An artificial intelligence electric vehicle controller PCB board performance test system

Abstract

The present invention belongs to the technical field of PCB board performance testing, and specifically discloses an artificial intelligence electric vehicle controller PCB board performance testing system. The system includes: a test object layout module, a test scenario setting module, a test item setting module, a test start tracking module, a performance test analysis module and a performance report generation feedback module. The present invention sets a load test scenario, a temperature test scenario and a path test scenario, and performs performance test analysis and feedback of acceleration, deceleration and braking operations from three dimensions of sensitivity, reliability and smoothness, thereby realizing a multi-dimensional evaluation of power performance, breaking the current deficiency of only considering the power accuracy level, ensuring the comprehensiveness of the performance test results, and improving the accuracy and reliability of the test results. At the same time, it can also enable the potential power problems of the electric vehicle controller PCB to be discovered and solved in a timely manner, thereby reducing the impact on the overall performance of the vehicle.

Description

Technical Field

[0001] The invention belongs to the technical field of PCB board performance testing and relates to an artificial intelligence electric vehicle controller PCB board performance testing system. Background Art

[0002] The PCB board of the electric vehicle controller is used to control the motor, battery management system and other functions of the electric vehicle. With the continuous advancement of electric vehicle technology, the requirements for the accuracy and other performance of the electric vehicle controller PCB board are getting higher and higher, which highlights the importance and necessity of performance testing of the electric vehicle controller PCB board.

[0003] At present, the power performance test of the electric vehicle controller PCB board is mainly carried out by simulating the accuracy of acceleration, deceleration and braking under different temperatures, humidity and road conditions, so as to judge the power performance of the electric vehicle controller PCB board. Obviously, there are still the following deficiencies: 1. The test scenario setting is relatively limited, and no comprehensive test is carried out in combination with the load, which makes the test coverage insufficient, and thus cannot improve the representativeness and rationality of the test results.

[0004] 2. The current test base is on the equipment side, that is, the accuracy of the acceleration, deceleration and braking responses of the electric vehicle controller PCB board is analyzed, without considering the user experience, that is, the smoothness of the acceleration, deceleration and braking processes is not further tested and evaluated.

[0005] 3. The dimension of power performance evaluation is relatively single. Currently, it only considers the power accuracy level, and does not conduct a comprehensive analysis of the sensitivity, reliability, and smoothness during the power test. This leads to the one-sidedness of the performance test results, reduces the accuracy and reliability of the test results, and may cause potential problems to not be discovered and resolved in a timely manner, thus affecting the overall performance of the vehicle. Summary of the invention

[0006] In view of this, in order to solve the problems raised in the above background technology, an artificial intelligence electric vehicle controller PCB board performance testing system is now proposed.

[0007] The purpose of the present invention can be achieved through the following technical solutions: The present invention provides an artificial intelligence electric vehicle controller PCB board performance test system, the system includes: a test object layout module, which is used to record the electric vehicle controller PCB board as a target test object and connect the test line to the target test object.

[0008] The test scenario setting module is used to set the test scenario corresponding to the target test object. The test scenarios include load test scenarios, path test scenarios and temperature test scenarios.

[0009] The test item setting module is used to set acceleration operation, deceleration operation and braking operation as each test item.

[0010] The test start tracking module is used to import the target test object into each test scenario, perform the test of each test item under each test scenario, and record the test data of each test item under each test scenario.

[0011] The performance test analysis module is used to perform performance test analysis based on the test data of each test item of the target test object in each test scenario to obtain performance test analysis results.

[0012] S1. Perform speed sensitivity analysis on the target test object to obtain the power sensitivity index and brake sensitivity index of the target test object, and record them as and .

[0013] S2. Perform speed reliability analysis on the target test object to obtain the power reliability index and braking reliability index of the target test object, and record them as and .

[0014] S3. Perform speed smoothness analysis on the target test object to obtain the power smoothness index and brake smoothness index of the target test object, and record them as and , and then , , , , and As a result of performance test analysis.

[0015] The performance report generation feedback module is used to generate a performance test analysis report of the target test object according to the performance test analysis results and provide feedback.

[0016] Furthermore, the speed sensitivity analysis of the target test object includes: extracting the test data of the acceleration test items under the load test scenario from the test data of each test item under each test scenario, and then extracting the number of acceleration tests under each applied load, the set acceleration time of each acceleration test and the actual recorded acceleration time.

[0017] The difference between the actual recorded acceleration time and the set acceleration time is recorded as the acceleration time difference, and the effective test ratio under each applied load is determined based on this, which is recorded as , is the applied load number, .

[0018] With the acceleration test order as the horizontal axis and the acceleration time difference as the vertical axis, a curve of the acceleration time under each applied load is constructed, from which the slope is extracted and used as the change rate of the test time difference, recorded as .

[0019] Statistical load test scenario acceleration sensitivity index , , and Set the The effective test ratio and time difference change rate of the reference under the applied load.

[0020] according to The analysis method is similar to that of the acceleration sensitivity index in the path test scenario and the acceleration sensitivity index in the temperature test scenario, and they are recorded as and , based on which the acceleration sensitivity index of the target test object is determined and recorded as .

[0021] According to the analysis method of the acceleration sensitivity index of the target test object, the deceleration sensitivity index and braking smoothness index of the target test object are obtained in the same way, and the deceleration sensitivity index of the target test object is recorded as , and then calculate the dynamic sensitivity index of the target test object.

[0022] Further, the confirming of the effective test ratio under each applied load includes: comparing the acceleration time difference of each acceleration test under each applied load with a set permissible acceleration time deviation.

[0023] If the acceleration time difference of a certain acceleration test under a certain applied load is less than or equal to the set permissible acceleration time deviation, the acceleration test under the applied load is recorded as a valid acceleration test.

[0024] The effective number of acceleration tests under each applied load is counted and compared with the number of acceleration tests under each applied load to obtain the effective test ratio under each applied load.

[0025] Further, the determination of the acceleration sensitivity index of the target test object includes: subtracting the acceleration sensitivity index in the load test scenario, the path test scenario, and the temperature test scenario from their set values, and counting the number of test scenarios with the difference greater than 0, recorded as .

[0026] like , then The acceleration sensitivity index used as the target test object.

[0027] like , then The acceleration sensitivity index used as the target test object.

[0028] Furthermore, the dynamic sensitivity index of the statistical target test object is specifically calculated as follows: , and Set the reference weight of acceleration sensitivity index and deceleration sensitivity index respectively. ,and .

[0029] Furthermore, the speed reliability analysis of the target test object includes: extracting the set acceleration value and the actual recorded acceleration value of each acceleration test under each applied load from the test data of the acceleration test item under the load test scenario.

[0030] The actual recorded acceleration value is subtracted from the set acceleration value, and the difference is recorded as the acceleration deviation value. The acceleration deviation value corresponding to each acceleration test under each applied load is compared with the set allowable acceleration deviation value.

[0031] An acceleration test in which the acceleration deviation value is less than or equal to the set permissible acceleration deviation value is recorded as a matching test.

[0032] The number of matching tests under each applied load is counted and compared with the number of accelerated tests under each applied load to obtain the test matching ratio under each applied load, which is recorded as .

[0033] Statistics of the acceleration reliability index under each applied load , , and The reference test matching ratio and acceleration sensitivity index are set respectively, and the acceleration reliability index under the load test scenario is confirmed.

[0034] The power reliability index and braking reliability index of the target test object are obtained by analyzing the power sensitivity index and braking sensitivity index of the target test object in the same way.

[0035] Furthermore, the confirmation of the acceleration reliability index in the load test scenario includes: combining each applied load in pairs to obtain each applied load group.

[0036] The acceleration loads in each applied load group are subtracted to obtain the acceleration load difference in each applied load group.

[0037] The acceleration reliability index difference of each applied load group is obtained by subtracting the acceleration reliability index of each applied load group.

[0038] The acceleration load difference of each applied load group is matched and compared with the reference acceleration reliability index difference for setting each acceleration load difference to obtain a matched reference acceleration reliability index difference.

[0039] If the reference acceleration reliability index difference of a certain applied load group is greater than the acceleration reliability index difference of the applied load group, the applied load group is recorded as a matching load group, the number of matching load groups is counted and compared with the number of applied load groups, and the ratio is recorded as the matching load ratio .

[0040] The maximum and minimum values ​​are extracted from the acceleration reliability index under each applied load and recorded as and , and the average acceleration reliability index is obtained by averaging, denoted as .

[0041] like ,Will As an acceleration reliability index in load testing scenarios, and They are the correction ratios corresponding to the reference matching load ratio and the unit compensation factor respectively.

[0042] like ,Will As an acceleration reliability index in load testing scenarios, It is the compensation ratio corresponding to the set unit compensation factor.

[0043] like ,Will As an acceleration reliability index in load testing scenarios.

[0044] Furthermore, the speed smoothness analysis of the target test object includes: extracting each acceleration time point under each applied load and the acceleration value corresponding to each acceleration time point from the test data of the acceleration test item under the load test scenario.

[0045] With the acceleration time point as the horizontal axis and the acceleration value as the vertical axis, the acceleration curve of each acceleration test under each applied load is constructed, and then the acceleration smoothness index of each acceleration test under each applied load is calculated, which is recorded as , Accelerated test sequence number, .

[0046] Set the acceleration smoothing evaluation compensation weight for each applied load , and then calculate the acceleration smoothness index under the load test scenario , , To speed up the number of tests, is the number of applied loads.

[0047] The power smoothness index and braking smoothness index of the target test object are obtained by analyzing the power sensitivity index and braking sensitivity index of the target test object in the same way.

[0048] Furthermore, the said counting the acceleration smoothness index of each acceleration test under each applied load comprises: extracting the number of fluctuation points from the acceleration curve of each acceleration test under each applied load, recorded as , and extract the horizontal distance and vertical distance between each fluctuation point, and then calculate the average horizontal distance and average vertical distance of each acceleration test under each applied load, which are recorded as and .

[0049] Statistics of acceleration smoothness index under each load test scenario , , , and They are the number of reference fluctuation points, horizontal distance and vertical distance respectively. Represents a natural constant.

[0050] Furthermore, the setting of the acceleration smoothness evaluation compensation weight under each applied load includes: taking the acceleration test order as the horizontal coordinate and the acceleration smoothness index as the vertical coordinate, constructing the acceleration smoothness index curve under each applied load, and locating the curve length above the average acceleration test smoothness index, recorded as , and the length of the smooth curve under each applied load is recorded as .

[0051] The variance of the acceleration smoothness index of each test under each applied load is calculated, and the calculation result is used as the acceleration smoothness difference index under each applied load, recorded as .

[0052] Statistical calculation of the acceleration smoothness evaluation compensation weight under each applied load , , and They are the acceleration smoothing difference index and the length ratio of the exceeding acceleration smoothing curve of the reference respectively.

[0053] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention effectively solves the problem of limited setting of current test scenarios by setting load test scenarios, temperature test scenarios and path test scenarios for testing, fully combines load and other test scenarios, realizes multi-scenario comprehensive testing of electric vehicle controller PCB boards, improves test coverage, and thereby improves the representativeness and rationality of test results.

[0054] (2) The present invention further refines the analysis of the acceleration smoothness, deceleration smoothness and braking smoothness under load test scenarios, temperature test scenarios and path test scenarios, thereby avoiding the deficiency that the current test foothold is only on the equipment side, and realizes further testing and evaluation of the smoothness of the acceleration, deceleration and braking processes of the electric vehicle controller PCB under different test scenarios, thereby fully considering the user side experience, and at the same time expanding the evaluation indicators of the electric vehicle controller PCB performance test, thereby improving the driving experience of subsequent users.

[0055] (3) The present invention sets load test scenarios, temperature test scenarios and path test scenarios, and performs performance test analysis and feedback of acceleration, deceleration and braking operations from three dimensions: sensitivity, reliability and smoothness. This realizes a multi-dimensional evaluation of power performance, breaks the current deficiency of only considering the power accuracy level, ensures the comprehensiveness of performance test results, improves the accuracy and reliability of test results, and on the other hand, enables the potential power problems of the electric vehicle controller PCB to be discovered and solved in a timely manner, and can also reduce the impact on the overall performance of the vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0057] Figure 1 It is a schematic diagram of the connection of each module of the system of the present invention. DETAILED DESCRIPTION

[0058] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] See also Figure 1 As shown, the present invention provides an artificial intelligence electric vehicle controller PCB board performance test system, the system includes: a test object layout module, a test scene setting module, a test item setting module, a test start tracking module, a performance test analysis module and a performance report generation feedback module.

[0060] In the above, the test start tracking module is connected with the test object layout module, the test scenario setting module, the test item setting module and the performance test analysis module respectively, and the performance test analysis module is also connected with the performance report generation feedback module.

[0061] The test object layout module is used to record the electric vehicle controller PCB board as a target test object and connect the test lines to the target test object.

[0062] It should be added that the specific connection method for connecting the test line of the target test object is: install the target test object on the test bench, and electrically connect the input end of the target test object with the output end of the test control terminal, and at the same time electrically connect the output end of the target test object with the input end of the test display terminal.

[0063] The test scenario setting module is used to set the test scenario corresponding to the target test object, and the test scenario includes a load test scenario, a path test scenario and a temperature test scenario.

[0064] The embodiment of the present invention performs testing by setting load test scenarios, temperature test scenarios and path test scenarios, thereby effectively solving the problem of limited current test scenario settings, fully combining load and other test scenarios, and realizing multi-scenario comprehensive testing of the electric vehicle controller PCB board, thereby improving the coverage of the test and further improving the representativeness and rationality of the test results.

[0065] The test item setting module is used to set acceleration operation, deceleration operation and braking operation as each test item.

[0066] The test start tracking module is used to import the target test object into each test scenario, perform the test of each test item in each test scenario, and record the test data of each test item in each test scenario.

[0067] The performance test analysis module is used to perform performance test analysis based on the test data of each test item of the target test object in each test scenario to obtain a performance test analysis result.

[0068] S1. Perform speed sensitivity analysis on the target test object to obtain the power sensitivity index and brake sensitivity index of the target test object, and record them as and .

[0069] It should be added that dynamic sensitivity refers to the vehicle's ability to respond quickly to the driver's input signal. This aspect of the evaluation includes the reaction speed of the electric vehicle and the dynamic performance of the vehicle under acceleration, deceleration, braking, etc. If the electric vehicle is slow to respond or not flexible enough, it may affect the driver's control and driving safety. Therefore, when conducting the performance test of the electric vehicle controller PCB board, it is necessary to analyze the speed sensitivity of the target test object.

[0070] S2. Perform speed reliability analysis on the target test object to obtain the power reliability index and braking reliability index of the target test object, and record them as and .

[0071] It should be added that power reliability refers to the stability and sustained performance of the system under various conditions. This aspect of the assessment includes stability during operation and whether the electric vehicle is susceptible to external environmental influences. If the electric vehicle is unstable under certain conditions or is susceptible to external interference, it may cause failures and safety hazards. Therefore, when conducting the performance test of the electric vehicle controller PCB board, it is necessary to conduct a speed reliability analysis of the target test object.

[0072] S3. Perform speed smoothness analysis on the target test object to obtain the power smoothness index and brake smoothness index of the target test object, and record them as and , and then , , , , and As a result of performance test analysis.

[0073] It should be added that power smoothness refers to the stability and smoothness of the vehicle during acceleration, deceleration, braking, etc. Smoothness analysis is performed because smooth acceleration, deceleration, and braking not only affect the user experience, but also directly affect driving safety. Therefore, a comprehensive analysis of the smoothness during acceleration, deceleration, and braking is performed to fully evaluate the safety hazards during acceleration, deceleration, and braking.

[0074] Exemplarily, the speed sensitivity analysis of the target test object includes: extracting the test data of the acceleration test items under the load test scenario from the test data of each test item under each test scenario, and then extracting the number of acceleration tests under each applied load, the set acceleration time of each acceleration test and the actual recorded acceleration time.

[0075] The difference between the actual recorded acceleration time and the set acceleration time is recorded as the acceleration time difference, and the effective test ratio under each applied load is determined based on this, which is recorded as , is the applied load number, .

[0076] Further, the confirming of the effective test ratio under each applied load includes: comparing the acceleration time difference of each acceleration test under each applied load with a set permissible acceleration time deviation.

[0077] If the acceleration time difference of a certain acceleration test under a certain applied load is less than or equal to the set permissible acceleration time deviation, the acceleration test under the applied load is recorded as a valid acceleration test.

[0078] The effective number of acceleration tests under each applied load is counted and compared with the number of acceleration tests under each applied load to obtain the effective test ratio under each applied load.

[0079] With the acceleration test order as the horizontal axis and the acceleration time difference as the vertical axis, a curve of the acceleration time under each applied load is constructed, from which the slope is extracted and used as the change rate of the test time difference, recorded as .

[0080] Statistical load test scenario acceleration sensitivity index , , and Set the The effective test ratio and time difference change rate of the reference under the applied load.

[0081] It should be added that the effective test ratio is specifically set according to the total number of tests. For the convenience of analysis, when the total number of tests is specifically set to 20 times, the effective test ratio can be specifically set to .

[0082] according to The analysis method is similar to that of the acceleration sensitivity index in the path test scenario and the acceleration sensitivity index in the temperature test scenario, and they are recorded as and , based on which the acceleration sensitivity index of the target test object is determined and recorded as .

[0083] Further, the determination of the acceleration sensitivity index of the target test object includes: subtracting the acceleration sensitivity index in the load test scenario, the path test scenario, and the temperature test scenario from their set values, and counting the number of test scenarios with the difference greater than 0, recorded as .

[0084] like , then The acceleration sensitivity index used as the target test object.

[0085] like , then The acceleration sensitivity index used as the target test object.

[0086] According to the analysis method of the acceleration sensitivity index of the target test object, the deceleration sensitivity index and braking smoothness index of the target test object are obtained in the same way, and the deceleration sensitivity index of the target test object is recorded as , and then calculate the dynamic sensitivity index of the target test object.

[0087] Furthermore, the dynamic sensitivity index of the statistical target test object is specifically calculated as follows: , and Set the reference weight of acceleration sensitivity index and deceleration sensitivity index respectively. ,and .

[0088] It should be added that the reference weights of the relevant sensitivity indexes are set for the main purpose of safety. Therefore, the weight of deceleration sensitivity is greater than the weight of acceleration sensitivity. The values ​​of the acceleration sensitivity index reference weight and the deceleration sensitivity index reference weight are both greater than 0 and less than 1. Specifically, for the convenience of analysis, The value can be 0.45. The value can be 0.55.

[0089] Exemplarily, the speed reliability analysis of the target test object includes: extracting the set acceleration value and the actual recorded acceleration value of each acceleration test under each applied load from the test data of the acceleration test item under the load test scenario.

[0090] The actual recorded acceleration value is subtracted from the set acceleration value, and the difference is recorded as the acceleration deviation value. The acceleration deviation value corresponding to each acceleration test under each applied load is compared with the set allowable acceleration deviation value.

[0091] An acceleration test in which the acceleration deviation value is less than or equal to the set permissible acceleration deviation value is recorded as a matching test.

[0092] The number of matching tests under each applied load is counted and compared with the number of accelerated tests under each applied load to obtain the test matching ratio under each applied load, which is recorded as .

[0093] Statistics of the acceleration reliability index under each applied load , , and The reference test matching ratio and acceleration sensitivity index are set respectively, and the acceleration reliability index under the load test scenario is confirmed.

[0094] Furthermore, the confirmation of the acceleration reliability index in the load test scenario includes: combining each applied load in pairs to obtain each applied load group.

[0095] The acceleration loads in each applied load group are subtracted to obtain the acceleration load difference in each applied load group.

[0096] The acceleration reliability index difference of each applied load group is obtained by subtracting the acceleration reliability index of each applied load group.

[0097] The acceleration load difference of each applied load group is matched and compared with the reference acceleration reliability index difference for setting each acceleration load difference to obtain a matched reference acceleration reliability index difference.

[0098] If the reference acceleration reliability index difference of a certain applied load group is greater than the acceleration reliability index difference of the applied load group, the applied load group is recorded as a matching load group, the number of matching load groups is counted and compared with the number of applied load groups, and the ratio is recorded as the matching load ratio .

[0099] It should be added that when the acceleration reliability index difference of a certain applied load group is less than the reference acceleration reliability index difference, it indicates that the difference between the acceleration reliability indices corresponding to the two applied loads is small, which further indicates that the acceleration reliability of the applied load group is relatively stable, so the applied load group is regarded as a matching load group.

[0100] The maximum and minimum values ​​are extracted from the acceleration reliability index under each applied load and recorded as and , and the average acceleration reliability index is obtained by averaging, denoted as .

[0101] like ,Will As an acceleration reliability index in load testing scenarios, and They are the correction ratios corresponding to the reference matching load ratio and the unit compensation factor respectively.

[0102] It should be added that when the matching load ratio is less than the reference matching load ratio, it indicates that the acceleration reliability index under the load test scenario tends to be less than Direction, that is, When the acceleration reliability index under load test scenarios is used, the selected result may be greater than the actual test result. , a reduction correction is needed.

[0103] It should be explained that using the minimum acceleration reliability index to represent the acceleration reliability index in the load test scenario is relatively extreme. When performing multiple load tests, the error of selecting the worst result as the final result is relatively large. and The difference between the two is used as the upper limit of the compensation acceleration reliability index, and according to and The compensation factor is set according to the difference of the value of the acceleration reliability index, and the corresponding compensation ratio under the unit compensation factor is set at the same time to improve the rationality and reliability of the confirmation of the value of the acceleration reliability index in the load test scenario. is the compensation factor, and it is negative compensation.

[0104] like ,Will As an acceleration reliability index in load testing scenarios, It is the compensation ratio corresponding to the set unit compensation factor.

[0105] It should be added that when the matching load ratio is greater than the reference matching load ratio, it indicates that the acceleration reliability index under the load test scenario tends to be greater than Direction, that is, When the acceleration reliability index under load test scenarios is used, the selected result may be smaller than the actual test result. , additional compensation is needed.

[0106] It should be explained that using the maximum acceleration reliability index to represent the acceleration reliability index in the load test scenario is relatively extreme. When performing multiple load tests, the error of selecting the best result as the final result is relatively large. and The difference between the two is used as the upper limit of the compensation acceleration reliability index, and according to and The compensation factor is set according to the difference between the values ​​of the acceleration reliability index and the corresponding compensation ratio under the unit compensation factor, so as to improve the rationality and reliability of the confirmation of the acceleration reliability index value under the load test scenario. is the compensation factor, and it is positive compensation.

[0107] like ,Will As an acceleration reliability index in load testing scenarios.

[0108] The power reliability index and braking reliability index of the target test object are obtained by analyzing the power sensitivity index and braking sensitivity index of the target test object in the same way.

[0109] Exemplarily, the speed smoothness analysis of the target test object includes: extracting each acceleration time point under each applied load and the acceleration value corresponding to each acceleration time point from the test data of the acceleration test item under the load test scenario.

[0110] With the acceleration time point as the horizontal axis and the acceleration value as the vertical axis, the acceleration curve of each acceleration test under each applied load is constructed, and then the acceleration smoothness index of each acceleration test under each applied load is calculated, which is recorded as , Accelerated test sequence number, .

[0111] Furthermore, the said counting the acceleration smoothness index of each acceleration test under each applied load comprises: extracting the number of fluctuation points from the acceleration curve of each acceleration test under each applied load, recorded as , and extract the horizontal distance and vertical distance between each fluctuation point, and then calculate the average horizontal distance and average vertical distance of each acceleration test under each applied load, which are recorded as and .

[0112] It should be supplemented that the fluctuation points refer to peak points or valley points in the curve.

[0113] Statistics of acceleration smoothness index under each load test scenario , , , and They are the number of reference fluctuation points, horizontal distance and vertical distance respectively. Represents a natural constant.

[0114] Set the acceleration smoothing evaluation compensation weight for each applied load , and then calculate the acceleration smoothness index under the load test scenario , , To speed up the number of tests, is the number of applied loads.

[0115] Furthermore, the setting of the acceleration smoothness evaluation compensation weight under each applied load includes: taking the acceleration test order as the abscissa and the acceleration smoothness index as the ordinate, constructing a smoothness index curve under each applied load, and locating the curve length above the average acceleration test smoothness index, recorded as , and the length of the smooth curve under each applied load is recorded as .

[0116] The variance of the acceleration smoothness index of each test under each applied load is calculated, and the calculation result is used as the acceleration smoothness difference index under each applied load, recorded as .

[0117] Statistical calculation of the acceleration smoothness evaluation compensation weight under each applied load , , and They are the acceleration smoothing difference index and the length ratio of the exceeding acceleration smoothing curve of the reference respectively.

[0118] The power smoothness index and braking smoothness index of the target test object are obtained by analyzing the power sensitivity index and braking sensitivity index of the target test object in the same way.

[0119] The embodiments of the present invention further refine the analysis of acceleration smoothness, deceleration smoothness and braking smoothness under load test scenarios, temperature test scenarios and path test scenarios, thereby avoiding the deficiency that the current test is based only on the equipment side, and achieving further testing and evaluation of the smoothness of acceleration, deceleration and braking processes of the electric vehicle controller PCB under different test scenarios, thereby fully considering the user experience, and at the same time expanding the evaluation indicators of the electric vehicle controller PCB performance test, thereby improving the driving experience of subsequent users.

[0120] The performance report generation feedback module is used to generate a performance test analysis report of the target test object according to the performance test analysis result and provide feedback.

[0121] The embodiment of the present invention sets load test scenarios, temperature test scenarios and path test scenarios, and performs performance test analysis and feedback of acceleration, deceleration and braking operations from three dimensions of sensitivity, reliability and smoothness, thereby realizing a multi-dimensional evaluation of power performance, breaking the current deficiency of only considering the power accuracy level, ensuring the comprehensiveness of performance test results, improving the accuracy and reliability of test results, and on the other hand, enabling potential power problems of the electric vehicle controller PCB to be discovered and resolved in a timely manner, and also reducing the impact on the overall performance of the vehicle.

[0122] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. An artificial intelligence electric vehicle controller PCB board performance test system, characterized by: The system includes: A test object layout module is used to record the electric vehicle controller PCB board as a target test object and connect the test lines to the target test object; A test scenario setting module is used to set the test scenario corresponding to the target test object. The test scenario includes a load test scenario, a path test scenario, and a temperature test scenario. A test item setting module, used to set acceleration operation, deceleration operation and braking operation as each test item; The test start tracking module is used to import the target test object into each test scenario, perform the test of each test item in each test scenario, and record the test data of each test item in each test scenario; The performance test analysis module is used to perform performance test analysis based on the test data of each test item of the target test object in each test scenario to obtain the performance test analysis results; S1. Perform speed sensitivity analysis on the target test object to obtain the power sensitivity index and brake sensitivity index of the target test object, and record them as and ; S2. Perform speed reliability analysis on the target test object to obtain the power reliability index and braking reliability index of the target test object, and record them as and ; S3. Perform speed smoothness analysis on the target test object to obtain the power smoothness index and brake smoothness index of the target test object, and record them as and , and then , , , , and As a result of performance test analysis; The performance report generation feedback module is used to generate a performance test analysis report of the target test object according to the performance test analysis results and provide feedback; The speed smoothness analysis of the target test object includes: Extracting each acceleration time point under each applied load and the acceleration value corresponding to each acceleration time point from the test data of the acceleration test item under the load test scenario; With the acceleration time point as the horizontal axis and the acceleration value as the vertical axis, the acceleration curve of each acceleration test under each applied load is constructed, and then the acceleration smoothness index of each acceleration test under each applied load is calculated, which is recorded as , is the applied load number, , Accelerated test sequence number, ; Set the acceleration smoothing evaluation compensation weight for each applied load , and then calculate the acceleration smoothness index under the load test scenario , , To speed up the number of tests, is the number of applied loads; The power smoothness index and the braking smoothness index of the target test object are obtained by analyzing the power sensitivity index and the braking sensitivity index of the target test object in the same way; The statistical acceleration smoothness index of each acceleration test under each applied load includes: The number of fluctuation points is extracted from the acceleration curve of each acceleration test under each applied load and recorded as , and extract the horizontal distance and vertical distance between each fluctuation point, and then calculate the average horizontal distance and average vertical distance of each acceleration test under each applied load, which are recorded as and ; Statistics of acceleration smoothness index under each load test scenario , , , and They are the number of reference fluctuation points, horizontal distance and vertical distance respectively. represents a natural constant; The step of setting the acceleration smoothness evaluation compensation weight under each applied load includes: With the acceleration test order as the horizontal axis and the acceleration smoothness index as the vertical axis, a smoothness index curve under each applied load is constructed, and the length of the curve above the average acceleration test smoothness index is located, which is recorded as , and the length of the smooth curve under each applied load is recorded as ; The variance of the acceleration smoothness index of each test under each applied load is calculated, and the calculation result is used as the acceleration smoothness difference index under each applied load, recorded as ; Statistical calculation of the acceleration smoothness evaluation compensation weight under each applied load , , and They are the acceleration smoothing difference index and the length ratio of the exceeding acceleration smoothing curve of the reference respectively.

2. According to claim 1, an artificial intelligence electric vehicle controller PCB board performance test system is characterized in that: The speed sensitivity analysis of the target test object comprises: Extract the test data of the acceleration test items under the load test scenario from the test data of each test item under each test scenario, and then extract the number of acceleration tests under each applied load, the set acceleration time of each acceleration test, and the actual recorded acceleration time; The difference between the actual recorded acceleration time and the set acceleration time is recorded as the acceleration time difference, and the effective test ratio under each applied load is determined based on this, which is recorded as , is the applied load number, ; With the acceleration test order as the horizontal axis and the acceleration time difference as the vertical axis, a curve of the acceleration time under each applied load is constructed, from which the slope is extracted and used as the change rate of the test time difference, recorded as ; Statistical load test scenario acceleration sensitivity index , , and Set the The effective test ratio and time difference change rate of the reference under the applied load; according to The analysis method is similar to that of the acceleration sensitivity index in the path test scenario and the acceleration sensitivity index in the temperature test scenario, and they are recorded as and , based on which the acceleration sensitivity index of the target test object is determined and recorded as ; According to the analysis method of the acceleration sensitivity index of the target test object, the deceleration sensitivity index and braking smoothness index of the target test object are obtained in the same way, and the deceleration sensitivity index of the target test object is recorded as , and then calculate the dynamic sensitivity index of the target test object.

3. The artificial intelligence electric vehicle controller PCB board performance test system according to claim 2 is characterized in that: The confirmation of the effective test ratio under each applied load includes: Compare the acceleration time difference of each acceleration test under each applied load with the set permissible acceleration time deviation; If the acceleration time difference of a certain acceleration test under a certain applied load is less than or equal to the set permissible acceleration time deviation, the acceleration test under the applied load is recorded as a valid acceleration test; The effective number of acceleration tests under each applied load is counted and compared with the number of acceleration tests under each applied load to obtain the effective test ratio under each applied load.

4. The artificial intelligence electric vehicle controller PCB board performance test system according to claim 2, characterized in that: The confirmation of the acceleration sensitivity index of the target test object includes: The acceleration sensitivity index in the load test scenario, the path test scenario, and the temperature test scenario are subtracted from their set values, and the number of test scenarios where the difference is greater than 0 is counted and recorded as ; like , then The acceleration sensitivity index as the target test object; like , then The acceleration sensitivity index used as the target test object.

5. The artificial intelligence electric vehicle controller PCB board performance test system according to claim 2 is characterized in that: The dynamic sensitivity index of the statistical target test object is specifically formulated as follows: , and Set the reference weight of acceleration sensitivity index and deceleration sensitivity index respectively. ,and .

6. The artificial intelligence electric vehicle controller PCB board performance test system according to claim 2, characterized in that: The speed reliability analysis of the target test object includes: Extracting the set acceleration value and the actual recorded acceleration value of each acceleration test under each applied load from the test data of the acceleration test item under the load test scenario; The actual recorded acceleration value is subtracted from the set acceleration value, and the difference is recorded as the acceleration deviation value. The acceleration deviation value corresponding to each acceleration test under each applied load is compared with the set permissible acceleration deviation value; An acceleration test in which the acceleration deviation value is less than or equal to the set permissible acceleration deviation value is recorded as a coincidence test; The number of matching tests under each applied load is counted and compared with the number of accelerated tests under each applied load to obtain the test matching ratio under each applied load, which is recorded as ; Statistics of the acceleration reliability index under each applied load , , and Set the reference test matching ratio and acceleration sensitivity index respectively, and confirm the acceleration reliability index under the load test scenario; The power reliability index and braking reliability index of the target test object are obtained by analyzing the power sensitivity index and braking sensitivity index of the target test object in the same way.

7. The artificial intelligence electric vehicle controller PCB board performance test system according to claim 6 is characterized in that: The acceleration reliability index under the confirmed load test scenario includes: Combining each applied load in pairs to obtain each applied load group; Subtract each acceleration load in each applied load group to obtain the acceleration load difference in each applied load group; Subtracting the acceleration reliability index under each applied load in each applied load group to obtain the acceleration reliability index difference of each applied load group; Matching and comparing the acceleration load difference of each applied load group with the reference acceleration reliability index difference for setting each acceleration load difference to obtain a matched reference acceleration reliability index difference; If the reference acceleration reliability index difference of a certain applied load group is greater than the acceleration reliability index difference of the applied load group, the applied load group is recorded as a matching load group, the number of matching load groups is counted and compared with the number of applied load groups, and the ratio is recorded as the matching load ratio ; The maximum and minimum values ​​are extracted from the acceleration reliability index under each applied load and recorded as and , and the average acceleration reliability index is obtained by averaging, denoted as ; like ,Will As an acceleration reliability index in load testing scenarios, and They are respectively the set reference matching load ratio and the correction ratio corresponding to the unit compensation factor; like ,Will As an acceleration reliability index in load testing scenarios, The compensation ratio corresponding to the set unit compensation factor; like ,Will As an acceleration reliability index in load testing scenarios.

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