An electronic hydraulic braking system for special unmanned tracked vehicles

Abstract

The present invention relates to the field of dynamic regulation and synchronization technology for vehicle motion control systems, and in particular to an electronic hydraulic braking system for special unmanned tracked vehicles, comprising a data acquisition module, a data fusion module, a dynamic decoupling control module, a hydraulic execution module, a redundant control module, and a bus communication module. The data acquisition module collects the vehicle's attitude angle, track slip rate, and hydraulic chamber pressure data in real time; the data fusion module generates a six-degree-of-freedom motion state vector through timestamp synchronization and Kalman filter error correction; the dynamic decoupling control module uses a model predictive control algorithm based on a mechanical and hydraulic coupling model to solve independent control instructions for pitch, steering, and torsion. The present invention implements multi-degree-of-freedom dynamic decoupling control through multi-source data fusion and a rolling optimization framework, suppresses mechanical and hydraulic interaction coupling interference, improves attitude tracking accuracy and brake distribution efficiency, and enhances system fault tolerance and motion stability under complex working conditions.

Description

Technical Field

[0001] The present invention relates to the technical field of dynamic regulation and synchronization of vehicle motion control systems, and in particular to an electronic hydraulic braking system for a special unmanned tracked vehicle. Background Art

[0002] The electronic hydraulic braking system for specialized unmanned tracked vehicles achieves dynamic braking control by integrating an electronic control unit (ECU) with a multimodal sensor network. The system utilizes a distributed topology. The ECU receives real-time signals from the inertial navigation unit, wheel speed sensors, and pressure sensors, and combines road surface recognition algorithms with vehicle dynamics models to generate control commands for the hydraulic actuators. A proportional solenoid valve group is deployed in the hydraulic circuit, precisely regulating the brake chamber pressure gradient via pulse-width modulation (PWM) signals to achieve linear distribution of braking torque. The system also incorporates a built-in fault prediction module that uses a Kalman filter algorithm to estimate the hydraulic oil temperature and valve response delay, triggering redundant braking strategies to maintain fail-safe mode. This architecture collaborates with the vehicle control system via a bus communication protocol, supporting adaptive terrain matching and autonomous braking decisions, effectively improving motion stability and energy recovery efficiency under complex operating conditions.

[0003] The technical pain point of the electronic hydraulic braking system for special unmanned tracked vehicles lies in the dynamic decoupling control under multi-degree-of-freedom motion coupling. Specifically, the real-time coordinated control of the pitch, steering, and torsion mechanisms leads to command conflicts due to the differences in the dynamic characteristics of the mechanical and hydraulic systems. For example, in an obstacle crossing scenario, when the leading vehicle is raised, the pitch cylinder thrust needs to be dynamically matched with the hydraulic damping of the steering damping lock mechanism. If the dynamic coupling relationship between the degrees of freedom is not solved in real time through the closed-loop control algorithm, the pitch cylinder thrust and the steering damping force will interfere with each other, causing the pitch angle to overshoot or the steering lock to fail, which in turn causes a sudden change in stress in the articulated mechanism or a surge in the slip rate of the contact surface between the track and the obstacle. Summary of the Invention

[0004] In view of the shortcomings of the existing technology, the present invention provides an electronic hydraulic braking system for a special unmanned tracked vehicle. The present invention solves the problem of dynamic decoupling control under multi-degree-of-freedom motion coupling based on a model predictive control algorithm.

[0005] In order to solve the above technical problems, the specific technical solutions of the present invention are as follows:

[0006] The electronic hydraulic braking system for a special unmanned tracked vehicle provided by the present invention comprises:

[0007] The data acquisition module collects the vehicle's attitude angle, track slip rate, and hydraulic chamber pressure data in real time. The data fusion module receives the vehicle's attitude angle, track slip rate, and hydraulic chamber pressure data, and generates a six-degree-of-freedom motion state vector through timestamp synchronization and Kalman filter error correction.

[0008] The dynamic decoupling control module inputs the six-degree-of-freedom motion state vector and the target attitude angle from the bus communication module into the preset model predictive control algorithm, and solves the independent control commands of pitch, turn and twist through the rolling optimization framework;

[0009] The hydraulic actuator module receives independent control commands and generates proportional valve duty cycle signals to adjust the hydraulic pressure gradients of the pitch cylinder and steering damping lock cylinder to distribute the braking torque;

[0010] Redundant control module detects the oil pressure sensor residual and valve body response delay of the hydraulic actuator module, and switches to the historical optimal control sequence or open-loop PID control in abnormal conditions;

[0011] The bus communication module receives the path planning instructions from the vehicle control system and transmits them to the dynamic decoupling control module, triggering the emergency braking pressure distribution of the hydraulic execution module in the event of sudden obstacles.

[0012] Furthermore, the electronic hydraulic braking system for a special unmanned tracked vehicle of the present invention includes a data acquisition module comprising: an inertial navigation unit, which receives a request for attitude angle acquisition, and based on the request, calculates the three-dimensional acceleration and angular velocity of the vehicle using quaternions to generate pitch angle, roll angle, and heading angle, and transmits the generated pitch angle, roll angle, and heading angle to the data fusion module;

[0013] The wheel speed sensor receives the track slip rate calculation request, monitors the track speed and calculates the actual slip rate based on the track circumference, and outputs it to the data fusion module;

[0014] The pressure sensor group is integrated into the pitch cylinder, steering damping lock cylinder and main hydraulic circuit respectively, measuring the hydraulic chamber pressure value in real time and feeding it back to the data fusion module.

[0015] Furthermore, the electronic hydraulic braking system for a special unmanned tracked vehicle of the present invention includes a data fusion module:

[0016] The timestamp alignment unit triggers multi-sensor synchronous sampling through hardware interrupts, receiving the pitch, roll, and heading angles generated by the inertial navigation unit in the data acquisition module, the actual slip rate calculated by the wheel speed sensor, and the hydraulic chamber pressure value fed back by the pressure sensor group;

[0017] The Kalman filter unit fuses the synchronized pitch angle, roll angle, and heading angle with the actual slip rate, corrects the estimated error of the attitude angle, generates a six-degree-of-freedom motion state vector, and outputs it to the dynamic decoupling control module.

[0018] Furthermore, the dynamic decoupling control module of the electronic hydraulic braking system for a special unmanned tracked vehicle of the present invention includes: a mechanical and hydraulic coupling modeling unit, which constructs the geometric parameters of the articulated mechanism including the pitch cylinder and the steering damping lock cylinder, and the dynamic equations of the proportional valve flow and pressure characteristic curve based on the mechanical and hydraulic coupling model;

[0019] The parameter identification unit receives the six-degree-of-freedom motion state vector from the data fusion module, updates the hydraulic oil elastic modulus and valve body flow coefficient online through the recursive least squares method, and outputs the updated parameters to the cost function construction unit of the rolling optimization framework for optimization target calculation.

[0020] Furthermore, the electronic hydraulic braking system for a special unmanned tracked vehicle of the present invention includes a rolling optimization framework comprising:

[0021] The prediction time domain division unit sets a multi-step prediction window according to the response delay of the hydraulic actuator module;

[0022] The cost function construction unit receives the six-degree-of-freedom motion state vector generated by the data fusion module and the target attitude angle deviation of the dynamic decoupling control module, and weights the attitude angle tracking error and the energy consumption index of the hydraulic execution module to form an optimization target;

[0023] The Lagrange multiplier solving unit decomposes the dynamic equations of the mechanical and hydraulic coupling modeling unit, solves the independent control instructions of pitch, steering and torsion according to the optimization objectives, and outputs them to the hydraulic execution module.

[0024] Furthermore, the electronic hydraulic braking system for a special unmanned tracked vehicle of the present invention includes a redundant control module comprising:

[0025] A fault detection unit identifies abnormal oil temperature or valve sticking based on the residual error between the real-time measurement value of the hydraulic actuator module's oil pressure sensor and the Kalman filter prediction value, as well as the valve response delay threshold;

[0026] The strategy switching unit calls the historical optimal control sequence of the dynamic decoupling control module under abnormal conditions, or switches to the preset open-loop PID control instructions and outputs them to the hydraulic execution module to maintain the basic brake pressure distribution.

[0027] Furthermore, the electronic hydraulic braking system for a special unmanned tracked vehicle of the present invention includes a bus communication module comprising:

[0028] The CAN protocol interaction unit receives the global path planning instructions from the vehicle control system through the J1939 protocol, interprets them into the target attitude angle of the dynamic decoupling control module, and transmits them to the dynamic decoupling control module;

[0029] The event trigger unit identifies the obstacle height exceeding the limit based on the six-degree-of-freedom motion state vector of the data fusion module in the sudden obstacle scenario, sends an emergency brake pressure distribution instruction to the hydraulic execution module to adjust the proportional valve duty cycle signal, and sends an attitude angle lock request to the dynamic decoupling control module to fix the current pitch angle and steering angle.

[0030] Beneficial effects of the present invention:

[0031] The beneficial effect of the present invention is that it realizes dynamic decoupling and high-precision braking distribution of multi-degree-of-freedom motion coupling through the collaborative mechanism of multi-source sensor data fusion and mechanical and hydraulic coupling model predictive control. The data fusion module generates a six-degree-of-freedom motion state vector based on timestamp synchronization and Kalman filter correction, eliminates the time domain deviation of multiple sensors, and improves the estimation accuracy of the vehicle attitude angle, slip rate and hydraulic pressure state; the dynamic decoupling control module solves the independent control instructions of pitch, steering and torsion through the rolling optimization framework, suppresses the motion interference caused by the mechanical and hydraulic interaction coupling, and optimizes attitude tracking and energy consumption balance; the redundant control module maintains the basic braking function when the hydraulic subsystem is abnormal based on the oil pressure residual detection and historical optimal sequence switching mechanism, thereby improving the fault tolerance of the system; the bus communication module realizes the coordinated response of emergency braking and attitude locking through the event trigger mechanism, and enhances the control robustness under complex working conditions. Each module forms a complete control link of multi-degree-of-freedom dynamic decoupling through timing synchronization and closed-loop feedback, effectively improving the motion stability and energy utilization efficiency of the special unmanned tracked vehicle in obstacle crossing, steering and emergency scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] 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.

[0033] Figure 1 A system architecture diagram of an electronic hydraulic braking system for a special unmanned tracked vehicle provided in an embodiment of the present invention.

[0034] Figure 2 This is a schematic diagram of the articulated mechanism provided in an embodiment of the present invention.

[0035] Figure 3 A schematic diagram of a vehicle posture provided by an embodiment of the present invention.

[0036] Figure 4This is a schematic diagram of the pitch hydraulic system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0037] 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.

[0038] See also Figure 1 The electronic hydraulic braking system for a special unmanned tracked vehicle provided by the present invention comprises:

[0039] The data acquisition module collects the vehicle's attitude angle, track slip rate, and hydraulic chamber pressure data in real time. The data fusion module receives the vehicle's attitude angle, track slip rate, and hydraulic chamber pressure data, and generates a six-degree-of-freedom motion state vector through timestamp synchronization and Kalman filter error correction.

[0040] The dynamic decoupling control module inputs the six-degree-of-freedom motion state vector and the target attitude angle from the bus communication module into the preset model predictive control algorithm, and solves the independent control commands of pitch, turn and twist through the rolling optimization framework;

[0041] The hydraulic actuator module receives independent control commands and generates proportional valve duty cycle signals to adjust the hydraulic pressure gradients of the pitch cylinder and steering damping lock cylinder to distribute the braking torque;

[0042] Redundant control module detects the oil pressure sensor residual and valve body response delay of the hydraulic actuator module, and switches to the historical optimal control sequence or open-loop PID control in abnormal conditions;

[0043] The bus communication module receives the path planning instructions from the vehicle control system and transmits them to the dynamic decoupling control module, triggering the emergency braking pressure distribution of the hydraulic execution module in the event of sudden obstacles.

[0044] The electronic hydraulic braking system for special unmanned tracked vehicles provided by the present invention realizes multi-degree-of-freedom dynamic decoupling control through the collaboration of multiple modules. The data acquisition module collects the vehicle's three-dimensional acceleration and angular velocity data in real time through the inertial navigation unit, and generates the pitch angle, roll angle and heading angle by combining quaternion solution. At the same time, the track speed is monitored through the wheel speed sensor and the actual slip rate is calculated in combination with the track circumference. The pressure sensor group is integrated into the pitch cylinder, steering damping lock cylinder and main hydraulic circuit to measure the hydraulic chamber pressure value in real time. The data fusion module triggers multi-sensor synchronous sampling through hardware interrupts, uses the timestamp alignment unit to eliminate time domain deviations, and fuses the inertial navigation data and wheel speed data through the Kalman filter to correct the attitude angle estimation error and generate a six-degree-of-freedom motion state vector including position, velocity, acceleration and angle.

[0045] The dynamic decoupling control module, based on the mechanical and hydraulic coupling model, constructs dynamic equations that include the geometric parameters of the articulated mechanism and the flow and pressure characteristic curves of the proportional valve. The six-degree-of-freedom motion state vector generated by the data fusion module and the target attitude angle deviation received by the bus communication module are input into the model predictive control algorithm. A rolling optimization framework is used to divide the prediction and control time domains, and a weighted cost function is designed that accounts for attitude angle tracking error and hydraulic energy consumption. The multi-degree-of-freedom coupling model is then decomposed into independent subproblems using the Lagrange multiplier method to solve independent control commands for pitch, steering, and twist.

[0046] The hydraulic actuator module generates a proportional valve duty cycle signal based on the independent control instructions output by the dynamic decoupling control module, adjusts the nonlinear area control quantity in combination with the valve body dead zone compensation table, dynamically adjusts the gear pump motor speed through the PID algorithm, and drives the hydraulic pressure gradient of the pitch cylinder and the steering damping lock cylinder to distribute the braking torque. The redundant control module monitors the hydraulic pressure sensor residual and valve body response delay of the hydraulic actuator module in real time. When abnormal oil temperature or valve body jamming is detected, it switches to the historical optimal control sequence or preset open-loop PID control instruction to maintain the basic brake pressure distribution. Figure 2 As shown, the articulated mechanism consists of an articulated bracket, a pitch cylinder, a steering damping lock cylinder, a torsion mechanism, and a connecting shaft for the trailing vehicle. The pitch cylinder drives the leading vehicle's pitch by telescoping, while the steering damping lock cylinder provides steering cushioning through horizontal swing. The hydraulic actuator module, receiving commands from the dynamic decoupling control module, precisely controls the hydraulic pressure gradients in the pitch and steering damping lock cylinders by adjusting the proportional valve duty cycle signals, thereby distributing the braking torque.

[0047] The bus communication module receives global path planning instructions from the vehicle control system via the CAN protocol interaction unit, interprets them as target attitude angles, and transmits them to the dynamic decoupling control module. In unexpected obstacle scenarios, the event triggering unit identifies excessive obstacle height based on the six-degree-of-freedom motion state vector from the data fusion module. It then sends an emergency brake pressure distribution command to the hydraulic actuator module to adjust the proportional valve duty cycle signal. Simultaneously, it sends an attitude angle lock request to the dynamic decoupling control module, fixing the current pitch and steering angles, achieving coordinated control of braking and attitude adjustment.

[0048] Specifically, the electronic hydraulic braking system for a special unmanned tracked vehicle of the present invention includes a data acquisition module comprising: an inertial navigation unit, which receives a request for attitude angle acquisition, and based on the request, calculates the vehicle's three-dimensional acceleration and angular velocity using quaternions to generate pitch angle, roll angle, and heading angle, and transmits the generated pitch angle, roll angle, and heading angle to a data fusion module;

[0049] The wheel speed sensor receives the track slip rate calculation request, monitors the track speed and calculates the actual slip rate based on the track circumference, and outputs it to the data fusion module;

[0050] The pressure sensor group is integrated into the pitch cylinder, steering damping lock cylinder and main hydraulic circuit respectively, measuring the hydraulic chamber pressure value in real time and feeding it back to the data fusion module.

[0051] The electronic hydraulic braking system for special unmanned tracked vehicles provided by the present invention realizes multi-degree-of-freedom dynamic decoupling control through the collaboration of multiple modules. The data acquisition module collects the vehicle's three-dimensional acceleration and angular velocity data in real time through the inertial navigation unit, and generates the pitch angle, roll angle and heading angle by combining quaternion solution. At the same time, the track speed is monitored through the wheel speed sensor and the actual slip rate is calculated in combination with the track circumference. The pressure sensor group is integrated into the pitch cylinder, steering damping lock cylinder and main hydraulic circuit to measure the hydraulic chamber pressure value in real time. The data fusion module triggers multi-sensor synchronous sampling through hardware interrupts, uses the timestamp alignment unit to eliminate time domain deviations, and fuses the inertial navigation data and wheel speed data through the Kalman filter to correct the attitude angle estimation error and generate a six-degree-of-freedom motion state vector including position, velocity, acceleration and angle.

[0052] The dynamic decoupling control module, based on the mechanical and hydraulic coupling model, constructs dynamic equations that include the geometric parameters of the articulated mechanism and the flow and pressure characteristic curves of the proportional valve. The six-degree-of-freedom motion state vector generated by the data fusion module and the target attitude angle deviation received by the bus communication module are input into the model predictive control algorithm. A rolling optimization framework is used to divide the prediction and control time domains, and a weighted cost function is designed that accounts for attitude angle tracking error and hydraulic energy consumption. The multi-degree-of-freedom coupling model is then decomposed into independent subproblems using the Lagrange multiplier method to solve independent control commands for pitch, steering, and twist. Figure 3The vehicle's multi-degree-of-freedom motion in complex terrain is demonstrated: twist, pitch, and steering angles. The dynamic decoupling control module uses a model predictive control algorithm to solve independent control commands based on mechanical and hydraulic coupling models (such as pitch cylinder geometry and steering damper lock cylinder characteristics).

[0053] The hydraulic actuator module generates a proportional valve duty cycle signal based on the independent control instructions output by the dynamic decoupling control module, adjusts the nonlinear area control quantity in combination with the valve body dead zone compensation table, dynamically adjusts the gear pump motor speed through the PID algorithm, and drives the hydraulic pressure gradient of the pitch cylinder and the steering damping lock cylinder to distribute the braking torque. The redundant control module monitors the hydraulic pressure sensor residual and valve body response delay of the hydraulic actuator module in real time. When abnormal oil temperature or valve body jamming is detected, it switches to the historical optimal control sequence or preset open-loop PID control instruction to maintain the basic brake pressure distribution. Figure 4 As shown, the hydraulic actuator module controls the hydraulic circuit via a proportional valve. When the dynamic decoupling module issues a pitch command, hydraulic oil flows through the reversing valve into the pitch cylinder, pushing it to extend or retract. The proportional valve's duty cycle signal adjusts the oil pressure gradient, achieving linear distribution of braking torque.

[0054] The bus communication module receives global path planning instructions from the vehicle control system via the CAN protocol interaction unit, interprets them as target attitude angles, and transmits them to the dynamic decoupling control module. In unexpected obstacle scenarios, the event triggering unit identifies excessive obstacle height based on the six-degree-of-freedom motion state vector from the data fusion module. It then sends an emergency brake pressure distribution command to the hydraulic actuator module to adjust the proportional valve duty cycle signal. Simultaneously, it sends an attitude angle lock request to the dynamic decoupling control module, fixing the current pitch and steering angles, achieving coordinated control of braking and attitude adjustment.

[0055] Specifically, the electronic hydraulic braking system for a special unmanned tracked vehicle of the present invention includes a data fusion module comprising:

[0056] The timestamp alignment unit triggers multi-sensor synchronous sampling through hardware interrupts, receiving the pitch, roll, and heading angles generated by the inertial navigation unit in the data acquisition module, the actual slip rate calculated by the wheel speed sensor, and the hydraulic chamber pressure value fed back by the pressure sensor group;

[0057] The Kalman filter unit fuses the synchronized pitch angle, roll angle, and heading angle with the actual slip rate, corrects the estimated error of the attitude angle, generates a six-degree-of-freedom motion state vector, and outputs it to the dynamic decoupling control module.

[0058] The data fusion module achieves synchronous acquisition and integration of multi-sensor data through a timestamp alignment unit. This unit utilizes a hardware interrupt trigger mechanism to send synchronous sampling instructions to the inertial navigation unit, wheel speed sensor, and pressure sensor group at a preset timer cycle, eliminating time domain deviations caused by differences in sensor sampling frequencies. The pitch, roll, and heading angle data output by the inertial navigation unit, the actual slip rate data calculated by the wheel speed sensor based on the track circumference, and the hydraulic chamber pressure value collected by the pressure sensor group are uniformly timestamped by the timestamp alignment unit and transmitted to the Kalman filter unit for data fusion processing.

[0059] The Kalman filter unit performs prediction and update iterations on synchronized multi-source sensor data. The prediction phase calculates theoretical estimates of the current attitude angle, slip rate, and pressure value based on the six-degree-of-freedom motion state vector at the previous moment and the vehicle dynamics model. The update phase performs a weighted fusion of the timestamp-aligned sensor measured data and the theoretical estimates. The Kalman gain is calculated to dynamically adjust the prediction error weights, correcting for deviations in the estimated pitch, roll, and heading angles. This generates a six-degree-of-freedom motion state vector comprising three-dimensional position, velocity, acceleration, and attitude angle. The fused state vector is transmitted via a bus to the dynamic decoupling control module, where it serves as a real-time input parameter for the model predictive control algorithm.

[0060] The data exchange between the timestamp alignment unit and the Kalman filter unit forms a closed-loop processing chain. After the synchronized sensor data is corrected by the Kalman filter, the output high-precision six-degree-of-freedom motion state vector is further fed back to the timestamp alignment unit to optimize the adaptive adjustment of the hardware interrupt trigger period and reduce clock drift errors during multi-sensor collaborative sampling. Through the coordinated mechanism of timing synchronization and data fusion, this module ensures that the vehicle motion state information obtained by the dynamic decoupling control module is temporally consistent and spatially correlated, supporting the real-time and stability of multi-degree-of-freedom decoupling control.

[0061] Specifically, the electronic hydraulic braking system for a special unmanned tracked vehicle of the present invention includes a dynamic decoupling control module comprising: a mechanical and hydraulic coupling modeling unit, which constructs, based on the mechanical and hydraulic coupling model, the geometric parameters of the articulated mechanism including the pitch cylinder and the steering damping lock cylinder, as well as the dynamic equations of the proportional valve flow and pressure characteristic curves;

[0062] The parameter identification unit receives the six-degree-of-freedom motion state vector from the data fusion module, updates the hydraulic oil elastic modulus and valve body flow coefficient online through the recursive least squares method, and outputs the updated parameters to the cost function construction unit of the rolling optimization framework for optimization target calculation.

[0063] The dynamic decoupling control module achieves multi-degree-of-freedom dynamic decoupling control through the collaboration of a mechanical and hydraulic coupling modeling unit and a parameter identification unit. Based on the geometric parameters of the articulated mechanism, such as the installation position and connecting rod length of the pitch and steering damping lock cylinders, and in combination with the flow and pressure characteristic curves of the proportional solenoid valve, the mechanical and hydraulic coupling modeling unit constructs a coupling model that includes the rigid-body dynamic equations of the mechanical subsystem and the nonlinear response characteristics of the hydraulic subsystem. In this model, the mechanical subsystem equations describe the equilibrium relationship between the inertial force and cylinder thrust for pitch, steering, and torsional motions, while the hydraulic subsystem equations quantify the force transmission characteristics of the hydraulic actuator based on the dynamic relationship between the proportional valve opening and the oil chamber pressure.

[0064] The parameter identification unit receives the six-degree-of-freedom motion state vector generated by the data fusion module and uses recursive least squares to online identify the hydraulic oil elastic modulus and valve flow coefficient. Specifically, the recursive least squares method dynamically updates the temperature drift compensation parameters of the hydraulic oil elastic modulus and the nonlinear correction parameters of the valve flow coefficient based on the six-degree-of-freedom motion state vector sequence within a sliding time window, combining the predicted output of the mechanical and hydraulic coupling model with the residual of the actual sensor data. The updated parameters are transmitted in real time to the cost function construction unit of the rolling optimization framework, which adjusts the weight ratio of attitude angle tracking error to hydraulic energy consumption to optimize the objective function of the model predictive control algorithm.

[0065] The output parameters of the mechanical and hydraulic coupling modeling unit and the updated results of the parameter identification unit form a closed-loop iterative mechanism. The dynamic equations of the coupling model are updated in real time within the rolling optimization framework. The coupling weights of the pitch cylinder thrust and steering damping force are adjusted based on the updated parameters provided by the parameter identification unit to suppress cross-interference between multiple degrees of freedom. The parameter identification unit continuously calibrates the model parameters using a recursive least squares method to compensate for elastic modulus degradation caused by hydraulic oil temperature fluctuations and flow characteristic deviations due to valve aging, ensuring the decoupling accuracy and robustness of the model predictive control algorithm under multiple operating conditions.

[0066] Specifically, the electronic hydraulic braking system for a special unmanned tracked vehicle of the present invention includes a rolling optimization framework comprising:

[0067] The prediction time domain division unit sets a multi-step prediction window according to the response delay of the hydraulic actuator module;

[0068] The cost function construction unit receives the six-degree-of-freedom motion state vector generated by the data fusion module and the target attitude angle deviation of the dynamic decoupling control module, and weights the attitude angle tracking error and the energy consumption index of the hydraulic execution module to form an optimization target;

[0069] The Lagrange multiplier solving unit decomposes the dynamic equations of the mechanical and hydraulic coupling modeling unit, solves the independent control instructions of pitch, steering and torsion according to the optimization objectives, and outputs them to the hydraulic execution module.

[0070] The rolling optimization framework achieves real-time optimization of multi-degree-of-freedom dynamic decoupling control through the synergistic effect of the prediction time domain division unit, the cost function construction unit, and the Lagrange multiplier solution unit. The prediction time domain division unit sets a multi-step prediction window that matches the control system sampling period based on the response delay time of the proportional valve in the hydraulic actuator module and the dynamic characteristics of the gear pump regulating oil pressure. Specifically, the step size of the prediction window is determined based on the steady-state time of the hydraulic oil pressure gradient change and the valve body switching frequency. This allows the prediction time domain of the model predictive control algorithm to cover the entire response process of the hydraulic actuator from receiving the command to the stabilization of the pressure, avoiding control command lags caused by insufficient prediction step size.

[0071] The cost function construction unit receives the six-degree-of-freedom motion state vector generated by the data fusion module and the target attitude angle deviation from the dynamic decoupling control module. It then normalizes and weights the attitude angle tracking error term and the energy consumption index of the hydraulic actuator module. The attitude angle tracking error term is calculated as the sum of the squares of the deviations between the actual and target values ​​of the pitch, roll, and steering angles. The energy consumption index is generated based on the operating duration of the proportional valve duty cycle signal and the integral of the gear pump motor power. The weight coefficient is dynamically adjusted based on the hydraulic oil elastic modulus and valve body flow coefficient updated online by the parameter identification unit. The attitude angle tracking weight is increased under high slip conditions, while hydraulic energy consumption is prioritized during steady-state driving.

[0072] The Lagrange multiplier solver performs constraint decomposition on the dynamic equations of the mechanical and hydraulic coupling modeling units, converting the multi-degree-of-freedom coupling model into independent optimization subproblems for pitch, steering, and torsion motions. Specifically, based on a weighted optimization objective constructed from a cost function, Lagrange multipliers are introduced to relax the coupling constraints between the mechanical and hydraulic subsystems, solving for the control instructions corresponding to each degree of freedom. The solved independent control instructions are transmitted via a bus to the hydraulic actuator module, driving the generation of proportional valve duty cycle signals to achieve precise distribution of pitch cylinder thrust and steering damping lock force. This solution process is iteratively executed within the rolling optimization framework and, combined with the window update mechanism of the prediction time domain partitioning unit, forms a closed-loop dynamic adjustment link to suppress cross-interference between multi-degree-of-freedom motions.

[0073] Specifically, the electronic hydraulic braking system for a special unmanned tracked vehicle of the present invention includes a redundant control module comprising:

[0074] A fault detection unit identifies abnormal oil temperature or valve sticking based on the residual error between the real-time measurement value of the hydraulic actuator module's oil pressure sensor and the Kalman filter prediction value, as well as the valve response delay threshold;

[0075] The strategy switching unit calls the historical optimal control sequence of the dynamic decoupling control module under abnormal conditions, or switches to the preset open-loop PID control instructions and outputs them to the hydraulic execution module to maintain the basic brake pressure distribution.

[0076] The redundant control module maintains braking function during abnormal conditions through a coordinated mechanism between a fault detection unit and a strategy switching unit. The fault detection unit calculates the pressure fluctuation amplitude and rate of change based on the residual between the real-time measurement value of the hydraulic actuator module's oil pressure sensor and the predicted pressure value generated by the Kalman filter in the data fusion module. When the residual exceeds a preset threshold and the valve response delay reaches a critical value, an oil temperature anomaly or valve sticking is detected. Oil temperature anomalies are identified by changes in the slope of the temperature-pressure characteristic curve of the oil pressure sensor data, while valve sticking is detected based on the time-domain lag between the proportional valve command signal and pressure feedback.

[0077] Upon receiving the abnormal condition signal from the fault detection unit, the strategy switching unit invokes the historically optimal control sequence of the dynamic decoupling control module. This historically optimal control sequence, stored in the dynamic decoupling control module's rolling optimization framework, includes a set of control instructions that minimize attitude angle tracking error and optimize energy consumption within a preset time window. If the abnormal condition persists or the historical sequence is no longer applicable, the strategy switching unit switches to a preset open-loop PID control instruction. This instruction is generated based on the proportional valve reference duty cycle and gear pump pressure reference value of the hydraulic actuator module. This instruction adjusts the oil pressure gradient using a fixed gain parameter to maintain the base brake pressure distribution.

[0078] Data interaction between the fault detection unit and the strategy switching unit forms a closed-loop fault-tolerant mechanism. Once the abnormal state is resolved, the strategy switching unit sends a reset command to the dynamic decoupling control module, restoring the rolling optimization logic of the model predictive control. The priority of the historically optimal control sequence is dynamically adjusted based on the fault type. For abnormal oil temperatures, low-energy control sequences are prioritized, while for valve sticking, low-frequency switching commands are selected to reduce mechanical impact. The output parameters of the open-loop PID control command are linked to the valve deadband compensation table of the hydraulic actuator module to prevent control failure in nonlinear regions and ensure stable pressure distribution for the basic braking function.

[0079] Specifically, the electronic hydraulic braking system for a special unmanned tracked vehicle of the present invention includes a bus communication module comprising:

[0080] The CAN protocol interaction unit receives the global path planning instructions from the vehicle control system through the J1939 protocol, interprets them into the target attitude angle of the dynamic decoupling control module, and transmits them to the dynamic decoupling control module;

[0081] The event trigger unit identifies the obstacle height exceeding the limit based on the six-degree-of-freedom motion state vector of the data fusion module in the sudden obstacle scenario, sends an emergency brake pressure distribution instruction to the hydraulic execution module to adjust the proportional valve duty cycle signal, and sends an attitude angle lock request to the dynamic decoupling control module to fix the current pitch angle and steering angle.

[0082] The bus communication module achieves real-time transmission of vehicle control commands and emergency response through the collaboration of the CAN protocol interaction unit and the event trigger unit. The CAN protocol interaction unit parses the global path planning instructions issued by the vehicle control system based on the J1939 protocol, converting the target turning radius, pitch angle, and driving speed parameters contained in the path information into the target attitude angle for the dynamic decoupling control module. During this conversion process, the protocol decoder extracts the heading angle deviation and pitch angle setpoints from the path planning instructions. The incremental adjustment to the target attitude angle is calculated based on the vehicle's current posture data and transmitted via the bus to the rolling optimization framework of the dynamic decoupling control module as the input reference for the model predictive control algorithm.

[0083] The event trigger unit monitors the six-degree-of-freedom motion state vector generated by the data fusion module in real time. By analyzing the composite indicators of vertical displacement change rate and pitch angle acceleration, it identifies obstacles exceeding the height limit in sudden obstacle scenarios. If the obstacle height exceeds a preset threshold, the event trigger unit sends an emergency brake pressure distribution command to the hydraulic actuator module. This command includes a step increment parameter for the proportional valve duty cycle signal and a speed increase command for the gear pump motor. This command rapidly increases the pressure in the main hydraulic circuit to achieve linear distribution of the emergency braking torque. Simultaneously, the event trigger unit sends an attitude angle lock request to the dynamic decoupling control module, freezing the current pitch and steering angle target inputs to suppress attitude oscillations caused by obstacle impact.

[0084] Data exchange between the CAN protocol interaction unit and the event triggering unit forms a closed-loop control link. The attitude angle lock request received by the dynamic decoupling control module triggers a constraint update in the rolling optimization framework, setting the target deviation terms for the pitch and steering angles to zero and forcing the control algorithm to maintain the current attitude. After the emergency brake pressure distribution command from the hydraulic actuator module is executed, the oil pressure sensor feeds real-time pressure data back to the event triggering unit, dynamically adjusting the incremental parameters of the duty cycle signal to balance braking distance and hydraulic system stability. This module, through a coordinated mechanism of command parsing and event response, ensures path tracking accuracy and emergency braking reliability under complex operating conditions.

[0085] The specific implementation of the present invention realizes dynamic decoupling control of multi-degree-of-freedom motion coupling through the collaboration of multiple modules. In the data acquisition module, the inertial navigation unit solves the three-dimensional acceleration and angular velocity of the vehicle through quaternions to generate the pitch angle, roll angle and heading angle; the wheel speed sensor calculates the actual slip rate based on the track circumference and rotation speed; the pressure sensor group measures the pressure values ​​of the pitch cylinder, steering damping lock cylinder and main hydraulic circuit in real time. The multi-source data is unified with the timestamp by the synchronous sampling mechanism triggered by the hardware interrupt and transmitted to the data fusion module. The Kalman filter fuses the synchronized attitude angle, slip rate and pressure data, corrects the attitude angle estimation error of the inertial navigation, and outputs a six-degree-of-freedom motion state vector including position, velocity, acceleration and attitude angle, eliminating the influence of the time domain deviation of the multi-sensor data on the control accuracy.

[0086] The dynamic decoupling control module constructs dynamic equations based on a mechanical and hydraulic coupling model, integrating the pitch cylinder's installation position, the steering damping lock mechanism's geometric parameters, and the proportional valve's flow and pressure characteristic curves to quantify the interactive coupling terms of multi-degree-of-freedom motion. The parameter identification unit uses recursive least squares to update the hydraulic oil elastic modulus and valve body flow coefficient online, compensating for model parameter drift caused by oil temperature changes. The rolling optimization framework sets the prediction time domain step size based on the response delay of the hydraulic actuator module. The six-degree-of-freedom motion state vector and the target attitude angle deviation are input into a weighted cost function. The Lagrange multiplier method is used to decouple the coupling constraints of the mechanical and hydraulic subsystems, generating independent control commands for pitch, steering, and torsion to suppress cross-interference in multi-degree-of-freedom motion.

[0087] The hydraulic actuator module converts independent control commands into proportional valve duty cycle signals, adjusts the oil pressure gradient in conjunction with the valve deadband compensation table, and drives the braking torque distribution between the pitch cylinder and the steering damper lock cylinder. The redundant control module monitors the oil pressure sensor residual and valve response delay in real time. When abnormal oil temperature or valve sticking is detected, it switches to the historically optimal control sequence or preset open-loop PID command to maintain base brake pressure. The bus communication module parses vehicle path planning commands via the J1939 protocol and converts them into the target attitude angle for the dynamic decoupling control module. The event trigger unit identifies obstacle height violations based on the six-degree-of-freedom motion state vector, sends an emergency braking command to the hydraulic actuator module, and locks the current attitude angle, achieving coordinated braking and attitude control in obstacle-crossing scenarios. Each module ensures the real-time and robustness of multi-degree-of-freedom dynamic decoupling control through timing synchronization and closed-loop data feedback.

[0088] This invention achieves dynamic decoupling control of multi-degree-of-freedom kinematic coupling through multi-source sensor data fusion and mechanical and hydraulic coupling modeling. The data acquisition module collects real-time data on the vehicle's attitude angle, track slip rate, and hydraulic chamber pressure. Through timestamp synchronization and Kalman filtering error correction in the data fusion module, a high-precision six-degree-of-freedom motion state vector is generated. This vector, which includes the vehicle's three-dimensional position, velocity, acceleration, and attitude angle information, provides real-time input parameters for the dynamic decoupling control module, eliminating the interference of temporal deviations in multi-sensor data on model prediction accuracy.

[0089] The dynamic decoupling control module constructs multi-degree-of-freedom dynamic equations based on a mechanical and hydraulic coupling model and implements the decoupling operation of the model predictive control algorithm in conjunction with a rolling optimization framework. The mechanical and hydraulic coupling modeling unit integrates the geometric parameters of the articulated mechanism with the flow and pressure characteristic curves of the proportional valve to quantify the interactive coupling terms of pitch, steering, and torsion motions. The rolling optimization framework uses a prediction time domain partitioning unit to set a prediction window that matches the response delay of the hydraulic actuator module. It constructs a cost function that weights the attitude angle tracking error and hydraulic energy consumption. The Lagrange multiplier method is then used to decompose the coupled dynamic equations to generate independent control commands for each degree of freedom, thereby suppressing cross-interference effects.

[0090] The hydraulic actuator module converts independent control commands into proportional valve duty cycle signals, adjusting the pressure gradients in the pitch and steering damper lock cylinders to distribute braking torque. The redundant control module monitors the oil pressure sensor residual error and valve response delay in real time. In abnormal conditions, it switches to the historically optimal control sequence or open-loop PID instructions to maintain basic braking function. The bus communication module uses an event-triggered mechanism to identify obstacle height violations. It then collaborates with the dynamic decoupling control module to lock the current attitude angle and trigger emergency braking, forming a closed-loop control chain with dynamic decoupling across multiple degrees of freedom.

Claims

1. An electronic hydraulic braking system for a special unmanned tracked vehicle, characterized in that: include: Data acquisition module, which collects vehicle attitude angle, track slip rate and hydraulic chamber pressure data in real time; The data fusion module receives the vehicle's attitude angle, track slip rate, and hydraulic chamber pressure data, and generates a six-degree-of-freedom motion state vector through timestamp synchronization and Kalman filter error correction; The dynamic decoupling control module inputs the six-degree-of-freedom motion state vector and the target attitude angle of the bus communication module into the preset model predictive control algorithm, and solves the independent control instructions of pitch, turn and twist through the rolling optimization framework; The hydraulic actuator module receives independent control commands and generates proportional valve duty cycle signals to adjust the hydraulic pressure gradients of the pitch cylinder and steering damping lock cylinder to distribute the braking torque; Redundant control module detects the oil pressure sensor residual and valve body response delay of the hydraulic actuator module, and switches to the historical optimal control sequence or open-loop PID control in abnormal conditions; The bus communication module receives the path planning instructions from the vehicle control system and transmits them to the dynamic decoupling control module, triggering the emergency brake pressure distribution of the hydraulic actuator module in the event of an unexpected obstacle; The dynamic decoupling control module includes: a mechanical and hydraulic coupling modeling unit, which constructs the dynamic equations of the pitch cylinder, steering damper lock cylinder, and proportional valve flow and pressure characteristic curves based on the mechanical and hydraulic coupling model; The parameter identification unit receives the six-degree-of-freedom motion state vector from the data fusion module, updates the hydraulic oil elastic modulus and valve body flow coefficient online through the recursive least squares method, and outputs the updated parameters to the cost function construction unit of the rolling optimization framework for optimization target calculation; The rolling optimization framework includes: The prediction time domain division unit sets a multi-step prediction window according to the response delay of the hydraulic actuator module; The cost function construction unit receives the six-degree-of-freedom motion state vector generated by the data fusion module and the target attitude angle deviation of the dynamic decoupling control module, and weights the attitude angle tracking error and the energy consumption index of the hydraulic execution module to form an optimization target; The Lagrange multiplier solving unit decomposes the dynamic equations of the mechanical and hydraulic coupling modeling unit, solves the independent control instructions of pitch, steering and torsion according to the optimization objectives, and outputs them to the hydraulic execution module.

2. The electronic hydraulic braking system for a special unmanned tracked vehicle according to claim 1, characterized in that: The data acquisition module includes: an inertial navigation unit, which receives attitude angle acquisition requirements, calculates the vehicle's three-dimensional acceleration and angular velocity through quaternions based on the attitude angle acquisition requirements, generates pitch angle, roll angle and heading angle, and transmits them to the data fusion module; The wheel speed sensor receives the track slip rate calculation request, monitors the track speed and calculates the actual slip rate based on the track circumference, and outputs it to the data fusion module; The pressure sensor group is integrated into the pitch cylinder, steering damping lock cylinder and main hydraulic circuit respectively, measuring the hydraulic chamber pressure value in real time and feeding it back to the data fusion module.

3. The electronic hydraulic braking system for a special unmanned tracked vehicle according to claim 2, characterized in that: The data fusion module includes: The timestamp alignment unit triggers multi-sensor synchronous sampling through hardware interrupts, receiving the pitch, roll, and heading angles generated by the inertial navigation unit in the data acquisition module, the actual slip rate calculated by the wheel speed sensor, and the hydraulic chamber pressure value fed back by the pressure sensor group; The Kalman filter unit fuses the synchronized pitch angle, roll angle, and heading angle with the actual slip rate, corrects the estimated error of the attitude angle, generates a six-degree-of-freedom motion state vector, and outputs it to the dynamic decoupling control module.

4. The electronic hydraulic braking system for a special unmanned tracked vehicle according to claim 1, characterized in that: Redundant control modules include: A fault detection unit identifies abnormal oil temperature or valve sticking based on the residual error between the real-time measurement value of the hydraulic actuator module's oil pressure sensor and the Kalman filter prediction value, as well as the valve response delay threshold; The strategy switching unit calls the historical optimal control sequence of the dynamic decoupling control module under abnormal conditions, or switches to the preset open-loop PID control instructions and outputs them to the hydraulic execution module to maintain the basic brake pressure distribution.

5. The electronic hydraulic braking system for a special unmanned tracked vehicle according to claim 1, characterized in that: The bus communication module includes: The CAN protocol interaction unit receives the global path planning instructions from the vehicle control system through the J1939 protocol, interprets them into the target attitude angle of the dynamic decoupling control module, and transmits them to the dynamic decoupling control module; The event trigger unit identifies the obstacle height exceeding the limit based on the six-degree-of-freedom motion state vector of the data fusion module in the sudden obstacle scenario, sends an emergency brake pressure distribution instruction to the hydraulic execution module to adjust the proportional valve duty cycle signal, and sends an attitude angle lock request to the dynamic decoupling control module to fix the current pitch angle and steering angle.

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