A vehicle headlight height test control method, system and vehicle controller

Abstract

The present application relates to a vehicle headlight height test control method, system and vehicle controller, and relates to the field of vehicle test control technology, including: in response to a test vehicle entering a test area, obtaining the vehicle model of the test vehicle, and reading the test template and static posture data corresponding to the vehicle model; reading the sensor data of the test vehicle; using the sensor data to calculate the dynamic posture data of the test vehicle; using the test template, predicting the height of the vehicle headlights for the static posture data and the dynamic posture data, and obtaining the set headlight height value; reading the actual headlight height value of the test vehicle from the sensor data; displaying the actual headlight height value and the set headlight height value, as well as the height difference value, on the central display screen of the test vehicle; in response to the headlight height adjustment operation, adjusting the height of the vehicle headlight according to the height difference value. The present application has the effect of improving the height test efficiency of the vehicle headlights and realizing the refined adjustment of the vehicle headlight height.

Description

Technical Field

[0001] The present application relates to the field of vehicle test control technology, and in particular to a vehicle headlight height test control method, system and vehicle controller. Background Art

[0002] With the rise of autonomous driving technology and intelligent network technology, vehicle safety performance has become one of the important criteria for measuring the quality of a vehicle. Among them, the intelligence level of the vehicle lighting system directly affects the safety and driving comfort of night driving, especially the accurate adjustment of the height of the headlights.

[0003] The vehicle headlight height calibration in related technology is usually manually adjusted by workers before the vehicle leaves the factory. Special tools are used to fine-tune the headlight height of each vehicle one by one according to the preset standard value to ensure that the vehicle's headlight height meets the design standards.

[0004] With respect to the above-mentioned related technologies, the inventors believe that the manual calibration of the headlight height is inefficient and easily affected by human factors, resulting in large deviations, which is not conducive to large-scale industrial production. Summary of the invention

[0005] In order to improve the efficiency of vehicle headlight height testing and achieve refined adjustment of vehicle headlight height, the present application provides a vehicle headlight height testing control method, system and controller.

[0006] In a first aspect, the present application provides a vehicle headlight height test control method, which adopts the following technical solution:

[0007] A vehicle headlight height test control method, comprising:

[0008] In response to a test vehicle entering a test area, obtaining a vehicle model of the test vehicle, and reading a test template and static posture data corresponding to the vehicle model;

[0009] During the motion test of the test vehicle, reading sensor data of the test vehicle;

[0010] Calculating dynamic posture data of the test vehicle using the sensor data;

[0011] Using the test template, predicting the height of the vehicle headlights on the static posture data and the dynamic posture data to obtain a set headlight height value;

[0012] Reading an actual headlight height value of the test vehicle from the sensor data;

[0013] Displaying the actual headlight height value and the set headlight height value, as well as a height difference between the actual headlight height value and the set headlight height value on a central display screen of the test vehicle;

[0014] In response to a headlight height adjustment operation, the height of the vehicle headlight is adjusted according to the height difference.

[0015] By adopting the above technical solution, the sensor data and static posture data of the test vehicle are read, and the dynamic posture data is calculated through the sensor data. The static posture data and dynamic posture data are used to predict the height of the vehicle headlights to obtain the set headlight height value. The height difference between the set headlight height value and the actual headlight height value is compared to adjust the height of the vehicle headlights. In this way, the automatic adjustment of the height of the vehicle headlights can be achieved, which can not only improve the height test efficiency of the vehicle headlights, but also realize the refined adjustment of the height of the vehicle headlights.

[0016] Optionally, receiving raw data sent by a sensor on the test vehicle;

[0017] Performing filtering processing on the original data to obtain filtered data, wherein the filtering processing is used to remove noise in the original data;

[0018] Set the sampling window;

[0019] Sampling N of the filtered data closest to the current moment from the filtered data through a sampling window to obtain sampled data, where N is a positive integer;

[0020] The average value of the sampled data is calculated to obtain the sensor data.

[0021] By adopting the above technical solution, the noise in the original data is removed, and the sampling window is used to ensure that the sampled data is representative, so that the sensor data is more accurate, which is conducive to ensuring the accuracy of the height test control of the vehicle headlights.

[0022] Optionally, a time interval is generated according to the current moment and a preset duration, the length of the time interval is equal to the preset duration, and the midpoint of the time interval is the current moment;

[0023] Filtering the screening data from the original data according to the time interval;

[0024] calculating the variance of the screening data;

[0025] Using a preset calculation formula, data processing is performed on the variance to generate a window length of the sampling window, wherein the window length is negatively correlated with the variance;

[0026] The sampling window is set according to the window length.

[0027] By adopting the above technical solution, the window length of the sampling window is set by screening the variance of the data, so that the sampling data sampled by the sampling window can better reflect the characteristics of the test vehicle, thereby ensuring the accuracy of the height test control of the vehicle headlights.

[0028] Optionally, generating a first test record of the test vehicle according to the height difference between the set headlight height value and the actual headlight height value;

[0029] Obtaining basic information of the test vehicle;

[0030] Packing the basic information and the first test record to generate a first test data packet for the test vehicle;

[0031] Upload the first test data packet to a preset server.

[0032] By adopting the above technical solution, after the test vehicle completes the test, the basic information and the first test record of the test vehicle are packaged, a first test data packet of the test vehicle is generated, and the first data packet is sent to a preset server, so that the vehicle test progress becomes traceable, which is conducive to subsequent data analysis and tracing.

[0033] Optionally, when the height difference is greater than a preset threshold, determining vehicles manufactured in the same batch as the test vehicle based on the basic information;

[0034] Reading a second test data packet of the vehicles manufactured in the same batch from the preset server;

[0035] Unpacking the second test data packet to obtain a second test record of the vehicles manufactured in the same batch;

[0036] The vehicle headlamp assembly process is updated according to the second test record.

[0037] By adopting the above technical solution, when a problem occurs with a test vehicle, a secondary inspection is performed on vehicles manufactured in the same batch as the test vehicle to ensure that the quality of vehicles manufactured in the same batch is also qualified, and the vehicle headlight assembly process is updated to ensure that the vehicle headlight assembly process is qualified, thereby ensuring that the height of the vehicle headlights meets the design requirements.

[0038] Optionally, the second test records are sorted according to a generation time sequence to obtain a test record sorting;

[0039] Calculating the difference between the adjacent second test records in the test record sorting to generate adjacent difference values;

[0040] Generate a discrete graph with the numbers of the adjacent differences as the horizontal axis and the adjacent differences as the vertical axis;

[0041] Fitting the discrete points in the discrete graph to obtain a fitting curve, and calculating the slopes of the numbered points on the fitting curve to obtain a curve slope set;

[0042] The vehicle headlight assembly process is adjusted according to the curve slope set.

[0043] By adopting the above technical solution, the vehicle headlight assembly process can be adjusted so that the subsequently manufactured vehicle headlights meet the design requirements, a fully automated testing optimization process is created, the productivity level of the automotive manufacturing industry is significantly improved, and it is conducive to maximizing the economies of scale.

[0044] Optionally, calculating the mean of the curve slope set to obtain a slope mean;

[0045] When the difference between the slope mean and the preset slope is less than the preset difference, updating the processing error of the vehicle headlight assembly process according to the slope difference;

[0046] When the difference between the slope mean and the preset slope is greater than the preset difference, a target duration is calculated according to the slope mean; and a processing error of the vehicle headlight assembly process is adjusted with the target duration as a period.

[0047] By adopting the above technical solution, different optimization methods for the vehicle headlight assembly process are designed according to different actual situations, ensuring that the height of the manufactured vehicle headlights meets the design requirements.

[0048] Optionally, the second test records are classified according to vehicle models of the vehicles manufactured in the same batch to obtain classified test records;

[0049] Performing a clustering operation on the target classification test records in the classification test records to obtain a clustering test record of the target classification test records;

[0050] Calculating the mean of the cluster test records to obtain the cluster test record mean;

[0051] When the mean value of the cluster test records is greater than a preset mean threshold value, the mean value of the cluster test records is mapped using a preset conversion formula to obtain a parameter update value;

[0052] The parameter update value is used to update the process parameters of the vehicle headlight assembly process of the target model corresponding to the target classification test record.

[0053] By adopting the above technical solution, the vehicle headlight assembly process can be adjusted so that the subsequently manufactured vehicle headlights meet the design requirements, a fully automated testing optimization process is created, the productivity level of the automotive manufacturing industry is significantly improved, and it is conducive to maximizing the economies of scale.

[0054] In a second aspect, the present application provides a vehicle headlight height test control system, which adopts the following technical solution:

[0055] A vehicle headlight height test control system, comprising:

[0056] An acquisition module is used to acquire a test template, set a headlight height value, static posture data, sensor data, raw data, a preset calculation formula, a preset threshold value, vehicles manufactured in the same batch, a preset difference value, a vehicle model, and a preset mean threshold value;

[0057] A memory for storing a program of any one of the above vehicle headlight height test control methods;

[0058] The program in the processor memory can be loaded and executed by the processor to implement any of the above vehicle headlight height test control methods.

[0059] By adopting the above technical solution, the sensor data and static posture data of the test vehicle are read, and the dynamic posture data is calculated through the sensor data. The static posture data and dynamic posture data are used to predict the height of the vehicle headlights to obtain the set headlight height value. The height difference between the set headlight height value and the actual headlight height value is compared to adjust the height of the vehicle headlights. In this way, the automatic adjustment of the height of the vehicle headlights can be achieved, which can not only improve the height test efficiency of the vehicle headlights, but also realize the refined adjustment of the height of the vehicle headlights.

[0060] In a third aspect, the present application provides a vehicle controller, which adopts the following technical solution:

[0061] A controller comprises a memory and a processor, wherein the memory stores a computer program which can be loaded by the processor and execute any one of the above methods.

[0062] In a fourth aspect, the present application provides a computer storage medium capable of storing a corresponding program, which is convenient for improving the efficiency of vehicle headlight height testing and realizing fine adjustment of vehicle headlight height, and adopts the following technical solution:

[0063] A computer-readable storage medium stores a computer program that can be loaded by a processor and execute any of the above-mentioned vehicle headlight height test control methods.

[0064] In summary, the present application includes at least one of the following beneficial technical effects:

[0065] Read the sensor data and static posture data of the test vehicle, and calculate the dynamic posture data through the sensor data. Use the static posture data and dynamic posture data to predict the height of the vehicle headlights and obtain the set headlight height value. Compare the height difference between the set headlight height value and the actual headlight height value, and adjust the height of the vehicle headlights. This can achieve automatic adjustment of the vehicle headlight height, which can not only improve the efficiency of the vehicle headlight height test, but also achieve fine adjustment of the vehicle headlight height;

[0066] Remove the noise in the original data and use the sampling window to ensure that the sampled data is representative, making the sensor data more accurate, which is conducive to ensuring the accuracy of the height test control of the vehicle headlights;

[0067] The window length of the sampling window is set by screening the variance of the data, so that the sampling data sampled by the sampling window can better reflect the characteristics of the test vehicle and ensure the accuracy of the height test control of the vehicle headlights. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 It is a flow chart of a vehicle headlight height test control method provided in an embodiment of the present application.

[0069] Figure 2 It is a flowchart of a method for generating sensor data provided in an embodiment of the present application.

[0070] Figure 3 It is a flowchart of a method for setting a sampling window provided in an embodiment of the present application.

[0071] Figure 4 It is a flowchart of a test data storage method provided in an embodiment of the present application.

[0072] Figure 5 It is a flow chart of a first updating method for a vehicle headlight assembly process provided in an embodiment of the present application.

[0073] Figure 6 It is a flow chart of a second updating method for a vehicle headlight assembly process provided in an embodiment of the present application.

[0074] Figure 7 It is a flow chart of a third updating method for a vehicle headlight assembly process provided in an embodiment of the present application.

[0075] Figure 8 It is a flow chart of a fourth updating method for a vehicle headlight assembly process provided in an embodiment of the present application.

[0076] Fig. 9 It is a structural schematic diagram of a vehicle headlight height test control system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0077] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figures 1 to 9 It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0078] The embodiment of the present application discloses a vehicle headlight height test control method. Figure 1 , the method comprising:

[0079] Step S101: in response to a test vehicle entering a test area, obtaining a vehicle model of the test vehicle, and reading a test template and static posture data corresponding to the vehicle model.

[0080] The test area is an area used to test the performance and quality of the vehicle. For example, before the vehicle leaves the factory, it is necessary to conduct performance and quality tests in the test area to ensure that the vehicle meets the production requirements.

[0081] Optionally, before the test vehicle enters the test area, the relevant personnel input the vehicle model of the test vehicle into the computer system. Optionally, the whole vehicle image of the test vehicle is captured by a camera. The whole vehicle image is processed by image recognition using an image recognition model to obtain the vehicle model of the test vehicle.

[0082] The test template is used to calculate the height of the vehicle's headlights using the vehicle's sensor data. The test template corresponds to the vehicle model one by one.

[0083] Static attitude data refers to the information about the direction and angle of the vehicle in three-dimensional space when it is stationary. Optionally, the static attitude data includes at least one of the static pitch angle, static yaw angle, and static roll angle. The static pitch angle describes the rotation of the vehicle along the lateral axis, mainly indicating the up and down tilt of the front and rear parts of the vehicle; the static yaw angle describes the rotation of the vehicle around the vertical axis, mainly indicating the change in the driving direction or orientation of the vehicle; the static roll angle describes the rotation of the vehicle along the longitudinal axis, indicating the left and right tilt of the vehicle.

[0084] Step S102: during the motion test of the test vehicle, the sensor data of the test vehicle is read.

[0085] The sensor data includes vehicle sensor data, wherein the vehicle sensor data includes but is not limited to at least one of acceleration, speed, angular velocity, temperature, and displacement distance.

[0086] In some other embodiments, the sensor data further includes external sensor data, wherein the external sensor data is generated by a sensor in the test area. The external sensor data includes but is not limited to at least one of acceleration, velocity, angular velocity, temperature, and displacement distance.

[0087] Step S103: Calculate the dynamic posture data of the test vehicle using the sensor data.

[0088] Dynamic posture data refers to information about the direction and angle of a vehicle in a moving state in a three-dimensional space. Optionally, the dynamic posture data includes at least one of a dynamic pitch angle, a dynamic yaw angle, and a dynamic roll angle. The dynamic pitch angle refers to the description of the rotation of the vehicle along the lateral axis, mainly indicating the up and down tilt of the front and rear parts of the vehicle; the dynamic yaw angle describes the rotation of the vehicle around the vertical axis, mainly indicating the change in the driving direction or orientation of the vehicle; the dynamic roll angle describes the rotation of the vehicle along the longitudinal axis, indicating the left and right tilt of the vehicle.

[0089] For example, the acceleration components of the test vehicle along the x-axis, y-axis, and z-axis measured by the accelerometer are: , and , then the dynamic pitch angle is , dynamic roll angle is , the magnetometer measures the geomagnetic field component as , and , then the dynamic yaw angle is .

[0090] Step S104: using the test template, predicting the height of the vehicle headlights on the static posture data and the dynamic posture data to obtain a set headlight height value.

[0091] The vehicle headlight height refers to the irradiation height of the vehicle headlight, and the vehicle headlight height will affect the irradiation range of the vehicle headlight. In some other embodiments, the vehicle headlight height can also be replaced by the vehicle headlight irradiation range.

[0092] Optionally, the test template is implemented using a CNN (convolutional neural network) model, an RNN (recurrent convolutional neural network) model, or an LSTM (long short-term memory neural network) model.

[0093] Exemplarily, after obtaining the set headlight height value, the set headlight height value is corrected according to the test scene. For example, if the test scene is a dim light scene, the set headlight height value needs to be corrected, and the set headlight height value is increased to increase the illumination range of the vehicle headlight.

[0094] Step S105: Read the actual headlight height value of the test vehicle from the sensor data.

[0095] Optionally, a test template is also provided inside the test vehicle, and the test vehicle can adjust the headlight height using the set headlight height value obtained by the test template. For example, after the test vehicle calculates the set headlight height value, the driving voltage of the headlight motor is adjusted in real time, thereby finely controlling the headlight elevation angle to achieve a change in the headlight height value.

[0096] Optionally, the controller hardware of the test vehicle uses a high-performance embedded microprocessor STM32F407, equipped with high-speed flash memory and RAM, and a built-in CAN bus controller to support two-way communication with the vehicle ECU and other sensor modules. After receiving the set headlight height value calculated by the test template, the microprocessor responds quickly, parses the sensor data stream, and adjusts the headlight drive current pulse width according to the pre-set target value to achieve stepless adjustment of the headlight lifting angle. In addition, the controller also integrates a temperature compensation circuit to ensure stable operation under extreme climatic conditions. Further, in order to ensure the reliability of the vehicle hardware, the electromagnetic compatibility (EMC) protection measures of the hardware can be enhanced, such as using a metal shield to wrap the key circuit board to prevent high-frequency signal crosstalk, and ensure that the controller hardware still maintains excellent performance in a harsh electromagnetic environment. Therefore, by optimizing the hardware circuit design, the electromagnetic compatibility is enhanced, the robustness of the system under various harsh external conditions is guaranteed, the service life is extended, and customer satisfaction is improved.

[0097] Step S106: Displaying the actual headlight height value and the set headlight height value, as well as the height difference between the actual headlight height value and the set headlight height value on the central display screen of the test vehicle.

[0098] The central display screen is a display screen located on the center console inside the vehicle. In this embodiment, the central display screen can display the actual headlight height value and the set headlight height value, and present the actual headlight height value and the set headlight height value in an animated form.

[0099] Furthermore, the environment in which the test vehicle is located can also be displayed on the central display screen, and the environment is used to represent at least one of the time period, lighting conditions, speed, vehicle density in the surrounding area, and road type.

[0100] Step S107: In response to the headlight height adjustment operation, the height of the vehicle headlight is adjusted according to the height difference.

[0101] Optionally, the headlight height adjustment operation includes manual headlight height adjustment operation and automatic headlight height adjustment operation. Manual headlight height adjustment operation is when the central display screen receives the operation of the vehicle headlight height by relevant personnel. For example, after the central display screen displays the actual headlight height value and the set headlight height value, the relevant personnel manually inputs the headlight height value, and the controller on the test vehicle adjusts the height of the vehicle headlight according to the aforementioned headlight height value. Automatic headlight height adjustment operation is when the controller on the vehicle adjusts the height of the vehicle headlight according to the height difference.

[0102] Exemplarily, if no manual headlight height adjustment operation is received, the controller on the test vehicle will perform an automatic headlight height adjustment operation. For example, if no manual headlight height adjustment operation is received within a preset time, the automatic headlight height adjustment operation is performed.

[0103] In some embodiments, when the difference between the headlight height value input by the manual headlight height adjustment operation and the height difference value is greater than a preset limit height difference value, a warning message is displayed on the central display screen, and the warning message is used to warn relevant personnel that the headlight height value input is beyond a reasonable range. The controller on the test vehicle will perform an automatic headlight height adjustment operation.

[0104] Optionally, when the height difference between the set headlight height value and the actual headlight height value is greater than a preset threshold, the height of the vehicle headlights is adjusted according to the height difference so that the headlight height of the test vehicle meets the set headlight height value.

[0105] In some other embodiments, when it is detected that the headlights deviate from the normal range, an alarm is immediately triggered to remind relevant personnel to intervene and correct in time to avoid the occurrence of potential safety hazards.

[0106] By adopting the above technical solution, the sensor data and static posture data of the test vehicle are read, and the dynamic posture data is calculated through the sensor data. The static posture data and dynamic posture data are used to predict the height of the vehicle headlights to obtain the set headlight height value. The height difference between the set headlight height value and the actual headlight height value is compared to adjust the height of the vehicle headlights. In this way, the automatic adjustment of the height of the vehicle headlights can be achieved, which can not only improve the height test efficiency of the vehicle headlights, but also realize the refined adjustment of the height of the vehicle headlights.

[0107] In the following embodiments, due to the interference of the external environment, the data output by the sensor usually carries various noises. In order to reduce the fluctuation effect caused by the external interference, the data output by the sensor needs to be preprocessed. Therefore, the embodiment of the present application discloses a method for generating sensor data. Figure 2 , the method comprising:

[0108] Step S201: receiving raw data sent by sensors on a test vehicle.

[0109] Raw data refers to the data generated by the sensor and has not undergone any data processing operations.

[0110] Step S202: filter the original data to obtain filtered data. The filtering process is used to remove noise in the original data.

[0111] Optionally, a Kalman filter is used to filter the original data to obtain filtered data.

[0112] Step S203: Setting a sampling window.

[0113] The sampling window is a time window with a certain length. Furthermore, the sampling window can slide on the time axis.

[0114] Step S204: sampling N filtered data closest to the current moment from the filtered data through a sampling window to obtain sampled data, where N is a positive integer.

[0115] Exemplarily, the right end point of the sampling window is aligned with the current time, and N filtered data near the right end point in the sampling window are read to obtain the sampling data. Alternatively, the midpoint of the sampling window is aligned with the current time, and N filtered data near the midpoint in the sampling window are read to obtain the sampling data.

[0116] In some other embodiments, N filtered data may be randomly sampled from the filtered data through a sampling window to obtain sampled data.

[0117] Step S205: Calculate the average value of the sampled data to obtain sensor data.

[0118] In this embodiment, the average value of the sampled data is calculated, which can suppress transient disturbances and make the output result more stable and reliable.

[0119] By adopting the above technical solution, the noise in the original data is removed, and the sampling window is used to ensure that the sampled data is representative, so that the sensor data is more accurate, which is conducive to ensuring the accuracy of the height test control of the vehicle headlights.

[0120] In the following embodiments, the length of the sampling window can be adjusted according to the actual situation so that the sampling window can adapt to the real scene. Therefore, the embodiment of the present application discloses a method for setting the sampling window. Figure 3 , the method comprising:

[0121] Step S301: Generate a time interval according to the current time and a preset duration. The length of the time interval is equal to the preset duration, and the midpoint of the time interval is the current time.

[0122] Exemplarily, the current time is taken as the origin, and half of the preset time length is extended along both sides in the time direction to obtain the two side endpoints of the time interval. The time interval is formed according to the two side endpoints.

[0123] Step S302: Filter the screening data from the original data according to the time interval.

[0124] Exemplarily, a random sampling operation is performed on the original data within the time interval to obtain the filtered data.

[0125] In some other embodiments, clustering calculation is performed on the raw data within the time interval to obtain raw data clusters. The raw data clusters including the most raw data are taken as the target raw data clusters. The raw data in the target raw data clusters are used as screening data.

[0126] Step S303: Calculate the variance of the screened data.

[0127] Exemplarily, the mean of the screening data is calculated to obtain the mean of the screening data. The difference between each screening data and the mean of the screening data is calculated, and the differences are summed and averaged to obtain the variance of the screening data.

[0128] Step S304: using a preset calculation formula, performing data processing on the variance to generate a window length of a sampling window, where the window length is negatively correlated with the variance.

[0129] Exemplarily, the preset calculation formula includes a mapping formula and a preset function, wherein the mapping formula is used to map the variance to a fixed interval, and the output value of the preset function is negatively correlated with the input value. The variance is mapped to obtain a mapping value of the variance, wherein the mapping value is positively correlated with the variance. Using the preset function, a function operation is performed on the mapping value to obtain a window length.

[0130] Step S305: setting the sampling window according to the window length.

[0131] Optionally, the length of the sampling window is set according to the window length, and the current moment is used as the right endpoint of the sampling window to obtain the sampling window.

[0132] By adopting the above technical solution, the window length of the sampling window is set by screening the variance of the data, so that the sampling data sampled by the sampling window can better reflect the characteristics of the test vehicle, thereby ensuring the accuracy of the height test control of the vehicle headlights.

[0133] In the following embodiments, after testing a vehicle, in order to facilitate subsequent data analysis and tracing. The present application embodiment discloses a test data storage method. Figure 4 , the method comprising:

[0134] Step S401: generating a first test record of a test vehicle according to a height difference between a set headlight height value and an actual headlight height value.

[0135] Optionally, the first test record includes a test item and a test result corresponding to the test item.

[0136] In the embodiment of the present application, taking the vehicle headlight height test as an example, when the height difference between the set headlight height value and the actual headlight height value is greater than a preset threshold, a first mark is added to the first test record. When the height difference between the set headlight height value and the actual headlight height value is less than the preset threshold, a second mark is added to the first test record. The first mark is different from the second mark. Relevant personnel can determine the result of the vehicle headlight height test by the difference between the first mark and the second mark. The first mark indicates that the test vehicle has not passed the vehicle headlight height test, and the second mark indicates that the test vehicle has passed the vehicle headlight height test.

[0137] Step S402: Obtain basic information of the test vehicle.

[0138] The basic information includes at least one of the vehicle number of the test vehicle, the vehicle test date, the vehicle production line, the vehicle model, the vehicle production date, the production line number of each accessory, and the model of each accessory.

[0139] Step S403: Pack the basic information and the first test record to generate a first test data packet for the test vehicle.

[0140] In some embodiments, the vehicle number and vehicle test date in the basic information are extracted, the vehicle number and vehicle test date are encoded, and a data packet identifier is generated. The basic information and the first test record are added to a compressed package, and the data packet identifier is used as a mark of the compressed package to obtain a first test data packet.

[0141] Step S404: Upload the first test data packet to a preset server.

[0142] The preset server is used to store the test data packet of the vehicle. Optionally, the preset server is a cloud server.

[0143] Optionally, when it is necessary to search for test data of a certain vehicle from a preset server, the search may be performed through the data packet identifier on the test data packet.

[0144] By adopting the above technical solution, after the test vehicle completes the test, the basic information and the first test record of the test vehicle are packaged, a first test data packet of the test vehicle is generated, and the first data packet is sent to a preset server, so that the vehicle test progress becomes traceable, which is conducive to subsequent data analysis and tracing.

[0145] In the following embodiments, after testing the height of the headlights of the test vehicle, the test results can be used to update the vehicle headlight assembly process to ensure that the height of the headlights of the subsequently manufactured vehicles meets the design requirements. Therefore, the embodiment of the present application discloses a method for updating the vehicle headlight assembly process. Figure 5 , the method comprising:

[0146] Step S501: when the height difference is greater than a preset threshold, determine vehicles manufactured in the same batch as the test vehicle based on basic information.

[0147] Exemplarily, the vehicle production line and vehicle production date in the basic information are read. Vehicles manufactured in the same batch are determined based on the vehicle production line and vehicle production date. The vehicle models of the vehicles manufactured in the same batch and the test vehicle may be the same or different.

[0148] The preset threshold is a preset experience value, and relevant personnel can adjust the preset threshold according to actual needs.

[0149] Step S502: Read a second test data packet of vehicles manufactured in the same batch from a preset server.

[0150] Exemplarily, after the vehicles manufactured in the same batch are determined, the data packet identifiers of the vehicles manufactured in the same batch are obtained. According to the data packet identifiers, the second test data packet is read from the preset server.

[0151] Step S503: unpacking the second test data packet to obtain the second test record of the vehicles manufactured in the same batch.

[0152] The second test record is the test record of vehicles manufactured in the same batch.

[0153] Exemplarily, a data compression method of a second test data packet is obtained, and the second test data packet is unpacked according to the data compression method to obtain a second test record of vehicles manufactured in the same batch.

[0154] Step S504: updating the vehicle headlight assembly process according to the second test record.

[0155] Optionally, the vehicle assembly process is updated according to the generation sequence of the second test record, or the vehicle assembly process is updated according to the vehicle models of the vehicles manufactured in the same batch in the second test record.

[0156] By adopting the above technical solution, when a problem occurs with a test vehicle, a secondary inspection is performed on vehicles manufactured in the same batch as the test vehicle to ensure that the quality of vehicles manufactured in the same batch is also qualified, and the vehicle headlight assembly process is updated to ensure that the vehicle headlight assembly process is qualified, thereby ensuring that the height of the vehicle headlights meets the design requirements.

[0157] In the following embodiment, the vehicle headlight assembly process is updated according to the generation sequence of the second test record. The present application embodiment discloses a second method for updating the vehicle headlight assembly process. Figure 6 , the method comprising:

[0158] Step S601: sort the second test records according to the generation time sequence to obtain the test record sorting.

[0159] Exemplarily, the second test records are sorted from early to late according to the generation time sequence to obtain the test record sorting.

[0160] Step S602: Calculate the difference between adjacent second test records in the test record sorting to generate adjacent difference values.

[0161] Exemplarily, if the test records are sorted to include the second test record A, the second test record B, the second test record C, and the second test record D in sequence, then the steps of calculating the difference between adjacent second test records include calculating the difference between the second test record A and the second test record B to obtain adjacent difference 1; calculating the difference between the second test record B and the second test record C to obtain adjacent difference 2; and calculating the difference between the second test record C and the second test record D to obtain adjacent difference 3.

[0162] Step S603: Generate a discrete graph with the numbers of adjacent differences as the horizontal axis and the adjacent differences as the vertical axis.

[0163] The serial numbers of the adjacent differences are determined according to the serial numbers of the adjacent second test records for which the adjacent differences are calculated in the test record sorting.

[0164] For example, the adjacent differences include the adjacent difference 1, adjacent difference 2 and adjacent difference 3, and the adjacent difference 1 is numbered 1, and the value of the adjacent difference 1 is used as the vertical axis to generate discrete points of the adjacent difference 1 in the discrete graph. The adjacent difference 2 and the adjacent difference 3 are similar, and will not be described here.

[0165] Step S604: fitting the discrete points in the discrete graph to obtain a fitting curve, and calculating the slopes of the numbered positions on the fitting curve to obtain a curve slope set.

[0166] Optionally, the discrete points in the discrete graph are fitted using a least squares method to obtain a fitting curve. Alternatively, the discrete points in the discrete graph are fitted using a polynomial fitting method to obtain a fitting curve.

[0167] Step S605: adjusting the vehicle headlight assembly process according to the curve slope set.

[0168] By adopting the above technical solution, the vehicle headlight assembly process can be adjusted so that the subsequently manufactured vehicle headlights meet the design requirements, a fully automated testing optimization process is created, the productivity level of the automotive manufacturing industry is significantly improved, and it is conducive to maximizing the economies of scale.

[0169] The present application embodiment discloses a third updating method for a vehicle headlight assembly process. Figure 7 , the method comprising:

[0170] Step S701: Calculate the mean of the curve slope set to obtain the slope mean.

[0171] In some other embodiments, a weighted average of the curve slope set may be calculated to obtain a slope mean.

[0172] Step S702: when the difference between the slope mean and the preset slope is less than the preset difference, updating the processing error of the vehicle headlight assembly process according to the slope difference.

[0173] The preset slope is a preset empirical value, and relevant personnel can adjust it according to actual needs. Exemplarily, the preset slope is 0. In an ideal vehicle headlight assembly process, the preset slope is 0, that is, the mean slope is close to 0, so the adjacent test records in the second test record are close, and it can be inferred that each test record in the second test record is close. However, according to the preconditions of this embodiment, it has been detected that there is a problem with the headlight height of the test vehicle, so similar problems will also exist in vehicles manufactured in the same batch. When the difference between the mean slope and the preset slope is less than the preset difference, it means that the processing equipment used in the vehicle headlight assembly process has a large error and needs to be recalibrated. Exemplarily, the processing error of the processing equipment used in the vehicle headlight assembly process is recalibrated.

[0174] Step S703: when the difference between the mean slope and the preset slope is greater than the preset difference, the target duration is calculated according to the mean slope.

[0175] When the difference between the slope mean and the preset slope is greater than the preset difference, similar to the description process of step S702, it can be inferred that there is a certain difference between each test record in the second test record. After multiple tests by the inventor, it was found that the processing error of the processing equipment in the vehicle headlight assembly process will gradually increase over time.

[0176] Optionally, the allowable error of the vehicle headlight assembly process is obtained, and the target duration is obtained according to the ratio of the allowable error to the slope mean.

[0177] Step S704: adjusting the processing error of the vehicle headlight assembly process with the target duration as a cycle.

[0178] Exemplarily, after the target time has passed, the processing error of the processing equipment used in the vehicle headlamp assembly process is recalibrated.

[0179] By adopting the above technical solution, different optimization methods for the vehicle headlight assembly process are designed according to different actual situations, ensuring that the height of the manufactured vehicle headlights meets the design requirements.

[0180] In the following embodiment, the vehicle headlight assembly process is updated according to the vehicle model of the same batch of manufactured vehicles. The present application embodiment discloses a second method for updating the vehicle headlight assembly process. Figure 8 , the method comprising:

[0181] The present application embodiment discloses a fourth updating method for a vehicle headlight assembly process. Figure 8 , the method comprising:

[0182] Step S801: Classify the second test records according to vehicle models of vehicles manufactured in the same batch to obtain classified test records.

[0183] Exemplarily, the second test records are classified according to vehicle models of vehicles manufactured in the same batch to obtain classified test records.

[0184] Step S802: performing clustering operation on the target classification test records in the classification test records to obtain cluster test records of the target classification test records.

[0185] Optionally, the clustering operation includes any one of a K-means clustering operation, a hierarchical clustering algorithm, a density-based clustering algorithm, and a model-based clustering algorithm.

[0186] Step S803: Calculate the mean of the cluster test records to obtain the mean of the cluster test records.

[0187] In some other embodiments, a weighted mean of the clustered test records is calculated to obtain a clustered test record mean.

[0188] Step S804: when the mean value of the cluster test records is greater than the preset mean threshold value, the mean value of the cluster test records is mapped using a preset conversion formula to obtain a parameter update value.

[0189] When the mean of the cluster test records is greater than the preset mean threshold, it indicates that there is a problem with the vehicle headlight assembly process of vehicles manufactured in the same batch and it needs to be updated.

[0190] Step S805: using the parameter update value to update the process parameters of the vehicle headlight assembly process of the target model corresponding to the target classification test record.

[0191] Exemplarily, a processing device for the assembly process of a vehicle headlight of a target model corresponding to the target classification test record is determined, and a process parameter of the processing device is updated according to the parameter update value.

[0192] By adopting the above technical solution, the vehicle headlight assembly process can be adjusted so that the subsequently manufactured vehicle headlights meet the design requirements, a fully automated testing optimization process is created, the productivity level of the automotive manufacturing industry is significantly improved, and it is conducive to maximizing the economies of scale.

[0193] Based on the same inventive concept, the embodiment of the present application provides a vehicle headlight height test control system, please refer to Fig. 9 The system comprises:

[0194] The acquisition module 901 is used to acquire the test template, set the headlight height value, static posture data, sensor data, raw data, preset calculation formula, preset threshold value, vehicles manufactured in the same batch, preset difference value, vehicle model and preset mean threshold value;

[0195] A memory 902, used to store a program of any one of the above vehicle headlight height test control methods;

[0196] Processor 903, the program in the memory can be loaded and executed by the processor to implement any of the above-mentioned vehicle headlight height test control methods.

[0197] By adopting the above technical solution, the sensor data and static posture data of the test vehicle are read, and the dynamic posture data is calculated through the sensor data. The static posture data and dynamic posture data are used to predict the height of the vehicle headlights to obtain the set headlight height value. The height difference between the set headlight height value and the actual headlight height value is compared to adjust the height of the vehicle headlights. In this way, the automatic adjustment of the height of the vehicle headlights can be achieved, which can not only improve the height test efficiency of the vehicle headlights, but also realize the refined adjustment of the height of the vehicle headlights.

[0198] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0199] An embodiment of the present application provides a computer-readable storage medium storing a computer program that can be loaded by a processor and executed by a vehicle headlight assembly process method.

[0200] Computer storage media include, for example, various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0201] Based on the same inventive concept, an embodiment of the present application provides a smart terminal, including a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute a vehicle headlight assembly process method.

[0202] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0203] The above are all preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Any feature disclosed in this specification (including the abstract and drawings), unless otherwise stated, can be replaced by other equivalent or alternative features with similar purposes. That is, unless otherwise stated, each feature is only an example of a series of equivalent or similar features.

Claims

1. A vehicle headlight height test control method, characterized in that: The method comprises: In response to a test vehicle entering a test area, obtaining a vehicle model of the test vehicle, and reading a test template and static posture data corresponding to the vehicle model; During the motion test of the test vehicle, reading sensor data of the test vehicle; Calculating dynamic posture data of the test vehicle using the sensor data; Using the test template, predicting the height of the vehicle headlights on the static posture data and the dynamic posture data to obtain a set headlight height value; Reading an actual headlight height value of the test vehicle from the sensor data; Displaying the actual headlight height value and the set headlight height value, as well as a height difference between the actual headlight height value and the set headlight height value on a central display screen of the test vehicle; In response to a headlight height adjustment operation, adjusting the height of the vehicle headlight according to the height difference; generating a first test record of the test vehicle according to the height difference between the set headlight height value and the actual headlight height value; Obtaining basic information of the test vehicle; Packing the basic information and the first test record to generate a first test data packet for the test vehicle; Uploading the first test data packet to a preset server; When the height difference is greater than a preset threshold, determining vehicles manufactured in the same batch as the test vehicle based on the basic information; Reading a second test data packet of the vehicles manufactured in the same batch from the preset server; Unpacking the second test data packet to obtain a second test record of the vehicles manufactured in the same batch; updating the vehicle headlight assembly process according to the second test record; The step of updating the vehicle headlight assembly process according to the second test record includes: sorting the second test record according to the generation time sequence to obtain a test record sorting; calculating the difference between the adjacent second test records in the test record sorting to generate adjacent differences; using the numbers of the adjacent differences as the horizontal axis and the adjacent differences as the vertical axis to generate a discrete graph; fitting the discrete points in the discrete graph to obtain a fitting curve, and calculating the slope of the numbered position on the fitting curve to obtain a curve slope set; adjusting the vehicle headlight assembly process according to the curve slope set; The step of adjusting the vehicle headlight assembly process according to the curve slope set includes: calculating the mean of the curve slope set to obtain the slope mean; when the difference between the slope mean and the preset slope is less than the preset difference, updating the processing error of the vehicle headlight assembly process according to the slope difference; when the difference between the slope mean and the preset slope is greater than the preset difference, calculating the target duration according to the slope mean; and adjusting the processing error of the vehicle headlight assembly process with the target duration as a period.

2. The vehicle headlight height test control method according to claim 1, characterized in that: The reading of sensor data of the test vehicle includes: Receiving raw data sent by sensors on the test vehicle; Performing filtering processing on the original data to obtain filtered data, wherein the filtering processing is used to remove noise in the original data; Set the sampling window; Sampling N of the filtered data closest to the current moment from the filtered data through a sampling window to obtain sampled data, where N is a positive integer; The average value of the sampled data is calculated to obtain the sensor data.

3. The vehicle headlight height test control method according to claim 2, characterized in that: The step of setting the sampling window comprises: Generate a time interval according to the current moment and a preset duration, the length of the time interval is equal to the preset duration, and the midpoint of the time interval is the current moment; Filtering the screening data from the original data according to the time interval; calculating the variance of the screening data; Using a preset calculation formula, data processing is performed on the variance to generate a window length of the sampling window, wherein the window length is negatively correlated with the variance; The sampling window is set according to the window length.

4. The vehicle headlight height test control method according to claim 1, characterized in that: The updating of the vehicle headlight assembly process according to the second test record includes: Classifying the second test records according to vehicle models of the vehicles manufactured in the same batch to obtain classified test records; Performing a clustering operation on the target classification test records in the classification test records to obtain a clustering test record of the target classification test records; Calculating the mean of the cluster test records to obtain the cluster test record mean; When the mean value of the cluster test records is greater than a preset mean threshold value, the mean value of the cluster test records is mapped using a preset conversion formula to obtain a parameter update value; The parameter update value is used to update the process parameters of the vehicle headlight assembly process of the target model corresponding to the target classification test record.

5. A vehicle headlight height test control system, characterized in that: The system comprises: An acquisition module is used to acquire a test template, set a headlight height value, static posture data, sensor data, raw data, a preset calculation formula, a preset threshold value, vehicles manufactured in the same batch, a preset difference value, a vehicle model, and a preset mean threshold value; A memory for storing a program of a vehicle headlight height test control method according to any one of claims 1 to 4; The program in the memory can be loaded and executed by the processor to implement the vehicle headlight height test control method as claimed in any one of claims 1 to 4.

6. A vehicle controller, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program which can be loaded by the processor and executes any one of the methods of claims 1 to 4.

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