Vehicle chassis performance verification method and device, vehicle and medium

Abstract

The invention provides a vehicle chassis performance verification method and device, a vehicle and a medium, the method and device are applied to the vehicle, a chassis of the vehicle is provided with a plurality of sensors, the vehicle is in communication connection with the sensors, and the method comprises the steps that a chassis data set sent by the sensors is received, a speed data set, an acceleration data set and a steering angle data set are extracted from the chassis data set in batches, and a speed change rate set is obtained through batch calculation according to speed data in the speed data set and collection moments corresponding to the speed data; and determining a chassis stability category corresponding to the vehicle according to the speed data set and the acceleration data set, determining a chassis controllability category corresponding to the vehicle according to the steering angle data set and the speed change rate data set, and displaying the chassis stability category and the chassis controllability category. According to the method, the chassis data are automatically collected and then are processed in batches, and visual display is realized, so that the efficiency and accuracy of chassis performance verification are improved.

Description

Technical Field

[0001] The present application relates to the field of chassis performance verification, and in particular to a vehicle chassis performance verification method, device, vehicle and medium. Background Art

[0002] In modern automobile design, automobile chassis working condition verification is a core link in automobile design and manufacturing, and its purpose is to ensure the performance and reliability of the chassis under various working conditions. Traditional verification methods mainly rely on manual or semi-automatic post-processing analysis of the collected data to calculate and evaluate verification indicators. However, this method has some significant shortcomings.

[0003] First, the traditional verification method has low data processing efficiency. The traditional manual processing method cannot efficiently process the data required for chassis verification. The speed of data processing often cannot keep up with the speed of data generation, resulting in delays in the verification process, which in turn affects the efficiency of the entire design and manufacturing process. Secondly, poor accuracy is another important defect of the traditional verification method. In the process of manual data analysis, the intervention of human factors inevitably introduces errors. These errors accumulate in various links of data processing and analysis, and may eventually lead to inaccurate verification results. Inaccurate results will not only affect the optimization of chassis design, but may also have a negative impact on the safety and performance of the vehicle. Summary of the invention

[0004] In view of the above problems, the embodiments of the present application propose a vehicle chassis performance verification method, device, vehicle and medium.

[0005] In a first aspect of the implementation of the present application, a vehicle chassis performance verification method is first provided, characterized in that it is applied to the vehicle, a plurality of sensors are arranged on the chassis of the vehicle, and a communication connection is established between the vehicle and the sensors, and the method comprises:

[0006] Receiving a chassis data set sent by the sensor; wherein the chassis data set includes a plurality of chassis raw data collected at different times, and the chassis raw data in the chassis data set are sorted according to the collection time;

[0007] Extracting speed data, acceleration data, and steering angle data in batches from the chassis data set to obtain a speed data set, an acceleration data set, and a steering angle data set;

[0008] The speed change rates are calculated in batches according to the speed data in the speed data set and the collection time corresponding to the speed data to obtain a speed change rate set;

[0009] determining a chassis stability category corresponding to the vehicle according to the speed data set and the acceleration data set;

[0010] Determining a chassis handling category corresponding to the vehicle according to the steering angle data set and the speed change rate data set;

[0011] The chassis stability category and the chassis handling category are displayed.

[0012] Optionally, the receiving the chassis data set sent by the sensor includes:

[0013] Receiving a plurality of chassis raw data sent by the sensor;

[0014] Performing data cleaning and / or mean filling processing on the original chassis data;

[0015] The processed chassis raw data are combined into the chassis data set.

[0016] Optionally, extracting speed data, acceleration data, and steering angle data in batches from the chassis data set to obtain a speed data set, an acceleration data set, and a steering angle data set includes:

[0017] Extracting the speed data in batches from the chassis data set, and sorting the speed data according to the collection time to obtain the speed data set;

[0018] Extracting the acceleration data in batches from the chassis data set, and sorting the acceleration data according to the collection time to obtain the acceleration data set;

[0019] The steering angle data are extracted in batches from the chassis data set, and the steering angle data are sorted according to the collection time to obtain the steering angle data set.

[0020] Optionally, batch calculating the speed change rates according to the speed data in the speed data set and the collection moments corresponding to the speed data to obtain the speed change rate set includes:

[0021] Batch calculating the speed change rate at the current collection moment according to the speed data at the current collection moment in the speed data set and the speed data at the previous collection moment in the speed data set;

[0022] The speed change rates are sorted according to the collection time to obtain the speed change rate set.

[0023] Optionally, determining a chassis stability category corresponding to the vehicle according to the speed data set and the acceleration data set comprises:

[0024] For any collection moment, if the speed data at the collection moment in the speed data set is greater than a first preset threshold, and the acceleration data at the collection moment in the acceleration data set is less than a second preset threshold, it is determined that the chassis stability category corresponding to the vehicle at the collection moment is the first stability category;

[0025] If the speed data at the collection moment in the speed data set is less than or equal to a first preset threshold, or the acceleration data at the collection moment in the acceleration data set is greater than or equal to a second preset threshold, then it is determined that the chassis stability category corresponding to the vehicle at the collection moment is the second stability category, and the first stability category is better than the second stability category.

[0026] Optionally, determining the chassis handling category corresponding to the vehicle according to the steering angle data set and the speed change rate data set includes:

[0027] For any collection moment, if the steering angle data at the collection moment in the steering angle data set is less than a third preset threshold, and the speed change rate data at the collection moment in the speed change rate set is within a first preset interval, then it is determined that the chassis maneuverability category corresponding to the vehicle at the collection moment is the first maneuverability category;

[0028] If the steering angle data at the collection moment in the steering angle data set is greater than or equal to a third preset threshold, or the speed change rate data at the collection moment in the speed change rate set is not in a first preset interval, then it is determined that the chassis maneuverability category corresponding to the vehicle at the collection moment is the second maneuverability category, and the first maneuverability category is better than the second maneuverability category.

[0029] Optionally, the displaying of the chassis stability category and the chassis handling category includes:

[0030] Sort the chassis stability categories according to the collection time to obtain the chassis stability category set;

[0031] Sort the chassis handling categories according to the collection time to obtain the chassis handling category set;

[0032] The chassis stability category set and the chassis handling category set are displayed.

[0033] In a second aspect of the implementation of the present application, a vehicle chassis performance verification device is also provided, characterized in that it is applied to the vehicle, a plurality of sensors are arranged on the chassis of the vehicle, and a communication connection is established between the vehicle and the sensors, and the device comprises:

[0034] A data collection module, configured to receive a chassis data set sent by the sensor; wherein the chassis data set includes a plurality of chassis raw data collected at different times, and the chassis raw data in the chassis data set are sorted according to the collection time;

[0035] A data extraction module, used for batch extracting speed data, acceleration data, and steering angle data from the chassis data set to obtain a speed data set, an acceleration data set, and a steering angle data set;

[0036] A speed change rate calculation module, used for batch calculating the speed change rate according to the speed data in the speed data set and the collection time corresponding to the speed data, to obtain a speed change rate set;

[0037] a stability determination module, configured to determine a chassis stability category corresponding to the vehicle according to the speed data set and the acceleration data set;

[0038] a maneuverability determination module, configured to determine a chassis maneuverability category corresponding to the vehicle according to the steering angle data set and the speed change rate data set;

[0039] A display module is used to display the chassis stability category and the chassis handling category.

[0040] In the third aspect of the implementation of the present application, a vehicle is also provided, characterized in that it includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor, and when the computer program is executed by the processor, the vehicle chassis performance verification method as described above is implemented.

[0041] In the fourth aspect of the implementation of the present application, a computer-readable storage medium is also provided, characterized in that a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the vehicle chassis performance verification method as described above is implemented.

[0042] The embodiments of the present application have the following advantages:

[0043] In an embodiment of the present application, a chassis data set sent by a receiving sensor is received, wherein the chassis data set includes a plurality of chassis raw data collected at different times, the chassis raw data in the chassis data set is sorted according to the collection time, speed data, acceleration data, and steering angle data are extracted in batches from the chassis data set to obtain a speed data set, an acceleration data set, and a steering angle data set, and the speed change rate is calculated in batches according to the speed data in the speed data set and the collection time corresponding to the speed data to obtain a speed change rate set, and the chassis stability category corresponding to the vehicle is determined according to the speed data set and the acceleration data set, and the chassis handling category corresponding to the vehicle is determined according to the steering angle data set and the speed change rate data set, and the chassis stability category and the chassis handling category are displayed. The present application automatically collects chassis data through sensors and performs batch processing, which reduces manual intervention and improves the efficiency and accuracy of data processing. In addition, the present application not only extracts key data such as speed, acceleration and steering angle, but also calculates the speed change rate, so that the chassis performance can be analyzed from multiple dimensions, which improves the comprehensiveness and depth of the analysis. This application can intuitively display the chassis performance by classifying and evaluating the chassis stability category and the chassis handling category, so that engineers can quickly understand and take corresponding improvement measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art.

[0045] Figure 1 is a flowchart of a vehicle chassis performance verification method provided by an embodiment of the present application;

[0046] Figure 2 It is a structural schematic diagram of a vehicle chassis performance verification device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0047] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, each embodiment of the present application will be described in detail below in conjunction with the accompanying drawings. However, it will be appreciated by those skilled in the art that in each embodiment of the present application, many technical details are proposed in order to enable the reader to better understand the present application. However, even without these technical details and various changes and modifications based on the following embodiments, the technical scheme claimed in the present application can also be implemented. The division of the following embodiments is for the convenience of description, and the specific implementation of the present application should not constitute any limitation, and the various embodiments can be combined with each other and referenced to each other without contradiction.

[0048] Reference Figure 1, showing a step flow chart of a vehicle chassis performance verification method provided by an embodiment of the present application, which is applied to the vehicle, and a plurality of sensors are arranged on the chassis of the vehicle, and there is a communication connection between the vehicle and the sensors.

[0049] It should be noted that the vehicle may be a vehicle that needs to undergo chassis performance verification. A processor may be provided on the vehicle to process data during the chassis performance verification process. The specific data processing process may be performed on the processor or in the cloud, and this application does not impose any restrictions on this.

[0050] Chassis performance refers to the performance and capabilities of the vehicle chassis system under various working conditions, which directly affects the vehicle's handling, stability, comfort and safety. Chassis performance can include the following aspects:

[0051] Maneuverability: refers to the vehicle's ability to respond to the driver's operations, including steering accuracy, acceleration and braking sensitivity, etc. Good maneuverability means that the vehicle can quickly and accurately execute the driver's instructions.

[0052] Stability: refers to the stability of the vehicle during driving and its ability to resist external interference. A vehicle with good stability can maintain stability and reduce roll and bumps when driving at high speed, turning or encountering uneven roads.

[0053] Comfort: refers to the riding experience of the vehicle for passengers during driving, including shock absorption effect, noise control, seat comfort, etc. A vehicle with good comfort can provide a smooth and quiet riding environment.

[0054] Safety: refers to the vehicle's ability to ensure safety in an emergency, including braking performance, anti-skid capability, collision safety, etc. A vehicle with high safety can effectively protect the safety of passengers and drivers in an emergency.

[0055] In the embodiment of the present application, the chassis performance of the vehicle can be verified based on the handling and stability.

[0056] It should be noted that the vehicle chassis is equipped with a number of sensors that can collect a variety of raw parameters in real time. These raw parameters can reflect the operating status of the vehicle chassis system. The sensors can be one or more of the following sensors:

[0057] Suspension system sensors can be used to measure the height of the vehicle suspension system to reflect the vehicle's posture under different loads. They can be used to measure the displacement of the suspension system to reflect the bumps of the vehicle during driving. They can also be used to measure the pressure in the suspension system to reflect the stiffness and damping state of the suspension system.

[0058] Braking system sensors can be used to measure the pressure in the braking system to reflect the braking force of the brake. They can be used to measure the temperature of the braking system to reflect the heat load and heat dissipation of the brake. They can also be used to measure the wear of the brake pads to reflect the service life of the brake.

[0059] The steering system sensor can be used to measure the steering angle of the steering wheel to reflect the steering status of the vehicle. It can also be used to measure the torque of the steering system to reflect the power assistance of the steering system.

[0060] Tire sensors can be used to measure tire pressure and reflect the tire inflation status. They can be used to measure tire temperature and reflect the tire heat load and heat dissipation. They can also be used to measure the degree of tire wear and reflect the tire service life.

[0061] Acceleration sensors can be used to measure the longitudinal acceleration (front and rear) of a vehicle, reflecting the acceleration and braking of the vehicle. They can be used to measure the lateral acceleration (left and right) of a vehicle, reflecting the turning and side sliding of the vehicle. They can also be used to measure the vertical acceleration of a vehicle, reflecting the bumps and vibrations of the vehicle.

[0062] The gyroscope sensor can be used to measure the angular velocity of the vehicle and reflect the rotation and posture changes of the vehicle.

[0063] The vehicle speed sensor can be used to measure the speed of the vehicle and reflect the driving status of the vehicle.

[0064] The engine speed sensor can be used to measure the engine speed and reflect the engine's operating status.

[0065] Oil pressure sensor can be used to measure the oil pressure of the engine and chassis system, reflecting the status of the lubrication and hydraulic system.

[0066] In the embodiment of the present application, data such as acceleration, vehicle speed, steering angle, etc. can be collected through acceleration sensors, vehicle speed sensors, and steering system sensors.

[0067] The method may specifically include the following steps:

[0068] Step 101, receiving a chassis data set sent by the sensor; wherein the chassis data set includes a plurality of chassis raw data collected at different times, and the chassis raw data in the chassis data set are sorted according to the collection time.

[0069] It should be noted that the chassis data set may be a large number of chassis raw data collected by several chassis sensors at different times, and the chassis raw data in the chassis data set may be sorted according to the collection time. In the embodiment of the present application, the chassis data set reflects the chassis status of the vehicle at different times.

[0070] The chassis raw data may include but is not limited to the following data: height of the vehicle suspension system, displacement of the suspension system, pressure in the suspension system, pressure in the brake system, temperature of the brake system, wear of the brake pads, steering angle of the steering wheel, torque of the steering system, air pressure of the tires, temperature of the tires, wear of the tires, longitudinal acceleration (front and rear), lateral acceleration (left and right), vertical acceleration, angular velocity of the vehicle, speed of the vehicle, engine speed, oil pressure of the engine and chassis system, etc. In the embodiment of the present application, the chassis raw data is the raw data collected by several sensors at different times.

[0071] The collection time may be a specific time point at which data is collected from various sensors. In the embodiment of the present application, a plurality of data collected at the same collection time may reflect the operating state of the vehicle chassis corresponding to the collection time.

[0072] In an embodiment of the present application, a chassis data set sent by a sensor may be received, wherein the chassis data set includes a plurality of chassis raw data collected at different times, and the chassis raw data in the chassis data set are sorted according to the collection time.

[0073] Step 102: extracting speed data, acceleration data, and steering angle data in batches from the chassis data set to obtain a speed data set, an acceleration data set, and a steering angle data set.

[0074] It should be noted that the speed data may be the speed of the vehicle measured by the vehicle speed sensor, the acceleration data may be the lateral (left-right) acceleration of the vehicle measured by the acceleration sensor, and the steering angle data may be the steering angle of the steering wheel measured by the steering system sensor.

[0075] The speed data set may be a plurality of speeds collected at different times, the acceleration data set may be a plurality of accelerations collected at different times, and the steering angle data set may be a plurality of steering angles collected at different times.

[0076] In an embodiment of the present application, speed data, acceleration data, and steering angle data may be extracted in batches from a chassis data set to obtain a speed data set, an acceleration data set, and a steering angle data set.

[0077] Step 103 , batch-calculating speed change rates according to the speed data in the speed data set and the collection moments corresponding to the speed data to obtain a speed change rate set.

[0078] It should be noted that the speed change rate may be a change rate of the vehicle speed obtained based on the speed data and the collection time, and the speed change rate set may be a change rate of the vehicle speed at multiple different times.

[0079] In the embodiment of the present application, the speed change rates can be calculated in batches according to the speed data in the speed data set and the collection moments corresponding to the speed data to obtain a speed change rate set.

[0080] Step 104 : determining a chassis stability category corresponding to the vehicle according to the speed data set and the acceleration data set.

[0081] It should be noted that the chassis stability category may refer to whether the vehicle chassis is stable or unstable. In the embodiment of the present application, the chassis stability category and the chassis handling category may be displayed. In the embodiment of the present application, the chassis handling category may be used to represent the stability of the vehicle.

[0082] In the embodiment of the present application, the chassis stability category corresponding to the vehicle may be determined based on the speed data set and the acceleration data set.

[0083] Step 105 : determining a chassis handling category corresponding to the vehicle according to the steering angle data set and the speed change rate data set.

[0084] It should be noted that the chassis handling category may refer to good vehicle handling or poor vehicle chassis handling. In the embodiment of the present application, the chassis handling category may be used to represent the handling of the vehicle.

[0085] In the embodiment of the present application, the chassis handling category corresponding to the vehicle may be determined according to the steering angle data set and the speed change rate data set.

[0086] Step 106 : Displaying the chassis stability category and the chassis handling category.

[0087] In a specific implementation, the chassis stability category and the chassis handling category may be output to a database or a preset file for storage, and then a visualization tool such as matplotlib or Tableau may be used to display the chassis stability category and the chassis handling category.

[0088] Among them, matplotlib can be a Python drawing library for creating static, dynamic and interactive visualizations. It can be applied to data analysis, scientific research, engineering technology and other fields, and can generate various high-quality charts such as line charts, scatter plots, histograms, bar charts, pie charts, etc.

[0089] Tableau is a data visualization tool that helps users quickly transform data into interactive charts, dashboards, and reports. It also provides an intuitive drag-and-drop interface that enables users without programming experience to easily create complex visualizations.

[0090] In an embodiment of the present application, a chassis data set sent by a receiving sensor is received, wherein the chassis data set includes a plurality of chassis raw data collected at different times, the chassis raw data in the chassis data set is sorted according to the collection time, speed data, acceleration data, and steering angle data are extracted in batches from the chassis data set to obtain a speed data set, an acceleration data set, and a steering angle data set, and the speed change rate is calculated in batches according to the speed data in the speed data set and the collection time corresponding to the speed data to obtain a speed change rate set, and the chassis stability category corresponding to the vehicle is determined according to the speed data set and the acceleration data set, and the chassis handling category corresponding to the vehicle is determined according to the steering angle data set and the speed change rate data set, and the chassis stability category and the chassis handling category are displayed. The present application automatically collects chassis data through sensors and performs batch processing, which reduces manual intervention and improves the efficiency and accuracy of data processing. In addition, the present application not only extracts key data such as speed, acceleration and steering angle, but also calculates the speed change rate, so that the chassis performance can be analyzed from multiple dimensions, which improves the comprehensiveness and depth of the analysis. This application can intuitively display the chassis performance by classifying and evaluating the chassis stability category and the chassis handling category, so that engineers can quickly understand and take corresponding improvement measures.

[0091] In an optional embodiment of the present application, step 101 further includes the following sub-steps:

[0092] S11: receiving a plurality of chassis raw data sent by the sensor;

[0093] S12: performing data cleaning and / or mean filling processing on the chassis original data;

[0094] S13: The processed chassis original data are combined into the chassis data set.

[0095] It should be noted that data cleaning can be an important step before data analysis, which involves preprocessing the raw data, such as identifying and handling outliers, which may be caused by data entry errors, measurement errors or other reasons. Outliers may affect the accuracy of the analysis results, so appropriate processing is required, such as correction, deletion or adjustment with statistical methods. To ensure the quality and usability of the data. Mean filling can be a method of dealing with missing values ​​in data, which involves replacing missing values ​​with the mean of the variable.

[0096] In an embodiment of the present application, a number of chassis raw data sent by a sensor may be received, data cleaning processing and / or mean filling processing may be performed on the chassis raw data, and the processed chassis raw data may be combined into a chassis data set.

[0097] In a specific implementation, the original chassis data may be as shown in Table 1:

[0098] Table 1 Chassis original data

[0099] Timestamp Speed ​​(m / s) <![CDATA[Acceleration (m / s 2 )]]> Steering angle (degrees) 10:00 65 4 10 10:01 null 3.9 10.2 10:02 67 null 10.5 10:03 70 2 null 10:04 55 5.5 40 10:05 75 4 15

[0100] Wherein, null represents that the value is missing. It should be noted that Table 1 only uses timestamp, speed, acceleration, and steering angle as examples to illustrate the form of chassis raw data, and chassis raw data may also include other data collected by sensors.

[0101] In the specific implementation, you can use Spark's filter function to clean outliers, and then use the fillna function to fill missing values. Convert the cleaned data into a Spark DataFrame.

[0102] The filter function may be a function for cleaning outliers, the fillna function may be a function for filling missing values, and Spark DataFrame may be a data structure in Spark, similar to a table in a relational database or a Pandas DataFrame in Python, but Spark DataFrame is used in a distributed environment.

[0103] In a specific implementation, the chassis data set may be as shown in Table 2:

[0104] Table 2 Chassis data set

[0105] Timestamp Speed ​​(m / s) <![CDATA[Acceleration (m / s 2 )]]> Steering angle (degrees) 10:00 65 4 10 10:01 66.4 3.9 10.2 10:02 67 3.88 10.5 10:03 70 2 17.14 10:04 55 5.5 40 10:05 75 4 15

[0106] It should be noted that Table 2 only uses timestamp, speed, acceleration, and steering angle as examples to illustrate the form of the chassis data set, and the chassis data set may also include other data collected by sensors.

[0107] In an optional embodiment of the present application, step 102 further includes the following sub-steps:

[0108] S21: extracting the speed data in batches from the chassis data set, and sorting the speed data according to the collection time to obtain the speed data set;

[0109] S22: extracting the acceleration data in batches from the chassis data set, and sorting the acceleration data according to the collection time to obtain the acceleration data set;

[0110] S23: extracting the steering angle data in batches from the chassis data set, and sorting the steering angle data according to the collection time to obtain the steering angle data set.

[0111] In an embodiment of the present application, speed data can be extracted in batches from a chassis data set, and the speed data can be sorted according to the collection time to obtain a speed data set. Acceleration data can be extracted in batches from a chassis data set, and the acceleration data can be sorted according to the collection time to obtain an acceleration data set. Steering angle data can be extracted in batches from a chassis data set, and the steering angle data can be sorted according to the collection time to obtain a steering angle data set.

[0112] In a specific implementation, the select function can be used to select key features. In Apache Spark, the select function can be used to select key feature columns in a DataFrame. The speed data set can be the speed column in Table 2 above, the acceleration data set can be the acceleration column in Table 2 above, and the steering angle data set can be the steering angle column in Table 2 above.

[0113] In an optional embodiment of the present application, step 103 further includes the following sub-steps:

[0114] S31: batch calculating the speed change rate at the current collection moment according to the speed data at the current collection moment in the speed data set and the speed data at the previous collection moment in the speed data set;

[0115] S32: Sort the speed change rates according to the collection time to obtain the speed change rate set.

[0116] In an embodiment of the present application, the speed change rate at the current collection moment can be calculated in batches based on the speed data at the current collection moment in the speed data set and the speed data at the previous collection moment in the speed data set, and then the speed change rates are sorted according to the collection moments to obtain a speed change rate set.

[0117] In a specific implementation, the chassis data including the speed change rate set may be as shown in Table 3:

[0118] Table 3 includes chassis data for speed change rate set

[0119]

[0120] In the specific implementation, the withColumn and lag functions can be used to calculate derived features such as the speed change rate. The withColumn function can be used to add a new column or replace an existing column. In the embodiment of the present application, a column of speed change rate can be added. The lag function can be used to calculate the lag value, that is, the value of the previous row or previous rows. The present application uses the lag function to calculate the speed change rate based on the speed of the previous row and the speed of the current row. The code can refer to the following example:

[0121] from pyspark.sql.functions import col,lag

[0122] from pyspark.sql.window import Window

[0123] # Calculate the speed change rate

[0124] window = Window.orderBy("timestamp")

[0125] df = df.withColumn("Speed ​​change rate",(col("Speed ​​(m / s)")-lag(col("Speed ​​(m / s)"),1).over(window)) / lag(col("Speed ​​(m / s)"),1).over(window))

[0126] df.show()

[0127] In an optional embodiment of the present application, step 104 further includes the following sub-steps:

[0128] S41: for any collection moment, if the speed data at the collection moment in the speed data set is greater than a first preset threshold, and the acceleration data at the collection moment in the acceleration data set is less than a second preset threshold, then determining that the chassis stability category corresponding to the vehicle at the collection moment is the first stability category;

[0129] S42: If the speed data at the collection moment in the speed data set is less than or equal to a first preset threshold, or the acceleration data at the collection moment in the acceleration data set is greater than or equal to a second preset threshold, then it is determined that the chassis stability category corresponding to the vehicle at the collection moment is the second stability category, and the first stability category is better than the second stability category.

[0130] It should be noted that the first stability category may mean that the chassis stability is stable. The second stability category may mean that the chassis stability is unstable. The first stability category is better than the second stability category, which may mean that the chassis stability corresponding to the first stability category is more stable than the chassis stability corresponding to the second stability category.

[0131] In the embodiment of the present application, for any collection time, if the speed data at the collection time in the speed data set is greater than the first preset threshold, and the acceleration data at the collection time in the acceleration data set is less than the second preset threshold, then it can be determined that the chassis stability category corresponding to the vehicle at the collection time is the first stability category. If the speed data at the collection time in the speed data set is less than or equal to the first preset threshold, or the acceleration data at the collection time in the acceleration data set is greater than or equal to the second preset threshold, then it can be determined that the chassis stability category corresponding to the vehicle at the collection time is the second stability category, and the first stability category is better than the second stability category.

[0132] Among them, the first preset threshold and the second preset threshold can be set according to actual needs.

[0133] In the specific implementation, you can use the when function to calculate the stability index according to predefined conditions. The when function is a conditional function in the pyspark.sql.functions module, which can calculate the value of the new column according to predefined conditions.

[0134] The predefined condition of the stability indicator can be that for each row of data, check whether the speed is greater than 60m / s and whether the acceleration is less than 5m / s 2 .

[0135] In the new stability column, you can mark samples that meet predefined conditions as "stable", otherwise they are marked as "unstable".

[0136] The calculation code of the stability index can refer to the following example:

[0137] df = df.withColumn ("Stability Index", when ((col ("Speed ​​(m / s)")>60) & (col ("Acceleration (m / s 2 )")<5),"stable").otherwise("unstable"))

[0138] In an optional embodiment of the present application, step 105 further includes the following sub-steps:

[0139] S51: for any collection moment, if the steering angle data at the collection moment in the steering angle data set is less than a third preset threshold, and the speed change rate data at the collection moment in the speed change rate set is within a first preset interval, then determining that the chassis maneuverability category corresponding to the vehicle at the collection moment is the first maneuverability category;

[0140] S52: If the steering angle data at the collection moment in the steering angle data set is greater than or equal to a third preset threshold, or the speed change rate data at the collection moment in the speed change rate set is not in a first preset interval, then it is determined that the chassis maneuverability category corresponding to the vehicle at the collection moment is the second maneuverability category, and the first maneuverability category is better than the second maneuverability category.

[0141] It should be noted that the first handling category may mean that the chassis handling is good. The second handling category may mean that the chassis handling is poor. The first handling category is better than the second handling category, which may mean that the chassis handling corresponding to the first handling category is better than the chassis handling corresponding to the second handling category.

[0142] In the embodiment of the present application, for any collection time, if the steering angle data at the collection time in the steering angle data set is less than the third preset threshold, and the speed change rate data at the collection time in the speed change rate set is within the first preset interval, then it can be determined that the chassis maneuverability category corresponding to the vehicle at the collection time is the first maneuverability category;

[0143] If the steering angle data at the collection time in the steering angle data set is greater than or equal to the third preset threshold, or the speed change rate data at the collection time in the speed change rate set is not in the first preset interval, it can be determined that the chassis controllability category corresponding to the vehicle at the collection time is the second controllability category, and the first controllability category is better than the second controllability category.

[0144] Among them, the first preset interval and the third preset threshold can be set according to actual needs.

[0145] In the specific implementation, the when function can be used to calculate the controllability index according to predefined conditions.

[0146] The predefined conditions of the maneuverability index may be to check, for each row of data, whether the steering angle is less than 20 degrees and whether the speed change rate is between -0.2 and 0.2.

[0147] In the new Handling column, you can mark items that meet predefined criteria as "Good" and items that do not meet predefined criteria as "Poor".

[0148] The calculation code of the stability index can refer to the following example:

[0149] df = df.withColumn("Handling index", when((col("Steering angle (degrees)") < 20) & (col("Speed ​​change rate"). between(-0.2, 0.2)), "Good"). otherwise("Bad"))

[0150] In an optional embodiment of the present application, step 106 further includes the following sub-steps:

[0151] S61: sorting the chassis stability categories according to the collection time to obtain the chassis stability category set;

[0152] S62: Sort the chassis handling categories according to the collection time to obtain the chassis handling category set;

[0153] S63: Displaying the chassis stability category set and the chassis handling category set.

[0154] It should be noted that the chassis stability category set may reflect the chassis stability category corresponding to the data collected by the sensor at different times. The chassis maneuverability category set may reflect the chassis maneuverability category corresponding to the data collected by the sensor at different times.

[0155] In an embodiment of the present application, the chassis stability categories can be sorted according to the collection time to obtain a chassis stability category set, and the chassis controllability categories can be sorted according to the collection time to obtain a chassis controllability category set, and the chassis stability category set and the chassis controllability category set can be displayed.

[0156] In a specific implementation, the chassis data including the chassis stability category set and the chassis handling category set may be as shown in Table 4:

[0157] Table 4 Chassis data including chassis stability category set and chassis handling category set

[0158]

[0159] In the embodiment of the present application, in addition to displaying the chassis stability category set and the chassis handling category set, other data in the chassis data and the association relationship between them can also be displayed, for example, the relationship between speed and acceleration can be displayed. The example code is as follows:

[0160] # Output the calculation results to a database or file

[0161] result_data.write.mode('overwrite').format('parquet').save(' / path / to / save / result')

[0162] #Visual display (assuming the relationship between speed and acceleration is displayed)

[0163] import matplotlib.pyplot as plt

[0164] #Example Visualization

[0165] Speed ​​= [65, 66.4, 67, 70, 55, 75]

[0166] acceleration = [4,4.9,3.88,2,5.5,4]

[0167] plt.figure(figsize=(10,6))

[0168] plt.scatter(speed, acceleration, c = 'blue', alpha = 0.5)

[0169] plt.xlabel('Speed ​​(m / s)')

[0170] plt.ylabel('Acceleration (m / s 2 )')

[0171] plt.title('Relationship between speed and acceleration')

[0172] plt.grid(True)

[0173] plt.show()

[0174] Reference Figure 2 , shows a schematic structural diagram of a vehicle chassis performance verification device provided by an embodiment of the present application, which is applied to the vehicle, and a plurality of sensors are arranged on the chassis of the vehicle, and a communication connection is established between the vehicle and the sensors, and the device includes:

[0175] The data collection module 201 is used to receive the chassis data set sent by the sensor; wherein the chassis data set includes a plurality of chassis raw data collected at different times, and the chassis raw data in the chassis data set are sorted according to the collection time;

[0176] The data extraction module 202 is used to extract speed data, acceleration data, and steering angle data in batches from the chassis data set to obtain a speed data set, an acceleration data set, and a steering angle data set;

[0177] The speed change rate calculation module 203 is used to batch calculate the speed change rate according to the speed data in the speed data set and the collection time corresponding to the speed data to obtain a speed change rate set;

[0178] A stability determination module 204, configured to determine a chassis stability category corresponding to the vehicle according to the speed data set and the acceleration data set;

[0179] A maneuverability determination module 205, configured to determine a chassis maneuverability category corresponding to the vehicle according to the steering angle data set and the speed change rate data set;

[0180] The display module 206 is used to display the chassis stability category and the chassis handling category.

[0181] In an optional embodiment of the present application, the data collection module 201 includes:

[0182] A chassis raw data receiving module, used for receiving a plurality of chassis raw data sent by the sensor;

[0183] A chassis raw data processing module, used for performing data cleaning and / or mean filling processing on the chassis raw data;

[0184] The chassis data set acquisition module is used to form the chassis data set from the processed chassis raw data.

[0185] In an optional embodiment of the present application, the data extraction module 202 includes:

[0186] A speed data set acquisition module, used for batch extracting the speed data from the chassis data set, sorting the speed data according to the collection time, and obtaining the speed data set;

[0187] An acceleration data set acquisition module, used to extract the acceleration data in batches from the chassis data set, sort the acceleration data according to the acquisition time, and obtain the acceleration data set;

[0188] The steering angle data set acquisition module is used to extract the steering angle data in batches from the chassis data set, sort the steering angle data according to the collection time, and obtain the steering angle data set.

[0189] In an optional embodiment of the present application, the speed change rate calculation module 203 includes:

[0190] A speed change rate calculation module, used for batch calculating the speed change rate at the current collection moment according to the speed data at the current collection moment in the speed data set and the speed data at the previous collection moment in the speed data set;

[0191] The speed change rate set acquisition module is used to sort the speed change rates according to the collection time to obtain the speed change rate set.

[0192] In an optional embodiment of the present application, the stability determination module 204 includes:

[0193] a first stability category determination module, configured to determine, for any collection moment, if the speed data at the collection moment in the speed data set is greater than a first preset threshold, and the acceleration data at the collection moment in the acceleration data set is less than a second preset threshold, then determine that the chassis stability category corresponding to the vehicle at the collection moment is the first stability category;

[0194] A second stability category determination module is used to determine that the chassis stability category corresponding to the vehicle at the collection moment is the second stability category if the speed data at the collection moment in the speed data set is less than or equal to a first preset threshold, or the acceleration data at the collection moment in the acceleration data set is greater than or equal to a second preset threshold, and the first stability category is better than the second stability category.

[0195] In an optional embodiment of the present application, the maneuverability determination module 205 includes:

[0196] a first maneuverability category determination module, configured to determine, for any collection moment, if the steering angle data at the collection moment in the steering angle data set is less than a third preset threshold, and the speed change rate data at the collection moment in the speed change rate set is within a first preset interval, then determine that the chassis maneuverability category corresponding to the vehicle at the collection moment is the first maneuverability category;

[0197] The second maneuverability category determination module is used to determine that the chassis maneuverability category corresponding to the vehicle at the collection moment is the second maneuverability category, and the first maneuverability category is better than the second maneuverability category, if the steering angle data at the collection moment in the steering angle data set is greater than or equal to a third preset threshold, or the speed change rate data at the collection moment in the speed change rate set is not in a first preset interval.

[0198] In an optional embodiment of the present application, the display module 206 includes:

[0199] A chassis stability category set acquisition module, used for sorting the chassis stability categories according to the collection time to obtain the chassis stability category set;

[0200] A chassis handling category set acquisition module, used to sort the chassis handling categories according to the collection time to obtain the chassis handling category set;

[0201] The display submodule is used to display the chassis stability category set and the chassis handling category set.

[0202] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0203] An embodiment of the present application also provides a vehicle, which may include a processor, a memory, and a computer program stored in the memory and capable of running on the processor. When the computer program is executed by the processor, the vehicle air-conditioning system parameter calibration method as described above is implemented.

[0204] An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the vehicle air-conditioning system parameter calibration method as described above is implemented.

[0205] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0206] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0207] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, devices, or computer program products. Therefore, the embodiments of the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the embodiments of the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0208] The embodiments of the present application are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0209] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0210] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0211] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present application.

[0212] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the above elements.

[0213] The vehicle chassis performance verification method, device, vehicle and medium provided are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A vehicle chassis performance verification method, It is characterized in that Applied to the vehicle, a plurality of sensors are arranged on the chassis of the vehicle, and a communication connection is established between the vehicle and the sensors. The method comprises: Receiving a chassis data set sent by the sensor; wherein the chassis data set includes a plurality of chassis raw data collected at different times, and the chassis raw data in the chassis data set are sorted according to the collection time; Extracting speed data, acceleration data, and steering angle data in batches from the chassis data set to obtain a speed data set, an acceleration data set, and a steering angle data set; The speed change rates are calculated in batches according to the speed data in the speed data set and the collection time corresponding to the speed data to obtain a speed change rate set; determining a chassis stability category corresponding to the vehicle according to the speed data set and the acceleration data set; Determining a chassis handling category corresponding to the vehicle according to the steering angle data set and the speed change rate data set; The chassis stability category and the chassis handling category are displayed.

2. The method according to claim 1, It is characterized in that The receiving the chassis data set sent by the sensor includes: Receiving a plurality of chassis raw data sent by the sensor; Performing data cleaning and / or mean filling processing on the original chassis data; The processed chassis raw data are combined into the chassis data set.

3. The method according to claim 1, It is characterized in that The batch extracting of speed data, acceleration data, and steering angle data from the chassis data set to obtain a speed data set, an acceleration data set, and a steering angle data set includes: Extracting the speed data in batches from the chassis data set, and sorting the speed data according to the collection time to obtain the speed data set; Extracting the acceleration data in batches from the chassis data set, and sorting the acceleration data according to the collection time to obtain the acceleration data set; The steering angle data are extracted in batches from the chassis data set, and the steering angle data are sorted according to the collection time to obtain the steering angle data set.

4. The method according to claim 3, It is characterized in that The batch calculating the speed change rate according to the speed data in the speed data set and the collection time corresponding to the speed data to obtain the speed change rate set includes: Batch calculating the speed change rate at the current collection moment according to the speed data at the current collection moment in the speed data set and the speed data at the previous collection moment in the speed data set; The speed change rates are sorted according to the collection time to obtain the speed change rate set.

5. The method according to claim 4, It is characterized in that The determining, according to the speed data set and the acceleration data set, a chassis stability category corresponding to the vehicle, comprises: For any collection moment, if the speed data at the collection moment in the speed data set is greater than a first preset threshold, and the acceleration data at the collection moment in the acceleration data set is less than a second preset threshold, it is determined that the chassis stability category corresponding to the vehicle at the collection moment is the first stability category; If the speed data at the collection moment in the speed data set is less than or equal to a first preset threshold, or the acceleration data at the collection moment in the acceleration data set is greater than or equal to a second preset threshold, then it is determined that the chassis stability category corresponding to the vehicle at the collection moment is the second stability category, and the first stability category is better than the second stability category.

6. The method according to claim 5, It is characterized in that The determining the chassis handling category corresponding to the vehicle according to the steering angle data set and the speed change rate data set comprises: For any collection moment, if the steering angle data at the collection moment in the steering angle data set is less than a third preset threshold, and the speed change rate data at the collection moment in the speed change rate set is within a first preset interval, then it is determined that the chassis maneuverability category corresponding to the vehicle at the collection moment is the first maneuverability category; If the steering angle data at the collection moment in the steering angle data set is greater than or equal to a third preset threshold, or the speed change rate data at the collection moment in the speed change rate set is not in a first preset interval, then it is determined that the chassis maneuverability category corresponding to the vehicle at the collection moment is the second maneuverability category, and the first maneuverability category is better than the second maneuverability category.

7. The method according to claim 6, It is characterized in that The display of the chassis stability category and the chassis handling category includes: Sort the chassis stability categories according to the collection time to obtain the chassis stability category set; Sort the chassis handling categories according to the collection time to obtain the chassis handling category set; The chassis stability category set and the chassis handling category set are displayed.

8. A vehicle chassis performance verification device, It is characterized in that Applied to the vehicle, a plurality of sensors are arranged on the chassis of the vehicle, and a communication connection is established between the vehicle and the sensors. The device comprises: A data collection module, configured to receive a chassis data set sent by the sensor; wherein the chassis data set includes a plurality of chassis raw data collected at different times, and the chassis raw data in the chassis data set are sorted according to the collection time; A data extraction module, used to extract speed data, acceleration data, and steering angle data in batches from the chassis data set to obtain a speed data set, an acceleration data set, and a steering angle data set; A speed change rate calculation module, used for batch calculating the speed change rate according to the speed data in the speed data set and the collection time corresponding to the speed data, to obtain a speed change rate set; a stability determination module, configured to determine a chassis stability category corresponding to the vehicle according to the speed data set and the acceleration data set; a maneuverability determination module, configured to determine a chassis maneuverability category corresponding to the vehicle according to the steering angle data set and the speed change rate data set; A display module is used to display the chassis stability category and the chassis handling category.

9. A vehicle, It is characterized in that The method comprises a processor, a memory and a computer program stored in the memory and capable of running on the processor, wherein when the computer program is executed by the processor, the vehicle chassis performance verification method as claimed in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, It is characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the vehicle chassis performance verification method according to any one of claims 1 to 7 is implemented.

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