A distributed steer-by-wire vehicle stability control method

Abstract

The application provides a distributed steer-by-wire vehicle stability control method, which comprises the following steps: a distributed steer-by-wire vehicle dynamics model, a two-degree-of-freedom reference model and a four-wheel steering angle distribution model are established; in the design of a yaw stability controller, a hybrid sensitivity robust control method is adopted, and the system uncertainty is fully considered, so that the target tracking performance and the system robustness can be ensured at the same time.

Description

Technical Field

[0001] The present invention relates to the field of automobile assisted driving, and in particular to a distributed steer-by-wire vehicle stability control method. Background Art

[0002] Distributed steer-by-wire systems utilize either two sets of steering actuators, one on each axle (front-and-rear axle type) or four sets on all four wheels (four-wheel distributed steer). Compared to front-wheel steer-by-wire systems, these systems eliminate the constraints of mechanical connections between the left and right wheels, providing a wider range of lateral control force. This allows for more precise, agile, and stable steering performance, and can handle specialized maneuvers such as low-speed steering, pivoting, diagonal maneuvers, and translational maneuvers. Four-wheel independent steering (FWS) handling and stability control is a highly nonlinear and complex process, and FWS systems are susceptible to uncertainties such as modeling uncertainty, external disturbances (such as road conditions and crosswinds), measurement noise, and parameter variations. Therefore, robust control is urgently needed to mitigate the impact of these uncertainties on FWS handling and stability control. Currently, various control methods used in distributed steer-by-wire vehicle stability control include sliding film control, PID control, model predictive control, and neural network control. While sliding film control offers advantages such as simplicity and robustness, it suffers from the problem of buffeting, making it unsuitable for distributed steer-by-wire vehicle stability control. While PID control boasts a simple design and flexible structure, it is primarily used in single-input, single-output systems. Model predictive control linearizes the vehicle model, reducing the computational effort during the control process and improving real-time control. However, this also reduces control accuracy, and the computational burden increases with the complexity of the system's dynamics. Neural network control can approximate external disturbances and modeling errors, offering strong robustness and fault tolerance. However, it suffers from slow learning speeds and long computation times, and analytically proving the convergence and stability of the learning process is difficult. H∞ robust control offers strong robustness and can mitigate the impact of uncertainty on four-wheel independent steering handling stability control. Summary of the Invention

[0003] The purpose of the present invention is to propose a distributed steer-by-wire vehicle stability control method that fully considers the uncertainty of the system and can ensure target tracking performance while taking into account the robustness of the system.

[0004] To achieve the above object, the technical solution of the present invention is: a distributed steer-by-wire vehicle stability control method, comprising the following steps:

[0005] S1. Establish a distributed steer-by-wire vehicle dynamics model;

[0006] S2. Establish a two-degree-of-freedom vehicle reference model;

[0007] S3. Establishing a four-wheel steering angle distribution model for a steer-by-wire vehicle;

[0008] S4. Design a distributed H∞ robust controller for yaw stability of steer-by-wire vehicles.

[0009] Preferably, establishing a distributed steer-by-wire vehicle dynamics model specifically includes:

[0010] Longitudinal dynamics model:

[0011]

[0012] Lateral dynamics model:

[0013]

[0014] Yaw dynamics model:

[0015]

[0016] Among them, for have:

[0017]

[0018] Where m is the vehicle mass; C D is the air resistance coefficient; A is the frontal area; v x and v y are the components of the vehicle's center of mass velocity on the x-axis and y-axis respectively; a x is the longitudinal acceleration; a y is the lateral acceleration; ω r is the yaw angular velocity of the vehicle; I z is the yaw moment of inertia of the vehicle around the z-axis; a and b are the distances from the center of mass of the vehicle to the front and rear axles, respectively; T W is half of the wheelbase; ij = fl, fr, rl, rr represent the left front wheel, right front wheel, left rear wheel and right rear wheel of the vehicle respectively; F tyij 、F txij are tire lateral force and tire longitudinal force respectively; F xij 、F yij F txij 、F tyij The longitudinal force and lateral force of each wheel decomposed and synthesized in the vehicle coordinate system; δ ij is the wheel angle;

[0019] Vertical load on each wheel F zij for:

[0020]

[0021] Where g is the acceleration due to gravity; h is the acceleration due to gravity. g is the height of the vehicle's center of mass from the ground;

[0022] Building the Magic Formula Tire Model:

[0023] Y(x)=Dsin{Carctan[Bx-E(Bx-arctan(Bx))]} (6)

[0024] Where Y(x) is the lateral force F of the tire tyij Or the longitudinal force F txij ; x is the tire slip angle α ij Or tire slip ratio λ ij ; B, C, D, and E are fitting parameters in the tire characteristic curve, which are stiffness factor, curve shape factor, curve peak factor, and curve curvature factor, respectively.

[0025] Preferably, the tire slip rate of each wheel is calculated as follows:

[0026]

[0027] Where u ij is the wheel center speed of each wheel; w ij is the angular velocity of each wheel; r is the rolling radius of the wheel;

[0028] The wheel center speed of each wheel is expressed as:

[0029]

[0030] The calculation of the sideslip angle of the four wheels is as follows:

[0031]

[0032] Preferably, the establishment of a two-degree-of-freedom vehicle reference model is specifically as follows:

[0033]

[0034] Where k f is the front wheel cornering stiffness of the reference model; k r is the rear wheel cornering stiffness of the reference model; δ f is the front wheel turning angle of the reference model; δ r is the rear wheel turning angle of the reference model; Δδ f The additional steering angle of the front wheels of the reference model; Δδ r is the additional steering angle of the rear wheels of the reference model; β is the sideslip angle of the vehicle's center of mass.

[0035] Preferably, the establishment of the distribution line four-wheel angle distribution model of the steer-by-wire vehicle is specifically as follows:

[0036] Based on the steering wheel angle sensor reading, a positive steering wheel angle indicates that the vehicle is turning left; a negative steering wheel angle indicates that the vehicle is turning right; a positive steering wheel angle indicates that the wheel is rotating counterclockwise; a negative steering wheel angle indicates that the wheel is rotating clockwise;

[0037] Introducing the vehicle front axle electric wheel steering judgment factor c f and rear axle electric wheel steering judgment factor c r , the expression is set as:

[0038]

[0039] The four-wheel steering angle distribution model is:

[0040]

[0041] Where L is the wheelbase of the vehicle's front and rear axles; B is the distance between the intersection of the left and right wheel kingpin axes and the ground.

[0042] Preferably, the establishment of the yaw stability H∞ robust controller includes the following steps:

[0043] S4.1. Define the parameters in the H∞ robust controller;

[0044] S4.2. Based on the two-degree-of-freedom vehicle reference model, establish the state space expression of the vehicle yaw stability H∞ robust controller;

[0045] S4.3. Establish the expression of the input-output transfer function in the H∞ robust controller;

[0046] S4.4. Solve the controller K(s) to make the system stable and meet the preset conditions.

[0047] Preferably, the parameters in the H∞ robust controller are defined as follows:

[0048] Select the additional turning angle Δδ of the front and rear wheels of the reference model f , Δδ r As the control quantity, that is, u=[Δδ f Δδ r ] T ; The vehicle's yaw rate ω r The vehicle's center of mass side slip angle β is the system state, that is, x=z0=[β ω r ] T ; Set the reference center of mass sideslip angle β d , reference pendulum angular velocity ω rd , the driver inputs the equivalent front wheel steering angle δ f and rear wheel turning angle δ r and the side wind disturbance F ywAs the interference signal input of the system, that is, w=[β d ω rd δ f δ r F yw ] T The tracking errors of the sideslip angle and yaw rate are the measured output signals and also the input signals of the controller, i.e., y = e = [e1 e2] T =[β d -βω rd -ω r ] T ; z is the performance variable, also known as the controlled output, z=[z 11 z 12 z 21 z 22 z 31 z 32 ] T =[β d -βω rd -ω r β ω r Δδ f Δδ r ] T ; P(s) is the generalized controlled object, that is, the transfer function matrix from input w, u to output z, y; K(s) is the controller.

[0049] Preferably, the state space expression of establishing the vehicle yaw stability H∞ robust controller is specifically:

[0050]

[0051] Where: D 22 =[0 0].

[0052] Preferably, the expression for establishing the input-output transfer function in the H∞ robust controller is specifically:

[0053] Let the sensitivity function S be the closed-loop transfer function from w to y, the complementary sensitivity function T be the closed-loop transfer function from w to z0, and the input sensitivity function R be the closed-loop transfer function from w to u;

[0054] The control outputs Z1, Z2, and Z3 of the system are the weighted products of e, z0, and u, respectively, namely:

[0055]

[0056] Where Z1=[Z 11 Z 12 ] TIndicates the system target tracking performance and interference suppression performance, Z 11 , Z 12 are the controlled outputs of the center of mass sideslip angle tracking error and the yaw angular velocity tracking error respectively; Z2=[Z 21 Z 22 ] T Indicates the robust stability and noise suppression performance of the system, Z 21 , Z 22 are the controlled outputs of the sideslip angle and yaw rate respectively; Z3=[Z 31 Z 32 ] T Indicates the size of the controller output, Z 31 , Z 32 They are the controlled outputs of the additional turning angles of the front and rear wheels respectively; W1=diag{W 11 ,W 12}、W2=diag{W 21 ,W 22} and W3=diag{W 31 ,W 32} represent the weighting functions of the three control performances Z1, Z2 and Z3 respectively;

[0057] Let the closed-loop transfer function from w to Z be T w→Z for:

[0058]

[0059] The input and output of the system are expressed as:

[0060]

[0061] Where Z = [Z1 Z2 Z3] T Indicates the total controlled output of the system; is δ f , δ r 、F yw to β and ω r The transfer function, G 11 , G 12 , G 13 are δ f , δ r 、F yw Transfer function to the sideslip angle β, G 14 , G 15 , G 16 are δ f , δ r 、F yw to the yaw angular velocity ω r The transfer function of is Δδ f, Δδ r to β and ω r The transfer function, G 01 , G 02 Δδ f , Δδ r Transfer function to the sideslip angle β, G 03 , G 04 Δδ f , Δδ r to the yaw angular velocity ω r The transfer function of .

[0062] Preferably, the controller K(s) is solved to make the system stable and satisfy the following preset conditions:

[0063]

[0064] In the formula, ξ is a very small positive number.

[0065] Compared with the prior art, the present invention has the following beneficial effects:

[0066] The mixed sensitivity algorithm in H∞ robust control theory can design weighting functions based on uncertain perturbation systems, fully accounting for system uncertainty. This approach provides a robust control system design method based on practical conditions, ensuring both target tracking performance and system robustness. H∞ robust control exhibits strong robustness, mitigating the effects of modeling uncertainty, external disturbances (such as road conditions and crosswinds), measurement noise, and parameter variations on the handling and stability control of four-wheel independent steering. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 Schematic diagram of the H∞ robust controller method for yaw stability of a distributed steer-by-wire vehicle according to the present invention.

[0068] Figure 2 This is a diagram of the distributed wire-controlled steering dynamics model of the present invention;

[0069] Figure 3 This is a reference model diagram of a two-degree-of-freedom vehicle according to the present invention. DETAILED DESCRIPTION

[0070] The technical solution of the present invention is further described in detail below with reference to the accompanying drawings:

[0071] The present invention can be implemented in many different forms and should not be considered to be limited to the embodiments described herein. On the contrary, these embodiments are provided to make this disclosure thorough and complete and will fully convey the scope of the invention to those skilled in the art. In the accompanying drawings, components are enlarged for clarity.

[0072] like Figure 1-3 As shown in Figure 1, the establishment of the H∞ robust controller for the yaw stability of the distributed steer-by-wire vehicle, the dynamic model of the distributed steer-by-wire vehicle, the two-degree-of-freedom reference model, and the four-wheel angle distribution model includes the following steps. In the figure, G(s) is the transfer function, v is the vehicle center of mass velocity, and F yf is the front wheel lateral force of the reference model, F yr is the rear wheel lateral force of the reference model, α f , α r are the front and rear wheel slip angles of the reference model respectively; other parameters will be defined below.

[0073] S1. Establish a distributed steer-by-wire vehicle dynamics model:

[0074] Longitudinal dynamics model:

[0075]

[0076] Lateral dynamics model:

[0077]

[0078] Yaw dynamics model:

[0079]

[0080] Among them, for have:

[0081]

[0082] Where m is the vehicle mass; C D is the air resistance coefficient; A is the frontal area; v x and v y are the components of the vehicle's center of mass velocity on the x-axis and y-axis respectively; a x is the longitudinal acceleration; a y is the lateral acceleration; ω r is the yaw angular velocity of the vehicle; I z is the yaw moment of inertia of the vehicle around the z-axis; a and b are the distances from the center of mass of the vehicle to the front and rear axles, respectively; T W is half of the wheelbase; ij = fl, fr, rl, rr represent the left front wheel, right front wheel, left rear wheel and right rear wheel of the vehicle respectively; F tyij 、F txij are tire lateral force and tire longitudinal force respectively; F xij 、F yij F txij 、F tyij The longitudinal force and lateral force of each wheel decomposed and synthesized in the vehicle coordinate system; δ ij is the wheel angle.

[0083] Considering the vertical load transfer of each wheel of the vehicle caused by the longitudinal acceleration and lateral acceleration during the movement, the vertical load F of each wheel is calculated according to the moment balance relationship. zij for:

[0084]

[0085] Where g is the acceleration due to gravity; h is the acceleration due to gravity. g is the height of the vehicle's center of mass from the ground.

[0086] Building the Magic Formula Tire Model:

[0087] Y(x)=Dsin{Carctan[Bx-E(Bx-arctan(Bx))]} (6)

[0088] Where Y(x) is the lateral force F of the tire tyij Or the longitudinal force F txij ; x is the tire slip angle α ij Or tire slip ratio λ ij ; B, C, D, and E are fitting parameters in the tire characteristic curve, which are stiffness factor, curve shape factor, curve peak factor, and curve curvature factor, respectively;

[0089] The tire slip ratio of each wheel is calculated as:

[0090]

[0091] Where u ij is the wheel center speed of each wheel; w ij is the angular velocity of each wheel; r is the rolling radius of the wheel;

[0092] The wheel center speed of each wheel can be expressed as:

[0093]

[0094] The slip angles of the four wheels are:

[0095]

[0096] S2. Establish a two-degree-of-freedom vehicle reference model:

[0097]

[0098] Where k f is the front wheel cornering stiffness of the reference model; k r is the rear wheel cornering stiffness of the reference model; δ f is the front wheel turning angle of the reference model; δ r is the rear wheel turning angle of the reference model; Δδf The additional steering angle of the front wheels of the reference model; Δδ r is the additional steering angle of the rear wheels of the reference model; β is the side slip angle of the vehicle’s center of mass;

[0099] S3. Establish a four-wheel steering angle distribution model for a steer-by-wire vehicle:

[0100] Introducing the vehicle front axle electric wheel steering judgment factor c f and rear axle electric wheel steering judgment factor c r , its expression can be set as:

[0101]

[0102] Taking into account factors such as vehicle left and right steering and four-wheel steering same-direction and reverse steering mode selection, the four-wheel angle distribution model is:

[0103]

[0104]

[0105] Where L is the wheelbase of the vehicle's front and rear axles; B is the distance between the intersection of the left and right wheel kingpin axes and the ground;

[0106] S4. Design a distributed H∞ robust controller for yaw stability of a steer-by-wire vehicle, specifically including the following steps:

[0107] S4.1. Define the parameters in the H∞ robust controller: Select the additional steering angles Δδ of the front and rear wheels of the reference model. f , Δδ r As the control quantity, that is, u=[Δδ f Δδ r ] T ; The vehicle's yaw rate ω r and the vehicle's center of mass side slip angle β is the system state, that is, x=z0=[βω r ] T ; Set the reference center of mass side slip angle β d , reference pendulum angular velocity ω rd , the driver inputs the equivalent front wheel steering angle δ f and rear wheel steering angle δ r and the side wind disturbance F yw As the interference signal input of the system, that is, w=[β d ω rd δ f δ r F yw ] T The tracking errors of the sideslip angle and yaw rate are the measured output signals and also the input signals of the controller, i.e., y = e = [e1 e2]T =[β d -βω rd -ω r ] T ; z is the performance variable, also known as the controlled output, z=[z 11 z 12 z 21 z 22 z 31 z 32 ] T =[β d -βω rd -ω r β ω r Δδ f Δδ r ] T ; P(s) is the generalized controlled object, that is, the transfer function matrix from input w, u to output z, y; K(s) is the controller;

[0108] S4.2. Combined with the two-degree-of-freedom vehicle reference model, the state space expression of the vehicle yaw stability H∞ robust controller is established:

[0109]

[0110] Where: D 22 =[0 0];

[0111] S4.3. Establish the expression of the input-output transfer function in the H∞ robust controller:

[0112] Let the sensitivity function S be the closed-loop transfer function from w to y, the complementary sensitivity function T be the closed-loop transfer function from w to z0, and the input sensitivity function R be the closed-loop transfer function from w to u;

[0113] The control outputs Z1, Z2, and Z3 of the system are the weighted products of e, z0, and u, respectively, namely:

[0114]

[0115] Where Z1=[Z 11 Z 12 ] T Indicates the system target tracking performance and interference suppression performance, Z 11 , Z 12 are the controlled outputs of the center of mass sideslip angle tracking error and the yaw angular velocity tracking error respectively; Z2=[Z 21 Z 22 ] T Indicates the robust stability and noise suppression performance of the system, Z 21, Z 22 are the controlled outputs of the sideslip angle and yaw rate respectively; Z3=[Z 31 Z 32 ] T Indicates the size of the controller output, Z 31 , Z 32 They are the controlled outputs of the additional turning angles of the front and rear wheels respectively; W1=diag{W 11 ,W 12}、W2=diag{W 21 ,W 22} and W3=diag{W 31 ,W 32} represent the weighting functions of the three control performances Z1, Z2 and Z3 respectively;

[0116] Let the closed-loop transfer function from w to Z be T w→Z for:

[0117]

[0118] The input and output of the system are expressed as:

[0119]

[0120]

[0121] Where Z = [Z1 Z2 Z3] T Indicates the total controlled output of the system; is δ f , δ r 、F yw to β and ω r The transfer function, G 11 , G 12 , G 13 are δ f , δ r 、F yw Transfer function to the sideslip angle β, G 14 , G 15 , G 16 are δ f , δ r 、F yw to the yaw angular velocity ω r The transfer function of is Δδ f , Δδ r to β and ω r The transfer function, G 01 , G 02 Δδ f , Δδ r Transfer function to the sideslip angle β, G03 , G 04 Δδ f , Δδ r to the yaw angular velocity ω r The transfer function of

[0122] S4.4. Determine the controller K(s) to make the system stable and satisfy:

[0123]

[0124] In the formula, ξ is a very small positive number.

[0125] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those skilled in the art in the art to which the present invention belongs. It should also be understood that terms such as those defined in common dictionaries should be understood to have meanings consistent with their meanings in the context of the prior art and, unless defined as such, will not be interpreted in an idealized or overly formal sense.

[0126] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A distributed steer-by-wire vehicle stability control method, characterized in that: The following steps are involved: S1. Establish a distributed steer-by-wire vehicle dynamics model; S2. Establish a two-degree-of-freedom vehicle reference model; S3. Establishing a four-wheel steering angle distribution model for a distributed line steer-by-wire vehicle; S4. Design a distributed H∞ robust controller for yaw stability of steer-by-wire vehicles; The establishment of the yaw stability H∞ robust controller includes the following steps: S4.

1. Define the parameters in the H∞ robust controller; S4.

2. Based on the two-degree-of-freedom vehicle reference model, establish the state space expression of the vehicle yaw stability H∞ robust controller; S4.

3. Establish the expression of the input-output transfer function in the H∞ robust controller; S4.

4. Solve the controller K(s) to make the system stable and meet the preset conditions; The expression for establishing the input-output transfer function in the H∞ robust controller is specifically: Let the sensitivity function S be the closed-loop transfer function from w to y, the complementary sensitivity function T be the closed-loop transfer function from w to z0, and the input sensitivity function R be the closed-loop transfer function from w to u; The control outputs Z1, Z2, and Z3 of the system are the weighted products of e, z0, and u, respectively, namely: Where Z1=[Z 11 Z 12 ] T Indicates the system target tracking performance and interference suppression performance, Z 11 、Z 12 are the controlled outputs of the center of mass sideslip angle tracking error and the yaw angular velocity tracking error respectively; Z2=[Z 21 Z 22 ] T Indicates the robust stability and noise suppression performance of the system, Z 21 、Z 22 are the controlled outputs of the sideslip angle and yaw rate respectively; Z3=[Z 31 Z 32 ] T Indicates the size of the controller output, Z 31 、Z 32 are the controlled outputs of the additional turning angles of the front and rear wheels respectively; W1=diag{W 11 ,W 12 }、W2=diag{W 21 ,W 22 } and W3=diag{W 31 ,W 32 } represent the weighting functions of the three control performances Z1, Z2 and Z3 respectively; Let the closed-loop transfer function from w to Z be T w→Z for: The input and output of the system are expressed as: Where Z = [Z1 Z2 Z3] T Indicates the total controlled output of the system; is δ f , δ r 、F yw to β and ω r The transfer function, G 11 , G 12 , G 13 are δ f , δ r 、F yw Transfer function to the sideslip angle β, G 14 , G 15 , G 16 are δ f , δ r 、F yw to the yaw angular velocity ω r The transfer function of is Δδ f , Δδ r to β and ω r The transfer function, G 01 , G 02 Δδ f , Δδ r Transfer function to the sideslip angle β, G 03 , G 04 Δδ f , Δδ r to the yaw angular velocity ω r The transfer function of .

2. A distributed steer-by-wire vehicle stability control method according to claim 1, characterized in that: The establishment of a distributed steer-by-wire vehicle dynamics model specifically includes: Longitudinal dynamics model: Lateral dynamics model: Yaw dynamics model: Among them, for have: Where m is the vehicle mass; C D is the air resistance coefficient; A is the frontal area; v x and v y are the components of the vehicle's center of mass velocity on the x-axis and y-axis respectively; a x is the longitudinal acceleration; a y is the lateral acceleration; ω r is the yaw angular velocity of the vehicle; I z is the yaw moment of inertia of the vehicle around the z-axis; a and b are the distances from the center of mass of the vehicle to the front and rear axles, respectively; T W is half of the wheelbase; ij = fl, fr, rl, rr represent the left front wheel, right front wheel, left rear wheel and right rear wheel of the vehicle respectively; F tyij 、F txij are tire lateral force and tire longitudinal force respectively; F xij 、F yij F txij 、F tyij The longitudinal force and lateral force of each wheel decomposed and synthesized in the vehicle coordinate system; δ ij is the wheel angle; Vertical load on each wheel F zij for: Where g is the acceleration due to gravity; h is the acceleration due to gravity. g is the height of the vehicle's center of mass from the ground; Building the Magic Formula Tire Model: Y(x)=D sin{C arctan[Bx-E(Bx-arctan(Bx))]} (6) Where Y(x) is the lateral force F of the tire tyij Or the longitudinal force F txij ; x is the tire slip angle α ij Or tire slip λ ij ; B, C, D, and E are fitting parameters in the tire characteristic curve, which are stiffness factor, curve shape factor, curve peak factor, and curve curvature factor, respectively.

3. A distributed steer-by-wire vehicle stability control method according to claim 2, characterized in that: The tire slip rate of each wheel is calculated as follows: Where u ij is the wheel center speed of each wheel; w ij is the angular velocity of each wheel; r is the rolling radius of the wheel; The wheel center speed of each wheel is expressed as: The calculation of the sideslip angle of the four wheels is as follows:

4. The distributed steer-by-wire vehicle stability control method according to claim 1, characterized in that: The establishment of the two-degree-of-freedom vehicle reference model is specifically as follows: Where k f is the front wheel cornering stiffness of the reference model; k r is the rear wheel cornering stiffness of the reference model; δ f is the front wheel turning angle of the reference model; δ r is the rear wheel turning angle of the reference model; Δδ f The additional steering angle of the front wheels of the reference model; Δδ r is the additional steering angle of the rear wheels of the reference model; β is the sideslip angle of the vehicle's center of mass.

5. The distributed steer-by-wire vehicle stability control method according to claim 1, characterized in that: The establishment of the distribution line four-wheel angle distribution model for steer-by-wire vehicles is specifically as follows: Based on the steering wheel angle sensor reading, a positive steering wheel angle indicates that the vehicle is turning left; a negative steering wheel angle indicates that the vehicle is turning right; a positive steering wheel angle indicates that the wheel is rotating counterclockwise; a negative steering wheel angle indicates that the wheel is rotating clockwise; Introducing the vehicle front axle electric wheel steering judgment factor c f and rear axle electric wheel steering judgment factor c r , the expression is set as: The four-wheel steering angle distribution model is: Where L is the wheelbase of the vehicle's front and rear axles; B is the distance between the intersection of the left and right wheel kingpin axes and the ground.

6. The distributed steer-by-wire vehicle stability control method according to claim 1, characterized in that: The parameters in the H∞ robust controller are defined as follows: Select the additional turning angle Δδ of the front and rear wheels of the reference model f , Δδ r As the control quantity, that is, u=[Δδ f Δδ r ] T ; The vehicle's yaw rate ω r The vehicle's center of mass side slip angle β is the system state, that is, x=z0=[β ω r ] T ; The reference center of mass sideslip angle β d , reference pendulum angular velocity ω rd , the driver inputs the equivalent front wheel steering angle δ f and rear wheel turning angle δ r and the side wind disturbance F yw As the interference signal input of the system, that is, w=[β d ω rd δ f δ r F yw ] T The tracking errors of the sideslip angle and yaw rate are the measured output signals and also the input signals of the controller, i.e., y = e = [e1 e2] T =[β d -βω rd -ω r ] T ; z is the performance variable, also known as the controlled output, that is, z=[z 11 z 12 z 21 z 22 z 31 z 32 ] T =[β d -βω rd -ω r β ω r Δδ f Δδ r ] T ; P(s) is the generalized controlled object, that is, the transfer function matrix from input w, u to output z, y; K(s) is the controller.

7. The distributed steer-by-wire vehicle stability control method according to claim 1, characterized in that: The state space expression of the H∞ robust controller for vehicle yaw stability is specifically as follows: Where: D 22 =[0 0].

8. The distributed steer-by-wire vehicle stability control method according to claim 1, characterized in that: Solve the controller K(s) to make the system stable and meet the following preset conditions: In the formula, ξ is a very small positive number.

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