Vehicle braking system and control method thereof

Abstract

The present invention provides a vehicle braking system and a control method thereof, belonging to the field of braking control technology; the modules include: a data acquisition module: according to the vehicle structure diagram, corresponding parameter type sensors are configured at different positions of the vehicle and vehicle parameter data is obtained in real time; a data processing module: pre-processing the vehicle parameter data of any parameter type, and classifying and fusing them according to the parameter type to obtain vehicle state data of different state types; a control decision module: according to the control algorithm, the control strength of the vehicle is obtained in combination with the vehicle state data; a signal execution module: generating a control signal of the vehicle according to the control strength, and controlling the actuator of the braking system of the vehicle according to the electronic control unit; a feedback module: judging the braking completion of the vehicle according to the braking effect of the actuator and dynamically adjusting the control decision. Improve safety, performance and braking efficiency, and optimize braking control.

Description

Technical Field

[0001] The present invention relates to the technical field of brake control, and in particular to a vehicle brake system and a control method thereof. Background Art

[0002] At present, with the widespread use of big data technology, electronic control technology has gradually been applied to the braking system, forming intelligent control methods such as electronic parking brake (EPB) and electronic stability program (ESP). However, vehicles mainly rely on mechanical braking systems, which have limited braking effects and are prone to wheel locking, resulting in reduced controllability.

[0003] Therefore, the present invention proposes a vehicle braking system and a control method thereof. Summary of the invention

[0004] The present invention provides a vehicle braking system and a control method thereof, which are used to obtain real-time parameter data of the vehicle, obtain control signals according to a control algorithm, generate control decisions for different actuators, and perform feedback dynamic adjustment after the decisions are executed.

[0005] In one aspect, the present invention provides a vehicle braking system and a control method thereof, comprising:

[0006] Data acquisition module: According to the vehicle structure diagram, corresponding parameter type sensors are configured at different locations of the vehicle and vehicle parameter data is acquired in real time;

[0007] Data processing module: pre-processes the vehicle parameter data of any parameter type, and classifies and fuses them according to the parameter type to obtain vehicle status data of different status types;

[0008] Control decision module: according to the control algorithm, combined with the vehicle status data, obtains the control strength of the vehicle;

[0009] A signal execution module: generates a control signal of the vehicle according to the control force, and controls the actuator of the braking system of the vehicle according to the electronic control unit;

[0010] Feedback module: According to the braking effect of the actuator, it determines the braking completion status of the vehicle and dynamically adjusts the control decision.

[0011] On the other hand, the data acquisition module includes:

[0012] Vehicle structure unit: obtain the vehicle structure diagram of the target research vehicle and obtain all functional components of the target research vehicle;

[0013] Sensor matching unit: According to the target key parameters of vehicle braking, the corresponding functional components are matched, and the corresponding sensor type is obtained based on the mapping table of key parameters-sensor type.

[0014] On the other hand, the data acquisition module further includes:

[0015] Sensor configuration unit: configure a unique first number for any sensor, configure a unique second number for any functional component, and install the sensor configuration to the installation position of the corresponding functional component according to the corresponding relationship between the sensor and the functional component;

[0016] Sensor interface: Connect the sensor to the vehicle acquisition system through an interface, and transmit the raw data acquired by the sensor in real time to the vehicle acquisition system through the interface to obtain vehicle parameter data.

[0017] On the other hand, the data processing module includes:

[0018] Interface data unit: obtains vehicle parameter data of any parameter type according to the interface, and performs structured conversion on the vehicle parameter data to obtain structured parameter data;

[0019] Standardization unit: using statistical methods to detect abnormal values ​​of the structured parameter data, removing the abnormal values ​​and performing standardization to obtain standard parameter data;

[0020] Classification unit: according to any state type, filter all parameter type names contained in the state type;

[0021] ; Among them, Sym represents the functional similarity between the current state type and any parameter type name, represents the preset weight coefficient of the ith function of the parameter type name, Indicates the preset matching degree between the ith function of the parameter type name and the current state type, n indicates that the parameter type name has a total of n function values, Represents the loss function based on the loss coefficient r1;

[0022] The parameter type names whose matching degree with the state type is greater than a preset threshold are classified into the state type to obtain vehicle state data of the state type.

[0023] On the other hand, the signal execution module includes:

[0024] Control algorithm unit: formulates control targets according to the vehicle's operating standards, and obtains control strength based on the control algorithm combined with vehicle status data;

[0025] ;in, represents the control strength of the control output of the current category, t represents the control output of the current category, represents the variance of the j-th vehicle status data. There are m types of vehicle status data in total. represents the control target threshold, Indicates the cumulative integral of the error of the current control output;

[0026] Finally, the control strength of all control outputs of the vehicle is obtained.

[0027] On the other hand, the signal execution module includes:

[0028] Control signal unit: Substitute the control force into the vehicle control decision model to generate a control signal corresponding to the control output;

[0029] Braking unit: matches all control signals to corresponding vehicle equipment, connects the control signal unit and vehicle equipment according to the electronic control unit, and the electronic control unit transmits any control signal to the actuator of the corresponding vehicle equipment of the braking system, and the actuator performs control.

[0030] On the other hand, the feedback module comprises:

[0031] Monitoring unit: obtains the real-time dynamic parameters of the vehicle after all actuators are executed, and judges the braking effect of the vehicle according to the control target. If any real-time dynamic parameter of the vehicle is not within the corresponding control target range, the braking effect of the corresponding actuator is judged to be unqualified; if the real-time dynamic parameter of the vehicle is within the corresponding control target range, it is judged to be qualified;

[0032] Adjustment unit: If the braking effect is unqualified, the type of unqualified braking effect is determined, and a request is sent to the braking system based on the unqualified type. The braking system performs feedback adjustment control according to the corresponding unqualified type and sends it to the corresponding actuator for decision control.

[0033] In another aspect, the present invention provides a vehicle braking control method, comprising:

[0034] Step 1: According to the vehicle structure diagram, configure corresponding parameter type sensors at different locations and obtain vehicle parameter data in real time;

[0035] Step 2: Preprocess the vehicle parameter data of any parameter type, and classify and fuse them according to the parameter type to obtain vehicle state data of different state types;

[0036] Step 3: Obtain the control force of the vehicle according to the control algorithm and in combination with the vehicle status data;

[0037] Step 4: generating a control signal of the vehicle according to the control force, and controlling the actuator of the braking system according to the electronic control unit;

[0038] Step 5: According to the braking effect of the actuator, determine the braking completion status of the vehicle and dynamically adjust the control decision.

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

[0040] The present invention provides a vehicle braking system and a control method thereof, which are used to obtain real-time parameter data of the vehicle, obtain control signals according to a control algorithm, generate control decisions for different actuators, and perform feedback dynamic adjustment after the decisions are executed. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0042] Figure 1 is a structural schematic diagram of a vehicle braking system provided by an embodiment of the present invention;

[0043] Figure 2 It is a flow chart of a vehicle braking control method provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] Embodiment 1:

[0046] like Figure 1 As shown, a vehicle braking system provided by an embodiment of the present invention includes:

[0047] Data acquisition module: According to the vehicle structure diagram, corresponding parameter type sensors are configured at different locations of the vehicle and vehicle parameter data is acquired in real time;

[0048] Data processing module: pre-processes the vehicle parameter data of any parameter type, and classifies and fuses them according to the parameter type to obtain vehicle status data of different status types;

[0049] Control decision module: according to the control algorithm, combined with the vehicle status data, obtains the control strength of the vehicle;

[0050] A signal execution module: generates a control signal of the vehicle according to the control force, and controls the actuator of the braking system of the vehicle according to the electronic control unit;

[0051] Feedback module: According to the braking effect of the actuator, it determines the braking completion status of the vehicle and dynamically adjusts the control decision.

[0052] In this embodiment, the vehicle structure diagram is a schematic diagram that shows the various parts of the vehicle and their interrelationships. The structure includes: body, chassis, power system, electronic control unit, etc.

[0053] In this embodiment, the parameter type sensor is a device used to monitor and measure various aspects of vehicle performance, and the types include: speed, acceleration, pressure, angle, etc.

[0054] In this embodiment, vehicle parameter data refers to various information related to vehicle performance, status and environment that is monitored and collected in real time by various sensors in a car or other type of vehicle.

[0055] In this embodiment, preprocessing is a step of cleaning, converting and organizing the original data during the data analysis and processing process.

[0056] In this embodiment, classification fusion is a technology in data processing, which is mainly used to integrate information from different sensors or data sources. Specifically, the data of the same category are feature fused through data fusion algorithms (such as weighted averaging, Kalman filtering, Bayesian fusion, etc.) to obtain more accurate state estimation.

[0057] In this embodiment, the vehicle status data refers to information reflecting the current working status of the vehicle collected in real time by various sensors during the operation of the vehicle, including: speed, position, pressure, etc.

[0058] In this embodiment, the control algorithm is a set of mathematical and logical rules used to implement control decisions and automated operations.

[0059] In this embodiment, the vehicle status data refers to various types of information reflecting the vehicle's operating status, performance, and environmental conditions at a specific moment, including: speed, position, pressure, etc.

[0060] In this embodiment, the control force refers to a quantitative value generated by the system based on real-time vehicle status data and control algorithms.

[0061] In this embodiment, the control signal in the vehicle control system refers to an electrical signal generated by a control decision module, which is used to instruct various actuators of the vehicle (such as a braking system, an accelerator, a steering system, etc.) on how to act.

[0062] In this embodiment, the ECU is a vital electronic component in a modern automobile, responsible for controlling and managing various functions of the automobile.

[0063] In this embodiment, the braking system is an important component of the vehicle, including: brakes, cylinders, brakes, etc.

[0064] In this embodiment, the actuator is a key component in the automation and control system, responsible for actually performing specific operations according to control signals or instructions.

[0065] In this embodiment, the braking effect refers to the actual reaction and performance of the vehicle after the braking force is applied, including: braking distance, response time, stability, etc.

[0066] In this embodiment, the braking completion status refers to the state and performance of the vehicle after the braking force is applied, and whether the braking process achieves the expected effect.

[0067] The working principle and beneficial effects of the above technical solution are: through sensor data fusion and intelligent control, the safety, accuracy and reliability of the vehicle braking system are improved, dynamic adjustment is achieved, and the braking effect is optimized.

[0068] Embodiment 2:

[0069] Based on the above embodiment 1, the data acquisition module includes:

[0070] Vehicle structure unit: obtain the vehicle structure diagram of the target research vehicle and obtain all functional components of the target research vehicle;

[0071] Sensor matching unit: According to the target key parameters of vehicle braking, the corresponding functional components are matched, and the corresponding sensor type is obtained based on the mapping table of key parameters-sensor type.

[0072] In this embodiment, the functional components include: a vehicle body, a chassis, a power system, an electronic control unit, etc.

[0073] In this embodiment, the target key parameters refer to the main indicators that affect the performance, safety and function of the vehicle, including: braking distance, response time, stability, etc.

[0074] In this embodiment, the key parameter-sensor type mapping table is a table indicating the mapping relationship between key parameters and sensor types.

[0075] The working principle and beneficial effects of the above technical solution are: identifying functional components through the vehicle structure diagram and matching key parameters with corresponding sensors to ensure accurate monitoring and control, and improve the safety and performance of the braking system.

[0076] Embodiment 3:

[0077] Based on the above embodiment 2, the data acquisition module further includes:

[0078] Sensor configuration unit: configure a unique first number for any sensor, configure a unique second number for any functional component, and install the sensor configuration to the installation position of the corresponding functional component according to the corresponding relationship between the sensor and the functional component;

[0079] Sensor interface: Connect the sensor to the vehicle acquisition system through an interface, and transmit the raw data acquired by the sensor in real time to the vehicle acquisition system through the interface to obtain vehicle parameter data.

[0080] In this embodiment, the first number refers to a unique identifier assigned to each sensor.

[0081] In this embodiment, the second number refers to a unique identifier assigned to each installation location.

[0082] In this embodiment, the interface refers to a hardware and software module that connects the sensor to the vehicle acquisition system.

[0083] In this embodiment, the vehicle data collection system is an integrated hardware and software platform that processes and analyzes the data generated by the vehicle during operation.

[0084] In this embodiment, raw data refers to data directly acquired by the sensor during real-time monitoring without being processed or analyzed.

[0085] The working principle and beneficial effects of the above technical solution are: by assigning unique numbers to sensors and functional components, accurate installation and real-time data transmission are ensured, thereby optimizing the data integration and intelligence level of the vehicle collection system and improving vehicle performance and system compatibility.

[0086] Embodiment 4:

[0087] Based on the above embodiment 1, the data processing module includes:

[0088] Interface data unit: obtains vehicle parameter data of any parameter type according to the interface, and performs structured conversion on the vehicle parameter data to obtain structured parameter data;

[0089] Standardization unit: using statistical methods to detect abnormal values ​​of the structured parameter data, removing the abnormal values ​​and performing standardization to obtain standard parameter data;

[0090] Classification unit: according to any state type, filter all parameter type names contained in the state type;

[0091] ; Among them, Sym represents the functional similarity between the current state type and any parameter type name, represents the preset weight coefficient of the ith function of the parameter type name, Indicates the preset matching degree between the ith function of the parameter type name and the current state type, n indicates that the parameter type name has a total of n function values, Represents the loss function based on the loss coefficient r1;

[0092] The parameter type names whose matching degree with the state type is greater than a preset threshold are classified into the state type to obtain vehicle state data of the state type.

[0093] In this embodiment, structured transformation refers to converting raw data or unstructured data into a format that is organized and easy to analyze and process.

[0094] In this embodiment, the structured parameter data refers to organized and formatted data.

[0095] In this embodiment, statistical methods are used to detect outliers, standardize data, and classify data, such as: Z-score method, IQR method, etc.

[0096] In this embodiment, an outlier refers to a data point that is significantly different from other data points in a data set.

[0097] In this embodiment, standardization is a method of converting numerical data of different scales into the same standard.

[0098] In this embodiment, the standard parameter data is a data set obtained by performing a series of processing on the vehicle parameter data.

[0099] In this embodiment, the state type refers to the operating state performance of the vehicle under specific conditions. The state type data is obtained by classifying and fusing the standard parameter data of the same type. For example, all the standard parameter data of the kth time node are classified and fused to obtain the state type data of the kth time node.

[0100] In this embodiment, the functional similarity is a metric used to quantify the similarity between different functional parameters.

[0101] In this embodiment, the preset threshold is a boundary value used to control the matching degree screening between the parameter type name and the current state type.

[0102] In this embodiment, the loss coefficient refers to an indicator used to evaluate the difference between the model prediction value and the actual value during the model training process.

[0103] The working principle and beneficial effects of the above technical solution are: vehicle parameter data is obtained through the interface, and after structuring, outlier processing and standardization, parameters related to specific status types are finally screened to achieve effective classification and matching, thereby improving data quality and the accuracy of vehicle status monitoring.

[0104] Embodiment 5:

[0105] Based on the above embodiment 1, the signal execution module includes:

[0106] Control algorithm unit: formulates control targets according to the vehicle's operating standards, and obtains control strength based on the control algorithm combined with vehicle status data;

[0107] ;in, represents the control strength of the control output of the current category, t represents the control output of the current category, represents the variance of the j-th vehicle status data. There are m types of vehicle status data in total. represents the control target threshold, Indicates the cumulative integral of the error of the current control output;

[0108] Finally, the control strength of all control outputs of the vehicle is obtained.

[0109] In this embodiment, the operating standard refers to a set of preset indicator standards, such as speed limit, acceleration performance, braking distance, etc.

[0110] In this embodiment, the control target refers to a specific performance set according to the vehicle's operating standard and actual state data, such as setting a target speed, controlling vehicle acceleration, deceleration, etc.

[0111] In this embodiment, the control algorithm is an algorithm that formulates a control target based on the vehicle's operating standards and status data, and calculates the corresponding control output strength.

[0112] In this embodiment, the error accumulation integral is the result of time integration of the error between the target value (control target) and the vehicle state data, and is used to reflect the accumulation of past errors.

[0113] The working principle and beneficial effects of the above technical solution are: dynamically calculate the control force according to the vehicle operation standards and status data, ensure precise control and stability, optimize errors, and achieve adaptability to multiple categories of states, thereby improving vehicle safety and intelligent management.

[0114] Embodiment 6:

[0115] Based on the above embodiment 1, the signal execution module includes:

[0116] Control signal unit: Substitute the control force into the vehicle control decision model to generate a control signal corresponding to the control output;

[0117] Braking unit: matches all control signals to corresponding vehicle equipment, connects the control signal unit and vehicle equipment according to the electronic control unit, and the electronic control unit transmits any control signal to the actuator of the corresponding vehicle equipment of the braking system, and the actuator performs control.

[0118] In this embodiment, the control decision model is a model that converts various inputs (such as sensor data, driver instructions, etc.) into specific control outputs to guide the behavior of the vehicle.

[0119] The working principle and beneficial effects of the above technical solution are: through the collaboration of the control signal unit and the brake unit, precise control of vehicle braking is achieved, response speed and stability are improved, driving safety is enhanced, and real-time fault diagnosis and maintenance are supported.

[0120] Embodiment 7:

[0121] Based on the above embodiment 6, the feedback module includes:

[0122] Monitoring unit: obtains the real-time dynamic parameters of the vehicle after all actuators are executed, and judges the braking effect of the vehicle according to the control target. If any real-time dynamic parameter of the vehicle is not within the corresponding control target range, the braking effect of the corresponding actuator is judged to be unqualified; if the real-time dynamic parameter of the vehicle is within the corresponding control target range, it is judged to be qualified;

[0123] Adjustment unit: If the braking effect is unqualified, the type of unqualified braking effect is determined, and a request is sent to the braking system based on the unqualified type. The braking system performs feedback adjustment control according to the corresponding unqualified type and sends it to the corresponding actuator for decision control.

[0124] In this embodiment, the real-time dynamic parameters of the vehicle refer to various physical quantities and performance indicators that reflect the state and behavior of the vehicle during the driving process of the vehicle, such as speed, acceleration, braking force, etc.

[0125] In this embodiment, the control target range refers to a set of ideal state parameter values ​​set according to specific safety standards and performance requirements during the driving of the vehicle, such as: vehicle speed range, acceleration range, braking force range, etc.

[0126] In this embodiment, the request refers to specific instruction information sent by the monitoring unit to the braking system when the monitoring unit detects that the braking effect is unsatisfactory.

[0127] The working principle and beneficial effects of the above technical solution are: by real-time monitoring of vehicle dynamic parameters, determining the braking effect, identifying the unqualified type, and adjusting the control, the safety, reliability and fault diagnosis capability of the braking system are improved, and accurate decision-making control is achieved.

[0128] Embodiment 8:

[0129] like Figure 2 As shown, a vehicle braking control method provided by an embodiment of the present invention includes:

[0130] Step 1: According to the vehicle structure diagram, configure corresponding parameter type sensors at different locations and obtain vehicle parameter data in real time;

[0131] Step 2: Preprocess the vehicle parameter data of any parameter type, and classify and fuse them according to the parameter type to obtain vehicle state data of different state types;

[0132] Step 3: Obtain the control force of the vehicle according to the control algorithm and in combination with the vehicle status data;

[0133] Step 4: generating a control signal of the vehicle according to the control force, and controlling the actuator of the braking system according to the electronic control unit;

[0134] Step 5: According to the braking effect of the actuator, determine the braking completion status of the vehicle and dynamically adjust the control decision.

[0135] The working principle and beneficial effects of the above technical solution are: through sensor data fusion and intelligent control, the safety, accuracy and reliability of the vehicle braking system are improved, dynamic adjustment is achieved, and the braking effect is optimized.

[0136] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A vehicle braking system, characterized in that: include: Data acquisition module: According to the vehicle structure diagram, corresponding parameter type sensors are configured at different locations of the vehicle and vehicle parameter data is acquired in real time; Data processing module: pre-processes vehicle parameter data of any parameter type, and classifies and fuses them according to parameter types to obtain vehicle status data of different status types, including: interface data unit: obtains vehicle parameter data of any parameter type according to the interface, and performs structured transformation on the vehicle parameter data to obtain structured parameter data; Standardization unit: using statistical methods to detect abnormal values ​​of the structured parameter data, removing the abnormal values ​​and standardizing them to obtain standard parameter data; Classification unit: according to any state type, filter all parameter type names contained in the state type; ; Among them, Sym represents the functional similarity between the current state type and any parameter type name, represents the preset weight coefficient of the ith function of the parameter type name, Indicates the preset matching degree between the ith function of the parameter type name and the current state type, n indicates that the parameter type name has a total of n function values, Represents the loss function based on the loss coefficient r1; Classifying parameter type names whose matching degree with the state type is greater than a preset threshold as the state type, and obtaining vehicle state data of the state type; Control decision module: according to the control algorithm, combined with the vehicle status data, obtains the control strength of the vehicle; A signal execution module: generates a control signal of the vehicle according to the control force, and controls the actuator of the braking system of the vehicle according to the electronic control unit, including: a control algorithm unit: formulates a control target according to the operation standard of the vehicle, and obtains the control force based on the control algorithm combined with the vehicle status data; ;in, represents the control strength of the control output of the current category, t represents the control output of the current category, represents the variance of the j-th vehicle status data. There are m types of vehicle status data in total. represents the control target threshold, Indicates the cumulative integral of the error of the current control output; Finally, the control strength of all control outputs of the vehicle is obtained; Feedback module: According to the braking effect of the actuator, it determines the braking completion status of the vehicle and dynamically adjusts the control decision.

2. A vehicle braking system according to claim 1, characterized in that: The data acquisition module comprises: Vehicle structure unit: obtain the vehicle structure diagram of the target research vehicle and obtain all functional components of the target research vehicle; Sensor matching unit: studies the target key parameters of vehicle braking according to the target, matches the corresponding functional components, and obtains the corresponding sensor type based on the mapping table of key parameters-sensor type.

3. A vehicle braking system according to claim 2, characterized in that: The data acquisition module further includes: Sensor configuration unit: configure a unique first number for any sensor, configure a unique second number for any functional component, and install the sensor configuration to the installation position of the corresponding functional component according to the corresponding relationship between the sensor and the functional component; Sensor interface: Connect the sensor to the vehicle acquisition system through an interface, and use the interface to transmit the raw data acquired by the sensor in real time to the vehicle acquisition system to obtain vehicle parameter data.

4. A vehicle braking system according to claim 1, characterized in that: The signal execution module comprises: Control signal unit: Substitute the control force into the vehicle control decision model to generate a control signal corresponding to the control output; Braking unit: matches all control signals to corresponding vehicle equipment, connects the control signal unit and vehicle equipment according to the electronic control unit, and the electronic control unit transmits any control signal to the actuator of the corresponding vehicle equipment of the braking system, and the actuator performs control.

5. A vehicle braking system according to claim 4, characterized in that: The feedback module comprises: Monitoring unit: obtains the real-time dynamic parameters of the vehicle after all actuators are executed, and judges the braking effect of the vehicle according to the control target. If any real-time dynamic parameter of the vehicle is not within the corresponding control target range, the braking effect of the corresponding actuator is judged to be unqualified; if the real-time dynamic parameter of the vehicle is within the corresponding control target range, it is judged to be qualified; Adjustment unit: If the braking effect is unqualified, the type of unqualified braking effect is determined, and a request is sent to the braking system based on the unqualified type. The braking system performs feedback adjustment control according to the corresponding unqualified type and sends it to the corresponding actuator for decision control.

6. A vehicle braking method, applied to a vehicle braking system according to any one of claims 1 to 5, characterized in that: include: Step 1: According to the vehicle structure diagram, configure corresponding parameter type sensors at different locations and obtain vehicle parameter data in real time; Step 2: Preprocess the vehicle parameter data of any parameter type, and classify and fuse them according to the parameter type to obtain vehicle state data of different state types; Step 3: Obtain the control force of the vehicle according to the control algorithm and in combination with the vehicle status data; Step 4: generating a control signal of the vehicle according to the control force, and controlling the actuator of the braking system according to the electronic control unit; Step 5: According to the braking effect of the actuator, determine the braking completion status of the vehicle and dynamically adjust the control decision.

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