A new energy unmanned tractor braking control method and system

Abstract

The application relates to the technical field of brake control, and discloses a new energy unmanned tractor brake control method and system. The method comprises the following steps: performing difference analysis on real-time operation data of a new energy unmanned tractor to obtain vehicle speed deviation data and wheel speed difference states; monitoring vehicle environment data, classifying segmented features of front slope information and obstacle distance information to obtain slope feature categories and distance feature categories; performing state space mapping on the slope feature categories, the distance feature categories and the vehicle speed deviation data to confirm a basic brake demand; adjusting a wheel brake pressure distribution ratio to obtain a wheel brake pressure parameter; encoding the wheel brake pressure parameter into a brake instruction to drive brake operation; and performing control effect evaluation on related data after brake operation to correct corresponding relationship parameters of state space mapping and wheel brake pressure distribution parameters. The application can improve the efficiency of new energy unmanned tractor brake control.

Description

Technical Field

[0001] This invention relates to the field of braking control technology, and in particular to a braking control method and system for a new energy unmanned tractor. Background Technology

[0002] In the current braking control process of new energy unmanned tractors, the analysis of real-time operating data is mostly limited to the independent processing of single-dimensional parameters. It fails to effectively integrate the differences and correlations between vehicle speed data and wheel speed data, resulting in the inability to accurately obtain the synergistic influence information between vehicle speed deviation data and wheel speed difference status. Consequently, the judgment of vehicle operating status is biased, and the confirmation of basic braking needs lacks comprehensive data support, affecting the accuracy of the initial decision-making for braking control.

[0003] Existing technologies for processing vehicle environmental data employ simplistic methods for classifying features related to slope and obstacle distance. They lack multi-level threshold grading after high-frequency noise filtering and fail to incorporate real-time operational data as a state correction factor for joint logical adjustment. This results in insufficient accuracy in classifying slope and distance features. Furthermore, in the braking pressure distribution phase, the appropriate matching relationship between wheel speed differences, braking intensity, and braking mode is not fully considered, leading to unreasonable wheel braking pressure distribution ratios and reduced stability and reliability of braking operations. Therefore, improving the accuracy and stability of braking control for new energy unmanned tractors has become an urgent problem to be solved. Summary of the Invention

[0004] This invention provides a braking control method and system for a new energy unmanned tractor to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides a braking control method for a new energy unmanned tractor, comprising:

[0006] S1. Perform difference analysis on the real-time operation data of the new energy unmanned tractor to obtain the vehicle speed deviation data and wheel speed difference status of the new energy unmanned tractor;

[0007] S2. Monitor the vehicle environment data of the new energy unmanned tractor, and classify the slope information and obstacle distance information of the vehicle environment data into segmented features to obtain the slope feature category and distance feature category of the new energy unmanned tractor.

[0008] S3. Perform state-space mapping on the slope feature category, the distance feature category and the vehicle speed deviation data to confirm the basic braking requirements of the new energy unmanned tractor;

[0009] S4. Based on the basic braking requirements and the wheel speed difference state, adjust the wheel braking pressure distribution ratio of the new energy unmanned tractor to obtain the wheel braking pressure parameters of the new energy unmanned tractor.

[0010] S5. Encode the wheel braking pressure parameters into a braking command for the new energy unmanned tractor, and drive the new energy unmanned tractor to perform braking operation with the braking command;

[0011] S6. Evaluate the control effect of the actual wheel cylinder pressure value and actual longitudinal deceleration of the new energy unmanned tractor after braking operation, and correct the correspondence parameters of the state space mapping and the wheel braking pressure distribution parameters based on the evaluation results.

[0012] In a preferred embodiment, the step of performing difference analysis on the real-time operating data of the new energy unmanned tractor to obtain the vehicle speed deviation data and wheel speed difference status of the new energy unmanned tractor includes:

[0013] Acquire the vehicle speed data and wheel speed data of the new energy unmanned tractor, and use the vehicle speed data and wheel speed data as the real-time operating data of the new energy unmanned tractor;

[0014] The vehicle speed data is compared with the preset expected vehicle speed data to obtain the vehicle speed deviation data of the new energy unmanned tractor.

[0015] At the same time, the wheel speed data is analyzed to identify axle rotational speed anomalies, thereby obtaining the wheel speed difference status of the new energy unmanned tractor.

[0016] In a preferred embodiment, the monitoring of the vehicle environment data of the new energy unmanned tractor, and the segmentation and feature classification of the forward slope information and obstacle distance information of the vehicle environment data, to obtain the slope feature category and distance feature category of the new energy unmanned tractor, including:

[0017] Acquire the vehicle pitch angle change data, angle beam data, and distance raw point cloud data of the new energy unmanned tractor;

[0018] By filtering out the high-frequency noise components of the vehicle pitch angle change data and the angle beam data, the forward slope information of the new energy unmanned tractor is obtained.

[0019] Using the obstacle center in the original point cloud data as the origin, the straight-line distance from the new energy unmanned tractor to the obstacle center is analyzed to obtain the obstacle distance information of the new energy unmanned tractor;

[0020] The forward slope information and the obstacle distance information are subjected to multi-level threshold grading processing to obtain the discretized levels of the forward slope information and the obstacle distance information;

[0021] The real-time operating data is introduced as a state correction factor, and the discrete level is jointly logically adjusted to obtain the slope feature category and distance feature category of the new energy unmanned tractor.

[0022] In a preferred embodiment, the step of performing state-space mapping of the slope feature category, the distance feature category, and the vehicle speed deviation data to confirm the basic braking requirements of the new energy unmanned tractor includes:

[0023] Using the slope feature category as the first state identifier, the distance feature category as the second state identifier, and the vehicle speed deviation data as the third state identifier, a comprehensive state description of the new energy unmanned tractor is constructed.

[0024] Based on the comprehensive state description, the working condition mode of the new energy unmanned tractor is matched to confirm the target working condition mode of the new energy unmanned tractor.

[0025] Retrieve the braking strategy that is linked to the target operating mode;

[0026] The first state identifier, the second state identifier, and the third state identifier are mapped to the braking strategy to obtain the basic braking requirements of the new energy unmanned tractor.

[0027] In a preferred embodiment, adjusting the wheel braking pressure distribution ratio of the new energy unmanned tractor according to the basic braking demand and the wheel speed difference state to obtain the wheel braking pressure parameters of the new energy unmanned tractor includes:

[0028] Semantic parsing is performed on the basic braking requirements to obtain the braking intensity level and braking mode type of the basic braking requirements;

[0029] Using the braking intensity level, the braking mode type, and the wheel speed difference state as composite control parameters, a preset braking force mapping table is queried to determine the overall braking force requirement and the independent braking force requirement of the wheels of the new energy unmanned tractor.

[0030] Based on the overall braking force requirement and the independent braking force requirement of each wheel, the wheel braking pressure distribution ratio of the new energy unmanned tractor is calculated.

[0031] The wheel braking pressure distribution ratio is used to synthesize parameters to obtain the wheel braking pressure parameters of the new energy unmanned tractor.

[0032] In a preferred embodiment, the formula for calculating the wheel braking pressure distribution ratio is as follows:

[0033] ;

[0034] In the formula, Indicates the first The braking pressure distribution ratio of each wheel This indicates the total number of wheels of the new energy unmanned tractor. Indicates the first The independent braking force requirement of each wheel Indicates the first The load distribution correction factor for each wheel. This indicates the preset slip sensitivity adjustment factor. Indicates the first Real-time linear velocity of each wheel This represents the average linear velocity of the wheel. Indicates the overall braking force demand. Indicates the first Additional force term for each wheel's mode. Indicates the first Additional force term for each wheel's mode. This indicates taking the absolute value. This indicates a summation operation.

[0035] In a preferred embodiment, encoding the wheel braking pressure parameters into a braking command for the new energy unmanned tractor, and driving the new energy unmanned tractor to perform braking operations using the braking command, includes:

[0036] The wheel braking pressure parameters are bound to the corresponding wheel identifiers, and the bound wheel braking pressure parameters and wheel identifiers are encapsulated into a braking command data frame for the new energy unmanned tractor.

[0037] The braking command data frame is sent to the braking actuator node of the new energy unmanned tractor;

[0038] The brake actuator node parses the brake command data frame to generate the pulse width modulation signal of the new energy unmanned tractor;

[0039] The pulse width modulation signal is applied to the brake pressure regulating valve of the new energy unmanned tractor to drive the opening degree of the brake pressure regulating valve to change.

[0040] Based on the change in opening degree, the flow rate of brake fluid flowing through the brake pressure regulating valve is changed, and the hydraulic pressure in the corresponding wheel brake cylinder of the new energy unmanned tractor is controlled in real time to perform the braking operation of the new energy unmanned tractor.

[0041] In a preferred embodiment, the step of evaluating the control effect of the actual wheel cylinder pressure value and actual longitudinal deceleration of the new energy unmanned tractor after braking operation, and correcting the correspondence parameters of the state space mapping and the wheel braking pressure parameters based on the evaluation results, includes:

[0042] The actual wheel cylinder pressure value and actual longitudinal deceleration of the new energy unmanned tractor after braking operation are compared and analyzed to obtain the pressure deviation value and longitudinal deceleration deviation value of the new energy unmanned tractor after braking operation.

[0043] The control effect of the braking operation is evaluated based on the pressure deviation value and the longitudinal deceleration deviation value.

[0044] When the control effect result is that the control effect does not meet the standard, the pressure deviation value and the longitudinal deceleration deviation value are mapped to a preset parameter compensation table, the compensation amount of the corresponding relationship parameter of the state space mapping and the compensation amount of the wheel braking pressure parameter are determined, and the compensation amount is superimposed on the corresponding parameter value.

[0045] In a preferred embodiment, evaluating the control effect of the braking operation based on the pressure deviation value and the longitudinal deceleration deviation value includes:

[0046] The absolute value of the pressure deviation is compared with a preset allowable pressure deviation threshold.

[0047] The absolute value of the longitudinal deceleration deviation is compared with a preset allowable threshold for longitudinal deceleration deviation.

[0048] If the absolute value of the pressure deviation does not exceed the allowable threshold for pressure deviation, and the absolute value of the longitudinal deceleration deviation does not exceed the allowable threshold for longitudinal deceleration deviation, then the control effect is deemed to be satisfactory.

[0049] If the absolute value of the pressure deviation exceeds the allowable threshold for pressure deviation, or the absolute value of the longitudinal deceleration deviation exceeds the allowable threshold for longitudinal deceleration deviation, then the control effect is deemed unsatisfactory.

[0050] The control effect being deemed satisfactory or unsatisfactory is taken as the control effect result of the braking operation.

[0051] To address the above problems, the present invention also provides a braking control system for a new energy unmanned tractor, the system comprising:

[0052] The data difference analysis module is used to perform difference analysis on the real-time operation data of the new energy unmanned tractor, and obtain the vehicle speed deviation data and wheel speed difference status of the new energy unmanned tractor.

[0053] The environmental data monitoring and feature classification module is used to monitor the vehicle environmental data of the new energy unmanned tractor, and to perform segmented feature classification on the forward slope information and obstacle distance information of the vehicle environmental data to obtain the slope feature category and distance feature category of the new energy unmanned tractor.

[0054] The state-space mapping and basic braking requirement confirmation module is used to perform state-space mapping on the slope feature category, the distance feature category and the vehicle speed deviation data to confirm the basic braking requirements of the new energy unmanned tractor.

[0055] The brake pressure distribution ratio adjustment module is used to adjust the wheel brake pressure distribution ratio of the new energy unmanned tractor according to the basic braking requirements and the wheel speed difference state, so as to obtain the wheel brake pressure parameters of the new energy unmanned tractor.

[0056] The braking command encoding and execution module is used to encode the wheel braking pressure parameters into braking commands for the new energy unmanned tractor, and to drive the new energy unmanned tractor to perform braking operations using the braking commands.

[0057] The braking control effect evaluation and parameter correction module is used to evaluate the actual wheel cylinder pressure value and actual longitudinal deceleration of the new energy unmanned tractor after braking operation, and correct the corresponding relationship parameters of the state space mapping and the wheel braking pressure parameters based on the evaluation results.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] 1. This invention, through differential analysis of real-time operating data of new energy unmanned tractors, can accurately obtain vehicle speed deviation data and wheel speed difference status; simultaneously, it performs high-frequency noise filtering and multi-level threshold grading on vehicle environmental data, and introduces real-time operating data as a state correction factor to accurately obtain slope and distance feature categories. Then, through state-space mapping to construct a comprehensive state description and matching operating mode to confirm basic braking requirements, braking decisions can fully align with vehicle operation and environmental realities, significantly improving the targeting of braking control and the accuracy of initial decisions.

[0060] 2. Based on the basic braking requirements and wheel speed differences, the wheel braking pressure distribution ratio can be calculated using a formula to achieve a reasonable distribution of braking pressure to each wheel, ensuring the stability of braking operation. Furthermore, after braking, by evaluating the actual wheel cylinder pressure value and longitudinal deceleration, the corresponding parameters of the state space mapping and the wheel braking pressure parameters can be corrected, continuously optimizing the control effect and further improving the accuracy and reliability of braking control, effectively ensuring the braking safety and efficiency of new energy unmanned tractors. Attached Figure Description

[0061] Figure 1 This is a flowchart illustrating a braking control method for a new energy unmanned tractor according to an embodiment of the present invention.

[0062] Figure 2 A functional block diagram of a braking control system for a new energy unmanned tractor provided in an embodiment of the present invention;

[0063] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0064] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0065] This application provides a braking control method for a new energy unmanned tractor. The executing entity of this new energy unmanned tractor braking control method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application embodiment: a server, a terminal, etc. In other words, the new energy unmanned tractor braking control method can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0066] Reference Figure 1 The diagram shown is a flowchart illustrating a braking control method for a new energy unmanned tractor according to an embodiment of the present invention. In this embodiment, the braking control method for a new energy unmanned tractor includes:

[0067] S1. Perform difference analysis on the real-time operation data of the new energy unmanned tractor to obtain the vehicle speed deviation data and wheel speed difference status of the new energy unmanned tractor;

[0068] In this embodiment of the invention, the step of performing difference analysis on the real-time operating data of the new energy unmanned tractor to obtain the vehicle speed deviation data and wheel speed difference status of the new energy unmanned tractor includes:

[0069] Acquire the vehicle speed data and wheel speed data of the new energy unmanned tractor, and use the vehicle speed data and wheel speed data as the real-time operating data of the new energy unmanned tractor;

[0070] The vehicle speed data is compared with the preset expected vehicle speed data to obtain the vehicle speed deviation data of the new energy unmanned tractor.

[0071] At the same time, the wheel speed data is analyzed to identify axle rotational speed anomalies, thereby obtaining the wheel speed difference status of the new energy unmanned tractor.

[0072] The vehicle speed data during the driving process is collected in real time by the vehicle speed sensor installed on the new energy unmanned tractor. At the same time, the wheel speed data of the corresponding wheel is collected in real time by the wheel speed sensor installed on each wheel of the vehicle. The collected vehicle speed data and the wheel speed data of all wheels are combined to determine the real-time operation data of the new energy unmanned tractor.

[0073] The desired vehicle speed data is set in advance according to the operating scenario requirements or preset control targets of the new energy unmanned tractor. Then, the collected real-time vehicle speed data is compared with the preset desired vehicle speed data one by one. Specifically, the vehicle speed data collected at the same time is subtracted from the preset desired vehicle speed data at that time. The result of each time is the vehicle speed deviation data of the new energy unmanned tractor.

[0074] Select any common time point and extract the wheel speed data of all wheels at that time point. Group the wheels according to the axle to which they belong. For example, group the wheel speed data of the front wheels of the vehicle into the front axle wheel speed group and the wheel speed data of the rear wheels into the rear axle wheel speed group. Calculate the arithmetic mean of the wheel speed data of all wheels in each axle wheel speed group. Then compare the arithmetic mean of different axle wheel speed groups. If the difference between the arithmetic mean of different axle wheel speed groups exceeds the reasonable range of wheel speed deviation when the vehicle is driving normally, it is determined that there is an abnormal inter-axle speed at that moment. Record this abnormal inter-axle speed situation to form the wheel speed difference status of the new energy unmanned tractor.

[0075] The beneficial effects are that the vehicle speed data and wheel speed data of the new energy unmanned tractor, as well as the real-time operating data determined by them, can be accurately obtained through a clear collection and processing method. Then, through a standardized difference comparison and inter-axle speed anomaly identification process, the vehicle speed deviation data and wheel speed difference status can be accurately obtained, providing accurate and reliable basic data support for the subsequent steps of braking control of the new energy unmanned tractor.

[0076] S2. Monitor the vehicle environment data of the new energy unmanned tractor, and classify the slope information and obstacle distance information of the vehicle environment data into segmented features to obtain the slope feature category and distance feature category of the new energy unmanned tractor.

[0077] In this embodiment of the invention, the monitoring of the vehicle environment data of the new energy unmanned tractor, and the segmentation and feature classification of the forward slope information and obstacle distance information of the vehicle environment data, to obtain the slope feature category and distance feature category of the new energy unmanned tractor, including:

[0078] Acquire the vehicle pitch angle change data, angle beam data, and distance raw point cloud data of the new energy unmanned tractor;

[0079] By filtering out the high-frequency noise components of the vehicle pitch angle change data and the angle beam data, the forward slope information of the new energy unmanned tractor is obtained.

[0080] Using the obstacle center in the original point cloud data as the origin, the straight-line distance from the new energy unmanned tractor to the obstacle center is analyzed to obtain the obstacle distance information of the new energy unmanned tractor;

[0081] The forward slope information and the obstacle distance information are subjected to multi-level threshold grading processing to obtain the discretized levels of the forward slope information and the obstacle distance information;

[0082] The real-time operating data is introduced as a state correction factor, and the discrete level is jointly logically adjusted to obtain the slope feature category and distance feature category of the new energy unmanned tractor.

[0083] By installing inertial measurement units and lidar equipment at key locations on the front of the vehicle and chassis of the new energy unmanned tractor, the inertial measurement units collect real-time data on the pitch angle changes in the vehicle's forward and backward directions during driving. The angle detection module of the lidar equipment collects real-time angle beam data of the area in front, and the point cloud acquisition module of the lidar equipment collects real-time raw point cloud data of the distance to obstacles in the environment in front. Thus, the vehicle pitch angle change data, angle beam data, and raw point cloud data of the new energy unmanned tractor are obtained.

[0084] High-frequency noise components in vehicle pitch angle change data and angle beam data are filtered out using a low-pass filter. Specifically, the vehicle pitch angle change data and angle beam data are input into a preset low-pass filter module. This module only allows signals below a set frequency threshold to pass through, while high-frequency noise signals above the threshold are blocked. Then, the vehicle pitch angle change data after filtering out high-frequency noise is correlated and integrated with the angle beam data. The deviation caused by vehicle body vibration in the angle beam data is corrected by the vehicle pitch angle change data, and finally, the slope information of the new energy unmanned tractor ahead can be accurately reflected by the inclination of the road ahead.

[0085] First, the original point cloud data is preprocessed to filter out the point cloud data that belong to obstacles. By calculating the average coordinates of these obstacle point cloud data in the three-dimensional coordinate system, the position corresponding to the average value is determined as the obstacle center. The obstacle center is used as the origin to establish a local coordinate system. At the same time, the center position of the front end of the new energy unmanned tractor is determined as the vehicle reference point. The straight-line distance between the coordinates of the vehicle reference point in the local coordinate system and the coordinates of the origin of the obstacle center is calculated. The value of this straight-line distance is the obstacle distance information of the new energy unmanned tractor.

[0086] Multiple continuous and non-overlapping threshold intervals are pre-defined for the slope information ahead. For example, 0°-3° is set as the first threshold interval, 3°-8° as the second threshold interval, and above 8° as the third threshold interval. The specific value of the processed slope information ahead is compared with these threshold intervals to determine the threshold interval to which it belongs. The preset level corresponding to this threshold interval is the discretization level of the slope information ahead. Similarly, multiple continuous and non-overlapping threshold intervals are pre-defined for obstacle distance information ahead. For example, 0-4 meters is set as the first threshold interval, 4-10 meters as the second threshold interval, and above 10 meters as the third threshold interval. The specific value of the obstacle distance information ahead is compared with these threshold intervals to determine the threshold interval to which it belongs. The preset level corresponding to this threshold interval is the discretization level of the obstacle distance information ahead.

[0087] The real-time operating data of the new energy unmanned tractor obtained in step S1 is introduced as a state correction factor to jointly adjust the discretization level of the forward slope information and obstacle distance information. For example, when the vehicle speed deviation data in the real-time operating data shows that the actual vehicle speed is higher than the expected vehicle speed, and the discretization level of the forward slope information is the level corresponding to the first threshold interval, the discretization level of the forward slope information is adjusted to the level corresponding to the second threshold interval. When the wheel speed difference status shows no abnormal rotation speed between axles, and the discretization level of the obstacle distance information is the level corresponding to the second threshold interval, the discretization level is kept unchanged. After the above joint logical adjustment, the final discretization level of the forward slope information is the slope feature category of the new energy unmanned tractor, and the discretization level of the obstacle distance information is the distance feature category of the new energy unmanned tractor.

[0088] The beneficial effect is that it can accurately acquire key information from vehicle environmental data through clear equipment collection and data processing methods, and transform it into information on the slope ahead and the distance to obstacles. Then, through multi-level threshold classification and real-time operation data correction, it can ensure that the obtained slope feature categories and distance feature categories accurately match the actual environmental conditions, providing accurate environmental data support for the subsequent confirmation of the braking requirements of new energy unmanned tractors.

[0089] S3. Perform state-space mapping on the slope feature category, the distance feature category and the vehicle speed deviation data to confirm the basic braking requirements of the new energy unmanned tractor;

[0090] In this embodiment of the invention, the step of performing state-space mapping of the slope feature category, the distance feature category, and the vehicle speed deviation data to confirm the basic braking requirements of the new energy unmanned tractor includes:

[0091] Using the slope feature category as the first state identifier, the distance feature category as the second state identifier, and the vehicle speed deviation data as the third state identifier, a comprehensive state description of the new energy unmanned tractor is constructed.

[0092] Based on the comprehensive state description, the working condition mode of the new energy unmanned tractor is matched to confirm the target working condition mode of the new energy unmanned tractor.

[0093] Retrieve the braking strategy that is linked to the target operating mode;

[0094] The first state identifier, the second state identifier, and the third state identifier are mapped to the braking strategy to obtain the basic braking requirements of the new energy unmanned tractor.

[0095] The slope feature category obtained after processing vehicle environmental data is defined as the first state identifier, the distance feature category obtained after processing vehicle environmental data is defined as the second state identifier, and the vehicle speed deviation data obtained after analyzing the differences in real-time operating data is defined as the third state identifier. Then, these three identifiers are combined in a fixed format of "first state identifier - second state identifier - third state identifier". At the same time, during the combination process, the specific state information corresponding to each identifier is supplemented, such as the specific level of the slope feature category, the specific level of the distance feature category, and the specific value of the vehicle speed deviation data, to form a text or data combination that can comprehensively reflect the correlation between the current environment and operating status of the new energy unmanned tractor. This combination is the comprehensive state description of the new energy unmanned tractor.

[0096] Multiple preset working condition modes are pre-stored in the control unit of the new energy unmanned tractor. Each preset working condition mode corresponds to a specific set of "slope feature category - distance feature category - vehicle speed deviation data" combination features. Then, the constructed comprehensive state description is compared with the combination features of all preset working condition modes one by one. During the comparison, the focus is on checking whether the specific information of the three identifiers in the comprehensive state description completely matches or conforms to the combination features of a certain preset working condition mode. When the preset working condition mode with the highest matching degree with the comprehensive state description and which meets the matching rules is found, this preset working condition mode is the target working condition mode of the new energy unmanned tractor.

[0097] A one-to-one binding relationship between operating modes and braking strategies is pre-established in the control unit of the new energy unmanned tractor, forming an operating mode-braking strategy binding table. This binding table clearly records the specific braking strategy corresponding to each preset operating mode, including braking intervention timing, initial braking force range, etc. After confirming the target operating mode, the control unit searches the operating mode-braking strategy binding table according to the name or code of the target operating mode, finds the braking strategy entry corresponding to the target operating mode, extracts the specific braking strategy content from the entry, and completes the retrieval of the braking strategy bound to the target operating mode.

[0098] The first, second, and third state identifiers are associated with the corresponding parameter dimensions in the retrieved braking strategy. For example, the level of the slope feature category is mapped to the braking adjustment parameters related to the slope in the braking strategy, the level of the distance feature category is mapped to the braking response speed parameters related to the distance to obstacles in the braking strategy, and the value of the vehicle speed deviation data is mapped to the braking intensity parameters related to the vehicle speed deviation in the braking strategy. Through this dimension mapping method, the specific information of the three identifiers is integrated into the parameter configuration of the braking strategy, ultimately forming an information set containing specific braking parameter requirements. This information set is the basic braking requirement of the new energy unmanned tractor.

[0099] The beneficial effects are that by defining clear status identifiers and constructing comprehensive status descriptions, it is possible to fully integrate the environmental status information of new energy unmanned tractors after environmental data processing and the operational status information after real-time operation data analysis. Then, through precise working condition mode matching and binding braking strategy retrieval, as well as the precise mapping of the three status identifiers to the braking strategy, it can ensure that the final confirmed basic braking requirements are fully adapted to the current actual situation of the vehicle, providing accurate and reliable demand basis for subsequent braking pressure adjustment and braking operation execution.

[0100] S4. Based on the basic braking requirements and the wheel speed difference state, adjust the wheel braking pressure distribution ratio of the new energy unmanned tractor to obtain the wheel braking pressure parameters of the new energy unmanned tractor.

[0101] In this embodiment of the invention, adjusting the wheel braking pressure distribution ratio of the new energy unmanned tractor according to the basic braking demand and the wheel speed difference state to obtain the wheel braking pressure parameters of the new energy unmanned tractor includes:

[0102] Semantic parsing is performed on the basic braking requirements to obtain the braking intensity level and braking mode type of the basic braking requirements;

[0103] Using the braking intensity level, the braking mode type, and the wheel speed difference state as composite control parameters, a preset braking force mapping table is queried to determine the overall braking force requirement and the independent braking force requirement of the wheels of the new energy unmanned tractor.

[0104] Based on the overall braking force requirement and the independent braking force requirement of each wheel, the wheel braking pressure distribution ratio of the new energy unmanned tractor is calculated.

[0105] The wheel braking pressure distribution ratio is used to synthesize parameters to obtain the wheel braking pressure parameters of the new energy unmanned tractor.

[0106] The formula for calculating the wheel braking pressure distribution ratio is as follows:

[0107] ;

[0108] In the formula, Indicates the first The braking pressure distribution ratio of each wheel This indicates the total number of wheels of the new energy unmanned tractor. Indicates the first The independent braking force requirement of each wheel Indicates the first The load distribution correction factor for each wheel. This indicates the preset slip sensitivity adjustment factor. Indicates the first Real-time linear velocity of each wheel This represents the average linear velocity of the wheel. Indicates the overall braking force demand. Indicates the first Additional force term for each wheel's mode. Indicates the first Additional force term for each wheel's mode. This indicates taking the absolute value. This indicates a summation operation.

[0109] The basic braking requirements of the confirmed new energy unmanned tractors are semantically parsed. The basic braking requirements contain structured information related to braking. According to the preset semantic parsing rules, they are divided into a braking intensity description part and a braking mode description part. From the braking intensity description part, keywords such as "light", "moderate" and "severe" indicating the intensity level are identified to determine the corresponding braking intensity level. From the braking mode description part, keywords such as "conventional braking", "emergency braking" and "retarded braking" indicating the braking method are identified to determine the corresponding braking mode type. Thus, the braking intensity level and braking mode type of the basic braking requirements are obtained.

[0110] A pre-set braking force mapping table is stored in the control unit of the new energy unmanned tractor. This mapping table records the overall braking force requirement and the independent braking force requirement of each wheel corresponding to different combinations of braking intensity levels, braking mode types and wheel speed difference states. The obtained braking intensity level, braking mode type and wheel speed difference state obtained after analyzing the differences in real-time operating data are used as composite control parameters. The table entries that completely match the specific values ​​of these three parameters are searched in the pre-set braking force mapping table. The corresponding numerical information is extracted from the matching entries to determine the overall braking force requirement and the independent braking force requirement of each wheel of the new energy unmanned tractor.

[0111] When calculating the wheel braking pressure distribution ratio of the new energy unmanned tractor, the calculation is first performed for each wheel. The independent braking force requirement of that wheel is multiplied by the load distribution correction coefficient of that wheel. The load distribution correction coefficient is a parameter that is preset and stored in the control unit based on the vehicle structure, wheel installation position, and typical working load distribution characteristics of the new energy unmanned tractor. Next, the difference between the real-time linear velocity and the average linear velocity of the wheel is calculated. The real-time linear velocity of the wheel is obtained by collecting wheel speed data from the wheel speed sensor, combining it with the preset diameter of the wheel, multiplying the wheel speed data by the wheel circumference, and then dividing by the unit time. The average linear velocity of the wheel is obtained by adding the real-time linear velocities of all wheels and dividing by the total number of wheels of the new energy unmanned tractor. Then, the absolute value of the above difference is taken, divided by the average linear velocity of the wheel, and multiplied by a preset slip sensitivity adjustment factor. The numerator is a parameter that is pre-set and stored in the control unit based on the braking system characteristics, tire grip performance, and different working road conditions of the new energy unmanned tractor. Then, this product is subtracted from 1, and the previously obtained "product of independent braking force demand and load distribution correction coefficient" is multiplied by this result. The mode additional force term of the wheel is added. The mode additional force term of the wheel is a parameter that is pre-set and stored in the control unit according to the different braking mode types of the new energy unmanned tractor and is retrieved according to the braking mode type. This gives the numerator value of the wheel. Then, the denominator value is calculated. The sum of the overall braking force demand and the mode additional force terms of all wheels is used as the denominator. The sum of the mode additional force terms of all wheels is obtained by accumulating the mode additional force terms of each wheel in sequence. Finally, the numerator value of each wheel is divided by the denominator value to obtain the braking pressure distribution ratio of each wheel, that is, the wheel braking pressure distribution ratio of the new energy unmanned tractor.

[0112] The baseline braking pressure value of the braking system is determined in advance based on the overall power requirements of the new energy unmanned tractor. The braking pressure distribution ratio of each wheel is multiplied by the baseline braking pressure value to obtain the specific braking pressure value corresponding to each wheel. The specific braking pressure values ​​of all wheels are associated and integrated with the corresponding wheel identifiers. The wheel identifiers are exclusive identifiers used to distinguish different wheels, such as left front wheel, right front wheel, left rear wheel, and right rear wheel. This forms a parameter set containing the corresponding braking pressure value of each wheel, thus obtaining the wheel braking pressure parameters of the new energy unmanned tractor.

[0113] The beneficial effects are that semantic parsing of basic braking requirements can accurately obtain two core braking parameters: braking intensity level and braking mode type. Combined with the pre-set braking force mapping table for wheel speed difference status query, the accuracy and reliability of overall braking force requirements and independent wheel braking force requirements can be ensured. When calculating the wheel braking pressure distribution ratio, the independent wheel braking force requirements, load distribution correction, slip influence adjustment, and additional force terms of braking mode are fully incorporated, so that the braking pressure distribution ratio of each wheel can accurately match its actual braking requirements. Then, through parameter synthesis, the distribution ratio is converted into specific braking pressure values ​​for each wheel. The final wheel braking pressure parameters can provide a precise basis for subsequent braking command coding and execution, effectively ensuring the coordination of braking force of each wheel during the braking process and improving the stability and safety of braking of new energy unmanned tractors.

[0114] S5. Encode the wheel braking pressure parameters into a braking command for the new energy unmanned tractor, and drive the new energy unmanned tractor to perform braking operation with the braking command;

[0115] In this embodiment of the invention, encoding the wheel braking pressure parameters into a braking command for the new energy unmanned tractor, and driving the new energy unmanned tractor to perform braking operations using the braking command, includes:

[0116] The wheel braking pressure parameters are bound to the corresponding wheel identifiers, and the bound wheel braking pressure parameters and wheel identifiers are encapsulated into a braking command data frame for the new energy unmanned tractor.

[0117] The braking command data frame is sent to the braking actuator node of the new energy unmanned tractor;

[0118] The brake actuator node parses the brake command data frame to generate the pulse width modulation signal of the new energy unmanned tractor;

[0119] The pulse width modulation signal is applied to the brake pressure regulating valve of the new energy unmanned tractor to drive the opening degree of the brake pressure regulating valve to change.

[0120] Based on the change in opening degree, the flow rate of brake fluid flowing through the brake pressure regulating valve is changed, and the hydraulic pressure in the corresponding wheel brake cylinder of the new energy unmanned tractor is controlled in real time to perform the braking operation of the new energy unmanned tractor.

[0121] First, the wheel identifiers corresponding to each wheel of the new energy unmanned tractor are clearly defined. The wheel identifiers are unique identifiers used to distinguish different wheels, such as "left front wheel", "right front wheel", "left rear wheel", and "right rear wheel". The wheel braking pressure parameters obtained by adjusting the wheel braking pressure distribution ratio are associated one by one with the corresponding wheel identifiers. That is, each wheel identifier is bound to a unique wheel braking pressure parameter. Then, according to the preset data frame format, all the bound wheel braking pressure parameters and wheel identifiers are integrated into a structured data unit. This structured data unit is the braking command data frame of the new energy unmanned tractor.

[0122] The completed braking command data frame is transmitted in a preset communication protocol format via the on-board communication bus on the new energy unmanned tractor. During the transmission process, the integrity and accuracy of the data frame are ensured. The braking command data frame is directly sent to the brake actuator node on the new energy unmanned tractor that is responsible for performing the braking operation, so that the brake actuator node can receive the braking command data frame.

[0123] After receiving the braking command data frame, the brake actuator node decomposes the data frame according to the preset parsing rules, extracts the wheel identifier and the corresponding wheel braking pressure parameter from the data frame, determines the required signal output strength based on the extracted wheel braking pressure parameter, and generates a pulse width modulation signal that matches the braking pressure parameter of each wheel through the signal generation module inside the brake actuator node. The duty cycle of the pulse width modulation signal corresponds to the value of the wheel braking pressure parameter. The larger the value, the higher the signal duty cycle, and the smaller the value, the lower the signal duty cycle. The generated signal is the pulse width modulation signal of the new energy unmanned tractor.

[0124] The generated pulse width modulation signal is transmitted through wires to the brake pressure regulating valves corresponding to each wheel of the new energy unmanned tractor. The pulse width modulation signal is applied to the electromagnetic coil of the brake pressure regulating valve. The electromagnetic coil generates electromagnetic forces of different magnitudes according to the duty cycle of the signal. The electromagnetic force drives the valve core inside the brake pressure regulating valve to move. The amount of valve core displacement changes with the change of the signal duty cycle, thereby changing the valve opening of the brake pressure regulating valve. The higher the duty cycle, the larger the valve opening, and the lower the duty cycle, the smaller the valve opening, thus driving the change of the opening of the brake pressure regulating valve.

[0125] When the opening of the brake pressure regulating valve changes, the flow rate of brake fluid flowing through the valve changes accordingly. The larger the opening, the more brake fluid flows through per unit time, and the smaller the opening, the less brake fluid flows through per unit time. This brake fluid is directly delivered to the brake wheel cylinder of the corresponding wheel. The change in brake fluid flow rate causes the hydraulic pressure inside the brake wheel cylinder to change in real time. When the hydraulic pressure increases, it pushes the piston inside the brake wheel cylinder to move. The piston drives the brake shoes or brake pads to contact the brake drum or brake disc to generate friction. The friction hinders the rotation of the wheel, thereby performing the braking operation of the new energy unmanned tractor.

[0126] The beneficial effect is that by binding and encapsulating the wheel braking pressure parameters with wheel identifiers, the braking command can be accurately matched to each wheel. The pulse width modulation signal is generated by the communication bus transmission and the actuator node parsing, which enables precise control of the braking pressure regulating valve. In turn, the hydraulic pressure of the regulating wheel cylinder is changed by the brake fluid flow, which ultimately ensures that the braking operation can be executed accurately as required, effectively improving the accuracy and response speed of the braking operation of the new energy unmanned tractor.

[0127] S6. Evaluate the control effect of the actual wheel cylinder pressure value and actual longitudinal deceleration of the new energy unmanned tractor after braking operation, and correct the correspondence parameters of the state space mapping and the wheel braking pressure distribution parameters based on the evaluation results.

[0128] In this embodiment of the invention, the evaluation of the control effect of the actual wheel cylinder pressure value and actual longitudinal deceleration of the new energy unmanned tractor after braking operation, and the correction of the correspondence parameters of the state space mapping and the wheel braking pressure distribution parameters based on the evaluation results, includes:

[0129] The actual wheel cylinder pressure value and actual longitudinal deceleration of the new energy unmanned tractor after braking operation are compared and analyzed to obtain the pressure deviation value and longitudinal deceleration deviation value of the new energy unmanned tractor after braking operation.

[0130] The control effect of the braking operation is evaluated based on the pressure deviation value and the longitudinal deceleration deviation value.

[0131] When the control effect result is that the control effect does not meet the standard, the pressure deviation value and the longitudinal deceleration deviation value are mapped to a preset parameter compensation table, the compensation amount of the corresponding relationship parameter of the state space mapping and the compensation amount of the wheel braking pressure parameter are determined, and the compensation amount is superimposed on the corresponding parameter value.

[0132] The evaluation of the control effect of the braking operation based on the pressure deviation value and the longitudinal deceleration deviation value includes:

[0133] The absolute value of the pressure deviation is compared with a preset allowable pressure deviation threshold.

[0134] The absolute value of the longitudinal deceleration deviation is compared with a preset allowable threshold for longitudinal deceleration deviation.

[0135] If the absolute value of the pressure deviation does not exceed the allowable threshold for pressure deviation, and the absolute value of the longitudinal deceleration deviation does not exceed the allowable threshold for longitudinal deceleration deviation, then the control effect is deemed to be satisfactory.

[0136] If the absolute value of the pressure deviation exceeds the allowable threshold for pressure deviation, or the absolute value of the longitudinal deceleration deviation exceeds the allowable threshold for longitudinal deceleration deviation, then the control effect is deemed unsatisfactory.

[0137] The control effect being deemed satisfactory or unsatisfactory is taken as the control effect result of the braking operation.

[0138] Pressure sensors installed on the brake cylinders of each wheel of the new energy unmanned tractor are used to collect the actual hydraulic pressure value inside each brake cylinder after the braking operation. This value is the actual cylinder pressure value of the new energy unmanned tractor after the braking operation. At the same time, inertial measurement units installed on the vehicle body are used to collect the actual deceleration value of the vehicle along the driving direction after the braking operation. This value is the actual longitudinal deceleration of the new energy unmanned tractor after the braking operation.

[0139] The target wheel cylinder pressure value and target longitudinal deceleration set before the braking operation are obtained in advance. The actual wheel cylinder pressure value of each wheel is subtracted from the corresponding target wheel cylinder pressure value to obtain the pressure deviation value of each wheel. The average value of all wheel pressure deviation values ​​is taken as the pressure deviation value of the new energy unmanned tractor after the braking operation. The actual longitudinal deceleration is subtracted from the target longitudinal deceleration to obtain the longitudinal deceleration deviation value of the new energy unmanned tractor after the braking operation.

[0140] Based on the performance indicators and safety requirements of the new energy unmanned tractor braking system, preset pressure deviation allowable threshold and preset longitudinal deceleration allowable threshold are set and stored in advance. These two thresholds are used to determine whether the braking control effect meets the requirements.

[0141] Calculate the absolute value of the pressure deviation value, compare the absolute value with the preset allowable pressure deviation threshold, and determine whether the absolute value of the pressure deviation value is less than or equal to the preset allowable pressure deviation threshold. At the same time, calculate the absolute value of the longitudinal deceleration deviation value, compare the absolute value with the preset allowable longitudinal deceleration threshold, and determine whether the absolute value of the longitudinal deceleration deviation value is less than or equal to the preset allowable longitudinal deceleration threshold.

[0142] If the absolute value of the pressure deviation does not exceed the preset allowable pressure deviation threshold, and the absolute value of the longitudinal deceleration deviation does not exceed the preset allowable longitudinal deceleration threshold, then the control effect of the braking operation is directly determined to be satisfactory; if the absolute value of the pressure deviation exceeds the preset allowable pressure deviation threshold, or the absolute value of the longitudinal deceleration deviation exceeds the preset allowable longitudinal deceleration threshold, then the control effect of the braking operation is directly determined to be unsatisfactory, and "control effect satisfactory" or "control effect unsatisfactory" is taken as the control effect result of this braking operation.

[0143] A preset parameter compensation table is stored in the control unit of the new energy unmanned tractor. The parameter compensation table records the compensation amount of the corresponding relationship parameters of the state space mapping for different pressure deviation value ranges and longitudinal deceleration deviation value ranges, as well as the compensation amount of the wheel braking pressure distribution parameters for different pressure deviation value ranges and longitudinal deceleration deviation value ranges.

[0144] When the control effect result is that the control effect does not meet the standard, the deviation value range to which it belongs is determined based on the current pressure deviation value and the deviation value range to which it belongs based on the current longitudinal deceleration deviation value. The table entry that completely matches these two deviation value ranges is searched in the preset parameter compensation table. The compensation amount of the corresponding state space mapping parameter and the compensation amount of the corresponding wheel braking pressure distribution parameter are extracted from the table entry.

[0145] The compensation amount of the extracted state-space mapping correspondence parameters is added to the corresponding parameters of the currently used state-space mapping to obtain the corrected state-space mapping correspondence parameters; at the same time, the compensation amount of the extracted wheel braking pressure distribution parameters is added to the currently used wheel braking pressure distribution parameters to obtain the corrected wheel braking pressure distribution parameters, thus completing the correction of the two parameters.

[0146] The beneficial effects are that by collecting the actual wheel cylinder pressure value and actual longitudinal deceleration after braking, deviation analysis and effect evaluation can be carried out, which can accurately determine whether the braking control meets the standard. If it does not meet the standard, the compensation amount can be determined by the preset compensation table and the relevant parameters can be corrected. The accuracy of state space mapping and the rationality of wheel braking pressure distribution can be continuously optimized, ensuring that the subsequent braking control effect is continuously improved, and further enhancing the accuracy and reliability of braking of new energy unmanned tractors.

[0147] like Figure 2 The diagram shown is a functional block diagram of a braking control system for a new energy unmanned tractor provided in an embodiment of the present invention.

[0148] The new energy unmanned tractor braking control system 100 described in this invention can be installed in an electronic device. Depending on the functions implemented, the new energy unmanned tractor braking control system 100 may include an operation data difference analysis module 101, an environmental data monitoring and feature classification module 102, a state space mapping and basic braking demand confirmation module 103, a braking pressure distribution ratio adjustment module 104, a braking command encoding and execution module 105, and a braking control effect evaluation and parameter correction module 106. The module described in this invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, stored in the memory of the electronic device.

[0149] In this embodiment, the functions of each module / unit are as follows:

[0150] The operation data difference analysis module 101 is used to perform difference analysis on the real-time operation data of the new energy unmanned tractor to obtain the vehicle speed deviation data and wheel speed difference status of the new energy unmanned tractor.

[0151] The environmental data monitoring and feature classification module 102 is used to monitor the vehicle environmental data of the new energy unmanned tractor, and to perform segmented feature classification on the forward slope information and obstacle distance information of the vehicle environmental data to obtain the slope feature category and distance feature category of the new energy unmanned tractor.

[0152] The state space mapping and basic braking requirement confirmation module 103 is used to perform state space mapping on the slope feature category, the distance feature category and the vehicle speed deviation data to confirm the basic braking requirements of the new energy unmanned tractor.

[0153] The brake pressure distribution ratio adjustment module 104 is used to adjust the wheel brake pressure distribution ratio of the new energy unmanned tractor according to the basic braking requirements and the wheel speed difference state, so as to obtain the wheel brake pressure parameters of the new energy unmanned tractor.

[0154] The braking command encoding and execution module 105 is used to encode the wheel braking pressure parameters into braking commands for the new energy unmanned tractor, and drive the new energy unmanned tractor to perform braking operations using the braking commands.

[0155] The braking control effect evaluation and parameter correction module 106 is used to evaluate the actual wheel cylinder pressure value and actual longitudinal deceleration of the new energy unmanned tractor after braking operation, and correct the correspondence parameters of the state space mapping and the wheel braking pressure distribution parameters according to the evaluation results.

[0156] In the several embodiments provided by this invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0157] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0158] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0159] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0160] This application embodiment can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0161] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A new energy unmanned tractor braking control method, characterized in that, The method comprises: S1, difference analysis is performed on real-time running data of the new energy unmanned tractor, and vehicle speed deviation data and wheel speed difference state of the new energy unmanned tractor are obtained; S2, vehicle environment data of the new energy unmanned tractor is monitored, and front slope information and obstacle distance information of the vehicle environment data are classified by segmented features, and slope feature categories and distance feature categories of the new energy unmanned tractor are obtained; S3, the slope feature categories, the distance feature categories and the vehicle speed deviation data are mapped in a state space, and the basic braking demand of the new energy unmanned tractor is confirmed; S4, according to the basic braking demand and the wheel speed difference state, the wheel braking pressure distribution ratio of the new energy unmanned tractor is adjusted, and the wheel braking pressure parameter of the new energy unmanned tractor is obtained; S5, the wheel braking pressure parameter is encoded as a braking instruction of the new energy unmanned tractor, and the new energy unmanned tractor is driven by the braking instruction to perform a braking operation; S6, the actual wheel cylinder pressure value and the actual longitudinal deceleration of the new energy unmanned tractor after the braking operation are evaluated, and according to the evaluation result, the corresponding relationship parameter of the state space mapping and the wheel braking pressure distribution parameter are corrected.

2. The new energy unmanned tractor braking control method according to claim 1, characterized in that, The difference analysis on the real-time running data of the new energy unmanned tractor, and the vehicle speed deviation data and the wheel speed difference state of the new energy unmanned tractor are obtained, comprising: Obtaining vehicle speed data and wheel speed data of the new energy unmanned tractor, and taking the vehicle speed data and the wheel speed data as real-time running data of the new energy unmanned tractor; Difference comparison is performed on the vehicle speed data and the preset expected vehicle speed data, and the vehicle speed deviation data of the new energy unmanned tractor is obtained; At the same time, the wheel speed data is identified for abnormal speed between shafts, and the wheel speed difference state of the new energy unmanned tractor is obtained.

3. The new energy unmanned tractor braking control method according to claim 1, characterized in that, The vehicle environment data of the new energy unmanned tractor is monitored, and the front slope information and the obstacle distance information of the vehicle environment data are classified by segmented features, and the slope feature categories and the distance feature categories of the new energy unmanned tractor are obtained, comprising: Obtaining vehicle pitch angle change data, angle beam data and distance original point cloud data of the new energy unmanned tractor; Filtering high-frequency noise components of the vehicle pitch angle change data and the angle beam data, and obtaining front slope information of the new energy unmanned tractor; Taking the obstacle center of the distance original point cloud data as the origin, analyzing the straight line distance from the new energy unmanned tractor to the obstacle center, and obtaining obstacle distance information of the new energy unmanned tractor; Multi-level threshold classification processing is performed on the front slope information and the obstacle distance information, and the discretization level of the front slope information and the obstacle distance information is obtained; The real-time running data is introduced as a state correction factor, and the discretization level is jointly logically adjusted, and the slope feature categories and the distance feature categories of the new energy unmanned tractor are obtained.

4. The new energy unmanned tractor braking control method according to claim 1, characterized in that, The state space mapping of the slope feature category, the distance feature category and the vehicle speed deviation data confirms the basic braking demand of the new energy unmanned tractor, including: Taking the slope feature category as a first state identifier, taking the distance feature category as a second state identifier, and taking the vehicle speed deviation data as a third state identifier, a comprehensive state description of the new energy unmanned tractor is constructed; According to the comprehensive state description, a working condition mode matching of the new energy unmanned tractor is performed to confirm a target working condition mode of the new energy unmanned tractor; A braking strategy bound with the target working condition mode is called; The first state identifier, the second state identifier and the third state identifier are mapped to the braking strategy to obtain the basic braking demand of the new energy unmanned tractor.

5. The new energy unmanned tractor braking control method according to claim 1, characterized in that, The adjustment of the wheel braking pressure distribution ratio of the new energy unmanned tractor according to the basic braking demand and the wheel speed difference state obtains a wheel braking pressure parameter of the new energy unmanned tractor, including: Semantic analysis is performed on the basic braking demand to obtain a braking intensity level and a braking mode type of the basic braking demand; Taking the braking intensity level, the braking mode type and the wheel speed difference state as a composite control parameter, a preset braking force mapping table is queried to determine a total braking force demand and a wheel independent braking force demand of the new energy unmanned tractor; Based on the total braking force demand and the wheel independent braking force demand, a wheel braking pressure distribution ratio of the new energy unmanned tractor is calculated; Parameter synthesis is performed on the wheel braking pressure distribution ratio to obtain a wheel braking pressure parameter of the new energy unmanned tractor.

6. The new energy unmanned tractor braking control method according to claim 5, characterized in that, The calculation formula of the wheel braking pressure distribution ratio is as follows: ； In the formula, Indicates the first The braking pressure distribution ratio of each wheel This indicates the total number of wheels of the new energy unmanned tractor. Indicates the first The independent braking force requirement of each wheel Indicates the first The load distribution correction factor for each wheel. This indicates the preset slip sensitivity adjustment factor. Indicates the first Real-time linear velocity of each wheel This represents the average linear velocity of the wheel. Indicates the overall braking force demand. Indicates the first Additional force term for each wheel's pattern. Indicates the first Additional force term for each wheel's pattern. This indicates taking the absolute value. This indicates a summation operation.

7. The new energy unmanned tractor braking control method according to claim 1, characterized in that, The wheel braking pressure parameter is encoded into a braking instruction of the new energy unmanned tractor, and the braking instruction is used to drive the new energy unmanned tractor to perform a braking operation, including: The wheel braking pressure parameter and a corresponding wheel identifier are bound, and the bound wheel braking pressure parameter and the wheel identifier are encapsulated into a braking instruction data frame of the new energy unmanned tractor; The braking instruction data frame is sent to a braking actuator node of the new energy unmanned tractor; The braking instruction data frame is parsed by the braking actuator node to generate a pulse width modulation signal of the new energy unmanned tractor; The pulse width modulation signal is applied to a braking pressure regulating valve of the new energy unmanned tractor to drive the opening degree change of the braking pressure regulating valve; According to the opening degree change, the hydraulic pressure in the wheel cylinder of the corresponding wheel of the new energy unmanned tractor is controlled in real time by changing the braking fluid flow through the braking pressure regulating valve to perform the braking operation of the new energy unmanned tractor.

8. The new energy unmanned tractor braking control method according to claim 1, characterized in that, The actual wheel cylinder pressure value and the actual longitudinal deceleration of the new energy unmanned tractor after the braking operation are evaluated, and according to the evaluation result, the corresponding relationship parameter of the state space mapping and the wheel braking pressure distribution parameter are corrected, including: The actual wheel cylinder pressure value and the actual longitudinal deceleration of the new energy unmanned tractor after the brake operation are compared and analyzed to obtain a pressure deviation value and a longitudinal deceleration deviation value of the new energy unmanned tractor after the brake operation; Based on the pressure deviation value and the longitudinal deceleration deviation value, the control effect of the brake operation is evaluated; When the control effect result is that the control effect is not up to standard, the pressure deviation value and the longitudinal deceleration deviation value are mapped to a preset parameter compensation table to determine the compensation amount of the corresponding relationship parameter of the state space mapping and the compensation amount of the wheel brake pressure parameter, and the compensation amount is superimposed on the corresponding parameter value.

9. The new energy unmanned tractor braking control method according to claim 8, characterized in that, The evaluation of the control effect of the brake operation based on the pressure deviation value and the longitudinal deceleration deviation value includes: The absolute value of the pressure deviation value is compared with a preset pressure deviation allowed threshold value; The absolute value of the longitudinal deceleration deviation value is compared with a preset longitudinal deceleration deviation allowed threshold value; If the absolute value of the pressure deviation value does not exceed the pressure deviation allowed threshold value, and the absolute value of the longitudinal deceleration deviation value does not exceed the longitudinal deceleration deviation allowed threshold value, it is determined that the control effect is up to standard; If the absolute value of the pressure deviation value exceeds the pressure deviation allowed threshold value, or the absolute value of the longitudinal deceleration deviation value exceeds the longitudinal deceleration deviation allowed threshold value, it is determined that the control effect is not up to standard; The control effect up to standard and the control effect not up to standard are taken as the control effect result of the brake operation.

10. A new energy unmanned tractor braking control system, characterized in that, A new energy unmanned tractor brake control method for realizing the brake control method of claim 1, the system comprises: a running data difference analysis module for analyzing the real-time running data of the new energy unmanned tractor to obtain vehicle speed deviation data and wheel speed difference state of the new energy unmanned tractor; an environmental data monitoring and feature classification module for monitoring vehicle environmental data of the new energy unmanned tractor, and classifying the front slope information and obstacle distance information of the vehicle environmental data into segments to obtain slope feature categories and distance feature categories of the new energy unmanned tractor; a state space mapping and basic brake demand confirmation module for mapping the slope feature categories, the distance feature categories and the vehicle speed deviation data into a state space to confirm the basic brake demand of the new energy unmanned tractor; a brake pressure distribution ratio adjustment module for adjusting the wheel brake pressure distribution ratio of the new energy unmanned tractor according to the basic brake demand and the wheel speed difference state to obtain a wheel brake pressure parameter of the new energy unmanned tractor; a brake instruction encoding and execution module for encoding the wheel brake pressure parameter into a brake instruction of the new energy unmanned tractor, and driving the new energy unmanned tractor to perform a brake operation with the brake instruction. The brake control effect evaluation and parameter correction module is configured to evaluate the control effect of the actual wheel cylinder pressure value and the actual longitudinal deceleration of the new energy unmanned tractor after the brake operation, and correct the corresponding relationship parameter of the state space mapping and the wheel brake pressure distribution parameter according to the evaluation result.

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