Redundant braking method and system based on automatic wheel intelligent traveling chassis

Abstract

The invention provides a redundant braking method and system based on an automatic wheel intelligent traveling chassis, and belongs to the field of vehicle braking. When braking of a single wheel of the vehicle fails, braking force distribution is conducted on the remaining wheels, and when the braking strength is large, the stability of the vehicle is guaranteed through the driving four-wheel steering system. When the wheels on the two different sides fail to brake, the required braking force is averagely distributed, so that the braking force on the two sides is equal, and the stability of the vehicle is ensured. When two or three wheels on the same side fail to brake, the braking force is guaranteed through the remaining wheels, and the stability of the vehicle is guaranteed through the driving four-wheel steering system. When braking of the four wheels all fails, the front wheel toe-in angle and the rear wheel toe-in angle are increased, the side slip angle of a vehicle tire is changed, the lateral force of the tire is increased, the longitudinal force of the vehicle is provided through the lateral force of the wheels, the stability of the vehicle is guaranteed, and the vehicle is braked. The method can effectively cope with different vehicle failure conditions, coordinates braking steering and vehicle stability control, and prevents the vehicle from being out of control.

Description

Technical Field

[0001] The present invention belongs to the field of vehicle braking, and in particular relates to a redundant braking method and system based on an automatic wheel intelligent driving chassis. Background Art

[0002] With the continuous advancement of new energy vehicles, wire-controlled chassis technology, integrating braking, drive, steering, and suspension, is rapidly developing. Distributed drive vehicles based on four-wheel independent steering, drive, and braking offer independent control, thereby improving the fault tolerance of new energy vehicles. Redundant control involves controlling the remaining actuators when one or more actuators fail, rationally allocating their actions to ensure stable driving and enhance safety.

[0003] For distributed drive vehicles, when the brake-by-wire system fails, the existing method involves multi-system coordinated control, using both electromechanical and hydraulic brakes for braking. When the electromechanical brake fails, the electronic control unit detects the brake failure and, through the brake circuit, opens the solenoid valve in the hydraulic brake actuator. This allows the brake fluid in the master cylinder to flow through the hydraulic line under pedal force and into the hydraulic brake actuator for redundant braking. However, this existing method still cannot completely eliminate hydraulic braking, and multi-system coordinated control increases hardware costs.

[0004] Automatic wheel intelligent driving chassis technology integrates wheel hub motors, wire-controlled braking, wire-controlled steering and active suspension technologies into one, and efficiently integrates multiple systems distributed in the car chassis, such as transmission, braking, drive, steering, suspension, etc. into a corner module, which can independently realize steering, braking, drive and other functions. Summary of the Invention

[0005] In view of the deficiencies in the prior art, the present invention provides a redundant braking method and system based on an automatic wheel intelligent driving chassis.

[0006] When the brakes of a single wheel fail, the braking force is first distributed to the remaining wheels to ensure braking force and vehicle stability. When the braking intensity is large, the braking force distribution cannot meet the vehicle stability requirements. Based on the automatic wheel intelligent driving chassis technology, the active four-wheel steering system is used to ensure vehicle stability. When the brakes of two wheels on opposite sides fail, the required braking force is evenly distributed to make the braking force on both sides equal to ensure vehicle stability. When the brakes of two or three wheels on the same side fail completely, the braking force is guaranteed by the remaining wheels, and the vehicle stability is guaranteed by the active four-wheel steering system. When the brakes of all four wheels fail, by increasing the front wheel toe angle and the rear wheel toe angle, the side slip angle of the vehicle tire is changed, the tire lateral force is increased, and the longitudinal force of the vehicle is provided by the lateral force of the wheel to ensure vehicle stability and brake the vehicle.

[0007] To achieve the above object, the present invention adopts the following technical solutions:

[0008] In a first aspect, the present invention provides a redundant braking method based on an automatic wheel intelligent driving chassis, comprising:

[0009] Collect vehicle information and determine whether the wheel brake fails based on the wheel brake pressure;

[0010] If the wheel brakes have not failed, the four wheels will brake normally;

[0011] If the wheel brakes fail, the number and location of the failed wheels are detected, and different redundant control strategies are executed for single-wheel brake failure, double-wheel brake failure, three-wheel brake failure, and four-wheel brake failure.

[0012] Optionally, the different redundant control strategies adopt a seven-degree-of-freedom vehicle dynamics model, including:

[0013] Longitudinal dynamic equation:

[0014]

[0015] Lateral dynamic equations:

[0016]

[0017] Yaw dynamics equation:

[0018]

[0019] Tire rotational dynamics equation:

[0020]

[0021] Where m is the vehicle mass, v x is the longitudinal velocity of the vehicle, v y is the lateral velocity of the car, ω z is the vehicle's yaw rate, F xfl 、F xfr 、F xrl 、F xrr are the longitudinal forces acting on the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively, F yfl 、F yfr 、F yrl 、F yrr are the lateral forces acting on the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively, δ fl , δ fr , δ rl , δ rr They are the left front wheel angle, right front wheel angle, left rear wheel angle, and right rear wheel angle, respectively. zrepresents the moment of inertia of the vehicle around the Z axis, a represents the distance from the center of mass to the front axle, b represents the distance from the center of mass to the rear axle, B is the vehicle wheelbase, J is the moment of inertia of the wheel, ω i is the angular deceleration of the wheel, i=fl, fr, rl, rr represent the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively, R represents the effective radius of the wheel, T μi is the braking torque of the wheel, T ri is the rolling resistance torque of the wheel.

[0022] Optionally, the different redundant control strategies adopt the following magic tire model:

[0023]

[0024] Among them, B y 、C y 、D y 、E y 、B x 、C x 、D x 、E x is the tire parameter, α i is the tire slip angle;

[0025] The vertical load of each tire is as follows:

[0026]

[0027] Among them, F zfl 、F zfr 、F zrl 、F zrr are the vertical loads on the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively; h is the height from the vehicle's center of mass to the ground, L = a + b.

[0028] Optionally, the redundant control strategy executed for single-wheel brake failure is:

[0029] When a single wheel fails to brake, the fuzzy rule is used to distribute the braking force to the remaining three wheels, with the yaw angular velocity ω z and braking intensity z as input variables, and the output variables are the braking force correction coefficients K1, K2, K3 of the remaining three wheels. Define each input variable and output variable, divide the yaw rate into negative large NB, negative small NS, stable Z, positive small PS, positive large PB, divide the braking intensity into low L, medium M, high H, and divide the braking force correction coefficient into large reduction D-, medium reduction D-, reduction D, maintain M, increase I, medium increase I+, and large increase I++;

[0030] The constraints on braking force distribution are as follows:

[0031]

[0032] Where m is the vehicle mass, g is the acceleration due to gravity, and F xi 、F yi 、F zi They represent the longitudinal force, lateral force and vertical load of the wheels respectively. The subscripts i = fl, fr, rl, rr represent the left front wheel, right front wheel, left rear wheel and right rear wheel respectively. μ represents the friction coefficient.

[0033] Optionally, after the braking force is distributed, if the vehicle yaw rate ω z Greater than the maximum value ω max For a certain period of time, the lateral displacement y and the yaw angular velocity ω z As a state variable, an adaptive non-singular terminal sliding mode algorithm is used to control the vehicle's four-wheel steering system to ensure vehicle stability.

[0034] Optionally, the redundant control strategy executed for dual-wheel brake failure is:

[0035] When two wheels fail to brake, first determine the position of the failed wheel, which can be divided into the following two situations:

[0036] 1) When the failed wheels are distributed on both sides, the braking force is distributed to the remaining two wheels using the average distribution method; after the braking force is distributed, if the vehicle yaw angular velocity ω z Greater than the maximum value ω max For a certain period of time, the lateral displacement y and the yaw angular velocity ω z As a state variable, the adaptive non-singular terminal sliding mode algorithm is used to control the vehicle's four-wheel steering system to ensure vehicle stability;

[0037] 2) When the failed wheels are located on the same side, ensure that the braking force of the remaining two wheels meets the total braking force requirement, using the lateral displacement y and the yaw angular velocity ω z As a state variable, an adaptive non-singular terminal sliding mode algorithm is used to control the vehicle's four-wheel steering system to ensure vehicle stability.

[0038] Optionally, the redundant control strategy executed for three-wheel brake failure is:

[0039] When the brakes of three wheels fail, the braking is fully borne by the remaining wheel; the lateral displacement y and the yaw angular velocity ω z As a state variable, the vehicle's four-wheel steering is controlled by an adaptive non-singular fast terminal sliding mode algorithm to ensure vehicle stability.

[0040] Optionally, the redundant control strategy executed for four-wheel brake failure is:

[0041] When all four vehicle brakes fail, the wheel toe angle is increased to rotate the four wheels toward the vehicle centerline, increasing the wheel lateral force, and providing the longitudinal force of the entire vehicle through the wheel lateral force; when braking by increasing the wheel toe angle, the objective function is to maximize the longitudinal deceleration, and the constraints are:

[0042]

[0043] Among them, a x is the longitudinal deceleration, a y is the lateral acceleration, m is the vehicle mass, F yi and F zi Denote the lateral force and vertical load of the wheel, δ i is the wheel angle, α i and α th,i are the tire slip angles and their thresholds, i = fl, fr, rl, rr represent the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively; μ represents the friction coefficient, β and β max Respectively represent the center of mass sideslip angle and its maximum value, ω z and ω max represent the yaw angular velocity and its maximum value respectively.

[0044] Optionally, a particle swarm optimization algorithm is used to find the optimal turning angles of the four wheels under the objective function and constraints, specifically:

[0045] The particle swarm is composed of four wheel corners, which are used as feasible solutions for the multi-objective particle swarm optimization algorithm. The yaw penalty term and the corner out-of-bounds penalty are introduced, and the fitness function f is set as:

[0046]

[0047] in, is the braking distance, v x is the longitudinal speed of the car, a x is the longitudinal deceleration, δ i and δ max are the wheel angles and their maximum values, respectively, λ1, λ2, λ3 are weight coefficients;

[0048] When the number of iterations reaches the set number or the fitness value is less than the set threshold, the iteration is terminated, thereby obtaining the optimal turning angles of the four wheels.

[0049] In a second aspect, the present invention provides a redundant braking system based on an automatic wheel intelligent driving chassis, comprising:

[0050] Braking control module, used to control normal braking of four wheels;

[0051] Brake failure detection module, used to determine whether the wheel brakes have failed based on the wheel brake pressure, and detect the number and location of failed wheels;

[0052] Braking redundancy switching module, used to switch to redundant control strategies when different wheel brakes fail, including single wheel brake failure, double wheel brake failure, three wheel brake failure and four wheel brake failure;

[0053] Braking redundancy module, used to execute different redundant control strategies when different wheel brakes fail;

[0054] Dynamic coordination control module, used to coordinate braking and steering with vehicle stability control.

[0055] The beneficial effects of the present invention are:

[0056] (1) The present invention addresses the problem of single-wheel brake failure by allocating the remaining wheel braking force based on fuzzy rules to ensure braking strength. When the brakes of two wheels on opposite sides fail, the present invention distributes the braking force according to an average distribution method to ensure vehicle stability and reduce vehicle side deviation.

[0057] (2) The present invention addresses the problem of vehicle lateral deviation caused by imbalanced braking forces on both sides when a single wheel fails in high-intensity braking, two wheels fail on the same side, or three wheels fail. The present invention uses lateral displacement and yaw angular velocity as state quantities. At the same time, in order to avoid singular problems, an adaptive non-singular terminal sliding mode control algorithm is designed. By controlling the vehicle's four-wheel steering system, the vehicle's lateral deviation is reduced and vehicle stability is ensured.

[0058] (3) The present invention addresses the problem of four-wheel brake failure by increasing the wheel toe angle, causing the front and rear wheels to rotate inward, changing the wheel slip angle, and increasing the wheel lateral force. The wheel lateral force provides the entire vehicle with longitudinal force, thereby slowing the vehicle down. Based on the particle swarm optimization algorithm, the optimal solution for each wheel angle is found, and the maximum longitudinal deceleration is provided while ensuring vehicle stability, so that the vehicle can be stopped quickly. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 The flowchart of a redundant braking method based on an automatic wheel intelligent driving chassis.

[0060] Figure 2 A flowchart of a redundant braking system based on an automatic wheel intelligent driving chassis

[0061] Figure 3 It is the trapezoidal membership function diagram of braking intensity.

[0062] Figure 4 It is the triangle membership function diagram of yaw rate. DETAILED DESCRIPTION

[0063] The present invention will now be described in further detail with reference to the accompanying drawings.

[0064] Example 1

[0065] This embodiment proposes a redundant braking method based on an automatic wheel intelligent driving chassis. Before execution, a seven-degree-of-freedom vehicle dynamics model is first established.

[0066] Longitudinal dynamic equation:

[0067]

[0068] Lateral dynamic equations:

[0069]

[0070] Yaw dynamics equation:

[0071]

[0072] Tire rotational dynamics equation:

[0073]

[0074] Where m is the vehicle mass, v x is the longitudinal velocity of the vehicle, v y is the lateral velocity of the car, ω z is the vehicle's yaw rate, F xfl 、F xfr 、F xrl 、F xrr are the longitudinal forces acting on the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively, F yfl 、F yfr 、F yrl 、F yrr are the lateral forces acting on the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively. fl , δ fr , δ rl , δ rr They are the left front wheel angle, right front wheel angle, left rear wheel angle, and right rear wheel angle, respectively. z represents the moment of inertia of the vehicle around the Z axis, a represents the distance from the center of mass to the front axle, b represents the distance from the center of mass to the rear axle, B is the vehicle wheelbase, J is the moment of inertia of the wheel, ω i is the angular deceleration of the wheel, i=fl,fr,rl,rr, R is the effective radius of the wheel, T μi is the braking torque of the wheel, T ri is the rolling resistance torque of the wheel.

[0075] The magic tire model used is:

[0076] F yi =D y sin{C y arctan[B y α i -E y (B y α i -arctan(B y α i ))]}

[0077] F xi =D x sin{C x arctan[B x α i -E x (B x α i -arctan(B x α i ))]}

[0078] Among them, B y 、C y 、D y 、E y 、B x 、C x 、D x 、E x is the tire parameter, α i is the tire slip angle.

[0079] The vertical load of the tire will change during the braking process of the car. The vertical load of each wheel is as follows:

[0080]

[0081] Among them, F z is the vertical load on the tire, h is the height from the vehicle's center of mass to the ground, and L = a + b.

[0082] The vehicle's sideslip angle is calculated as follows:

[0083] Left front wheel slip angle:

[0084]

[0085] Right front wheel slip angle:

[0086]

[0087] Left rear wheel slip angle:

[0088]

[0089] Right rear wheel slip angle:

[0090]

[0091] like Figure 1 As shown, the redundant braking method based on the automatic wheel intelligent driving chassis proposed in this embodiment takes into account the braking distribution and vehicle stability when the brakes of different numbers of wheels fail. The specific steps are as follows:

[0092] S1: When a single wheel fails, the braking force of the remaining wheels is distributed, and the braking force of the remaining three wheels is used to compensate for the braking force of the failed wheel. In order to ensure braking performance and stability, stability fault-tolerant control of brake failure is achieved through four-wheel steering.

[0093] The braking force is distributed using fuzzy rules, with the yaw angular velocity ω z and braking intensity z as input variables. Yaw angular velocity ω z is the difference between the actual and expected yaw rate, and the braking intensity z is the deceleration intensity required by the driver. The output variables are the braking force correction coefficients K1, K2, and K3 for the remaining three wheels. Define each input and output variable and divide the variables into different fuzzy sets. The yaw rate is divided into negative large NB, negative small NS, stable Z, positive small PS, and positive large PB. The braking intensity z is divided into low L, medium M, and high H. The braking force correction coefficient is divided into a large reduction D-, a medium reduction D-, a reduction D, a maintenance M, an increase I, a medium increase I+, and a large increase I++. When the vehicle brakes, when the left wheel fails, the left longitudinal force is reduced due to the reduction in the braking force of the left wheel; when the right wheel fails, the braking force of the right wheel is reduced, and the right longitudinal force is reduced. When a single wheel brake fails, priority is given to ensuring vehicle stability, while ensuring that the longitudinal braking force of the entire vehicle reaches the expected target, and that the single wheel braking force does not exceed the friction ellipse limit. Therefore, the constraints are as follows:

[0094]

[0095] This embodiment utilizes fuzzy rules based on a predefined fuzzy rule base to determine braking force distribution under different braking intensities. Because the sideslip angle cannot be directly measured, yaw rate and braking intensity are used for determination. A specific fuzzy rule base example is provided, using the right rear wheel brake failure as an example. The fuzzy rule table is shown in Table 1.

[0096] Table 1 Fuzzy rules table

[0097]

[0098]

[0099] The braking intensity adopts a trapezoidal function, such as Figure 3As shown in the figure, the low braking intensity range is [0, 0.4], the medium braking intensity range is [0.3, 0.7], and the high braking intensity range is [0.6, 1]. The key points of low braking intensity are [0, 0.2, 0.3, 0.4], the key points of medium braking intensity are [0.3, 0.5, 0.6, 0.7], and the key points of high braking intensity are [0.6, 0.8, 1.0, 1.2].

[0100] The yaw rate is calculated using trigonometric functions, such as Figure 4 As shown. The negative large NB range is ω z ≤-15° / s, negative small NS range is -20° / s<ω z ≤0° / s, stable Z range is -5° / s<ω z <+5° / s, the positive minimum PS range is 0° / s≤ω z <+20° / s, the positive PB range is +15° / s≤ω z .

[0101] The activation weight is equal to the product of the precondition membership, and the formula is as follows:

[0102] Weight = μ z μ ω

[0103] Among them, μ z is the braking intensity membership under the premise, μ ω is the yaw rate membership under the premise.

[0104] Based on the activation weights, the remaining wheel braking force distribution coefficients are calculated.

[0105] During high-intensity braking, in order to ensure the braking strength, the braking force on both sides is large. Simply adjusting the braking force distribution cannot fully guarantee the vehicle stability. Therefore, when the vehicle yaw angular velocity is detected to be greater than the maximum value allowed by the regulations, max After a certain period of time, the vehicle's active four-wheel steering system intervenes to adjust vehicle stability.

[0106] When the tire slip angle is small, the lateral force and the wheel slip angle are linearly related, that is, F yi =k i α i Since the sideslip angle of the center of mass cannot be measured directly, the lateral displacement y and yaw angular velocity ω are used z As the state quantity, the front and rear wheel angles are input, and the coaxial wheel angles are equal, the state space equation is as follows:

[0107]

[0108] The rear wheel turning angle is proportional to the front wheel turning angle, which is δ r=k δ δ f Among them, the proportional coefficient k δ Varies with speed.

[0109] For the convenience of calculation, the state equation is simplified as:

[0110]

[0111] in,

[0112] To avoid the singularity problem, this embodiment uses a non-singular terminal sliding mode algorithm to calculate the front wheel angle and the rear wheel angle, and let e ω =ψ-ψ d , e y =yy d , e=e ω +ξe y , the designed improved non-singular terminal sliding mode is:

[0113]

[0114] Where ψ is the yaw angle, ψ d For an ideal yaw angle, γ1>0, γ2>0, p and q must satisfy the conditions 1<q<2, p>q, and ξ is the trade-off coefficient.

[0115] e represents the system tracking error, which is expressed as:

[0116]

[0117] Where D(t) is a bounded perturbation.

[0118] Taking the derivative of s, we get:

[0119]

[0120] The equivalent control objective is Thus, the equivalent control δ can be obtained feq :

[0121]

[0122] Switching control δ fsw for:

[0123]

[0124] Where η>0 is the switching gain, are the estimated values of a0, a1, and a2, and sgn(s) is the sign function.

[0125] The parameters are updated by the following adaptation rates:

[0126]

[0127] Among them, κ0, κ1, κ2 are any positive numbers.

[0128] Combined, we can get the active steering control front wheel angle δ f for:

[0129]

[0130] To avoid chattering, use the saturation function sat Instead of the sign function, the saturation function is:

[0131]

[0132] Where s is the sliding surface and Δ is the boundary layer thickness.

[0133] Therefore, the front wheel turning angle δ f for:

[0134]

[0135] The rear wheel turning angle is:

[0136]

[0137] For stability analysis, the Lyapunov function is selected as:

[0138]

[0139] The time derivative of V is:

[0140]

[0141] Bring in have to:

[0142]

[0143] Simplified:

[0144]

[0145] From this, we can see that the system is asymptotically stable at the sliding surface s=0.

[0146] S2: When the brakes of two wheels fail completely, it is divided into single-side wheel brake failure, double front wheel brake failure, double rear wheel brake failure, and single front wheel and single rear wheel brake failure.

[0147] 1) Double front wheel brake failure, double rear wheel brake failure, single front wheel and single rear wheel brake failure

[0148] In the event of dual wheel failure, when one wheel on each of the left and right sides is detected to have failed, this embodiment distributes the braking coefficients evenly to the remaining wheels on both sides by an average distribution method, thereby ensuring both braking force and vehicle stability.

[0149] First, calculate the total required braking force F according to the brake pedal travel total , when one wheel on each side fails, the total required braking force is borne by the remaining two wheels, that is:

[0150]

[0151] The average braking force per wheel is:

[0152] F remaining =0.5F total

[0153] Since the vertical load on each tire is different, the maximum longitudinal force on each tire is F ximax =μF zi Therefore, each wheel has a different maximum longitudinal force. When the average braking force exceeds the maximum longitudinal force of one wheel, the braking force difference between the two sides will cause the vehicle to swerve. To address this swerve, active four-wheel steering is still used to ensure vehicle stability during braking.

[0154] The active four-wheel steering system is controlled by the vehicle's yaw rate to determine whether it intervenes. When the vehicle's yaw rate is detected to be greater than the maximum value allowed by the regulations, the system max After a certain period of time, the vehicle's active four-wheel steering system intervenes to adjust vehicle stability.

[0155] Let e ω =ψ-ψ d , e y =yy d , e=e ω +ξe y , the designed improved non-singular terminal sliding mode is:

[0156]

[0157] Where ψ is the yaw angle, ψ d For an ideal yaw angle, γ1>0, γ2>0, p and q must satisfy the conditions 1<q<2, p>q, and ξ is the trade-off coefficient.

[0158] e represents the system tracking error, which is expressed as:

[0159]

[0160] Where D(t) is a bounded perturbation.

[0161] Taking the derivative of s, we get:

[0162]

[0163] The equivalent control objective is , thus, we can get the equivalent control δ feq for:

[0164]

[0165] Switching control δ fsw for:

[0166]

[0167] Where η>0 is the switching gain, are the estimated values of a0, a1, and a2, and sgn(s) is the sign function.

[0168] The parameters are updated by the following adaptation rates:

[0169]

[0170] Among them, κ0, κ1, κ2 are any positive numbers.

[0171] Combined, we can get the active steering control front wheel angle δ f for:

[0172]

[0173] To avoid chattering, use the saturation function Instead of the sign function, the saturation function is:

[0174]

[0175] Where s is the sliding surface and Δ is the boundary layer thickness.

[0176] Therefore, the front wheel turning angle δ f for:

[0177]

[0178] The rear wheel turning angle is:

[0179]

[0180] For stability analysis, the Lyapunov function is selected as:

[0181]

[0182] The time derivative of V is:

[0183]

[0184] Bring in have to:

[0185]

[0186] Simplified:

[0187]

[0188] From this, we can see that the system is asymptotically stable at the sliding surface s=0.

[0189] 2) Unilateral wheel brake failure

[0190] When one wheel fails, the vehicle stability is guaranteed while the braking force is guaranteed. The total required braking force F is calculated based on the brake pedal travel. total , the total required braking force is borne by the remaining two wheels, that is:

[0191]

[0192] The braking force of each wheel is proportional to the longitudinal force. For example, when the left braking force fails, the braking force of each wheel on the right is:

[0193]

[0194] Since only one side of the wheel has braking force, the vehicle will deviate to the side. The active four-wheel steering system adjusts the front and rear wheel angles to control the vehicle's stability.

[0195] The simplified state equation is:

[0196]

[0197] Let e ω =ψ-ψ d , e y =yy d , e=e ω +ξe y , the designed improved non-singular terminal sliding mode is:

[0198]

[0199] Where ψ is the yaw angle, ψ d For an ideal yaw angle, γ1>0, γ2>0, p and q must satisfy the conditions 1<q<2, p>q, and ξ is the trade-off coefficient.

[0200] e represents the system tracking error, which is expressed as:

[0201]

[0202] Where D(t) is a bounded perturbation.

[0203] Taking the derivative of s, we get:

[0204]

[0205] The equivalent control objective is Thus, the equivalent control δ can be obtained feq for:

[0206]

[0207] Switching control δ fsw for:

[0208]

[0209] Where η>0 is the switching gain, are the estimated values of a0, a1, and a2, and sgn(s) is the sign function. The parameters are updated by the following adaptive rate:

[0210]

[0211] Among them, κ0, κ1, κ2 are any positive numbers.

[0212] Combined, we can get the active steering control front wheel angle δ f for:

[0213]

[0214] To avoid chattering, use the saturation function Instead of the sign function, the saturation function is:

[0215]

[0216] Where s is the sliding surface and Δ is the boundary layer thickness.

[0217] Therefore, the front wheel turning angle δ f for:

[0218]

[0219] The rear wheel turning angle is:

[0220]

[0221] For stability analysis, the Lyapunov function is selected as:

[0222]

[0223] The time derivative of V is:

[0224]

[0225] Bring in have to:

[0226]

[0227] Simplified:

[0228]

[0229] From this, we can see that the system is asymptotically stable at the sliding surface s=0.

[0230] S3: When the brakes on three wheels fail, the vehicle's braking force is completely provided by the remaining wheels. Therefore, due to the uneven distribution of braking force on both sides, the vehicle will yaw excessively. To ensure vehicle stability while maintaining braking performance, this embodiment uses an adaptive non-singular fast terminal sliding mode algorithm to calculate the front and rear wheel adjustment angles.

[0231] The simplified state equation is:

[0232]

[0233] Let e ω =ψ-ψ d , e y =yy d , e=e ω +ξe y , the designed improved non-singular terminal sliding mode is:

[0234]

[0235] Where ψ is the yaw angle, ψ d For an ideal yaw angle, γ1>0, γ2>0, p and q must satisfy the conditions 1<q<2, p>q, and ξ is the trade-off coefficient.

[0236] e represents the system tracking error, which is expressed as:

[0237]

[0238] Where D(t) is a bounded perturbation.

[0239] Taking the derivative of s, we get:

[0240]

[0241] The equivalent control objective is , thus, we can get the equivalent control δ feq :

[0242]

[0243] Switching control δ fsw for:

[0244]

[0245] Where η>0 is the switching gain, are the estimated values of a0, a1, and a2, and sgn(s) is the sign function.

[0246] The parameters are updated by the following adaptation rates:

[0247]

[0248] Among them, κ0, κ1, κ2 are any positive numbers.

[0249] Combined, we can get the active steering control front wheel angle δ f for:

[0250]

[0251] To avoid chattering, use the saturation function Instead of the sign function, the saturation function is:

[0252]

[0253] Where s is the sliding surface and Δ is the boundary layer thickness.

[0254] Therefore, the front wheel turning angle δ f for:

[0255]

[0256] The rear wheel turning angle is:

[0257]

[0258] For stability analysis, the Lyapunov function is selected as:

[0259]

[0260] The time derivative of V is:

[0261]

[0262] Bring in have to:

[0263]

[0264] Simplified:

[0265]

[0266] From this, we can see that the system is asymptotically stable at the sliding surface s=0.

[0267] S4: When all four wheels fail, the automatic wheel intelligent driving chassis technology allows each wheel to rotate independently. This allows the wheel toe angle to be increased, providing lateral force to the vehicle's longitudinal force, thereby achieving braking deceleration. If the tire force limit is not reached, the wheel toe angle is increased to maximize the vehicle's longitudinal force while maintaining vehicle stability.

[0268] When the brakes fail completely, combined with the tire side slip characteristics, the vehicle motion equation is:

[0269]

[0270] Among them, a x is the longitudinal deceleration, a y is the lateral acceleration, ω is the yaw rate, and the lateral force is obtained using the magic tire formula.

[0271] When braking by increasing the wheel toe angle, there are some constraints, the side slip angle does not exceed the side slip angle threshold α corresponding to the lateral force peak. th The tire adhesion limit is less than the maximum friction force, and the yaw rate and the center of mass side slip angle do not exceed the maximum limit allowed. The objective function is to minimize the braking distance, and the constraints are:

[0272]

[0273] Among them, the sideslip angle threshold α th Equal to the magic tire formula The value of the sideslip angle when .

[0274] This embodiment uses a particle swarm algorithm to search for the optimal solution. The specific steps of the particle swarm algorithm are as follows:

[0275] In a d-dimensional search space, there are n particles forming a population x=(x1,x2,…,x n ), the i-th particle is represented as a d-dimensional vector:

[0276] x i =(x i1 ,x i2 ,…,x id )i=1,2,…,n

[0277] The velocity of the i-th particle is:

[0278] v i =(v i1 ,v i2 ,…,v id )i=1,2,…,n

[0279] Combining the objective function and the penalty function, we get the fitness function f. The smaller the function value, the higher the fitness. The fitness value of the optimal position found by the i-th particle is p i , the fitness value of the optimal position searched by the group is p g .

[0280] The optimal position searched by the i-th particle is the individual extreme value, and the individual optimal solution is:

[0281] p i =(p i1 ,p i2 ,…,p id )

[0282] The optimal position searched by the entire particle swarm is the group extreme value, and the group optimal solution is:

[0283] p g =(p g1 ,p g2 ,…,p gd )

[0284] Update the particle swarm speed and position. According to the particle swarm algorithm formula, update the speed and position of each particle so that the particle moves toward the optimal solution. The updated particle swarm speed and position are as follows:

[0285]

[0286] Among them, v id is the particle velocity, ω is the inertia weight, c1, c2 are learning factors, r1, r2 are random numbers in [0, 1], p i is the individual optimal solution, p g is the optimal solution for the group, x i is the position of the particle, and t is the current iteration number.

[0287] The particle population is composed of four wheel corners, and the particle population is x i =(α1,α2,α3,α4), the four wheel angles are used as feasible solutions for the multi-objective particle swarm algorithm. Initial settings include the number of particles N, the number of iterations T, the self- and group learning factors c1, c2, the inertia weight ω, and the boundary α th wait.

[0288] To ensure vehicle stability, a yaw penalty term is introduced. To ensure that the vehicle corner is within the safety boundary, a corner out-of-bounds penalty is introduced. Combining the objective function and the penalty function term, we get the appropriate function:

[0289]

[0290] in, is the braking distance, λ1, λ2, λ3 are weight coefficients.

[0291] When the number of iterations reaches the set number of iterations or the fitness value is less than the specified threshold, the iteration is terminated, thereby obtaining the optimal steering angles of the four wheels.

[0292] Based on the above, this embodiment designs a redundant braking method for the vehicle in the event of single-wheel, double-wheel, three-wheel and four-wheel brake failure for the automatic wheel intelligent driving chassis, so as to solve the problem of vehicle lateral deviation and impact on braking performance when brakes on different wheels fail.

[0293] Example 2

[0294] This embodiment proposes a redundant braking system based on an automatic wheel intelligent driving chassis, which is used to implement the redundant braking method of embodiment 1. The system includes a braking control module, a braking failure detection module, a braking redundancy switching module, a braking redundancy module, and a dynamic coordination control module. The braking control module is the main braking system control unit, controlling normal braking; the braking failure detection module is responsible for detecting the number and location of wheel failures; the braking redundancy switching module is responsible for seamlessly switching to redundant braking control when different wheels fail; the braking redundancy module is responsible for implementing different redundant control strategies when different wheels fail; and the dynamic coordination control module is responsible for coordinating braking steering and vehicle stability control to prevent vehicle loss of control.

[0295] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions based on the principles of the present invention are within the scope of protection of the present invention. It should be noted that for those skilled in the art, various improvements and modifications that do not depart from the principles of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A redundant braking method based on an automatic wheel intelligent driving chassis, characterized in that: include: Collect vehicle information and determine whether the wheel brake has failed based on the wheel brake pressure; If the wheel brakes have not failed, the four wheels will brake normally; If the wheel brakes fail, the number and location of the failed wheels are detected, and different redundant control strategies are executed for single-wheel brake failure, double-wheel brake failure, three-wheel brake failure, and four-wheel brake failure.

2. The redundant braking method based on the automatic wheel intelligent driving chassis according to claim 1, characterized in that: The different redundant control strategies employ a seven-degree-of-freedom vehicle dynamics model, including: Longitudinal dynamic equation: Lateral dynamic equations: Yaw dynamics equation: Tire rotational dynamics equation: Where m is the vehicle mass, v x is the longitudinal velocity of the car, v y is the lateral velocity of the car, ω z is the vehicle's yaw rate, F xfl 、F xfr 、F xrl 、F xrr are the longitudinal forces acting on the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively, F yfl 、F yfr 、F yrl 、F yrr are the lateral forces acting on the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively, δ fl , δ fr , δ rl , δ rr They are the left front wheel angle, right front wheel angle, left rear wheel angle, and right rear wheel angle, respectively. z represents the moment of inertia of the vehicle around the Z axis, a represents the distance from the center of mass to the front axle, b represents the distance from the center of mass to the rear axle, B is the vehicle wheelbase, J is the moment of inertia of the wheel, ω i is the angular deceleration of the wheel, i=fl, fr, rl, rr represent the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively, R represents the effective radius of the wheel, T μi is the braking torque of the wheel, T ri is the rolling resistance torque of the wheel.

3. The redundant braking method based on the automatic wheel intelligent driving chassis according to claim 2, characterized in that: The different redundant control strategies adopt the following magic tire model: Among them, B y 、C y 、D y 、E y 、B x 、C x 、D x 、E x is the tire parameter, α i is the tire slip angle; The vertical load of each tire is as follows: Among them, F zfl 、F zfr 、F zrl 、F zrr are the vertical loads on the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively; h is the height from the vehicle's center of mass to the ground, L = a + b.

4. The redundant braking method based on the automatic wheel intelligent driving chassis according to claim 1, characterized in that: The redundant control strategy for single wheel brake failure is: When a single wheel fails to brake, the fuzzy rule is used to distribute the braking force to the remaining three wheels, with the yaw angular velocity ω z and braking intensity z as input variables, and the output variables are the braking force correction coefficients K1, K2, K3 of the remaining three wheels. Define each input variable and output variable, divide the yaw rate into negative large NB, negative small NS, stable Z, positive small PS, positive large PB, divide the braking intensity into low L, medium M, high H, and divide the braking force correction coefficient into large reduction D-, medium reduction D-, reduction D, maintain M, increase I, medium increase I+, and large increase I++; The constraints on braking force distribution are as follows: Where m is the vehicle mass, g is the acceleration due to gravity, and F xi 、F yi 、F zi They represent the longitudinal force, lateral force and vertical load of the wheels respectively. The subscripts i = fl, fr, rl, rr represent the left front wheel, right front wheel, left rear wheel and right rear wheel respectively. μ represents the friction coefficient.

5. The redundant braking method based on the automatic wheel intelligent driving chassis according to claim 4, characterized in that: After the braking force is distributed, if the vehicle yaw rate ω z Greater than the maximum value ω max For a certain period of time, the lateral displacement y and the yaw angular velocity ω z As the state variable, the adaptive non-singular terminal sliding mode algorithm is used to control the vehicle four-wheel steering system.

6. The redundant braking method based on the automatic wheel intelligent driving chassis according to claim 1, characterized in that: The redundant control strategy for dual-wheel brake failure is: When two wheels fail to brake, first determine the position of the failed wheel, which can be divided into the following two situations: 1) When the failed wheels are distributed on both sides, the braking force is distributed to the remaining two wheels using the average distribution method; after the braking force is distributed, if the vehicle yaw angular velocity ω z Greater than the maximum value ω max For a certain period of time, the lateral displacement y and the yaw angular velocity ω z As a state variable, the vehicle's four-wheel steering system is controlled using an adaptive non-singular terminal sliding mode algorithm; 2) When the failed wheels are located on the same side, ensure that the braking force of the remaining two wheels meets the total braking force requirement, using the lateral displacement y and the yaw angular velocity ω z As the state variable, the adaptive non-singular terminal sliding mode algorithm is used to control the vehicle four-wheel steering system.

7. The redundant braking method based on the automatic wheel intelligent driving chassis according to claim 1, characterized in that: The redundant control strategy for three-wheel brake failure is: When the brakes of three wheels fail, the braking is fully borne by the remaining wheel; the lateral displacement y and the yaw angular velocity ω z As a state variable, the vehicle four-wheel steering system is controlled by an adaptive non-singular fast terminal sliding mode algorithm.

8. The redundant braking method based on the automatic wheel intelligent driving chassis according to claim 1, characterized in that: The redundant control strategy for four-wheel brake failure is: When all four vehicle brakes fail, the wheel toe angle is increased to rotate the four wheels toward the vehicle centerline, increasing the wheel lateral force, and providing the longitudinal force of the entire vehicle through the wheel lateral force; when braking by increasing the wheel toe angle, the objective function is to maximize the longitudinal deceleration, and the constraints are: Among them, a x is the longitudinal deceleration, a y is the lateral acceleration, m is the vehicle mass, F yi and F zi Denote the lateral force and vertical load of the wheel, δ i is the wheel angle, α i and α th,i are the tire slip angles and their thresholds, i = fl, fr, rl, rr represent the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively; μ represents the friction coefficient, β and β max Respectively represent the center of mass sideslip angle and its maximum value, ω z and ω max represent the yaw angular velocity and its maximum value respectively.

9. The redundant braking method based on the automatic wheel intelligent driving chassis according to claim 8, characterized in that: Under the objective function and constraints, the particle swarm optimization algorithm is used to find the optimal turning angles of the four wheels, specifically: The particle swarm is composed of four wheel corners, which are used as feasible solutions for the multi-objective particle swarm optimization algorithm. The yaw penalty term and the corner out-of-bounds penalty are introduced, and the fitness function f is set as: in, is the braking distance, v x is the longitudinal speed of the car, a x is the longitudinal deceleration, δ i and δ max are the wheel angles and their maximum values, respectively, λ1, λ2, λ3 are weight coefficients; When the number of iterations reaches the set number or the fitness value is less than the set threshold, the iteration is terminated, thereby obtaining the optimal turning angles of the four wheels.

10. A redundant braking system based on an automatic wheel intelligent driving chassis, characterized in that: include: Braking control module, used to control normal braking of four wheels; Brake failure detection module, used to determine whether the wheel brakes have failed based on the wheel brake pressure, and detect the number and location of failed wheels; Braking redundancy switching module, used to switch to redundant control strategies when different wheel brakes fail, including single wheel brake failure, double wheel brake failure, three wheel brake failure and four wheel brake failure; Braking redundancy module, used to execute different redundant control strategies when different wheel brakes fail; Dynamic coordination control module, used to coordinate braking and steering with vehicle stability control.

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