971 results about "Torque distribution" patented technology

The invention provides a control method based on differential rotation speed torque distribution, which relates to the technical field of intelligent control and comprises the following steps: performing difference calculation on an initial input quantity and a preset rotation speed instruction to generate a rotation speed deviation signal and a deviation change rate, and establishing a dynamic membership function library through a fuzzy controller; mapping the rotating speed deviation and the change rate thereof into a fuzzy language variable, performing reasoning operation according to a preset fuzzy control rule base, and outputting a frequency regulation quantity and a torque compensation coefficient of the frequency converter; and reading the generated torque compensation coefficient and shaft system torque values actually measured by the two torquemeters, calculating a dynamic difference value between the current total load torque and the target torque, establishing a torque distribution weight model according to the transmission characteristics of the differential mechanism, and generating differential torque correction instructions of the two motors in combination with the real-time rotating speed values. The control performance of differential drive is improved.

The invention discloses an electric forklift multi-mode driving switching method and system based on multivariable cooperation, and relates to the technical field of industrial vehicle intelligent control. The method is used for solving the problems of one-sided working condition sensing, switching oscillation and safety fault tolerance deficiency in multi-mode driving. The method comprises the following steps: firstly, generating a dynamically weighted working condition feature vector through multi-source sensing data fusion, and quantifying a stability risk, an energy consumption constraint and a power demand; secondly, based on a stability risk trigger steering safety envelope, arbitrating a multi-mode priority and correcting a torque upper limit in combination with a fuzzy rule to form an anti-conflict execution sequence; then, torque distribution and a steering angle acceleration instruction are optimized in a rolling mode in the safe envelope boundary, center-of-gravity shift is synchronously restrained, the track precision is improved, and energy consumption is reduced; finally, the control authority is transferred adaptively according to the operation intensity of a driver, when the decision is abnormal, the load-ramp rule base is degraded, an instruction is transferred through an S-shaped curve, and a torque balancing strategy is executed at the high position of a pallet fork to maintain stable.

The invention relates to the technical field of aerocar mode switching, and discloses a distributed driving aerocar self-adaptive fault-tolerant control method for actuator multimode failure, which comprises the following steps: constructing a unified six-degree-of-freedom dual-mode state space model; residual signals are generated based on extended Kalman filtering and a sliding-mode observer, and fault types and positions are positioned in real time through a lightweight classifier; the method comprises the following steps: extracting residual time-frequency features, identifying hard faults by using a lightweight convolutional neural network, quantifying soft fault degrees through an incremental support vector machine, fusing multi-source information based on a Bayesian network to output fault types, levels and confidence coefficients, and introducing an incremental learning mechanism to realize self-evolution of a diagnosis model; a virtual control instruction is generated by adopting hierarchical sliding mode control, thrust and torque distribution of remaining actuators is optimized based on a dynamic quadratic programming algorithm, control parameters are adjusted online in combination with a Lyapunov adaptive law, aerodynamic interference and model uncertainty are inhibited, attitude stability and trajectory tracking in air-ground mode switching are guaranteed, and the method has the advantages of being high in reliability and high in reliability. And the fault-tolerant performance and the operation safety of the hovercar in the air-ground mode switching process are obviously enhanced.

The invention discloses a chassis coordination control method and system based on tire side deviation state evaluation, and relates to the technical field of four-wheel steering four-wheel drive vehicle dynamics control. The method comprises the steps that an expected front wheel rotation angle is determined based on an expected steering wheel rotation angle input by a driver, and a front wheel rotation angle is determined; further determining a feed-forward front wheel steering angle, a feed-forward rear wheel steering angle and an additional yaw moment based on feed-forward control and feedback control, determining a first tire slip angle and a second tire slip angle based on a road adhesion coefficient, and further determining a wheel torque control weight, a feedback front wheel steering angle control weight and a feedback rear wheel steering angle control weight; and further determining a driving yaw moment, a feedback front wheel steering angle and a feedback rear wheel steering angle, determining a total longitudinal force based on an expected longitudinal acceleration input by a driver, and performing four-wheel torque distribution based on the total longitudinal force and the driving yaw moment to obtain a four-wheel driving torque. The driving stability of the vehicle under the limiting working condition can be improved.

The invention discloses a vehicle stability adaptive control method under low attachment road surface multi-source interference, and belongs to the field of vehicle control, and the method comprises the following steps: S1, multi-source interference perception and attachment coefficient prediction; s2, dynamic correction of tire dynamic parameters: correcting tire cornering stiffness and slippage stiffness on line; s3, multi-source interference collaborative observation and estimation: dynamically estimating an interference source by using an enhanced extended state observer; s4, phase plane stability envelope analysis and weight adjustment: dynamically allocating control priorities; and S5, on the premise of considering an interference source, performing dynamic torque distribution and actuator cooperative control: optimizing four-wheel torque by using a quadratic programming algorithm to obtain a torque distribution result. By adopting the vehicle stability adaptive control method under the low-attached road surface multi-source interference, the problems of insufficient modeling precision, weak interference suppression, target conflict and redundancy deficiency in low-attached road surface vehicle stability control are solved, and the trajectory tracking precision and the yaw stability are remarkably improved.

The invention discloses a high dynamic response control method and system for a linear actuator of a humanoid robot, and the method comprises the steps: collecting the pressure and moment data of a contact point, carrying out the data preprocessing and signal calibration processing, and obtaining the calibration pressure and moment data; based on the calibrated pressure and torque data, performing high-frequency signal extraction to obtain dynamic change characteristics, and performing distribution diagram construction in combination with the pressure and torque data to obtain a pressure distribution diagram and a torque distribution diagram; performing data fusion processing according to the pressure distribution diagram and the torque distribution diagram, generating real-time contact area distribution, and performing dynamic prediction model construction based on the pressure and torque data to obtain a dynamic prediction model; according to the dynamic prediction model, actuator output force and joint angle adjustment amount are calculated, output torque and angle compensation amount are generated, torque distribution optimization and force feedback compensation are carried out, and an optimized final control signal is obtained. According to the method, high-dynamic response control of the controller can be realized.

The invention relates to a speed planning optimization method and system for industrial robot repeated path operation, and the method comprises the steps: carrying out the constraint iterative learning speed planning based on path arc length coordinates, building a precise rigid-flexible coupling dynamic model of a robot, and obtaining the motion constraint condition of the robot; calculating the speed planning motion performance of the robot through the motion performance evaluation function, and updating the parameters of the motion performance evaluation function based on a dynamic linear scaling mechanism; an intelligent iterative learning mechanism based on arc length coordinate parameterization, dynamic constraint on-line satisfaction and provable monotonic convergence performance is realized through an updating law of an iterative learning motion performance evaluation function; and outputting the optimal speed curve of the robot. Track deviation, vibration data and energy consumption characteristics are automatically recorded when a task is executed each time, the root of a problem is autonomously analyzed, key parameters such as an acceleration curve and joint torque distribution are dynamically adjusted, and dependence on manual parameter adjustment in repeated operation is eliminated.

The invention discloses a distributed driving automobile control method. The method comprises the steps that 1, dynamic parameters of an automobile are collected in real time, and the equivalent adhesion coefficient of each wheel is calculated; 2, dividing types and optimizing torque distribution according to pavement adhesion coefficients: respectively adopting priority, uniform and dynamic weight distribution strategies for low, high and asymmetric pavements; 3, establishing a multi-objective optimization model, and solving an optimal torque distribution scheme considering the tire utilization rate and the yaw stability by using a quadratic programming algorithm; 4, compensating a torque error and motor response delay by adopting sliding mode control and a feedforward-feedback mechanism; and 5, the control parameters are dynamically corrected based on errors of the longitudinal acceleration and the yaw velocity, and torque limiting or safety mode switching is triggered. Through multi-strategy collaborative optimization, the stability and driving efficiency of the vehicle under different attachment road surfaces are improved, the tire slipping risk is reduced, and driving safety under extreme working conditions is guaranteed.

The invention relates to the technical field of forklift control, and discloses a refrigeration house unmanned forklift anti-skid control method and system based on multi-sensor fusion, and the method comprises the steps: synchronously collecting wheel angular velocity, vehicle body inertia data, motor current, vibration and acoustic signals through a multi-mode sensor, and carrying out the time alignment and feature extraction; inputting a time-space diagram neural network to estimate the friction coefficient and the optimal slip rate of each wheel in real time; and in combination with model predictive control, four-wheel independent torque distribution is optimized in a rolling manner under the condition that physical constraints are met, so that high-precision tracking and dynamic stability are realized. The system comprises a data acquisition module, a data processing module, a friction estimation module, a torque distribution module and an execution module. The attachment change can be sensed in advance, and the safety, efficiency and operation precision of the unmanned forklift in the wet and slippery refrigeration house environment are improved.

The invention provides a tractor semitrailer full-working-condition active stability control system and method, and belongs to the technical field of vehicle engineering. The system comprises a kinetic model module, a reference quantity determination module and an active stability controller module. The dynamic model module constructs a linear three-degree-of-freedom tractor semitrailer model, a hub motor model and a longitudinal driver model. The reference quantity determination module generates an ideal state value according to the steady state condition of the system and corrects the ideal state value in combination with the road attachment condition. The active stability controller module is divided into three layers, an MIMO-IMFAC controller calculates additional yawing moment, a torque optimization controller optimizes tire load distribution through a quadratic programming algorithm, and a driving / braking torque distribution controller preferentially uses regenerative braking and dynamically adjusts braking torque of the semitrailer according to the yawing moment. By adopting the control system and the control method, the stability and the dynamic response capability of the vehicle under complex working conditions are remarkably improved.

The invention provides a new energy light truck energy distribution method and system, and the method comprises the steps: obtaining the position and track of a vehicle to obtain the road section data of a current driving road section, carrying out the data preprocessing of the road section data, and carrying out the fusion of the preprocessed data, so as to obtain the current load and driving state of the vehicle; inputting the preprocessed data into an initial energy consumption model, introducing a deep learning algorithm to dynamically adjust model parameters of the initial energy consumption model to obtain an iterated target energy consumption model, and obtaining energy consumption coefficient data according to the target energy consumption model; and a motor torque demand curve is generated in real time according to the current load, the road slope and the predicted endurance mileage, torque distribution data are adjusted in combination with an adaptive algorithm, the adjusted torque distribution data are transmitted into a vehicle power control system to obtain real-time operation data of the vehicle, and then energy distribution is conducted on the new energy light truck. According to the invention, the endurance prediction precision is improved, and the real-time adaptive optimization of torque distribution control is realized.

The invention relates to the technical field of new energy automobile electric control, and discloses a torque compatible intelligent matching system and method for a new energy automobile, and the system comprises a parameter pre-storage module, an EOL configuration module, a dynamic selection module, a data collection module, a torque calculation module, and an execution output module. A driving system configuration identifier is written in through a vehicle production line EOL terminal to realize hardware adaptation selection; an eagle optimization algorithm is innovatively integrated and improved to construct a historical driving database, an output proportion table is periodically adjusted to improve the driving smoothness, and meanwhile a supplier batch compensation mechanism is established to solve the hardware tolerance problem; fault grading processing is achieved through parameter table dual redundancy check, and torque distribution efficiency is continuously optimized in combination with a full-life-cycle closed-loop self-learning module. According to the scheme, the development cost adaptive to different power systems is reduced, and the core pain points of poor multi-source hardware compatibility, weak working condition adaptability and extensive energy efficiency management of the new energy automobile are solved.

The invention relates to the technical field of vehicle braking control, and discloses a vehicle braking control system based on a high-speed permanent magnet synchronous motor, which comprises a state sensing module, a braking force calculation module, a braking force control module and a braking force control module, the torque distribution module distributes the total braking torque into a predictable regenerative component and a precisely matched friction component, a deterministic regenerative braking force datum line is established, a braking system is converted into stable output control from passive response energy fluctuation, and linear mapping of pedal travel and deceleration is achieved; and meanwhile, by combining road bumping degree perception and model online correction, the output stability is kept under the complex working condition, and the technical problem that energy recovery and control quality in a hybrid braking system are difficult to consider at the same time is solved.

The invention provides a vehicle torque distribution method and a double-electric-drive-axle vehicle, and relates to the technical field of new energy automobiles. The method is applied to a vehicle controller of a double-electric-drive-axle vehicle and comprises the steps that actual operation parameters of two motors in the double-electric-drive-axle vehicle are obtained; the total demand torque of the double-electric-drive-axle vehicle is obtained; according to the total demand torque and the actual operation parameters of each motor, the demand power of each motor under the multiple preset distribution coefficients is calculated; determining the corresponding total demand power according to the demand power of each motor under the plurality of preset distribution coefficients; determining a target distribution coefficient from the plurality of preset distribution coefficients according to the total demand power corresponding to the plurality of preset distribution coefficients; and performing torque distribution control on the two motors by adopting the target distribution coefficient according to the total demand torque. The target distribution coefficients of the motors are dynamically determined, then the two motors are controlled, the overall energy efficiency of the vehicle reaches the optimal level, energy efficiency waste is avoided, and the driving experience is improved.

The invention relates to the technical field of driving control, and discloses a somatosensory driving control method and system of a scooter. The method comprises the following steps: acquiring an original somatosensory signal of the scooter; performing resonance amplification and multi-mode frequency mixing on the original somatosensory signal to obtain a somatosensory characteristic signal; establishing a scooter-rider coupling system dynamic model based on the somatosensory characteristic signal, and performing real-time state calculation to obtain a current state parameter and a state deviation value; performing motion sensing body weight distribution change mapping conversion on the current state parameter and the state deviation value to obtain a riding control demand parameter; and calculating a real-time driving control signal sequence according to the riding control demand parameters, and carrying out front and rear wheel motor torque dynamic distribution on the real-time driving control signal sequence to obtain a target motor driving execution instruction set. The problem of delay in traditional somatosensory control is eliminated, and safe and stable motor driving control is realized by combining dynamic torque distribution and a safety monitoring mechanism of road adhesion conditions.

The invention belongs to the field of distributed driving automobile control, and discloses a distributed driving automobile path tracking and stability control optimization method and related equipment, and the method comprises the steps: firstly building a tire cornering stiffness dynamic range through multi-source sensing data, and reducing the influence of nonlinear characteristics on a model; then, through a dynamic output feedback model prediction control algorithm, an estimation state sequence and an error boundary of a vehicle side slip angle are calculated online, an optimal control gain is matched in real time based on a two-dimensional table, a combined control quantity of a four-wheel steering angle and an additional yawing moment is formed, and parameter uncertainty caused by vehicle speed change is effectively compensated; and finally, torque distribution is carried out by adopting a quadratic programming algorithm and taking tire utilization rate minimization as a target. According to the method, the vehicle path tracking precision and the transverse stability under the complex working condition are improved, meanwhile, the tire saturation risk is reduced, the tire utilization rate is reduced, the transverse tracking error is reduced, and unified optimization of safety and controllability in the automatic driving process is achieved.

The invention belongs to the field of vehicle stability control, and particularly relates to a control method suitable for integration of four-wheel independent drive and active rear wheel steering. Comprising the steps of establishing a whole vehicle dynamics model suitable for controller design, performing stable region division by combining front and rear wheel side slip angle phase planes, setting an ideal yaw velocity and an ideal side slip angle, designing a feedforward and PID feedback integrated controller, performing torque distribution and the like. According to steering wheel rotation angle input, corresponding parameters of the vehicle are combined, the vehicle stability coefficient, the ideal yaw velocity and the side slip angle are calculated, the feedforward and PID feedback integrated controller inputs the calculated rear wheel rotation angle into the controlled vehicle, the calculated additional yaw moment obtains the basic driving moment based on pedal information, and the vehicle stability coefficient, the ideal yaw velocity and the side slip angle are calculated. Torques corresponding to four wheels are input to a controlled vehicle through torque distribution, so that the purpose of integrated control is achieved, and the vehicle handling stability is improved.

The invention discloses an industrial robot collaborative optimization system, which relates to the technical field of humanoid robots and comprises a joint state acquisition module for acquiring joint torque, angular velocity, acceleration and external disturbance data in real time; the joint first constraint analysis module is used for decomposing a motion task into a high-level task and bottom-level joint control, introducing joint limiting and torque saturation constraint, solving joint optimal torque distribution through QP quadratic programming, and obtaining a first joint torque distribution result; the second joint constraint analysis module is used for designing a multi-objective optimization function based on the first joint torque distribution result and a humanoid robot joint real-time state database, carrying out weight self-adaption according to the humanoid robot joint real-time state database, synthesizing the weight of the multi-objective optimization function according to a dynamic weight, and obtaining a second joint torque distribution result; and solving an optimal joint angle, speed and moment sequence to obtain a joint moment optimal distribution result. Joint abrasion can be effectively reduced, and meanwhile task adaptability and energy efficiency optimization are enhanced.

The invention provides a vehicle stability control method, device and system and electronic equipment, relates to the technical field of vehicle active safety control, and aims to construct a control framework based on a two-degree-of-freedom dynamical model and realize accurate control of the yaw velocity and the side slip angle of a vehicle. By introducing the road adhesion coefficient and combining the vertical load of each wheel for independent torque distribution, the tire adhesion utilization rate and the environmental adaptability and safety of the vehicle under different road conditions (such as ice and snow, wet and slippery conditions and dry conditions) are improved. According to the scheme, calculation is easy and convenient, response is rapid, good engineering practicability is achieved, and the robustness and adaptability of the system under the complex working condition are enhanced while the vehicle stability and the path tracking capacity are improved.

The invention provides a distributed driving vehicle preset performance fault-tolerant control method and system based on an adaptive neural network observer. The method comprises the following steps: constructing a vehicle dynamics model containing motor faults and unknown disturbance; in order to realize real-time estimation of faults and disturbance and break through the limitation on disturbance derivative boundaries, a self-adaptive neural network observer is designed; aiming at the problem that the control direction is uncertain, an upper-layer controller is designed based on a preset performance control theory, a Nussbaum function and an obstacle Lyapunov function are introduced, it is ensured that system dynamic errors meet preset performance constraints all the time, and accurate tracking control over the transverse force, the longitudinal force and the yawing moment of a vehicle is achieved; in order to improve the system coordination capability under the multi-motor fault working condition, an optimal torque distribution model fusing the motor torque constraint and the tire force limit is constructed, collaborative optimization control of the driving and steering system is realized through a quadratic programming algorithm, and the stability and safety of the whole vehicle in the fault state are improved.

The application discloses a kind of distributed drive electric vehicle stability control method and system, desired centroid side slip angle and yaw angular velocity are calculated as control target according to vehicle dynamics model, actual centroid side slip angle and yaw angular velocity are estimated in real time by Kalman filtering.Further through stability judging law, vehicle state is identified using phase plane method.According to vehicle state, it is divided into: stable domain, coordination domain and non-stable domain.Further control target value and actual value are input into model reference adaptive controller, and the size of additional yaw moment and front wheel angle is respectively solved.The weight size of the two is calculated by the vehicle stability region determined in stability law.Additional front wheel angle can be directly input into vehicle actuator, if direct torque control is needed, additional yaw moment size needs to be input into torque distribution module for real-time solution, and finally left and right wheel torque value of front axle is output to vehicle actuator.

Disclosed in the present application is a torque vectoring control system for an in-wheel-motor four-wheel-drive vehicle. In the torque vectoring control system, a driving style identification module determines the driving style of a driver during the travel of an in-wheel-motor four-wheel-drive vehicle; a vehicle state sensing module acquires a steering wheel angle and a longitudinal vehicle speed in real time, and performs fault state monitoring on the in-wheel-motor four-wheel-drive vehicle; a vehicle motion control module calculates an ideal yaw rate target of the in-wheel-motor four-wheel-drive vehicle; and a torque vectoring control module calculates an additional yaw moment on the basis of the ideal yaw rate target and an actual yaw rate, executes a corresponding fault handling strategy on the basis of a fault state monitoring result, and then performs torque distribution on the basis of the additional yaw moment combined with the fault state monitoring result to generate an additional driving torque and an additional braking torque of each wheel. The present application realizes self-adaptive yaw stability control for drivers having different driving styles.

The invention relates to the technical field of closed-loop drift control, and particularly discloses a closed-loop drift control method and system for an autonomous vehicle in an uncertain environment, and the method comprises the steps: building a vehicle kinematic model based on a Frenet coordinate system, and constructing an MPC path tracking controller with a preview mechanism; establishing a three-degree-of-freedom vehicle dynamics model with additional yawing moment; the method comprises the following steps: establishing a UniTile-Ctrl tire dynamic model; designing a robust drift controller by combining LQR and integral sliding mode control on the basis of the whole vehicle dynamic model and the tire dynamic model, designing a torque distribution module by taking minimization of distribution error and tire load utilization rate as targets on the basis of ideal rear wheel rotating speed and additional yawing moment output by the robust controller, and outputting a torque distribution model; according to the drifting vehicle tracking control method, closed-loop drifting control can be achieved, the drifting vehicle tracking control performance and robustness are improved, and safety guarantee is provided for limit control over the uncertain road surface of the vehicle.

A vehicle and a control method and apparatus therefor, a storage medium, and a computer program product, relating to the technical field of vehicles. The control method for a vehicle comprises: correcting an ideal yaw rate on the basis of desired steering characteristic information; obtaining an additional yaw moment on the basis of an ideal sideslip angle, the corrected ideal yaw rate, and an actual sideslip angle and an actual yaw rate of a vehicle; and performing torque distribution on the basis of the additional yaw moment. In the method, the ideal yaw rate is corrected on the basis of the desired steering characteristic information, so that, on the basis of the ideal sideslip angle, the corrected ideal yaw rate, and the actual sideslip angle and the actual yaw rate of the vehicle, variable steering characteristics of the vehicle are achieved by means of torque control, thereby enabling the vehicle to obtain higher steering sensitivity.

The invention relates to the field of power control, and particularly discloses an electric four-wheel drive torque distribution method based on a climbing working condition, which comprises the following steps: defining vehicle state parameters, power system parameters, vehicle real-time driving state parameters and road condition parameters; carrying out torque calculation by utilizing Julia, considering shaft load, friction coefficient, motor efficiency and yaw velocity correction, obtaining a comprehensive weight of a front shaft and a rear shaft, and carrying out normalized torque distribution; and establishing model simulation through Modelica, and verifying the effectiveness of the distribution scheme. According to the invention, the climbing performance of the vehicle can be improved, the control flexibility and driving stability of the vehicle are improved, the energy consumption is reduced, the dynamic stability is enhanced, and the method is suitable for power control of the electric four-wheel-drive vehicle under the climbing working condition.

The invention discloses a pivot steering control system and method based on a four-wheel steering driving automobile and the automobile, and belongs to the technical field of automobiles. The in-situ steering control system obtains the state information of a vehicle through the state observation module, and the algorithm decision-making module receives the state information sent by the state observation module and then carries out decision-making calculation output processing according to the state information. And a pivot steering control decision containing a wheel steering angle adjusting instruction and a wheel output torque adjusting instruction is obtained, so that the four wheels are controlled to deflect by specific directions and angles through the control execution module, driving is conducted according to the deflection angles of the vehicles in the specific directions, and pivot steering control over the vehicles is achieved. The in-situ steering control system can dynamically adjust steering angles and torque distribution of the four wheels according to actual driving working conditions, the accuracy and response speed of in-situ steering control are improved, and the vehicle can accurately achieve in-situ steering according to an expected posture.

The invention discloses a distributed driving ideal yaw target setting and stability control method, which comprises the following steps of: establishing a whole vehicle dynamics model suitable for controller design, inputting related parameters through a vehicle, combining front and rear wheel side slip angle phase planes, carrying out region division of a stable state, and carrying out target setting and stability control on the whole vehicle dynamics model. According to the method, maneuverability and stability analysis and setting are carried out on the yaw velocity, the yaw velocity is fused, steady state control and feed-forward control are generated through the first step and the second step of a three-step method, then feedback control is carried out through an LQR controller, finally, the three quantities are superposed to obtain the needed additional yaw moment, reasonable distribution control is carried out based on the additional yaw moment, and the control precision is improved. The method aims at minimizing the distribution error and reducing the tire load utilization rate, adopts a multi-target optimization torque distribution strategy to distribute the four-wheel torque, and controls the four-wheel torque of the vehicle so as to achieve the purpose of distributed driving control.

The invention relates to the technical field of forklift control, in particular to an efficient and energy-saving off-road forklift electric drive system and a control method. Multi-source data is collected through a multi-source sensor, and data preprocessing is carried out; outputting a control decision instruction according to a priority decision rule based on the preprocessed data in combination with a fuzzy logic algorithm; in combination with the working condition characteristics and the real-time data, dynamic parameter adjustment is performed on the rotating speed, the torque and the current parameters of the motor by utilizing a reinforcement learning framework, and a PWM duty ratio control instruction is generated; on the basis of a PWM duty ratio control instruction and a hydraulic pressure signal fed back by a hydraulic system, the same-frequency anti-phase compensation torque is calculated, a signal is injected to suppress fluctuation, and torque distribution and hydraulic flow are adjusted through a ramp function; and establishing a hierarchical health early warning mechanism according to the historical data, judging the current early warning level, and outputting a maintenance strategy instruction according to the early warning level. According to the scheme, equipment health management and stability are enhanced through reinforcement learning dynamic optimization and graded early warning.

The invention relates to the technical field of vehicle control, in particular to a torque distribution control method for a four-wheel-drive pure fuel vehicle, which comprises the following steps of: 1) acquiring data by using a plurality of sensors, and performing data fusion processing on the acquired data; (2) according to the fused data, the real-time road condition of the vehicle is obtained, and the current vehicle driving mode is judged; and 3) distributing the torque of the front and rear wheels of the vehicle according to the real-time road condition and the vehicle driving mode. Power distribution (namely torque distribution) is intelligently regulated and controlled by accurately sensing road conditions and driving requirements, so that the fuel economy is considered while the driving stability and controllability of the vehicle under complex road conditions can be greatly improved, and a safer, more efficient and more comfortable driving environment is created for a driver.

The invention discloses a plug-in hybrid power bus energy management system and method based on extremum search, and the method comprises the steps: initializing a management system, specifically, initializing a threshold parameter initial value; outer-layer extremum searching is carried out based on current input data to obtain global reference parameters, and the input data comprise current outer-layer reference parameters and complete driving period working condition data; performing inner-layer extremum search on the basis of the global reference parameter in combination with the driving condition of the current road section to obtain an adaptive threshold parameter of each road section; vehicle energy management, including mode switching, torque distribution, and battery management, is performed based on global reference parameters and / or adaptive threshold parameters in combination with real-time vehicle states. According to the method, the limitation of a traditional method based on a fixed parameter rule is overcome, meanwhile, low calculation requirements, high reliability and nearly optimal performance are achieved, and the deployment feasibility in large-scale mass production of vehicles is ensured.