Vehicle trajectory tracking and driving stability fault-tolerant control method and device

Abstract

The invention relates to the technical field of vehicle control, in particular to a vehicle trajectory tracking and driving stability fault-tolerant control method and device, and can solve the challenges that lumped disturbance prior upper bound unknown, communication network congestion and actuator faults are difficult to cope with at the same time in the prior art to a certain extent. And the buffeting problem caused by the traditional sliding mode switching gain and the singularity problem in the solving process are solved. The method comprises the following steps: establishing a vehicle dynamics model, a control error model and a related model; designing an adaptive robust terminal sliding mode trajectory tracking controller and a stability controller; event triggering conditions are designed, and the influence of communication network congestion is reduced; and a torque optimization distribution strategy with an actuator fault factor is designed, so that the fault-tolerant capability of the system is improved. The problems of system parameter uncertainty, external disturbance, communication resource limitation, buffeting, singularity, actuator faults and the like can be effectively solved, and therefore accurate control over the intelligent vehicle is achieved under the complex driving working condition.

Description

Technical Field

[0001] The present application relates to the field of vehicle control technology, and in particular to a vehicle trajectory tracking and driving stability fault-tolerant control method and device. Background Art

[0002] With the rapid advancement of autonomous driving technology and intelligent transportation systems, vehicle trajectory tracking control and driving stability control have become the core elements for realizing autonomous driving functions, and are also a hot topic of research.

[0003] Trajectory tracking control aims to ensure that the vehicle can accurately follow the preset desired path in changing working conditions, while driving stability control is committed to ensuring that the vehicle maintains stability under extreme conditions. When facing complex driving environments, inherent challenges such as the uncertainty of vehicle system parameters, the impact of external disturbances, limited CAN communication resources, and possible failures of actuators make it particularly important to study how to achieve effective trajectory tracking control and stability control under these complex conditions. This not only has far-reaching theoretical value, but also has great practical significance.

[0004] Although existing control methods have made some progress, they often ignore the consideration of lumped disturbances with unknown upper bounds, and hardly address the controller network congestion problem caused by limited CAN communication resources. Summary of the invention

[0005] In order to solve the challenges that existing technologies are difficult to simultaneously deal with unknown upper bound lumped disturbances, communication network congestion and actuator failures, the chattering problem and the problem of solving singularities in traditional sliding mode control are overcome.

[0006] The embodiment of the present application is implemented as follows:

[0007] In a first aspect, the present application provides a vehicle trajectory tracking and driving stability fault-tolerant control method, comprising:

[0008] Establish vehicle dynamics model, control error model and related models;

[0009] Design adaptive robust terminal sliding mode trajectory tracking and stability controller;

[0010] Design event trigger conditions;

[0011] Design a torque optimization distribution strategy with actuator failure factors.

[0012] In a possible implementation, establishing the vehicle dynamics model, the control difference model and related models further includes:

[0013] Establish the longitudinal, lateral and yaw dynamic equations of the vehicle;

[0014] Build tire model;

[0015] Build a motor model;

[0016] Establish the path tracking error model and longitudinal velocity tracking error model considering lumped disturbance;

[0017] A stability control error model based on yaw rate and sideslip angle of center of mass is established.

[0018] In one possible implementation, the designing of an adaptive robust terminal sliding mode trajectory tracking and stability controller further includes:

[0019] Design the control law of the adaptive robust terminal sliding mode path tracking controller and the corresponding adaptive update law;

[0020] Design the control law of the adaptive robust terminal sliding mode longitudinal velocity tracking controller and the corresponding adaptive update law;

[0021] Design the control law of the adaptive robust terminal sliding mode stability controller based on yaw rate and the corresponding adaptive update law;

[0022] Design the control law of the adaptive robust terminal sliding mode stability controller based on the sideslip angle of the center of mass and the corresponding adaptive update law;

[0023] The total yaw moment applied to the vehicle body is obtained by combining the stability controller based on yaw rate and the stability controller based on sideslip angle of center of mass.

[0024] In a possible implementation, the design event triggering condition further includes:

[0025] Design an event-triggered mechanism for an adaptive robust terminal sliding mode path tracking controller;

[0026] Design an event-triggered mechanism for an adaptive robust terminal sliding mode longitudinal velocity tracking controller;

[0027] Design an event triggering mechanism for an adaptive robust terminal sliding mode stability controller based on yaw rate;

[0028] Design an event-triggered mechanism for an adaptive robust terminal sliding mode stability controller based on the sideslip angle of the center of mass.

[0029] In a possible implementation, the design of a torque optimization allocation strategy with actuator failure factors further includes:

[0030] A torque optimization allocation strategy with equality constraints of fault factors and physical inequality constraints of actuators is established.

[0031] In a possible implementation, the longitudinal, lateral and yaw dynamic equations of the vehicle are established as follows:

[0032]

[0033] Where m represents the vehicle mass, a x and a y are the longitudinal acceleration and lateral acceleration of the vehicle respectively; γ represents the yaw angle of the vehicle, and its first-order derivative is the yaw angular velocity ω r ;I z is the moment of inertia of the vehicle around the z-axis; F Xfl 、F Xfr 、F Xrl and F Xrr Respectively represent the longitudinal tire forces of the front left wheel, front right wheel, rear left wheel and rear right wheel; F Yfl 、F Yfr 、F Yrl and F Yrr represents the lateral tire force of the front left wheel, front right wheel, rear left wheel and rear right wheel respectively; B is the wheelbase; a and b are the distances from the center of mass of the vehicle to the front axle and rear axle respectively; δ f Indicates the front wheel turning angle.

[0034] In a possible implementation, the tire model is established, and the model is expressed as:

[0035] y=Dsin(Ctan -1 (Bx-E(Bx-tan -1 Bx)))

[0036] Among them, y can represent the tire longitudinal force or lateral force, and x represents the slip rate or sideslip angle.

[0037] The motor model is established, and its model is expressed as:

[0038]

[0039] Among them, T m and T e They are the actual output torque and theoretical output torque of the motor respectively.

[0040] In a possible implementation, the path tracking error model and the longitudinal velocity tracking error model considering the lumped disturbance are established, and the model is expressed as:

[0041]

[0042] in, is the second-order derivative of the path tracking error with respect to time; D1(t) is the lumped disturbance, δ fis the control variable of the path tracking controller; λ1 and λ2 are the weight coefficients of heading tracking and lateral error.

[0043]

[0044] in, is the first-order derivative of the longitudinal tracking error with respect to time; D2(t) is the lumped disturbance, F xd is the control variable of the longitudinal speed tracking controller, is the desired longitudinal velocity.

[0045] In a possible implementation, the stability control error models based on the yaw rate and the sideslip angle of the center of mass are established respectively, and the models are expressed as follows:

[0046]

[0047] in, is the second-order derivative of the yaw rate tracking error with respect to time; D3(t) is the lumped disturbance, M zdγ is the control variable of the stability controller based on yaw rate; ω rd is the desired yaw rate.

[0048]

[0049] in, is the second-order derivative of the center of mass sideslip angle tracking error with respect to time; D4(t) is the lumped disturbance, M zdβ is the control quantity of the stability controller based on the sideslip angle of the center of mass; β d is the desired sideslip angle of the center of mass.

[0050] In a second aspect, the present application provides a vehicle trajectory tracking and driving stability fault-tolerant control device, comprising:

[0051] Model building module, used to build vehicle dynamics model, control error model and related models;

[0052] Update law design module for designing adaptive robust terminal sliding mode trajectory tracking and stability controllers;

[0053] Condition design module, used to design event trigger conditions;

[0054] Strategy design module, used to design torque optimization distribution strategy with actuator failure factors.

[0055] The technical solution provided by this application can at least achieve the following beneficial effects:

[0056] This application overcomes the problem of requiring a priori knowledge of the upper bound of disturbance in existing methods by proposing an adaptive update law, and can effectively overcome the negative effects of system parameter uncertainty and external disturbances during vehicle driving.

[0057] This application proposes an event triggering mechanism, which can effectively reduce the communication burden and save the CAN communication resources of the whole vehicle without significantly affecting the control performance.

[0058] This application introduces fault factors into the torque optimization distribution strategy to achieve vehicle fault-tolerant control when the actuator fails. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0060] Figure 1 It is a flow chart of a vehicle trajectory tracking and driving stability fault-tolerant control method shown in an exemplary embodiment of the present application;

[0061] Figure 2 It is a schematic diagram of a specific implementation process of a vehicle trajectory tracking and driving stability fault-tolerant control method shown in an exemplary embodiment of the present application;

[0062] Figure 3 It is a structural schematic diagram of a vehicle trajectory tracking and driving stability fault-tolerant control device shown in an exemplary embodiment of the present application.

[0063] Attached mark:

[0064] 1. Model building module; 2. Update law design module; 3. Condition design module; 4. Strategy design module. DETAILED DESCRIPTION

[0065] In order to make the purpose, implementation mode and advantages of the present application clearer, the exemplary implementation mode of the present application will be clearly and completely described below in conjunction with the drawings in the exemplary embodiments of the present application. Obviously, the described exemplary embodiments are only part of the embodiments of the present application, not all of the embodiments. It should be understood that the specific embodiments described here are only used to explain the present application and are not used to limit the present application.

[0066] It should be noted that the brief description of terms in this application is only for the convenience of understanding the embodiments described below, and is not intended to limit the embodiments of this application. Unless otherwise specified, these terms should be understood according to their ordinary and common meanings.

[0067] The terms "first", "second", "third", etc. in the specification and claims of this application and the above drawings are used to distinguish similar or similar objects or entities, and do not necessarily mean to limit a specific order or sequence, unless otherwise noted. It should be understood that the terms used in this way can be interchangeable under appropriate circumstances.

[0068] The terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover but not exclude inclusion, for example, a product or device comprising a list of components is not necessarily limited to all the components expressly listed but may include other components not expressly listed or inherent to such product or device.

[0069] Before explaining the vehicle trajectory tracking and driving stability fault-tolerant control method provided in the embodiment of the present application, the application scenario and implementation environment of the embodiment of the present application are first introduced.

[0070] With the rapid advancement of autonomous driving technology and intelligent transportation systems, vehicle trajectory tracking control and driving stability control have become the core elements for realizing autonomous driving functions, and are also a hot topic of research.

[0071] Trajectory tracking control aims to ensure that the vehicle can accurately follow the preset desired path in changing working conditions, while driving stability control is committed to ensuring that the vehicle maintains stability under extreme conditions. When facing complex driving environments, inherent challenges such as the uncertainty of vehicle system parameters, the impact of external disturbances, limited CAN communication resources, and possible failures of actuators make it particularly important to study how to achieve effective trajectory tracking control and stability control under these complex conditions. This not only has far-reaching theoretical value, but also has great practical significance.

[0072] Although existing control methods have made some progress, they often ignore the consideration of lumped disturbances with unknown upper bounds, and hardly address the controller network congestion problem caused by limited CAN communication resources.

[0073] Based on this, the present application provides a method and device for fault-tolerant control of vehicle trajectory tracking and driving stability. By establishing a vehicle dynamics model, a control error model and related models, an adaptive robust terminal sliding mode trajectory tracking controller and a stability controller are designed, and event triggering conditions are optimized to reduce the impact of communication network congestion. A torque optimization allocation strategy that considers actuator failures is introduced, thereby significantly improving the fault tolerance of the system. This innovative solution effectively solves the challenge that existing technologies are difficult to simultaneously cope with unknown upper bound lumped disturbances, communication network congestion and actuator failures, while overcoming the jitter problem and singularity solution problem in traditional sliding mode control. It ensures precise control of intelligent vehicles under complex driving conditions and improves the reliability and safety of the system.

[0074] Next, the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems will be described in detail through embodiments and in combination with the accompanying drawings. The embodiments may be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. Obviously, the described embodiments are part of the embodiments of the present application, not all of them.

[0075] Figure 1 It is a flow chart of a vehicle trajectory tracking and driving stability fault-tolerant control method shown in an exemplary embodiment of the present application.

[0076] In an exemplary embodiment, Figure 1 As shown, a vehicle trajectory tracking and driving stability fault-tolerant control method is provided. In this embodiment, the method may include the following steps:

[0077] Step 1: Establish vehicle dynamics model, control error model and related models.

[0078] Step 2: Design an adaptive robust terminal sliding mode trajectory tracking and stability controller.

[0079] Step 3: Design event trigger conditions.

[0080] Step 4: Design a torque optimization allocation strategy with actuator failure factors.

[0081] Figure 2 It is a schematic diagram of the specific implementation process of the vehicle trajectory tracking and driving stability fault-tolerant control method shown in an exemplary embodiment of the present application.

[0082] In one possible implementation, Figure 2 As shown, the specific implementation process of the vehicle trajectory tracking and driving stability fault-tolerant control method is as follows:

[0083] Step 1: Establish vehicle dynamics model, control error model and related models.

[0084] Wherein, step 1 includes steps S11 to S15:

[0085] Step S11: Establishing the longitudinal, lateral and yaw dynamic equations of the vehicle to describe the motion state of the vehicle when in motion:

[0086]

[0087] Where m represents the vehicle mass, a x and a y are the longitudinal acceleration and lateral acceleration of the vehicle respectively; γ represents the yaw angle of the vehicle, and its first-order derivative is the yaw angular velocity ω r ;I z is the moment of inertia of the vehicle around the z-axis; F Xfl 、F Xfr 、F Xrl and F Xrr Respectively represent the longitudinal tire forces of the front left wheel, front right wheel, rear left wheel and rear right wheel; F Yfl 、F Yfr 、F Yrl and F Yrr represents the lateral tire force of the front left wheel, front right wheel, rear left wheel and rear right wheel respectively; B is the wheelbase; a and b are the distances from the center of mass of the vehicle to the front axle and rear axle respectively; δ f Indicates the front wheel turning angle.

[0088] S12: Establish a tire model to describe nonlinear tire forces:

[0089] y=Dsin(Ctan -1 (Bx-E(Bx-tan -1 Bx)));

[0090] Among them, y can represent the tire longitudinal force or lateral force, and x represents the slip rate or sideslip angle.

[0091] S13: Establish a motor model to describe the relationship between the actual output torque and the theoretical output torque of the motor:

[0092]

[0093] Among them, T m and T e They are the actual output torque and theoretical output torque of the motor respectively.

[0094] S14: Establish the path tracking error model and longitudinal velocity tracking error model considering the lumped disturbance:

[0095]

[0096] in, is the second-order derivative of the path tracking error with respect to time; D1(t) is the lumped disturbance, δ f is the control variable of the path tracking controller; λ1 and λ2 are the weight coefficients of heading tracking and lateral error.

[0097]

[0098] in, is the first-order derivative of the longitudinal tracking error with respect to time; D2(t) is the lumped disturbance, F xd is the control variable of the longitudinal speed tracking controller, is the desired longitudinal velocity.

[0099] S15: Establish stability control error models based on yaw rate and center of mass sideslip angle respectively:

[0100]

[0101] in, is the second-order derivative of the yaw rate tracking error with respect to time; D3(t) is the lumped disturbance, M zdγ is the control variable of the stability controller based on yaw rate; ω rd is the desired yaw rate.

[0102]

[0103] in, is the second-order derivative of the center of mass sideslip angle tracking error with respect to time; D4(t) is the lumped disturbance, M zdβ is the control quantity of the stability controller based on the sideslip angle of the center of mass; β d is the desired sideslip angle of the center of mass.

[0104] Step 2: Design an adaptive robust terminal sliding mode trajectory tracking controller and a stability controller. Step 2 includes steps S21 to S25:

[0105] Step S21: First, select the non-singular fast terminal sliding surface and approach rate, then bring the path tracking error model in S14 into the sliding surface and approach rate, calculate the equivalent control law and switching control law of the front wheel angle respectively, and design the adaptive update law corresponding to the controller:

[0106]

[0107] Among them, s p is the sliding surface, τ 11 and τ 12 are all constants greater than zero, 1 <r 12 <2, r 11 >r 12, k1>0 is the switching gain, ε1>0 is a small positive constant, and are the estimated gains corresponding to the uncertain parameters θ0, θ1 and θ2 respectively.

[0108]

[0109] Wherein, Υ0, Υ1 and Υ2 are constants greater than zero.

[0110] S22: First, the non-singular fast terminal sliding surface and approach rate are selected. Then, the longitudinal velocity tracking error model in S14 is introduced into the sliding surface and approach rate. The equivalent control law and switching control law of the longitudinal demand force are calculated respectively, and the adaptive update law corresponding to the controller is designed:

[0111]

[0112] in, is the sliding surface, τ 21 and τ 22 are all normal numbers, 1 <r 21 <2, r 21 >r 22 , k2>0 is the switching gain, ε2>0 is a small positive constant, and are the estimated gains corresponding to the uncertain parameters θ0, θ1 and θ2 respectively.

[0113]

[0114] Wherein, R0, R1 and R2 are constants greater than zero.

[0115] S23: First, select the non-singular fast terminal sliding surface and approach rate. Then, bring the stability control error model based on yaw rate in S15 into the sliding surface and approach rate. Calculate the equivalent control law and switching control law of the yaw moment based on yaw rate respectively, and design the adaptive update law corresponding to the controller:

[0116]

[0117] Among them, s γ is the sliding surface, τ 31 and τ 32 are all normal numbers, 1 <r 31 <2, r 31 >r 32 , k3>0 is the switching gain, ε3>0 is a small positive constant, and The uncertain parameters are and The corresponding estimated gain.

[0118]

[0119] Where Γ0, Γ1 and Γ2 are constants greater than zero.

[0120] S24: First, select the non-singular fast terminal sliding surface and approach rate. Then, bring the stability control error model based on the sideslip angle of the center of mass in S15 into the sliding surface and approach rate. Calculate the equivalent control law and switching control law of the yaw moment based on the sideslip angle of the center of mass, and design the adaptive update law corresponding to the controller:

[0121]

[0122] Among them, s β is the sliding surface, τ 41 and τ 42 are all normal numbers, 1 <r 41 <2, r 41 >r 42 , k4>0 is the switching gain, ε4>0 is a small positive constant, and are the estimated gains corresponding to the uncertain parameters σ0, σ1 and σ2 respectively.

[0123]

[0124] Wherein, Ω0, Ω1 and Ω2 are constants greater than zero.

[0125] S25: Combining the stability controller based on yaw rate and the stability controller based on the sideslip angle of the center of mass, the total yaw moment applied to the vehicle body is:

[0126] M zd =η1M zdγ +η2M zdβ ;

[0127] Where η1 and η2 are weight coefficients.

[0128] Step 3: Sampling information at a fixed period may cause unnecessary information transmission and may also aggravate network congestion, thereby triggering network saturation caused by network bandwidth limitations. This saturation state may eventually lead to network-induced delays and affect system performance. In order to effectively alleviate these network congestion problems, the following event trigger conditions are designed to reduce network load and improve overall communication efficiency.

[0129] S31: Design of an event-triggered mechanism for an adaptive robust terminal sliding mode path tracking controller:

[0130]

[0131] Where v1(t) = δ f|ETC (t)-δ f (t k ), 0<φ1<1, χ1 is a normal number.

[0132] S32: Design of event triggering mechanism for adaptive robust terminal sliding mode longitudinal velocity tracking controller:

[0133]

[0134] Where v2(t) = F xd∣ETC (t)-F xd (t k ), 0<φ2<1, χ2 is a normal number.

[0135] S33: Design of an event-triggered mechanism for an adaptive robust terminal sliding mode stability controller based on yaw rate:

[0136]

[0137] Where, v3(t) = M zdγ∣ETC (t)-M zdγ (t k ), 0<φ3<1, χ3 is a normal number.

[0138] S34: Design of an event triggering mechanism for an adaptive robust terminal sliding mode stability controller based on the sideslip angle of the center of mass:

[0139]

[0140] Where, v4(t) = M zdβ∣ETC (t)-M zdβ (t k ), 0<φ4<1, χ4 is a normal number.

[0141] Step 4: Design a torque optimization allocation strategy with actuator failure factors:

[0142]

[0143] Among them, k ij is the actuator failure factor, R e is the effective radius, F zij is the vertical load, T dmax The maximum torque that the actuator can provide.

[0144] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the instructions, these steps are not necessarily executed in sequence according to the order of the instructions. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the above-mentioned embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the steps or stages in other steps.

[0145] Corresponding to the above-mentioned embodiments of the vehicle trajectory tracking and driving stability fault-tolerant control method, the present application also provides embodiments of the vehicle trajectory tracking and driving stability fault-tolerant control device by adopting the same technical concept.

[0146] Figure 3 It is a structural schematic diagram of a vehicle trajectory tracking and driving stability fault-tolerant control device shown in an exemplary embodiment of the present application.

[0147] In an exemplary embodiment, Figure 3 As shown, the vehicle trajectory tracking and driving stability fault-tolerant control device includes:

[0148] The model building module 1 is used to build a vehicle dynamics model, a control error model and related models.

[0149] Update law design module 2 is used to design adaptive robust terminal sliding mode trajectory tracking and stability controller.

[0150] The condition design module 3 is used to design event triggering conditions.

[0151] The strategy design module 4 is used to design a torque optimization distribution strategy with actuator failure factors.

[0152] For the specific definition of the vehicle trajectory tracking and driving stability fault-tolerant control device, please refer to the definition of the vehicle trajectory tracking and driving stability fault-tolerant control method above, which will not be repeated here. The various modules in the above-mentioned vehicle trajectory tracking and driving stability fault-tolerant control device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0153] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0154] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A vehicle trajectory tracking and driving stability fault-tolerant control method, characterized in that: include: Establish vehicle dynamics model, control error model and related models; Design adaptive robust terminal sliding mode trajectory tracking and stability controller; Design event trigger conditions; Design a torque optimization distribution strategy with actuator failure factors.

2. The vehicle trajectory tracking and driving stability fault-tolerant control method according to claim 1, characterized in that: The establishing of the vehicle dynamics model, the control difference model and related models further includes: Establish the longitudinal, lateral and yaw dynamic equations of the vehicle; Build tire model; Build a motor model; Establish the path tracking error model and longitudinal velocity tracking error model considering lumped disturbance; A stability control error model based on yaw rate and sideslip angle of center of mass is established.

3. The vehicle trajectory tracking and driving stability fault-tolerant control method according to claim 1, characterized in that: The design of an adaptive robust terminal sliding mode trajectory tracking and stability controller further comprises: Design the control law of the adaptive robust terminal sliding mode path tracking controller and the corresponding adaptive update law; Design the control law of the adaptive robust terminal sliding mode longitudinal velocity tracking controller and the corresponding adaptive update law; Design the control law of the adaptive robust terminal sliding mode stability controller based on yaw rate and the corresponding adaptive update law; Design the control law of the adaptive robust terminal sliding mode stability controller based on the sideslip angle of the center of mass and the corresponding adaptive update law; The total yaw moment applied to the vehicle body is obtained by combining the stability controller based on yaw rate and the stability controller based on sideslip angle of center of mass.

4. The vehicle trajectory tracking and driving stability fault-tolerant control method according to claim 1, characterized in that: The design event triggering condition further includes: Design an event-triggered mechanism for an adaptive robust terminal sliding mode path tracking controller; Design an event-triggered mechanism for an adaptive robust terminal sliding mode longitudinal velocity tracking controller; Design an event triggering mechanism for an adaptive robust terminal sliding mode stability controller based on yaw rate; Design an event-triggered mechanism for an adaptive robust terminal sliding mode stability controller based on the sideslip angle of the center of mass.

5. The vehicle trajectory tracking and driving stability fault-tolerant control method according to claim 1, characterized in that: The design of the torque optimization allocation strategy with actuator failure factors further includes: A torque optimization allocation strategy with equality constraints of fault factors and physical inequality constraints of actuators is established.

6. The vehicle trajectory tracking and driving stability fault-tolerant control method according to claim 2, characterized in that: The longitudinal, lateral and yaw dynamic equations of the vehicle are established as follows: Where m represents the vehicle mass, a x and a y are the longitudinal acceleration and lateral acceleration of the vehicle respectively; γ represents the yaw angle of the vehicle, and its first-order derivative is the yaw angular velocity ω r ;I z is the moment of inertia of the vehicle around the z-axis; F Xfl 、F Xfr 、F Xrl and F Xrr Respectively represent the longitudinal tire forces of the front left wheel, front right wheel, rear left wheel and rear right wheel; F Yfl 、F Yfr 、F Yrl and F Yrr represents the lateral tire force of the front left wheel, front right wheel, rear left wheel and rear right wheel respectively; B is the wheelbase; a and b are the distances from the center of mass of the vehicle to the front axle and rear axle respectively; δ f Indicates the front wheel turning angle.

7. The vehicle trajectory tracking and driving stability fault-tolerant control method according to claim 2, characterized in that: The tire model is established, and its model is expressed as: y=Dsin(Ctan -1 (Bx-E(Bx-tan -1 Bx))) Among them, y can represent the tire longitudinal force or lateral force, and x represents the slip rate or sideslip angle. The motor model is established, and its model is expressed as: Among them, T m and T e They are the actual output torque and theoretical output torque of the motor respectively.

8. The vehicle trajectory tracking and driving stability fault-tolerant control method according to claim 2, characterized in that: The path tracking error model and longitudinal velocity tracking error model considering the lumped disturbance are established, and the model is expressed as follows: in, is the second-order derivative of the path tracking error with respect to time; D1(t) is the lumped disturbance, δ f is the control variable of the path tracking controller; λ1 and λ2 are the weight coefficients of heading tracking and lateral error. in, is the first-order derivative of the longitudinal tracking error with respect to time; D2(t) is the lumped disturbance, F xd is the control variable of the longitudinal speed tracking controller, is the desired longitudinal velocity.

9. The vehicle trajectory tracking and driving stability fault-tolerant control method according to claim 2, characterized in that: The stability control error models based on yaw rate and center of mass sideslip angle are established respectively, and the models are expressed as follows: in, is the second-order derivative of the yaw rate tracking error with respect to time; D3(t) is the lumped disturbance, M zdγ is the control variable of the stability controller based on yaw rate; ω rd is the desired yaw rate. in, is the second-order derivative of the center of mass sideslip angle tracking error with respect to time; D4(t) is the lumped disturbance, M zdβ is the control quantity of the stability controller based on the sideslip angle of the center of mass; β d is the desired sideslip angle of the center of mass.

10. A vehicle trajectory tracking and driving stability fault-tolerant control device, characterized in that: include: Model building module, used to build vehicle dynamics model, control error model and related models; Update law design module for designing adaptive robust terminal sliding mode trajectory tracking and stability controllers; Condition design module, used to design event trigger conditions; Strategy design module, used to design torque optimization distribution strategy with actuator failure factors.

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