Hot-line work vehicle anti-roll stability control system based on PID (Proportion Integration Differentiation) algorithm

Abstract

The invention relates to the technical field of automatic control, in particular to a hot-line work vehicle anti-roll stability control system based on a PID (Proportion Integration Differentiation) algorithm. The slope recognition unit is used for acquiring the ground slope and the topographic change in the advancing direction of a vehicle body by using a multi-mode sensor mounted at the front part of the working vehicle; the stability prediction unit is used for monitoring the running parameters of the vehicle body in real time, predicting the stability of the vehicle body on the ramp based on the ground gradient and further generating a regulation factor; the control optimization unit is used for adjusting a suspension system and a power system of the vehicle body by combining a PID control algorithm according to the adjustment factors transmitted by the stability prediction unit; according to the system, the friction force influence between the vehicle body and the ramp is introduced, the control strategy can be dynamically adjusted, the stability of the vehicle body is optimized, heeling or instability in complex terrains is avoided, and the safety and reliability of the operation vehicle on the ramp are improved.

Description

Technical Field

[0001] The present invention relates to the field of automatic control technology, in particular to an anti-roll stability control system for a live working vehicle based on a PID algorithm. Background Art

[0002] With the continuous expansion of power infrastructure construction and the growing demand for maintenance, live working vehicles are playing an increasingly important role in the inspection and emergency repair of power systems. These vehicles not only need to travel on conventional roads, but also often have to work in complex terrain conditions such as the wild and mountainous areas, including slopes and uneven ground. However, existing technologies may not have stability control strategies specifically for slope adaptation, and therefore cannot automatically adjust the control of the vehicle body according to its state on different slopes. This may lead to increased risk of vehicle roll and increased difficulty in operation during the mission, thereby affecting work efficiency and endangering the safety of workers. Therefore, an anti-roll stability control system for live working vehicles based on the PID algorithm is designed. Summary of the Invention

[0003] The purpose of the present invention is to provide an anti-roll stability control system for an electric working vehicle based on a PID algorithm, so as to solve the problem that the above-mentioned background technology has no stability control strategy specifically for slope adaptation, and therefore cannot automatically adjust and control the vehicle body according to the state of the vehicle body on different slopes, resulting in an increased risk of vehicle roll and increased difficulty in operation during the execution of the task.

[0004] To achieve the above object, the present invention provides a PID algorithm-based anti-roll stability control system for a live working vehicle, comprising: A slope identification unit, configured to obtain corrected ground slope information on a travel path of the live working vehicle; a stability prediction unit, connected to the slope identification unit, for predicting the roll stability of the live working vehicle based on the corrected ground slope information and the real-time operating parameters of the live working vehicle, and generating an adjustment factor when an instability risk is predicted; a control optimization unit connected to the stability prediction unit, configured to adjust at least one vehicle body subsystem of the live working vehicle according to the adjustment factor and in combination with a PID control algorithm to maintain or restore the driving stability of the live working vehicle; and A feedback alarm unit is connected to the stability prediction unit, and is used to display the operating parameters of the live working vehicle and the corrected ground slope information, and to send an alarm signal when receiving the adjustment factor.

[0005] As a further improvement of this technical solution, the slope recognition unit includes: a multimodal sensor for acquiring the original ground slope in the forward direction of the live working vehicle; and An inertial measurement module, configured to monitor in real time the attitude change parameters of the live working vehicle, wherein the attitude change parameters include pitch angle and roll angle; The inertial measurement module is used to combine the posture change parameter with the original ground slope, and correct the original ground slope to obtain the corrected ground slope information.

[0006] As a further improvement of this technical solution, the stable prediction unit includes: A data acquisition module, used for collecting the operating status data of the live working vehicle in real time; an analysis and evaluation module, connected to the data acquisition module and the slope identification unit, for calculating and generating a stability score based on the operating status data and the corrected ground slope information; and The judgment and decision-making module is connected to the analysis and evaluation module, and is used to compare the stability score with a preset dynamic safety threshold, and generate the adjustment factor when the stability score is lower than the dynamic safety threshold.

[0007] As a further improvement of the present technical solution, the analysis and evaluation module performs a comprehensive evaluation based on at least one of the current load of the live working vehicle, the center of gravity height that changes with the load, the roll moment, the pitch moment and the lateral acceleration when calculating the stability score.

[0008] As a further improvement of the technical solution, the stability prediction unit introduces the influence of friction between the vehicle body and the ramp for optimization when predicting the roll stability of the live working vehicle; The optimization of the friction effect includes: determining an effective friction coefficient based on the corrected ground slope information and current weather conditions; and adjusting at least one of the roll moment, the pitch moment, the lateral acceleration, and / or adjusting the stability score based on the effective friction coefficient.

[0009] As a further improvement of the present technical solution, the dynamic safety threshold used by the judgment and decision module is based on a baseline safety threshold and is dynamically adjusted according to at least one of the corrected ground slope information, the weather impact level, and the current load of the live working vehicle; Furthermore, the magnitude of the adjustment factor is associated with the degree to which the stability score deviates from the dynamic safety threshold and the current load of the live working vehicle.

[0010] As a further improvement of the present technical solution, the control optimization unit adjusts the vehicle body subsystem through the PID control algorithm and combines the adjustment factor as the output gain modulation parameter or target setting adjustment parameter of the PID control algorithm.

[0011] As a further improvement of this technical solution, the vehicle body subsystem includes a suspension system; The control optimization unit is used to adjust the spring stiffness and / or shock absorber damping coefficient of the suspension system; the adjustment is based on the error between the current roll angle of the live working vehicle and the target roll angle and / or the error between the current pitch angle and the target pitch angle, and the control quantity is calculated by the PID control algorithm, and is adjusted in combination with the adjustment factor and the influence function of the corrected ground slope information.

[0012] As a further improvement of this technical solution, the vehicle body subsystem includes a power system; The control optimization unit is used to adjust the driving force output and / or power output of the power system; the adjustment is based on the error between the current stability score of the live working vehicle and the target stability score, the control amount is calculated by the PID control algorithm, and the adjustment is performed in combination with the influence function of the adjustment factor and the corrected ground slope information.

[0013] As a further improvement of the present technical solution, when the inertial measurement module corrects the original ground slope, the vertical component and horizontal component of the pitch angle of the live working vehicle, and the cosine value of the roll angle are combined with the vertical component and horizontal component of the original ground slope to compensate for the deviation in the perception of the original ground slope caused by changes in the vehicle body posture.

[0014] Compared with the prior art, the present invention has the following beneficial effects: 1. In the anti-roll stability control system of the live working vehicle based on the PID algorithm, the ground slope is dynamically corrected by taking into account the inclination of the vehicle body, making the slope recognition more accurate when the vehicle body posture changes. The slope correction data can be used to adjust the control strategy, making the system more stable in actual operation.

[0015] 2. In the anti-roll stability control system of the live working vehicle based on the PID algorithm, the influence of friction between the vehicle body and the slope is introduced when predicting the stability of the vehicle body on the slope. This can more accurately reflect the actual contact between the vehicle body and the ground, thereby improving the accuracy of stability prediction. By considering the influence of friction, the system can dynamically adjust the control strategy, optimize the stability of the vehicle body, avoid roll or instability in complex terrain, and improve the safety and reliability of the working vehicle on the slope. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is the overall flow chart of the present invention; The meaning of each number in the figure is: 1. Slope recognition unit; 11. Inertial measurement module; 2. Stability prediction unit; 21. Data acquisition module; 22. Analysis and evaluation module; 23. Judgment and decision module; 3. Control optimization unit; 4. Feedback alarm unit. DETAILED DESCRIPTION

[0017] The following will provide a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0018] See also Figure 1 As shown, a PID algorithm-based anti-roll stability control system for a live working vehicle is provided, comprising: a slope recognition unit 1, a stability prediction unit 2, a control optimization unit 3 and a feedback alarm unit 4.

[0019] The slope recognition unit 1 is used to obtain the ground slope and terrain changes in the vehicle's forward direction using a multimodal sensor installed at the front of the work vehicle; the multimodal sensor includes a laser radar, a ground scanning radar and a stereo camera.

[0020] The slope recognition unit 1 includes an inertial measurement module 11, which is used to monitor the posture change parameters of the vehicle body in real time, and combine the posture change parameters of the vehicle body with the ground slope to correct the ground slope information; the posture change parameters include pitch angle and roll angle.

[0021] The specific steps of the inertial measurement module 11 are as follows: Ground slope obtained by multimodal sensors: ; in, is the ground slope; is the change in ground height (vertical height change along the vehicle's forward direction); is the horizontal distance in the direction of vehicle travel.

[0022] Ground slope after introducing vehicle posture change parameters: ; in, It is the estimated ground slope after introducing the vehicle posture change parameters; is the pitch angle of the vehicle body; is the rolling angle of the vehicle body; is the vertical component of the ground slope; is the horizontal component of the ground slope; is the vertical component of the vehicle body pitch angle; is the horizontal component of the vehicle body pitch angle; The inverse tangent function returns the correct quadrant value. It takes two inputs (in this case, the numerator and the denominator To calculate the angle, this function avoids quadrant issues that can occur when using the tangent function alone, providing more accurate results. By combining the pitch angle with the ground slope, we can adjust the impact of vehicle tilt on slope perception. When the pitch angle is large, the vehicle's forward and backward tilt will cause the perceived ground slope to become steeper or flatter. The introduction of the roll angle helps correct for errors that may occur when the vehicle tilts laterally, especially when the vehicle tilts not only forward and backward but also left and right. By combining the roll angle with the pitch angle, the horizontal component of the ground slope perception can be adjusted.

[0023] By dynamically correcting the ground slope based on the vehicle's tilt (pitch and roll angles), the system achieves more accurate slope detection as the vehicle's posture changes. Whether on a slope or over uneven terrain, the vehicle's posture affects wheel contact. Slope-corrected data can be used to adjust control strategies, such as error calculation in the PID controller, ensuring greater system stability in actual operation.

[0024] Finally, the actual slope between the vehicle body and the ground is obtained: ; in, is the final ground slope; It is a correction term after filtering, calibration and optimization, which is used to eliminate the final deviation caused by sensor error, environmental factors, etc.

[0025] The stability prediction unit 2 is used to monitor the operating parameters of the vehicle body in real time, and predict the stability of the vehicle body on the slope based on the ground slope, and then generate an adjustment factor and transmit it to the control optimization unit 3 and the feedback alarm unit 4. In the process of predicting the stability of the vehicle body on the slope, the influence of the friction between the vehicle body and the slope is introduced for optimization.

[0026] The stability prediction unit 2 includes a data acquisition module 21 , an analysis and evaluation module 22 and a judgment and decision module 23 .

[0027] In stable prediction unit 2: The data acquisition module 21 is used to collect vehicle operating status data in real time through various sensors, and transmit the real-time vehicle operating status data to the analysis and evaluation module 22 .

[0028] The analysis and evaluation module 22 is used to predict the stability of the vehicle on the slope based on the collected vehicle running status data and the ground slope, and then generate a stability score.

[0029] The judgment and decision module 23 is used to compare the stability score with a preset safety threshold. If the preset safety threshold is exceeded, an adjustment factor is generated and transmitted to the control optimization unit 3 and the feedback alarm unit 4.

[0030] The specific steps of the analysis and evaluation module 22 are as follows: Car body center of gravity: ; in, is the height of the vehicle's center of gravity; is the vehicle body load; is the initial center of gravity height; is the change in center of gravity height caused by the load.

[0031] The center of gravity of the vehicle will change accordingly with the load amount. When the vehicle is loaded with more cargo, the center of gravity will increase, which may affect the overall stability and handling of the vehicle.

[0032] Rolling moment of the vehicle body (around the vehicle's longitudinal axis): ; in, is the rolling moment of the vehicle body; is the vehicle body mass; is the acceleration due to gravity; The gravitational moment of a vehicle is determined by both its mass and its load. The load affects not only the mass of the vehicle but also its relative angle to the ground, thus affecting the moment at the center of gravity. An increase in load raises the center of gravity, which in turn affects the lateral moment of the vehicle. As the load increases, the risk of the vehicle rolling increases.

[0033] Pitching moment of the vehicle body (around the vehicle's lateral axis): ; in, is the pitching moment of the vehicle body; If the load is concentrated at one end of the vehicle, the longitudinal moment of gravity will increase, affecting the stability of the vehicle. The increase in load increases the longitudinal moment of gravity, affecting the stability of the vehicle. The greater the load, the more susceptible the vehicle is to uneven ground, increasing the risk of instability.

[0034] Lateral acceleration of the vehicle: ; in, is the lateral acceleration of the vehicle body, is the vehicle speed, and R is the turning radius.

[0035] Stability Rating: in, Score the vehicle's stability; is the critical roll angle of the vehicle body; is the critical pitch angle of the vehicle body (the pitch angle here refers to These critical angles are determined by design and experience; and are the maximum allowable lateral and longitudinal moments, respectively; is the safe lateral acceleration threshold of the vehicle body; is the roll angle weighting coefficient; is the pitch angle weighting coefficient; is the lateral moment weighting coefficient; is the longitudinal moment weighting coefficient; is the lateral acceleration weighting coefficient.

[0036] In some situations, it may be necessary to emphasize the impact of certain factors on stability. For example, when driving on a steep slope, the impact of the vehicle's pitch angle and roll angle on rollover will increase significantly. In this case, you can increase and If the vehicle load is heavy and the slope is flat, the longitudinal moment has a smaller impact, so you can reduce the weight of When the vehicle is traveling at high speed, the contribution of lateral acceleration to stability risk becomes more critical, and the weight of other influencing factors can be increased. The weight of .

[0037] In different working scenarios, such as when a live working vehicle needs to frequently change its working position, it may encounter different slope conditions and changes in vehicle posture. The use of dynamically adjusted weighting coefficients can adjust the focus of the stability score according to the current ground conditions and vehicle status, providing more precise control signals.

[0038] In the stability prediction unit 2, the friction between the vehicle and the ramp is introduced to optimize the stability of the vehicle on the ramp. The optimization results are as follows: Friction: ; in, is the effective or actual friction coefficient after taking into account the effects of slope and weather; is the reference friction coefficient of the ground on a horizontal surface (for example, the friction coefficient of a dry asphalt road); The term is used to approximately correct the effect of slope on the normal force, thereby affecting the effective friction force; is the weather impact adjustment factor, the value range of this factor is usually , used to represent the reduction in friction coefficient caused by weather conditions such as rain, snow, and ice. For example, on a dry road , slightly slippery road It is 0.7, and on severely icy roads it is close to 0.1. The value of can be determined dynamically based on sensor data (such as a rain sensor) or external information (such as a weather forecast).

[0039] Friction directly affects the vehicle's traction and friction torque. The revised formulas for vehicle torque and acceleration should account for the effects of friction, especially on slopes, where the magnitude of friction can affect the vehicle's ability to maintain stable driving.

[0040] Rolling moment due to friction constraint: ; in, is the rolling moment constrained by friction; the introduction of friction affects the magnitude of the lateral moment; On a slope, the reduction in friction may lead to an increase in the lateral moment of the vehicle, thereby increasing the risk of rollover.

[0041] Pitching moment of the vehicle body: ; in, To optimize the longitudinal torque of the rear vehicle, friction affects the longitudinal torque of the vehicle. On a slope, reduced friction will lead to an increase in the longitudinal torque of the vehicle, further affecting the stability of the vehicle.

[0042] Lateral acceleration of the vehicle: ; in, To optimize the lateral acceleration of the rear vehicle, the reduction in friction results in greater lateral acceleration on slopes, increasing the risk of rollover. This effect is further exacerbated by the increased load.

[0043] Stability Rating: in, To optimize the vehicle stability score, Friction influence coefficient (0≤β≤1).

[0044] The specific steps of the judgment decision module 23 are as follows: To set a dynamic security threshold: ; in, is the dynamic safety threshold; is the baseline safety threshold (under ideal conditions, such as flat, dry road surface, and no-load); Slope correction coefficient (negative value), used to adjust the slope according to the ground slope. Adjust the threshold; Indicates the absolute value of the slope; is the comprehensive weather influence coefficient (negative value); The weather factor reflects the adjustment of the safety threshold due to weather such as rain and snow. For example, a lower threshold may be required on a slippery road. is the load influence coefficient (negative value), indicating different loads The specific values ​​of each k factor are carefully calibrated based on experimental data to ensure that It can reasonably and effectively reflect the actual risk level. Through such a design, when the slope increases, the weather deteriorates or the load increases, the overall adjustment factor in the bracket will be less than 1 (but usually greater than 0, unless the design allows for extreme conditions), so that Lower than , requiring vehicles to have higher stability scores can be judged as stable.

[0045] Generate decision factors: ; in, is the decision factor.

[0046] if Indicates that the vehicle is stable and the operation can continue; if Indicates that the vehicle is unstable and there is a risk of rollover, triggering the generation of an adjustment factor. This factor is a key parameter used to guide subsequent control actions: ; in, is the regulating factor; It is the maximum adjustment coefficient of the control system and determines the maximum adjustment range; is the load influence coefficient, which indicates the impact of load changes on stability regulation.

[0047] The role of this regulator is to: (1) The size of the adjustment factor conveys the degree of deviation in vehicle stability. It indicates how much adjustment is needed to restore the vehicle to a safe state or target state. The larger the adjustment factor, the stronger the adjustment force of the control system. For example, when the stability score is far below the safety threshold, The value of is large, resulting in the adjustment factor If the load is too large, the control unit will increase the adjustment force of the suspension system, power system and other modules to avoid rollover or instability. It mainly reflects the "amplitude" or "gain" of the adjustment. The actual adjustment direction (for example, increasing or decreasing the spring stiffness) will be determined by the error term inside the PID controller (such as , , ) is determined by the sign of .

[0048] (2) The size of the adjustment factor is proportional to the vehicle's stability deviation. It indicates how much adjustment is required to restore the vehicle to a safe state. The larger the adjustment factor, the stronger the control system's adjustment force. For example, when the stability score is far below the safety threshold, the adjustment factor is large, and the control unit will increase the adjustment force of modules such as the suspension system and powertrain to avoid rollover or instability.

[0049] (3) The adjustment factor also includes the influence of load information. As the vehicle load increases, stability decreases, and the adjustment factor will increase appropriately, prompting the control system to respond to the load change. The system will adjust the suspension system stiffness, shock absorber and other hardware configurations based on the load information to ensure that the vehicle body remains stable under large loads.

[0050] (4) The adjustment factor is modified based on environmental conditions (such as slope, wetness, etc.). When the slope or wetness conditions change, the adjustment factor will reflect the impact of friction and ground conditions on vehicle stability. In this way, the control optimization unit can adjust the system response in real time to ensure the adaptability and safety of the vehicle in different ground environments.

[0051] The control optimization unit 3 is used to adjust the suspension system and power system of the vehicle body according to the adjustment factor transmitted from the stability prediction unit 2 in combination with the PID control algorithm.

[0052] The control optimization unit 3 responds in real time based on the adjustment factor. The adjustment factor and the error term in the PID controller together convey the following information: Adjust the intensity: Adjustment factor The magnitude (absolute value) of the adjustment factor reflects the required adjustment effort. For example, a larger adjustment factor indicates a greater risk to vehicle stability or a greater deviation from the target state, requiring more significant adjustments to the suspension, powertrain, or other related systems.

[0053] The actual adjustment direction is determined by the error term in the PID controller (e.g. If the error is negative, the PID output will try to adjust in one direction; if it is positive, in the other direction. It acts as a gain modulation factor of this PID output, affecting the size of the final adjustment amount.

[0054] Response to Load Changes: The load factor in the adjustment factor indicates how the control optimization unit adjusts the vehicle's suspension and powertrain as the load changes. A heavily loaded vehicle may face greater stability risks, and the control optimization unit will adjust the vehicle's stance or suspension stiffness based on the load response of the adjustment factor.

[0055] Environmental Factors: The adjustment factor also accounts for the impact of environmental conditions (such as slope and slippery conditions) on the stability score. For example, on steep slopes or in slippery conditions, friction decreases, and adjusting the adjustment factor will inform the control optimization unit that stronger control measures are needed, such as reducing vehicle speed or adjusting vehicle posture.

[0056] The suspension system of the vehicle body is adjusted in the control optimization unit 3 as follows: Spring rate adjustment: ; in, is the spring rate after adjustment; is the base spring stiffness; is the proportional coefficient of the PID controller; is the error between the current roll angle of the vehicle and the target roll angle; is the integral coefficient of the PID controller; is the differential coefficient of the PID controller; is a function that reflects the effect of slope on suspension adjustment. For example, as the slope increases, the suspension stiffness needs to be adjusted accordingly.

[0057] Its main purpose is to dynamically adjust the spring stiffness of the suspension system based on the error between the current vehicle roll angle and the target value using the proportional, integral and differential functions of the PID controller. The change of function The suspension adjusts accordingly, allowing the system to better adapt to varying terrain conditions. When encountering steep slopes, an appropriate increase in spring rate helps maintain vehicle posture and reduces unwanted vibration. This adaptive adjustment helps improve vehicle stability and ride comfort, especially during aerial work or other situations requiring extreme stability.

[0058] In this embodiment, ,in, Is a positive constant representing the spring stiffness relative to the base stiffness The maximum relative increase. is a positive constant representing the slope sensitivity. The larger the value, the faster the spring rate increases with grade. Indicates the absolute value of the final ground slope, expressed in radians.

[0059] Shock absorber damping coefficient adjustment: ; in, is the adjusted damping coefficient; is the basic damping coefficient; is the error between the vehicle's current pitch angle and the target pitch angle; It is a function that reflects the influence of slope on the adjustment of damping coefficient.

[0060] PID control strategy is also used, combined with a function that reflects the influence of slope , enabling refined management of shock absorber performance. When the vehicle is on an inclined surface, appropriate damping settings effectively suppress body sway, enhancing handling and increasing passenger safety. Furthermore, by monitoring and responding to changes in vehicle angle in real time, this mechanism maximizes the suspension system's vibration damping while maintaining comfort.

[0061] In this embodiment, ,when (flat ground), is 1. The increase, Monotonically increasing to increase the damping coefficient.

[0062] in, Is a positive constant representing the damping coefficient of the shock absorber relative to the base damping The maximum relative increase. is a positive constant representing the slope sensitivity.

[0063] The power system for regulating the vehicle body in the control optimization unit 3 is specifically as follows: Driving force output adjustment: ; in, is the adjusted driving force; is the basic driving force; is the error between the vehicle stability score and the target stability score; It is a function that reflects the effect of slope on driving force output.

[0064] According to the gap between the vehicle's overall stability score and the preset target, the driving force provided by the motor is adjusted in a timely manner. The influence of function This ensures smooth progress even on uneven terrain. This measure not only helps overcome the challenges posed by the external environment, but also prevents potential dangers caused by sudden acceleration or deceleration.

[0065] In this embodiment, , is a positive constant representing the slope sensitivity. The larger the value, the greater the impact of the slope on the driving force. In all possible The PID adjustment term is reversed or reset to zero.

[0066] Power output adjustment: ; in, is the adjusted power output; is the basic power output; A function that reflects the adjustment effect of slope on power output.

[0067] Introducing a function that reflects the slope effect The system can flexibly allocate energy resources according to actual needs, avoiding unnecessary energy waste. More importantly, in the face of an emergency, timely and accurate power adjustment can quickly restore the normal operation of the vehicle.

[0068] In this embodiment, , is a positive constant, which also represents the slope sensitivity.

[0069] The suspension and powertrain adjustment formulas described above combine adjustment factors, slope information, and a PID algorithm to optimize vehicle stability through real-time feedback control. PID control dynamically adjusts suspension and powertrain parameters based on the vehicle's posture, stability score, and load information to adapt to varying ground conditions and prevent vehicle roll or instability.

[0070] The feedback alarm unit 4 is used to display the real-time parameters of the vehicle body and slope through the vehicle-mounted display screen, and to issue an alarm when an adjustment factor is received.

[0071] The basic principles, main features, and advantages of the present invention are shown and described above. It should be understood by those skilled in the art that the present invention is not limited to the above-described embodiments. The above-described embodiments and descriptions are merely preferred examples of the present invention and are not intended to limit the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention, and such changes and modifications fall within the scope of the invention claimed.

Claims

1. A PID algorithm-based anti-roll stability control system for live working vehicles, characterized in that: include: A slope identification unit, configured to obtain corrected ground slope information on a travel path of the live working vehicle; a stability prediction unit, connected to the slope identification unit, for predicting the roll stability of the live working vehicle based on the corrected ground slope information and the real-time operating parameters of the live working vehicle, and generating an adjustment factor when an instability risk is predicted; a control optimization unit, connected to the stability prediction unit, for adjusting at least one vehicle body subsystem of the live working vehicle according to the adjustment factor and in combination with a PID control algorithm to maintain or restore the driving stability of the live working vehicle; as well as A feedback alarm unit is connected to the stability prediction unit, and is used to display the operating parameters of the live working vehicle and the corrected ground slope information, and to send an alarm signal when receiving the adjustment factor.

2. The anti-roll stability control system for live working vehicles based on PID algorithm according to claim 1 is characterized in that: The slope recognition unit includes: a multimodal sensor for acquiring the original ground slope in the forward direction of the live working vehicle; and An inertial measurement module, configured to monitor in real time the attitude change parameters of the live working vehicle, wherein the attitude change parameters include pitch angle and roll angle; The inertial measurement module is used to combine the posture change parameter with the original ground slope, and correct the original ground slope to obtain the corrected ground slope information.

3. The anti-roll stability control system for live working vehicles based on PID algorithm according to claim 1 or 2, characterized in that: The stable prediction unit comprises: A data acquisition module, used for collecting the operating status data of the live working vehicle in real time; an analysis and evaluation module, connected to the data acquisition module and the slope identification unit, for calculating and generating a stability score based on the operating status data and the corrected ground slope information; and The judgment and decision-making module is connected to the analysis and evaluation module, and is used to compare the stability score with a preset dynamic safety threshold, and generate the adjustment factor when the stability score is lower than the dynamic safety threshold.

4. The anti-roll stability control system for live working vehicles based on PID algorithm according to claim 3 is characterized in that: When calculating the stability score, the analysis and evaluation module performs a comprehensive evaluation based on at least one of the current load of the live working vehicle, the center of gravity height that changes with the load, the rolling moment, the pitching moment, and the lateral acceleration.

5. The anti-roll stability control system for live working vehicles based on PID algorithm according to claim 3 or 4, characterized in that: The stability prediction unit introduces the influence of friction between the vehicle body and the ramp to optimize when predicting the roll stability of the live working vehicle; The optimization of the friction effect includes: determining an effective friction coefficient based on the corrected ground slope information and current weather conditions; and adjusting at least one of the roll moment, the pitch moment, and the lateral acceleration based on the effective friction coefficient, and / or adjusting the stability score.

6. The anti-roll stability control system for a live working vehicle based on a PID algorithm according to any one of claims 3 to 5, characterized in that: The dynamic safety threshold used by the judgment and decision module is based on a baseline safety threshold and is dynamically adjusted according to at least one of the corrected ground slope information, the weather impact level, and the current load of the live working vehicle; Furthermore, the magnitude of the adjustment factor is associated with the degree to which the stability score deviates from the dynamic safety threshold and the current load of the live working vehicle.

7. The anti-roll stability control system for a live working vehicle based on a PID algorithm according to any one of claims 1 to 6, characterized in that: The control optimization unit adjusts the vehicle body subsystem through the PID control algorithm and combines the adjustment factor as an output gain modulation parameter or a target setting adjustment parameter of the PID control algorithm.

8. The anti-roll stability control system for a live working vehicle based on a PID algorithm according to any one of claims 1 to 7, characterized in that: The vehicle body subsystem includes a suspension system; The control optimization unit is used to adjust the spring stiffness and / or shock absorber damping coefficient of the suspension system; the adjustment is based on the error between the current roll angle of the live working vehicle and the target roll angle and / or the error between the current pitch angle and the target pitch angle, and the control quantity is calculated by the PID control algorithm, and is adjusted in combination with the adjustment factor and the influence function of the corrected ground slope information.

9. The anti-roll stability control system for a live working vehicle based on a PID algorithm according to any one of claims 1 to 8, characterized in that: The vehicle body subsystem includes a power system; The control optimization unit is used to adjust the driving force output and / or power output of the power system; the adjustment is based on the error between the current stability score of the live working vehicle and the target stability score, the control amount is calculated by the PID control algorithm, and the adjustment is performed in combination with the influence function of the adjustment factor and the corrected ground slope information.

10. The anti-roll stability control system for live working vehicles based on PID algorithm according to claim 2, characterized in that: When correcting the original ground slope, the inertial measurement module combines the vertical component and horizontal component of the pitch angle of the live working vehicle and the cosine value of the roll angle with the vertical component and horizontal component of the original ground slope to compensate for the deviation in the perception of the original ground slope caused by changes in the vehicle body posture.

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