Vehicle, control method and control device therefor

Abstract

The application discloses a vehicle and a control method and a control device thereof, and the method comprises the following steps: constructing a state space equation of a vehicle model and a state space equation of a rear wheel steering model according to parameters of the vehicle; determining a rear wheel steering error equation of the vehicle based on the state space equation of the vehicle model and the state space equation of the rear wheel steering model; determining a closed-loop feedback compensation amount according to the rear wheel steering error equation, and determining a feedforward compensation amount according to the rear wheel steering error equation and a control emphasis; determining a target rear wheel steering angle according to the closed-loop feedback compensation amount and the feedforward compensation amount; and controlling the vehicle based on the target rear wheel steering angle. The control method can accurately determine the angle of the rear wheel steering angle, and improves the controllability and stability of the vehicle.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicles, in particular to a control method of a vehicle, a control device of a vehicle and a vehicle. BACKGROUND

[0002] The active rear wheel steering technology, as a chassis control system for improving the handling and stability of vehicles, has a very broad development prospect in the future. When the vehicle is driving at low speed, the active rear wheel steering technology can make the vehicle more flexible in handling, which is very helpful when driving in the city, parking or avoiding obstacles. When the vehicle is driving at high speed, the active rear wheel steering technology can improve the understeering ability of the vehicle and make the vehicle more stable and safe. In addition, the active rear wheel steering technology can also be combined with active safety control, automatic driving and other technologies to improve the driving experience and safety.

[0003] In the related art, the yaw rate is taken as the target, and the target value output of the rear wheel steering angle is realized by using PID (Proportional Integral Derivative) control according to the error between the target yaw rate and the actual yaw rate, and the control scheme is simple. However, this scheme is limited by the algorithm, and when the error between the target yaw rate and the actual yaw rate is large, the target rear wheel steering angle may suddenly change, which is not conducive to the rear wheel actuator. At the same time, this scheme cannot comprehensively consider the changes of other vehicle characteristic signals such as the center of mass side slip angle or lateral acceleration during real vehicle calibration, which may cause other problems. SUMMARY

[0004] The present application aims to at least solve one of the technical problems in the related art. To this end, the first object of the present application is to provide a control method of a vehicle, which constructs a state space equation of a vehicle model and a state space equation of a rear wheel steering model according to parameters of the vehicle, determines a rear wheel steering error equation of the vehicle based on the state space equation of the vehicle model and the state space equation of the rear wheel steering model, determines a closed-loop feedback compensation amount according to the rear wheel steering error equation, determines a feedforward compensation amount according to the rear wheel steering error equation and a control emphasis, determines a target rear wheel steering angle according to the closed-loop feedback compensation amount and the feedforward compensation amount, and controls the vehicle based on the target rear wheel steering angle, so as to accurately determine the angle of the rear wheel steering angle and improve the handling and stability of the vehicle.

[0005] The second object of the present application is to provide a control device of a vehicle.

[0006] The third object of the present application is to provide a vehicle.

[0007] To achieve the above object, the embodiment of the first aspect of the present application provides a control method of a vehicle, which comprises: constructing a state space equation of a vehicle model and a state space equation of a rear wheel steering model according to parameters of the vehicle; determining a rear wheel steering error equation of the vehicle based on the state space equation of the vehicle model and the state space equation of the rear wheel steering model; determining a closed-loop feedback compensation amount according to the rear wheel steering error equation, and determining a feedforward compensation amount according to the rear wheel steering error equation and a control emphasis; determining a target rear wheel steering angle according to the closed-loop feedback compensation amount and the feedforward compensation amount; and controlling the vehicle based on the target rear wheel steering angle.

[0008] According to the control method of the vehicle, the state space equation of the vehicle model and the state space equation of the rear wheel steering model are constructed according to the parameters of the vehicle, the rear wheel steering error equation of the vehicle is determined based on the state space equation of the vehicle model and the state space equation of the rear wheel steering model, the closed-loop feedback compensation amount is determined according to the rear wheel steering error equation, the feedforward compensation amount is determined according to the rear wheel steering error equation and the control emphasis, the target rear wheel steering angle is determined according to the closed-loop feedback compensation amount and the feedforward compensation amount, and the vehicle is controlled based on the target rear wheel steering angle. Thus, the method can accurately determine the angle of the rear wheel steering angle, and improve the controllability and stability of the vehicle.

[0009] In addition, the control method of the vehicle according to the above embodiment of the present application can have the following additional technical features:

[0010] According to one embodiment of the present application, the rear wheel steering error equation is:

[0011]

[0012] wherein, u = δ r err = x - x d is an error state vector, Δ1 is a first error, and Δ2 is a second error, wherein, wherein, is a front wheel cornering stiffness, is a rear wheel cornering stiffness, m is a vehicle mass, I z is a moment of inertia of the vehicle around a Z axis of a vehicle body coordinate system, l f is a distance from a mass center to a front axle, l r is a distance from the mass center to a rear axle, v x is a longitudinal vehicle speed, δ r is a rear wheel steering angle, β is an actual mass center cornering angle, is an actual vehicle yaw rate, β d is an ideal mass center cornering angle, is an ideal yaw rate, the first error is w*(C-Cd ), the second error is x d *(A-A d ), w = δ f , δ f is a front wheel steering angle, τ β is a mass center side slip angle low-pass filter time constant, is a yaw rate low-pass filter time constant, is a target mass center side slip angle gain, is a target yaw rate gain.

[0013] According to one embodiment of the present application, the determining a closed-loop feedback compensation quantity according to the rear wheel steering error equation comprises: performing linear quadratic programming solution based on a linear part of the rear wheel steering error equation to determine a closed-loop feedback gain; and determining the closed-loop feedback compensation quantity according to the closed-loop feedback gain and an error state vector.

[0014] According to one embodiment of the present application, the closed-loop feedback gain is:

[0015] K FB = (R + B T P k+1 B) -1 B T P k+1 A

[0016] wherein K FB is a feedback gain, R is a control penalty parameter, P k+1 is a Riccati equation iterative solution matrix, wherein, is a front wheel side slip stiffness, is a rear wheel side slip stiffness, m is a vehicle mass, I z is a vehicle moment of inertia about a body coordinate system Z axis, l f is a mass center to front axle distance, l r is a mass center to rear axle distance, v x is a longitudinal vehicle speed.

[0017] According to one embodiment of the present application, the determining the closed-loop feedback compensation quantity according to the closed-loop feedback gain and the error state vector comprises: taking an opposite number of a product of the feedback gain and the error state vector as the closed-loop feedback compensation quantity.

[0018] According to one embodiment of the present application, the determining a feedforward compensation quantity according to the rear wheel steering error equation and a control emphasis comprises: performing emphasis solution on the rear wheel steering error equation to respectively obtain a yaw rate emphasized feedforward compensation quantity and a mass center side slip angle emphasized feedforward compensation quantity.

[0019] According to one embodiment of the present application, the feedforward compensation amount focused on yaw rate is determined by the following equation:

[0020]

[0021] wherein, is the feedforward compensation amount focused on yaw rate, K FB represents the closed loop feedback gain, is the front wheel cornering stiffness, is the rear wheel cornering stiffness, m is the vehicle mass, I z is the vehicle moment of inertia about the Z axis of the vehicle body coordinate system, l f is the distance from the center of mass to the front axle, l r is the distance from the center of mass to the rear axle, v x is the longitudinal vehicle speed, Δ1 is a first error, Δ2 is a second error, the first error is w*(C-C d ), and the second error is w = δ f , δ f is the front wheel steering angle, τ β is the center of mass cornering angle low pass filter time constant, is the yaw rate low pass filter time constant, is a target center of mass cornering angle gain, is a target yaw rate gain.

[0022] According to one embodiment of the present application, the feedforward compensation amount focused on center of mass cornering angle is determined by the following equation:

[0023]

[0024] wherein, u FFβ is the feedforward compensation amount focused on center of mass cornering angle, K FB is the closed loop feedback gain, is the rear wheel cornering stiffness, is the front wheel cornering stiffness, m is the vehicle mass, I z is the vehicle moment of inertia about the Z axis of the vehicle body coordinate system, l f is the distance from the center of mass to the front axle, l r is the distance from the center of mass to the rear axle, v x is the longitudinal vehicle speed, Δ1 is a first error, Δ2 is a second error, the first error is w*(C-C d ), and the second error is xd (A-A d ), w = δ f , δ f is a front wheel steering angle, τ β is a mass side slip angle low-pass filter time constant, is a yaw rate low-pass filter time constant, is a target mass side slip angle gain, is a target yaw rate gain.

[0025] According to one embodiment of the present application, the determining the target rear wheel steering angle according to the closed-loop feedback compensation and the feedforward compensation comprises: determining the target rear wheel steering angle according to a sum of the closed-loop feedback compensation and the feedforward compensation.

[0026] According to one embodiment of the present application, the state space equation of the vehicle model is:

[0027]

[0028] wherein, β d is the ideal mass side slip angle, is the ideal yaw rate;

[0029] The state space equation of the rear wheel steering model is:

[0030]

[0031] wherein, β is the actual mass side slip angle, is the actual vehicle yaw rate.

[0032] According to one embodiment of the present application, the method further comprises: filtering the ideal mass side slip angle and the ideal yaw rate based on filter parameters.

[0033] To achieve the above object, the second embodiment of the present application proposes a control device of a vehicle, which comprises: a construction module, configured to construct a state space equation of a vehicle model and a state space equation of a rear wheel steering model according to parameters of the vehicle; a first determination module, configured to determine a rear wheel steering error equation of the vehicle based on the state space equation of the vehicle model and the state space equation of the rear wheel steering model; a second determination module, configured to determine a closed-loop feedback compensation according to the rear wheel steering error equation, and determine a feedforward compensation according to the rear wheel steering error equation and a control emphasis; a third determination module, configured to determine a target rear wheel steering angle according to the closed-loop feedback compensation and the feedforward compensation; and a control module, configured to control the vehicle based on the target rear wheel steering angle.

[0034] According to the control device of the vehicle of the embodiment of the present application, the constructing module is configured to construct a state space equation of a vehicle model and a state space equation of a rear wheel steering model according to parameters of the vehicle, the first determining module is configured to determine a rear wheel steering error equation of the vehicle based on the state space equation of the vehicle model and the state space equation of the rear wheel steering model, the second determining module is configured to determine a closed-loop feedback compensation amount according to the rear wheel steering error equation and a feedforward compensation amount according to the rear wheel steering error equation and a control emphasis, the third determining module is configured to determine a target rear wheel steering angle according to the closed-loop feedback compensation amount and the feedforward compensation amount, and the control module is configured to control the vehicle based on the target rear wheel steering angle. Thus, the device can accurately determine the angle of the rear wheel steering angle, and improve the controllability and stability of the vehicle.

[0035] To achieve the above object, the third aspect of the embodiment of the present application provides a vehicle, comprising a memory, a processor and a program stored in the memory and executable on the processor, wherein when the processor executes the program, the vehicle control method is realized.

[0036] According to the vehicle of the embodiment of the present application, by executing the vehicle control method, the angle of the rear wheel steering angle can be accurately determined, and the controllability and stability of the vehicle are improved.

[0037] Additional aspects and advantages of the present application will be made apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0038] Figure 1 Flow chart of the vehicle control method according to the embodiment of the present application;

[0039] Figure 2 Flow chart of the vehicle control method according to one specific example of the present application;

[0040] Figure 3 Block schematic diagram of the vehicle control device according to the embodiment of the present application;

[0041] Figure 4 Block schematic diagram of the vehicle according to the embodiment of the present application. DETAILED DESCRIPTION

[0042] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the drawings, wherein the same or similar notations represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below are exemplary and are intended to explain the present application, and cannot be understood as limiting the present application.

[0043] A control method of a vehicle, a control device of a vehicle, and a vehicle according to embodiments of the present application are described below with reference to the accompanying drawings.

[0044] Figure 1 A flowchart of a control method of a vehicle according to an embodiment of the present application.

[0045] As shown in Figure 1 the control method of the vehicle according to the embodiment of the present application can include the following steps:

[0046] S1, constructing a state space equation of a vehicle model and a state space equation of a rear wheel steering model according to parameters of the vehicle.

[0047] S2, determining a rear wheel steering error equation of the vehicle based on the state space equation of the vehicle model and the state space equation of the rear wheel steering model.

[0048] S3, determining a closed-loop feedback compensation amount according to the rear wheel steering error equation, and determining a feedforward compensation amount according to the rear wheel steering error equation and a control emphasis.

[0049] S4, determining a target rear wheel steering angle according to the closed-loop feedback compensation amount and the feedforward compensation amount.

[0050] S5, controlling the vehicle based on the target rear wheel steering angle.

[0051] Specifically, when constructing the state space equation of the vehicle model and the state space equation of the rear wheel steering model, the equations can be constructed according to parameters of the vehicle. That is, the equations can be constructed based on a two-degree-of-freedom model (lateral motion and yaw motion) and rear wheel steering control, for example, the parameters of the vehicle can include a vehicle mass, a moment of inertia of the vehicle around a vertical axis, a wheelbase of the vehicle, a front wheel cornering stiffness, a rear wheel cornering stiffness, a distance from a mass center to a front axle, a distance from the mass center to a rear axle, a longitudinal vehicle speed, etc. When determining the state space equation of the vehicle model, a state variable can be defined as a mass center cornering angle and a yaw angular velocity, and an input variable can be defined as a front wheel steering angle, that is, the front wheel steering angle can be determined according to a current steering angle of a steering wheel, so that the state space equation of the vehicle can be determined according to a vehicle dynamics equation, and converted into a standard state space form. Similarly, when determining the state space equation of the rear wheel steering model, a rear wheel steering angle can be added as an input variable, and the state space equation of the vehicle can be determined according to the vehicle dynamics equation, and converted into the standard state space form.

[0052] After the state space equation of the vehicle model and the state space equation of the rear wheel steering model are determined, the rear wheel steering error equation of the vehicle can be determined according to the state space equation of the vehicle model and the state space equation of the rear wheel steering model, that is, the rear wheel steering error equation of the vehicle is used to describe the difference between the actual rear wheel steering angle and the target rear wheel steering angle. By determining the rear wheel steering error equation, a physical model can be obtained for solving the optimal closed-loop feedback compensation and the feedforward compensation. Thus, after the rear wheel steering error equation is determined, the closed-loop feedback compensation can be determined according to the rear wheel steering error equation, that is, the closed-loop feedback control can be used to compensate for the error, so as to ensure that the actual response of the rear wheel steering of the vehicle is consistent with the target response. The error between the actual output and the target output can be measured, and the control input can be dynamically adjusted to minimize the error and make the error approach zero. And the feedforward compensation can be determined according to the rear wheel steering error equation and the control emphasis. For example, the control emphasis can be selected according to whether the center of mass side slip angle or the yaw rate is emphasized. The control emphasis with the center of mass side slip angle means that the error between the measured center of mass side slip angle of the actual vehicle and the target center of mass side slip angle is zero. The control emphasis with the yaw rate means that the error between the measured yaw rate of the actual vehicle and the target yaw rate is zero.

[0053] After the closed-loop feedback compensation and the feedforward compensation are determined, the target rear wheel steering angle can be determined according to the closed-loop feedback compensation and the feedforward compensation. For example, the target rear wheel steering angle can be determined through a predetermined corresponding relationship. For example, the relationship between the closed-loop feedback compensation, the feedforward compensation and the target rear wheel steering angle is predetermined. After the closed-loop feedback compensation and the feedforward compensation are determined, the corresponding relationship can be directly called to obtain the target rear wheel steering angle. That is, by combining the feedforward control and the feedback control, a more optimal control effect can be achieved, so that the rear wheel steering system of the vehicle can stably and accurately track the target trajectory under various conditions.

[0054] After the target rear wheel steering angle is obtained, the vehicle can be controlled according to the target rear wheel steering angle. For example, the actual rear wheel steering angle can be adjusted according to the target rear wheel steering angle. For example, the actual steering of the rear wheel can be realized through an electric servo motor or a hydraulic servo system. That is, by accurately controlling the rear wheel steering angle, the side slip of the vehicle during high-speed driving can be effectively reduced, the stability of the vehicle can be improved, the steering flexibility of the vehicle during low-speed driving can be improved, the vehicle can be more easily controlled in a narrow space, the turning radius of the vehicle can be reduced, the turning efficiency can be improved, and the control performance of the vehicle can be enhanced. Thus, the angle of the rear wheel steering angle can be accurately determined, and the controllability and stability of the vehicle can be improved.

[0055] According to an embodiment of the present application, the rear wheel steering error equation is:

[0056]

[0057] wherein, wherein, u = δ r , err = x - x d is an error state vector, Δ1 is a first error, and Δ2 is a second error, wherein, wherein, is a front wheel cornering stiffness, is a rear wheel cornering stiffness, m is a vehicle mass, I z is a moment of inertia of the vehicle about the Z axis of the vehicle body coordinate system, l f is a distance from the mass center to the front axle, l r is a distance from the mass center to the rear axle, v x is a longitudinal vehicle speed, δ r is a rear wheel steering angle, and β is an actual mass center cornering angle, is an actual vehicle yaw rate, β d is an ideal mass center cornering angle, is an ideal yaw rate, the first error is w*(C-C d ), and the second error is x d *(A-A d ), w = δ f , δ f is a front wheel steering angle, τ β is a mass center cornering angle low-pass filter time constant, is a yaw rate low-pass filter time constant, is a target mass center cornering angle gain, is a target yaw rate gain.

[0058] Further, according to an embodiment of the present application, a state space equation of a vehicle model is:

[0059]

[0060] wherein, β d is the ideal mass center cornering angle, is the ideal yaw rate;

[0061] A state space equation of a rear wheel steering model is:

[0062]

[0063] wherein, β is an actual mass center cornering angle, is an actual vehicle yaw rate.

[0064] Further, according to an embodiment of the present application, the control method of the vehicle further includes filtering the ideal mass center cornering angle and the ideal yaw rate based on a filter parameter.

[0065] Specifically, the rear wheel steering error equation of the vehicle is determined based on the state space equation of the vehicle model and the state space equation of the rear wheel steering model, as shown in the above formula (1). Specifically, the state space equation of the vehicle model, i.e., the above formula (2), is first determined, and the input quantity w is the front wheel steering angle, and the state quantity x is the ideal center side slip angle β d , and the ideal vehicle yaw rate And in order to avoid the harm to the rear wheel steering controller caused by the jump or step of the target rear wheel steering angle, the ideal target signal can be filtered to realize the smooth transition of the target value. The filtering parameters of the ideal center side slip angle and the ideal yaw rate can be adjusted according to actual needs. For example, the yaw rate and the center side slip angle target state space equation can be constructed based on the filtering parameters:

[0066]

[0067] Wherein,

[0068] Wherein, τ β is the center side slip angle low-pass filter time constant; is the yaw rate low-pass filter time constant; is the ideal center side slip angle gain; is the ideal yaw rate gain; β d is the ideal center side slip angle; is the ideal yaw rate.

[0069] Therefore, the rear wheel steering error equation (1) can be determined according to the state space equation (3) of the rear wheel steering model and the filtered state space equation (4) of the vehicle model, that is, and are subtracted to obtain which can be transformed into Let x-x d = err, and after simplification, we can get Wherein, err is the error state vector, that is, the difference between the measured x (actual actual center side slip angle and actual vehicle yaw rate) and the ideal center side slip angle and the ideal yaw rate is simulated and calculated by the state space equation (3) of the rear wheel steering model.

[0070] According to one embodiment of the present application, the closed-loop feedback compensation quantity is determined according to the rear wheel steering error equation, which comprises: performing linear quadratic programming based on the linear part of the rear wheel steering error equation to determine the closed-loop feedback gain; and determining the closed-loop feedback compensation quantity according to the closed-loop feedback gain and the error state vector.

[0071] Specifically, when determining the closed-loop feedback compensation amount according to the rear wheel steering error equation, the linear quadratic programming can be solved according to the linear part of the rear wheel steering error equation to determine the closed-loop feedback gain. That is, when determining the closed-loop feedback gain, the uncontrollable error caused by the front wheel steering is not considered, the linear quadratic programming (LQR) is solved according to the linear part of the rear wheel steering error equation, and the actual adjustment control amount constraint condition R and the state constraint condition Q can be used to meet the real vehicle calibration effect. After the closed-loop feedback gain is determined, the closed-loop feedback compensation amount can be determined according to the closed-loop feedback gain and the error state vector. That is, the error state vector contains the deviation information between the current system state and the expected state, that is, the deviation between the actual vehicle center side slip angle and the ideal vehicle center side slip angle, and the deviation between the actual vehicle yaw rate and the ideal vehicle yaw rate. The closed-loop feedback gain can optimally respond to the error state, reduce the deviation and improve the control accuracy. Therefore, the closed-loop feedback compensation amount can be determined through the preset corresponding relationship, for example, the relationship between the closed-loop feedback gain, the error state vector and the closed-loop feedback compensation amount is determined in advance. After the closed-loop feedback gain and the error state vector are determined, the corresponding relationship is directly called to obtain the closed-loop feedback compensation amount.

[0072] Further, according to an embodiment of the present application, the closed-loop feedback gain is:

[0073] K FB =(R+B T P k+1 B) -1 B T P k+1 A(5)

[0074] wherein K FB is the feedback gain, R is the control penalty parameter, P k+1 is the Riccati equation iterative solution matrix, wherein, is the front wheel cornering stiffness, is the rear wheel cornering stiffness, m is the vehicle mass, I z is the vehicle moment of inertia around the Z axis of the vehicle body coordinate system, l f is the distance from the center of mass to the front axle, l r is the distance from the center of mass to the rear axle, v x is the longitudinal vehicle speed.

[0075] Specifically, when the linear quadratic programming is solved according to the linear part of the rear wheel steering error equation to determine the closed-loop feedback gain, the closed-loop feedback gain can be determined by the above formula (5), that is, according to the vehicle parameters such as the front wheel cornering stiffness rear wheel cornering stiffness vehicle mass m, vehicle moment of inertia I zthe distance from the center of mass to the front axle l f the distance from the center of mass to the rear axle l r the longitudinal vehicle speed v x the control penalty parameter R and the Riccati equation iterative solution matrix P k+1 are determined together. And the maximum step of the Riccati equation iterative solution matrix P k+1 , that is, the size of the update amount at each iteration, and the maximum error of the Riccati equation iterative solution matrix P k+1 , that is, the condition for stopping iteration, that is, when the difference between the current solution and the last solution is less than this maximum error, stop iteration, to improve the efficiency and accuracy of the calculation.

[0076] According to one embodiment of the present application, the closed-loop feedback compensation quantity is determined according to the closed-loop feedback gain and the error state vector, which includes: taking the opposite number of the product of the feedback gain and the error state vector as the closed-loop feedback compensation quantity.

[0077] Specifically, when determining the closed-loop feedback compensation quantity according to the closed-loop feedback gain and the error state vector, the opposite number of the product of the feedback gain and the error state vector can be taken as the closed-loop feedback compensation quantity, for example, the closed-loop feedback gain is K FB , and the error state vector is err, then the closed-loop feedback compensation quantity u FB can be determined as -K FB *err.

[0078] According to one embodiment of the present application, the feedforward compensation quantity is determined according to the rear wheel steering error equation and the control emphasis, which includes: solving the rear wheel steering error equation with emphasis to obtain the feedforward compensation quantity with yaw rate emphasis and the feedforward compensation quantity with center of mass side slip angle emphasis, respectively.

[0079] Further, according to one embodiment of the present application, the feedforward compensation quantity with yaw rate emphasis is determined by the following formula:

[0080]

[0081] wherein, is the feedforward compensation quantity with yaw rate emphasis, K FB represents the closed-loop feedback gain, is the front wheel cornering stiffness, is the rear wheel cornering stiffness, m is the vehicle mass, I z is the moment of inertia of the vehicle around the Z axis of the vehicle body coordinate system, l f is the distance from the center of mass to the front axle l r is the distance from the center of mass to the rear axle l xfor longitudinal vehicle speed, Δ1 is a first error, Δ2 is a second error, the first error is w*(C-C d ), and the second error is x d *(A-A d ), w=δ f , δ f is a front wheel steering angle, τ β is a center of mass side slip angle low-pass filter time constant, is a yaw rate low-pass filter time constant, is a target center of mass side slip angle gain, is a target yaw rate gain.

[0082] Further, according to one embodiment of the present application, a front feed compensation amount focused on a center of mass side slip angle is determined by the following equation:

[0083]

[0084] where u FFβ is the front feed compensation amount focused on the center of mass side slip angle, K FB is a closed loop feedback gain, is a rear wheel cornering stiffness, is a front wheel cornering stiffness, m is a total vehicle mass, I z is a total vehicle moment of inertia about the vehicle body coordinate system Z axis, l f is a center of mass to front axle distance, l r is a center of mass to rear axle distance, v x is a longitudinal vehicle speed, Δ1 is a first error, Δ2 is a second error, the first error is w*(C-C d ), and the second error is x d *(A-A d ), w=δ f , δ f is a front wheel steering angle, τ β is a center of mass side slip angle low-pass filter time constant, is a yaw rate low-pass filter time constant, is a target center of mass side slip angle gain, is a target yaw rate gain.

[0085] Specifically, when determining the front feed compensation amount according to the rear wheel steering error equation and the control focus, the rear wheel steering error equation can be solved with emphasis, and a front feed compensation amount focused on a yaw rate and a front feed compensation amount focused on a center of mass side slip angle are obtained respectively. For example, when determining the closed loop feedback compensation amount u FBThen, the closed-loop feedback compensation amount u can be... FB Substituting this into the rear wheel steering error equation (1) and simplifying it, we can obtain the following: For ease of calculation, let Therefore, when the yaw rate is the focus, the feedforward compensation amount can be determined by the above formula (6), and when the centroid side slip angle is the focus, the feedforward compensation amount can be determined by the above formula (7).

[0086] According to one embodiment of the present invention, determining the target rear wheel steering angle based on the closed-loop feedback compensation amount and the feedforward compensation amount includes: determining the target rear wheel steering angle based on the sum of the closed-loop feedback compensation amount and the feedforward compensation amount.

[0087] Specifically, when determining the target rear wheel steering angle based on the closed-loop feedback compensation and feedforward compensation, the target rear wheel steering angle can be determined based on the sum of the closed-loop feedback compensation and feedforward compensation. In other words, to obtain the target rear wheel steering angle more accurately, compensation can be made using feedforward compensation; that is, the target rear wheel steering angle is obtained by adding the closed-loop feedback compensation and the feedforward compensation. By combining feedforward and feedback compensation, various complex driving conditions can be better handled, improving vehicle handling stability and safety, and enhancing ride comfort.

[0088] Furthermore, in embodiments of the present invention, the rear-wheel closed-loop algorithm can be set to a specific speed to close the vehicle speed, which must not be lower than 0. This means that when the vehicle speed is lower than the closing speed, the rear-wheel steering closed-loop control is disabled to avoid division by zero and other potential control problems. A steering dead zone can be provided through the steering wheel angle determination function unit, enabling the rear-wheel steering to close with the front wheel angle. Specifically, changes in steering wheel angle within a certain range will not trigger rear-wheel steering control. For example, the steering dead zone refers to a range within which changes in steering wheel angle will not cause a response from the rear-wheel steering system. For instance, if a ±5-degree steering dead zone is set, the rear-wheel steering system will not respond when the steering wheel angle changes within ±5 degrees. The rear-wheel steering system will only activate when the steering wheel angle exceeds this range, improving vehicle stability and control predictability, especially avoiding unnecessary rear-wheel steering response during small angle adjustments.

[0089] The following is combined with Figure 2 The control method of the present invention will be described below.

[0090] As a specific example, the vehicle control method of the present invention may include the following steps:

[0091] S101, construct the state-space equations of the vehicle model and the rear-wheel steering model based on the vehicle parameters.

[0092] S102, the rear wheel steering error equation of the vehicle is determined based on the state-space equation of the vehicle model and the state-space equation of the rear wheel steering model.

[0093] S103, based on the linear part of the rear wheel steering error equation, performs linear quadratic programming to solve the closed-loop feedback gain.

[0094] S104, take the negative of the product of the feedback gain and the error state vector as the closed-loop feedback compensation amount.

[0095] S105, the rear wheel steering error equation is solved with emphasis, and the feedforward compensation amount with yaw rate as the emphasis and the feedforward compensation amount with center of gravity sideslip angle as the emphasis are obtained respectively.

[0096] S106, determine the target rear wheel angle based on the sum of the closed-loop feedback compensation and the feedforward compensation.

[0097] In summary, the vehicle control method according to embodiments of the present invention constructs state-space equations for a vehicle model and a rear-wheel steering model based on vehicle parameters; determines the rear-wheel steering error equation based on these equations; determines the closed-loop feedback compensation amount based on the rear-wheel steering error equation; determines the feedforward compensation amount based on the rear-wheel steering error equation and the control focus; determines the target rear-wheel steering angle based on the closed-loop feedback compensation amount and the feedforward compensation amount; and controls the vehicle based on the target rear-wheel steering angle. Therefore, this method can accurately determine the rear-wheel steering angle, improving vehicle handling and stability.

[0098] Corresponding to the above embodiments, the present invention also proposes a vehicle control device.

[0099] like Figure 3 As shown, the vehicle control device 100 of this embodiment includes: a construction module 110, a first determination module 120, a second determination module 130, a third determination module 140, and a control module 150.

[0100] The system comprises the following modules: Construction module 110 constructs the state-space equations of the vehicle model and the rear-wheel steering model based on the vehicle's parameters; First determination module 120 determines the rear-wheel steering error equation based on the state-space equations of the vehicle model and the rear-wheel steering model; Second determination module 130 determines the closed-loop feedback compensation amount based on the rear-wheel steering error equation, and determines the feedforward compensation amount based on the rear-wheel steering error equation and the control focus; Third determination module 140 determines the target rear-wheel steering angle based on the closed-loop feedback compensation amount and the feedforward compensation amount; and Control module 150 controls the vehicle based on the target rear-wheel steering angle.

[0101] According to one embodiment of the present invention, the rear wheel steering error equation is:

[0102]

[0103] in, u = δ r err=xx d Let Δ1 be the first error and Δ2 be the second error, where Δ1 is the first error and Δ2 is the second error. in, For the front wheel lateral stiffness, Where m is the rear wheel lateral stiffness, and I is the total vehicle mass. z Let l be the moment of inertia of the entire vehicle about the Z-axis of the vehicle body coordinate system. f l is the distance from the center of mass to the front axle. r v is the distance from the center of mass to the rear axle. x For longitudinal vehicle speed, δ r β is the rear wheel steering angle, and β is the actual sideslip angle of the center of gravity. β is the actual yaw rate of the entire vehicle. d For the ideal centroid sideslip angle, For the ideal yaw rate, the first error is w*(CC) d The second error is x. d *(AA d ), w = δ f δ f τ is the front wheel steering angle. β The time constant of the low-pass filter is the centroid sideslip angle. The yaw rate is the low-pass filter time constant. For the target centroid sideslip angle gain, The target yaw rate gain.

[0104] According to one embodiment of the present invention, the second determining module 130 determines the closed-loop feedback compensation amount based on the rear wheel steering error equation, specifically used for: performing linear quadratic programming based on the linear part of the rear wheel steering error equation to determine the closed-loop feedback gain; and determining the closed-loop feedback compensation amount based on the closed-loop feedback gain and the error state vector.

[0105] According to one embodiment of the present invention, the closed-loop feedback gain is:

[0106] K FB = (R+B) T P k+1 B) -1 B T P k+1 A

[0107] Among them, K FBR is the feedback gain, R is the control penalty parameter, and P is the control penalty parameter. k+1 To iteratively solve the matrix for the Riccati equation, in, For the front wheel lateral stiffness, Where m is the rear wheel lateral stiffness, and I is the total vehicle mass. z Let l be the moment of inertia of the entire vehicle about the Z-axis of the vehicle body coordinate system. f l is the distance from the center of mass to the front axle. r v is the distance from the center of mass to the rear axle. x This refers to the longitudinal speed of the vehicle.

[0108] According to one embodiment of the present invention, the second determining module 130 determines the closed-loop feedback compensation amount based on the closed-loop feedback gain and the error state vector, specifically by taking the negative of the product of the feedback gain and the error state vector as the closed-loop feedback compensation amount.

[0109] According to one embodiment of the present invention, the second determining module 130 determines the feedforward compensation amount based on the rear wheel steering error equation and the control focus, specifically used for: performing a focus solution on the rear wheel steering error equation to obtain the feedforward compensation amount with yaw rate as the focus and the feedforward compensation amount with center of gravity sideslip angle as the focus.

[0110] According to one embodiment of the present invention, the feedforward compensation amount, which is based on yaw rate, is determined by the following formula:

[0111]

[0112] in, This is a feedforward compensation amount that focuses on yaw rate. K FB Indicates the closed-loop feedback gain. For the front wheel lateral stiffness, Where m is the rear wheel lateral stiffness, and I is the total vehicle mass. z Let l be the moment of inertia of the entire vehicle about the Z-axis of the vehicle body coordinate system. f l is the distance from the center of mass to the front axle. r v is the distance from the center of mass to the rear axle. x Let w be the longitudinal vehicle speed, Δ1 be the first error, and Δ2 be the second error. The first error is w*(CC). d The second error is x. d *(AA d ), w = δ f δ f τ is the front wheel steering angle. β The time constant of the low-pass filter is the centroid sideslip angle. The yaw rate is the low-pass filter time constant. For the target centroid sideslip angle gain, The target yaw rate gain.

[0113] According to one embodiment of the present invention, the feedforward compensation amount, with regard to the centroid sideslip angle, is determined by the following formula:

[0114]

[0115] Among them, u FFβ This is the feedforward compensation amount with a focus on the centroid sideslip angle. K FB For closed-loop feedback gain, For rear wheel lateral stiffness, Let m be the front wheel lateral stiffness, m be the vehicle mass, and I be the total mass. z Let l be the moment of inertia of the entire vehicle about the Z-axis of the vehicle body coordinate system. f l is the distance from the center of mass to the front axle. r v is the distance from the center of mass to the rear axle. x Let w be the longitudinal vehicle speed, Δ1 be the first error, and Δ2 be the second error. The first error is w*(CC). d The second error is x. d *(AA d ), w = δ f δ f τ is the front wheel steering angle. β The time constant of the low-pass filter is the centroid sideslip angle. The yaw rate is the low-pass filter time constant. For the target centroid sideslip angle gain, The target yaw rate gain.

[0116] According to one embodiment of the present invention, the third determining module 140 determines the target rear wheel steering angle based on the closed-loop feedback compensation amount and the feedforward compensation amount, specifically for: determining the target rear wheel steering angle based on the sum of the closed-loop feedback compensation amount and the feedforward compensation amount.

[0117] According to one embodiment of the present invention, the state-space equation of the vehicle model is:

[0118]

[0119] in, β d The ideal centroid sideslip angle, The ideal yaw rate;

[0120] The state-space equations for the rear-wheel steering model are:

[0121]

[0122] in, β is the actual centroid sideslip angle. This represents the actual yaw rate of the entire vehicle.

[0123] According to one embodiment of the present invention, the control module 150 is further configured to: filter the ideal centroid sideslip angle and the ideal yaw rate based on the filtering parameters.

[0124] It should be noted that for details not disclosed in the vehicle control device of this embodiment of the invention, please refer to the details disclosed in the vehicle control method of this embodiment of the invention, which will not be repeated here.

[0125] According to an embodiment of the present invention, a vehicle control device includes a construction module for constructing state-space equations for a vehicle model and a rear-wheel steering model based on vehicle parameters; a first determining module for determining a rear-wheel steering error equation based on the state-space equations of the vehicle model and the rear-wheel steering model; a second determining module for determining a closed-loop feedback compensation amount based on the rear-wheel steering error equation, and a feedforward compensation amount based on the rear-wheel steering error equation and the control focus; a third determining module for determining a target rear-wheel steering angle based on the closed-loop feedback compensation amount and the feedforward compensation amount; and a control module for controlling the vehicle based on the target rear-wheel steering angle. Thus, the device can accurately determine the rear-wheel steering angle, improving the vehicle's handling and stability.

[0126] Corresponding to the above embodiments, the present invention also proposes a vehicle.

[0127] like Figure 4 As shown, the vehicle 200 of this embodiment may include: a memory 210, a processor 220, and a program stored in the memory 210 and executable on the processor 220. When the processor 220 executes the program, it implements the above-described vehicle control method.

[0128] According to an embodiment of the present invention, by executing the above-described vehicle control method, the angle of the rear wheel steering can be accurately determined, thereby improving the vehicle's handling and stability.

[0129] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0130] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0131] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0132] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0133] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; 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; they can refer to the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0134] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for controlling a vehicle, characterized in that, The method includes: Based on the parameters of the vehicle, construct the state-space equations of the vehicle model and the state-space equations of the rear-wheel steering model; The rear wheel steering error equation of the vehicle is determined based on the state space equation of the vehicle model and the state space equation of the rear wheel steering model. The closed-loop feedback compensation amount is determined based on the rear wheel steering error equation, and the feedforward compensation amount is determined based on the rear wheel steering error equation and the control focus. The target rear wheel angle is determined based on the closed-loop feedback compensation amount and the feedforward compensation amount; The vehicle is controlled based on the target rear wheel steering angle; The step of determining the closed-loop feedback compensation amount based on the rear wheel steering error equation includes: solving a linear quadratic programming problem based on the linear part of the rear wheel steering error equation to determine the closed-loop feedback gain; determining the closed-loop feedback compensation amount based on the closed-loop feedback gain and the error state vector; wherein the error state vector is determined based on the difference between the actual state variables and the ideal state variables, wherein the actual state variables include the actual center of gravity sideslip angle and the actual vehicle yaw rate, and the ideal state variables include the ideal center of gravity sideslip angle and the ideal yaw rate.

2. The vehicle control method according to claim 1, characterized in that, The rear wheel steering error equation is: in, , , Let be the error state vector. For the first error, The second error is, where, , ,in, For the front wheel lateral stiffness, For rear wheel lateral stiffness, For the overall vehicle quality, Let Z be the moment of inertia of the entire vehicle about the Z-axis of the vehicle body coordinate system. This is the distance from the center of gravity to the front axle. This is the distance from the center of mass to the rear axle. For longitudinal vehicle speed, For the rear wheel steering angle, This is the actual sideslip angle of the centroid. This represents the actual yaw rate of the entire vehicle. For the ideal centroid sideslip angle, For the ideal yaw rate, the first error is w*(C- The second error is *(A- ), , , , , , The time constant of the low-pass filter is the centroid sideslip angle. The yaw rate is the low-pass filter time constant. For the target centroid sideslip angle gain, The target yaw rate gain.

3. The vehicle control method according to claim 2, characterized in that, The closed-loop feedback gain is: in, For feedback gain, To control the penalty parameters, To iteratively solve the matrix for the Riccati equation, , ,in, For the front wheel lateral stiffness, For rear wheel lateral stiffness, For the overall vehicle quality, Let Z be the moment of inertia of the entire vehicle about the Z-axis of the vehicle body coordinate system. This is the distance from the center of gravity to the front axle. This is the distance from the center of mass to the rear axle. This refers to the longitudinal speed of the vehicle.

4. The vehicle control method according to claim 1, characterized in that, Determining the closed-loop feedback compensation amount based on the closed-loop feedback gain and the error state vector includes: The negative of the product of the feedback gain and the error state vector is taken as the closed-loop feedback compensation amount.

5. The vehicle control method according to claim 1, characterized in that, The step of determining the feedforward compensation amount based on the rear wheel steering error equation and the control focus includes: The rear wheel steering error equation is solved with emphasis to obtain the feedforward compensation amount with yaw rate as the emphasis and the feedforward compensation amount with center of gravity sideslip angle as the emphasis.

6. The vehicle control method according to claim 5, characterized in that, The feedforward compensation amount, which emphasizes yaw rate, is determined by the following formula: in, The feedforward compensation amount is based on yaw rate. , , , , , , , , This represents the closed-loop feedback gain. For the front wheel lateral stiffness, For rear wheel lateral stiffness, For the overall vehicle quality, Let Z be the moment of inertia of the entire vehicle about the Z-axis of the vehicle body coordinate system. This is the distance from the center of gravity to the front axle. This is the distance from the center of mass to the rear axle. For longitudinal vehicle speed, The first error, The second error is w*(C-). The second error is *(A- ), , , , , , The time constant of the low-pass filter is the centroid sideslip angle. The yaw rate is the low-pass filter time constant. For the target centroid sideslip angle gain, The target yaw rate gain.

7. The vehicle control method according to claim 5, characterized in that, The feedforward compensation amount, which is based on the centroid sideslip angle, is determined using the following formula: in, The feedforward compensation amount is based on the centroid sideslip angle. , , , , , Let be the closed-loop feedback gain. For rear wheel lateral stiffness, For the front wheel lateral stiffness, For the overall vehicle quality, Let Z be the moment of inertia of the entire vehicle about the Z-axis of the vehicle body coordinate system. This is the distance from the center of gravity to the front axle. This is the distance from the center of mass to the rear axle. For longitudinal vehicle speed, The first error, The second error is w*(C-). The second error is *(A- ), , , , , , The time constant of the low-pass filter is the centroid sideslip angle. The yaw rate is the low-pass filter time constant. For the target centroid sideslip angle gain, The target yaw rate gain.

8. The vehicle control method according to claim 1, characterized in that, Determining the target rear wheel steering angle based on the closed-loop feedback compensation amount and the feedforward compensation amount includes: The target rear wheel angle is determined based on the sum of the closed-loop feedback compensation and the feedforward compensation.

9. The vehicle control method according to claim 2, characterized in that, The state-space equations of the vehicle model are: in, , The ideal centroid sideslip angle, The ideal yaw rate; The state-space equation of the rear-wheel steering model is: in, , The actual centroid sideslip angle, The actual yaw rate of the entire vehicle.

10. The vehicle control method according to claim 9, characterized in that, The method further includes: The ideal centroid sideslip angle and the ideal yaw rate are filtered based on the filtering parameters.

11. A vehicle control device, characterized in that, The device includes: A construction module is used to construct the state-space equations of the vehicle model and the state-space equations of the rear-wheel steering model based on the parameters of the vehicle. The first determining module is used to determine the rear wheel steering error equation of the vehicle based on the state space equation of the vehicle model and the state space equation of the rear wheel steering model. The second determining module is used to determine the closed-loop feedback compensation amount based on the rear wheel steering error equation, and to determine the feedforward compensation amount based on the rear wheel steering error equation and the control focus. The third determining module is used to determine the target rear wheel steering angle based on the closed-loop feedback compensation amount and the feedforward compensation amount; A control module is used to control the vehicle based on the target rear wheel steering angle; The step of determining the closed-loop feedback compensation amount based on the rear wheel steering error equation includes: solving a linear quadratic programming problem based on the linear part of the rear wheel steering error equation to determine the closed-loop feedback gain; determining the closed-loop feedback compensation amount based on the closed-loop feedback gain and the error state vector; wherein the error state vector is determined based on the difference between the actual state variables and the ideal state variables, wherein the actual state variables include the actual center of gravity sideslip angle and the actual vehicle yaw rate, and the ideal state variables include the ideal center of gravity sideslip angle and the ideal yaw rate.

12. A vehicle, characterized in that, include: A memory, a processor, and a program stored in the memory and executable on the processor, wherein when the processor executes the program, it implements a vehicle control method according to any one of claims 1-10.

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