Vehicle control method, control equipment, vehicle and storage medium

Abstract

The embodiment of the invention provides a vehicle control method, control equipment, a vehicle and a storage medium, and the method comprises the steps: obtaining current vehicle data and a current vertical input value corresponding to the vertical input of a road surface when the vehicle passes through a large-curvature curve; inputting the current vertical input value into a predetermined roll center height function relational expression, and determining a roll center height expression corresponding to the height from the roll center to the ground; based on the roll center height expression and the current vehicle data, target dynamic models of the front wheel turning angle and the wheel camber angle in the yaw degree of freedom, the lateral degree of freedom and the roll degree of freedom are constructed; carrying out optimization solution on the target kinetic model, and determining an optimal rotation angle value corresponding to a front wheel rotation angle and an optimal camber angle value corresponding to a wheel camber angle; and based on the optimal corner value and the optimal camber angle value, a target component of the vehicle is controlled to work. According to the method, the vehicle can be stably controlled to pass through the large-curvature curve without reducing the speed of the vehicle, and the passing efficiency of the vehicle is improved.

Description

Technical Field

[0001] This application relates to the field of autonomous driving technology, and in particular to a vehicle control method, control device, vehicle, and storage medium. Background Technology

[0002] In the field of autonomous driving technology, controlling a vehicle to navigate through curves with significant curvature requires maintaining stable driving to prevent dangerous situations such as exceeding stability boundaries and rollovers. Current technologies typically achieve this by reducing vehicle speed. However, this method usually comes at the cost of reduced traffic efficiency, significantly lowering overall efficiency. Therefore, improving traffic efficiency while ensuring smooth cornering through curves, and ultimately enhancing the vehicle's autonomous cornering capability, is a key technical challenge that needs to be addressed. Summary of the Invention

[0003] This application provides a vehicle control method, control device, vehicle, and storage medium, aiming to solve the technical problem of how to improve vehicle traffic efficiency while ensuring the smoothness of the vehicle through curves with large curvature, thereby improving the vehicle's autonomous cornering ability.

[0004] A vehicle control method, comprising: When a vehicle passes through a curve with high curvature, acquire the current vehicle data and the current vertical input value corresponding to the road vertical input; Based on the current vertical input value corresponding to the road vertical input and the predetermined roll center height function relationship, the roll center height expression is determined. The roll center height expression is used to characterize the relationship between the wheel camber angle and the roll center height from the ground. Based on the roll center height expression and the current vehicle data, a target dynamic model is constructed corresponding to the front wheel steering angle and wheel camber angle in the yaw, lateral, and roll degrees of freedom. The target dynamics model is optimized and solved to determine the optimal steering angle value corresponding to the front wheel steering angle and the optimal camber angle value corresponding to the wheel camber angle; Based on the optimal steering angle value and the optimal camber angle value, the target components of the vehicle are controlled to operate.

[0005] In this embodiment, when a vehicle passes through a high-curvature curve, based on the current vertical input value corresponding to the road surface vertical input, a precise expression for the roll center height, corresponding to the height of the roll center above the ground, is generated. Based on this roll center height expression and current vehicle data, a target dynamics model with good coupling effect on the yaw, lateral, and roll degrees of freedom is constructed. This model is then optimized to determine the optimal steering angle and camber angle values ​​for controlling the vehicle's stable passage through the high-curvature curve. This method ensures the vehicle's handling and roll stability when passing through high-curvature curves by rationally controlling the front wheel steering angle and camber angle, thereby controlling the vehicle to pass smoothly through the curve. This method ensures handling and roll stability without reducing vehicle speed, effectively improving the vehicle's passage efficiency through high-curvature curves. This method achieves the goal of improving vehicle passage efficiency while ensuring stability through curves with large curvature, thus enhancing the vehicle's autonomous cornering ability.

[0006] Preferably, the current vertical input value includes the vertical input value of the left wheel and the vertical input value of the right wheel; the wheel camber angle includes the camber angle of the left rear wheel and the camber angle of the right rear wheel; The expression for the roll center height is as follows: ; in, The height of the tilt center from the ground. This is the vertical input value for the left wheel. This is the vertical input value for the right wheel. The camber angle of the left rear wheel. The camber angle of the right rear wheel. , , , , , , and represents the fitting coefficient.

[0007] In this embodiment, the camber angle (left rear wheel camber angle and right rear wheel camber angle) is used to characterize the camber center height expression corresponding to the height of the camber center from the ground, so that it is feasible to construct a target dynamic model and solve for the optimal camber angle value corresponding to the camber angle in the subsequent camber center height expression.

[0008] Preferably, the functional relationship of the roll center height is determined in the following manner: Based on the test vertical input value corresponding to the road vertical input and the test camber control value input to the vehicle camber actuator, determine the coordinate positions of multiple preset hard points; Based on the multiple coordinate positions, determine the real-time angle value corresponding to the wheel camber angle and the real-time height value corresponding to the height of the tilt center from the ground; The roll center height function is determined by fitting the real-time angle value, the real-time height value, the test vertical input value, and the test camber angle control value. This function is used to characterize the relationship between the roll center height from the ground, the road vertical input, and the wheel camber angle.

[0009] In this embodiment, the coordinate positions of preset hard points in the vehicle are tested in real time using a large number of test vertical input values ​​and test camber angle control values. Based on the real-time test coordinate positions, a large number of real-time angle values ​​and real-time height values ​​are determined. Based on the real-time angle values, real-time height values, test vertical input values, and test camber angle control values, curve fitting calculations are performed to accurately characterize the functional relationship between the roll center height from the ground, the road vertical input, the left rear wheel camber angle, and the right rear wheel camber angle.

[0010] Preferably, the target dynamic model includes a first dynamic equation, a second dynamic equation, and a third dynamic equation; The first dynamic equation is determined based on the vehicle's lateral acceleration, vehicle's longitudinal velocity, vehicle's yaw rate, roll angular acceleration, roll center height expression, and wheel lateral force; The second dynamic equation is determined based on the yaw moment of inertia, yaw angular acceleration, and wheel lateral force; The third dynamic equation is determined based on the roll moment of inertia, the roll center height expression, the roll angle, the roll angular acceleration, the vehicle lateral acceleration, the vehicle longitudinal velocity, the vehicle yaw rate, and the roll angular velocity. The lateral force of the wheel is determined based on the vehicle's lateral velocity, longitudinal velocity, yaw rate, front wheel steering angle, roll angle, left rear wheel camber angle, and right rear wheel camber angle.

[0011] In this embodiment, the measured current vehicle data is processed using vehicle dynamics principles to construct a first dynamic equation, a second dynamic equation, and a third dynamic equation. These equations are used to accurately characterize the coupling relationship between the yaw, lateral, and roll degrees of freedom, so that the vehicle can be accurately and reasonably controlled in the future based on the first, second, and third dynamic equations.

[0012] Preferably, solving the target dynamics model to determine the optimal steering angle value corresponding to the front wheel steering angle and the optimal camber angle value corresponding to the wheel camber angle includes: The target dynamics model is linearized to determine the target state space equation corresponding to the control variables, and the target optimization function and target constraints corresponding to the target state space equation are determined; the control variables include the front wheel steering angle, the left rear wheel camber angle, and the right rear wheel camber angle. Based on the objective optimization function and the objective constraints, the objective state space equation is solved by rolling optimization to determine the optimal control value corresponding to the control quantity. The optimal control value includes the optimal steering angle value corresponding to the front wheel steering angle, the optimal left rear wheel camber angle value corresponding to the left rear wheel camber angle, and the optimal right rear wheel camber angle value corresponding to the right rear wheel camber angle.

[0013] In this embodiment, the target dynamics model is linearized to determine the target state space equation. Rolling optimization is then performed on the target state space equation based on the target optimization function and target constraints to obtain the optimal steering angle corresponding to the front wheel angle, the optimal left rear wheel camber angle corresponding to the left rear wheel camber angle, and the optimal right rear wheel camber angle corresponding to the right rear wheel camber angle. This allows for appropriate vehicle control at the next moment, ensuring the vehicle's handling and roll stability when navigating sharp curves. This allows for smooth passage through sharp curves without reducing vehicle speed, effectively improving traffic efficiency.

[0014] Preferably, the objective optimization function is to minimize the sum of the predicted output error term, the control quantity change term, and the preset correction term; The prediction output error term is the sum of the prediction error function values ​​at all times within the prediction time domain; the prediction error function value is determined based on the difference between the prediction output value and the reference output value in the target state space equation; the reference output value is determined based on the current vehicle data. The control quantity change term is the sum of the control quantity change function values ​​at any two adjacent times within the control time domain; the control quantity change function value is determined based on the difference between the control quantities at any two adjacent times within the control time domain.

[0015] In this embodiment, the prediction output error term is determined based on the difference between the predicted output value and the reference output value, and the control quantity change term is determined based on the difference between the control quantities at any two adjacent times. By minimizing the prediction output error term and the control quantity change term, the vehicle is ensured to take large-curvature corners with optimal control values.

[0016] Preferably, the target constraints include control quantity constraints, control quantity change constraints, and predicted output quantity constraints. The control quantity constraint condition is that the control quantity is within a preset control range; The control quantity change constraint condition is the difference between the control quantities at any two adjacent times, which is within a preset change range; The constraint condition for the predicted output is that the predicted output value is within a preset output range.

[0017] In this embodiment, the magnitude of the control quantity is constrained by the control quantity constraint condition, the change of the control quantity between two adjacent time points is constrained by the control quantity change constraint condition, and the magnitude of the predicted output value is constrained by the predicted output quantity constraint condition, which helps to control the stability of vehicle driving, especially under large curvature curves.

[0018] A control device includes a processor and a memory, wherein, Memory, used to store computer programs; The processor is used to execute the program stored in the memory to implement the vehicle control method described above.

[0019] A vehicle including the aforementioned control equipment.

[0020] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the vehicle control method described above. Attached Figure Description

[0021] Figure 1 This is a flowchart of a vehicle control method provided in an embodiment of this application; Figure 2 This is another flowchart of a vehicle control method provided in one embodiment of this application; Figure 3 This is another flowchart of a vehicle control method provided in one embodiment of this application; Figure 4 This is a structural diagram of a control device provided in an embodiment of this application; Figure 5 This is a schematic diagram of the geometric relationship between a preset hard point and a roll center provided in an embodiment of this application; Figure 6 This is a schematic diagram of the dynamic model of a vehicle in the XOY plane according to an embodiment of this application; Figure 7 This is a schematic diagram of the dynamic model of a vehicle in the ZOY plane according to an embodiment of this application. Detailed Implementation

[0022] To make the technical problems, technical solutions, and beneficial effects solved by this application clearer, the following detailed description is provided in conjunction with embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0023] This application provides a vehicle control method, comprising: when a vehicle passes through a high-curvature curve, acquiring current vehicle data and the current vertical input value corresponding to the road surface vertical input; determining a roll center height expression based on the current vertical input value corresponding to the road surface vertical input and a pre-determined roll center height function relationship, wherein the roll center height expression characterizes the relationship between the wheel camber angle and the height of the roll center from the ground; constructing a target dynamic model corresponding to the front wheel steering angle and the wheel camber angle in yaw, lateral, and roll degrees of freedom based on the roll center height expression and the current vehicle data; optimizing and solving the target dynamic model to determine the optimal steering angle value corresponding to the front wheel steering angle and the optimal camber angle value corresponding to the wheel camber angle; and controlling the operation of target components of the vehicle based on the optimal steering angle value and the optimal camber angle value. This method rationally controls the front wheel steering angle and wheel camber angle of the vehicle. By using the optimal steering angle and optimal camber angle values, it controls the vehicle to stably pass through large-curvature curves, ensuring the vehicle's handling stability and roll stability. This method can smoothly control the vehicle to pass through large-curvature curves without reducing the vehicle's speed. It can improve the vehicle's traffic efficiency while ensuring the vehicle's stability when passing through curves with large curvature, thereby improving the vehicle's autonomous cornering ability.

[0024] In one embodiment, such as Figure 1 As shown, a vehicle control method is provided, which is applied to... Figure 4 Taking the control equipment in the example, the following steps are included: S101: When a vehicle passes through a curve with high curvature, acquire the current vehicle data and the current vertical input value corresponding to the road vertical input; S102: Based on the current vertical input value corresponding to the road vertical input and the pre-determined roll center height function relationship, determine the roll center height expression, which is used to characterize the relationship between the wheel camber angle and the roll center height from the ground. S103: Based on the roll center height expression and current vehicle data, construct the target dynamic model corresponding to the front wheel steering angle and wheel camber angle in yaw, lateral and roll degrees of freedom; S104: Optimize the target dynamics model to determine the optimal steering angle value corresponding to the front wheel steering angle and the optimal camber angle value corresponding to the wheel camber angle; S105: Controls the operation of the target components of the vehicle based on the optimal steering angle and optimal camber angle values.

[0025] In this context, a high-curvature curve refers to a curve with a large curvature. Road surface vertical input refers to the input that causes the vehicle's wheels to deform due to road surface deformation. In this example, the road surface vertical input can be the normal force exerted by the road surface on the wheels. The current vertical input value refers to the value of the road surface vertical input experienced by the vehicle at the current moment as it passes through the high-curvature curve. Current vehicle data refers to vehicle-related data at the current moment as the vehicle passes through the high-curvature curve, such as the current vehicle speed.

[0026] As an example, in step S101, when the control device determines that the vehicle is currently traversing a high-curvature curve, it acquires the current vertical input value of the road surface vertical input collected by sensors mounted on the vehicle at the current moment, along with the current vehicle data, to control the vehicle and ensure its smooth passage through the high-curvature curve. In this example, an image sensor can be mounted on the vehicle to acquire images of the road surface the vehicle is traversing in real time, and transmit the acquired images to the control device. The control device then determines whether the road surface the vehicle is currently traversing is a high-curvature curve based on the received images.

[0027] The roll center height refers to the height of the vehicle's roll center from the ground. The roll center height function is a relationship between the vertical input of the road surface, the wheel camber angle, and the roll center height from the ground; this function can be obtained through fitting a large amount of data. The roll center height expression is the expression used to determine the roll center height from the ground. The wheel camber angle is the angle between the plane where the wheel is located and the longitudinal vertical plane.

[0028] As an example, in step S102, the control device inputs the current vertical input value of the vehicle on the high-curvature curve into a pre-determined function relationship of the roll center height, which is characterized by the vertical input of the road surface and the wheel camber angle, to obtain the roll center height expression, which is characterized by the wheel camber angle, so as to determine the multi-degree-of-freedom target dynamic model based on the roll center height expression.

[0029] Among them, yaw degree of freedom refers to the degree of freedom of the vehicle around the Z-axis in the three-dimensional coordinate system. Lateral degree of freedom refers to the degree of freedom of the vehicle around the Y-axis in the three-dimensional coordinate system, that is, the degree of freedom of the vehicle in the lateral direction. Roll degree of freedom refers to the degree of freedom of the vehicle around the X-axis in the three-dimensional coordinate system, that is, the degree of freedom of the vehicle in the longitudinal direction. The target dynamics model is a model used to characterize the force and motion relationship in the vehicle.

[0030] As an example, in step S103, the control device performs kinematic analysis in the directions corresponding to the vehicle's yaw, lateral, and roll degrees of freedom according to Newton's second law. This determines a target dynamic model characterized by the expression for the roll center height at the current moment and the current vehicle data. The target dynamic model accurately represents the coupling relationship between the three degrees of freedom: yaw, lateral, and roll. In this example, the front wheel steering angle and wheel camber angle are unknowns to be controlled in the constructed target dynamic model.

[0031] The optimal steering angle value refers to the optimal front wheel steering angle at the next moment. The optimal camber angle value refers to the optimal wheel camber angle at the next moment.

[0032] As an example, in step S104, the control device uses a model predictive control (MPC) algorithm to perform rolling optimization on the target dynamics model corresponding to the current moment for a future period of time, and determines the values ​​of the front wheel steering angle and wheel camber angle at each moment in the future period of time. The value of the front wheel steering angle at the first moment in the future period of time is determined as the optimal steering angle value at the next moment, and the value of the wheel camber angle at the first moment in the future period of time is determined as the optimal camber angle value at the next moment, so as to control the vehicle to pass through the high curvature curve with the optimal steering angle value and the optimal camber angle value at the next moment.

[0033] The target component refers to the component that executes the optimal steering angle and optimal camber angle values.

[0034] As an example, in step S105, the control device controls the target components of the vehicle to operate at the next moment, so that the front wheel steering angle reaches the optimal steering angle value and the wheel camber angle reaches the optimal camber angle value, so as to control the vehicle to efficiently pass through large curvature curves with smooth handling stability and roll stability. In this example, the target component for controlling the front wheel steering angle is the vehicle steering wheel, and the target component for controlling the vehicle camber angle is the vehicle camber angle actuator. When the controller determines the optimal steering angle value and the optimal camber angle value corresponding to the next moment, it determines the input value for controlling the vehicle steering wheel based on the optimal steering angle value, controls the steering wheel to operate according to the input value to make the front wheel steering angle of the vehicle reach the optimal steering angle value, and determines the control value for controlling the vehicle camber angle actuator based on the optimal camber angle value, controls the vehicle camber angle actuator to operate according to the control value to make the wheel camber angle of the vehicle reach the optimal camber angle value.

[0035] In this embodiment, the control device repeatedly executes steps S101 to S105 at each moment when it determines that the vehicle is passing through a large curvature curve, so as to control the vehicle to pass through the large curvature curve efficiently and stably at each moment with the optimal turning angle and the optimal camber angle.

[0036] In this embodiment, when a vehicle passes through a high-curvature curve, based on the current vertical input value corresponding to the road surface vertical input, a precise expression for the roll center height, corresponding to the height of the roll center above the ground, is generated. Based on this roll center height expression and current vehicle data, a target dynamics model with good coupling effect on the yaw, lateral, and roll degrees of freedom is constructed. This model is then optimized to determine the optimal steering angle and camber angle values ​​for controlling the vehicle's stable passage through the high-curvature curve. This method ensures the vehicle's handling and roll stability when passing through high-curvature curves by rationally controlling the front wheel steering angle and camber angle, thereby controlling the vehicle to pass smoothly through the curve. This method ensures handling and roll stability without reducing vehicle speed, effectively improving the vehicle's passage efficiency through high-curvature curves. This method achieves the goal of improving vehicle passage efficiency while ensuring stability through curves with large curvature, thus enhancing the vehicle's autonomous cornering ability.

[0037] In one embodiment, the current vertical input value includes the left wheel vertical input value and the right wheel vertical input value; the wheel camber angle includes the left rear wheel camber angle and the right rear wheel camber angle; The expression for roll center height is: ; in, The height of the tilt center from the ground. This is the vertical input value for the left wheel. This is the vertical input value for the right wheel. The camber angle of the left rear wheel. The camber angle of the right rear wheel. , , , , , , and represents the fitting coefficient.

[0038] As an example, the control device determines the vertical input value of the left wheel. Vertical input value of the right wheel At that time, and Substitute the predetermined fitting coefficients , , , , , , and From the corresponding function formula for the roll center height, we can obtain the expression for the roll center height corresponding to the height of the roll center above the ground. Among them, the camber angle of the left rear wheel and right rear wheel camber angle For the unknown quantities that need to be optimized.

[0039] In this embodiment, the camber angle (left rear wheel camber angle and right rear wheel camber angle) is used to characterize the camber center height expression corresponding to the height of the camber center from the ground, so that it is feasible to construct a target dynamic model and solve for the optimal camber angle value corresponding to the camber angle in the subsequent camber center height expression.

[0040] In one embodiment, such as Figure 2 As shown, the functional relationship of the roll center height is determined in the following way: S201: Based on the test vertical input value corresponding to the road vertical input and the test camber control value input to the vehicle camber actuator, determine the coordinate positions of multiple preset hard points; S202: Based on multiple coordinate positions, determine the real-time angle value corresponding to the wheel camber angle and the real-time height value corresponding to the height of the roll center from the ground; S203: Based on the real-time angle value, real-time height value, test vertical input value, and test camber angle control value, a fitting process is performed to determine the roll center height function relationship. The roll center height function relationship is used to characterize the relationship between the roll center height from the ground, the road vertical input, and the wheel camber angle.

[0041] The preset hardpoint refers to a hardpoint pre-set on the vehicle, typically at the factory. The test vertical input value refers to the vertical input value of the road surface acting on the wheel, used to test the coordinate position corresponding to the preset hardpoint. In this example, the test vertical input values ​​include the left wheel test vertical input value and the right wheel test vertical input value. The left wheel test vertical input value is the vertical input value of the road surface acting on the left wheel, used to test the coordinate position corresponding to the preset hardpoint. The right wheel test vertical input value is the vertical input value of the road surface acting on the right wheel, used to test the coordinate position corresponding to the preset hardpoint. The test camber angle control value refers to the value input to the vehicle's camber angle actuator, used to control the camber angle actuator to test the wheel camber angle at the coordinate position corresponding to the preset hardpoint.

[0042] As an example, in step S201, when the control device determines that the left wheel of the vehicle is affected by the left wheel test vertical input value, the right wheel of the vehicle is affected by the right wheel test vertical input value, and the camber angle actuator of the vehicle is controlled by the test camber angle control value, it tests and obtains the position coordinates corresponding to the preset hard point of the vehicle in real time. In this example, as shown... Figure 5As shown, there are 12 preset hardpoints, labeled 1 to 12. The test camber angle control value includes the test camber angle control value applied to the left and right camber angle actuators. When the control equipment acquires the real-time vertical input values ​​of the left and right wheels and the test camber angle control value, the coordinate positions of preset hardpoints 1-12 are as follows: , , , , , , , , , , , .

[0043] The real-time angle value refers to the angle value corresponding to the camber angle determined based on the coordinate position of the preset hardpoint. In this example, the real-time angle value includes a first real-time angle value and a second real-time angle value. The first real-time angle value refers to the angle value corresponding to the left rear wheel camber angle determined based on the coordinate position of the preset hardpoint. The second real-time angle value refers to the angle value corresponding to the right rear wheel camber angle determined based on the coordinate position of the preset hardpoint. The real-time height value refers to the value corresponding to the height of the roll center from the ground determined based on the coordinate position of the preset hardpoint.

[0044] As an example, in step S202, such as Figure 5 As shown, among the 12 preset hard points numbered 1 to 12, preset hard points numbered 1 to 6 are on the left side of the vehicle, and preset hard points numbered 7 to 12 are on the right side of the vehicle. The control device determines the coordinates of the equivalent point 'a' on the right side of the vehicle based on the geometric relationship between the preset hard points in the vehicle. Specifically, the coordinates of the equivalent point 'a' on the right side of the vehicle are determined based on the coordinate positions of the preset hard points numbered 1 to 4. The specific calculation method includes: determining the slope based on the two hard points numbered 1 and 2. Determine the slope based on the coordinates of the preset hard points labeled 3 and 4. According to the slope and slope Determine the system of equations The coordinates of the equivalent point 'a' on the right side of the vehicle are determined by solving a system of simultaneous equations. Similarly, the control equipment determines the coordinates of the equivalent point b on the left side of the vehicle based on the geometric relationship between preset hard points in the vehicle. Specifically, it determines the slope based on the two hard points labeled 7 and 8. Determine the slope based on the coordinates of the preset hard points labeled 9 and 10. According to the slope and slope Determine the system of equations The coordinates of the equivalent point b on the left side of the vehicle are determined by solving a system of simultaneous equations. .

[0045] The control equipment determines the real-time position of the vehicle's roll center based on the coordinates of preset hard points numbered 6 and 12, as well as the coordinates of equivalent point a on the right side of the vehicle and equivalent point b on the left side. Specifically, this involves determining the slope based on the coordinates of the preset hard point numbered 6 on the left side of the vehicle and the coordinates of equivalent point a. Based on the coordinates of the preset hard point numbered 12 on the right side of the vehicle and the coordinates of the equivalent point b, the slope is determined. According to the slope and Determine the system of equations Solving the system of equations, we obtain the real-time position corresponding to the vehicle's roll center RC. The ordinate of the real-time position corresponding to the roll center RC The real-time height value corresponding to the height of the tilt center from the ground is determined. ,Right now Understandably, Figure 5 In the diagram, the intersection of the straight line between preset hard point 6 and the equivalent point a on the right side of the vehicle, and the straight line between preset hard point 12 and the equivalent point b on the left side of the vehicle, is the roll center RC. Therefore, based on the coordinates of preset hard points 6 and 12, and the coordinates of the equivalent points a on the right side and b on the left side of the vehicle, the real-time position of the vehicle's roll center can be accurately determined. Furthermore, the coordinates of the preset hard points are determined using a two-dimensional coordinate system corresponding to the ground as a reference frame; therefore, the ordinate of the real-time position of the roll center is... This is the real-time height value corresponding to the height of the tilt center from the ground. .

[0046] The control device determines the first real-time angle value corresponding to the camber angle of the left rear wheel based on the position coordinates of the preset hard points labeled 5 and 6. Based on the position coordinates corresponding to the preset hard points numbered 11 and 12, the second real-time angle value corresponding to the right rear wheel camber angle is determined. In this example, , .

[0047] As an example, in step S203, the control device repeatedly executes steps S201 to S202 to perform multiple tests to obtain a large number of first real-time angle values ​​corresponding to the left rear wheel camber angle, second real-time angle values ​​corresponding to the right rear wheel camber angle, and real-time height values ​​corresponding to the height of the roll center from the ground. By performing curve fitting on a large number of first real-time angle values, second real-time angle values, real-time height values, left wheel test vertical input values, right wheel test vertical input values, and test camber angle control values, the functional relationship between the height of the roll center from the ground, the road surface vertical input, and the roll center height corresponding to the left and right rear wheel camber angles is determined.

[0048] In this example, as Figure 5 As shown, the test camber control values ​​include the test camber control values ​​of the vehicle camber actuator on the left and the test camber control values ​​of the vehicle camber actuator on the right.

[0049] The control device measures the camber angle of the left rear wheel by using a large number of first real-time angle values, the test camber angle control value received by the left vehicle camber angle actuator, and the test vertical input value of the left wheel. The input corresponding to the vehicle camber angle actuator on the left side Vertical input to the road surface on the left Curve fitting is performed on the relationship between them to determine the input corresponding to the vehicle camber actuator on the left side of the first fitted curve. The corresponding fitting coefficient 'a' and the vertical input of the road surface on the left. The corresponding fitting coefficient b is used to determine the first fitted curve. .

[0050] The control device measures the right rear wheel camber angle by using a large number of second real-time angle values, the test camber angle control value received by the right vehicle camber angle actuator, and the test vertical input value of the right wheel. The input corresponding to the vehicle camber angle actuator on the right side Vertical input to the road surface on the right Curve fitting is performed on the relationship between the two parameters to determine the input corresponding to the vehicle camber actuator on the right side of the second fitted curve. The corresponding fitting coefficient c and the vertical input of the road surface on the right. The corresponding fitting coefficient d is used to determine the second fitted curve. .

[0051] The control device receives test camber angle control values ​​from a large number of vehicle camber angle actuators on the left and right sides, along with test vertical input values ​​for the left and right wheels, and real-time height values. This information is then used to control the corresponding inputs to the vehicle camber angle actuators on the left side. The input corresponding to the vehicle camber angle actuator on the right side Vertical input of the road surface on the left Vertical input of the road surface on the right side and the height of the tilt center from the ground Curve fitting is performed on the relationship between them to determine the input corresponding to the vehicle camber actuator on the left side of the third fitted curve. The corresponding fitting coefficient e, and the input corresponding to the vehicle camber angle actuator on the right. The corresponding fitting coefficient f, and the vertical input of the road surface on the left. The corresponding fitting coefficient j, and the vertical input of the road surface on the right. The corresponding fitting coefficient p is used to determine the third fitting curve. .

[0052] The control device combines the first, second, and third fitted curves to determine the roll center height function, which characterizes the relationship between the roll center height above the ground, the vertical input of the road surface, and the camber angles of the left and right rear wheels. The roll center height function is as follows: .in, and Obtained through real-time data collection. and The target dynamics model is determined in real time through subsequent target dynamics modeling. A set , and , corresponding to one .

[0053] In this embodiment, the coordinate positions of preset hard points in the vehicle are tested in real time using a large number of test vertical input values ​​and test camber angle control values. Based on the real-time test coordinate positions, a large number of real-time angle values ​​and real-time height values ​​are determined. Based on the real-time angle values, real-time height values, test vertical input values, and test camber angle control values, curve fitting calculations are performed to accurately characterize the functional relationship between the roll center height from the ground, the road vertical input, the left rear wheel camber angle, and the right rear wheel camber angle.

[0054] In one embodiment, the target dynamics model includes a first dynamic equation, a second dynamic equation, and a third dynamic equation; The first dynamic equation is determined based on the vehicle's lateral acceleration, longitudinal velocity, yaw rate, roll acceleration, roll center height, and wheel lateral force. The second dynamic equation is determined based on the yaw moment of inertia, yaw angular acceleration, and lateral force of the wheel; The third dynamic equation is determined based on the roll moment of inertia, the roll center height expression, the roll angle, the roll angular acceleration, the vehicle lateral acceleration, the vehicle longitudinal velocity, the vehicle yaw rate, and the roll angular velocity. The lateral force of a wheel is determined based on the vehicle's lateral velocity, longitudinal velocity, yaw rate, front wheel steering angle, roll angle, left rear wheel camber angle, and right rear wheel camber angle.

[0055] Among them, the first dynamic equation, the second dynamic equation, and the third dynamic equation refer to the dynamic equations in the target dynamic model used to characterize the force and motion relationship of the vehicle.

[0056] Lateral acceleration refers to the acceleration of a vehicle in the lateral direction. For example... Figure 6 As shown, the lateral direction is the direction corresponding to the y-axis in the vehicle coordinate system. The vehicle's lateral acceleration is its velocity in the lateral direction. derivative with respect to time Vehicle longitudinal speed refers to the speed of a vehicle in the longitudinal direction. For example... Figure 6 As shown, the longitudinal direction is the x-axis direction in the vehicle coordinate system, and the vehicle's longitudinal velocity is... Vehicle yaw rate refers to the angular velocity of a vehicle in the yaw direction. For example... Figure 6 As shown, the yaw degree of freedom is in the direction of the vehicle's Z-axis, which is perpendicular to the xoy plane. The vehicle's yaw angular velocity is... Roll acceleration refers to the acceleration corresponding to the roll angle in the roll degree of freedom direction. Roll acceleration is the acceleration corresponding to the roll angle. corresponding acceleration By roll angle It is calculated using the second derivative with respect to time. For example... Figure 7 As shown, roll angle This is the angle between the vehicle and the Z-axis. Wheel lateral force refers to the force exerted by the wheel in the lateral direction. For example... Figure 6 As shown, the lateral force of the wheel includes the lateral force of the left front wheel. Right front wheel lateral force Lateral force of the left rear wheel and the lateral force of the right rear wheel Among them, the lateral force of the left front wheel This represents the lateral force acting on the left front wheel. The lateral force acting on the right front wheel... This represents the lateral force acting on the right front wheel. The lateral force acting on the left rear wheel... This represents the lateral force on the left rear wheel. The lateral force on the right rear wheel... This represents the lateral force acting on the right rear wheel.

[0057] As an example, the control device, based on Newton's second law, measures the vehicle's lateral acceleration in the lateral degree of freedom direction. and wheel lateral force and angular acceleration of the roll direction in the roll degree of freedom and the expression for the roll center height The yaw rate of the vehicle in the yaw direction. and vehicle longitudinal speed Vehicle dynamics modeling is performed to determine the first dynamic equation, which characterizes the coupling relationship among the three degrees of freedom: yaw, lateral, and roll. The first dynamic equation is: in, = . This is the distance from the vehicle's center of gravity to its roll center. This represents the height of the vehicle's sprung mass from the ground when no rollover has occurred. For example... Figure 7 As shown, the vehicle's center of gravity is CG, and its roll center is RC. In this example, the change in the center of gravity CG can be ignored. = . For vehicle quality. This refers to the sprung mass of the vehicle. Vehicle mass. and sprung mass All measurements were taken at the factory and are stored in the vehicle's system database, which can be directly accessed when needed.

[0058] Here, yaw moment of inertia refers to the vehicle's moment of inertia in the yaw direction. Yaw angular acceleration refers to the vehicle's acceleration in the yaw degree of freedom direction. In this example, the yaw moment of inertia is... Yaw acceleration It is the first derivative of the yaw rate.

[0059] As an example, the control device, based on Newton's second law, applies the lateral force to the left front wheel of the vehicle in the lateral degree of freedom direction. Right front wheel lateral force Lateral force of the left rear wheel and the lateral force of the right rear wheel The yaw moment of inertia of the vehicle in the yaw direction. and yaw acceleration And the distance from the center of gravity to the front axle pre-stored in the vehicle system database. and the distance from the center of gravity to the rear axle Vehicle dynamics modeling is performed to determine the second dynamic equation. The second dynamic equation is: In this example, as Figure 6 As shown, the distance from the center of mass to the front axle and the distance from the center of gravity to the rear axle These are inherent attributes of the vehicle and are all constant values.

[0060] Here, the roll moment of inertia refers to the moment of inertia in the roll direction. Roll angular velocity. It refers to the angular velocity of a vehicle in the roll direction, expressed through the roll angle. The first derivative with respect to time is determined.

[0061] As an example, the control device, according to Newton's second law, measures the moment of inertia of the roll rotation in the direction of the roll degree of freedom. , Expression for roll center height yaw angle roll acceleration lateral acceleration of the vehicle and roll rate vehicle longitudinal speed And the vehicle yaw rate in the yaw degree of freedom direction. Vehicle dynamics modeling is performed to determine the third dynamic equation. The third dynamic equation is: in, = , , Let be the moment of inertia of the vehicle about its roll center. It is the acceleration due to gravity. This refers to the vehicle's suspension roll stiffness. This refers to the vehicle's roll damping. Both the suspension roll stiffness and roll damping are preset values.

[0062] In this example, the lateral force of the left front wheel Lateral force on the right front wheel Lateral force of the left rear wheel And the lateral force of the right rear wheel .in, ( These are the lateral stiffness values ​​corresponding to the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively, and are the vehicle's attribute values. and These are the camber stiffness of the left rear wheel and the camber stiffness of the right rear wheel, respectively, and are vehicle attribute values. , ,in, Let be the vehicle's roll steering coefficient, be a characteristic parameter of the vehicle, and be a constant value. This refers to the steering angle of the vehicle's front wheels. This refers to the vehicle's lateral speed. Lateral speed is the speed of a vehicle in the lateral direction. . ( These are the sideslip angles corresponding to the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel, respectively. This refers to the camber angle of the vehicle's left rear wheel. This refers to the camber angle of the vehicle's right rear wheel.

[0063] In this embodiment, the measured current vehicle data is processed using vehicle dynamics principles to construct a first dynamic equation, a second dynamic equation, and a third dynamic equation. These equations are used to accurately characterize the coupling relationship between the yaw, lateral, and roll degrees of freedom, so that the vehicle can be accurately and reasonably controlled in the future based on the first, second, and third dynamic equations.

[0064] In one embodiment, such as Figure 3 As shown, step S104, which involves solving the target dynamics model to determine the optimal steering angle value corresponding to the front wheel steering angle and the optimal camber angle value corresponding to the wheel camber angle, includes: S301: Perform model linearization on the target dynamics model, determine the target state space equation corresponding to the control variables, and determine the target optimization function and target constraints corresponding to the target state space equation; the control variables include the front wheel steering angle, the left rear wheel camber angle, and the right rear wheel camber angle; S302: Based on the objective optimization function and objective constraints, perform rolling optimization to solve the objective state space equation and determine the optimal control value corresponding to the control quantity. The optimal control value includes the optimal steering angle value corresponding to the front wheel steering angle, the optimal left rear wheel camber angle value corresponding to the left rear wheel camber angle, and the optimal right rear wheel camber angle value corresponding to the right rear wheel camber angle.

[0065] The target state-space equation refers to the state equation after linearization of the target dynamics model. The target optimization function is the optimization function used to reasonably determine the optimal steering angle, optimal left rear wheel camber angle, and optimal right rear wheel camber angle over a future time period. The target constraints are the conditions used to constrain the control variables and / or predicted output variables in the target state-space equation.

[0066] As an example, in step S301, the control device performs model linearization on the constructed target dynamics model to determine the target state-space equation corresponding to the control quantity. In this example, the target state-space equation is: The control equipment determines the vehicle's control parameters at each moment, including the front wheel steering angle, left rear wheel camber angle, and right rear wheel camber angle. This refers to the real-time vehicle status data acquired at the current moment, including real-time collected vehicle data. Specifically, , The control parameters used to control the vehicle include the front wheel steering angle, the left rear wheel camber angle, and the right rear wheel camber angle. Specifically, , For the predicted output of the target state-space equation, specifically, , The sideslip angle is the vehicle's center of gravity. , For vehicle state variables The derivative, The system matrix is ​​the state-space equation of the target. , Let be the input matrix of the target state-space equation. , The output matrix of the target state-space equation. , The characteristic matrix of the target state-space equation is... , specifically, , , , , , , , , , , , , , , , , , , , , , , , , , .

[0067] After determining the target state-space equations corresponding to the control quantities (front wheel steering angle, left rear wheel camber angle, and right rear wheel camber angle), the control equipment sets minimizing the prediction error of the target state-space equations and minimizing the change in control quantities as optimization objectives, determines the target optimization function, and uses the control quantities and predicted output quantities of the target state-space equations as target constraints, so as to optimize and solve the target state-space equations according to the target optimization function and target constraints.

[0068] As an example, in step S302, the control device performs rolling optimization on the target state space equation for a future time period based on the target optimization function and target constraints, and determines the values ​​of the control quantities (front wheel steering angle, left rear wheel camber angle, and right rear wheel camber angle) at each moment within the future time period. The value of the control quantity corresponding to the first moment in the future time period is determined as the optimal value of the control quantity corresponding to the next moment, that is, the optimal steering angle value corresponding to the front wheel steering angle, the optimal left rear wheel camber angle value corresponding to the left rear wheel camber angle, and the optimal right rear wheel camber angle value corresponding to the right rear wheel camber angle.

[0069] In this embodiment, the target dynamics model is linearized to determine the target state space equation. Rolling optimization is then performed on the target state space equation based on the target optimization function and target constraints to obtain the optimal steering angle corresponding to the front wheel angle, the optimal left rear wheel camber angle corresponding to the left rear wheel camber angle, and the optimal right rear wheel camber angle corresponding to the right rear wheel camber angle. This allows for appropriate vehicle control at the next moment, ensuring the vehicle's handling and roll stability when navigating sharp curves. This allows for smooth passage through sharp curves without reducing vehicle speed, effectively improving traffic efficiency.

[0070] In one embodiment, the objective optimization function is to minimize the sum of the predicted output error term, the control variable change term, and the preset correction term; The prediction output error term is the sum of the prediction error function values ​​at all times within the prediction time domain; the prediction error function value is determined based on the difference between the predicted output value and the reference output value in the target state space equation; the reference output value is determined based on the current vehicle data. The control quantity change term is the sum of the control quantity change function values ​​at any two adjacent times within the control time domain; the control quantity change function value is determined based on the difference between the control quantities at any two adjacent times within the control time domain.

[0071] The prediction output error term refers to the function term used to minimize the prediction error of the target state-space equation. The control quantity change term refers to the function term used to minimize the change in the control quantity of the target state-space equation. The preset correction term refers to the correction term used to modify the target optimization function to ensure its accuracy.

[0072] In this context, the prediction time domain refers to the time domain used for model prediction. The predicted output value refers to the output value at each time step within the prediction time domain, predicted by the target state-space equation. The reference output value refers to a preset reference value used to judge the prediction error of the predicted output value. The prediction error function value refers to a function value used to characterize the difference between the predicted output value and the reference output value at each time step within the prediction time domain.

[0073] As an example, the control device uses a model predictive control (MPC) algorithm to predict the target state-space equations in the prediction time domain and outputs the results at each time step within the prediction time domain. Corresponding predicted output value For each time step, the corresponding predicted output value Reference output value corresponding to each time step The difference is processed to determine the prediction error function value for each time step. In this example, a preset correction coefficient for each time step is used. For each time step, the corresponding predicted output value Reference output value corresponding to each time step The squared difference term is corrected to obtain the prediction error function value at each time step in the prediction time domain. The control device will predict the time domain [1, Within [the range], the prediction error function values ​​corresponding to all times. The sum of these values ​​is used to determine the prediction output error term. In this example, the prediction output error term is: .

[0074] In this example, the vehicle's center of gravity sideslip angle is... yaw rate and roll angle Determined as the predicted output quantity , specifically, Reference output value for ,Right now =0, = , =0. Where, , This is the reciprocal of the lane curvature. Understandably, it represents the vehicle's center of gravity sideslip angle. Set to 0 to minimize the vehicle's sideslip angle when cornering with a large curvature. , adjust the yaw angle Set to 0 to minimize the roll angle when the vehicle is cornering with a large curvature. This ensures the vehicle's stability when cornering.

[0075] In this context, the control time domain refers to the time domain used for model control. The control variable change function value refers to the function value used to characterize the degree of change of the control variable at each moment within the control time domain.

[0076] In this example, when the control device uses the Model Predictive Control (MPC) algorithm to predict the target state-space equation in the prediction time domain, it uses a preset correction coefficient at any two adjacent time points within the control time domain. By correcting the square of the difference between the control quantities at any two adjacent time points, we obtain the function value of the control quantity change at any two adjacent time points in the control time domain. ,in, The control device will control the time domain [1, Within [the range], the change function values ​​of the control quantity at any two adjacent time points. The sum of these values ​​is determined as the control variable change term, which is: .

[0077] In this example, the control device queries the system database for pre-stored preset correction items. ,in, and These are all preset constants. The control device will predict the output error term. Control quantity change item and preset correction items The function that minimizes the sum of the values ​​is determined as the objective optimization function. In this example, the objective optimization function is: .

[0078] In this embodiment, the front wheel steering angle Left rear wheel camber angle and right rear wheel camber angle Determined as control quantity , specifically, The vehicle's center of gravity sideslip angle yaw rate and roll angle Determined as the predicted output quantity , specifically, Due to yaw rate Used to characterize the state and tilt angle corresponding to the yaw degree of freedom. The centroid sideslip angle is used to characterize the state corresponding to the tilt degree of freedom. Used to characterize the state corresponding to the lateral degrees of freedom, by solving the front wheel steering angle. Left rear wheel camber angle and right rear wheel camber angle This minimizes the objective optimization function used to characterize the prediction error and the change in control quantity, thereby enabling the vehicle to achieve better coupling in yaw, roll and lateral degrees of freedom, so as to ensure that the vehicle can corner with large curvature with optimal control values.

[0079] In this embodiment, the prediction output error term is determined based on the difference between the predicted output value and the reference output value, and the control quantity change term is determined based on the difference between the control quantities at any two adjacent times. By minimizing the prediction output error term and the control quantity change term, the vehicle is ensured to take large-curvature corners with optimal control values.

[0080] In one embodiment, the target constraints include control quantity constraints, control quantity change constraints, and predicted output quantity constraints. The control quantity constraint condition is that the control quantity is within the preset control range; The constraint condition for the change of control quantity is that the difference between the control quantity at any two adjacent times is within a preset range. The constraint for the predicted output is that the predicted output value is within the preset output range.

[0081] Among them, control quantity constraints refer to the conditions used to constrain the control quantity. Control quantity change constraints refer to the conditions used to constrain the change in the control quantity. Predicted output constraints refer to the conditions used to constrain the predicted output. Preset control range refers to the range corresponding to the preset upper and lower limits of the control quantity. Preset change range refers to the range corresponding to the preset upper and lower limits of the change in the control quantity at each time point. Preset output range refers to the range corresponding to the preset upper and lower limits of the predicted output.

[0082] As an example, the control device uses a preset control range. , Within the time domain of constraint control, the magnitude of the control quantity at each moment determines the control quantity constraint conditions. The control quantity constraint conditions are as follows: The control equipment adopts a preset variation range. , Within the constraint control time domain, the magnitude of the change in the control quantity at each moment determines the constraint conditions for the change in the control quantity. The constraint conditions for the change in the control quantity are as follows: The control device uses a preset output range. , To constrain the magnitude of the predicted output value in the state-space equations, the constraint conditions for the predicted output are determined as follows: .

[0083] In this example, the control quantity Including front wheel steering angle Left rear wheel camber angle and right rear wheel camber angle Predicted output Including the vehicle's center of gravity sideslip angle yaw rate and roll angle The control equipment determines the constraints on the control quantities, including the front wheel steering angle. The value is within the preset steering angle range, left rear wheel camber angle The values ​​and the right rear wheel camber angle The value is within the preset rear wheel steering angle range. The control equipment determines the control quantity change constraints, including the front wheel steering angle at any two adjacent moments. The change is within the preset range of front wheel steering angle variation, and the left rear wheel camber angle at any two adjacent moments. The change in the right rear wheel camber angle at any two adjacent moments The change in the angle of inclination is within the preset range. The control equipment determines the constraints for the predicted output, including the centroid sideslip angle. The values ​​are within the preset sideslip angle range, and the yaw rate is... The values ​​are within the preset angular velocity range and roll angle. The value is within the preset roll angle range.

[0084] Understandably, excessively large or small control variables, excessively large or small changes in control variables between adjacent time points, and excessively large or small predicted output variables can all lead to instability of the vehicle during controlled cornering. In this embodiment, by constraining the magnitude of the control variable through control variable constraints, constraining the changes in the control variable between adjacent time points through control variable change constraints, and constraining the magnitude of the predicted output value through predicted output constraints, it is helpful to control the stability of vehicle driving, especially in curves with large curvature.

[0085] This application also provides a control device 40, please refer to... Figure 4 It includes a memory 410 and a processor 420, wherein the memory 410 is used to store computer programs; and the processor 420 is used to execute the programs stored in the memory 410 to implement the vehicle control method described in any embodiment of this application.

[0086] This application also provides a vehicle that includes the control device described in the above embodiments.

[0087] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the vehicle control method described in any embodiment of this application.

[0088] In this application, "multiple" refers to two or more.

[0089] In this application, unless otherwise expressly defined, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0090] The terms “first,” “second,” “third,” “fourth,” etc., in this application (if any) are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0091] In this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, in this application, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0092] Unless otherwise specified, all steps in this application may be performed sequentially or randomly. For example, if the method includes steps A and B, it means that the method may include steps A and B performed sequentially, or it may include steps B and A performed sequentially. For example, if the method may also include step C, it means that step C may be added to the method in any order. For example, the method may include steps A, B, and C, or it may include steps A, C, and B, or it may include steps C, A, and B, etc.

[0093] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A vehicle control method, characterized in that, include: When a vehicle passes through a curve with high curvature, acquire the current vehicle data and the current vertical input value corresponding to the road vertical input; Based on the current vertical input value corresponding to the road vertical input and the predetermined roll center height function relationship, the roll center height expression is determined. The roll center height expression is used to characterize the relationship between the wheel camber angle and the roll center height from the ground. Based on the roll center height expression and the current vehicle data, a target dynamic model is constructed corresponding to the front wheel steering angle and wheel camber angle in yaw, lateral and roll degrees of freedom. The target dynamics model is optimized and solved to determine the optimal steering angle value corresponding to the front wheel steering angle and the optimal camber angle value corresponding to the wheel camber angle; Based on the optimal steering angle value and the optimal camber angle value, the target component of the vehicle is controlled to operate.

2. The vehicle control method according to claim 1, characterized in that, The current vertical input value includes the vertical input value of the left wheel and the vertical input value of the right wheel; the wheel camber angle includes the camber angle of the left rear wheel and the camber angle of the right rear wheel; The expression for the roll center height is as follows: ; in, The height of the tilt center from the ground. This is the vertical input value for the left wheel. This is the vertical input value for the right wheel. The camber angle of the left rear wheel. The camber angle of the right rear wheel. , , , , , , and represents the fitting coefficient.

3. The vehicle control method according to claim 1, characterized in that, The functional relationship of the roll center height is determined in the following way: Based on the test vertical input value corresponding to the road vertical input and the test camber control value input to the vehicle camber actuator, determine the coordinate positions of multiple preset hard points; Based on the multiple coordinate positions, determine the real-time angle value corresponding to the wheel camber angle and the real-time height value corresponding to the height of the tilt center from the ground; The roll center height function is determined by fitting the real-time angle value, the real-time height value, the test vertical input value, and the test camber angle control value. This function is used to characterize the relationship between the roll center height from the ground, the road vertical input, and the wheel camber angle.

4. The vehicle control method according to claim 1, characterized in that, The target dynamic model includes a first dynamic equation, a second dynamic equation, and a third dynamic equation; The first dynamic equation is determined based on the vehicle's lateral acceleration, vehicle's longitudinal velocity, vehicle's yaw rate, roll angular acceleration, roll center height expression, and wheel lateral force; The second dynamic equation is determined based on the yaw moment of inertia, yaw angular acceleration, and wheel lateral force; The third dynamic equation is determined based on the roll moment of inertia, the roll center height expression, the roll angle, the roll angular acceleration, the vehicle lateral acceleration, the vehicle longitudinal velocity, the vehicle yaw rate, and the roll angular velocity. The lateral force of the wheel is determined based on the vehicle's lateral velocity, longitudinal velocity, yaw rate, front wheel steering angle, roll angle, left rear wheel camber angle, and right rear wheel camber angle.

5. The vehicle control method according to claim 1, characterized in that, Solving the target dynamics model to determine the optimal steering angle value corresponding to the front wheel steering angle and the optimal camber angle value corresponding to the wheel camber angle includes: The target dynamics model is linearized to determine the target state space equation corresponding to the control variables, and the target optimization function and target constraints corresponding to the target state space equation are determined; the control variables include the front wheel steering angle, the left rear wheel camber angle, and the right rear wheel camber angle. Based on the objective optimization function and the objective constraints, the objective state space equation is solved by rolling optimization to determine the optimal control value corresponding to the control quantity. The optimal control value includes the optimal steering angle value corresponding to the front wheel steering angle, the optimal left rear wheel camber angle value corresponding to the left rear wheel camber angle, and the optimal right rear wheel camber angle value corresponding to the right rear wheel camber angle.

6. The vehicle control method according to claim 5, characterized in that, The objective optimization function is to minimize the sum of the predicted output error term, the control variable change term, and the preset correction term; The prediction output error term is the sum of the prediction error function values ​​at all times within the prediction time domain; the prediction error function value is determined based on the difference between the prediction output value and the reference output value in the target state space equation; the reference output value is determined based on the current vehicle data. The control quantity change term is the sum of the control quantity change function values ​​at any two adjacent times within the control time domain; the control quantity change function value is determined based on the difference between the control quantities at any two adjacent times within the control time domain.

7. The vehicle control method according to claim 5, characterized in that, The target constraints include control quantity constraints, control quantity change constraints, and predicted output constraints. The control quantity constraint condition is that the control quantity is within a preset control range; The control quantity change constraint condition is the difference between the control quantities at any two adjacent times, which is within a preset change range; The constraint condition for the predicted output is that the predicted output value is within a preset output range.

8. A control device, characterized in that, Including processor and memory, among which, Memory, used to store computer programs; A processor for executing a program stored in a memory to implement the vehicle control method according to any one of claims 1-7.

9. A vehicle, characterized in that, Includes the control device as described in claim 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the vehicle control method according to any one of claims 1-7.

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