A differential steering fault-tolerant control method and system based on active disturbance rejection

Abstract

The application provides a differential steering fault-tolerant control method and system based on active disturbance rejection, which comprises the following steps: acquiring a vehicle reference yaw angle, an actual yaw angle, a reference front wheel steering angle and an actual front wheel steering angle; obtaining an additional yaw moment by using an active disturbance rejection yaw angle control method according to the vehicle reference yaw angle and the actual yaw angle; obtaining a differential moment by using an active disturbance rejection steering angle control method according to the vehicle reference front wheel steering angle and the actual front wheel steering angle; acquiring a required longitudinal driving force of the vehicle; determining the torque of each wheel based on a torque distribution method of optimal tire load rate according to the additional yaw moment, the differential moment and the required longitudinal driving force of the vehicle; and controlling the vehicle to realize lateral motion according to the torque of each wheel. According to the scheme provided in the application, front wheel steering and vehicle lateral control are realized by using the difference between the longitudinal forces of left and right wheels, so that the safety and reliability of vehicle driving can be improved.

Description

Technical Field

[0001] The present application relates to the field of automobile control technology, and in particular to a differential steering fault-tolerant control method and system based on auto-disturbance rejection. Background Art

[0002] As a vehicle's lateral control system, steer-by-wire systems offer advantages such as high control precision and rapid response, significantly improving vehicle handling performance and providing a foundation for the development of autonomous driving. However, because steer-by-wire systems rely on electronic signals and electronically controlled components for steering control, a system failure could render the driver unable to control the vehicle's steering through traditional mechanical connections. This could potentially cause the vehicle to stray from its lane, collide, or cause serious accidents, posing a significant threat to driving safety.

[0003] An effective strategy for dealing with steer-by-wire failure is to independently control the four-wheel drive braking force to achieve differential steering. On the one hand, the ground-driven braking force of the left and right wheels generates a differential torque around the kingpin that drives the steering trapezoid, enabling vehicle steering. On the other hand, the ground-driven braking force of the left and right wheels generates an additional yaw moment around the vehicle's center of mass, controlling the vehicle's lateral motion. Therefore, differential steering can be considered a backup steering system in the event of a steer-by-wire system failure, improving the vehicle's fault tolerance.

[0004] Currently, the main methods for differential steering control after a steering system failure include PID, SMC, LQR, and MPC. PID is an error-based, model-free control method with a simple structure and convenient design, but poor robustness. SMC, LQR, and MPC all have a certain degree of robustness to system uncertainties and unknown multi-source disturbances, but SMC suffers from high-frequency chattering and requires high model accuracy. LQR is primarily applicable to linear systems and requires solving the Riccati equation, which is computationally complex. MPC requires real-time optimization solutions, which places high demands on computing resources, and the uncertainty of the system model can affect the control effect. Therefore, a robust differential steering fault-tolerant control method that does not rely on an accurate model is urgently needed. Summary of the Invention

[0005] In response to the above-mentioned technical problems that need to be solved, the present application provides a differential steering fault-tolerant control method and system based on self-disturbance rejection, which does not rely on an accurate model and has strong robustness, and can improve the lateral control capability after the wire-controlled steering fails.

[0006] To achieve the above objectives, the first embodiment of the present application proposes a differential steering fault-tolerant control method based on active disturbance rejection, comprising:

[0007] Obtaining the vehicle's reference yaw angle, actual yaw angle, reference front wheel steering angle, and actual front wheel steering angle;

[0008] According to the reference yaw angle and the actual yaw angle of the vehicle, an additional yaw moment is obtained by using a self-disturbance rejection yaw angle control method;

[0009] According to the reference front wheel steering angle and the actual front wheel steering angle of the vehicle, a differential moment is obtained by using a self-disturbance rejection steering angle control method;

[0010] Obtaining a required longitudinal driving force of the vehicle;

[0011] According to the additional yaw moment, the differential moment and the required longitudinal driving force of the vehicle, each wheel torque is determined based on a torque distribution method optimized according to tire load rate;

[0012] According to the each wheel torque, the vehicle is controlled to realize lateral motion.

[0013] Optionally, the additional yaw moment obtained according to the reference yaw angle and the actual yaw angle of the vehicle by using the self-disturbance rejection yaw angle control method comprises:

[0014] A vehicle yaw dynamics model is constructed and written in an integral series form;

[0015] A first differential tracker is constructed according to the reference yaw angle, the reference yaw angle is smoothed by the first differential tracker, a smoothed reference yaw angle and a first derivative of the reference yaw angle are obtained;

[0016] A first extended state observer is constructed according to the actual yaw angle of the vehicle at the current time and the additional yaw moment at the previous time, the actual yaw angle at the current time, a first derivative of the actual yaw angle, a first unknown model dynamic and an unknown multi-source disturbance are estimated in real time by the first extended state observer;

[0017] A first nonlinear feedback control law is constructed in combination with the estimation result of the first extended state observer, the additional yaw moment at the current time is obtained according to the first nonlinear feedback control law.

[0018] Optionally, the vehicle yaw dynamics model is constructed and written in the integral series form, comprising:

[0019] The vehicle yaw dynamics model is constructed, and a specific formula is as follows:

[0020]

[0021] In the formula, r is a vehicle yaw angle, v x is a vehicle longitudinal speed, v y is a vehicle lateral speed, δ f is a front wheel steering angle, ΔM is an additional yaw moment, d1 is a first unknown multi-source disturbance, C fis the cornering stiffness of the front tire, C r is the cornering stiffness of the rear tire, l f is the distance from the vehicle's center of mass to the front axle, l r is the distance between the vehicle's center of mass and the rear axle, I z is the moment of inertia of the vehicle around the z-axis;

[0022] The constructed vehicle yaw dynamics model is written in the form of an integral series type, and the specific formula is as follows:

[0023]

[0024] Where, y1=r, u1=ΔM,

[0025] Optionally, the first differential tracker is constructed as follows:

[0026]

[0027] Where r1(k+1) is the smooth reference yaw angle at the k+1th moment, r2(k+1) is the first-order differential of the smooth reference yaw angle at the k+1th moment, r1(k) is the smooth reference yaw angle at the kth moment, r2(k) is the first-order differential of the smooth reference yaw angle at the kth moment, and r d (k) is the reference yaw angle at the kth moment, h1 is the sampling period, λ1 is the parameter that determines the tracking speed, and fst(*) function is the fastest control comprehensive function;

[0028] The first extended state observer is constructed as follows:

[0029]

[0030] Where z1 is the estimated value of the actual yaw angle, z2 is the estimated value of the first-order derivative of the actual yaw angle, z3 is the estimated value of the first unmodeled dynamics and disturbance, and e 01 is the actual yaw angle estimation error, fal(*) function is the fastest control comprehensive function, β 01 ,β 02 ,β 03 ,α 01 ,α 02 ,κ1 are the first extended state observer parameters;

[0031] The mathematical equation of the first nonlinear feedback control law is:

[0032] u1=β1fal(e1,α1,λ2)+β2fal(e2,α2,λ2)+b1z3

[0033] Where e1 is the actual yaw angle tracking error and e1 = r1 - z1, e2 is the actual yaw angle first-order derivative tracking error and e2 = r2 - z2, β1, β2, α1, α2, λ2 are all parameters of the first nonlinear feedback control law.

[0034] Optionally, obtaining the differential torque by adopting an active disturbance rejection steering angle control method according to the reference front wheel steering angle and the actual front wheel steering angle of the vehicle includes:

[0035] Construct an equivalent dynamic model of the steer-by-wire actuator system and write it in the form of an integral series type;

[0036] constructing a second differential tracker according to the reference front wheel steering angle, and smoothing the reference front wheel steering angle by the second differential tracker to obtain a smoothed reference front wheel steering angle and a first-order derivative of the reference front wheel steering angle;

[0037] constructing a second extended state observer based on the actual front wheel steering angle at the current moment and the differential torque at the previous moment, and estimating the actual front wheel steering angle at the current moment, the first-order derivative of the front wheel steering angle, the second unmodeled dynamics, and the unknown multi-source disturbance in real time through the second extended state observer;

[0038] A second nonlinear feedback control law is constructed in combination with the estimation result of the second extended state observer, and the differential torque at the current moment is obtained according to the second nonlinear feedback control law.

[0039] Optionally, constructing an equivalent dynamic model of the steer-by-wire execution system and writing it in an integral series form includes:

[0040] Construct an equivalent dynamic model of the wire-controlled steering execution system. The specific formula is as follows:

[0041]

[0042] Among them, δ f is the vehicle front wheel steering angle, ΔM z is the differential torque, T s Represents the equivalent torque output by the steering motor. When the wire-controlled steering system fails completely, T s =0; τ z is the sum of the positive moments of the left and right front wheels, τ f represents the friction torque of the steering actuator, d2 is the second unknown multi-source disturbance, J eq and B eq are the equivalent moment of inertia and equivalent damping of the steering actuator respectively;

[0043] The equivalent dynamic model of the constructed steer-by-wire execution system is written in the form of an integral series type, and the specific formula is as follows:

[0044]

[0045] wherein y2 = δ f , u2 = AM z ,

[0046] Optionally, the second derivative tracker is configured as:

[0047]

[0048] wherein r3(k+1) is the smoothed reference front wheel steering angle at the k+1 time, r4(k+1) is the first derivative of the smoothed reference front wheel steering angle at the k+1 time, r3(k) is the smoothed reference front wheel steering angle at the k time, r4(k) is the first derivative of the smoothed reference front wheel steering angle at the k time, δ fd (k) is the reference front wheel steering angle at the k time, h2 is the sampling period of the second derivative tracker, and λ3 is a parameter in the second derivative tracker that determines the speed of tracking;

[0049] The second extended state observer is configured as:

[0050]

[0051] wherein z4 is the estimated value of the actual front wheel steering angle, z5 is the estimated value of the first derivative of the actual front wheel steering angle, z6 is the estimated value of the un-modeled dynamics and unknown multi-source disturbance, e 02 is the estimation error of the actual front wheel steering angle, β 04 , β 05 , β 06 , α 03 , α 04 , κ2 are all parameters of the second extended state observer;

[0052] The mathematical equation of the second nonlinear feedback control law is:

[0053] u2 = β3fal(e3, α3, λ4) + β4fal(e4, α4, λ4) + b2z6

[0054] wherein e3 is the tracking error of the actual front wheel steering angle and e3 = r3 - z4, e4 is the tracking error of the first derivative of the actual front wheel steering angle and e4 = r4 - z5, β3, β4, α3, α4, λ4 are all parameters of the second nonlinear feedback control law.

[0055] Optionally, the method for determining the torque of each wheel based on the optimal torque distribution method of the tire load rate according to the additional yaw moment, the differential moment, and the required longitudinal driving force of the vehicle comprises:

[0056] constructing a vehicle longitudinal force constraint objective function according to the additional yaw moment, the differential torque, and the required longitudinal driving force of the vehicle, based on the maximum output torque of the vehicle's driving and braking motors and road adhesion conditions;

[0057] The active set method is used to solve the longitudinal force constraint objective function of the electric vehicle to determine the current torque of each wheel of the vehicle.

[0058] Optionally, the specific formula of the vehicle longitudinal force constraint objective function is:

[0059]

[0060] The constraints are:

[0061]

[0062] Among them, F xeq is the longitudinal driving force required for the vehicle, F xfl ,F xrl ,F xfr ,F xrr are the longitudinal forces of the left front wheel, left rear wheel, right front wheel, and right rear wheel of the vehicle, respectively, and F zfl ,F zrl ,F zfr ,F zrr are the vertical forces of the left front wheel, left rear wheel, right front wheel, and right rear wheel of the vehicle respectively, μ is the road adhesion coefficient, l w is the vehicle wheelbase, r w is the equivalent radius of the tire, T max is the maximum output torque of the vehicle driving brake motor, r σ The kingpin offset, τ is the kingpin caster angle, σ is the kingpin inclination angle, c ij Used to adjust the weight coefficient of the wheel longitudinal force in the optimization objective function.

[0063] To achieve the above objectives, a second embodiment of the present application proposes a differential steering fault-tolerant control system based on active disturbance rejection, comprising:

[0064] A first acquisition module is used to acquire a reference yaw angle, an actual yaw angle, a reference front wheel steering angle, and an actual front wheel steering angle of the vehicle;

[0065] a yaw angle control module, configured to obtain an additional yaw moment by adopting an active disturbance rejection yaw angle control method according to the reference yaw angle and the actual yaw angle of the vehicle;

[0066] a steering angle control module, configured to obtain a differential torque by adopting an active disturbance rejection steering angle control method according to the reference front wheel steering angle and the actual front wheel steering angle of the vehicle;

[0067] A second acquisition module is used to obtain the longitudinal driving force required by the vehicle;

[0068] a wheel torque distribution module, configured to determine the torque of each wheel based on a torque distribution method with an optimal tire load rate according to the additional yaw moment, the differential torque, and the required longitudinal driving force of the vehicle;

[0069] The driving module is used to control the vehicle to achieve lateral movement according to the torque of each wheel.

[0070] The technical solutions provided by the embodiments of this application bring at least the following beneficial effects:

[0071] First, the present application provides a differential steering fault-tolerant control method and system based on active disturbance rejection. The active disturbance rejection control method not only ensures the smoothness of the reference signal and the stability of the control output, thereby improving the dynamic performance of the system, but also effectively copes with model uncertainty and unknown multi-source disturbances by estimating and compensating the total disturbance of the system in real time, thereby reducing dependence on the system model and improving the robustness of the system.

[0072] Second, the present application provides a differential steering fault-tolerant control method and system based on ADRC, which controls the yaw angle and steering angle respectively through two parallel ADRC controllers, thereby achieving decoupling of the two. This can effectively reduce the dimension of the control system, has a simple structure, is easy to implement, and broadens the application scope of ADRC.

[0073] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0075] Figure 1 is a flow chart of a differential steering fault-tolerant control method based on active disturbance rejection according to an embodiment of the present application;

[0076] Figure 2 is a flow chart of an active disturbance rejection yaw angle control method according to an embodiment of the present application;

[0077] Figure 3 is a flow chart of an active disturbance rejection steering angle control method according to an embodiment of the present application;

[0078] Figure 4 It is a block diagram of a differential steering fault-tolerant control system based on active disturbance rejection according to an embodiment of the present application. DETAILED DESCRIPTION

[0079] The following describes in detail embodiments of the present application. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0080] The purpose of the present invention is to provide a differential steering fault-tolerant control method and system based on active disturbance rejection, which utilizes the unequal longitudinal forces of the left and right wheels to achieve front wheel steering and vehicle lateral control, thereby improving the safety and reliability of vehicle driving.

[0081] The following describes a differential steering fault-tolerant control method and system based on active disturbance rejection according to an embodiment of the present application with reference to the accompanying drawings.

[0082] Figure 1 FIG. 1 is a flow chart of a differential steering fault-tolerant control method based on active disturbance rejection according to an embodiment of the present application. Figure 1 As shown, the method includes the following steps:

[0083] Step 101: Obtain a reference yaw angle, an actual yaw angle, a reference front wheel steering angle, and an actual front wheel steering angle of the vehicle.

[0084] The reference yaw angle refers to the yaw angle that the vehicle control system expects to achieve. It is usually calculated based on the driver's actions (such as steering input), the vehicle's state (such as speed) and other factors (such as road conditions); the actual yaw angle refers to the actual yaw angle of the vehicle, that is, the angle between the vehicle's longitudinal axis and the reference direction, usually measured by sensors installed on the vehicle; the reference front wheel steering angle refers to the front wheel steering angle expected by the vehicle control system, which is calculated based on the driver's steering input or other control strategies; the actual front wheel steering angle refers to the actual steering angle of the front wheels, usually measured by sensors installed on the steering mechanism.

[0085] In the embodiment of the present application, there is no limitation on the method for obtaining the above-mentioned vehicle reference yaw angle, actual yaw angle, reference front wheel steering angle and actual front wheel steering angle.

[0086] Step 102 : According to the reference yaw angle and the actual yaw angle of the vehicle, an active disturbance rejection yaw angle control method is used to obtain an additional yaw moment.

[0087] Figure 2 FIG. 1 is a flow chart of an active disturbance rejection yaw angle control method according to an embodiment of the present application. Figure 2 As shown, in the embodiment of the present application, step 102 specifically includes:

[0088] Step 201 : construct a vehicle yaw dynamics model and write it in an integral series form.

[0089] In order to facilitate analysis and control design, the constructed vehicle yaw dynamics model is written in the form of an integral series model, which can clearly represent the changes in vehicle status over time.

[0090] First, the vehicle yaw dynamics model is constructed, and its specific formula is as follows:

[0091]

[0092] Where r is the vehicle yaw angle, v x is the vehicle longitudinal velocity, v y is the vehicle lateral velocity, δ f is the front wheel steering angle, ΔM is the additional yaw moment, d1 is the first unknown multi-source disturbance, C f is the cornering stiffness of the front tire, C r is the cornering stiffness of the rear tire, l f is the distance from the vehicle's center of mass to the front axle, l r is the distance between the vehicle's center of mass and the rear axle, I z is the moment of inertia of the vehicle around the z-axis.

[0093] Then, the constructed vehicle yaw dynamics model is written in the form of an integral series type. The specific formula is as follows:

[0094]

[0095] Where, y1=r, u1=ΔM,

[0096] Step 202 : construct a first differential tracker based on the reference yaw angle, and smooth the reference yaw angle using the first differential tracker to obtain a smoothed reference yaw angle and a first-order derivative of the reference yaw angle.

[0097] In the embodiment of the present application, the first differential tracker is constructed as follows:

[0098]

[0099] Where r1(k+1) is the smooth reference yaw angle at the k+1th moment, r2(k+1) is the first-order differential of the smooth reference yaw angle at the k+1th moment, r1(k) is the smooth reference yaw angle at the kth moment, r2(k) is the first-order differential of the smooth reference yaw angle at the kth moment, and r d (k) is the reference yaw angle at the kth moment, h1 is the sampling period, λ1 is the parameter that determines the tracking speed, and fst(*) function is the fastest control comprehensive function.

[0100] In step 203, a first extended state observer is constructed based on the actual yaw angle of the vehicle at the current moment and the additional yaw torque at the previous moment. The first extended state observer is used to estimate the actual yaw angle at the current moment, the first-order derivative of the actual yaw angle, the first unmodeled dynamics, and the unknown multi-source disturbances in real time.

[0101] In the embodiment of the present application, the first extended state observer is constructed as follows:

[0102]

[0103] Where z1 is the estimated value of the actual yaw angle, z2 is the estimated value of the first-order derivative of the actual yaw angle, z3 is the estimated value of the first unmodeled dynamics and disturbance, and e 01 is the actual yaw angle estimation error, fal(*) function is the fastest control comprehensive function, β 01 ,β 02 ,β 03 ,α 01 ,α 02 ,κ1 are the parameters of the first extended state observer.

[0104] Step 204 : construct a first nonlinear feedback control law in combination with the estimation result of the first extended state observer, and obtain the additional yaw moment at the current moment according to the first nonlinear feedback control law.

[0105] In the embodiment of the present application, the mathematical equation of the first nonlinear feedback control law is:

[0106] u1=β1fal(e1,α1,λ2)+β2fal(e2,α2,λ2)+b1z3

[0107] Where e1 is the actual yaw angle tracking error and e1 = r1 - z1, e2 is the actual yaw angle first-order derivative tracking error and e2 = r2 - z2, β1, β2, α1, α2, λ2 are all parameters of the first nonlinear feedback control law.

[0108] Step 103 : According to the reference front wheel steering angle and the actual front wheel steering angle of the vehicle, an active disturbance rejection steering angle control method is adopted to obtain a differential torque.

[0109] Figure 3 FIG. 1 is a flow chart of an auto-disturbance rejection steering angle control method according to an embodiment of the present application. Figure 3 As shown, in the embodiment of the present application, step 103 specifically includes:

[0110] Step 301 : construct an equivalent dynamics model of the steer-by-wire execution system and write it in an integral series form.

[0111] In order to facilitate analysis and control design, the constructed equivalent dynamic model of the wire-controlled steer-by-wire execution system is written in the form of an integral series model. The integral series model can clearly represent the changes in vehicle status over time.

[0112] First, the equivalent dynamics model of the steer-by-wire execution system is constructed. The specific formula is as follows:

[0113]

[0114] Among them, δ f is the vehicle front wheel steering angle, ΔM z is the differential torque, T s Represents the equivalent torque output by the steering motor. When the wire-controlled steering system fails completely, T s =0; τ z is the sum of the positive moments of the left and right front wheels, τ f represents the friction torque of the steering actuator, d2 is the second unknown multi-source disturbance, J eq and B eq are the equivalent moment of inertia and equivalent damping of the steering actuator, respectively.

[0115] Then, the equivalent dynamic model of the constructed steer-by-wire execution system is written in the form of an integral series type. The specific formula is as follows:

[0116]

[0117] Where y2 = δ f , u2=ΔM z ,

[0118] Step 302: construct a second differential tracker based on the reference front wheel steering angle, and smooth the reference front wheel steering angle using the second differential tracker to obtain a smoothed reference front wheel steering angle and a first-order derivative of the reference front wheel steering angle.

[0119] In the embodiment of the present application, the second differential tracker is constructed as follows:

[0120]

[0121] Where r3(k+1) is the smooth reference front wheel steering angle at the k+1th moment, r4(k+1) is the first-order derivative of the smooth reference front wheel steering angle at the k+1th moment, r3(k) is the smooth reference front wheel steering angle at the kth moment, r4(k) is the first-order derivative of the smooth reference front wheel steering angle at the kth moment, and δ fd (k) is the reference front wheel steering angle at the kth moment, h2 is the sampling period of the second differential tracker, and λ3 is the parameter in the second differential tracker that determines the tracking speed.

[0122] Step 303: Construct a second extended state observer based on the actual front wheel steering angle at the current moment and the differential torque at the previous moment. The second extended state observer is used to estimate the actual front wheel steering angle at the current moment, the first-order derivative of the front wheel steering angle, the second unmodeled dynamics, and the unknown multi-source disturbance in real time.

[0123] In the embodiment of the present application, the second extended state observer is constructed as follows:

[0124]

[0125] Where z4 is the estimated value of the actual front wheel steering angle, z5 is the estimated value of the first-order derivative of the actual front wheel steering angle, z6 is the estimated value of the unmodeled dynamics and unknown multi-source disturbances, and e 02 is the actual front wheel steering angle estimation error, β 04 ,β 05 ,β 06 ,α 03 ,α 04 ,κ2 are the parameters of the second extended state observer.

[0126] Step 304 : construct a second nonlinear feedback control law in combination with the estimation result of the second extended state observer, and obtain the differential torque at the current moment according to the second nonlinear feedback control law.

[0127] In the embodiment of the present application, the mathematical equation of the second nonlinear feedback control law is:

[0128] u2=β3fal(e3,α3,λ4)+β4fal(e4,α4,λ4)+b2z6

[0129] Wherein, e3 is the actual front wheel steering angle tracking error and e3 = r3-z4, e4 is the actual front wheel steering angle first-order derivative tracking error and e4 = r4-z5, β3, β4, α3, α4, λ4 are all parameters of the second nonlinear feedback control law.

[0130] Step 104 : Obtain the longitudinal driving force required by the vehicle.

[0131] In the embodiment of the present application, the longitudinal driving force required by the vehicle includes rolling resistance, wind resistance, slope resistance and acceleration resistance.

[0132] Among them, rolling resistance is usually related to the weight of the vehicle and road conditions; wind resistance depends on the vehicle's speed, frontal area and air resistance coefficient; slope resistance refers to the component of gravity along the slope that needs to be overcome when the vehicle is driving on a slope; acceleration resistance is related to the vehicle's mass and acceleration.

[0133] It is understandable that in actual situations, additional factors may need to be considered, such as the friction coefficient between the tire and the ground, the vehicle load, etc. Furthermore, the actual driving force required by the vehicle needs to be converted through factors such as the engine output torque, the transmission speed ratio, and the final drive speed ratio to obtain the actual driving force on the wheels. In the embodiments of this application, the process of obtaining the required longitudinal driving force of the vehicle is not specifically limited, and the specific determination depends on the resistance in the actual scenario.

[0134] Step 105 : determining the torque of each wheel based on a torque distribution method with optimal tire load rate according to the additional yaw moment, the differential torque, and the required longitudinal driving force of the vehicle.

[0135] In an embodiment of the present application, a vehicle longitudinal force constraint objective function is first constructed based on the additional yaw moment, differential torque and required longitudinal driving force of the vehicle, the maximum output torque of the vehicle's drive and brake motors and the road adhesion conditions; then, the effective set method is used to solve the electric vehicle longitudinal force constraint objective function to determine the current torque of each wheel of the vehicle.

[0136] As a possible implementation method, the specific formula of the vehicle longitudinal force constraint objective function is:

[0137]

[0138] The constraints are:

[0139]

[0140] Among them, F xeq is the longitudinal driving force required by the vehicle, F xfl ,F xrl ,F xfr ,F xrr are the longitudinal forces of the left front wheel, left rear wheel, right front wheel, and right rear wheel of the vehicle, respectively, and F zfl ,F zrl ,F zfr ,F zrr are the vertical forces of the left front wheel, left rear wheel, right front wheel, and right rear wheel of the vehicle respectively, μ is the road adhesion coefficient, l w is the vehicle wheelbase, r w is the equivalent radius of the tire, T max is the maximum output torque of the vehicle's driving brake motor, r σ The kingpin offset, τ is the kingpin caster angle, σ is the kingpin inclination angle, c ij Used to adjust the weight coefficient of the wheel longitudinal force in the optimization objective function.

[0141] Finally, by solving the above optimization problem, the longitudinal force F of each wheel can be obtained xfl ,F xrl ,Fxfr ,F xrr , so that the driving and braking torque T of each wheel of the vehicle can be determined ij , the specific calculation formula is:

[0142] T ij =F xij r w (ij=lf,rf,lr,rr)

[0143] Step 106 : Control the vehicle to achieve lateral movement according to the torque of each wheel.

[0144] It can be understood that, through the above steps, the driving and braking torque of each wheel has been obtained, and each driving and braking torque is allocated to the corresponding wheel, so as to control the vehicle to achieve lateral movement.

[0145] Figure 4 It is a block diagram of a differential steering fault-tolerant control system based on active disturbance rejection according to an embodiment of the present application.

[0146] like Figure 4 As shown, the system includes:

[0147] The first acquisition module 1 is used to obtain a reference yaw angle, an actual yaw angle, a reference front wheel steering angle and an actual front wheel steering angle of the vehicle;

[0148] A yaw angle control module 2 is configured to obtain an additional yaw moment by adopting an active disturbance rejection yaw angle control method according to a reference yaw angle and an actual yaw angle of the vehicle;

[0149] A steering angle control module 3 is configured to obtain a differential torque by adopting an active disturbance rejection steering angle control method according to a reference front wheel steering angle and an actual front wheel steering angle of the vehicle;

[0150] The second acquisition module 4 is used to obtain the longitudinal driving force required by the vehicle;

[0151] a wheel torque distribution module 5, configured to determine the torque of each wheel based on a torque distribution method with an optimal tire load rate according to the additional yaw moment, the differential torque and the required longitudinal driving force of the vehicle;

[0152] The driving module 6 is used to control the vehicle to achieve lateral movement according to the torque of each wheel.

[0153] Regarding the system in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0154] In summary, the differential steering fault-tolerant control method and system based on self-disturbance rejection proposed in this embodiment can achieve precise vehicle lateral control through differential steering after the steering system fails without the need for a precise system model, and can handle unmodeled system dynamics and unknown multi-source disturbances, and has robustness.

[0155] In addition, the present application utilizes two parallel ADRCs to decouple the steering angle and the yaw angle, effectively reducing the dimension of the controller, simplifying the structure, and further expanding the application scope of ADRC.

[0156] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this application can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of this application can be achieved. This is not limited herein.

[0157] The above specific embodiments do not constitute a limitation on the scope of protection of this application. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application shall be included within the scope of protection of this application.

Claims

1. A differential steering fault-tolerant control method based on active disturbance rejection, characterized in that: include: Obtaining the vehicle's reference yaw angle, actual yaw angle, reference front wheel steering angle, and actual front wheel steering angle; Obtaining an additional yaw moment using an active disturbance rejection yaw angle control method according to the reference yaw angle and the actual yaw angle of the vehicle; Obtaining a differential torque using an active disturbance rejection steering angle control method according to the reference front wheel steering angle and the actual front wheel steering angle of the vehicle; Obtain the longitudinal driving force required by the vehicle; determining the torque of each wheel based on a torque distribution method with an optimal tire load rate according to the additional yaw moment, the differential torque, and the required longitudinal driving force of the vehicle; Controlling the vehicle to achieve lateral movement according to the torque of each wheel; The method of obtaining an additional yaw moment by adopting an active disturbance rejection yaw angle control method according to the reference yaw angle and the actual yaw angle of the vehicle includes: Construct the vehicle yaw dynamics model and write it in the form of integral series type; constructing a first differential tracker according to the reference yaw angle, and smoothing the reference yaw angle by the first differential tracker to obtain a smoothed reference yaw angle and a first-order derivative of the reference yaw angle; constructing a first extended state observer based on the actual yaw angle of the vehicle at a current moment and the additional yaw moment at a previous moment, and estimating the actual yaw angle at a current moment, a first-order derivative of the actual yaw angle, a first unmodeled dynamic, and unknown multi-source disturbances in real time through the first extended state observer; A first nonlinear feedback control law is constructed in combination with the estimation result of the first extended state observer, and the additional yaw moment at the current moment is obtained according to the first nonlinear feedback control law.

2. The method according to claim 1, characterized in that The vehicle yaw dynamics model is constructed and written in the form of an integral series type, including: Construct the vehicle yaw dynamics model. The specific formula is as follows: Where, is the vehicle yaw angle, is the vehicle longitudinal velocity, is the vehicle lateral velocity, is the front wheel steering angle, is the additional yaw moment, is the first unknown multi-source disturbance, is the cornering stiffness of the front tire, is the cornering stiffness of the rear tire, is the distance from the vehicle's center of mass to the front axle, is the distance from the vehicle's center of mass to the rear axle, is the moment of inertia of the vehicle around the z-axis, Parameters that determine the speed of tracking; The constructed vehicle yaw dynamics model is written in the form of an integral series type, and the specific formula is as follows: Where, , , , .

3. The method according to claim 2, characterized in that The first differential tracker is constructed as follows: Where, For the The smoothed reference yaw angle at time , For the The first-order differential of the smoothed reference yaw angle at time , For the The smoothed reference yaw angle at time , For the The first-order differential of the smoothed reference yaw angle at time , For the The reference yaw angle at time , is the sampling period, To determine the parameters of tracking speed, The function is the fastest control comprehensive function; The first extended state observer is constructed as follows: Where, is the estimated value of the actual yaw angle, is the estimated value of the first-order derivative of the actual yaw angle, is the estimate of the first unmodeled dynamics and disturbance, is the actual yaw angle estimation error, Function is the fastest control synthesis function, are the first extended state observer parameters; The mathematical equation of the first nonlinear feedback control law is: Where, is the actual yaw angle tracking error and , is the actual yaw angle first-order derivative tracking error and , are all parameters of the first nonlinear feedback control law.

4. The method according to claim 1, wherein The method of obtaining a differential torque by adopting an active disturbance rejection steering angle control method according to the reference front wheel steering angle and the actual front wheel steering angle of the vehicle includes: Construct an equivalent dynamic model of the steer-by-wire actuator system and write it in the form of an integral series type; constructing a second differential tracker according to the reference front wheel steering angle, and smoothing the reference front wheel steering angle by the second differential tracker to obtain a smoothed reference front wheel steering angle and a first-order derivative of the reference front wheel steering angle; constructing a second extended state observer based on the actual front wheel steering angle at the current moment and the differential torque at the previous moment, and estimating the actual front wheel steering angle at the current moment, the first-order derivative of the front wheel steering angle, the second unmodeled dynamics, and the unknown multi-source disturbance in real time through the second extended state observer; A second nonlinear feedback control law is constructed in combination with the estimation result of the second extended state observer, and the differential torque at the current moment is obtained according to the second nonlinear feedback control law.

5. The method according to claim 4, characterized in that The equivalent dynamic model of the steer-by-wire execution system is constructed and written in the form of an integral series type, including: Construct an equivalent dynamic model of the wire-controlled steering execution system. The specific formula is as follows: in, is the vehicle front wheel steering angle, is the differential torque, Represents the equivalent torque output by the steering motor. When the wire-controlled steering system fails completely, ; is the sum of the positive moments of the left and right front wheels, Represents the friction torque of the steering actuator, is the second unknown multi-source disturbance, and are the equivalent moment of inertia and equivalent damping of the steering actuator respectively; The equivalent dynamic model of the constructed steer-by-wire execution system is written in the form of an integral series type, and the specific formula is as follows: in, , , , .

6. The method according to claim 5, characterized in that The second differential tracker is constructed as follows: Where, For the The smoothed reference front wheel steering angle at time , For the The first derivative of the smoothed reference front wheel steering angle at time , For the The smoothed reference front wheel steering angle at time , For the The first derivative of the smoothed reference front wheel steering angle at time , For the The reference front wheel steering angle at time , is the sampling period of the second differential tracker, It is the parameter that determines the tracking speed in the second differential tracker; The second extended state observer is constructed as follows: Where, is the estimated value of the actual front wheel steering angle, is the estimated value of the first-order derivative of the actual front wheel steering angle, is an estimate of the unmodeled dynamics and unknown multi-source disturbances, is the actual front wheel steering angle estimation error, are the parameters of the second extended state observer; The mathematical equation of the second nonlinear feedback control law is: Where, is the actual front wheel steering angle tracking error and , is the first-order derivative tracking error of the actual front wheel steering angle and , are all parameters of the second nonlinear feedback control law.

7. The method according to claim 1, characterized in that The determining of each wheel torque based on a torque distribution method with an optimal tire load rate according to the additional yaw moment, the differential torque, and the required longitudinal driving force of the vehicle includes: constructing a vehicle longitudinal force constraint objective function according to the additional yaw moment, the differential torque, and the required longitudinal driving force of the vehicle, based on the maximum output torque of the vehicle's driving and braking motors and road adhesion conditions; The vehicle longitudinal force constraint objective function is solved using an active set method to determine the current torque of each wheel of the vehicle.

8. The method according to claim 7, characterized in that The specific formula of the vehicle longitudinal force constraint objective function is: The constraints are: in, is the longitudinal driving force required for the vehicle, are the longitudinal forces of the vehicle’s left front wheel, left rear wheel, right front wheel, and right rear wheel, respectively. are the vertical forces on the left front wheel, left rear wheel, right front wheel, and right rear wheel of the vehicle, respectively. is the road adhesion coefficient, is the vehicle wheelbase, is the equivalent radius of the tire, is the maximum output torque of the vehicle driving brake motor, is the kingpin offset, is the caster angle, is the kingpin inclination angle, Used to adjust the weight coefficient of the wheel longitudinal force in the optimization objective function.

9. A differential steering fault-tolerant control system based on active disturbance rejection, characterized in that: include: A first acquisition module is used to acquire a reference yaw angle, an actual yaw angle, a reference front wheel steering angle, and an actual front wheel steering angle of the vehicle; a yaw angle control module, configured to obtain an additional yaw moment by adopting an active disturbance rejection yaw angle control method according to the reference yaw angle and the actual yaw angle of the vehicle; a steering angle control module, configured to obtain a differential torque by adopting an active disturbance rejection steering angle control method according to the reference front wheel steering angle and the actual front wheel steering angle of the vehicle; A second acquisition module is used to obtain the longitudinal driving force required by the vehicle; a wheel torque distribution module, configured to determine the torque of each wheel based on a torque distribution method with an optimal tire load rate according to the additional yaw moment, the differential torque, and the required longitudinal driving force of the vehicle; A driving module, configured to control the vehicle to achieve lateral movement according to the torque of each wheel; The method of obtaining an additional yaw moment by adopting an active disturbance rejection yaw angle control method according to the reference yaw angle and the actual yaw angle of the vehicle includes: Construct the vehicle yaw dynamics model and write it in the form of integral series type; constructing a first differential tracker according to the reference yaw angle, and smoothing the reference yaw angle by the first differential tracker to obtain a smoothed reference yaw angle and a first-order derivative of the reference yaw angle; constructing a first extended state observer based on the actual yaw angle of the vehicle at a current moment and the additional yaw moment at a previous moment, and estimating the actual yaw angle at a current moment, a first-order derivative of the actual yaw angle, a first unmodeled dynamic, and unknown multi-source disturbances in real time through the first extended state observer; A first nonlinear feedback control law is constructed in combination with the estimation result of the first extended state observer, and the additional yaw moment at the current moment is obtained according to the first nonlinear feedback control law.

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