Vehicle climbing performance test method and system based on dynamic scenarios

Abstract

The present invention is applicable to the field of vehicle performance testing, and provides a vehicle climbing performance test method and system based on dynamic scenarios. The system includes: a vehicle model identification and classification module, a test rule definition and sound capture module, a data acquisition and binding module, a performance analysis and sound feature recognition module, and a configuration comparison and evaluation report generation module. The method takes into account the situation where four wheels cannot touch the ground under special circumstances, and specially designs a three-wheel climbing performance test. This flexibility enables the vehicle to be evaluated under more complex and realistic environmental conditions, ensuring the applicability and extensiveness of the test results. In addition, detailed tests are carried out on the performance of different models under different touchdown combinations to help identify the adaptability and performance limits of each model in various dynamic scenarios.

Description

Technical Field

[0001] The present invention belongs to the field of vehicle performance testing, and in particular relates to a vehicle climbing performance testing method and system based on dynamic scenarios. Background Art

[0002] The vehicle climbing performance test is an important indicator for evaluating the vehicle's climbing ability under different slopes and conditions, and is designed to understand the performance of the vehicle's power system, traction, stability, etc. This test is usually conducted at a dedicated test site, with the slope set to different levels, such as 10%, 20%, 30%, etc., to simulate various road conditions in actual driving. During the test, researchers will conduct static and dynamic tests. The static test measures the maximum climbing angle of the vehicle when it is stationary on the ramp, while the dynamic test measures the acceleration time and speed change of the vehicle on the ramp through acceleration.

[0003] Key parameters that affect climbing performance include engine power, torque, vehicle weight, and tire grip. The greater the engine power and the stronger the low-speed torque, the better the climbing ability; at the same time, the weight of the vehicle and the friction between the tires and the ground will directly affect the traction. After completing the test, the researchers will analyze the collected data, including speed, acceleration time, and traction loss, to evaluate the vehicle's climbing performance. In addition, the test also focuses on safety to ensure that the vehicle remains stable during the climbing process and avoid risks such as skidding or loss of control. Through these tests, manufacturers can optimize vehicle design and improve its performance and safety in actual use.

[0004] Many test methods assume that the vehicle's four tires are always in contact with the ground during the climbing process. This assumption simplifies the test process, but in actual driving, especially in uneven or complex terrain (such as rugged mountain roads, soft sand, and muddy environments), it is difficult for the vehicle's four tires to always keep in contact with the ground. Therefore, it is impossible to fully evaluate the vehicle's performance in real scenarios. Summary of the invention

[0005] The purpose of the present invention is to provide a vehicle climbing performance testing method based on dynamic scenarios, aiming to solve the technical problems existing in the prior art identified in the background technology.

[0006] The present invention is implemented in this way: a vehicle climbing performance test method based on dynamic scenarios, the method comprising:

[0007] Identify the vehicle models to be tested and classify all models, including four-wheel drive, front-wheel drive and rear-wheel drive, and set dynamic scenarios with different combinations of ramps and road environments;

[0008] Define test rules and data recording rules for each type of vehicle, and capture the sound data generated by the vehicle when climbing the slope during each test;

[0009] Collect and record the performance data of each type of vehicle in different dynamic scenarios in batches, test the vehicle using each test rule, and bind the recorded sound data to the batch;

[0010] Analyze the performance of each type of vehicle under different dynamic scenarios and test rules, identify the sound features in the batch of sound data, evaluate the correlation between the sound features and vehicle performance indicators, and comprehensively analyze the vehicle climbing performance of different types of vehicles under different conditions by combining performance and correlation;

[0011] Compare test results under different drive modes and tire contact conditions, identify optimal configuration and performance, and generate evaluation reports.

[0012] As a further solution of the present invention, the method of identifying the vehicle model to be tested and classifying all vehicle models, including four-wheel drive, front-wheel drive and rear-wheel drive, and setting a number of dynamic scenes with different combinations of ramps and road environments, specifically includes:

[0013] Obtain the information of the vehicle model to be tested, and classify the vehicle models into three categories according to the driving mode: four-wheel drive 4WD, front-wheel drive FWD, and rear-wheel drive RWD;

[0014] Design different ramps according to the vehicle's climbing ability, including slope and length, and set several road conditions for each ramp;

[0015] The ramp is combined with the road environment to form several dynamic scenes.

[0016] As a further solution of the present invention, the test rules and data recording rules are defined for each type of vehicle, and the sound data generated by the vehicle when climbing the slope is captured during each test, specifically including:

[0017] Develop testing rules for each vehicle type, including:

[0018] Four-wheel drive:

[0019] Gradeability with all tires in contact with the ground;

[0020] The gradeability of any tire when it leaves the ground;

[0021] Front-wheel drive:

[0022] Gradeability with all tires in contact with the ground;

[0023] Gradeability when any front wheel leaves the ground;

[0024] The climbing ability when any rear wheel leaves the ground;

[0025] Rear-wheel drive:

[0026] Gradeability with all tires in contact with the ground;

[0027] The climbing ability when any rear wheel leaves the ground;

[0028] The climbing ability when any front wheel leaves the ground;

[0029] Record the hill climbing performance of different models under different contact combinations, including:

[0030] Four-wheel drive: power distribution, torque output of each tire, speed change at the start and apex of the slope;

[0031] Front-wheel drive: three ground contact combinations of vehicle speed, tire slip, engine status, power delivery and traction;

[0032] RWD: three ground contact combinations of vehicle speed, tire slip, engine status, power delivery and traction;

[0033] Capture all the sound data of the vehicle while climbing the slope.

[0034] As a further solution of the present invention, the method of collecting and recording the performance data of each type of vehicle in different dynamic scenes in batches, testing the vehicle using each test rule, and binding the recorded sound data with the batch specifically includes:

[0035] Each vehicle model is tested in different dynamic scenarios one by one, and the vehicle performance data is recorded in real time during the test;

[0036] Set the audio collection frequency to capture the sound of the vehicle in real time;

[0037] The performance data recorded in each test is associated with the corresponding sound data, and tag information is added to each batch of data.

[0038] As a further solution of the present invention, the performance of each type of vehicle under different dynamic scenarios and test rules is analyzed, and the sound features in the batch of sound data are identified, and the correlation between the sound features and the vehicle performance indicators is evaluated, and the vehicle climbing performance of different types of vehicles under different conditions is comprehensively analyzed in combination with the performance and the correlation, specifically including:

[0039] Integrate all collected performance and sound data, check and clean up outliers and noise in the data;

[0040] Calculate the vehicle performance indicators of each model in different dynamic scenarios according to the test rules, and conduct comparative analysis of the performance data;

[0041] Specific:

[0042] ;

[0043] ;

[0044] ;

[0045] in, It represents the ratio of the variance between different groups to the variance within the group. represents the between-group mean square, represents the sum of squares between groups, that is, the difference between the means of different groups and the overall mean, is the number of groups, represents the within-group mean square, represents the within-group sum of squares, that is, the differences between data points within a group, is the total number of sample points;

[0046] The captured sound data is processed to evaluate the correlation between each audio feature and the vehicle performance index, identify the audio features that affect the vehicle's climbing performance, and conduct quantitative analysis;

[0047] Specific:

[0048] ;

[0049] in, is the correlation coefficient, which indicates the strength of the linear relationship between two variables. is the number of sample points, that is, the number of recorded audio clips, is a specific audio feature, is the vehicle performance index, is the sum of the products of the audio features of all sample points and the vehicle performance indicators, and is the sum of audio features and vehicle performance indicators, and is the sum of the squares of the audio features and the vehicle performance index;

[0050] Comprehensively evaluate the performance data and sound characteristic analysis results;

[0051] Specific:

[0052] ;

[0053] in, is the dependent variable, indicating the climbing time, are independent variables, representing audio features and vehicle performance indicators, is the intercept, which represents the value of the dependent variable when all independent variables are zero. is the regression coefficient, which indicates the influence of the independent variable on the dependent variable. is the error term.

[0054] Another object of the present invention is to provide a vehicle climbing performance test system based on dynamic scenarios, the system comprising:

[0055] The vehicle type recognition and classification module is used to identify the vehicle type to be tested and classify all vehicle types, including four-wheel drive, front-wheel drive and rear-wheel drive, and set dynamic scenes with different combinations of ramps and road environments;

[0056] The test rule definition and sound capture module is used to define the test rules and data recording rules for each type of vehicle, and capture the sound data generated by the vehicle when climbing the slope during each test;

[0057] The data collection and binding module is used to collect and record the performance data of each type of vehicle in different dynamic scenarios in batches, using each test rule to test the vehicle, and bind the recorded sound data to the batch;

[0058] Performance analysis and sound feature recognition module, used to analyze the performance of each type of vehicle under different dynamic scenarios and test rules, identify the sound features in the batch of sound data, evaluate the correlation between the sound features and vehicle performance indicators, and comprehensively analyze the vehicle climbing performance of different types of vehicles under different conditions by combining performance and correlation;

[0059] The configuration comparison and evaluation report generation module is used to compare the test results under different driving modes and tire contact conditions, identify the optimal configuration and performance, and generate an evaluation report.

[0060] As a further solution of the present invention, the vehicle type identification and classification module includes:

[0061] The vehicle model information acquisition and classification unit is used to obtain the information of the vehicle model to be tested and classify the vehicle models into three categories according to the driving mode: four-wheel drive 4WD, front-wheel drive FWD, and rear-wheel drive RWD;

[0062] The ramp design and road environment setting unit is used to design different ramps according to the climbing ability of the vehicle, including the slope and slope length, and set a number of road environment for each ramp;

[0063] The dynamic scene combination unit is used to combine the ramp and the road environment to form a number of dynamic scenes.

[0064] As a further solution of the present invention, the test rule definition and sound capture module includes:

[0065] A test rule formulation unit, used to formulate test rules for each vehicle model;

[0066] Climbing performance recording unit, used to record the climbing performance of different models under different ground contact combinations;

[0067] The sound data capturing unit is used to capture all the sound data of the vehicle during the climbing process.

[0068] As a further solution of the present invention, the data collection and binding module includes:

[0069] Dynamic scenario test unit, used to test each vehicle model in different dynamic scenarios one by one, and record the vehicle performance data in real time during the test;

[0070] An audio collection setting unit is used to set the audio collection frequency and capture the sound emitted by the vehicle in real time;

[0071] The data association and labeling unit is used to associate the performance data recorded in each test with the corresponding sound data and add labeling information to each batch of data.

[0072] As a further solution of the present invention, the performance analysis and sound feature recognition module includes:

[0073] Data integration and cleaning unit, used to integrate all collected performance data and sound data, and check and clean up outliers and noise in the data;

[0074] Performance index calculation and comparative analysis unit, used to calculate the vehicle performance index of each vehicle model in different dynamic scenarios according to the test rules, and to conduct comparative analysis of the performance data;

[0075] The sound data processing and feature analysis unit is used to process the captured sound data, evaluate the correlation between each audio feature and the vehicle performance index, identify the audio features that affect the vehicle's climbing performance, and perform quantitative analysis;

[0076] The comprehensive evaluation unit is used to comprehensively evaluate the performance data and the sound characteristic analysis results.

[0077] The beneficial effects of the present invention are:

[0078] This method takes into account the situation where four wheels cannot touch the ground under special circumstances, and specially designs a three-wheel climbing performance test. This flexibility enables the vehicle to be evaluated under more complex and realistic environmental conditions, ensuring the applicability and extensiveness of the test results. In addition, the performance of different models (four-wheel drive, front-wheel drive, rear-wheel drive) under different contact combinations is carefully tested to help identify the adaptability and performance limits of each model in various dynamic scenarios.

[0079] The integrated audio recording system provides an acoustic feedback analysis perspective for vehicle performance. By capturing the sounds emitted by the vehicle during different climbing processes, it is possible to analyze the sound characteristics (such as tire sliding sound, power transmission sound, etc.), providing an additional dimension for vehicle performance evaluation. This multi-dimensional data integration helps to more fully understand the dynamic performance of the vehicle in motion. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] Figure 1 A flow chart of a vehicle climbing performance test method based on a dynamic scenario provided by an embodiment of the present invention;

[0081] Figure 2 A flowchart for identifying the vehicle model to be tested and classifying all vehicle models provided by an embodiment of the present invention;

[0082] Figure 3 A flowchart for defining test rules and data recording rules for each type of vehicle model provided in an embodiment of the present invention, and capturing the sound data generated by the vehicle when climbing a slope during each test;

[0083] Figure 4 A flowchart for collecting and recording the performance data of each type of vehicle in different dynamic scenarios in batches and using each test rule to test the vehicle in an embodiment of the present invention;

[0084] Figure 5 A flowchart for comprehensively analyzing the climbing performance of different types of vehicles under different conditions provided by an embodiment of the present invention;

[0085] Figure 6 A structural block diagram of a vehicle climbing performance test system based on dynamic scenarios provided by an embodiment of the present invention;

[0086] Figure 7 A structural block diagram of a vehicle type identification and classification module provided in an embodiment of the present invention;

[0087] Figure 8 A structural block diagram of a test rule definition and sound capture module provided in an embodiment of the present invention;

[0088] Fig. 9 A structural block diagram of a data acquisition and binding module provided in an embodiment of the present invention;

[0089] Fig.10 This is a structural block diagram of the performance analysis and sound feature recognition module provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0090] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0091] It is understood that the terms "first", "second", etc. used in this application may be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish a first element from another element. For example, without departing from the scope of this application, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script.

[0092] Figure 1 A flow chart of a vehicle climbing performance test method based on a dynamic scenario provided by an embodiment of the present invention, such as Figure 1 As shown, the method includes:

[0093] S100, identifies the vehicle model to be tested and classifies all vehicle models, including four-wheel drive, front-wheel drive and rear-wheel drive, and sets several dynamic scenarios with different combinations of ramps and road environments;

[0094] like Figure 2 As shown, the method identifies the vehicle model to be tested and classifies all vehicle models, including four-wheel drive, front-wheel drive and rear-wheel drive, and sets several dynamic scenes with different combinations of slopes and road environments, specifically including:

[0095] S110, obtaining information of the vehicle model to be tested, and classifying the vehicle models into three categories according to the driving mode: four-wheel drive type 4WD, front-wheel drive type FWD, and rear-wheel drive type RWD;

[0096] S120, designing different ramps according to the climbing ability of the vehicle, including the slope and the slope length, and setting a number of road surface environments for each ramp;

[0097] S130, combining the ramp with the road environment to form a plurality of dynamic scenes.

[0098] In this step, you first need to collect the technical parameters of the vehicle to be tested, including vehicle type, engine power, torque, weight, drive mode, tire type and other information, which can be obtained by consulting the manufacturer's information, the owner's manual or contacting the manufacturer directly. Then, the vehicle models are divided into three categories according to the drive mode: four-wheel drive (4WD), suitable for complex conditions, with strong climbing ability; front-wheel drive (FWD), suitable for ordinary driving in the case of front-wheel drive, but may face the problem of insufficient traction when climbing; rear-wheel drive (RWD), which can effectively distribute the vehicle weight and is suitable for certain road conditions, but may slip in some cases.

[0099] Next, design a variety of ramps, including different slopes (such as 10%, 15%, 20%, 25%, etc.) and slope lengths (short and long), and set up several road environments on each ramp, such as dry, slippery, snow-covered, sandy, etc., to test the vehicle's climbing performance under different conditions. In this process, the characteristics of each road environment (such as friction coefficient, surface roughness, etc.) need to be recorded for subsequent analysis. The designed ramps and road environments are combined to form several dynamic scenes, such as combining ramps with different slopes with different road environments to construct specific test conditions. This ensures that each dynamic scene can truly reflect the actual driving environment, so as to facilitate the reliability and applicability of the test results.

[0100] The detailed classification of vehicle models and the systematic design of ramp and road environment provide a scientific basis for subsequent testing. Different test conditions ensure the reliability and validity of the results. At the same time, this comprehensiveness can comprehensively evaluate the performance of vehicles in a variety of complex environments by considering different combinations of ramp and road environment, covering a variety of driving scenarios, making the test results more universally applicable. In addition, targeted classification and testing of vehicle models with different drive modes can optimize the characteristics of each drive mode. By comparing the performance of different configurations, it can help manufacturers and users understand which configurations perform better under specific conditions.

[0101] In terms of the richness of data collection, acoustic feedback analysis combined with vehicle performance testing can obtain multi-dimensional data. This richness of data provides more information sources for subsequent analysis and helps to discover potential room for improvement. In terms of practicality, by designing a variety of dynamic scenarios, this test method is not only applicable to laboratory environments, but also to evaluations under actual road conditions, making the test results more practical and providing an effective reference for vehicle design and user selection. Finally, the test design for special environments (such as three-wheel climbing) ensures that the performance of the vehicle can be fully evaluated when encountering extreme situations in actual driving scenarios, thereby providing protection for safe driving.

[0102] S200 defines test rules and data recording rules for each type of vehicle, and captures the sound data generated by the vehicle when climbing the slope during each test;

[0103] like Figure 3 As shown, the test rules and data recording rules are defined for each type of vehicle, and the sound data generated by the vehicle when climbing the slope is captured during each test, including:

[0104] S210, develops test rules for each vehicle type, including:

[0105] Four-wheel drive:

[0106] Gradeability with all tires in contact with the ground;

[0107] The gradeability of any tire when it leaves the ground;

[0108] Front-wheel drive:

[0109] Gradeability with all tires in contact with the ground;

[0110] Gradeability when any front wheel leaves the ground;

[0111] The climbing ability when any rear wheel leaves the ground;

[0112] Rear-wheel drive:

[0113] Gradeability with all tires in contact with the ground;

[0114] The climbing ability when any rear wheel leaves the ground;

[0115] Gradeability when any front wheel leaves the ground;

[0116] S220, record the hill climbing performance of different models under different contact combinations, including:

[0117] Four-wheel drive: power distribution, torque output of each tire, speed change at the start and apex of the slope;

[0118] Front-wheel drive: three ground contact combinations of vehicle speed, tire slip, engine status, power delivery and traction;

[0119] RWD: three ground contact combinations of vehicle speed, tire slip, engine status, power delivery and traction;

[0120] S230, capturing all sound data of the vehicle during the climbing process.

[0121] To ensure the scientific and systematic nature of the test, clear test rules need to be defined for each vehicle model in order to comprehensively evaluate its climbing ability under different conditions. For four-wheel drive (4WD), the test rules include the climbing ability when all tires are in contact with the ground, and the climbing ability when any tire is off the ground. The purpose of this design is to evaluate the performance of four-wheel drive models under different driving conditions. The performance data recorded includes key indicators such as power distribution, torque output of each tire, and speed changes at the start and apex of the slope, so as to analyze the performance of the vehicle in various dynamic scenarios.

[0122] For front-wheel drive (FWD), the test rules should cover the climbing ability when all tires are in contact with the ground, and the climbing ability when any front or rear wheel is off the ground. This type of design can help understand how the vehicle's climbing ability changes with a front-wheel drive layout, especially when traction is lost. The records include information such as vehicle speed, tire slip, engine status, power transmission and traction under the three contact combinations to ensure that the dynamic characteristics of the front-wheel drive model are fully reflected.

[0123] The test rules for rear-wheel drive (RWD) vehicles should also include the climbing ability when all tires are in contact with the ground, and the climbing ability when any rear wheel or front wheel is off the ground. This design can deeply analyze the performance of rear-wheel drive vehicles under different tire contact conditions, especially the power distribution under the rear-wheel drive layout. The recorded data includes vehicle speed, tire slip, engine status, power transmission and traction under three contact combinations, which helps evaluate the overall climbing ability of rear-wheel drive vehicles.

[0124] By integrating the audio recording system, the sounds emitted by the vehicle in different dynamic scenarios, such as tire sliding, engine running and power transmission, can be analyzed in detail, providing another data dimension for vehicle performance. Sound feature analysis will provide important supplementary data for subsequent performance evaluation.

[0125] Clear test rules ensure that the performance of the vehicle under different conditions can be comprehensively and scientifically evaluated. This detailed rule setting not only enhances the systematic nature of the test, but also improves the reliability of the results, making the performance comparison between different models more fair and reasonable. The rules designed for models with different drive modes can accurately reflect the climbing ability and limitations of the model under specific conditions, making the data more targeted. By recording important indicators such as power distribution, torque output and vehicle speed changes, it provides rich data support for subsequent performance analysis, helping engineers and designers identify potential optimization space.

[0126] Capturing sound data provides a new perspective for vehicle performance analysis. The correlation analysis between sound characteristics and vehicle performance can reveal dynamic changes during the climbing process and provide a deep understanding of the vehicle's performance under extreme conditions. This multi-dimensional analysis method makes the test results more comprehensive and can better guide vehicle design and improvement.

[0127] S300, collecting and recording the performance data of each type of vehicle in different dynamic scenarios in batches, using each test rule to test the vehicle, and binding the recorded sound data with the batch;

[0128] like Figure 4As shown, the method collects and records the performance data of each type of vehicle in different dynamic scenes in batches, tests the vehicle using each test rule, and binds the recorded sound data with the batch, specifically including:

[0129] S310 tests each vehicle model in different dynamic scenarios one by one, and during the test, records the vehicle's performance data in real time;

[0130] S320, setting the audio collection frequency to capture the sound emitted by the vehicle in real time;

[0131] S330, associating the performance data of each test record with the corresponding sound data, and adding tag information to each batch of data.

[0132] In this step, it is necessary to ensure that the performance of each model under various test conditions is fully recorded. During the test, the vehicle's performance data should be recorded in real time, including power output, speed changes, traction, tire slip and other indicators to ensure the accuracy and completeness of the data.

[0133] In terms of audio collection, it is very important to set a reasonable audio collection frequency, so that the sound of the vehicle can be captured in real time, including the sliding sound when the tire contacts the ground, the sound of the engine running, and various sounds generated during the power transmission process. This process can not only help analyze the performance of the vehicle under different kinetic energy states, but also provide important information for subsequent sound feature analysis.

[0134] In terms of data association, the performance data recorded in each test must be closely associated with the corresponding sound data. To ensure the traceability and organization of the data, it is necessary to add tag information to each batch of data. The tag content can include test date, vehicle model, dynamic scene, test conditions, etc. This systematic recording method will make subsequent data analysis more efficient and convenient, and facilitate the identification of any potential patterns or anomalies.

[0135] By testing each model one by one, we can ensure that the performance of all models in a real dynamic environment is fully evaluated, which enhances the reliability and scientificity of the data. The combination of real-time recording of performance data and sound data makes the test not limited to traditional performance indicators, but also provides a new analysis angle for sound characteristics. The results can reveal the power changes and vehicle behavior during the climbing process, providing rich reference materials for subsequent performance analysis.

[0136] By setting the frequency of audio acquisition and associating it with performance data, a direct connection between vehicle performance and sound characteristics can be established. This multi-dimensional data integration will provide engineers and designers with deeper insights and help them understand the subtle differences in vehicle performance under different conditions. By adding tag information to each batch of data, the efficiency of data management can be effectively improved, making the subsequent analysis and report generation process smoother.

[0137] S400, analyzes the performance of each type of vehicle under different dynamic scenarios and test rules, identifies the sound features in the batch of sound data, evaluates the correlation between the sound features and the vehicle performance indicators, and comprehensively analyzes the vehicle climbing performance of different types of vehicles under different conditions based on the performance and correlation;

[0138] like Figure 5 As shown, the performance of each type of vehicle under different dynamic scenarios and test rules is analyzed, and the sound features in the batch of sound data are identified, and the correlation between the sound features and the vehicle performance indicators is evaluated. In combination with the performance and correlation, the vehicle climbing performance of different types of vehicles under different conditions is comprehensively analyzed, specifically including:

[0139] S410, integrating all collected performance data and sound data, checking and cleaning up outliers and noise in the data;

[0140] S420, calculating the vehicle performance index of each vehicle model in different dynamic scenarios according to the test rules, and performing comparative analysis of the performance data;

[0141] Specific:

[0142] ;

[0143] ;

[0144] ;

[0145] in, It represents the ratio of the variance between different groups to the variance within the group. represents the between-group mean square, represents the sum of squares between groups, that is, the difference between the means of different groups and the overall mean, is the number of groups, represents the within-group mean square, represents the within-group sum of squares, that is, the differences between data points within a group, is the total number of sample points;

[0146] S430, processing the captured sound data, evaluating the correlation between each audio feature and the vehicle performance index, identifying the audio features that affect the vehicle's climbing performance, and performing quantitative analysis;

[0147] Specific:

[0148] ;

[0149] in, is the correlation coefficient, which indicates the strength of the linear relationship between two variables. is the number of sample points, that is, the number of recorded audio clips, is a specific audio feature, is the vehicle performance index, is the sum of the products of the audio features of all sample points and the vehicle performance indicators, and is the sum of audio features and vehicle performance indicators, and is the sum of the squares of the audio features and the vehicle performance index;

[0150] S440, comprehensively evaluates the performance data and the sound characteristic analysis results;

[0151] Specific:

[0152] ;

[0153] in, is the dependent variable, indicating the climbing time, are independent variables, representing audio features and vehicle performance indicators, is the intercept, which represents the value of the dependent variable when all independent variables are zero. is the regression coefficient, which indicates the influence of the independent variable on the dependent variable. is the error term.

[0154] This step integrates all the collected performance data and sound data to ensure that subsequent analysis is based on a complete and consistent data set. During this process, it is necessary to carefully check and clean up outliers and noise in the data, which can improve data quality and ensure the accuracy of analysis results.

[0155] Next, the vehicle performance indicators of each model in different dynamic scenarios are calculated according to the test rules. These indicators may include climbing time, maximum climbing angle, power output efficiency, etc. When conducting comparative analysis of performance data, the analysis of variance (ANOVA) method needs to be applied. Specifically, the ratio of the variance between different groups to the variance within the group is calculated to determine the significant differences in the performance of different models in the same or different dynamic scenarios.

[0156] In terms of sound data processing, by identifying audio features that affect the vehicle's climbing performance and performing quantitative analysis, the relationship between sound features and performance can be revealed. The specific analysis method includes calculating the correlation coefficient, which represents the strength of the linear relationship between the two variables. The number of sample points is the number of recorded audio clips. The sum of the products of specific audio features and vehicle performance indicators will be used to quantify this relationship.

[0157] Finally, the performance data and the sound feature analysis results are comprehensively evaluated by establishing a regression model to analyze the relationship between the dependent variable (such as climbing time) and the independent variables (audio features and vehicle performance indicators). In the structure of the regression model, the intercept represents the value of the dependent variable when all independent variables are zero, the regression coefficient represents the degree of influence of the independent variable on the dependent variable, and the error term is used to measure the prediction error of the model.

[0158] This step ensures a solid foundation for analysis by integrating performance data and audio data and performing comprehensive outlier processing. The use of variance analysis to compare the performance differences of different models makes the test results statistically significant, thus providing a scientific basis for vehicle performance optimization. In addition, the quantitative analysis between sound characteristics and performance indicators not only enriches the understanding of vehicle performance, but also provides specific guidance for future vehicle design and improvement. This comprehensive evaluation process combines multi-dimensional data to make the final analysis results more comprehensive and in-depth, which can effectively support vehicle engineers' performance improvement decisions under different conditions. This highly systematic data integration and analysis will provide strong support for subsequent research and applications, and further promote the innovation and development of vehicle climbing performance test methods.

[0159] S500 compares test results under different drive modes and tire contact conditions, identifies the optimal configuration and performance, and generates an evaluation report.

[0160] Figure 6 The structural block diagram of the vehicle climbing performance test system based on dynamic scenarios provided by the embodiment of the present invention is as follows: Figure 6 As shown, the system comprises:

[0161] The vehicle type recognition and classification module 100 is used to recognize the vehicle type to be tested and classify all vehicle types, including four-wheel drive type, front-wheel drive type and rear-wheel drive type, and set a number of dynamic scenes with different combinations of ramps and road environments;

[0162] The test rule definition and sound capture module 200 is used to define the test rules and data recording rules for each type of vehicle model, and to capture the sound data generated by the vehicle when climbing the slope during each test;

[0163] The data collection and binding module 300 is used to collect and record the performance data of each type of vehicle in different dynamic scenes in batches, using each test rule to test the vehicle, and bind the recorded sound data to the batch;

[0164] The performance analysis and sound feature recognition module 400 is used to analyze the performance of each type of vehicle under different dynamic scenarios and test rules, identify the sound features in the batch of sound data, evaluate the correlation between the sound features and the vehicle performance indicators, and comprehensively analyze the vehicle climbing performance of different types of vehicles under different conditions based on the performance and correlation;

[0165] The configuration comparison and evaluation report generation module 500 is used to compare the test results under different driving modes and tire contact conditions, identify the optimal configuration and performance, and generate an evaluation report.

[0166] like Figure 7 As shown, the vehicle type identification and classification module 100 includes:

[0167] The vehicle model information acquisition and classification unit 110 is used to acquire the information of the vehicle model to be tested, and classify the vehicle models into three categories according to the driving mode: four-wheel drive type 4WD, front-wheel drive type FWD, and rear-wheel drive type RWD;

[0168] The ramp design and road surface environment setting unit 120 is used to design different ramps according to the climbing ability of the vehicle, including the slope and the slope length, and set a number of road surface environments for each ramp;

[0169] The dynamic scene combination unit 130 is used to combine the ramp and the road environment to form a plurality of dynamic scenes.

[0170] like Figure 8 As shown, the test rule definition and sound capture module 200 includes:

[0171] A test rule formulation unit 210, used to formulate test rules for each vehicle type;

[0172] A climbing performance recording unit 220, used to record the climbing performance of different vehicle models under different ground contact combinations;

[0173] The sound data capturing unit 230 is used to capture all sound data of the vehicle during the climbing process.

[0174] like Fig. 9 As shown, the data collection and binding module 300 includes:

[0175] The dynamic scene test unit 310 is used to test each vehicle model in different dynamic scenes one by one, and during the test process, the performance data of the vehicle is recorded in real time;

[0176] An audio collection setting unit 320, used to set the audio collection frequency and capture the sound emitted by the vehicle in real time;

[0177] The data association and marking unit 330 is used to associate the performance data recorded in each test with the corresponding sound data, and add marking information to each batch of data.

[0178] like Fig.10 As shown, the performance analysis and sound feature recognition module 400 includes:

[0179] The data integration and cleaning unit 410 is used to integrate all the collected performance data and sound data, and check and clean up the abnormal values ​​and noise in the data;

[0180] The performance index calculation and comparison analysis unit 420 is used to calculate the vehicle performance index of each vehicle model in different dynamic scenarios according to the test rules, and to perform comparative analysis of the performance data;

[0181] The sound data processing and feature analysis unit 430 is used to process the captured sound data, evaluate the correlation between each audio feature and the vehicle performance index, identify the audio features that affect the vehicle's climbing performance, and perform quantitative analysis;

[0182] The comprehensive evaluation unit 440 is used to comprehensively evaluate the performance data and the sound feature analysis results.

[0183] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0184] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0185] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0186] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

[0187] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A vehicle climbing performance test method based on dynamic scenarios, characterized in that: The method comprises: Identify the vehicle models to be tested and classify all models, including four-wheel drive, front-wheel drive and rear-wheel drive, and set dynamic scenarios with different combinations of ramps and road environments; Define test rules and data recording rules for each type of vehicle, and capture the sound data generated by the vehicle when climbing the slope during each test; Collect and record the performance data of each type of vehicle in different dynamic scenarios in batches, test the vehicle using each test rule, and bind the recorded sound data to the batch; Analyze the performance of each type of vehicle under different dynamic scenarios and test rules, identify the sound features in the batch of sound data, evaluate the correlation between the sound features and vehicle performance indicators, and comprehensively analyze the vehicle climbing performance of different types of vehicles under different conditions by combining performance and correlation; Compare test results under different driving modes and tire contact conditions, identify the optimal configuration and performance, and generate evaluation reports; The method of collecting and recording the performance data of each type of vehicle in different dynamic scenarios in batches, testing the vehicle using each test rule, and binding the recorded sound data with the batch specifically includes: Each vehicle model is tested in different dynamic scenarios one by one, and the vehicle performance data is recorded in real time during the test; Set the audio collection frequency to capture the sound of the vehicle in real time; Associating the performance data recorded in each test with the corresponding sound data, and adding tag information to each batch of data; The analysis of the performance of each type of vehicle under different dynamic scenarios and test rules, and identification of the sound features in the batch of sound data, evaluation of the correlation between the sound features and the vehicle performance indicators, and comprehensive analysis of the vehicle climbing performance of different types of vehicles under different conditions in combination with the performance and correlation, specifically includes: Integrate all collected performance and sound data, check and clean up outliers and noise in the data; Calculate the vehicle performance indicators of each model in different dynamic scenarios according to the test rules, and conduct comparative analysis of the performance data; Specific: in, It represents the ratio of the variance between different groups to the variance within the group. represents the between-group mean square, represents the sum of squares between groups, that is, the difference between the means of different groups and the overall mean, is the number of groups, represents the within-group mean square, represents the within-group sum of squares, that is, the differences between data points within a group, is the total number of sample points; The captured sound data is processed to evaluate the correlation between each audio feature and the vehicle performance index, identify the audio features that affect the vehicle's climbing performance, and conduct quantitative analysis; Specific: in, is the correlation coefficient, which indicates the strength of the linear relationship between two variables. is the number of sample points, that is, the number of recorded audio clips, is a specific audio feature, is the vehicle performance index, is the sum of the products of the audio features of all sample points and the vehicle performance indicators, and is the sum of audio features and vehicle performance indicators, and is the sum of the squares of the audio features and the vehicle performance index; Comprehensively evaluate the performance data and sound characteristic analysis results; Specific: in, is the dependent variable, indicating the climbing time, are independent variables, representing audio features and vehicle performance indicators, is the intercept, which represents the value of the dependent variable when all independent variables are zero. is the regression coefficient, which indicates the influence of the independent variable on the dependent variable. is the error term.

2. The method according to claim 1, characterized in that The method of identifying the vehicle model to be tested and classifying all vehicle models, including four-wheel drive, front-wheel drive and rear-wheel drive, and setting several dynamic scenes with different combinations of slopes and road environments, specifically includes: Obtain the information of the vehicle model to be tested, and classify the vehicle models into three categories according to the driving mode: four-wheel drive, front-wheel drive, and rear-wheel drive; Design different ramps according to the vehicle's climbing ability, including slope gradient and slope length, and set several road surface environments for each type of ramp; Combine the ramp with the road environment to form several dynamic scenes.

3. The method according to claim 2, characterized in that The test rules and data recording rules are defined for each type of vehicle, and the sound data generated by the vehicle when climbing the slope is captured during each test, including: Develop test rules for each vehicle type, including: Four-wheel drive: Gradeability with all tires in contact with the ground; The gradeability of any tire when it leaves the ground; Front-wheel drive: Gradeability with all tires in contact with the ground; Gradeability when any front wheel leaves the ground; The climbing ability when any rear wheel leaves the ground; Rear-wheel drive: Gradeability with all tires in contact with the ground; The climbing ability when any rear wheel leaves the ground; Gradeability when any front wheel leaves the ground; Record the hill climbing performance of different models under different contact combinations, including: Four-wheel drive: power distribution, torque output of each tire, speed change at the start and apex of the slope; Front-wheel drive: three ground contact combinations of vehicle speed, tire slip, engine status, power delivery and traction; RWD: three ground contact combinations of vehicle speed, tire slip, engine status, power delivery and traction; Capture all the sound data of the vehicle while climbing the slope.

4. A vehicle climbing performance test system based on dynamic scenarios for implementing the method as claimed in claim 1, characterized in that: The system comprises: The vehicle type recognition and classification module is used to identify the vehicle type to be tested and classify all vehicle types, including four-wheel drive, front-wheel drive and rear-wheel drive, and set dynamic scenes with different combinations of ramps and road environments; The test rule definition and sound capture module is used to define the test rules and data recording rules for each type of vehicle, and capture the sound data generated by the vehicle when climbing the slope during each test; The data collection and binding module is used to collect and record the performance data of each type of vehicle in different dynamic scenarios in batches, using each test rule to test the vehicle, and bind the recorded sound data to the batch; Performance analysis and sound feature recognition module, used to analyze the performance of each type of vehicle under different dynamic scenarios and test rules, identify the sound features in the batch of sound data, evaluate the correlation between the sound features and vehicle performance indicators, and comprehensively analyze the vehicle climbing performance of different types of vehicles under different conditions by combining performance and correlation; The configuration comparison and evaluation report generation module is used to compare the test results under different driving modes and tire contact conditions, identify the optimal configuration and performance, and generate an evaluation report.

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