An automotive braking fault-tolerant predictive control method and system

Abstract

The present invention discloses an automotive braking fault-tolerant predictive control method and system. The method includes defining the effective state vectors of the inlet valve group and the outlet valve group and the effective flow rate vector of the brake wheel cylinder group in the normal mode according to the judgment result that the vehicle does not trigger the braking fault-tolerant control; predicting the future state of the vehicle speed based on the first dynamic equation from the effective flow rate vector of the brake wheel cylinder group in the normal mode to the vehicle speed to obtain the first state prediction result; obtaining the first optimal flow rate vector of the brake wheel cylinder group and the first optimal state vectors of the corresponding inlet valve group and outlet valve group according to the constructed cost function; and using the electronic hydraulic braking system to respond to the first optimal state vectors of the inlet valve group and the outlet valve group to perform braking fault-tolerant control on the vehicle. The present invention can improve the dynamic performance of automotive braking fault-tolerant control, ensure the optimal switching state of the electromagnetic switching valves during the automotive braking fault-tolerant process, and enhance the robustness of automotive braking fault-tolerant control.

Description

Technical Field

[0001] The present invention relates to the technical field of automotive braking, and particularly to an automotive braking fault-tolerant prediction control method and system. Background Art

[0002] The electro-hydraulic braking system (EHB) is a core component of an automobile, which determines the braking performance of the whole vehicle. When the driver steps on the brake pedal or the vehicle has an active braking requirement, the EHB actively and independently adjusts the brake fluid pressure at the four wheels through the organic cooperation of a high-pressure source and solenoid valves to brake the vehicle. At present, the EHB mainly adjusts the hydraulic pressure of the brake wheel cylinder through on-off solenoid valves and proportional solenoid valves. Among them, the on-off solenoid valve has been widely used in the industry due to its simple structure and low cost. The EHB system equipped with electromagnetic on-off valves has become the core braking product in the current automotive industry research and development.

[0003] Particularly, when a fault occurs in the EHB where a certain braking circuit cannot provide effective braking force due to brake oil leakage in the brake pipe, brake disc wear, etc., safety accidents such as vehicle deviation and instability are likely to be induced during vehicle braking. Therefore, the EHB needs to have braking fault-tolerant ability. The existing EHB braking fault-tolerant control algorithms are mainly implemented based on a cascaded control method, which includes a braking fault-tolerant control outer loop and a hydraulic pressure control inner loop. The two control loops are independently cascade-controlled, and the hydraulic pressure control loop usually adopts a PWM control method. The above cascaded braking fault-tolerant control method has the following defects: 1) There are multiple cascaded control loops, and the hydraulic pressure control requires an additional PWM generator, so the braking fault-tolerant control structure is complex and the cost is high; 2) The control frequency bands of the braking fault-tolerant control outer loop and the hydraulic pressure control inner loop are similar, which greatly limits the dynamic performance of the EHB braking fault-tolerant; 3) It is difficult to characterize the quantitative relationship between the on-off state of the on-off solenoid valve and the vehicle speed, and the optimal on-off state of the on-off solenoid valve cannot be guaranteed during the braking fault-tolerant control process. Summary of the Invention

[0004] The present invention aims to solve at least one of the technical problems in the related art to some extent.

[0005] To this end, the present invention proposes an automotive braking fault-tolerant predictive control method, which solves the problem of complex control structure caused by cascade control of multiple control loops in the existing cascade braking fault-tolerant control method, solves the problem that the hydraulic pressure PWM control method requires an additional PWM generator, solves the problem of poor dynamic performance of vehicle speed control caused by the similar frequency bands of the outer loop of vehicle speed fault-tolerant control and the inner loop of hydraulic pressure control, and solves the problem that it is difficult to achieve the optimal switching control of the on-off solenoid valve during the automotive fault-tolerant braking control process, achieving the effects of canceling the cascade control structure of the existing automotive fault-tolerant braking control and the PWM generator module of hydraulic pressure control, reducing the complexity and cost of the control structure, improving the dynamic performance of automotive fault-tolerant braking control, and realizing the optimal control of the on-off solenoid valve during the fault-tolerant braking control process.

[0006] Another object of the present invention is to propose an automotive braking fault-tolerant predictive control system.

[0007] To achieve the above object, on the one hand, the present invention proposes an automotive braking fault-tolerant predictive control method, including:

[0008] Based on vehicle measurement data, determine whether the vehicle triggers stability control, and define the effective state vectors of the inlet valve group and the outlet valve group and the effective flow vector of the brake wheel cylinder group in the normal mode according to the judgment result that the vehicle does not trigger braking fault-tolerant control;

[0009] Based on the first dynamic equation from the effective flow vector of the brake wheel cylinder group to the vehicle speed in the normal mode constructed, predict the future state of the vehicle speed to obtain the first state prediction result;

[0010] According to the cost function of vehicle speed control in the normal mode constructed based on the first state prediction result, obtain the first optimal flow vector of the brake wheel cylinder group and the first optimal state vectors of the corresponding inlet valve group and outlet valve group;

[0011] Use the electronic hydraulic braking system to respond to the first optimal state vectors of the inlet valve group and the outlet valve group to perform braking fault-tolerant control on the vehicle.

[0012] The automotive braking fault-tolerant predictive control method of the embodiments of the present invention may further have the following additional technical features:

[0013] In an embodiment of the present invention, after determining whether the vehicle triggers stability control based on vehicle measurement data, the method further includes:

[0014] According to the judgment result that the vehicle triggers stability control, perform state isolation on the faulty oil circuit of the braking system and the inlet valve and outlet valve of the corresponding oil circuit to obtain the state isolation result;

[0015] Obtain the effective state vectors of the inlet valve group and the outlet valve group and the effective flow vector of the brake wheel cylinder group in the fault mode based on the state isolation result;

[0016] Predict the future state of the vehicle speed according to the second dynamic equation from the effective flow vector of the brake wheel cylinder group to the vehicle speed in the fault mode to obtain the second state prediction result;

[0017] Obtain the second optimal flow vector of the brake wheel cylinder group and the corresponding second optimal state vectors of the inlet valve group and the outlet valve group according to the cost function of vehicle speed control in the fault mode constructed based on the second state prediction result, and use the electronic hydraulic braking system to respond to the second optimal state vector to perform braking fault tolerance control on the vehicle.

[0018] In an embodiment of the present invention, before determining whether the vehicle triggers stability control based on the vehicle measurement data, the method further includes:

[0019] Obtain the vehicle measurement data; wherein, the vehicle measurement data includes vehicle state, brake system state and fault information;

[0020] Perform filtering processing on the vehicle measurement data to obtain filtered data.

[0021] In an embodiment of the present invention, predicting the future state of the vehicle speed according to the first dynamic equation from the effective flow vector of the brake wheel cylinder group to the vehicle speed in the normal mode to obtain the first state prediction result includes:

[0022] Construct the first dynamic equation from the effective flow vector of the brake wheel cylinder group to the vehicle speed in the normal mode;

[0023] Based on the first dynamic equation, real-time estimate the first lumped disturbance term of vehicle speed control and brake wheel cylinder group hydraulic pressure control in the normal mode; wherein, the first lumped disturbance term includes real-time estimating the torque lumped disturbance term of vehicle speed control and the flow lumped disturbance term of brake wheel cylinder group hydraulic pressure control in the normal mode of the brake system by using a discrete-time extended state observer;

[0024] Based on the first lumped disturbance term, establish a vehicle speed prediction model of the vehicle in the normal mode, and predict the future state of the vehicle speed to obtain the first state prediction result.

[0025] In an embodiment of the present invention, predicting the future state of the vehicle speed according to the second dynamic equation from the effective flow vector of the brake wheel cylinder group to the vehicle speed in the fault mode to obtain the second state prediction result includes:

[0026] Construct the second dynamic equation from the effective flow vector of the brake wheel cylinder group to the vehicle speed in the fault mode;

[0027] Based on the second dynamic equation, a second lumped disturbance term for vehicle vehicle speed control and brake wheel cylinder group hydraulic pressure control in the fault mode is estimated in real time; wherein, the second lumped disturbance term includes a torque lumped disturbance term for vehicle vehicle speed control and a flow lumped disturbance term for brake wheel cylinder group hydraulic pressure control estimated in real time by using a discrete-time extended state observer in the brake system fault mode.

[0028] Based on the second lumped disturbance term, a vehicle speed prediction model for the vehicle in the fault mode is established, and the future state of the vehicle speed is predicted to obtain a second state prediction result.

[0029] To achieve the above object, on the other hand, the present invention proposes an automotive brake fault-tolerant prediction control system, including:

[0030] A first vehicle speed control model module, configured to determine whether the vehicle triggers stability control based on vehicle measurement data, and define an effective state vector of the inlet valve group and the outlet valve group and an effective flow vector of the brake wheel cylinder group in the normal mode according to the judgment result that the vehicle does not trigger brake fault-tolerant control.

[0031] A first vehicle speed prediction model module, configured to predict the future state of the vehicle speed to obtain a first state prediction result based on a first dynamic equation from the effective flow vector of the brake wheel cylinder group to the vehicle speed constructed in the normal mode.

[0032] A first optimal state vector calculation module, configured to obtain a first optimal flow vector of the brake wheel cylinder group and a first optimal state vector of the corresponding inlet valve group and outlet valve group according to a cost function of vehicle speed control in the normal mode constructed based on the first state prediction result; and use the electronic hydraulic brake system to respond to the first optimal state vector of the inlet valve group and the outlet valve group to perform brake fault-tolerant control on the vehicle.

[0033] The beneficial effects of the present invention are:

[0034] 1) The present invention can achieve automotive brake fault-tolerant control only by using one brake fault-tolerant prediction controller, cancels the traditional cascade control structure including a vehicle speed control link, a braking force fault-tolerant distribution link, a hydraulic pressure control link, and a PWM generator link, and greatly reduces the control structure complexity and cost of the automotive brake fault-tolerant control system.

[0035] 2) The present invention adopts a non-cascade vehicle brake fault-tolerant control structure, and the vehicle speed control performance no longer depends on the limitation of the hydraulic pressure control performance, and the dynamic control performance of vehicle speed control / brake fault-tolerant control is greatly improved.

[0036] 3) The present invention for the first time constructs a quantitative mathematical relationship between the switching states of the inlet valve group and the outlet valve group of the brake wheel cylinder group and the vehicle speed under normal and fault modes of the braking system, and can directly obtain the optimal switching signals of the inlet valve group and the outlet valve group through vehicle speed prediction and cost function optimization, ensuring the optimal performance of the vehicle speed / braking fault-tolerant control system.

[0037] 4) The present invention uses the method of discrete extended state observation to online estimate the lumped disturbance terms of vehicle speed control and brake wheel cylinder hydraulic pressure control, which has strong robustness and complex environment adaptability.

[0038] The automotive braking fault-tolerant predictive control method and system of the embodiments of the present invention can solve the problems of complex control structure and high cost of the existing automotive cascaded braking fault-tolerant control method, realize the effect of directly obtaining the optimal switching state of the switching valve through predictive control, enhance the adaptability of the control system to complex environments, and will strongly promote the industrialization promotion and application of automotive braking systems and accelerate the localization process of key vehicle braking components.

[0039] The additional aspects and advantages of the present invention will be partly given in the following description, partly will become obvious from the following description, or will be understood through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The above and / or additional aspects and advantages of the present invention will become obvious and easy to understand from the following description of the embodiments in conjunction with the drawings, wherein:

[0041] Figure 1 is a flowchart of an automotive braking fault-tolerant predictive control method according to an embodiment of the present invention;

[0042] Figure 2 is a simplified schematic diagram of an automotive electro-hydraulic braking system involved in an embodiment of the present invention;

[0043] Figure 3 is a flowchart of another automotive braking fault-tolerant predictive control method according to an embodiment of the present invention;

[0044] Figure 4 is a structural diagram of an automotive braking fault-tolerant predictive control system according to an embodiment of the present invention.

[0045] Among them, 1. High-pressure supply device, 2. Inlet valve group, 21. Inlet valve 1, 22. Inlet valve 2, 23. Inlet valve 3, 24. Inlet valve 4, 3. Brake wheel cylinder group, 31. Brake wheel cylinder 1, 32. Brake wheel cylinder 2, 33. Brake wheel cylinder 3, 34. Brake wheel cylinder 4, 4. Outlet valve, 41. Outlet valve 1, 42. Outlet valve 2, 43. Outlet valve 3, 44. Outlet valve 4, 5. Low-pressure oil return device, 6. Sensor group, 61. First pressure sensor, 62. Second pressure sensor, 63. Third pressure sensor, 64. Fourth pressure sensor, 65. Fifth pressure sensor, 7. Brake control device. 71. Data processing unit, 72. Fault-tolerant control trigger unit, 73. Reference model unit, 74. Normal mode brake control unit, 741. First vehicle speed control model module, 742. First disturbance observation module, 743. Second disturbance observation module, 744. First vehicle speed prediction model module, 745. First cost function module, 746. First optimal state vector calculation module, 75. Fault mode brake control unit, 751. Second vehicle speed control model module, 752. Third disturbance observation module, 753. Fourth disturbance observation module, 754. Second vehicle speed prediction model module, 755. Second cost function module, 756. Second optimal state vector calculation module. Detailed implementation manners

[0046] It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments may be combined with each other. The present invention will be described in detail below with reference to the drawings and in combination with the embodiments.

[0047] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0048] The automotive brake fault-tolerant predictive control method and system proposed according to the embodiments of the present invention will be described below with reference to the drawings.

[0049] Figure 1 It is a flowchart of an automotive brake fault-tolerant predictive control method according to an embodiment of the present invention.

[0050] As Figure 1 shown, the method includes but is not limited to the following steps:

[0051] S101. Determine whether the vehicle triggers stability control based on vehicle measurement data, and define the effective state vector of the inlet valve group and the outlet valve group and the effective flow vector of the brake wheel cylinder group in the normal mode according to the judgment result that the vehicle does not trigger the brake fault tolerance control;

[0052] S102. Predict the future state of the vehicle speed to obtain the first state prediction result based on the first dynamic equation from the effective flow vector of the brake wheel cylinder group to the vehicle speed in the normal mode;

[0053] S103. Obtain the first optimal flow vector of the brake wheel cylinder group and the first optimal state vector of the corresponding inlet valve group and outlet valve group according to the cost function of vehicle speed control in the normal mode based on the first state prediction result;

[0054] S104. Use the electronic hydraulic braking system to respond to the first optimal state vector of the inlet valve group and the outlet valve group to perform brake fault tolerance control on the vehicle.

[0055] Further, after determining whether the vehicle triggers stability control based on vehicle measurement data, the present invention further includes:

[0056] Perform state isolation on the faulty oil circuit of the braking system and the inlet valve and outlet valve of the corresponding oil circuit according to the judgment result that the vehicle triggers stability control to obtain a state isolation result;

[0057] Obtain the effective state vector of the inlet valve group and the outlet valve group and the effective flow vector of the brake wheel cylinder group in the fault mode based on the state isolation result;

[0058] Predict the future state of the vehicle speed to obtain the second state prediction result according to the second dynamic equation from the effective flow vector of the brake wheel cylinder group to the vehicle speed in the fault mode;

[0059] Obtain the second optimal flow vector of the brake wheel cylinder group and the second optimal state vector of the corresponding inlet valve group and outlet valve group according to the cost function of vehicle speed control in the fault mode based on the second state prediction result, and use the electronic hydraulic braking system to respond to the second optimal state vector to perform brake fault tolerance control on the vehicle.

[0060] Specifically, Figure 2 is a simplified diagram of the vehicle brake fault tolerance prediction control system of the present invention, as Figure 2 shown, Figure 3 is a flowchart of another vehicle stability prediction control method of the present invention, as Figure 3 shown, and specifically includes the following steps:

[0061] Step S1: Obtain vehicle status, braking system status and fault information online, and filter the measurement data;

[0062] Step S2: Determine whether the braking fault tolerance control is triggered. If triggered, execute Step S9; otherwise, execute Step S3;

[0063] Step S3: Define the effective state vectors of the inlet valve group 2 and the outlet valve group 4 and the effective flow vector of the brake wheel cylinder group 3 in the normal mode, and form the corresponding vector sets;

[0064] Step S4: Construct the dynamic equation from the effective flow vector of the brake wheel cylinder group 3 to the vehicle speed in the normal mode and discretize it;

[0065] Step S5: Estimate the lumped disturbance terms of the vehicle speed control and the hydraulic pressure control of the brake wheel cylinder group 3 in real time in the normal mode;

[0066] Step S6: Establish a vehicle speed prediction model for the vehicle in the normal mode and predict the future state of the vehicle speed;

[0067] Step S7: Formulate the cost function for the vehicle speed control in the normal mode;

[0068] Step S8: Optimize the cost function for the vehicle speed control in the normal mode, directly obtain the optimal flow vector of the brake wheel cylinder group 3 and the optimal state vectors of the corresponding inlet valve group 2 and outlet valve group 4, and then jump to Step S16;

[0069] Step S9: Actively isolate the faulty oil circuit of the braking system, and the inlet valve and outlet valve of the corresponding oil circuit are de-energized and drained;

[0070] Step S10: Define the effective state vectors of the inlet valve group 2 and the outlet valve group 4 and the effective flow vector of the brake wheel cylinder group 3 in the fault mode, and form the corresponding vector sets;

[0071] Step S11: Construct the dynamic equation from the effective flow vector of the brake wheel cylinder group 3 to the vehicle speed in the fault mode and discretize it;

[0072] Step S12: Estimate the lumped disturbance terms of the vehicle speed control and the hydraulic pressure control of the brake wheel cylinder group 3 in real time in the fault mode;

[0073] Step S13: Establish a vehicle speed prediction model for the vehicle in the fault mode and predict the future state of the vehicle speed;

[0074] Step S14: Formulate the cost function for the vehicle speed control in the fault mode;

[0075] Step S15: Optimize the cost function for the vehicle speed control in the fault mode, and directly obtain the optimal flow vector of the brake wheel cylinder group 3 and the optimal state vectors of the corresponding inlet valve group 2 and outlet valve group 4;

[0076] Step S16: Apply the optimal state vectors of the inlet valve group 2 and the outlet valve group 4 to the electronic hydraulic braking system to achieve braking fault tolerance control of the vehicle.

[0077] Further, in step S3, define the effective state vectors of the inlet valve group 2 and the outlet valve group 4 and the effective flow rate vectors of the brake wheel cylinder group 3 in the normal mode to form the corresponding vector sets. The specific formulas are as follows:

[0078] M0

[0079] where M0 represents the normal mode of the braking system. Among them, and are the effective state vector set and the switch state vector of the inlet valve group 2 and the outlet valve group 4 in the M0 mode, respectively. respectively represent the switch state vectors of the first inlet valve 21 and the first outlet valve 41, the second inlet valve 22 and the second outlet valve 42, the third inlet valve 23 and the third outlet valve 43, and the fourth inlet valve 24 and the fourth outlet valve 44. S lfI and S lfO respectively represent the switch states of the first inlet valve 21 and the first outlet valve 41, and and S rfI and S rfO respectively represent the switch states of the second inlet valve 22 and the second outlet valve 42, and and S lrI and S lrO respectively represent the switch states of the third inlet valve 23 and the third outlet valve 43, and and S rrI and S rrO respectively represent the switch states of the fourth inlet valve 24 and the fourth outlet valve 44, and and S lfI , S lfO , S rfI , S rfO , S lrI , S lrO , S rrI , S rrO ∈ {0, 1} can only take the values 0 and 1, where 0 represents the off state and 1 represents the on state. and Q ijmn =[Q lf i, Qrf j, Q lrm , Q rrn T , where i, j, m, n = 0, 1, 2 are the effective flow rate vector sets and effective flow rate vectors of the brake wheel cylinder group 3 in the M0 mode. Q lf i, Q rf i, Q lr i, Q rr i, where i = 0, 1, 2 are the brake fluid volume flow rates flowing into the first brake wheel cylinder 31, the second brake wheel cylinder 32, the third brake wheel cylinder 33, and the fourth brake wheel cylinder 34 respectively. Q 0000 ~Q 2222 are the state vectors S of the inlet valve group 2 and the outlet valve group 4 in the M0 mode respectively v taking values of S 0000 ~S 2222 when the flow rate vectors of the brake wheel cylinder group 3 are as follows:

[0080] M0: Q w = Q ijmn = [Q lf i, Q rfj , Q lrm , Q rrn T , when S v = S ijmn , i, j, m, n = 0, 1, 2

[0081] where Q w is the flow rate vector flowing into the brake wheel cylinder group 3 at the current moment. Q lf0 , Q lf1 and Q lf2 are the brake fluid volume flow rates flowing into the first brake wheel cylinder 31 when the first inlet valve 21 and the first outlet valve 41 are fully closed, when the first inlet valve 21 is closed and the first outlet valve 41 is conducting, and when the first inlet valve 21 is conducting and the first outlet valve 41 is closed respectively. Q lr0 , Q lr1 and Q lr2 are the brake fluid volume flow rates flowing into the second brake wheel cylinder 32 when the second inlet valve 22 and the second outlet valve 42 are fully closed, when the second inlet valve 22 is closed and the second outlet valve 42 is conducting, and when the second inlet valve 22 is conducting and the second outlet valve 42 is closed respectively. Q rf0 , Q rf1 and Q rf2 are the brake fluid volume flow rates flowing into the third brake wheel cylinder 33 when the third inlet valve 23 and the third outlet valve 43 are fully closed, when the third inlet valve 23 is closed and the third outlet valve 43 is conducting, and when the third inlet valve 23 is conducting and the third outlet valve 43 is closed respectively. Q​​rr0 , Q rr1 and Q rr2 are the brake fluid volume flow rates flowing into the brake wheel cylinder four 34 when the inlet valve four 24 and the outlet valve four 44 are fully closed, the inlet valve four 24 is closed and the outlet valve four 44 is conducting, and the inlet valve four 24 is conducting and the outlet valve four 44 is closed, respectively. Q lf0 , Q lf1 , Q lf2 , Q lr0 , Q lr1 , Q lr2 , Q rf0 , Q rf1 , Q rf2 , Q rr0 , Q rr1 and Q rr2 The specific formulas for

[0082]

[0083] where P h , P r , P w1 , P w2 , P w3 and P w4 are the hydraulic pressures of the high-pressure supply device 1, the low-pressure oil return device 5, the brake wheel cylinder one 31, the brake wheel cylinder two 32, the brake wheel cylinder three 33, and the brake wheel cylinder four 34, respectively. c d is the flow coefficient, A s is the flow-through area, and ρ is the brake fluid density.

[0084] Furthermore, in step S4, a dynamic equation of the effective flow vector of the brake wheel cylinder group 3 to the vehicle speed in the normal mode is constructed and discretized; the dynamic equation of the effective flow vector of the brake wheel cylinder group 3 to the vehicle speed in the normal mode is specifically as follows:

[0085] M0:

[0086] where x1 = V x and T w = [T w1 , T w2 , T w3 , T w4 T are the vehicle speed and the wheel-end drive torque vector, respectively. T w1 , T w2 , T w3 and T w4 are the drive torques of the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel, respectively. x2 = [P w1 , P​w2 , P w3 , P w4 T is the hydraulic pressure vector of the brake wheel cylinder group 3 in M0 mode. U = Q w is the flow rate vector of the brake wheel cylinder group 3. D v is the lumped disturbance term for vehicle vehicle speed control, D w = [D w1 , D w2 , D w3 , D w4 T is the lumped disturbance vector for hydraulic pressure control of the brake wheel cylinder group 3 in M0 mode, D w1 , D w2 , D w3 and D w4 are respectively the lumped disturbance terms for hydraulic pressure control of the first brake wheel cylinder 31, the second brake wheel cylinder 32, the third brake wheel cylinder 33 and the fourth brake wheel cylinder 34. B v1 == -(P 2T / mr)[1, 1, 1, 1], B v2 = (1 / mr)[1, 1, 1, 1], B p = diag{κ w / V w1 , κ w / V w1 , κ w / V w1 , κ w / V w4} is the system parameter matrix; where, m is the vehicle mass, r is the effective wheel radius, P 2T is the conversion coefficient from hydraulic pressure to braking torque, κ w is the bulk modulus of the brake fluid, V w1 , V w2 , V w3 and V w4 are respectively the volumes of the first brake wheel cylinder 31, the second brake wheel cylinder 32, the third brake wheel cylinder 33 and the fourth brake wheel cylinder 34. Further, the dynamic equation from the effective flow rate vector of the brake wheel cylinder group 3 to the vehicle vehicle speed in normal mode is discretized, and the specific formula is as follows:

[0087] M0:

[0088] where, x1(k) and x1(k + 1) are respectively the vehicle vehicle speeds at time k and time k + 1. x2(k) and x2(k + 1) are respectively the hydraulic pressure vectors of the brake wheel cylinder group 3 at time k and time k + 1 in M0 mode. T w ​​(k) is the wheel-end drive torque vector at time k. U(k) is the flow rate vector of the brake wheel cylinder group 3 at time k.

[0089] D VK (k) = D V ·T S is the lumped disturbance term for vehicle speed control at time k.

[0090] D WK (k) = D W ·T S is the lumped disturbance vector for the hydraulic pressure control of the brake wheel cylinder group 3 at time k in M0 mode. B V1K = B V1 ·T S 、B V2K = B V2 ·T S and B pK = B p ·T S is the system parameter matrix. T S is the sampling time.

[0091] Furthermore, the lumped disturbance terms for vehicle speed control and the hydraulic pressure control of the brake wheel cylinder group 3 in the normal mode are estimated in real time in step S5, and the specific formulas are as follows:

[0092] M0:

[0093] where z 11 (k) and z 11 (k + 1) are the estimated values of the vehicle speed at time k and k + 1 respectively, and z 12 (k) and z 12 (k + 1) are the estimated values of the lumped disturbance terms for vehicle speed control at time k and k + 1 in M0 mode respectively. z 21 (k) and z 21 (k + 1) are the estimated values of the hydraulic pressure vectors of the brake wheel cylinder group 3 at time k and k + 1 in M0 mode respectively. z 22 (k) and z 22 (k + 1) are the estimated values of the lumped disturbance vectors for the hydraulic pressure control of the brake wheel cylinder group 3 at time k and k + 1 in M0 mode respectively. L 11 、L 12 、L 21 and L 22 are the observer gain matrices.

[0094] Furthermore, a vehicle speed prediction model for the vehicle in the normal mode is established in step S6, and the future state of the vehicle speed is predicted; among them, the one-step prediction equation of the vehicle speed prediction model is specifically as follows:

[0095] M0:

[0096] Among them, is the one-step predicted value of the vehicle speed at time k + 1, is the one-step predicted value of the hydraulic pressure vector of the brake wheel cylinder group 3 at time k + 1 in M0 mode. Further, the specific formula of the two-step prediction equation of the vehicle speed prediction model is as follows:

[0097] M0:

[0098] Among them, is the two-step predicted value of the vehicle speed at time k + 2, is the two-step predicted value of the hydraulic pressure vector of the brake wheel cylinder group 3 at time k + 2 in M0 mode.

[0099] Further, the cost function for formulating vehicle speed control in the normal mode in step S7 is specifically formulated as follows:

[0100] M0:

[0101] Among them, J, J1, and J2 are respectively the cost function for vehicle speed control, the speed error cost function, and the hydraulic pressure cost function in M0 mode. x1d(k + 2) and e1(k + 2) are respectively the reference value and error of the vehicle speed at time k + 2. ε 1P > 0, ε 1I > 0, and ε 1D > 0 are respectively the proportional coefficient, integral coefficient, and differential coefficient of the vehicle speed control error cost function. ε2 = ε 2s [1, -1, 1, -1] is the coefficient matrix of the hydraulic pressure cost function.

[0102] Further, in step S8, the cost function for optimizing vehicle speed control in the normal mode is used to directly obtain the optimal flow vector of the brake wheel cylinder group 3 and the optimal state vectors of the corresponding inlet valve group 2 and outlet valve group 4, specifically formulated as follows:

[0103] M0:

[0104] Among them, the solution methods for the optimization problem include, but are not limited to, the enumeration method and mixed integer programming.

[0105] Further, in step S10, the effective state vectors of the inlet valve group 2 and the outlet valve group 4 and the effective flow vector of the brake wheel cylinder group 3 in the fault mode are defined to form the corresponding vector sets, specifically formulated as follows:

[0106] M1:

[0107] M2:

[0108] M3:

[0109] M4:

[0110] Among them, M1, M2, M3, and M4 respectively represent the failure modes in which the left front wheel, right front wheel, left rear wheel, and right rear wheel brake oil circuits cannot provide effective braking force. Among them, and are respectively the effective state vector sets of the inlet valve group 2 and the outlet valve group 4 in the M1 mode, M2 mode, M3 mode, and M4 mode. and are respectively the switch state vectors of the inlet valve group 2 and the outlet valve group 4 in the M1 mode, M2 mode, M3 mode, and M4 mode. and are respectively the effective flow rate vector sets of the brake wheel cylinder group 3 in the M1 mode, M2 mode, M3 mode, and M4 mode. and are respectively the effective flow rate vectors of the brake wheel cylinder group 3 in the M1 mode, M2 mode, M3 mode, and M4 mode. and are respectively the state vectors S of the inlet valve group 2 and the outlet valve group 4 v taking values in the M1 mode M2 mode M3 mode and M4 mode when the flow rate vectors of the brake wheel cylinder group 3 are specifically defined as follows:

[0111] M1:

[0112] M2:

[0113] M3:

[0114] M4:

[0115] Furthermore, in the step S11, a dynamic equation from the effective flow rate vector of the brake wheel cylinder group 3 to the vehicle speed in the failure mode is constructed and discretized; among them, the dynamic equation from the effective flow rate vector of the brake wheel cylinder group 3 to the vehicle speed in the failure mode is specifically as follows:

[0116] M1:

[0117] M2:

[0118] M3:

[0119] M4:

[0120] where x1 = V x is the vehicle speed. and are the hydraulic pressure vectors of the brake wheel cylinder group 3 in M1 mode, M2 mode, M3 mode, and M4 mode, respectively. and are the lumped disturbance vectors of the hydraulic pressure control of the brake wheel cylinder group 3 in M1 mode, M2 mode, M3 mode, and M4 mode, respectively. and are the system parameter matrices. Further, the dynamic equation from the effective flow rate vector of the brake wheel cylinder group 3 to the vehicle speed in the fault mode is discretized, and the specific formula is as follows:

[0121] M1:

[0122] M2:

[0123] M3:

[0124] M4:

[0125] where x1(k) and x1(k + 1) are the vehicle speeds at time k and time k + 1, respectively. and are the hydraulic pressure vectors of the brake wheel cylinder group 3 at time k in M1 mode, M2 mode, M3 mode, and M4 mode, respectively; and are the hydraulic pressure vectors of the brake wheel cylinder group 3 at time k + 1 in M1 mode, M2 mode, M3 mode, and M4 mode, respectively.

[0126]

[0127] and are the lumped disturbance vectors of the hydraulic pressure control of the brake wheel cylinder group 3 at time k in M1 mode, M2 mode, M3 mode, and M4 mode, respectively.

[0128] and is the system parameter matrix. T s is the sampling time.

[0129] Furthermore, the lumped disturbance terms of vehicle vehicle speed control and brake wheel cylinder group 3 hydraulic pressure control in the real-time estimation fault mode in step S12 are as follows:

[0130] M1:

[0131] M2:

[0132] M3:

[0133] M4:

[0134] where z 11 (k) and z 11 (k + 1) are the estimated values of the vehicle speed at time k and time k + 1, respectively. and are the estimated values of the lumped disturbance terms of vehicle speed control at time k in modes M1, M2, M3, and M4, respectively. and are the estimated values of the lumped disturbance terms of vehicle speed control at time k + 1 in modes M1, M2, M3, and M4, respectively. and are the estimated values of the hydraulic pressure vectors of brake wheel cylinder group 3 at time k in modes M1, M2, M3, and M4, respectively. and are the estimated values of the hydraulic pressure vectors of brake wheel cylinder group 3 at time k + 1 in modes M1, M2, M3, and M4, respectively. and are the estimated values of the lumped disturbance vectors of brake wheel cylinder group 3 hydraulic pressure control at time k in modes M1, M2, M3, and M4, respectively. and are the estimated values of the lumped disturbance vectors of brake wheel cylinder group 3 hydraulic pressure control at time k + 1 in modes M1, M2, M3, and M4, respectively. and are the observer gain matrices.

[0135] Furthermore, in step S13, a vehicle speed prediction model for the vehicle in the fault mode is established, and the future state of the vehicle speed is predicted; among them, the one-step prediction equation of the vehicle speed prediction model is as follows:

[0136] M1:

[0137] M2:

[0138] M3:

[0139] M4:

[0140] Among them, is the one-step predicted value of the vehicle speed at the (k + 1)-th moment, and are the one-step predicted values of the hydraulic pressure vectors of the brake wheel cylinder group 3 at the (k + 1)-th moment in M1 mode, M2 mode, M3 mode, and M4 mode respectively. Further, the specific formula of the two-step prediction equation of the vehicle speed prediction model in the fault mode is as follows:

[0141] M1:

[0142] M2:

[0143] M3:

[0144] M4:

[0145] Among them, is the two-step predicted value of the vehicle speed, and are the two-step predicted values of the hydraulic pressure vectors of the brake wheel cylinder group 3 in M1 mode, M2 mode, M3 mode, and M4 mode respectively.

[0146] Further, the cost function for controlling the vehicle speed in the specified fault mode in step S14 has the following specific formula:

[0147] M1:

[0148] M2:

[0149] M3:

[0150] M4:

[0151] Among them, J F1 、J1 F1 and J2 F1 are the cost function for vehicle speed control, the vehicle speed error cost function, and the hydraulic pressure cost function in M1 mode respectively; J F2 、J1 F2and J2 F2 are the cost function, vehicle speed error cost function, and hydraulic pressure cost function for vehicle speed control in mode M2 respectively; J F3 , J1 F3 and J2 F3 are the cost function, vehicle speed error cost function, and hydraulic pressure cost function for vehicle speed control in mode M3; J F4 , J1 F4 and J2 F4 are the cost function, vehicle speed error cost function, and hydraulic pressure cost function for vehicle speed control in mode M4 respectively. and are the coefficient matrices of the hydraulic pressure cost function.

[0152] Furthermore, in the step S15, the cost function for optimizing vehicle speed control in the fault mode is used to directly obtain the optimal flow vector of the brake wheel cylinder group 3 and the optimal state vectors of the corresponding inlet valve group 2 and outlet valve group 4. The specific formula is as follows:

[0153] M1:

[0154] M2:

[0155] M3:

[0156] M4:

[0157] Among them, the solution methods for the optimization problem include but are not limited to the enumeration method and mixed integer programming.

[0158] The vehicle braking fault-tolerant predictive control method according to the embodiment of the present invention cancels the cascade control structure of the classical braking fault-tolerant control and the PWM generator module necessary for the classical PWM hydraulic pressure control, reduces the structural complexity and cost of the control system, and improves the dynamic performance of the control system; innovatively adopts the discrete extended state observation method to eliminate the influence of unknown parameters and uncertain disturbance terms, and improves the adaptability of the control system to complex environments. And the present invention can achieve precise fault-tolerant control of the vehicle braking system under the conditions of no cascade control structure and no PWM drive, and does not require accurate system model information, which is suitable for large-scale industrial promotion and application, and will accelerate the localization process of key vehicle components.

[0159] To implement the above embodiment, as Figure 4 shown, this embodiment also provides a vehicle braking fault-tolerant predictive control system, which includes a first vehicle speed control model module 741, a first vehicle speed prediction model module 744, and a first optimal state vector calculation module 746;

[0160] The first vehicle speed control model module 741 is used to determine whether the vehicle triggers stability control based on vehicle measurement data, and define the effective state vectors of the inlet valve group and the outlet valve group and the effective flow vector of the brake wheel cylinder group in the normal mode according to the judgment result that the vehicle does not trigger the brake fault tolerance control;

[0161] The first vehicle speed prediction model module 744 is used to predict the future state of the vehicle speed based on the first dynamic equation from the effective flow vector of the brake wheel cylinder group to the vehicle speed in the normal mode to obtain the first state prediction result;

[0162] The first optimal state vector calculation module 746 is used to obtain the first optimal flow vector of the brake wheel cylinder group and the first optimal state vectors of the corresponding inlet valve group and outlet valve group according to the cost function of vehicle speed control in the normal mode constructed based on the first state prediction result; and use the electronic hydraulic braking system to respond to the first optimal state vectors of the inlet valve group and the outlet valve group to perform brake fault tolerance control on the vehicle.

[0163] Further, the system further includes:

[0164] The second vehicle speed control model module 751 is used to perform state isolation on the fault oil circuit of the braking system and the inlet valve and the outlet valve of the corresponding oil circuit according to the judgment result that the vehicle triggers stability control to obtain a state isolation result; and obtain the effective state vectors of the inlet valve group and the outlet valve group and the effective flow vector of the brake wheel cylinder group in the fault mode based on the state isolation result;

[0165] The second vehicle speed prediction model module 754 is used to predict the future state of the vehicle speed based on the second dynamic equation from the effective flow vector of the brake wheel cylinder group to the vehicle speed in the fault mode to obtain the second state prediction result;

[0166] The second optimal state vector calculation module 756 is used to obtain the second optimal flow vector of the brake wheel cylinder group and the second optimal state vectors of the corresponding inlet valve group and outlet valve group according to the cost function of vehicle speed control in the fault mode constructed based on the second state prediction result, and use the electronic hydraulic braking system to respond to the second optimal state vectors to perform brake fault tolerance control on the vehicle.

[0167] Specifically, the system includes: a data processing unit 71, a fault-tolerant control trigger unit 72, a reference model unit 73, a conventional braking control unit 74, a first vehicle speed control model module 741, a first disturbance observation module 742, a second disturbance observation module 743, a first vehicle speed prediction model module 744, a first cost function module 745, a first optimal state vector calculation module 746, a fault braking control unit 75, a second vehicle speed control model module 751, a third disturbance observation module 752, a fourth disturbance observation module 753, a second vehicle speed prediction model module 754, a second cost function module 755, and a second optimal state vector calculation module 756.

[0168] Further, the above-mentioned data processing unit 71 is used to obtain vehicle state, braking system state, and fault information, and perform filtering processing on the measurement data.

[0169] Further, the above-mentioned fault-tolerant control trigger module 72 is used to determine whether the vehicle enters the braking fault-tolerant control stage.

[0170] Further, the above-mentioned reference model unit 73 is used to calculate the reference value of the vehicle speed.

[0171] Further, the above-mentioned conventional braking control unit 74 uses a predictive control method to achieve braking control of the vehicle under fault-free conditions.

[0172] Further, the above-mentioned first vehicle speed control model module 741 is used to construct a quantitative mathematical model of the switch states of the inlet valve group 2 and the outlet valve group 4 to the vehicle speed in the normal mode of the braking system.

[0173] Further, the above-mentioned first disturbance observation module 742 and the second disturbance observation module 743 use the discrete-time extended state observer method to estimate in real time the total disturbance term of the torque for vehicle speed control and the total disturbance term of the flow rate for hydraulic pressure control of the brake wheel cylinder group 3 in the normal mode of the braking system.

[0174] Further, the above-mentioned first vehicle speed prediction model module 744 is used to construct a one-step prediction equation and a two-step prediction equation for the vehicle speed in the normal mode of the braking system, and perform online prediction on the future state of the vehicle speed.

[0175] Further, the above-mentioned first cost function module 745 is used to formulate the cost function for vehicle speed control in the normal mode of the braking system.

[0176] Further, the above-mentioned first optimal state vector calculation module 746 obtains the optimal hydraulic pressure vector of the brake wheel cylinder group 3 at the current moment, as well as the optimal state vectors of the corresponding oil inlet valve group 2 and the oil outlet valve group 4 by optimizing the cost function of vehicle speed control in the normal mode of the braking system, so as to realize the vehicle braking control in the normal mode of the braking system.

[0177] Further, the above-mentioned fault braking control unit 75 adopts a predictive control method to realize the braking fault tolerance control of the vehicle under fault conditions.

[0178] Further, the above-mentioned second vehicle speed control model module 751 is used to construct a quantitative mathematical model of the switching states of the oil inlet valve group 2 and the oil outlet valve group 4 to the vehicle speed in the fault mode of the braking system.

[0179] Further, the above-mentioned third disturbance observation module 752 and the fourth disturbance observation module 753 adopt the method of discrete-time extended state observer to estimate in real time the lumped disturbance term of the torque for vehicle speed control and the lumped disturbance term of the flow rate for hydraulic pressure control of the brake wheel cylinder group 3 in the fault mode of the braking system.

[0180] Further, the above-mentioned second vehicle speed prediction model module 754 is used to construct a one-step prediction equation and a two-step prediction equation for the vehicle speed in the fault mode of the braking system, and perform an online prediction on the future state of the vehicle speed.

[0181] Further, the above-mentioned second cost function module 755 is used to formulate the cost function of vehicle speed control in the fault mode of the braking system.

[0182] Further, the above-mentioned second optimal state vector calculation module 756 obtains the optimal hydraulic pressure vector of the brake wheel cylinder group 3 at the current moment, as well as the optimal state vectors of the oil inlet valve group 2 and the oil outlet valve group 4 by optimizing the cost function of vehicle speed control in the fault mode of the braking system, so as to realize the braking fault tolerance control of the vehicle in the fault mode of the braking system.

[0183] The automotive braking fault tolerance prediction control system according to the embodiment of the present invention cancels the cascade control structure of the classical braking fault tolerance control and the PWM generator module necessary for the classical PWM hydraulic pressure control, reduces the structural complexity and cost of the control system, and improves the dynamic performance of the control system; innovatively adopts the method of discrete extended state observation to eliminate the influence of unknown parameters and uncertain disturbance terms, and improves the adaptability of the control system to complex environments. And the present invention can realize the precise fault tolerance control of the vehicle braking system under the conditions of no cascade control structure and no PWM drive, and does not require accurate system model information, is suitable for large-scale industrial promotion and application, and will accelerate the localization process of key vehicle components.

[0184] In the description of this specification, the descriptions referring to terms such as "one embodiment", "some embodiments", "examples", "specific examples", or "some examples", etc., mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0185] In addition, the terms "first" and "second" are used only for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise specifically defined.

Claims

1. An automotive braking fault-tolerant predictive control method, characterized in that, Including: Judging whether the vehicle triggers stability control based on vehicle measurement data, and defining the effective state vector of the inlet valve group and the outlet valve group and the effective flow vector of the brake wheel cylinder group in the normal mode according to the judgment result that the vehicle does not trigger brake fault control; Predicting the future state of the vehicle speed to obtain a first state prediction result based on the first dynamic equation from the effective flow vector of the brake wheel cylinder group to the vehicle speed in the normal mode; Obtaining the first optimal flow vector of the brake wheel cylinder group and the first optimal state vector of the corresponding inlet valve group and outlet valve group according to the cost function of vehicle speed control in the normal mode constructed based on the first state prediction result; Using the electronic hydraulic braking system to respond to the first optimal state vector of the inlet valve group and the outlet valve group to perform brake fault control on the vehicle; After judging whether the vehicle triggers stability control based on vehicle measurement data, the method further includes: Performing state isolation on the faulty oil circuit of the braking system and the inlet valve and outlet valve of the corresponding oil circuit according to the judgment result that the vehicle triggers stability control to obtain a state isolation result; Obtaining the effective state vector of the inlet valve group and the outlet valve group and the effective flow vector of the brake wheel cylinder group in the fault mode based on the state isolation result; Predicting the future state of the vehicle speed to obtain a second state prediction result according to the second dynamic equation from the effective flow vector of the brake wheel cylinder group to the vehicle speed in the fault mode; Obtaining the second optimal flow vector of the brake wheel cylinder group and the second optimal state vector of the corresponding inlet valve group and outlet valve group according to the cost function of vehicle speed control in the fault mode constructed based on the second state prediction result, and using the electronic hydraulic braking system to respond to the second optimal state vector to perform brake fault control on the vehicle.

2. The method according to claim 1, wherein Before judging whether the vehicle triggers stability control based on the vehicle measurement data, the method further includes: Obtaining the vehicle measurement data; wherein, the vehicle measurement data includes vehicle state, braking system state and fault information; Performing filtering processing on the vehicle measurement data to obtain filtered data.

3. The method according to claim 1, characterized in that, Predicting the future state of the vehicle speed to obtain a first state prediction result based on the first dynamic equation from the effective flow vector of the brake wheel cylinder group to the vehicle speed in the normal mode, including: Constructing the first dynamic equation from the effective flow vector of the brake wheel cylinder group to the vehicle speed in the normal mode; Based on the first dynamic equation, real-time estimating the first lumped disturbance term of vehicle speed control and brake wheel cylinder hydraulic pressure control in the normal mode; wherein, the first lumped disturbance term includes real-time estimating the torque lumped disturbance term of vehicle speed control and the flow lumped disturbance term of brake wheel cylinder hydraulic pressure control in the normal mode of the braking system by using a discrete-time extended state observer; Establishing a vehicle speed prediction model of the vehicle in the normal mode based on the first lumped disturbance term, and predicting the future state of the vehicle speed to obtain a first state prediction result.

4. The method according to claim 1, wherein Predicting the future state of the vehicle speed to obtain a second state prediction result according to the second dynamic equation from the effective flow vector of the brake wheel cylinder group to the vehicle speed in the fault mode, including: Construct a second dynamic equation for the effective flow rate vector of the brake wheel cylinder group in the fault mode to the vehicle speed; Based on the second dynamic equation, estimate in real time a second lumped disturbance term for vehicle speed control and hydraulic pressure control of the brake wheel cylinder group in the fault mode; wherein, the second lumped disturbance term includes a moment lumped disturbance term for vehicle speed control and a flow rate lumped disturbance term for hydraulic pressure control of the brake wheel cylinder group estimated in real time by using a discrete-time extended state observer in the fault mode of the braking system; Based on the second lumped disturbance term, establish a vehicle speed prediction model in the fault mode and predict the future state of the vehicle speed to obtain a second state prediction result.

5. A vehicle braking fault-tolerant prediction control system, characterized in that, It includes: A first vehicle speed control model module for determining whether the vehicle triggers stability control based on vehicle measurement data, and defining the effective state vectors of the inlet valve group and the outlet valve group and the effective flow rate vector of the brake wheel cylinder group in the normal mode according to the judgment result that the vehicle does not trigger brake fault tolerance control; A first vehicle speed prediction model module for predicting the future state of the vehicle speed based on the first dynamic equation of the effective flow rate vector of the brake wheel cylinder group to the vehicle speed constructed in the normal mode to obtain a first state prediction result; A first optimal state vector calculation module for obtaining the first optimal flow rate vector of the brake wheel cylinder group and the first optimal state vectors of the corresponding inlet valve group and outlet valve group according to the cost function of vehicle speed control in the normal mode constructed based on the first state prediction result; And use the electronic hydraulic braking system to respond to the first optimal state vectors of the inlet valve group and the outlet valve group to perform brake fault tolerance control on the vehicle; The system further includes: A second vehicle speed control model module for isolating the states of the fault oil circuit of the braking system and the inlet valve and the outlet valve of the corresponding oil circuit according to the judgment result that the vehicle triggers stability control to obtain a state isolation result; and obtaining the effective state vectors of the inlet valve group and the outlet valve group and the effective flow rate vector of the brake wheel cylinder group in the fault mode based on the state isolation result; A second vehicle speed prediction model module for predicting the future state of the vehicle speed based on the second dynamic equation of the effective flow rate vector of the brake wheel cylinder group to the vehicle speed in the fault mode to obtain a second state prediction result; A second optimal state vector calculation module for obtaining the second optimal flow rate vector of the brake wheel cylinder group and the second optimal state vectors of the corresponding inlet valve group and outlet valve group according to the cost function of vehicle speed control in the fault mode constructed based on the second state prediction result, and using the electronic hydraulic braking system to respond to the second optimal state vectors to perform brake fault tolerance control on the vehicle.

6. The system according to claim 5, wherein Before the first vehicle speed control model module, it further includes: a data processing unit for: Obtain the vehicle measurement data; wherein, the vehicle measurement data includes vehicle state, braking system state and fault information; Perform filtering processing on the vehicle measurement data to obtain filtered data.

7. The system according to claim 5, characterized in that, After the first vehicle speed control model module, it further includes a first disturbance observation module and a second disturbance observation module; The first disturbance observer module is used to estimate in real time the lumped disturbance term of the torque for vehicle speed control in the normal mode of the braking system by means of a discrete-time extended state observer; and, The second disturbance observer module is used to estimate in real time the lumped disturbance term of the flow rate for the hydraulic pressure control of the brake wheel cylinder group in the normal mode of the braking system by means of a discrete-time extended state observer.

8. The system according to claim 5, characterized in that After the second vehicle speed control model module, a third disturbance observer module and a fourth disturbance observer module are further included. The third disturbance observer module is used to estimate in real time the lumped disturbance term of the torque for vehicle speed control in the fault mode of the braking system by means of a discrete-time extended state observer; and, The fourth disturbance observer module is used to estimate in real time the lumped disturbance term of the flow rate for the hydraulic pressure control of the brake wheel cylinder group in the fault mode of the braking system by means of a discrete-time extended state observer.

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