A steering control method and device

Abstract

A vehicle steering control method and apparatus are disclosed. The method includes: determining a tire force range based on the road surface adhesion coefficient and the real-time load transfer of the vehicle; determining a steering coordination rate between autonomous steering and differential steering based on the tire force range; the steering coordination rate indicating the weight of autonomous steering and differential steering; determining a target wheel angle and a target yaw moment based on the steering coordination rate and yaw rate error; providing the target wheel angle to the autonomous steering system and the target yaw moment to the differential steering system. This method is a steering coordination control method for autonomous steering and differential steering based on trajectory tracking, which can improve trajectory tracking accuracy.

Description

Technical Field

[0001] This application relates to the field of intelligent vehicle technology, and in particular to a steering control method and device. Background Technology

[0002] As a vehicle control method, in order to enable the vehicle to travel along a predetermined path and trajectory, there exists a steering control method that uses autonomous steering and differential steering together to perform trajectory tracking. Specifically, in this method, when the autonomous steering of the front wheels alone cannot suppress the lateral deviation to a small range (i.e., the lateral deviation is too large), differential steering (DS) is used to assist the autonomous steering of the front wheels, thereby enabling the vehicle to reliably travel along the predetermined path.

[0003] However, the above-mentioned steering control method only uses autonomous steering and differential steering together to track the trajectory when the lateral deviation generated by autonomous steering is large. It does not give full play to the coordination between autonomous steering and differential steering. Under certain driving conditions (such as high-speed driving conditions or other extreme conditions), the lateral response speed is slow and the tracking accuracy is low. Summary of the Invention

[0004] This application provides a steering control method and apparatus, which can improve trajectory tracking accuracy.

[0005] The first aspect of this application provides a steering control method, comprising: acquiring a tire force range; determining a steering coordination rate based on the tire force range, the steering coordination rate indicating the weight of the steering amount generated by the vehicle's autonomous steering system and the steering amount generated by the vehicle's differential steering system; acquiring a yaw rate error; determining a target wheel angle and a target yaw moment based on the yaw rate error and the steering coordination rate; and sending a first control command, the first control command including a control command for causing the autonomous steering system to generate the target wheel angle and a control command for causing the differential steering system to generate the target yaw moment.

[0006] By employing the steering control method described above, the steering coordination rate, i.e. the weight of autonomous steering and differential steering, is determined based on the tire force range. Therefore, the tire force can be fully utilized, the lateral response speed can be improved, the turning radius can be reduced, and the trajectory tracking accuracy can be improved.

[0007] In addition, since the steering coordination rate is determined by taking into account the tire force range, the vehicle's handling stability and safety can be improved even under extreme driving conditions (such as low road adhesion coefficient and high-speed driving).

[0008] Furthermore, the steering control method proposed in this embodiment utilizes a dual-system coupled steering control system—an autonomous steering system and a differential system—providing redundancy and enhancing vehicle driving safety under extreme conditions. Additionally, for example, when the autonomous steering system fails or malfunctions, the differential steering system can take over, further improving vehicle driving safety.

[0009] As a possible implementation of the first aspect, in the above method, the road adhesion coefficient and / or the load variation of multiple wheels of the vehicle are obtained; and the tire force range is determined based on the road adhesion coefficient and / or the load variation.

[0010] By considering the road surface adhesion coefficient and the load variation of the wheel, the tire force range can be determined, and the tire force range can be reliably planned.

[0011] As a possible implementation of the first aspect, one or more of the vehicle's acceleration, roll motion parameters, or pitch motion parameters in the lateral, longitudinal, and vertical directions are obtained; and the load change is determined based on one or more of the acceleration, roll motion parameters, or pitch motion parameters.

[0012] By considering the vehicle's acceleration in the lateral, longitudinal, and vertical directions, as well as its roll motion parameters or pitch motion parameters, the load variation can be determined reliably.

[0013] As a possible implementation of the first aspect, determining the steering coordination rate based on the tire force range may specifically include: obtaining the tire lateral relative utilization rate and a preset base coordination rate, wherein the tire lateral relative utilization rate indicates the ratio of lateral tire force to total tire force, and the base coordination rate is an initial parameter of the steering coordination rate; and determining the steering coordination rate based on the base coordination rate, the tire lateral relative utilization rate, and the tire force range.

[0014] Steering amount can typically be determined by steering radius or yaw angle.

[0015] A second aspect of this application provides a vehicle steering control device, comprising a processing module and a transceiver module. The processing module is used to acquire tire force range and yaw rate error, determine steering coordination rate based on tire force range, the steering coordination rate indicating the weight of steering amount generated by the vehicle's autonomous steering system and steering amount generated by the vehicle's differential steering system, and determine target wheel angle and target yaw moment based on yaw rate error and steering coordination rate. The transceiver module is used to send a first control command, the first control command including a control command for causing the autonomous steering system to generate the target wheel angle and a control command for causing the differential steering system to generate the target yaw moment.

[0016] As a possible implementation of the second aspect, the processing module is specifically used to obtain the road surface adhesion coefficient and / or the load variation of multiple wheels of the vehicle; and to determine the tire force range based on the road surface adhesion coefficient and / or the load variation.

[0017] As a possible implementation of the second aspect, the processing module is specifically used to obtain one or more of the vehicle's acceleration, roll motion state parameters, or pitch motion state parameters in the lateral, longitudinal, and vertical directions; and to determine the load change based on one or more of the acceleration, roll motion state parameters, or pitch motion state parameters.

[0018] As a possible implementation of the second aspect, the processing module is specifically used to obtain the tire lateral relative utilization rate and the preset basic coordination rate. The tire lateral relative utilization rate indicates the ratio of lateral tire force to total tire force, and the basic coordination rate is the initial parameter of the steering coordination rate. The steering coordination rate is determined based on the basic coordination rate, the tire lateral relative utilization rate, and the tire force range.

[0019] Steering amount can be determined by steering radius or yaw angle.

[0020] The technical effects of the second aspect of this application are basically the same as those described in the first aspect, and will not be repeated here.

[0021] A third aspect of this application provides a computing device including a processor and a memory, the memory storing program instructions that, when executed by the processor, cause the processor to perform any of the methods described in the first aspect.

[0022] A fourth aspect of this application provides a computer-readable storage medium storing program instructions that, when executed by a computer, cause the computer to perform any of the methods described in the first aspect.

[0023] The fifth aspect of this application provides a computer program product including program instructions that, when executed by a computer, cause the computer to perform any of the methods described in the first aspect.

[0024] These and other aspects of this application will become more apparent in the description of the following embodiments(s). Attached Figure Description

[0025] Figure 1 A schematic diagram of the structure of a vehicle to which the steering control method of one embodiment of this application is applied;

[0026] Figure 2 A flowchart illustrating a steering control method provided in one embodiment of this application;

[0027] Figure 3This is a schematic block diagram of a steering control device provided in one embodiment of the present application;

[0028] Figure 4 A schematic diagram of the structure of an electronic control unit provided in one embodiment of this application;

[0029] Figure 5 An explanatory diagram of a steering control method provided in one embodiment of this application;

[0030] Figure 6 This is a schematic diagram illustrating the vehicle state involved in trajectory tracking control in one embodiment of this application;

[0031] Figure 7 This is a schematic diagram illustrating the attachment ellipse involved in one embodiment of this application;

[0032] Figure 8 This is a schematic diagram illustrating the range of coordination rates involved in one embodiment of this application;

[0033] Figure 9 This is a simplified diagram of the force analysis of vehicle motion involved in the description of one embodiment of this application;

[0034] Figure 10 This is a schematic diagram illustrating the tire force range involved in one embodiment of this application;

[0035] Figure 11 This is a schematic diagram of a steering system architecture (of a vehicle) used in a steering control method according to an embodiment of this application. Detailed Implementation

[0036] As a vehicle control method, in order to enable the vehicle to travel along a predetermined path and trajectory, there exists a steering control method that uses autonomous steering and differential steering together to perform trajectory tracking. Specifically, in this method, when the autonomous steering of the front wheels alone cannot suppress the lateral deviation to a small range (i.e., the lateral deviation is too large), differential steering is used to assist the autonomous steering of the front wheels, thereby enabling the vehicle to reliably travel along the predetermined path.

[0037] However, the above-mentioned steering control method only uses autonomous steering and differential steering together to track the trajectory when the lateral deviation generated by autonomous steering is large. It does not give full play to the coordination between autonomous steering and differential steering. Under certain driving conditions (such as high-speed driving conditions or other extreme conditions), the lateral response speed is slow and the tracking accuracy is low.

[0038] In view of this, one embodiment of this application provides a steering control method that can improve trajectory tracking accuracy.

[0039] Before describing the steering control method, let's first describe the relevant structure of a vehicle to which this steering control method is applied.

[0040] Figure 1 This is a schematic diagram of a vehicle structure to which the steering control method of one embodiment of this application is applied. Figure 1 As shown, the vehicle 100 is a distributed drive vehicle, with hub motors 120 installed in each of its four wheels 110. The hub motors 120 drive and brake the wheels 110. Furthermore, the hub motors 120 can be independently controlled (motor controller not shown), resulting in different torques on the coaxial wheels 110, thus generating differential torque and enabling differential steering of the vehicle 100. In other words, the hub motors 120 constitute a differential steering (DS) system.

[0041] Alternatively, as another example of a distributed drive vehicle, instead of the hub motor 120, wheel-side motors can be installed near each of the four wheels 110. These wheel-side motors are connected to the wheels 110 via transmission mechanisms, enabling them to drive and brake the wheels 110. Furthermore, the method described in this embodiment can also be applied to other types of vehicles.

[0042] In addition, such as Figure 1 As shown, the vehicle 100 also includes a steering wheel 20, a torque and angle sensor 30, a steering motor 40, a clutch 70, a reduction gear 50, a steering unit 60, and a steering controller 90. The steering wheel 20 is used by the driver to perform steering operations. The torque and angle sensor 30 is used to detect the steering angle and the torque received by the steering wheel 20. The steering motor 40 is used to drive the steering wheel 20 to rotate. The reduction gear 50 is used to reduce the rotation of the steering motor 40 and transmit it to the steering wheel 20. The clutch 70 is located between the steering motor 40 and the reduction gear 50 and is used to control the connection between the drive motor 40 and the reduction gear 50. The steering unit 60 is used to convert the rotation of the steering wheel 20 into linear motion, etc., to drive the two front wheels 110 to rotate. The steering controller 90 is used to control the steering motor 40 and the clutch 70 according to the driver's operation of the steering wheel 20 or according to the instructions of the Vehicle Domain Controller (VDC) 10 (described later). The steering controller 90 can be constructed using an electronic control unit (ECU). The torque and angle sensor 30, steering motor 40, clutch 70, reduction mechanism 50, steering gear 60, and steering controller 90 constitute the electric power steering (EPS) system. In addition to the above-mentioned structural elements, the EPS system also includes structural elements such as vehicle speed sensor.

[0043] This EPS system has an assist function to help the driver's steering operation. In addition, it also has an autonomous steering function that actively steers the wheels 110 according to the instructions of the controller (e.g., the vehicle domain controller 10). Therefore, it can be said that the EPS system constitutes an autonomous steering system. As another example of an autonomous steering system, a four-wheel steering (4WS) system can also be used.

[0044] In addition, such as Figure 1 As shown, vehicle 100 has a vehicle domain controller 10, which provides services to vehicle components in the body domain and vehicle components in the chassis domain. Vehicle components in the body domain include window and door regulators, electric rearview mirrors, air conditioning, central locking, etc. Vehicle components in the chassis domain include components in the braking system, steering system, and acceleration system, such as the accelerator pedal.

[0045] In addition, the vehicle domain controller 10 also undertakes the overall control function of the differential steering system and the autonomous steering system. Under its control, when it is necessary to control the vehicle 100 to turn, the differential steering system and the autonomous steering system can be activated separately, or the differential steering system and the autonomous steering system can be activated together (simultaneously). By activating the differential steering system and the autonomous steering system together to perform steering control, effects such as improved vehicle stability during steering can be achieved.

[0046] The following reference Figures 2-4 The present application describes a steering control method provided in one embodiment. This steering control method is a steering coordination control method based on trajectory tracking that coordinates the autonomous steering system and the differential steering system. It can be applied in autonomous driving or as an auxiliary driving function in manual driving.

[0047] Figure 2 This is a flowchart illustrating a steering control method provided in an embodiment of this application. The steering control method is executed by a control device. In this embodiment, the control device is a vehicle domain controller. Specifically, the vehicle domain controller may include functional modules for implementing vehicle dynamics control, and these functional modules execute the aforementioned steering control method. Alternatively, as another embodiment, the steering control method may also be executed by a controller independent of the vehicle controller, which is used for implementing vehicle dynamics control.

[0048] The steering control method provided in the embodiments of this application will be described in detail below. The method may specifically include the following:

[0049] S1. Acquire vehicle dynamics-related information. This information includes the vehicle's real-time lateral and longitudinal positions obtained through cameras and other means. Vehicle dynamics-related parameters include the heading angle obtained through the vehicle's Inertial Measurement Unit (IMU). Side roll angle θ Roll Pitch angle θ Pitch Longitudinal acceleration a x Lateral acceleration a y Vertical acceleration a z This also includes the yaw rate *r* and the road adhesion coefficient *μ*, which are estimated through calculation. Regarding the estimation of the yaw rate, the ESP system receives the angle signal from the steering wheel torque angle sensor and combines it with the vehicle speed signal to estimate the expected yaw rate of the vehicle body at that vehicle speed and steering wheel angle. Here, the inertial measurement unit (IMU) is a device that measures the three-axis attitude angles (or angular rates) and acceleration of an object. Generally, an IMU contains three single-axis accelerometers and three single-axis gyroscopes. The accelerometers detect the acceleration signals of the object along the three independent axes of the carrier coordinate system, while the gyroscopes detect the angular velocity and acceleration of the object in three-dimensional space.

[0050] The following is a brief description of the estimation of the road surface adhesion coefficient. The road surface adhesion coefficient is equal to the ratio of the tire longitudinal force to the vertical load. The estimation of the road surface adhesion coefficient is the estimation of the maximum adhesion rate. The adhesion coefficient μ and the tire slip ratio s have a μ-s curve relationship. The slip ratio can be estimated and calculated by signals such as wheel speed, vehicle speed and ground force. Combined with longitudinal acceleration, the adhesion coefficient can be calculated.

[0051] In addition, the yaw rate r and the road adhesion coefficient μ can be estimated by the vehicle domain controller, or obtained by the vehicle domain controller from other controllers.

[0052] S2 determines the lateral displacement error and heading angle error based on the vehicle's real-time position signal, and then determines the path planning based on these errors to obtain the target yaw rate. Specifically, for example, assuming the vehicle travels at a constant speed during trajectory tracking, the path tracking target can specifically consider lateral tracking accuracy, i.e., minimizing the lateral error and heading angle error. For example, a pre-aiming control algorithm can be used to obtain the target yaw rate.

[0053] S3, based on changes in the road surface adhesion coefficient and / or vertical load (sometimes simply referred to as load), plans the dynamic range of tire forces (sometimes simply referred to as tire force range). The tire force range indicates the distributable range of tire forces. The road surface adhesion coefficient affects tire forces, and therefore the tire force range can be determined based on the road surface adhesion coefficient. Additionally, changes in the vertical load on a wheel alter its tire force range, and thus the tire force range can be determined based on the amount of change in vertical load. The amount of change in vertical load can be determined based on one or more of the vehicle's acceleration in the lateral, longitudinal, and vertical directions, roll motion parameters (roll angle), or pitch motion parameters (pitch angle). The real-time vertical load of each wheel is determined based on the amount of change in vertical load, and the tire force range of each wheel is determined based on the real-time vertical load.

[0054] S4. Determine the steering coordination rate based on the basic coordination rate and tire force range. The steering coordination rate (sometimes simply called the coordination rate) can also be referred to as the control coefficient of the autonomous steering controller and the differential steering controller. It indicates the weight of autonomous steering and differential steering; in other words, it indicates the weight of the steering amount generated by the vehicle's autonomous steering system and the steering amount generated by the vehicle's differential steering system. The steering amount here can be determined by the steering radius or yaw angle. The basic coordination rate is the initial parameter of the steering coordination rate, which can be preset, for example, based on experiments or experience.

[0055] S5 determines the target wheel angle and target yaw moment based on the yaw rate error and steering coordination rate. After determining the steering coordination rate (i.e., the weights of autonomous steering and differential steering) in S4, the target wheel angle generated by the autonomous steering system and the target yaw moment generated by the differential steering system can be determined based on the yaw rate error and the weights of autonomous and differential steering. It can be understood that the yaw rate error is obtained based on the target yaw rate and the current yaw rate.

[0056] S6, send control commands based on the target wheel angle and yaw moment. That is, generate and send control commands based on the target wheel angle and target yaw moment. These control commands include control commands for causing the autonomous steering system to generate the target wheel angle and control commands for causing the differential steering system to generate the target yaw moment.

[0057] By employing the steering control method described above, the steering coordination rate, i.e. the weight of autonomous steering and differential steering, is determined based on the tire force range. Therefore, the tire force can be fully utilized, the lateral response speed can be improved, the turning radius can be reduced, and the trajectory tracking accuracy can be improved.

[0058] In addition, since the steering coordination rate is determined by taking into account the tire force range, the vehicle's handling stability and safety can be improved even under extreme driving conditions (such as low road adhesion coefficient and high-speed driving).

[0059] Furthermore, the steering control method proposed in this embodiment does not require additional on-board hardware (such as the hardware required for hub motors to drive electric vehicles).

[0060] Furthermore, in this embodiment, the vehicle state quantity threshold is corrected by considering road surface adhesion conditions and / or vertical load transfer, and the steering coordination rate is determined on this basis, thereby improving vehicle driving safety.

[0061] Furthermore, the steering control method proposed in this embodiment utilizes a dual-system coupled steering control system—an autonomous steering system and a differential system—providing redundancy and enhancing vehicle driving safety under extreme conditions. Additionally, for example, when the autonomous steering system fails or malfunctions, the differential steering system can take over, further improving vehicle driving safety.

[0062] Furthermore, when applied to manual driving, the method of this embodiment can reduce the driver's workload and lower the driving burden.

[0063] Optionally, in S2, the target center of gravity sideslip angle can also be determined, and in S5, the target wheel turning angle and yaw moment can be determined based on the yaw rate error and the center of gravity sideslip angle error. In this way, the vehicle can maintain a stable posture when turning, improving the comfort of the occupants.

[0064] Figure 3 This is a schematic block diagram of a steering control device provided in one embodiment of this application. The steering control device is used to perform reference... Figure 2 The described steering control method. For example... Figure 3 As shown, the steering control device 200 includes a processing module 210 and a transceiver module 220. The processing module 210 can be used to execute the above-mentioned S2-S5, and the transceiver module 220 can be used to execute the above-mentioned S1 and S6.

[0065] Furthermore, this steering control device can be constructed using an Electronic Control Unit (ECU), which is a control device composed of integrated circuits used to perform a series of functions such as data analysis, processing, and transmission. For example... Figure 4 As shown in the figure, this application provides an ECU, which includes a microcomputer, an input circuit, an output circuit, and an analog-to-digital (A / D) converter.

[0066] The main function of the input circuit is to preprocess the input signal (such as a signal from a sensor). Different input signals require different processing methods. Specifically, since there are two types of input signals: analog signals and digital signals, the input circuit can include input circuits that process analog signals and input circuits that process digital signals.

[0067] The main function of an A / D converter is to convert analog signals into digital signals. After being preprocessed by the corresponding input circuit, the analog signal is input to the A / D converter for processing and conversion into a digital signal that can be accepted by a microcomputer.

[0068] The output circuit is a device that establishes a connection between the microcomputer and the actuator. Its function is to convert the processing results from the microcomputer into control signals to drive the actuator. The output circuit generally uses power transistors, which control the electronic circuit of the actuator by turning it on or off according to the instructions of the microcomputer.

[0069] A microcomputer includes a central processing unit (CPU), memory, and input / output (I / O) interfaces. The CPU connects to the memory and I / O interfaces via a bus, allowing them to exchange information. The memory can be read-only memory (ROM) or random access memory (RAM), etc. The I / O interface is the connection circuit between the CPU and input circuits, output circuits, or A / D converters for information exchange. Specifically, I / O interfaces can be divided into bus interfaces and communication interfaces. The memory stores programs, and the CPU can execute programs accessed from memory. Figure 2 The steering control method described in the corresponding embodiment.

[0070] As can be seen from the above, the embodiments of this application provide a computing device, which includes a processor and a memory. The memory stores program instructions, which are executed when executed by the processor. Figure 2 The steering control method described in the corresponding embodiment. Additionally, embodiments of this application also provide a computer-readable storage medium (memory) and a computer program product included in the computing device.

[0071] The following reference Figure 5 A steering control method provided in one embodiment of this application will be described.

[0072] Figure 5 This is an illustration of a steering control method provided in one embodiment of this application.

[0073] First, let's briefly describe the notation used in the following description. In the following description, regarding three-dimensional directions, unless otherwise specified, x represents the vehicle's longitudinal direction, y represents the vehicle's lateral direction, and z represents the vehicle's vertical direction. Additionally, regarding front, rear, left, and right, f represents front, r represents rear, l represents left, and r represents right. The "·" above the letters indicates a differential; one "·" indicates a first-order differential, and two "·" indicate a second-order differential. For example, θ... Roll Indicates the roll angle. This represents the roll acceleration. Unless otherwise specified, the meanings of the symbols throughout the instruction manual are consistent.

[0074] like Figure 5 As shown, the steering control method of this embodiment includes the following.

[0075] S10: Obtain vehicle dynamics-related parameter information to facilitate subsequent path planning and use the trajectory tracking controller (model) established based on the steering dynamics model to determine the target front wheel steering angle and target yaw moment.

[0076] Here, vehicle dynamics-related parameters include the heading angle obtained through the vehicle's inertial measurement unit. Side roll angle θ Roll Pitch angle θ Pitch Longitudinal acceleration a x Lateral acceleration a y Vertical acceleration a z This also includes calculating and estimating yaw rate r and road adhesion coefficient μ. Yaw rate r and road adhesion coefficient μ can be estimated by the vehicle domain controller, or they can be obtained by the vehicle domain controller from other controllers.

[0077] S20: Based on the real-time position of the vehicle and other vehicle status signals, such as using a pre-aiming control algorithm, lateral displacement and heading angle tracking are achieved to obtain the target yaw rate and the target center of mass sideslip angle.

[0078] S30: Based on the yaw rate error and the center of gravity sideslip angle error, and combined with the steering coordination rate detailed below, the target front wheel steering angle and target yaw moment are determined by using the established model predictive control (MPC) trajectory tracking controller for front wheel steering and differential steering, and the command based on this is output so that the autonomous steering system generates the target front wheel steering angle and the differential steering system generates the target yaw moment.

[0079] Here, MPC trajectory tracking control is a control method that aims to decompose optimization control problems with longer time spans, or even infinite time spans, into several optimization control problems with shorter or finite time spans, while still pursuing the optimal solution to a certain extent. Model predictive control consists of three elements: predictive model, online rolling optimization, and feedback correction.

[0080] S40: Based on the basic coordination rate of front wheel steering and differential steering, the lateral relative utilization rate of tires, and the vehicle posture, the range of coordination rate is determined, while the boundary of the coordination rate is constrained by the dynamic tire force distribution area detailed below.

[0081] S50: Based on the road surface adhesion coefficient, and taking into account the load transfer effects caused by the vehicle's acceleration in the lateral, longitudinal, and vertical directions, as well as its roll and pitch movements, the dynamic tire force distribution area is planned.

[0082] S60: Based on the coordination control optimization model constructed based on the steering coordination rate and other constraints, solve to determine the steering coordination rate (i.e., solve to obtain the optimal coordination rate).

[0083] S70: Determine the EPS torque requirement based on the target front wheel steering angle, determine the required drive torque for each wheel based on the target yaw moment, and finally complete the closed-loop control of the motor. Here, S70 can be executed separately by the EPS system controller and the wheel hub motor controller.

[0084] The contents of S20-S60 are described in more detail below.

[0085] S20: Based on the real-time position of the vehicle and other vehicle status signals, such as using a pre-aiming control algorithm, lateral displacement and heading angle tracking are achieved to obtain the target yaw rate and the target center of mass sideslip angle.

[0086] The specific algorithm design is as follows:

[0087] Figure 6 This is a schematic diagram illustrating the vehicle state involved in trajectory tracking control in one embodiment of this application. The S-shaped curve in the diagram represents the vehicle's target path, and CG is the vehicle's center of mass. (Refer to...) Figure 5 If we define the arc length of the starting point of the target path as σ = 0, then the arc length from the starting point at time T is expressed as follows:

[0088]

[0089] In the above formula, ρ(σ) represents the curvature at point T on the path, which is related to the arc length of that point from the starting point.

[0090] The lateral and heading errors of the vehicle are expressed as follows:

[0091]

[0092] The goal is to make the lateral and heading errors in the above equation globally asymptotically stable and converge to zero, while simultaneously satisfying the vehicle's stability requirements. When designing the trajectory tracking controller, the control objective is:

[0093]

[0094] With the goal of achieving global asymptotic stability of lateral and heading errors, the target yaw rate is designed and obtained through a backstepping algorithm as follows:

[0095]

[0096] In the above formula, k1 and k2 represent weighting coefficients, which are constants greater than zero. k1 and k2 must satisfy the condition k2 > k1v. x To determine the asymptotic stability of lateral and heading errors.

[0097] In addition, the aiming error can be expressed as follows:

[0098] e a =e + L sinψ(2-5)

[0099] In the above formula, L is the aiming distance, and e a To account for aiming error, a small-angle assumption is made regarding the heading angle error, simplifying the above formula to:

[0100] e a =e + Lψ(2-6)

[0101] Comparing formulas (2-4) and (2-6), we can obtain L = 1 / k1, and the target's yaw rate can be further expressed as:

[0102]

[0103] In addition, the target value of the lateral velocity is designed to approach 0, that is:

[0104]

[0105] Since the sideslip angle of the target's center of mass is the ratio of the lateral velocity to the longitudinal velocity, when the longitudinal velocity is constant, the sideslip angle of the target's center of mass is zero.

[0106] S30: Based on the yaw rate error, center of gravity sideslip angle error, and steering coordination rate, the target front wheel steering angle and target yaw moment are determined by using the established model predictive control (MPC) trajectory tracking controller for front wheel steering and differential steering.

[0107] First, the design of the trajectory tracking controller is described.

[0108] First, establish a front-wheel steering dynamics model. The front wheel autonomous steering will result in a steering angle δ f As input to the system, the vehicle dynamics equations are expressed as follows:

[0109]

[0110] The nonlinear brush tire model will be used to calculate the longitudinal and lateral forces of the tire;

[0111] The state variables are:

[0112] x1 = [r β] T

[0113] The input quantity is:

[0114] u1=δ f

[0115] Next, a differential steering dynamics model was established, and the differential torque M was defined. z As a system input, the differential steering system can be represented as follows:

[0116]

[0117] In the above formula, J f J r Let d represent the equivalent yaw inertia of the front and rear axles, respectively. f d r τ represents the equivalent damping of the front and rear axles, respectively. Af τ Ar τ represents the return torque of the front and rear tires, respectively. Ff τ Fr These represent the friction torque of the front and rear tires, respectively.

[0118] The vehicle dynamics equations are expressed as follows:

[0119]

[0120] M z =M f +M r =(F2-F1)l c +(F4-F3)l c

[0121] In the above formula, F1 and F2 are the driving forces of the two front wheels, F3 and F4 are the driving forces of the two rear wheels, and a and b are the distances from the front and rear axles to the center of mass, respectively.

[0122] In addition, the state variables in the above formula are:

[0123] x2=[r β δ f δ r ] T

[0124] The input quantity is:

[0125] u2 = M z

[0126] The vehicle dynamics models based on front-wheel active steering and differential steering are uniformly written in the following nonlinear time-varying form:

[0127]

[0128] For distributed drive vehicles, in addition to the front wheel EPS enabling autonomous steering, differential steering systems can be implemented on both the front and rear axles. The states and inputs are as follows:

[0129]

[0130] Considering trajectory tracking error, the target value of the yaw rate r must be met. * This allows for asymptotic stability; lateral stability requires the system to meet the target value β of the sideslip angle following the center of mass. * Therefore, the system output is defined as follows:

[0131] y = [r β] T (3-6)

[0132] The system model after discretizing the above (3-4) state equations:

[0133] x k+1 -x k =T□f(x) k ,u k (3-7)

[0134] Simplifying calculations: For nonlinear models, both the state variable x(k) at the current time k and the control input u(k-1) need to be linearized.

[0135] Δx(k+1)=A k Δx(k)+B k Δu(k)

[0136]

[0137] The discretized linear time-varying prediction model is obtained:

[0138] x p+1,k =A p,k x p,k +B p,k u p,k +d p,k (3-9)

[0139] For front-wheel autonomous steering: During the MPC control process, the goal is to achieve the best trajectory tracking effect with the minimum steering angle input. The objective function is constructed as follows:

[0140]

[0141] In the above formula, ΔU is the control input increment, and N p N c These represent the prediction steps and control compensation, respectively. Q, R, and ρ are the corresponding weight coefficients, and ε is the relaxation factor.

[0142] Similarly, for differential steering trajectory tracking, the objective function is designed as follows:

[0143]

[0144] Based on real-time calculated steering coordination rate, and in order to achieve the best trajectory tracking performance and minimize steering angle and yaw moment, a multi-objective optimization model is established as follows:

[0145] min J=λ c J1(x(k),u1(k-1),ΔU(k))+(1-λ c )J2(x(k),u2(k-1),ΔU(k))

[0146]

[0147] Based on the above optimization model, the optimal control increment sequence at the current time can be obtained as follows:

[0148]

[0149] Then, the first term of the optimal control increment sequence is taken as the current actual control quantity of the system, and finally rolling optimization is performed to obtain the result of the entire control timing.

[0150] S40: Based on the basic coordination rate of front wheel steering and differential steering, the lateral relative utilization rate of tires, and the vehicle posture, the range of coordination rate is determined, while the boundary of the coordination rate is constrained by the dynamic tire force distribution area detailed below.

[0151] First, a preliminary experiment comparing front-wheel EPS and differential steering (DS) was conducted. Specifically, a certain front-wheel steering angle and differential yaw moment were input, and circular motion was performed at different vehicle speeds, recording the actual driving steering radius R1(v). x ), R2(v x Normalize the inputs (front wheel steering angle, yaw moment) to obtain the steering radius per unit input:

[0152]

[0153] In the above formula, δ f,test M Z,test These represent the front wheel steering angle and differential torque input, respectively, in the steering circle experiment.

[0154] Therefore, based on the control effects of both in steering control, the weight of front wheel steering can be determined:

[0155]

[0156] In the above formula, ω b,1 This represents the basic coordination rate of the front wheel EPS in lateral tracking control during circular motion, and is the initial parameter of the steering coordination rate.

[0157] The control states of the two systems should be constrained under different driving conditions so that the vehicle does not need to simultaneously perform front wheel steering and differential braking control under certain operating conditions. The acceleration process is not considered in the driving conditions. Then, based on different operating conditions and the estimated vehicle posture, the vehicle driving state is determined as shown in Table 1.

[0158] Table 1. Vehicle Driving Status Table

[0159]

[0160] In the table above, r is the yaw rate, δ f The front wheel steering angle, r t δ is the yaw rate threshold. t This represents the front wheel steering angle threshold. K is the stability factor, characterizing the steady-state response in the vehicle handling stability test, as shown in the following equation:

[0161]

[0162] In the above formula, m represents the mass of the car; l f Indicates the distance from the front axle to the vehicle's center of gravity; l r k1 represents the distance from the rear axle to the vehicle's center of gravity; k2 represents the front axle lateral stiffness; k2 represents the rear axle lateral stiffness; L represents the vehicle's wheelbase: L = l f +l r .

[0163] Based on the vehicle driving status in Table 1, for example, according to Table 2, obtain the control status of the front-wheel steering (FS) controller and the differential steering (DS) controller.

[0164] Table 2 Controllable State Table for Dual System (FS / DS)

[0165]

[0166] Based on the controller states in the table above, the state coefficients η for the front wheel steering and differential steering control strategies are defined under different vehicle driving conditions. s,1 ,η s,2 Both are 0-1 variables (taking the value 0 or 1).

[0167] When controlling front wheel steering, the front wheels experience a lateral force from the ground, resulting in a certain turning angle. Differential steering, by controlling the difference in driving torque between the left and right wheels of a four-wheel independently driven electric vehicle (i.e., differential torque), not only generates yaw motion but also acts on the steering system to drive the wheels to rotate at a certain angle. The forces exerted by the ground on the tires include lateral force (lateral force, transverse force) and longitudinal force, both of which satisfy the adhesion ellipse relationship, such as... Figure 7 As shown, the lateral force is affected not only by the magnitude of the driving force and braking force, but also by the tire slip angle; the larger the slip angle, the greater the lateral force. Considering that front wheel steering generates tire lateral force, and that the driving torque difference of differential steering is controlled by the tire longitudinal force, and combining the limit values ​​of the tire's lateral and longitudinal forces, the expression for the tire's lateral relative utilization rate is established as follows:

[0168]

[0169] In the above formula, ω f,2 F represents the lateral relative utilization rate of the tire. yi F is the lateral force acting on tire i. xi The longitudinal force acting on tire i, and the ultimate values ​​of the lateral and longitudinal tire forces F. yi,lim F xi,lim Obtained from the tire adhesion ellipse. A diagram of the tire adhesion ellipse can be found here. Figure 7 .

[0170] F yi The lateral force on tire i (in this embodiment, there are 4 tires, so i is a positive integer less than or equal to 4) is proportional to the slip angle when the tire is in the linear region. When it is in the nonlinear region, the lateral force is obtained by looking up the calibrated data in a table, and its expression is:

[0171]

[0172] In the above formula, whether it belongs to the linear or nonlinear region can be determined based on the size of the sideslip angle. In addition, the size of the sideslip angle, the condition of the road surface, and the condition of the tires (tire pressure, etc.) can also be considered for judgment.

[0173] Based on the (target) differential torque M z Given the wheelbase d, the longitudinal force F of each tire can be obtained. xi The following relationship must be satisfied:

[0174]

[0175] The coordination rate expressions for the front wheel steering and differential steering systems, determined by considering the overall basic coordination rate, tire lateral relative utilization rate, and vehicle posture, are as follows:

[0176]

[0177] In the above formula, λ c,1 λ represents the control coefficient of the front wheel steering controller in coordinated control. c,2 This represents the control coefficient of the differential steering controller in coordinated control. Combined with the tire force dynamic distribution region mentioned below, the coordination rate range can be obtained as follows: Figure 8 As shown. Figure 8 In the diagram, the elliptical line represents the boundary of the tire force range, and the shaded line represents the variation range of the tire force range boundary. This means that due to differences in vehicle load and road adhesion coefficient, the tire force that a vehicle can exert varies, hence the existence of such boundary variations. The solid vector line on the left corresponds to the basic coordination rate. The solid vector line on the right corresponds to the steering coordination rate under a specific operating condition (such as normal driving conditions, not exceeding the dynamic boundary), while the dashed vector line corresponds to the steering coordination rate of front wheel steering and differential steering under extreme operating conditions (such as when making large-angle, rapid turns, requiring a larger lateral force).

[0178] S50: Based on the road adhesion coefficient, and taking into account the load transfer effects caused by the vehicle's acceleration in the lateral, longitudinal, and vertical directions, as well as its roll and pitch movements, a dynamic tire force distribution area (tire force range) is planned.

[0179] In order to coordinate the control of front wheel steering and differential steering, it is necessary to accurately obtain the maximum lateral force and longitudinal force provided by the road to the tires, which provides boundary constraints for calculating the feasible solution of the coordination rate. Therefore, the embodiments of this application plan the tire force distribution area (tire force range) in real time based on the road adhesion coefficient and considering the vehicle body motion posture.

[0180] Vertical load F zi The range of tire forces affecting the vehicle. This application's embodiments consider the impact of X, Y, and Z three-dimensional motion on load transfer, mainly including the vehicle's acceleration in the lateral, longitudinal, and vertical directions, as well as roll and pitch motions. Figure 9 The following is a simplified diagram of the force analysis of the vehicle body during motion. Next, we will establish the relationship expression for the load transfer (load change) caused by the vehicle body motion.

[0181] Lateral acceleration a y The load transfer between the left and right wheels is as follows:

[0182]

[0183] The lateral tilting motion causes the load transfer between the left and right wheels as follows:

[0184]

[0185] In the above formula, I x Let x be the moment of inertia about the x-axis (longitudinal axis). This is the roll angle acceleration.

[0186] Longitudinal acceleration a x The load transfer between the front and rear axles is as follows:

[0187]

[0188] Based on the load transfer caused by the aforementioned roll motion, the load transfer between the front and rear axles caused by the pitch motion can be obtained similarly:

[0189]

[0190] In the above formula, This is the pitch acceleration.

[0191] Consider the acceleration a in the vertical direction z The resulting vertical load transfer is as follows:

[0192] ΔF″″′ z =-ma z (5-5)

[0193] In summary, the estimated values ​​of the vertical loads on the four wheels are as follows:

[0194]

[0195] Taking the left front wheel as an example, the change in dynamic vertical load caused by its three-dimensional motion is defined as ΔF. zfl ,Right now:

[0196]

[0197] Considering dynamic load transfer and combining it with the attachment ellipse, the lateral and longitudinal forces acting on the tire satisfy the following:

[0198]

[0199] In the above formula, m is the vehicle mass, which can be the sprung mass (unloaded mass) or the actual mass estimated in real time (non-unloaded mass).

[0200] Furthermore, as shown in the above equation, the boundary of the attached ellipse changes with the load, as determined by ΔF. zfl The resulting dynamically distributable tire force area is as follows: Figure 10 As shown. Figure 10In the diagram, the elliptical line represents the boundary of the tire force range, and the shaded area represents the range of variation of the tire force boundary. The vector line on the right corresponds to the resultant force of the braking force and the lateral force, where θ is the angle between the resultant force and the braking force. The vector line on the left corresponds to the resultant force after considering the vertical force (an example).

[0201] based on Figure 10 From the ellipse in the diagram, we can obtain the maximum lateral force and maximum longitudinal force of the tire:

[0202] F yfl,lim =μF zfl sinθ, F xfl,lim =μF zfl cosθ(5-9)

[0203] The MPC controller described in S30 enables the vehicle to track the target yaw rate and the target center of gravity sideslip angle. However, under some extreme conditions (low ground adhesion coefficient, uneven force distribution among tires), it cannot provide sufficient tire force to achieve the target yaw rate. Therefore, to improve driving stability, the yaw rate is constrained by combining the front and rear axle tire force limits.

[0204]

[0205] In the above formula, F yf,lim ,F yr,lim These are the maximum lateral forces on the front and rear axles, respectively:

[0206]

[0207] Additionally, in operating conditions with low friction coefficients or high curvature paths, the center of gravity sideslip angle can be constrained to ensure it does not become excessive. The relationship between the center of gravity sideslip angle and the front and rear tire sideslip angles is as follows:

[0208]

[0209] The center of gravity slip angle can be kept within a reasonable range by limiting the tire slip angle:

[0210] α i ≤α i,lim =f(F yi,lim ,k i (5-13)

[0211] In addition, the limit values ​​of the above vehicle state signals (yaw rate, sideslip angle) are fed back to the MPC trajectory tracking controller in S30 and transformed into inequality constraints for rolling optimization solution.

[0212] In addition, S40 and S50 can be considered as one process.

[0213] S60: Based on the coordination control optimization model constructed based on the steering coordination rate and other constraints, solve to determine the steering coordination rate (i.e., solve to obtain the optimal coordination rate).

[0214] First, the design of the coordinated control optimization model is described.

[0215] In order to minimize the front wheel steering angle and yaw moment, and to ensure that the force on each tire is small, a comprehensive objective function J1 is established based on the coordination rate.

[0216]

[0217] The objective function mainly consists of three parts: the first term is the sum of the angle error within the control domain time, the second term is the sum of the torque error within the control domain time, and the third term is the sum of the load rates of each tire.

[0218] In the above formula, Δδ f (k+i) represents the front wheel steering angle error value at time k+i; ΔM z (k+i) represents the yaw moment error value at time k+i; R represents the corresponding weight matrix; N c Indicates the control domain step size.

[0219] Combining the yaw rate, sideslip angle threshold expressions established in S50, and other constraints, we construct constraint conditions for equality and inequality, and finally establish a constrained optimization model:

[0220]

[0221] In the above formula, ε represents the relaxation factor, ensuring the optimization problem is solvable. Inequality constraint (6-2-3) indicates that the force balance of each tire is considered, ξ lim The constraint coefficient is used; Equation 6-2-4) represents the constraint on longitudinal force by comprehensively considering the performance of the hub motor and the road adhesion conditions; the above optimization problem can be transformed into a quadratic programming (QP) problem for solution, for example, by using the effective set method or the interior point method. Here, the quadratic programming problem is a constrained nonlinear programming problem, and the objective function f(x) is a quadratic function. It has a simple form and can be solved using general methods for solving nonlinear programming problems, as well as specific solution methods.

[0222] Using the optimization model described above, the steering coordination rate can be determined and provided to the MPC trajectory tracking controller in S30 to determine the target front wheel steering angle and the target yaw moment.

[0223] The steering control method of this embodiment determines the steering coordination rate, i.e. the weight of autonomous steering and differential steering, based on the tire force range. Therefore, it can fully utilize tire force, improve lateral response speed, reduce turning radius, and improve trajectory tracking accuracy.

[0224] In addition, since the steering coordination rate is determined by taking into account the tire force range, the vehicle's handling stability and safety can be improved even under extreme driving conditions (such as low road adhesion coefficient and high-speed driving).

[0225] Furthermore, the steering control method proposed in this embodiment does not require additional on-board hardware (such as the hardware required for hub motors to drive electric vehicles).

[0226] Furthermore, in this embodiment, the vehicle state quantity threshold is corrected by considering road surface adhesion conditions and / or vertical load transfer, and the steering coordination rate is determined on this basis, thereby improving vehicle driving safety.

[0227] Furthermore, the steering control method proposed in this embodiment utilizes a dual-system coupled steering control system—an autonomous steering system and a differential system—providing redundancy and enhancing vehicle driving safety under extreme conditions. Additionally, for example, when the autonomous steering system fails or malfunctions, the differential steering system can take over, further improving vehicle driving safety.

[0228] Figure 11 This is a schematic diagram of a steering system architecture (of a vehicle) used in a steering control method according to an embodiment of this application.

[0229] like Figure 11 As shown, the system architecture mainly includes the following modules:

[0230] Signal processing module: This mainly includes modules for detection and acquisition, parameter estimation, and identification, with the aim of obtaining steering control-related information. Specifically, it involves acquiring the vehicle's real-time lateral and longitudinal positions (X and Y) via a camera and obtaining the yaw angle via an IMU. Side roll angle θ Roll Pitch angle θ Pitch Longitudinal acceleration a x Lateral acceleration a y Vertical acceleration a z The parameter estimation module primarily acquires the sideslip angle β and yaw rate r, while the identification module acquires the road surface adhesion coefficient μ in real time. The signal processing module can be used to perform the functions described in S10 above. The parameter estimation module and the identification module can also be integrated into the VDC.

[0231] The following provides brief examples of methods for estimating the center of gravity sideslip angle, the yaw rate, and the road surface adhesion coefficient.

[0232] Center of gravity sideslip angle estimation: Based on the two-degree-of-freedom vehicle model, it can be simplified to a linear estimation model with lateral velocity as the state. The lateral velocity state value can be estimated using the linear Kalman filter method. Finally, based on the relationship between the sideslip angle of the center of mass and the longitudinal and lateral velocities, the following can be calculated:

[0233] Yaw rate estimation: The ESP system receives angle signals from the steering wheel angle sensor and combines them with the vehicle speed signal to estimate the yaw rate value that should exist at that vehicle speed and steering wheel angle.

[0234] Road surface adhesion coefficient: The estimation of the road surface adhesion coefficient is the estimation of the maximum adhesion rate. The adhesion coefficient μ and the tire slip ratio s have a μ-s curve relationship. The slip ratio can be estimated and calculated by signals such as wheel speed, vehicle speed and ground force. The adhesion coefficient can be calculated by combining longitudinal acceleration.

[0235] Path planning module: Assuming the vehicle travels at a constant speed during trajectory tracking, the path tracking target can specifically consider lateral tracking accuracy, i.e., minimizing lateral error and heading angle error. A pre-aiming control algorithm is used to obtain the target yaw rate and center of gravity sideslip angle. This path planning module can be used to perform the content described in S20 above.

[0236] MPC trajectory tracking module: Based on the vehicle dynamics model of front-wheel steering and differential steering, a dual-system coordination rate model predictive controller is established. By controlling the yaw rate and center of gravity sideslip angle to target values, the lateral tracking requirements of trajectory tracking can be met. The controller solves for the target front wheel steering angle. yaw moment with target The MPC trajectory tracking module can be used to perform the contents of S30 above.

[0237] Coordination Control Module (Model): This module comprehensively considers the basic coordination rate, relative utilization rate, and vehicle posture to determine the coordination rate range. A comprehensive objective function J1 is established to minimize the front wheel steering angle and yaw moment, as well as the tire load rate. The influence of X, Y, and Z three-dimensional motion on load transfer is considered to determine the tire force distribution area, providing boundary constraints for the coordination rate range. Finally, based on the objective function and other constraints, a coordination rate optimization model is constructed, which is transformed into a quadratic programming problem to obtain the optimal coordination rate for the dual systems (front wheel steering and differential steering). This coordination control module can be used to execute the contents described in S40-S60 above.

[0238] In addition, to reduce the number of controllers and hardwired connections, and to fully utilize the powerful computing capabilities of the domain controller, the aforementioned path planning module, MPC trajectory tracking module, coordinated control module, and vehicle attitude estimation module are all integrated into the VDC for real-time calculation, ultimately obtaining the control command front wheel steering angle δ. f,c and the yaw moment M z,c The driving torque command T is assigned to the four wheels. i .

[0239] Motor control strategy module: The front wheel autonomous steering controller receives the steering angle and completes closed-loop steering control; the hub motors of all four wheels receive VDC torque commands T. i Then, torque closed-loop control is completed. This motor control strategy module can be used to execute the contents of S70 above. In addition, some or all of the functions of the motor control strategy module can also be integrated into VDC.

[0240] Furthermore, it goes without saying that the embodiments of this application also provide a vehicle including the above-described system architecture, as well as the steering control device, computing device, etc., described in the above embodiments.

[0241] It should be understood that, unless otherwise specified or logically conflicting, the terminology and / or descriptions in the various embodiments of this application are consistent and can be referenced by each other. Technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0242] Furthermore, terms such as "first," "second," and "third" in the specification and claims are used only to distinguish similar objects and do not represent a specific ordering of the objects. Where permissible, the specific order or sequence of the objects can be interchanged. The designations representing specific aspects of the method, such as S10, S20, etc., do not necessarily indicate that the actions must be performed in the order indicated by the designations; where permissible, the order can be interchanged, or the actions can be performed simultaneously. The term "comprising" used in the specification and claims should not be construed as limiting itself to the contents listed thereafter; it does not exclude the presence of other elements or steps.

Claims

1. A steering control method, characterized in that, include: Obtain the tire force range, which indicates the range within which tire force can be distributed; The steering coordination ratio is determined based on the tire force range, and the steering coordination ratio indicates the weight of the steering amount generated by the vehicle's autonomous steering system and the steering amount generated by the vehicle's differential steering system. Obtain the yaw rate error; The target wheel angle and target yaw moment are determined based on the yaw rate error and the steering coordination rate. Send a first control command, the first control command including a control command for causing the autonomous steering system to generate the target wheel angle and a control command for causing the differential steering system to generate the target yaw moment.

2. The steering control method according to claim 1, characterized in that, The range for obtaining tire force specifically includes: Obtain the road surface adhesion coefficient and / or the load variation of multiple wheels of the vehicle; The tire force range is determined based on the road surface adhesion coefficient and / or the load variation.

3. The steering control method according to claim 2, characterized in that, The acquisition of the load changes of multiple wheels of the vehicle specifically includes: Obtain one or more of the acceleration, roll motion parameters, or pitch motion parameters of the vehicle in the lateral, longitudinal, and vertical directions; The load change is determined based on one or more of the acceleration, the roll motion state parameters, or the pitch motion state parameters.

4. The steering control method according to any one of claims 1-3, characterized in that, The determination of steering coordination ratio based on the tire force range specifically includes: The relative lateral utilization rate of the tires is obtained and a preset basic coordination rate is obtained. The relative lateral utilization rate of the tires indicates the ratio of lateral tire force to total tire force, and the basic coordination rate is the initial parameter of the steering coordination rate. The steering coordination rate is determined based on the basic coordination rate, the tire lateral relative utilization rate, and the tire force range.

5. The steering control method according to any one of claims 1-3, characterized in that, The steering amount is determined by the steering radius or yaw angle.

6. A vehicle steering control device, characterized in that, Includes processing modules and transceiver modules. The processing module is used to acquire the tire force range and yaw rate error, determine the steering coordination rate based on the tire force range, the steering coordination rate indicating the weight of the steering amount generated by the vehicle's autonomous steering system and the steering amount generated by the vehicle's differential steering system, determine the target wheel angle and target yaw moment based on the yaw rate error and the steering coordination rate, and the tire force range indicating the distributable range of tire force. The transceiver module is used to send a first control command, which includes a control command for causing the autonomous steering system to generate the target wheel angle and a control command for causing the differential steering system to generate the target yaw moment.

7. The steering control device according to claim 6, characterized in that, The processing module is specifically used for, Obtain the road surface adhesion coefficient and / or the load variation of multiple wheels of the vehicle; The tire force range is determined based on the road surface adhesion coefficient and / or the load variation.

8. The steering control device according to claim 7, characterized in that, The processing module is specifically used for, Obtain one or more of the acceleration, roll motion parameters, or pitch motion parameters of the vehicle in the lateral, longitudinal, and vertical directions; The load change is determined based on one or more of the acceleration, the roll motion state parameters, or the pitch motion state parameters.

9. The steering control device according to any one of claims 6-8, characterized in that, The processing module is specifically used for, The relative lateral utilization rate of the tires is obtained and a preset basic coordination rate is obtained. The relative lateral utilization rate of the tires indicates the ratio of lateral tire force to total tire force, and the basic coordination rate is the initial parameter of the steering coordination rate. The steering coordination rate is determined based on the basic coordination rate, the tire lateral relative utilization rate, and the tire force range.

10. The steering control device according to any one of claims 6-8, characterized in that, The steering amount is determined by the steering radius or yaw angle.

11. A computing device, characterized in that, It includes a processor and a memory, the memory storing program instructions that, when executed by the processor, cause the processor to perform the method of any one of claims 1-5.

12. A computer-readable storage medium storing program instructions, characterized in that, When the program instructions are executed by a computer, the computer performs the method according to any one of claims 1-5.

13. A computer program product, characterized in that, It includes program instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1-5.

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