A hierarchical architecture multi-objective performance control method and system based on a steer-by-wire system

Abstract

The present application relates to the technical field of automobile steering control, in particular to a layered architecture multi-target performance control method and system based on a steer-by-wire system, comprising obtaining vehicle-related parameters and tire-related parameters; obtaining a current driving mode of the automobile, obtaining a current target performance coefficient based on the driving mode, obtaining a vehicle performance target and a weight coefficient based on the target performance coefficient; compensating multiple targets based on the vehicle-related parameters, the tire-related parameters, the vehicle performance target and the weight coefficient. The above method of the present application realizes the control output of the front and rear wheels based on a unified control method, meets the vehicle performance requirements of different scenes and functions, and the whole system can meet the control of SBW front-wheel steer-by-wire, RWS rear-wheel active steering and four-wheel steer-by-wire. Only the performance target coefficient, the weight coefficient, the calibration parameter and the constraint parameter need to be set and debugged for different systems, which can greatly shorten the development cycle.

Description

Technical Field

[0001] This invention relates to the field of automotive steering control technology, and more specifically, to a hierarchical architecture multi-objective performance control method and system based on a steer-by-wire system. Background Technology

[0002] Steer-by-wire (SBW) is an advanced system that eliminates traditional mechanical connections, transmitting the driver's steering intentions and controlling wheel steering entirely through electrical signals. Currently a standard feature in high-end vehicles, it enhances low-speed maneuverability and high-speed stability. With the development of high-end and intelligent domestic models, vehicles equipped with rear-wheel active steering, front steer-by-wire, and even four-wheel steer-by-wire systems are gradually emerging, and more models with this feature are expected to appear in the future. Steer-by-wire control strategies are currently a key research and development focus for OEMs and component manufacturers.

[0003] However, current technologies employ different control strategies for different scenarios and functions, requiring independent modeling and calibration based on scenario and functional requirements. This results in complex algorithms, time-consuming calibration, and large software space consumption. Rear-wheel steer-by-wire, front-wheel steer-by-wire, and four-wheel steer-by-wire use different control methods, making it difficult to meet the needs of different products and vehicle configurations. Linearizing and simplifying the control algorithm fails to meet the nonlinear characteristics of vehicles and the control accuracy and real-time requirements under large steering angles. Summary of the Invention

[0004] The purpose of this invention is to provide a hierarchical architecture multi-objective performance control method and system based on a steer-by-wire system to solve the above-mentioned problems in the prior art.

[0005] This invention is achieved through the following technical solution:

[0006] A hierarchical architecture multi-objective performance control method based on a steer-by-wire system includes:

[0007] Obtain the basic parameters of the current vehicle, and based on the basic parameters, identify the whole vehicle parameters and tire parameters to obtain the relevant parameters of the whole vehicle and tires.

[0008] Obtain the current driving mode of the vehicle, obtain the current target performance coefficient based on the driving mode, and obtain the overall vehicle performance target and weight coefficient based on the target performance coefficient;

[0009] The initial output control request is corrected by compensating for multiple targets based on vehicle-related parameters, tire-related parameters, vehicle performance targets, and weighting coefficients.

[0010] Establish a constraint model and set constraint trigger conditions. When the vehicle's operating parameters are measured, the utilization rate is output through the constraint model based on the operating parameters. If the utilization rate is greater than or equal to the constraint trigger conditions, feedback compensation is performed on the corresponding constraint object.

[0011] Preferably, obtaining the vehicle performance target and weighting coefficients based on the target performance coefficient includes:

[0012] The vehicle performance targets include target yaw rate gain, target center of gravity sideslip angle gain, and target overall vehicle lateral velocity gain.

[0013] Establish a mapping table of performance coefficients and weighting coefficients for different driving modes regarding steering wheel angle and vehicle speed. The performance coefficients include yaw rate performance coefficient, center of gravity sideslip angle performance coefficient, and overall vehicle lateral speed performance coefficient. The weighting coefficients include yaw rate weighting coefficient, center of gravity sideslip angle weighting coefficient, and overall vehicle lateral speed weighting coefficient.

[0014] Based on the current driving mode, steering wheel angle, and vehicle speed, the performance coefficient and weighting coefficient are obtained by indexing the mapping table.

[0015] Based on the current performance ratio and performance coefficient, the target yaw rate gain, the target centroid sideslip angle gain, and the target vehicle global lateral velocity gain are obtained.

[0016] Preferably, the step of calculating control requests for multiple targets based on vehicle-related parameters, tire-related parameters, vehicle performance targets, and weighting coefficients, and outputting front and rear wheel steering angle control requests, includes: target weighted sliding surfaces, equivalent control terms, switching control, delay compensators, and control execution constraints.

[0017] Preferably, the compensation for the target weight sliding surface includes obtaining the sliding surface by taking the control target error after multi-target weighting as input:

[0018]

[0019] In the formula, For sliding surface, The angular velocity weighting coefficient is used. For yaw rate tracking error, The weighting coefficient for the centroid sideslip angle. This represents the tracking error of the centroid sideslip angle.

[0020] Preferably, the compensation for the equivalent control term includes dividing the equivalent control into linear and nonlinear range conditions based on the overall dynamics and tire characteristics, and establishing an equivalent control model with the front and rear wheel steering angles as boundaries:

[0021]

[0022] In the formula, For equivalent control items, , These are the equivalent control terms for the front and rear wheels, respectively. It is a Jacobian matrix. Let be the desired rate of change of yaw rate.

[0023] Preferably, the switching control compensation includes defining the switching term using a saturation function:

[0024]

[0025] In the formula, To switch control compensation terms, For switching gain coefficients, For the boundary layer, It is a saturation function.

[0026] Preferably, compensating the delay compensator includes:

[0027] Based on the Smith predictor to eliminate the impact of execution delay, the delay compensation items for the front and rear wheels are as follows:

[0028]

[0029]

[0030]

[0031] In the formula, This is a front wheel delay compensation item. This is a front wheel steering command. This is the actual steering angle of the front wheels. For the Laplace operator, This is a rear wheel delay compensation item. This is a rear wheel steering command. This is the actual steering angle of the rear wheels. For delay compensation control items, The delay time constant of the front wheel actuator. The delay time constant for the rear wheel actuator;

[0032] Compensating the control execution includes combining multiple control terms into a final control law output:

[0033]

[0034] In the formula, This is the final wheel angle control output request, including front wheel and rear wheel steering control output requests.

[0035] Preferably, the establishment of the constraint model includes establishing tire adhesion limit constraints, steering angle magnitude constraints, and execution speed constraints:

[0036] The tire adhesion limit constraints include:

[0037]

[0038]

[0039] In the formula, The maximum lateral force of the tire. To improve tire utilization, For the vertical load of the tire, To estimate the required tire lateral force;

[0040] The steering angle magnitude constraint includes obtaining the maximum steering angle of the wheel:

[0041]

[0042]

[0043] In the formula, The maximum turning angle of the wheel. For tire lateral stiffness, This represents the maximum slip ratio corresponding to the tire's adhesion limit. This is a wheel steering angle command. For the first actuator stroke utilization rate;

[0044] The execution speed constraint includes: based on the thrust-rate characteristic curves of the forward and rearward steering actuators: ,Will Converted to maximum wheel rotation speed For control output Differentiate to obtain the required speed ;

[0045]

[0046] In the formula, For the actuator's maximum speed, The actuator's speed curve is represented by a change in load. For actuator load, For the second actuator stroke utilization rate, For time.

[0047] Preferably, the step of providing feedback compensation to the corresponding constraint object includes:

[0048] The triggering state and over-limit state of the constraint state are fed back to the hierarchical compensation. The feedback results include:

[0049] Constraint trigger state: ;

[0050] Constraint overrun rate: ;

[0051] If the constraint is not triggered, the control request is output to the next limiting module;

[0052] When any constraint condition is triggered, initiate the compensation input and define the compensation influence factor matrix:

[0053]

[0054] The sliding surface is corrected based on the compensation influence factor matrix to compensate for the equivalent control.

[0055] In the formula, This is the trigger state for tire adhesion limit constraints. This is the trigger state for the corner amplitude constraint. To trigger the execution of speed constraints, To compensate for the impact factor, This is a compensation factor for the tire adhesion limit constraint. The compensation influence factor for the angle amplitude constraint, This is a compensation factor for implementing speed constraints.

[0056] Secondly, the present invention also provides a hierarchical architecture multi-objective performance control system based on a steer-by-wire system, comprising:

[0057] The data and status recognition module is configured to acquire the basic parameters of the current vehicle, and based on the basic parameters, perform vehicle parameter recognition and tire parameter recognition to obtain vehicle-related parameters and tire-related parameters.

[0058] The vehicle performance planning module is configured to obtain the current driving mode of the vehicle, obtain the current target performance coefficient based on the driving mode, and obtain the vehicle performance target and weight coefficient based on the target performance coefficient.

[0059] The front and rear wheel distribution module is configured to calculate control requests for multiple targets based on vehicle-related parameters, tire-related parameters, vehicle performance targets, and weighting coefficients; correct the initial output control request; output the current wheel steering angle control request; establish a constraint model and set constraint trigger conditions; when the vehicle's operating parameters are used, the utilization rate is output through the constraint model based on the operating parameters; if the utilization rate is greater than or equal to the constraint trigger condition, feedback compensation is performed on the corresponding constraint object.

[0060] The technical solution of the present invention has at least the following advantages and beneficial effects:

[0061] Using the above-mentioned method of the present invention, the control output of the front and rear wheels is realized based on a unified control method, which has wide applicability and meets the vehicle performance requirements of different scenarios and functions. The whole system can meet the control of SBW front wheel steer-by-wire, RWS rear wheel active steering, and four-wheel steer-by-wire. Only the performance target coefficient, weight coefficient, calibration parameter, and constraint parameter need to be set and debugged for different systems, which can significantly shorten the development cycle.

[0062] It is applicable to all scenarios. The control algorithm and dynamic equations meet the precise requirements of nonlinear and large-angle driving conditions, as well as longitudinal and lateral composite conditions. At the same time, it adopts small-angle linear and interpolation methods to meet the real-time requirements of the control system.

[0063] It has rich scalability and defines the performance of functional scenarios through the architecture design of performance target coefficients and weight coefficients, providing interfaces and convenience for the subsequent integration of adaptive and intelligent decision-making systems. It can train and output performance target coefficients and weight coefficients based on vehicle data and driver wearable data.

[0064] The use of a compensated sliding mode controller gives the control system strong anti-interference performance, compensating for differences between the vehicle / tire model and the actual vehicle, and ensuring control stability and robustness. The multi-layered architecture, especially the actuator constraint mechanism, provides the control system with excellent safety. Attached Figure Description

[0065] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0066] Figure 1 This is a schematic diagram of the process of the present invention;

[0067] Figure 2 This is a schematic diagram of the process for observing the lateral velocity and center of gravity sideslip angle of the vehicle according to the present invention;

[0068] Figure 3 This is the overall relaxation sliding mode control logic diagram of the present invention;

[0069] Figure 4 This is a schematic diagram of the equivalent control logic of the present invention. Detailed Implementation

[0070] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0071] The module division in this application is a logical division. In actual application, there may be other division methods. For example, multiple modules may be combined into or integrated into another system, or some features may be ignored or not executed.

[0072] In addition, the connection, coupling or communication in this application can be a direct connection, coupling or communication between related objects, or an indirect connection, coupling or communication through other devices. Furthermore, the connection, coupling or communication between objects can be electrical or other similar forms, and no limitation is made in this application.

[0073] The independently described modules or sub-modules may or may not be physically separated; they may be implemented in software or hardware, and some modules or sub-modules may be implemented in software, with the processor calling the software to implement the function of these modules or sub-modules, while other modules or sub-modules may be implemented in hardware, such as through hardware circuits. Furthermore, some or all of the modules can be selected to achieve the purpose of this application's solution according to actual needs.

[0074] Please refer to Figures 1-4 A hierarchical architecture multi-objective performance control method based on a steer-by-wire system includes:

[0075] S101: Obtain the basic parameters of the current vehicle, and perform vehicle parameter recognition and tire parameter recognition based on the basic parameters to obtain vehicle-related parameters and tire-related parameters;

[0076] Basic parameter processing mainly involves processing and converting the sensor signals input to the steering system to obtain the wheel angle signal.

[0077] Vehicle parameter identification involves calculating and identifying parameters that cannot be directly obtained by sensors to meet control requirements. These parameters mainly include: vehicle lateral speed, equivalent sideslip angles of the front and rear axles, stability factors, sideslip angle of the center of gravity, and the vehicle's speed along the X and Y axes in the global coordinate system.

[0078] Tire parameter identification includes: tire vertical load, tire longitudinal slip ratio, longitudinal force, tire slip angle, lateral force, and tire adhesion coefficient.

[0079] S102: Obtain the current driving mode of the vehicle, obtain the current target performance coefficient based on the driving mode, and obtain the overall vehicle performance target and weight coefficient based on the target performance coefficient;

[0080] S103: Calculates control requests for multiple targets based on vehicle-related parameters, tire-related parameters, vehicle performance targets, and weighting coefficients; corrects the initial output control request; and outputs the current wheel angle control request.

[0081] S104: Establish a constraint model and set constraint trigger conditions. When the vehicle's operating parameters are measured, the utilization rate is output through the constraint model based on the operating parameters. If the utilization rate is greater than or equal to the constraint trigger conditions, feedback compensation is performed on the corresponding constraint object.

[0082] Using the above-mentioned method of the present invention, the control output of the front and rear wheels is realized based on a unified control method, which has wide applicability and meets the vehicle performance requirements of different scenarios and functions. The whole system can meet the control of SBW front wheel steer-by-wire, RWS rear wheel active steering, and four-wheel steer-by-wire. Only the performance target coefficient, weight coefficient, calibration parameter, and constraint parameter need to be set and debugged for different systems, which can significantly shorten the development cycle.

[0083] It is applicable to all scenarios. The control algorithm and dynamic equations meet the precise requirements of nonlinear and large-angle driving conditions, as well as longitudinal and lateral composite conditions. At the same time, it adopts small-angle linear and interpolation methods to meet the real-time requirements of the control system.

[0084] An exemplary embodiment of the present invention relates to the estimation of wheel vertical load:

[0085] The inputs for estimating wheel vertical load include: longitudinal vehicle speed and longitudinal acceleration of the entire vehicle. Lateral acceleration yaw angle ,

[0086] Vehicle and suspension parameters: wheelbase Front and rear track width / Center of mass height , distance from center of gravity to front / rear distance a / b, and vehicle roll inertia Front / rear axle roll stiffness / Front / rear axle roll damping coefficient parameter.

[0087] In addition to accurately estimating static and inertia damping coefficients, the introduction of these coefficients can estimate dynamic wheel vertical loads. This approach can also be adapted to vehicles with active suspension and active stabilizer bars, allowing dynamic adjustments to be reflected in roll stiffness and roll damping.

[0088] The roll dynamics equations are as follows:

[0089]

[0090] In the formula, Let m be the roll angle and m be the vehicle mass. This refers to the lateral acceleration of the entire vehicle.

[0091] Front and rear axle roll moments based on roll and suspension characteristics:

[0092]

[0093] In the formula, This refers to the front axle roll moment. This is the rear axle roll moment.

[0094] Calculation of vertical load on four wheels:

[0095]

[0096]

[0097]

[0098]

[0099] In the formula, The load is vertical to the left front wheel. The load is the vertical load on the right front wheel. It is the acceleration due to gravity. For the vertical load on the left rear wheel, The vertical load is for the right rear wheel.

[0100] Regarding tire longitudinal parameter identification, this embodiment provides two acquisition methods depending on the available information.

[0101] The first method:

[0102] The inputs include: front and rear driving torques, braking torques, wheel moment of inertia, and wheel speeds, which are directly calculated based on wheel dynamics.

[0103] Wheel longitudinal dynamic equation:

[0104]

[0105] In the formula, For the longitudinal force of the tire, Wheel rotational inertia (including brake discs, wheel hubs, etc.). For driving torque, For braking torque, The effective radius of a tire can be defined as a known quantity related to the vertical load (the effect of normal tire pressure is ignored). The wheel's rotational acceleration is calculated by differentiating the wheel's real-time rotational speed.

[0106] The second method:

[0107] Unlike the first method, which cannot directly obtain the front and rear driving torques and braking torques, this method requires calculation using the magic formula tire model, thus necessitating knowledge of the coefficients of the tire magic formula.

[0108] Based on the Magic Formula's relationship between tire longitudinal slip ratio and longitudinal force:

[0109]

[0110] In the formula, For longitudinal slip ratio, The stiffness factor controls the slope (stiffness) of the curve. The shape factor controls the range of the main shape of the curve. The peak factor is equal to the peak value of the longitudinal force (maximum frictional force). The curvature factor changes the smoothness of curvature. Vertical Shift corrects for the longitudinal force at zero slip; it is usually set to 0. This refers to the longitudinal slip ratio.

[0111] Longitudinal slip ratio The formula is:

[0112]

[0113] In the formula, The speed of the tire center along the forward direction (reference vehicle speed). This represents the angular velocity of the wheel.

[0114] This solution employs two methods for longitudinal force estimation and performs fusion verification to ensure redundancy in the longitudinal force estimation. It also addresses situations where some systems cannot provide braking torque, driving torque, or accurate magic tire coefficients. The longitudinal parameter identification outputs the longitudinal slip ratios of the four tires (front, rear, left, and right). Longitudinal force .

[0115] Regarding the identification and estimation of vehicle parameters, the key to vehicle parameter estimation is the center of gravity sideslip angle. The sideslip angle is the core objective of this control method and a key state parameter of the vehicle. The sideslip angle is defined as follows: ( / Therefore, the lateral velocity of the center of mass can be estimated first. Since the lateral dynamics of the vehicle are directly related to the lateral force of the tires, and the calculation of the lateral force of the tires requires the calculation of the front and rear axle roll angles and the final tire roll angle from the vehicle's center of gravity sideslip angle, these calculations are performed simultaneously in one module.

[0116] Input parameters that can be provided from other vehicle systems and sensors include: IMU data ( ), Vehicle speed signal, front wheel steering angle Rear wheel steering angle Because it needs to meet the control requirements of all scenarios, it is necessary to consider the tire nonlinearity and the coupling of the longitudinal and lateral forces of the tires on the lateral side of the vehicle under large steering angles. The core dynamic equations are as follows:

[0117]

[0118]

[0119]

[0120]

[0121]

[0122]

[0123] In the formula, The moment of inertia of the vehicle's yaw motion. For input parameters or observables, The lateral force is from the front wheel. For the longitudinal force of the front wheel, The lateral force is from the rear wheel. For the longitudinal force of the rear wheel, The absolute speed of the entire vehicle, This refers to the front tire slip angle. Additional steering angle for the front suspension system. Front axle side slip angle, The rear tire slip angle, Additional steering angle for the rear suspension system. The rear axle slip angle includes kinematic and elasto-kinematic steering. Its value can be obtained through suspension K&C testing or simulation. Angle compensation is performed based on a lookup table to obtain a more accurate tire slip angle.

[0124] Based on the above dynamic equations, tire force is calculated using the magic formula, whose coefficients are obtained through six-component force testing and magic formula identification. The formula for calculating lateral force is as follows:

[0125]

[0126] In the formula, This refers to the tire slip angle. This represents the horizontal offset. The coefficients in the formula can be obtained through tire six-component force testing and identification.

[0127] To identify multiple correlation parameters and eliminate the influence of noise, an Extended Kalman Filter (EKF) observer is used. The design of the Extended Kalman Filter (EKF) observer is as follows:

[0128] 1. Dynamic model (state equation)

[0129] (1) Derivation of state equations

[0130]

[0131] The ultimate goal of state equations is To obtain the vehicle's center of gravity sideslip angle, and the yaw rate measured by the IMU. Lateral acceleration Obtain calculation Other parameters required in the formula.

[0132] In the formula, For the lateral speed of the entire vehicle, For the differential matrix of state variables, a common conformation in control theory is... The input is a matrix representing the steering angles of the front and rear wheels. , The sensor input is also a control variable of the system, therefore it needs to be obtained. , The equivalent lateral force on the bicycle model's axle needs to be calculated using the tire slip angle to obtain the tire lateral force.

[0133] (2) Calculation of equivalent lateral force

[0134] Front wheel slip angle:

[0135]

[0136] Rear wheel slip angle:

[0137]

[0138] Equivalent lateral forces before and after:

[0139] Because load transfer is taken into account, the vertical loads on the left and right tires are not equal. Therefore, based on the input of the tire vertical load and the slip angle, the following results are obtained:

[0140] =

[0141] =

[0142] In the formula The lateral force is from the left front wheel. The lateral force is from the right front wheel. The lateral force is from the left rear wheel. The lateral force is for the right rear wheel. The difference in steering angle between the left and right wheels is ignored here to avoid overly complex calculations.

[0143] 2. Observation Equation (Sensor Measurement)

[0144]

[0145] in, To observe noise.

[0146] Actual physical relationship:

[0147] Lateral acceleration is measured directly. The dynamics, Provided directly by the sensor

[0148] 3. EKF Observer Implementation Steps

[0149] (1) Discretization Model

[0150] Discretization of state equations (Euler method):

[0151]

[0152] Discretization of the observation equation:

[0153]

[0154] In the formula, These are the state variables from the previous time step. Input variables for the current moment. For time intervals, The observations at the current moment.

[0155] (2) Jacobian matrix calculation (EKF core)

[0156] State transition Jacobi :

[0157]

[0158] In the formula, State transition matrix.

[0159] The state transition Jacobian is a key matrix used to linearize nonlinear state equations. It is obtained by taking the partial derivative of the nonlinear function in the state equation and is one of the core steps in the implementation of EKF.

[0160] In the EKF observer for vehicle parameter identification, the state equation is a nonlinear dynamic model (involving the coupling relationship between state parameters such as vehicle lateral velocity and center of gravity sideslip angle and tire force and steering angle). To achieve state prediction and updating of EKF, the nonlinear state equation needs to be discretized, and the state transition Jacobian matrix needs to be calculated to describe the dynamic changes of state variables in a linear approximation manner.

[0161] Observation matrix Jacobi: :

[0162]

[0163] In the formula, This is the observation matrix.

[0164] The observer outputs observations and related calculations, including: the lateral velocity of the entire vehicle. , centroid side slip angle Front and rear axle slip angles / Front and rear tire slip angles Lateral forces of front and rear tires / The lateral force of the tire takes into account the influence of the vertical load, calculates the difference between the left and right wheels caused by the load transfer separately, and finally applies it to the front and rear single wheels of the bicycle model.

[0165] Regarding tire adhesion coefficient identification:

[0166] Tire adhesion coefficient recognition needs to meet different road surface requirements, using tire force, slip ratio, and sideslip angle as inputs, while also incorporating road surface characteristic factors. , The accurate value can be based on the road surface definition after the camera and lidar image recognition of the whole vehicle intelligent driving system.

[0167] The identification steps are as follows:

[0168] Step 1: Road surface characteristic factors generate

[0169] Input: Vertical load Tire force Longitudinal slip ratio Side slip angle

[0170]

[0171] Among the candidates Taken from the preset set {0, 0.134, 0.6, 1}, representing typical road surfaces. For measuring longitudinal tire force, The measured lateral tire force.

[0172] Step 2: Dynamic Correction of Magic Formula Parameters

[0173] Step 3: UKF State Estimation and Multi-Sensor Fusion

[0174] State variables:

[0175] Observation equation:

[0176]

[0177] in, Input from the tire longitudinal and lateral deviation calculation module.

[0178] Sensor dynamic weights:

[0179]

[0180] In the formula, For the state variable matrix, These are the coefficients of adhesion for the four wheels. For the observed variable matrix, To estimate the longitudinal force of each wheel tire, To estimate the lateral forces of each wheel tire, for Estimate weights, for Estimate weights, For sensor weights, For matrix The traces For matrix The "traces".

[0181] Regarding the estimation of the vehicle's global speed:

[0182] Absolute speed of the whole vehicle

[0183] In the global coordinate system, the longitudinal and lateral velocity components of the vehicle's center of gravity. and :

[0184]

[0185]

[0186] Global speed primarily uses lateral speed as the vehicle performance target for lane changes and emergency avoidance scenarios. These scenarios typically involve a straight line before steering, thus requiring a zeroing mechanism. This means the global coordinate system dynamically changes. Specifically, this is achieved when the steering wheel remains within a certain timeframe (default 3 seconds) with a value ≤ A0 (definable), i.e., a straight line for a certain period. During this time, the global coordinate system defaults to the vehicle's direction of travel. When steering begins, the yaw rate is integrated in real-time to calculate the yaw angle, which is then used for calculating lateral and longitudinal speeds. The detailed formulas are as follows:

[0187]

[0188] In the formula, This is the moment when the steering wheel exceeds the calculated threshold after being set to zero. This refers to any moment during the turning process.

[0189] In one exemplary embodiment of the present invention, obtaining the vehicle performance target and weighting coefficients based on the target performance coefficients includes:

[0190] S201: The vehicle performance targets include target yaw rate gain, target center of gravity sideslip angle gain, and target overall vehicle lateral velocity gain;

[0191] S202: Establish a mapping table of performance coefficients and weighting coefficients for different driving modes regarding steering wheel angle and vehicle speed. The performance coefficients include yaw rate performance coefficient, center of gravity sideslip angle performance coefficient, and overall vehicle lateral speed performance coefficient. The weighting coefficients include yaw rate weighting coefficient, center of gravity sideslip angle weighting coefficient, and overall vehicle lateral speed weighting coefficient.

[0192] Define the initial range of multi-objective performance coefficients, performance weight coefficients, and corresponding vehicle performance ranges directly related to steering. This can satisfy the functional control objectives of different drive-by-wire types and different scenarios, specifically including:

[0193] The yaw rate performance coefficient (PC_YawRate) primarily characterizes the rate of change of the vehicle's heading angle. This coefficient has a significant impact on low-speed U-turns, parking, and sharp cornering conditions. The coefficient ranges from 0 to 1, where 0 indicates no yaw rate and 1 indicates the vehicle's yaw rate is the defined maximum achievable value. For front-wheel steerable vehicles, it represents the maximum front wheel steering angle; for vehicles with only rear-wheel or four-wheel steerable systems, it represents the maximum front wheel steering angle, with the rear wheel steering angle being the opposite. The yaw rate weighting coefficient (WC_YawRate) also ranges from 0 to 1, with 0 to 1 representing the relative importance of the yaw rate.

[0194] The vehicle center-of-gravity sideslip performance coefficient, PC_VehSlip, primarily characterizes the ratio of a vehicle's lateral velocity to its longitudinal velocity. This coefficient carries significant weight in conditions such as drifting, sideslipping, and emergency steering. The coefficient ranges from 0 to 1, where 0 indicates no sideslip and the vehicle's steering is purely yaw motion, and 1 represents the maximum permissible or defined vehicle center-of-gravity sideslip angle. For vehicles with front-wheel steer-by-wire, this represents the maximum front wheel angle; for vehicles with only rear-wheel or four-wheel steer-by-wire, it represents the maximum front wheel angle, with the rear wheel angle being the maximum in the same direction. Furthermore, the value of the vehicle center-of-gravity sideslip angle represented by the coefficient 1 varies at different speeds. The vehicle center-of-gravity sideslip weight coefficient, WC_VehSlip, also ranges from 0 to 1, with 0 to 1 representing the relative importance of the vehicle center-of-gravity sideslip angle.

[0195] The overall vehicle lateral velocity performance coefficient PC_LatVel primarily characterizes the vehicle's global lateral velocity in the geodetic coordinate system. It plays a significant role in scenarios such as lane changes, emergency avoidance, and continuous lane shifts. The coefficient ranges from 0 to 1, and the lateral velocity is determined by a combination of the vehicle's heading angle and sideslip angle. A coefficient of 0 indicates no lateral velocity, while 1 indicates the vehicle's lateral velocity is the maximum allowed or defined lateral velocity. The overall vehicle lateral velocity weighting coefficient WC_LatVel also ranges from 0 to 1, with 0 to 1 representing the relative importance of the overall vehicle lateral velocity.

[0196] S203: Based on the current driving mode, steering wheel angle, and vehicle speed, the performance coefficient and weighting coefficient are obtained by indexing the mapping table.

[0197] The functional scenario coefficient definition module defines different performance coefficients or performance coefficient calculation methods in dynamically changing scenarios, based on the vehicle's driving scenarios and the functions of the steer-by-wire system. The included functional scenarios are as follows:

[0198] In the standard function mode, vehicle speed is the primary variable for weighting coefficients. Its multi-objective performance coefficients mainly focus on yaw rate and sideslip angle performance targets. Therefore, the global lateral velocity weighting coefficient WC_LatVel can be defined as zero. The weighting coefficients for yaw rate and sideslip angle can be defined based on vehicle speed, as shown in Table 1 below.

[0199] Table 1. Weighting Coefficients for Conventional Functional Modes

[0200]

[0201] The performance coefficients for standard functions are shown in Table 2 below:

[0202] Table 2 Performance Coefficients for Conventional Functional Modes

[0203]

[0204] The customizable handling function mode, compared to the conventional function, provides users with flexible handling performance definition capabilities under certain vehicle conditions. The vehicle conditions are defined as a speed range of 40-100 km / h and a lateral acceleration ≤0.6g. Control calculations are performed based on defined coefficients. In addition to defining weighted coefficients based primarily on vehicle speed, a coefficient for steering wheel angle is also defined. Its multi-objective performance coefficients primarily focus on yaw rate and sideslip angle performance targets; therefore, the global lateral velocity weight coefficient WC_LatVel can be defined as zero. The yaw rate and sideslip angle weight coefficients can be defined based on the vehicle speed and steering wheel angle inputs, as shown in Table 3 below.

[0205] Table 3 Weighting coefficients for customizable controllability modes

[0206]

[0207] The performance coefficients of the customizable controllability features are shown in Table 4 below:

[0208] Table 4 Performance coefficients of the customizable controllability function mode

[0209]

[0210] Crab mode is characterized by the absence of yaw motion; the lateral movement of the vehicle is caused by a large overall vehicle sideslip angle resulting from the front and rear turning angles in the same direction. It is a special mode, and its weighting coefficients are shown in Table 5 below.

[0211] Table 5 Weighting coefficients of the crab-walking pattern

[0212]

[0213] The performance coefficients of the crab mode are shown in Table 6 below:

[0214] Table 6 Performance coefficients of Crab Mode

[0215]

[0216] The emergency obstacle avoidance mode is mainly used in emergency turning scenarios at medium to high speeds to achieve lateral movement at the fastest speed while maintaining safety. Its weighting coefficients are shown in Table 7 below:

[0217] Table 7 Weighting coefficients of emergency obstacle avoidance function modes

[0218]

[0219] The performance coefficients of the emergency obstacle avoidance function are shown in Table 8 below:

[0220] Table 8 Performance coefficients of emergency obstacle avoidance mode

[0221]

[0222] The lane-change mode is a functional mode primarily used in standard slalom and double lane-change scenarios. It is activated by the user and aims for faster passing speeds. Besides requiring rapid lateral movement, it also demands a certain level of safety in vehicle handling. Therefore, its performance requirements are more complex, and the weighting coefficients need to be optimized and adjusted through simulation and experimentation. The reference weighting coefficients are shown in Table 9 below.

[0223] Table 9 Performance coefficients of the line-shifting mode functional modes

[0224]

[0225] The performance coefficients of the line shifting mode function are shown in Table 10 below:

[0226] Table 10 Performance coefficients of the line shifting mode function

[0227]

[0228] The drift mode function requires more vehicle yaw movement, sideslip angle, and smaller lateral movement, while also requiring reduced steering wheel angle input (higher sensitivity) and more precise control in drift mode. Therefore, it needs to use steering wheel angle as an input, and its reference weighting coefficients are shown in Table 11 below:

[0229] Table 11 Weighting coefficients for drift mode functionality

[0230]

[0231] The performance coefficients of the drift mode function are shown in Table 12 below:

[0232] Table 12 Performance coefficients of the drift mode function

[0233]

[0234] Regarding the determination of driving mode, the following example is given:

[0235] The required input signals include:

[0236] Function mode on / off signals: Crab mode on / off signal, custom control function on / off signal, line movement mode on / off signal, drift mode on / off signal

[0237] Vehicle status parameters: vehicle speed signal, lateral acceleration signal, longitudinal acceleration signal, yaw rate acceleration signal, steering wheel angular velocity, steering wheel angle, brake pedal strength, fault signals, etc.

[0238] The arbitration logic is as follows:

[0239] When the fault signal of the whole vehicle or the drive-by-wire system is true, the system function mode is 0.

[0240] When the fault signal of the whole vehicle or the drive-by-wire system is false, and the crab mode signal, the lane-shifting mode signal, and the drift mode signal are enabled, the system function modes are 3, 4, and 6 respectively. At the same time, only one of the above mode signals can be enabled.

[0241] When the fault signal of the whole vehicle or the drive-by-wire system is false, and the custom handling function mode is enabled, and the crab mode signal, the line-shifting mode signal, and the drift mode signal are enabled at the same time, the system function mode is 3, 4, and 6 respectively. When the crab mode signal, the line-shifting mode signal, and the drift mode signal are disabled, the system function mode is 2.

[0242] When the fault signal of the whole vehicle or the drive-by-wire system is false, when it is turned on, and the crab mode signal, lane-shifting mode signal, drift mode signal, and handling custom function mode are turned off, the lateral acceleration is ≥0.7g (calibrable), the yaw rate is ≥100deg / s^2 (calibrable), and the system function mode is 7.

[0243] When the fault signal of the whole vehicle or the drive-by-wire system is false, when it is turned on, and the crab mode signal, lane-shifting mode signal, drift mode signal, and handling custom function mode are turned off, the longitudinal acceleration is ≥0.5g (calibrable), the brake pedal is ≥60% (calibrable), the steering wheel angular velocity is ≥200deg / s (calibrable), and the system function mode is 5.

[0244] When the fault signal of the whole vehicle or the drive-by-wire system is false, and the crab mode signal, lane-shifting mode signal, drift mode signal, and handling custom function mode are all off when the system is turned on, the system function mode does not meet the judgment requirements of 5 and 7, and the system function mode is 1.

[0245] The module output signal represents the system function mode, and the mode is defined as follows:

[0246] Mode=0, fault mode

[0247] Mode=1, Normal function mode

[0248] Mode=2, customizable controllability mode

[0249] Mode=3, Crab Mode

[0250] Mode=4, Line shifting mode

[0251] Mode=5, Emergency Steering Mode

[0252] Mode=6, Drift Mode

[0253] Mode=7, Extreme Side-Slide Mode

[0254] S204: Based on the current performance ratio and performance coefficient, obtain the target yaw rate gain, the target centroid sideslip angle gain, and the target vehicle global lateral velocity gain.

[0255] The module's inputs include:

[0256] Target coefficient, steering wheel angle, and vehicle speed.

[0257] The module's output includes:

[0258] Target yaw rate gain, target center of gravity sideslip angle gain, target vehicle global lateral velocity gain

[0259] The method and steps are as follows:

[0260] Based on the 3D data of the functional scenario, Target_VehPerferCoeffiicients, current vehicle speed IPBVehSpeed, and steering wheel angle HWA_SteeringAngle, data fitting and interpolation are performed. The interpolation method can be linear point slope, linear Lagrange, etc., and the current target performance coefficient is obtained after interpolation.

[0261] Multiply the current target performance coefficient by the current performance ratio, such as the yaw rate gain ratio (YawRateGain_Ratio), which is defined as follows: , The maximum performance coefficient is 1, therefore = This value can be defined through testing, simulation, and calibration. In addition to considering the physical limits of the vehicle's performance, it can also be defined within the physical limits based on safety and the vehicle's performance style.

[0262] To further ensure that the output does not exceed the expected range, a saturation calculation is performed. The upper and lower limits of this saturation process are 1D data that varies with vehicle speed.

[0263] After passing through the vehicle performance planning layer, multiple vehicle performance targets and weight coefficients required for the current vehicle state are output in real time. The vehicle performance targets serve as control targets for the front and rear wheel allocation, and the weight coefficients are used for optimization allocation when multiple targets cannot be satisfied simultaneously.

[0264] In one exemplary embodiment of the present invention, the calculation of control requests for multiple targets based on vehicle-related parameters, tire-related parameters, vehicle performance targets, and weighting coefficients includes: constraining the target weight sliding surface, equivalent control terms, switching control, delay compensator, and control execution.

[0265] Multi-objective trade-offs are made based on weighting coefficients and system operating modes.

[0266] enter ： .

[0267] Output: Adjusted target .

[0268] In the formula, For the target yaw rate, For the target centroid sideslip angle, These are the weighting coefficients. Driving mode For the longitudinal speed of the vehicle, For yaw rate control error, This is the error controlled by the centroid side slip angle.

[0269] Target decomposition is performed based on system control mode and weighting coefficients, due to the relationship... The lateral velocity of the vehicle is determined by the vehicle speed, yaw rate, and sideslip angle. Therefore, given a fixed vehicle speed, determining the lateral velocity, yaw rate, and sideslip angle is sufficient to determine the third objective. Thus, based on the unified control mode and weighting coefficients, the three objectives are first transformed into two more direct parameters reflecting the vehicle's state: yaw rate and sideslip angle. The transformation method is as follows:

[0270] Mode=3, the system function mode is crab mode, with yaw rate and vehicle lateral speed as the main performance targets. The center of gravity sideslip angle is calculated by yaw rate, vehicle lateral speed and current vehicle speed. In this mode, the yaw rate is generally required to be zero, and the vehicle lateral speed is mainly generated by the center of gravity sideslip angle.

[0271] Mode=7, the system function mode is emergency steering mode. In this mode, the vehicle needs to have a faster lateral avoidance speed. Therefore, the yaw rate and the center of gravity sideslip angle will be obtained based on the optimal lateral speed decomposition. At the same time, the results must not exceed the boundaries of the yaw rate and the center of gravity sideslip angle.

[0272] In other system function modes, the yaw rate and center of mass sideslip angle performance targets will be directly used as control targets.

[0273] The yaw rate and lateral dynamics equations for a four-wheel steering vehicle are as follows:

[0274]

[0275]

[0276] Transforming the equation, we get:

[0277]

[0278]

[0279] Since control needs to satisfy all operating conditions, the trigonometric function relationships in the equations cannot be simply linearized. At the same time, there is a coupling relationship between tire force and steering angle in the equations. Therefore, variable structure sliding mode control is finally selected to meet the requirements of real-time control, anti-interference and robustness.

[0280] The sliding mode controller module includes: target weight sliding surface, equivalent control term, switching control, delay compensator, and control integration.

[0281] Specifically, the target weight sliding surface compensation includes obtaining the sliding surface by taking the multi-objective weighted control target error as input:

[0282]

[0283] In the formula, For sliding surface, The angular velocity weighting coefficient is used. For yaw rate tracking error, The weighting coefficient for the centroid sideslip angle. This represents the tracking error of the centroid sideslip angle.

[0284] Secondly, the compensation for the equivalent control term includes dividing the equivalent control into linear and nonlinear range conditions based on the overall dynamics and tire characteristics, and establishing an equivalent control model with the front and rear wheel steering angles as boundaries:

[0285]

[0286] In the formula, For equivalent control items, , These are the equivalent control terms for the front and rear wheels, respectively. It is a Jacobian matrix. Let be the desired rate of change of yaw rate.

[0287]

[0288]

[0289]

[0290]

[0291]

[0292] when , At the same time, when the angle is less than or equal to 5° (which can be defined), the vehicle dynamics and tire characteristics exhibit strong linearity. Meanwhile, the projection of the longitudinal force of the tires has negligible impact on the lateral and yaw dynamics of the entire vehicle, and the Jacobian matrix elements can be simplified.

[0293]

[0294]

[0295]

[0296]

[0297] In the formula, For the front wheel lateral stiffness, This refers to the rear wheel lateral stiffness.

[0298] When a vehicle is in a non-braking, accelerating state, the contribution of tire lateral force to lateral kinematics is relatively small, therefore when (Adjustable), the elements of the Jacobian matrix can be simplified to:

[0299]

[0300]

[0301]

[0302]

[0303] when , For angles greater than 5°, nonlinear equations are used for calculation. For trigonometric functions, a trigonometric function mapping table is employed to ensure real-time calculation and avoid singularities. Tire lateral forces are calculated using measured or identified magic formula coefficients, resulting in a lookup table. This table is a three-dimensional table, and the input is... , , Output ,in, This refers to the tire slip angle. For the vehicle's vertical load. The adhesion coefficient, This refers to the lateral force of the tire.

[0304] Specifically, the switching control compensation includes defining the switching term using a saturation function:

[0305]

[0306] In the formula, To switch control compensation terms, For switching gain coefficients, For boundary layer.

[0307] Specifically, compensating the delay compensator includes:

[0308] Based on the Smith predictor to eliminate the impact of execution latency, the latency compensation items for the front and rear wheels are as follows:

[0309]

[0310]

[0311]

[0312] In the formula, This is a front wheel delay compensation item. This is a front wheel steering command. This is the actual steering angle of the front wheels. For the Laplace operator, This is a rear wheel delay compensation item. This is a rear wheel steering command. This is the actual steering angle of the rear wheels. For delay compensation control items, The delay time constant of the front wheel actuator. The delay time constant for the rear wheel actuator;

[0313] Compensating for the control integration includes combining multiple control terms into a final control law output:

[0314]

[0315] In the formula, This is the final wheel angle control output request, including front wheel and rear wheel steering control output requests.

[0316] In one embodiment, establishing the constraint model includes establishing tire adhesion limit constraints, steering angle magnitude constraints, and execution speed constraints:

[0317] The tire adhesion limit constraints include:

[0318]

[0319]

[0320]

[0321] In the formula, The maximum lateral force of the tire. To improve tire utilization, For the vertical load of the tire, To estimate the required tire lateral force;

[0322] The steering angle magnitude constraint includes obtaining the maximum steering angle of the wheel:

[0323]

[0324]

[0325]

[0326] In the formula, The maximum turning angle of the wheel. For tire lateral stiffness, This represents the maximum slip ratio corresponding to the tire's adhesion limit. This is a wheel steering angle command. For the first actuator stroke utilization rate;

[0327] The execution speed constraint includes: based on the thrust-rate characteristic curves of the forward and rearward steering actuators: ,Will Converted to maximum wheel rotation speed For control output Differentiate to obtain the required speed ;

[0328]

[0329]

[0330] In the formula, For the actuator's maximum speed, The speed curve of the actuator as a function of load is represented. For actuator load, For the second actuator stroke utilization rate, For time.

[0331] In one embodiment, the step of performing feedback compensation on the corresponding constraint object includes:

[0332] Feedback compensation is used when the input control request exceeds the limit constraints. The control output needs to be limited and fed back to the front-end controller to compensate for the control. If it still cannot be achieved, the control target needs to be corrected. When setting the vehicle performance target coefficient, the actuator limit is already defined. Further constraints are applied to make the entire control system more reliable and meet the functional safety requirements.

[0333] The triggering state and over-limit state of the constraint state are fed back to the hierarchical compensation. The feedback results include:

[0334] Constraint trigger state: ;

[0335] Constraint overrun rate: ;

[0336] If the constraint is not triggered, the control request is output to the next limiting module;

[0337] When any constraint condition is triggered, initiate the compensation input and define the compensation influence factor matrix:

[0338]

[0339] The sliding surface is corrected based on the compensation influence factor matrix to compensate for the equivalent control.

[0340] In the formula, This is the trigger state for tire adhesion limit constraints. This is the trigger state for the corner amplitude constraint. To trigger the execution of speed constraints, To compensate for the impact factor, This is a compensation factor for the tire adhesion limit constraint. The compensation influence factor for the angle amplitude constraint, This is a compensation factor for implementing speed constraints.

[0341] in,

[0342] In the formula, For the i-th type of compensation factor, The excess rate corresponding to the i-th type of compensation influence factor.

[0343] Equivalent control law compensation:

[0344]

[0345] Dynamic correction of sliding surface:

[0346]

[0347] This represents the Hadamard product (element-wise multiplication).

[0348] Goal Restructuring:

[0349]

[0350] In the formula, This is the equivalent control after compensation. For the corrected sliding surface, This is the yaw rate error coefficient. For yaw rate error, The error coefficient for the centroid sideslip angle. This is the error in the centroid sideslip angle. For the target yaw rate, For the target centroid sideslip angle, To reconstruct the target yaw rate, The target centroid sideslip angle for reconstruction.

[0351] The order of the above three methods is the priority order of compensation. Adjustment is made at 90% of the constraint limit, which has a closed-loop and preventive effect.

[0352] Setting a limiting output directly limits the output if it still exceeds the actuator constraint after compensation and correction. This prevents the output request from exceeding the limit, which could cause system failure and actuator damage. It is the last line of defense for the control system. It directly adopts a saturated output method and limits the output based on the actuator stroke and maximum speed.

[0353] A hierarchical multi-objective performance control system based on a steer-by-wire system includes:

[0354] The data and status recognition module is configured to acquire the basic parameters of the current vehicle, and based on the basic parameters, perform vehicle parameter recognition and tire parameter recognition to obtain vehicle-related parameters and tire-related parameters.

[0355] The vehicle performance planning module is configured to obtain the current driving mode of the vehicle, obtain the current target performance coefficient based on the driving mode, and obtain the vehicle performance target and weight coefficient based on the target performance coefficient.

[0356] The front and rear wheel distribution module is configured to calculate control requests for multiple targets based on vehicle-related parameters, tire-related parameters, vehicle performance targets, and weighting coefficients; correct the initial output control request; output the current wheel steering angle control request; establish a constraint model and set constraint trigger conditions; when the vehicle's operating parameters are used, the utilization rate is output through the constraint model based on the operating parameters; if the utilization rate is greater than or equal to the constraint trigger condition, feedback compensation is performed on the corresponding constraint object.

[0357] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0358] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. This computer software product, stored in a storage medium, includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0359] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A layered architecture multi-objective performance control method based on a steer-by-wire system, characterized in that, The method comprises the following steps: Obtain the basic parameters of the current vehicle, identify the vehicle parameters and tire parameters based on the basic parameters, and obtain the vehicle-related parameters and tire-related parameters; Obtain the driving mode of the current vehicle, obtain the target performance coefficient based on the driving mode, and obtain the vehicle performance target and weight coefficient based on the target performance coefficient; Based on the vehicle-related parameters, tire-related parameters, vehicle performance target and weight coefficient, the control request calculation of multiple targets is carried out, the initial output control request is corrected, and the current wheel angle control request is output; A constraint model is established, a constraint trigger condition is set, the running parameters of the vehicle are obtained, and the utilization rate is output through the constraint model based on the running parameters; if the utilization rate is greater than or equal to the constraint trigger condition, feedback compensation is performed on the corresponding constraint object; The target performance coefficient is used to obtain the vehicle performance target and weight coefficient, which comprises: The vehicle performance target comprises target yaw rate gain, target mass side slip angle gain and target vehicle global lateral velocity gain; A mapping table of performance coefficients and weight coefficients of different driving modes about steering wheel angle and vehicle speed is established, the performance coefficients comprise yaw rate performance coefficient, mass side slip angle performance coefficient and vehicle global lateral velocity performance coefficient, and the weight coefficients comprise yaw rate weight coefficient, mass side slip angle weight coefficient and vehicle global lateral velocity weight coefficient; The performance coefficients and weight coefficients are indexed in the mapping table based on the current driving mode, steering wheel angle and vehicle speed; The target yaw rate gain, target mass side slip angle gain and target vehicle global lateral velocity gain are obtained based on the current performance ratio and performance coefficient.

2. The hierarchical architecture multi-objective performance control method for a steer-by-wire system according to claim 1, wherein The control request calculation of multiple targets based on the vehicle-related parameters, tire-related parameters, vehicle performance target and weight coefficient comprises: constraint of target weight sliding mode surface, equivalent control item, switching control, delay compensator and control execution.

3. The hierarchical architecture multi-objective performance control method for a steer-by-wire system according to claim 2, wherein The compensation of the target weight sliding mode surface comprises: taking the control target error weighted by multiple targets as input to obtain the sliding mode surface: wherein is a slip plane, is a yaw rate weighting factor, is a yaw rate tracking error, is a mass side slip angle weighting factor, is a mass side slip angle tracking error.

4. The hierarchical architecture multi-objective performance control method for a drive-by-wire steering system according to claim 3, wherein The compensation of the equivalent control item comprises: dividing the equivalent control into linear and nonlinear range conditions based on the integral dynamics and tire characteristics, taking the front and rear wheel angle as the boundary, and establishing an equivalent control model: wherein are equivalent control terms, , are front and rear wheel equivalent control terms, respectively, is a Jacobian matrix, is a desired yaw rate change.

5. The layered architecture multi-objective performance control method for a steer-by-wire system according to claim 4, wherein, The compensation of the switching control comprises: defining the switching item by using a saturation function: wherein is a switching control compensation term, is a switching gain coefficient, is a boundary layer, is a saturation function.

6. The hierarchical architecture multi-objective performance control method for a drive-by-wire steering system according to claim 5, wherein The compensation of the delay compensator comprises: Eliminate the execution delay effect based on the Smith predictor, and the front and rear wheel delay compensation items are: wherein is a front wheel delay compensation term, is a front wheel steering command, is a front wheel actual steering angle, is a Laplacian operator, is a rear wheel delay compensation term, is a rear wheel steering command, is a rear wheel actual steering angle, is a delay compensation control term, is a front wheel actuator delay time constant, is a rear wheel actuator delay time constant; The compensation of the control integration comprises: integrating multiple control items into the final control law output: In the formula, is the final wheel angle control output request, including front wheel and rear wheel steering control output request.

7. The layered architecture multi-objective performance control method for a steer-by-wire system according to claim 6, wherein, The establishment of the constraint model comprises the establishment of tire adhesion limit constraint, angle amplitude constraint and execution speed constraint: The tire adhesion limit constraint comprises: wherein is the maximum tire lateral force, is the tire utilization, is the tire vertical load, is the estimated required tire lateral force; The angle amplitude constraint comprises obtaining the maximum wheel angle: wherein is the maximum wheel angle, is the tire cornering stiffness, is the maximum slip ratio corresponding to the tire adhesion limit, is the wheel angle command, is the first actuator stroke utilization; The execution speed constraint includes: based on the thrust-rate characteristic curve of the front and rear steering actuators: , converting the wheel angle maximum speed , differentiating the control output to obtain the required speed ; wherein is the maximum velocity of the actuator, is the velocity profile of the actuator as a function of load, is the load of the actuator, is the second actuator stroke utilization, is time.

8. The layered architecture multi-objective performance control method for a steer-by-wire system according to claim 7, wherein, The feedback compensation of the corresponding constraint object comprises: The trigger state and overrun state of the constraint state are fed back to the hierarchical compensation, and the feedback result comprises: Constraint condition trigger state: ; Constraining the overrunning rate: ​ When the constraint condition is not triggered, the control request is output to the next limiting module; When any constraint condition is triggered, the compensation input is started, and the compensation influence factor matrix is defined: The sliding mode surface is modified based on a compensation influence factor matrix, and equivalent control is compensated; wherein is a triggering state for the tire adhesion limit constraint, is a triggering state for the cornering amplitude constraint, is a triggering state for the execution speed constraint, is a compensation impact factor, is a compensation impact factor for the tire adhesion limit constraint, is a compensation impact factor for the cornering amplitude constraint, is a compensation impact factor for the execution speed constraint.

9. A hierarchical architecture multi-objective performance control system based on a steer-by-wire system, characterized in that, The method for performing the hierarchical architecture multi-objective performance control of the steer-by-wire system according to any one of claims 1-8 comprises: The data and state identification module is configured to acquire basic parameters of the current vehicle, perform vehicle parameter identification and tire parameter identification based on the basic parameters, and obtain vehicle-related parameters and tire-related parameters; The vehicle performance planning module is configured to acquire a driving mode of the current vehicle, obtain a current target performance coefficient based on the driving mode, and obtain a vehicle performance target and a weight coefficient based on the target performance coefficient; The front and rear wheel distribution module is configured to perform control request calculation on multiple targets based on the vehicle-related parameters, the tire-related parameters, the vehicle performance target and the weight coefficient, correct the initial output control request, and output a current wheel angle control request; a constraint model is established, a constraint trigger condition is set, operating parameters of the vehicle are acquired, and a utilization rate is output based on the operating parameters through the constraint model; if the utilization rate is greater than or equal to the constraint trigger condition, a corresponding constraint object is feedback compensated.

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