A control method for transient switching process of vehicle extreme working condition and application thereof

Abstract

The present application belongs to the field of vehicle control technology, and relates to a control method for transient switching process of vehicle extreme working condition and application thereof. When the vehicle is in transient switching process, the vehicle motion state is represented as a coordinate point in a phase plane, i.e. a drift point. A steady-state equation of the drift point is constructed according to a vehicle dynamics equation. A controllable domain under steady state, i.e. a value boundary of the drift point, is solved through a control variable of the steady state. A trajectory searching method based on graph theory is used to find a moving trajectory in the phase plane for moving from a current drift point to a target drift point in the shortest time. An optimal trajectory adjustment control strategy is used to adjust and control an actual moving trajectory so as to make it approach the moving trajectory, so as to control the vehicle in the extreme working condition to a normal state or a drift state. The present application solves the problems of nonlinear solving difficulty and slow switching speed, and can be applied to drift control.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of vehicle motion state control, and particularly relates to a control method for a transient switching process of a vehicle in an extreme working condition and application thereof. BACKGROUND

[0002] A vehicle is very easy to lose control in an extreme working condition, for example, if control is not proper when a vehicle is controlled on an icy road, a great danger will be caused by loss of control. The drifting working condition of a vehicle on an icy road is a special stable working condition in a conventional driving working condition, and the vehicle will not lose control at this time. Therefore, if the vehicle is controlled to a conventional working condition or a drifting working condition by electronic control software when the vehicle has a tendency to lose control (hereinafter referred to as a tendency to lose stability), the vehicle can be controlled from a dangerous state to a safe state to ensure the stability of the vehicle. However, the control of the vehicle when it has a tendency to lose stability usually shows strong nonlinearity (the force of a tire is not proportional to its deformation), which makes the control at this time very difficult. Therefore, the current research usually analyzes how to keep the vehicle in a stable working condition when it is close to a conventional working condition or a drifting working condition, and the control of the process from a tendency to lose stability to a region without a tendency to lose stability is still less involved. For example, the patent with publication number CN120056996A proposes a closed-loop control structure formed according to the error relationship between the yaw angular velocity of a vehicle drifting equilibrium state and the actual state. The theoretical basis of this control method is not clear, the feedback parameters are adjusted according to the actual control effect, and it is an empirical control method. Therefore, in the actual transient switching process, the convergence of the yaw angular velocity is very slow. The patent with publication number CN120171532A needs the driver to first control the vehicle to the vicinity of a drifting equilibrium state, and then the control strategy proposed is involved to ensure that the state of the vehicle is maintained near the equilibrium state. The patent with publication number CN120096574A proposes an optimal control solving method based on a cost function and a constraint. In theory, this control method can handle the transient switching process, but due to the nonlinearity of the vehicle, the optimal solving operation amount of the cost function will be extremely large, which requires a high-performance computer to realize the control in actual application. SUMMARY

[0003] The present application aims to overcome the deficiencies in the prior art and provide a control method for a transient switching process of a vehicle in an extreme working condition and application thereof.

[0004] To achieve the purpose of the present application, the following technical solutions are adopted.

[0005] A control method for a transient switching process of a vehicle in an extreme working condition, comprising the following steps:

[0006] S1, when the vehicle is in transient switching process, the motion state of the vehicle is represented as a coordinate point in the phase plane, i.e. a drift point, a steady-state equation of the drift point is constructed according to a vehicle dynamics equation, and a controllable domain of the drift point at steady state, i.e. a value boundary of the drift point, is solved through a control variable of the steady state;

[0007] S2, according to the value boundary, a trajectory search method based on graph theory is used to find a moving trajectory in the phase plane for moving from the current drift point to the target drift point in the shortest time, and an actual moving trajectory is adjusted and controlled to approach the moving trajectory through an optimal trajectory adjustment control strategy, so that the vehicle in the extreme working condition can be controlled to a normal state or a drift state.

[0008] Further, the vehicle dynamics equation is:

[0009] ,

[0010] In the formula, 、 is the front wheel and rear wheel lateral force, is the front wheel steering angle, is the total vehicle mass, 、 is the longitudinal and lateral speed, is the yaw rate, 、 is the distance from the center of mass to the front axle and the rear axle, is the rotational inertia of the vehicle in the plane, is the lateral speed with respect to time, is the yaw rate with respect to time.

[0011] Further, the steady-state equation is:

[0012] .

[0013] In the formula: 、 is the front wheel and rear wheel lateral force in the balanced state, is the yaw rate in the balanced state.

[0014] Further, the expression of the value boundary is:

[0015] ;

[0016] In the formula: represents four vertices of a quadrilateral in the phase plane, i.e. the limit value of beta and the rate of change of r, wherein i takes values T, B, L and R respectively representing the upper, lower, left and right vertices; , represents the projection of the front wheel lateral force in the lateral direction of the vehicle body, and express The maximum and minimum values ​​of is the lateral force on the rear wheel, and express The maximum and minimum values ​​of .

[0017] Furthermore, the method for determining the shortest time includes the following steps:

[0018] S51, the phase plane is arranged with the same width and height Divided into chessboard grids, each grid is divided ... To represent the grid;

[0019] S52, the center point coordinates of each grid The control variables of the front and rear wheels corresponding to the vehicle motion state represented by and The maximum and minimum values ​​of the value are brought into the expression of the value boundary, and the control domain of each grid can be obtained ;

[0020] S53, the center point coordinates of each grid The movement direction is limited to eight directions, namely up, down, left, right, upper left, lower left, upper right, and lower right, and is represented by a vector representation, which means that each movement can only move to one of the eight adjacent grids; wherein: the expression of the vector representation is:

[0021] ;

[0022] Where: is a set of moving directions, and the vector in the brackets represents the moving direction. Indicates moving to the right. Indicates moving to the left. Indicates downward movement. Indicates upward movement. Move to the lower right. Move to the lower left. Move to the upper right. Indicates movement to the upper left; Indicates that the width and height of the chessboard grid are the same, The vector represented by , which means the distance to the right is , The vector represented by , which means moving to the left by ; The vector represented by is ; The vector represented by is ; The vector represented by is ; The vector represented by is ; The vector represented by is ; The vector represented by is ;

[0023] S54, assign a moving cost to the 8 paths of the center point of the current grid , and select the moving time as the moving cost, and define the moving time as:

[0024] ;

[0025] In the formula: is the target moving direction, is the vector with the smallest angle and the longest length in the control domain with , representing the change of will reach the grid represented by the direction fastest; if and have an angle , representing that the grid cannot be reached by any value in the control domain, then the time to reach the grid is recorded as infinite (inf), otherwise the time required to move is the shortest, then the moving time is: .

[0026] Further, the trajectory search method comprises the following steps:

[0027] S61, assign the current motion state and the target motion state to the nearest grid, respectively, denoted as and ;

[0028] S62, record the line connecting and as the initial path , and the initial path The number of moving grids is denoted as n, and the current moving grid number i is denoted as 1;

[0029] S63, according to the expression of the vector representation and the expression of the moving time, adopting The path search algorithm calculates to The path P with the lowest evaluation function in the middle; wherein: the evaluation function is:

[0030] ,

[0031] In the formula: is the Euclidean distance, indicating the geometric distance between the current motion state and the target motion state, and the moving time cost is , is the weight of the moving time, and by changing the size of the value, the weight of the distance and time used in the search can be adjusted;

[0032] S64, when i≤n, it indicates that the end point has not been reached, and the following steps are performed in a loop until i≤n is not satisfied or is changed:

[0033] S641, it is judged whether All the inflection points P in the path are inserted between the start point and the end point of the set , and the The i-th point is assigned to the current target point , and the distance between the current position and the inflection point is calculated as ;

[0034] S642, it is judged whether is satisfied, if satisfied, then jump to the next inflection point, until not satisfied, set ;

[0035] S643, according to the current target point , the control target and of and are calculated, which are , , in the formula: is the expected convergence time, if you want to converge faster, then adjust the value to be small, but it may cause shock;

[0036] S644, according to the actual situation of the control domain , limit and not to exceed the control domain , to obtain and​ For ultimate control.

[0037] The present invention also discloses an application based on the above method in vehicle drift control, comprising the following steps:

[0038] S1. When the vehicle is in a transient switching process, the vehicle's motion state is represented as a coordinate point in the phase plane, i.e., a drift point. The steady-state equation of the drift point is constructed based on the vehicle dynamics equation. The controllable domain of the drift point in the steady state, i.e., the value boundary of the drift point, is solved using the steady-state control variable.

[0039] S2. Based on the value boundary, a trajectory search method based on graph theory is used to find a movement trajectory in the phase plane that completes the movement from the current drift point to the target drift point in the shortest time, and the actual movement trajectory is adjusted and controlled by the optimal trajectory adjustment control strategy to make it approach the movement trajectory;

[0040] S3. Substituting a drift point in the actual moving trajectory that is close to the moving trajectory into the steady-state equation to obtain control targets for the front and rear wheel control variables at the drift point, and converting the front and rear wheel control variables into the front wheel steering angle and rear wheel speed, respectively, using the magic formula of the tire;

[0041] S4. Input the front wheel steering angle into a PID controller designed based on the sideslip angle error, and the output value of the PID controller is the front wheel steering angle compensation value to obtain the actual front wheel steering angle control value; input the rear wheel speed into a PID controller designed based on the yaw rate error, and the output value of the PID controller is the rear wheel speed compensation value to obtain the actual rear wheel speed control value, and use the actual front wheel steering angle control value and the actual rear wheel speed control value to control the vehicle in the extreme working condition to a normal state or a drift state.

[0042] Beneficial effects

[0043] This method addresses the safety control requirements of vehicles under extreme operating conditions and addresses the transient switching process that a vehicle must undergo when switching between different steady states (normal operation, left drift, right drift), or from transient to steady state. It solves the problems of difficult nonlinear solutions and slow switching speeds in existing technologies.

[0044] The application of this method in vehicle drift control involves switching the vehicle from drifting to the left to drifting to the right (or from right to left) to achieve drifting in a figure-8 manner. It can also perform many complex drifting actions. At the same time, when the vehicle is in an unstable state, it can be controlled to normal operation or drifting state through transient switching control to improve vehicle safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1Fig. 1 is a diagram of a control field; wherein: the angles between the directions of up, upper left, left, lower left and down and the control field are all greater than 45° pi / 4 , the arrival time is inf , and the arrival times of upper right, right and lower right can be calculated as 0.061s, 0.053s, 0.053s;

[0046] Figure 2 Fig. 2 is a diagram of moving trajectories from an initial point to a target point by using different strategies;

[0047] Figure 3 Fig. 3 is a diagram of convergence times under different working conditions;

[0048] Figure 4 Fig. 4 is a diagram of actual drift curves under the condition of adhesion of 0.75, wherein: (a) is a diagram of actual drift curves of a side slip angle; (b) is a diagram of actual drift curves of a yaw rate; (c) is a diagram of actual drift curves of a moving trajectory. DETAILED DESCRIPTION

[0049] The present application will be further described below in conjunction with the accompanying drawings. The following examples are only used to more clearly illustrate the technical solutions of the present application, and cannot be used to limit the protection scope of the present application.

[0050] As an embodiment of the present application, as shown in Fig. 5, a control method for a transient switching process of a vehicle under extreme working conditions comprises the following steps: Figure 1

[0051] I. Calculation method of a steady state and a controllable field of vehicle drift

[0052] The motion state of a vehicle can be generally described by a yaw rate , a side slip angle and a longitudinal speed (vehicle speed) . As long as the three quantities are determined, the motion of a vehicle in a plane is also determined. However, since the longitudinal speed of a vehicle usually does not change under a transient switching working condition, the state of the vehicle can be represented by coordinates in a plane, which is also called a phase plane. The steady state of a vehicle is calculated by the following method.

[0053] Step 1: Construct the dynamic equation of the vehicle. The known motion equation of a vehicle is as follows:

[0054] (1)

[0055] In the formula, Fxf, Fxr, Fyf and Fyr are lateral forces of front wheels and rear wheels, δf is a front wheel steering angle, m is the mass of the whole vehicle, g is the acceleration of gravity, and , is the longitudinal speed of the vehicle. ,​​​ is the longitudinal velocity, is the lateral velocity, , is the distance from the center of mass to the front and rear axles, is the rotational inertia of the vehicle in the plane, is the lateral velocity is the derivative of the lateral velocity with respect to time, is the yaw rate is the derivative of the yaw rate with respect to time;

[0056] According to the definition of the side slip angle , the above equations can be rewritten as:

[0057] (2)

[0058] (3)

[0059] Step 2: Construct the steady-state equation. For the steady-state drift point, the motion state of the vehicle remains unchanged at this time, i.e. and , bring into equation (2) and (3) to get the steady-state equation:

[0060] (4)

[0061] In the formula: the subscript indicates that the variable is a steady-state control variable.

[0062] Step 3: Solve the controllable domain of in the steady-state, that is, the value boundary of . When the vehicle is in the current state , and , the range of change is calculated by equation (2) and (3) to get equation (5):

[0063] (5) In the formula:

[0064] is the abbreviation of . Bring the maximum value

[0065] , the minimum value of , and the maximum value and the minimum value of into equation (5) respectively, and the value boundary of can be obtained:

[0066] ​(6)

[0067] In the formula: T, B, L, R respectively represent the upper, lower, left and right vertices of the value boundary.

[0068] II. Control domain-based arrival time calculation method.

[0069] In the phase plane, the current state of the vehicle is denoted as , and the target state of the vehicle is denoted as The switching process from to is the transient switching process, and the switching trajectory that can complete the switching process in the shortest time (the trajectory generated by drawing each time of the switching process on the phase plane) is the optimal trajectory. In order to find the optimal switching trajectory, we propose a trajectory search method based on graph theory.

[0070] Step 1: In order to reduce the amount of calculation, the phase plane is divided into a chessboard grid according to the same width and height , and each grid is represented by the coordinates of its center point .

[0071] Step 2: Calculate the control domain of each grid , which is calculated by bringing the maximum and minimum values of and corresponding to the state of the center point into formula (6), i.e. the control domain can be obtained.

[0072] Step 3: In order to reduce the amount of calculation of path search, the movement direction is limited to eight directions, namely up, down, left, right, left up, left down, right up, and right down, represented by vectors as formula (7), which means that each move can only move to one of the eight adjacent grids. Obviously, other grid division methods can also be chosen here to refine the path, but this will increase the amount of calculation.

[0073] (7)

[0074] In the formula: is the set of movement directions, and the vector in the parentheses represents the movement direction, represents moving right, represents moving left, represents moving down, represents moving up, represents moving right down, represents moving left down, represents moving right up, and ​represents moving to the left up; represents the width and height of the chessboard grid are the same, represents the vector is represents moving to the right distance is , represents the vector is represents moving to the left distance is ; represents the vector is represents moving to the down distance is ; represents the vector is represents moving to the up distance is ; represents the vector is represents moving to the right down distance is ; represents the vector is represents moving to the left down distance is ; represents the vector is represents moving to the right up distance is ; represents the vector is represents moving to the left up distance is ;

[0075] Step 4: give the center point of the current grid 8 path movement cost. Here the movement time is selected as the movement cost, defined as:

[0076] (8)

[0077] In the formula: is the target moving direction, as defined in equation (7), is the vector with the smallest angle and the longest length in the control domain with (representing the grid along the vector change will be the fastest to reach the direction represented by the grid).

[0078] In equation (8), if the angle between and is , it means that any value in the control domain cannot reach the grid, then the time to reach the grid is recorded as infinity (inf), otherwise the time required to move is the shortest, then the moving time is .

[0079] The results of the above steps 1-4 are shown in Figure 1 , at this time and​ -1.4 rad / s and -0.7 rad , the vehicle speed is 5m / s, and the adhesion is 0.3, Figure 1 The middle red area is the control domain, in which the angles between the directions of up, upper left, left, lower left and down and the control domain are all greater than pi / 4 , the arrival time is inf , while the arrival times of upper right, right and lower right can be calculated as 0.061s, 0.053s, 0.053s.

[0080] III. Transient switching process optimal trajectory search method based on graph theory

[0081] Step 1: Assign the current state and the target state to their nearest grid, denoted as: and .

[0082] Step 2: The line connecting and is recorded as the initial path , the number of moving grids of the initial path is denoted as n, and the current moving grid number i is set to 1.

[0083] Step 3: Calculate the optimal path: according to equations (7) and (8), use the path search algorithm to calculate the path P with the lowest evaluation function from to . The evaluation function is , where: is the Euclidean distance, representing the geometric distance between the current point and the target point, the moving time cost is , is the weight of moving time, and by changing the size of this value, the weight of distance and time used in the search can be adjusted.

[0084] S4, adjust the control strategy according to the optimal path. Obviously, the optimal path obtained by search can be used for drift control, and its internal contains different strategies. In actual control, the control strategy needs to be adjusted according to the current state, so that the actual trajectory in the phase plane is closest to the path obtained by search. This step is as follows: when i≤n, it means that the end point has not been reached, and the following steps are repeated until i≤n is not satisfied or changes.

[0085] S41, judge all the inflection points P in the given path (inflection points represent the point where the path changes direction) are inserted into Between the start and end points of the set, The i-th point Assign the current target point , calculate the current position And the distance of the inflection point is ;

[0086] S42, determine If satisfied, jump to the next inflection point (indicating that the distance to the inflection point is greater than the distance to the previous inflection point, then the inflection point is meaningless), until not satisfied ;

[0087] S43, according to the current target point Then you can calculate And The control target And , calculated as , , in which: The desired convergence time, if you want to converge faster, reduce the value, but it may trigger shock.

[0088] S44, according to the actual situation of the control domain Limit And Do not exceed the control domain, get And Used for final control.

[0089] As an embodiment of the present application, a control method for vehicle extreme working condition transient switching process is applied in drift control, that is, the control method of vehicle drift, including the following steps:

[0090] Step 1: bring And Into equation (4), that is, get And The control target;

[0091] Step 2: according to the magic formula of the tire, convert Into front wheel steering angle Convert Into rear wheel speed ;

[0092] Step 3: design a PID controller based on the side slip angle error The output value of the PID controller is the front wheel steering angle compensation , then the actual control value of the front wheel steering angle is ; Design a PID controller based on the yaw rate error The output value of the controller is the rear wheel speed compensation , the actual control value of rear wheel speed is .

[0093] The control effect of the control method for the transient switching process of the vehicle extreme working condition in actual application:

[0094] Figure 2 is a moving trajectory graph from the initial point to the target point by using different strategies, red is the graph search method proposed in the application, green is the first yaw rate and then side slip angle, pink is the first side slip angle and then yaw rate, and blue is the simultaneous control of yaw rate and side slip angle.

[0095] Figure 3 is a comparison graph of convergence time under different working conditions, wherein: working condition 1 is adhesion 0.75 and speed 10 m / s, working condition 2 is adhesion 0.3 and speed 10 m / s, working condition 3 is adhesion 0.75 and speed 5 m / s, and working condition 4 is adhesion 0.4 and speed 5 m / s, and the method proposed in the four working conditions is the fastest convergence.

[0096] Figure 4 is a drift actual curve graph under the adhesion condition of 0.75, from Figure 4 , it can be seen from (a), (b) and (c) that the vehicle reverses at 25s, the vehicle trajectory presents an "8" shape, and under the working condition, the process is from one drift transient point to another drift transient point, and the side slip angle and yaw rate are quickly converged to the target value.

[0097] The preferred embodiments of the embodiments of the application are described above with reference to the accompanying drawings, and are not limited to the scope of the embodiments of the application. Any modifications, equivalent replacements and improvements made by those skilled in the art without departing from the scope and essence of the embodiments of the application shall be within the scope of the embodiments of the application.

Claims

1. A control method for a vehicle extreme operating condition transient switching process, characterized by: The method comprises the following steps: S1, when the vehicle is in a transient switching process, representing the motion state of the vehicle as a coordinate point in a phase plane, i.e., a drift point, constructing a steady-state equation of the drift point according to a vehicle dynamics equation, and solving a controllable domain of the drift point at a steady state, i.e., a value boundary of the drift point, through a control variable at the steady state; S2, according to the value boundary, finding a moving trajectory for moving from a current drift point to a target drift point in the shortest time in the phase plane by using a trajectory search method based on graph theory, and adjusting and controlling an actual moving trajectory to approach the moving trajectory through an optimal trajectory adjustment control strategy, so as to control the vehicle in an extreme working condition to a normal state or a drift state.

2. The control method for vehicle extreme operating condition transient switching process according to claim 1, characterized in that: The vehicle dynamics equation is: ， wherein: , is the front, rear wheel side force, is the front wheel steering angle, is the vehicle mass, , is the longitudinal, lateral velocity, is the yaw rate, , is the distance of the center of mass to the front, rear axle, is the rotational inertia of the vehicle in the plane, is the lateral velocity is the differential of the lateral velocity with respect to time, is the yaw rate is the differential of the yaw rate with respect to time.

3. The control method for vehicle extreme operating condition transient switching process according to claim 1, characterized in that: The steady-state equation is: ； In the formulae: , is the lateral force of the front wheel and the rear wheel in the balanced state, is the yaw rate in the balanced state.

4. The control method for vehicle extreme operating condition transient switching process according to claim 1, characterized in that: The expression of the value boundary is: ； wherein: denotes the four vertices of a quadrangle in the phase plane, i.e. the limits of the beta and r rate of change, wherein i takes the values T, B, L, R for the top, bottom, left, right vertices, respectively; denotes the projection of the front wheel side force in the body side direction, and denotes the maximum and minimum of is the side force of the rear wheel, and denotes the maximum and minimum of 5. The control method for vehicle extreme operating condition transient switching process according to claim 1, characterized in that: The determination method of the shortest time comprises the following steps: S51, the phase plane is arranged in the same width and height Divided into chessboard grids, each grid is divided ... To represent the grid; S52, the center point coordinate of each grid is calculated the control variable of the front and rear wheels corresponding to the represented vehicle motion state and the maximum and minimum values of the expression of the control domain of each grid are taken into the expression of the value boundary, i.e. ; S53, the center point coordinates of each grid The movement direction is limited to eight directions, namely up, down, left, right, upper left, lower left, upper right, and lower right, and is represented by a vector representation, which means that each movement can only move to one of the eight adjacent grids; wherein: the expression of the vector representation is: ； wherein: is a set of movement directions, the vector in the parentheses represents a movement direction, represents moving right, represents moving left, represents moving down, represents moving up, represents moving right down, represents moving left down, represents moving right up, represents moving left up; represents that the width and height of the chessboard grid are the same, represents the vector is , represents moving right a distance of , represents the vector is , represents moving left a distance of ; represents the vector is , represents moving down a distance of ; represents the vector is , represents moving up a distance of ; represents the vector is , represents moving right down a distance of ; represents the vector is , represents moving left down a distance of ; represents the vector is , represents moving right up a distance of ; represents the vector is , represents moving left up a distance of ; S54, give the center point of the current grid The 8 paths are assigned movement costs, and the movement time is selected as the movement cost, and the movement time is defined as: ； In the formula: is the target moving direction, is the vector with the smallest angle and the longest length in the control domain, representing the change along the vector is the grid reached fastest in the direction represented by the vector; if and the angle between is , it means that the grid cannot be reached with any value in the control domain, and the time to reach the grid is recorded as infinite inf, otherwise the time to reach the grid is The time required to move is the shortest, and the moving time is: .

6. The control method for vehicle extreme operating condition transient switching process according to claim 1, characterized in that: The trajectory search method comprises the following steps: S61, assign the current motion state and the target motion state to the respective nearest grid, denoted as and ; S62, the and The connection of the initial path The initial path The number of the mobile grid of the initial path is n, and the current mobile grid number i is 1. S63, from the expression of the vector representation and the expression of the moving time, adopt The path search algorithm calculates to The path P with the lowest evaluation function in the middle; wherein: the evaluation function is: ， Where: is the Euclidean distance, which represents the geometric distance between the current motion state and the target motion state. The moving time cost is , The weight of the moving time can be adjusted by changing the value The weighting of distance and time during search; S64, when i≤n, it means that the end point has not been reached, and the loop proceeds to the following steps until i≤n is not satisfied or Changes: S641、judgment Insert all the inflection points P in the given path into The set between the start and end points of the path The i-th point Assign the current target point to the current target point , calculate the current position The distance between the inflection point is ; S642、judging whether the condition is met, if yes, jump to the next corner until the condition is not met, set ; S643、according to the current target point calculating and the control target and , calculated as , , where: is the desired convergence time, convergence is accelerated, then the value is adjusted small; S644, according to the control domain The actual situation, limit And No more than the control domain , get And For final control.

7. Use of the method according to any one of claims 1 to 6 in vehicle drift control, characterized in that: The method comprises the following steps: S1, when the vehicle is in a transient switching process, representing the motion state of the vehicle as a coordinate point in a phase plane, i.e., a drift point, constructing a steady-state equation of the drift point according to a vehicle dynamics equation, and solving a controllable domain of the drift point at a steady state, i.e., a value boundary of the drift point, through a control variable at the steady state; S2, according to the value boundary, finding a moving trajectory for moving from a current drift point to a target drift point in the shortest time in the phase plane by using a trajectory search method based on graph theory, and adjusting and controlling an actual moving trajectory to approach the moving trajectory through an optimal trajectory adjustment control strategy; S3, bringing the drift point in the actual moving trajectory approaching the moving trajectory into the steady-state equation to obtain a control target of a front wheel control variable and a rear wheel control variable of the drift point, and converting the front wheel control variable and the rear wheel control variable into a front wheel steering angle and a rear wheel speed respectively through a magic formula of a tire; S4, inputting the front wheel steering angle into a PID controller based on a side slip angle error design, and outputting a front wheel steering angle compensation amount to obtain an actual front wheel steering angle control value; inputting the rear wheel speed into a PID controller based on a yaw rate error design, and outputting a rear wheel speed compensation amount to obtain an actual rear wheel speed control value, and using the actual front wheel steering angle control value and the actual rear wheel speed control value to control the vehicle in the extreme working condition to the normal state or the drift state.

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