1112 results about "Rollover" patented technology

The invention relates to a vehicle suspension control method and device, computer equipment and a readable storage medium. The method comprises the following steps: combining obtained vehicle body dynamics time series data, vehicle control time series data and environment perception time series data in a vehicle driving process into time series data of multiple channels, determining a self-adaptive modal number of the time series data under each channel according to the time series data under each channel, and determining the self-adaptive modal number of the time series data under each channel according to the self-adaptive modal number of the time series data under each channel; and performing modal decomposition on the time sequence data based on the adaptive modal number, extracting frequency domain characteristics of the time sequence data, integrating the frequency domain characteristics of the time sequence data of the multiple channels, inputting the frequency domain characteristics into a trained suspension control parameter prediction model to obtain target time sequence characteristics for predicting suspension control parameters, and performing prediction on the suspension control parameters based on the target time sequence characteristics. Vehicle suspension control parameters are obtained through prediction, and a suspension system of the vehicle is controlled based on the vehicle suspension control parameters. By adopting the method, the risk of rollover of the vehicle can be obviously reduced.

The invention relates to the technical field of forklift driving stability control, in particular to a forklift driving stability control system based on ultrasonic and laser composite ranging, which comprises a composite ranging module, a multi-modal data fusion module, a stability prediction and control module, an execution mechanism control module and an online learning system. The composite distance measuring module collects surrounding environment information and corrects motion errors through a dynamic compensation algorithm; the multi-modal data fusion module dynamically adjusts the weight of the sensor based on an environmental interference factor, and realizes space-time calibration in combination with extended Kalman filtering; the stability prediction and control module is fused with the vehicle dynamic characteristics to predict the rollover risk and generate a hierarchical control instruction; the actuating mechanism control module drives actuating components such as an active suspension and an electronic differential mechanism through a layered framework. The method can adapt to complex working conditions, the prediction precision and fault-tolerant capability are improved, safety and efficiency are balanced, the maintenance cost is reduced, and the method is suitable for various forklifts.

The invention discloses a motor-driven tractor-semitrailer driving stability control method which comprises the following steps: firstly, establishing a tractor-semitrailer three-degree-of-freedom dynamic model, and solving yaw velocity expected values and side slip angle expected values of a tractor and a semitrailer according to driver input and actual vehicle states; secondly, according to the deviation between the expected value and the actual value of the vehicle state quantity, an upper-layer controller outputs the expected additional yaw moment, and the adaptive capacity to the parameter change of the semitrailer is achieved; the lower layer controller then outputs a torque on each wheel according to the desired additional yaw moment and the vehicle state, including a driving torque on the driving wheel and a braking torque on all wheels. By the adoption of the method for controlling the running stability of the motor-driven tractor-semitrailer, unstable working conditions such as rollover and folding of the tractor-semitrailer in the running process can be avoided, the running stability is improved, and meanwhile the method has the self-adaptive capacity for load changes of the semitrailer.

The invention discloses an anti-rollover control method and system for a balanced heavy forklift truck, and relates to the field of forklift truck intelligent control, and the method comprises the steps: collecting forklift truck working condition data through a sensor group, transmitting the data to a central controller through a CAN bus, and carrying out the preprocessing; inputting a rollover risk assessment algorithm, calculating a boundary condition of a static stability triangle and dynamic lateral moment balance, generating a rollover risk coefficient in combination with working condition data of the forklift, and outputting a decision instruction set; dynamic load adjustment is carried out through a hydraulic servo controller, and load pose parameters are obtained; a motor controller is driven to implement torque vector distribution, a braking energy recovery unit is involved, controllable slow-release braking is applied to wheels on the inner side, and adjusted wheel motion state parameters are obtained; and comparing the theoretical prediction model to carry out residual analysis, triggering a residual correction strategy, and carrying out repetitive control. The working state of the forklift is collected in real time and dynamically analyzed, so that the safety of the forklift in the operation process is improved.

The invention provides an anti-rollover control method and system for an electric automobile, and relates to the field of automobile body posture control. The control method comprises the following steps: collecting vehicle driving data; calculating a transverse load transfer rate based on the vehicle driving data, and calculating a comprehensive risk index in combination with the transverse load transfer rate and a sprung mass roll angle; the method comprises the following steps: presetting a comprehensive risk index early warning threshold value and a comprehensive risk index danger threshold value, judging the rollover working condition and the comprehensive risk index of the automobile, and executing a corresponding rollover prevention control strategy: when the rigidity of the suspension is changed, the comprehensive risk index still increases and exceeds the comprehensive risk index danger threshold value; the anti-rollover moment is changed by changing the control force of the suspensions on the two sides. After the suspension control force suppresses roll for a certain period of time, the comprehensive risk index is still not reduced to be below the early warning threshold value, the active steering system intervenes in combined control, the active steering system has two steering modes including front wheel steering and four-wheel steering, and different steering modes are used under different working conditions.

The invention discloses an active anti-rollover control system and method for an electric heavy truck based on joint early warning, and the system comprises a vehicle motion state obtaining module, a rollover index numerical calculation module, an anti-rollover early warning module, and an anti-rollover integrated control module, and the rollover index numerical calculation module is used for calculating an LTR value and a ZMP value; the anti-rollover integrated control module is connected with the anti-rollover early warning module and calculates a rollover time TTR value through comparison with a threshold value, the anti-rollover early warning module sends out different early warning signals through comparison of the TTR and the threshold value, different control systems are adopted for anti-rollover control, and the anti-rollover integrated control module comprises a control subsystem and a coordination controller. According to the electric heavy truck active anti-rollover control system and method based on combined early warning, two appropriate control subsystems are selected according to an early warning signal to carry out anti-rollover coordination control, a coordination controller uses a Nash equilibrium algorithm to solve and obtain an optimal control quantity, and coordination control is carried out. And the anti-rollover performance of the electric heavy truck is greatly improved.

The invention relates to the technical field of semitrailers, and discloses a side-turning self-dumping semitrailer which comprises a semitrailer body, a carriage, a driving mechanism and a movable side carriage door, and a side baffle structure and a door locking structure corresponding to the movable side carriage door are arranged on a lower side beam of the carriage. The side baffle structure comprises a baffle, a balance weight beam arranged on the top of the outer side face of the baffle and a plurality of supporting pipes vertically arranged on the baffle, and the bottoms of the supporting pipes are connected with a lower side beam pivot of the carriage. The side baffle structure and the door locking structure of the rollover self-dumping semitrailer can be opened and closed by ingeniously utilizing the rollover acting force of the carriage, the reliability is high, additional power sources (such as an oil cylinder and an air cylinder) do not need to be arranged, the manufacturing cost and the maintenance cost are reduced, and meanwhile the oil leakage risk is avoided. Due to the linkage design of the movable side compartment door and the baffle, the unloading process is smoother, manual intervention is not needed, and the problem that tires are prone to being buried by goods during unloading of an existing side-tipping dumper is fundamentally solved.

The invention discloses a rollover risk prediction method for an operation machine, and the method comprises the steps: determining target attitude information corresponding to the operation machine and a target rotation angle of the operation machine around a first rollover line under the condition that the operation machine is in a bucket supporting condition, the target posture information is used for representing the supporting posture of the operation machine under the bucket supporting working condition, and the first tip-over line is a connecting line between supporting points of the operation machine under the bucket supporting working condition; determining a target stability parameter corresponding to the operation machine based on the target attitude information, the target rotation angle and a preset mapping relation; the mapping relation is used for representing the relation among the rotation angle, the attitude information and the stability parameter of the operation machine; and determining the tipping risk of the operation machine according to the stability parameter. According to the invention, the tipping risk of the operation machine can be accurately determined.

Provided are a method and apparatus for controlling rollover prevention of a tank truck, a cloud, a tank truck, and a system for controlling rollover prevention of a tank truck. The method includes: obtaining vehicle information sent by the tank truck and liquid filling information obtained based on a sensor; inputting the vehicle information and the liquid filling information into a vehicle fine model and a liquid sloshing fine model respectively, and outputting a first parameter calibration result and a second parameter calibration result respectively; and transmitting the first parameter calibration result and the second parameter calibration result to the tank truck, determining a control target of the tank truck by combining vehicle state sensor information observation and liquid related sensor information observation, and controlling the rollover prevention of the tank truck based on the control target.

The invention discloses a vehicle driving risk prediction method and device in an off-road environment based on a large model, and relates to the technical field of off-road risk prediction, and the method comprises the steps: obtaining current vehicle state data and current environment perception data; determining a target multi-axis rollover risk index based on the current vehicle state data; determining a target lateral instability index based on the current vehicle state data and the current environment perception data; fusing the target multi-axis rollover risk index and the target lateral instability index to generate target risk level data; based on the current vehicle state data, the current environment perception data and the target risk level data, generating a target operation recommendation sequence through a large cross-country decision model; and outputting risk early warning information based on the target operation recommendation sequence.

The invention discloses a coil unloading centering method and related equipment, relates to the field of strip steel, and mainly aims to solve the problems that steel coils are not accurate enough in centering under the condition of coil unloading, and deflection and rollover of the steel coils are easily caused. The method comprises the following steps: acquiring first single-side edge position data of target strip steel; converting the first single-side edge position data from a first coordinate system to a second coordinate system to obtain second single-side edge position data; and based on the second single-side edge position data and the width data of the target strip steel, the vertical offset of the center line of the target strip steel relative to the center line of the unit is determined, and the vertical offset is used for adjusting the position of a coil unloading vehicle. The device is used for the coil unloading centering process.

The invention discloses an axle staged cooling system, an axle staged cooling assembly and an engineering vehicle. The axle staged cooling system comprises an engine first-stage cooling system, an engine second-stage cooling system, an axle first-stage cooling system and an axle second-stage cooling system. Each stage of cooling system controls cooling water and oil path trend through a thermolator in each loop, controls axle cooling oil and engine cooling water to exchange heat, and meets different cooling requirements of an axle. The temperature sensor in each loop outputs water and oil temperature signals to a motor of the cooling fan, so that the rotating speed of the fan is increased to different degrees along with the temperature rise of each cooling system, and different cooling powers are matched. According to the grading system, the engine and the axles can work at the proper temperature at the same time, the two heat exchangers cool cooling oil of the front axle, cooling oil of the middle axle and cooling oil of the rear axle respectively, the cooling capacity of the front axle is improved, the braking effectiveness of the front axle is guaranteed, and rollover caused by serious backward movement of the gravity center of a vehicle during emergency braking is prevented.

The invention provides a semi-trailer rollover early warning method and system based on dynamic threshold value prediction. The early warning method comprises the steps that the transverse acceleration, the yaw velocity, the vehicle speed, the suspension pressure and the front lane curvature of a semi-trailer are obtained in real time; according to the collected and calculated data and a linear trend extrapolation method, constructing a dynamic rollover risk threshold function and a comprehensive risk index function, and calculating a rollover risk threshold, a real-time risk value and a predicted risk value; the item with the higher value in the real-time risk value and the predicted risk value is selected and compared with a rollover risk threshold value, and whether early warning is triggered or not is judged, and a control instruction is issued; the early warning system comprises a semitrailer state monitoring unit, a lane curvature recognition unit, a rollover risk threshold calculation unit, a real-time risk value calculation unit, a predicted risk value calculation unit and an early warning control unit, and is used for realizing the early warning method, so that the response speed and the judgment accuracy of the semitrailer rollover early warning system under variable working conditions are improved.

The invention discloses an anti-rollover control method for a four-wheel steering vehicle based on deep reinforcement learning, and the method achieves the collaborative optimization of a four-wheel steering angle and a braking force through constructing a reinforcement learning frame of hybrid model driving and data driving. A hierarchical network structure is adopted to separate stability decision and execution control, and the generalization ability of the algorithm is improved in combination with virtual-real transfer learning. The anti-rollover control robustness under the complex working condition is remarkably improved, and the method can be applied to an active safety system of an intelligent driving vehicle.

The invention discloses a rollover risk pre-judgment and speed closed-loop control system and method integrating an IMU and an encoder, and relates to the technical field of vehicle active safety control. The system comprises an inertial measurement unit, an encoder, a controller, an execution mechanism and an alarm, the inertial measurement unit provides vehicle attitude data, and the encoder provides vehicle speed information. And the controller fuses the data in real time to calculate a vehicle rollover risk index, and sets a double-threshold criterion: when the risk is close to a threshold, an early warning is given, and when the risk exceeds the threshold, a deceleration control instruction is sent to the execution mechanism. The executing mechanism adjusts vehicle power output or braking accordingly, and automatic speed reduction is achieved. The controller forms a closed-loop control loop through feedback of the encoder, the speed reduction force is dynamically adjusted, and the speed of the vehicle is stably reduced to a safe range. Through the method, the rollover risk of the vehicle can be sensed in advance and actively intervened, rollover accidents are avoided, and the rollover-resistant safety of the vehicle is remarkably improved.

The invention discloses a hazardous chemical substance transportation early warning system based on a fuzzy neural network, and relates to the technical field of traffic transportation and road safety monitoring. According to the hazardous chemical substance transportation early warning system based on the fuzzy neural network, road geometric influence in original data of a sensor is accurately stripped from dynamic response of a vehicle; according to the method, false risk signals caused by road design can be eliminated, the method focuses on instability risks really caused by dynamic factors such as vehicle control and load transfer, and the rollover risk can be judged more essentially and more accurately; converting the preprocessed characteristic quantity into a fuzzy linguistic variable, reasoning by simulating a fuzzy rule of human expert experience, and finally outputting continuous risk indexes and levels; the processing mode not only better conforms to the imprecise characteristic of risk assessment, but also enhances the adaptability and robustness of the system to different vehicle types, loads and road conditions.

The invention relates to a rail-mounted automatic guided vehicle provided with a plate folding and stacking station, which belongs to the technical field of automatic warehouse logistics and comprises two groups of guide rail main bodies, and a storing and taking assembly is arranged on the two groups of guide rail main bodies in a sliding manner. The storing and taking assembly comprises a shuttling goods taking assembly arranged on the two guide rail bodies in a sliding mode, a fork assembly arranged in the shuttling goods taking assembly and used for storing and taking goods or trays, and a tray folding and stacking assembly used for stacking the trays. The bottom of the shuttling goods taking assembly is further provided with a plurality of anti-overturning assemblies. When goods are taken, the telescopic pallet forks can quickly fork and move the goods into a vehicle, the goods putting link works according to the types of the goods, the goods circulation time is shortened, the warehouse operation efficiency is improved, tray stacking and tray disassembling work achieves precise operation through cooperation of multiple components, the tray utilization rate is improved, and the safety is guaranteed to be reliable through the rollover prevention mechanism; when the gravity center shifts, the buffer pad is compressed, and the limiting clamping wheel and the forced limiting hook act together, so that rollover is effectively prevented, and the safety of personnel and equipment is guaranteed.

The invention relates to the field of surveying and mapping unmanned ships, and discloses a combined surveying and mapping unmanned ship which comprises a ship body, a handle is rotatably connected to the outer wall of the ship body, a detection head is fixedly connected to the upper surface of the ship body, a battery box is fixedly connected to the upper surface of the ship body, and a protective net is fixedly connected to the outer wall of the ship body. A first motor is fixedly connected to the interior of the ship body, the output end of the first motor is rotationally connected to the interior of the ship body and fixedly connected with a propelling impeller, a limiting strip is fixedly connected to the outer wall of the output end of the first motor, and a first fixing block is fixedly connected to the outer wall of the ship body. The mounting blocks move to drive the bearing buoys to move so as to adjust the positions of the bearing buoys, weight distribution of the ship body can be optimized, water flow impact and storm interference can be balanced, the inclination or rollover risk of the ship body can be reduced, the ship can flexibly carry different devices according to task types due to the position adjustability, and sailing deviation caused by device weight concentration is avoided; and the multi-scene operation capability is improved.

The utility model discloses an unmanned ship rollover prevention device which comprises two rollover prevention assemblies of the same structure, the two rollover prevention assemblies are symmetrically and fixedly installed on the two side portions of a ship body, each rollover prevention assembly comprises an installation base, an extension module and a driving module, the installation bases are fixedly installed on the side portions of the ship body, and the extension modules are fixedly installed on the side portions of the ship body. A mounting groove is formed in the mounting base, one end of the extension module is fixedly mounted in the mounting base, the extension module is located in the mounting groove, and the driving module is mounted in the ship body and connected with the extension module; according to the anti-rollover device for the unmanned ship, the anti-rollover assemblies are arranged on the two sides of the ship body correspondingly, when the anti-rollover assemblies are unfolded, the buoyancy of the ship body can be effectively enhanced, meanwhile, the base contact area of the ship body and the water surface is enlarged, the overall supporting area of the ship body is enlarged, and the wind wave resistance is improved; the situation that the ship body rolls over due to overlarge storm waves is effectively reduced, then the safety of the ship body is effectively guaranteed, and the possibility that the ship body is damaged is reduced.

The invention provides an obstacle crossing method and device of a robot, the robot, a medium and a product, and relates to the technical field of intelligent robots, the robot is provided with a mechanical arm, and the mechanical arm is used for grabbing an object; the method comprises the following steps: determining the current state of a mechanical arm under the condition that the existence of a stepped obstacle is detected and the robot meets obstacle crossing conditions; controlling the robot to execute a corresponding target obstacle crossing strategy according to the current state; and the target obstacle crossing strategy at least comprises a passive obstacle crossing strategy, and the passive obstacle crossing strategy is to execute the sprint action based on the adjusted speed, so that unnecessary chassis lifting is avoided in the obstacle crossing process, the instability risk is further reduced, the stability and the overall robustness of the robot are kept, and the safety is improved. Due to the fact that the appropriate target obstacle crossing strategy can be selected according to the current state of the mechanical arm, the task execution continuity is guaranteed, the rollover risk caused by extending of the mechanical arm is avoided, and the mechanical structure damage risk caused by rollover or obstacle crossing failure is reduced.

The invention discloses a robot orchard cross slope rollover prevention method based on space-time prediction enhanced control, and aims to solve the problem of inaccurate centroid time-varying estimation caused by load and mechanical arm actions. According to the method, a vehicle-arm-load space-time diagram and a terrain contact diagram are constructed through multi-source sensing, gravity center distribution containing heavy tail uncertainty is estimated through risk gating attention cross coupling and a space-time diagram network, physical constraint projection and residual error correction are implemented, a rolling angle and a rolling stability margin are predicted through an action condition Transform, and the rolling angle and the rolling stability margin are predicted. Conditional risk value risk indexes are embedded into a sampling type model for predictive control and are constrained by a control obstacle function, so that the technical effects of reducing the rollover risk and improving the gravity center estimation credibility and the operation safety under a cross slope and a soft soil form are achieved.

The invention relates to the technical field of vehicles, in particular to a vehicle frame multi-objective optimization method based on rollover collision battery pack safety, which comprises the following steps of: constructing a battery homogenization mechanical model to obtain the distance between current collectors of a positive electrode and a negative electrode of a battery under stress; establishing a battery electrical model through the equivalent circuit, and judging whether the battery is short-circuited in the battery electrical model according to the distance between the current collectors of the positive electrode and the negative electrode; establishing a mobile charging vehicle frame three-dimensional model to obtain an instant angular velocity, and analyzing the damage degree of the battery through the coupling model; and converting each unit of the finite element analysis model into independent cells, adjusting cell attributes according to a preset rule, and performing multi-round iteration by adjusting the cell attributes so as to complete optimization of the frame model. According to the method, aiming at the defect of safety optimization of the battery pack during rollover collision, the lightweight of the frame and the improvement of the safety of the battery pack can be realized at the same time, and the optimization efficiency of a complex model is effectively improved.

The invention discloses a vehicle anti-rollover stability control system and method, and relates to the technical field of intelligent control, and the system comprises a driving behavior dynamic monitoring module which collects the behavior data of a driver in real time through a multi-sensor fusion module; the driving environment dynamic monitoring module is used for real-time driving environment data; the driving risk prediction module is used for performing dual-channel risk prediction; the rollover intervention judgment module is used for generating an intervention instruction; and the front rollover intervention module is used for implementing risk intervention according to the intervention instruction and feeding back the operation of the driver in real time to carry out dynamic cooperative control. The technical problem that the rollover risk cannot be timely and accurately controlled under the complex driving condition due to the lack of comprehensive monitoring of the driver behavior and the environment information in the prior art is solved, and the purposes of performing double-channel risk prediction and prospective dynamic intervention by fusing the driving behavior and the environment data and improving the rollover risk control accuracy are achieved. And the technical effects of robustness and real-time performance of vehicle control are improved.

The utility model provides a universal wheel system and a patrol robot, and relates to the field of robots. The universal wheel system provided by the utility model is applied to but not limited to a patrol robot, and comprises a chassis shell, a chassis, a main beam and a telescopic universal wheel assembly, wherein the chassis shell is mounted at the bottom of the robot; the chassis is mounted in the chassis shell; the main beam is mounted on the downward side of the chassis; the universal wheel assembly is movably connected with the main beam so as to switch the stretching state or the contracting state relative to the chassis shell. Under the normal condition, the universal wheel assembly is contracted in the chassis shell; and when the robot is in a jumping type terrain with a gradient such as a lower step, the universal wheel assembly extends out of the chassis shell to enlarge the chassis area, so that the gravity center of the robot is lowered, and rollover is avoided.

The utility model belongs to the technical field of unmanned helicopters, and particularly relates to a self-adaptive full-autonomous electromagnetic adsorption type landing assisting device for a multi-rotor unmanned aerial vehicle. Comprising a main body supporting frame, a self-recovery sliding electromagnetic adsorption mechanism and a control box, wherein the self-recovery sliding electromagnetic adsorption mechanism and the control box are arranged on the main body supporting frame; the main body supporting frame is connected with a foot stool of the multi-rotor unmanned aerial vehicle through a connecting structure; when the multi-rotor unmanned aerial vehicle lands, the self-recovery sliding electromagnetic adsorption mechanism makes contact with the landing platform and then sends a trigger signal to the control box, the control box controls the self-recovery sliding electromagnetic adsorption mechanism to be magnetically attracted to the landing platform, and landing of the multi-rotor unmanned aerial vehicle is assisted. The landing trigger state can be judged more accurately through the mechanical trigger limit switch, it is guaranteed that the multi-rotor unmanned aerial vehicle is stably, accurately and quickly locked with the mother platform, and sideslip or rollover is prevented.

An over actuated system capable of controlling wheel parameters, such as speed (e.g., by torque and braking), steering angles, caster angles, camber angles, and toe angles, of wheels in an associated vehicle. The system may determine the associated vehicle is in a rollover state and adjust wheel parameters to prevent vehicle rollover. Additionally, the system may determine a driving state and dynamically adjust wheel parameters to optimize driving, including, for example, cornering and parking. Such a system may also dynamically detect wheel misalignment and provide alignment and / or corrective driving solutions. Further, by utilizing degenerate solutions for driving, the system may also estimate tire-surface parameterization data for various road surfaces and make such estimates available for other vehicles via a network.

The application relates to the field of automobile safety technology and provides a vehicle detection dynamic rollover early warning method, a system and electronic equipment, which comprises the following steps: based on a target vehicle, receiving multi-source data of a real-time monitoring unit integrated with an accelerometer and a gyroscope, setting a complementary filtering framework, combining vehicle posture information and EKF principles to establish a dynamic model; predicting the vehicle posture and calculating dynamic parameters, comparing the dynamic parameters with preset threshold values, judging whether a rollover early warning signal is triggered or not, solving the technical problem that the accuracy of rollover early warning is insufficient under the influence of various interference factors in a complex and constantly changing driving environment, setting the complementary filtering framework, effectively filtering out noise, improving the accuracy of vehicle posture estimation by using the EKF principle, simultaneously, deeply analyzing the multidimensional correlation among the vehicle posture, road conditions and dynamic running parameters, quickly judging the rollover risk and triggering the early warning signal, and reducing the probability of rollover accidents.

The invention discloses a vehicle rolling critical condition prediction method and device. The method comprises the following steps: acquiring n groups of rolling data about vehicle rolling; based on the n groups of vehicle rollover parameters, performing new data synthesis processing to obtain m groups of enhanced rollover parameters corresponding to the vehicle rollover parameters; inputting the enhanced tumbling parameter into the implicit neural network, and outputting a tumbling result corresponding to the enhanced tumbling parameter; training the initial explicit neural network through the enhanced tumbling parameter and a tumbling result corresponding to the enhanced tumbling parameter to obtain a trained explicit neural network; and determining a critical condition for triggering the rolling of the target vehicle through the explicit neural network according to the input actual rolling parameter of the target vehicle. In this way, the implicit neural network is used to learn the rolling discrimination capability from the small-scale real vehicle rolling data; and then a large number of reasonable enhanced rolling parameters are generated to train an explicit neural network so as to output critical conditions of vehicle rolling expressed in a specific parameter threshold form.

A valve assembly includes a body engageable with a container, an internal cavity, and a vent outlet. A wall divides the internal cavity into a first chamber and a second chamber, the first chamber being between the bottom end of the body and the wall, and the second chamber being between the top end of the body and the wall, in communication with the vent outlet. An umbrella valve is coupled to the wall and has a central passage and an umbrella portion. The umbrella portion is positioned within the second chamber and is configured to engage a top side of the wall. The umbrella portion is configured to deform away from the top side of the wall to vent a gas along a first pathway from the first chamber to the vent outlet in response to pressure within the first chamber exceeding a cracking pressure of the umbrella valve.

The invention discloses a commercial vehicle longitudinal and transverse cooperative anti-yaw stability control system and method, and aims to solve the problem that a traditional vehicle stability control system is lagged in response and cannot actively prevent the risk of instability. The method comprises the following steps: firstly, constructing a self-adaptive digital twinborn model which can be synchronized with a physical vehicle in real time through an online parameter identification technology; then, forward simulation is carried out based on the high-fidelity model, and the future state trajectory of the vehicle is converted into a quantified stability risk potential field containing multi-dimensional information such as yawing, rollover and hinge folding; the core of the method is that by analyzing the gradient of the risk potential field in the state space, the instability risk mode playing a leading role at present is accurately and dynamically identified. According to the method, fundamental transformation from passive response to active prevention is achieved, and the driving safety and stability of the commercial vehicle under the limiting working condition are remarkably improved through accurate prediction and risk classification.