728 results about "Control torque" patented technology

The invention provides a water surface and underwater heterogeneous cooperative control method and device based on a preset time disturbance observer. The control method mainly comprises the steps that a water surface unmanned ship controller calculates an expected control torque according to a specified expected trajectory, the actual state information of an unmanned ship body and a compensation value obtained by the observer; the underwater unmanned vehicle controller calculates an expected control moment according to the expected trajectory obtained by the guidance method, the actual state information of the water surface unmanned ship, the actual state information of the underwater unmanned vehicle body and a compensation value obtained by the observer; and heterogeneous cooperative control of the water surface unmanned ship and the underwater unmanned vehicle is realized. According to the method, guidance of water surface and underwater heterogeneous cooperative control is completed by fusing vertical projection and a sight line method; according to the improved self-adaptive integral terminal sliding mode control method, the external interference is estimated by using the preset time interference observer and is compensated in the controller to improve the anti-interference capability of the system, and the robustness and rapidity of the system are improved while the tracking precision of the system is improved by the provided improved self-adaptive integral terminal sliding mode control method.

The invention relates to the technical field of extended-range electric vehicle control, and discloses an engine starting control method and system for an extended-range electric vehicle, and the method comprises the following steps: obtaining the operation information of the extended-range electric vehicle, the operation information comprises the actual temperature of an engine, the actual rotating speed of a range extender, the state of charge (SOC) of a power battery and the maximum dischargeable power; when the starting request mark position of the engine is set, the generator is controlled to enter a torque control mode, and the engine enters a starting mode; and based on the actual temperature of the engine and the actual rotating speed of the range extender, the pre-control torque of the generator is activated through the enabling flag bit. By accurately controlling the rotating speed and the torque of the generator, smooth starting of the engine is achieved, the requirement for starting the engine in various vehicle using scenes is met, meanwhile, the actual temperature of the engine, the SOC of a power battery and the like are considered, the target rotating speed of the started engine and the starting torque of the generator are flexibly controlled, and the starting efficiency is improved. The starting performance of the engine is improved.

The invention provides a vehicle anti-skid control method, device and system and a vehicle. According to at least one driving wheel of the vehicle, the chassis wheel speed, the actual wheel speed, the wheel end actual torque, the adhesion coefficient, the total wheel load, the target slip rate, the wheel radius and the vehicle speed are obtained; a feedforward control torque is determined according to an attachment coefficient, a total wheel load and a wheel radius, a wheel speed deviation is determined according to a target slip rate, a chassis wheel speed and an actual wheel speed, a torque deviation is adjusted through a vehicle speed, the attachment coefficient and the wheel speed deviation to obtain a feedback control torque, and the feedback control torque and the attachment coefficient are superposed to serve as an output torque for vehicle anti-skid control. Dynamic wheel load changes and wheel load changes caused by the vehicle on the ramp road surface are considered, the total wheel load is estimated in real time, feed-forward control is introduced to obtain the feed-forward control torque, feedback control is compensated, and the stability and accuracy of anti-skid control are enhanced when the ramp road surface and the loads change.

The invention discloses an attitude control method and system for a tandem type four-foot wheel-legged robot, and relates to the technical field of robot control, and the method comprises the steps: synthesizing a mass center kinematics analysis model by using a pre-established wheel-legged robot, and resolving according to expected attitude information to obtain an expected joint angle; on the basis of generating a joint feedback torque based on an actual joint angle and an expected joint angle, according to error disturbance obtained through observation, calculating to obtain a joint feedforward torque; according to the actual joint angle, the actual wheel information and the expected wheel information, the wheel control torque is obtained through calculation; and finally, according to the joint control torque and the wheel control torque, the posture change and wheel advancing of the wheel-legged robot are controlled. According to the attitude control method provided by the invention, through cooperative actuation of the wheels and the leg joints, the stability of the four-legged robot in the running state is effectively ensured, and the anti-interference capability and the control capability on the motion attitude of the robot in the running process are improved.

The invention provides an exoskeleton robot self-adaptive control method and related equipment, and relates to the technical field of exoskeleton robots. The method comprises the following steps: acquiring motion information and position information of each movable joint in the exoskeleton robot; inputting the motion information and the position information into a pre-trained angle prediction model to obtain a target angle of each movable joint; the difference value between the target angle and the actual angle output by the exoskeleton controller serves as an angle error; constructing a virtual control quantity based on the angle error; the virtual control quantity is combined with motion parameters of the exoskeleton robot to be input into a disturbance observer, and estimated disturbance is generated; the angle error, the virtual control quantity and the estimated disturbance are input into an adaptive neural network controller, and the control torque of each movable joint is obtained; and based on the control torque of each movable joint, generating a control signal of each movable joint. The method and the device have good control precision.

In a vehicle steering assist device that includes an electric power steering device that generates a control torque that modifies a return torque for urging a steering wheel to a neutral position, a steering assist ECU that controls the control torque, and a surrounding information detecting device (camera sensor, radar sensor) that detects at least information in front of a vehicle, the control torque is controlled such that a ratio of a change amount of the modified return torque to a change amount of a steering operation amount at the start of avoidance steering decreases when an obstacle is detected in front of the vehicle by the surrounding information detecting device and the avoidance steering for the vehicle to avoid collision with the obstacle is determined to be required.

The invention discloses a force sense feedback control method for an intelligent mechanical arm, which comprises the following steps of: 1, acquiring data through a multi-modal sensor and fusing the data to obtain a multi-dimensional perception vector; 3, calculating a force sense tracking error and a change rate and triggering an event-driven control decision mechanism; 4, designing a nonlinear compensation control rule and outputting a control torque instruction, wherein a control system comprises a multi-mode sensing module, a dynamic prediction module, an event-driven control module and a cooperative calculation module; according to the method, multi-mode sensing information is fused with the lifting force sense representation capacity, advanced adjustment is achieved in combination with a dynamic force sense prediction mechanism, event-driven control is used for reducing calculation redundancy, robustness to complex interference is enhanced through a nonlinear compensation strategy, and finally high-precision and low-delay force sense control of the mechanical arm in a dynamic interaction scene is achieved.

The invention belongs to a robot control method, and provides a human-guided robot-environment interaction self-adaptive control method and a related device for solving the technical problems that an existing human-guided robot-environment interaction control method is insufficient in motion stability, low in human operator safety and low in control precision. And estimating an optimal impedance parameter through a state space model, and learning a human-guided reference trajectory through a neural network in combination with the optimal impedance parameter. Then, in combination with a robot Jacobian matrix and a human-guided reference trajectory, a reference joint speed and an estimated acceleration of a joint space are obtained through closed-loop inverse kinematics, then network parameters of a robot dynamic model are obtained through approximation of an uncertain dynamic model, and finally, the robot dynamic model is obtained through combination with the reference joint speed and the network parameters of the joint space. And the mechanical arm control torque is obtained through the offset width fuzzy neural network. Accurate and compliant control under uncertain motion and dynamics conditions is realized.

The invention discloses an underwater propeller thrust distribution control method and system based on QP optimization, which are used for avoiding redundant power consumption caused by improper distribution under redundant propeller configuration and prolonging underwater operation time and endurance mileage of a robot. The method comprises the steps that a preset attitude control instruction of the underwater robot and actual attitude information fed back by a current sensor are acquired, total disturbance acting on the underwater robot is estimated in real time based on the active disturbance rejection control principle, and expected total control force and total control torque instructions are calculated; constructing a quadratic programming problem based on the total control force and the total control moment instruction; solving a quadratic programming problem to obtain a first thrust instruction of each propeller after optimization; whether a propeller fault exists or not is diagnosed in real time, and when the fault is detected, a control efficiency matrix or a physical limitation constraint in the quadratic programming problem is dynamically adjusted; and solving again based on the adjusted quadratic programming problem to obtain a second thrust instruction of each propeller under fault tolerance.

The invention provides a four-rotor unmanned aerial vehicle anti-wind-disturbance robust flight control method and system, and belongs to the technical field of unmanned aerial vehicle control, and the method comprises the steps: collecting the real-time state data of an unmanned aerial vehicle, the real-time state information comprises the position, speed, height, three-axis attitude angle and three-axis angular speed; acquiring an expected inspection track instruction, generating an expected attitude angle instruction and a total lift instruction in combination with the real-time state data, performing wind disturbance estimation by adopting a neural network, and compensating the expected attitude angle instruction and the total lift instruction; calculating a control torque increment by adopting an increment backstepping method based on the expected attitude angle instruction and the real-time state data, and obtaining a control torque instruction by combining the control torque at the previous moment; and the control torque instruction and the total lift instruction are distributed to the rotating speeds of four motors of the four-rotor unmanned aerial vehicle, and the motors execute the rotating speed instructions to drive the unmanned aerial vehicle to complete a wind disturbance resisting flight task. The method can actively adapt to wind field changes, and it is guaranteed that the unmanned aerial vehicle can still fly accurately, stably and safely under disturbance.

The invention discloses a hydraulic mechanical arm motion control method based on low-pressure volume elastic modulus compensation. The method comprises the steps that a dynamic linearization model of the multi-degree-of-freedom hydraulic mechanical arm containing the effective volume elastic modulus is established, a backstepping method is used for designing a self-adaptive robust controller, an expected joint angle is input into the self-adaptive robust controller, meanwhile, online self-adaptive parameter updating is carried out, and the optimal joint angle is obtained. The self-adaptive robust controller outputs virtual control flow of the multi-degree-of-freedom hydraulic mechanical arm after processing, and valve port control voltage is obtained after static mapping so as to control a hydraulic valve; and the multi-degree-of-freedom hydraulic mechanical arm outputs the actual control flow, the actual joint control torque and the actual joint angle to the self-adaptive robust controller in real time, and motion closed-loop control over the multi-degree-of-freedom hydraulic mechanical arm is achieved. According to the method, the high-precision motion tracking performance can be achieved under the condition that the hydraulic mechanical arm keeps stable low pressure.

The invention discloses an improved FWN-based torque double-domain constraint control method for a flexible arm space robot, and the method comprises the steps: constructing a dynamic model of a flexible arm space robot system, and constructing a torque double-domain constraint control system mathematical model in combination with the posture of a body and the constraint of the amplitude and the amplitude change rate of the control torque of a joint hinge; a torque double-domain constraint controller based on the improved fuzzy wavelet network is constructed, the torque double-domain constraint controller meets a torque double-domain constraint control system mathematical model, and corresponding control laws comprise an improved fuzzy wavelet network control law and an improved fuzzy wavelet network parameter self-adjusting control law; and the body attitude angle and the joint angle of the robot and the deformation coordinate and the vibration amplitude of the flexible arm are adjusted through the control torque which is generated by the torque double-domain constraint controller and subjected to double-domain constraint till the control target is achieved. According to the method, the problems of saturation effect and dynamic performance degradation of the actuator caused by insufficient consideration of double-domain constraints of the torque amplitude and the change rate of the joint driving mechanism are solved.

The invention discloses a cooperative control method for conversion of torque control and rotating speed control of an engine and a generator and a medium. The method comprises the following steps: calculating available recovery torque of a generator, and requesting an engine to load reserve torque by a vehicle control unit; activating an engine rotation speed control flag bit, an engine control rotation speed mode and a generator control torque mode; determining a target rotating speed and a target torque, further determining a generator torque filtering rate, and respectively controlling and adjusting the rotating speed and the torque; and exiting the engine rotation speed control flag bit, the engine control torque mode and the generator control rotation speed mode. By increasing the reserve torque of the engine, the torque adjusting capacity of the engine is improved, the engine and the generator are cooperatively controlled, and engine speed fluctuation is reduced.

The invention provides a driving anti-slip optimization control method based on vehicle-road cooperation road fusion estimation, and the method comprises the following steps: S1, fusing vehicle-mounted and roadside visual recognition information, and obtaining a vehicle-road cooperation road state recognition result through employing a weighted voting method in combination with road invariant hypothesis and historical information assistance judgment; s2, adaptively adjusting parameters of a dynamic estimator by using a pavement state recognition result, establishing a sample set based on a pavement fusion estimation result, introducing a fuzzy clustering algorithm of particle swarm optimization to realize self-evolution optimization of the structure and the parameters of the estimator, and outputting a fused attachment coefficient estimation result; and S3, designing a slip rate and wheel acceleration combined control strategy to deal with potential slip in advance, and outputting a control torque result of a slip rate controller. Compared with the prior art, the method integrates visual perception and dynamic information to realize accurate estimation of the pavement state, supports advanced intervention of the slip rate controller before slip, and improves the driving stability of the whole vehicle.

The invention relates to the technical field of hoisting equipment intelligent control based on multi-sensor cooperation, and discloses a hoisting equipment intelligent control method based on multi-sensor cooperation. A control unit reads and stores parameters such as air density, windward projection area, wind load arm length, arm section rotational inertia, rated output force of a hydraulic cylinder, sampling period and the like, and static self-inspection and dynamic calibration are performed on a wind speed sensor, a rotary encoder and a pressure sensor respectively; multiple paths of wind speeds are collected in parallel during operation, fused wind speeds are obtained through weighted fusion after abnormities are removed, and the wind load torque is calculated and limited by combining the windward area and the force arm length; reading two continuous encoder angle differences, performing amplitude limiting, calculating an angular velocity and kinetic energy, performing adaptive adjustment according to kinetic energy deviation, and performing amplitude limiting on a damping coefficient to generate a damping torque; and the amplitude-limited wind load torque and damping torque are synthesized into total control torque, and after amplitude limiting, the total control torque is converted into amplitude-limiting hydraulic cylinder operation output force which is issued and executed by a control unit.

The invention relates to the technical field of intelligent traffic control, and discloses a self-balancing two-wheeled vehicle queue formation control system which comprises a cloud scheduling platform, a formation control unit and a vehicle end execution unit. And the cloud scheduling platform generates a global avoidance path based on the accumulated gravitational potential energy change and the pavement flatness coefficient, and executes dynamic position complementing. The formation control unit constructs a communication topology and executes formation switching based on environmental perception; the cooperative control module adopts an attitude position coupling algorithm, an expected acceleration is corrected through a gain function attenuating along with an attitude angle index, and the attitude balance is maintained preferentially when a tracking error is eliminated. The vehicle end execution unit is provided with an environment sensing and composite actuating module, and a hub motor and a control moment gyroscope are used for responding to longitudinal driving and transverse balance instructions respectively, so that dynamic decoupling is achieved. According to the invention, the control conflict between two-wheeled vehicle formation trajectory tracking and attitude stability is effectively solved, and the driving safety of the system is improved.

The invention relates to the technical field of rehabilitation robot control, and particularly discloses a gait prediction compensation admittance control method and system for lower limb rehabilitation exoskeleton, and the method comprises the steps: inputting a multi-dimensional motion vector into a time sequence prediction model, and outputting a prediction result of a gait phase at a future moment; if the maximum probability output by the time sequence prediction model is lower than a preset threshold value, automatically switching to a pre-constructed rule criterion to carry out gait phase recognition; an admittance control parameter matched with the gait phase prediction result is called from an admittance parameter mapping table, and a main control torque is calculated based on the called admittance control parameter; calculating a compensation torque based on the deviation between the actual human-computer interaction force and the expected interaction force; and the main control torque and the compensation torque are superposed to serve as a final torque driving instruction of the exoskeleton motor. Real-time gait prediction, admittance parameter self-adaptive adjustment and interaction force error dynamic compensation can be fused, and high-flexibility and high-safety man-machine collaborative rehabilitation training is achieved.

The invention provides a flywheel unloading method based on an electric pushing mechanical arm in a position protection period. The flywheel unloading method comprises the steps that a joint corner combination is selected when the thrust direction is in a position protection allowable range; the control torque under the joint rotation angle combination of each mechanical arm is determined, and an initial table look-up matrix is established; determining an optimal torque and a torque error allowable range; according to the control torque, the optimal torque and the torque error allowable range, grade division is conducted on the joint corner combination; constructing a cost function according to the optimal torque and the control torque; on the basis of grade division, the smaller the cost function is, the higher the priority of the joint corner combination is; selecting a joint corner combination with the highest priority from the initial look-up table matrix, performing permutation and combination of joint corners around the joint corner combination in a fine step length manner, determining a corresponding control moment, forming a second-order look-up table matrix, and selecting a joint corner combination with the highest priority; and circularly selecting the joint corner combination with the highest priority to obtain a final joint corner combination.

A method of controlling a torque of a driving system of an electric vehicle includes determining whether a brake pedal is additionally applied at a time when only an acceleration pedal is applied. The method also includes determining an amount of a braking torque corresponding to an amount of the applied brake pedal amount. The method further includes reflecting the amount of the braking torque in one or both of a front wheel torque command and a rear wheel torque command selected according to information indicating a current vehicle driving state and front and rear wheel torque distribution states. The method additionally includes controlling a front wheel motor and a rear wheel motor according to the front wheel torque command and the rear wheel torque command.

According to the mechanical arm control method and system based on the self-adaptive force field, the motion state of a patient is monitored, the motion state is compared with a demonstration space trajectory, and training performance information of the patient is obtained. Based on the training performance information and the constructed adaptive force field model, auxiliary force applied to the patient is obtained through calculation, wherein the auxiliary force comprises normal force, tangential force and viscous force. And the applied auxiliary torque is calculated based on the tail end posture of the mechanical arm and the target posture, the joint control torque is obtained according to the auxiliary force and the auxiliary torque, and the dynamic torque and the null space control torque of the robot dynamic model are obtained. And the joint control torque, the dynamic torque and the null space control torque are combined to obtain the comprehensive control torque for controlling the mechanical arm. Therefore, the self-adaptive adjustment of the auxiliary force is realized based on the position, speed and direction of the patient, and the time degree of freedom can be obtained in the motion of the self-adaptive force field, so that the patient obtains more freedom of active motion under the assistance of the space force field.

A system for determining a secondary axle torque of a hybrid vehicle is disclosed. The hybrid vehicle includes a primary axle driven by an engine and a secondary axle driven by an electric motor. The system includes one or more sensors configured to detect a driver torque request, and a control module in communication with the one or more sensors. The control module is configured to receive data from the one or more sensors indicative of the driver torque request, calculate a primary torque target for the primary axle based on an optimal engine torque, calculate a secondary torque target for the secondary axle based on the calculated primary torque target and the driver torque request, and generate a secondary torque command to drive the secondary axle based on the calculated secondary torque target and the driver torque request. Other example systems and methods are also disclosed.

The invention discloses a quick control method and system for elastic compensation of a rope-driven elbow joint and a storage medium, and relates to the technical field of rope-driven joint control. The rapid control method comprises the following steps: determining a dynamic target of the rope-driven elbow joint; determining the angular displacement of the movable part, the rotational inertia of the movable part, the angular displacement of the driving part, the rope deformation quantity of the first rope and the rope deformation quantity of the second rope; determining an expected track of the movable part; determining an expected moment of force of the movable part; determining an expected track of the driving part; and the control torque of the driving part is determined according to the angular displacement of the movable part, the expected track of the movable part, the angular displacement of the driving part, the expected track of the driving part, the rope deformation quantity of the first rope and the rope deformation quantity of the second rope. According to the rope-driven elbow joint, a compensation item of rope elasticity is introduced into the control torque of the driving part, and the movement precision of the rope-driven elbow joint is improved.

The present invention relates to the field of electric vehicles and to a highly adaptable creep control method for pure electric heavy-duty trucks. After the pure electric heavy-duty truck enters creep mode, the method performs P-term dynamic proportional control to obtain P-term dynamic proportional control torque; performs I-term dynamic integral proportional closed-loop control to obtain I-term dynamic proportional integral closed-loop regulation control torque; performs slope feedforward torque compensation control to obtain slope compensation torque; and performs vehicle weight feedforward torque compensation control to obtain vehicle weight compensation torque. The P-term dynamic proportional control torque, I-term dynamic proportional integral closed-loop regulation control torque, slope compensation torque, and vehicle weight compensation torque are added together to obtain creep closed-loop regulation control torque. The creep closed-loop regulation control torque is then subjected to a fixed limit to prevent abnormal torque output caused by closed-loop regulation. Through the method of the present invention, stable creep speed control can be achieved for pure electric heavy-duty trucks operating with or without a trailer, unloaded, fully loaded, and under various slope conditions.

method of controlling torque of a vehicle driving device is provided. The method includes estimating speed of a driving system of a vehicle from vehicle driving information collected from the vehicle and calculating speed difference between actually measured speed of the driving system and the estimated speed of the driving system. A nominal rate limit value is determined according to the vehicle driving information and a required real-time rate correction amount is determined according to the calculated speed difference. A torque command variation is determined based on the determined nominal rate limit value and the determined required real-time rate correction amount. A torque command after correction in a previous control period is corrected by the determined torque command variation to determine a torque command after correction in a current control period.

The invention relates to a vehicle escape method, device and equipment and a medium. The method comprises the steps that the suspension height and the first slip rate of each wheel are determined; judging the escape working condition of the vehicle according to the suspension height and the first slip rate; wherein the detrapping working conditions comprise a wheel slipping working condition and a working condition that wheels sink into the ground; when the disengagement working condition is the wheel slipping working condition, a first disengagement strategy is executed, and the first disengagement strategy comprises the steps that the slip rate of slipping wheels is increased, and torque transfer is controlled between a front axle and a rear axle; and when the detrapping working condition is that the wheels are trapped in the ground, a second detrapping strategy is executed, and the second detrapping strategy comprises the step of controlling the height of the suspension. The method can adapt to various different escape working conditions, the suspension, the slip rate, the torque of the front shaft and the torque of the rear shaft and the like can be comprehensively controlled in the escape strategy, and the escape capacity of the vehicle is effectively improved.

The invention relates to an aircraft turbine engine (T) comprising an electric machine (1) connected to a transmission line (2) and a control device (3) configured to determine the currents flowing through the electric machine (1) so that it provides an electric machine torque in accordance with a control torque, wherein the control device (3) comprises a correction module (4) configured to correct the torsional mode (Mt) of the transmission line (2), wherein the correction module (4) is configured to determine a time measurement of a torque parameter of the rotor (12) of the electric machine (1) over a monitoring range, calculate a correction torque from the time measurement over the monitoring range, and calculate the control torque from a reference torque (TRQcons) and the correction torque.

The invention discloses an anti-interference flight control method for a multi-rotor unmanned aerial vehicle. The method comprises the following steps: establishing an attitude dynamic model of the multi-rotor unmanned aerial vehicle; according to a moment of momentum theorem and an Euler equation, establishing an unmanned aerial vehicle attitude kinetic equation; setting a control moment in the man-machine attitude kinetic equation as a dependent variable, and performing first-order Taylor expansion at any point; adding expectation into the expanded kinetic equation to obtain an improved incremental nonlinear dynamic inverse controller; using real-time measured values of motion variables of the multi-rotor unmanned aerial vehicle in the improved incremental nonlinear dynamic inverse controller, and optimizing the improved incremental nonlinear dynamic inverse controller by adopting a control closed-loop transfer function of an attitude angular acceleration loop and a disturbance closed-loop transfer function of the attitude angular acceleration loop; and controlling the attitude of the multi-rotor unmanned aerial vehicle by using the optimized improved incremental nonlinear dynamic inverse controller. According to the method, the dependence of the unmanned aerial vehicle control method on the model can be reduced, and the stability of the multi-rotor unmanned aerial vehicle is improved.

The invention discloses a vehicle, a control method and device thereof and a controller, and relates to the technical field of vehicles. Under the condition that the vehicle runs on the road of the target type and an acceleration instruction is received, if the controller determines that the expected output torque of the power system is larger than the target torque and the torque rising gradient is larger than the gradient threshold value, the output torque of the power system can be increased according to the target gradient smaller than the torque rising gradient. Under the conditions that the output torque of the power system reaches the expected output torque and the slip rate of the wheels is larger than the slip rate threshold value, the controller can trigger the traction force control system to conduct torque control. Therefore, when the wheels slip, the stability of the vehicle can be improved by controlling the torque through the traction force control system. And before, when the vehicle predicts that the vehicle slips on the basis of the expected output torque and the torque rise gradient, the torque rise gradient can be limited in advance, so that the vehicle is prevented from slipping to a great extent, and the driving stability of the vehicle is further improved.

The invention discloses a sliding friction control method of a hydraulic torque converter and a related device, and if the vehicle speed is smaller than a preset vehicle speed threshold value, a gearbox is in a gear shifting process, and a lock-up clutch of the hydraulic torque converter is in a lock-up state, the torque capacity of the lock-up clutch of the hydraulic torque converter is controlled to be reduced based on a first torque rate. And if the difference value between the torque capacity of the hydraulic torque converter lock-up clutch and the engine torque is smaller than or equal to the first torque threshold value, target feed-forward control torque is determined according to the engine torque request value, the target turbine rotating speed and the target speed difference of the engine, and the hydraulic torque converter lock-up clutch is controlled based on the target feed-forward torque. Therefore, in different stages of gear shifting, the torque capacity of the lock-up clutch of the hydraulic torque converter is controlled in a self-adaptive mode, so that slip frequency needed by different stages is generated, incomplete locking of the hydraulic torque converter is achieved, vibration and noise of a transmission system can be reduced, and fuel economy and driving smoothness can be effectively considered.

The invention discloses a torsion beam assembly, a vehicle and a control method of the vehicle, the torsion beam assembly comprises two longitudinal beams which extend in the front-back direction of the vehicle, one end of each longitudinal beam is suitable for being connected with a wheel, the other end of each longitudinal beam is suitable for being connected with a vehicle body, and the number of the longitudinal beams is two; the cross beam extends in the left-right direction of the vehicle, the left end and the right end of the cross beam are connected with the two longitudinal beams respectively, and the cross beam can move in the front-back direction of the vehicle relative to the longitudinal beams; the driving part is connected with the cross beam, and the driving part is suitable for driving the cross beam to move back and forth relative to the longitudinal beam. According to the torsion beam assembly, the torsion rigidity of the torsion beam assembly can be adjusted by adjusting the relative positions of the cross beams and the longitudinal beams in the front-back direction, so that the adaptability of the torsion beam assembly to road conditions is improved, and the driving experience of people in a vehicle is improved.