Vehicle commissioning detection system

Abstract

The application discloses a kind of vehicle debugging detection systems, including background management system, PAD operating system and data acquisition system, the data acquisition system includes T-Box, external sensor and detection controller, the PAD operating system is issued debugging detection instruction to vehicle body and detection controller by the T-Box of data acquisition system, after receiving debugging detection instruction, vehicle body sends all state data to T-Box, while detection controller sends the information collected by external sensor to T-Box, T-Box transmits the detection data received to PAD operating system, PAD operating system obtains detection item information from background management system, according to the detection data obtained in real time, PAD operating system completes detection and uploads detection data to background management system, the present application has the advantages of being able to assist debugging detection personnel to efficiently complete debugging detection work, improve personnel interchangeability, automatic detection qualified rate, paperless office, process data analysis storage and the like.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle debugging detection, in particular to a vehicle debugging detection system. BACKGROUND

[0002] With the increasing types and quantities of special vehicles in airports, the existing product debugging detection stage has the following problems: first, the experience of the debugging detection personnel is highly dependent, and the personal technical level of the debugging detection personnel is strictly required; second, the debugging detection personnel between different projects have poor interchangeability, and a large number of debugging detection personnel need to be equipped, increasing the labor cost; third, the debugging detection process is manually measured, and the measurement results will have certain deviations due to different manual reaction speeds and tool usage methods, affecting the debugging consistency; fourth, the existing debugging detection report is mainly paper-based and manually filled, which is not conducive to storage and retrieval; fifth, the current debugging detection only records the result data, and there is no technical means to record the process data, and the problems in the debugging process need to be manually recorded by the debugging detection personnel, which is low in efficiency.

[0003] Therefore, it is urgent to design a debugging detection system capable of assisting the debugging detection personnel to efficiently complete the debugging detection work, automatically detecting the qualified rate, paperless office, process data analysis and storage, etc. SUMMARY

[0004] The present application aims to solve the above problems in the prior art and provide a vehicle debugging detection system capable of assisting the debugging detection personnel to efficiently complete the debugging detection work, improving the interchangeability of personnel, automatically detecting the qualified rate, paperless office, process data analysis and storage.

[0005] The technical solution adopted by the present application to solve the technical problems is:

[0006] A vehicle debugging detection system, characterized in that it comprises a background management system, a PAD operation system and a data acquisition system, wherein the data acquisition system comprises a T-Box, an external sensor and a detection controller.

[0007] The PAD operation system issues a debugging detection instruction to the vehicle body and the detection controller through the T-Box of the data acquisition system, after receiving the debugging detection instruction, the vehicle body sends all state data to the T-Box, and the detection controller sends the information collected by the external sensor to the T-Box, and the T-Box transmits the received detection data to the PAD operation system.

[0008] The PAD operation system downloads the detection project information from the background management system, and completes the detection according to the real-time detection data and uploads the detection data to the background management system.

[0009] The cooperation between the background management system, PAD operating system and data acquisition system helps the auxiliary personnel to complete the debugging and testing work efficiently, realizes the digitalization and paperless operation of the debugging and testing stage, ensures the consistency of the debugging and testing results, reduces the dependence on the experience of the debugging and testing personnel, and improves the interchangeability of the debugging and testing personnel.

[0010] The data acquisition system of the present invention adopts CAN bus communication with the vehicle body, the data acquisition system adopts MQTT communication with the PAD operating system, and the PAD operating system adopts 4G Internet of Things card communication with the background management system.

[0011] The background management system of the present invention has dictionary configuration, authority management and data query functions. The type dictionary defines the options for the entire debugging and detection system vehicle type, detection item, detection sensor type, sensor model, and judgment basis conditions;

[0012] After the type dictionary is established, a mapping association method is used to edit and match each vehicle model and the corresponding test items. Each test item configured according to the above mapping relationship will be stored on the server. When the corresponding vehicle model test is required, the test items are retrieved according to the vehicle model and specifications and downloaded to the PAD operating system for subsequent testing;

[0013] Authority management sets authority for personnel according to their division of labor;

[0014] Data query includes process data query and result data query. Process data query retrieves the data collected during the debugging and testing process and the number of debugging and testing items during the debugging and testing process according to the timeline. Result data query retrieves the final test report. Process data query is beneficial for technical and quality inspection engineers to conduct their own demand analysis on product data and provide direct data support for improving product quality.

[0015] After the PAD operating system of the present invention imports all the CAN bus data of the vehicle, it preprocesses the data. The specific preprocessing method is as follows:

[0016] Perform frame separation to divide the data stream into independent message frames;

[0017] Cyclic redundancy check (CRC) is used to detect and filter transmission errors, extract data fields based on data length codes, and retain timestamps.

[0018] The present invention parses the digital quantity data of the vehicle CAN bus according to the CAN bus data parsing rules, and according to the data configuration specifically required by each detection item and the physical quantity data obtained through the parsing, enables each detection item to obtain the required physical quantity data, inputs the specified data into the judgment algorithm model of the detection item, and completes the detection judgment.

[0019] The PAD operating system of the present invention uses a judgment algorithm model to determine whether the performance of the test items is qualified. During the "Forward Driving Braking Performance Check" test, the RTK integrated navigation system sends time, vehicle speed, and latitude and longitude information in real time, which are transmitted to the PAD operating system via the T-Box. When the brake pedal is pressed, the vehicle speed begins to decrease and the vehicle starts to brake. When the vehicle speed stabilizes at ≤N km / h, the vehicle stops.

[0020] Select the longitude and latitude coordinates at the moment of sudden speed drop and the longitude and latitude coordinates when the speed stabilizes at N km / h. Use the haversine formula to calculate the distance between the two points to obtain the forward braking distance. When the obtained forward braking distance value is within the qualified range, it means that the test is qualified.

[0021] The specific calculation method of the forward braking distance of the present invention is:

[0022] Step S1: During the process from vehicle moving to braking stop, a set of discrete time points [t1, t2, ..., t n ] and the corresponding velocity values ​​[v(t1),v(t2),…,v(t n )];

[0023] Step S2: preprocessing the original data;

[0024] Step S3: Calculate the first-order difference of the velocity values ​​between adjacent time points, set 2 times the standard deviation of the difference sequence as the threshold, and the calculation formula is:

[0025] Δv(t i )=v(t i+1 )-v(t i );

[0026]

[0027] T = 2σ;

[0028] Where, i=0,1,2,…,n-1,Δv(t i ) is the first-order difference of the velocity value, μ is the mean of the difference sequence, σ is the standard deviation of the difference sequence, and T is the set threshold, which is twice the standard deviation of the difference sequence;

[0029] When the first-order difference reaches or exceeds the threshold, that is, |Δv(t i )|≥T, the velocity v(t i ) is the speed at the moment of braking, that is, v brake ;

[0030] When the vehicle speed is stable at ≤N km / h, the vehicle is judged to have stopped. At this time, the vehicle speed is v stop ;

[0031] Step S4: After obtaining the latitude and longitude of the braking start and end points, calculate the forward braking distance using the following formula:

[0032]

[0033] Δlat=lat2-lat1;

[0034] Δlon=lon2-lon1;

[0035] Where R is the radius of the earth, Δlat is the difference in latitude between the starting point and the end point, Δlon is the difference in longitude between the starting point and the end point, and the vehicle speed v(t i )=v brake When the latitude and longitude coordinates are (lon1,lat1), the vehicle speed v(t i )=v stop When , the longitude and latitude coordinates are (lon2,lat2).

[0036] The PAD operating system described in the present invention determines whether the performance of the detection item is qualified through the judgment algorithm model. During the "minimum left / right turning radius inspection" item detection process, the PAD operating system receives the vehicle latitude and longitude coordinates sent by RTK in real time, first smoothes the original GPS data, selects multiple groups of data points as sample points, and then uses the UTM projection method to convert the latitude and longitude coordinates into coordinates in the plane direct coordinate system. Finally, arc fitting and least squares method are used to calculate the minimum left / right turning radius. When the obtained minimum left / right turning radius is within the qualified range, it means that the test is qualified.

[0037] The specific calculation method of the minimum left / right turning radius of the present invention is:

[0038] Create a circle about the center (x c ,y c ) and radius R turn The equation is linearized and the optimal solution, i.e. the turning radius, is obtained using the least squares method. The calculation formula is:

[0039] z i =(x i -x c ) 2 +(y i -y c ) 2 ;

[0040]

[0041] Aθ=B;

[0042] in,

[0043] θ=(A T A) -1 A T B;

[0044]

[0045] Where z i is the intermediate variable of the circle equation, with n sampling points (x i ,y i ), where i = 1, 2, ..., n, and finally the minimum turning radius R is obtained. turn .

[0046] The PAD operating system of the present invention determines whether the performance of the test item is qualified by using a judgment algorithm model. The specific method for detecting the item "rear wheel following delay time check in four-wheel walking mode" is as follows:

[0047] Step S1: In the four-wheel walking mode, obtain the front and rear wheel angle values ​​during the detection process;

[0048] Step S2: Perform data preprocessing, use the IQR interquartile range statistical method to remove outliers or erroneous points, synchronize timestamps, and ensure the time alignment of the front and rear wheel angle data;

[0049] Step S3: Select a time interval that includes the entire steering process, intercept the front wheel angle curve segment within the time interval for calculation, fit the sample curve segment into a smooth curve by fitting a third-order polynomial function, use the least squares method to calculate the minimum sum of squared residuals SSE, and then find the best fitting parameters a, b, c, d of the front wheel angle fitting function. The fitting curve solution method for the front wheel angle and the rear wheel angle is the same. The solution formula for the front wheel angle fitting curve is:

[0050] f Fangle (t) = at 3 +bt 2 +ct+d;

[0051]

[0052] Where, t i and f Fangle (t i ) are the timestamp and front wheel angle measurement, n is the number of data points, SSE is the sum of the squares of the difference between the predicted value and the true value (i.e., residual) of each data point, and the optimal fitting parameters are obtained by minimizing the sum of the squares of the residuals;

[0053] Calculate the process of minimizing the sum of squared residual errors (SSE) by using the Apache Commons Math library in Java to perform least squares fitting and obtain the optimal fitting parameters and the optimal fitting curve;

[0054] Step S4: After obtaining the optimal fitting curve, the average angle before the front wheel steering starts is determined as a reference line, and the time point at which the front wheel fitting curve intersects the reference line is found. At the same time, the average angle before the rear wheel steering starts is determined as a reference line, and the time point at which the rear wheel fitting curve intersects the reference line is found. The rear wheel following delay time can be calculated by taking the difference between the two time points.

[0055] f Fangle (t F )-reference_angle_f=0;

[0056] f Rangle (t R )-reference_angle_r=0;

[0057] t delay =t R -t F ;

[0058] Where, f Fangle (t) and f Rangle (t) are the third-order polynomial functions of the front wheel angle and the rear wheel angle, reference_angle_f and reference_angle_r are the average angles of the front and rear wheels before they start turning, t F is the time point when the third-order polynomial function curve of the front wheel angle intersects with its reference line, t R is the time point when the third-order polynomial function curve of the rear wheel angle intersects with its reference line, t delay It is the delay time for the rear wheel to follow;

[0059] Step S5: When the obtained rear wheel following delay time is within the qualified range, the test is qualified.

[0060] The beneficial effects of the present invention are as follows: the cooperation of the background management system, the PAD operating system and the data acquisition system enables auxiliary personnel to efficiently complete the debugging and testing work, realizes the digitization and paperless operation of the debugging and testing stage, ensures the consistency of the debugging and testing results, reduces the dependence on the experience of the debugging and testing personnel, and improves the interchangeability of the debugging and testing personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a communication diagram of the debugging and detection system of the present invention.

[0062] Figure 2 It is a functional configuration diagram of the background management system of the present invention.

[0063] Figure 3 It is a data analysis flow chart of the PAD operating system of the present invention.

[0064] Figure 4 It is the front and rear wheel angle value obtained in four-wheel walking mode. DETAILED DESCRIPTION

[0065] The present invention will be described below with reference to the accompanying drawings and embodiments.

[0066] As attached Figure 1 As shown, a vehicle debugging and testing system includes a background management system, a PAD operating system, and a data acquisition system. The debugging and testing system can be mounted on an aircraft tractor to assist debugging and testing personnel in completing debugging and testing work efficiently. The data acquisition system includes a T-Box, external sensors, and a detection controller.

[0067] The PAD operating system sends debugging and detection instructions to the vehicle body and detection controller through the T-Box of the data acquisition system. After receiving the debugging and detection instructions, the vehicle body sends all status data to the T-Box. At the same time, the detection controller sends the signals collected by the external sensor to the T-Box. The T-Box transmits all the received detection data to the PAD operating system in real time;

[0068] The PAD operating system downloads and obtains the test item information from the background management system. In this embodiment, the PAD operating system downloads and obtains the test report template from the background management system. Based on the real-time test data, the PAD operating system completes the test of all mechanical and electrical test items. After the mechanical commissioning technician and the electrical commissioning technician sign and confirm, the test report is generated. The PAD operating system uploads the test data, test records, and test report to the background management system.

[0069] The cooperation between the background management system, PAD operating system and data acquisition system assists personnel to complete the debugging and testing work efficiently. The debugging and testing system uses sensors installed on the external tooling or the vehicle body to control the collection of triggered data through the handheld PAD terminal, and outputs the measurement results through pre-made algorithms. At the same time, it records the debugging process data and summarizes the projects that require multiple debugging, which is convenient for production assembly personnel or technicians to improve and optimize, and reduces the professional and technical requirements of debugging personnel. Only equipment use training is required, which improves the interchangeability of personnel, alleviates the problem of insufficient personnel, and realizes paperless work. After debugging is completed, electronic reports are directly generated for easy storage and review.

[0070] The data acquisition system and the vehicle body adopt CAN bus communication mode, the data acquisition system and the PAD operating system adopt MQTT communication mode, the PAD operating system and the background management system adopt 4G Internet of Things card communication, the transmission speed is fast, and is used for uploading detection report and process data and downloading detection report template; the T-Box of the data acquisition system performs data transmission and reception work, has 4G communication function, WiFi ad hoc network function, two-way CAN bus interface and local data storage function, and the T-Box and the vehicle body and the T-Box and the detection controller adopt CAN bus communication in the embodiment.

[0071] The background management system includes operable Web webpage and server, the background management system has the functions of dictionary configuration, permission management, data query, detection item management and detection record viewing, and the type dictionary is used for defining options of vehicle model, detection item, detection sensor type, sensor model and judgment basis condition of the entire debugging and detection system;

[0072] After the type dictionary is established, each vehicle model and corresponding detection item is edited and matched in a mapping association mode, each detection item configured according to the mapping relationship is stored to the server, when corresponding vehicle model detection is needed, the detection item is retrieved according to the vehicle model and specification, and is downloaded to the PAD operating system for subsequent detection;

[0073] The permission management sets the permissions of personnel according to personnel division of labor, and is divided into administrator permission, engineering permission, debugging personnel permission, quality inspection personnel permission, after-sales personnel permission and the like;

[0074] The data query includes process data query and result data query, the process data query retrieves the data collected in the debugging and detection process and the debugging and detection times of the detection item in the debugging and detection process according to the time axis, the process data query is beneficial to the demand analysis of product data of technical and quality inspection engineers, and directly provides data support for improving product quality; the result data query is used for retrieving the final detection report, and the detection report is displayed in the form of a formatted report;

[0075] The server is used for storing detection data, and realizing access and content configuration of the detection platform;

[0076] The detection item and vehicle model matching of the debugging and detection system are editable, the configuration end adopts B / S (Brower / Sever, browser / server mode) structure design, the self-editing of the detection item content and the binding of the detection sensor are realized through operation on the Web webpage.

[0077] The PAD operating system is an on-site handheld operating tool for debugging and testing personnel. It can perform vehicle body status inspections, calculate the inspection data using a judgment algorithm model, determine whether each inspection item is qualified, display the inspection operation interface, and view inspection records at any time.

[0078] The PAD operating system establishes two links in total. One is to exchange data with the server through the 4G interface. Its main function is to download the configured inspection items and requirements of the inspected equipment to the PAD end for inspection one by one. Its secondary function is to upload the results after the inspection to the server to generate a inspection report for storage and review; the other is to establish communication with the on-site T-Box end, read the inspection parameters, and use the built-in algorithm of the PAD end to determine whether the performance inspection items are qualified.

[0079] After the debugger logs in to the PAD operating system, he first connects to the T-Box gateway of the data acquisition system through the WIFI interface. After the gateway is successfully connected, he clicks on the "Vehicle Status Bar" to connect to the vehicle body; then clicks on "Synchronize Inspection Items" to obtain the inspection item information from the background management system. According to the model and specification number information of the vehicle to be inspected, the debugger selects the corresponding inspection report. The inspection items include 6 categories, such as pre-power-on inspection and post-power-on inspection. According to the inspection method, the inspection items can also be divided into manual confirmation inspection items and automatic confirmation inspection items. Each inspection item is marked with "project description, operating specifications and judgment criteria" for reference. Photos or videos can be uploaded during the inspection.

[0080] During the detection process, the PAD operating system receives the CAN bus digital data transmitted by the T-box, and performs data analysis based on the CAN bus communication protocol between the debugging detection system and the aircraft tractor; the data received by the PAD operating system includes the product number, product specification number, and all CAN bus digital data. Before the detection begins, the PAD operating system downloads the test report templates corresponding to all product specification numbers from the background management system, and at the same time receives the vehicle physical quantity data type and data parsing rules for all product specification numbers. According to the product number in all the CAN bus data of the vehicle, the test report template carrying the same product number can be found. The test report template carries the product specification number. At the same time, the physical quantity data required for the specific test item can be queried in the test report template. According to the product specification number in the test report template, the CAN bus data parsing rules carrying the same product specification number can be found;

[0081] After the PAD operating system imports all the CAN bus data of the vehicle, it preprocesses the data. The specific preprocessing method is as follows:

[0082] Perform frame separation to divide the data stream into independent message frames;

[0083] The cyclic redundancy check (CRC) is used to detect transmission errors and filter, and the data field is extracted according to the data length code, and the time stamp is reserved.

[0084] According to the CAN bus data analysis rule, the vehicle CAN bus digital data is analyzed, and the CAN bus digital data is analyzed. The data analysis rule specifies the position (starting bit), size (bit number), scaling factor and offset of the physical quantity represented by the CAN bus digital data, and the vehicle CAN bus digital data is converted into specific physical quantity data according to the CAN bus data analysis rule.

[0085] Physical_Value=f(Raw_Data);

[0086] In the formula, Raw_Data is the digital data read from the CAN bus after preprocessing, Physical_Value is the physical quantity data required by the detection item, and f(Raw_Data) is the CAN bus data analysis function.

[0087] The digital data and physical quantity data are respectively:

[0088] Digital data: data in the CAN bus, which is encapsulated into the data field of the CAN message frame, and the maximum digital quantity that can be transmitted by each CAN message is 64 bits;

[0089] Physical quantity data: the data of the actual physical phenomenon measured by the sensor or the actuator and converted into digital format, such as angle, pressure, speed, position coordinate, etc.

[0090] According to the data configuration required by each detection item in the detection report template and the physical quantity data obtained by analyzing the vehicle CAN bus data, each detection item in the detection report template can obtain the required physical quantity data, and the specified data is input into the detection item judgment algorithm model to complete the detection judgment.

[0091] The PAD operating system determines whether the performance of the detection item is qualified through the judgment algorithm model, and the specific detection item and detection and judgment process are as follows:

[0092] 1. The operation specification of the detection item "forward driving brake performance check" is:

[0093] ① Keep the equipment in high-voltage power-on state;

[0094] ② Engage the forward gear;

[0095] ③ Control the speed of the accelerator pedal at 20km / h;

[0096] ④ Select the start detection option on the detection terminal;

[0097] ⑤ Release the accelerator pedal;

[0098] ⑥ Press the brake pedal to the maximum limit position;

[0099] ⑦The equipment comes to a complete stop;

[0100] ⑧Select the option to end the test at the test terminal;

[0101] ⑨The system automatically confirms the results;

[0102] ⑩The detection terminal displays the actual braking distance.

[0103] During the project testing process, the RTK integrated navigation system sends time, vehicle speed, and latitude and longitude information in real time, which is transmitted to the PAD operating system via the T-Box. When the brake pedal is pressed, the vehicle speed begins to decrease and the vehicle starts to brake. When the vehicle speed stabilizes at ≤N km / h, the vehicle stops. In this embodiment, the vehicle stops when the vehicle speed stabilizes at ≤0.3 km / h.

[0104] Select the longitude and latitude coordinates at the moment of sudden speed drop and the longitude and latitude coordinates when the speed stabilizes at N km / h. Use the haversine formula to calculate the distance between the two points to obtain the forward braking distance. When the obtained forward braking distance value is within the qualified range, it means that the test is qualified.

[0105] The specific calculation method for forward braking distance is:

[0106] Step S1: When the vehicle is moving at a speed of 20 km / h and stops, a set of discrete time points [t1, t2, ..., t n ] and the corresponding velocity values ​​[v(t1),v(t2),…,v(t n )];

[0107] Step S2: pre-processing the original data and using Kalman filter to smooth the data;

[0108] Step S3: Calculate the first-order difference of the velocity values ​​between adjacent time points, set 2 times the standard deviation of the difference sequence as the threshold, and the calculation formula is:

[0109] Δv(t i )=v(t i+1 )-v(t i );

[0110]

[0111] T = 2σ;

[0112] Where, i=0,1,2,…,n-1,Δv(t i) is the first-order difference of the velocity value, μ is the mean of the difference sequence, σ is the standard deviation of the difference sequence, and T is the set threshold, which is twice the standard deviation of the difference sequence;

[0113] When the first-order difference reaches or exceeds the threshold, that is, |Δv(t i )|≥T, the velocity v(t i ) is the speed at the moment of braking, that is, v brake ;

[0114] When the vehicle speed is stable at ≤N km / h, the vehicle is judged to have stopped. At this time, the vehicle speed is v stop ;

[0115] Step S4: After obtaining the latitude and longitude of the braking start and end points, calculate the forward braking distance using the following formula:

[0116]

[0117] Δlat=lat2-lat1;

[0118] Δlon=lon2-lon1;

[0119] Where R = 6378 km, R is the radius of the earth, Δlat is the difference in latitude between the starting point and the end point, Δlon is the difference in longitude between the starting point and the end point, and the vehicle speed v(t i )=v brake When the latitude and longitude coordinates are (lon1,lat1), the vehicle speed v(t i )=v stop When , the longitude and latitude coordinates are (lon2,lat2).

[0120] 2. For the test item “Minimum left turn radius inspection”, the operating specifications are as follows:

[0121] ① Keep the equipment powered on at high voltage;

[0122] ②Turn the steering wheel to the leftmost limit position;

[0123] ③ Engage the forward gear;

[0124] ④ Maintain idle speed;

[0125] ⑤Select the start detection option on the detection terminal;

[0126] ⑥The device rotates one circle;

[0127] ⑦The detection terminal selects the end of detection;

[0128] ⑧The system automatically confirms the results.

[0129] During the project inspection process, the PAD operating system receives the vehicle's latitude and longitude coordinates sent by RTK in real time. First, the Kalman filter method is used to smooth the original GPS data, and multiple groups of data points are selected as sample points. Then, the UTM projection method is used to convert the latitude and longitude coordinates into coordinates in the plane direct coordinate system. Finally, arc fitting and least squares method are used to calculate the minimum left-turn radius. When the obtained minimum left-turn radius is within the qualified range, it means that the inspection is qualified.

[0130] The specific calculation method of the minimum left turn radius is:

[0131] Create a circle about the center (x c ,y c ) and radius R turn The equation is linearized and the optimal solution, i.e. the turning radius, is obtained using the least squares method. The calculation formula is:

[0132] z i =(x i -x c ) 2 +(y i -y c ) 2 ;

[0133]

[0134] Aθ=B;

[0135] in,

[0136] θ=(A T A) -1 A T B;

[0137]

[0138] Where z i is the intermediate variable of the circle equation, with n sampling points (x i ,y i ), where i = 1, 2, ..., n, and finally the minimum turning radius R is obtained. turn .

[0139] In this embodiment, the detection, calculation and determination process of the “minimum right turn radius detection” detection item is basically the same as that of the “minimum left turn radius detection”.

[0140] 3. The test item "Rear wheel following delay time inspection in four-wheel travel mode" has the following operating specifications:

[0141] ① Keep the equipment powered on at high voltage;

[0142] ②Switch the walking mode to four-wheel mode;

[0143] ③ Return the steering wheel to the center position and engage the forward gear;

[0144] ④ The vehicle speed is stable at 10km / h;

[0145] ⑤Select the start detection option on the detection terminal;

[0146] ⑥Wait for data collection to be completed;

[0147] ⑦Then turn the steering wheel left one circle and keep turning;

[0148] ⑧The detection terminal selection operation is completed;

[0149] ⑨Wait for data collection to be completed and the system to automatically confirm the results;

[0150] ⑩The detection terminal displays the actual following angle difference.

[0151] "Rear wheel following delay time inspection in four-wheel travel mode", the specific inspection method is as follows:

[0152] Step S1: In the four-wheel walking mode, obtain the front and rear wheel angle values ​​during the detection process;

[0153] Step S2: Perform data preprocessing, use the IQR interquartile range statistical method to remove outliers or erroneous points, synchronize timestamps, and ensure the time alignment of the front and rear wheel angle data;

[0154] Step S3: Select a time interval that includes the entire steering process, intercept the front wheel angle curve segment within the time interval for calculation, fit the sample curve segment into a smooth curve by fitting a third-order polynomial function, use the least squares method to calculate the minimum sum of squared residuals SSE, and then find the best fitting parameters a, b, c, d of the front wheel angle fitting function. The fitting curve solution method for the front wheel angle and the rear wheel angle is the same. The solution formula for the front wheel angle fitting curve is:

[0155] f Fangle (t) = at 3 +bt 2 +ct+d;

[0156]

[0157] Where, t i and f Fangle (t i ) are the timestamp and front wheel angle measurement, n is the number of data points, SSE is the sum of the squares of the difference between the predicted value and the true value (i.e., residual) of each data point, and the optimal fitting parameters are obtained by minimizing the sum of the squares of the residuals;

[0158] Calculate the process of minimizing the sum of squared residual errors (SSE) by using the Apache Commons Math library in Java to perform least squares fitting and obtain the optimal fitting parameters and the optimal fitting curve;

[0159] Step S4: After obtaining the optimal fitting curve, the average angle before the front wheel steering starts is determined as a reference line, and the time point at which the front wheel fitting curve intersects the reference line is found. At the same time, the average angle before the rear wheel steering starts is determined as a reference line, and the time point at which the rear wheel fitting curve intersects the reference line is found. The rear wheel following delay time can be calculated by taking the difference between the two time points.

[0160] f Fangle (t F )-reference_angle_f=0;

[0161] f Rangle (t R )-reference_angle_r=0;

[0162] t delay =t R -t F ;

[0163] Where, f Fangle (t) and f Rangle (t) are the third-order polynomial functions of the front wheel angle and the rear wheel angle, reference_angle_f and reference_angle_r are the average angles of the front and rear wheels before they start turning, t F is the time point when the third-order polynomial function curve of the front wheel angle intersects with its reference line, t R is the time point when the third-order polynomial function curve of the rear wheel angle intersects with its reference line, t delay It is the delay time for the rear wheel to follow;

[0164] Step S5: When the obtained rear wheel following delay time is within the qualified range, the test is qualified.

[0165] Regarding the mechanical structure of the debugging and detection system in this embodiment, the entire debugging and detection system control cabinet is installed on a toolbox trolley, which can be quickly disassembled and moved with the product being tested. The control cabinet contains electrical components such as the power distribution module, detection controller, T-Box, etc. The wiring harness is connected through quick-plug connectors and is equipped with a data item hub for long-distance wiring. The toolbox can be used to store sensors and other accessories of the debugging and detection system as well as debugging tools used in daily life.

[0166] In this embodiment, an aircraft tractor is used as an example for description, but the present invention is not limited to this example, and other vehicles can also be applied to the debugging and detection system.

Claims

1. A vehicle debugging and detection system, characterized by: It includes a background management system, a PAD operating system and a data acquisition system, wherein the data acquisition system includes a T-Box, an external sensor and a detection controller; The PAD operating system sends debugging and detection instructions to the vehicle body and detection controller through the T-Box of the data acquisition system. After receiving the debugging and detection instructions, the vehicle body sends all status data to the T-Box. At the same time, the detection controller sends the information collected by the external sensor to the T-Box, and the T-Box transmits the received detection data to the PAD operating system; The PAD operating system downloads and obtains the test item information from the background management system. Based on the real-time test data, the PAD operating system completes the test and uploads the test data to the background management system. The PAD operating system determines whether the performance of the test item is qualified by the judgment algorithm model. The specific method for testing the item "rear wheel following delay time inspection in four-wheel walking mode" is as follows: Step S1: In the four-wheel walking mode, obtain the front and rear wheel angle values ​​during the detection process; Step S2: Perform data preprocessing, use the IQR interquartile range statistical method to remove outliers or erroneous points, synchronize timestamps, and ensure the time alignment of the front and rear wheel angle data; Step S3: Select a time interval that includes the entire steering process, intercept the front wheel angle curve segment within the time interval for calculation, fit the sample curve segment into a smooth curve by fitting a third-order polynomial function, use the least squares method to calculate the minimum sum of squared residuals SSE, and then find the best fitting parameters a, b, c, d of the front wheel angle fitting function. The fitting curve solution method for the front wheel angle and the rear wheel angle is the same. The solution formula for the front wheel angle fitting curve is: f Fangle (t)=at 3 +bt 2 +ct+d; Where, t i and f Fangle (t i ) are the timestamp and front wheel angle measurement, n is the number of data points, SSE is the sum of the squares of the differences between the predicted value and the true value of each data point, and the optimal fitting parameters are obtained by minimizing the sum of squared residuals; Calculate the process of minimizing the sum of squared residual errors (SSE) by using the Apache Commons Math library in Java to perform least squares fitting and obtain the optimal fitting parameters and the optimal fitting curve; Step S4: After obtaining the optimal fitting curve, the average angle before the front wheel steering starts is determined as a reference line, and the time point at which the front wheel fitting curve intersects the reference line is found. At the same time, the average angle before the rear wheel steering starts is determined as a reference line, and the time point at which the rear wheel fitting curve intersects the reference line is found. The rear wheel following delay time can be calculated by taking the difference between the two time points. f Fangle (t F )-reference_angle_f=0; f Rangle (t R )-reference_angle_r=0; t delay =t R -t F ; Where, f Fangle (t) and f Rangle (t) are the third-order polynomial functions of the front wheel angle and the rear wheel angle, reference_angle_f and reference_angle_r are the average angles of the front and rear wheels before they start turning, respectively. F is the time point when the third-order polynomial function curve of the front wheel angle intersects with its reference line, t R is the time point when the third-order polynomial function curve of the rear wheel angle intersects with its reference line, t delay It is the delay time for the rear wheel to follow; Step S5: When the obtained rear wheel following delay time is within the qualified range, the test is qualified.

2. A vehicle debugging and detection system according to claim 1, characterized in that: The data acquisition system and the vehicle body use the CAN bus communication method, the data acquisition system and the PAD operating system use the MQTT communication method, and the PAD operating system and the background management system use the 4G Internet of Things card communication method.

3. A vehicle debugging and detection system according to claim 1 or 2, characterized in that: The backend management system has dictionary configuration, authority management and data query functions. The type dictionary defines options for the entire debugging and detection system vehicle type, detection item, detection sensor type, sensor model, and judgment basis conditions; After the type dictionary is established, a mapping association method is used to edit and match each vehicle model and the corresponding test items. Each test item configured according to the above mapping association method is stored on the server. When the corresponding vehicle model test is required, the test items are retrieved according to the vehicle model and specifications and downloaded to the PAD operating system for subsequent testing; Authority management sets authority for personnel according to their division of labor; Data query includes process data query and result data query. Process data query retrieves the data collected during the debugging and testing process and the number of debugging and testing items during the debugging and testing process according to the timeline. Result data query retrieves the final test report.

4. A vehicle debugging and detection system according to claim 1 or 2, characterized in that: After the PAD operating system imports all the CAN bus data of the vehicle, it preprocesses the data. The specific preprocessing method is as follows: Perform frame separation to divide the data stream into independent message frames; Cyclic redundancy check (CRC) is used to detect and filter transmission errors, extract data fields based on data length codes, and retain timestamps.

5. A vehicle debugging and detection system according to claim 4, characterized in that: According to the CAN bus data parsing rules, the vehicle CAN bus digital data is parsed. According to the specific data configuration required by each test item and the physical quantity data obtained through parsing, each test item can obtain the required physical quantity data, and the specified data is input into the judgment algorithm model of the test item to complete the detection judgment.

6. A vehicle debugging and detection system according to claim 5, characterized in that: The PAD operating system uses an algorithm model to determine whether the performance of the test items is qualified. During the "Forward Driving Braking Performance Check" test, the RTK integrated navigation system sends time, vehicle speed, and latitude and longitude information in real time, which are transmitted to the PAD operating system via the T-Box. When the brake pedal is pressed, the vehicle speed begins to decrease and the vehicle brakes. When the vehicle speed stabilizes at ≤N km / h, the vehicle stops. Select the longitude and latitude coordinates at the moment of sudden speed drop and the longitude and latitude coordinates when the speed stabilizes at N km / h. Use the haversine formula to calculate the distance between the two points to obtain the forward braking distance. When the obtained forward braking distance value is within the qualified range, it means that the test is qualified.

7. A vehicle debugging and detection system according to claim 6, characterized in that: The specific calculation method for forward braking distance is: Step S1: During the process from vehicle moving to braking stop, a set of discrete time points [t1, t2, ..., t n ] and the corresponding velocity values ​​[v(t1),v(t2),…,v(t n )]; Step S2: preprocessing the original data; Step S3: Calculate the first-order difference of the velocity values ​​between adjacent time points, set 2 times the standard deviation of the difference sequence as the threshold, and the calculation formula is: Δv(t i )=v(t i+1 )-v(t i ); T = 2σ; Where, i=0,1,2,…,n-1,Δv(t i ) is the first-order difference of the velocity value, μ is the mean of the difference sequence, σ is the standard deviation of the difference sequence, and T is the set threshold, which is twice the standard deviation of the difference sequence; When the first-order difference reaches or exceeds the threshold, that is, |Δv(t i )|≥T, the velocity v(t i ) is the speed at the moment of braking, that is, v brake ; When the vehicle speed is stable at ≤N km / h, the vehicle is judged to have stopped. At this time, the vehicle speed is v stop ; Step S4: After obtaining the latitude and longitude of the braking start and end points, calculate the forward braking distance using the following formula: Δlat=lat2-lat1; Δlon=lon2-lon1; Where R is the radius of the earth, Δlat is the difference in latitude between the starting point and the end point, Δlon is the difference in longitude between the starting point and the end point, and the vehicle speed v(t i )=v brake When the latitude and longitude coordinates are (lon1,lat1), the vehicle speed v(t i )=v stop When , the longitude and latitude coordinates are (lon2,lat2).

8. The vehicle debugging and detection system according to claim 5, characterized in that: The PAD operating system determines whether the performance of the test items is qualified through the judgment algorithm model. During the "minimum left / right turning radius inspection" item inspection process, the PAD operating system receives the vehicle latitude and longitude coordinates sent by RTK in real time, first smoothes the original GPS data, selects multiple groups of data points as sample points, and then uses the UTM projection method to convert the latitude and longitude coordinates into coordinates in the plane direct coordinate system. Finally, arc fitting and least squares method are used to calculate the minimum left / right turning radius. When the obtained minimum left / right turning radius is within the qualified range, it means that the test is qualified.

9. The vehicle debugging and detection system according to claim 8, characterized in that: The specific calculation method for the minimum left / right turning radius is: Create a circle about the center (x c ,y c ) and radius R turn The equation is linearized and the optimal solution, i.e. the turning radius, is obtained using the least squares method. The calculation formula is: z i =(x i -x c ) 2 +(and i -and c ) 2 ; Aθ=B; in, θ=(A T A) -1 A T B; Where z i is the intermediate variable of the circle equation, with n sampling points (x i ,y i ), where i = 1, 2, ..., n, and finally the minimum turning radius R is obtained. turn .

Images