A method of stability control for a steer-by-wire four-wheel steering vehicle

Abstract

The application discloses a kind of line control four-wheel steering vehicle stability control method, belong to vehicle steering control field.The vehicle yaw rate signal and ideal yaw rate collected as the input signal of active disturbance rejection controller, with the ideal yaw rate as target, additional front wheel angle needed to guarantee yaw rate tracking is calculated, to compensate for front wheel angle;The mass side slip angle deviation collected as the input signal of rear wheel angle controller, with the mass side slip angle as target, rear wheel angle is calculated and output.The application can guarantee the tracking of yaw rate and the zero of mass side slip angle, improve the stability of vehicle in steering process, and can be applied to control the stability of four-wheel steering vehicle.

Description

Technical Field

[0001] This invention belongs to the field of vehicle steering control technology, specifically relating to a steer-by-wire vehicle stability controller based on active disturbance rejection control and PID control. Background Technology

[0002] Steer-by-wire (SBW) eliminates some of the mechanical connection between the steering wheel and the steering wheels, overcoming various limitations of traditional steering systems and further improving vehicle handling, comfort, and safety. Four-wheel steering (4WS), as a new type of independent steering technology, can independently control the turning angle of each wheel, improving vehicle handling stability.

[0003] Currently, methods such as PID control, fuzzy control, sliding mode control, neural network control, and robust H∞ control are mainly used to improve vehicle handling stability. Due to the greater degree of freedom in automotive steer-by-wire design, more stringent requirements are placed on the control strategy for active steering. Traditional PID control and sliding mode control are insufficient to meet the requirements of active steering stability control and cannot adequately handle model uncertainties and system disturbances.

[0004] Active Disturbance Rejection Control (ADRC) is a control strategy derived from the control theory concept of "error elimination based on error." Unlike model-based control, it is completely independent of the mathematical model of the controlled object. Its most prominent feature is that it attributes all uncertainties acting on the controlled object to "unknown disturbances," without needing to know the laws governing the disturbances. Instead, it uses the input and output data of the controlled object to estimate and compensate for them in real time. ADRC features fast response, short settling time, strong anti-interference capability, and simple algorithms that are easy to implement in engineering, thus it has been widely used in the field of engineering control.

[0005] There are many methods to improve the stability of four-wheel steering vehicles during steering. Common methods include feedback on yaw rate and feedback on center of gravity sideslip angle. The main goal is to control the yaw rate of the vehicle to the expected standard by using some control algorithms in combination with feedback. However, the center of gravity sideslip angle output by the controlled vehicle is not guaranteed much, and the stability of the vehicle during steering needs to be improved. Summary of the Invention

[0006] The purpose of this invention is to provide a method for controlling the stability of a four-wheel steering vehicle to improve the stability of the four-wheel steering vehicle during the steering process.

[0007] To address the aforementioned technical problems, this invention controls the vehicle's yaw rate and sideslip angle separately. This ensures both the tracking of the controlled vehicle's yaw rate and the simultaneous reduction of the sideslip angle to zero, thereby improving vehicle stability during cornering and providing the driver with a better driving experience. The specific technical solution adopted in this invention is as follows.

[0008] A method for controlling the stability of a four-wheel steering vehicle, characterized by being based on active disturbance rejection control and PID control, specifically includes the following steps:

[0009] Step 1: Use sensors to collect the vehicle speed V and steering wheel angle δ of the controlled vehicle. sw As the input signal to the feedforward controller, the front wheel steering angle δ of the four-wheel steer-by-wire vehicle is calculated. f ;

[0010]

[0011] in,

[0012]

[0013] L f L is the distance from the car's center of gravity to the front axle. r Let m be the distance from the car's center of gravity to the rear axle, and C be the car's mass. f For the lateral stiffness of the front tires, C r Let i be the tire lateral stiffness of the rear wheel, and δ be the steering wheel angle. sw With the front wheel steering angle δ f The ideal angular transmission ratio between them This represents the steady-state yaw rate gain of the vehicle, which is approximately 0.16–0.33 s. -1 ;

[0014] Step 2: Acquire the vehicle yaw rate γ, and compare the acquired vehicle yaw rate signal γ with the ideal yaw rate γ. d As the input signal to the active disturbance rejection controller, to track the ideal yaw rate γ d To achieve the control objective, the output u of the active disturbance rejection controller is calculated and used as the additional front wheel steering angle Δδ. f The additional front wheel steering angle Δδ will be added. f With the initial front wheel steering angle δ f The sum of these values ​​is used as the new front wheel steering angle δ of the vehicle. fz The output is given to the controlled vehicle, thereby enabling the vehicle's yaw rate γ to better track the vehicle's ideal yaw rate γ. d ;

[0015] Step 3: Collect the sideslip angle β of the centroid and the ideal sideslip angle β.d The deviation is used as the input to the rear wheel steering angle controller. With the zero centroid sideslip angle as the target, the output c(t) of the rear wheel steering angle controller is calculated and used as the rear wheel steering angle δ. r The rear wheel steering angle controller uses a PID controller;

[0016] Step 4, the additional front wheel steering angle Δδ output by the active disturbance rejection controller f The front wheel steering angle δ output by the feedforward controller f The sum of δ fz The new front wheel steering angle is output to the controlled vehicle, while the rear wheel steering angle δ output by the PID controller is also used. r Output to the controlled vehicle.

[0017] The active disturbance rejection controller (ANSCEF) construction method includes the design of the fastest tracking differentiator (TD), the extended state observer (ESO), and the feedback control law. The TD is used to set the transient process for a given signal and extract the differential value of the signal. The ESO is the key in the active disturbance rejection technology. It can not only observe the state variables and their derivative estimates, but also estimate and compensate for system disturbances. The NLSEF nonlinearly combines the outputs of the TD and ESO, and together with the disturbance compensation, forms the control quantity of the system.

[0018] The design of the fastest tracking differentiator TD is as follows:

[0019] The input of the fastest tracking differentiator TD module is v, and the outputs are v1 and v2; v is the desired signal value, v1 represents the tracking value of the desired signal v, and v2 represents the estimated value of the derivative of the desired signal v.

[0020] A closed-loop control system that uses yaw rate as the feedback signal;

[0021] If an active disturbance rejection control strategy is used, then the desired signal value v mentioned above represents the ideal yaw rate γ. d ;

[0022]

[0023] Among them, the fastest control synthesis function fhan is the core function of the tracking differentiator TD in the Active Disturbance Rejection Controller (ADRC), which enables the state variables to quickly track the system input. The fhan function is defined as follows:

[0024] Let fsg(x,d) = (sign(x+d) - sign(xd)) / 2

[0025] Then the function fhan(x1,x2,r,d) can be expressed as

[0026]

[0027] r0 represents the speed factor, which determines the tracking speed; h0 is the filtering factor of the tracking differentiator. When the integration step size h is determined, increasing the filtering factor is an effective way to enhance the filtering effect.

[0028] The extended state observer (ESO) is designed as follows:

[0029] The inputs to the Extended State Observer (ESO) module are y and the product of the system control quantity u and the system proportional parameter b0. The outputs are z1, z2 and z3. y is the output value of the controlled object, i.e. the feedback value of the control system. z1 is the estimated value of y. z2 is the estimated value of the derivative of y. z3 is the estimated value of the overall disturbance caused by internal and external factors to the controlled vehicle.

[0030] In a closed-loop control system that uses yaw rate as feedback signal, if an active disturbance rejection control strategy is used, the output value y of the controlled object represents the actual yaw angle γ.

[0031]

[0032] In the formula, e is the observation error, β1, β2, β3 are the adjustable parameters of the extended state observer, h is the system step size, b0 is the system proportional parameter, u is the system control quantity, and fe, fe1 are the system intermediate variables.

[0033] The fal function is defined as follows:

[0034]

[0035] In the formula, sign(x) is the sign function:

[0036]

[0037] The fal function is a special nonlinear structure and is the core part of the extended state observer (ESO) in the active disturbance rejection controller. The ESO uses the nonlinear structure fal function and then selects the observer parameters to obtain the estimated values ​​of all system states.

[0038] The design of the feedback control law is as follows:

[0039] The feedback control law module nonlinearly combines the outputs of the TD module and the ESO module to obtain the nonlinear state error feedback output u0;

[0040]

[0041] v1 and v2 represent the transient processes of the first-order tracking differentiator output; z1 and z2 represent the outputs of the extended state observer; c, r1, and h1 are the adjustable parameters of the nonlinear error feedback law.

[0042] The disturbance compensation process is designed as follows: The disturbance compensation process feeds back the nonlinear state error output u0, which, together with the disturbance compensation, constitutes the control quantity of the system.

[0043] u = u0 - z3 / b0

[0044] u is the control quantity input to the controlled object after disturbance compensation, and u corresponds to the additional front wheel steering angle Δδ. f .

[0045] This invention offers several advantages. It uses the acquired vehicle yaw rate signal and the ideal yaw rate as input signals to an active disturbance rejection controller (ADRC). With the goal of tracking the ideal yaw rate, it calculates the additional front wheel angle required to ensure yaw rate tracking. The sum of this additional front wheel angle and the initial front wheel angle is output as the new front wheel angle to the controlled vehicle. Similarly, it uses the acquired sideslip angle deviation as input signals to a rear wheel angle controller, aiming to zero out the sideslip angle, and calculates and outputs the rear wheel angle. This invention simultaneously ensures yaw rate tracking and that the sideslip angle approaches zero, improving vehicle stability during cornering. Attached Figure Description

[0046] Figure 1 This is a logic block diagram of the four-wheel steer-by-wire control system of the present invention;

[0047] Figure 2 This is a block diagram of the active disturbance rejection controller;

[0048] Figure 3 This is a block diagram of a PID controller. Detailed Implementation

[0049] The technical solutions of the present invention will be described in detail below with reference to the accompanying drawings.

[0050] The overall control logic of the four-wheel steer-by-wire system is as follows: Figure 1 As shown, the specific steps include the following:

[0051] First, using vehicle speed and steering wheel angle information collected by sensors as input signals to the feedforward controller, the front wheel steering angle δ of the four-wheel steer-by-wire vehicle is calculated. f .

[0052] Then, the vehicle yaw rate signal γ is acquired and output to the ADRC control module to track the ideal yaw rate γ. d To control the target, the additional front wheel steering angle Δδ was calculated. f It is used to correct the vehicle's yaw rate γ.

[0053] Simultaneously, the centroid sideslip angle β and the ideal centroid sideslip angle β are collected.d The deviation is used as the input to the rear wheel steering angle controller. With the goal of zeroing the centroid sideslip angle, the calculated output rear wheel steering angle δ is then used. r The rear wheel steering angle controller uses a PID controller, and its control block diagram is as follows: Figure 3 As shown, the controller input r(t) represents the difference between the actual sideslip angle β and the ideal sideslip angle β of the controlled vehicle. d The difference is given by the output c(t), which represents the rear wheel steering angle δ. r The calculation formula for a PID controller is as follows: During the simulation, the controller parameter is k. p =10,k i =80,k d =0.1.

[0054] Finally, the additional front wheel steering angle Δδ output by the active disturbance rejection controller is... f The front wheel steering angle δ output by the feedforward controller f The sum of δ fz The new front wheel steering angle is output to the controlled vehicle, while the rear wheel steering angle δ output by the PID controller is also used. r Output to the controlled vehicle.

[0055] The front wheel steering angle controller uses an ADRC controller, which consists of three parts: a tracking differentiator (TD), an extended state observer (ESO), and a nonlinear state error feedback control law (NLSEF). The ADRC control block diagram is shown below. Figure 2 As shown, the function of TD is to set the transient response for a given signal and extract the differential value of the signal; ESO is the key in active disturbance rejection technology, which can not only observe the state variables and their derivative estimates, but also estimate and compensate for system disturbances; NLSEF nonlinearly combines the outputs of TD and ESO, together with disturbance compensation, to form the control quantity of the system. The design steps of the active disturbance rejection controller are as follows:

[0056] Design of the fastest tracking differentiator TD:

[0057] The fastest tracking differentiator module takes v as input and outputs v1 and v2. v is the desired signal value, v1 represents the tracked value of the desired signal v, and v2 represents the estimated value of the derivative of the desired signal v.

[0058] The research content of this invention is a closed-loop control system with yaw rate as the feedback signal. If an active disturbance rejection control strategy is used, the aforementioned desired signal value v represents the ideal yaw rate γ.d .

[0059]

[0060] In the formula, r0 represents the speed factor, which determines the tracking speed; parameter h0 is the filtering factor of the tracking differentiator. When the integration step size h is determined, increasing the filtering factor is an effective way to enhance the filtering effect.

[0061] Let fsg(x,d) = (sign(x+d) - sign(xd)) / 2

[0062] Then u = fhan(x1,x2,r,d) can be expressed as

[0063]

[0064] Design of Extended State Observer (ESO):

[0065] The inputs to the extended state observer module are y and the product of the system control quantity u and the system proportional parameter b0. The outputs are z1, z2, and z3. y is the output value of the controlled object, i.e., the feedback value of the control system; z1 is the estimated value of y; z2 is the estimated value of the derivative of y; and z3 is the estimated value of the overall disturbance caused by internal and external factors to the controlled object.

[0066] The research content of this invention is a closed-loop control system with yaw rate as feedback signal. If an active disturbance rejection control strategy is used, the output value y of the controlled object represents the actual yaw angle γ.

[0067]

[0068] In the formula, e is the observation error, β1, β2, and β3 are the adjustable parameters of the extended state observer, h is the system step size, b0 is the system proportional parameter, u is the system control quantity, and fe and fe1 are the system intermediate variables.

[0069] in,

[0070]

[0071] In the formula, sign(x) is the sign function:

[0072]

[0073] Design of feedback control laws:

[0074] The feedback control law module nonlinearly combines the outputs of the TD module and the ESO module to obtain the nonlinear state error feedback output u. 0。

[0075]

[0076] In the formula, v1 and v2 are the transient processes of the first-order tracking differentiator output, z1 and z2 are the outputs of the extended state observer, and c, r1, and h1 are the adjustable parameters of the nonlinear error feedback law.

[0077] Disturbance compensation process:

[0078] This process combines the nonlinear state error feedback output u0 with disturbance compensation to form the system's control quantity.

[0079] u = u0 - z3 / b0

[0080] In the formula, u is the control quantity input to the controlled object after disturbance compensation, and u corresponds to the additional front wheel steering angle Δδ. f .

[0081] To verify the steerable four-wheel steering vehicle stability control method based on active disturbance rejection control and PID control of the present invention, a simulation experiment of steerable four-wheel steering vehicle stability control was conducted on the MATLAB / Simulink platform. The controller parameters are shown in Table 1.

[0082] Table 1. Parameters of Active Disturbance Rejection Controller

[0083]

[0084] The above embodiments are used to illustrate the design concept and features of the present invention, which can be understood by those skilled in the art.

Claims

1. A method of stability control for a steer-by-wire four-wheel-steering vehicle, characterized by Based on active disturbance rejection control and PID control, specifically comprising the following steps: Step 1, the sensor collects the speed V and steering wheel angle information δ of the vehicle to be controlled sw As a feedforward controller input signal, the front wheel angle δ of the four-wheel steer-by-wire vehicle is calculated f ; Wherein, L f is the distance from the center of mass of the vehicle to the front axle, L r is the distance from the center of mass of the vehicle to the rear axle, m is the mass of the vehicle, C f is the tire cornering stiffness of the front wheels, C r is the tire cornering stiffness of the rear wheels, i is the steering wheel angle δ sw is the ideal angular transmission ratio between the steering wheel angle δ f and the front wheel angle δ is the vehicle steady state yaw rate gain, which is approximately 0.16-0.33 s -1 ; Step 2, collect vehicle yaw rate γ, add the collected vehicle yaw rate signal γ and the ideal yaw rate γ d as an input signal of the active disturbance rejection controller to track the ideal yaw rate γ d As a control target, the output quantity u of the active disturbance rejection controller is calculated f , as an additional front wheel steering angle Δδ f , and the initial front wheel steering angle δ f is added to obtain a new vehicle front wheel steering angle δ fz , which is output to the controlled vehicle, so that the vehicle yaw rate γ better tracks the ideal vehicle yaw rate γ d ; Step 3: Collect the sideslip angle β of the centroid and the ideal sideslip angle β. d The deviation is used as the input to the rear wheel steering angle controller. With the zero centroid sideslip angle as the target, the output c(t) of the rear wheel steering angle controller is calculated and used as the rear wheel steering angle δ. r The rear wheel steering angle controller uses a PID controller; Step 4: Add the additional front wheel angle Δδ f output from the disturbance controller to the front wheel angle δ f output from the feedforward controller fz as the new front wheel angle output to the vehicle, while the rear wheel angle δ r output from the PID controller is output to the vehicle.

2. A drive-by-wire four-wheel steering vehicle stability control method according to claim 1, characterized by, The active disturbance rejection controller construction method comprises design of a fastest tracking differentiator TD, design of an extended state observer ESO and design of a feedback control law; the differentiator TD is used to set a transition process for a given signal and extract a differential value of the signal; the ESO is a key in the active disturbance rejection technology, which can not only observe state variables and their derivative estimation values, but also estimate and compensate for system disturbances; the NLSEF performs nonlinear combination on outputs of the TD and the ESO to form a control amount of the system in combination with disturbance compensation.

3. A steer-by-wire four-wheel-steering vehicle stability control method according to claim 2, characterized by The design of the fastest tracking differentiator TD is as follows: The input of the fastest tracking differentiator TD module is v, and the output is v1 and v2; v is a desired signal value, v1 represents a tracking value of the desired signal v, and v2 represents an estimated value of a differential of the desired signal v; A closed-loop control system with a yaw rate as a feedback signal; If an active disturbance rejection control strategy is used, the above-mentioned desired signal value v represents the ideal yaw rate γ d ; Wherein, the fastest control synthesis function fhan is a core function of the tracking differentiator TD in the active disturbance rejection controller ADRC, so that a state variable can quickly track a system input; the fhan function is defined as follows: Let fsg(x, d) = (sign(x + d) - sign(x - d)) / 2 Then the function fhan(x1, x2, r, d) can be expressed as r0 represents a speed factor, which determines a tracking speed; h0 is a filter factor of the tracking differentiator, and when an integral step size h is determined, enlarging the filter factor is an effective means to enhance the filter effect.

4. A steer-by-wire four-wheel-steering vehicle stability control method according to claim 2, characterized by The design of the extended state observer ESO is as follows: The input of the extended state observer ESO module is y and a product of a system control amount u and a system proportional parameter b0, and the output is z1, z2 and z3; y is an output value of a controlled object, i.e., a feedback value of the control system, z1 is an estimated value of y, z2 is an estimated value of a differential of y, and z3 is an estimated value of a total disturbance of the controlled vehicle caused by internal and external factors; A closed-loop control system with a yaw rate as a feedback signal, if an active disturbance rejection control strategy is used, the output value y of the controlled object represents an actual yaw angle γ; In the formula, e is an observation error, β1, β2, β3 are adjustable parameters of the extended state observer, h is a step size of the system, b0 is a proportional parameter of the system, u is a control amount of the system, and fe, fe1 are intermediate variables of the system; The fal function is defined as follows: In the formula, sign(x) is a sign function: The fal function is a special nonlinear structure, which is a core part of the extended state observer ESO in the active disturbance rejection controller; the ESO uses the nonlinear structure fal function, and then selects observer parameters, so that estimated values of all states of the system can be obtained.

5. A steer-by-wire four-wheel-steering vehicle stability control method according to claim 2, characterized by The design of the feedback control law is as follows: The feedback control law module performs nonlinear combination on outputs of the TD module and the ESO module to obtain a nonlinear state error feedback output amount u0; v1 and v2 are transition processes of the first-order tracking differentiator outputs; z1 and z2 are outputs of the extended state observer; c, r1 and h1 are adjustable parameters of the nonlinear error feedback law.

6. A steer-by-wire four-wheel-steering vehicle stability control method according to claim 2, characterized by The design of the disturbance compensation process is as follows: the disturbance compensation process combines the nonlinear state error feedback output quantity u0with the disturbance compensation to form the control quantity of the system; u = u0- z3b0 u is the control amount input to the control object after disturbance compensation, and u corresponds to the additional front wheel steering angle Δδ f .

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