A redundancy braking method and system based on automatic wheel intelligent chassis

Abstract

The application provides a redundancy braking method and system based on an automatic wheel intelligence chassis, and belongs to the field of vehicle braking. When single wheel braking of a vehicle fails, braking force distribution is performed on the remaining wheels. When the braking intensity is large, the active four-wheel steering system is used to ensure the stability of the vehicle. When braking of two wheels on different sides fails, the required braking force is evenly distributed to make the braking force on both sides equal, thereby ensuring the stability of the vehicle. When braking of two or three wheels on the same side fails, the remaining wheels are used to ensure the braking force, and the active four-wheel steering system is used to ensure the stability of the vehicle. When braking of all four wheels fails, the toe-in angle of the front wheels and the toe-in angle of the rear wheels are increased, the tire side slip angle of the vehicle is changed, the tire lateral force is increased, the longitudinal force of the vehicle is provided by the wheel lateral force, the stability of the vehicle is ensured, and the vehicle is braked. The application can effectively deal with different vehicle failure conditions, coordinate braking, steering and vehicle stability control, and prevent the vehicle from losing control.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of vehicle braking, and particularly relates to a redundancy braking method and system based on an automatic wheel intelligent chassis. BACKGROUND

[0002] With the continuous progress of new energy vehicles, the drive-by-wire chassis technology integrating braking, driving, steering and suspension is rapidly developing. The distributed drive vehicle based on four-wheel independent steering, independent driving and independent braking has the characteristics of independent controllability, thereby improving the fault tolerance of new energy vehicles. Redundancy control is to control the remaining actuators when one or more actuators of the vehicle fail, to reasonably distribute the execution actions of the actuators, to ensure the stable driving of the vehicle, and to improve the safety of the vehicle.

[0003] For the distributed drive vehicle, when the drive-by-wire braking fails, the existing method is to use the electronic mechanical braking and hydraulic braking for braking through the multi-system collaborative control. When the electronic mechanical braking fails, the electronic control unit observes the braking failure, opens the electromagnetic valve in the hydraulic braking actuator through the brake line, and makes the brake fluid in the brake master cylinder enter the hydraulic brake actuator under the action of the pedal force to perform redundancy braking. The existing method still cannot completely get rid of the hydraulic braking, and the multi-system collaborative control increases the hardware cost.

[0004] The automatic wheel intelligent chassis technology integrates the hub motor, drive-by-wire braking, drive-by-wire steering and active suspension technology into one, and efficiently integrates the transmission, braking, driving, steering and suspension systems distributed in the chassis of the vehicle into an angle module, which can independently realize the functions of steering, braking and driving. SUMMARY

[0005] The application provides a redundancy braking method and system based on an automatic wheel intelligent chassis.

[0006] When a single wheel braking fails, the braking force is first distributed to the remaining wheels to ensure the braking force and the stability of the vehicle. When the braking intensity is large, the braking force distribution cannot meet the stability of the vehicle. Based on the automatic wheel intelligent chassis technology, the active four-wheel steering system is used to ensure the stability of the vehicle. When two opposite wheels fail, the required braking force is evenly distributed to ensure the stability of the vehicle. When two or three wheels on the same side fail, the braking force is ensured by the remaining wheels, and the active four-wheel steering system is used to ensure the stability of the vehicle. When all four wheels fail, the front wheel toe angle and the rear wheel toe angle are increased to change the tire side slip angle, increase the tire lateral force, rely on the wheel lateral force to provide the longitudinal force of the vehicle, ensure the stability of the vehicle and brake the vehicle.

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

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

[0009] Collecting vehicle information, and determining whether the wheel braking pressure is invalid;

[0010] If the wheel braking is not invalid, then four-wheel normal braking is performed;

[0011] If the wheel braking is invalid, then the number and position of the invalid wheel are detected, and different redundancy control strategies are performed for single-wheel braking invalidity, double-wheel braking invalidity, three-wheel braking invalidity and four-wheel braking invalidity.

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

[0013] A longitudinal dynamics equation:

[0014]

[0015] A lateral dynamics equation:

[0016]

[0017] A yaw dynamics equation:

[0018]

[0019] A tire rotation dynamics equation:

[0020]

[0021] Wherein, m is the vehicle mass, v x is the longitudinal speed of the vehicle, v y is the lateral speed of the vehicle, ω z is the yaw angular speed of the vehicle, F xfl , F xfr , F xrl , F xrr are the longitudinal forces received by the left front wheel, the right front wheel, the left rear wheel and the right rear wheel, respectively, F yfl , F yfr , F yrl , F yrr are the lateral forces received by the left front wheel, the right front wheel, the left rear wheel and the right rear wheel, respectively, δ fl , δ fr , δ rl , δ rr are the left front wheel angle, the right front wheel angle, the left rear wheel angle and the right rear wheel angle, respectively, and I zLet ω represent the vehicle's moment of inertia about the Z-axis, 'a' represent the distance from the center of mass to the front axle, 'b' represent the distance from the center of mass to the rear axle, 'B' be the vehicle's track width, and 'J' be the moment of inertia of the wheels. i Let i = fl, fr, rl, rr represent the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively, and R represent the effective radius of the wheel. μi T is the braking torque of the wheel. ri This is the rolling resistance torque of the wheel.

[0022] Optionally, the different redundancy 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 For tire parameters, α i This refers to the tire slip angle;

[0025] The vertical loads on each tire are as follows:

[0026]

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

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

[0029] When braking of a single wheel fails, fuzzy rules are used to distribute braking force to the remaining three wheels at a yaw rate ω. z The braking intensity z is used as the input variable, and the output variables are the braking force correction coefficients K1, K2, K3 for the remaining three wheels. Each input and output variable is defined as follows: the yaw rate is divided into negative large NB, negative small NS, stable Z, positive small PS, and positive large PB; the braking intensity is divided into low L, medium M, and high H; and the braking force correction coefficient is divided into large reduction D--, medium reduction D-, reduction D, maintain M, increase I, medium increase I+, and large increase I++.

[0030] The constraints for brake force distribution are as follows:

[0031]

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

[0033] Optionally, after the braking force is distributed, if the vehicle's yaw rate ω z Greater than the maximum value ω max For a given duration, the lateral displacement y and the yaw rate ω are expressed as... 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 in response to dual-wheel braking failure is as follows:

[0035] When the brakes of two wheels fail, first determine the location of the failed wheel, which can be divided into the following two cases:

[0036] 1) When the failed wheels are distributed on both sides, apply braking force to the remaining two wheels using an average distribution method; after the braking force is distributed, if the vehicle's yaw rate ω z Greater than the maximum value ω max For a given duration, the lateral displacement y and the yaw rate ω are expressed as... 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.

[0037] 2) When the failed wheels are distributed on the same side, ensure that the braking force of the remaining two wheels reaches the total braking force requirement, based on the lateral displacement y and yaw rate 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 implemented in response to three-wheel braking failure is as follows:

[0039] When the brakes of three wheels fail, the braking is fully borne by the remaining wheel; with lateral displacement y and yaw rate 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 in response to four-wheel brake failure is as follows:

[0041] When all four vehicle brakes fail, the wheel toe angle is increased, causing the four wheels to rotate towards the vehicle's centerline, increasing the lateral force on the wheels. This lateral force then provides the longitudinal force for the entire vehicle. When braking by increasing the wheel toe angle, the objective function is to maximize the longitudinal deceleration, with the following constraints:

[0042]

[0043] Among them, a x For longitudinal deceleration, a y F is the lateral acceleration, m is the vehicle mass, and F is the lateral acceleration. yi and F zi δ represents the lateral force and vertical load on the wheel, respectively. i Let α be the wheel rotation angle. i and α th,i These represent the tire slip angle and its threshold, i = fl, fr, rl, rr, representing the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively, μ representing the coefficient of friction, and β and β max These represent the centroid sideslip angle and its maximum value, ω and ω, respectively. z and ω max These represent the yaw rate and its maximum value, respectively.

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

[0045] The particle swarm consists of four wheel turning angles, which are used as feasible solutions for a multi-objective particle swarm optimization algorithm. A yaw penalty and an angle overshoot penalty are introduced, and the appropriate function f is defined as follows:

[0046]

[0047] in, v is the braking distance. x Let a be the longitudinal speed of the car. x For longitudinal deceleration, δ i and δ max These are the wheel rotation angles and their maximum values, respectively, with λ1, λ2, and λ3 being weighting coefficients.

[0048] The iteration terminates when the number of iterations reaches the set number or the fitness value is less than the set threshold, thus obtaining the optimal turning angle of the four wheels.

[0049] Secondly, 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 all four wheels;

[0051] The brake failure detection module is used to determine whether the wheel brakes have failed based on the wheel brake pressure, and to detect the number and location of wheel failures.

[0052] The braking redundancy switching module is used to switch to the redundancy control strategy when different wheel brakes fail, including single wheel brake failure, dual wheel brake failure, three wheel brake failure and four wheel brake failure;

[0053] The braking redundancy module is used to execute different redundancy control strategies when the braking of different wheels fails.

[0054] The dynamic coordination control module is used to coordinate braking, steering, and vehicle stability control.

[0055] The beneficial effects of this invention are:

[0056] (1) This invention addresses the problem of single-wheel braking failure by allocating the remaining wheel braking force based on fuzzy rules to ensure braking strength. When the braking of two wheels on opposite sides fails, the braking force is allocated according to the average allocation method to ensure vehicle stability and reduce vehicle lateral deviation.

[0057] (2) This invention addresses the problem of vehicle lateral deviation caused by the imbalance of braking forces on both sides when single-wheel high-intensity braking fails, dual-wheel same-side braking fails, or three-wheel braking fails. It uses lateral displacement and yaw rate as state variables. At the same time, in order to avoid singular problems, it designs an adaptive non-singular terminal sliding mode control algorithm to reduce vehicle lateral deviation and ensure vehicle stability by controlling the vehicle's four-wheel steering system.

[0058] (3) This 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, increasing the wheel lateral force, and using the wheel lateral force to provide the longitudinal force of the whole vehicle, thereby decelerating the vehicle; based on the particle swarm optimization algorithm, it finds the optimal solution for the turning angle of each wheel, and provides the maximum longitudinal deceleration under the premise of ensuring vehicle stability, so that the vehicle can stop quickly. Attached Figure Description

[0059] Figure 1 This is a 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 autonomous intelligent driving chassis.

[0061] Figure 3 This is a trapezoidal membership function graph of braking intensity.

[0062] Figure 4 This is a graph of the membership functions of the yaw rate triangle. Detailed Implementation

[0063] The 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] The yaw dynamics equation:

[0071]

[0072] Tire rotational dynamics equations:

[0073]

[0074] Where m is the vehicle mass, v x v is the longitudinal velocity of the car. y Let ω be the lateral velocity of the car. z F is the yaw rate of the car. xfl F xfr F xrl F xrr F represents the longitudinal force acting on the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively. yfl F yfr F yrl F yrr These represent 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 These are the steering angles of the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively. z Let ω represent the vehicle's moment of inertia about the Z-axis, 'a' represent the distance from the center of mass to the front axle, 'b' represent the distance from the center of mass to the rear axle, 'B' be the vehicle's track width, and 'J' be the moment of inertia of the wheels. i Let i be the angular deceleration of the wheel, i = fl, fr, rl, rr, R represent the effective radius of the wheel, and T represent the angular deceleration of the wheel. μi T is the braking torque of the wheel. ri This 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 For tire parameters, α i This refers to the tire slip angle.

[0079] The vertical load on the tires will change during vehicle braking. The vertical loads on each wheel are as follows:

[0080]

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

[0082] The vehicle slip 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 considers the braking distribution and vehicle stability when the braking of different numbers of wheels fails. The specific steps are as follows:

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

[0093] The braking force is distributed using fuzzy rules, with the yaw rate ω. z The braking intensity z is used as the input variable. Yaw rate ω z The yaw rate is the difference between the actual and expected values, 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. Each input and output variable is defined and divided into different fuzzy sets. Yaw rate is divided into negative large NB, negative small NS, stable Z, positive small PS, and positive large PB; braking intensity *z* is divided into low L, medium M, and high H; and braking force correction coefficients are divided into significantly reduced D--, moderately reduced D-, reduced D, maintained M, increased I, moderately increased I+, and significantly increased I++. When the vehicle brakes, if the left wheel fails, the left longitudinal force decreases due to the reduced braking force on the left wheel; if the right wheel fails, the right longitudinal force decreases due to the reduced braking force on the right wheel. When a single wheel brakes, vehicle stability is prioritized, while ensuring that the overall longitudinal braking force 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 uses fuzzy rules to obtain the braking force distribution under different braking intensities based on a set fuzzy rule library. Since the sideslip angle of the center of gravity cannot be directly measured, the yaw rate and braking intensity are used for judgment. A specific example of the fuzzy rule library is given, taking the right rear wheel brake failure as an example. The fuzzy rule table is shown in Table 1.

[0096] Table 1 Fuzzy Rule Table

[0097]

[0098]

[0099] Braking strength is expressed as a trapezoidal function, such as Figure 3As shown, 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 for low braking intensity are [0, 0.2, 0.3, 0.4], for medium braking intensity are [0.3, 0.5, 0.6, 0.7], and for high braking intensity are [0.6, 0.8, 1.0, 1.2].

[0100] The yaw rate is expressed using a trigonometric function, such as... Figure 4 As shown. The range of negative NB 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 small PS range is 0° / s≤ω z <+20° / s, the range of PB is +15° / s≤ω z .

[0101] The activation weight is equal to the product of the precondition membership degrees, as shown in the following formula:

[0102] weight = μ z ·μ ω

[0103] Where, μ z The membership degree of braking intensity under the given conditions, μ ω The membership degree of the yaw rate under the given conditions.

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

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

[0106] When the tire slip angle is small, the lateral force and the wheel slip angle have a linear relationship, i.e., F yi =k i α i Since the sideslip angle of the center of mass cannot be directly measured, the lateral displacement y and the yaw rate ω are used instead. z As state variables, the rotation angles of the front and rear wheels are input variables. Assuming that the rotation angles of wheels on the same axle are equal, the state-space equations are as follows:

[0107]

[0108] The rear wheel steering angle is proportional to the front wheel steering angle, and is δ. r=k δ δ f Among them, the proportionality coefficient k δ It changes with speed.

[0109] For ease of calculation, the state equation is simplified to:

[0110]

[0111] in,

[0112] To avoid singularity issues, this embodiment employs a non-singular terminal sliding mode algorithm to calculate the front wheel steering angle and the rear wheel steering angle, letting e ω =ψ-ψ d e y =yy d e = e ω +ξe y The improved non-singular terminal sliding mode design is as follows:

[0113]

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

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

[0116]

[0117] Where D(t) represents the bounded perturbation.

[0118] Differentiating with respect to s, we get:

[0119]

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

[0121]

[0122] Switching control δ fsw for:

[0123]

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

[0125] The parameters are updated by the following adaptive rate:

[0126]

[0127] Where κ0, κ1, and κ2 are any positive numbers.

[0128] By combining these methods, the front wheel steering angle δ for active steering control can be obtained. f for:

[0129]

[0130] To avoid chattering, a saturation function `sat` is used. 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 steering angle δ f for:

[0134]

[0135] The rear wheel steering angle is:

[0136]

[0137] For stability analysis, the Lyapunov function was chosen as follows:

[0138]

[0139] The time derivative of V is:

[0140]

[0141] Substitute have to:

[0142]

[0143] Simplifying, we get:

[0144]

[0145] Therefore, it can be seen that the system is asymptotically stable at the sliding surface s=0.

[0146] S2: When the braking of both wheels completely fails, it is divided into single-side wheel braking failure, double front wheel braking failure, double rear wheel braking failure, and single front wheel plus single rear wheel braking failure.

[0147] 1) Failure of both front wheels brakes, failure of both rear wheels brakes, failure of one front wheel and one rear wheel brakes

[0148] When two wheels fail, if one wheel on each side fails, this embodiment uses an average distribution method to distribute the braking coefficient equally to the remaining two wheels, ensuring braking force while maintaining vehicle stability.

[0149] First, calculate the total required braking force F based on the brake pedal travel. total When one wheel on each side fails, the total braking force required 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] Because the vertical load on each tire is different, the maximum longitudinal force on each tire is F. ximax =μF zi Therefore, the maximum longitudinal force on each wheel is different. When the average braking force exceeds the maximum longitudinal force on one of the wheels, a difference in braking force exists between the two sides, causing the vehicle to swerve. To address this swerving issue, an active four-wheel steering system is still used to ensure vehicle stability during braking.

[0154] The active four-wheel steering system is activated by controlling the vehicle's yaw rate. When the vehicle's yaw rate is detected to be greater than the specified maximum allowable value ω... max After a certain period of time, the vehicle's active four-wheel steering system intervenes to adjust the vehicle's stability.

[0155] Let e ω =ψ-ψ d e y =yy d e = e ω +ξe y The improved non-singular terminal sliding mode design is as follows:

[0156]

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

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

[0159]

[0160] Where D(t) represents the bounded perturbation.

[0161] Differentiating with respect to s, we get:

[0162]

[0163] The equivalent control objective is Therefore, the equivalent control δ can be obtained. feq for:

[0164]

[0165] Switching control δ fsw for:

[0166]

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

[0168] The parameters are updated by the following adaptive rate:

[0169]

[0170] Where κ0, κ1, and κ2 are any positive numbers.

[0171] By combining these methods, the front wheel steering angle δ for active steering control can be obtained. f for:

[0172]

[0173] To avoid chattering, a saturation function is used. 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 steering angle δ f for:

[0177]

[0178] The rear wheel steering angle is:

[0179]

[0180] For stability analysis, the Lyapunov function was chosen as follows:

[0181]

[0182] The time derivative of V is:

[0183]

[0184] Substitute have to:

[0185]

[0186] Simplifying, we get:

[0187]

[0188] Therefore, it can be seen that the system is asymptotically stable at the sliding surface s=0.

[0189] 2) Braking failure on one side of wheel

[0190] In the event of single-wheel failure, vehicle stability and braking force must be maintained simultaneously. The total required braking force F is calculated based on the brake pedal travel. total The total braking force required 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 braking force on the left side fails, the braking force of each wheel on the right side is:

[0193]

[0194] Since only one wheel has braking force, the vehicle will veer to one side. The active four-wheel steering system adjusts the front wheel angle and the rear wheel angle to control the vehicle and maintain 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 improved non-singular terminal sliding mode design is as follows:

[0198]

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

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

[0201]

[0202] Where D(t) represents the bounded perturbation.

[0203] Differentiating with respect to s, we get:

[0204]

[0205] The equivalent control objective is Therefore, 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. Let a0, a1, and a2 be the estimated values, and sgn(s) be the sign function. The parameters are updated by the following adaptive rate:

[0210]

[0211] Where κ0, κ1, and κ2 are any positive numbers.

[0212] By combining these methods, the front wheel steering angle δ for active steering control can be obtained. f for:

[0213]

[0214] To avoid chattering, a saturation function is used. 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 steering angle δ f for:

[0218]

[0219] The rear wheel steering angle is:

[0220]

[0221] For stability analysis, the Lyapunov function was chosen as follows:

[0222]

[0223] The time derivative of V is:

[0224]

[0225] Substitute have to:

[0226]

[0227] Simplifying, we get:

[0228]

[0229] Therefore, it can be seen that the system is asymptotically stable at the sliding surface s=0.

[0230] S3: When the braking of three wheels fails, the vehicle's braking force is entirely provided by the remaining wheels. Therefore, due to the uneven distribution of braking force on both sides, the vehicle will yaw excessively. In order to ensure vehicle stability and maintain braking performance, this embodiment uses an adaptive non-singular fast terminal sliding mode algorithm to calculate the adjustment angle of the front and rear wheels.

[0231] The simplified state equation is:

[0232]

[0233] Let e ω =ψ-ψ d e y =yy d e = e ω +ξe y The improved non-singular terminal sliding mode design is as follows:

[0234]

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

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

[0237]

[0238] Where D(t) represents the bounded perturbation.

[0239] Differentiating with respect to s, we get:

[0240]

[0241] The equivalent control objective is Therefore, the equivalent control δ can be obtained. feq :

[0242]

[0243] Switching control δ fsw for:

[0244]

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

[0246] The parameters are updated by the following adaptive rate:

[0247]

[0248] Where κ0, κ1, and κ2 are any positive numbers.

[0249] By combining these methods, the front wheel steering angle δ for active steering control can be obtained. f for:

[0250]

[0251] To avoid chattering, a saturation function is used. 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 steering angle δ f for:

[0255]

[0256] The rear wheel steering angle is:

[0257]

[0258] For stability analysis, the Lyapunov function was chosen as follows:

[0259]

[0260] The time derivative of V is:

[0261]

[0262] Substitute have to:

[0263]

[0264] Simplifying, we get:

[0265]

[0266] Therefore, it can be seen that the system is asymptotically stable at the sliding surface s=0.

[0267] S4: When all four wheels fail to brake, based on the automatic wheel intelligent chassis technology, each wheel can rotate independently. Therefore, by increasing the wheel toe angle, lateral force can be used to provide longitudinal force to the entire vehicle, thereby obtaining braking deceleration. When the tire force limit is not reached, the wheel toe angle is increased to maximize the longitudinal force of the entire vehicle while ensuring vehicle stability.

[0268] When braking completely fails, considering tire lateral slip characteristics, the vehicle's equation of motion is:

[0269]

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

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

[0272]

[0273] Among them, the side slip angle threshold α th Equals the Magic Tire Formula The value of the sideslip angle at that time.

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

[0275] In a d-dimensional search space, there is a population x = (x1, x2, ..., xn) consisting of n particles. 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 obtain 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 found by the group is p. g .

[0280] The optimal position found by the i-th particle, i.e., the individual extreme value, is:

[0281] p i =(p i1 ,p i2 ,…,p id )

[0282] The optimal position found by the entire particle swarm, i.e., the swarm extremum, is the swarm optimal solution:

[0283] p g =(p g1 ,p g2 ,…,p gd )

[0284] Update the particle swarm velocity and position. Based on the particle swarm optimization formula, update the velocity and position of each particle to move them towards the optimal solution. The updated particle swarm velocity and position are as follows:

[0285]

[0286] Among them, v id Let ω be the particle velocity, ω be the inertial weight, c1 and c2 be the learning factors, and r1 and r2 be random numbers within the range [0,1]. i For the individual optimal solution, p g For the group optimal solution, x i Let t be the position of the particle and t be the current iteration number.

[0287] The particle swarm consists of four wheel corners, and the particle swarm is x. i = (α1, α2, α3, α4), the four wheel turning angles are considered as feasible solutions for the multi-objective particle swarm optimization algorithm. Initially, the number of particles N, the number of iterations T, the self and swarm learning factors c1 and c2, the inertia weight ω, and the boundary α are set. th wait.

[0288] To ensure vehicle stability, a yaw penalty term is introduced; simultaneously, to ensure the vehicle's turning angle remains within the safety boundary, a turning angle exceeding the boundary penalty term is introduced. Combining the objective function and the penalty function term, the appropriate function is obtained:

[0289]

[0290] in, λ1, λ2, and λ3 represent the braking distance and are weighting coefficients.

[0291] The iteration terminates when the number of iterations reaches the set number of iterations or the fitness value is less than the specified threshold, thus obtaining the optimal turning angle of the four wheels.

[0292] Based on the above, this embodiment designs a redundant braking method for the automatic wheel intelligent driving chassis under single-wheel, dual-wheel, three-wheel and four-wheel braking failure, which solves the problem of vehicle lateral deviation and impact on braking performance when different wheel brakes fail.

[0293] Example 2

[0294] This embodiment proposes a redundant braking system based on an automatic wheel intelligent driving chassis to execute the redundant braking method of Embodiment 1. It 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 executing 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 falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing 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 brakes have failed based on the wheel brake pressure. If the wheel brakes do not fail, all four wheels will brake normally; If a wheel brake fails, the number and location of the failed wheel are detected, and different redundancy control strategies are executed for single wheel brake failure, dual wheel brake failure, three wheel brake failure and four wheel brake failure respectively. The redundant control strategy implemented in response to dual-wheel braking failure is as follows: When the brakes of two wheels fail, first determine the location of the failed wheel, which can be divided into the following two cases: 1) When the failed wheels are distributed on both sides, apply braking force to the remaining two wheels using an average distribution method; after the braking force is distributed, if the vehicle's yaw rate... Greater than the maximum value For a certain duration, the lateral displacement is... and yaw rate As a state variable, an adaptive non-singular terminal sliding mode algorithm is used to control the vehicle's four-wheel steering system; 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, so as to achieve lateral displacement. and yaw rate As a state variable, the adaptive non-singular terminal sliding mode algorithm is used to control the vehicle's four-wheel steering system.

2. The redundant braking method based on an automatic wheel intelligent driving chassis as described in claim 1, characterized in that: The different redundancy control strategies employ a seven-degree-of-freedom vehicle dynamics model, including: Longitudinal dynamic equation: ； Lateral dynamic equations: ； The yaw dynamics equation: ； Tire rotational dynamics equations: ； in, For vehicle quality, For the longitudinal speed of the car, For the lateral speed of the car, The yaw rate of the car. , , , These represent the longitudinal forces acting on the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively. , , , These represent the lateral forces acting on the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively. , , , These are the steering angles of the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively. This represents the moment of inertia of the vehicle about the Z-axis. This represents the distance from the center of gravity to the front axle. This represents the distance from the center of mass to the rear axle. The wheelbase of the vehicle. Let be the moment of inertia of the wheel. The angular deceleration of the wheel, These represent the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively. Indicates the effective radius of the wheel. The braking torque of the wheel. This is the rolling resistance torque of the wheel.

3. The redundant braking method based on an automatic wheel intelligent driving chassis as described in claim 2, characterized in that: The different redundancy control strategies adopt the following magic tire model: ； in, , , , , , , , For tire parameters, This refers to the tire slip angle; The vertical loads on each tire are as follows: ； ； ； ； in, , , , The vertical loads are for the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively. The height of the vehicle's center of gravity from the ground. .

4. The redundant braking method based on an automatic wheel intelligent driving chassis as described in claim 1, characterized in that: The redundant control strategy implemented in response to single-wheel braking failure is as follows: When the braking of a single wheel fails, fuzzy rules are used to distribute braking force to the remaining three wheels, based on yaw rate. The braking intensity z is taken as the input variable, and the output variable is the braking force correction coefficient of the remaining three wheels. Each input and output variable is defined, and the yaw rate is divided into negative large NB, negative small NS, stable Z, positive small PS, and positive large PB. The braking intensity is divided into low L, medium M, and high H. The braking force correction coefficient is divided into significantly reduced D--, medium reduced D-, reduced D, maintained M, increased I, medium increased I+, and significantly increased I++. The constraints for brake force distribution are as follows: ； in, For vehicle quality, Represents gravitational acceleration. , , These represent the longitudinal force, lateral force, and vertical load of the wheel, respectively, with subscripts... These represent the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively. This represents the coefficient of friction.

5. The redundant braking method based on an automatic wheel intelligent driving chassis as described in claim 4, characterized in that: After the braking force is distributed, if the vehicle's yaw rate Greater than the maximum value For a certain duration, the lateral displacement is... and yaw rate As a state variable, the adaptive non-singular terminal sliding mode algorithm is used to control the vehicle's four-wheel steering system.

6. The redundant braking method based on an automatic wheel intelligent driving chassis as described in claim 1, characterized in that: The redundant control strategy implemented in response to three-wheel brake failure is as follows: When the brakes of three wheels fail, the braking is fully borne by the remaining wheel; with lateral displacement and yaw rate As a state variable, the vehicle's four-wheel steering system is controlled by an adaptive non-singular fast terminal sliding mode algorithm.

7. The redundant braking method based on an automatic wheel intelligent driving chassis as described in claim 1, characterized in that: The redundant control strategy implemented in response to four-wheel brake failure is as follows: When all four vehicle brakes fail, the wheel toe angle is increased, causing the four wheels to rotate towards the vehicle's centerline, increasing the lateral force on the wheels. This lateral force then provides the longitudinal force for the entire vehicle. When braking by increasing the wheel toe angle, the objective function is to maximize the longitudinal deceleration, with the following constraints: ； in, For longitudinal deceleration, It is lateral acceleration. For vehicle quality, and These represent the lateral force and vertical load on the wheel, respectively. For the turning angle of the wheel, and These are the tire slip angle and its threshold. These represent the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively. Indicates the coefficient of friction. and These represent the centroid sideslip angle and its maximum value, respectively. and These represent the yaw rate and its maximum value, respectively.

8. The redundant braking method based on an automatic wheel intelligent driving chassis as described in claim 7, 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 consists of four wheel turning angles, which are used as feasible solutions for a multi-objective particle swarm optimization algorithm. A yaw penalty and an angle overshoot penalty are introduced, and a suitable function is defined. for: ； in, Braking distance, For the longitudinal speed of the car, For longitudinal deceleration, and These are the wheel rotation angle and its maximum value. , , These are the weighting coefficients; The iteration terminates when the number of iterations reaches the set number or the fitness value is less than the set threshold, thus obtaining the optimal turning angle of the four wheels.

9. 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 all four wheels; The brake failure detection module is used to determine whether the wheel brakes have failed based on the wheel brake pressure, and to detect the number and location of wheel failures. The braking redundancy switching module is used to switch to redundancy control strategies for different wheel braking failures, including single-wheel braking failure, dual-wheel braking failure, three-wheel braking failure, and four-wheel braking failure. The redundancy control strategy executed for dual-wheel braking failure is as follows: When the brakes of two wheels fail, first determine the location of the failed wheel, which can be divided into the following two cases: 1) When the failed wheels are distributed on both sides, apply braking force to the remaining two wheels using an average distribution method; after the braking force is distributed, if the vehicle's yaw rate... Greater than the maximum value For a certain duration, the lateral displacement is... and yaw rate As a state variable, an adaptive non-singular terminal sliding mode algorithm is used to control the vehicle's four-wheel steering system; 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, so as to achieve lateral displacement. and yaw rate As a state variable, an adaptive non-singular terminal sliding mode algorithm is used to control the vehicle's four-wheel steering system; The braking redundancy module is used to execute different redundancy control strategies when the braking of different wheels fails. The dynamic coordination control module is used to coordinate braking, steering, and vehicle stability control.

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