A tracked vehicle rapid braking stability control method, system and medium

Abstract

The application discloses a kind of tracked vehicle quick brake stability control method, system and medium, the method includes the following steps: obtaining and caching the historical pose of unmanned tracked vehicle, generates pose set based on the historical pose;Determine whether the unmanned tracked vehicle enters quick brake process;In response to the unmanned tracked vehicle entering the quick brake process, calculate reference trajectory based on the pose set;According to the pose of the unmanned tracked vehicle and the reference trajectory, brake stability control process is executed;The application can consider the stability control of lateral and longitudinal simultaneously, carry out anti-deflection control in braking process, so that unmanned tracked vehicle obtains smooth quick brake stability, solves the problem that existing brake scheme cannot effectively carry out anti-deflection control in braking process, has high application value.

Description

Technical Field

[0001] This invention relates to the field of vehicle braking control technology, specifically to the field of rapid braking technology for unmanned tracked vehicles, and particularly to a method, system, and medium for rapid braking stability control of tracked vehicles. Background Technology

[0002] Autonomous vehicles are mainly divided into wheeled and tracked types. Due to their superior off-road capabilities, tracked vehicles are increasingly being used in specialized fields. The most basic function of tracked vehicles is all-terrain driving; therefore, the control terminal or autonomous driving control system of tracked vehicles must have the ability to precisely control a series of functions, including straight-line driving, steering, reversing, center steering, and braking. Currently, tracked vehicles are trending towards higher speeds and heavier loads, thus placing increasingly higher demands on their braking performance.

[0003] Traditional tracked vehicles do not exhibit significant directional stability issues during braking due to mechanical constraints. For example, in single-drive tracked vehicles, the rigid mechanical connection between the two drive wheels makes it easy to maintain equal rotational speeds on both sides, ensuring directional stability during braking. However, unmanned tracked vehicles typically employ a dual-motor independent drive system with separate drive wheels on each side, featuring wire-controlled mechanical braking. Without mechanical constraints between the drive wheels, the braking systems on both sides are independent, making them prone to uneven deceleration, severe vehicle yaw, and even rollover due to varying ground loads on both sides. Therefore, achieving stability control during rapid braking of unmanned tracked vehicles is becoming increasingly crucial.

[0004] Existing rapid braking schemes for unmanned tracked vehicles typically only consider how to achieve combined mechanical and electric braking performance. Other schemes use mechanical braking, electric braking, and electro-hydraulic retarders as control components to achieve more complex combined technologies. For example, CN109249922A, a hybrid unmanned tracked vehicle electromechanical combined drive-by-wire braking system and method, achieves the combination of mechanical braking and electric motor braking, improving the braking efficiency of tracked vehicles. These rapid braking schemes mainly focus on controlling the longitudinal movement of the vehicle during rapid braking, with stable vehicle deceleration as the primary control objective. Their aim is to maximize ground adhesion while effectively utilizing the characteristics of electric braking, mechanical braking, and electro-hydraulic retarders to improve overall braking force and dynamic braking performance. Furthermore, the left and right braking systems are considered to have identical response processes.

[0005] However, in off-road environments, the ground load on the two drive wheels may differ significantly, and the control of various braking components may also have errors. Therefore, controlling the vehicle solely from the perspective of longitudinal dynamics is completely insufficient. Once the vehicle body veers, the tracked vehicle has actually entered a steering condition rather than a simple straight-line braking condition. At this point, the vehicle's steering dynamics must be considered to adjust the braking force on the left and right sides to ensure stable control of lateral dynamics and prevent large body veers. Currently, for anti-yaw control during the braking process of unmanned tracked vehicles, only a few studies have discussed the control of the vehicle's lateral movement—adjusting the lateral movement of the unmanned tracked vehicle based on the yaw angle. However, tracked vehicles experience significant slippage and turning processes in off-road environments. Therefore, using the vehicle's own signals, such as the rotational speeds of the two drive wheels, cannot accurately calculate the yaw angle, and thus cannot effectively perform anti-yaw control during braking. Summary of the Invention

[0006] The purpose of this invention is to address the aforementioned problems in the prior art by providing a method, system, and medium for controlling the rapid braking stability of tracked vehicles, thereby solving the problem of braking stability control during rapid braking of unmanned tracked vehicles in the prior art.

[0007] To solve the above-mentioned technical problems, the specific technical solution of the present invention is as follows:

[0008] On one hand, the present invention provides a method for rapid braking stability control of tracked vehicles, comprising the following steps: acquiring and caching the historical poses of unmanned tracked vehicles, and generating a pose set based on the historical poses;

[0009] Determine whether the unmanned tracked vehicle has entered a rapid braking process;

[0010] In response to the unmanned tracked vehicle entering the rapid braking process, a reference trajectory is calculated based on the pose set;

[0011] The braking stability control process is executed based on the pose of the unmanned tracked vehicle and the reference trajectory, and the braking stability control process continues throughout the rapid braking process.

[0012] As an improved solution, the step of executing the braking stability control process based on the pose of the unmanned tracked vehicle and the reference trajectory further includes:

[0013] The first pose of the unmanned tracked vehicle at the moment it enters the rapid braking process is obtained, and the braking stability control process is executed based on the first pose and the reference trajectory.

[0014] As an improved solution, the braking stability control process includes:

[0015] Calculate the difference in the desired braking torque between the two sides of the unmanned tracked vehicle;

[0016] Calculate the sum of the desired braking torques on both sides of the unmanned tracked vehicle;

[0017] The actual braking force of each braking component of the unmanned tracked vehicle is calculated based on the difference between the expected braking torques on both sides and the sum of the expected braking torques on both sides.

[0018] The braking action is performed based on the actual braking force.

[0019] As an improved approach, the step of acquiring and caching the historical poses of the unmanned tracked vehicle, and generating a pose set based on the historical poses, further includes:

[0020] A set interval distance is set, and the historical pose of the unmanned tracked vehicle is obtained based on the high-precision positioning system on the unmanned tracked vehicle according to the interval distance. Several of the historical poses are cached to form the pose set. The historical poses are 6-dimensional coordinates in Gaussian rectangular coordinate system, which are used to represent the center position and orientation of the unmanned tracked vehicle.

[0021] As an improved solution, the step of determining whether the unmanned tracked vehicle has entered a rapid braking process further includes:

[0022] Obtain control commands, including: desired vehicle speed, desired steering curvature, desired braking deceleration, and desired gear;

[0023] Set a speed threshold and obtain the current speed of the unmanned tracked vehicle;

[0024] The conditions for the unmanned tracked vehicle to enter the rapid braking process are as follows: the current vehicle speed is greater than the vehicle speed threshold, the desired vehicle speed is 0, the desired steering curvature is 0, the desired braking deceleration is a value between 0 and the maximum braking deceleration that the unmanned tracked vehicle can achieve, and the desired gear is a forward gear.

[0025] As an improved approach, the step of calculating the reference trajectory based on the pose set further includes:

[0026] A sampling quantity is set, and a sampling set is generated based on the sampling quantity, the first pose, and the pose set. Using polynomial interpolation, the trajectory equation of the x and y coordinate values ​​of the vehicle's historical trajectory is obtained. The coordinates of the sampling set are substituted into the trajectory equation to solve for the curve equation of the reference trajectory. By taking the derivative, the coordinates of the first pose are substituted into the curve equation to obtain the curve curvature at the first pose, thereby obtaining the reference heading angle of the unmanned tracked vehicle at the coordinate point of the first pose.

[0027] As an improved approach, the step of calculating the difference in desired braking torque between the two sides of the unmanned tracked vehicle further includes:

[0028] The difference ΔT between the two sides of the desired braking torque * It satisfies the following formula:

[0029] △T * =k1△d+k2△θ

[0030] Where k1 and k2 are the coefficients for parameter tuning, △d is the distance the unmanned tracked vehicle deviates from the reference trajectory, and △θ is the difference between the actual heading angle of the unmanned tracked vehicle and the heading angle of the nearest point on the reference trajectory.

[0031] The step of calculating the sum of the desired braking torques on both sides of the unmanned tracked vehicle further includes:

[0032] The sum of the desired braking torques on both sides ∑T * =k3b * , where b * Let k3 be the desired braking deceleration, and k3 characterize the linear relationship between braking deceleration and braking torque.

[0033] As an improved approach, the step of calculating the actual braking force of each braking component of the unmanned tracked vehicle based on the difference between the desired braking torques on both sides and the sum of the desired braking torques on both sides further includes:

[0034] The actual braking force satisfies the following set of equations:

[0035]

[0036] in, These represent the braking forces that should be applied to the left and right drive wheels, respectively. These represent the target torques of the left and right drive motors, respectively. These represent the target torques for the left and right steerable mechanical brakes, respectively.

[0037] On the other hand, the present invention also provides a rapid braking stability control system for tracked vehicles, including: a high-precision positioning system, a vehicle controller, an unmanned driving system, and an unmanned driving controller;

[0038] The high-precision positioning system is used to acquire the historical pose of the unmanned tracked vehicle and send it to the unmanned driving system;

[0039] The autonomous driving system is used to send the historical poses to the vehicle controller; the vehicle controller is used to generate a pose set based on the historical poses.

[0040] The vehicle controller is used to acquire control commands sent by the unmanned driving controller, and determine whether the unmanned tracked vehicle has entered a rapid braking process by combining the current vehicle speed and the control commands.

[0041] In response to the unmanned tracked vehicle entering the rapid braking process, the vehicle controller calculates a reference trajectory based on the pose set;

[0042] The vehicle controller is also used to execute a braking stability control process based on the pose of the unmanned tracked vehicle and the reference trajectory.

[0043] On the other hand, the present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the rapid braking stability control method for a tracked vehicle.

[0044] The beneficial effects of the technical solution of this invention are:

[0045] 1. The rapid braking stability control method for tracked vehicles described in this invention divides rapid braking stability control into lateral control and longitudinal control during the rapid braking process of unmanned tracked vehicles. A reference trajectory is generated using the historical pose of the unmanned driving system to ensure that the unmanned tracked vehicle does not deflect during braking. A lateral control algorithm generates a braking torque difference; a longitudinal control algorithm generates a braking torque sum. Then, through various constraints and allocation strategies, the target braking torque for the motor and drive-by-wire mechanical braking is generated, enabling the unmanned tracked vehicle to achieve smooth rapid braking stability. This method solves the problem that existing braking schemes cannot effectively prevent deflection during braking and has high application value.

[0046] 2. The tracked vehicle rapid braking stability control system of the present invention can realize the tracked vehicle rapid braking stability control method of the present invention through the cooperation of a high-precision positioning system, a vehicle controller, an unmanned driving system and an unmanned driving controller; during the rapid braking process of the unmanned tracked vehicle, the unmanned tracked vehicle can obtain smooth rapid braking stability through the joint control of lateral and longitudinal directions.

[0047] 3. The computer-readable storage medium of the present invention can guide the high-precision positioning system, the vehicle controller, the unmanned driving system and the unmanned driving controller to cooperate, thereby realizing the rapid braking stability control method for tracked vehicles of the present invention. Furthermore, the computer-readable storage medium of the present invention also effectively improves the operability of the rapid braking stability control method for tracked vehicles. Attached Figure Description

[0048] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0049] Figure 1 This is a flowchart illustrating the rapid braking stability control method for tracked vehicles described in Embodiment 1 of the present invention. Detailed Implementation

[0050] During operation, the high-precision positioning system of the unmanned tracked vehicle remains operational, constantly acquiring accurate historical vehicle poses. The vehicle controller caches these historical poses for a certain period and, combined with the current vehicle speed and the autonomous driving system's control commands, determines whether the unmanned tracked vehicle has entered a rapid braking control process. When rapid braking is initiated, a braking reference trajectory, conforming to dynamic constraints and typically a straight line, is calculated. Based on the vehicle's deviation from the reference trajectory, the difference in braking torque between the two drive wheels is calculated, i.e., lateral stability control is performed. Based on the desired braking deceleration, vehicle speed, and ground adhesion constraints sent by the autonomous driving system, the sum of the braking torques of the two drive wheels is calculated, i.e., longitudinal stability control is performed. By using the difference and sum of braking torques, the maximum electric braking constraint, and the characteristics of the mechanical brake pressure on both sides, the real-time braking force of each braking element is calculated, and real-time control is completed. When the desired braking deceleration decreases to zero, or the actual vehicle deceleration has reached zero, the braking process is complete, and the braking stability control process exits.

[0051] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0052] The terms "first," "second," etc., used in this specification, claims, and accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, apparatus, product, or device that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0053] In the description of this invention, it should be noted that:

[0054] VCU (vehicle control unit) is the vehicle controller;

[0055] ACU (autonomous control unit) is the controller for unmanned driving;

[0056] The unmanned tracked vehicle adopts a scheme of independent drive by dual motors and separate wire-controlled mechanical braking for each of the dual drive wheels. There is no mechanical constraint on the two drive wheels, and the braking systems on both sides are independent of each other.

[0057] Example 1

[0058] This embodiment provides a method for controlling the stability of tracked vehicles during rapid braking, such as... Figure 1 As shown, it includes the following steps:

[0059] S1. Cache the historical poses of unmanned tracked vehicles and generate a pose set;

[0060] Unmanned tracked vehicles are typically equipped with high-precision positioning systems. The unmanned driving system of unmanned tracked vehicles obtains the vehicle's pose through the high-precision positioning system. The pose of unmanned tracked vehicles includes longitude, latitude, elevation, and three orientation angles in space, as well as pitch angle, yaw angle, and roll angle, which can be converted into 6-dimensional coordinates in Gaussian rectangular coordinate system after certain calculations, which can completely represent the vehicle's position and orientation.

[0061] The autonomous driving system sends the position and posture data to the vehicle control unit (VCU) in real time. The VCU is the core control unit that controls the braking process.

[0062] The VCU internally caches a certain number of historical pose sequences according to specified caching rules, forming a set:

[0063] P = {Q0, Q1, Q2, ..., Q} n}

[0064] Where Q is defined as Q = [x, y, z, α, β, θ] T x, y, z are the three-dimensional displacement coordinates in space, and α, β, θ are the three-dimensional angles in space.

[0065] To facilitate the generation of reference trajectories, the preferred caching rule is a distance interval. When the VCU receives the pose data from the autonomous driving system, it caches a certain number of poses at specific intervals, i.e., Q0, Q1, Q2...Q... N They are arranged in chronological order, and the distances between Q0 and Q1, and between Q1 and Q2, are within the distance interval.

[0066] High-precision positioning systems provide high-frequency feedback on the pose of unmanned tracked vehicles, such as up to 50Hz, with a time interval of 0.02s. If the pose of the unmanned tracked vehicle is recorded at specific time intervals, the distance between two adjacent poses may be as small as 0.01m or as large as 0.1m under different vehicle speeds. Unequal historical pose intervals are detrimental to trajectory calculation. Therefore, the actual algorithm in this embodiment records the historical pose of the unmanned tracked vehicle at approximately 0.5m intervals. This ensures a smooth historical trajectory, resulting in a smooth reference trajectory for future calculations.

[0067] S2. Determine whether the rapid braking process has begun;

[0068] The vehicle speed threshold is set, and the VCU examines the control commands sent by the autonomous driving controller ACU. At the same time, it compares the current vehicle speed with the vehicle speed threshold to determine whether it is necessary to enter the rapid braking process. The control commands include: desired vehicle speed, desired steering curvature, desired braking deceleration, desired gear, etc.

[0069] This invention focuses on the rapid braking process. Therefore, in a general sense, the current vehicle speed should be greater than the vehicle speed threshold, the desired vehicle speed should be 0, the desired steering curvature should be 0, the desired braking deceleration should be a value between 0 and the maximum braking deceleration that the vehicle can achieve, and the desired gear should be a forward gear. The desired braking deceleration is the desired deceleration value calculated by the autonomous driving system, and its value does not exceed the maximum braking deceleration that the chassis can achieve. Setting the vehicle speed threshold is to avoid triggering the next control process when the actual vehicle speed is too low. When the actual vehicle speed is too low, there is no need to perform braking stability control.

[0070] It should be noted that when the desired steering curvature is not 0, the unmanned tracked vehicle does not simply perform braking, but also needs to perform steering. This is another control method and is not within the scope of this invention.

[0071] S3. Calculate the reference trajectory during braking;

[0072] Given set P, select N coordinates spaced at intervals of 0.5 meters, denoted as [Q0, Q1, Q2, ..., Q...]. N-1 Q N The appropriate method is to use polynomial interpolation to obtain the trajectory equation of the x and y coordinates of the vehicle's historical trajectory.

[0073]

[0074] Then, substituting the coordinates into the Lagrange interpolation equation, the curve equation of the reference trajectory can be solved. By taking the derivative and substituting the Q0 coordinates, the curvature of the Q0 curve can be obtained, and thus the reference heading of the autonomous vehicle at that specific coordinate point can be obtained. The number of historical poses, or N, can be selected according to the characteristics of the actual vehicle, and is usually no less than 8 points.

[0075] Q0 represents the position of the unmanned tracked vehicle at the moment of entering the rapid braking control process, i.e., the first position; Q1, Q2, Q3, ..., Q N-1 Q N It is a historical pose taken in reverse, which is taken from a set of specific distance intervals mentioned above. This set is constantly updated, and the latest pose is the first pose of the unmanned tracked vehicle.

[0076] The significance of referencing the braking trajectory is that, in the tangential direction of point Q0, the unmanned tracked vehicle maintains this trajectory of traveling in a straight line, so that it can continue to travel along this straight line during subsequent braking.

[0077] It should be noted that using Lagrange interpolation is only one method in this embodiment; other interpolation methods may also be used.

[0078] S4. Calculate the difference in the desired braking torque on both sides;

[0079] When the tracked vehicle deviates from the braking reference trajectory during braking, and veers off course, the difference in braking torque ΔT between the two drive wheels must be calculated. * It can be determined by the following formula:

[0080] △T * =k1△d+k2△θ

[0081] Where k1 and k2 are the coefficients of the parameter adjustment, △d is the distance of the vehicle from the reference trajectory, and △θ is the difference between the actual heading angle of the vehicle and the heading angle of the nearest point on the reference braking trajectory.

[0082] k1 and k2 are variable parameters adjusted based on the response capability of the actual vehicle control system, and are generally calibrated and determined according to the characteristics of a certain type of vehicle. In particular, for a specific model of tracked unmanned vehicle, the difference in torque between its two drive wheels should have an upper limit. k1 is a parameter characterized by the deviation distance. In actual vehicle calibration, based on the vehicle's dynamic characteristics and the steering resistance of the tracked vehicle, an estimate can be made of the difference in driving wheel braking torque that should be applied to correct the deviation after a deviation occurs. The applicable value of k1 can be obtained through the correspondence of this estimate, and the same applies to k2.

[0083] It should be noted that "deflection" in this application specifically refers to any of the following situations occurring during the braking process of the unmanned tracked vehicle:

[0084] 1. The center position of the tracked vehicle is not on the reference track; 2. The orientation of the tracked vehicle is not along the tangent direction of the reference track.

[0085] S5. Calculate the sum of the desired braking torques on both sides;

[0086] Typically, during vehicle motion, the target braking deceleration b * There is a certain correspondence between the sum of the required braking torque in the longitudinal direction and the actual vehicle calibration, which can be obtained through actual vehicle calibration.

[0087] ∑T * =k3b *

[0088] Specifically, for a specific model of tracked unmanned vehicle, its maximum braking deceleration is basically determined, and the braking torque of the driving wheel at which the maximum braking deceleration is achieved is also determined. The relationship between the two can usually be measured through vehicle braking characteristic experiments. When the vehicle is not stopped and is in the process of braking, there is usually a relatively regular linear correspondence between braking deceleration and braking torque. Therefore, k3 is defined to characterize this relationship, and k3 is also an important control parameter of this invention.

[0089] S6. Calculate the actual braking force of each braking component;

[0090] These represent the braking forces that should be applied to the left and right drive wheels, respectively.

[0091] These represent the target torques of the left and right drive motors, respectively. Since the actual torque response of the motors is very fast and the accuracy is high, when the vehicle is still in motion, the drive torque of the motors can be considered equal to the actual torque.

[0092] These represent the target torques of the left and right drive-by-wire mechanical brakes, respectively. In particular, the target torque and target braking pressure are usually mapped by a lookup table, and the mapping relationship is obtained from the actual vehicle calibration.

[0093] T Lm ,T Rm These represent the actual torque of the left and right steerable mechanical brakes, respectively, and have a mapping relationship with the actual braking pressure.

[0094] The following system of equations holds true:

[0095]

[0096] They are also constrained by the corresponding maximum electric braking torque limit and the ground adhesion. Furthermore, because the electric braking response is very fast, the electric braking force is prioritized to reach its upper limit before applying the corresponding mechanical braking force. In actual vehicle control, the electric braking force of the motor is directly controlled first. The target electric braking torque is generated according to its upper limit and sent to the motor controller, which then executes the braking action according to the target electric braking torque.

[0097] S7. Determine whether to disengage the braking process;

[0098] When the desired braking deceleration decreases to zero, or the actual vehicle speed has already dropped to zero, the braking process is complete, and the braking stability control process exits. Otherwise, it returns to step S4 for continuous correction control. It should be noted that if the vehicle speed has already dropped to zero but deflection still exists, braking stability control also exits. This invention applies control to suppress deflection during the process from the start of braking to stopping the vehicle; once the vehicle has stopped, it is not appropriate to apply any further actions.

[0099] This invention utilizes a high-precision positioning system for unmanned tracked vehicles to obtain the vehicle's accurate pose and generate its historical trajectory. At the start of rapid braking, a reasonable reference trajectory for the braking process is calculated, typically a straight line. During braking, the unmanned tracked vehicle is consistently prevented from deviating from this reference trajectory laterally. Longitudinally, the control algorithms effectively coordinate the desired braking deceleration transmitted from the autonomous driving system, the difference in braking torque between the two sides due to reference trajectory deviation suppression, the actual vehicle speed, the actual vehicle's electric braking, and mechanical braking, achieving smooth braking deceleration control in the longitudinal direction. Through this combined lateral and longitudinal control, the unmanned tracked vehicle achieves stable rapid braking.

[0100] Example 2

[0101] This embodiment is based on the same inventive concept as the rapid braking stability control method for tracked vehicles described in Embodiment 1, and provides a rapid braking stability control system for tracked vehicles, including: a high-precision positioning system, a vehicle controller, an unmanned driving system, and an unmanned driving controller;

[0102] The high-precision positioning system is used to acquire the historical pose of the unmanned tracked vehicle and send it to the unmanned driving system;

[0103] The autonomous driving system is used to send the historical poses to the vehicle controller; the vehicle controller is used to generate a pose set based on the historical poses.

[0104] The vehicle controller is used to acquire control commands sent by the unmanned driving controller and determine whether the unmanned tracked vehicle has entered a rapid braking process based on the control commands.

[0105] In response to the unmanned tracked vehicle entering the rapid braking process, the vehicle controller calculates a reference trajectory based on the pose set;

[0106] The vehicle controller is also used to execute a braking stability control process based on the pose of the unmanned tracked vehicle and the reference trajectory.

[0107] This invention considers the stability control of the rapid braking process of unmanned tracked vehicles simultaneously in both the lateral and longitudinal directions. Laterally, the high-precision positioning equipment of the unmanned tracked vehicle caches its historical pose, thereby obtaining a straight and smooth reference trajectory for the braking process. By adjusting the braking torque difference between the two drive wheels, deviation from the reference trajectory is suppressed, achieving lateral braking stability. Longitudinally, based on the target braking deceleration, the braking torque of the motor and the drive-by-wire mechanical brakes is rationally allocated to obtain a smooth and stable deceleration. The combined and coupled lateral and longitudinal controls optimize the stability of the unmanned tracked vehicle's braking process.

[0108] Example 3

[0109] This embodiment provides a computer-readable storage medium, including:

[0110] The storage medium is used to store computer software instructions for implementing the tracked vehicle rapid braking stability control method described in Embodiment 1 above. It includes a program for executing the tracked vehicle rapid braking stability control method. Specifically, the executable program can be built into the tracked vehicle rapid braking stability control system described in Embodiment 2. In this way, the tracked vehicle rapid braking stability control system can implement the tracked vehicle rapid braking stability control method described in Embodiment 1 by executing the built-in executable program.

[0111] Furthermore, the computer-readable storage medium in this embodiment can be any combination of one or more readable storage media, wherein the readable storage medium includes an electrical, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof.

[0112] Unlike existing technologies, this application presents a method, system, and medium for controlling the rapid braking stability of tracked vehicles. During the rapid braking process of unmanned tracked vehicles, rapid braking stability control is divided into lateral control and longitudinal control. A reference trajectory is generated using the historical pose of the unmanned driving system to ensure that the unmanned tracked vehicle does not deflect during braking. A lateral control algorithm generates the braking torque difference; a longitudinal control algorithm generates the braking torque sum. Then, through various constraints and allocation strategies, the target braking torque for the motor and drive-by-wire mechanical braking is generated, enabling the unmanned tracked vehicle to achieve smooth rapid braking stability. This solves the problem that existing braking schemes cannot effectively prevent deflection during braking, and has high application value.

[0113] It should be understood that in the various embodiments of this document, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this document.

[0114] It should also be understood that, in the embodiments herein, the term "and / or" is merely a description of the relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following associated objects have an "or" relationship.

[0115] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this document.

[0116] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0117] In the embodiments provided herein, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the couplings or direct couplings or communication connections shown or discussed may be indirect couplings or communication connections through some interfaces, devices, or units, or they may be electrical, mechanical, or other forms of connection.

[0118] The units described as separate components may or may not be physically separate. The components shown as units 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 units can be selected to achieve the purpose of the embodiments described herein, depending on actual needs.

[0119] Furthermore, the functional units in the various embodiments of this document 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 as a software functional unit.

[0120] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this paper, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this paper. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0121] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for controlling the stability of tracked vehicles during rapid braking, characterized in that, Includes the following steps: Acquire and cache the historical poses of the unmanned tracked vehicle, and generate a pose set based on the historical poses; Determine whether the unmanned tracked vehicle has entered a rapid braking process; In response to the unmanned tracked vehicle entering the rapid braking process, a reference trajectory is calculated based on the pose set; The braking stability control process is executed based on the pose of the unmanned tracked vehicle and the reference trajectory. The step of executing the braking stability control process based on the pose of the unmanned tracked vehicle and the reference trajectory further includes: The first pose of the unmanned tracked vehicle at the moment of entering the rapid braking process is obtained, and the braking stability control process is executed according to the first pose and the reference trajectory. The braking stability control process includes: Calculate the difference in the desired braking torque between the two sides of the unmanned tracked vehicle; Calculate the sum of the desired braking torques on both sides of the unmanned tracked vehicle; The actual braking force of each braking component of the unmanned tracked vehicle is calculated based on the difference between the expected braking torques on both sides and the sum of the expected braking torques on both sides. The braking action is performed based on the actual braking force. The step of calculating the reference trajectory based on the pose set further includes: A sampling quantity is set, and a sampling set is generated based on the sampling quantity, the first pose, and the pose set. Polynomial interpolation is used to obtain the trajectory equation of the x and y coordinate values ​​of the vehicle's historical trajectory. The coordinates of the sampling set are substituted into the trajectory equation to solve for the curve equation of the reference trajectory. By taking the derivative, the coordinates of the first pose are substituted into the curve equation to obtain the curve curvature at the first pose, and thus the reference heading angle of the unmanned tracked vehicle at the coordinate point of the first pose is obtained. The step of calculating the difference in the desired braking torque between the two sides of the unmanned tracked vehicle further includes: The difference in the desired braking torque on both sides It satisfies the following formula: ; Where k1 and k2 are the coefficients for parameter tuning. The distance by which the unmanned tracked vehicle deviates from the reference trajectory. The difference between the actual heading angle of the unmanned tracked vehicle and the heading angle of the nearest point on the reference trajectory; The step of calculating the sum of the desired braking torques on both sides of the unmanned tracked vehicle further includes: The sum of the desired braking torques on both sides is: ,in For the desired braking deceleration, k3 represents the linear relationship between braking deceleration and braking torque; The step of calculating the actual braking force of each braking component of the unmanned tracked vehicle based on the difference between the desired braking torques on both sides and the sum of the desired braking torques on both sides further includes: The actual braking force satisfies the following set of equations: ; in, These represent the braking forces that should be applied to the left and right drive wheels, respectively. These represent the target torques of the left and right drive motors, respectively. These represent the target torques for the left and right steerable mechanical brakes, respectively.

2. The method for controlling the rapid braking stability of a tracked vehicle according to claim 1, characterized in that: The step of acquiring and caching the historical poses of the unmanned tracked vehicle, and generating a pose set based on the historical poses, further includes: A set interval distance is set, and the historical pose of the unmanned tracked vehicle is obtained based on the high-precision positioning system on the unmanned tracked vehicle according to the interval distance. Several of the historical poses are cached to form the pose set. The historical poses are 6-dimensional coordinates in Gaussian rectangular coordinate system, which are used to represent the center position and orientation of the unmanned tracked vehicle.

3. The method for controlling the rapid braking stability of a tracked vehicle according to claim 2, characterized in that: The step of determining whether the unmanned tracked vehicle has entered a rapid braking process further includes: Obtain control commands, including: desired vehicle speed, desired steering curvature, desired braking deceleration, and desired gear; Set a speed threshold and obtain the current speed of the unmanned tracked vehicle; The conditions for the unmanned tracked vehicle to enter the rapid braking process are as follows: the current vehicle speed is greater than the vehicle speed threshold, the desired vehicle speed is 0, the desired steering curvature is 0, the desired braking deceleration is a value between 0 and the maximum braking deceleration that the unmanned tracked vehicle can achieve, and the desired gear is a forward gear.

4. A rapid braking stability control system for tracked vehicles, employing the rapid braking stability control method for tracked vehicles as described in claim 1, characterized in that... The control system includes: a high-precision positioning system, a vehicle controller, an unmanned driving system, and an unmanned driving controller; The high-precision positioning system is used to acquire the historical pose of the unmanned tracked vehicle and send it to the unmanned driving system; The autonomous driving system is used to send the historical poses to the vehicle controller; the vehicle controller is used to generate a pose set based on the historical poses. The vehicle controller is used to acquire control commands sent by the unmanned driving controller, and determine whether the unmanned tracked vehicle has entered a rapid braking process by combining the current vehicle speed and the control commands. In response to the unmanned tracked vehicle entering the rapid braking process, the vehicle controller calculates a reference trajectory based on the pose set; The vehicle controller is also used to execute a braking stability control process based on the pose of the unmanned tracked vehicle and the reference trajectory.

5. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the rapid braking stability control method for a tracked vehicle as described in any one of claims 1 to 3.

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