A vehicle control method, apparatus, electronic device, and storage medium

Abstract

This application discloses a vehicle control method, device, electronic device, and storage medium. The method includes: constructing a parameter matrix required for a vehicle lateral deviation state equation based on the front wheel angle; discretizing the parameter matrix; obtaining a vehicle lateral deviation state equation based on the front wheel angle change based on the discrete parameter matrix, the front wheel angle change, vehicle state variables, and the vehicle lateral deviation state equation based on the front wheel angle; constructing an objective function based on the weights corresponding to the front wheel angle change, vehicle state variables, and the vehicle state variables; determining the target front wheel angle change when the objective function is minimized using the vehicle lateral deviation state equation based on the front wheel angle change; confirming the target front wheel angle based on the target front wheel angle change and the current front wheel angle; determining the target steering wheel angle based on the target front wheel angle and steering ratio; and performing vehicle control based on the target steering wheel angle.

Description

Technical Field

[0001] This application relates to the field of vehicle control technology, and more specifically, to a vehicle control method, apparatus, electronic device, and storage medium. Background Technology

[0002] Lateral control is a method of controlling the lateral deviation of a vehicle by controlling the steering wheel angle. In related technologies, the goal of vehicle lateral control schemes is to minimize the steering wheel angle, i.e., to minimize the steering wheel angle. However, the performance indicators for evaluating the effectiveness of vehicle lateral control are minimizing lateral deviation and yaw angle deviation, as well as minimizing steering wheel wobble. It is important to note that minimizing steering wheel wobble is not the same as minimizing steering wheel angle. Therefore, the vehicle lateral control schemes in related technologies cannot directly and effectively adjust these three performance indicators for evaluating control effectiveness.

[0003] Therefore, minimizing the three performance indicators of lateral deviation, heading angle deviation, and steering wheel sway in vehicle lateral control, and improving the vehicle lateral control effect, is a technical problem that needs to be solved by those skilled in the art. Summary of the Invention

[0004] The purpose of this application is to provide a vehicle control method, device, electronic device, and computer-readable storage medium that improve the lateral control effect of a vehicle.

[0005] To achieve the above objectives, this application provides a vehicle control method, comprising:

[0006] The parameter matrix required to construct the vehicle lateral deviation state equation based on the front wheel steering angle is then discretized.

[0007] Based on the discrete parameter matrix, the change in front wheel angle, and the vehicle state variables, the vehicle lateral deviation state equation based on the change in front wheel angle is obtained; wherein, the vehicle state variables include lateral deviation, lateral deviation rate of change, heading angle deviation, heading angle rate of change, and the front wheel angle at the previous moment.

[0008] An objective function is constructed based on the weights corresponding to the front wheel angle change, the vehicle state variable, the front wheel angle change, and the vehicle state variable, respectively. The target front wheel angle change at the minimum value of the objective function is determined using the vehicle lateral deviation state equation based on the front wheel angle change.

[0009] The target front wheel angle is determined based on the change in the target front wheel angle and the current front wheel angle. The target steering wheel angle is determined based on the target front wheel angle and the steering ratio. Vehicle control is then performed based on the target steering wheel angle.

[0010] The vehicle lateral deviation state equation based on the change in front wheel steering angle is as follows: the vehicle state variable at time k+1 is the sum of the first product at time k and the second product at time k. The first product at time k is the product of the change in front wheel steering angle at time k and the first parameter matrix. The second product at time k is the product of the change in front wheel steering angle at time k and the second parameter matrix. The first parameter matrix is ​​a parameter matrix constructed based on the single-wheel lateral stiffness of the front wheel, the single-wheel lateral stiffness of the rear wheel, the front overhang length, the rear overhang length, the longitudinal velocity, the vehicle mass, and the moment of inertia. The second parameter matrix is ​​a parameter matrix constructed based on the single-wheel lateral stiffness of the front wheel, the front overhang length, the vehicle mass, and the moment of inertia. The moment of inertia is the moment of inertia about the z-axis, which is an axis perpendicular to the ground.

[0011] The vehicle lateral deviation state equation based on the change in front wheel steering angle is as follows:

[0012] X inc (k+1)=A inc_d X inc (k)+B inc_d U inc (k);

[0013] Among them, X inc (k) represents the vehicle state variable at time k, X inc (k+1) represents the vehicle state variable at time k+1, U inc (k) = ΔU(k), which is the change in the front wheel steering angle at time k. A d Let be the discrete first parameter matrix. B d It is a discrete second parameter matrix.

[0014] Wherein, the objective function is the sum of the objective values ​​corresponding to all time points, and the objective value corresponding to time k is the sum of the third product and the fourth product at time k. The third product at time k is the product of the transpose of the vehicle state variable at time k, the first weight matrix, and the vehicle state variable at time k. The fourth product at time k is the product of the transpose of the change in front wheel steering angle at time k, the second weight matrix, and the change in front wheel steering angle at time k. The first weight matrix is ​​a matrix constructed from the weights corresponding to the vehicle state variables, and the second weight matrix is ​​the weight corresponding to the change in front wheel steering angle.

[0015] The objective function is: X inc (k) represents the vehicle state variable at time k. For X inc The transpose of (k), Uinc (k) = ΔU(k), which is the change in the front wheel steering angle at time k. For U inc The transpose of (k), Q inc Let R be the first weight matrix. inc This is the second weight matrix.

[0016] The step of determining the target front wheel angle change when the objective function is minimized using the vehicle lateral deviation state equation based on the front wheel angle change includes:

[0017] Based on the vehicle lateral deviation state equation based on the change in front wheel steering angle and the objective function, construct the Riccati equation and determine the objective equation value when the Riccati equation converges.

[0018] The intermediate matrix is ​​determined based on the objective equation value, the discrete parameter matrix, and the weights corresponding to the change in front wheel steering angle.

[0019] The target front wheel steering angle change is determined based on the intermediate matrix and the adjusted state variable matrix.

[0020] This also includes:

[0021] Determine the reference weights corresponding to the lateral deviation, the rate of change of the lateral deviation, the heading angle deviation, the rate of change of the heading angle deviation, and the change in the front wheel steering angle, respectively;

[0022] Determine the vehicle speed weighting coefficients corresponding to the lateral deviation, the heading angle deviation, and the change in front wheel steering angle based on the current vehicle speed;

[0023] Determine the radius of curvature weighting coefficients corresponding to the lateral deviation, the heading angle deviation, and the change in front wheel steering angle based on the current radius of curvature.

[0024] The baseline weights corresponding to the lateral deviation rate of change and the heading angle deviation rate of change are respectively used as the final weights corresponding to the lateral deviation rate of change and the heading angle deviation rate of change;

[0025] The product of the baseline weight, vehicle speed weight, and radius of curvature weight corresponding to the lateral deviation, the heading angle deviation, and the change in front wheel steering angle, respectively, is used as the final weight corresponding to the lateral deviation, the heading angle deviation, and the change in front wheel steering angle, respectively.

[0026] Before determining the reference weights corresponding to the lateral deviation, the amount of change in lateral deviation, the heading angle deviation, the rate of change of heading angle deviation, and the rate of change of front wheel steering angle, the method further includes:

[0027] Set all vehicle speed weights and all curvature radius weights to baseline values;

[0028] The vehicle is calibrated on a straight road at a reference speed. The reference weights corresponding to the lateral deviation, the rate of change of the lateral deviation, the heading angle deviation, and the change of the heading angle deviation are set as reference values. The reference weights corresponding to the change of the front wheel angle are adjusted until the steering wheel swing is within the expected index. The reference weights corresponding to the lateral deviation and the heading angle deviation are adjusted until the lateral deviation and the heading angle deviation are within the expected index.

[0029] Calibrate on a straight road at different vehicle speeds, adjust the vehicle speed weighting coefficient corresponding to the change in front wheel angle until the steering wheel swing is within the expected index, and adjust the vehicle speed weighting coefficients corresponding to the lateral deviation and the heading angle deviation until the lateral deviation and the heading angle deviation are within the expected index;

[0030] The vehicle is calibrated on curves with different radii of curvature using the reference speed. The curvature radius weighting coefficient corresponding to the change in front wheel angle is adjusted until the steering wheel swing is within the expected index. The curvature radius weighting coefficients corresponding to the lateral deviation and the heading angle deviation are adjusted until the lateral deviation and the heading angle deviation are within the expected index.

[0031] The control effect on curves with different radii of curvature was tested at different vehicle speeds. When the expected target was not met, the corresponding curvature radius weight coefficient was adjusted until the expected target was met.

[0032] To achieve the above objectives, this application provides a vehicle control device, comprising:

[0033] A construction module is used to construct the parameter matrix required for the vehicle lateral deviation state equation based on the front wheel steering angle, and to discretize the parameter matrix.

[0034] The first determining module is used to obtain a vehicle lateral deviation state equation based on the change in front wheel angle based on a discrete parameter matrix, the change in front wheel angle, vehicle state variables, and the vehicle lateral deviation state equation of the front wheel angle; wherein, the vehicle state variables include lateral deviation, lateral deviation rate of change, heading angle deviation, heading angle deviation rate of change, and the front wheel angle at the previous moment.

[0035] The second determining module is used to construct an objective function based on the weights corresponding to the front wheel angle change, the vehicle state variable, the front wheel angle change, and the vehicle state variable, and to determine the target front wheel angle change when the objective function is minimized using the vehicle lateral deviation state equation based on the front wheel angle change.

[0036] The control module is used to confirm the target front wheel angle based on the change in the target front wheel angle and the current front wheel angle, determine the target steering wheel angle based on the target front wheel angle and the steering ratio, and perform vehicle control based on the target steering wheel angle.

[0037] To achieve the above objectives, this application provides an electronic device, comprising:

[0038] Memory, used to store computer programs;

[0039] A processor is used to execute computer programs to implement the steps of the vehicle control method described above.

[0040] To achieve the above objectives, this application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the vehicle control method described above.

[0041] As can be seen from the above scheme, the vehicle control method provided in this application includes: constructing a parameter matrix required for a vehicle lateral deviation state equation based on the front wheel angle, and discretizing the parameter matrix; obtaining a vehicle lateral deviation state equation based on the front wheel angle change based on the discrete parameter matrix, the front wheel angle change, vehicle state variables, and the vehicle lateral deviation state equation based on the front wheel angle; wherein, the vehicle state variables include lateral deviation, lateral deviation change rate, heading angle deviation, heading angle change rate, and the front wheel angle at the previous moment; constructing an objective function based on the weights corresponding to the front wheel angle change, the vehicle state variables, the front wheel angle change, and the vehicle state variables respectively, and determining the target front wheel angle change when the objective function is minimized using the vehicle lateral deviation state equation based on the front wheel angle change; confirming the target front wheel angle based on the target front wheel angle change and the current front wheel angle, determining the target steering wheel angle based on the target front wheel angle and the steering ratio, and performing vehicle control based on the target steering wheel angle.

[0042] The vehicle control method provided in this application constructs a vehicle lateral deviation state equation based on the change in front wheel steering angle. An objective function is constructed based on the weights corresponding to the change in front wheel steering angle, vehicle state variables, and the change in front wheel steering angle itself. The target change in front wheel steering angle is determined using the vehicle lateral deviation state equation based on the change in front wheel steering angle, at which the objective function is minimized. Minimizing the objective function minimizes the three performance indicators: lateral deviation, heading angle deviation, and change in front wheel steering angle (i.e., steering wheel sway), thereby improving the vehicle's lateral control performance. This application also discloses a vehicle control device, an electronic device, and a computer-readable storage medium, which can achieve the same technical effects.

[0043] It should be understood that the above general description and the following detailed description are merely exemplary and do not limit this application. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. The drawings are used to provide a further understanding of this disclosure and constitute a part of the specification. They are used together with the following detailed description to explain this disclosure, but do not constitute a limitation of this disclosure. In the drawings:

[0045] Figure 1 This is a schematic diagram of a vehicle lateral control scheme in related technologies;

[0046] Figure 2 This is a flowchart illustrating a vehicle control method according to an exemplary embodiment;

[0047] Figure 3 This is a schematic diagram of the vehicle lateral control scheme provided in this embodiment;

[0048] Figure 4 This is a flowchart illustrating a method for calibrating the weights corresponding to each vehicle state variable and the change in front wheel steering angle, according to an exemplary embodiment.

[0049] Figure 5 This is a structural diagram illustrating a vehicle control device according to an exemplary embodiment;

[0050] Figure 6 This is a structural diagram of an electronic device according to an exemplary embodiment. Detailed Implementation

[0051] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. Furthermore, in the embodiments of this application, "first," "second," etc., are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0052] Vehicle lateral control schemes in related technologies, such as Figure 1 As shown, the vehicle state-space equations are constructed based on a two-degree-of-freedom model of a front-wheel steering vehicle. A state-space equation describes the relationship between a system's inputs, outputs, and state variables. It includes state equations (which describe the relationship between state variables and inputs) and output equations (which describe the relationship between outputs and state variables).

[0053] Where X represents the deviations of the system's state variables. e1 represents the lateral deviation between the vehicle and the target trajectory, e2 represents the heading angle deviation between the vehicle and the target trajectory, U represents the front wheel steering angle corresponding to the system input, and T represents the desired yaw rate of change.

[0054] C f For the front wheel single-wheel lateral stiffness, C r For the single-wheel lateral stiffness of the rear wheel, l f For the front overhang length, l r V is the rear overhang length. x Let m be the vehicle's longitudinal velocity, and I be the total vehicle mass. z Let be the moment of inertia of the vehicle about the z-axis, which is the axis perpendicular to the ground.

[0055] Then, a feedback control system is constructed based on the state equations (the B1T part is compensated by feedforward), with feedback control U = -KX. For linear control systems with quadratic forms, the optimal solution can be calculated using LQR (linear quadratic regulator) control, which means finding the optimal feedback matrix K such that the following objective function is optimal:

[0056]

[0057] Where Q represents the weights of the deviations in the state variable X in the objective function, and R represents the weights of the input variable U in the objective function. Given the LQR algorithm, we can obtain: A d and B d These are the discretized matrices of matrices A and B, respectively. Matrix P satisfies the Riccati equation: Based on the vehicle status information and the planned trajectory, the various state variables of X are calculated. The optimal feedback controller coefficient K is calculated using the LQR algorithm mentioned above. Then, the feedback controller output is calculated and superimposed with the feedforward output to obtain U, the current desired steering wheel angle. The corresponding steering wheel angle is calculated based on the steering transmission ratio and then sent to EPS (Electric Power Steering).

[0058] In the vehicle lateral control schemes of related technologies, the goal is to minimize the steering wheel angle, that is, to minimize the steering wheel angle. However, the performance indicators for evaluating the vehicle lateral control effect are to minimize the lateral deviation and heading angle deviation, and to minimize the steering wheel wobble. However, small steering wheel wobble and small steering wheel angle are not the same concept. It can be seen that the vehicle lateral control schemes of related technologies cannot directly and effectively adjust the three performance indicators for evaluating the control effect.

[0059] Therefore, a discrete vehicle state space equation is constructed based on the changes in front wheel angle, the adjusted state variable matrix, the weights corresponding to the vehicle state variables and the changes in front wheel angle, and then an objective function is constructed. When the objective function takes the minimum value, the three performance indicators of lateral deviation, heading angle deviation, and changes in front wheel angle (i.e., steering wheel sway) can be minimized, thereby improving the lateral control effect of the vehicle.

[0060] This application discloses a vehicle control method that improves the lateral control effect of a vehicle.

[0061] See Figure 2 A flowchart illustrating a vehicle control method according to an exemplary embodiment, such as... Figure 2 As shown, it includes:

[0062] S101: Construct the parameter matrix required for the vehicle lateral deviation state equation based on the front wheel steering angle, and discretize the parameter matrix.

[0063] The vehicle lateral control scheme provided in this embodiment is as follows: Figure 3 As shown. In this step, firstly, the parameter matrix required for the vehicle lateral deviation state equation based on the front wheel steering angle is constructed based on the vehicle parameters. The vehicle parameters may include the front wheel single-wheel lateral stiffness, the rear wheel single-wheel lateral stiffness, the front overhang length, the rear overhang length, the longitudinal velocity, the vehicle mass, the moment of inertia, etc.

[0064] As a feasible implementation method, the parameter matrix required for constructing the vehicle lateral deviation state equation based on the front wheel steering angle includes: constructing a first parameter matrix based on the front wheel single-wheel lateral stiffness, rear wheel single-wheel lateral stiffness, front overhang length, rear overhang length, longitudinal velocity, vehicle mass, and moment of inertia; wherein the moment of inertia is the moment of inertia about the z-axis, and the z-axis is an axis perpendicular to the ground; and constructing a second parameter matrix based on the front wheel single-wheel lateral stiffness, the front overhang length, the vehicle mass, and the moment of inertia.

[0065] In practical implementation, the first parameter matrix Second parameter matrix Among them, C f For the front wheel single-wheel lateral stiffness, C r For the single-wheel lateral stiffness of the rear wheel, lf For the front overhang length, l r V is the rear overhang length. x Let m be the vehicle's longitudinal velocity, and I be the total vehicle mass. z Let be the moment of inertia of the vehicle about the z-axis, which is the axis perpendicular to the ground.

[0066] Next, the parameter matrix is ​​discretized to obtain a discrete parameter matrix. As a feasible implementation, the discretization of the parameter matrix includes: discretizing the first parameter matrix using the midpoint Euler method; and discretizing the second parameter matrix using the forward Euler method.

[0067] In practice, the midpoint Euler method is used to discretize the first parameter matrix A: The matrix B is discretized using the forward Euler method: B d =B*T.

[0068] S102: Based on the discrete parameter matrix, the change in front wheel angle, vehicle state variables, and the vehicle lateral deviation state equation of the front wheel angle, a vehicle lateral deviation state equation based on the change in front wheel angle is obtained; wherein, the vehicle state variables include lateral deviation, lateral deviation rate of change, heading angle deviation, heading angle rate of change, and the front wheel angle at the previous moment.

[0069] In this step, firstly, a pre-aiming control point is selected on the desired trajectory. The lateral deviation, heading angle deviation, and corresponding rate of change between the vehicle's trajectory and the target trajectory at the control point are calculated. Combined with the recorded front wheel steering angle from the previous step, the vehicle's current state variables can be obtained. e1 represents the lateral deviation between the vehicle and the target trajectory line. e2 represents the lateral deviation change, and e2 represents the heading angle deviation between the vehicle and the target trajectory line. This represents the change in heading angle deviation.

[0070] Secondly, the vehicle state variables are discretized to obtain a discrete state variable matrix X(k).

[0071] Then, the discrete state variable matrix is ​​adjusted based on the front wheel steering angle at the previous moment to obtain the adjusted state variable matrix X. inc (k), the adjusted state variable matrix

[0072] Finally, a vehicle lateral deviation state equation based on the front wheel angle change is constructed based on the discrete parameter matrix, the front wheel angle change, and the vehicle state variables. As a feasible implementation, the vehicle lateral deviation state equation based on the front wheel angle change is as follows: the vehicle state variable at time k+1 is the sum of the first product at time k and the second product at time k. The first product at time k is the product of the front wheel angle change at time k and the first parameter matrix. The second product at time k is the product of the front wheel angle change at time k and the second parameter matrix. The first parameter matrix is ​​a parameter matrix constructed based on the front wheel single-wheel lateral stiffness, rear wheel single-wheel lateral stiffness, front overhang length, rear overhang length, longitudinal velocity, vehicle mass, and moment of inertia. The second parameter matrix is ​​a parameter matrix constructed based on the front wheel single-wheel lateral stiffness, the front overhang length, the vehicle mass, and the moment of inertia. The moment of inertia is the moment of inertia about the z-axis, which is an axis perpendicular to the ground.

[0073] That is, the vehicle lateral deviation state equation based on the change in front wheel steering angle is:

[0074] X inc (k+1)=A inc_d X inc (k)+B inc_d U inc (k);

[0075] Among them, X inc (k) is the adjusted state variable matrix at time k, X inc (k+1) is the adjusted state variable matrix at time k+1, U inc (k) = ΔU(k), which is the change in the front wheel steering angle at time k. A d Let be the discrete first parameter matrix. B d It is a discrete second parameter matrix.

[0076] S103: Construct an objective function based on the weights corresponding to the front wheel angle change, the vehicle state variable, the front wheel angle change, and the vehicle state variable, and use the vehicle lateral deviation state equation based on the front wheel angle change to determine the target front wheel angle change when the objective function is minimized;

[0077] In this step, corresponding weights are assigned to the vehicle state variables and the changes in front wheel steering angle, thereby determining the first weight matrix Q. inc Second weight matrix R inc The first weight matrix Q inc The matrix constructed for the weights corresponding to the vehicle state variables, the second weight matrix R incThe weights corresponding to the changes in front wheel steering angle are used to construct an objective function. In one feasible implementation, the objective function is the sum of the objective sums at all times. The objective sum at time k is the sum of the third product and the fourth product at time k. The third product at time k is the product of the transpose of the vehicle state variables at time k, the first weight matrix, and the vehicle state variables at time k. The fourth product at time k is the product of the transpose of the changes in front wheel steering angle at time k, the second weight matrix, and the changes in front wheel steering angle at time k.

[0078] That is, the objective function is: X inc (k) represents the vehicle state variable at time k. For X inc The transpose of (k), U inc (k) = ΔU(k), which is the change in the front wheel steering angle at time k. For U inc The transpose of (k), Q inc Let R be the first weight matrix. inc This is the second weight matrix.

[0079] Q inc It is a 5×5 diagonal matrix representing the weights of each vehicle state variable:

[0080]

[0081] Where Q1, Q2, Q3, Q4, and Q5 are the weights corresponding to lateral deviation, lateral deviation change, heading angle deviation, heading angle deviation change, and the previously output wheel angle, respectively. Since the influence of the previously output wheel angle can be disregarded during vehicle lateral control, Q5 can be set to 0. R inc It is a 1×1 matrix, i.e., a constant, representing the weight corresponding to the change in the front wheel steering angle.

[0082] It's understandable that the required stability of the steering wheel varies at different vehicle speeds, and fine-tuning the control performance is necessary for corners with varying curvatures. Therefore, it's necessary to set Q parameters for different vehicle speeds and corners with different curvatures. inc and R inc .

[0083] As a feasible implementation method, the method further includes: determining the reference weights corresponding to the lateral deviation, the rate of change of the lateral deviation, the heading angle deviation, the rate of change of the heading angle deviation, and the change in the front wheel angle; determining the vehicle speed weight coefficients corresponding to the lateral deviation, the heading angle deviation, and the change in the front wheel angle based on the current vehicle speed; determining the radius of curvature weight coefficients corresponding to the lateral deviation, the heading angle deviation, and the change in the front wheel angle based on the current radius of curvature; using the reference weights corresponding to the rate of change of the lateral deviation and the rate of change of the heading angle deviation as the final weights corresponding to the rate of change of the lateral deviation and the rate of change of the heading angle deviation, respectively; and using the product of the reference weights, the vehicle speed weight, and the radius of curvature weights corresponding to the lateral deviation, the heading angle deviation, and the change in the front wheel angle, respectively, as the final weights corresponding to the lateral deviation, the heading angle deviation, and the change in the front wheel angle, respectively.

[0084] In practice, the weights corresponding to lateral deviation, heading angle deviation, and front wheel steering angle change are determined by the baseline weight, vehicle speed weight, and radius of curvature weight, respectively. The vehicle speed weight and radius of curvature weight are coefficients obtained by looking up from a pre-calibrated coefficient table based on different vehicle speeds. The weights corresponding to the lateral deviation change rate and heading angle deviation change rate are the baseline weights. The final Q... inc and R inc as follows:

[0085] Q i，i＝1，3 =Q_Base i，i＝1，3 *Q_Speedfactor i，i＝1，3 *Q_Radiusfactor i，i＝1，3 ;

[0086] Q i，i＝2，4 =Q_Base i，i＝2，4 ;

[0087] R inc =R_Base*R_Speedfacotor*R_Radiusfacotor.

[0088] Among them, Q_Base i，i＝1，3 Q_Speedfactor represents the baseline weight corresponding to the lateral deviation or heading angle deviation. i，i＝1，3 Q_Radiusfactor represents the vehicle speed weight corresponding to lateral deviation or heading angle deviation. i，i＝1，3 Q_Base represents the radius of curvature weight corresponding to lateral deviation or heading angle deviation. i，i＝2，4R_Base represents the baseline weight corresponding to the rate of change of lateral deviation or the rate of change of heading angle. R_Base represents the baseline weight corresponding to the change in front wheel steering angle. R_Speedfacotor represents the speed weight corresponding to the change in front wheel steering angle. R_Radiusfacotor represents the radius of curvature weight corresponding to the change in front wheel steering angle.

[0089] Furthermore, the target front wheel steering angle change at the minimum of the objective function is determined. As a feasible implementation, determining the target front wheel steering angle change at the minimum of the objective function using the vehicle lateral deviation state equation based on the front wheel steering angle change includes: constructing a Riccati equation based on the vehicle lateral deviation state equation based on the front wheel steering angle change and the objective function; determining the objective equation value when the Riccati equation converges; determining an intermediate matrix based on the objective equation value, the discrete parameter matrix, and the weights corresponding to the front wheel steering angle change; and determining the target front wheel steering angle change based on the intermediate matrix and the adjusted state variable matrix.

[0090] In practical implementation, the Riccati equation is constructed as follows:

[0091]

[0092] Let the initial value of matrix P be Q. inc Calculate P in multiple iterations next When P next When the difference between the current matrix P and the previous matrix P is small, convergence is considered achieved, and the iteration stops to obtain the current matrix P. next That is, the objective equation value.

[0093] Furthermore, the intermediate matrix is ​​obtained. The target front wheel steering angle change is determined based on the intermediate matrix and the adjusted state variable matrix, ΔU(k)=-K(k)X inc (k), where ΔU(k) ​​represents the change in the front wheel steering angle of the target.

[0094] S104: Confirm the target front wheel angle based on the target front wheel angle change and the current front wheel angle, determine the target steering wheel angle based on the target front wheel angle and steering ratio, and perform vehicle control based on the target steering wheel angle.

[0095] In this step, the target front wheel angle U(k) = ΔU(k) ​​+ U(k-1) + Feedforward(k) is determined based on the change in the target front wheel angle and the current front wheel angle, where U(k-1) is the current front wheel angle, which is also the front wheel angle at the previous moment, Feedforward(k) is the feedforward output, and U(k) is the target front wheel angle.

[0096] Furthermore, the product of the target front wheel angle and the steering speed ratio is the target steering wheel angle, which is output to the EPS actuator for vehicle lateral control.

[0097] The vehicle control method provided in this application constructs a vehicle lateral deviation state equation based on the change in front wheel angle. An objective function is constructed based on the weights corresponding to the change in front wheel angle, vehicle state variables, and the change in front wheel angle. The target change in front wheel angle is determined using the vehicle lateral deviation state equation based on the change in front wheel angle, and the objective function is minimized. Minimizing the objective function minimizes the three performance indicators: lateral deviation, heading angle deviation, and change in front wheel angle (i.e., steering wheel sway), thereby improving the vehicle's lateral control performance.

[0098] This embodiment describes the calibration method for the weights corresponding to each vehicle state variable and the change in front wheel steering angle. Specifically:

[0099] See Figure 4 A flowchart illustrating a method for calibrating the weights corresponding to each vehicle state variable and the change in front wheel steering angle, according to an exemplary embodiment, is shown below. Figure 4 As shown, it includes:

[0100] S201: Set all vehicle speed weights and all curvature radius weights to the baseline value;

[0101] The purpose of this embodiment is to calibrate the weights of each vehicle state variable and the change in front wheel steering angle under different vehicle speeds and radii of curvature. This includes the baseline weights corresponding to lateral deviation, the rate of change of lateral deviation, the heading angle deviation, the rate of change of heading angle deviation, and the change in front wheel steering angle, as well as the vehicle speed weights and radius of curvature weights corresponding to lateral deviation, heading angle deviation, and the change in front wheel steering angle, respectively. In this step, all vehicle speed weights and all radius of curvature weights are set to baseline values, such as 1.

[0102] S202: Calibrate on a straight road at a reference speed, set the reference weights corresponding to the lateral deviation, the rate of change of the lateral deviation, the heading angle deviation, and the change of the heading angle deviation as reference values, adjust the reference weights corresponding to the change of the front wheel angle until the steering wheel swing is within the desired index, and adjust the reference weights corresponding to the lateral deviation and the heading angle deviation until the lateral deviation and the heading angle deviation are within the desired index;

[0103] In this step, calibration is performed on a straight road using a reference vehicle speed, for example, 40 km / h. The reference weights for lateral deviation, lateral deviation rate of change, heading angle deviation, and heading angle deviation rate of change are set to reference values, such as 1. First, the reference weights corresponding to the change in front wheel steering angle, i.e., the R_Base coefficient, are adjusted until the steering wheel sway meets the requirements. Then, the reference weights corresponding to lateral deviation and heading angle deviation, i.e., the Base coefficients of Q1 and Q3, are adjusted until the lateral deviation and heading angle deviation stabilize within the desired range.

[0104] S203: Calibrate on a straight road at different vehicle speeds, adjust the vehicle speed weighting coefficient corresponding to the change in front wheel angle until the steering wheel swing is within the expected index, and adjust the vehicle speed weighting coefficients corresponding to the lateral deviation and the heading angle deviation until the lateral deviation and the heading angle deviation are within the expected index.

[0105] In this step, calibration is performed on a straight road at different vehicle speeds. First, the speed weight corresponding to the change in front wheel steering angle, i.e., R_Speedfactor, is adjusted until the steering wheel swing is stable. Then, the speed weights corresponding to lateral deviation and heading angle deviation, i.e., Speedfactor of Q1 and Q3, are adjusted until the lateral deviation and heading angle deviation are stable within the expected index.

[0106] S204: Calibrate on curves with different radii of curvature using the reference vehicle speed, adjust the curvature radius weighting coefficient corresponding to the change in front wheel angle until the steering wheel swing is within the expected index, and adjust the curvature radius weighting coefficients corresponding to the lateral deviation and the heading angle deviation until the lateral deviation and the heading angle deviation are within the expected index.

[0107] In this step, calibration is performed on curves with different radii of curvature at a reference vehicle speed. For example, calibration is performed on curves with different radii of curvature at a vehicle speed of 40 km / h. First, the curvature radius weight corresponding to the change in front wheel steering angle, i.e., R_Radiusfactor, is adjusted until the steering wheel swing is stable. Then, the curvature radius weights corresponding to the lateral deviation and heading angle deviation, i.e., the Radiusfactors of Q1 and Q3, are adjusted until the lateral deviation and heading angle deviation are stable within the expected range.

[0108] S205: Test the control effect on curves with different radii of curvature at different vehicle speeds. If the expected target is not met, adjust the corresponding curvature radius weight coefficient until the expected target is met.

[0109] In this step, the control effect on curves with different radii of curvature is tested at different vehicle speeds. If the expected target is not met, the corresponding curvature radius weight is finely adjusted until it meets the expected target.

[0110] The following describes a vehicle control device provided in an embodiment of this application. The vehicle control device described below and the vehicle control method described above can be referred to each other.

[0111] See Figure 5 A structural diagram of a vehicle control device is shown according to an exemplary embodiment, such as... Figure 5 As shown, it includes:

[0112] The construction module 100 is used to construct the parameter matrix required for the vehicle lateral deviation state equation based on the front wheel steering angle, and to discretize the parameter matrix.

[0113] The first determining module 200 is used to obtain a vehicle lateral deviation state equation based on the change in front wheel angle based on a discrete parameter matrix, the change in front wheel angle, vehicle state variables, and the vehicle lateral deviation state equation of the front wheel angle; wherein, the vehicle state variables include lateral deviation, lateral deviation rate of change, heading angle deviation, heading angle rate of change, and the front wheel angle at the previous moment.

[0114] The second determining module 300 is used to construct an objective function based on the weights corresponding to the front wheel angle change, the vehicle state variable, the front wheel angle change, and the vehicle state variable, and to determine the target front wheel angle change when the objective function is minimized using the vehicle lateral deviation state equation based on the front wheel angle change.

[0115] The control module 400 is used to confirm the target front wheel angle based on the target front wheel angle change and the current front wheel angle, determine the target steering wheel angle based on the target front wheel angle and the steering ratio, and perform vehicle control based on the target steering wheel angle.

[0116] The vehicle control device provided in this application constructs a vehicle lateral deviation state equation based on the change in front wheel angle. It constructs an objective function based on the weights corresponding to the change in front wheel angle, vehicle state variables, and the change in front wheel angle. It uses the vehicle lateral deviation state equation based on the change in front wheel angle to determine the target change in front wheel angle when the objective function is minimized. When the objective function is minimized, the three performance indicators of lateral deviation, heading angle deviation, and change in front wheel angle (i.e., steering wheel sway) can be minimized, thereby improving the vehicle lateral control effect.

[0117] Based on the above embodiments, as a preferred implementation, the vehicle lateral deviation state equation based on the change in front wheel steering angle is as follows: the vehicle state variable at time k+1 is the sum of the first product at time k and the second product at time k. The first product at time k is the product of the change in front wheel steering angle at time k and the first parameter matrix. The second product at time k is the product of the change in front wheel steering angle at time k and the second parameter matrix. The first parameter matrix is ​​a parameter matrix constructed based on the single-wheel lateral stiffness of the front wheel, the single-wheel lateral stiffness of the rear wheel, the front overhang length, the rear overhang length, the longitudinal speed, the vehicle mass, and the moment of inertia. The second parameter matrix is ​​a parameter matrix constructed based on the single-wheel lateral stiffness of the front wheel, the front overhang length, the vehicle mass, and the moment of inertia. The moment of inertia is the moment of inertia about the z-axis, which is an axis perpendicular to the ground.

[0118] Based on the above embodiments, as a preferred implementation, the vehicle lateral deviation state equation based on the change in front wheel steering angle is:

[0119] X inc (k+1)=A inc_d X inc (k)+B inc_d U inc (k);

[0120] Among them, X inc (k) represents the vehicle state variable at time k, X inc (k+1) represents the vehicle state variable at time k+1, U inc (k) = ΔU(k), which is the change in the front wheel steering angle at time k. A d Let be the discrete first parameter matrix. B d It is a discrete second parameter matrix.

[0121] Based on the above embodiments, as a preferred implementation, the objective function is the sum of the objective sums corresponding to all times. The objective sum at time k is the sum of the third product and the fourth product at time k. The third product at time k is the product of the transpose of the vehicle state variable at time k, the first weight matrix, and the vehicle state variable at time k. The fourth product at time k is the product of the transpose of the change in front wheel steering angle at time k, the second weight matrix, and the change in front wheel steering angle at time k. The first weight matrix is ​​a matrix constructed from the weights corresponding to the vehicle state variables, and the second weight matrix is ​​the weight corresponding to the change in front wheel steering angle.

[0122] Based on the above embodiments, as a preferred implementation, the objective function is: Xinc (k) represents the vehicle state variable at time k. For X inc The transpose of (k), U inc (k) = ΔU(k), which is the change in the front wheel steering angle at time k. For U inc The transpose of (k), Q inc Let R be the first weight matrix. inc This is the second weight matrix.

[0123] Based on the above embodiments, as a preferred implementation, the second determining module 300 is specifically used to: construct a Riccati equation according to the vehicle lateral deviation state equation based on the change in front wheel steering angle and the objective function, and determine the objective equation value when the Riccati equation converges; determine an intermediate matrix based on the objective equation value, the discrete parameter matrix, and the weights corresponding to the change in front wheel steering angle; and determine the target change in front wheel steering angle based on the intermediate matrix and the adjusted state variable matrix.

[0124] Based on the above embodiments, as a preferred embodiment, it further includes:

[0125] The weight determination module is used to determine the baseline weights corresponding to the lateral deviation, the rate of change of the lateral deviation, the heading angle deviation, the rate of change of the heading angle deviation, and the change in the front wheel angle, respectively; determine the vehicle speed weight coefficients corresponding to the lateral deviation, the heading angle deviation, and the change in the front wheel angle, respectively, based on the current vehicle speed; determine the radius of curvature weight coefficients corresponding to the lateral deviation, the heading angle deviation, and the change in the front wheel angle, respectively, based on the current radius of curvature; use the baseline weights corresponding to the rate of change of the lateral deviation and the rate of change of the heading angle deviation as the final weights corresponding to the rate of change of the lateral deviation and the rate of change of the heading angle deviation, respectively; and use the product of the baseline weights, vehicle speed weights, and radius of curvature weights corresponding to the lateral deviation, the heading angle deviation, and the change in the front wheel angle, respectively, as the final weights corresponding to the lateral deviation, the heading angle deviation, and the change in the front wheel angle, respectively.

[0126] Based on the above embodiments, as a preferred embodiment, it further includes:

[0127] The calibration module is used to set all vehicle speed weights and all curvature radius weights to baseline values; calibrate on a straight road at the baseline vehicle speed, setting the baseline weights corresponding to the lateral deviation, the rate of change of the lateral deviation, the heading angle deviation, and the change in heading angle deviation to baseline values; adjusting the baseline weights corresponding to the change in front wheel steering angle until the steering wheel sway is within the desired index; adjusting the baseline weights corresponding to the lateral deviation and the heading angle deviation until the lateral deviation and the heading angle deviation are within the desired index; calibrating on a straight road at different vehicle speeds, adjusting the vehicle speed weight coefficients corresponding to the change in front wheel steering angle until the steering wheel sway is within the desired index. Adjust the vehicle speed weighting coefficients corresponding to the lateral deviation and the heading angle deviation until the lateral deviation and the heading angle deviation are within the expected targets; calibrate on curves with different radii of curvature using the reference vehicle speed, adjust the radius of curvature weighting coefficient corresponding to the change in front wheel steering angle until the steering wheel sway is within the expected targets, and adjust the radius of curvature weighting coefficients corresponding to the lateral deviation and the heading angle deviation until the lateral deviation and the heading angle deviation are within the expected targets; test the control effect on curves with different radii of curvature using different vehicle speeds, and when the expected targets are not met, adjust the corresponding radius of curvature weighting coefficients until the corresponding expected targets are met.

[0128] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0129] Based on the hardware implementation of the above program modules, and in order to implement the method of the embodiments of this application, the embodiments of this application also provide an electronic device. Figure 6 This is a structural diagram of an electronic device according to an exemplary embodiment, such as... Figure 6 As shown, the electronic device includes:

[0130] Communication interface 1 enables information exchange with other devices, such as network devices;

[0131] Processor 2 is connected to communication interface 1 to enable information exchange with other devices and, when running a computer program, executes the vehicle control method provided by one or more of the above-mentioned technical solutions. The computer program is stored in memory 3.

[0132] Of course, in practical applications, the various components in an electronic device are coupled together through bus system 4. It can be understood that bus system 4 is used to achieve communication and connection between these components. In addition to the data bus, bus system 4 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 6 The general will label all buses as Bus System 4.

[0133] The memory 3 in this embodiment is used to store various types of data to support the operation of the electronic device. Examples of such data include any computer program used to operate on the electronic device.

[0134] It is understood that memory 3 can be volatile memory or non-volatile memory, or both. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), ferromagnetic random access memory (FRAM), flash memory, magnetic surface memory, optical disc, or compact disc read-only memory (CD-ROM); magnetic surface memory can be disk storage or magnetic tape storage. Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), SyncLink Dynamic Random Access Memory (SLDRAM), and Direct Rambus Random Access Memory (DRRAM).The memory 3 described in the embodiments of this application is intended to include, but is not limited to, these and any other suitable types of memory.

[0135] The methods disclosed in the embodiments of this application can be applied to processor 2, or implemented by processor 2. Processor 2 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in processor 2 or by instructions in the form of software. The processor 2 may be a general-purpose processor, DSP, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 2 can implement or execute the methods, steps and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the methods disclosed in the embodiments of this application can be directly manifested as being executed by a hardware decoding processor, or being executed by a combination of hardware and software modules in the decoding processor. The software modules may be located in a storage medium, which is located in memory 3. Processor 2 reads the program in memory 3 and completes the steps of the aforementioned method in combination with its hardware.

[0136] When processor 2 executes the program, it implements the corresponding processes in the various methods of the embodiments of this application. For the sake of brevity, these will not be described in detail here.

[0137] In an exemplary embodiment, this application also provides a storage medium, namely a computer storage medium, specifically a computer-readable storage medium, such as a memory 3 that stores a computer program, which can be executed by a processor 2 to complete the aforementioned method steps. The computer-readable storage medium can be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface memory, optical disc, CD-ROM, etc.

[0138] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0139] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause an electronic device (which may be a personal computer, server, network device, etc.) to execute all or part of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0140] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A vehicle control method, characterized in that, include: The parameter matrix required to construct the vehicle lateral deviation state equation based on the front wheel steering angle is discretized. Based on the discrete parameter matrix, the change in front wheel angle, and the vehicle state variables, the vehicle lateral deviation state equation based on the change in front wheel angle is obtained; wherein, the vehicle state variables include lateral deviation, lateral deviation rate of change, heading angle deviation, heading angle rate of change, and the front wheel angle at the previous moment. An objective function is constructed based on the weights corresponding to the front wheel angle change, the vehicle state variable, the front wheel angle change, and the vehicle state variable, respectively. The target front wheel angle change at the minimum value of the objective function is determined using the vehicle lateral deviation state equation based on the front wheel angle change. The target front wheel angle is determined based on the change in the target front wheel angle and the current front wheel angle. The target steering wheel angle is determined based on the target front wheel angle and the steering ratio. Vehicle control is then performed based on the target steering wheel angle.

2. The vehicle control method according to claim 1, characterized in that, The vehicle lateral deviation state equation based on the change in front wheel steering angle is as follows: the vehicle state variable at time k+1 is the sum of the first product at time k and the second product at time k. The first product at time k is the product of the change in front wheel steering angle at time k and the first parameter matrix. The second product at time k is the product of the change in front wheel steering angle at time k and the second parameter matrix. The first parameter matrix is ​​a parameter matrix constructed based on the single-wheel lateral stiffness of the front wheel, the single-wheel lateral stiffness of the rear wheel, the front overhang length, the rear overhang length, the longitudinal velocity, the vehicle mass, and the moment of inertia. The second parameter matrix is ​​a parameter matrix constructed based on the single-wheel lateral stiffness of the front wheel, the front overhang length, the vehicle mass, and the moment of inertia. The moment of inertia is the moment of inertia about the z-axis, which is an axis perpendicular to the ground.

3. The vehicle control method according to claim 2, characterized in that, The vehicle lateral deviation state equation based on the change in front wheel steering angle is: X inc (k+1)=A inc_d X inc (k)+B inc_d U inc (k); Among them, X inc (k) represents the vehicle state variable at time k, X inc (k+1) represents the vehicle state variable at time k+1, U inc (k) = ΔU(k), which is the change in the front wheel steering angle at time k. A d Let be the discrete first parameter matrix. B d It is a discrete second parameter matrix.

4. The vehicle control method according to claim 1, characterized in that, The objective function is the sum of the objective values ​​at all times. The objective value at time k is the sum of the third product and the fourth product at time k. The third product at time k is the product of the transpose of the vehicle state variable at time k, the first weight matrix, and the vehicle state variable at time k. The fourth product at time k is the product of the transpose of the change in front wheel steering angle at time k, the second weight matrix, and the change in front wheel steering angle at time k. The first weight matrix is ​​a matrix constructed from the weights corresponding to the vehicle state variables, and the second weight matrix is ​​the weight corresponding to the change in front wheel steering angle.

5. The vehicle control method according to claim 4, characterized in that, The objective function is: X inc (k) represents the vehicle state variable at time k. For X inc The transpose of (k), U inc (k) = ΔU(k), which is the change in the front wheel steering angle at time k. For U inc The transpose of (k), Q inc Let R be the first weight matrix. inc This is the second weight matrix.

6. The vehicle control method according to claim 1, characterized in that, The step of determining the target front wheel angle change when the objective function is minimized using the vehicle lateral deviation state equation based on the front wheel angle change includes: Based on the vehicle lateral deviation state equation based on the change in front wheel steering angle and the objective function, construct the Riccati equation and determine the objective equation value when the Riccati equation converges. The intermediate matrix is ​​determined based on the objective equation value, the discrete parameter matrix, and the weights corresponding to the change in front wheel steering angle. The target front wheel steering angle change is determined based on the intermediate matrix and the adjusted state variable matrix.

7. The vehicle control method according to claim 1, characterized in that, Also includes: Determine the reference weights corresponding to the lateral deviation, the rate of change of the lateral deviation, the heading angle deviation, the rate of change of the heading angle deviation, and the change in the front wheel steering angle, respectively; Determine the vehicle speed weighting coefficients corresponding to the lateral deviation, the heading angle deviation, and the change in front wheel steering angle based on the current vehicle speed; Determine the radius of curvature weighting coefficients corresponding to the lateral deviation, the heading angle deviation, and the change in front wheel steering angle based on the current radius of curvature. The baseline weights corresponding to the lateral deviation rate of change and the heading angle deviation rate of change are respectively used as the final weights corresponding to the lateral deviation rate of change and the heading angle deviation rate of change; The product of the baseline weight, vehicle speed weight, and radius of curvature weight corresponding to the lateral deviation, the heading angle deviation, and the change in front wheel steering angle, respectively, is used as the final weight corresponding to the lateral deviation, the heading angle deviation, and the change in front wheel steering angle, respectively.

8. The vehicle control method according to claim 7, characterized in that, Before determining the reference weights corresponding to the lateral deviation, the amount of change in lateral deviation, the heading angle deviation, the rate of change of heading angle deviation, and the rate of change of front wheel steering angle, the method further includes: Set all vehicle speed weights and all curvature radius weights to baseline values; The vehicle is calibrated on a straight road at a reference speed. The reference weights corresponding to the lateral deviation, the rate of change of the lateral deviation, the heading angle deviation, and the change of the heading angle deviation are set as reference values. The reference weights corresponding to the change of the front wheel angle are adjusted until the steering wheel swing is within the expected index. The reference weights corresponding to the lateral deviation and the heading angle deviation are adjusted until the lateral deviation and the heading angle deviation are within the expected index. Calibrate on a straight road at different vehicle speeds, adjust the vehicle speed weighting coefficient corresponding to the change in front wheel angle until the steering wheel swing is within the expected index, and adjust the vehicle speed weighting coefficients corresponding to the lateral deviation and the heading angle deviation until the lateral deviation and the heading angle deviation are within the expected index; The vehicle is calibrated on curves with different radii of curvature using the reference speed. The curvature radius weighting coefficient corresponding to the change in front wheel angle is adjusted until the steering wheel swing is within the expected index. The curvature radius weighting coefficients corresponding to the lateral deviation and the heading angle deviation are adjusted until the lateral deviation and the heading angle deviation are within the expected index. The control effect on curves with different radii of curvature was tested at different vehicle speeds. When the expected target was not met, the corresponding curvature radius weight coefficient was adjusted until the expected target was met.

9. A vehicle control device, characterized in that, include: A construction module is used to construct the parameter matrix required for the vehicle lateral deviation state equation based on the front wheel steering angle, and to discretize the parameter matrix. The first determining module is used to obtain a vehicle lateral deviation state equation based on the change in front wheel angle based on a discrete parameter matrix, the change in front wheel angle, vehicle state variables, and the vehicle lateral deviation state equation of the front wheel angle; wherein, the vehicle state variables include lateral deviation, lateral deviation rate of change, heading angle deviation, heading angle deviation rate of change, and the front wheel angle at the previous moment. The second determining module is used to construct an objective function based on the weights corresponding to the front wheel angle change, the vehicle state variable, the front wheel angle change, and the vehicle state variable, and to determine the target front wheel angle change when the objective function is minimized using the vehicle lateral deviation state equation based on the front wheel angle change. The control module is used to confirm the target front wheel angle based on the change in the target front wheel angle and the current front wheel angle, determine the target steering wheel angle based on the target front wheel angle and the steering ratio, and perform vehicle control based on the target steering wheel angle.

10. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor for executing the computer program to implement the steps of the vehicle control method as described in any one of claims 1 to 8.

11. 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 steps of the vehicle control method as described in any one of claims 1 to 8.

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