Vehicle brake-by-wire method and system

Abstract

The present application relates to a vehicle wire-controlled braking method and system, and relates to the technical field of wire-controlled braking. The method includes: acquiring environmental information and vehicle posture information around the vehicle; identifying road conditions based on the environmental information and obtaining dynamic parameters of the vehicle based on the vehicle posture information and a vehicle dynamics model; obtaining a vehicle state assessment result based on the identified road conditions and the vehicle dynamic parameters; the vehicle state assessment result is obtained based on the driving state and potential risks of the vehicle under the current road conditions; determining the braking force distribution ratio and adjustment amount of each wheel using a braking force distribution matrix and a braking force adjustment algorithm based on the vehicle state assessment result; and adjusting the brake fluid pressure of each wheel based on the determined braking force distribution ratio and adjustment amount of each wheel.

Description

Technical Field

[0001] The present application relates to the technical field of wire-controlled braking, and in particular to a vehicle wire-controlled braking method and system. Background Art

[0002] In modern transportation, a vehicle's braking system plays a vital role in ensuring safety and performance. Traditional vehicle braking systems are primarily based on mechanical and hydraulic principles, often distributing braking force in a relatively fixed manner. For example, for most vehicles, the braking force distribution between the front and rear wheels is pre-set based on the vehicle's static axle load distribution and can only be adjusted to a limited extent under varying driving conditions. This traditional braking system has exposed numerous limitations when coping with increasingly complex traffic environments and diverse road conditions.

[0003] How to solve the above problems is a technical problem that needs to be overcome by those skilled in the art. Summary of the Invention

[0004] In order to at least partially solve the above technical problems, the present application provides a vehicle wire control braking method and system.

[0005] In a first aspect, the present application provides a vehicle wire control braking method adopting the following technical solution.

[0006] A vehicle brake-by-wire method, comprising:

[0007] Obtaining environmental information around the vehicle and vehicle posture information;

[0008] Identifying road conditions based on the environmental information and obtaining dynamic parameters of the vehicle based on the vehicle posture information and a vehicle dynamics model;

[0009] Obtaining a vehicle state assessment result based on the identified road condition and the vehicle dynamic parameters; the vehicle state assessment result is obtained based on the driving state and potential risks of the vehicle under the current road condition;

[0010] Determining the braking force distribution ratio and adjustment amount of each wheel using a braking force distribution matrix and a braking force adjustment algorithm based on the vehicle state evaluation result;

[0011] The brake fluid pressure of each wheel is adjusted based on the determined braking force distribution ratio and adjustment amount of each wheel.

[0012] By adopting the above technical solution,.

[0013] Optionally, identifying a road condition based on the environmental information includes:

[0014] Use the on-board camera to collect image information around the vehicle;

[0015] Processing the collected image information to extract road features; the road features include road surface texture, signs, color, and surrounding object features;

[0016] The road conditions are divided into different categories according to the extracted road features, and the different categories of road conditions include dry road surface, wet road surface and icy road surface.

[0017] Optionally, obtaining the dynamic parameters of the vehicle based on the vehicle posture information and the vehicle dynamics model includes:

[0018] Measuring vehicle acceleration, angular velocity and attitude angle based on inertial measurement unit;

[0019] Based on the vehicle dynamics model, calculate the vehicle's speed, center of mass position, center of mass sideslip angle and vertical load of each wheel;

[0020] The vehicle's roll moment and pitch moment are calculated based on the vehicle's suspension system characteristics and tire characteristics.

[0021] Optionally, obtaining a vehicle state assessment result based on the identified road condition and the vehicle dynamic parameters includes:

[0022] Determine the basic braking characteristics of the vehicle under the current road condition based on the identified road condition; wherein, for a dry road surface, determine the braking friction coefficient range to be a first braking friction coefficient range, and the maximum allowable braking deceleration to be the first maximum braking deceleration; for a slippery road surface, determine the braking friction coefficient range to be a second braking friction coefficient range, and the maximum allowable braking deceleration to be the second maximum braking deceleration, and the second braking friction coefficient range is smaller than the first braking friction coefficient range, and the second maximum braking deceleration is smaller than the first maximum braking deceleration; for an icy road surface, determine the braking friction coefficient range to be a third braking friction coefficient range, and the maximum allowable braking deceleration to be the third maximum braking deceleration, and the third braking friction coefficient range is smaller than the second braking friction coefficient range, and the third maximum braking deceleration is smaller than the second maximum braking deceleration;

[0023] Evaluate the vehicle's driving stability based on the vehicle's dynamic parameters;

[0024] The vehicle status assessment results are obtained based on the basic braking characteristics of the road conditions and the driving stability of the vehicle and are divided into different levels; the different levels include safe state, low-risk state, medium-risk state and high-risk state.

[0025] Optionally, a vehicle state assessment result is obtained based on basic braking characteristics of road conditions and driving stability of the vehicle and is divided into different levels, including:

[0026] When the vehicle is on a dry road, the speed does not exceed the first speed threshold, the center of mass position offset does not exceed the first center of mass offset threshold, and the acceleration does not exceed the first acceleration threshold, and the center of mass side slip angle does not exceed the first side slip angle threshold, the vehicle state assessment result is classified as a safe state; when the vehicle is on a slippery road, the speed is greater than the first speed threshold and less than the second speed threshold, the center of mass position offset is greater than the first center of mass offset threshold and less than the second center of mass offset threshold, or the maximum difference in wheel vertical load is greater than the first load difference threshold and less than the second load difference threshold, the vehicle state assessment result is classified as a low-risk state; when the vehicle is on an icy road, the speed is greater than the second speed threshold, or the center of mass side slip angle is greater than the second side slip angle threshold, or the slip rate of the wheel during braking is greater than the first slip rate threshold, the vehicle state assessment result is classified as a medium-risk state;

[0027] When the vehicle is in any road condition, the speed is greater than the third speed threshold, or the center of mass position offset is greater than the second center of mass offset threshold, or the acceleration is greater than the second acceleration threshold, or the maximum difference in wheel vertical load is greater than the second load difference threshold, the vehicle state assessment result is classified as a high-risk state.

[0028] Optionally, determining the braking force distribution ratio and adjustment amount of each wheel using a braking force distribution matrix and a braking force adjustment algorithm based on the vehicle state assessment result includes:

[0029] Searching for a corresponding initial braking force distribution ratio range in a braking force distribution matrix based on the vehicle state assessment result; wherein the braking force distribution matrix stores the braking force distribution ratio ranges for each wheel under different vehicle state assessment results; for a safe state, searching for a first braking force distribution ratio range; for a low-risk state, searching for a second braking force distribution ratio range; for a medium-risk state, searching for a third braking force distribution ratio range; and for a high-risk state, searching for a fourth braking force distribution ratio range;

[0030] The vehicle's deceleration, wheel slip rate, yaw angular velocity and wheel angular acceleration are used as input parameters and fed into the braking force adjustment algorithm. The initial braking force distribution ratio range found in the braking force distribution matrix is ​​adjusted according to the input parameters to determine the final braking force distribution ratio and adjustment amount for each wheel.

[0031] Optionally, the initial braking force distribution ratio range found from the braking force distribution matrix is ​​adjusted according to the input parameters to determine the final braking force distribution ratio and adjustment amount for each wheel, including:

[0032] Inputting the vehicle's deceleration, wheel slip rate, yaw rate, and wheel angular acceleration as input vectors into a neural network; the neural network considers optimal braking force distribution under different input parameter combinations during training;

[0033] After the forward propagation calculation of the neural network, the braking force distribution ratio and adjustment amount of each wheel are obtained;

[0034] The initial ratio range provided by the comprehensive braking force distribution matrix and the adjustment amount obtained by the braking force adjustment algorithm are used to determine the final braking force distribution ratio and adjustment amount of each wheel.

[0035] Optionally, the neural network has the following structure: an input layer includes four neurons that receive the vehicle's deceleration, wheel slip rate, yaw angular velocity and wheel angular acceleration; two hidden layers, the first hidden layer includes 16 neurons, and the second hidden layer includes 8 neurons; the output layer includes eight neurons, of which the first four neurons output the braking force distribution ratio of each wheel, and the last four neurons output the braking force adjustment amount of each wheel; the mean square error is used as the loss function; vehicle data of various braking operations under different road conditions are collected as training samples, and the vehicle data includes the vehicle's deceleration, wheel slip rate, yaw angular velocity, wheel angular acceleration and the corresponding optimal braking force distribution ratio and adjustment amount; the training data is input into the neural network, and forward propagation calculation is performed, and back propagation is performed to update the network weights and bias based on the mean square error between the calculated result and the true result, and the iteration is repeated until the loss value is less than the first preset value.

[0036] Optionally, the step of establishing the braking force distribution matrix includes:

[0037] Divide the vehicle status assessment results into multiple status categories based on various possible road conditions and different driving states of the vehicle;

[0038] For each state category, the braking force distribution ratio range of each wheel is preliminarily determined by combining vehicle dynamics theory and historical braking data;

[0039] Using vehicle dynamics simulation software to simulate and verify the initially determined braking force distribution ratio range; adjusting the braking force distribution ratio range according to the simulation results;

[0040] Conduct braking tests at different test sites using test scenarios based on the aforementioned different state categories. Collect actual vehicle braking data, analyze the vehicle's braking performance under the initial braking force distribution ratio range in different states, and adjust the braking force distribution ratio range based on the performance test results.

[0041] The braking force distribution ratio range of each wheel under different vehicle state evaluation results determined after theoretical analysis, simulation verification and test verification is stored in the braking force distribution matrix.

[0042] In a second aspect, the present application provides a vehicle brake-by-wire system that adopts the following technical solution.

[0043] A brake-by-wire system for an unmanned vehicle, comprising:

[0044] The first processing module is used to obtain the vehicle's surrounding environment information and vehicle posture information;

[0045] A second processing module is configured to: identify a road condition based on the environmental information and obtain dynamic parameters of the vehicle based on the vehicle posture information and a vehicle dynamics model;

[0046] A third processing module is configured to obtain a vehicle state assessment result based on the identified road condition and the vehicle dynamic parameters; the vehicle state assessment result is obtained based on the vehicle's driving state and potential risks under the current road condition;

[0047] a fourth processing module, configured to determine a braking force distribution ratio and an adjustment amount of each wheel using a braking force distribution matrix and a braking force adjustment algorithm based on the vehicle state evaluation result;

[0048] The fifth processing module is used to adjust the brake fluid pressure of each wheel based on the determined braking force distribution ratio and adjustment amount of each wheel. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 This is a flow chart of a vehicle brake-by-wire method according to an embodiment of the present application;

[0050] Figure 2 This is a system block diagram of a vehicle brake-by-wire system according to an embodiment of the present application;

[0051] In the figure, 201 is the first processing module; 202 is the second processing module; 203 is the third processing module; 204 is the fourth processing module; 205 is the fifth processing module. DETAILED DESCRIPTION

[0052] The following is combined with Figure 1-2 The present application is further described with reference to the following specific examples:

[0053] The present application discloses a vehicle brake-by-wire method, comprising the following steps:

[0054] Step 101: Acquire environmental information and vehicle posture information surrounding the vehicle. Specifically, environmental information surrounding the vehicle can be collected by various sensors installed on the vehicle, such as cameras, millimeter-wave radars, lidars, and ultrasonic sensors. This information includes road conditions, such as road surface texture and color, the presence of obstacles, the position and speed of other vehicles, and traffic signs. Vehicle posture information is data describing the vehicle's position and motion in space, typically measured by an inertial measurement unit. It includes vehicle accelerations: longitudinal acceleration, lateral acceleration, angular velocity, and attitude angle.

[0055] Step 102: Identify road conditions based on the environmental information and obtain vehicle dynamic parameters based on the vehicle posture information and a vehicle dynamics model. A vehicle dynamics model is a mathematical model based on the principles of physics that describes the motion of a vehicle under various forces and moments. The vehicle dynamics model is based on the vehicle's mass, moment of inertia, suspension system characteristics, tire characteristics, wheelbase, and track width. Dynamic parameters such as the center of mass position, sideslip angle, and vertical load on each wheel can be calculated using the vehicle dynamics model. The vehicle's dynamic parameters change in real time with changes in the vehicle's driving state and external environment, and are used to assess the vehicle's driving state and braking requirements.

[0056] Step 103: Obtain a vehicle state assessment result based on the identified road conditions and the vehicle's dynamic parameters. The vehicle state assessment result is based on the vehicle's driving state and potential risks under the current road conditions. The vehicle's driving state and potential risks are comprehensively evaluated based on the vehicle's current road conditions and dynamic parameters. Vehicle state assessment results are generally categorized into different levels, such as safe (stable vehicle with minimal risk), low-risk (minor vehicle instability may occur but overall controllable), medium-risk (some degree of vehicle instability requiring appropriate braking adjustments), and high-risk (unstable vehicle with potential loss of control requiring emergency braking adjustments).

[0057] Step 104: Based on the vehicle state assessment results, the braking force distribution ratio and adjustment amount for each wheel are determined using the braking force distribution matrix and a braking force adjustment algorithm. The braking force distribution ratio is the baseline value for braking force distribution. Based on the vehicle state assessment results, the braking force distribution ratio obtains an initial distribution scheme from the braking force distribution matrix, reflecting the approximate braking force distribution of the vehicle under different states. The braking force adjustment amount is a fine-tuning value calculated by the braking force adjustment algorithm based on this baseline and real-time vehicle information.

[0058] Ultimately, the actual braking force at each wheel is calculated by adding or subtracting the appropriate braking force adjustment amount based on the total braking force distributed according to the braking force distribution ratio. This allows the braking system to precisely control the braking force at each wheel, ensuring optimal braking performance under varying road conditions and driving scenarios.

[0059] Step 105 : Adjust the brake fluid pressure of each wheel based on the determined braking force distribution ratio and adjustment amount of each wheel.

[0060] Specifically, the environmental information around the vehicle and the vehicle posture information are obtained, and the dynamic parameters of the vehicle are calculated by identifying the road conditions and vehicle posture information and combining them with the vehicle dynamics model; the vehicle state assessment result is obtained according to the identified road conditions and dynamic parameters, and based on the vehicle state assessment result, the braking force distribution ratio and adjustment amount of each wheel are determined using the braking force distribution matrix and the braking force adjustment algorithm. The braking force distribution matrix provides a basic value for the braking force distribution, and the braking force adjustment algorithm adjusts the braking force according to the real-time state of the vehicle. The two are combined to distribute the braking force according to the actual situation of the vehicle; based on the determined braking force distribution ratio and adjustment amount of each wheel, the brake fluid pressure of each wheel is adjusted, which enables the braking system to control the braking force of each wheel according to the different states and needs of the vehicle, thereby effectively shortening the braking distance under different road conditions, improving the braking stability of the vehicle, preventing wheel locking or vehicle loss of control, and significantly enhancing the braking performance and safety of the vehicle under various driving conditions, thereby ensuring the safe driving of the vehicle.

[0061] As a specific implementation of a vehicle brake-by-wire method, identifying a road condition based on the environmental information includes:

[0062] Use the on-board camera to collect image information around the vehicle;

[0063] Processing the collected image information to extract road features; the road features include road surface texture, signs, color, and surrounding object features;

[0064] The road conditions are divided into different categories according to the extracted road features, and the different categories of road conditions include dry road surface, wet road surface and icy road surface.

[0065] Specifically, the on-board camera is used to collect image information around the vehicle, and the collected image information is processed to extract road features, and important information such as road surface texture, signs, color, and surrounding object features are filtered out from the image; the road conditions are divided into different categories according to the extracted road features.

[0066] As a specific implementation of a vehicle brake-by-wire method, obtaining the vehicle's dynamic parameters based on the vehicle posture information and the vehicle dynamics model includes:

[0067] Measuring vehicle acceleration, angular velocity and attitude angle based on inertial measurement unit;

[0068] Based on the vehicle dynamics model, calculate the vehicle's speed, center of mass position, center of mass sideslip angle and vertical load of each wheel;

[0069] The vehicle's roll moment and pitch moment are calculated based on the vehicle's suspension system characteristics and tire characteristics.

[0070] Specifically, the acceleration, angular velocity and attitude angle of the vehicle are measured based on the inertial measurement unit;

[0071] Based on the vehicle dynamics model, the vehicle's speed, center of mass position, center of mass slip angle, and vertical load on each wheel are calculated. The calculated vehicle speed indicates the vehicle's speed; the center of mass position indicates the vehicle's weight distribution. During braking, the center of mass shifts, affecting the forces acting on each wheel. This information helps prevent vehicle instability caused by improper braking force distribution. This can include preventing excessive front braking and insufficient rear braking due to a forward center of mass shift, or preventing rear wheel locking and insufficient front braking due to a rearward center of mass shift. The center of mass slip angle indicates whether the vehicle's trajectory is consistent with expectations. A large center of mass slip angle indicates the potential for vehicle deviation. The vertical load on each wheel indicates the weight borne by each wheel. Different vertical loads affect wheel grip. The vehicle's roll and pitch moments are calculated based on the vehicle's suspension and tire characteristics. Roll moment characterizes the vehicle's roll when cornering or navigating uneven roads. Excessive roll moment can cause the vehicle to roll over. By calculating and monitoring this moment, braking strategies can be adjusted in advance to ensure vehicle stability. Pitch moment reflects the vehicle's pitch during acceleration and braking. During emergency braking, a large pitch moment can cause the vehicle to tilt forward. This information can be used to adjust the braking force distribution between the front and rear wheels to prevent excessive forward tilt and loss of control.

[0072] As a specific implementation of a vehicle brake-by-wire method, obtaining a vehicle state assessment result based on the identified road condition and the vehicle dynamic parameters includes:

[0073] Determine the basic braking characteristics of the vehicle under the current road condition based on the identified road condition; wherein, for a dry road surface, determine the braking friction coefficient range to be a first braking friction coefficient range, and the maximum allowable braking deceleration to be the first maximum braking deceleration; for a slippery road surface, determine the braking friction coefficient range to be a second braking friction coefficient range, and the maximum allowable braking deceleration to be the second maximum braking deceleration, and the second braking friction coefficient range is smaller than the first braking friction coefficient range, and the second maximum braking deceleration is smaller than the first maximum braking deceleration; for an icy road surface, determine the braking friction coefficient range to be a third braking friction coefficient range, and the maximum allowable braking deceleration to be the third maximum braking deceleration, and the third braking friction coefficient range is smaller than the second braking friction coefficient range, and the third maximum braking deceleration is smaller than the second maximum braking deceleration;

[0074] Evaluate the vehicle's driving stability based on the vehicle's dynamic parameters;

[0075] The vehicle status assessment results are obtained based on the basic braking characteristics of the road conditions and the driving stability of the vehicle and are divided into different levels; the different levels include safe state, low-risk state, medium-risk state and high-risk state.

[0076] In one embodiment of a vehicle brake-by-wire method, a vehicle state assessment result is obtained based on basic braking characteristics of road conditions and vehicle driving stability, and the vehicle state assessment result is divided into different levels, including:

[0077] When the vehicle is on a dry road, the speed does not exceed the first speed threshold, the center of mass position offset does not exceed the first center of mass offset threshold, and the acceleration does not exceed the first acceleration threshold, and the center of mass side slip angle does not exceed the first side slip angle threshold, the vehicle state assessment result is classified as a safe state; when the vehicle is on a slippery road, the speed is greater than the first speed threshold and less than the second speed threshold, the center of mass position offset is greater than the first center of mass offset threshold and less than the second center of mass offset threshold, or the maximum difference in wheel vertical load is greater than the first load difference threshold and less than the second load difference threshold, the vehicle state assessment result is classified as a low-risk state; when the vehicle is on an icy road, the speed is greater than the second speed threshold, or the center of mass side slip angle is greater than the second side slip angle threshold, or the slip rate of the wheel during braking is greater than the first slip rate threshold, the vehicle state assessment result is classified as a medium-risk state;

[0078] When the vehicle is in any road condition, the speed is greater than the third speed threshold, or the center of mass position offset is greater than the second center of mass offset threshold, or the acceleration is greater than the second acceleration threshold, or the maximum difference in wheel vertical load is greater than the second load difference threshold, the vehicle state assessment result is classified as a high-risk state.

[0079] In one embodiment of a vehicle brake-by-wire method, a braking force distribution matrix and a braking force adjustment algorithm are used based on the vehicle state assessment result to determine the braking force distribution ratio and adjustment amount of each wheel, including:

[0080] Searching for a corresponding initial braking force distribution ratio range in a braking force distribution matrix based on the vehicle state assessment result; wherein the braking force distribution matrix stores the braking force distribution ratio ranges for each wheel under different vehicle state assessment results; for a safe state, searching for a first braking force distribution ratio range; for a low-risk state, searching for a second braking force distribution ratio range; for a medium-risk state, searching for a third braking force distribution ratio range; and for a high-risk state, searching for a fourth braking force distribution ratio range;

[0081] The vehicle's deceleration, wheel slip rate, yaw angular velocity and wheel angular acceleration are used as input parameters and fed into the braking force adjustment algorithm. The initial braking force distribution ratio range found in the braking force distribution matrix is ​​adjusted according to the input parameters to determine the final braking force distribution ratio and adjustment amount for each wheel.

[0082] Specifically, based on the vehicle state assessment results, the braking force distribution matrix searches for the corresponding initial braking force distribution ratio range, providing a preliminary braking force distribution plan. When the vehicle is in a safe state, by searching the first braking force distribution ratio range, the braking system ensures that braking force is distributed to each wheel according to a conventional and verified ratio while the vehicle is operating stably. This ensures good braking performance and maneuverability during normal driving, and avoids accidents caused by improper braking force distribution. When the vehicle is in a low-risk state, the second braking force distribution ratio range allows the braking system to make adaptive adjustments in advance to maintain driving stability when the vehicle begins to experience minor instability, such as slight changes in road conditions or minor fluctuations in vehicle dynamic parameters. The third braking force distribution ratio range searched for in medium-risk states allows the braking system to prevent further risk when the vehicle exhibits significant instability, such as minor wheel slip or vehicle deviation from its normal trajectory. In high-risk states, the fourth braking force distribution ratio range is searched, ensuring maximum safety in critical situations where the vehicle could lose control. The braking force adjustment algorithm uses the vehicle's deceleration, wheel slip, yaw rate, and wheel angular acceleration as input parameters. These key parameters, reflecting the vehicle's real-time state, adjust the initial braking force distribution ratio and range. When the vehicle's deceleration is high, indicating a need for stronger braking, the brake force adjustment algorithm can adjust the braking force distribution ratio and amount accordingly to achieve more effective braking. When the wheel slip is high, indicating a potential wheel slip risk, the algorithm can adjust the braking force distribution to appropriately reduce the braking force on that wheel to prevent locking and maintain the vehicle's steering ability. Changes in yaw rate reflect the vehicle's steering stability, and adjusting the braking force accordingly ensures that the vehicle does not lose control during cornering. Wheel angular acceleration reflects the wheel's rotational state, and adjusting the braking force ensures normal wheel rotation and vehicle stability.

[0083] In one embodiment of a vehicle brake-by-wire method, an initial braking force distribution ratio range found in a braking force distribution matrix is ​​adjusted based on input parameters to determine a final braking force distribution ratio and adjustment amount for each wheel, including:

[0084] Inputting the vehicle's deceleration, wheel slip rate, yaw rate, and wheel angular acceleration as input vectors into a neural network; the neural network considers optimal braking force distribution under different input parameter combinations during training;

[0085] After the forward propagation calculation of the neural network, the braking force distribution ratio and adjustment amount of each wheel are obtained;

[0086] The initial ratio range provided by the comprehensive braking force distribution matrix and the adjustment amount obtained by the braking force adjustment algorithm are used to determine the final braking force distribution ratio and adjustment amount of each wheel.

[0087] As one of the implementation methods of a vehicle wire control braking method, the neural network has the following structure: an input layer includes four neurons, which receive the vehicle's deceleration, wheel slip rate, yaw angular velocity and wheel angular acceleration; two hidden layers, the first hidden layer includes 16 neurons, and the second hidden layer includes 8 neurons; the output layer includes eight neurons, of which the first four neurons output the braking force distribution ratio of each wheel, and the last four neurons output the braking force adjustment amount of each wheel; the mean square error is used as the loss function; vehicle data of various braking operations under different road conditions are collected as training samples, and the vehicle data includes the vehicle's deceleration, wheel slip rate, yaw angular velocity, wheel angular acceleration and the corresponding optimal braking force distribution ratio and adjustment amount; the training data is input into the neural network, and forward propagation calculation is performed, and back propagation is performed to update the network weights and bias based on the mean square error between the calculated result and the actual result, and the iteration is repeated until the loss value is less than a first preset value.

[0088] As one implementation of a vehicle brake-by-wire method, the step of establishing the braking force distribution matrix includes:

[0089] Divide the vehicle status assessment results into multiple status categories based on various possible road conditions and different driving states of the vehicle;

[0090] For each state category, the braking force distribution ratio range of each wheel is preliminarily determined by combining vehicle dynamics theory and historical braking data;

[0091] Using vehicle dynamics simulation software to simulate and verify the initially determined braking force distribution ratio range; adjusting the braking force distribution ratio range according to the simulation results;

[0092] Conduct braking tests at different test sites using test scenarios based on the aforementioned different state categories. Collect actual vehicle braking data, analyze the vehicle's braking performance under the initial braking force distribution ratio range in different states, and adjust the braking force distribution ratio range based on the performance test results.

[0093] The braking force distribution ratio range of each wheel under different vehicle state evaluation results determined after theoretical analysis, simulation verification and test verification is stored in the braking force distribution matrix.

[0094] Specifically, the vehicle state assessment results are divided into multiple state categories based on various possible road conditions and driving states. For each state category, a preliminary range of braking force distribution ratios for each wheel is determined by combining vehicle dynamics theory and historical braking data. This preliminary range of braking force distribution ratios is verified using vehicle dynamics simulation software. By simulating various complex situations, potential problems, such as wheel locking, vehicle loss of control, or excessive braking distances, can be identified in advance. Based on the simulation results, the braking force distribution ratio range is adjusted. Braking tests are conducted at various test sites based on different state categories, and actual vehicle braking data is collected. The actual vehicle braking performance under different states is analyzed using the preliminary braking force distribution ratio ranges. Based on the test results, further adjustments are made to ensure that the braking force distribution ratio ranges are more accurate in practice. Finally, the wheel braking force distribution ratio ranges determined based on theoretical analysis, simulation, and test validation for each vehicle state assessment result are stored in a braking force distribution matrix.

[0095] The present application also provides a vehicle brake-by-wire system, comprising:

[0096] The first processing module 201 is used to obtain the vehicle's surrounding environment information and vehicle posture information;

[0097] The second processing module 202 is configured to: identify road conditions based on the environmental information and obtain dynamic parameters of the vehicle based on the vehicle posture information and a vehicle dynamics model;

[0098] The third processing module 203 is configured to obtain a vehicle state assessment result based on the identified road condition and the vehicle dynamic parameters; the vehicle state assessment result is obtained based on the vehicle's driving state and potential risks under the current road condition;

[0099] The fourth processing module 204 is configured to determine the braking force distribution ratio and adjustment amount of each wheel using a braking force distribution matrix and a braking force adjustment algorithm based on the vehicle state evaluation result;

[0100] The fifth processing module 205 is configured to adjust the brake fluid pressure of each wheel based on the determined braking force distribution ratio and adjustment amount of each wheel.

[0101] It should be noted that the above embodiments are only used to illustrate the present application and are not intended to limit the technical solutions described in the present application. Although this specification has described the present application in detail with reference to the above embodiments, ordinary technicians in this field should understand that technicians in the relevant technical field can still modify or replace the present application with equivalents, and all technical solutions and improvements that do not depart from the spirit and scope of the present application should be included in the scope of the claims of the present application.

Claims

1. A vehicle brake-by-wire method, characterized in that: include: Obtaining environmental information around the vehicle and vehicle posture information; Identifying road conditions based on the environmental information, and obtaining dynamic parameters of the vehicle based on the vehicle posture information and a vehicle dynamics model; the dynamic parameters of the vehicle include vehicle speed, acceleration, center of mass position, center of mass sideslip angle, and vertical load of each wheel; Obtaining a vehicle state assessment result based on the identified road condition and the vehicle dynamic parameters; the vehicle state assessment result is obtained based on the driving state and potential risks of the vehicle under the current road condition, and the vehicle state assessment result includes a safe state, a low-risk state, a medium-risk state, and a high-risk state; When the vehicle is on a dry road, the speed does not exceed the first speed threshold, the center of mass position offset does not exceed the first center of mass offset threshold, the acceleration does not exceed the first acceleration threshold, and the center of mass sideslip angle does not exceed the first sideslip angle threshold, the vehicle state assessment result is classified as a safe state; When the vehicle is on a slippery road, the speed is greater than the first speed threshold and less than the second speed threshold, the center of mass offset is greater than the first center of mass offset threshold and less than the second center of mass offset threshold, or the maximum difference in wheel vertical load is greater than the first load difference threshold and less than the second load difference threshold, the vehicle state assessment result is classified as a low-risk state; When the vehicle is on an icy road and the speed is greater than the second speed threshold, or the sideslip angle of the center of mass is greater than the second sideslip angle threshold, or the wheel slip rate of the vehicle is greater than the first slip rate threshold during braking, the vehicle state assessment result is classified as a medium-risk state; When the vehicle is in any road condition, the speed is greater than the third speed threshold, or the center of mass position offset is greater than the second center of mass offset threshold, or the acceleration is greater than the second acceleration threshold, or the maximum difference in wheel vertical load is greater than the second load difference threshold, the vehicle state assessment result is classified as a high-risk state; Based on the vehicle state assessment result, a braking force distribution ratio and an adjustment amount of each wheel are determined using a braking force distribution matrix and a braking force adjustment algorithm; wherein the braking force distribution matrix stores the braking force distribution ratio ranges of each wheel under different vehicle state assessment results; for a safe state, a first braking force distribution ratio range is searched; for a low-risk state, a second braking force distribution ratio range is searched; for a medium-risk state, a third braking force distribution ratio range is searched; for a high-risk state, a fourth braking force distribution ratio range is searched; the vehicle's deceleration, wheel slip rate, yaw angular velocity, and wheel angular acceleration are input as input parameters to the braking force adjustment algorithm, and the initial braking force distribution ratio range found from the braking force distribution matrix is ​​adjusted according to the input parameters to determine the final braking force distribution ratio and adjustment amount of each wheel; The brake fluid pressure of each wheel is adjusted based on the determined braking force distribution ratio and adjustment amount of each wheel.

2. The vehicle brake-by-wire method according to claim 1, characterized in that: Identifying a road condition based on the environmental information includes: Use the on-board camera to collect image information around the vehicle; Processing the collected image information to extract road features; the road features include road surface texture, signs, color, and surrounding object features; The road conditions are divided into different categories according to the extracted road features, and the different categories of road conditions include dry road surface, wet road surface and icy road surface.

3. The vehicle brake-by-wire method according to claim 2, characterized in that: The dynamic parameters of the vehicle are obtained based on the vehicle posture information and the vehicle dynamics model, including: Measuring vehicle acceleration, angular velocity and attitude angle based on inertial measurement unit; Based on the vehicle dynamics model, calculate the vehicle's speed, center of mass position, center of mass sideslip angle and vertical load of each wheel; The vehicle's roll moment and pitch moment are calculated based on the vehicle's suspension system characteristics and tire characteristics.

4. The vehicle brake-by-wire method according to claim 3, characterized in that: Obtaining a vehicle state assessment result based on the identified road condition and the vehicle dynamic parameters, including: Determine the basic braking characteristics of the vehicle under the current road condition based on the identified road condition; wherein, for a dry road surface, determine the braking friction coefficient range to be a first braking friction coefficient range, and the maximum allowable braking deceleration to be the first maximum braking deceleration; for a slippery road surface, determine the braking friction coefficient range to be a second braking friction coefficient range, and the maximum allowable braking deceleration to be the second maximum braking deceleration, and the second braking friction coefficient range is smaller than the first braking friction coefficient range, and the second maximum braking deceleration is smaller than the first maximum braking deceleration; for an icy road surface, determine the braking friction coefficient range to be a third braking friction coefficient range, and the maximum allowable braking deceleration to be the third maximum braking deceleration, and the third braking friction coefficient range is smaller than the second braking friction coefficient range, and the third maximum braking deceleration is smaller than the second maximum braking deceleration; Evaluate the vehicle's driving stability based on the vehicle's dynamic parameters; The vehicle status assessment results are obtained based on the basic braking characteristics of the road conditions and the driving stability of the vehicle and are divided into different levels; the different levels include safe state, low-risk state, medium-risk state and high-risk state.

5. The vehicle brake-by-wire method according to claim 1, characterized in that: The initial braking force distribution ratio range found in the braking force distribution matrix is ​​adjusted according to the input parameters to determine the final braking force distribution ratio and adjustment amount for each wheel, including: Inputting the vehicle's deceleration, wheel slip rate, yaw rate, and wheel angular acceleration as input vectors into a neural network; the neural network considers optimal braking force distribution under different input parameter combinations during training; After the forward propagation calculation of the neural network, the braking force distribution ratio and adjustment amount of each wheel are obtained; The initial ratio range provided by the comprehensive braking force distribution matrix and the adjustment amount obtained by the braking force adjustment algorithm are used to determine the final braking force distribution ratio and adjustment amount of each wheel.

6. The vehicle brake-by-wire method according to claim 5, characterized in that: The neural network has the following structure: an input layer comprising four neurons that receive the vehicle's deceleration, wheel slip rate, yaw angular velocity, and wheel angular acceleration; two hidden layers, the first hidden layer comprising 16 neurons and the second hidden layer comprising 8 neurons; an output layer comprising eight neurons, the first four neurons of which output the braking force distribution ratio of each wheel, and the last four neurons output the braking force adjustment amount of each wheel; a mean square error is used as a loss function; vehicle data of various braking operations performed by vehicles under different road conditions are collected as training samples, the vehicle data including the vehicle's deceleration, wheel slip rate, yaw angular velocity, wheel angular acceleration, and the corresponding optimal braking force distribution ratio and adjustment amount; the training data is input into the neural network, forward propagation calculation is performed, and back propagation is performed to update the network weights and bias based on the mean square error between the calculated result and the actual result, and iteration is repeated until the loss value is less than a first preset value.

7. The vehicle brake-by-wire method according to claim 6, characterized in that: The steps of establishing the braking force distribution matrix include: Divide the vehicle status assessment results into multiple status categories based on various possible road conditions and different driving states of the vehicle; For each state category, the braking force distribution ratio range of each wheel is preliminarily determined by combining vehicle dynamics theory and historical braking data; Using vehicle dynamics simulation software to simulate and verify the initially determined braking force distribution ratio range; adjusting the braking force distribution ratio range according to the simulation results; Conduct braking tests at different test sites using test scenarios based on the aforementioned different state categories. Collect actual vehicle braking data, analyze the vehicle's braking performance under the initial braking force distribution ratio range in different states, and adjust the braking force distribution ratio range based on the performance test results. The braking force distribution ratio range of each wheel under different vehicle state evaluation results determined after theoretical analysis, simulation verification and test verification is stored in the braking force distribution matrix.

8. A brake-by-wire system for an unmanned vehicle, characterized in that: include: The first processing module is used to obtain the vehicle's surrounding environment information and vehicle posture information; a second processing module, configured to: identify a road condition based on the environmental information and obtain dynamic parameters of the vehicle based on the vehicle posture information and a vehicle dynamics model; the dynamic parameters of the vehicle including vehicle speed, acceleration, center of mass position, center of mass sideslip angle, and vertical load of each wheel; The third processing module is used to obtain a vehicle state evaluation result based on the identified road conditions and the vehicle dynamic parameters; the vehicle state evaluation result is obtained based on the driving state and potential risks of the vehicle under the current road conditions, and the vehicle state evaluation result includes a safe state, a low-risk state, a medium-risk state, and a high-risk state; wherein, When the vehicle is on a dry road, the speed does not exceed the first speed threshold, the center of mass position offset does not exceed the first center of mass offset threshold, the acceleration does not exceed the first acceleration threshold, and the center of mass sideslip angle does not exceed the first sideslip angle threshold, the vehicle state assessment result is classified as a safe state; When the vehicle is on a slippery road, the speed is greater than the first speed threshold and less than the second speed threshold, the center of mass offset is greater than the first center of mass offset threshold and less than the second center of mass offset threshold, or the maximum difference in wheel vertical load is greater than the first load difference threshold and less than the second load difference threshold, the vehicle state assessment result is classified as a low-risk state; When the vehicle is on an icy road and the speed is greater than the second speed threshold, or the sideslip angle of the center of mass is greater than the second sideslip angle threshold, or the wheel slip rate of the vehicle is greater than the first slip rate threshold during braking, the vehicle state assessment result is classified as a medium-risk state; When the vehicle is in any road condition, the speed is greater than the third speed threshold, or the center of mass position offset is greater than the second center of mass offset threshold, or the acceleration is greater than the second acceleration threshold, or the maximum difference in wheel vertical load is greater than the second load difference threshold, the vehicle state assessment result is classified as a high-risk state; a fourth processing module, configured to determine, based on the vehicle state assessment result, a braking force distribution ratio and an adjustment amount for each wheel using a braking force distribution matrix and a braking force adjustment algorithm; wherein the braking force distribution matrix stores a braking force distribution ratio range for each wheel under different vehicle state assessment results; for a safe state, searching for a first braking force distribution ratio range; for a low-risk state, searching for a second braking force distribution ratio range; for a medium-risk state, searching for a third braking force distribution ratio range; and for a high-risk state, searching for a fourth braking force distribution ratio range; and inputting the vehicle's deceleration, wheel slip rate, yaw angular velocity, and wheel angular acceleration as input parameters into the braking force adjustment algorithm, and adjusting the initial braking force distribution ratio range found in the braking force distribution matrix according to the input parameters to determine a final braking force distribution ratio and adjustment amount for each wheel. The fifth processing module is used to adjust the brake fluid pressure of each wheel based on the determined braking force distribution ratio and adjustment amount of each wheel.

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