Anti-lock braking system control strategy design method based on electronic mechanical braking system

Abstract

The invention discloses an anti-lock braking system control strategy design method based on an electronic mechanical braking system, and belongs to the field of automobile braking. The control strategy design method of the electronic mechanical braking system and the anti-lock braking system is integrated. According to the anti-lock braking system, the motor is controlled, the braking pressure of the wheels is actively adjusted, then the optimal slip rate is maintained, the wheels continuously obtain the peak longitudinal adhesive force and the large lateral adhesive force, and then the braking distance is shortened. In the strategy design method, the anti-lock braking system controller adopts the fuzzy control strategy based on the optimal slip rate of the wheels, real-time online closed-loop control of the optimal slip rate and the braking pressure is achieved by controlling the current variation of the execution motor of the electronic mechanical braking system, and the method has the advantages of being high in response speed, high in control precision, high in stability, high in reliability and the like. The efficiency is high.

Description

Technical Field

[0001] The invention belongs to the field of automobile braking, and in particular relates to an anti-lock braking system (ABS) control strategy design method based on an electronic mechanical braking system. Background Art

[0002] At present, intelligent and electronic technologies are deeply integrated with the automobile industry, and the electromechanical braking system (Electromechanical Braking System) has become the development focus of the automobile braking industry. The electromechanical braking system replaces the traditional hydraulic pipeline with signal lines and related electrical integrated components. The electronic pedal sensor senses the braking demand, and the controller outputs the braking force by controlling the motor. The compact structure is easy to integrate into the vehicle communication technology, and it is easy to combine with the anti-lock braking system (ABS). As an active safety device, the anti-lock braking system ABS currently mainly controls the wheel slip rate. The anti-lock braking system ABS based on the electromechanical braking system controls the motor and actively adjusts the wheel braking pressure to maintain the optimal slip rate, so that the wheel can continuously obtain the peak longitudinal adhesion and large lateral adhesion, shortening the braking distance while improving the braking stability.

[0003] In recent years, design methods for electronic mechanical brake system controllers have emerged in an endless stream, and a large amount of research has been done at home and abroad. For example, China Patent Publication No. CN116853204A, published on 2023-10-27, discloses an electronic mechanical brake control system and its control method. The method achieves redundant braking by setting a main brake control unit and an auxiliary brake control unit. It also has the function of redundant power supply, thereby improving braking reliability. Another example is the Chinese patent publication number CN111497803A, published on 2020-08-07. This invention patent discloses a hub motor electronic mechanical composite brake anti-lock braking system ABS control method and system. This method detects whether the brake pedal is pressed by setting a supercapacitor energy management unit, and determines whether the anti-lock braking system ABS controller controls the electronic mechanical braking system controller to perform mechanical braking according to the power of the supercapacitor; but the electronic mechanical braking system actuators in these invention patents mostly have many mechanical parts and complex structures, and the logic threshold control algorithm widely used in these invention patents cannot ensure that the wheel slip rate is at the optimal slip rate, that is, it cannot exert the best braking performance. Based on the above discussion, the present invention proposes a control strategy design method for an anti-lock braking system ABS based on an electronic mechanical braking system, including hardware design and control algorithm design, which makes the structure more compact and simple, improves the braking efficiency, and can achieve real-time online closed-loop control of the optimal slip rate and braking pressure. Summary of the invention

[0004] In order to solve the deficiencies in the prior art, the present invention discloses a control strategy design method for an anti-lock braking system (ABS) based on an electronic mechanical braking system.

[0005] The present invention provides a control strategy design method for an anti-lock braking system based on an electronic mechanical braking system, comprising the following steps:

[0006] 1) Overall structural design of actuator of electromechanical brake system;

[0007] 2) Overall framework design of the control system of the electronic mechanical braking system;

[0008] 3) Establish a mathematical model of the electronic mechanical brake system actuator and a vehicle dynamics system model;

[0009] 4) Establishment of fuzzy controller for anti-lock braking system of vehicles based on electronic mechanical braking system,

[0010] The controller of the anti-lock braking system adopts a control strategy based on the optimal slip rate of the wheel. It realizes real-time online closed-loop control of the optimal slip rate and brake pressure by controlling the current change of the electric mechanical braking system execution motor. By using fuzzy control, predicting and processing various nonlinear problems, through precise calculation and analysis, and combining practical experience,

[0011] To change and optimize the control system.

[0012] According to the control strategy design method of the anti-lock braking system based on the electronic mechanical braking system,

[0013] In step 4), when designing the controller, a single input error e can be taken as the controlled quantity, or a double input, namely the error e and the rate of change of the error ec, can be taken as the controlled quantity, or a three-input, namely e, ec, and ecc (the rate of change of ec), can be taken as the controlled quantity. According to the number of input quantities, a one-dimensional, two-dimensional, or three-dimensional controller is used. The fuzzy controller adopts a two-dimensional controller. The input quantity is the deviation between the optimal slip rate and the actual slip rate and the rate of change of the deviation. The output quantity is the current change value ΔI of the actuator motor of the electronic mechanical brake system;

[0014] Among them, the rate of change of deviation ec is defined as:

[0015]

[0016] Where ec is the rate of change of the deviation;

[0017] T is the sampling interval;

[0018] After selecting the input and output variables of the fuzzy controller, determine the quantization factor, proportional factor and fuzzy domain; the quantization factor and proportional factor are called conversion coefficients, which are used to enlarge or reduce the value range of the input signal to meet the requirements of the fuzzy domain; the fuzzy domain is the value range of the controller calculation, and the physical domain is the range of changes produced by the actual input quantity. The quantization factor, proportional factor and fuzzy domain variables need to be determined according to the specific configuration and requirements; if the physical domain of the input quantity is X = [-a, a], the fuzzy domain N j =[-n j ,n j ], quantization factor k j =n j / a, where:

[0019]

[0020] The input variable x can always be transformed to obtain n∈N within the normal value range. j =[-n j ,n j ], that is, n≤n j .

[0021] After determining the above three variables, it is necessary to select fuzzy language variables. The present invention determines the deviation and the rate of change of the deviation as word set A, and the current change value determines the word set B. The content and meaning of word sets A and B can be defined by oneself; the membership function of each language variable should be determined later, wherein the fuzzy language value represents a fuzzy subset, and the fuzzy subset and its domain must correspond to each other, so it is described by the membership function. The selection of the membership function type does not require a unified standard, and can be the same or different. The membership functions of e and ec are proportionally distributed, and the membership function of the current change value ΔI exerts more control near the zero point;

[0022] After completing the above steps, the fuzzy control rules should be established, the fuzzy control state should be analyzed, and the fuzzy control state should be analyzed according to the change trend of the deviation e and the rate of change of the deviation ec. The purpose is to formulate rules to eliminate system errors so as to maintain the system slip rate at the optimal slip rate; discretize e and ec, and record the input quantities as ei and eci respectively, then:

[0023] e i =s i0 -s i #(3)

[0024]

[0025] In the formula, s i0 ——target slip rate;

[0026] s i ——actual slip rate;

[0027] Δt——the time interval between two sampling points;

[0028] k——current sampling point;

[0029] (k-1)——the previous sampling point;

[0030] Finally, fuzzy reasoning and clarification are performed, that is, the fuzzy equation is solved based on the input fuzzy set using the fuzzy inclusion relationship, and the Mandani method is used for fuzzy reasoning to obtain the fuzzy reasoning output surface, so that any pair of input quantities can have a corresponding clear output quantity, and the control system can be realized in correspondence with each specific value.

[0031] According to the control strategy design method of the anti-lock braking system based on the electronic mechanical braking system,

[0032] The overall structure of the actuator includes a torque motor, a deceleration and torque-increasing device, and a motion conversion device. The torque motor adopts a permanent magnet brushless DC torque motor, the deceleration and torque-increasing device adopts a planetary gear reducer, and there are three external meshings between each level of planetary gear and the sun gear, and the angle between the two is designed to be 120 degrees. The motion conversion device adopts a ball screw.

[0033] According to the control strategy design method of the anti-lock braking system based on the electronic mechanical braking system,

[0034] The overall framework of the control system includes an integrated braking intention recognition module, a response control module and an anti-lock braking system ABS control module. The braking intention recognition module integrates an electronic pedal sensor and a central control unit. The driver transmits the force applied to the pedal to the electronic pedal, and the change of the sensor signal on the electronic pedal indirectly reflects the braking intention.

[0035] In the response control module, the controller acts on the actuator torque motor, which eliminates the brake gap and accurately outputs the braking force. After the braking starts, the torque motor current and speed are controlled. After receiving the brake signal, the torque motor quickly eliminates the gap and moves towards the target braking force required by the driver.

[0036] In the anti-lock braking system control module, the anti-lock braking system makes the wheels at the maximum longitudinal adhesion coefficient and the larger lateral adhesion coefficient. When the anti-lock braking system is enabled, the actuator output braking force is corrected in a biased manner, and the wheel slip rate is set to the desired amount. The desired amount can be obtained from the road surface optimal slip rate online identification system, so that the wheel slip rate can be maintained after reaching the desired amount during braking.

[0037] According to the control strategy design method of the anti-lock braking system based on the electronic mechanical braking system,

[0038] The mathematical model of the electronic mechanical braking system actuator and the vehicle dynamics system model are established. The mathematical model of the electronic mechanical braking system actuator includes four parts: permanent magnet brushless DC torque motor model, permanent magnet brushless DC torque motor friction model, planetary gear reducer model and ball screw model; the vehicle dynamics system model includes a single wheel model and a tire model; among them, the single wheel model mainly considers the force conditions during wheel braking when it is established, and the tire model uses the Burckhardt model.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] 1. The design scheme of the electronic mechanical brake system actuator given in this patent includes the selection of torque motor, deceleration and torque increase device, and motion conversion device, which makes the structure of the actuator more compact, solves the lag problem of braking response, improves braking efficiency, and meets the braking intensity requirements.

[0041] 2. In the anti-lock braking system ABS control strategy design method based on the electronic mechanical braking system described in this patent, all anti-lock braking system ABS controllers adopt a fuzzy control strategy based on the optimal slip rate of the wheel, and achieve real-time online closed-loop control of the optimal slip rate and braking pressure by controlling the current change of the electronic mechanical braking system execution motor. It has the advantages of fast response speed, high control accuracy, strong stability and high efficiency, and has guiding significance for the design of subsequent control strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The present invention will be further described below in conjunction with the accompanying drawings, in which:

[0043] Figure 1 A flow chart of the control strategy design method of the anti-lock braking system ABS based on the electronic mechanical braking system of the present invention;

[0044] Figure 2 The flowchart of the structure design of the actuator of the electronic mechanical brake system in the present invention;

[0045] Figure 3 The overall framework diagram of the control system of the electronic mechanical braking system of the present invention; DETAILED DESCRIPTION

[0046] The present invention is described in detail below in conjunction with the accompanying drawings:

[0047] See also Figure 1 The method for designing an anti-lock braking system (ABS) control strategy based on an electronic mechanical braking system described in the present invention mainly includes the following steps: overall structural design of an electronic mechanical braking system actuator, overall framework design of an electronic mechanical braking system control system, establishment of a mathematical model of an electronic mechanical braking system actuator and a vehicle dynamics system model, and establishment of an anti-lock braking system (ABS) fuzzy controller based on an electronic mechanical braking system vehicle. These steps will be described in detail below.

[0048] The first step is the overall structural design of the electromechanical brake system actuator.

[0049] As the core component of the wheel brake module and the power element that directly performs braking, the performance of the electronic mechanical brake system actuator directly determines the braking efficiency of the vehicle. Therefore, the basic braking efficiency of the electronic mechanical brake system actuator should be fully considered during design so that it can transmit the braking force in a timely, efficient and accurate manner.

[0050] The electronic mechanical brake system actuator in the present invention mainly includes a torque motor, a deceleration and torque increase device and a motion conversion device, so it is necessary to select solutions for these three parts respectively;

[0051] The torque motor of the actuator of the electronic mechanical brake system is used as a power source to output high-speed, low-torque force; in the present invention, a permanent magnet brushless DC torque motor is used in the selection of the torque motor, which has large torque when turned on, strong overload bearing capacity, simple and convenient speed change, and safe and reliable performance in all aspects; in addition, it is small in size, low in noise, high in efficiency, and light in weight, which can also ensure the maximum service life;

[0052] The deceleration and torque increasing device of the actuator of the electronic mechanical brake system decelerates and increases the torque of the force output by the torque motor, and outputs a force with low speed and high torque; the present invention adopts a planetary gear reducer, and there are three external meshings between the planetary gears and the sun gear at each level, and the angle between the two is designed to be 120 degrees, which has the characteristics of large transmission ratio, small size and smooth movement;

[0053] The motion conversion device of the actuator of the electronic mechanical brake system converts the transmitted rotational motion into axial linear motion, pushing the brake block to clamp the brake disc to complete the braking; the motion conversion device of the present invention adopts a ball screw, which can obtain a large axial thrust with a small torque, and the motion is reversible, and has the advantages of high precision, stable operation and high reliability;

[0054] The second step is to design the overall framework of the control system based on the electronic mechanical braking system

[0055] The present invention integrates a braking intention recognition module, a response control module and an anti-lock braking system ABS control module on the electronic mechanical braking system, and builds an overall principle framework of a control system based on the electronic mechanical braking system according to the control characteristics of each module;

[0056] The braking intention recognition module integrates the electronic pedal sensor signal collection of the electronic mechanical braking system and the central control unit to analyze and make decisions on the sensor signal and distribute the braking force at the same time; the driver's braking intention is transmitted to the electronic pedal through the magnitude of the force acting on the pedal, and the change of the sensor signal on the electronic pedal indirectly reflects the braking intention. The process of the central control unit analyzing the signal is the embodiment of the braking intention recognition process;

[0057] In the response control module, the electronic mechanical brake system controller acts on the torque motor of the electronic mechanical brake system actuator to achieve rapid clearance elimination and accurate output of braking force after the start of braking, which is conducive to shortening the braking distance. The realization of this process requires the design of the control of the torque motor current, speed, etc. after the start of braking. After receiving the braking signal, the torque motor quickly eliminates the gap and moves towards the target braking force required by the driver, which is the process of the response control module working;

[0058] In the anti-lock braking system ABS control module, the anti-lock braking system ABS makes the wheels at the maximum longitudinal adhesion coefficient and the largest lateral adhesion coefficient, achieving the shortest braking distance and better braking stability; when the anti-lock braking system ABS is enabled, the actuator output braking force is corrected in a biased manner, and the wheel slip rate is set to the desired amount, which can be obtained from the road surface optimal slip rate online identification system. Through the designed control algorithm, the wheel slip rate is always maintained after reaching the desired amount during braking. The above is the working process of the anti-lock braking system ABS control module;

[0059] The third step is to establish the mathematical model of the electronic mechanical brake system actuator and the vehicle dynamics system model

[0060] The mathematical model of the electronic mechanical brake system actuator includes four parts: permanent magnet brushless DC torque motor model, permanent magnet brushless DC torque motor friction model, planetary gear reducer model and ball screw model. In order to improve the accuracy of subsequent simulation of the electronic mechanical brake system actuator, the friction of the motor must be considered, so it is necessary to establish a permanent magnet brushless DC torque motor friction model. The vehicle dynamics system model includes a single wheel model and a tire model. When establishing the single wheel model, the force condition of the wheel during braking is mainly considered, and the tire model uses the Burckhardt model.

[0061] The fourth step is to establish the fuzzy controller of the anti-lock braking system ABS based on the electronic mechanical braking system vehicle

[0062] Since the present invention is mainly aimed at the control strategy design of the anti-lock braking system ABS control module, the control strategy of the braking intention recognition module and the response control module will not be repeated here; the anti-lock braking system ABS controller in the present invention adopts a control strategy based on the optimal slip rate of the wheel, and realizes the real-time online closed-loop control of the optimal slip rate and braking pressure by controlling the current change of the execution motor of the electronic mechanical braking system;

[0063] By using fuzzy control, various complex nonlinear problems can be predicted and handled more accurately. It can change and optimize the control system through accurate calculation and analysis, combined with practical experience, especially when dealing with complex nonlinear problems such as anti-lock braking system ABS, which is more flexible and reliable;

[0064] When designing a controller, a single input error e can be taken as the controlled quantity, or a double input, namely the error e and the rate of change of the error ec, can be taken as the controlled quantity, or a three-input, namely e, ec, ecc (rate of change of ec), can be taken as the controlled quantity. According to the number of input quantities, it corresponds to a one-dimensional, two-dimensional, or three-dimensional controller. The two-dimensional controller has a better control effect than the one-dimensional controller. Although the three-dimensional controller has a more precise control quantity and better dynamic characteristics, its complex structure increases the amount of inference calculation and time. Therefore, the two-dimensional controller is relatively uncomplicated but can obtain stable and accurate control characteristics, and has become a controller widely used in fuzzy control at present; the fuzzy controller designed in the present invention adopts a two-dimensional controller, the input quantity is the deviation between the optimal slip rate and the actual slip rate and the rate of change of the deviation, and the output quantity is the current change value ΔI of the actuator motor of the electronic mechanical braking system;

[0065] Among them, the rate of change of deviation ec is defined as:

[0066]

[0067] Where ec is the rate of change of the deviation;

[0068] T is the sampling interval;

[0069] After selecting the input and output variables of the fuzzy controller, determine the quantization factor, proportional factor and fuzzy domain; the quantization factor and proportional factor are called conversion coefficients, which enlarge or reduce the value range of the input signal to meet the requirements of the fuzzy domain; the fuzzy domain is the value range of the controller calculation, and the physical domain is the variation range of the actual input quantity, which cannot be directly applied to the calculation of fuzzy control. In order to convert the physical domain into the corresponding fuzzy domain, the quantization factor conversion is required; the quantization factor, proportional factor and fuzzy domain variables need to be determined according to the specific configuration and requirements; if the physical domain of the input quantity is X = [-a, a], the fuzzy domain N j =[-n j ,n j ], quantization factor k j =n j / a, where:

[0070]

[0071] The input variable x can always be transformed to obtain n∈N within the normal value range. j =[-n j ,n j ], that is, n≤n j .

[0072] After determining the above three variables, it is necessary to select fuzzy language variables. The present invention determines the deviation and the rate of change of the deviation as word set A, and the current change value determines the word set B. The content and meaning of word sets A and B can be defined by oneself; the membership function of each language variable should be determined later, wherein the fuzzy language value represents a fuzzy subset, and the fuzzy subset and its domain must correspond to each other, so it is described by the membership function. The selection of the membership function type does not require a unified standard, and can be the same or different. The membership functions of e and ec are proportionally distributed, and the membership function of the current change value ΔI applies more control near the zero point to ensure fine control;

[0073] After completing the above steps, the fuzzy control rules should be established, the fuzzy control state should be analyzed, and the fuzzy control state should be analyzed according to the change trend of the deviation e and the rate of change of the deviation ec. The purpose is to formulate rules to eliminate system errors so as to maintain the system slip rate at the optimal slip rate; discretize e and ec, and record the input quantities as ei and eci respectively, then:

[0074] e i =s i0 -s i (3)

[0075]

[0076] In the formula, s i0 ——target slip rate;

[0077] s i ——actual slip rate;

[0078] Δt——the time interval between two sampling points;

[0079] k——current sampling point;

[0080] (k-1)——the previous sampling point;

[0081] Finally, fuzzy reasoning and clarification are performed, that is, the fuzzy equation is solved based on the input fuzzy set using the fuzzy inclusion relationship, and the Mandani method is used for fuzzy reasoning to obtain the fuzzy reasoning output surface, so that any pair of input quantities can have a corresponding clear output quantity, and the control system can be realized in correspondence with each specific value.

[0082] After completing the above steps, fuzzy control rules should be established. The number of control rules is related to the number of fuzzy language subsets. Finally, fuzzy reasoning and clarification are required, that is, the fuzzy equation is solved based on the input fuzzy set using the fuzzy inclusion relationship. In the present invention, since the reasoning process is relatively long, the Mandani method is used for fuzzy reasoning to obtain the fuzzy reasoning output surface, so that any pair of input quantities can have a clear output quantity corresponding to it, and the control system can be controlled accordingly for each specific value.

Claims

1. A control strategy design method for an anti-lock braking system based on an electronic mechanical braking system, characterized in that: The following steps are included: 1) Overall structural design of actuator of electromechanical brake system; 2) Overall framework design of the control system of the electronic mechanical braking system; 3) Establish the mathematical model of the electronic mechanical brake system actuator and the vehicle dynamics system model; 4) Establishment of fuzzy controller for anti-lock braking system of vehicles based on electronic mechanical braking system, The controller of the anti-lock braking system adopts a control strategy based on the optimal wheel slip rate. It realizes real-time online closed-loop control of the optimal slip rate and braking pressure by controlling the current change of the electric mechanical braking system's actuator motor. It predicts and handles various nonlinear problems through the use of fuzzy control, and changes and optimizes the control system through precise calculation and analysis, as well as practical experience.

2. The anti-lock braking system control strategy design method based on the electronic mechanical braking system according to claim 1 is characterized in that: In step 4), when designing the controller, a single input error e can be taken as the controlled quantity, or a double input, namely the error e and the rate of change of the error ec, can be taken as the controlled quantity, or a three-input, namely e, ec, and ecc (the rate of change of ec), can be taken as the controlled quantity. According to the number of input quantities, it corresponds to a one-dimensional, two-dimensional, or three-dimensional controller. The fuzzy controller uses a two-dimensional controller. The input quantity is the deviation between the optimal slip rate and the actual slip rate and the rate of change of the deviation. The output quantity is the current change value ∆𝐼 of the actuator motor of the electronic mechanical brake system; Among them, the rate of change of deviation ec is defined as: ， Where ec is the rate of change of the deviation; T is the sampling interval; After selecting the input and output variables of the fuzzy controller, determine the quantization factor, proportional factor and fuzzy domain; the quantization factor and proportional factor are called conversion coefficients, which are used to enlarge or reduce the value range of the input signal to meet the requirements of the fuzzy domain; the fuzzy domain is the value range of the controller calculation, and the physical domain is the range of changes produced by the actual input quantity. The quantization factor, proportional factor and fuzzy domain variables need to be determined according to the specific configuration and requirements; if the physical domain of the input quantity is X=[-a,a], the fuzzy domain N j =[-n j ,n j ], quantization factor k j =n j / a, where: ， The input variable 𝑥 can always be guaranteed to be within the normal value range after transformation. ,Right now , After determining the above three variables, it is necessary to select fuzzy language variables. The present invention determines the deviation and the rate of change of the deviation as word set A, and the current change value determines the word set B. The content and meaning of word sets A and B can be defined by oneself; the membership function of each language variable should be determined later, wherein the fuzzy language value represents a fuzzy subset, and the fuzzy subset and its domain must correspond to each other, so it is described by the membership function. The selection of the membership function type does not require a unified standard, and can be the same or different. The membership functions of e and ec are proportionally distributed, and the membership function of the current change value ∆𝐼 exerts more control near the zero point; After completing the above steps, the fuzzy control rules should be established and the fuzzy control state should be analyzed. The fuzzy control state should be analyzed according to the changing trend of the deviation 𝑒 and the rate of change of the deviation 𝑒𝑐. The purpose is to formulate rules to eliminate system errors so as to maintain the system slip rate at the optimal slip rate. Discretize 𝑒 and 𝑒𝑐, and record the input quantities as 𝑒𝑖 and 𝑒𝑐𝑖 respectively, then: ， ， In the formula, ——target slip rate; ——actual slip rate; ——Time interval between two sampling points; k——current sampling point; (k-1)——the previous sampling point; Finally, fuzzy reasoning and clarification are performed, that is, the fuzzy equation is solved based on the input fuzzy set using the fuzzy inclusion relationship, and the Mandani method is used for fuzzy reasoning to obtain the fuzzy reasoning output surface, so that any pair of input quantities can have a corresponding clear output quantity, and the control system can be realized in correspondence with each specific value.

3. The control strategy design method of the anti-lock braking system based on the electronic mechanical braking system according to claim 1 is characterized in that: The overall structure of the actuator includes a torque motor, a deceleration and torque-increasing device, and a motion conversion device. The torque motor adopts a permanent magnet brushless DC torque motor, the deceleration and torque-increasing device adopts a planetary gear reducer, and there are three external meshings between each level of planetary gear and the sun gear, and the angle between the two is designed to be 120 degrees. The motion conversion device adopts a ball screw.

4. The anti-lock braking system control strategy design method based on the electronic mechanical braking system according to claim 1 is characterized in that: The overall framework of the control system includes an integrated braking intention recognition module, a response control module and an anti-lock braking system ABS control module. The braking intention recognition module integrates an electronic pedal sensor and a central control unit. The driver transmits the force applied to the pedal to the electronic pedal, and the change of the sensor signal on the electronic pedal indirectly reflects the braking intention. In the response control module, the controller acts on the actuator torque motor, which eliminates the brake gap and accurately outputs the braking force. After the braking starts, the torque motor current and speed are controlled. After receiving the brake signal, the torque motor quickly eliminates the gap and moves towards the target braking force required by the driver. In the anti-lock braking system control module, the anti-lock braking system makes the wheels at the maximum longitudinal adhesion coefficient and the larger lateral adhesion coefficient. When the anti-lock braking system is enabled, the actuator output braking force is corrected in a biased manner, and the wheel slip rate is set to the desired amount. The desired amount can be obtained from the road surface optimal slip rate online identification system, so that the wheel slip rate can be maintained after reaching the desired amount during braking.

5. The anti-lock braking system control strategy design method based on the electronic mechanical braking system according to claim 1 is characterized in that: The mathematical model of the electronic mechanical braking system actuator and the vehicle dynamics system model are established. The mathematical model of the electronic mechanical braking system actuator includes four parts: permanent magnet brushless DC torque motor model, permanent magnet brushless DC torque motor friction model, planetary gear reducer model and ball screw model; the vehicle dynamics system model includes a single wheel model and a tire model; among them, the single wheel model mainly considers the force conditions during wheel braking when it is established, and the tire model uses the Burckhardt model.

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