Chassis control parameter generation method, system, device and equipment of trackless transport vehicle and medium

Abstract

The invention discloses a chassis control parameter generation method, system, device and equipment for a trackless transport vehicle and a medium, and the method comprises the steps: obtaining a target vehicle identifier of the trackless transport vehicle, recognizing the vehicle type of the trackless transport vehicle according to the target vehicle identifier, and obtaining the vehicle type information; according to the vehicle type information, selecting a corresponding calibration action sequence to test the trackless transport vehicle to obtain target test data; testing the trackless transport vehicle according to the calibration action sequence to obtain target test data; performing parameter identification according to the target test data to obtain a first chassis control parameter; and generating a chassis control model corresponding to the trackless transport vehicle according to the first chassis control parameter. The chassis control parameters of any type of trackless transport vehicle can be adaptively generated, one-to-one manual configuration is not needed, the cost is low, and the efficiency is high.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of trackless transport vehicle control, in particular to a chassis control parameter generation method, system, device, equipment and medium for trackless transport vehicle. BACKGROUND

[0002] At present, the automatic driving modification of underground trackless transport vehicles faces severe challenges. First, underground vehicles have different brands, models, and degrees of obsolescence, and their drive-by-wire chassis interface protocols and dynamic response characteristics (such as response delay, gain, and linearity) of actuators (steering, braking, and driving) are different.

[0003] In related technologies, the configuration of chassis control parameters for various types of trackless transport vehicles is usually customized for a specific vehicle model, and relies on control engineers to conduct a large amount of tedious manual road testing and parameter setting, resulting in a deployment period of several weeks for new vehicle models, high cost, and low efficiency. SUMMARY

[0004] The present application aims to provide a chassis control parameter generation method, system, device, equipment and medium for trackless transport vehicle, which can adaptively generate chassis control parameters for any type of trackless transport vehicle without manual one-to-one configuration, with low cost and high efficiency.

[0005] In a first aspect, the present application provides a chassis control parameter generation method for trackless transport vehicle, comprising the following steps: Obtaining a target vehicle identifier of a trackless transport vehicle, the target vehicle identifier being used to indicate the identity of an uncalibrated trackless transport vehicle; Identifying the vehicle type of the trackless transport vehicle according to the target vehicle identifier to obtain vehicle type information; Selecting a corresponding calibration action sequence according to the vehicle type information to test the trackless transport vehicle and obtaining target test data; Performing parameter identification according to the target test data to obtain first chassis control parameters; Generating a corresponding chassis control model for the trackless transport vehicle according to the first chassis control parameters.

[0006] According to some embodiments of the present application, the vehicle information of the trackless transport vehicle is obtained, comprising: Obtaining an identifier of the trackless transport vehicle; Judging whether the trackless transport vehicle has a chassis control model according to the identifier; In the case where there is no chassis control model, generating a target vehicle identifier of the trackless transport vehicle according to the identifier.

[0007] According to some embodiments of the present application, the vehicle types include Ackerman type, hinge type and track type, and the selecting a corresponding calibration action sequence to test the trackless vehicle according to the vehicle type information includes: In a case where the vehicle type information indicates that the trackless vehicle is of the Ackerman type, a first calibration action sequence is selected to test the trackless vehicle; the first calibration action sequence includes a longitudinal calibration action and a first lateral calibration action, the longitudinal calibration action is used to indicate acceleration test and braking test of the trackless vehicle; the first lateral calibration action is used to indicate circular motion test and step steering test of the trackless vehicle; Or, in a case where the vehicle type information indicates that the trackless vehicle is of the hinge type, a second calibration action sequence is selected to test the trackless vehicle; the second calibration action sequence includes a longitudinal calibration action and a second lateral calibration action; the second lateral calibration action is used to indicate left and right limit steering test of the hinge angle of the trackless vehicle; Or, in a case where the vehicle type information indicates that the trackless vehicle is of the track type, a third calibration action sequence is selected to test the trackless vehicle; the third calibration action sequence includes a longitudinal calibration action and a third lateral calibration action; the third lateral calibration action is used to indicate center steering and straight driving test of the trackless vehicle.

[0008] According to some embodiments of the present application, the target test data includes first test data corresponding to the Ackerman type, second test data corresponding to the hinge type and third test data corresponding to the track type, and the first chassis control parameter includes a first sub-chassis control parameter, a second sub-chassis control parameter and a third sub-chassis control parameter; the parameter identification according to the target test data includes: According to the first test data, the first sub-chassis control parameter is obtained by parameter identification, and the first sub-chassis control parameter includes acceleration gain, braking gain, acceleration time constant, braking time constant, steering gain, steering time constant and steering zero position; Or, according to the first test data, the second sub-chassis control parameter is obtained by parameter identification, and the second sub-chassis control parameter includes acceleration gain, braking gain, acceleration time constant, braking time constant, hinge control gain, hinge response time constant and steering zero position; Or, according to the third test data, the third sub-chassis control parameter is obtained by parameter identification, and the third sub-chassis control parameter includes acceleration gain, braking gain, acceleration time constant, braking time constant, hinge control gain, hinge response time constant and steering zero position.

[0009] According to some embodiments of the present application, before the step of testing the trackless transport vehicle according to the selected corresponding calibration action sequence, the method further comprises: generating a vehicle navigation instruction for guiding the trackless transport vehicle to a safe calibration area.

[0010] According to some embodiments of the present application, after the step of generating the corresponding chassis control model of the trackless transport vehicle according to the first chassis control parameter, the method further comprises: obtaining running data of the trackless transport vehicle; calculating a running deviation value according to the running data, the running deviation value being used to indicate a deviation between a control instruction and an actual response state of the trackless transport vehicle; performing performance degradation analysis on the trackless transport vehicle according to the running deviation value, and generating a performance analysis result; in a case where the performance analysis result indicates that the trackless transport vehicle has performance degradation, generating a re-calibration command, the re-calibration command being used to instruct to re-test and re-identify parameters of the trackless transport vehicle to obtain a second chassis control parameter; updating the chassis control model of the trackless transport vehicle according to the second chassis control parameter.

[0011] In a second aspect, embodiments of the present application provide an automatic control system of a trackless transport vehicle in a well, comprising a controller, which performs control of the trackless transport vehicle by using the method for generating a chassis control parameter of a trackless transport vehicle according to the first aspect.

[0012] In a third aspect, embodiments of the present application provide a device for generating a chassis control parameter of a trackless transport vehicle, comprising: an identification obtaining module, configured to obtain a target vehicle identification of a trackless transport vehicle, the target vehicle identification being used to indicate an identity of a trackless transport vehicle that has not been calibrated; a type identifying module, configured to identify a vehicle type of the trackless transport vehicle according to the target vehicle identification, and obtain vehicle type information; a vehicle testing module, configured to test the trackless transport vehicle according to the vehicle type information by using a corresponding calibration action sequence, and obtain target testing data; a parameter identifying module, configured to perform parameter identification according to the target testing data, and obtain a first chassis control parameter; a control model generating module, configured to generate a corresponding chassis control model of the trackless transport vehicle according to the first chassis control parameter.

[0013] In a fourth aspect, embodiments of the present application provide an electronic device, comprising a processor and a memory storing computer program instructions. The processor implements the chassis control parameter generation method of the trackless transport vehicle according to the first aspect when executing the computer program instructions.

[0014] In a fifth aspect, an embodiment of the present application provides a computer readable storage medium, and the computer readable storage medium stores computer program instructions, and the computer program instructions are executed by a processor to implement the chassis control parameter generation method of the trackless transport vehicle according to the first aspect.

[0015] The chassis control parameter generation method, system, device, equipment and medium of the trackless transport vehicle according to the embodiments of the present application have at least the following beneficial effects: In the embodiment, first, a target vehicle identifier of the trackless transport vehicle is acquired; then, a vehicle type of the trackless transport vehicle is identified according to the target vehicle identifier, and vehicle type information is obtained; then, a corresponding calibration action sequence is selected according to the vehicle type information to test the trackless transport vehicle, and target test data is obtained; then, parameter identification is performed according to the target test data, and first chassis control parameters are obtained; finally, a chassis control model corresponding to the trackless transport vehicle is generated according to the first chassis control parameters. The present application can adaptively generate chassis control parameters of any type of trackless transport vehicle, without manual one-to-one manual configuration, and has low cost and high efficiency.

[0016] Additional aspects and advantages of the present application will be in part apparent and in part pointed out hereinafter. BRIEF DESCRIPTION OF DRAWINGS

[0017] The present application will be further described below in conjunction with the accompanying drawings and embodiments, in which: Figure 1 A flowchart of an embodiment of the chassis control parameter generation method of the trackless transport vehicle provided by the present application is shown in the figure; Figure 2 A structural diagram of the chassis control parameter generation device of the trackless transport vehicle provided by the present application is shown in the figure Figure 3 A structural diagram of the electronic device provided by the present application is shown in the figure. DETAILED DESCRIPTION

[0018] The features and exemplary embodiments of various aspects of the present application will be described in detail below, in order to make the purposes, technical solutions and advantages of the present application more clear and apparent, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are intended to explain the present application only, not to limit the present application. The present application can be implemented without some of these specific details by those skilled in the art. The following description of the embodiments is merely intended to provide a better understanding of the present application by showing examples of the present application.

[0019] In this document, relational terms such as first and second and the like can be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises... a" does not, without more constraints, exclude the presence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0020] To solve the problems in the prior art, the embodiment of the present application provides a chassis control parameter generation method, system, device, equipment and medium of a trackless transport vehicle. First, the chassis control parameter generation method of the trackless transport vehicle provided by the embodiment of the present application is introduced.

[0021] Figure 1 A flowchart of the chassis control parameter generation method of the trackless transport vehicle provided by the embodiment of the present application is shown. The method is applied to an electronic device, and a chassis control parameter generation method of a trackless transport vehicle, comprising the following steps: S101, obtaining a target vehicle identifier of a trackless transport vehicle, the target vehicle identifier being used to indicate the identity of an uncalibrated trackless transport vehicle; S102, identifying a vehicle type of the trackless transport vehicle according to the target vehicle identifier, to obtain vehicle type information; S103, selecting a corresponding calibration action sequence according to the vehicle type information to test the trackless transport vehicle, to obtain target test data; S104, performing parameter identification according to the target test data, to obtain first chassis control parameters; S105, generating a chassis control model corresponding to the trackless transport vehicle according to the first chassis control parameters.

[0022] In the embodiment, first, a target vehicle identifier of a trackless transport vehicle is obtained; then, a vehicle type of the trackless transport vehicle is identified according to the target vehicle identifier, to obtain vehicle type information; next, a corresponding calibration action sequence is selected according to the vehicle type information to test the trackless transport vehicle, to obtain target test data; then, parameter identification is performed according to the target test data, to obtain first chassis control parameters; finally, a chassis control model corresponding to the trackless transport vehicle is generated according to the first chassis control parameters. The present application can adaptively generate chassis control parameters of any type of trackless transport vehicle, without manual one-to-one manual configuration, with low cost and high efficiency.

[0023] It should be noted that in the above step S101, obtaining the target vehicle identifier of the trackless transport vehicle refers to obtaining the identifier corresponding to the trackless transport vehicle without setting the chassis control parameter. Specifically, the unique identifier corresponding to each trackless transport vehicle can be obtained through the vehicle gateway, and then the existing identifier is traversed in the vehicle file. If it exists, it indicates that the trackless transport vehicle has calibrated chassis control parameters and does not need to be configured. If it does not exist, it is determined to be a new vehicle without calibration, and the identifier of the trackless transport vehicle is taken as the target vehicle identifier.

[0024] In the above step S102, the vehicle type of the trackless transport vehicle is identified according to the target vehicle identifier, which refers to identifying the vehicle type of the trackless transport vehicle according to the unique identifier of the vehicle, i.e. through the gateway identification of the vehicle. For example, it belongs to the Ackerman type trackless transport vehicle, the articulated type trackless transport vehicle or the track type trackless transport vehicle. It should be noted that in the underground application scenario of the mine, each trackless transport vehicle is equipped with a gateway to establish a remote communication connection with the ground control station. When assigning identifiers, different types of vehicles have corresponding rule identifiers, such as 1 network segment for articulated vehicle model vehicles, 2 network segment for Ackerman chassis model vehicles, and 3 network segment for track vehicle model vehicles. Therefore, by identifying the identifier of the vehicle, the vehicle type of the trackless transport vehicle can be confirmed.

[0025] The calibration action sequence in the above step S103 refers to various types of test actions preset according to different vehicles. Generally, the calibration action is divided into two categories: longitudinal calibration and transverse calibration. Longitudinal calibration and transverse calibration correspond to the motion control of the vehicle in different directions. Longitudinal calibration corresponds to the action in the front-rear direction of the vehicle, such as acceleration and braking. Transverse calibration corresponds to the action in the left-right direction of the vehicle, such as steering.

[0026] Different calibration actions are selected for testing for different vehicle types, which can better obtain the chassis control parameters corresponding to the vehicle type. Therefore, in this application, the corresponding calibration action sequence is selected according to the vehicle type information to test the trackless transport vehicle. Specifically, taking the Ackerman type trackless transport vehicle as an example, the longitudinal calibration test is to accelerate and brake at 20%, 50% and 80% of the command power respectively, and maintain for a period of time to observe the steady-state response. The transverse calibration test is to control the vehicle to perform circular motion and step steering. When the vehicle performs longitudinal or transverse calibration corresponding motion, the measurement data is obtained through the sensor, such as synchronously collecting the actual acceleration, deceleration and yaw angular velocity of the vehicle by using high-precision IMU and wheel speed meter. The actual angle and speed are obtained through the angle sensor and speed sensor.

[0027] The parameter identification according to the target test data in the step S104 is to identify the obtained vehicle test data by a parameter identification algorithm, and calculate the chassis control parameters of the trackless transport vehicle. The chassis control parameters of the trackless transport vehicle mainly include gain parameters and time constants, such as acceleration gain, brake gain, acceleration time constant, brake time constant, etc.

[0028] The parameter identification algorithm can use recursive least squares method or dynamic response method for parameter identification. For example, the gain K of longitudinal calibration is taken as an example, the algorithm collects the data sequence of "step input instruction u" and "actual acceleration a". The recursive least squares method is used to fit the gain K in a=K*u. For dynamic response, a first-order model a(s) / u(s)=K / (τs+1) is fitted, and the gain K and time constant τ are obtained.

[0029] Specifically, a first-order inertial system is used to construct a continuous system model, and the expression is: a(s) / u(s)=K / (τs+1); The time domain response formula is: a(t)=K×u×(1-e^(-t / τ)); Where a(t) is the actual acceleration at time t (m / s2), the gain K can be the acceleration gain K_acc or the brake gain K_brake, and the time constant τ can be the acceleration time constant τ_acc or the brake time constant τ_brake.

[0030] In summary, the chassis control parameters of the trackless transport vehicle are obtained by the following steps: A throttle instruction is given to the vehicle as a step input instruction u, that is, the throttle is suddenly stepped to a certain fixed position and kept. Then the actual acceleration a(t) of the vehicle is recorded over time, and finally the collected data is used to estimate K and τ by curve fitting.

[0031] In the step S105, the chassis control model corresponding to the trackless transport vehicle is generated according to the first chassis control parameters, which means that the calculated gain K and time constant τ are stored in the dynamic parameter library as the exclusive control model of the trackless transport vehicle. The system generates control commands according to the chassis control model of each trackless transport vehicle to realize automatic driving.

[0032] The following is a detailed description of system parameter identification using the least squares method, as follows: First, a discrete-time system model corresponding to the trackless transport vehicle is established, and the expression is as follows: y[k]=α·y[k-1]+β·u[k-1]+ε[k]; Where k represents the current time, and k-1 represents the previous time. y[k] is the system output at the current time (i.e., the acceleration at the current time); y[k-1] is the system output at the previous time (i.e., the acceleration at the previous time); u[k-1] is the system input at the previous time (i.e., the throttle or brake command at the previous time). α is the system inertia coefficient (0 < α < 1). β is the system gain coefficient, and ε[k] represents the random error term at time k, including measurement noise and unmodeled dynamics. β and ε[k] are the system parameters to be identified, and the specific calculation steps are as follows: 1) For N data points, construct the matrix equation Y = Φθ + E; Output vector: Y=[y[1],y[2],...,y[N]] ; Data matrix: Φ=[[y[0],u[0]],[y[1],u[1]],...,[y[N-1],u[N-1]]]; Parameter vector: θ=[α,β] ; Error vector: E=[ε[1],ε[2],...,ε[N]] ; 2) Least squares method solution formula: θ=[α,β] =(Φ Φ) -1 Φ Y; Φ Φ=[Σy²[k-1]Σy[k-1]u[k-1]]; [Σy[k-1]u[k-1]Σu²[k-1]]; Φ Y = [Σy[k-1]y[k]]; [Σu[k-1]y[k]]; Extract the discrete parameters α and β from θ.

[0033] 3) Continuous parameter conversion: After obtaining the discrete parameters α and β, convert them into continuous system parameters: τ = -Δt / ln(α); K = β / (1-α); Where Δt is the sampling period, τ is the time constant, and K is the system gain.

[0034] In some implementations, obtaining vehicle information for the trackless transport vehicle may include: Obtain the identifier of the trackless transport vehicle; Determine whether the trackless transport vehicle has a chassis control model based on the identifier; In the absence of a chassis control model, the target vehicle identifier for the trackless transport vehicle is generated based on the identifier.

[0035] In this embodiment, the identifier of the trackless transport vehicle is first obtained. Then, based on the identifier, it is determined whether the trackless transport vehicle has a chassis control model. Finally, if no chassis control model exists, a target vehicle identifier for the trackless transport vehicle is generated based on the identifier. This embodiment can automatically identify whether a trackless transport vehicle has a chassis control model and generate a target vehicle identifier for a new vehicle without a chassis control model, thereby improving automation efficiency.

[0036] Specifically, the unique identifier corresponding to each trackless transport vehicle is obtained through the vehicle gateway. Then, the existing identifiers are traversed in the vehicle-side file. If they exist, it means that the trackless transport vehicle already has the calibrated chassis control parameters and no parameter configuration is required. If they do not exist, it is considered to be a new uncalibrated vehicle, and the identifier of the trackless transport vehicle is used as the target vehicle identifier.

[0037] In some implementations, the vehicle types include Ackerman, articulated, and tracked types. Selecting the corresponding calibration sequence of actions based on the vehicle type information to test the trackless transport vehicle may include: When the vehicle type information indicates that the trackless transport vehicle is an Ackerman type, the first calibration action sequence is selected to test the trackless transport vehicle; the first calibration action sequence includes a longitudinal calibration action and a first lateral calibration action. The longitudinal calibration action is used to indicate that the trackless transport vehicle is to be subjected to acceleration test and braking test; the first lateral calibration action is used to indicate that the trackless transport vehicle is to be subjected to circular motion test and step turn test. Alternatively, if the vehicle type information indicates that the trackless transport vehicle is an articulated type, the second calibration action sequence is selected to test the trackless transport vehicle; the second calibration action sequence includes a longitudinal calibration action and a second lateral calibration action; the second lateral calibration action is used to indicate that the trackless transport vehicle is subjected to a left and right limit steering test of the articulation angle. Alternatively, if the vehicle type information indicates that the trackless transport vehicle is a tracked type, the third calibration action sequence is selected to test the trackless transport vehicle; the third calibration action sequence includes longitudinal calibration action and third lateral calibration action; the third lateral calibration action is used to indicate that the trackless transport vehicle is subjected to center steering and straight-line driving tests.

[0038] In this embodiment, corresponding calibration actions and lateral calibration actions are designed and tested according to different vehicle types, which can obtain target test data for this type of vehicle and improve the reliability of chassis control parameters.

[0039] Specifically, Ackerman, articulated, and tracked trackless transport vehicles require different test actions due to their different vehicle types. Based on the structural and motion characteristics of the three types of vehicles, this application analyzes that Ackerman, articulated, and tracked vehicles all use the same longitudinal calibration action but different lateral calibration actions. The same longitudinal calibration action is to perform acceleration and braking tests. The purpose of performing longitudinal calibration actions is to obtain longitudinal action test data. Based on the longitudinal action test data, the acceleration gain K_acc, braking gain K_brake, acceleration time constant τ_acc, and braking time constant τ_brake can be calculated.

[0040] Furthermore, the first lateral calibration involves performing circular motion and step steering tests on an Ackerman-type trackless transport vehicle to obtain first lateral motion test data. Based on this data, the steering gain K_δ, steering time constant τ_δ, and steering zero position of the Ackerman chassis can be calculated. Similarly, the second lateral calibration involves performing left and right limit steering tests on an articulated trackless transport vehicle to obtain second lateral motion test data. Based on this data, the articulation control gain K_φ, articulation response time τ_φ, and steering zero position of the articulated chassis can be calculated. Likewise, the third lateral calibration involves performing center steering and straight-line driving tests on a tracked trackless transport vehicle to obtain third lateral motion test data. Based on this data, the differential steering gain K_ω, steering response time τ_ω, and steering zero position of the tracked chassis can be calculated.

[0041] In some implementations, the target test data includes first test data corresponding to the Ackerman type, second test data corresponding to the hinge type, and third test data corresponding to the tracked type. The first chassis control parameters include first sub-chassis control parameters, second sub-chassis control parameters, and third sub-chassis control parameters. Based on the target test data, parameter identification is performed to obtain the first chassis control parameters, including: Based on the first test data, parameter identification is performed to obtain the first sub-chassis control parameters, which include acceleration gain, braking gain, acceleration time constant, braking time constant, steering gain, steering time constant, and steering zero position. Alternatively, based on the first test data, parameter identification is performed to obtain the second sub-chassis control parameters, which include acceleration gain, braking gain, acceleration time constant, braking time constant, articulation control gain, articulation response time constant, and steering zero position. Alternatively, parameter identification can be performed based on the third test data to obtain the third sub-chassis control parameters, which include acceleration gain, braking gain, acceleration time constant, braking time constant, articulation control gain, articulation response time constant, and steering zero position.

[0042] In this embodiment, by identifying parameters based on test data of different vehicle types, the chassis control parameters of that type of vehicle can be obtained in a targeted manner, thereby quickly determining the most suitable chassis control parameters for each vehicle and improving efficiency.

[0043] Specifically, the first test data refers to the longitudinal motion test data and the first lateral motion test data of the Ackerman type trackless transport vehicle, and the first sub-chassis control parameters refer to the acceleration gain K_acc, braking gain K_brake, acceleration time constant τ_acc, braking time constant τ_brake, steering gain K_δ, steering time constant τ_δ, and steering zero position of the Ackerman chassis.

[0044] Similarly, the second test data refers to the longitudinal motion test data and the second lateral motion test data of the articulated trackless transport vehicle, and the second sub-chassis control parameters refer to the acceleration gain K_acc, braking gain K_brake, acceleration time constant τ_acc, braking time constant τ_brake, articulation control gain K_φ, articulation response time τ_φ, and steering zero position of the articulated vehicle chassis.

[0045] Similarly, the third test data refers to the longitudinal motion test data and the third lateral motion test data of the tracked trackless transport vehicle, and the third sub-chassis control parameters refer to the acceleration gain K_acc, braking gain K_brake, acceleration time constant τ_acc, braking time constant τ_brake, articulation control gain K_φ, differential steering gain K_ω, steering response time τ_ω, and steering zero position of the tracked vehicle chassis.

[0046] In some implementations, before testing the trackless transport vehicle by selecting the corresponding calibration sequence of actions based on vehicle type information, the following may also be included: Generate vehicle navigation instructions, which are used to guide the trackless transport vehicle to the designated safe area.

[0047] In this embodiment, before testing the trackless transport vehicle, a vehicle navigation command is generated to guide the trackless transport vehicle to the safety calibration area. This enables the trackless transport vehicle to automatically navigate to the safety calibration area without manual operation, thus improving testing efficiency.

[0048] It should be noted that due to the complex underground environment of the mine, testing needs to be conducted in a safety calibration area to avoid affecting the normal production process. Therefore, before testing the trackless transport vehicle, vehicle navigation instructions are generated to guide the trackless transport vehicle to the safety calibration area to improve the level of automation.

[0049] In some implementations, after generating the chassis control model corresponding to the trackless transport vehicle based on the first chassis control parameters, the following may also be included: Obtain operational data from the trackless transport vehicle; The operational deviation value is calculated based on the operational data. The operational deviation value is used to indicate the deviation between the control commands and the actual response state of the trackless transport vehicle. Based on the operational deviation values, a performance degradation analysis of the trackless transport vehicle is performed, and performance analysis results are generated. If the performance analysis results indicate that the trackless transport vehicle has experienced performance degradation, a recalibration command is generated. The recalibration command is used to instruct the trackless transport vehicle to be retested and its parameters identified to obtain the second chassis control parameters. The chassis control model of the trackless transport vehicle is updated based on the second chassis control parameters.

[0050] In this embodiment, the operating data of the trackless transport vehicle is first acquired, then the operating deviation value is calculated based on the operating data. Performance degradation analysis is then performed on the trackless transport vehicle based on the operating deviation value, generating performance analysis results. If the performance analysis results indicate that the trackless transport vehicle has experienced performance degradation, a recalibration command is generated. The chassis control model of the trackless transport vehicle is updated based on the second chassis control parameters. This allows for automatic monitoring of the trackless transport vehicle's performance during daily operation and adaptive compensation when the trackless transport vehicle experiences a decrease in braking efficiency.

[0051] It should be noted that due to the harsh underground environment and long continuous working hours, the chassis performance of the trackless transport vehicle often deteriorates after several months of operation, resulting in poorer automatic driving tracking and control and potential safety hazards. Therefore, this application first acquires the trackless transport vehicle's operating data in real time through sensors; then, a performance monitor calculates the operating deviation value based on the operating data. The operating deviation value refers to the deviation between the issued control command and the actual response state. Operating deviation value = actual response - expected response. For example, there is a deviation between the braking command and the actual deceleration, or between the steering command and the actual steering angle, or between the articulation command and the actual articulation angle, etc.

[0052] Performance degradation analysis of trackless transport vehicles based on operational deviation values ​​refers to comparing the average of multiple operational deviation values ​​with a preset threshold. When the average deviation value exceeds the preset threshold, it is determined that the performance has degraded; when the average deviation value does not exceed the preset threshold, it is determined that the performance has not degraded.

[0053] Performance degradation analysis can also be performed by setting specific values ​​for the normal range and degradation behavior, as shown in Table 1 below.

[0054] Table 1 Performance Degradation Judgment Table

[0055] By monitoring variables to obtain operating deviation values, and then substituting these values ​​into Table 1, we can analyze whether the deviation falls within the normal range or indicates a decline, thereby outputting the corresponding performance analysis results.

[0056] After the system determines that its performance has degraded, a recalibration command is generated to retest and re-identify the parameters of the trackless transport vehicle to obtain the second chassis control parameters. Retesting and re-identifying parameters means obtaining new chassis control parameters as the second chassis control parameters according to steps S103-104, and then updating the chassis control model based on these second chassis control parameters.

[0057] For example, taking brake performance degradation as an example, after the system generates a recalibration command, it automatically triggers a parking alarm and enters an automatic calibration program. The system controls the vehicle to perform several braking actions and collects data. Then, it uses the least squares algorithm to quickly re-estimate the braking gain and immediately updates the chassis control model with the new braking gain. When the controller's decision layer issues another braking command, the mapping module automatically calculates a new braking command to compensate for the degradation, thereby ensuring that the vehicle ultimately achieves the target deceleration.

[0058] This application also relates to an automatic control system for an underground trackless transport vehicle, including a controller, which controls the trackless transport vehicle using the chassis control parameter generation method of the trackless transport vehicle described in the above embodiments.

[0059] Based on the method for generating chassis control parameters of a trackless transport vehicle provided in the above embodiments, this application also provides a specific implementation of a device for generating chassis control parameters of a trackless transport vehicle.

[0060] like Figure 2 As shown, the chassis control parameter generation device 200 for the trackless transport vehicle provided in this application embodiment may include: The identifier acquisition module 201 is used to acquire the target vehicle identifier of the trackless transport vehicle. The target vehicle identifier is used to indicate the identity of the unmarked trackless transport vehicle. The type recognition module 202 is used to identify the vehicle type of the trackless transport vehicle based on the target vehicle identifier and obtain vehicle type information; The vehicle testing module 203 is used to select the corresponding calibration action sequence based on the vehicle type information to test the trackless transport vehicle and obtain target test data. The parameter identification module 204 is used to identify parameters based on the target test data to obtain the first chassis control parameters. The control model generation module 205 is used to generate a chassis control model corresponding to the trackless transport vehicle based on the first chassis control parameters.

[0061] The chassis control parameter generation device 200 of the trackless transport vehicle in this application embodiment is used to execute the chassis control parameter generation method of the trackless transport vehicle in the above embodiment. Its specific processing procedure is the same as that of the chassis control parameter generation method of the trackless transport vehicle in the above embodiment, and will not be described in detail here.

[0062] Figure 3 A schematic diagram of the hardware structure of the electronic device provided in an embodiment of this application is shown.

[0063] An electronic device may include a processor 301 and a memory 302 storing computer program instructions.

[0064] Specifically, the processor 301 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0065] Memory 302 may include mass storage for data or instructions. For example, and not limitingly, memory 302 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 302 may include removable or non-removable (or fixed) media. Where appropriate, memory 302 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 302 is non-volatile solid-state memory.

[0066] In some embodiments, memory 302 may include read-only memory (ROM), random access memory (RAM), disk storage media device, optical storage media device, flash memory device, electrical, optical, or other physical / tangible memory storage device. Thus, generally, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to one aspect of this disclosure.

[0067] The processor 301 reads and executes computer program instructions stored in the memory 302 to implement any of the chassis control parameter generation methods for trackless transport vehicles in the above embodiments.

[0068] In one example, the electronic device may also include a communication interface 303 and a bus 310. For example, Figure 3As shown, the processor 301, memory 302, and communication interface 303 are connected through bus 310 and complete communication with each other.

[0069] The communication interface 303 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0070] Bus 310 includes hardware, software, or both, that couples components of an online data traffic metering device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 310 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, any suitable bus or interconnect is contemplated herein.

[0071] Furthermore, in conjunction with the chassis control parameter generation method for the trackless transport vehicle in the above embodiments, this application embodiment can provide a computer storage medium for implementation. This computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the chassis control parameter generation methods for the trackless transport vehicle in the above embodiments.

[0072] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0073] The functional blocks shown in the above-described structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0074] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0075] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0076] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method of generating chassis control parameters for a trackless vehicle, characterized by, The method comprises the following steps: obtaining a target vehicle identifier of the trackless vehicle, the target vehicle identifier being used to indicate the identity of the uncalibrated trackless vehicle; identifying the vehicle type of the trackless vehicle according to the target vehicle identifier to obtain vehicle type information; selecting a corresponding calibration action sequence according to the vehicle type information to test the trackless vehicle to obtain target test data; testing the trackless vehicle according to the calibration action sequence to obtain target test data; performing parameter identification according to the target test data to obtain first chassis control parameters; generating a corresponding chassis control model of the trackless vehicle according to the first chassis control parameters.

2. The method of generating chassis control parameters for a trackless vehicle of claim 1, wherein, The vehicle information of the trackless vehicle is obtained, comprising: obtaining an identifier of the trackless vehicle; determining whether a chassis control model exists for the trackless vehicle according to the identifier; generating a target vehicle identifier of the trackless vehicle according to the identifier in the case where no chassis control model exists.

3. The method of generating parameters for controlling a chassis of a trackless vehicle according to claim 1, wherein, The vehicle type comprises Ackerman type, hinge type and track type, and the calibration action sequence corresponding to the vehicle type information is selected to test the trackless vehicle, comprising: in the case where the vehicle type information indicates that the trackless vehicle is of Ackerman type, a first calibration action sequence is selected to test the trackless vehicle; the first calibration action sequence comprises longitudinal calibration actions and first transverse calibration actions, the longitudinal calibration actions being used to indicate acceleration test and braking test of the trackless vehicle, and the first transverse calibration actions being used to indicate circular motion test and step steering test of the trackless vehicle; or, in the case where the vehicle type information indicates that the trackless vehicle is of hinge type, a second calibration action sequence is selected to test the trackless vehicle; the second calibration action sequence comprises longitudinal calibration actions and second transverse calibration actions, the second transverse calibration actions being used to indicate left and right limit steering test of the trackless vehicle at a hinge angle; or, in the case where the vehicle type information indicates that the trackless vehicle is of track type, a third calibration action sequence is selected to test the trackless vehicle; the third calibration action sequence comprises longitudinal calibration actions and third transverse calibration actions, the third transverse calibration actions being used to indicate center steering and straight driving test of the trackless vehicle.

4. The method of generating parameters for controlling a chassis of a trackless vehicle according to claim 3, wherein, The target test data comprises first test data corresponding to Ackerman type, second test data corresponding to hinge type and third test data corresponding to track type, and the first chassis control parameters comprise first sub-chassis control parameters, second sub-chassis control parameters and third sub-chassis control parameters; the first chassis control parameters are obtained by performing parameter identification according to the target test data, comprising: the first sub-chassis control parameters are obtained by performing parameter identification according to the first test data, the first sub-chassis control parameters comprising acceleration gain, braking gain, acceleration time constant, braking time constant, steering gain, steering time constant and steering zero position; Or, according to the first test data, the parameter identification is carried out to obtain the second sub-chassis control parameter, and the second sub-chassis control parameter includes an acceleration gain, a brake gain, an acceleration time constant, a brake time constant, a hinge control gain, a hinge response time constant and a steering zero position. Or, according to the third test data, the parameter identification is carried out to obtain the third sub-chassis control parameter, and the third sub-chassis control parameter includes an acceleration gain, a brake gain, an acceleration time constant, a brake time constant, a hinge control gain, a hinge response time constant and a steering zero position.

5. The method of generating chassis control parameters for a trackless vehicle of claim 1, wherein, Before the test on the trackless transport vehicle according to the corresponding calibration action sequence selected according to the vehicle type information, the method further comprises: generating vehicle navigation instructions for guiding the trackless transport vehicle to a safe calibration area.

6. The method of generating parameters for controlling a chassis of a trackless vehicle according to claim 1, wherein, After the corresponding chassis control model of the trackless transport vehicle is generated according to the first chassis control parameter, the method further comprises: obtaining running data of the trackless transport vehicle; calculating a running deviation value according to the running data, the running deviation value being used to indicate the deviation between the control instruction and the actual response state of the trackless transport vehicle; performing performance degradation analysis on the trackless transport vehicle according to the running deviation value to generate a performance analysis result; in the case that the performance analysis result indicates that the trackless transport vehicle has performance degradation, generating a recalibration command, the recalibration command being used to instruct the trackless transport vehicle to be tested and parameter-identified again to obtain a second chassis control parameter; updating the chassis control model of the trackless transport vehicle according to the second chassis control parameter.

7. An automatic control system for a trackless underground haulage vehicle, characterized in that The device comprises a controller, and the controller is controlled by the chassis control parameter generation method of the trackless transport vehicle according to any one of claims 1 to 6.

8. A device for generating chassis control parameters for a trackless vehicle, characterized in that The device comprises: an identification obtaining module configured to obtain a target vehicle identification of the trackless transport vehicle, the target vehicle identification being used to indicate the identity of the uncalibrated trackless transport vehicle; a type identifying module configured to identify the vehicle type of the trackless transport vehicle according to the target vehicle identification to obtain vehicle type information; a vehicle testing module configured to test the trackless transport vehicle according to the corresponding calibration action sequence selected according to the vehicle type information to obtain target test data; a parameter identifying module configured to perform parameter identification according to the target test data to obtain a first chassis control parameter; a control model generating module configured to generate the corresponding chassis control model of the trackless transport vehicle according to the first chassis control parameter.

9. An electronic device, comprising: The device comprises a processor and a memory storing computer program instructions; The processor executes the computer program instructions to realize the chassis control parameter generation method of the trackless transport vehicle according to any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer program instructions, and the computer program instructions are executed by the processor to realize the chassis control parameter generation method of the trackless transport vehicle according to any one of claims 1 to 6.

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