A wheel motion law curve method, device and storage medium

Abstract

The present invention discloses a method, device and storage medium for determining a wheel motion law curve. The method part obtains the operating data of a vehicle in an actual usage scenario, the operating data including the vehicle's wheel instantaneous acceleration data, wheel instantaneous speed data and steering wheel instantaneous angle data, and then determines the vehicle's wheel bounce and rotation corresponding relationship data based on the wheel instantaneous acceleration data, wheel instantaneous speed data and steering wheel instantaneous angle data. Finally, the wheel motion law curve is determined based on the wheel bounce and rotation relationship data of different vehicles. In the present invention, the wheel motion law curve is determined by using big data means, and the sample data used is huge and the sample data is actual working condition data, which can significantly reduce data errors, improve data accuracy and diversity, provide a large amount of accurate basic data for obtaining the wheel motion law, and ensure the accuracy of the wheel motion law curve.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle manufacturing, and in particular to a wheel motion law curve method, device and storage medium. Background Art

[0002] During vehicle driving, the wheels experience both vertical wheel hop motion and steering motion around the kingpin axis. The relationship between wheel hop motion and steering motion is called the wheel motion relationship, also known as the wheel motion law. Tire envelope design is affected to a certain extent by the wheel motion law.

[0003] Traditionally, wheel motion laws used in tire envelope design are often developed through road testing, using wheel motion data from the test process. These wheel motion laws, however, utilize limited wheel motion data and exhibit significant discrepancies with actual vehicle operating conditions. These laws lack accurate foundational data, resulting in low accuracy. Summary of the Invention

[0004] The present invention provides a wheel motion law curve method, device and storage medium to solve the problem in the prior art that the wheel motion law has no accurate basic data support, resulting in low accuracy of the wheel motion law.

[0005] A method for determining a wheel motion law curve, comprising:

[0006] Acquiring operating data of the vehicle in an actual usage scenario, the operating data including instantaneous wheel acceleration data, instantaneous wheel speed data, and instantaneous steering wheel angle data of the vehicle;

[0007] Determining wheel bounce and rotation correspondence data of the vehicle according to the instantaneous acceleration data of the vehicle wheels, the instantaneous rotation speed data of the wheels, and the instantaneous steering wheel angle data;

[0008] The wheel motion law curve is determined based on the wheel bounce and rotation relationship data of different vehicles.

[0009] Furthermore, the determining of the wheel bounce and rotation correspondence data of the vehicle based on the instantaneous acceleration data of the vehicle wheels, the instantaneous rotation speed data of the wheels, and the instantaneous steering wheel angle data includes:

[0010] determining wheel hop displacement data of the vehicle at different moments according to the wheel instantaneous acceleration data and the wheel instantaneous speed data;

[0011] Determining the maximum wheel runout displacement and the maximum steering angle of the steering wheel;

[0012] Dividing each wheel jump position in the wheel jump displacement data by the maximum jump displacement to obtain wheel jump travel percentage data of the vehicle at different times;

[0013] Dividing each instantaneous steering wheel angle in the instantaneous steering wheel angle data by the maximum turning angle to obtain steering stroke percentage data of the vehicle at different moments;

[0014] The wheel hop displacement percentage data is matched with the steering stroke percentage data at the same moment to obtain the wheel hop and rotation correspondence data.

[0015] Furthermore, determining the wheel hop displacement data of the vehicle at different moments based on the wheel instantaneous acceleration data and the wheel instantaneous speed data includes:

[0016] performing error correction on the wheel instantaneous acceleration data to obtain corrected instantaneous acceleration data;

[0017] performing a secondary integration operation on the modified instantaneous acceleration data according to the instantaneous wheel speed data to obtain initial wheel hop displacement data of the vehicle at different moments;

[0018] Compensation correction is performed on the initial wheel hop displacement data to obtain wheel hop displacement data of the vehicle at different moments.

[0019] Furthermore, performing error correction on the wheel instantaneous acceleration data to obtain corrected instantaneous acceleration data includes:

[0020] Determine gravitational acceleration and measurement instrument errors;

[0021] Filtering the wheel instantaneous acceleration data to obtain denoised instantaneous acceleration data after eliminating random errors;

[0022] The corrected instantaneous acceleration data is determined based on the denoised instantaneous acceleration data, the gravitational acceleration, and the measurement instrument error.

[0023] Furthermore, the determining the corrected instantaneous acceleration data according to the denoised instantaneous acceleration data, the gravitational acceleration and the measuring instrument error includes:

[0024] A coordinate system is established with the axis of the vehicle wheel as the origin, the forward direction of the vehicle is the y-axis, the horizontal direction of the vehicle is the x-axis, and the vertical direction of the vehicle is the z-axis;

[0025] Determining the z-axis acceleration of the wheel in the z-axis direction in the noise-removed instantaneous acceleration data;

[0026] Subtracting the gravity acceleration from all the z-axis accelerations to obtain first wheel acceleration data;

[0027] The measuring instrument error is subtracted from all accelerations in the first wheel acceleration data to obtain the corrected instantaneous acceleration data.

[0028] Furthermore, performing a secondary integration operation on the modified instantaneous acceleration data according to the instantaneous wheel speed data to obtain initial wheel hop displacement data of the vehicle at different moments includes:

[0029] Determining a wheel motion cycle of the vehicle according to the wheel instantaneous speed data, wherein the wheel motion cycle is a duration from a start moment to an end moment of the wheel motion in the wheel instantaneous speed data;

[0030] Dividing the corrected instantaneous acceleration data into a plurality of groups of preset data including wheel accelerations at different times according to the starting time and the ending time;

[0031] Determining the wheel acceleration at each moment in the preset data, wherein the wheel acceleration includes accelerations in multiple directions;

[0032] performing a quadratic integration operation on the accelerations in the multiple directions to obtain multiple initial wheel hop displacements;

[0033] The multiple wheel hop displacements at different moments are aggregated to obtain initial wheel hop displacement data of the vehicle at different moments.

[0034] Furthermore, compensating and correcting the initial wheel hop displacement data to obtain wheel hop displacement data of the vehicle at different moments includes:

[0035] Determining a starting time speed and an ending time speed from the instantaneous wheel speed data;

[0036] Determining the acceleration at the start time in the corrected instantaneous acceleration data;

[0037] Determine the starting time round jump displacement in the initial round jump displacement data;

[0038] Determining a compensation parameter based on the wheel motion cycle, the wheel hop displacement at the start time, the acceleration at the start time, the speed at the start time, and the speed at the end time;

[0039] Compensation calculation is performed on each wheel hop displacement in the initial wheel hop displacement data according to the compensation parameter to obtain wheel hop displacement data of the vehicle at different moments.

[0040] Furthermore, determining the wheel motion law curve based on the wheel bounce and rotation correspondence data of different vehicles includes:

[0041] According to the corresponding relationship, all the wheel bounce and rotation corresponding relationship data are made into a scatter plot;

[0042] Some noise points in the scatter plot are eliminated and the boundary of the scatter plot is fitted to obtain the wheel motion law curve.

[0043] A device for determining a wheel motion law curve, comprising:

[0044] An acquisition module is used to acquire operating data of a vehicle in an actual usage scenario, wherein the operating data includes instantaneous acceleration data of the wheels, instantaneous rotational speed data of the wheels, and instantaneous steering wheel angle data of the vehicle;

[0045] a first determining module, configured to determine wheel bounce and rotation correspondence data of the vehicle based on the instantaneous acceleration data of the vehicle's wheels, the instantaneous rotation speed data of the wheels, and the instantaneous steering wheel angle data;

[0046] The second determination module is used to determine the wheel motion law curve according to the wheel bounce and rotation relationship data of different vehicles.

[0047] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned method for determining a wheel motion law curve are implemented.

[0048] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned method for determining a wheel motion law curve.

[0049] In one solution provided by the above-mentioned wheel motion law curve determination method, device and storage medium, the operating data of the vehicle in the actual use scenario is obtained, and the operating data includes the vehicle's wheel instantaneous acceleration data, wheel instantaneous speed data and steering wheel instantaneous angle data, and then the vehicle's wheel bounce and rotation correspondence data are determined based on the wheel instantaneous acceleration data, wheel instantaneous speed data and steering wheel instantaneous angle data, and finally the wheel motion law curve is determined based on the wheel bounce and rotation relationship data of different vehicles; in the present invention, by obtaining the operating data of different vehicles in actual use scenarios and using big data means to obtain the wheel motion law curve, the amount of sample data used is huge and the sample data is actual working condition data, which can significantly reduce data errors, improve data accuracy and diversity, provide a large amount of accurate basic data for obtaining the wheel motion law, and ensure the accuracy of the wheel motion law curve. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0051] Figure 1 Schematic diagram of the installation position of the sensor on the wheel in one embodiment of the present invention;

[0052] Figure 2 yes Figure 1 A partial enlarged schematic diagram;

[0053] Figure 3 This is a flow chart of a method for determining a wheel motion law curve according to an embodiment of the present invention;

[0054] Figure 4 It is a scatter plot of wheel runout and rotation relationship data for different vehicles;

[0055] Figure 5 2 is a schematic structural diagram of a device for determining a wheel motion law curve in one embodiment of the present invention;

[0056] Figure 6 FIG. 1 is another structural diagram of a device for determining a wheel motion law curve in one embodiment of the present invention.

[0057] Among them, the reference numerals in the figures are:

[0058] 1-Acceleration sensor; 2-Wheel speed sensor; 3-Wheel. DETAILED DESCRIPTION

[0059] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0060] The wheel motion law curve determination method provided in an embodiment of the present invention can be applied to a wheel motion law curve determination system. The wheel motion law curve determination system includes a large number of vehicles and a wheel motion law curve determination device, wherein the vehicles and the wheel motion law curve determination device communicate via a network for data transmission. The wheel motion law curve determination device obtains vehicle operating data in actual use scenarios via the network. The operating data includes the vehicle's wheel instantaneous acceleration data, wheel instantaneous speed data, and steering wheel instantaneous angle data. The vehicle's wheel runout and rotation correspondence data are then determined based on the wheel instantaneous acceleration data, wheel instantaneous speed data, and steering wheel instantaneous angle data. Finally, a wheel motion law curve is determined based on the wheel runout and rotation relationship data of different vehicles to improve the accuracy of the wheel motion law curve, facilitate the subsequent design of more accurate tire envelope data based on the wheel motion law curve, and use the wheel runout and rotation relationship data of different vehicles for other chassis-related R&D work to guide the correction of simulation models. In addition, the vehicle operating data can be differentiated based on different vehicle models and user groups to obtain wheel motion law curves that suit different vehicle models or user groups.

[0061] The wheel motion law curve determination device can be a vehicle manufacturer's data center. After receiving a large amount of vehicle operating data via the cloud, the data center analyzes and processes the data to obtain wheel runout and rotation relationship data for different vehicles, thereby determining the wheel motion law curve. The data center can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0062] The above vehicle includes an acceleration sensor, a wheel speed sensor, a steering wheel angle sensor and a vehicle controller module. Figure 1 and Figure 2 As shown, acceleration sensors 1 are set on the front and rear axle joints of the vehicle's wheels 3 to collect instantaneous acceleration of the wheels, wheel speed sensors 2 are set on the wheels to collect instantaneous rotational speed of the wheels, and a steering wheel angle sensor is set on the vehicle steering wheel to collect instantaneous angle of the steering wheel. The vehicle-mounted controller is fixed to the vehicle through a bracket, receives the instantaneous acceleration value of the wheels collected by the acceleration sensor, the instantaneous rotational speed of the wheels collected by the wheel speed sensor, and the instantaneous angle of the steering wheel collected by the steering wheel angle sensor, and sends them to the cloud through a wireless remote module so that the data center can receive and collect them.

[0063] Among them, the wheel speed sensor can be the wheel speed sensor equipped with the original vehicle, the steering wheel angle sensor can be the steering wheel angle sensor equipped with the original vehicle, and the on-board controller can be the vehicle ECU. The steering wheel angle sensor collects the instantaneous angle of the steering wheel and can directly read the sensor signal from the CAN bus to obtain the instantaneous angle of the steering wheel.

[0064] In this embodiment, the vehicle includes a wheel speed sensor, a steering wheel angle sensor and an on-board controller module for exemplary purposes only. In other embodiments, the vehicle also includes a detection module and a fixed bracket. The detection module can be a square component containing an acceleration sensor. The fixed bracket can be manufactured according to the detection module. After the manufacturing is completed, the detection module is installed on the fixed bracket, and the fixed bracket can be fixed to the front and rear axle joints of the vehicle by screwing or welding.

[0065] In one embodiment, if Figure 3 As shown, a method for determining a wheel motion law curve is provided. The method is described by taking an example of a wheel motion law curve determination device in a wheel motion law curve determination system as an example, and includes the following steps:

[0066] S10: Acquire operating data of the vehicle in an actual usage scenario, where the operating data includes instantaneous acceleration data of the vehicle's wheels, instantaneous rotational speed data of the wheels, and instantaneous steering wheel angle data.

[0067] When the vehicle is running, the on-board controller receives the instantaneous wheel acceleration value collected by the acceleration sensor on the vehicle, the instantaneous wheel speed collected by the wheel speed sensor, and the instantaneous steering wheel angle collected by the steering wheel angle sensor, and sends it to the cloud through the wireless remote module. The wheel motion law curve determination device obtains the vehicle's operating data in the actual usage scenario. After collecting a certain amount of operating data, it extracts the instantaneous wheel acceleration data, instantaneous wheel speed data and instantaneous steering wheel angle data of each vehicle.

[0068] S20: Determine vehicle wheel bounce and rotation correspondence data based on the vehicle's wheel instantaneous acceleration data, wheel instantaneous rotation speed data, and steering wheel instantaneous angle data.

[0069] After obtaining the vehicle's wheel instantaneous acceleration data, wheel instantaneous speed data and steering wheel instantaneous angle data, the vehicle's wheel bounce and rotation correspondence data are determined based on the vehicle's wheel instantaneous acceleration data, wheel instantaneous speed data and steering wheel instantaneous angle data.

[0070] Among them, different steering wheel angles correspond to different wheel steering angles. According to the instantaneous wheel acceleration data and the instantaneous wheel speed data, the wheel hop motion displacement of the vehicle wheel at different times can be determined. According to the instantaneous steering wheel angle data, the steering motion displacement of the wheel at different times can be determined. The wheel hop displacement and steering displacement of the wheel at the same time are matched to obtain the corresponding relationship data of the vehicle's wheel hop and rotation.

[0071] S30: Determine a wheel motion law curve based on wheel bounce and rotation relationship data of different vehicles.

[0072] After obtaining the wheel runout and rotation relationship data of each vehicle, a wheel runout and rotation relationship curve, ie, a wheel motion law curve, is drawn based on the wheel runout and rotation relationship data of different vehicles.

[0073] In this embodiment, by obtaining the operating data of the vehicle in the actual usage scenario, the operating data includes the instantaneous acceleration data of the vehicle's wheels, the instantaneous speed data of the wheels and the instantaneous angle data of the steering wheel, and then determining the vehicle's wheel bounce and rotation correspondence data based on the instantaneous acceleration data, the instantaneous speed data and the instantaneous angle data of the steering wheel. Finally, the wheel motion law curve is determined based on the wheel bounce and rotation relationship data of different vehicles. The wheel motion law curve obtained by big data means has a huge amount of sample data and the sample data is actual working condition data, which can significantly reduce data errors, improve data accuracy and diversity, provide a large amount of accurate basic data for obtaining the wheel motion law, and ensure the accuracy of the wheel motion law curve.

[0074] In one embodiment, if Figure 2 As shown, in step S20, the vehicle wheel bounce and rotation correspondence data is determined based on the vehicle wheel instantaneous acceleration data, the wheel instantaneous speed data and the steering wheel instantaneous angle data, which specifically includes the following steps:

[0075] S21: Determine wheel hop displacement data of the vehicle at different moments according to the wheel instantaneous acceleration data and the wheel instantaneous rotational speed data.

[0076] After obtaining the wheel instantaneous acceleration data, wheel instantaneous speed data and steering wheel instantaneous angle data of each vehicle, the wheel hop displacement data of the vehicle at different moments is determined according to the wheel instantaneous acceleration data and wheel instantaneous speed data.

[0077] Among them, the instantaneous wheel speed can be used as the basis for collecting the instantaneous wheel acceleration (for example, the instantaneous wheel speed of 0 is used as the basis for collecting the instantaneous wheel acceleration. When the instantaneous wheel speed is not 0, the wheel moves, and the instantaneous wheel acceleration starts to be collected at this time. When the instantaneous wheel speed is 0, the wheel stops moving, and the collection of the instantaneous wheel speed is stopped at this time, thereby obtaining the instantaneous wheel speed data within the wheel movement cycle). After collecting the instantaneous wheel acceleration, the instantaneous wheel acceleration at the same moment is integrated to obtain the wheel hop speed at that moment, that is, the jumping speed of the wheel at that moment. The wheel hop speed at that moment is then integrated to obtain the wheel hop displacement at that moment, and then the wheel hop displacement data of the vehicle at different moments can be obtained.

[0078] S22: Determine the maximum bouncing displacement of the wheel and determine the maximum steering angle of the steering wheel.

[0079] At the same time, it is also necessary to determine the maximum runout displacement of the wheel (tire runout displacement) to determine the wheel runout percentage, and to determine the maximum steering wheel angle to determine the steering travel percentage.

[0080] S23: Each wheel jump position in the wheel jump displacement data is divided by the maximum wheel jump displacement to obtain wheel jump travel percentage data of the vehicle at different times.

[0081] After obtaining the wheel hop displacement data of the vehicle at different times and the maximum wheel hop displacement, each wheel hop position in the wheel hop displacement data is divided by the maximum wheel hop displacement to obtain the wheel hop travel percentage data of the vehicle at different times.

[0082] For example, the tire runout displacement at time t is s(t), and the maximum tire runout displacement is s max , then the wheel jump stroke percentage F at time t is: After obtaining the wheel hop travel percentage F at each moment, the wheel hop travel percentage F at different moments are summarized to obtain wheel hop travel percentage data of the vehicle at different moments.

[0083] S24: Divide each instantaneous steering wheel angle in the instantaneous steering wheel angle data by the maximum turning angle to obtain steering stroke percentage data of the vehicle at different moments.

[0084] After determining the maximum steering wheel angle, each steering wheel instantaneous angle in the steering wheel instantaneous angle data is divided by the maximum steering wheel angle to obtain steering stroke percentage data of the vehicle at different moments.

[0085] For example, let the steering wheel angle at time t be ωω and the maximum steering wheel angle be ω max , then the steering stroke percentage I at time t is: After obtaining the steering stroke percentage I at each moment, the steering stroke percentages I at different moments are summarized to obtain steering stroke percentage data of the vehicle at different moments.

[0086] S25: Corresponding the wheel hop displacement percentage data with the steering stroke percentage data at the same moment to obtain wheel hop and rotation correspondence data.

[0087] After obtaining the wheel hop displacement percentage data and the steering stroke percentage data at different moments, the wheel hop displacement percentage data is matched with the steering stroke percentage data at the same moment to obtain the wheel hop and rotation correspondence data.

[0088] In this embodiment, the wheel hop displacement data of the vehicle at different moments are determined based on the instantaneous wheel acceleration data and the instantaneous wheel speed data, the maximum wheel hop displacement is determined, and the maximum steering wheel angle is determined. Each wheel hop displacement in the wheel hop displacement data is divided by the maximum hop displacement to obtain the wheel hop travel percentage data of the vehicle at different moments. Each steering wheel instantaneous angle in the steering wheel instantaneous angle data is divided by the maximum angle to obtain the steering travel percentage data of the vehicle at different moments. The wheel hop displacement percentage data is corresponded with the steering travel percentage data at the same moment to obtain the wheel hop and rotation correspondence data. The steps for obtaining the wheel hop and rotation correspondence data are refined, and the wheel hop displacement percentage data is corresponded with the steering travel percentage data at the same moment, making the data more intuitive and convenient for analysis and use.

[0089] In one embodiment, step S21, i.e., determining wheel hop displacement data of the vehicle at different moments based on the wheel instantaneous acceleration data and the wheel instantaneous speed data, specifically includes the following steps:

[0090] S211: Perform error correction on the wheel instantaneous acceleration data to obtain corrected instantaneous acceleration data.

[0091] After obtaining the wheel instantaneous acceleration data, it is necessary to perform error correction on the wheel instantaneous acceleration data, including eliminating the measurement error of the wheel instantaneous acceleration collected by the acceleration sensor, removing the noise in the wheel instantaneous acceleration data, etc., so that the corrected instantaneous acceleration number is more accurate.

[0092] S212: Performing a secondary integration operation on the corrected instantaneous acceleration data according to the instantaneous wheel speed data to obtain initial wheel hop displacement data of the vehicle at different moments.

[0093] After obtaining the corrected instantaneous acceleration, the start and end times of the wheel movement are determined according to the instantaneous wheel speed in the wheel instantaneous speed data. The duration between the start and end times is the wheel movement cycle.

[0094] For example, when the instantaneous speed of the wheel is 0, the wheel stops moving, and when the instantaneous speed of the wheel is not 0, the wheel starts moving. Therefore, the preset speed of 0 can be used as the basis for collecting the instantaneous acceleration of the wheel. When the instantaneous speed of the wheel is not 0, the instantaneous acceleration of the wheel starts to be collected. When the instantaneous speed of the wheel is 0, the instantaneous speed of the wheel stops being collected. The moment of starting collection is the starting moment of the wheel motion cycle, and the moment of stopping collection is the ending moment of the wheel motion cycle, thereby obtaining the instantaneous speed data of the wheel within the wheel motion cycle, and correcting the instantaneous acceleration data of the wheel within the wheel motion cycle to obtain the corrected instantaneous acceleration data within the wheel motion cycle.

[0095] After obtaining the corrected instantaneous acceleration data within different wheel motion cycles, a secondary integration operation is performed on the corrected instantaneous acceleration at the same moment in the corrected instantaneous acceleration data to obtain the initial wheel hop displacement at that moment. Then, the initial wheel hop displacements at different moments are summarized to obtain the initial wheel hop displacement data of the vehicle at different moments.

[0096] The calculation formula is:

[0097]

[0098]

[0099] Where v(t) is the wheel hop velocity at time t, s(t) is the initial wheel hop displacement at time t, t0 is the starting time, a(t) is the wheel acceleration at time t, s(t0) is the initial wheel hop displacement at the starting time, and v(t0) is the wheel hop velocity at the starting time.

[0100] S213: Compensate and correct the initial wheel hop displacement data to obtain wheel hop displacement data of the vehicle at different times.

[0101] When acceleration sensors and speed sensors measure corresponding data, measurement errors can occur. Over time, these errors can increase, causing significant discrepancies between measured and actual values. Therefore, it's necessary to reset the acquired wheel acceleration data to ensure more accurate calculated wheel hop velocity and displacement. Therefore, after obtaining initial wheel hop displacement data, compensation corrections are performed to obtain wheel hop displacement data at different times, improving its accuracy.

[0102] In this embodiment, error correction is performed on the instantaneous acceleration data of the wheel to obtain corrected instantaneous acceleration data, and then a quadratic integration operation is performed on the corrected instantaneous acceleration data according to the instantaneous speed data of the wheel to obtain initial wheel hop displacement data of the vehicle at different moments. Finally, compensation correction is performed on the initial wheel hop displacement data to obtain wheel hop displacement data of the vehicle at different moments. The steps of determining the wheel hop displacement data of the vehicle at different moments according to the instantaneous acceleration data and the instantaneous speed data of the wheel are refined, error correction is performed on the instantaneous acceleration data of the wheel, and compensation is performed on the initial wheel hop displacement data, thereby improving the accuracy of the wheel hop displacement data and further improving the accuracy of the wheel bounce and rotation correspondence data.

[0103] In one embodiment, step S211, i.e., performing error correction on the wheel instantaneous acceleration data to obtain corrected instantaneous acceleration data, specifically includes the following steps:

[0104] S2111: Determine gravitational acceleration and measurement instrument errors.

[0105] The instrument error is the inherent error of the acceleration sensor. The instrument error for measuring instantaneous wheel acceleration data can be estimated through calibration. For example, before measurement, the sensor can be kept stationary and in a static zero-input environment. Multiple tests can be performed and the arithmetic mean of the measured values ​​can be used as an estimate of the instrument error.

[0106] S2112: Filter the wheel instantaneous acceleration data to obtain denoised instantaneous acceleration data after eliminating random errors.

[0107] After obtaining the wheel instantaneous acceleration data, it is necessary to first perform filtering processing on the wheel instantaneous acceleration data to obtain denoised instantaneous acceleration data after eliminating random errors, so that the denoised instantaneous acceleration data is smoother and more accurate.

[0108] For example, Kalman filtering can be performed on wheel instantaneous acceleration data to eliminate random errors in the measurement process. Kalman filtering consists of two stages: prediction and update. In the prediction stage, the filter uses the estimate of the previous state (the previous acceleration) to estimate the current state. In the update stage, the filter uses the observed value of the current state to optimize the predicted value obtained in the prediction stage to obtain a more accurate new estimate. Inputting the wheel instantaneous acceleration data into the Kalman filter model outputs the de-noised instantaneous acceleration after eliminating random errors.

[0109] In this embodiment, performing Kalman filtering on the wheel instantaneous acceleration data is only an exemplary description. In other embodiments, other methods may be used to filter the wheel instantaneous acceleration data, which will not be described in detail here.

[0110] S2113: Determine the corrected instantaneous acceleration data based on the denoised instantaneous acceleration data, the gravitational acceleration, and the measurement instrument error.

[0111] The acceleration sensor can collect accelerations in multiple directions on the wheel. When the acceleration collected by the acceleration sensor is the acceleration in the direction perpendicular to the vehicle, the acceleration will also be affected by the acceleration of gravity, generating an offset component of the acceleration of gravity. Therefore, it is necessary to eliminate the influence of the acceleration of gravity and the error of the measuring instrument at the same time. That is, the corrected instantaneous acceleration data is determined based on the denoised instantaneous acceleration data, the acceleration of gravity, and the error of the measuring instrument to further improve the accuracy of the corrected instantaneous acceleration data.

[0112] In this embodiment, the gravitational acceleration and the measuring instrument error are determined, and then the wheel instantaneous acceleration data is filtered to obtain denoised instantaneous acceleration data after eliminating random errors. Then, the corrected instantaneous acceleration data is determined based on the denoised instantaneous acceleration data, the gravitational acceleration and the measuring instrument error. The detailed process of performing error correction on the wheel instantaneous acceleration data and obtaining the corrected instantaneous acceleration data is refined, providing a basis for obtaining the corrected instantaneous acceleration data.

[0113] In one embodiment, step S2111, i.e., determining the corrected instantaneous acceleration data based on the denoised instantaneous acceleration data, the gravitational acceleration, and the measurement instrument error, specifically includes the following steps:

[0114] S01: A coordinate system is established with the axis of the vehicle wheel as the origin, the vehicle's forward direction as the y-axis, the vehicle's horizontal direction as the x-axis, and the vehicle's vertical direction as the z-axis.

[0115] A coordinate system is established with the vehicle's wheel axis as the origin, with the vehicle's forward direction as the y-axis, the vehicle's horizontal direction as the x-axis, and the vehicle's vertical direction as the z-axis. The accelerometer can measure acceleration in three directions on the wheel: the x-axis, the y-axis, and the z-axis.

[0116] S02: Determine the z-axis acceleration of the wheel in the z-axis direction in the noise-eliminating instantaneous acceleration data.

[0117] After obtaining the filtered denoised instantaneous acceleration data, it is necessary to determine the z-axis acceleration of the wheel in the z-axis direction in the denoised instantaneous acceleration data.

[0118] S03: Subtract gravity acceleration from all z-axis accelerations to obtain first wheel acceleration data.

[0119] In the noise-eliminating instantaneous acceleration data, all z-axis accelerations are subtracted from gravity acceleration to eliminate the influence of gravity acceleration on wheel acceleration, thereby obtaining first wheel acceleration data. The first wheel acceleration data is wheel acceleration data at different moments after eliminating the influence of gravity acceleration.

[0120] S04: Subtract the measurement instrument error from all accelerations in the first wheel acceleration data to obtain corrected instantaneous acceleration data.

[0121] After the first wheel acceleration data is obtained, all accelerations in the first wheel acceleration data are subtracted by a measurement instrument error to obtain corrected instantaneous acceleration data.

[0122] In this embodiment, a coordinate system is established with the axis of the vehicle wheel as the origin, the forward direction of the vehicle is the y-axis, the horizontal direction of the vehicle is the x-axis, and the vertical direction of the vehicle is the z-axis. The z-axis acceleration of the wheel in the z-axis direction in the noise-eliminating instantaneous acceleration data is determined, the gravity acceleration is subtracted from all z-axis accelerations, and the first wheel acceleration data is obtained by summing them up. The measuring instrument error is subtracted from all accelerations in the first wheel acceleration data to obtain corrected instantaneous acceleration data. The steps of determining the corrected instantaneous acceleration data based on the noise-eliminating instantaneous acceleration data, the gravity acceleration and the measuring instrument error are clarified, the influence of the gravity acceleration on the vehicle instantaneous acceleration is eliminated, and the accuracy of the vehicle acceleration is improved.

[0123] In one embodiment, step S212, i.e., performing a quadratic integration operation on the modified instantaneous acceleration data based on the instantaneous wheel speed data to obtain the initial wheel hop displacement data of the vehicle at different moments, specifically includes the following steps:

[0124] S2121: Determine a wheel motion cycle of the vehicle based on the instantaneous wheel speed data. The wheel motion cycle is the duration from the start moment to the end moment of the wheel motion in the instantaneous wheel speed data.

[0125] The starting and ending times of the wheel motion are determined based on the wheel instantaneous speed data at different times. The duration between the starting and ending times is the wheel motion cycle.

[0126] For example, when the instantaneous speed of the wheel is 0, the wheel stops moving; when the instantaneous speed of the wheel is not 0, the wheel starts moving; when the instantaneous speed of the wheel is not 0, the wheel instantaneous acceleration is collected; when the instantaneous speed of the wheel is 0, the wheel instantaneous speed collection is stopped. The moment when collection starts is the starting moment of the wheel motion cycle, and the moment when collection stops is the ending moment of the wheel motion cycle.

[0127] S2122: Divide the corrected instantaneous acceleration data into multiple groups of preset data including wheel accelerations at different times according to the start time and the end time.

[0128] After determining the start and end times of the wheel movement, the instantaneous acceleration data is corrected and divided into multiple groups of preset data including wheel accelerations at different times according to the start and end times of the wheel movement.

[0129] S2123: Determine the wheel acceleration at each moment in the preset data, where the wheel acceleration includes accelerations in multiple directions.

[0130] After obtaining multiple sets of preset data, the wheel acceleration at each moment in the preset data will be determined, wherein the wheel acceleration at each moment includes accelerations in multiple directions, such as three accelerations of the wheel on the x-axis, y-axis and z-axis.

[0131] S2124: Perform a quadratic integration operation on the accelerations in multiple directions to obtain multiple initial wheel jump displacements.

[0132] After determining a wheel acceleration, a quadratic integration operation is performed on the wheel acceleration in multiple directions to obtain multiple initial wheel hop displacements. For example, the three accelerations on the x-axis, y-axis, and z-axis are sequentially integrated to obtain three wheel hop velocities on the x-axis, y-axis, and z-axis. Furthermore, the three wheel hop velocities are integrated to obtain three initial wheel hop displacements on the x-axis, y-axis, and z-axis.

[0133] S2125: Summarize the multiple wheel hop displacements at different times to obtain the initial wheel hop displacement data of the vehicle at different times.

[0134] After obtaining the initial wheel hop displacement at all moments in the wheel motion cycle, multiple wheel hop displacements at different moments are aggregated to obtain the initial wheel hop displacement data of the vehicle at different moments in the wheel motion cycle. This increases the data sample of the initial wheel hop displacement data and further ensures data accuracy.

[0135] In this embodiment, the wheel motion cycle of the vehicle is determined based on the instantaneous wheel speed data. The wheel motion cycle is the duration from the start moment to the end moment of the wheel motion in the instantaneous wheel speed data. The corrected instantaneous acceleration data is divided into multiple groups of preset data including wheel accelerations at different moments according to the start moment and the end moment. The wheel acceleration at each moment in the preset data is determined. The wheel acceleration includes accelerations in multiple directions. A quadratic integration operation is then performed on the accelerations in multiple directions to obtain multiple initial wheel hop displacements. Finally, the multiple wheel hop displacements at different moments are summarized to obtain the initial wheel hop displacement data of the vehicle at different moments. The detailed process of performing a quadratic integration operation on the corrected instantaneous acceleration data based on the instantaneous wheel speed data to obtain the initial wheel hop displacement data of the vehicle at different moments is refined, providing a calculation basis for obtaining the initial wheel hop displacement data.

[0136] In one embodiment, step S213, i.e., compensating and correcting the initial wheel hop displacement data to obtain wheel hop displacement data of the vehicle at different moments, specifically includes the following steps:

[0137] S2131: Determine the starting speed and the ending speed in the wheel instantaneous speed data.

[0138] S2132: Determine the acceleration at the starting time in the corrected instantaneous acceleration data.

[0139] S2133: Determine the starting moment round jump displacement in the initial round jump displacement data.

[0140] S2134: Determine compensation parameters based on the wheel motion cycle, the wheel jump displacement at the start time, the acceleration at the start time, the speed at the start time, and the speed at the end time.

[0141] S2135: Compensation calculation is performed on each wheel hop displacement in the initial wheel hop displacement data according to the compensation parameters to obtain wheel hop displacement data of the vehicle at different times.

[0142] When the vehicle is stopped, that is, when the wheel speed sensor reads a wheel speed of 0, it can be assumed that there is no wheel bounce at this time, and the wheel bounce speed is 0. Based on this setting, the reconstruction algorithm below can obtain the compensation parameters:

[0143] Assume that the quadratic polynomial for wheel jump velocity reconstruction is: vr(t)=v(t)+b1t 2 +b2t+b3;

[0144] Then the reconstruction polynomial of the displacement is:

[0145] Then the acceleration reconstruction polynomial is: ar(t) = a(t) + 2b1t + b2;

[0146] where vr(t), sr(t), and ar(t) are the wheel hop velocity, displacement, and acceleration at time t after compensation, respectively; v(t), s(t), and a(t) are the wheel hop velocity, displacement, and acceleration at time t before compensation, respectively; and b1, b2, b3, and b4 are compensation parameters.

[0147] Assuming the initial displacement sr(t0) is 0, the wheel hop velocity vr(t0) before the wheel moves is 0, and the wheel hop velocity vr after the wheel moves is f ) is 0, and the initial acceleration of the wheel ar(t0) is also 0, according to the above formula, we can get: b2=-a(t0), b3=-v(t0), b4=-s(t0), where T is the wheel motion cycle, i.e., the end time t of the wheel motion f The difference between t0 and the start time of the wheel movement.

[0148] Substituting the above compensation parameters into the above reconstruction polynomial, we can see that the compensation polynomial for wheel hop speed and displacement is:

[0149]

[0150]

[0151] Where t is the current time t of calculation, vr(t) and sr(t) are the wheel hopping velocity and displacement at time t after compensation, v(t) and s(t) are the wheel hopping velocity and displacement at time t before compensation, a(t0) is the acceleration at the starting time, v(t0) is the wheel hopping velocity at the starting time, and v(t f ) is the wheel hop velocity at the end moment, s(t0) is the wheel hop displacement at the start moment, which can be obtained based on the speed and acceleration at the start moment, and T is the wheel motion period.

[0152] Based on the displacement compensation polynomial described above, the wheel hop displacement data for the vehicle at different moments within the wheel motion cycle can be obtained. Furthermore, if the instantaneous wheel acceleration collected by the sensor is acceleration in multiple directions, and the acceleration at each moment in the corrected instantaneous acceleration data is also acceleration in multiple directions, then the initial wheel hop displacement at each moment in the initial wheel hop displacement data also includes initial wheel hop displacements in multiple directions. When compensating the initial wheel hop displacement data, the initial wheel hop displacement in each direction must be compensated. Then, square root calculations are performed based on the compensated wheel hop displacements in multiple directions to obtain the final wheel hop displacement at each moment, ultimately yielding the vehicle's wheel hop displacement data at different moments.

[0153] For example, if the wheel acceleration at time t is the acceleration in the x-axis, y-axis, and z-axis directions, then the initial wheel hop displacements on the x-axis, y-axis, and z-axis at time t can be obtained by performing a quadratic integration of the wheel accelerations on the x-axis, y-axis, and z-axis according to the wheel speed at time t. This can then lead to the compensated wheel hop displacements on the x-axis, y-axis, and z-axis at time t: sx(t), sy(t), and sz(t). According to the formula: The wheel hop displacement data of the vehicle at different times can be obtained.

[0154] In this embodiment, the compensation parameters are determined by the wheel motion cycle, wheel hop displacement at the starting moment, acceleration at the starting moment, rotational speed at the starting moment, and rotational speed at the ending moment. The method for determining the compensation parameters is clarified, and the initial wheel hop displacement data is compensated and corrected by the compensation parameters. The specific process of obtaining the wheel hop displacement data of the vehicle at different moments is refined, providing a basis for calculating the final wheel hop displacement data.

[0155] In one embodiment, step S30, i.e., determining a wheel motion law curve based on wheel bounce and rotation correspondence data of different vehicles, specifically includes the following steps:

[0156] S31: Creating a scatter plot of all wheel bounce and rotation correspondence data according to the correspondence.

[0157] After obtaining the wheel bounce and rotation correspondence data of different vehicles, all the wheel bounce and rotation correspondence data are made into a scatter plot according to the correspondence at each moment. For example, after obtaining the wheel bounce and rotation correspondence data of different vehicles, the correspondence between the wheel bounce travel percentage and the steering travel percentage at time t can be determined, and the correspondence can be displayed as follows: Figure 3 In the scatter plot shown.

[0158] S32: Eliminate some noise points in the scatter plot and fit the boundary of the scatter plot to obtain a wheel motion law curve.

[0159] After obtaining the scatter plot of the wheel runout and rotation correspondence data, some noise points outside the scatter plot are removed and the boundary of the scatter plot is fitted to obtain the wheel motion law curve. Figure 4 As shown in the figure, after removing the black scattered points outside the house-shaped black line, the wheel motion law curve is obtained as the house-shaped black line diagram.

[0160] In this embodiment, all wheel bounce and rotation correspondence data are made into a scatter plot according to the correspondence, and then some noise points in the scatter plot are eliminated and the boundary of the scatter plot is fitted to obtain the wheel motion law curve. The specific process of determining the wheel motion law curve based on the wheel bounce and rotation correspondence data of different vehicles is refined, and all wheel bounce and rotation correspondence data are displayed in the form of a scatter plot, so that the result is clear at a glance, and some noise points in the scatter plot are eliminated, and the boundary of the scatter plot is fitted to ensure the accuracy of the wheel motion law curve.

[0161] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0162] In one embodiment, a wheel motion law curve determination device is provided, which corresponds to the wheel motion law curve determination method in the above embodiment. Figure 5 As shown, the wheel motion law curve determination device includes an acquisition module 501, a first determination module 502 and a second determination module 503. The functional modules are described in detail as follows:

[0163] An acquisition module 501 is configured to acquire operating data of a vehicle in an actual usage scenario, wherein the operating data includes instantaneous acceleration data of the wheels, instantaneous rotational speed data of the wheels, and instantaneous steering wheel angle data of the vehicle;

[0164] a first determining module 502 for determining wheel bounce and rotation correspondence data of the vehicle based on the instantaneous acceleration data of the vehicle wheels, the instantaneous rotation speed data of the wheels, and the instantaneous steering wheel angle data;

[0165] The second determining module 503 is configured to determine a wheel motion law curve based on the wheel bounce and rotation relationship data of different vehicles.

[0166] Furthermore, the first determining module 502 is specifically configured to:

[0167] determining wheel hop displacement data of the vehicle at different moments according to the wheel instantaneous acceleration data and the wheel instantaneous speed data;

[0168] Determining the maximum wheel runout displacement and the maximum steering angle of the steering wheel;

[0169] Dividing each wheel jump position in the wheel jump displacement data by the maximum jump displacement to obtain wheel jump travel percentage data of the vehicle at different times;

[0170] Dividing each instantaneous steering wheel angle in the instantaneous steering wheel angle data by the maximum turning angle to obtain steering stroke percentage data of the vehicle at different moments;

[0171] The wheel hop displacement percentage data is matched with the steering stroke percentage data at the same moment to obtain the wheel hop and rotation correspondence data.

[0172] Furthermore, the first determining module 502 specifically further comprises:

[0173] performing error correction on the wheel instantaneous acceleration data to obtain corrected instantaneous acceleration data;

[0174] performing a secondary integration operation on the modified instantaneous acceleration data according to the instantaneous wheel speed data to obtain initial wheel hop displacement data of the vehicle at different moments;

[0175] Compensation correction is performed on the initial wheel hop displacement data to obtain wheel hop displacement data of the vehicle at different moments.

[0176] Furthermore, the first determining module 502 specifically further comprises:

[0177] Determine gravitational acceleration and measurement instrument errors;

[0178] Filtering the wheel instantaneous acceleration data to obtain denoised instantaneous acceleration data after eliminating random errors;

[0179] The corrected instantaneous acceleration data is determined based on the denoised instantaneous acceleration data, the gravitational acceleration, and the measurement instrument error.

[0180] Furthermore, the first determining module 502 specifically further comprises:

[0181] A coordinate system is established with the axis of the vehicle wheel as the origin, the forward direction of the vehicle is the y-axis, the horizontal direction of the vehicle is the x-axis, and the vertical direction of the vehicle is the z-axis;

[0182] Determining the z-axis acceleration of the wheel in the z-axis direction in the noise-removed instantaneous acceleration data;

[0183] Subtracting the gravity acceleration from all the z-axis accelerations to obtain first wheel acceleration data;

[0184] The measuring instrument error is subtracted from all accelerations in the first wheel acceleration data to obtain the corrected instantaneous acceleration data.

[0185] Furthermore, the first determining module 502 specifically further comprises:

[0186] Determining a wheel motion cycle of the vehicle according to the wheel instantaneous speed data, wherein the wheel motion cycle is a duration from a start moment to an end moment of the wheel motion in the wheel instantaneous speed data;

[0187] Determining the wheel acceleration at each moment in the preset data, wherein the wheel acceleration includes accelerations in multiple directions;

[0188] performing a quadratic integration operation on the accelerations in the multiple directions to obtain multiple initial wheel hop displacements;

[0189] The multiple wheel hop displacements at different moments are aggregated to obtain initial wheel hop displacement data of the vehicle at different moments.

[0190] Furthermore, the first determining module 502 specifically further comprises:

[0191] Determining a starting time speed and an ending time speed from the instantaneous wheel speed data;

[0192] Determining the acceleration at the start time in the corrected instantaneous acceleration data;

[0193] Determine the starting time round jump displacement in the initial round jump displacement data;

[0194] Determining a compensation parameter based on the wheel motion cycle, the wheel hop displacement at the start time, the acceleration at the start time, the speed at the start time, and the speed at the end time;

[0195] Compensation calculation is performed on each wheel hop displacement in the initial wheel hop displacement data according to the compensation parameter to obtain wheel hop displacement data of the vehicle at different moments.

[0196] Furthermore, the second determining module 502 is specifically configured to:

[0197] According to the corresponding relationship, all the wheel bounce and rotation corresponding relationship data are made into a scatter plot;

[0198] Some noise points in the scatter plot are eliminated and the boundary of the scatter plot is fitted to obtain the wheel motion law curve.

[0199] The specific limitations of the wheel motion law curve determination device can be found in the limitations of the wheel motion law curve determination method described above and will not be further elaborated here. Each module in the aforementioned wheel motion law curve determination device can be implemented in whole or in part via software, hardware, or a combination thereof. Each of these modules can be embedded in or independent of a processor in a computer device in hardware form, or stored in a computer device memory in software form, allowing the processor to call and execute the corresponding operations of each module.

[0200] In one embodiment, a device for determining a wheel motion law curve is provided. The device includes a processor, memory, a network interface, a display screen, and an input device connected via a system bus. The processor of the device provides computing and control capabilities. The computer device's memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operating system and computer program stored in the non-volatile storage medium. The network interface of the device is used to communicate with an external server via a network connection. When executed by the processor, the computer program implements a method for determining a wheel motion law curve.

[0201] In one embodiment, Figure 6 As shown, a device for determining a wheel motion law curve is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented:

[0202] Acquiring operating data of the vehicle in an actual usage scenario, the operating data including instantaneous wheel acceleration data, instantaneous wheel speed data, and instantaneous steering wheel angle data of the vehicle;

[0203] Determining wheel bounce and rotation correspondence data of the vehicle according to the instantaneous acceleration data of the vehicle wheels, the instantaneous rotation speed data of the wheels, and the instantaneous steering wheel angle data;

[0204] The wheel motion law curve is determined based on the wheel bounce and rotation relationship data of different vehicles.

[0205] In one embodiment, a readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0206] Acquiring operating data of the vehicle in an actual usage scenario, the operating data including instantaneous wheel acceleration data, instantaneous wheel speed data, and instantaneous steering wheel angle data of the vehicle;

[0207] Determining wheel bounce and rotation correspondence data of the vehicle according to the instantaneous acceleration data of the vehicle wheels, the instantaneous rotation speed data of the wheels, and the instantaneous steering wheel angle data;

[0208] The wheel motion law curve is determined based on the wheel bounce and rotation relationship data of different vehicles.

[0209] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0210] Those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0211] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. A method for determining a wheel motion law curve, characterized in that: include: Acquiring operating data of the vehicle in an actual usage scenario, the operating data including instantaneous wheel acceleration data, instantaneous wheel speed data, and instantaneous steering wheel angle data of the vehicle; Determining wheel bounce and rotation correspondence data of the vehicle according to the instantaneous acceleration data of the vehicle wheels, the instantaneous rotation speed data of the wheels, and the instantaneous steering wheel angle data; Determining a wheel motion law curve based on the wheel bounce and rotation relationship data of different vehicles; The determining of the wheel bounce and rotation correspondence data of the vehicle according to the instantaneous acceleration data of the vehicle wheel, the instantaneous rotation speed data of the wheel, and the instantaneous steering wheel angle data includes: determining wheel hop displacement data of the vehicle at different moments according to the wheel instantaneous acceleration data and the wheel instantaneous speed data; Determining the maximum wheel runout displacement and the maximum steering angle of the steering wheel; Dividing each wheel jump position in the wheel jump displacement data by the maximum jump displacement to obtain wheel jump travel percentage data of the vehicle at different times; Dividing each instantaneous steering wheel angle in the instantaneous steering wheel angle data by the maximum turning angle to obtain steering stroke percentage data of the vehicle at different moments; The wheel hop displacement percentage data is matched with the steering stroke percentage data at the same moment to obtain the wheel hop and rotation correspondence data.

2. The method for determining a wheel motion law curve according to claim 1, wherein: Determining the wheel hop displacement data of the vehicle at different moments according to the wheel instantaneous acceleration data and the wheel instantaneous speed data includes: performing error correction on the wheel instantaneous acceleration data to obtain corrected instantaneous acceleration data; performing a secondary integration operation on the modified instantaneous acceleration data according to the instantaneous wheel speed data to obtain initial wheel hop displacement data of the vehicle at different moments; Compensation correction is performed on the initial wheel hop displacement data to obtain wheel hop displacement data of the vehicle at different moments.

3. The method for determining a wheel motion law curve according to claim 2, wherein: The error correction of the wheel instantaneous acceleration data to obtain corrected instantaneous acceleration data includes: Determine gravitational acceleration and measurement instrument errors; Filtering the wheel instantaneous acceleration data to obtain denoised instantaneous acceleration data after eliminating random errors; The corrected instantaneous acceleration data is determined based on the denoised instantaneous acceleration data, the gravitational acceleration, and the measurement instrument error.

4. The method for determining a wheel motion law curve according to claim 3, wherein: The determining the corrected instantaneous acceleration data according to the denoised instantaneous acceleration data, the gravitational acceleration, and the measuring instrument error comprises: A coordinate system is established with the axis of the vehicle wheel as the origin, the forward direction of the vehicle is the y-axis, the horizontal direction of the vehicle is the x-axis, and the vertical direction of the vehicle is the z-axis; Determining the z-axis acceleration of the wheel in the z-axis direction in the noise-removed instantaneous acceleration data; Subtracting the gravity acceleration from all the z-axis accelerations to obtain first wheel acceleration data; The measuring instrument error is subtracted from all accelerations in the first wheel acceleration data to obtain the corrected instantaneous acceleration data.

5. The method for determining a wheel motion law curve according to claim 2, wherein: The performing a secondary integration operation on the modified instantaneous acceleration data according to the instantaneous wheel speed data to obtain initial wheel hop displacement data of the vehicle at different moments includes: Determining a wheel motion cycle of the vehicle according to the wheel instantaneous speed data, wherein the wheel motion cycle is a duration from a start moment to an end moment of the wheel motion in the wheel instantaneous speed data; Dividing the corrected instantaneous acceleration data into a plurality of groups of preset data including wheel accelerations at different times according to the starting time and the ending time; Determining the wheel acceleration at each moment in the preset data, wherein the wheel acceleration includes accelerations in multiple directions; performing a quadratic integration operation on the accelerations in the multiple directions to obtain multiple initial wheel hop displacements; The multiple wheel hop displacements at different moments are aggregated to obtain initial wheel hop displacement data of the vehicle at different moments.

6. The method for determining a wheel motion law curve according to claim 5, wherein: The compensating and correcting the initial wheel hop displacement data to obtain wheel hop displacement data of the vehicle at different moments includes: Determining a starting time speed and an ending time speed from the instantaneous wheel speed data; Determining the acceleration at the start time in the corrected instantaneous acceleration data; Determine the starting time round jump displacement in the initial round jump displacement data; Determining a compensation parameter based on the wheel motion cycle, the wheel hop displacement at the start time, the acceleration at the start time, the speed at the start time, and the speed at the end time; Compensation calculation is performed on each wheel hop displacement in the initial wheel hop displacement data according to the compensation parameter to obtain wheel hop displacement data of the vehicle at different moments.

7. The method for determining a wheel motion law curve according to any one of claims 1 to 6, wherein: Determining the wheel motion law curve based on the wheel bounce and rotation correspondence data of different vehicles includes: According to the corresponding relationship, all the wheel bounce and rotation corresponding relationship data are made into a scatter plot; Some noise points in the scatter plot are eliminated and the boundary of the scatter plot is fitted to obtain the wheel motion law curve.

8. A device for determining a wheel motion law curve, characterized in that: include: An acquisition module is used to acquire operating data of a vehicle in an actual usage scenario, wherein the operating data includes instantaneous acceleration data of the wheels, instantaneous rotational speed data of the wheels, and instantaneous steering wheel angle data of the vehicle; a first determining module, configured to determine wheel bounce and rotation correspondence data of the vehicle based on the instantaneous acceleration data of the vehicle's wheels, the instantaneous rotation speed data of the wheels, and the instantaneous steering wheel angle data; a second determining module, configured to determine a wheel motion law curve based on the wheel bounce and rotation relationship data of different vehicles; The determining of the wheel bounce and rotation correspondence data of the vehicle according to the instantaneous acceleration data of the vehicle wheel, the instantaneous rotation speed data of the wheel, and the instantaneous steering wheel angle data includes: determining wheel hop displacement data of the vehicle at different moments according to the wheel instantaneous acceleration data and the wheel instantaneous speed data; Determining the maximum wheel runout displacement and the maximum steering angle of the steering wheel; Dividing each wheel jump position in the wheel jump displacement data by the maximum jump displacement to obtain wheel jump travel percentage data of the vehicle at different times; Dividing each instantaneous steering wheel angle in the instantaneous steering wheel angle data by the maximum turning angle to obtain steering stroke percentage data of the vehicle at different moments; The wheel hop displacement percentage data is matched with the steering stroke percentage data at the same moment to obtain the wheel hop and rotation correspondence data.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for determining a wheel motion law curve according to any one of claims 1 to 7 are implemented.

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