Active steering control method and system for a four-wheel-steering bus

Abstract

The application discloses a kind of four-wheel steering passenger car active steering control method and system, the present application method includes obtaining the reference vehicle state reference amount REF of four-wheel steering passenger car in current state, and the lateral load transfer rate LTR of four-wheel steering passenger car in current state is calculated;With lateral load transfer rate LTR as constraint condition, the quadratic programming problem of four-wheel steering passenger car about vehicle lateral displacement deviation is optimized and solved based on reference vehicle state reference amount REF, and control amount u is obtained to control the steering angle of rear wheel rear of four-wheel steering passenger car, the present application can effectively reduce the lateral load transfer rate peak value and vehicle lateral displacement deviation of passenger car, effectively improve the stability of vehicle side wind environment travel.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of stability control of four-wheel steering passenger cars, and particularly relates to an active steering control method and system for four-wheel steering passenger cars. BACKGROUND

[0002] Public transportation is the lifeblood of urban travel, and some cities in China have begun to promote the electrification of public transportation. The driving safety and stability of electric public transportation are of great concern to the public, and more complex road conditions also put higher requirements on the safety control system of the vehicle. Four-wheel steering, as one of the important technologies for vehicle stability control, has been applied to passenger cars by some vehicle manufacturers, with the expectation of improving the driving stability of passenger cars. Four-wheel steering vehicles have gradually become the main object of research and control stability in the automotive industry. Through analysis of the current research status at home and abroad, it is found that the current research objects are mostly four-wheel steering sedans, and there are few studies on the stability control of four-wheel steering passenger cars. Compared with sedans, passenger cars have a higher center of gravity and are more prone to roll and slide instability, so their driving safety cannot be ignored. SUMMARY

[0003] The technical problem to be solved by the present application is to provide an active steering control method and system for four-wheel steering passenger cars, which can effectively reduce the peak value of the lateral load transfer rate of the passenger car and the lateral displacement deviation of the vehicle, and effectively improve the stability of the vehicle driving in a crosswind environment.

[0004] To solve the above technical problems, the technical scheme adopted by the present application is:

[0005] An active steering control method for a four-wheel steering passenger car, comprising:

[0006] S101, obtaining a reference vehicle state reference quantity REF of the four-wheel steering passenger car in the current state, and calculating a lateral load transfer rate LTR of the four-wheel steering passenger car in the current state;

[0007] S102, taking the lateral load transfer rate LTR as a constraint condition, and based on the reference vehicle state reference quantity REF, optimizing and solving a quadratic programming problem of the four-wheel steering passenger car about the lateral displacement deviation of the vehicle to obtain a control quantity u for controlling the steering angle of the rear wheel rear of the four-wheel steering passenger car.

[0008] Optionally, the calculation function expression of the lateral load transfer rate LTR in step S101 is:

[0009] ,

[0010] In the above formula, LTR LTR is the lateral load transfer rate, F zflF is a vertical load of the left front wheel, zrl F is a vertical load of the left rear wheel, zfr F is a vertical load of the right front wheel, zrr F is a vertical load of the right rear wheel, and the calculation function expression of the vertical loads of the left front wheel, the left rear wheel, the right front wheel and the right rear wheel is:

[0011] ,

[0012] ,

[0013] ,

[0014] ,

[0015] In the above formula, F zfl F is a vertical load of the left front wheel, zrl F is a vertical load of the left rear wheel, zfr F is a vertical load of the right front wheel, zrr F is a vertical load of the right rear wheel, m M is the mass of the four-wheel steering passenger car, g a is the acceleration, h is the height from the vehicle mass center to the suspension center, and are the accelerations of the four-wheel steering passenger car in the x and y axis directions respectively, and T is the wheelbase of the vehicle, l f is the distance from the front axle to the vehicle mass center; l r is the distance from the rear axle to the vehicle mass center.

[0016] Optionally, step S102 comprises:

[0017] S201, establishing a nonlinear control state equation of the four-wheel steering passenger car based on a reference vehicle state reference quantity REF;

[0018] S202, performing Taylor expansion at the reference value of the current state to linearize the nonlinear control state equation of the four-wheel steering passenger car to obtain a linearized control state equation;

[0019] S203, discretizing the linearized control state equation using forward Euler to obtain a discretized control state equation;

[0020] S204, predicting in a prediction time domain according to the discretized control state equation to obtain a prediction expression, and transforming the prediction formula to obtain a quadratic programming problem about the lateral displacement deviation of the vehicle;

[0021] S205, the quadratic programming problem about the lateral displacement deviation of the vehicle is solved by optimization in MATLAB within the constraint range of the lateral load transfer rate LTR, so as to obtain the control amount u for controlling the steering angle of the rear wheel rear of the four-wheel steering passenger car.

[0022] Optionally, the function expression of the nonlinear control state equation of the four-wheel steering passenger car established in step S201 is:

[0023]

[0024] In the above formula, is the reference value of the current state is the symbolic sign of the control state equation function, is the reference value of the current state, is the reference value of the control amount u, is the state quantity derivative matrix, is the state quantity matrix, is the control input matrix, is the output quantity matrix, and are the cornering stiffness of the front and rear wheels, and are the distances from the front and rear axles to the center of mass of the vehicle, is the moment of inertia around the Z axis in the vehicle coordinate system, is the mass of the four-wheel steering passenger car, is the speed of the four-wheel steering passenger car in the x-axis direction,

[0025]

[0026] In the above formula, is the actual value of the current state, is the control amount for controlling the steering angle of the rear wheel rear of the four-wheel steering passenger car, is the control state equation.

[0027] Optionally, the function expression of the control state equation after the discretization processing obtained in step S203 is:

[0028]

[0029] In the above formula, is the current state at k+1, is the current state at k, is the control amount at k, and are intermediate variables,​​​​ is the sampling time, and

[0030] ,

[0031] in the above formula, I is an identity matrix, T is a sampling period, is a control state equation at the current time is a derivative of the actual value of the current state, is a control state equation at the current time is a derivative of the control amount at the current time.

[0032] Optionally, the function expression of the prediction expression obtained in step S204 is:

[0033] ,

[0034] in the above formula, is the current state at time k, is the control amount at time k, and

[0035] , ,

[0036] , ,

[0037] in the above formula, ~ is a prediction time domain after time k ~ is a prediction state value in each of the prediction time domains after time k ~ is a control time domain, is a prediction time domain; ~ is a control state equation in each of the prediction time domains after time k ~ is a derivative of the actual value of the current state, ~ is a derivative of the control amount at time t after time k, ~ is a prediction control value in each of the control time domains after time k ~ is a control time domain, is a prediction time domain, and ~ is a prediction control value in each of the control time domains after time k ~ is a control time domain, is a prediction time domain, and ​​​​​​​​The function expression of the quadratic programming problem obtained in step S204 is:

[0038] ,

[0039] In the above formula, is an intermediate variable, is a control variable for controlling the steering angle of the rear wheel rear of the four-wheel steering passenger car, is a control state equation, and has:

[0040] ,

[0041] In the above formula, Q and R are both weight matrices.

[0042] Optionally, when the quadratic programming problem about the lateral displacement deviation of the vehicle in step S205 is optimized and solved in MATLAB within the constraint range of the lateral load transfer rate LTR, the function expression of the objective function used is:

[0043] ,

[0044] In the above formula, min represents taking the minimum value, is an objective function, is a state quantity matrix, is a control quantity matrix, is a prediction time domain; the prediction in the prediction time domain of all control quantities, is a reference value of the control quantity at k, is the difference between the actual output value and the reference value in the control time domain , is a weight matrix of the relaxation factor; is a relaxation factor, is a weight matrix of the vehicle lateral displacement control; is the predicted value of the vehicle lateral displacement at k, is the reference value of the vehicle lateral displacement at k, is a control weight matrix of the lateral load transfer rate; is the actual value of the lateral load transfer rate LTR, is the reference value of the lateral load transfer rate LTR, is a weight matrix of the rear wheel control; is a weight matrix; is a relaxation factor.

[0045] In addition, the present application also provides an active steering control simulation system of a four-wheel steering passenger car, comprising:

[0046] A vehicle simulator is configured to simulate a four-wheel-steering bus based on a steering angle of rear wheels rear of the four-wheel-steering bus in a previous time step to obtain a current state of the four-wheel-steering bus, to obtain front wheel steering angle data front of the four-wheel-steering bus and vertical load of the four-wheel-steering bus.

[0047] A reference model calculation unit is configured to collect the front wheel steering angle data front of the four-wheel-steering bus in the current state, and to calculate a reference vehicle state reference quantity REF in the current state in combination with vehicle structure parameters of the four-wheel-steering bus.

[0048] A lateral load transfer rate calculation unit is configured to calculate a lateral load transfer rate LTR of the four-wheel-steering bus in the current state.

[0049] An MPC controller is configured to take the lateral load transfer rate LTR as a constraint condition, to optimize and solve a quadratic programming problem of the four-wheel-steering bus in relation to a vehicle lateral displacement deviation based on the reference vehicle state reference quantity REF to obtain a control quantity u for controlling the steering angle of the rear wheels rear of the four-wheel-steering bus.

[0050] The output end of the vehicle simulator is connected to the input ends of the reference model calculation unit and the lateral load transfer rate calculation unit respectively, the output ends of the reference model calculation unit and the lateral load transfer rate calculation unit are connected to the control end of the MPC controller respectively, and the output end of the MPC controller is connected to the input end of the vehicle simulator through a delay module.

[0051] In addition, the present application also provides an active steering control system of a four-wheel-steering bus, which comprises a microprocessor and a memory connected to each other, and the microprocessor is programmed or configured to execute the active steering control method of the four-wheel-steering bus.

[0052] In addition, the present application also provides a computer readable storage medium, which stores a computer program for being programmed or configured by a microprocessor to execute the active steering control method of the four-wheel-steering bus.

[0053] Compared with the prior art, the present application has the following advantages: the method of the present application comprises obtaining a reference vehicle state reference amount REF of the four-wheel steering passenger car in the current state, and calculating a lateral load transfer ratio LTR of the four-wheel steering passenger car in the current state; a quadratic programming problem of the four-wheel steering passenger car with respect to a vehicle lateral displacement deviation is optimized and solved based on the reference vehicle state reference amount REF, taking the lateral load transfer ratio LTR as a constraint condition, to obtain a control amount u for controlling the steering angle of the rear wheel rear of the four-wheel steering passenger car, since the lateral load transfer ratio LTR is taken as a constraint condition, and the vehicle lateral displacement deviation is taken as a factor in the quadratic programming problem, the peak value of the lateral load transfer ratio of the passenger car and the vehicle lateral displacement deviation can be effectively reduced, the trajectory tracking ability of the vehicle in the high-speed crosswind driving condition can be effectively improved, the lateral load transfer ratio LTR value of the vehicle is effectively constrained, the lateral displacement of the high-speed vehicle is effectively controlled, and the stability of the vehicle driving in the crosswind environment is effectively improved. BRIEF DESCRIPTION OF DRAWINGS

[0054] Figure 1 It is a basic flowchart of the method of the embodiment of the present application.

[0055] Figure 2 It is a vehicle dynamics model diagram of the four-wheel steering passenger car in the embodiment of the present application.

[0056] Figure 3 It is a diagram of a two-degree-of-freedom vehicle model in the embodiment of the present application.

[0057] Figure 4 It is a structure diagram of a simulation system in the embodiment of the present application.

[0058] Figure 5 It is a front wheel steering angle response curve in the double lane shift condition in the embodiment of the present application.

[0059] Figure 6 It is a rear wheel steering angle response curve in the double lane shift condition in the embodiment of the present application.

[0060] Figure 7 It is a lateral displacement comparison in the double lane shift condition in the embodiment of the present application.

[0061] Figure 8 It is a LTR value comparison in the double lane shift condition in the embodiment of the present application.

[0062] Figure 9 It is a front wheel steering angle response curve in the snake condition in the embodiment of the present application.

[0063] Figure 10 It is a rear wheel steering angle response curve in the snake condition in the embodiment of the present application.

[0064] Figure 11 For the lateral displacement comparison under the snake running condition in the embodiment of the application.

[0065] Figure 12 For the LTR value comparison under the snake running condition in the embodiment of the application. DETAILED DESCRIPTION

[0066] As Figure 1 shown, the embodiment provides an active steering control method for a four-wheel steering passenger car, comprising:

[0067] S101, obtaining a reference vehicle state reference quantity REF of the four-wheel steering passenger car in a current state, and calculating a lateral load transfer ratio LTR of the four-wheel steering passenger car in the current state;

[0068] S102, taking the lateral load transfer ratio LTR as a constraint condition, and based on the reference vehicle state reference quantity REF, optimizing and solving a quadratic programming problem of the four-wheel steering passenger car about a vehicle lateral displacement deviation to obtain a control quantity u for controlling a steering angle of a rear wheel rear of the four-wheel steering passenger car.

[0069] In the embodiment, the calculation function expression of the lateral load transfer ratio LTR in step S101 is:

[0070] ,

[0071] In the above formula, LTR is the lateral load transfer ratio, F zfl is a vertical load of a left front wheel, F zrl is a vertical load of a left rear wheel, F zfr is a vertical load of a right front wheel, F zrr is a vertical load of a right rear wheel, and the calculation function expressions of the vertical loads of the left front wheel, the left rear wheel, the right front wheel and the right rear wheel are:

[0072] ,

[0073] ,

[0074] ,

[0075] ,

[0076] In the above formula, F zfl is a vertical load of a left front wheel, F zrl is a vertical load of a left rear wheel, F zfr is a vertical load of a right front wheel, F zrr is a vertical load of a right rear wheel, mis the mass of the four-wheel steering bus, g is the acceleration, is the height of the vehicle center of mass to the suspension center, and are the accelerations of the four-wheel steering bus in the x and y axis directions, respectively, T is the wheel base of the vehicle, l f is the distance from the front axle to the vehicle center of mass; l r is the distance from the rear axle to the vehicle center of mass.

[0077] The research object of the method of the present embodiment is a four-wheel steering bus, and the vehicle is modeled and analyzed for the structural characteristics of the four-wheel steering, mainly including a twelve-degree-of-freedom vehicle dynamics modeling, a H.B.Pacejke tire model modeling, and a two-degree-of-freedom vehicle model modeling. In the present embodiment, a twelve-degree-of-freedom nonlinear vehicle dynamics model is established to describe the vehicle dynamics performance of the four-wheel steering bus in a crosswind environment, as shown in the vehicle dynamics model Figure 2 , wherein: To is the mass side slip angle of the four-wheel steering bus, and are the velocity components in the x and y axes, respectively, and are the friction forces in the x and y axes of the left rear wheel, respectively, and are the friction forces in the x and y axes of the right rear wheel, respectively, and are the friction forces in the x and y axes of the left front wheel, respectively, and are the friction forces in the x and y axes of the right front wheel, respectively, T is the wheel base of the vehicle, l f is the distance from the front axle to the vehicle center of mass; l r is the distance from the rear axle to the vehicle center of mass. The twelve degrees of freedom include four degrees of freedom of the vehicle body in the longitudinal, lateral, roll, and yaw directions, and the rotation and steering degrees of freedom of the wheels. The longitudinal dynamics equation of the vehicle can be expressed as:

[0078] = ,

[0079] In the above formula, is the mass of the vehicle; is the longitudinal and lateral velocity of the vehicle; is the yaw angular velocity of the vehicle; is the longitudinal force of the left front wheel of the vehicle; is the longitudinal force of the right front wheel of the vehicle; is the longitudinal force of the left rear wheel of the vehicle; vehicle right rear wheel longitudinal force; vehicle left front wheel lateral force; vehicle right front wheel lateral force; vehicle left rear wheel lateral force; vehicle right rear wheel lateral force; left front wheel steering angle; right front wheel steering angle; left rear wheel steering angle; right rear wheel steering angle. The lateral dynamics equation of the vehicle can be expressed as:

[0080]

[0081]

[0082] In the above formulae, is the moment of inertia of the vehicle about the z axis; is the distance from the front axle to the center of mass of the vehicle; is the distance from the rear axle to the center of mass of the vehicle; is the wheelbase of the vehicle. The vertical load of the tires, i.e., the vertical load of the left front wheel, the left rear wheel, the right front wheel, and the right rear wheel, is expressed as a function as shown above; the side slip angle of each wheel is calculated as:

[0083]

[0084]

[0085]

[0086]

[0087] In the above formulae, is the side slip angle of the left front wheel; is the side slip angle of the right front wheel; is the side slip angle of the left rear wheel; is the side slip angle of the right rear wheel.

[0088] The tire is the only medium in contact with the ground for the vehicle body, and the dynamic characteristics of the tire have a great influence on the dynamic characteristics of the vehicle. In the present embodiment, a H.B. Pacejke tire (Magic Formula model) is selected as the calculation model of the tire force, and the tire force The general expression of the formula is:

[0089]

[0090] In the above formulae, is the longitudinal slip,​​​​​​​​​ is the vertical direction drift of the curve; B, C, D, E are the stiffness factor, shape factor, peak factor (maximum value of the curve) and curvature factor (indicating the shape near the maximum value of the curve) respectively. By substituting the values of each factor obtained by test into the calculation formula of the tire longitudinal force, tire lateral force and tire aligning moment, the calculation formula of the tire longitudinal force, tire lateral force and tire aligning moment can be obtained, wherein:

[0091] Tire longitudinal force The calculation formula is:

[0092] ,

[0093] and ; ; ; ; ; ; ; .

[0094] The tire lateral force calculation formula is:

[0095] ,

[0096] and ; ; ; ; ; ; .

[0097] Tire aligning moment The calculation formula is:

[0098] ,

[0099] and ; ; ; ; ; ; .

[0100] wherein, is the horizontal direction drift of the curve, is the increment of ; is the vertical direction drift of the curve; is the tire side slip angle; S is the longitudinal slip rate; is the tire roll angle, which corrects the horizontal and vertical drifts of the curve zero point and the stiffness respectively; F z is the vertical load; Ai , B j , C k are fitting parameters (i = 1…13, j = 1…10, k = 0…17), respectively, as shown in Tables 1 to 3 in this embodiment.

[0101] Table 1: Value examples of fitting parameter A i .

[0102]

[0103] Table 2: Value examples of fitting parameter B j .

[0104]

[0105] Table 3: Value examples of fitting parameter C k .

[0106]

[0107] In this embodiment, the tire model formula built based on the above data is simulated and verified in MATLAB, to verify the tire force change under different loads, and the result conforms to the magic tire theoretical change rule.

[0108] In this embodiment, step S102 comprises:

[0109] S201, establishing a nonlinear control state equation of a four-wheel steering passenger car based on a reference vehicle state reference quantity REF;

[0110] S202, performing Taylor expansion at the reference value of the current state to linearize the nonlinear control state equation of the four-wheel steering passenger car to obtain a linearized control state equation;

[0111] S203, performing discretization processing on the linearized control state equation using forward Euler to obtain a discretized control state equation;

[0112] S204, performing prediction in a prediction time domain according to the discretized control state equation to obtain a prediction expression, and transforming the prediction formula to obtain a quadratic programming problem about vehicle lateral displacement deviation;

[0113] S205, optimizing and solving the quadratic programming problem about vehicle lateral displacement deviation in MATLAB within the constraint range of lateral load transfer rate LTR, to obtain a control quantity u for controlling the steering angle of the rear wheel rear of the four-wheel steering passenger car.

[0114] Previous experiments and verifications have confirmed that the two-degree-of-freedom model of a car can accurately reflect the vehicle state during driving, so the two-degree-of-freedom model of a car is also widely used in the design of vehicle controllers. Figure 3 As shown in the figure: is the sideslip angle of the center of mass; is the yaw angular velocity; and are the side slip angles of the front and rear wheels, and is the lateral force of the front and rear wheels of the vehicle; a and b is the distance from the front and rear wheels to the center of mass of the vehicle; L is the front and rear wheelbase. Figure 3 The functional expression of the two-degree-of-freedom vehicle model is:

[0115] ,

[0116] In the above formula, are the longitudinal and lateral speeds of the vehicle; is the vehicle's yaw rate; is the moment of inertia of the vehicle around the z-axis; and are the steering angles of the front and rear wheels, a and b is the distance from the front and rear wheels to the vehicle's center of mass, and is the lateral force of the front and rear wheels of the vehicle; according to the tire linearization assumption, there is a tire lateral force formula:

[0117] ,

[0118] In the above formula, and is the cornering stiffness of the front and rear wheels.

[0119] According to the small angle approximation formula, there is: ; ; Substituting the tire lateral force formula into the function expression of the two-degree-of-freedom vehicle model and simplifying it according to the small-angle formula, the vehicle's dynamic differential equation is as follows:

[0120] ,

[0121] It can be further simplified into the vehicle state equation:

[0122] ,

[0123] In the above formula, is the state matrix, for the input matrix, for the output matrix.

[0124] In general, the lateral stability of a passenger vehicle mainly includes two aspects of sideslip instability and rollover instability. In the absence of external interference, the instability of the vehicle mainly occurs when the vehicle state changes (such as lane changing, turning, overtaking and other working conditions). In these working conditions, due to the change of tire cornering angle, the tire force changes, and then the whole vehicle force changes, causing sideslip or roll instability. The specific situation is as follows, in the lane changing and turning working conditions, when the tire lateral force cannot provide the required centripetal force for the change of vehicle state, at this time the vehicle instability working condition is mainly sideslip instability, which will seriously affect the driving safety of other vehicles on the same lane; when the tire force can provide the required centripetal force for the vehicle, the vehicle can keep driving in the lane, but due to the influence of centrifugal force and the flexible structure of the vehicle suspension, the vehicle body will produce an outward inclination angle, at this time the vehicle instability working condition is mainly roll instability, which has the risk of rollover. When there is external factors such as crosswind interference, the influence of crosswind on the driving stability of a passenger vehicle is much greater than that on a sedan, because the passenger vehicle has a larger wind area on the side and a higher center of gravity. With the increase of crosswind speed, the instability risk of the passenger vehicle increases greatly; and in the crosswind working condition, the tire force of the passenger vehicle is complex, and the tire force critical conditions of sideslip instability and roll instability may exist simultaneously. Therefore, this paper studies the coupling control of the sideslip and rollover instability working conditions of a passenger vehicle under crosswind interference. In this embodiment, a rear wheel active steering lateral stability control method based on MPC is proposed to improve the lateral stability of the passenger vehicle under crosswind working conditions. The control method of rear wheel active steering is designed based on MPC, which predicts the change of vehicle state quantity by querying the current state and the sequence change in the control time domain, solves the optimal control problem at each time step through the rolling optimization result in the control time domain, and realizes the control of the vehicle state target. Specifically, the function expression of the nonlinear control state equation of the four-wheel steering passenger vehicle established in step S201 of this embodiment is:

[0125]

[0126] In the above formula, is the reference value of the current state is the symbolic sign of the control state equation function of is the reference value of the current state, is the reference value of the control quantity u, is the derivative matrix of the state quantity, is the state quantity matrix, is the input matrix of the control, is the output matrix, and are the cornering stiffness of the front and rear wheels,​​ and is the distance from the front axle to the center of mass of the vehicle, is the moment of inertia about the Z axis in the vehicle coordinate system, is the mass of the four-wheel-steering bus, is the speed of the four-wheel-steering bus in the x axis direction, the function expression of the linearized control state equation obtained in step S202 is:

[0127] ,

[0128] In the above equation, is the actual value of the current state, is the control amount for controlling the steering angle of the rear wheel rear of the four-wheel-steering bus, is the control state equation. In the following, the subscript with r indicates a reference parameter unless otherwise specified.

[0129] According to the function expression of the nonlinear control state equation and the function expression of the linearized control state equation, the linear error of the vehicle state model can be obtained as:

[0130] ,

[0131] wherein, ; ; ; , is the derivative of the control state equation at the current time with respect to the actual value of the current state , is the derivative of the control state equation at the current time with respect to the control amount . Therefore, the function expression of the discretized control state equation obtained in step S203 of the embodiment is:

[0132] ,

[0133] In the above equation, is the current state at time k+1, is the current state at time k, is the control amount at time k, and is an intermediate variable, is the sampling time, and has:

[0134] ,

[0135] In the above equation, Iis the unit matrix, T is the sampling period, is the control state equation at the current moment The actual value of the current state The derivative of is the control state equation at the current moment Control quantity The derivative of .

[0136] In this embodiment, the function expression of the prediction expression obtained in step S204 is:

[0137] ,

[0138] In the above formula, is the current state at time k, is the control quantity at time k, and:

[0139] , ,

[0140] , ,

[0141] In the above formula, ~ is the prediction time domain after time k ~ Each predicted state value in To control the time domain, For the prediction time domain; ~ are the prediction time domains after time k ~ The control state equation within The actual value of the current state The derivative of The control state equation at any time t after time k is Control quantity The derivative of ~ are the control time domains after time k ~ The various predicted control values ​​within To control the time domain; is the prediction time domain, and .

[0142] In this embodiment, the function expression of the quadratic programming problem obtained in step S204 is:

[0143] ,

[0144] In the above formula, is an intermediate variable, is the control value used to control the steering angle of the rear wheels of a four-wheel steering bus. is the control state equation, and:

[0145] ,

[0146] In the above formula, Q and R are both weight matrices.

[0147] also, , .

[0148] In this embodiment, when optimizing and solving the quadratic programming problem regarding the vehicle lateral displacement deviation in MATLAB within the constraint range of the lateral load transfer rate LTR in step S205, the function expression of the objective function used is:

[0149] ,

[0150] In the above formula, min means taking the minimum value. is the objective function, is the state matrix, is the control matrix, is the prediction time domain; k-time prediction in the prediction time domain The collection of all control quantities, is the reference value of the control quantity at time k, To control the time domain The difference between the actual output value and the reference value, is the weight matrix of relaxation factors; is the relaxation factor, is the weight matrix of vehicle lateral displacement control; The predicted value of vehicle lateral displacement at time k, The reference value of the vehicle lateral displacement at time k, is the control weight matrix for controlling the lateral load transfer rate; is the actual value of the lateral load transfer rate LTR, is the reference value of the lateral load transfer rate LTR, is the weight matrix for rear wheel control; is the weight matrix; is the relaxation factor (used to prevent the objective function from having no solution). That is, the lateral displacement deviation of the vehicle. By optimizing and solving the above formula in each control cycle, the control quantity control sequence in the control time domain can be obtained. Taking the first parameter in the control quantity control sequence as the actual control quantity can effectively reduce the peak value of the lateral load transfer rate and the lateral displacement deviation of the bus, and effectively improve the stability of the vehicle in a crosswind environment.

[0151] Since the MPC controller takes the vehicle's rear wheel steering angle as the control object, it is necessary to consider the extreme position of the vehicle's rear wheel steering angle. Therefore, it is used as a constraint to constrain the control. The control output should satisfy:

[0152] ,

[0153] In the above formula, for ~ The control amount at the moment (rear wheel output angle), and They are the maximum and minimum values ​​of the control amount (rear wheel output angle), which are generally taken as , represents the maximum steering value of the left and right steering angles of the vehicle, which is limited by the vehicle bogie structure. The vehicle roll state parameter is the roll angle, but since the roll angle is not easy to measure in the vehicle, this embodiment introduces the lateral load transfer rate LTR (Lateral Transfer Ratio) as a monitoring indicator for the current vehicle roll angle, which becomes one of the important reference values ​​for the vehicle's active anti-rollover. In this embodiment, the constraint condition of the lateral load transfer rate LTR is that the lateral load transfer rate LTR is less than or equal to 0.8. In addition, the required threshold value can also be used as needed. When the lateral load transfer rate LTR is greater than or equal to 0.8, the vehicle is considered to be in a rollover risk state; when the lateral load transfer rate LTR is less than 0.8, the vehicle's roll angle is considered to be within a safe range and the vehicle is not at risk of rollover.

[0154] like Figure 4 As shown, this embodiment also provides an active steering control system for a four-wheel steering bus, comprising:

[0155] The vehicle simulator (vs_sf) is used to simulate the four-wheel steering bus based on the steering angle of the rear wheels of the four-wheel steering bus in the previous shot to obtain the current state of the four-wheel steering bus, thereby obtaining the front wheel steering angle data front of the four-wheel steering bus and the vertical load of the four-wheel steering bus;

[0156] A reference model calculation unit is used to collect the front wheel angle data front of the four-wheel steering bus in the current state, and calculate the reference vehicle state reference value REF in the current state in combination with the vehicle structural parameters of the four-wheel steering bus;

[0157] a lateral load transfer ratio calculation unit configured to calculate a lateral load transfer ratio LTR of the four-wheel-steering passenger vehicle in a current state;

[0158] an MPC controller configured to optimize and solve a quadratic programming problem of the four-wheel-steering passenger vehicle with respect to a vehicle lateral displacement deviation based on a reference vehicle state reference quantity REF, taking the lateral load transfer ratio LTR as a constraint condition, to obtain a control quantity u for controlling a steering angle of rear wheels rear of the four-wheel-steering passenger vehicle;

[0159] an output end of the vehicle simulator is connected to input ends of the reference model calculation unit and the lateral load transfer ratio calculation unit respectively, output ends of the reference model calculation unit and the lateral load transfer ratio calculation unit are connected to control ends of the MPC controller respectively, and an output end of the MPC controller is connected to an input end of the vehicle simulator through a delay module.

[0160] Referring to Figure 4 In the embodiment, the vehicle simulator specifically adopts a Trucksim-Simulink joint simulation method to verify the effect of the rear wheel steering control of the MPC, a Tour bus 5.5T / 10T (S_S) vehicle model in Trucksim is selected as a simulation model, and vehicle model parameters are shown in Table 1.

[0161] Table 1: Vehicle model parameter table.

[0162]

[0163] The output parameters of the vehicle include the yaw rate, the sideslip angle, the slip ratio, the roll angle, and the tire force of each direction, etc. The control parameters are the steering angle and the rear wheel steering angle, etc. Combined with the MPC control algorithm and the design of the Trucksim vehicle model, a Trucksim-Simulink co-simulation model is built in MATLAB. The co-simulation model outputs the relevant parameters of the test vehicle by the Trucksim vehicle model, in which the front wheel steering angle data is used as the input of the vehicle reference model to ensure the consistency of the test vehicle and the reference model in driving conditions. At the same time, the vehicle structure parameters can be used to calculate the reference vehicle state reference (yaw rate, sideslip angle, lateral acceleration, tire vertical load, etc.). The tire vertical load output from the Trucksim vehicle model and the vehicle reference model is used to calculate the lateral load transfer ratio (LTR). The above parameters can be input into the MPC controller for data processing and rear wheel steering angle control output, and the rear wheel steering angle is output back to the Trucksim vehicle model for tracking control. The vehicle model under various conditions is simulated for comparison. For the convenience of describing the results, the reference vehicle model under windless conditions is denoted as REF (Reference Model), the vehicle model with only front wheel steering under crosswind conditions is denoted as NWS (Nose Wheel Steering), and the active rear wheel steering vehicle under crosswind conditions with MPC control is denoted as FWS (Four Wheel Steering). In order to verify the effectiveness of the active rear wheel steering based on MPC in controlling the roll stability of the four-wheel steering vehicle under the high-speed crosswind disturbance environment, a Trucksim-Simulink co-simulation platform is built. The simulation environment parameters are set as follows: According to the national standard of Wind Force Grade issued in June 2012 in China, the wind force is divided into 0-12 grades, and according to the recommendation of the traffic management department, the wind speed of 6 or above is not recommended to drive at high speed or the road will be under traffic control. Therefore, the simulation environment is set to a lateral wind speed of six levels, i.e. the simulation wind speed is 40 km / h, and the angle between the wind direction and the vehicle forward direction is 90°. The speed limit of domestic highway is 80-120 km / h, the speed limit of national and provincial roads is 80 km / h, and the speed limit of urban roads is 60 km / h. Considering the urban congestion and the existence of buildings, the vehicle is difficult to maintain a high speed in the city, and the wind speed is difficult to reach the standard of six-grade wind. Therefore, the simulation is carried out on the relatively open national and provincial roads with the vehicle driving at a constant speed of 80 km / h on the road with a road adhesion coefficient

[0164] ​Double lane shift is one of the common working conditions of vehicle stability control. In order to verify the active rear wheel steering control method based on MPC, double lane shift verification is carried out on the Trucksim-Simulink joint simulation platform. The vehicle enters the test scene at a constant longitudinal speed of 80 km / h, and the driver controls the front wheel steering angle to track the path, and completes the double lane shift working condition. The change of the front wheel steering angle of the vehicle is as shown in Figure 5 . Figure 6-8 The simulation response characteristics and test results of the REF, NWS and FWS vehicles in the double lane shift working condition mainly include the rear wheel steering angle response curve, the lateral displacement comparison curve of the vehicle running track, and the lateral load transfer rate comparison curve of the vehicle. Figure 6 The rear wheel steering angle response curve of the FWS vehicle under the MPC control can quickly respond when entering the crosswind environment and can be adjusted according to the vehicle state. Figure 7 The lateral displacement change of the REF, NWS and FWS vehicles when completing the double lane shift working condition is that under the interference of crosswind, the maximum deviation peak of the NWS vehicle is 0.566 m, and the overall deviation of the running path is 0.495 m; After the MPC intervention, the lateral displacement deviation of the FWS vehicle is controlled, the peak deviation is 0.232 m, and the overall deviation is only 0.056 m. Figure 8 The change of the vehicle LTR (lateral load transfer rate LTR) value under the crosswind interference working condition is that according to the simulation results, the peak value of the lateral load transfer rate LTR of the NWS vehicle can reach 0.807, which has the risk of rollover; The peak value of the lateral load transfer rate LTR of the FWS vehicle is 0.627; The peak value of the lateral load transfer rate LTR of the REF vehicle is 0.593. The simulation results of the double lane shift simulation working condition show that the active steering control method of the four-wheel steering passenger car of the embodiment can effectively improve the trajectory tracking ability of the vehicle in the high-speed crosswind driving working condition, and effectively constrain the lateral load transfer rate LTR value of the vehicle, and can improve the roll stability of the vehicle.

[0165] The snake working condition is also one of the common working conditions, and the vehicle and road setting are consistent with the double lane shift working condition. The vehicle enters the test scene at a constant longitudinal speed of 80 km / h, and the driver completes the snake working condition according to the preset path. The change of the front wheel steering angle of the vehicle is as shown in Figure 9 . Figure 10-12 The rear wheel response curve, the lateral displacement curve of the vehicle and the change curve of the lateral LTR value of the REF, NWS and FWS vehicles in the snake working condition. Figure 10 The response curve of the rear wheel in the snake working condition, after the vehicle enters the crosswind driving working condition, the rear wheel quickly responds and participates in the real-time adjustment of the vehicle state. Figure 11For the lateral displacement variation curve of the vehicle, the maximum deviation of the lateral displacement of the NWS vehicle and the REF vehicle under the side wind interference is 1.234 m, and the overall deviation of the path is 0.502 m; the maximum deviation of the lateral displacement of the FWS vehicle in the snake running condition is 0.512 m, and the overall deviation of the path is only 0.148 m. Figure 12 For the lateral load transfer rate LTR value variation of the vehicle in the snake running condition simulation, the peak value of the lateral load transfer rate LTR of the NWS vehicle is as high as 0.856, which is in the range of rollover danger; the peak value of the lateral load transfer rate LTR of the FWS vehicle is 0.618; and the peak value of the lateral load transfer rate LTR of the REF vehicle is 0.568. The snake running condition simulation result shows that the MPC can effectively constrain the value of the lateral load transfer rate LTR of the vehicle, and effectively improve the tracking ability of the vehicle running track, and improve the maneuverability and stability of the vehicle.

[0166] In summary, for the side wind stability control problem of the passenger car, the lateral load transfer rate (LTR) is introduced as the evaluation index of the vehicle roll stability, the cooperative control problem of the passenger car side slip and roll instability condition is analyzed, and the active rear wheel steering control optimization method based on the MPC is designed. In the side wind condition, the peak value of the LTR of the FWS vehicle in the double moving line condition is reduced by 22.3% compared with the peak value of the LTR of the NWS vehicle. In the snake running condition, the peak value of the LTR of the FWS vehicle is reduced by 27.8% compared with the peak value of the LTR of the NWS vehicle. Under the MPC active steering control, the roll stability of the high-speed vehicle is effectively controlled. In the side wind double moving line condition, the peak value of the path deviation of the FWS vehicle is reduced by 59.0% compared with the NWS vehicle; the overall path deviation of the FWS vehicle is reduced by about 77.6% compared with the NWS vehicle. In the side wind snake running condition, the peak value of the path deviation of the FWS vehicle is reduced by 58.5% compared with the NWS vehicle; the overall path deviation of the FWS vehicle is reduced by about 70.5% compared with the NWS vehicle. Under the MPC active steering control, the lateral displacement of the high-speed vehicle is effectively controlled. It can be seen that the active steering control method of the four-wheel steering passenger car can effectively improve the track tracking ability of the vehicle in the high-speed side wind running condition, effectively constrain the value of the lateral load transfer rate LTR of the vehicle, effectively control the lateral displacement of the high-speed vehicle, and improve the roll stability of the vehicle.

[0167] In addition, the embodiment also provides an active steering control system of a four-wheel steering passenger car, which comprises a microprocessor and a memory connected with each other, and the microprocessor is programmed or configured to execute the active steering control method of the four-wheel steering passenger car.

[0168] In addition, the embodiment also provides a computer readable storage medium, and the computer readable storage medium stores a computer program for programming or configuring a microprocessor to execute the active steering control method of the four-wheel steering passenger car.

[0169] Those skilled in the art will appreciate that embodiments of the application can be readily used as software, hardware, or a combination of software and hardware. In a software embodiment, the methods can be tangibly embodied in a machine-readable storage medium having stored thereon instructions that can be used to program a processing system to perform the methods. The term "processor" should be interpreted broadly to encompass a complete processing system, including a central processing unit, a microprocessor, a microcontroller, a digital signal processor, a microcomputer, a programmable logic controller, a general purpose computer or any other processing system. The methods can be implemented using instructions stored on a machine-readable storage medium, such as a floppy disk, a hard disk, a CD-ROM, a RAM, a ROM, a PROM, an EPROM, an EEPROM, a cassette, a magnetic tape, an optical storage medium, a memory card, a digital versatile disk (DVD), etc. The methods can also be implemented using instructions stored on a machine-readable storage medium in combination with a processor capable of executing the instructions. Figure 1 one or more functions specified in the flow or flows and / or blocks Figure 1 one or more functions specified in the flow or flows and / or blocks Figure 1 one or more functions specified in the flow or flows and / or blocks Figure 1 one or more functions specified in the flow or flows and / or blocks Figure 1 one or more functions specified in the flow or flows and / or blocks Figure 1 one or more functions specified in the flow or flows and / or blocks

[0170] The above description is only preferred embodiments of the application. The protection scope of the application is not limited to the above-mentioned embodiments. Any technical scheme falling within the idea of the application should be considered as falling within the protection scope of the application.

Claims

1. An active steering control method for a four-wheel steering passenger car, characterized in that: include: S101, obtaining a reference vehicle state reference quantity REF of the four-wheel steering bus in the current state, and calculating a lateral load transfer rate LTR of the four-wheel steering bus in the current state; the reference vehicle state reference quantity REF includes a yaw angular velocity, a sideslip angle of the center of mass, a lateral acceleration, and a tire vertical load; S102, using the lateral load transfer rate LTR as a constraint condition, and optimizing and solving a quadratic programming problem regarding the vehicle lateral displacement deviation of the four-wheel steering bus based on a reference vehicle state reference REF, to obtain a control variable u for controlling the steering angle of the rear wheels of the four-wheel steering bus; Step S102 includes: S201, establishing a nonlinear control state equation for a four-wheel steering bus based on a reference vehicle state reference REF; S202, performing Taylor expansion on the nonlinear control state equation of the four-wheel steering bus at a reference value of the current state to obtain a linearized control state equation; S203, discretizing the linearized control state equation using forward Euler to obtain a discretized control state equation; S204: performing prediction in the prediction time domain based on the discretized control state equation to obtain a prediction expression, and transforming the prediction formula to obtain a quadratic programming problem for the vehicle lateral displacement deviation; S205: Optimize and solve the quadratic programming problem for the vehicle lateral displacement deviation in MATLAB within the constraint of the lateral load transfer rate (LTR), thereby obtaining a control variable u for controlling the steering angle of the rear wheels of the four-wheel steering bus. When optimizing and solving the quadratic programming problem for the vehicle lateral displacement deviation in MATLAB within the constraint of the lateral load transfer rate (LTR), the objective function expression used is: ， In the above formula, min means taking the minimum value. is the objective function, is the state matrix, is the control matrix, For the prediction time domain; k-time prediction in the prediction time domain The collection of all control quantities, is the reference value of the control quantity at time k, To control the time domain The difference between the actual output value and the reference value, is the weight matrix of relaxation factors; is the relaxation factor, is the weight matrix of vehicle lateral displacement control; The predicted value of vehicle lateral displacement at time k, The reference value of the vehicle lateral displacement at time k, is the control weight matrix for controlling the lateral load transfer rate; is the actual value of the lateral load transfer rate LTR, is the reference value of the lateral load transfer rate LTR, is the weight matrix for rear wheel control.

2. The active steering control method for a four-wheel steering bus according to claim 1, characterized in that: The calculation function expression of the lateral load transfer rate LTR in step S101 is: ， In the above formula, LTR is the lateral load transfer rate, F zfl is the vertical load on the left front wheel, F zrl is the vertical load on the left rear wheel, F zfr is the vertical load on the right front wheel, F zrr is the vertical load on the right rear wheel, and the calculation function expressions of the vertical loads on the left front wheel, left rear wheel, right front wheel and right rear wheel are: ， ， ， ， In the above formula, m is the mass of the four-wheel steering bus, g is the acceleration, is the height from the vehicle's center of mass to the center of suspension, and are the accelerations of the four-wheel steering bus in the x-axis and y-axis directions, T is the left and right wheelbase of the vehicle, l f is the distance from the front axle to the vehicle's center of mass; l r is the distance from the rear axle to the vehicle's center of mass.

3. The active steering control method for a four-wheel steering bus according to claim 1, characterized in that: The functional expression of the nonlinear control state equation of the four-wheel steering bus established in step S201 is: = ， In the above formula, Reference value for the current state The symbol for the control state equation function is, is the reference value of the current state, is the reference value of the control quantity u, is the state derivative matrix, is the state matrix, is the control input matrix, is the output matrix, and is the cornering stiffness of the front and rear wheels, and is the distance from the front and rear axles to the vehicle's center of mass, is the moment of inertia around the Z axis in the vehicle coordinate system, is the mass of the four-wheel steering bus, is the speed of the four-wheel steering bus in the x-axis direction. The function expression of the linearized control state equation obtained in step S202 is: ， In the above formula, is the actual value of the current state, is the control value used to control the steering angle of the rear wheels of a four-wheel steering bus. is the control state equation.

4. The active steering control method for a four-wheel steering bus according to claim 3, characterized in that: The function expression of the control state equation after discretization obtained in step S203 is: ， In the above formula, is the current state at time k+1, is the current state at time k, is the control quantity at time k, and is an intermediate variable, is the sampling time, and: ， In the above formula, I is the unit matrix, T is the sampling period, is the control state equation at the current moment The actual value of the current state The derivative of is the control state equation at the current moment Control quantity The derivative of .

5. The active steering control method for a four-wheel steering bus according to claim 4, characterized in that: The function expression of the prediction expression obtained in step S204 is: ， In the above formula, is the current state at time k, is the control quantity at time k, and: ， ， ， ， In the above formula, ~ is the prediction time domain after time k ~ Each predicted state value in To control the time domain, For the prediction time domain; ~ are the prediction time domains after time k ~ The control state equation within The actual value of the current state The derivative of The control state equation at any time t after time k is Control quantity The derivative of ~ are the control time domains after time k ~ The various predicted control values ​​within , and there are The function expression of the quadratic programming problem obtained in step S204 is: ， In the above formula, is an intermediate variable, is the control value used to control the steering angle of the rear wheels of a four-wheel steering bus. is the control state equation, and: ， In the above formula, Q and R are both weight matrices.

6. An active steering control simulation system for a four-wheel steering passenger vehicle using the active steering control method for a four-wheel steering passenger vehicle according to any one of claims 1 to 5, characterized in that: include: A vehicle simulator is used to simulate the four-wheel steering bus based on the steering angle of the rear wheels of the four-wheel steering bus in the previous shot to obtain the current state of the four-wheel steering bus, so as to obtain the front wheel steering angle data front of the four-wheel steering bus and the vertical load of the four-wheel steering bus; A reference model calculation unit is used to collect the front wheel angle data front of the four-wheel steering bus in the current state, and calculate the reference vehicle state reference value REF in the current state in combination with the vehicle structural parameters of the four-wheel steering bus; A lateral load transfer rate calculation unit is used to calculate the lateral load transfer rate LTR of the four-wheel steering bus in the current state; The MPC controller is used to use the lateral load transfer rate LTR as a constraint condition, and optimize the quadratic programming problem of the four-wheel steering bus regarding the vehicle lateral displacement deviation based on the reference vehicle state reference quantity REF to obtain a control quantity u for controlling the steering angle of the rear wheel of the four-wheel steering bus, including: S201, establishing a nonlinear control state equation of the four-wheel steering bus based on the reference vehicle state reference quantity REF; S202, performing Taylor expansion on the nonlinear control state equation of the four-wheel steering bus at the reference value of the current state to obtain a linearized control state equation; S203, using forward Euler to discretize the linearized control state equation to obtain the discretized control state equation; S204, performing prediction in the prediction domain based on the discretized control state equation to obtain a prediction expression, and transforming the prediction formula to obtain a quadratic programming problem for the vehicle lateral displacement deviation; S205, optimizing and solving the quadratic programming problem for the vehicle lateral displacement deviation within the constraint range of the lateral load transfer rate LTR in MATLAB, thereby obtaining a control variable u for controlling the steering angle of the rear wheels of the four-wheel steering bus; The output end of the vehicle simulator is connected to the input end of the reference model calculation unit and the lateral load transfer rate calculation unit respectively. The output ends of the reference model calculation unit and the lateral load transfer rate calculation unit are connected to the control end of the MPC controller respectively. The output end of the MPC controller is connected to the input end of the vehicle simulator through a delay module.

7. An active steering control system for a four-wheel steering passenger vehicle, comprising a microprocessor and a memory connected to each other, characterized in that: The microprocessor is programmed or configured to execute the active steering control method for a four-wheel steering passenger vehicle according to any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, wherein: The computer program is used to be programmed or configured by a microprocessor to execute the active steering control method for a four-wheel steering passenger vehicle according to any one of claims 1 to 5.

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