Method and system for controlling transverse stability of vehicle during braking on split road surface

Abstract

The invention provides a transverse stability control method and system during braking of a vehicle on a split road surface, and belongs to the technical field of vehicle transverse stability control. According to the method, the expected braking strength zd is compared with the maximum braking strength zth which can be generated by the whole vehicle on the low-adhesion road surface, and when zd is smaller than or equal to zth, the braking force at the high-adhesion position is restrained, and the difference value between the braking force at the high-adhesion position and the braking force at the low-adhesion position is reduced or even eliminated through the design of the controller; when z dgt; when zth is greater than zth, through the design of a controller, the braking force at the low attachment part is kept at a peak value, the braking force at the high attachment part is regulated and controlled, and meanwhile, the rear wheel turning angle is controlled, so that an additional yawing moment is generated, and the expected yawing moment of the whole vehicle is compensated. The invention further provides a split road surface stability comprehensive risk index, and the stability of the vehicle during braking on the split road surface is comprehensively evaluated. When the vehicle exceeds a steady state boundary, active four-wheel steering intervenes. According to the invention, the transverse stability of the vehicle during braking on the split road surface is effectively improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of vehicle lateral stability control, and is based on a distributed drive electric vehicle, and particularly relates to a method and a system for controlling the lateral stability of a vehicle during braking on a split road surface. Background Art

[0002] A split road surface refers to a road surface where there is a large difference in the road adhesion coefficients on the left and right sides of the vehicle when it is driving. This kind of road condition is common in snowy areas. The snow is cleared to the roadside. When the vehicle is driving close to the roadside, one side of the wheels is on the snowy road surface and the other side of the wheels is on the dry road surface. When braking on this kind of road surface, the different road adhesion coefficients on both sides will cause different braking forces on the left and right wheels, and the generated yaw moment will cause the vehicle to deviate during braking. This phenomenon will not only affect the handling stability of the vehicle, but may also cause serious safety hazards.

[0003] It is crucial to improve the lateral stability of the vehicle during braking on a split road surface. At present, most of the existing technologies ensure the lateral stability of the vehicle during braking on a split road surface through active steering or direct yaw moment control, but the pertinence to the split road surface is not strong. Summary of the Invention

[0004] Aiming at the deficiencies in the prior art, the present invention provides a method and a system for controlling the lateral stability of a vehicle during braking on a split road surface.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] In the first aspect, the present invention provides a method for controlling the lateral stability of a vehicle during braking on a split road surface, including:

[0007] Collect vehicle data, calculate the difference Δα in the average angular deceleration on both sides according to the vehicle data, and fuse the difference Δα in the average angular deceleration on both sides and the steady-state region of the ω-β phase plane into a comprehensive risk index M for the stability of the split road surface, where ω is the vehicle yaw angular velocity and β is the sideslip angle of the center of mass; set a threshold M for the comprehensive risk index th , when M ≤ M th , the vehicle brakes normally; when M > M th , enable the control strategy until M ≤ M th and the duration exceeds the set threshold t th ;

[0008] The control strategy is: judge the stability through the ω-β phase plane. When |ω + B1β| ≤ B2, compare the maximum braking intensity z th that the whole vehicle can generate on the low-adhesion road surface and the desired braking intensity z d . If z d ≤ z th, the execution controller 1 regulates the braking forces at the high - adhesion area and the low - adhesion area; if z d >z th , the execution controller 2 keeps the braking force at the low - adhesion area at the peak value, only regulates the braking force at the high - adhesion area, and controls the rear - wheel steering angle at the same time; when |ω + B1β|>B2, the execution controller 3 makes the active four - wheel steering intervene and work.

[0009] Optionally, the vehicle data includes vehicle yaw angular velocity, longitudinal vehicle speed, lateral vehicle speed, angular velocities corresponding to each wheel, steering wheel angle, and brake pedal stroke.

[0010] Optionally, calculating the difference Δα in the average angular deceleration on both sides according to the vehicle data is specifically as follows:

[0011] According to the left - front - wheel angular velocity ω 11 , the right - front - wheel angular velocity ω 12 , the left - rear - wheel angular velocity ω 21 and the right - rear - wheel angular velocity ω 22 , the angular deceleration of each wheel is calculated by time - difference to obtain the left - front - wheel angular deceleration α 11 , the right - front - wheel angular deceleration α 12 , the left - rear - wheel angular deceleration α 21 and the right - rear - wheel angular deceleration α 22 ;

[0012] Calculate the left - hand - side average angular deceleration α L and the right - hand - side average angular deceleration α R as:

[0013]

[0014] Then the difference Δα in the average angular deceleration on both sides is:

[0015] Δα = α L -α R .

[0016] Optionally, the comprehensive risk index M for the split - surface road stability is:

[0017]

[0018] where α th is the threshold value of the absolute value of the difference in the average angular deceleration on both sides, B = |ω + B1β| is the ω - β phase - plane stability evaluation index, B th is the threshold value of B, and λ1 and λ2 are weight coefficients, and λ1+λ2 = 1.

[0019] Optionally, the maximum braking intensity z th that the whole vehicle can generate on the low - adhesion road surface = μ1, where μ1 is the road adhesion coefficient at the low - adhesion area.

[0020] Optionally, the desired braking intensity z d is obtained by the following method:

[0021] Based on fuzzy control for braking intention recognition, the braking pedal travel and the braking pedal operation speed are used as the inputs of the braking intention recognition, and the desired braking intensity z d is used as the output of the braking intention recognition.

[0022] Optionally, the first controller adopts a hierarchical design; the input of the upper-layer controller is the deviation between the vehicle yaw rate ω and the reference yaw rate ω r and the deviation between the center-of-mass side slip angle β and the reference center-of-mass side slip angle β r , and the output is the additional yaw moment M Z . The additional yaw moment M Z is sent to the lower-layer controller as the target of the braking force distribution;

[0023] The lower-layer controller takes the tire utilization rate as the optimization target, and the objective function J is:

[0024]

[0025] where μ ij is the road surface adhesion coefficient corresponding to the wheel, F xij is the longitudinal force received by the wheel, F zij is the vertical force received by the wheel, and the subscripts 11, 12, 21, and 22 respectively represent the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel;

[0026] When distributing the braking force, the following constraint conditions are satisfied:

[0027]

[0028] where F x is the total longitudinal force of the vehicle, D is the wheel track, R W is the effective radius of the wheel, T max is the maximum braking torque that the brake can generate, μ1 is the road surface adhesion coefficient at the low-adhesion area, m is the mass of the vehicle above the spring, and g is the acceleration due to gravity;

[0029] The lower-layer controller combines the objective function and the constraint conditions to obtain the braking force required for each wheel, controls the brake to generate the target braking force, and thus generates the target additional yaw moment.

[0030] Optionally, the second controller adopts a hierarchical design; the input of the upper-layer controller is the deviation between the vehicle yaw rate ω and the reference yaw rate ω r and the deviation between the center-of-mass side slip angle β and the reference center-of-mass side slip angle β rThe deviation is output as the additional yaw moment M Z and the rear wheel steering angle δ r ; The rear wheel steering angle δ r is sent to the steering system, and the wheels reach the corresponding steering angles through the rear wheel steering motor, thereby generating the corresponding additional yaw moment; The additional yaw moment M Z is sent to the lower layer controller as the target of braking force distribution;

[0031] The lower layer controller takes the tire utilization rate as the optimization target, and the objective function J is:

[0032]

[0033] where μ ij is the road adhesion coefficient corresponding to the wheel, F xij is the longitudinal force received by the wheel, F zij is the vertical force received by the wheel, and the subscripts 11, 12, 21, and 22 represent the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively;

[0034] The following constraint conditions are satisfied during braking force distribution:

[0035]

[0036] where F x is the total longitudinal force of the vehicle, D is the wheel track, R W is the effective radius of the wheel, T max is the maximum braking torque that the brake can generate, is the peak adhesion coefficient, μ2 is the road adhesion coefficient at the high adhesion area, m is the mass of the vehicle above the spring, g is the acceleration due to gravity, the left side is the low adhesion road surface, and the right side is the high adhesion road surface;

[0037] The lower layer controller combines the objective function and the constraint conditions to obtain the braking forces required for each wheel, controls the brake to generate the target braking force, and thus generates the target additional yaw moment.

[0038] Optionally, the controller three adopts a hierarchical design; The input of the upper layer controller is the deviation between the vehicle yaw angular velocity ω and the reference yaw angular velocity ω r and the deviation between the center of mass sideslip angle β and the reference center of mass sideslip angle β r The output is the front wheel steering angle δ f and the rear wheel steering angle δ r and the additional yaw moment M Z ; The front wheel steering angle δ f and the rear wheel steering angle δ r are sent to the steering system, and the wheels reach the corresponding steering angles through the steering motor, thereby generating the corresponding additional yaw moment; The additional yaw moment M ZSend it to the lower - layer controller as the target of braking force distribution;

[0039] The lower - layer controller takes the tire utilization rate as the optimization target, and the objective function J is:

[0040]

[0041] Where, μ ij is the road surface adhesion coefficient corresponding to the wheel, F xij is the longitudinal force received by the wheel, F zij is the vertical force received by the wheel, and the subscripts 11, 12, 21, and 22 represent the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively;

[0042] When distributing the braking force, the following constraint conditions are satisfied:

[0043]

[0044] Where, F x is the total longitudinal force of the vehicle, D is the wheelbase of the vehicle, R W is the effective radius of the wheel, T max is the maximum braking torque that the brake can generate, μ1 is the road surface adhesion coefficient at the low - adhesion area, μ2 is the road surface adhesion coefficient at the high - adhesion area, m is the mass of the vehicle above the spring, g is the acceleration due to gravity, the left side is the low - adhesion road surface, and the right side is the high - adhesion road surface;

[0045] The lower - layer controller combines the objective function and the constraint conditions to obtain the required braking force for each wheel, controls the brake to generate the target braking force, and thus generates the target additional yaw moment.

[0046] In a second aspect, the present invention provides a lateral stability control system for a vehicle during braking on a split - surface road, including: a vehicle data acquisition unit, a vehicle stability monitoring unit, and a split - surface road braking lateral stability control unit;

[0047] The vehicle data acquisition unit acquires vehicle data; the vehicle stability monitoring unit calculates the difference Δα in the average angular deceleration on both sides according to the vehicle data, and fuses the difference Δα in the average angular deceleration on both sides and the steady - state region of the ω - β phase plane into a split - surface road stability comprehensive risk index M, where ω is the vehicle yaw angular velocity and β is the sideslip angle of the center of mass; set a comprehensive risk index threshold M th , when M ≤ M th , the vehicle brakes normally; when M > M th , the split - surface road braking lateral stability control unit activates the control strategy until M ≤ M th and the duration exceeds the set threshold t th ;

[0048] The control strategy for starting the split - road surface braking lateral stability control unit is as follows: the stability is judged through the ω - β phase plane. When |ω + B1β| ≤ B2, compare the maximum braking intensity z that the whole vehicle can generate on the low - adhesion road surface th and the desired braking intensity z d . If z d ≤ z th , execute Controller 1, and regulate the braking forces at high - adhesion and low - adhesion areas; if z d > z th , execute Controller 2, keep the braking force at the low - adhesion area at the peak value, only regulate the braking force at the high - adhesion area, and control the rear - wheel steering angle at the same time; when |ω + B1β| > B2, execute Controller 3 to make the active four - wheel steering intervene.

[0049] The beneficial effects of the present invention are as follows: The control strategy of the present invention is designed for split - road surfaces and is more suitable for braking on split - road surfaces, effectively solving the problem that the existing technology is not targeted enough for split - road surfaces. By comparing the desired braking intensity with the maximum braking intensity that the whole vehicle can generate on the low - adhesion road surface, when the desired braking intensity does not exceed the maximum braking intensity that the whole vehicle can generate on the low - adhesion road surface, through the design of the controller, the braking force at the high - adhesion area is suppressed, and the difference from the braking force at the low - adhesion area is reduced or even eliminated; when the desired braking intensity exceeds the maximum braking intensity that the whole vehicle can generate on the low - adhesion road surface, through the design of the controller, keep the braking force at the low - adhesion area at the peak value, only regulate the braking force at the high - adhesion area, which can minimize the yaw moment generated during braking on split - road surfaces; at the same time, control the rear - wheel steering angle to generate an additional yaw moment to compensate the desired yaw moment of the whole vehicle. The present invention also proposes a comprehensive risk index for split - road surface stability, and comprehensively evaluates the stability of the vehicle during braking on split - road surfaces through the difference in average angular deceleration on both sides of the vehicle and the steady - state area of the ω - β phase plane. When it is detected that the vehicle exceeds the steady - state boundary, the active four - wheel steering intervenes to further ensure the stability of the vehicle. In summary, the present invention effectively improves the lateral stability of the vehicle during braking on split - road surfaces and ensures the braking safety of the vehicle. Description of the Drawings

[0050] Figure 1 It is a structural diagram of a lateral stability control system for a vehicle during braking on a split - road surface.

[0051] Figure 2 It is a flowchart of a lateral stability control method for a vehicle during braking on a split - road surface. Detailed Embodiments

[0052] Now, the present invention will be further described in detail with reference to the drawings.

[0053] Embodiment 1

[0054] This embodiment proposes a lateral stability control system for a vehicle during braking on a split road surface, such as Figure 1 shown. The system includes a vehicle data acquisition unit, a vehicle stability monitoring unit, a road surface recognition unit, a braking intention recognition unit, a lateral stability control unit for braking on a split road surface, and a vehicle execution unit.

[0055] The vehicle data acquisition unit acquires the required data, such as vehicle yaw rate, longitudinal vehicle speed, lateral vehicle speed, angular velocity corresponding to each wheel, steering wheel angle, braking pedal stroke, etc., and sends the acquired data to the corresponding data processing unit for calculation and processing.

[0056] The vehicle stability monitoring unit calculates the difference Δα between the average angular decelerations on both sides, and fuses the difference Δα between the average angular decelerations on both sides and the steady-state region of the ω-β phase plane into a comprehensive risk index M for the lateral stability of the split road surface, where ω is the vehicle yaw rate and β is the sideslip angle of the center of mass. Set M th as the threshold of the comprehensive risk index. When M is greater than M th , the control strategy will be enabled.

[0057] The road surface recognition unit processes the data acquired by the data acquisition unit to obtain the road surface adhesion coefficient μ1 at the low-adhesion area and the road surface adhesion coefficient μ2 at the high-adhesion area.

[0058] Calculate the maximum braking intensity z that the whole vehicle can generate on this low-adhesion road surface th , the maximum braking intensity z that the whole vehicle can generate on the low-adhesion road surface th = μ1.

[0059] The braking intention recognition unit recognizes the braking intention based on fuzzy control, takes the braking pedal stroke and the braking pedal operation speed as the inputs of the braking intention recognition unit, and takes the desired braking intensity z d as the output of the braking intention recognition module.

[0060] The lateral stability control unit for braking on a split road surface enables the control strategy, and then the vehicle execution unit executes it.

[0061] Embodiment 2

[0062] Based on the lateral stability control system proposed in Embodiment 1, this embodiment proposes a lateral stability control method for a vehicle during braking on a split road surface, such as Figure 2 shown. The specific steps are as follows:

[0063] Step 1: The vehicle data acquisition unit acquires the data required for this method and sends the acquired data to the corresponding data processing unit for calculation and processing.

[0064] Step 2: The vehicle stability monitoring unit calculates the difference in average angular deceleration Δα between the two sides, and fuses the difference in average angular deceleration between the two sides and the steady-state region of the ω-β phase plane into the comprehensive risk index M of split-road surface stability, and sets M th as the threshold of the comprehensive risk index. When M is greater than M th , the following control strategies will be enabled.

[0065] Step 3: The road surface recognition unit processes the data collected by the data acquisition unit to obtain the road surface adhesion coefficient μ1 at the low-adhesion area and the road surface adhesion coefficient μ2 at the high-adhesion area.

[0066] Step 4: Calculate the maximum braking intensity z that the whole vehicle can generate on the low-adhesion road surface th , z th = μ1.

[0067] Step 5: Based on fuzzy control, identify the braking intention. The braking pedal stroke and the braking pedal operation speed are used as the inputs of the braking intention recognition unit, and the desired braking intensity z d is used as the output of the braking intention recognition module.

[0068] Step 6.1: When z d ≤z th , it means that the desired braking intensity can be generated without fully utilizing the high-adhesion road surface for braking. Through the design of the controller, the braking forces at the high-adhesion area and the low-adhesion area are regulated, and neither exceeds the adhesion limit at the low-adhesion area. By suppressing the braking force at the high-adhesion area, the difference in braking force from the low-adhesion area is reduced or even eliminated, and the yaw moment generated during braking on the split-road surface is eliminated as much as possible.

[0069] Step 6.2: When z d >z th , it means that braking on the high-adhesion road surface is required to achieve the desired braking intensity. Through the design of the controller, the braking force at the low-adhesion area is maintained at the peak value, and only the braking force at the high-adhesion area is regulated, which can minimize the yaw moment generated during braking on the split-road surface. At the same time, the rear wheel steering angle δ r is controlled to generate an additional yaw moment to compensate for the desired yaw moment of the whole vehicle.

[0070] Step 7: The vehicle stability monitoring unit judges the stability through the ω-β phase plane. The stable region of the ω-β phase plane is divided by the double-line method, and the stable region formula is expressed as |ω + B1β| ≤ B2, where the coefficients B1 and B2 are boundary parameters. When |ω + B1β| ≤ B2, only the control strategies described in Step 6.1 or Step 6.2 are used; if the value of |ω + B1β| rises above B2, active four-wheel steering also intervenes to ensure the stability of the vehicle.

[0071] Step 8: When the vehicle stability monitoring unit calculates that the comprehensive risk index M ≤ M th and the duration exceeds t th then exit the above control strategy.

[0072] Further, expand and explain Step 2:

[0073] Obtain the left front wheel angular velocity ω 11 , right front wheel angular velocity ω 12 , left rear wheel angular velocity ω 21 , and right rear wheel angular velocity ω 22 from the vehicle data acquisition module. Calculate the angular deceleration α of each wheel through time difference, and the left front wheel angular deceleration α 11 , right front wheel angular deceleration α 12 , left rear wheel angular deceleration α 21 , and right rear wheel angular deceleration α 22 can be obtained.

[0074] Calculate the left side average angular deceleration α L and the right side average angular deceleration α R :

[0075]

[0076] Let Δα be the difference between the left and right side average angular decelerations:

[0077] Δα = α L - α R

[0078] For the open road surface stability comprehensive risk index M:

[0079]

[0080] where α th is the threshold value of the absolute value of the difference between the left and right side average angular decelerations, B = |ω + B1β| is the ω-β phase plane stability evaluation index, B th is its threshold value, λ1 and λ2 are the weight coefficients of the two, and λ1 + λ2 = 1.

[0081] Set the comprehensive risk index threshold M th to 1. When M > 1, the open road surface braking lateral stability control unit starts to work.

[0082] Further, expand and explain Step 5:

[0083] Triangle functions are selected for the braking intention recognition to fuzzify the input quantities. The fuzzy subsets of the braking pedal stroke are (L, M, H), the fuzzy subsets of the braking pedal operation speed are (L, M, H), and the fuzzy subsets of the braking intensity are (L, M, H). The defuzzification process uses the weighted average method to calculate the exact braking intensity. The specific fuzzy rules are shown in the following table.

[0084] Table 1 Fuzzy Rules

[0085]

[0086] Furthermore, the description of step 6.1 is expanded as follows:

[0087] This controller is designed in a hierarchical manner. The input of the upper-layer controller is the deviation between the vehicle yaw rate and the sideslip angle of the center of mass and the reference yaw rate and the sideslip angle of the center of mass, and the output is the additional yaw moment; the lower-layer controller distributes the braking torque according to the longitudinal required braking force and the required yaw moment.

[0088] Upper-layer controller

[0089] Establish a two-degree-of-freedom vehicle model:

[0090]

[0091] where m is the sprung mass of the vehicle; a is the distance from the front axle to the center of mass, b is the distance from the rear axle to the center of mass; v x is the longitudinal speed of the vehicle, v y is the lateral speed of the vehicle; k1 and k2 are the cornering stiffnesses of the front and rear wheels respectively; δ f represents the front wheel steering angle; ω is the vehicle yaw rate, β is the sideslip angle of the center of mass, I z represents the moment of inertia of the vehicle about the Z axis, M Z is the corrected yaw moment.

[0092] Select the state variables as the sideslip angle β of the center of mass and the yaw rate ω, then the state space equation is as follows:

[0093]

[0094] The state variable x = [β ω] Τ , the output variable y = [β ω] Τ , the control variable u = M Z , δ f The front wheel steering angle is a known quantity and can be used as a system disturbance, and the state equation is written as follows:

[0095]

[0096] where,

[0097]

[0098] Discretize the above continuous system with a sampling time of t s , and the state-space expression after discretization is as follows:

[0099]

[0100] where k represents the time instant and τ represents the integration variable.

[0101] To reduce or eliminate the static error, an integral term is introduced, and the state-space equation is rewritten in the following incremental form:

[0102]

[0103] where Δx(k) = x(k) - x(k - 1), Δu(k) = u(k) - u(k - 1), and ΔΨ(k) = Ψ(k) - Ψ(k - 1).

[0104] Set the prediction horizon to P and the control horizon to m MPC , and the control horizon does not exceed the prediction horizon. Outside the control horizon, Δu(k + i) = 0 (i ≥ m MPC ). Assuming that the external input disturbance remains unchanged within the prediction horizon P, that is, ΔΨ(k + i) = 0 (i = 1, 2,..., P - 1), then the P-step prediction output vector and m MPC step control input vector can be defined as follows:

[0105] Y P (k + 1|k) = [y(k + 1|k) y(k + 2|k)... y(k + P|k)] T

[0106] ΔU(k + 1|k) = [Δu(k + 1) Δu(k + 2)... Δu(k + m MPC - 1)] T

[0107] where y(k + i|k) is the output of the system predicted at time k for time k + i, and Δu(k + i) is the change in the system control at time k + i.

[0108] According to the incremental form of the state-space equation, the expression for the P-step prediction output Y P (k + 1|k) can be derived:

[0109] Y P (k + 1|k) = S x Δx(k) + Ν y y(k) + S u ΔU(k) + S Ψ ΔΨ(k)

[0110] Among them,

[0111]

[0112]

[0113] where I is a unit vector, S x , Ν y , S u , S Ψ is the coefficient matrix of Y P (k + 1|k).

[0114] Define the reference sequence as follows:

[0115] R(k + 1) = [r(k + 1) r(k + 2)…r(k + P)] T

[0116] where r(k + i) represents the reference value at time k + i, and r(k + i) = [β r ω r Τ , β r is the reference centroid side slip angle, and ω r is the reference yaw angular velocity.

[0117] During steady-state driving, the centroid side slip angular velocity of the vehicle yaw angular acceleration Substituting into the above state space equation gives:

[0118]

[0119] where, is the stability coefficient, β d is the ideal centroid side slip angle, and ω d is the ideal yaw angular velocity.

[0120] Taking the reference centroid side slip angle as 0 can ensure the stability of the vehicle during high-speed driving. Considering that the road surface adhesion condition will impose certain constraints on the yaw angular velocity, the final reference centroid side slip angle and reference yaw angular velocity for optimization can be expressed as:

[0121]

[0122] where μ is the road surface adhesion coefficient and g is the acceleration due to gravity.

[0123] To achieve the ideal control effect, the actual yaw angular velocity and centroid side slip angle should coincide with the corresponding ideal values as soon as possible, while considering the control amplitude of the vehicle yaw moment. Then the objective function is selected as follows:

[0124]

[0125] Among them, Γ y,i is the weight matrix of the output error predicted at the i-th step, and Γ u,i is the weight matrix of the control increment predicted at the i-th step, and Γ y,i , Γ u,i are all diagonal matrices.

[0126] Set the constraint conditions as follows:

[0127]

[0128] Among them, the subscripts max and min correspond to their maximum and minimum values respectively.

[0129] Rewrite the objective function into matrix form:

[0130] J(x(k), ΔU(k), m MPC , P) = ||Γ y (Y P (k + 1|k) - R(k + 1))|| 2 + ||Γ u ΔU(k)|| 2

[0131] Among them, Γ y = diag(Γ y,1 , Γ y,2 , …, Γ y,P ), Γ u = diag(Γ u,1 , Γ u,2 , …, Γ u,P ).

[0132] The optimal control sequence ΔU * (k) can be solved as:

[0133]

[0134] E P (k + 1|k) = R(k + 1) - S x Δx(k) - Ν y y(k) - S Ψ ΔΨ(k)

[0135] Take the first item in the ΔU * (k) sequence to obtain the current control input, that is, u(k) = u(k - 1) + Δu(k), which is also the current required yaw moment value M Z . Send the additional yaw moment M Z to the lower-level controller as the target of braking force distribution.

[0136] Lower - layer controller

[0137] The tire utilization rate can characterize the stability margin of the tire, and it can be selected as the optimization objective. Since the lateral force of the tire is uncontrollable, only the longitudinal force of the tire is considered. Then the objective function is as follows:

[0138]

[0139] Among them, μ ij is the road adhesion coefficient corresponding to the wheel, F xij is the longitudinal force received by the wheel, F zij is the vertical force received by the wheel (the subscript i = 1, 2 represents the front and the rear, the subscript j = 1, 2 represents the left and the right, 11 represents the left front wheel, 12 represents the right front wheel, 21 represents the left rear wheel, and 22 represents the right rear wheel).

[0140] When distributing the braking force, the following constraint conditions should be met:

[0141]

[0142] Among them, F x is the total longitudinal force of the vehicle, D is the wheelbase of the vehicle, R W is the effective radius of the wheel, T max is the maximum braking torque that the brake can generate, and μ1 is the road adhesion coefficient at the low - adhesion area.

[0143] Combining the objective function and the constraint conditions, the braking force required for each wheel can be obtained, and the brake is controlled to generate the target braking force, thus ensuring the stable driving of the vehicle.

[0144] Furthermore, the description of step 6.2 is expanded as follows:

[0145] This controller is designed in a hierarchical manner. The input of the upper - layer controller is the difference between the vehicle's yaw rate and the sideslip angle of the center of mass and the reference yaw rate and the sideslip angle of the center of mass, and the output is the additional yaw moment and the rear - wheel steering angle; the lower - layer controller distributes the braking torque according to the longitudinal required braking force and the required yaw moment.

[0146] Upper - layer controller

[0147] A two - degree - of - freedom model of the vehicle is established, and the state variables are selected as the sideslip angle β of the center of mass and the yaw rate ω. Then the state - space equation is as follows:

[0148]

[0149] Among them, δ r represents the rear - wheel steering angle.

[0150] The state variable x = [β ω] Τ, the output y = [β ω] Τ , the control variable u = [δ r M Z Τ , δ f The front wheel steering angle is a known quantity and can be used as a system disturbance. The state equation is written as follows:

[0151]

[0152] Among them,

[0153]

[0154] Discretize the above state - space equation and rewrite it in incremental form. Obtain the optimal control sequence ΔU * (k). There are detailed steps in the above text, and only a brief description is given below.

[0155] Set the constraint conditions as follows:

[0156]

[0157] Among them, the subscripts max and min correspond to their maximum and minimum values respectively.

[0158] Take the first item of the optimal control sequence ΔU * (k) to obtain the output of the upper - layer controller, the rear wheel steering angle δ r and the additional yaw moment M Z . Send δ r to the steering system, and make the wheel reach the corresponding steering angle through the rear - wheel steering motor, thereby generating the corresponding additional yaw moment. Send the additional yaw moment M Z to the lower - layer controller as the target of braking force distribution.

[0159] Lower - layer controller

[0160] The tire utilization rate can characterize the stability margin of the tire. It can be selected as the optimization objective. Since the lateral force of the tire is uncontrollable, only the longitudinal force of the tire is considered. Then the objective function is:

[0161]

[0162] When distributing the braking force, the following constraint conditions should be met:

[0163]

[0164] Among them, F x is the total longitudinal force of the vehicle, D is the wheel track, R W is the effective radius of the wheel, T max ​is the maximum braking torque that the brake can generate. is the peak adhesion coefficient, and μ2 is the road adhesion coefficient at high adhesion (assuming the left side is a low-adhesion road surface and the right side is a high-adhesion road surface).

[0165] is the maximum braking force that the ground can generate. Keep the braking force at the low-adhesion side at the maximum value. When the target braking intensity z d is reached, the braking force difference between the left and right sides can be minimized, that is, the yaw moment generated during braking on the split road surface can be minimized. The remaining additional yaw moment is compensated by the yaw moment generated by the rear wheel steering angle.

[0166] Combining the objective function and the constraint conditions, the braking forces required for each wheel can be obtained, and the brake is controlled to generate the target braking force, thereby generating the target additional yaw moment.

[0167] Further, the description of step 7 is expanded as follows:

[0168] When the value of |ω + B1β| rises above B2, direct yaw moment control and active four-wheel steering are adopted to ensure vehicle stability.

[0169] Upper controller

[0170] A two-degree-of-freedom vehicle model is established, and the state variables are selected as the sideslip angle β of the center of mass and the yaw angular velocity ω. Then the state space equation is as follows:

[0171]

[0172] State variable x = [β ω] Τ , output y = [β ω] Τ , control variable u = [δ f δ r M Z Τ , then the state equation:

[0173]

[0174] Among them,

[0175]

[0176] Discretize the above state space equation and rewrite it in incremental form. Obtain the optimal control sequence ΔU * (k). There are detailed steps in the above text, and only a brief description is given below.

[0177] Set the constraint conditions as follows:

[0178] ​

[0179] Among them, the subscripts max and min correspond to their maximum and minimum values respectively.

[0180] Obtain the optimal control sequence ΔU * The first term of (k) can obtain the output of the upper controller, that is, the front wheel steering angle δ f , the rear wheel steering angle δ r and the additional yaw moment M Z . Send δ f , δ r to the steering system controller, and through the steering motor, the wheels reach the corresponding steering angles, thereby generating the corresponding additional yaw moment. Send the additional yaw moment M Z to the lower controller as the target of braking force distribution.

[0181] Lower controller

[0182] The tire utilization rate can characterize the stability margin of the tire. It can be selected as the optimization target. Since the lateral force of the tire is uncontrollable, only the longitudinal force of the tire is considered. Then the objective function is:

[0183]

[0184] When distributing the braking force, the following constraints should be met:

[0185]

[0186] Among them, μ1 is the road adhesion coefficient at the low-adhesion area, and μ2 is the road adhesion coefficient at the high-adhesion area. It is assumed that the left side is the low-adhesion road surface and the right side is the high-adhesion road surface.

[0187] Combining the objective function and the constraint conditions, the braking forces required for each wheel can be obtained, and the brake is controlled to generate the target braking force, thereby generating the target additional yaw moment.

[0188] The above is only the preferred implementation mode of the present invention. The protection scope of the present invention is not limited to the above embodiments. All technical solutions within the idea of the present invention belong to the protection scope of the present invention. It should be noted that for those of ordinary skill in the art, several improvements and refinements made without departing from the principle of the present invention should be regarded as within the protection scope of the present invention.

Claims

1. A method for controlling the lateral stability of a vehicle during braking on a two-way road surface, characterized in that, Including: Collect vehicle data, calculate the difference in average angular deceleration Δα between the two sides based on the vehicle data, and fuse the difference in average angular deceleration Δα between the two sides and the steady-state region of the ω-β phase plane into the comprehensive risk index M for the stability of the split road surface, where ω is the vehicle yaw rate and β is the sideslip angle of the center of mass; Set the threshold M of the comprehensive risk index th , when M ≤ M th , the vehicle brakes normally; when M > M th , enable the control strategy until M ≤ M th and the duration exceeds the set threshold t th ; The control strategy is as follows: the stability is judged through the ω-β phase plane. When |ω + B1β| ≤ B2, compare the maximum braking intensity z that the vehicle can generate on a low-adhesion road surface th and the desired braking intensity z d . If z d ≤ z th , execute Controller 1 to regulate the braking forces at high-adhesion and low-adhesion areas; If z d > z th , execute Controller 2, so that the braking force at the low - adhesion surface remains at the peak value, only regulate the braking force at the high - adhesion surface, and at the same time control the rear - wheel steering angle; when |ω + B1β|> B2, execute Controller 3, so that the active four - wheel steering intervenes and works.

2. A method for controlling the lateral stability of a vehicle during braking on a split road surface as claimed in claim 1, characterized in that: The vehicle data includes vehicle yaw rate, sideslip angle of the center of mass, longitudinal vehicle speed, lateral vehicle speed, angular velocity corresponding to each wheel, steering wheel angle, and brake pedal stroke.

3. The lateral stability control method for a vehicle during braking on an oncoming road surface according to claim 1, characterized in that: The calculation of the difference in average angular deceleration Δα between the two sides based on the vehicle data is specifically as follows: According to the left front wheel angular velocity ω 11 , the right front wheel angular velocity ω 12 , the left rear wheel angular velocity ω 21 and the right rear wheel angular velocity ω 22 , calculate the angular deceleration of each wheel through time difference to obtain the left front wheel angular deceleration α 11 , the right front wheel angular deceleration α 12 , the left rear wheel angular deceleration α 21 and the right rear wheel angular deceleration α 22 ; Calculate the average angular deceleration α on the left side L and the average angular deceleration α on the right side R as follows: Then the difference in average angular deceleration Δα between the two sides is: Δα = α L -α R 。 4. A method for controlling the lateral stability of a vehicle during braking on an oncoming road surface according to claim 3, characterized in that: The comprehensive risk index M for the stability of the split road surface is: Among them, α th is the threshold value of the absolute value of the difference in average angular deceleration on both sides, B = |ω + B1β| is the ω-β phase plane stability evaluation index, and B th is the threshold value of B, λ1 and λ2 are weight coefficients, and λ1 + λ2 = 1.

5. A method for controlling the lateral stability of a vehicle during braking on a split road surface according to claim 1, characterized in that: The maximum braking intensity z that the entire vehicle can generate on a low-adhesion road surface th = μ1, where μ1 is the road surface adhesion coefficient at the low-adhesion location.

6. A lateral stability control method for a vehicle during braking on a split road surface as claimed in claim 1, characterized in that: the desired braking intensity z d is obtained as follows: Brake intention recognition is carried out based on fuzzy control, taking the brake pedal travel and the brake pedal operation speed as the inputs for brake intention recognition, and taking the desired braking intensity z d as the output of brake intention recognition.

7. A method for controlling the lateral stability of a vehicle during braking on a split road surface as claimed in claim 1, characterized in that: The first controller adopts a hierarchical design; the input of the upper-layer controller is the deviation between the vehicle yaw rate ω and the reference yaw rate ω r and the deviation between the sideslip angle β of the center of mass and the reference sideslip angle β r , and the output is the additional yaw moment M Z . The additional yaw moment M Z is sent to the lower-layer controller as the target of braking force distribution; The lower-layer controller takes tire utilization as the optimization goal, and the objective function J is: Among them, μ ij is the road adhesion coefficient corresponding to the wheel, F xij is the longitudinal force received by the wheel, F zij is the vertical force received by the wheel, and the subscripts 11, 12, 21, and 22 represent the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively; When performing braking force distribution, the following constraint conditions are satisfied: Among them, F x is the total longitudinal force of the vehicle, D is the wheel track, R W is the effective radius of the wheel, T max is the maximum braking torque that the brake can generate, μ1 is the road adhesion coefficient at the low-adhesion area, m is the mass of the vehicle above the spring, and g is the acceleration due to gravity; The lower-layer controller combines the objective function and the constraint conditions to obtain the braking force required for each wheel, controls the brake to generate the target braking force, and thus generates the target additional yaw moment.

8. A lateral stability control method for a vehicle during braking on a split road surface as claimed in claim 1, characterized in that: The second controller adopts a hierarchical design; the input of the upper-layer controller is the deviation between the vehicle yaw rate ω and the reference yaw rate ω r and the deviation between the sideslip angle β of the center of mass and the reference sideslip angle β r , and the output is the additional yaw moment M Z and the rear wheel steering angle δ r ; the rear wheel steering angle δ r is sent to the steering system, and the wheel reaches the corresponding steering angle through the rear wheel steering motor, thereby generating the corresponding additional yaw moment; the additional yaw moment M Z is sent to the lower-layer controller as the target of braking force distribution; The lower-layer controller takes tire utilization as the optimization goal, and the objective function J is: Among them, μ ij is the road surface adhesion coefficient corresponding to the wheel, F xij is the longitudinal force received by the wheel, F zij is the vertical force received by the wheel, and the subscripts 11, 12, 21, and 22 represent the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively; When performing braking force distribution, the following constraint conditions are satisfied: Among them, F x is the total longitudinal force of the vehicle, D is the wheel track, R W is the effective radius of the wheel, T max is the maximum braking torque that the brake can generate, is the peak adhesion coefficient, μ2 is the road adhesion coefficient at the high-adhesion area, m is the mass of the vehicle above the springs, g is the acceleration due to gravity, the left side is the low-adhesion road surface, and the right side is the high-adhesion road surface; The lower-layer controller combines the objective function and the constraint conditions to obtain the braking force required for each wheel, controls the brake to generate the target braking force, and thus generates the target additional yaw moment.

9. A method for controlling the lateral stability of a vehicle during braking on a split road surface as claimed in claim 1, characterized in that: The third controller adopts a hierarchical design; the input of the upper-layer controller is the deviation between the vehicle yaw rate ω and the reference yaw rate ω r and the deviation between the sideslip angle β of the center of mass and the reference sideslip angle β r , and the outputs are the front wheel steering angle δ f , the rear wheel steering angle δ r and the additional yaw moment M Z ; the front wheel steering angle δ f and the rear wheel steering angle δ r are sent to the steering system, and the corresponding steering angles of the wheels are achieved through the steering motor, thereby generating the corresponding additional yaw moment; the additional yaw moment M Z is sent to the lower-layer controller as the target of braking force distribution; The lower-layer controller takes tire utilization as the optimization goal, and the objective function J is: where, μ ij is the road surface adhesion coefficient corresponding to the wheel, F xij is the longitudinal force received by the wheel, F zij is the vertical force received by the wheel, and the subscripts 11, 12, 21, and 22 represent the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively; When performing braking force distribution, the following constraint conditions are satisfied: Among them, F x is the total longitudinal force of the vehicle, D is the wheel track, R W is the effective radius of the wheel, T max is the maximum braking torque that the brake can generate, μ1 is the road adhesion coefficient at the low-adhesion area, μ2 is the road adhesion coefficient at the high-adhesion area, m is the mass of the vehicle above the springs, g is the acceleration due to gravity, the left side is the low-adhesion road surface, and the right side is the high-adhesion road surface; The lower-layer controller combines the objective function and the constraint conditions to obtain the braking force required for each wheel, controls the brake to generate the target braking force, and thus generates the target additional yaw moment.

10. A lateral stability control system for a vehicle during braking on a two-way road surface, characterized in that, Including: A vehicle data acquisition unit, a vehicle stability monitoring unit, and a split-road-surface braking lateral stability control unit; The vehicle data acquisition unit acquires vehicle data; The vehicle stability monitoring unit calculates the difference in average angular deceleration Δα between the two sides based on the vehicle data, and fuses the difference in average angular deceleration Δα between the two sides and the steady-state region of the ω-β phase plane into the comprehensive risk index M for the stability of the split road surface, where ω is the vehicle yaw rate and β is the sideslip angle of the center of mass; Set the threshold M of the comprehensive risk index th , when M ≤ M th , the vehicle brakes normally; when M > M th , the crosswise stability control unit of the on-off road surface braking starts the control strategy until M ≤ M th and the duration exceeds the set threshold t th ; The control strategy for starting the split road surface braking lateral stability control unit is as follows: the stability is judged through the ω-β phase plane. When |ω + B1β| ≤ B2, compare the maximum braking intensity z that the whole vehicle can generate on the low adhesion road surface th and the expected braking intensity z d . If z d ≤ z th , execute Controller 1 to regulate the braking forces at high adhesion areas and low adhesion areas; If z d > z th , execute Controller 2 to keep the braking force at the low - adhesion area at its peak, only regulate the braking force at the high - adhesion area, and at the same time control the rear - wheel steering angle; when |ω + B1β| > B2, execute Controller 3 to make the active four - wheel steering intervene and work.

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