Self-diagnosis based unmanned vehicle braking system and method

Abstract

The application relates to the technical field of unmanned vehicle braking control, and discloses an unmanned trolley braking system and method based on self-diagnosis, which comprises a data acquisition unit, a control unit, a driving unit and a braking unit; the data acquisition unit acquires trolley operation data and transmits the data to the control unit; the control unit is internally provided with a self-diagnosis braking algorithm, real-time deceleration and theoretical braking distance are calculated through pre-braking test, the braking unit is controlled to perform basic braking, and the driving unit performs positive rotation or reverse rotation point compensation according to braking deviation; the method adopts a closed-loop process, that is, firstly, self-diagnosis test parameter calculation is performed, then, formal braking is performed, and finally, point compensation is implemented. The application dynamically adapts to complex working conditions. The application realizes real-time sensing and accurate compensation of braking capacity, greatly improves parking accuracy, reduces safety hazards, is suitable for high-precision braking scenes such as material handling in industrial and mining enterprises, and has remarkable practicability and popularization value.

Description

Technical Field

[0001] This invention relates to the field of braking control technology for autonomous vehicles, specifically to a braking system and method for an autonomous vehicle based on self-diagnosis. Background Technology

[0002] In material handling operations in industrial and mining enterprises, unmanned freight vehicles (such as slag bag flatbed trucks) have become core equipment due to their high efficiency and safety. Their braking performance directly affects operational efficiency and on-site safety. However, the braking systems of existing unmanned vehicles face many technical challenges and struggle to meet the requirements for high-precision braking. First, the dynamic degradation of braking capacity is a significant issue. Brakes rely on friction for braking; with increased use, the friction pads gradually wear down, leading to an irregular decrease in braking capacity. Traditional fixed-parameter braking systems cannot detect this change in real time and continue to operate according to the initial braking parameters, easily causing braking deviations. Second, there is a significant difference in weight between empty and loaded vehicles. The weight difference between an empty slag flatbed truck and a loaded truck carrying high-temperature slag can reach hundreds of kilograms to tens of tons. This huge weight difference results in a significant difference in braking distance between empty and loaded vehicles. A single braking strategy cannot accommodate both conditions, often leading to excessive braking for empty vehicles and insufficient braking for loaded vehicles. Third, the road surface at work sites often has irregular slopes, which directly change the braking distance. Current technology lacks a dynamic compensation mechanism for this variable, further exacerbating the problem of insufficient braking accuracy. Finally, existing braking methods mostly use fixed braking parameters or simple distance-speed matching control, which cannot cope with the braking deviations caused by the superposition of the above complex working conditions. This easily leads to premature stopping or exceeding the stopping point, causing safety hazards such as equipment collisions and material spillage.

[0003] Therefore, there is an urgent need for a braking system and method that can sense changes in braking capacity in real time, dynamically adapt to differences in mass and the effects of slope, and accurately correct braking deviations to address the shortcomings of existing technologies. Summary of the Invention

[0004] This invention provides a self-diagnostic braking system and method for autonomous vehicles to solve the problems existing in the background art.

[0005] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows: A self-diagnostic braking system for an autonomous vehicle includes a data acquisition unit, a control unit, a drive unit, and a braking unit. The data acquisition unit is electrically connected to the control unit and is used to collect the operating data of the autonomous vehicle and transmit it to the control unit. The control unit is electrically connected to both the drive unit and the braking unit, and has a built-in self-diagnostic braking algorithm. This algorithm is used to calculate the real-time deceleration and theoretical braking distance based on the operating data, and to control the drive unit and the braking unit to coordinately perform braking actions and inching compensation. The braking unit is used to provide basic braking force, and the drive unit is used to perform inching compensation actions to correct braking deviations.

[0006] Furthermore, the data acquisition unit includes a speed sensor, a distance detection sensor, and a timing module; the speed sensor is used to acquire the given speed v of the vehicle. c Actual speed v m (including interval time, initial velocity v) m1 velocity v at the end time m2 A rotary encoder is selected and installed on the axle of the driven wheel of the trolley to avoid speed detection errors caused by slippage of the driving wheel and improve detection accuracy. The distance detection sensor is a laser rangefinder, installed on the front side of the trolley facing the parking point, to ensure the directness and accuracy of distance detection, and is used to collect the actual distance L between the trolley and the parking point. s The timing module uses a high-precision real-time clock module with a sampling frequency of not less than 100Hz to collect the braking time t of the trolley. s Parking time t p and the interval t during the deceleration process c This provides precise time parameters to support the calculation of deceleration and theoretical braking distance.

[0007] Furthermore, the control unit uses an STM32F407 microcontroller with a built-in self-diagnostic braking algorithm. This algorithm includes a data processing module, a braking parameter calculation module, and a compensation control module. The data processing module filters and organizes the collected operational data, removing abnormal data to ensure the accuracy of parameter calculations. The braking parameter calculation module calculates the deceleration *a* for each deceleration based on the processed data. n and theoretical braking distance L c The compensation control module is used to calculate the jog pulse parameters based on the actual braking state and output compensation commands to achieve accurate correction of braking deviation.

[0008] Furthermore, the drive unit is a servo motor connected to the drive wheels of the vehicle, used to perform forward or reverse inching compensation actions; the braking unit is an electromagnetic brake installed at the wheels of the vehicle, used to provide basic braking force, and the braking force can be adjusted by the control unit.

[0009] A self-diagnostic braking method for an autonomous vehicle, applied to the aforementioned braking system, includes the following steps: S1: Pre-braking test and data acquisition: When the vehicle reaches the preset braking test area, the control unit controls the braking unit to perform a pre-braking test. The braking force of the pre-braking test is 30%-50% of the formal braking force, and the test time does not exceed 2 seconds to avoid affecting the normal driving trajectory of the vehicle; the distance between the preset braking test area and the target stopping point is not less than the theoretical braking distance L. c This is twice the speed of the target speed, ensuring sufficient distance for actual braking after the test; simultaneously, the data acquisition unit synchronously acquires the given speed v during the test. c Actual speed v m (including v) m1 v m2 ), actual distance L from the parking spot s The timing module collects braking time t, etc. s The interval t during the deceleration process c The time data is collected and all data is transmitted to the control unit.

[0010] S2: Parameter Calculation: The self-diagnostic braking algorithm of the control unit is activated. The data processing module filters and organizes the collected data, removing outliers. The braking parameter calculation module calculates the parameters based on the organized data using the formula: , Calculate the real-time deceleration a n (where v) m1 Let t be the interval time. c The actual velocity at the initial moment, v m2 Let t be the interval time. c (actual speed at the end) Then, using the formula: , Derivation of theoretical braking distance L c This calculation process does not require the precise weight of the vehicle, thus avoiding calculation errors caused by differences in the weight of empty and loaded vehicles, while also adapting to the impact of road slope on braking performance.

[0011] S3: Formal Braking: When the distance detection sensor detects the actual distance L between the car and the stopping point... s ≥L c At this time, the control unit sends a formal braking command to the braking unit, and the braking unit performs braking with a preset formal braking force, causing the car to begin to decelerate.

[0012] S4: Jog Compensation: During braking, the control unit obtains the vehicle's driving status and distance to the stopping point in real time through the data acquisition unit, judges the braking deviation, and performs corresponding compensation: If the car is detected to have decelerated to a stop prematurely (before reaching the target parking point): the control drive unit performs forward jogging compensation. The acceleration of the forward jogging compensation is consistent with the direction of the car's travel, thus extending the braking distance. If the estimated stopping distance of the car exceeds the target stopping point, the control drive unit performs reverse jogging compensation. The acceleration of the reverse jogging compensation is opposite to the direction of the car's movement, which increases the braking effect and shortens the braking distance.

[0013] The core parameter calculation logic for jog compensation is as follows: Basic jog time calculation: Based on the momentum formula: ; Derivation of jog time: , Where Δ v The target velocity change required to correct braking deviation, where 'a' is the acceleration during the jogging process; Pulse period parameter calculation: The pulse period T of the jog compensation consists of the jog acceleration time t1 and the coasting deceleration time t2 without drive. The distance and speed in each time period are calculated using the following formula: , in, l 1 represents the distance traveled during time interval t1. l 2 represents the distance traveled during time interval t2. v 0 The initial velocity before jogging is... v 1 The speed of the car after time period t1 ends. v 2 t2 is the final velocity of the trolley after time interval t2, and a is the acceleration during the jogging process; Overall parameter integration and reverse solution: The total distance the car travels within the pulse period is: ; Set the target final speed based on actual braking deviation requirements. v 2 Then, using the above formula for total distance traveled and final velocity... v 2 The calculation formula can be reversed to obtain the corresponding jog acceleration time t1 and undriven coasting deceleration time t2, ensuring that the jog compensation accurately matches the braking deviation correction requirements. Parameter calibration: In practical applications, the reverse solution results can be verified through multiple tests to calibrate the optimal values ​​of t1 and t2 under different working conditions, thereby further improving the compensation accuracy. At the same time, in order to avoid secondary deviations caused by overcompensation, the duration of a single jog compensation should not exceed 0.5 seconds, and the cumulative number of compensations should not exceed 3.

[0014] The present invention has the following beneficial effects: (1) Braking capacity self-diagnosis, adapting to dynamic working conditions: This invention calculates the braking deceleration under the current working conditions in real time through pre-testing before each braking, accurately senses the braking capacity decay, does not rely on fixed parameters, and can dynamically adapt to the difference in the weight of empty and loaded vehicles and the influence of road slope, breaking through the limitations of traditional braking systems.

[0015] (2) Significantly improved braking accuracy: By accurately calculating the theoretical braking distance and using inching compensation closed-loop control, combined with the reverse solution logic of total moving distance and final velocity, the target compensation effect can be accurately matched. This invention can effectively avoid safety hazards such as equipment collision and material spillage.

[0016] (3) Highly practical and cost-controllable: The system adopts existing mature sensors, controllers and other hardware, without the need for additional special equipment. It has a simple structure and controllable cost, and can be directly upgraded and adapted to existing unmanned vehicles. The method and process are clear, and key parameters can be obtained by reverse solving the formula. It can be put into use without complicated debugging.

[0017] (4) High safety and stable operation: The pre-braking test adopts a low force and short time design, which does not affect the normal driving trajectory of the trolley; the inching compensation is set with a single duration and cumulative number of limits to avoid over-compensation; each unit works together to form a closed loop control to ensure that the braking process is stable and reliable and adapts to the complex working environment of industrial and mining enterprises. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the overall architecture of the braking system of the present invention; Figure 2 This is a schematic diagram of the self-diagnostic braking algorithm module structure of the present invention; Figure 3 This is a schematic diagram of the braking method of the present invention; In the diagram: 1-Data acquisition unit, 11-Speed ​​sensor, 12-Distance detection sensor, 13-Timing module, 2-Control unit, 21-Data processing module, 22-Brake parameter calculation module, 23-Compensation control module, 3-Drive unit, 4-Brake unit, 5-Unmanned vehicle. Detailed Implementation

[0019] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings. It should be noted that these descriptions are for the purpose of aiding understanding the present invention, but do not constitute a limitation thereof. Furthermore, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0020] like Figure 1 As shown, the self-diagnostic autonomous vehicle braking system of the present invention includes a data acquisition unit 1, a control unit 2, a drive unit 3 and a braking unit 4. The data acquisition unit 1 is electrically connected to the control unit 2, and the control unit 2 is electrically connected to the drive unit 3 and the braking unit 4 respectively.

[0021] Data acquisition unit 1 includes a speed sensor 11, a distance detection sensor 12, and a timing module 13. In this embodiment, the speed sensor 11 is a rotary encoder of model E6B2-CWZ6C, which is installed at the axle of the driven wheel of the unmanned vehicle 5 to collect the vehicle's given speed vc and actual speed v. m The distance detection sensor 12 is a laser rangefinder of model HL-G103-A-C5, installed on the front side of the car facing the parking point, used to collect the actual distance L between the car and the parking point. s The timing module 13 uses a high-precision real-time clock module, model DS3231, to collect the braking time t of the trolley. s Parking time t p and the interval t during the deceleration process c The sampling frequency is 100Hz.

[0022] Control unit 2 uses an STM32F407 microcontroller with a built-in self-diagnostic braking algorithm, such as... Figure 2 As shown, the self-diagnostic braking algorithm includes a data processing module 21, a braking parameter calculation module 22, and a compensation control module 23. Each module implements its corresponding function through software programming.

[0023] The drive unit 3 uses a servo motor of model MS1H2-50B30CB, which is connected to the drive wheel of the trolley and is used to perform inching compensation actions; the braking unit 4 uses an electromagnetic brake of model DHD-15, which is installed at the wheel of the trolley and is used to provide basic braking force.

[0024] like Figure 3 As shown, the self-diagnostic braking method for autonomous vehicles of the present invention is applied to the above-mentioned braking system, and the specific implementation steps are as follows: S1: Pre-braking test and data acquisition: When the slag bag flatbed truck (unmanned vehicle 5) travels to the preset braking test area 15 meters away from the target parking point, the control unit 2 sends a pre-braking command to the braking unit 4. The braking unit 4 performs pre-braking with 40% of the normal braking force, and the test time is 1.5 seconds; at the same time, the speed sensor 11 collects the given speed v during the test. c =5m / s, interval time t c =0.5s initial velocity v m1 =4.8m / s, actual velocity v at the end time m2 =4.2m / s, distance detection sensor 12 collects the actual distance L between the car and the parking point at this time. s =14.5m, timing module 13 collects the interval time t during the deceleration process. c =0.5s, and all data is transmitted to control unit 2.

[0025] S2: Parameter Calculation: The self-diagnostic braking algorithm of control unit 2 is activated. Data processing module 21 filters and organizes the collected data. After confirming that there is no abnormal data, braking parameter calculation module 22 calculates the parameters according to the formula: (The negative sign indicates deceleration.) Calculate the real-time deceleration a n ; Then, using the formula: , Derivation of theoretical braking distance L c .

[0026] S3: Formal Braking: When the distance detection sensor 12 detects the actual distance L between the car and the stopping point... s When the distance reaches 7.35m (i.e., Ls=Lc), the control unit 2 sends a formal braking command to the braking unit 4, and the braking unit 4 performs braking with 100% braking force, causing the car to begin to decelerate.

[0027] S4: Jog Compensation: During braking, the control unit 2 monitors in real time through the data acquisition unit 1. When it detects that the car has decelerated to 1m away from the stopping point, it is expected that the car will stop in advance (with a deviation of about 0.3m), and the target final speed is set. v 2 =0.3m / s to correct for this deviation; Calculation of jogging pulse width: The driver outputs power F, the jogging time is t, and the impulse generated within the jogging time t is: ; The compensation control module 23 is based on the momentum formula:

[0028] Combining the target velocity deviation Δv = 0.3 m / s and the real-time deceleration a = 1.2 m / s 2 The jogging time t = 0.25s was calculated; then the jogging acceleration time t1 and the undriven coasting deceleration time t2 were solved in reverse using the following formulas: Formula for total distance traveled: ; Final velocity formula: v 2 =v 1 +at 2 =v 0 +at 1 t 2 +at 2 , Substitution v 0 =0m / s, a=1.2m / s², v 2 =0.3m / s, t1+t2=0.25s, solving for t1, we get t1=0.1s and t2=0.15s; Further calculations of parameters for each stage:

[0029] Total distance traveled within a pulse cycle l 1 + l 2 ==0.006 + 0.0315 = 0.0375m; Control unit 2 sends a forward jog command to drive unit 3. Drive unit 3 performs jog compensation according to the above parameters, and the car moves forward by about 0.0375m, finally stopping precisely at the target parking point.

[0030] In this embodiment, the self-diagnosis of braking capability is achieved through pre-braking test. Combined with the reverse solution logic of jogging parameters, the compensation requirements are accurately adapted and the braking deviation is effectively corrected, which fully verifies the practicality and superiority of the present invention.

Claims

1. A braking system for an autonomous vehicle based on self-diagnosis, characterized in that, It includes a data acquisition unit (1), a control unit (2), a drive unit (3), and a braking unit (4). The data acquisition unit (1) is electrically connected to the control unit (2) and is used to collect the operating data of the unmanned vehicle (5) and transmit it to the control unit (2). The control unit (2) is electrically connected to the drive unit (3) and the braking unit (4) respectively. It has a built-in self-diagnostic braking algorithm, which is used to calculate the real-time deceleration and theoretical braking distance based on the operating data, and control the drive unit (3) and the braking unit (4) to perform braking actions and inching compensation in coordination. The braking unit (4) is used to provide basic braking force, and the drive unit (3) is used to perform inching compensation actions to correct braking deviation.

2. The self-diagnostic-based autonomous vehicle braking system according to claim 1, characterized in that, The data acquisition unit (1) includes a speed sensor (11), a distance detection sensor (12), and a timing module (13); the speed sensor (11) is used to acquire the given speed v of the vehicle. c Actual speed v m The distance detection sensor (12) is used to collect the actual distance L between the car and the parking point. s The timing module (13) is used to collect the braking time t of the trolley. s Parking time t p and the interval t during the deceleration process c .

3. The self-diagnostic-based braking system for unmanned vehicles according to claim 2, characterized in that, The speed sensor (11) is a rotary encoder, the distance detection sensor (12) is a laser rangefinder, and the timing module (13) is a high-precision real-time clock module.

4. The self-diagnostic-based autonomous vehicle braking system according to claim 1, characterized in that, The self-diagnostic braking algorithm includes a data processing module (21), a braking parameter calculation module (22), and a compensation control module (23). The braking parameter calculation module (22) is used to calculate the deceleration for each deceleration based on the processed data. a n and theoretical braking distance L c The compensation control module (23) is used to calculate the jog pulse parameters according to the actual braking state and output compensation commands.

5. The self-diagnostic-based braking system for unmanned vehicles according to claim 4, characterized in that, The reduction a n The calculation formula is: ， Where v m1 Let t be the interval time. c The actual velocity at the initial moment, v m2 Let t be the interval time. c The actual speed at the end; the formula for calculating the theoretical braking distance Lc is: 。 6. A braking method for an autonomous vehicle based on self-diagnosis, characterized in that, Applied to the braking system according to any one of claims 1-5, comprising the following steps: S1: When the driverless car (5) travels to the preset braking test area, the control unit (2) controls the braking unit (4) to perform a pre-braking test, and the data acquisition unit (1) synchronously collects the running data and time data during the test. S2: Control unit (2) uses a self-diagnostic braking algorithm, based on the formula: ， Calculate the real-time deceleration a n ; Then, according to the formula: ， Derivation of theoretical braking distance L c ; S3: When the distance detection sensor (12) detects the actual distance L between the driverless car (5) and the parking point s ≥L c At that time, the control unit (2) controls the braking unit (4) to start the formal braking; S4: During braking, the control unit (2) judges the braking status of the unmanned vehicle (5) in real time. If it detects that the vehicle stops in advance, the control drive unit (3) performs forward jogging compensation to extend the braking distance. If it detects that the stopping distance exceeds the stopping point, the control drive unit (3) performs reverse jogging compensation to shorten the braking distance.

7. The self-diagnostic braking method for an unmanned vehicle according to claim 6, characterized in that, The basic jogging time for jogging compensation in step S4 is calculated using the momentum formula: The jogging pulse width is calculated as follows: the driver outputs power F, the jogging time t, and the impulse generated within the jogging time t is: , , Where Δ v The target speed change required to correct braking deviation, a This refers to the acceleration during the inching process.

8. The braking method for an unmanned vehicle based on self-diagnosis according to claim 7, characterized in that, The acceleration time t1 and the deceleration time t2 without drive constitute a pulse period T. The distance and speed in each time period are calculated using the following formula: in, l 1 The distance traveled within time period t1. l 2 The distance traveled during time period t2 v 0 The initial velocity before jogging is... v 1 The speed of the driverless car (5) after time period t1 ends. v 2 The final velocity of the unmanned vehicle (5) after time period t2 ends, and a is the acceleration during the jogging process; the total distance the vehicle moves within the pulse period is: ， Using the total distance traveled formula and the final velocity v 2 The calculation formula can be used to solve for the target's final velocity. v 2 The corresponding jog acceleration time t1 and the undriven coasting deceleration time t2.

9. The braking method for an unmanned vehicle based on self-diagnosis according to claim 6, characterized in that, The braking force of the pre-braking test in step S1 is 30%-50% of the formal braking force, the test time does not exceed 2 seconds, and the normal driving trajectory of the unmanned vehicle (5) is not affected during the test. The distance between the preset braking test area and the target parking point is not less than the theoretical braking distance L. c 2 times.

10. The braking method for an unmanned vehicle based on self-diagnosis according to claim 6, characterized in that, The duration of a single jog compensation in step S4 shall not exceed 0.5 seconds, and the cumulative number of compensations shall not exceed 3. The acceleration of the forward jog compensation is in the same direction as the driving direction of the unmanned vehicle (5), and the acceleration of the reverse jog compensation is opposite to the driving direction of the unmanned vehicle (5).

Images