CN118464480B - A method and system for testing dynamic and static performance of air suspension for automobile - Google Patents

Abstract

The application discloses a dynamic and static performance testing method and system of an air suspension for an automobile, belonging to the field of performance testing, wherein the method comprises the following steps: obtaining suspension static parameters through static tests, and carrying out dynamic tests by combining road environment random search dynamic working conditions to obtain smoothness scores; correcting the smoothness score based on the static rigidity, continuously searching and testing in the adjacent working condition space, and integrating the corrected smoothness score, the rigidity score and the working condition qualification rate of the plurality of working conditions to obtain the dynamic and static performance test result of the air suspension. The application solves the technical problems of incomplete coverage working condition and weak test pertinence of dynamic and static performance test of the air suspension in the prior art, combines random search of actual road environment and expansion test of adjacent working condition space through comprehensive static and dynamic test, and introduces the working condition qualification rate to correct test results, thereby achieving the technical effects of comprehensively covering the use working condition of the air suspension and improving the test pertinence and effectiveness.

Description

A method and system for testing dynamic and static performance of air suspension for automobile

Technical Field

The invention relates to the field of performance testing, and in particular to a method and system for testing the dynamic and static performance of an air suspension for an automobile.

Background Art

In the automobile suspension system, air suspension is widely used in the vehicle field due to its variable stiffness and active adjustment characteristics, and its dynamic and static performance directly affects the vehicle's driving smoothness, handling stability and driving safety. In the prior art, the test methods for the dynamic and static performance of air suspension are mainly divided into two categories: bench test and real vehicle road test. Among them, the bench test simulates the road surface on the test bench to test the dynamic and static stiffness, damping characteristics, etc. of the suspension, but due to the single bench test condition, it is difficult to fully simulate the actual road conditions; although the real vehicle road test can obtain the dynamic and static performance under real road conditions, due to the lack of comprehensive coverage and classification analysis of the test conditions, the dynamic and static performance test of air suspension in the prior art does not cover the conditions comprehensively and the test is not targeted.

Summary of the invention

The present application provides a method and system for testing the dynamic and static performance of an automobile air suspension, aiming to solve the technical problems in the prior art that the dynamic and static performance test of an air suspension does not fully cover the working conditions and the test is not targeted.

In view of the above problems, the present application provides a method and system for testing the dynamic and static performance of an automobile air suspension.

The first aspect disclosed in the present application provides a method for testing the dynamic and static performance of an automobile air suspension, the method comprising: using a plurality of test loads to perform a static test on the automobile air suspension to be tested, obtaining a plurality of static stroke parameters under the plurality of test loads, and calculating and obtaining a plurality of static stroke change parameters; obtaining a plurality of road environments for the automobile air suspension, performing a random search under the plurality of test loads and the plurality of road environments, and obtaining a first dynamic test condition including a first test load and a first road environment, wherein the search probability of the plurality of dynamic test conditions is set according to the occurrence rates of the plurality of test loads and the plurality of road environments, and performing a random search; testing the air suspension under the first dynamic test condition, obtaining a first dynamic test result, and analyzing the obtained result; A first smoothness score is obtained; a first stiffness score is obtained by analysis according to a first stroke change parameter of a first test load, and the first smoothness score is corrected and calculated to obtain a corrected first corrected smoothness score; a search test is continued in an adjacent test condition space within the first dynamic test condition, and after reaching a preset number of searches, a plurality of corrected smoothness scores and a plurality of stiffness scores are obtained; a plurality of corrected smoothness scores and a plurality of stiffness scores are weightedly calculated according to the search probabilities of a plurality of selected dynamic test conditions to obtain a result smoothness score and a result stiffness score, and a condition pass rate is obtained according to the pass rates of the plurality of corrected smoothness scores and the plurality of stiffness scores, and the result smoothness score and the result stiffness score are corrected to obtain a dynamic and static performance test result.

Another aspect disclosed in the present application provides a dynamic and static performance test system for an automobile air suspension, the system comprising: a static test module, for using a plurality of test loads to perform a static test on an automobile air suspension to be tested, obtaining a plurality of static stroke parameters under a plurality of test loads, and calculating and obtaining a plurality of static stroke change parameters; a working condition search module, for obtaining a plurality of road environments for the automobile air suspension, performing a random search under a plurality of test loads and a plurality of road environments, and obtaining a first dynamic test working condition including a first test load and a first road environment, wherein the search probability of a plurality of dynamic test working conditions is set according to the occurrence rates of the plurality of test loads and the plurality of road environments, and a random search is performed; a dynamic test module, for testing the air suspension under the first dynamic test working condition, obtaining a first dynamic test result, and analyzing the obtained result; a first smoothness score is obtained; a stiffness evaluation module is used to analyze and obtain a first stiffness score according to a first stroke change parameter of the first test load, and to perform correction calculation on the first smoothness score to obtain a corrected first corrected smoothness score; a neighboring search module is used to continue the search test in the neighboring test condition space within the first dynamic test condition, and obtain multiple corrected smoothness scores and multiple stiffness scores after reaching a preset number of searches; a comprehensive evaluation module is used to perform weighted calculation on multiple corrected smoothness scores and multiple stiffness scores according to the search probabilities of multiple selected dynamic test conditions to obtain a result smoothness score and a result stiffness score, and obtain a condition pass rate according to the pass rates of the multiple corrected smoothness scores and the multiple stiffness scores, and correct the result smoothness score and the result stiffness score to obtain the dynamic and static performance test results.

One or more technical solutions provided in this application have at least the following technical effects or advantages:

Since a variety of test loads are used to perform static tests on the air suspension, a variety of static stroke parameters are obtained, and a variety of static stroke change parameters are calculated to comprehensively evaluate the static characteristics of the air suspension under different load conditions, providing a basis for subsequent dynamic testing and comprehensive performance evaluation; a variety of road environments for automotive air suspension are obtained, and a first dynamic test condition including a first test load and a first road environment is obtained by random search in combination with a variety of test loads, and a corresponding search probability is set according to the occurrence rate of each test load and road environment, and the actual road conditions and vehicle load conditions are comprehensively considered to obtain the first dynamic test condition by random search. The targeted and representative dynamic test conditions improve the effectiveness and comprehensiveness of the test; the air suspension is tested under the first dynamic test condition to obtain the first dynamic test result, and the first smoothness score is obtained based on the analysis. The smoothness of the suspension is directly evaluated through dynamic testing to provide a basis for subsequent performance synthesis; according to the first stroke change parameter corresponding to the first test load, the first stiffness score is analyzed and obtained, and the first smoothness score is corrected to obtain the first corrected smoothness score. The static characteristic test results are combined with the dynamic characteristic test results, and the smoothness score is corrected by the stiffness score to achieve dynamic and static performance. Comprehensive evaluation improves the reliability and comprehensiveness of the test results; continues to search in the adjacent test condition space of the first dynamic test condition until the preset number of searches is reached, and multiple modified smoothness scores and multiple stiffness scores are obtained. By expanding the adjacent condition space, the test conditions are further enriched and refined to improve the precision and credibility of the test results; multiple modified smoothness scores and multiple stiffness scores are weighted according to the search probability of multiple dynamic test conditions to obtain the result smoothness score and result stiffness score, and the condition pass rate is calculated based on the pass rate of multiple scores, and finally the modified dynamic and static performance is obtained The test results are corrected by introducing the working condition qualification rate on the basis of the comprehensive score to further improve the reliability of the test results. At the same time, weights are given to different working conditions through weighted calculation of the search probability to make the test results more in line with the actual usage situation. The technical solution solves the technical problems in the prior art that the dynamic and static performance test of air suspension does not fully cover the working conditions and the test is not targeted. Through comprehensive static and dynamic tests, combined with random searches of actual road environments and extended tests of adjacent working condition spaces, and the introduction of working condition qualification rate to correct the test results, the technical effect of fully covering the working conditions of air suspension use and improving the test targeting and effectiveness is achieved.

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

FIG1 is a schematic flow chart of a method for testing the dynamic and static performance of an air suspension for an automobile according to an embodiment of the present application;

FIG2 is a schematic structural diagram of a dynamic and static performance testing system for an automobile air suspension provided in an embodiment of the present application.

Explanation of the reference numerals: static test module 11 , working condition search module 12 , dynamic test module 13 , stiffness evaluation module 14 , proximity search module 15 , comprehensive evaluation module 16 .

DETAILED DESCRIPTION

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 testing the dynamic and static performance of an air suspension for an automobile. First, the air suspension is tested under a variety of load conditions through static testing to obtain comprehensive static characteristic parameters; then, in combination with the actual road environment and vehicle load state, a random search method is used to obtain targeted and representative dynamic test conditions; on this basis, each dynamic condition is tested and evaluated to obtain a smoothness score of the suspension performance, and the static characteristics are combined with the dynamic characteristics to correct the smoothness score; in order to further improve the precision and credibility of the test, the search test is expanded in the adjacent space of each dynamic test condition to obtain multiple corrected smoothness scores and multiple stiffness scores; then, based on the aforementioned scores, combined with the weighted calculation of the probability of occurrence of the condition and the correction of the condition qualification rate, the dynamic and static performance test results of the air suspension are obtained.

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.

Embodiment 1, as shown in FIG1 , the embodiment of the present application provides a method for testing the dynamic and static performance of an air suspension for an automobile, the method comprising:

S1: using a variety of test loads to perform a static test on the automobile air suspension to be tested, obtaining a plurality of static stroke parameters under the plurality of test loads, and calculating and obtaining a plurality of static stroke change parameters.

Specifically, when the load of the air suspension changes, the amount of air pumped in is adjusted to change the support force, so that the height of the vehicle remains relatively stable. Therefore, different loads are applied to the tested air suspension, such as full load, half load, etc., to simulate various load conditions that may be encountered in actual use. Under each test load, the static travel parameters of the air suspension are measured. Among them, the static travel parameters reflect the height position of the air suspension under the load condition in a stationary state.

By comparing multiple static stroke parameters obtained under different test loads with preset standard stroke parameters, multiple static stroke change parameters are obtained, which reflect the degree of change in the height position of the air suspension when the load changes. Among them, the smaller the absolute value of the static stroke change parameter, the smaller the change in the height position of the air suspension with the load change, that is, the greater its stiffness. On the contrary, if the absolute value of the static stroke change parameter is large, it means that the stiffness of the air suspension is relatively small.

By obtaining multiple static stroke parameters and multiple static stroke change parameters under various test loads, the stability of the air suspension's height maintenance under different static loads is comprehensively evaluated, providing a basis for subsequent dynamic tests and supporting the final dynamic and static comprehensive performance test results.

S2: Acquire multiple road environments for the air suspension of the automobile, perform random searches on the multiple test loads and the multiple road environments, and obtain a first dynamic test condition including a first test load and a first road environment, wherein the search probabilities of the multiple dynamic test conditions are set according to the occurrence rates of the multiple test loads and the multiple road environments, and perform random searches.

Specifically, during the actual driving of the car, the air suspension needs to adapt to various complex and changeable road environments and load conditions. In order to comprehensively evaluate the dynamic and static performance of the air suspension, it is necessary to obtain a variety of road environments that the air suspension for the car experiences during its actual working process, such as ramps with different potholes and different curvature radii.

The collected multiple road environments and multiple test loads are combined to obtain a set of dynamic test conditions that fully reflect the actual working state of the air suspension. At the same time, since the frequencies of occurrence of different dynamic test conditions are different in practice, the search probabilities of multiple dynamic test conditions are allocated according to the probability of occurrence of road conditions and loads. For example, the probability of occurrence of each test load and road environment is multiplied, and then divided by the sum of the probabilities of the test loads and road environments in all conditions, so as to obtain the normalized search probability of each dynamic test condition.

For the dynamic test condition set, a random search method is adopted to sample according to the search probability of each dynamic test condition. The dynamic test condition with a greater search probability has a greater probability of being selected. After random search, a first dynamic test condition including a first test load and a first road environment is obtained. Among them, the first dynamic test condition is any condition in the dynamic test condition set. Through random sampling, various scenarios encountered by the air suspension in actual use are simulated with a relatively small number of tests, ensuring the comprehensiveness of the test. At the same time, in order to obtain complete test results, each condition in the dynamic test condition set needs to be tested.

By considering the probability of occurrence of different dynamic test conditions, the distribution of test samples is closer to the actual situation, and the test results are more representative. At the same time, the random search strategy is adopted to reduce the test cost and improve the test efficiency to a certain extent. While ensuring the comprehensiveness of the test, the pertinence and effectiveness of the test are taken into account, providing reliable support for the dynamic and static performance evaluation of the air suspension.

S3: Under the first dynamic test condition, the air suspension is tested to obtain a first dynamic test result, and a first smoothness score is obtained by analysis.

Specifically, after the first dynamic test condition is determined, an actual dynamic test is performed on the air suspension, that is, a vehicle equipped with the tested air suspension is driven under the load and road environment specified by the first dynamic test condition, while the motion data of the suspension is collected.

The first dynamic test result is obtained by analyzing the collected data. The first dynamic test result includes the stroke change rate, which reflects the height change of the air suspension under the dynamic working condition. The smaller the stroke change rate, the smoother the height change of the suspension under the working condition, and the better the ride comfort of the vehicle. On the contrary, if the stroke change rate is large, it means that the height change of the suspension is more drastic, and the ride comfort of the vehicle is relatively poor.

In order to quantitatively evaluate the vehicle's ride comfort performance under the first dynamic test condition, a ride comfort score was introduced. A ride comfort evaluation model was established by analyzing a large amount of air suspension test data. The model takes historical dynamic test results (travel change rate) as input and the corresponding ride comfort score as output, and is trained through machine learning.

The first dynamic test results were input into the trained smoothness evaluation model to generate the first smoothness score, which quantified the smoothness performance of the air suspension under the first dynamic test condition and provided a data basis for subsequent analysis.

S4: Analyze and obtain a first stiffness score according to a first stroke change parameter of the first test load, and perform correction calculation on the first smoothness score to obtain a corrected first corrected smoothness score.

Specifically, after obtaining the first smoothness score, the effect of static stiffness on vehicle smoothness is further considered, and the first smoothness score is corrected using the obtained static travel change parameters.

First, from the multiple static stroke change parameters obtained, the static stroke change parameter corresponding to the load condition of the first dynamic test condition is selected as the first stroke change parameter. The first stroke change parameter reflects the static stiffness characteristics of the air suspension under the load condition of the first dynamic test condition. Then, the first stroke change parameter is analyzed using a pre-established stiffness evaluation model to obtain a first stiffness score. Among them, the stiffness evaluation model is obtained by machine learning training on a large amount of static test data of air suspension, with the static stroke change parameter as input and the corresponding stiffness score as output. The first stiffness score quantifies the static stiffness characteristics of the air suspension under the load condition of the first dynamic test condition.

Considering that static stiffness is closely related to the ride comfort of the vehicle, the first stiffness score is used to adjust the first ride comfort score. Specifically, the ratio of the first stiffness score to the preset standard stiffness score is calculated, and the ratio is used as the ride comfort correction coefficient, and then the first ride comfort score is multiplied by the correction coefficient to obtain the first corrected ride comfort score.

Through the correction calculation of the first ride comfort score, the influence of static stiffness is further considered on the basis of the first ride comfort score. If the static stiffness of the air suspension is large (that is, the first stiffness score is high), then its ability to buffer vibration will be relatively weak, and the ride comfort of the vehicle will be affected to a certain extent. At this time, the correction coefficient will be relatively small, lowering the first corrected ride comfort score. On the contrary, if the static stiffness of the air suspension is moderate (that is, the first stiffness score is close to the preset standard), then the correction coefficient will be close to 1, and the first corrected ride comfort score will be closer to the first ride comfort score.

By establishing the relationship between static stiffness and dynamic ride comfort, the ride comfort evaluation is made more comprehensive and accurate by means of correction calculation. At the same time, the stiffness evaluation model is constructed using machine learning methods to improve the efficiency and accuracy of stiffness evaluation.

S5: Continue to perform the search test in the adjacent test condition space within the first dynamic test condition, and obtain a plurality of modified smoothness scores and a plurality of stiffness scores after reaching a preset number of searches.

Specifically, after obtaining the first modified smoothness score and the first stiffness score, the search space of the first dynamic test condition is further expanded, and the search and testing of the test condition are continued within the neighborhood of the first dynamic test condition.

First, according to the load conditions and road environment conditions of the first dynamic test condition, its position in the dynamic test condition set is determined. Then, with the first dynamic test condition as the center, test conditions within a certain range are selected as its adjacent test condition space. Among them, the conditions in the adjacent test condition space have similar load conditions and road environment conditions as the first dynamic test condition. Next, in the adjacent test condition space, according to the search probability of each condition, a random search is performed, and the second dynamic test condition is selected for testing. Under the second dynamic test condition, the air suspension is tested and the static stroke change parameters are analyzed and corrected and calculated to obtain the second corrected smoothness score and the second stiffness score.

Then, with the second dynamic test condition as the new center, continue to construct its adjacent test condition space, and search and test in it. Repeat this process until the preset number of searches is completed, and multiple modified smoothness scores and multiple stiffness scores are obtained. By focusing on exploring the condition space around the first dynamic test condition, more relevant test data can be obtained, so as to make a more accurate assessment of the dynamic and static performance of the area. At the same time, since the search range is local, the test is more targeted, avoiding unnecessary testing costs. Among them, the preset number of searches is determined according to actual needs and test resources. The more searches, the richer the test data obtained, and the higher the reliability of the evaluation results, but at the same time, the time and cost of the test will increase accordingly.

By conducting local searches in the space of adjacent test conditions, the richness of the test data is improved while ensuring the targeted nature of the test, providing a more reliable basis for subsequent comprehensive evaluation.

S6: According to the search probability of multiple selected dynamic test conditions, the multiple modified smoothness scores and the multiple stiffness scores are weightedly calculated to obtain a result smoothness score and a result stiffness score, and according to the pass rates of the multiple modified smoothness scores and the multiple stiffness scores, the condition pass rate is obtained, the result smoothness score and the result stiffness score are corrected to obtain dynamic and static performance test results.

Specifically, after obtaining multiple modified smoothness scores and multiple stiffness scores, these scoring data are comprehensively analyzed to obtain the dynamic and static performance test results of the air suspension.

First, for each selected dynamic test condition, there is a corresponding search probability. This search probability reflects the frequency of the condition in actual use, and also reflects the contribution of the condition to the overall performance evaluation. Using these search probabilities, the corresponding modified smoothness scores and stiffness scores are weighted averaged to obtain the resulting smoothness score and the resulting stiffness score. Specifically, each modified smoothness score and stiffness score is multiplied by the search probability of the corresponding condition, and then the sum and average are taken to obtain the resulting smoothness score and the resulting stiffness score, which comprehensively considers the importance of different conditions and can better reflect the overall performance of the air suspension in actual use.

Secondly, the qualified rate is introduced to further correct the resulting smoothness score and the resulting stiffness score. Specifically, for each corrected smoothness score and stiffness score, it is determined whether it has reached the preset qualified standard. Then, the number of scores that meet the qualified standard is counted and divided by the total number of scores to obtain the qualified rate of multiple corrected smoothness scores and multiple stiffness scores. The qualified rate reflects the stability and reliability of the performance of the air suspension under various working conditions. Subsequently, the qualified rate is used to correct the resulting smoothness score and the resulting stiffness score to obtain the dynamic and static performance test results. For example, the resulting smoothness score and the resulting stiffness score are multiplied by the qualified rate respectively as the dynamic and static performance test results.

Through weighted averaging and pass rate correction, dynamic and static performance test results are obtained that comprehensively consider the importance of different working conditions and performance stability. This not only reflects the performance of the air suspension under various working conditions, but also reflects its reliability level under extreme conditions, thereby improving the pertinence and effectiveness of the test.

Furthermore, the embodiment of the present application also includes:

Collect various loads of the automobile air suspension during operation to obtain various test loads; use the various test loads to perform a static test on the automobile air suspension to be tested to obtain a plurality of static stroke parameters; and calculate and obtain a plurality of static stroke change parameters based on the plurality of static stroke parameters and the standard stroke parameters of the air suspension.

In a feasible implementation, first, various load conditions that may be encountered during the actual use of the air suspension are obtained to obtain a variety of test loads. In specific implementation, these load data can be collected in a variety of ways. For example, in actual vehicle testing, on-board sensors are used to record load changes during driving; through simulation, multiple load conditions are generated according to vehicle parameters and operating conditions. Through load collection, multiple test loads that reflect the actual working state of the air suspension are obtained, covering various usage scenarios of the air suspension, including different working conditions such as full load, half load, and no load, as well as load changes under different driving conditions such as acceleration, braking, and turning.

After obtaining the test load, the air suspension is subjected to an actual static test. Specifically, under each test load, the static displacement of the air suspension, i.e., the static stroke parameter, is measured. The static stroke parameter reflects the compression of the suspension elastic element (such as the air spring) under the current load conditions. The size of the static stroke parameter is closely related to the size of the load. Under heavy load conditions, the air spring will be compressed more and the static stroke parameter will be larger; conversely, under light load conditions, the static stroke parameter will be smaller. By testing the static stroke parameters under different loads, the static characteristics of the air suspension can be comprehensively evaluated.

Although the static stroke parameter can reflect the working state of the suspension under different loads, its absolute value is often affected by the design parameters of the suspension itself, which is not convenient for horizontal comparison. In order to better evaluate the advantages and disadvantages of the static characteristics of the suspension, the static stroke variation parameter is introduced. Specifically, each static stroke parameter is compared with the standard stroke parameter of the air suspension, and the difference between the two is calculated as the corresponding static stroke variation parameter. Among them, the standard stroke parameter is the static displacement of the suspension under the design state, which is determined by the designer according to the vehicle parameters and usage requirements. The static stroke variation parameter reflects the degree of displacement deviation of the suspension relative to the design state under the actual load. If the static stroke variation parameter is small, it means that the suspension can better maintain the design state and adapt to the change of load; if. The static stroke variation parameter is large, it means that the static characteristics of the suspension need to be improved.

By collecting actual loads, measuring static stroke parameters, and calculating static stroke change parameters, the static characteristics of the air suspension were systematically evaluated, providing an important reference for subsequent dynamic performance testing and comprehensive evaluation.

Furthermore, the embodiment of the present application also includes:

Collect various road environments during the working process of the automobile air suspension; collect the appearance ratios of the various test loads and the various road environments in the working process as multiple road appearance rates and multiple load appearance rates; traverse and combine the various test loads and the various road environments to obtain multiple dynamic test conditions, and calculate and set multiple search probabilities for the multiple dynamic test conditions based on the multiple road appearance rates and the multiple load appearance rates; and randomly search the multiple dynamic test conditions according to the multiple search probabilities to obtain a first dynamic test condition.

In a feasible implementation, first, through real vehicle testing or simulation, the road environment data during the suspension operation is collected to obtain various road conditions that may be encountered during the actual use of the air suspension, and multiple road environments are obtained to cover various usage scenarios of the air suspension, representing various situations that the air suspension may encounter on actual roads. Among them, the road environment data includes: road surface type (such as asphalt road, cement road, gravel road, etc.), road surface condition (such as flatness, roughness, slope, etc.), and road surface geometric characteristics (such as curvature radius, superelevation, etc.). After obtaining multiple test loads and multiple road environments, the historical working condition data is mined through data analysis, and the number of occurrences or time proportions of each test load and each road environment are counted as the corresponding load occurrence rate and road occurrence rate, and multiple road occurrence rates and multiple load occurrence rates are obtained to reflect the commonness of different working conditions in actual use.

After obtaining the load occurrence rate and road occurrence rate, a dynamic test condition set containing all possible conditions is obtained by arranging and combining the test loads and road environments, including multiple dynamic test conditions, which fully covers the dynamic working state of the air suspension. Then, according to the load occurrence rate of each test load and the road occurrence rate of each road environment, the occurrence probability of each dynamic test condition is calculated as its search probability. Among them, the load occurrence rate and road occurrence rate corresponding to each dynamic test condition are multiplied, and then divided by the sum of the occurrence probabilities of all conditions, so as to obtain a normalized search probability, and set multiple search probabilities for multiple dynamic test conditions. The introduction of search probability makes the generation and selection of dynamic test conditions match the actual use status, which not only ensures the comprehensive coverage of the test, but also takes into account the pertinence of the test. Common conditions with high frequency of occurrence will obtain a higher search probability, and have a greater chance of being selected first in subsequent tests. Subsequently, using a random sampling method such as a roulette algorithm, the search probability of each dynamic test condition is regarded as the sector area on the roulette wheel, and then a number between 0 and 1 is randomly generated. The selected dynamic test condition is determined according to which sector the number falls in, as the first dynamic test condition. Among them, the dynamic test condition with a large search probability has a greater chance of being selected.

Furthermore, the embodiment of the present application also includes:

Under the first dynamic test condition, the air suspension is tested to obtain a first dynamic test result, wherein the first dynamic test result includes a stroke change rate; based on the test data record of the air suspension, a sample dynamic test result set and a sample smoothness score set are collected; using the sample dynamic test result set and the sample smoothness score set, a smoothness analyzer is constructed, and the first dynamic test result is input and analyzed to obtain a first smoothness score.

In a preferred embodiment, after obtaining the first dynamic test condition, an actual dynamic test is performed on the air suspension, and a vehicle carrying the tested air suspension is driven in a specified road environment, while applying specified load conditions, and collecting the motion response data of the suspension in real time to obtain the first dynamic test result. The first dynamic test result includes a stroke change rate, which reflects the speed of the dynamic displacement of the air suspension during the vehicle's driving, that is, the rate of change of the suspension displacement per unit time. The greater the stroke change rate, the more violent the dynamic response of the air suspension, and the worse the vehicle's ride comfort may be; conversely, the smaller the stroke change rate, the smoother the dynamic response of the air suspension, and the better the vehicle's ride comfort may be.

After obtaining the first dynamic test result, in order to quantitatively evaluate it, a smoothness analysis model, namely a smoothness analyzer, is constructed. First, the dynamic test result data of various models of air suspension in the past and the corresponding smoothness score data are collected to obtain a sample dynamic test result set and a sample smoothness score set. During the collection process, the data is screened and preprocessed as necessary to remove obviously abnormal or erroneous records to ensure the quality and reliability of the sample set. At the same time, attention is paid to the distribution balance of data samples, and different types of suspensions and different levels of smoothness are covered as much as possible to avoid affecting the generalization ability of subsequent models due to sample skew. Then, machine learning algorithms such as support vector machines and random forests are used. The sample dynamic test results are used as the input features of the model, and the sample smoothness scores are used as the output targets of the model. The smoothness analyzer is obtained through training, and the corresponding relationship between the dynamic test results and the smoothness scores is established.

Subsequently, the first dynamic test result is input into the trained smoothness analyzer. The smoothness analyzer gives a quantitative smoothness score based on the first dynamic test result, namely the first smoothness score, which reflects the smoothness level of the air suspension under the first dynamic test condition and provides data basis for subsequent dynamic and static performance test results.

Furthermore, the embodiment of the present application also includes:

According to the static test data record of the air suspension, a sample stroke change parameter set and a sample stiffness score set are collected; the sample stroke change parameter set and the sample stiffness score set are used to construct a stiffness score classifier, and the first stroke change parameter is classified to obtain a first stiffness score; according to the ratio of the first stiffness score to a preset stiffness score, a smoothness correction coefficient is generated, and the first smoothness score is corrected and calculated to obtain a first corrected smoothness score.

In a preferred embodiment, first, static test result data of various types of suspensions in the past are collected to obtain static test data records of air suspensions, and the stroke change data of each test sample under different load conditions are extracted. At the same time, the stiffness score data corresponding to each test sample is collected, wherein the stiffness score data is given by a professional engineer based on experience or obtained based on bench test results. The acquired stroke change data and stiffness score data are screened and preprocessed to ensure the quality and representativeness of the data, and a sample stroke change parameter set and a sample stiffness score set are obtained. Then, a stiffness score classifier is constructed using the sample stroke change parameter set and the sample stiffness score set. For example, a decision tree, naive Bayes, K nearest neighbor and other methods are used to train a stiffness score classifier by taking the sample stroke change parameters as features and the sample stiffness score as a category label, so as to judge the stiffness score to which the input stroke change parameters belong based on the input stroke change parameters.

When the first stroke change parameter (i.e., the static stroke change parameter of the air suspension under the load corresponding to the first dynamic test condition) is input into the trained stiffness score classifier, the stiffness score of the stiffness score classifier, i.e., the first stiffness score, reflects the static stiffness characteristics of the suspension under the current load. After obtaining the first stiffness score, it is combined with the dynamic performance score to correct the first smoothness score to obtain a more comprehensive and balanced result. Specifically, a preset stiffness score is set as the target stiffness level of the air suspension, and the preset stiffness score is determined according to the performance requirements and usage conditions of the whole vehicle; then, the ratio of the first stiffness score to the preset stiffness score is calculated and used as the smoothness correction coefficient, which reflects the degree of deviation between the actual stiffness characteristics of the air suspension and the expected stiffness characteristics. If the smoothness correction coefficient is greater than 1, it means that the suspension is too hard and will damage the smoothness; if the smoothness correction coefficient is less than 1, it means that the suspension is too soft and will affect the support and stability; then, the first smoothness score is multiplied by the smoothness correction coefficient to obtain the corrected first corrected smoothness score. As the first corrected smoothness score, it comprehensively considers the dynamic performance and static characteristics of the suspension, and can more objectively and accurately reflect its comprehensive performance level.

Furthermore, the embodiment of the present application also includes:

According to the first test load and the first road environment in the first dynamic test condition, the similarity between the test load and the road environment in other dynamic test conditions and the first test load and the first road environment is analyzed, and multiple condition similarities are obtained by weighted calculation; similar dynamic test conditions corresponding to the largest multiple condition similarities are selected to construct an adjacent test condition space in the first dynamic test condition; in the adjacent test condition space, a random search is performed according to the search probability of multiple similar dynamic test conditions to obtain a second dynamic test condition; under the second dynamic test condition, the air suspension is tested to obtain a second dynamic test result, and a second smoothness score is obtained by analysis; the adjacent test condition space in the second dynamic test condition is continued to be constructed, and the search test is continued until a preset number of searches is reached to obtain multiple modified smoothness scores and multiple stiffness scores.

In a feasible implementation, first, all dynamic test conditions except the first dynamic test condition in multiple dynamic test conditions are traversed, and the similarity between them and the first dynamic test condition is calculated respectively. Among them, the calculation of similarity takes into account two factors, one is the similarity of the test load, and the other is the similarity of the road environment. For the similarity of the test load, the load parameters (such as load capacity, load distribution, etc.) of the two conditions are directly compared, and the indicators such as the Euclidean distance or cosine similarity between the two conditions are calculated; for the similarity of the road environment, the parameters such as the road type and road surface condition of the two conditions are compared. After obtaining the load similarity and road similarity, the load similarity and road similarity are combined in a weighted manner to obtain a comprehensive condition similarity. Among them, the weights of the load similarity and the road similarity are determined according to the importance of the impact on the suspension performance. By analyzing the similarity between the test load and the road environment in other dynamic test conditions and the first test load and the first road environment, multiple condition similarities are obtained. After calculating the similarity of all working conditions, select several test conditions with the greatest similarity as the adjacent working conditions of the first dynamic test condition to form a neighboring test condition space. For example, set the number of working conditions to be selected, and select the working conditions with the highest similarity in descending order according to the number of working conditions set, or select all working conditions with a similarity greater than a preset similarity threshold. The selected adjacent working conditions constitute a local test space, namely, the adjacent test condition space. In the adjacent test condition space, the performance differences between the various working conditions are relatively small, and the comparability and continuity of the test results are good.

Subsequently, in the adjacent test condition space, a second test condition is randomly selected for testing according to the search probability, and an actual suspension test is performed on the selected second dynamic test condition, and its smoothness performance is evaluated to obtain a second smoothness score. At the same time, the second stiffness score of the second test condition is obtained through the stiffness score classifier, and the second modified smoothness score is obtained based on the second stiffness score and the second smoothness score. Then, taking the second dynamic test condition as the new benchmark, random search and testing are continued in its adjacent test condition space. Through iterative execution, a new modified smoothness score and stiffness score will be obtained for each iteration. When the preset number of searches is reached, the iteration stops. The modified smoothness scores and stiffness scores obtained in all iterations are summarized to obtain multiple modified smoothness scores and multiple stiffness scores.

Furthermore, the embodiment of the present application also includes:

According to the search probability of multiple selected dynamic test conditions in the search test process, multiple condition weights are allocated; according to the multiple condition weights, the multiple modified smoothness scores and the multiple stiffness scores are weighted and calculated to obtain a result smoothness score and a result stiffness score; it is judged whether the multiple modified smoothness scores and the multiple stiffness scores meet the preset smoothness score and the preset stiffness score, and the number of yes scores is counted to calculate the condition qualification rate; according to the condition qualification rate, the result smoothness score and the result stiffness score are modified and calculated to obtain the dynamic and static performance test results.

In a preferred embodiment, each dynamic test condition has a search probability, which reflects the frequency of the condition appearing on the actual road and the possibility of being selected for testing. The greater the search probability of the condition, the more important its test results will be in the final evaluation. Therefore, according to the search probability of each dynamic test condition, a corresponding weight is assigned to it, and multiple condition weights corresponding to multiple dynamic test conditions are obtained. Then, the modified smoothness score of each dynamic test condition is multiplied by its corresponding weight, and then summed to obtain the resulting smoothness score, and the stiffness score of each dynamic test condition is multiplied by its corresponding weight, and then summed to obtain the resulting stiffness score.

Subsequently, the preset smoothness score and the preset stiffness score are extracted as the criterion for measuring whether the performance of the air suspension meets the standard. Among them, the preset smoothness score and the preset stiffness score are determined according to factors such as the performance requirements of the whole vehicle. Then, the modified smoothness score and stiffness score of each dynamic test condition are judged whether they meet the preset smoothness score and the preset stiffness score. The number of working conditions that meet the preset smoothness score and the preset stiffness score is counted and divided by the total number of working conditions to obtain the working condition qualification rate, which reflects the excellent performance of the air suspension under various working conditions. After that, the difference between the working condition qualification rate and the qualification rate threshold is used to determine the scaling factor, and then the result smoothness score and the result stiffness score are multiplied by the scaling factor respectively to obtain the final dynamic and static performance test results. Among them, if the working condition qualification rate is lower than the qualification rate threshold, the dynamic and static performance test results will be reduced accordingly; conversely, if the working condition qualification rate is greater than the qualification rate threshold, the dynamic and static performance test results will be improved accordingly.

In summary, the method for testing the dynamic and static performance of an automobile air suspension provided in the embodiments of the present application has the following technical effects:

Using multiple test loads, static tests are performed on the automotive air suspension to be tested, multiple static stroke parameters under multiple test loads are obtained, and multiple static stroke change parameters are calculated to comprehensively evaluate the static characteristics of the air suspension under different load conditions, providing a basis for subsequent dynamic testing and comprehensive performance evaluation. Obtain multiple road environments for automotive air suspension, perform random searches under multiple test loads and multiple road environments, and obtain a first dynamic test condition including a first test load and a first road environment, wherein the search probability of multiple dynamic test conditions is set according to the occurrence rate of multiple test loads and multiple road environments, perform random searches, comprehensively consider the actual road conditions and vehicle load conditions, and obtain targeted and representative dynamic test conditions through random searches to improve the effectiveness and comprehensive coverage of the test. Under the first dynamic test condition, test the air suspension, obtain the first dynamic test result, and analyze and obtain the first smoothness score, and directly evaluate the smoothness of the suspension through dynamic testing to provide a basis for subsequent performance synthesis. According to the first stroke change parameter of the first test load, the first stiffness score is analyzed and obtained, and the first smoothness score is corrected and calculated to obtain the corrected first corrected smoothness score. The static characteristic test results are combined with the dynamic characteristic test results, and the smoothness score is corrected by the stiffness score to achieve a comprehensive evaluation of dynamic and static performance and improve the reliability and comprehensiveness of the test results. In the adjacent test condition space within the first dynamic test condition, the search test is continued, and after reaching the preset search times, multiple corrected smoothness scores and multiple stiffness scores are obtained. By expanding the adjacent condition space, the test conditions are further enriched and refined, and the precision and credibility of the test results are improved. According to the search probability of multiple selected dynamic test conditions, multiple modified smoothness scores and multiple stiffness scores are weightedly calculated to obtain the resulting smoothness score and the resulting stiffness score, and according to the pass rates of the multiple modified smoothness scores and the multiple stiffness scores, the condition pass rate is obtained, the resulting smoothness score and the resulting stiffness score are corrected to obtain the dynamic and static performance test results, and the condition pass rate is introduced on the basis of the score for correction to improve the reliability of the test results. At the same time, weights are given to different conditions through weighted calculation of the search probability to make the test results more in line with actual usage conditions, thereby achieving the technical effect of comprehensively covering the air suspension usage conditions and improving the test pertinence and effectiveness.

Embodiment 2, based on the same inventive concept as the method for testing the dynamic and static performance of an automobile air suspension in the aforementioned embodiment, as shown in FIG. 2 , the embodiment of the present application provides a system for testing the dynamic and static performance of an automobile air suspension, the system comprising:

The static test module 11 is used to perform a static test on the automobile air suspension to be tested using a plurality of test loads, obtain a plurality of static stroke parameters under the plurality of test loads, and calculate a plurality of static stroke change parameters;

A working condition search module 12 is used to obtain a plurality of road environments of the air suspension for the automobile, and to perform a random search in the plurality of test loads and the plurality of road environments to obtain a first dynamic test working condition including a first test load and a first road environment, wherein the search probability of the plurality of dynamic test working conditions is set according to the occurrence rates of the plurality of test loads and the plurality of road environments, and the random search is performed;

A dynamic test module 13 is used to test the air suspension under the first dynamic test condition to obtain a first dynamic test result and analyze and obtain a first ride comfort score;

The stiffness evaluation module 14 is used to analyze and obtain a first stiffness score according to a first stroke change parameter of a first test load, and to perform correction calculation on the first smoothness score to obtain a corrected first corrected smoothness score;

A neighboring search module 15, configured to continue searching the test in the neighboring test condition space in the first dynamic test condition, and obtain a plurality of modified ride comfort scores and a plurality of stiffness scores after reaching a preset number of searches;

The comprehensive evaluation module 16 is used to perform weighted calculation on the multiple modified smoothness scores and the multiple stiffness scores according to the search probabilities of the multiple selected dynamic test conditions to obtain the result smoothness score and the result stiffness score, and obtain the condition qualification rate according to the qualification rates of the multiple modified smoothness scores and the multiple stiffness scores, and to correct the result smoothness score and the result stiffness score to obtain the dynamic and static performance test results.

Furthermore, the static test module 11 includes the following execution steps:

Collect various loads of the automotive air suspension during operation and obtain various test loads;

Using the multiple test loads, a static test is performed on the automotive air suspension to be tested to obtain multiple static travel parameters;

A plurality of static stroke variation parameters are calculated according to the plurality of static stroke parameters and a standard stroke parameter of the air suspension.

Furthermore, the operating condition search module 12 includes the following execution steps:

Collect various road environments during the working process of automobile air suspension;

Collecting the occurrence ratios of the multiple test loads and the multiple road environments in the working project as multiple road occurrence rates and multiple load occurrence rates;

Traversing and combining the multiple test loads and the multiple road environments to obtain multiple dynamic test conditions, and calculating and setting multiple search probabilities of the multiple dynamic test conditions according to the multiple road appearance rates and the multiple load appearance rates;

According to the multiple search probabilities, a first dynamic test condition is obtained by randomly searching among the multiple dynamic test conditions.

Furthermore, the dynamic test module 13 includes the following execution steps:

Under the first dynamic test condition, testing the air suspension to obtain a first dynamic test result, wherein the first dynamic test result includes a stroke change rate;

According to the test data records of the air suspension, a sample dynamic test result set and a sample smoothness score set are collected;

The sample dynamic test result set and the sample smoothness score set are used to construct a smoothness analyzer, and the first dynamic test result is input and analyzed to obtain a first smoothness score.

Furthermore, the stiffness evaluation module 14 includes the following execution steps:

According to the static test data record of the air suspension, a sample travel change parameter set and a sample stiffness score set are collected;

Using the sample stroke change parameter set and the sample stiffness score set, constructing a stiffness score classifier, classifying the first stroke change parameter, and obtaining a first stiffness score;

A ride comfort correction coefficient is generated according to a ratio of the first stiffness score to a preset stiffness score, and a correction calculation is performed on the first ride comfort score to obtain a first corrected ride comfort score.

Furthermore, the neighboring search module 15 includes the following execution steps:

According to the first test load and the first road environment in the first dynamic test condition, analyzing the similarity between the test load and the road environment in other dynamic test conditions and the first test load and the first road environment, and performing weighted calculation to obtain multiple condition similarities;

Select similar dynamic test conditions corresponding to the largest number of conditions similarities, and construct a neighboring test condition space within the first dynamic test condition;

In the adjacent test condition space, a random search is performed according to the search probability of a plurality of similar dynamic test conditions to obtain a second dynamic test condition;

Under the second dynamic test condition, the air suspension is tested to obtain a second dynamic test result, and a second ride comfort score is obtained by analysis;

Continue to construct the adjacent test condition space within the second dynamic test condition, and continue to perform the search test until a preset number of searches is reached to obtain multiple modified smoothness scores and multiple stiffness scores.

Furthermore, the comprehensive evaluation module 16 includes the following execution steps:

According to the search probabilities of multiple selected dynamic test conditions during the search test process, multiple condition weights are allocated;

According to the multiple working condition weights, weighted calculation is performed on the multiple modified smoothness scores and the multiple stiffness scores to obtain a result smoothness score and a result stiffness score;

Determining whether the plurality of modified ride comfort scores and the plurality of stiffness scores meet a preset ride comfort score and a preset stiffness score, counting the number of scores that are determined to be yes, and calculating a qualified rate of the working condition;

According to the working condition qualification rate, the result smoothness score and the result stiffness score are corrected and calculated to obtain the dynamic and static performance test results.

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.

Furthermore, the first or second mentioned above may not only represent an order relationship, but may also represent a specific concept, and/or refer to the selection of multiple elements individually or in whole. Obviously, those skilled in the art may 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 equivalents, the present application intends to include these changes and variations.

Claims (8)

1. The dynamic and static performance test method of the air suspension for the automobile is characterized by comprising the following steps of:

Performing static test on the air suspension for the automobile to be tested by adopting various test loads to obtain a plurality of static travel parameters under the various test loads, and calculating to obtain a plurality of static travel variation parameters;

acquiring multiple road environments of an air suspension for an automobile, performing random search on the multiple test loads and the multiple road environments to obtain a first dynamic test working condition comprising a first test load and the first road environment, wherein the search probability of the multiple dynamic test working conditions is set according to the occurrence rate of the multiple test loads and the multiple road environments, and performing random search;

Under the first dynamic test working condition, testing the air suspension to obtain a first dynamic test result, and analyzing to obtain a first smoothness score;

Analyzing to obtain a first stiffness score according to a first travel variation parameter of a first test load, and performing correction calculation on the first smoothness score to obtain a corrected first corrected smoothness score;

In the adjacent test working condition space in the first dynamic test working condition, continuing to search and test, and after the preset search times are reached, obtaining a plurality of correction smoothness scores and a plurality of rigidity scores;

And weighting and calculating the plurality of correction smoothness scores and the plurality of rigidity scores according to the search probabilities of the plurality of selected dynamic test conditions to obtain a result smoothness score and a result rigidity score, obtaining a condition qualification rate according to the plurality of correction smoothness scores and the qualification rates of the plurality of rigidity scores, and correcting the result smoothness score and the result rigidity score to obtain a dynamic and static performance test result.

2. The method for testing the dynamic and static performance of the air suspension for the automobile according to claim 1, wherein a plurality of test loads are adopted, the air suspension for the automobile to be tested is subjected to static test, a plurality of static stroke parameters under the plurality of test loads are obtained, and a plurality of static stroke variation parameters are obtained through calculation, and the method comprises the steps of:

collecting various loads of an air suspension for an automobile in the working process to obtain various test loads;

Performing static test on the air suspension for the automobile to be tested by adopting the plurality of test loads to obtain a plurality of static stroke parameters;

and calculating to obtain a plurality of static travel variation parameters according to the plurality of static travel parameters and the standard travel parameters of the air suspension.

3. The method for testing dynamic and static performance of an air suspension for an automobile according to claim 1, wherein obtaining a plurality of road environments of the air suspension for an automobile, performing random search on the plurality of test loads and the plurality of road environments, obtaining a first dynamic test condition including a first test load and a first road environment, comprises:

Collecting various road environments of an air suspension for an automobile in the working process;

collecting the occurrence ratios of the various test loads and the various road environments in the working engineering as a plurality of road occurrence ratios and a plurality of load occurrence ratios;

Traversing and combining the multiple test loads and multiple road environments to obtain multiple dynamic test working conditions, and calculating multiple search probabilities for setting the multiple dynamic test working conditions according to the multiple road occurrence rates and the multiple load occurrence rates;

and randomly searching in the multiple dynamic test working conditions according to the multiple search probabilities to obtain a first dynamic test working condition.

4. The method for testing dynamic and static performance of an air suspension for an automobile according to claim 1, wherein under the first dynamic test condition, testing the air suspension to obtain a first dynamic test result, and analyzing to obtain a first smoothness score, comprises:

under the first dynamic test working condition, testing the air suspension to obtain a first dynamic test result, wherein the first dynamic test result comprises a stroke change rate;

collecting a sample dynamic test result set and a sample smoothness scoring set according to test data records of the air suspension;

And constructing a smoothness analyzer by adopting the sample dynamic test result set and the sample smoothness score set, and carrying out input analysis on the first dynamic test result to obtain a first smoothness score.

5. The method for testing dynamic and static performance of an air suspension for an automobile according to claim 1, wherein analyzing to obtain a first stiffness score according to a first travel variation parameter of a first test load, and performing correction calculation on the first smoothness score to obtain a corrected first corrected smoothness score, comprises:

collecting a sample stroke change parameter set and a sample rigidity scoring set according to the static test data record of the air suspension;

constructing a rigidity grading classifier by adopting the sample stroke change parameter set and the sample rigidity grading set, classifying the first stroke change parameter, and obtaining a first rigidity grade;

And generating a ride comfort correction coefficient according to the ratio of the first stiffness score to a preset stiffness score, and carrying out correction calculation on the first ride comfort score to obtain a first corrected ride comfort score.

6. The method for testing dynamic and static performance of an air suspension for an automobile according to claim 1, wherein the searching test is continued in the adjacent test working condition space in the first dynamic test working condition, and after reaching the preset searching times, a plurality of correction smoothness scores and a plurality of rigidity scores are obtained, comprising:

Analyzing the similarity between the test load and the road environment in other dynamic test working conditions and the first test load and the first road environment according to the first test load and the first road environment in the first dynamic test working conditions, and weighting and calculating to obtain a plurality of working condition similarity;

Selecting similar dynamic test working conditions corresponding to the maximum similarity of a plurality of working conditions, and constructing adjacent test working condition spaces in the first dynamic test working conditions;

in the adjacent test working condition space, performing random search according to the search probabilities of a plurality of similar dynamic test working conditions to obtain a second dynamic test working condition;

Under the second dynamic test working condition, testing the air suspension to obtain a second dynamic test result, and analyzing to obtain a second smoothness score;

and continuously constructing adjacent test working condition spaces in the second dynamic test working condition, and continuously performing search test until the preset search times are reached, so as to obtain a plurality of correction smoothness scores and a plurality of rigidity scores.

7. The method for testing dynamic and static performance of an air suspension for an automobile according to claim 1, wherein the steps of weighting and calculating the plurality of correction smoothness scores and the plurality of rigidity scores according to the search probabilities of a plurality of selected dynamic test conditions to obtain a result smoothness score and a result rigidity score, obtaining a condition qualification rate according to the qualification rates of the plurality of correction smoothness scores and the plurality of rigidity scores, and correcting the result smoothness score and the result rigidity score comprise:

distributing and obtaining a plurality of working condition weights according to the searching probability of a plurality of selected dynamic test working conditions in the searching test process;

Weighting and calculating the correction ride scores and the rigidity scores according to the working condition weights to obtain a result ride score and a result rigidity score;

judging whether the plurality of correction smoothness scores and the plurality of rigidity scores meet the preset smoothness scores and the preset rigidity scores, counting the number of the correction smoothness scores and the rigidity scores which are judged to be yes, and calculating to obtain the qualification rate of the working condition;

and correcting and calculating the result smoothness score and the result rigidity score according to the working condition qualification rate to obtain a dynamic and static performance test result.

8. A dynamic and static performance test system for an air suspension for an automobile, for implementing the dynamic and static performance test method for an air suspension for an automobile according to any one of claims 1 to 7, the system comprising:

The static test module is used for carrying out static test on the automobile air suspension to be tested by adopting various test loads, obtaining a plurality of static travel parameters under the various test loads, and calculating to obtain a plurality of static travel variation parameters;

The working condition searching module is used for acquiring various road environments of the air suspension for the automobile, randomly searching the various test loads and the various road environments to acquire a first dynamic test working condition comprising a first test load and the first road environment, setting the searching probability of the various dynamic test working conditions according to the occurrence rate of the various test loads and the various road environments, and randomly searching;

The dynamic test module is used for testing the air suspension under the first dynamic test working condition to obtain a first dynamic test result and analyzing to obtain a first smoothness score;

The stiffness evaluation module is used for analyzing and obtaining a first stiffness score according to a first travel variation parameter of a first test load, and carrying out correction calculation on the first smoothness score to obtain a corrected first correction smoothness score;

the proximity search module is used for continuing the search test in a proximity test working condition space in the first dynamic test working condition and obtaining a plurality of correction smoothness scores and a plurality of rigidity scores after reaching the preset search times;

The comprehensive evaluation module is used for carrying out weighted calculation on the plurality of correction smoothness scores and the plurality of rigidity scores according to the search probabilities of the plurality of selected dynamic test working conditions to obtain a result smoothness score and a result rigidity score, obtaining a working condition qualification rate according to the plurality of correction smoothness scores and the qualification rates of the plurality of rigidity scores, and correcting the result smoothness score and the result rigidity score to obtain a dynamic and static performance test result.