Vehicle dynamics model establishment method, device and equipment and storage medium

Abstract

The invention discloses a vehicle dynamics model establishment method and device, equipment and a storage medium. Comprising the steps of obtaining working condition calibration parameters of a target vehicle, and determining test working conditions corresponding to the target vehicle according to the working condition calibration parameters; obtaining initial parameters of the model; and performing iterative calculation on the model initial parameters based on each test working condition to determine each model correction parameter, and establishing a vehicle dynamics model according to the model correction parameters. A real vehicle is tested and calibrated to obtain all vehicle speed calibration values, all steering wheel angle calibration values and all load weight calibration values of a target vehicle, then all corresponding test working conditions are determined, the vehicle is tested under the condition that a large-radius test site is not needed, iterative calculation is carried out on initial parameters of the model under all the test working conditions, and the test efficiency is improved. The initial parameters of the model comprise a front wheel steering angle initial value and a tire cornering stiffness initial value, and accurate modeling of conversion from the steering wheel steering angle to the vehicle body yaw rate can be completed.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle dynamics, and in particular, to a method, device, equipment and storage medium for establishing a vehicle dynamics model. Background Art

[0002] Trucks have a large turning radius and are easily affected by vehicle speed. Therefore, when using an algorithm to control the lateral performance of a truck, it is necessary to conduct sufficient verification through simulation before road testing. An accurate yaw dynamics model plays an extremely important role in the iteration of the lateral control algorithm before road testing.

[0003] The transmission ratio from the steering wheel angle to the front wheel angle is a key parameter of vehicle yaw dynamics. Generally, vehicle manufacturers will provide a transmission ratio comparison table calculated at the factory. Due to the assembly relationship and the mutual influence relationship of each part in the whole vehicle state, there will be a deviation from the transmission ratio relationship at the time of factory production. Therefore, when performing dynamic modeling, it is necessary to correct the above comparison table.

[0004] Since the steering wheel works in the small steering angle area in most working conditions when the vehicle is turning, at this time, the corresponding turning radius of the truck is large and the required site is also large, and the existing calibration methods are not applicable. Summary of the Invention

[0005] The present invention provides a method, device, equipment and storage medium for establishing a vehicle dynamics model, so as to realize iterative correction of model parameters and complete accurate modeling of the conversion from the steering wheel angle to the vehicle body yaw rate.

[0006] According to an aspect of the present invention, there is provided a method for establishing a vehicle dynamics model, the method including:

[0007] Obtain the working condition calibration parameters of the target vehicle, and determine the corresponding test working conditions of the target vehicle according to each working condition calibration parameter, wherein the working condition calibration parameters include each vehicle speed calibration value, each steering wheel angle calibration value and each load weight calibration value;

[0008] Obtain the initial model parameters, wherein the initial model parameters include the initial value of the front wheel angle and the initial value of the tire cornering stiffness;

[0009] Perform iterative calculation on the initial model parameters based on each test working condition to determine each model correction parameter, and establish a vehicle dynamics model according to the model correction parameters.

[0010] Optionally, determine each test condition corresponding to the target vehicle according to the calibration parameters of each working condition, including: taking the specified working condition calibration parameters as fixed working conditions, where the fixed working conditions include specified vehicle speed, specified steering wheel angle, and specified load weight; generating each first working condition according to the calibration values of each vehicle speed, specified steering wheel angle, and specified load weight; generating each second working condition according to the calibration values of each steering wheel angle, specified load weight, and each vehicle speed; generating each third working condition according to the calibration values of each load weight, each vehicle speed, and each steering wheel angle; taking each first working condition, each second working condition, and each third working condition as each test condition.

[0011] Optionally, perform iterative calculations on the initial model parameters based on each test condition to determine each model correction parameter, including: determining the iterative value of the tire cornering stiffness corresponding to each test condition according to the initial model parameters; determining the iterative value of the front wheel angle according to the iterative value of the tire cornering stiffness; performing iterative calculations according to the iterative value of the tire cornering stiffness and the iterative value of the front wheel angle to determine the iterative change amount; determining the model correction parameter according to the iterative change amount.

[0012] Optionally, determine the iterative value of the tire cornering stiffness corresponding to each test condition according to the initial model parameters, including: obtaining the yaw rate gain algorithm and determining the test condition parameters corresponding to each test condition; substituting the initial value of the front wheel angle and the test condition parameters into the yaw rate gain algorithm to determine the calculated value of the tire cornering stiffness; taking the average value of the calculated value of the tire cornering stiffness and the initial value of the tire cornering stiffness as the iterative value of the tire cornering stiffness.

[0013] Optionally, determine the iterative value of the front wheel angle according to the iterative value of the tire cornering stiffness, including: performing simulation calibration on the target vehicle to generate a simulation dynamics model; substituting the iterative value of the tire cornering stiffness into the simulation dynamics model to obtain the calculated value of the front wheel angle output by the model; taking the average value of the calculated value of the front wheel angle and the initial value of the front wheel angle as the iterative value of the front wheel angle.

[0014] Optionally, determine the model correction parameter according to the iterative change amount, including: when the iterative change amount is less than the preset threshold, determining the target round corresponding to the iterative change amount; taking the target value of the tire cornering stiffness and the target value of the front wheel angle corresponding to the target round as the model correction parameter.

[0015] Optionally, establish a vehicle dynamics model according to the model correction parameter, including: calibrating the simulation dynamics model through the model correction parameter to generate a vehicle dynamics model.

[0016] According to another aspect of the present invention, there is provided a device for establishing a vehicle dynamics model, the device includes:

[0017] A test condition determination module, configured to obtain the condition calibration parameters of a target vehicle, and determine each test condition corresponding to the target vehicle according to each condition calibration parameter, wherein the condition calibration parameters include each vehicle speed calibration value, each steering wheel angle calibration value, and each load weight calibration value;

[0018] A model initial parameter acquisition module, configured to obtain model initial parameters, wherein the model initial parameters include an initial value of the front wheel angle and an initial value of the tire cornering stiffness;

[0019] A model correction parameter determination module, configured to perform iterative calculations on the model initial parameters based on each test condition to determine each model correction parameter, and establish a vehicle dynamics model according to the model correction parameters.

[0020] According to another aspect of the present invention, there is provided an electronic device, the electronic device comprising:

[0021] At least one processor; and

[0022] A memory communicatively connected to the at least one processor; wherein,

[0023] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute a vehicle dynamics model establishment method according to any embodiment of the present invention.

[0024] According to another aspect of the present invention, there is provided a computer-readable storage medium storing computer instructions for causing a processor to implement a vehicle dynamics model establishment method according to any embodiment of the present invention when executed.

[0025] The technical solution of the embodiment of the present invention obtains each vehicle speed calibration value, each steering wheel angle calibration value, and each load weight calibration value of the target vehicle through test calibration of the actual vehicle, and then determines the corresponding test conditions, and tests the vehicle without a large-radius test site. By performing iterative calculations on the model initial parameters under each test condition, the model initial parameters include the initial value of the front wheel angle and the initial value of the tire cornering stiffness, and an accurate model of the conversion from the steering wheel angle to the vehicle body yaw rate can be completed.

[0026] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. Description of the Drawings

[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0028] Figure 1 is a flowchart of a method for establishing a vehicle dynamics model according to Embodiment 1 of the present invention;

[0029] Figure 2 is a flowchart of another method for establishing a vehicle dynamics model according to Embodiment 1 of the present invention;

[0030] Figure 3 is a flowchart of another method for establishing a vehicle dynamics model according to Embodiment 2 of the present invention;

[0031] Figure 4 is a schematic structural diagram of a device for establishing a vehicle dynamics model according to Embodiment 3 of the present invention;

[0032] Figure 5 is a schematic structural diagram of an electronic device for implementing the method for establishing a vehicle dynamics model in the embodiments of the present invention. Detailed Embodiments

[0033] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0034] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above accompanying drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such used data can be interchanged under appropriate circumstances so that the embodiments of the present invention described here can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily need to be limited to those clearly listed steps or units, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0035] Embodiment 1

[0036] Figure 1 FIG. 1 is a flowchart of a method for establishing a vehicle dynamics model according to Embodiment 1 of the present invention. This embodiment is applicable to the situation of correcting a vehicle dynamics model. The method can be executed by a vehicle dynamics model establishment device, which can be implemented in the form of hardware and / or software, and can be configured in a computer controller. As Figure 1 shown, the method includes:

[0037] S110. Obtain the condition calibration parameters of the target vehicle, and determine the corresponding test conditions of the target vehicle according to each condition calibration parameter. Among them, the condition calibration parameters include the calibration values of each vehicle speed, the calibration values of each steering wheel angle, and the calibration values of each load weight.

[0038] Among them, the condition refers to the driving situation during the vehicle driving process, including the vehicle speed, steering wheel angle, and load weight corresponding to different driving situations. The condition calibration parameter refers to the calibration data obtained by testing the target vehicle. By taking one of the condition calibration parameters as a fixed value and the other two as variable values, the full conditions corresponding to the target vehicle, that is, each test condition, can be determined. Each test condition includes a combination of different types of condition calibration parameters, that is, the test data generated by testing the actual vehicle. In this embodiment, iterative calculations are performed on the initial model parameters for each group of test data included in each test condition, and then the model correction parameters are determined.

[0039] S120. Obtain the initial model parameters, where the initial model parameters include the initial value of the front wheel angle and the initial value of the tire cornering stiffness.

[0040] Specifically, the initial model parameters include the initial value of the front wheel angle and the initial value of the tire cornering stiffness. The initial model parameters can be data provided by the vehicle manufacturer or component suppliers, or the estimated values in the by-wire system can also be used.

[0041] S130. Perform iterative calculations on the initial model parameters based on each test condition to determine each model correction parameter, and establish a vehicle dynamics model according to the model correction parameters.

[0042] It should be noted that the technical solution of the embodiment of the present invention calibrates the conversion relationship from the steering wheel angle to the vehicle body yaw rate, including the transmission ratio relationship from the steering wheel angle to the front wheel angle and the tire cornering stiffness that affects the conversion from the front wheel angle to the vehicle body yaw rate. And based on each same test condition, three tests will be conducted, and the average value of the three test results will be taken to finally determine the model correction parameters corresponding to each test condition.

[0043] Figure 2The figure below is a flowchart of a method for establishing a vehicle dynamics model provided in the first embodiment of the present invention. Step S130 mainly includes the following steps S131 to S135:

[0044] S131. Determine the iterative value of the tire cornering stiffness corresponding to each test condition according to the initial model parameters.

[0045] Optionally, determining the iterative value of the tire cornering stiffness corresponding to each test condition according to the initial model parameters includes: obtaining the yaw rate gain algorithm and determining the test condition parameters corresponding to each test condition; substituting the initial value of the front wheel angle and the test condition parameters into the yaw rate gain algorithm to determine the calculated value of the tire cornering stiffness; taking the average value of the calculated value of the tire cornering stiffness and the initial value of the tire cornering stiffness as the iterative value of the tire cornering stiffness.

[0046] Specifically, the yaw rate gain algorithm is represented by the following formula (1):

[0047]

[0048] In the formula, ω r represents the body yaw rate, with the unit of ° / s, δ represents the front wheel angle, with the unit of °, u represents the vehicle longitudinal speed, with the unit of m / s, L represents the wheelbase of the vehicle's front and rear wheels, and if there are multiple axles, the equivalent wheelbase is taken, with the unit of m, and K is the stability factor, with the unit of s 2 / m 2 , which is an important parameter characterizing the steady-state response of the vehicle, and is represented by the following formula (2):

[0049]

[0050] Among them, m represents the vehicle mass, with the unit of kg, a and b respectively represent the longitudinal distances from the vehicle's center of mass to the front and rear axles, with the unit of m, k 1 and k 2 respectively represent the tire cornering stiffnesses of the vehicle's front and rear wheels, with the unit of N / rad. When performing back substitution, it is assumed that the tire cornering stiffnesses of the front and rear wheels are equal, that is, k 1 = k 2 / 4. Combining the above two formulas can calculate the calculated value of the tire cornering stiffness. Then, taking the average value of the calculated value of the tire cornering stiffness and the initial value of the tire cornering stiffness as the iterative value of the tire cornering stiffness.

[0051] S132. Determine the iterative value of the front wheel angle according to the iterative value of the tire cornering stiffness.

[0052] Optionally, determining the iterative value of the front wheel steering angle according to the iterative value of the tire cornering stiffness includes: performing simulation calibration on the target vehicle to generate a simulation dynamics model; substituting the iterative value of the tire cornering stiffness into the simulation dynamics model to obtain the calculated value of the front wheel steering angle output by the model; taking the average value of the calculated value of the front wheel steering angle and the initial value of the front wheel steering angle as the iterative value of the front wheel steering angle.

[0053] Specifically, substituting the iterative value of the tire cornering stiffness calculated in the previous step into the simulation dynamics model can obtain the calculated value of the front wheel steering angle output. Then, taking the average value of the calculated value of the front wheel steering angle and the initial value of the front wheel steering angle as the iterative value of the front wheel steering angle.

[0054] S133. Perform iterative calculations based on the iterative value of the tire cornering stiffness and the iterative value of the front wheel steering angle to determine the iterative change amount.

[0055] S134. Determine the model correction parameters according to the iterative change amount.

[0056] Optionally, determining the model correction parameters according to the iterative change amount includes: when the iterative change amount is less than the preset threshold, determining the target round corresponding to the iterative change amount; taking the target value of the tire cornering stiffness and the target value of the front wheel steering angle corresponding to the target round as the model correction parameters.

[0057] Specifically, repeat S131 and S132 in sequence according to the iterative value of the tire cornering stiffness and the iterative value of the front wheel steering angle to perform iterative calculations until the iterative change amount of the tire cornering stiffness and the front wheel steering angle in the nth step relative to the previous step is less than the preset threshold. The preset threshold is set in advance by the user according to the iterative requirements. Exemplarily, the change amount threshold corresponding to the tire cornering stiffness can be 10 N / °, and the change amount threshold corresponding to the front wheel steering angle can be 0.02°. When the iterative change amount is less than the preset threshold, the iterative round at this time can be used as the target round, and the target value of the tire cornering stiffness and the target value of the front wheel steering angle corresponding to the target round are the model correction parameters.

[0058] S135. Establish a vehicle dynamics model according to the model correction parameters.

[0059] Optionally, establishing a vehicle dynamics model according to the model correction parameters includes: calibrating the simulation dynamics model through the model correction parameters to generate a vehicle dynamics model.

[0060] It can be known that in this embodiment, the simulation dynamics model is calibrated through the model correction parameters. After calibrating all angles, the least squares method is used for fitting and smoothing to obtain the front wheel steering angle corresponding to each steering wheel angle, which is the steering system transmission ratio. At the same time, the tire cornering stiffness is also corrected. Through iterative correction of the model parameters, accurate modeling of the conversion from the steering wheel angle to the vehicle body yaw rate is completed.

[0061] In the technical solution of the embodiment of the present invention, by performing test calibration on a real vehicle to obtain the calibration values of various vehicle speeds, the calibration values of various steering wheel angles, and the calibration values of various load weights of the target vehicle, and then determining the corresponding various test conditions, the vehicle can be tested without a large-radius test site. By performing iterative calculations on the initial parameters of the model under various test conditions, where the initial parameters of the model include the initial value of the front wheel angle and the initial value of the tire cornering stiffness, the accurate modeling of the conversion from the steering wheel angle to the vehicle body yaw rate can be completed.

[0062] Embodiment 2

[0063] Figure 3 FIG. is a flowchart of a method for establishing a vehicle dynamics model provided in Embodiment 2 of the present invention. In this embodiment, on the basis of the above Embodiment 1, the specific process of determining the corresponding various test conditions of the target vehicle according to the calibration parameters of each condition is added. Among them, the specific contents of steps S270-S280 are substantially the same as those of steps S120-S130 in Embodiment 1, so they will not be elaborated in this embodiment. As Figure 3 shown, the method includes:

[0064] S210. Obtain the calibration parameters of the working conditions of the target vehicle.

[0065] Specifically, the calibration parameters of the working conditions are obtained by performing real vehicle tests to obtain calibration data, and calibrating the parameters of working conditions such as the vehicle speed being 30-100 km / h, the steering wheel angle being between ±10°, and the truck load being empty without a trailer, semi-loaded with a trailer, and fully loaded with a trailer.

[0066] In a specific embodiment, as shown in Table 1 below, the calibration values of each steering wheel angle (unit: degree) are shown:

[0067] Table 1

[0068] -10 -5 -2 -1 -0.5 0 0.5 1 2 5 10

[0069] In a specific embodiment, as shown in Table 2 below, the calibration values of each vehicle speed (unit: km / h) are shown:

[0070] Table 2

[0071] 30 40 50 60 70 80 90 100

[0072] S220. Take the specified working condition calibration parameters as the fixed working condition, where the fixed working condition includes the specified vehicle speed, the specified steering wheel angle, and the specified load weight.

[0073] Exemplarily, the specified working condition calibration parameters can be that the truck is empty without a trailer, the vehicle speed is 30 km / h, and the steering wheel angle is -10°.

[0074] S230. Generate each first working condition based on each vehicle speed, specified steering wheel angle, and specified load weight calibration value.

[0075] Specifically, fix the steering wheel angle and the load weight, use the vehicle speed as the variable value to calibrate the influence caused by the change in the vertical load of the tire due to the change in vehicle speed, which in turn leads to the change in the cornering stiffness of the tire.

[0076] S240. Generate each second working condition based on each steering wheel angle, specified load weight, and each vehicle speed calibration value.

[0077] Specifically, on the basis of the first working condition, release the steering wheel angle as the variable value to generate each second working condition, and calibrate the corresponding front wheel angle under each steering wheel angle, which is the steering transmission ratio.

[0078] S250. Generate each third working condition based on each load weight, each vehicle speed, and each steering wheel angle calibration value.

[0079] Specifically, on the basis of the second working condition, release the load weight as the variable value to generate each third working condition, so as to calibrate the influence caused by the change in the vertical load of the tire due to the change in the truck load, which in turn leads to the change in the cornering stiffness of the tire.

[0080] S260. Take each first working condition, each second working condition, and each third working condition as each test working condition.

[0081] S270. Obtain the initial parameters of the model, where the initial parameters of the model include the initial value of the front wheel angle and the initial value of the cornering stiffness of the tire.

[0082] S280. Perform iterative calculations on the initial parameters of the model based on each test working condition to determine each model correction parameter, and establish a vehicle dynamics model according to the model correction parameters.

[0083] Optionally, perform iterative calculations on the initial parameters of the model based on each test working condition to determine each model correction parameter, including: determining the iterative value of the cornering stiffness of the tire corresponding to each test working condition according to the initial parameters of the model; determining the iterative value of the front wheel angle according to the iterative value of the cornering stiffness of the tire; performing iterative calculations according to the iterative value of the cornering stiffness of the tire and the iterative value of the front wheel angle to determine the iterative change amount; determining the model correction parameter according to the iterative change amount.

[0084] Optionally, determining the iterative value of the cornering stiffness of the tire corresponding to each test working condition according to the initial parameters of the model includes: obtaining the yaw rate gain algorithm, determining the test working condition parameters corresponding to each test working condition; substituting the initial value of the front wheel angle and the test working condition parameters into the yaw rate gain algorithm to determine the calculated value of the cornering stiffness of the tire; taking the average value of the calculated value of the cornering stiffness of the tire and the initial value of the cornering stiffness of the tire as the iterative value of the cornering stiffness of the tire.

[0085] Optionally, determining the iterative value of the front wheel steering angle according to the iterative value of the tire cornering stiffness includes: performing simulation calibration on the target vehicle to generate a simulation dynamics model; substituting the iterative value of the tire cornering stiffness into the simulation dynamics model to obtain the calculated value of the front wheel steering angle output by the model; taking the average value of the calculated value of the front wheel steering angle and the initial value of the front wheel steering angle as the iterative value of the front wheel steering angle.

[0086] Optionally, determining the model correction parameter according to the iterative change amount includes: when the iterative change amount is less than a preset threshold, determining the target round corresponding to the iterative change amount; taking the target value of the tire cornering stiffness and the target value of the front wheel steering angle corresponding to the target round as the model correction parameter.

[0087] Optionally, establishing a vehicle dynamics model according to the model correction parameter includes: calibrating the simulation dynamics model through the model correction parameter to generate a vehicle dynamics model.

[0088] The technical solution of the embodiment of the present invention obtains the calibration values of each vehicle speed, the calibration values of each steering wheel angle, and the calibration values of each load weight of the target vehicle by testing and calibrating the actual vehicle, and then determines the corresponding test conditions. The vehicle can be tested without a large-radius test site. By performing iterative calculations on the initial model parameters under each test condition, the initial model parameters include the initial value of the front wheel steering angle and the initial value of the tire cornering stiffness, and the accurate modeling of the conversion from the steering wheel angle to the body yaw rate can be completed.

[0089] Embodiment III

[0090] Figure 4 It is a schematic structural diagram of a vehicle dynamics model establishment device provided by Embodiment III of the present invention. As Figure 4 shown, the device includes: a test condition determination module 310, configured to obtain the condition calibration parameters of the target vehicle, and determine the corresponding test conditions of the target vehicle according to each condition calibration parameter, where the condition calibration parameters include the calibration values of each vehicle speed, the calibration values of each steering wheel angle, and the calibration values of each load weight;

[0091] a model initial parameter acquisition module 320, configured to acquire model initial parameters, where the model initial parameters include the initial value of the front wheel steering angle and the initial value of the tire cornering stiffness;

[0092] a model correction parameter determination module 330, configured to perform iterative calculations on the model initial parameters based on each test condition to determine each model correction parameter, and establish a vehicle dynamics model according to the model correction parameter.

[0093] Optionally, the test condition determination module 310 specifically includes: a test condition determination unit configured to: use the specified condition calibration parameters as fixed conditions, where the fixed conditions include a specified vehicle speed, a specified steering wheel angle, and a specified load weight; generate respective first conditions according to the calibration values of respective vehicle speeds, the specified steering wheel angle, and the specified load weight; generate respective second conditions according to the calibration values of respective steering wheel angles, the specified load weight, and respective vehicle speeds; generate respective third conditions according to the calibration values of respective load weights, respective vehicle speeds, and respective steering wheel angles; and use the respective first conditions, the respective second conditions, and the respective third conditions as respective test conditions.

[0094] Optionally, the model correction parameter determination module 330 specifically includes: a tire cornering stiffness iteration value determination unit configured to: determine the tire cornering stiffness iteration values corresponding to respective test conditions according to the initial model parameters; a front wheel angle iteration value determination unit configured to: determine the front wheel angle iteration values according to the tire cornering stiffness iteration values; an iterative calculation unit configured to: perform iterative calculations according to the tire cornering stiffness iteration values and the front wheel angle iteration values to determine the iterative change amount; and a model correction parameter determination unit configured to: determine the model correction parameters according to the iterative change amount.

[0095] Optionally, the tire cornering stiffness iteration value determination unit is specifically configured to: obtain the yaw rate gain algorithm, and determine the test condition parameters corresponding to respective test conditions; substitute the initial front wheel angle value and the test condition parameters into the yaw rate gain algorithm to determine the calculated value of the tire cornering stiffness; and use the average value of the calculated value of the tire cornering stiffness and the initial value of the tire cornering stiffness as the tire cornering stiffness iteration value.

[0096] Optionally, the front wheel angle iteration value determination unit is specifically configured to: perform simulation calibration on the target vehicle to generate a simulation dynamics model; substitute the tire cornering stiffness iteration value into the simulation dynamics model to obtain the calculated value of the front wheel angle output by the model; and use the average value of the calculated value of the front wheel angle and the initial front wheel angle value as the front wheel angle iteration value.

[0097] Optionally, the model correction parameter determination unit is specifically configured to: when the iterative change amount is less than a preset threshold, determine the target round corresponding to the iterative change amount; and use the target value of the tire cornering stiffness and the target value of the front wheel angle corresponding to the target round as the model correction parameters.

[0098] Optionally, the model correction parameter determination module 330 further includes: a vehicle dynamics model establishment unit configured to: calibrate the simulation dynamics model by using the model correction parameters to generate a vehicle dynamics model.

[0099] The technical solution of the embodiment of the present invention obtains the calibration values of each vehicle speed, each steering wheel angle, and each load weight of the target vehicle by performing test calibration on the actual vehicle, and then determines the corresponding test conditions. Without the need for a large-radius test site, the vehicle can be tested. By performing iterative calculations on the initial parameters of the model under each test condition, where the initial parameters of the model include the initial value of the front wheel angle and the initial value of the tire cornering stiffness, the accurate modeling of the conversion from the steering wheel angle to the vehicle body yaw rate can be completed.

[0100] The vehicle dynamics model establishment device provided by the embodiment of the present invention can execute the vehicle dynamics model establishment method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0101] Embodiment 4

[0102] Figure 5 The structural schematic diagram of the electronic device 10 that can be used to implement the embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0103] As Figure 5 shown, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc. The memory stores a computer program executable by at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.

[0104] Multiple components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disc, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0105] The processor 11 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a vehicle dynamics model establishment method. That is: obtaining the working condition calibration parameters of the target vehicle, determining the respective test working conditions corresponding to the target vehicle according to the respective working condition calibration parameters, where the working condition calibration parameters include respective vehicle speed calibration values, respective steering wheel angle calibration values, and respective load weight calibration values; obtaining the initial model parameters, where the initial model parameters include the initial value of the front wheel angle and the initial value of the tire cornering stiffness; performing iterative calculations on the initial model parameters based on the respective test working conditions to determine the respective model correction parameters, and establishing a vehicle dynamics model according to the model correction parameters.

[0106] In some embodiments, a vehicle dynamics model establishment method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the vehicle dynamics model establishment method described above can be executed. Alternatively, in other embodiments, the processor 11 can be configured to execute a vehicle dynamics model establishment method by any other suitable means (e.g., by means of firmware).

[0107] The various embodiments of the systems and techniques described above in this specification can be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGA), application specific integrated circuits (ASIC), application specific standard products (ASSP), systems on a chip (SOC), complex programmable logic devices (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which may be a special-purpose or general-purpose programmable processor that receives data and instructions from, and transmits data and instructions to, a storage system, at least one input device, and at least one output device.

[0108] The computer programs for implementing the methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions / operations specified in the flowchart and / or block diagram to be implemented. The computer programs can be executed entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

[0109] In the context of the present invention, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0110] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which the user can provide input to the electronic device. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0111] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected to each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), blockchain network, and the Internet.

[0112] The computing system can include a client and a server. The client and the server are generally remote from each other and typically interact through a communication network. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0113] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is made herein.

[0114] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for establishing a vehicle dynamics model, characterized in that, it includes: Obtain the working condition calibration parameters of the target vehicle, and determine the corresponding test working conditions of the target vehicle according to each of the working condition calibration parameters, wherein the working condition calibration parameters include each vehicle speed calibration value, each steering wheel angle calibration value, and each load weight calibration value; Obtain the initial model parameters, wherein the initial model parameters include the initial value of the front wheel angle and the initial value of the tire cornering stiffness; Based on each of the test working conditions, perform iterative calculations on the initial model parameters to determine each model correction parameter, and establish a vehicle dynamics model according to the model correction parameters.

2. The method according to claim 1, characterized in that, The step of determining the corresponding test working conditions of the target vehicle according to each of the working condition calibration parameters includes: Taking the specified working condition calibration parameters as the fixed working condition, wherein the fixed working condition includes the specified vehicle speed, the specified steering wheel angle, and the specified load weight; Generate each first working condition according to each of the vehicle speeds, the specified steering wheel angle, and the specified load weight calibration values; Generate each second working condition according to each of the steering wheel angles, the specified load weight, and each of the vehicle speed calibration values; Generate each third working condition according to each of the load weights, each of the vehicle speeds, and each of the steering wheel angle calibration values; Take each of the first working conditions, each of the second working conditions, and each of the third working conditions as each of the test working conditions.

3. The method according to claim 1, characterized in that, The step of performing iterative calculations on the initial model parameters based on each of the test working conditions to determine each model correction parameter includes: Determine the iterative value of the tire cornering stiffness corresponding to each test working condition according to the initial model parameters; Determine the iterative value of the front wheel angle according to the iterative value of the tire cornering stiffness; Perform iterative calculations according to the iterative value of the tire cornering stiffness and the iterative value of the front wheel angle to determine the iterative change amount; Determine the model correction parameter according to the iterative change amount.

4. The method according to claim 3, characterized in that, The step of determining the iterative value of the tire cornering stiffness corresponding to each test working condition according to the initial model parameters includes: Obtain the yaw rate gain algorithm and determine the test working condition parameters corresponding to each of the test working conditions; Substitute the initial value of the front wheel angle and each of the test working condition parameters into the yaw rate gain algorithm to determine the calculated value of the tire cornering stiffness; Take the average value of the calculated value of the tire cornering stiffness and the initial value of the tire cornering stiffness as the iterative value of the tire cornering stiffness.

5. The method according to claim 3, characterized in that, The step of determining the iterative value of the front wheel angle according to the iterative value of the tire cornering stiffness includes: Perform simulation calibration on the target vehicle to generate a simulation dynamics model; Substitute the iterative value of the tire cornering stiffness into the simulation dynamics model to obtain the calculated value of the front wheel angle output by the model; Take the average value of the calculated value of the front wheel angle and the initial value of the front wheel angle as the iterative value of the front wheel angle.

6. The method according to claim 3, characterized in that, The step of determining the model correction parameter according to the iterative change amount includes: When the iterative change amount is less than a preset threshold, determine the target round corresponding to the iterative change amount; Use the target value of the tire cornering stiffness and the target value of the front wheel steering angle corresponding to the target round as the model correction parameters.

7. The method according to claim 5, wherein, the establishing a vehicle dynamics model according to the model correction parameters includes: Calibrating the simulation dynamics model through the model correction parameters to generate the vehicle dynamics model.

8. A vehicle dynamics model establishing device, wherein, it includes: A test condition determination module, configured to obtain the condition calibration parameters of a target vehicle, and determine each test condition corresponding to the target vehicle according to each of the condition calibration parameters, wherein the condition calibration parameters include each vehicle speed calibration value, each steering wheel angle calibration value, and each load weight calibration value; A model initial parameter acquisition module, configured to acquire model initial parameters, wherein the model initial parameters include an initial value of the front wheel steering angle and an initial value of the tire cornering stiffness; A model correction parameter determination module, configured to perform iterative calculation on the model initial parameters based on each of the test conditions to determine each model correction parameter, and establish a vehicle dynamics model according to the model correction parameters.

9. An electronic device, wherein, the electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method according to any one of claims 1-7.

10. A computer storage medium, wherein, the computer storage medium stores computer instructions, and the computer instructions are used to cause a processor to execute the method according to any one of claims 1-7 when executed.

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