Sliding mode fault-tolerant control method, terminal and storage medium of automobile steer-by-wire system

Abstract

The application relates to the technical field of automobile fault-tolerant control, and discloses a sliding mode fault-tolerant control method of an automobile steer-by-wire system, a terminal and a storage medium. The method first establishes a nonlinear bond graph model of the steer-by-wire system, and establishes a dynamic model of a front wheel subsystem in the steer-by-wire system; then based on the dynamic model of the front wheel subsystem, a sliding mode controller is used to control the actual angle of the front wheel to track a reference angle, so that the automobile travels on a desired track; when a sensor fault of the automobile is detected, a sliding mode observer is used to estimate a sensor fault value, the fault influence is eliminated, and fault-tolerant control is realized. The application solves the fault-tolerant problem of the vehicle in the process of driving.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of automobile fault-tolerant control, in particular to a sliding mode fault-tolerant control method for a steer-by-wire system of an automobile, a terminal and a storage medium. BACKGROUND

[0002] With the development of the automobile industry, consumers have higher requirements for the safety, energy saving and environmental performance of automobiles, and traditional automobile steering systems gradually fail to meet modern demands.

[0003] Early automobile steering systems mainly use mechanical structures, and the transmission ratio between the steering wheel and the steering wheel is fixed, resulting in poor steering dynamics and kinematics of the automobile. In addition, the mechanical steering system has the disadvantages of large steering torque and difficult driver control. To improve this problem, a hydraulic power steering system is introduced, which provides power through the engine and improves the lightness and flexibility of steering, but its energy consumption is high.

[0004] With the widespread application of electronic technology, electric power steering systems (EPS) have gradually developed and been widely used, which have improved the stability of steering to some extent. However, the traditional steering system still relies on the steering transmission shaft, which may cause serious impact injuries to the driver in the event of a traffic accident. In order to solve this problem, the steer-by-wire system (SBW) has emerged. The steer-by-wire system cancels the mechanical connection and relies on sensors, actuators and electronic control units (ECU) to complete steering control, improving safety and driving comfort. However, the system has a high dependence on sensors and is easily affected by sensor failures, thereby affecting driving safety. Therefore, timely detection, tracking and compensation of faults are crucial for the steer-by-wire system.

[0005] During long-term use, the sensors of the steer-by-wire system may fail due to aging or environmental influences. If the failure cannot be detected in time or there is a lack of effective compensation mechanism, it may lead to loss of control of steering and cause serious safety hazards. However, there is still a lack of a sliding mode fault-tolerant control method for the steer-by-wire system of an automobile in the prior art to effectively deal with sensor failures, which needs to be solved urgently. SUMMARY

[0006] In order to overcome the defects in the prior art, the present application provides a sliding mode fault-tolerant control method for a steer-by-wire system of an automobile, a terminal and a storage medium, which solves the fault-tolerant problem of the vehicle during driving.

[0007] To achieve the above purpose, the present application provides the following technical solutions:

[0008] The present application discloses a sliding mode fault-tolerant control method for a steer-by-wire system of an automobile, comprising the following steps:

[0009] S1. Establishing a nonlinear bond graph model of the steer-by-wire system, thereby establishing a dynamic model of the front wheel subsystem in the steer-by-wire system;

[0010] S2. Based on the dynamic model of the front wheel subsystem, using a sliding mode controller to control the actual angle of the front wheel to track the reference angle, so that the vehicle travels on the desired trajectory;

[0011] S3. When a sensor failure of the vehicle is detected, a sliding mode observer is used to estimate the sensor fault value, eliminate the fault influence and realize fault-tolerant control.

[0012] As a further improvement of the above scheme, step S1 includes the following specific steps:

[0013] S11. The steer-by-wire system is divided into a steering wheel subsystem and a front wheel subsystem; wherein the steering wheel subsystem includes a steering wheel, a feedback motor, a reducer, a feedback motor driver, a steering wheel angle sensor and a feedback motor angle sensor, and the front wheel subsystem includes a steering motor driver, a steering motor, a reducer, a gear, a rack, a front wheel, a steering motor angle sensor, a gear angle sensor and a front wheel angle sensor;

[0014] S12. A nonlinear bond graph model is constructed based on the bond graph theory; wherein the basic elements of the nonlinear bond graph model include a one-port element, a two-port element and a multi-port element; the one-port element includes a potential source Se, a flow source Sf, a dissipation element R, an inertia element I, a capacitance element C and a flow sensor {Df1, Df2, …, Df5}; the two-port element includes a transformer TF and a gyrator GY; the multi-port element includes a 1-type node and a 0-type node;

[0015] S13. The dynamic model of the front wheel subsystem is established by the nonlinear bond graph model, and its expression is as follows:

[0016]

[0017] In the formula, K s is the steering motor torque constant; U2 is the input voltage of the steering motor; R m is the viscous friction coefficient of the steering motor; θ s is the steering motor angle, and are the first and second derivatives of θ s , respectively; C s is the stiffness of the steering motor shaft; x r is the rack displacement; G p1 is the reduction ratio of the reducer; r p is the gear radius; J sI p represents the friction of the rack; C p represents the stiffness of the rack; G p2 represents the ratio of the rack linear velocity to the front wheel angular velocity; θ fw is the actual front wheel angle; M p represents the mass of the rack; θ fk is the front wheel angle; R fk is the friction between the tire and the ground; J fk is the moment of inertia of the front wheel; g m is the steering motor friction torque characteristic function, g r is the gear friction torque characteristic function, g fk is the front wheel friction torque characteristic function, the expression formulas of the three are where T s,i and T c,i are the Coulomb friction torque and static friction torque of the corresponding components, λ i is a constant representing the transition between T s,i and T c,i , μ is the independent variable; T e is the self-aligning torque.

[0018] As a further improvement of the above scheme, step S2 comprises the following specific steps:

[0019] S21. Setting the system state and system input according to the dynamic model of the front wheel subsystem; wherein the system input is the steering motor driver input voltage u, and the expression formula of the system state x(t) is:

[0020]

[0021] In the formula, t represents time; the superscript T is the transpose symbol;

[0022] S22. Establishing a state space model of the steer-by-wire system in a healthy state, the expression formula is:

[0023]

[0024] In the formula, is the derivative of the system state variable; y(t) is the system output, i.e. the front wheel angle; u(t) is the sliding mode control rate, i.e. the function of the steering motor driver input voltage u changing with time; f(x, t) is a nonlinear term; Ψ(x, t) is a lumped disturbance; A, B and c are the state transition coefficient matrix, the input coefficient matrix and the output coefficient matrix respectively;

[0025] S23. Simplifying the dynamic model of the front wheel subsystem to obtain the dynamic equation of the front wheel subsystem:

[0026]

[0027] wherein J eq is the equivalent rotational inertia; B eq is the equivalent damping coefficient; T f is the nonlinear friction torque; K e is the motor output torque coefficient;

[0028] S24. Set a sliding mode control rate in combination with the dynamic equation, and use a sliding mode controller to control the input voltage signal of the steering motor driver according to the sliding mode control rate, so that the actual angle of the front wheel tracks the reference angle thereof; wherein the calculation formula of the input voltage u of the steering motor driver is:

[0029]

[0030] wherein θ fwd is the reference signal of the front wheel turning angle; c>0; s is a sliding surface; εsgn(·) is a sign function term, and k>0 is a linear term.

[0031] As a further improvement of the above scheme, in step S3, when it is detected that the sensor has failed, the sliding mode observer automatically controls the motor output size according to its own design to realize fault tolerance; wherein the design method of the sliding mode observer includes the following specific steps:

[0032] S31. Establish a state space model of the steer-by-wire system under sensor failure, and the expression formula is:

[0033]

[0034] wherein x is the state variable of the automobile, y s (t) is the output of the steer-by-wire system; u r (t) is the control input, i.e. the input voltage of the steering motor driver; K r is the feedback motor torque constant, J w is the rotational inertia of the front wheel, B w is the viscous friction coefficient of the front wheel; B s = [0 K r / G r J w ] T , G r is the transmission ratio between the rack displacement and the front wheel turning angle; C sy = [1 0] is the output gain matrix; is a nonlinear term in the steer-by-wire system; E s = [0 1]T Ψ3(x s , t) is the lumped disturbance; M s = 1; f s (t) is the sensor fault;

[0035] S32. Augment the state space model of the steer-by-wire system under sensor fault to obtain an augmented matrix:

[0036]

[0037] wherein, is the augmented state variable, wherein z(t) is a self-defined variable, which can be the output y s (t) to achieve low-pass filtering, and satisfies the formula: A f is a stable filter matrix, defined as a diagonal positive definite matrix;

[0038] S33. Design a sliding mode observer using the augmented matrix, expressed as:

[0039]

[0040] wherein, is the estimated value of ; is the estimated value of ; is the augmented transpose of τ s (x s , t), i.e. v is the discontinuous term in the sliding mode observer; L1 is the gain matrix of the sliding mode observer.

[0041] As a further improvement of the above scheme, after the design of the sliding mode observer, the sensor fault estimate, i.e. the discontinuous term v in the sliding mode observer, is calculated, expressed as:

[0042]

[0043] wherein, e y and ρ1 are positive scalar gains, ρ1>β fs ; H1 is an arbitrary matrix satisfying the formula P1 is a 3x3 real symmetric matrix; δ1 is a positive scalar;

[0044] Calculate wherein, is the estimated value of f s (t);

[0045] The fault-tolerant control of the faulty sensor is completed by using the following formula, and the fault-tolerant formula is as follows:

[0046]

[0047] In the formula, is the front wheel steering angle after fault tolerance; y3(t) is the actual output of the faulty sensor; is the sensor fault estimation error, which can converge to zero in a limited time.

[0048] The application further discloses a computer terminal, including a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the slip mode fault-tolerant control method of the automobile steer-by-wire system when executing the computer program.

[0049] The application further discloses a computer readable storage medium, which stores a computer program, and the program is executable on the processor to implement the steps of the slip mode fault-tolerant control method of the automobile steer-by-wire system.

[0050] Compared with the prior art, the application has the beneficial effects that:

[0051] The application provides a slip mode fault-tolerant control method of an automobile steer-by-wire system based on a bond graph model, and solves the fault-tolerant problem of a vehicle during driving. BRIEF DESCRIPTION OF DRAWINGS

[0052] Figure 1 FIG. 1 is a flowchart of the slip mode fault-tolerant control method of the automobile steer-by-wire system in the embodiment 1 of the application.

[0053] Figure 2 FIG. 2 is a bond graph of the steering wheel part of the steer-by-wire system in the embodiment 1 of the application.

[0054] Figure 3 FIG. 3 is a bond graph of the feedback motor and reducer part of the steer-by-wire system in the embodiment 1 of the application.

[0055] Figure 4 FIG. 4 is a bond graph of the feedback motor driver part of the steer-by-wire system in the embodiment 1 of the application.

[0056] Figure 5 FIG. 5 is a bond graph of the steering motor driver part of the steer-by-wire system in the embodiment 1 of the application.

[0057] Figure 6Bond graph for the steer-by-wire system steering motor part in Example 1 of the present invention.

[0058] Figure 7 Bond graph for the steer-by-wire system rack and pinion part in Example 1 of the present invention.

[0059] Figure 8 Bond graph for the steer-by-wire system front wheel part in Example 1 of the present invention.

[0060] Figure 9 Block diagram of the steering wheel input module for the rear-end model in Example 1 of the present invention.

[0061] Figure 10 Block diagram of the friction input module for the hand wheel in Example 1 of the present invention.

[0062] Figure 11 Block diagram of the steering wheel input module and the "To Workplace" module in Example 1 of the present invention, where data is exported to the workspace.

[0063] Figure 12 Block diagram of the "To File" module in Example 1 of the present invention, where data is exported to generate a.mat file.

[0064] Figure 13 Block diagram of the CarSim and MATLAB co-simulation module in Example 1 of the present invention.

[0065] Figure 14 Software interface diagram of the model state for the input sine wave signal in Example 1 of the present invention, under normal fault conditions.

[0066] Figure 15 Software interface diagram of the model state for the input sine wave signal in Example 1 of the present invention, under gradual fault conditions.

[0067] Figure 16 Software interface diagram of the model state for the input ramp signal in Example 1 of the present invention, under intermittent fault conditions.

[0068] Figure 17 Software interface diagram of the model state for the input ramp signal in Example 1 of the present invention, under gradual fault conditions.

[0069] Figure 18 Software interface diagram of the error evaluation for the input sine wave signal in Example 1 of the present invention, under normal fault conditions.

[0070] Figure 19 Software interface diagram of the error evaluation for the input sine wave signal in Example 1 of the present invention, under gradual fault conditions.

[0071] Figure 20 Error evaluation software interface diagram under intermittent fault condition for input ramp signal in embodiment 1 of the present application.

[0072] Figure 21 Error evaluation software interface diagram under gradual fault condition for input ramp signal in embodiment 1 of the present application.

[0073] Figure 22 Computer terminal structure schematic diagram in embodiment 2 of the present application. DETAILED DESCRIPTION

[0074] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0075] Embodiment 1

[0076] Please refer to Figure 1 The embodiment provides a sliding mode fault-tolerant control method of a steer-by-wire system, which comprises the following steps, i.e., S1-S3.

[0077] S1. A nonlinear bond graph model of the steer-by-wire system is established to establish a dynamic model of a front wheel subsystem in the steer-by-wire system.

[0078] Step S1 comprises the following specific steps, i.e., S11-S13.

[0079] S11. The steer-by-wire system is divided into a steering wheel subsystem and a front wheel subsystem; wherein the steering wheel subsystem comprises a steering wheel, a feedback motor, a reducer, a feedback motor driver, a steering wheel angle sensor and a feedback motor angle sensor, and the front wheel subsystem comprises a steering motor driver, a steering motor, a reducer, a gear, a rack, a front wheel, a steering motor angle sensor, a gear angle sensor and a front wheel angle sensor.

[0080] S12. A nonlinear bond graph model is constructed based on the bond graph theory; wherein basic elements of the nonlinear bond graph model comprise a one-port element, a two-port element and a multi-port element; the one-port element comprises a potential source Se, a flow source Sf, a dissipation element R, an inertia element I, a capacitance element C and a flow sensor {Df1, Df2, …, Df5}; the two-port element comprises a transformer TF and a gyrator GY; and the multi-port element comprises a 1-type node and a 0-type node.

[0081] The nonlinear bond graph model of the steer-by-wire system of the front-wheel-steering vehicle of the present embodiment can be divided into seven parts: steering wheel part, feedback motor and reducer part, feedback motor driver part, steering motor driver part, steering motor part, rack and pinion part, and front wheel part, whose bond graphs are shown in Figures 2 to 8 .

[0082] The elements contained in the steering wheel part include a source Se: T h , a dissipative element R: R w , an inertial element I: J w , a capacitive element C: , and a flow sensor Df1: , where T h represents the input torque of the steering wheel, R w represents the mechanical friction force suffered by the steering wheel, J w represents the moment of inertia of the steering wheel, K h represents the stiffness of the steering column connected to the steering wheel, and represents the angular velocity of the steering wheel.

[0083] The elements contained in the feedback motor and reducer part include a transformer TF: G fm , dissipative elements {R: R mr1 , R: R mr2}, an inertial element I: J fm , a gyrator GY: K fm , and a flow sensor Df2: , where G fm is the reduction ratio, R mr1 is the mechanical friction force of the feedback motor, R mr2 is the resistance of the electrical part of the feedback motor, J fm is the moment of inertia of the rotor of the feedback motor, K fm is the current-torque constant, and is the angular velocity of the feedback motor.

[0084] The elements contained in the feedback motor driver part include a transformer Tf: K1 and a flow source Sf: U1. Where K1 represents the voltage-current ratio, and U1 is the input voltage of the feedback motor driver.

[0085] The elements contained in the steering motor driver part include a flow source Sf: U2 and a transformer TF: K2. Where K2 represents the voltage-current ratio, and U2 is the input voltage of the steering motor driver.

[0086] The elements contained in the steering motor part include dissipative elements {R: R s1 , R: R s2}, a gyrator GY: K m , and an inertial element I: Js , a capacitive element C: and a flow sensor Df3: where R s1 is the resistance of the electrical part of the steering motor, R s2 is the mechanical friction of the steering motor, K m is the current-torque constant, J s is the moment of inertia of the rotor of the steering motor, K s is the stiffness of the shaft of the steering motor, is the angular velocity of the steering motor.

[0087] The rack and pinion part contains elements with a transformer TF: a dissipative element R: R r , an inertial element I: M r , a transformer TF: G r2 , a capacitive element C: and a flow sensor Df4: where G r1 is the reduction ratio, r p is the gear radius, R r is the mechanical friction of the rack, M r is the mass of the rack, G r2 is the ratio of the linear velocity of the rack to the angular velocity of the front wheel, K r is the stiffness of the rack, is the linear velocity of the rack.

[0088] The front wheel part contains elements with a dissipative element R: R f , an inertial element I: J f , a potential source Se: T e and a flow sensor Df5: where R f is the friction between the front wheel and the road, J f is the moment of inertia, T e is the self-aligning torque, is the angular velocity of the front wheel.

[0089] The five mechanical frictions {R w , R mr1 , R s2 , R r , R f} in the steer-by-wire system are all nonlinear, and their potential and flow constitutive relations can be expressed as:

[0090]

[0091] where B v , T v,c and T v,srespectively represent the viscous friction coefficient, the Coulomb friction torque and the static friction torque, v e {w, mr1, s2, r, f}, e h and f h , h e {2, 9, 22, 29, 36} respectively represent the potential and flow of the corresponding power bond.

[0092] Figure 4 In the formula, is the feedback motor driver controller, E1 is the steering wheel feedback torque reference value T rf , and the difference between the actual value T af . Where N v is the speed coefficient, N f is the torque transmission ratio between the steering wheel and the front wheel; In the formula, Figure 5 , h e {2, 9, 22, 29, 36} respectively represent the potential and flow of the corresponding power bond. is the steering motor driver controller, is the difference between the desired front wheel angle and the actual front wheel angle, wherein N θ is the steering transmission ratio.

[0093] S13. The dynamic model of the front wheel subsystem is established by the nonlinear bond graph model. Since the focus of the application is on the front wheel angle tracking performance of the steer-by-wire system when the front wheel subsystem sensor fails, only the dynamic model of the front wheel subsystem is established, and its expression is as follows:

[0094]

[0095] In the formula, K s is the steering motor torque constant; U2 is the input voltage of the steering motor; R m is the viscous friction coefficient of the steering motor; θ s is the steering motor angle, and are the first derivative and the second derivative of θ s respectively; C s is the stiffness of the steering motor shaft; x r is the rack displacement; G p1 is the reduction ratio of the reducer; r p is the gear radius; J s is the moment of inertia of the steering motor rotor; R p represents the friction of the rack; C p represents the rack stiffness; G p2 represents the ratio of the rack linear velocity to the front wheel angular velocity; θ fw is the actual front wheel angle; M p represents the mass of the rack; θ fk is the front wheel angle; R fk is the friction between the tire and the ground; Jfk Jf is the moment of inertia of the front wheel; g m Jf is the friction torque characteristic function of the steering motor; g r Jf is the friction torque characteristic function of the gear; g fk Jf is the friction torque characteristic function of the front wheel; the expression formula of the three is Wherein, T s,i and T c,i are the Coulomb friction torque and static friction torque of the corresponding component respectively, λ i is a constant representing the transition between T s,i and T c,i , μ is the independent variable; T e is the self-aligning torque.

[0096] S2. Based on the dynamic model of the front wheel subsystem, a sliding mode controller is used to control the actual angle of the front wheel to track the reference angle, so that the car travels on the desired trajectory.

[0097] Step S2 includes the following specific steps, namely S21-S24.

[0098] S21. According to the dynamic model of the front wheel subsystem, the system state and the system input are set; wherein the system input is the steering motor driver input voltage u, and the expression formula of the system state x(t) is:

[0099]

[0100] In the formula, t represents time; the superscript T is the transpose symbol.

[0101] S22. Establish the state space model of the steer-by-wire system in the healthy state, the expression formula is:

[0102]

[0103] In the formula, is the derivative of the system state variable; y(t) is the system output, that is, the front wheel angle; u(t) is the sliding mode control rate, that is, the steering motor driver input voltage u as a function of time; f(x,t) is a nonlinear term; Ψ(x,t) is a lumped disturbance; A, B and c are state transition coefficient matrix, input coefficient matrix and output coefficient matrix respectively.

[0104] S23. The dynamic equation of the front wheel subsystem is obtained by simplifying the dynamic model of the front wheel subsystem:

[0105]

[0106] In the formula, J eq is the equivalent moment of inertia; B eq is the equivalent damping coefficient; Tf is the nonlinear friction torque; K e is the motor output torque coefficient.

[0107] S24. Set the sliding mode control rate according to the kinetic equation, and use the sliding mode controller to control the input voltage signal of the steering motor driver according to the sliding mode control rate, so that the actual angle of the front wheel tracks the reference angle. Wherein the sliding surface s of the sliding mode controller is:

[0108]

[0109] Wherein, c>0; e=θ fwd -θ fw ;θ fwd is the reference signal of the front wheel steering angle;

[0110] The reaching law of the sliding mode controller is:

[0111]

[0112] Wherein, εsgn(s) is a sign function term, and k>0 is a linear term.

[0113] The calculation formula of the input voltage u of the steering motor driver is:

[0114]

[0115] Wherein, θ fwd is the reference signal of the front wheel steering angle; c>0; s is the sliding surface; εsgn(·) is a sign function term, and k>0 is a linear term.

[0116] S3. When the sensor fault of the vehicle is detected, the sensor fault value is estimated by the sliding mode observer to eliminate the fault influence and realize fault-tolerant control.

[0117] In step S3, when the sensor fault is detected, the sliding mode observer automatically controls the motor output size according to its own design to realize fault tolerance.

[0118] It should be noted that how to detect the sensor fault is not the invention point, and in the present embodiment, the technical content in the invention publication CN118011799A can be referred to for implementation.

[0119] Wherein, the design method of the sliding mode observer includes the following specific steps, i.e. S31-S33.

[0120] S31. The present application mainly considers the failure of front wheel angle sensor. Since the state space model of step S22 is too complex, it is quite challenging to directly design a fault reconstruction strategy to estimate the fault value. In order to solve this problem, the present application carries out certain model conversion reconstruction before fault reconstruction. Therefore, the state space model of the steer-by-wire system under sensor failure is established, and the expression formula is:

[0121]

[0122] In the formula, is the state variable of the automobile, y s (t) is the output of the steer-by-wire system; u r (t) is the control input, i.e. the input voltage of the steering motor driver; K r is the feedback motor torque constant, J w is the rotational inertia of the front wheel, B w is the viscous friction coefficient of the front wheel; B s = [0 K r / G r J w ] T , G r is the transmission ratio between rack displacement and front wheel steering angle; C sy = [1 0] is the output gain matrix; is the nonlinear term in the steer-by-wire system; E s = [0 1] T ; Ψ3(x s , t) is the lumped disturbance; M s = 1; f s (t) is the sensor failure.

[0123] S32. In order to build a sliding mode observer, the state space model of the steer-by-wire system under sensor failure is first augmented and reconstructed to obtain the augmented matrix:

[0124]

[0125] In the formula, is the augmented state variable, wherein z(t) is a self-defined variable, which can be the output y s (t) to achieve low-pass filtering, and satisfies the formula: A f is a stable filtering matrix, which is defined as a diagonal positive definite matrix;

[0126] S33. The sliding mode observer is designed using the augmented matrix, and the expression formula is:

[0127]

[0128] wherein, is the estimated value of ; and is the estimated value of ; and is the estimated value of s (x s , t) is the augmented transpose of v is the discontinuous term in the sliding mode observer, used to adjust the system state estimation; L1 is the sliding mode observer gain matrix, used to adjust the system rapidity.

[0129] After the sliding mode observer is designed, the sensor fault estimation value, i.e. the discontinuous term v in the sliding mode observer, is calculated, and the expression formula is:

[0130]

[0131] wherein, e y and ρ1 are positive scalar gains, ρ1>β fs ; H1 is an arbitrary matrix satisfying the formula ; P1 is a 3x3 order real symmetric matrix, used to determine and ensure system stability; δ1 is a positive scalar, used to reduce chattering caused by v.

[0132] Calculate wherein, is the estimated value of f s (t).

[0133] The following formula is used to complete fault-tolerant of the faulty sensor, and the fault-tolerant formula is as follows:

[0134]

[0135] wherein, is the front wheel steering angle after fault-tolerant; y3(t) is the actual output of the faulty sensor; is the sensor fault estimation error, which can converge to zero in a finite time.

[0136] In this embodiment, MATLAB software is also used to establish a front-end environment connected with the back-end model, for parameter adjustment and model state observation. And joint simulation is performed with CarSim to observe the running state of the car model.

[0137] 1. Total function of front end

[0138] 1.1 Parameter setting: set the input waveform, sliding surface parameters, chattering control of approach rate, approach rate of approach rate, moment of inertia, damping coefficient, mechanical friction and other parameters.

[0139] 1.2, Sensor fault injection: Select fault modes such as no fault, gradual fault, intermittent fault, failure fault, sudden fault, etc.

[0140] 1.3, Simulation content: Steering wheel input waveform, front wheel angle tracking waveform, vehicle trajectory graph waveform, fault image waveform.

[0141] 1.4, Error evaluation: Real-time monitoring of front wheel tracking error and fault estimation error.

[0142] 2, Jump between APP interfaces

[0143] An APP interface corresponds to a MATLAB APP file, and the jump between APP interfaces is realized by opening and closing the file. The specific implementation process is as follows:

[0144] Add a "button" module in the APP interface and add a callback function to it.

[0145] For example: run("CANSHU1.mlapp");

[0146] delete(app);

[0147] It means closing the current interface and opening the interface corresponding to "CANSHU1.mlapp".

[0148] 3, Data transmission between front and back ends

[0149] 3.1, Front-end data input to back-end model

[0150] Add "drop-down box", "edit field (numeric)" and other modules in the APP interface, and add a callback function to them.

[0151] Example 1: When selecting different input waveforms, you can use the "drop-down box" module to add different waveform names in its drop-down items. Then add the callback function:

[0152] value = app. DropDown. Value;

[0153] global a4;

[0154] switch value

[0155] case'sine wave'

[0156] a4 = 1;

[0157] case 'constant'

[0158] a4 = 2;

[0159] case 'ramp'

[0160] a4 = 3;

[0161] end

[0162] Inctrl = a4;

[0163] assignin('base', 'Inctrl', Inctrl);

[0164] If the drop-down box selects'sine wave', the value of Inctrl is 1 (as shown in Figure 9 ), and the model outputs a sine wave.

[0165] Example 2: When setting the model parameters, the 'Edit Field (numeric)' module can be used, and a callback function can be added to it:

[0166] Bh = app.EditField.Value;

[0167] assignin('base', 'Bh', Bh);

[0168] Enter 0.01 in the 'Edit Field (numeric)' module, and the value of Bh (as shown in Figure 10 ) in the model is 0.01, and the corresponding steering wheel (hand wheel) friction is 0.01.

[0169] 3.2, Input the backend model data to the frontend interface

[0170] Add a 'To Workspace' module in the model to transfer data to the workspace, then call it through code in the frontend, or add a 'To File' module to transfer data to a ***.mat file, then call it through code in the frontend.

[0171] Example 1: When drawing a static graph of the steering wheel input waveform in the APP interface, add a 'To Workspace' module at the steering wheel waveform input of the model (as shown in Figure 11 ), then add a 'Coordinate Area' module and a 'Button' module in the APP interface, and add a callback function in the 'Button' module:

[0172] cla(app.UIAxes_2);

[0173] out = sim('test01');

[0174] IN = out.IN;

[0175] plot(IN, 'Parent', app.UIAxes_2, 'Color', 'r');

[0176] hold(app.UIAxes_2,"on");

[0177] After pressing the "button", the coordinate area will display a static graph of the steering wheel input waveform.

[0178] Example 2: When drawing a dynamic graph of front wheel steering angle tracking in the APP interface, add a "ToFile" module (e.g., ...) to the front wheel steering angle output of the model. Figure 12 (As shown), change the "Save Format" in the "To File" module to "Array", then add a "Coordinate Area" module and a "Button" module to the APP interface, and add a callback function in the "Button" module:

[0179] sim("test01");

[0180] load OUT1.mat;

[0181] x = OUT1(1,:);

[0182] y = OUT1(2,:);

[0183] h1=animatedline(app.UIAxes,"Color",'b','LineWidth',1);

[0184] a = tic;

[0185] for i = 1:(length(x))

[0186] addpoints(h1,x(i),y(i));

[0187] b = toc(a);

[0188] if b > (1 / 100)

[0189] drawnow

[0190] a = tic;

[0191] end

[0192] end

[0193] drawnow

[0194] After pressing the "button", the coordinate area will display a dynamic graph of the front wheel steering angle tracking.

[0195] 4. Co-simulation of Simulink and CarSim

[0196] First, configure the car environment of CarSim, such as vehicle type, road, etc., and connect CarSim and Simulink by using the "Run Control with Simulink" module in CarSim. Then, set the input and output parameters.

[0197] As shown in Figure 13 , in the CarSim and MATLAB joint simulation module, the input is the front wheel steering angle of the vehicle (i.e., vs_sf), and the output is the X and Y components of the vehicle model's travel trajectory (i.e., X.mat and Y.mat). In CarSim, a 3D graph of the vehicle model's travel can be seen, and in the APP interface, the dynamic vehicle travel trajectory curve is displayed in the "coordinate area".

[0198] In this embodiment, the nominal values of the steer-by-wire system parameters are as shown in Table 1:

[0199] Parameter Nominal value Parameter Nominal value Parameter Nominal value B w ]]> 0.05 Nm / rad J s ]]> 2.8e -4 kg·m 2 ]]> [CAT mr1,s ]]> 0.06 Nm J w ]]> 0.028 kg-m 2 ]] K s ]]> 1 Nm / rad [CAT s2,c ]]> 0.05 Nm K h ]]> 4 Nm / rad G r1 ]]> 15 [CAT s2,s ]]> 0.69 Nm G fm ]]> 5 r p ]]> 0.08m [CAT r,c ]]> 0.6 Nm B mr1 ]]> 2.06e -4 Nm / rad B r ]]> 20 Nm / rad [CAT r,s ]]> 0.61 Nm J fm ]]> 4.5e -5 kg·m 2 ]]> M r ]]> 3 kg [CAT f,c ]]> 0.6 Nm K fm ]]> 0.123 Nm / A G r2 ]]> 1.4 [CAT f,s ]]> 0.7 Nm [R mr2 ]]> 0.22 Ω K r ]] 250 Nm / rad

[0019] N v ]]> 0.19 [K1] 1 A / V B f ]]> 25 Nm / rad <![CDATA[N f ]]> 700 [K2] 7 A / V J f ]]> 0.05 kg-m 2 ]] [0002N θ ]]> 12 [R s1 ]]> 0.03 Ω [CAT w,c ]]> 0.33 Nm s2 ]]> ​ 0.007 K m ]]> 0.097 Nm / A [CAT w,s ]]> 0.331 Nm r ]]> ​ 0.006 B s2 ]]> 0.0124 Nm / rad [CAT mr1,c ]]> 0.059 Nm <![CDATA[α w ,a mr1 ,a f ]]> 0.001

[0200] This embodiment references the CarSim and MATLAB APP to establish a front-end environment connected with a back-end model, which can conveniently adjust the model parameters, observe the model state, and observe the vehicle model's travel trajectory.

[0201] Please refer to Figures 14 to 21 , under different fault conditions, the system is added to the sine or ramp input, Figures 14 to 17 It can be seen that the actual front wheel steering angle value can stably follow the ideal value, and the vehicle model's travel trajectory meets the expectation, verifying that the effect of the sliding mode fault-tolerant control method of the present application is remarkable. From Figures 18 to 21 It can be seen that the front wheel tracking error is controlled within 0.03 rad, and the fault estimation error is controlled within 0.05 rad, further verifying the excellent fault-tolerant effect of the present application when a fault occurs during vehicle driving.

[0202] Embodiment 2

[0203] The computer terminal provided in this embodiment includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the sliding mode fault-tolerant control method of the steer-by-wire system of the vehicle are implemented.

[0204] As shown in Figure 22 , the computer terminal provided in this embodiment includes at least one processor 101 and a memory 102 connected with the at least one processor 101. In this embodiment, the specific connection medium between the processor 101 and the memory 102 is not limited, Figure 22 In this embodiment, the connection between the processor 101 and the memory 102 is taken by way of example through a bus 100. The bus 100 is connected Figure 22The connection between other components is only schematically shown by thick lines, and is not limited. The bus 100 can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, Figure 22 The bus 100 is only shown by one thick line, but does not mean that there is only one bus or only one type of bus. Alternatively, the processor 101 can also be called a controller, and the name is not limited.

[0205] In the embodiment, the memory 102 stores instructions executable by the at least one processor 101, and the at least one processor 101 can execute the foregoing method by executing the instructions stored in the memory 102.

[0206] The processor 101 is the control center of the device, and can connect all parts of the control device through various interfaces and lines. By running or executing the instructions stored in the memory 102 and calling the data stored in the memory 102, the device can process various functions and data, thereby monitoring the whole device.

[0207] In a possible design, the processor 101 can include one or more processing units, and the processor 101 can integrate an application processor and a modem processor. The application processor mainly processes operating systems, user interfaces, and application programs, etc., and the modem processor mainly processes wireless communication. It can be understood that the foregoing modem processor can also not be integrated into the processor 101. In some embodiments, the processor 101 and the memory 102 can be implemented on the same chip, and in some embodiments, they can also be implemented on independent chips respectively.

[0208] The processor 101 can be a general-purpose processor, such as a central processing unit (CPU), a digital signal processor, an application-specific integrated circuit, a field programmable gate array, or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, and can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments. The general-purpose processor can be a microprocessor or any conventional processor, etc. The steps of the slip fault-tolerant control method of the vehicle steer-by-wire system disclosed in Embodiment 1 can be directly embodied by a hardware processor for execution, or a combination of hardware and software modules in the processor 101 for execution.

[0209] The memory 102, as a non-volatile computer readable storage medium, can be used to store non-volatile software programs, non-volatile computer executable programs and modules. The memory 102 can include at least one type of storage medium, for example, can include flash memory, hard disk, multimedia card, card type memory, random access memory (RAM), static random access memory (SRAM), programmable read-only memory (PROM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), magnetic memory, magnetic disk, optical disk, etc. The memory 102 is any other medium capable of carrying or storing desired program code in the form of instructions or data structures and capable of being accessed by a computer, but is not limited thereto. The memory 102 in the embodiment can also be a circuit or any other device capable of realizing a storage function, used to store program instructions and / or data.

[0210] By programming the processor 101, the code corresponding to the safety verification method introduced in the foregoing embodiments can be fixed in the chip, so that the chip can execute the steps of the method shown in the figure at runtime. Figure 1 How to program the processor 101 is a technology known to those skilled in the art, and will not be described here.

[0211] Embodiment 3

[0212] The embodiment provides a computer readable storage medium, which stores a computer program, and the program is executed by a processor to realize the steps of the slip mode fault-tolerant control method of the vehicle steer-by-wire system according to the embodiment 1.

[0213] The computer readable storage medium can include a flash memory, a hard disk, a multimedia card micro type memory (e.g., SD or DX memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, and the like. In some embodiments, the storage medium can be an internal storage unit of the computer device, such as a hard disk or a memory of the computer device. In other embodiments, the storage medium can also be an external storage device of the computer device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, and the like. Of course, the storage medium can include both an internal storage unit and an external storage device of the computer device. In the present embodiment, the memory is generally used to store an operating system and various application programs installed in the computer device, and the like. In addition, the memory can also be used to temporarily store various data that has been output or will be output.

[0214] The above merely provides the preferred embodiment of the present application, and the protection scope of the present application is not limited thereto. Any person skilled in the art, according to the technical range disclosed in the present application and the inventive concept, can make equivalent replacements or changes, and all of them should be covered in the protection scope of the present application.

Claims

1. A sliding mode fault-tolerant control method for a vehicle steer-by-wire system, characterized in that, Includes the following steps: S1. Establish a nonlinear bond graph model of the steer-by-wire system, and use this model to establish a dynamic model of the front wheel subsystem in the steer-by-wire system; S2. Based on the dynamic model of the front wheel subsystem, a sliding mode controller is used to control the actual angle of the front wheel to track its reference angle so that the car travels on the desired trajectory. S3. When a sensor malfunction is detected in the vehicle, the sensor malfunction value is estimated using a sliding mode observer to eliminate the malfunction's impact and achieve fault-tolerant control. Step S1 includes the following specific steps: S11. The steer-by-wire system is divided into a steering wheel system and a front wheel subsystem; wherein, the steering wheel system includes a steering wheel, a feedback motor, a reducer, a feedback motor driver, a steering wheel angle sensor, and a feedback motor angle sensor, and the front wheel subsystem includes a steering motor driver, a steering motor, a reducer, a gear, a rack, a front wheel, a steering motor angle sensor, a gear angle sensor, and a front wheel angle sensor. S12. Construct a nonlinear bond graph model based on bond graph theory; wherein, the basic components of the nonlinear bond graph model include a single-port element, a two-port element, and a multi-port element; the single-port element includes a potential source. Se Source Sf Dissipative components R Inertial elements I Capacitive components C and flow sensor The dual-port element includes a converter. Rotary The multi-port element includes type 1 nodes and type 0 nodes. S13. A dynamic model of the front wheel subsystem is established using a nonlinear bond graph model, and its expression is as follows: In the formula, The torque constant of the steering motor; It is the input voltage of the steering motor; The coefficient of viscous friction of the steering motor; For the steering motor angle, and They are respectively The first and second derivatives; For the stiffness of the steering motor shaft; This represents the rack displacement; The reduction ratio of the reducer; Where is the gear radius; This is the moment of inertia of the steering motor rotor; This indicates the frictional force of the rack; Indicates rack stiffness; This represents the ratio of the rack's linear velocity to the front wheel's angular velocity. This is the actual steering angle of the front wheels; Indicates the mass of the rack; The steering angle of the front wheels; This refers to the friction between the tire and the ground. The moment of inertia of the front wheel; Let the friction torque characteristic function of the steering motor be _____. This is the characteristic function of gear friction torque. Let be the characteristic function of the front wheel friction torque; the formulas for the three are as follows: , ,in, and These are the Coulomb friction torque and static friction torque of the corresponding components, respectively. It is a representation and The constant of the transition between them, As the independent variable; This is the self-correcting torque; Step S2 includes the following specific steps: S21. Set the system state and system input based on the dynamic model of the front wheel subsystem; whereby the system input is the steering motor driver input voltage. System status The formula for expressing it is: In the formula, Indicates time; superscript T It is the transpose symbol; S22. Establish a state-space model of the steer-by-wire system under healthy conditions, expressed by the following formula: In the formula, The derivative of the system state variables; This is the system output, specifically the front wheel steering angle. This refers to the sliding mode control rate, i.e., the input voltage of the steering motor driver. Function that changes with time; It is a nonlinear term; For lumped interference; , and These are the state transition coefficient matrix, the input coefficient matrix, and the output coefficient matrix, respectively. S23. After simplifying the dynamic model of the front wheel subsystem, the dynamic equations of the front wheel subsystem are obtained: In the formula, It is the equivalent moment of inertia; This is the equivalent damping coefficient; It is a nonlinear frictional torque; This refers to the motor output torque coefficient; S24. Based on the aforementioned dynamic equations, a sliding mode control rate is set, and a sliding mode controller controls the input voltage signal of the steering motor driver according to the sliding mode control rate, so that the actual angle of the front wheel tracks its reference angle; wherein, the input voltage of the steering motor driver... The calculation formula is: In the formula, This serves as a reference signal for the front wheel steering angle. ; It is a sliding surface; For symbolic function terms, It is a linear term; In step S3, when a sensor malfunction is detected, the sliding mode observer automatically controls the motor output according to its own design to achieve fault tolerance; the design method of the sliding mode observer includes the following specific steps: S31. Establish a state-space model of the steer-by-wire system under sensor failure, expressed by the following formula: In the formula, Let the state variable be the car. Output for the steer-by-wire system; The control input is the input voltage of the steering motor driver. , To provide feedback on the motor torque constant, Let be the moment of inertia of the front wheel. The coefficient of viscous friction of the front wheel; , This is the transmission ratio between the rack displacement and the front wheel steering angle; This is the output gain matrix; This refers to the nonlinear term in the steer-by-wire system. ; For lumped interference; ; The problem is a sensor malfunction. S32. Augmented reconstruction of the state-space model of the steer-by-wire system under sensor failure conditions yields the augmented matrix: In the formula, Let be the augmented state variables, where This is a user-defined variable, which can be used for output. Implement low-pass filtering that satisfies the formula: ; , The stable filtering matrix is ​​defined as a diagonal positive definite matrix; ; ; ; ; ; S33. Design a sliding mode observer using the augmented matrix, expressed as follows: In the formula, for The estimated value; for The estimated value; for The augmented transpose, i.e. ; For discontinuities in the sliding mode observer; is the gain matrix of the sliding mode observer.

2. The sliding mode fault-tolerant control method for a vehicle steer-by-wire system according to claim 1, characterized in that, After completing the design of the sliding mode observer, calculate the sensor failure prediction value, i.e., the discontinuity term in the sliding mode observer. v The formula is as follows: In the formula, and For positive scalar gain, ; To satisfy the formula Any matrix, It is a 3×3 real symmetric matrix; It is a positive scalar; calculate ;in, for The estimated value; The following formula is used to achieve fault tolerance for faulty sensors: In the formula, The front wheel steering angle after tolerance; This is the actual output of the faulty sensor; The error is the sensor fault estimation error, which converges to zero within a finite time.

3. A computer terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the sliding mode fault-tolerant control method for the automotive steer-by-wire system as described in any one of claims 1 to 2.

4. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the sliding mode fault-tolerant control method for the automotive steer-by-wire system as described in any one of claims 1 to 2.

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