. These mileage data help determine the test time and driving conditions of each surface, thereby providing a basis for the subsequent configuration of the number of steering tests. According to the driving characteristic variability and driving mileage, combined with the preset number of tests, the number of steering tests on each surface is calculated. Generally speaking, the greater the driving characteristic variability (such as bumpy roads or roads with less stable driving behavior), the more steering tests are required. According to the configured number of steering tests, multiple test surfaces and multiple driving characteristic data are used to conduct steering performance tests. The test includes measuring the steering accuracy and steering response speed of each test. Data is collected through on-board sensors and the results of each test are recorded.

[0049] For all steering performance tests, the mean of the steering accuracy set and steering response speed set are calculated respectively. Mean calculation can help eliminate the influence of accidental factors and obtain more stable and reliable performance evaluation results. Finally, the steering accuracy and steering response speed of each test test road surface are obtained.

[0050] By combining the driving characteristics variability and driving mileage to configure the number of steering tests, the accuracy and comprehensiveness of the test can be ensured. For roads with large variability, increasing the number of tests can better evaluate the stability of steering accuracy and response speed, especially in unstable road environments, and can capture the performance differences of the steering system under different conditions. It can provide an in-depth understanding of the steering performance of electric tricycles under different road conditions, thereby optimizing the steering system and improving the safety and controllability of the vehicle in actual use.

[0051] Furthermore, according to the multiple driving characteristic change degrees and the multiple driving mileages, combined with the preset test times, multiple turn detection times are calculated and configured, as shown in the following formula: ; in, is the number of turning detections on the i-th test road surface, To preset the number of tests, is the driving characteristic change degree corresponding to the road surface detected in the i-th test, The driving mileage corresponding to the i-th test detection road surface.

[0052] Specifically, a preset number of steering performance tests is set for each test road surface. The preset number of tests can be set according to the test requirements, such as 5 tests on a flat road surface and more tests on a complex bumpy road surface, such as 10 times. Each test test road surface is analyzed to calculate the degree of change of the driving characteristics of the road surface. The greater the degree of change, the more significant the change in the user's driving behavior on the road surface. The driving mileage of the user on each test test road surface is obtained. Road surfaces with longer driving mileage indicate that the user has performed more driving operations on the road surface, so more steering detection times are required. The number of steering detection times for each road surface is calculated based on the degree of change of driving characteristics and driving mileage, combined with the preset number of tests. and are the sum of all road surface variations and mileages respectively. Through this formula, combined with the variation and driving mileage, the specific number of tests for each road surface can be configured.

[0053] Based on the calculated number of steering detections, multiple steering performance tests are performed on each road surface. Each test includes recording the steering accuracy and steering response speed. Steering accuracy can be calculated by the difference between the actual steering angle and the target steering angle, and steering response speed is determined by measuring the time required for the steering operation to complete.

[0054] By properly configuring the number of steering tests according to the driving characteristics and driving mileage, it is possible to ensure that the test data for each test road surface is comprehensive and representative. This configuration method can provide a scientific basis for the optimization of the steering system of electric tricycles, ensuring that the vehicle has excellent steering performance and driving experience under various road conditions.

[0055] Furthermore, according to a plurality of driving mileages, a plurality of driving characteristic variation degrees, a plurality of steering accuracies and a plurality of steering response speeds, a steering performance test result of the electric tricycle is calculated and obtained as follows: ; Among them, FDC is the steering performance score in the steering performance test results. and are the accuracy weight and speed weight respectively, is the steering accuracy obtained by the test on the road surface of the ith test, Steering response speed obtained from the ith test road test.

[0056] Specifically, the user's driving characteristic data, including driving speed, steering speed, steering torque and other data, are collected to calculate the driving characteristic variation. Each road surface has its corresponding driving characteristic variation and driving mileage. For each test test road surface, the steering accuracy and steering response speed are calculated. The steering accuracy can be obtained by calculating the error between the actual steering angle and the target steering angle; the steering response speed measures the time required from the driver starting the steering operation to the vehicle completing the steering. According to the road conditions, driving characteristic variation and driving mileage, the weights of steering accuracy and response speed are set respectively. For example, on a road surface with high steering accuracy requirements, the weight of steering accuracy is larger; on a road surface with a faster response speed, the weight of response speed is larger.

[0057] The higher the score, the better the steering system performs on the road and the better it can adapt to the user's driving habits. The greater the steering accuracy and response speed, the higher the score. The greater the driving characteristics change, the higher the steering accuracy and response speed required to improve the score.

[0058] This steering performance scoring method can comprehensively consider multiple factors such as driving characteristics variability, driving mileage, steering accuracy and response speed to obtain a steering performance score for each road condition. The scoring criteria for steering accuracy and response speed are related to the diversity of driving behavior and the complexity of driving roads, ensuring that the driving habits and road conditions of different users are fully considered.

[0059] In summary, the electric tricycle steering performance detection method provided in the embodiment of the present application has the following technical effects: 1. By combining a variety of test roads and driving characteristics data, the number of steering performance tests is scientifically configured to ensure comprehensiveness and accuracy under different driving conditions. By collecting and analyzing data such as driving speed, steering speed and steering torque, the steering performance of the electric tricycle in actual use can be truly reflected. This method can not only adapt to different road conditions, but also provide reliable data support for the optimization of the steering system of the electric tricycle, and improve the stability and safety of the steering system.

[0060] 2. By analyzing the variability of multiple driving characteristic data, the driver's behavior fluctuations on different road surfaces are quantified, revealing the impact of driving characteristic variability on steering performance. By analyzing the fluctuations of driving speed, steering speed, and steering torque on each test road surface, the stability of the steering system can be evaluated more accurately. This method helps to identify the advantages and disadvantages of the steering system in different driving environments, and provides a basis for adjusting and optimizing the steering control system, thereby improving the overall performance of the electric tricycle.

[0061] 3. By combining the driving characteristic variation degree with the driving mileage, the number of steering tests can be flexibly configured to ensure the adequacy and accuracy of the steering performance test on different test roads. By calculating the relationship between driving mileage and variation degree, the configuration of the number of tests is optimized, which effectively avoids resource waste and improves the scientificity and reliability of the test results. This method can more comprehensively evaluate the performance of the steering system under various road conditions and provide accurate data support for further optimizing the steering system of electric tricycles.

[0062] Embodiment 2 is based on the same inventive concept as the method for detecting the steering performance of an electric tricycle in the above embodiment. Figure 2 As shown, the embodiment of the present application provides a steering performance detection system for an electric tricycle, the system comprising: The characteristic data acquisition module 11 is used to obtain a variety of test test roads for steering performance testing of the electric tricycle, and collect the user's driving characteristic data on the various test test roads, wherein each driving characteristic data includes a driving speed, a steering speed and a steering torque; the variation degree acquisition module 12 is used to analyze the driving characteristic variation degree of the multiple driving characteristic data to obtain a plurality of driving characteristic variation degrees; the performance test module 13 is used to configure a plurality of steering test times according to the plurality of driving characteristic variation degrees and the driving mileage of the user on the various test test roads, and perform steering performance test tests according to the various test test roads and the plurality of driving characteristic data to obtain a plurality of steering precisions and a plurality of steering response speeds; the performance test result acquisition module 14 is used to calculate and obtain the steering performance test result of the electric tricycle according to a plurality of driving mileages, a plurality of driving characteristic variation degrees, a plurality of steering precisions and a plurality of steering response speeds.

[0063] Furthermore, the characteristic data acquisition module 11 is also used to perform the following steps: obtaining a variety of test test roads for testing the steering performance of the electric tricycle; based on the recorded data of the user driving the electric tricycle, collecting the driving speed, steering speed and steering torque of the user on the various test test roads to obtain multiple driving speed sets, multiple steering speed sets and multiple steering torque sets; calculating the mean of the multiple driving speed sets, multiple steering speed sets and multiple steering torque sets to obtain the average driving speed, average steering speed and average steering torque of the user on the various test test roads, and integrating them into multiple driving characteristic data.

[0064] Furthermore, the variation degree obtaining module 12 is also used to perform the following steps: calculating a first speed characteristic variation degree of the first test test road surface according to a first driving speed set of the first test test road surface in the multiple driving speed sets and a first average driving speed; continuing to calculate a first steering characteristic variation degree and a first torque characteristic variation degree of the first test test road surface according to a first steering speed set and a first steering torque set; calculating a first driving characteristic variation degree of the first test test road surface according to the first speed characteristic variation degree, the first steering characteristic variation degree and the first torque characteristic variation degree; continuing to calculate multiple driving characteristic variation degrees according to multiple driving speed sets, multiple steering speed sets and multiple steering torque sets of other multiple test test road surfaces, in combination with multiple average driving speeds, multiple average steering speeds and multiple average steering torques.

[0065] Furthermore, the variation degree obtaining module 12 is also used to perform the following steps: randomly selecting multiple first driving speeds in the first driving speed set; calculating the driving speed deviation ratio between the mean of the multiple randomly selected first driving speeds and the first average driving speed as the speed characteristic variation degree; continuing to randomly select multiple groups of first driving speeds, calculating multiple speed characteristic variation degrees, and calculating the mean as the first speed characteristic variation degree.

[0066] Furthermore, the performance test module 13 is also used to perform the following steps: obtain a preset number of tests for steering performance testing of the electric tricycle; obtain multiple driving mileages of the user on multiple test test roads based on the recorded data of the user driving the electric tricycle; calculate and configure multiple steering detection times based on the multiple driving characteristic change degrees and multiple driving mileages, combined with the preset number of tests; perform steering performance test tests on the electric tricycle according to the multiple steering detection times, using the multiple test test roads and multiple driving characteristic data, to obtain multiple test steering accuracy sets and multiple test steering response speed sets; calculate the average of the multiple test steering accuracy sets and the multiple test steering response speed sets, respectively, to obtain multiple steering accuracies and multiple steering response speeds.

[0067] Furthermore, the performance test module 13 is also used to perform the following steps: ; in, is the number of turning detections on the i-th test road surface, To preset the number of tests, is the driving characteristic change degree corresponding to the road surface detected in the i-th test, The driving mileage corresponding to the i-th test detection road surface.

[0068] Furthermore, the performance test module 13 is also used to perform the following steps: ; Among them, FDC is the steering performance score in the steering performance test results. and are the accuracy weight and speed weight respectively, is the steering accuracy obtained by the test on the road surface of the ith test, Steering response speed obtained from the ith test road test.

[0069] Any step of the method described above can be stored as a computer instruction or program in an unlimited computer memory, and can be called and recognized by an unlimited computer processor to implement any method in the embodiments of the present application, without any unnecessary restrictions.

[0070] Furthermore, the first or second mentioned above not only represents an order relationship, but also represents a specific concept, and / or refers to the selection of multiple elements individually or in whole. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application intends to include these modifications and variations.

Claims

1. A method for detecting the steering performance of an electric tricycle, characterized in that: The method comprises: Acquire multiple test test roads for testing the steering performance of the electric tricycle, and collect driving characteristic data of the user on the multiple test test roads, wherein each driving characteristic data includes a driving speed, a steering speed, and a steering torque; Performing driving characteristic change degree analysis on a plurality of driving characteristic data to obtain a plurality of driving characteristic change degrees; According to a plurality of driving characteristic variation degrees and the driving mileage of the user on a plurality of test test roads, a plurality of steering test times are configured, and a steering performance test is performed according to the plurality of test test roads and a plurality of driving characteristic data to obtain a plurality of steering accuracies and a plurality of steering response speeds; The steering performance detection result of the electric tricycle is obtained by calculation according to a plurality of driving mileages, a plurality of driving characteristic variation degrees, a plurality of steering accuracies and a plurality of steering response speeds.

2. The electric tricycle steering performance detection method according to claim 1, characterized in that: Acquire multiple test roads for testing the steering performance of the electric tricycle, and collect driving characteristic data of the user on the multiple test roads, including: Obtaining various test test roads for testing the steering performance of electric tricycles; According to the recorded data of the user driving the electric tricycle, the driving speed, steering speed and steering torque of the user on the multiple test detection roads are collected to obtain multiple driving speed sets, multiple steering speed sets and multiple steering torque sets; The averages of the multiple driving speed sets, the multiple steering speed sets and the multiple steering torque sets are calculated to obtain the average driving speed, the average steering speed and the average steering torque of the user on the multiple test detection roads, and are integrated into multiple driving characteristic data.

3. The electric tricycle steering performance detection method according to claim 2, characterized in that: The driving characteristic variation degree analysis is performed on the multiple driving characteristic data to obtain multiple driving characteristic variation degrees, including: calculating a first speed characteristic variation degree of the first test detection road surface according to a first driving speed set of the first test detection road surface in the plurality of driving speed sets and a first average driving speed; Continuing to calculate and obtain a first steering characteristic variation degree and a first torque characteristic variation degree of the first test detection road surface according to the first steering speed set and the first steering torque set; Calculating a first driving characteristic variation degree of the first test detection road surface according to the first speed characteristic variation degree, the first steering characteristic variation degree and the first torque characteristic variation degree; Continue to detect multiple driving speed sets, multiple steering speed sets and multiple steering torque sets of the road surface based on multiple other tests, combine multiple average driving speeds, multiple average steering speeds and multiple average steering torques, and calculate multiple driving characteristic change degrees.

4. The electric tricycle steering performance detection method according to claim 3, characterized in that: Calculating and obtaining a first speed characteristic variation degree of the first test detection road surface according to a first driving speed set of the first test detection road surface in the plurality of driving speed sets and a first average driving speed includes: randomly selecting a plurality of first driving speeds within the first driving speed set; Calculating a driving speed deviation ratio between an average of a plurality of randomly selected first driving speeds and the first average driving speed as a speed characteristic variation degree; Continue to randomly select multiple groups of first driving speeds, calculate multiple speed feature variation degrees, and calculate the average value as the first speed feature variation degree.

5. The electric tricycle steering performance detection method according to claim 1, characterized in that: According to a plurality of driving characteristic variation degrees and the driving mileage of the user on a plurality of test detection roads, a plurality of steering detection times are configured, and a steering performance test is performed according to the plurality of test detection roads and a plurality of driving characteristic data to obtain a plurality of steering accuracies and a plurality of steering response speeds, including: Obtain the preset number of tests for the steering performance test of the electric tricycle; According to the recorded data of the user driving the electric tricycle, a plurality of driving mileages of the user on a plurality of test detection roads are obtained; According to the multiple driving characteristic change degrees and the multiple driving mileages, combined with the preset test times, calculating and configuring multiple turning detection times; According to the plurality of steering detection times, the plurality of test detection road surfaces and the plurality of driving characteristic data are used to perform a steering performance test on the electric tricycle, to obtain a plurality of test steering accuracy sets and a plurality of test steering response speed sets; The averages of the plurality of test steering accuracy sets and the plurality of test steering response speed sets are calculated respectively to obtain a plurality of steering accuracies and a plurality of steering response speeds.

6. The method for detecting the steering performance of an electric tricycle according to claim 5, characterized in that: According to the multiple driving characteristic change degrees and the multiple driving mileages, combined with the preset test times, multiple turn detection times are calculated and configured, as shown in the following formula: ; in, is the number of turning detections on the i-th test road surface, To preset the number of tests, is the driving characteristic change degree corresponding to the road surface detected in the i-th test, The driving mileage corresponding to the i-th test detection road surface.

7. The method for detecting the steering performance of an electric tricycle according to claim 6, characterized in that: According to a plurality of driving mileages, a plurality of driving characteristic variation degrees, a plurality of steering accuracies and a plurality of steering response speeds, a steering performance test result of the electric tricycle is calculated and obtained as follows: ; Among them, FDC is the steering performance score in the steering performance test results. and are the accuracy weight and speed weight respectively, is the steering accuracy obtained by the test on the road surface of the ith test, Steering response speed obtained from the ith test road test.

8. A steering performance detection system for an electric tricycle, characterized in that: Used to execute the electric tricycle steering performance detection method according to any one of claims 1 to 7, the system comprises: A characteristic data acquisition module is used to obtain a variety of test test roads for testing the steering performance of the electric tricycle, and collect the driving characteristic data of the user on the various test test roads, wherein each driving characteristic data includes a driving speed, a steering speed and a steering torque; A variation degree obtaining module, used for analyzing the driving characteristic variation degree of a plurality of driving characteristic data to obtain a plurality of driving characteristic variation degrees; A performance test module, configured to configure a plurality of steering test times according to a plurality of driving characteristic change degrees and the driving mileage of the user on a plurality of test test roads, and to perform a steering performance test according to the plurality of test test roads and a plurality of driving characteristic data, to obtain a plurality of steering accuracies and a plurality of steering response speeds; The performance test result acquisition module is used to calculate and obtain the steering performance test result of the electric tricycle according to multiple driving mileages, multiple driving characteristic change degrees, multiple steering accuracies and multiple steering response speeds.

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