Unmanned crawler braking system and method based on self-adaptive control

Abstract

The invention relates to the technical field of dynamic parameter correction of self-adaptive control systems, in particular to an unmanned crawler braking system and method based on self-adaptive control. The system comprises a data acquisition module, a viscosity dynamic compensation module, a control instruction generation module and a distributed execution module. The data collection module collects vehicle motion state parameters through an accelerometer, a pitch angle sensor and a hydraulic oil temperature sensor, GPS time service and a CAN bus clock are adopted to calibrate the time sequence of a multi-source sensor, and the control instruction generation module fuses the pitch angle, the steering torque parameter and the viscosity variation. According to the method, through closed-loop viscosity correction, instruction time sequence optimization and low-temperature adaptability regulation and control, the problem of braking torque control deviation of a multi-degree-of-freedom articulated mechanism caused by nonlinear change of the viscosity of a hydraulic medium is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of dynamic parameter correction of adaptive control systems, and in particular to an unmanned tracked vehicle braking system and method based on adaptive control. Background Art

[0002] The adaptive control-based braking system for unmanned tracked vehicles dynamically optimizes control strategies to cope with complex terrain and dynamic conditions by collecting real-time vehicle motion and environmental parameters. The system incorporates the kinematic characteristics of multi-degree-of-freedom articulated mechanisms and utilizes a feedback control mechanism to coordinate the dynamic distribution of braking force between the front and rear vehicles, avoiding dynamic coupling imbalances caused by pitch, torsion, or steering degrees of freedom. By integrating hydraulic system status monitoring data, such as oil pressure and temperature feedback, the control algorithm compensates for the impact of hydraulic fluid viscosity changes on braking response, improving control stability in both low and high temperature environments. Multi-sensor fusion technology analyzes the ground friction coefficient, slope, and obstacle distribution in real time, allowing the control unit to adjust the braking torque and application timing to balance braking efficiency and anti-skid requirements. Furthermore, the system employs robust algorithms to address sensor noise and communication delays, ensuring that basic braking functionality is maintained even when some subsystems experience anomalies.

[0003] Adaptive control-based braking systems for unmanned tracked vehicles must address the issue of braking torque control deviation in multi-degree-of-freedom articulated mechanisms operating in complex terrain, caused by the nonlinear change in hydraulic medium viscosity with ambient temperature. Specifically, when low temperatures cause the viscosity of the hydraulic oil to increase, the brake actuator response lags and dynamic damping increases, resulting in overshoot in pitch or torsion degrees of freedom and disrupting the balance of the front and rear vehicles. For example, in a low-temperature environment, when a tracked vehicle crosses a 0.8m obstacle, the hydraulic system's sudden change in viscosity prevents it from accurately matching the pitch cylinder extension and retraction timing, causing the front vehicle's pitch angle to exceed the design threshold of 30°, leading to the risk of track slippage and center of mass shift. Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the present invention provides an unmanned tracked vehicle braking system and method based on adaptive control. The present invention solves the problem of braking torque control deviation caused by the nonlinear change of hydraulic medium viscosity with ambient temperature in multi-degree-of-freedom articulated mechanisms under complex terrain.

[0005] In order to solve the above technical problems, the specific technical solutions of the present invention are as follows: In a first aspect, the present invention provides an unmanned tracked vehicle braking system based on adaptive control, comprising: A data acquisition module configured to collect vehicle motion state parameters, pitch angle data, and real-time oil temperature data through an accelerometer, a pitch angle sensor, and a hydraulic oil temperature sensor; a viscosity dynamic compensation module, which is in communication with the data acquisition module and is configured to generate a hydraulic medium viscosity correction coefficient based on real-time oil temperature data and calculate a viscosity change based on a preset viscosity-temperature correspondence table; a control command generation module, which interacts with the viscosity dynamic compensation module and is configured to receive a viscosity correction coefficient, fuse pitch angle data with steering torque parameters of the multi-degree-of-freedom articulated mechanism, and generate a brake control command including a timing advance, where the timing advance is calculated by combining the viscosity change and a hydraulic actuator response hysteresis model; A distributed execution module, connected to the control command generation module, is configured to parse brake control commands and dynamically distribute them to the front and rear vehicle hydraulic execution units via the electronic control units in the redundant control channels, thereby synchronously adjusting the extension and retraction timing of the pitch cylinder and the steering damper lock cylinder; Among them, when the real-time angle value is greater than the preset 30° elevation angle threshold, the distributed execution module generates and prioritizes the brake pressure adjustment instruction of the rear vehicle based on the difference between the real-time angle value and the 30° elevation angle threshold to match the dynamic balance requirements of the front vehicle posture.

[0006] Furthermore, the data acquisition module of the adaptive control-based unmanned tracked vehicle braking system of the present invention includes: A timestamp synchronization unit is configured to calibrate the acquisition timing of the accelerometer, hydraulic oil temperature sensor, and pitch angle sensor through GPS timing and CAN bus clock, and output time-aligned vehicle motion state parameters, including pitch angle data and steering torque parameters; The sliding window filtering unit is connected to the timestamp synchronization unit and is configured to receive the time-aligned vehicle motion state parameters, reconstruct the time series of pitch angle data and steering torque parameters based on the dynamic delay model of the communication link, and eliminate the phase offset caused by the difference in signal transmission path. The filtered time series is input into the viscosity dynamic compensation module.

[0007] Furthermore, the control instruction generation module of the adaptive control-based unmanned tracked vehicle braking system of the present invention includes: a model prediction control unit configured to receive the viscosity change output by the viscosity dynamic compensation module, predict the nonlinear relationship between the output pressure of the hydraulic pump station and the extension and retraction rate of the pitch cylinder based on a preset viscosity-temperature correspondence table, and generate an advance control instruction including a timing advance amount, the timing advance amount being calculated by a response lag model of the hydraulic actuator; The viscosity correction factor calculation unit is connected to the model prediction control unit and is configured to convert the viscosity change into a temperature-related viscosity correction factor, and input the correction factor into the pitch cylinder target position calculation logic to adjust the trigger timing of the advance control command and generate the final brake control command.

[0008] Furthermore, the distributed execution module of the adaptive control-based unmanned tracked vehicle braking system of the present invention includes: a priority dispatching unit configured to, when the real-time angle value is higher than a 30° elevation angle threshold, receive a real-time angle value fed back by an elevation angle sensor of a leading vehicle, calculate a difference between the real-time angle value and the 30° elevation angle threshold, generate a dispatch priority parameter for a brake pressure adjustment command for a trailing vehicle based on the difference, and input the dispatch priority parameter into an electronic control unit in a redundant control channel; The parallel processing unit is connected to the priority scheduling unit and is configured to parse and distribute the priority parameters when the difference is within a preset range corresponding to the dynamic balance requirement of the leading vehicle's posture, and synchronously send the brake pressure adjustment instructions of the trailing vehicle and the extension and retraction action timing of the pitch cylinder through the electronic control unit in the redundant control channel, so as to force the timing matching of the hydraulic execution units of the leading and trailing vehicles.

[0009] Furthermore, the unmanned tracked vehicle braking system based on adaptive control of the present invention further includes: a hydraulic circuit preheating module configured to receive the ambient temperature parameter collected by the data acquisition module and activate a graded heating strategy when the ambient temperature falls below a preset threshold of -35°C; A staged heating strategy includes: In the first stage, heating control is used to reduce the yield stress of the hydraulic oil through the low-power heating unit of the hydraulic pump station and monitor the changes in oil viscosity in real time; In the second stage of circulation control, when the oil yield stress is lower than the preset critical value, the hydraulic pump station is driven to perform no-load circulation to accelerate the recovery of oil fluidity; The hydraulic circuit preheating module feeds back the preheated oil viscosity data to the viscosity dynamic compensation module through the hydraulic oil temperature sensor of the data acquisition module for updating the viscosity-temperature correspondence table.

[0010] Furthermore, the hydraulic circuit preheating module of the unmanned tracked vehicle braking system based on adaptive control of the present invention includes: a viscosity adaptive heating unit configured to receive real-time oil temperature data collected by a hydraulic oil temperature sensor, generate a target viscosity curve based on a preset viscosity-temperature correspondence table, generate a gradient heating parameter based on the difference between the target viscosity curve and the real-time oil temperature data, and drive the low-power heating unit to adjust the heating power to reduce the yield stress of the oil; The cold start response unit is connected to the viscosity adaptive heating unit and is configured to receive the preheated oil viscosity data before the braking command is triggered, adjust the oil viscosity to the preset threshold value corresponding to the graded heating strategy in the target viscosity curve, trigger the hydraulic pump station no-load cycle to accelerate the recovery of oil fluidity, and shorten the low-temperature cold start response cycle.

[0011] In a second aspect, the present invention provides an unmanned tracked vehicle braking method based on adaptive control, which is applicable to any unmanned tracked vehicle braking system based on adaptive control, comprising: collecting vehicle motion state parameters, pitch angle data, and real-time oil temperature data through an accelerometer, a pitch angle sensor, and a hydraulic oil temperature sensor; According to the real-time oil temperature data, the hydraulic medium viscosity correction coefficient is generated based on the preset viscosity-temperature correspondence table, and the viscosity change is calculated; The pitch angle data is integrated with the steering torque parameters of the multi-degree-of-freedom articulated mechanism, combined with the viscosity change and the hydraulic actuator response hysteresis model to generate a braking control command including the timing advance amount; The brake control command is parsed and dynamically distributed to the hydraulic actuator units of the front and rear vehicles through the electronic control unit of the redundant control channel. When the real-time angle value is higher than the 30° elevation angle threshold, the brake pressure adjustment command of the rear vehicle is generated and prioritized based on the difference between the real-time angle value and the 30° elevation angle threshold, and the extension and retraction timing of the pitch cylinder and the steering damping lock cylinder are synchronously adjusted.

[0012] Beneficial effects of the present invention: This invention significantly improves the braking performance and stability of unmanned tracked vehicles in complex terrain through a multi-module coordinated control mechanism. The data acquisition module uses GPS timing and sliding window filtering to eliminate timing and phase offsets between multi-sensor signals, providing high-precision data input for subsequent control. The dynamic viscosity compensation module dynamically corrects the nonlinear temperature variation of hydraulic oil viscosity based on a viscosity-temperature mapping table. Combined with a model predictive control unit, it generates advanced control commands. Viscosity correction factors compensate for the response lag of the hydraulic actuator, optimizing the triggering timing of braking commands. The distributed execution module utilizes redundant control channels to enforce timing synchronization between the hydraulic actuators of the leading and trailing vehicles. The priority scheduling unit dynamically adjusts the command distribution logic based on the lead vehicle's pitch angle difference to avoid pitch overshoot and center of mass shift. The hydraulic circuit preheating module utilizes a graded heating strategy and a closed-loop viscosity feedback mechanism to rapidly restore oil fluidity in low-temperature environments and update the viscosity parameter mapping, enhancing the system's robustness in extreme temperatures. Through real-time parameter correction, command timing optimization, and low-temperature adaptability, this technical solution effectively addresses the problem of braking torque control deviation in multi-degree-of-freedom articulated mechanisms caused by nonlinear variations in hydraulic medium viscosity. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the technical solution of the present invention, the following is a brief introduction to the drawings required for use in the embodiments. Obviously, for ordinary technicians in this field, other drawings can be obtained based on the drawings without paying any creative labor.

[0014] Figure 1A flowchart of a braking method for an unmanned tracked vehicle based on adaptive control provided in an embodiment of the present invention.

[0015] Figure 2 Schematic diagram of the steering damping lock, pitch and torsion mechanism in the articulated mechanism provided in an embodiment of the present invention.

[0016] Figure 3 This is a schematic diagram of the pitch hydraulic system of the articulated mechanism provided in an embodiment of the present invention.

[0017] Figure 4 This is a schematic diagram of the hydraulic system of the steering damping locking mechanism provided in an embodiment of the present invention.

[0018] Figure 5 A schematic diagram of the pump station composition provided in an embodiment of the present invention.

[0019] Figure 6 Schematic diagram of a fuel tank thermostat provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the specific embodiments of the present invention and the corresponding drawings. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. The technical solutions provided by each embodiment of the present invention are described in detail below in conjunction with the drawings. In order to better understand the purpose of the present invention, the present invention is further described in detail below.

[0021] In a first aspect, the present invention provides an unmanned tracked vehicle braking system based on adaptive control, comprising: A data acquisition module configured to collect vehicle motion state parameters, pitch angle data, and real-time oil temperature data through an accelerometer, a pitch angle sensor, and a hydraulic oil temperature sensor; a viscosity dynamic compensation module, which is in communication with the data acquisition module and is configured to generate a hydraulic medium viscosity correction coefficient based on real-time oil temperature data and calculate a viscosity change based on a preset viscosity-temperature correspondence table; a control command generation module, which interacts with the viscosity dynamic compensation module and is configured to receive a viscosity correction coefficient, fuse pitch angle data with steering torque parameters of the multi-degree-of-freedom articulated mechanism, and generate a brake control command including a timing advance, where the timing advance is calculated by combining the viscosity change and a hydraulic actuator response hysteresis model; A distributed execution module, connected to the control command generation module, is configured to parse brake control commands and dynamically distribute them to the front and rear vehicle hydraulic execution units via the electronic control units in the redundant control channels, thereby synchronously adjusting the extension and retraction timing of the pitch cylinder and the steering damper lock cylinder; Among them, when the real-time angle value is greater than the preset 30° elevation angle threshold, the distributed execution module generates and prioritizes the brake pressure adjustment instruction of the rear vehicle based on the difference between the real-time angle value and the 30° elevation angle threshold to match the dynamic balance requirements of the front vehicle posture.

[0022] The adaptively controlled braking system for unmanned tracked vehicles provided by this invention achieves dynamic braking force adjustment in complex terrain through the collaboration of multiple modules. The data acquisition module utilizes an accelerometer, a pitch angle sensor, and a hydraulic oil temperature sensor to acquire vehicle motion parameters, pitch angle data, and hydraulic oil temperature data in real time. This module uses GPS timing and the CAN bus clock to calibrate the acquisition timing of various sensors, outputting time-aligned vehicle motion parameters. This eliminates timing deviations caused by differences in sensor signal transmission paths and provides consistent data input for subsequent modules.

[0023] After receiving real-time oil temperature data, the dynamic viscosity compensation module analyzes the nonlinear variation of hydraulic fluid viscosity with temperature based on a preset viscosity-temperature mapping table, generates a viscosity correction coefficient, and calculates the viscosity change. This table, which uses experimentally calibrated viscosity values ​​at different temperatures and an interpolation algorithm to construct a continuous mapping, enables the compensation module to dynamically correct for the effects of sudden changes in hydraulic fluid viscosity on braking response in low or high temperature environments.

[0024] The control command generation module integrates the pitch angle data and the steering torque parameters of the multi-degree-of-freedom articulated mechanism, combines the viscosity change and the hydraulic actuator response hysteresis model, and generates a braking control command including the timing advance. The model prediction control unit predicts the dynamic relationship between the hydraulic pump station output pressure and the pitch cylinder extension and contraction rate through the viscosity-temperature correspondence table to generate the advance control command; the viscosity correction factor calculation unit converts the viscosity change into a temperature-related correction factor and embeds it into the pitch cylinder target position calculation logic, such as Figure 3 The figure shows the control circuit of the pitch cylinder (including the reversing valve and the check valve). This circuit responds to the advance control command and adjusts the flow direction of the hydraulic oil to achieve cylinder extension and retraction. The timing advance is calculated by the viscosity change and the response lag model to ensure that the command is triggered earlier when the viscosity increases (such as in low temperature environment) to compensate for the delay. Similarly, Figure 4 As shown, it shows how the solenoid reversing valve and throttle valve switch states (damping or locking) according to the command, the throttle valve buffers vibration, the viscosity correction factor optimizes the command triggering timing, avoids steering overshoot, adjusts the command triggering timing, and compensates for the response delay of the hydraulic system caused by increased viscosity.

[0025] After the distributed execution module analyzes the brake control command, it dynamically distributes the command to the front and rear vehicle hydraulic execution units through the electronic control unit in the redundant control channel. The priority scheduling unit monitors the difference between the real-time angle value fed back by the front vehicle elevation sensor and the 30° elevation threshold in real time, and dynamically adjusts the distribution priority of the rear vehicle brake pressure adjustment command; when the difference reaches the preset range, the parallel processing unit forces the synchronization of the rear vehicle brake pressure adjustment command and the timing of the pitch cylinder extension and retraction action to avoid track slippage or center of mass shift caused by the front vehicle's posture exceeding the limit. Figure 2 As shown in the figure, the articulated mechanism (including the pitch cylinder and steering damper lock cylinder) is the target of execution. The electronic control unit distributes commands based on priority parameters to synchronize the cylinder extension and retraction timing. For example, when the front vehicle pitch angle approaches the 30° threshold, the command is preferentially distributed to the steering damper lock cylinder to prevent posture imbalance.

[0026] The hydraulic circuit preheating module activates a staged heating strategy when the ambient temperature drops below -35°C. This strategy reduces the yield stress of the hydraulic oil using low-power heating units. Once fluidity is restored, it triggers a no-load cycle in the pump station, accelerating the uniform distribution of oil temperature. Viscosity data from the preheated oil is fed back to the dynamic viscosity compensation module via a hydraulic oil temperature sensor. This dynamically updates the viscosity-temperature relationship table, creating a closed-loop parameter correction mechanism that improves control stability in extremely low-temperature environments.

[0027] Specifically, the data acquisition module of the unmanned tracked vehicle braking system based on adaptive control of the present invention includes: A timestamp synchronization unit is configured to calibrate the acquisition timing of the accelerometer, hydraulic oil temperature sensor, and pitch angle sensor through GPS timing and CAN bus clock, and output time-aligned vehicle motion state parameters, including pitch angle data and steering torque parameters; The sliding window filtering unit is connected to the timestamp synchronization unit and is configured to receive the time-aligned vehicle motion state parameters, reconstruct the time series of pitch angle data and steering torque parameters based on the dynamic delay model of the communication link, and eliminate the phase offset caused by the difference in signal transmission path. The filtered time series is input into the viscosity dynamic compensation module.

[0028] The data acquisition module achieves timing alignment and signal optimization for multi-source sensor data through a timestamp synchronization unit and a sliding window filter. The timestamp synchronization unit utilizes a dual-source calibration mechanism, combining GPS timing signals with the CAN bus clock signal, to synchronize the raw acquisition timing of the accelerometer, hydraulic oil temperature sensor, and pitch angle sensor across all devices. GPS timing provides a global time reference, while the CAN bus clock corrects for local clock deviations in each sensor. The output of time-aligned vehicle motion parameters, including pitch angle data and steering torque parameters, eliminates data timeline offsets caused by differences in sensor sampling cycles.

[0029] After receiving the aligned data output from the timestamp synchronization unit, the sliding window filter unit uses a sliding window filtering algorithm to reconstruct the time series of pitch angle and steering torque parameters based on the dynamic delay model of the communication link. The dynamic delay model establishes the delay distribution of the signal transmission path based on historical communication delay data and compensates for differences in transmission delay from different sensors to the control unit by interpolating data within the window. The filtered time series eliminates phase offsets, forming a time-consistent data stream. This data stream is then fed into the viscosity dynamic compensation module, providing synchronized pitch angle and steering torque inputs for viscosity correction coefficient calculation.

[0030] In the above process, the timestamp synchronization unit solves the problem of unifying the time base of multi-sensor data, and the sliding window filtering unit addresses timing misalignment caused by differences in signal transmission paths. Together, they ensure the time synchronization and phase consistency of the vehicle motion state parameters output by the data acquisition module, providing the foundation for the precise calculations of the subsequent viscosity dynamic compensation module. This technical solution, through a dual-layer process of timing calibration and signal reconstruction, meets the precision requirements of multi-source heterogeneous data fusion in control systems.

[0031] Specifically, the control instruction generation module of the unmanned tracked vehicle braking system based on adaptive control of the present invention includes: a model prediction control unit configured to receive the viscosity change output by the viscosity dynamic compensation module, predict the nonlinear relationship between the output pressure of the hydraulic pump station and the extension and retraction rate of the pitch cylinder based on a preset viscosity-temperature correspondence table, and generate an advance control instruction including a timing advance amount, the timing advance amount being calculated by a response lag model of the hydraulic actuator; The viscosity correction factor calculation unit is connected to the model prediction control unit and is configured to convert the viscosity change into a temperature-related viscosity correction factor, and input the correction factor into the pitch cylinder target position calculation logic to adjust the trigger timing of the advance control command and generate the final brake control command.

[0032] The control instruction generation module dynamically optimizes the braking control instructions through the collaboration of the model prediction control unit and the viscosity correction factor calculation unit. The model prediction control unit receives the viscosity change output by the viscosity dynamic compensation module and analyzes the nonlinear law of the hydraulic medium viscosity change with temperature based on the preset viscosity-temperature correspondence table. It predicts the dynamic coupling relationship between the hydraulic pump station output pressure and the pitch cylinder extension and contraction rate. The viscosity-temperature correspondence table uses experimental calibration of the viscosity characteristic curve at different temperatures and interpolates real-time oil temperature data to generate a continuous parameter map, which is used to quantify the impact of hydraulic oil viscosity on the actuator response speed. The model prediction control unit generates an advance control instruction based on the prediction results, where the timing advance is calculated using the hydraulic actuator response lag model. This model fits the delay characteristics of the hydraulic system under viscosity changes through historical response data and dynamically corrects the instruction trigger time to offset mechanical lag.

[0033] The viscosity correction factor calculation unit converts viscosity changes into temperature-dependent viscosity correction factors, quantifying the weight of temperature fluctuations on the dynamic characteristics of the hydraulic system. This correction factor maps the relationship between viscosity changes and temperature parameters through linear interpolation or piecewise functions. This correction factor is embedded in the pitch cylinder target position calculation logic to adjust the triggering timing of the lead control command. For example, when viscosity increases in low-temperature environments, the correction factor increases the lead triggering amount to compensate for the delayed effect of increased hydraulic oil flow resistance. After redundancy checking, the adjusted command is generated as the final brake control command, ensuring that the command timing matches the actual responsiveness of the hydraulic actuator.

[0034] In the above process, the model prediction control unit solves the dynamic modeling and command prediction problems of the hydraulic system, while the viscosity correction factor calculation unit solves the dynamic parameter compensation problem. Through data interaction and logical nesting, the two form a closed-loop command generation mechanism. This technical solution, based on the fusion analysis of real-time viscosity changes and historical response data, is used to adaptively correct brake control commands, meeting the accuracy and real-time requirements of unmanned tracked vehicle posture control under complex operating conditions.

[0035] Specifically, the distributed execution module of the unmanned tracked vehicle braking system based on adaptive control of the present invention includes: a priority dispatching unit configured to, when the real-time angle value is higher than a 30° elevation angle threshold, receive a real-time angle value fed back by an elevation angle sensor of a leading vehicle, calculate a difference between the real-time angle value and the 30° elevation angle threshold, generate a dispatch priority parameter for a brake pressure adjustment command for a trailing vehicle based on the difference, and input the dispatch priority parameter into an electronic control unit in a redundant control channel; The parallel processing unit is connected to the priority scheduling unit and is configured to parse and distribute the priority parameters when the difference is within a preset range corresponding to the dynamic balance requirement of the leading vehicle's posture, and synchronously send the brake pressure adjustment instructions of the trailing vehicle and the extension and retraction action timing of the pitch cylinder through the electronic control unit in the redundant control channel, so as to force the timing matching of the hydraulic execution units of the leading and trailing vehicles.

[0036] The distributed execution module achieves timing matching between the hydraulic actuators of the leading and trailing vehicles through a collaborative mechanism between the priority scheduling unit and the parallel processing unit. The priority scheduling unit receives the real-time angle value from the leading vehicle's elevation sensor and calculates the difference between it and the 30° elevation threshold. The absolute value of this difference reflects the severity of the leading vehicle's deviation from equilibrium. This difference calculation utilizes a dynamic weighting algorithm, adjusting the weight coefficient based on the vehicle's motion state parameters to generate the priority parameters for distributing brake pressure adjustment commands to the trailing vehicle. The priority parameters are transmitted to the command queue via the electronic control unit in the redundant control channel, dynamically adjusting the command distribution order to prioritize communication bandwidth and computing resources for critical commands.

[0037] The parallel processing unit monitors the priority parameters in real time and triggers the synchronization logic when the difference falls into the preset range corresponding to the dynamic balance requirements of the leading vehicle's posture. The preset range is set according to the kinematic model of the multi-degree-of-freedom articulated mechanism. For example, when the difference is between 5° and 10°, it is determined to be a critical state requiring forced synchronization. After the synchronization logic analyzes the priority parameters, it sends a timestamp alignment instruction through the electronic control unit in the redundant control channel, forcing the rear vehicle's brake pressure adjustment instruction and the pitch cylinder extension and retraction action to be executed within the same clock cycle. The redundant control channel adopts a dual CAN bus architecture. The main channel transmits the brake pressure adjustment instruction, and the backup channel transmits the pitch cylinder control signal. Millisecond-level timing synchronization is achieved through hardware trigger signals, eliminating execution deviations caused by communication delays or computing resource competition.

[0038] In the above process, the priority scheduling unit solves the problem of dynamically adjusting command dispatch priorities, while the parallel processing unit solves the problem of forced synchronization of multiple actuators. Through hardware-level coordination using differential analysis and redundant channels, these two units ensure strict timing matching of the hydraulic actuators on the front and rear vehicles, avoiding the risk of excessive pitch angles or center of mass shifts caused by timing misalignment. This technical solution, based on a coupled design of dynamic priority allocation and redundant communication, meets the posture control requirements of unmanned tracked vehicles in complex terrain.

[0039] Specifically, the unmanned tracked vehicle braking system based on adaptive control of the present invention further includes: a hydraulic circuit preheating module configured to receive the ambient temperature parameter collected by the data acquisition module and activate a graded heating strategy when the ambient temperature falls below a preset threshold of -35°C; A staged heating strategy includes: In the first stage, heating control is used to reduce the yield stress of the hydraulic oil through the low-power heating unit of the hydraulic pump station and monitor the changes in oil viscosity in real time; In the second stage of circulation control, when the oil yield stress is lower than the preset critical value, the hydraulic pump station is driven to perform no-load circulation to accelerate the recovery of oil fluidity; The hydraulic circuit preheating module feeds back the preheated oil viscosity data to the viscosity dynamic compensation module through the hydraulic oil temperature sensor of the data acquisition module to update the viscosity-temperature correspondence table. Figure 5 As shown in the figure, the structure of the heating unit (such as thermostat) and the oil tank is shown, and the low-power heating unit is integrated here to gradually increase the oil temperature. Figure 6 As shown, the thermostat dynamically adjusts power based on oil temperature sensor data to reduce yield stress. The pump station motor starts and stops intermittently during the no-load cycle to accelerate oil flow. Preheat data feedback forms a closed loop, updating the viscosity map and improving low-temperature robustness.

[0040] The hydraulic circuit preheating module achieves rapid recovery of hydraulic oil fluidity in extremely low-temperature environments through a graded heating strategy. After receiving the ambient temperature parameters collected by the data acquisition module, the hydraulic circuit preheating module triggers the first stage of heating control when the ambient temperature falls below the -35°C threshold. The low-power heating unit gradually heats the hydraulic pump station oil in a stepped power increase mode, controlling the heating rate through pulse width modulation technology to avoid local overheating of the oil and causing sudden changes in viscosity. During the heating process, the hydraulic oil temperature sensor collects real-time oil viscosity change data and dynamically evaluates the progress of oil fluidity recovery in combination with the yield stress calculation model. When the yield stress drops to the preset critical value, the control switches to the second stage.

[0041] In the second stage, circulation control drives the hydraulic pump station to perform a no-load cycle. The pump station motor starts and stops intermittently at a preset duty cycle, forcing the oil to circulate at a low speed within the circuit. A closed-loop flow monitoring mechanism is employed during the no-load cycle. The pump station speed is adjusted based on feedback from the flow sensor to align the oil flow rate with the decreasing viscosity trend, accelerating the uniform distribution of oil temperature and the recovery of fluidity. After preheating, the oil viscosity data is transmitted to the viscosity dynamic compensation module via the hydraulic oil temperature sensor, triggering a dynamic update of the viscosity-temperature correspondence table. This table interpolates and corrects the original calibration curve based on the measured viscosity value after preheating, compensating for mapping deviations caused by oil aging or batch differences, thus forming a closed-loop parameter calibration mechanism.

[0042] This process addresses actuator response lag caused by excessive hydraulic oil viscosity in extremely low-temperature environments by synergizing staged heating with cyclic control. The data interaction between the preheating module and the dynamic viscosity compensation module enables adaptive correction of hydraulic fluid characteristic parameters, enhancing the control robustness of the braking system over a wide temperature range.

[0043] Specifically, the hydraulic circuit preheating module of the unmanned tracked vehicle braking system based on adaptive control of the present invention includes: a viscosity adaptive heating unit configured to receive real-time oil temperature data collected by a hydraulic oil temperature sensor, generate a target viscosity curve based on a preset viscosity-temperature correspondence table, generate a gradient heating parameter based on the difference between the target viscosity curve and the real-time oil temperature data, and drive the low-power heating unit to adjust the heating power to reduce the yield stress of the oil; The cold start response unit is connected to the viscosity adaptive heating unit and is configured to receive the preheated oil viscosity data before the braking command is triggered, adjust the oil viscosity to the preset threshold value corresponding to the graded heating strategy in the target viscosity curve, trigger the hydraulic pump station no-load cycle to accelerate the recovery of oil fluidity, and shorten the low-temperature cold start response cycle.

[0044] The hydraulic circuit preheating module optimizes oil viscosity in low-temperature environments through the coordinated control of a viscosity-adaptive heating unit and a cold-start response unit. The viscosity-adaptive heating unit receives real-time oil temperature data from the hydraulic oil temperature sensor and generates a target viscosity curve based on a preset viscosity-temperature relationship table. This target viscosity curve uses a piecewise linear interpolation algorithm to convert experimentally calibrated discrete viscosity-temperature data into a continuous function, reflecting the theoretical viscosity of the hydraulic oil at different temperatures. The difference between the real-time oil temperature data and the target viscosity curve is processed using a proportional-integral algorithm to generate a gradient heating parameter. This parameter drives the low-power heating unit to gradually increase heating power in a stepped power regulation mode, reducing the oil's yield stress to the flowable threshold.

[0045] The cold start response unit receives preheated oil viscosity data before the brake command is triggered. Using a viscosity feedback closed-loop control mechanism, it adjusts the oil viscosity to the preset threshold in the target viscosity curve corresponding to the graded heating strategy. This threshold is set based on the minimum viscosity requirement for the hydraulic pump station's no-load cycle. When the viscosity reaches the threshold, the hydraulic pump station is triggered to perform intermittent no-load cycles. The no-load cycle uses pulse-width modulation technology to control the start and stop cycles of the pump station's motor, forcing the oil to flow at a low speed within the circuit, accelerating uniform temperature distribution and fluidity recovery. Preheated viscosity data is fed back in real time to the viscosity dynamic compensation module via the hydraulic oil temperature sensor, which dynamically updates the viscosity-temperature correspondence table to correct parameter deviations caused by oil aging or environmental fluctuations.

[0046] In the above process, the viscosity adaptive heating unit addresses the dynamic tracking and heating control of low-temperature oil viscosity, while the cold start response unit addresses viscosity threshold matching and fluidity recovery. These two elements collaborate through the timing of gradient heating parameter generation, closed-loop viscosity adjustment, and pump station no-load cycling to shorten the hydraulic system's cold start response cycle and ensure that the hydraulic actuator achieves the preset response capability before the brake command is triggered. This technical solution, based on a coupled design of dynamic viscosity parameter correction and actuator preheating, improves the control reliability of unmanned tracked vehicles in extremely low-temperature environments.

[0047] See also Figure 1 In a second aspect, the present invention provides an unmanned tracked vehicle braking method based on adaptive control, which is applied to any unmanned tracked vehicle braking system based on adaptive control, comprising: S101, collecting vehicle motion state parameters, pitch angle data, and real-time oil temperature data through an accelerometer, a pitch angle sensor, and a hydraulic oil temperature sensor; S102, generating a hydraulic medium viscosity correction coefficient based on the real-time oil temperature data and a preset viscosity-temperature correspondence table, and calculating a viscosity change; S103, fusing the pitch angle data with the steering torque parameter of the multi-degree-of-freedom articulated mechanism, combining the viscosity change and the hydraulic actuator response hysteresis model, and generating a braking control instruction including a time-series advance amount; S104: Analyze the brake control instructions and dynamically distribute them to the hydraulic actuator units of the front and rear vehicles through the electronic control unit of the redundant control channel. When the real-time angle value is higher than the 30° elevation angle threshold, generate and prioritize the brake pressure adjustment instructions for the rear vehicle based on the difference between the real-time angle value and the 30° elevation angle threshold, and synchronously adjust the extension and retraction timing of the pitch cylinder and the steering damping lock cylinder.

[0048] The adaptive control-based unmanned tracked vehicle braking method provided by the present invention achieves precise braking under complex working conditions through multi-step closed-loop control. During the data acquisition phase, the vehicle's motion state parameters, pitch angle data, and real-time oil temperature data are synchronously acquired through an accelerometer, a pitch angle sensor, and a hydraulic oil temperature sensor. The timestamp synchronization unit uses GPS timing and a CAN bus clock to calibrate the acquisition timing of each sensor and output time-aligned vehicle motion state parameters; the sliding window filter unit reconstructs the timing sequence of pitch angle and steering torque parameters based on the dynamic delay model of the communication link, eliminating the phase offset caused by differences in signal transmission paths and providing consistent data input for subsequent processing.

[0049] During the dynamic viscosity compensation phase, a preset viscosity-temperature correspondence table is queried based on real-time oil temperature data to generate a hydraulic medium viscosity correction factor and calculate the viscosity change. This table is based on experimentally calibrated viscosity characteristic curves at different temperatures. A piecewise linear interpolation algorithm is used to construct a continuous mapping relationship. The difference between the real-time oil temperature data and the calibration curve is weighted to calculate the viscosity change, quantifying the dynamic characteristics of hydraulic oil viscosity fluctuations with temperature.

[0050] The control command generation stage integrates pitch angle data, steering torque parameters, and viscosity change, and combines this with a hydraulic actuator response lag model to generate a braking control command that includes a timing advance. The model prediction control unit uses a viscosity-temperature mapping table to predict the nonlinear relationship between the hydraulic pump station's output pressure and the pitch cylinder's extension and retraction rate, generating a lead control command. The viscosity correction factor calculation unit converts the viscosity change into a temperature-dependent correction factor, embeds it into the pitch cylinder's target position calculation logic, and adjusts the command trigger timing to compensate for the hydraulic system's response lag, ultimately generating the final braking control command.

[0051] During the command execution phase, the electronic control unit (ECU) in the redundant control channel analyzes and dynamically distributes commands. The priority scheduling unit generates priority parameters for the rear vehicle's brake pressure adjustment commands based on the difference between the real-time angle feedback from the front vehicle's pitch sensor and the 30° pitch angle threshold. When the difference reaches a preset range, the parallel processing unit synchronizes the rear vehicle's brake command and the pitch cylinder extension and retraction timing via the redundant control channel of the dual CAN bus architecture, forcing the front and rear vehicle hydraulic actuators to complete their actions within the same clock cycle, thus preventing posture imbalance caused by timing deviations.

[0052] This approach, through the coordinated integration of synchronous data acquisition, dynamic viscosity compensation, command timing optimization, and redundant execution control, forms a closed-loop adaptive adjustment mechanism to address the issue of braking torque control deviation in multi-degree-of-freedom articulated vehicles under low temperatures or dynamic loads. This technical solution, based on the fusion of real-time parameter feedback and historical model analysis, enables dynamic correction and robust control of the braking system.

[0053] The specific implementation of the present invention is as follows: The data acquisition module uses an accelerometer, a pitch angle sensor, and a hydraulic oil temperature sensor to collect vehicle motion state parameters, pitch angle data, and oil temperature data in real time. The timestamp synchronization unit uses GPS timing and the CAN bus clock to calibrate the multi-sensor acquisition timing, eliminating timing deviations caused by transmission path differences. The sliding window filtering unit reconstructs the timing sequence of pitch angle and steering torque parameters based on a dynamic delay model of the communication link, and outputs phase-aligned filtered data to the viscosity dynamic compensation module. The viscosity dynamic compensation module queries a preset viscosity-temperature correspondence table based on real-time oil temperature data, generates a hydraulic medium viscosity correction coefficient, and calculates the viscosity change. The correspondence table is experimentally calibrated using viscosity characteristic curves at different temperatures, and combined with an interpolation algorithm to construct a continuous mapping relationship. The viscosity change is used to quantify the dynamic impact of oil viscosity fluctuations with temperature. The control command generation module's model prediction control unit predicts the nonlinear relationship between the hydraulic pump station's output pressure and the pitch cylinder's extension and retraction rate based on a viscosity-temperature correspondence table, generating advance control commands that include a timing advance. The viscosity correction factor calculation unit converts the viscosity change into a temperature-dependent correction factor, embedding it into the pitch cylinder's target position calculation logic. This adjusts the command trigger timing to compensate for the hydraulic system's response lag, ultimately generating the final brake control command. The distributed execution module parses and distributes commands via the electronic control units of redundant control channels. The priority scheduling unit dynamically adjusts the priority of the rear vehicle's brake pressure command based on the difference between the real-time angle feedback from the lead vehicle's elevation sensor and the 30° elevation threshold. The parallel processing unit forcibly synchronizes the rear vehicle's brake command with the pitch cylinder's extension and retraction timing when the difference reaches a preset range. A dual CAN bus architecture is used to achieve millisecond-level hardware synchronization to prevent attitude imbalance. The hydraulic circuit preheating module activates a graded heating strategy when the ambient temperature falls below -35°C. The low-power heating unit reduces the oil's yield stress through stepped power regulation. Once the yield stress falls below a preset threshold, the pump station triggers an unloaded cycle to accelerate fluidity recovery. Preheated viscosity data is fed back to the dynamic viscosity compensation module via a hydraulic oil temperature sensor, which dynamically updates the viscosity-temperature mapping table. This implementation addresses the issue of braking torque control deviation in multi-degree-of-freedom articulated mechanisms caused by nonlinear changes in hydraulic medium viscosity in complex terrain through the coordinated integration of timing synchronization, closed-loop viscosity correction, command prediction optimization, and low-temperature preheating control.

[0054] The technical solution of the present invention solves the problem of braking torque deviation caused by nonlinear changes in hydraulic medium viscosity in multi-degree-of-freedom articulated mechanisms through a multi-module collaborative control mechanism. The specific technical path is as follows: The data acquisition module synchronously acquires the vehicle's motion status, pitch angle, and real-time oil temperature data through the accelerometer, pitch angle sensor, and hydraulic oil temperature sensor. The timestamp synchronization unit uses GPS timing and CAN bus clock to calibrate the timing of each sensor to eliminate phase offsets caused by differences in signal transmission paths. Figure 2As shown, the steering damper lock cylinder, pitch cylinder, and torsion mechanism in the articulated mechanism are the direct targets for data acquisition. Sensors (such as a pitch angle sensor) can be integrated at these locations to monitor the cylinder extension and retraction status and mechanism posture in real time, providing basic input for the viscosity dynamic compensation module. The viscosity dynamic compensation module queries a preset viscosity-temperature mapping table based on real-time oil temperature data to generate a hydraulic medium viscosity correction factor. This correction factor is used to adjust the timing of subsequent control commands. A sliding window filter reconstructs the timing sequence and inputs it into the viscosity dynamic compensation module. Based on the preset viscosity-temperature mapping table, the viscosity dynamic compensation module analyzes the nonlinear mapping between oil temperature and viscosity, generates a viscosity correction factor, and calculates the viscosity change, thereby correcting in real time the impact of sudden changes in hydraulic oil viscosity on actuator response. The viscosity-temperature mapping table is constructed through experimental calibration and an interpolation algorithm. A dynamic update mechanism, combined with feedback data from the preheating module, further calibrates the parameter mapping accuracy.

[0055] The control command generation module integrates pitch angle, steering torque parameters, and viscosity change, and combines this with the hydraulic actuator response lag model to generate braking control commands that include timing advances. The model prediction control unit predicts the dynamic relationship between the hydraulic pump station's output pressure and the cylinder's extension and retraction rate based on a viscosity-temperature correspondence table, generating advance control commands. The viscosity correction factor calculation unit converts the viscosity change into a temperature-dependent correction factor, adjusting the command trigger timing to compensate for the mechanical delay caused by increased viscosity. The distributed execution module dynamically allocates commands through redundant control channels. The priority scheduling unit adjusts the priority of the rear vehicle's braking commands based on the difference between the lead vehicle's pitch angle and the 30° threshold. The parallel processing unit forcibly synchronizes the action timing of the front and rear vehicle actuators, eliminating the risk of pitch imbalance caused by hydraulic response lag.

[0056] The hydraulic circuit preheating module activates a staged heating strategy when the ambient temperature falls below -35°C. The first stage uses low-power heating to reduce the hydraulic oil's yield stress, while the second stage drives the pump station to cycle unloaded to accelerate fluidity recovery. The viscosity-adaptive heating unit generates gradient heating parameters based on the real-time oil temperature and target viscosity curve. The cold-start response unit adjusts the oil viscosity to a preset threshold before the brake command is triggered, ensuring the hydraulic system meets required response requirements. This post-preheat viscosity data is fed back to the dynamic viscosity compensation module, forming a closed-loop parameter correction chain to improve control stability in extremely low-temperature conditions.

[0057] The above technical solution realizes adaptive compensation of nonlinear changes in hydraulic medium viscosity through the coordination of synchronous data acquisition, dynamic viscosity correction, instruction timing optimization and low-temperature preheating control, and solves the problem of braking torque control deviation of multi-degree-of-freedom articulated mechanisms in complex terrain.

Claims

1. The unmanned tracked vehicle braking system based on adaptive control is characterized by: include: A data acquisition module configured to collect vehicle motion state parameters, pitch angle data, and real-time oil temperature data through an accelerometer, a pitch angle sensor, and a hydraulic oil temperature sensor; a viscosity dynamic compensation module, which is in communication with the data acquisition module and is configured to generate a hydraulic medium viscosity correction coefficient based on real-time oil temperature data and calculate a viscosity change based on a preset viscosity-temperature correspondence table; a control command generation module, which interacts with the viscosity dynamic compensation module and is configured to receive a viscosity correction coefficient, fuse pitch angle data with steering torque parameters of the multi-degree-of-freedom articulated mechanism, and generate a brake control command including a timing advance, where the timing advance is calculated by combining the viscosity change and a hydraulic actuator response hysteresis model; A distributed execution module, connected to the control command generation module, is configured to parse brake control commands and dynamically distribute them to the front and rear vehicle hydraulic execution units via the electronic control units in the redundant control channels, thereby synchronously adjusting the extension and retraction timing of the pitch cylinder and the steering damper lock cylinder; Among them, when the real-time angle value is greater than the preset 30° elevation angle threshold, the distributed execution module generates and prioritizes the brake pressure adjustment instruction of the rear vehicle based on the difference between the real-time angle value and the 30° elevation angle threshold to match the dynamic balance requirements of the front vehicle posture.

2. The unmanned tracked vehicle braking system based on adaptive control according to claim 1, characterized in that: The data acquisition module includes: A timestamp synchronization unit is configured to calibrate the acquisition timing of the accelerometer, hydraulic oil temperature sensor, and pitch angle sensor through GPS timing and CAN bus clock, and output time-aligned vehicle motion state parameters, including pitch angle data and steering torque parameters; The sliding window filtering unit is connected to the timestamp synchronization unit and is configured to receive the time-aligned vehicle motion state parameters, reconstruct the time series of pitch angle data and steering torque parameters based on the dynamic delay model of the communication link, and eliminate the phase offset caused by the difference in signal transmission path. The filtered time series is input into the viscosity dynamic compensation module.

3. The unmanned tracked vehicle braking system based on adaptive control according to claim 2, characterized in that: The control instruction generation module includes: a model prediction control unit configured to receive the viscosity change output by the viscosity dynamic compensation module, predict the nonlinear relationship between the output pressure of the hydraulic pump station and the extension and retraction rate of the pitch cylinder based on a preset viscosity-temperature correspondence table, and generate an advance control instruction including a timing advance amount, the timing advance amount being calculated by a response lag model of the hydraulic actuator; The viscosity correction factor calculation unit is connected to the model prediction control unit and is configured to convert the viscosity change into a temperature-related viscosity correction factor, and input the correction factor into the pitch cylinder target position calculation logic to adjust the trigger timing of the advance control command and generate the final brake control command.

4. The unmanned tracked vehicle braking system based on adaptive control according to claim 3, characterized in that: The distributed execution module includes: a priority dispatching unit configured to, when the real-time angle value is higher than a 30° elevation angle threshold, receive a real-time angle value fed back by an elevation angle sensor of a leading vehicle, calculate a difference between the real-time angle value and the 30° elevation angle threshold, generate a dispatch priority parameter for a brake pressure adjustment command for a trailing vehicle based on the difference, and input the dispatch priority parameter into an electronic control unit in a redundant control channel; The parallel processing unit is connected to the priority scheduling unit and is configured to parse and distribute the priority parameters when the difference is within a preset range corresponding to the dynamic balance requirement of the leading vehicle's posture, and synchronously send the brake pressure adjustment instructions of the trailing vehicle and the extension and retraction action timing of the pitch cylinder through the electronic control unit in the redundant control channel, so as to force the timing matching of the hydraulic execution units of the leading and trailing vehicles.

5. The unmanned tracked vehicle braking system based on adaptive control according to claim 4, characterized in that: Also includes: a hydraulic circuit preheating module configured to receive the ambient temperature parameter collected by the data acquisition module and activate a graded heating strategy when the ambient temperature falls below a preset threshold of -35°C; A staged heating strategy includes: In the first stage, heating control is used to reduce the yield stress of the hydraulic oil through the low-power heating unit of the hydraulic pump station and monitor the changes in oil viscosity in real time; In the second stage of circulation control, when the oil yield stress is lower than the preset critical value, the hydraulic pump station is driven to perform no-load circulation to accelerate the recovery of oil fluidity; The hydraulic circuit preheating module feeds back the preheated oil viscosity data to the viscosity dynamic compensation module through the hydraulic oil temperature sensor of the data acquisition module for updating the viscosity-temperature correspondence table.

6. The unmanned tracked vehicle braking system based on adaptive control according to claim 5, characterized in that: The hydraulic circuit preheating module includes: a viscosity adaptive heating unit configured to receive real-time oil temperature data collected by a hydraulic oil temperature sensor, generate a target viscosity curve based on a preset viscosity-temperature correspondence table, generate a gradient heating parameter based on the difference between the target viscosity curve and the real-time oil temperature data, and drive the low-power heating unit to adjust the heating power to reduce the yield stress of the oil; The cold start response unit is connected to the viscosity adaptive heating unit and is configured to receive the preheated oil viscosity data before the braking command is triggered, adjust the oil viscosity to the preset threshold value corresponding to the graded heating strategy in the target viscosity curve, trigger the hydraulic pump station no-load cycle to accelerate the recovery of oil fluidity, and shorten the low-temperature cold start response cycle.

7. An unmanned tracked vehicle braking method based on adaptive control, applied to an unmanned tracked vehicle braking system based on adaptive control as claimed in any one of claims 1 to 6, characterized in that: include: The vehicle motion state parameters, pitch angle data and real-time oil temperature data are collected through the accelerometer, pitch angle sensor and hydraulic oil temperature sensor; According to the real-time oil temperature data, the hydraulic medium viscosity correction coefficient is generated based on the preset viscosity-temperature correspondence table, and the viscosity change is calculated; The pitch angle data is integrated with the steering torque parameters of the multi-degree-of-freedom articulated mechanism, combined with the viscosity change and the hydraulic actuator response hysteresis model to generate a braking control command including the timing advance amount; The brake control command is parsed and dynamically distributed to the hydraulic actuator units of the front and rear vehicles through the electronic control unit of the redundant control channel. When the real-time angle value is higher than the 30° elevation angle threshold, the brake pressure adjustment command of the rear vehicle is generated and prioritized based on the difference between the real-time angle value and the 30° elevation angle threshold, and the extension and retraction timing of the pitch cylinder and the steering damping lock cylinder are synchronously adjusted.

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