767 results about "Torque distribution" patented technology

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 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 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 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 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 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.

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 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 multi-power platform control, in particular to a platform multi-power output driving system and a driving output method. The driving output method comprises the following steps: monitoring a current multi-power unit state in real time, acquiring parameters, preprocessing parameter data, and outputting current acquired data; dynamically acquiring real-time required power of each power unit according to the current acquired data, adjusting an output torque distribution proportion of each power unit, and outputting distribution data; dynamically adjusting the output power of the power unit for different terrain types according to the current ground condition data; the driving system comprises a current parameter data acquisition module, an output torque distribution module and an output power dynamic adjustment module. By means of the mode, dynamic load changes under complex terrains are dealt with, and power waste is avoided.

The invention discloses a wheel-foot composite robot and a motion control method thereof, a terminal and a storage medium, and the motion control method of the wheel-foot composite robot enables the wheel-foot composite robot to have remarkable robustness and dynamic stability in a complex environment by performing self-adaptive control on a four-foot form and a two-wheel form under a unified control framework. The method specifically comprises the following steps: identifying a current motion form, and performing real-time integral estimation on an error between an expected state and an actual state by using a robust adaptive model predictive control algorithm in a four-foot form to obtain an equivalent external disturbance vector for control solution, thereby realizing online disturbance compensation and adaptive torque distribution. The robot has stronger anti-interference capability on load change and ground disturbance in a four-foot form, and can keep stable gaits and accurate attitude control under a relatively high load condition.

The invention relates to an automobile finite time path tracking fault-tolerant control method considering steering actuator faults. The method comprises the following steps: firstly, establishing a vehicle dynamics model and a steering execution mechanism dynamics model, designing a path tracking control strategy by applying a model prediction control method, and establishing an upper-layer path tracking controller; then, on the basis of a differential driving auxiliary steering principle, a preset performance control method of finite time convergence and a nonsingular fast terminal sliding mode control theory are combined, and a steering actuator fault-tolerant controller is established; and finally, designing a torque distribution controller by adopting an optimal control theory, and solving an optimal four-wheel driving torque control quantity through quadratic programming. According to the method, the influence caused by the failure of the steering actuator can be effectively compensated, the safety and the stability of the vehicle are remarkably improved, and a feasible solution is provided for the fault-tolerant control of the steering actuator in a future intelligent vehicle path tracking scene.

The invention provides a cooperative control method and system for an electric trailer and a main vehicle and a vehicle, and relates to the technical field of new energy vehicles and intelligent control. The method comprises the steps that the states of a main vehicle and an electric trailer are obtained, and when the states meet preset state conditions, a driving mode is entered; in the driving mode, the main vehicle electric driving system and the electric trailer electric driving system are controlled to output driving torque based on the torque required by a driver and a torque distribution strategy; acquiring a braking request signal and mode switching information; if the braking request signal indicates that the multi-stage energy recovery switch is pressed down or the brake pedal is stepped down and the mode switching information meets a first switching condition, switching to a braking mode; if the mode switching information meets a second switching condition, switching to a driving mode; and in the braking mode, the main vehicle electric driving system and the electric trailer electric driving system are controlled to conduct braking energy recovery based on the required braking torque and the allowable recovery power of the battery. The control efficiency and the system adaptability are improved.

The invention discloses a double-electric-drive-axle tractor torque distribution method and device and a storage medium, and belongs to the technical field of vehicle dynamics control. The method comprises the steps that the gear and speed ratio of an intermediate axle gearbox controller, the gear and speed ratio of a rear axle gearbox controller and the current accelerator pedal opening degree are obtained; acquiring a required motor torque according to the current accelerator pedal opening degree; when the gears of the intermediate axle gearbox controller and the rear axle gearbox controller are consistent, the required motor torque is averagely distributed to an intermediate axle motor and a rear axle motor; and when the gears of the intermediate axle gearbox controller and the rear axle gearbox controller are not consistent, the required motor torque is distributed to an intermediate axle motor and a rear axle motor based on the speed ratio of the intermediate axle gearbox controller and the rear axle gearbox controller. The technical problem that when double electric drive axles are adopted for driving in the prior art, wheels of a middle axle or a rear axle slip in the running process, and vehicle maneuverability and driving safety are affected can be solved.

The invention discloses a suspension pitching cooperative control system and method combining dynamic vertical force distribution and multi-mode braking, and particularly relates to the field of vehicle suspensions. Meanwhile, the braking torque distribution unit and the suspension system are controlled in real time by defining a state machine; vehicle low-speed target braking torque and tire vertical force are calculated through the expected deceleration and correspondingly input into a braking torque distribution unit and a four-degree-of-freedom suspension model; converting the four-degree-of-freedom suspension model into a state-space equation and discretizing the state-space equation to obtain a prediction model, and further deriving a state prediction equation of the future N steps; designing a cost function comprising a state quantity weight matrix Q, an input quantity weight matrix R and a state final value weight matrix F, substituting a prediction state into the cost function to obtain an optimal input sequence, dynamically adjusting suspension rigidity, damping and a braking force distribution strategy, and correcting a control instruction in real time by using closed-loop feedback of a vehicle body attitude sensor, so as to improve the stability of a vehicle body. And the suspension pitching control is realized.

The invention provides a wheel torque distribution method, device and equipment and a vehicle, and is applied to the technical field of vehicle control, and the method comprises the steps: determining the structure perception characteristics representing the torque control priority of each wheel based on the current wheel state data, and determining the torque control priority of each wheel based on the wheel state data of a first preset time period until the current moment; and predicting the state of each wheel in a second preset time period after the current moment to obtain state prediction information of each wheel, performing torque distribution on each wheel based on the structure perception characteristics and the state prediction information, and determining the target torque of each wheel. The key driving wheel, namely the wheel with the highest torque control priority, can be effectively identified, so that the wheel torque is reasonably distributed in time, the intelligent distribution of the wheel torque is realized, the vehicle escape time and energy consumption are reduced, and the control precision is improved.

The invention belongs to the technical field of heavy-load vehicle control, and particularly discloses a bottom die trolley walking control method and system, and the control method comprises the steps: starting a task and setting parameters; collecting multi-dimensional data in real time; a displacement target is judged; calculating theoretical motion parameters; target torque distribution and instruction adjustment; and finishing the task and resetting the system. According to the control method, torque control, speed control, displacement control and energy consumption optimization are fused, a closed-loop feedback strategy, a fuzzy PID self-adaptive algorithm and a multi-motor cooperative algorithm are utilized, and track pre-detection and energy recovery are combined, so that the heavy-load and high-rigidity bottom die trolley can still run stably and accurately under the non-ideal track condition, and the control method is suitable for large-scale production. The control precision and stability of trolley running are remarkably improved, running deviation caused by poor rails and structural rigidity is reduced, the linear and dimensional precision of segmental beam prefabrication is guaranteed, and meanwhile the equipment failure rate, the maintenance cost and the energy consumption are reduced.

The invention relates to the technical field of intelligent robot control and artificial intelligence, and discloses a robot dynamic trajectory control method based on reinforcement learning and multi-sensor fusion, and the method comprises the steps: firstly fusing multi-modal sensor data through extended Kalman filtering, and predicting the time sequence distribution of dynamic obstacles through a long-short-term memory network; meanwhile, the dynamic operability and singularity risk factors of the robot are calculated, on this basis, a reinforcement learning network based on an attention mechanism is constructed to generate a high-level motion strategy, the high-level motion strategy is converted into a bottom-layer execution instruction through a variable impedance controller and a convex optimization torque distribution module, and singular points are avoided by using null-space characteristics. In addition, according to the method, model parameters are finely adjusted in real time by monitoring and predicting errors and the safety intervention degree on line. According to the method, organic fusion of logic decision and physical execution is realized through a layered architecture, and the operation safety, robustness and control precision of the robot in a dynamic environment are remarkably improved.

The invention relates to the technical field of vehicle power distribution, and discloses a multi-motor torque distribution method and a vehicle, and the method comprises the steps: determining an initial total torque demand according to a torque request and a first torque limit value of the vehicle at the current moment, and carrying out the smoothing of the initial total torque demand, so as to obtain a smoothed total torque demand; determining an initial torque distribution coefficient according to the smoothed total torque demand, the current vehicle speed of the vehicle and the driving mode, and smoothing the initial torque distribution coefficient to obtain a smoothed torque distribution coefficient; and second torque limiting values corresponding to the multiple motors are obtained, and the current torque distribution result of the multiple motors is determined according to the smoothed total torque requirement, the smoothed torque distribution coefficient and the second torque limiting values. The torque distribution strategy can be dynamically adjusted according to the limiting value conditions of various working conditions, the accuracy and flexibility of torque distribution are remarkably improved, and the power requirement and the driving stability of the vehicle can be considered.

The invention discloses a transverse movement control system and method based on rear wheel steering, a controller and a vehicle, and belongs to the technical field of vehicles. The transverse movement control system obtains state information of a vehicle through a state observation module, and after an algorithm decision module receives the state information sent by the state observation module, decision calculation output processing is conducted according to the state information, so that a transverse movement control decision containing a wheel steering angle adjusting instruction and a wheel output torque adjusting instruction is obtained. Therefore, the front wheels and the rear wheels are controlled by the control execution module to deflect by a specific angle in the transverse movement direction in the opposite directions and are driven reversely, and transverse movement control over the vehicle is achieved. The transverse movement control system can dynamically adjust steering angles and torque distribution of front and rear wheels according to actual driving working conditions, the accuracy and response speed of transverse movement control are improved, and the vehicle can accurately transversely move along an expected track.

The present application relates to the technical field of vehicles, and provides a vehicle mode control method, a storage medium and a vehicle. In an embodiment of the present application, first, when a vehicle is in a power-split mode, an initial output power of an engine is determined, and a target torque distribution mode is determined on the basis of first working condition information of the vehicle; then, second working condition information corresponding to the target torque distribution mode is acquired, and a target engine torque and a target engine rotating speed of the engine are determined on the basis of the second working condition information and the initial output power; finally, the engine is controlled to operate according to the target engine torque and the target engine rotating speed. An embodiment of the present application, when the vehicle is in the power-split mode, can match an appropriate target torque distribution mode, and calculate a target engine torque and a target engine rotating speed matching a working condition the vehicle is in, so that the engine can meet driving requirements under various working conditions, thereby effectively improving a user's driving experience.

The invention relates to the technical field of central differential adjustment, in particular to a torque distribution optimization-based central differential dynamic adjustment method, which comprises the following steps of: predicting a driving state based on a vehicle dynamics model and generating a feedforward torque distribution reference instruction; monitoring the rotating speed difference of front and rear drive axles in real time and generating a feedback torque correction instruction; the feedforward instruction and the feedback instruction are superposed to generate a total torque distribution instruction, and a central differential mechanism is controlled to execute inter-axle torque distribution; when it is detected that an individual wheel slips, the control system cooperates with an electronic stability program controller to work, and a total torque distribution instruction is dynamically adjusted by interacting a cooperation request and braking state information so as to achieve accurate distribution of driving torque to the best attached wheel; and meanwhile, the temperature of the multiple clutches is monitored in real time, predictive thermal management control or system protection strategies are executed in a graded mode according to temperature threshold values, and the reliability and durability of system work are ensured.

A brake system (10) comprising: a brake caliper (12) supporting a brake pad (14), and having a first brake piston (24) and a second brake piston (28) that are configured to move the brake pad; a first rotary to linear stage mechanism (32) connected to the first brake piston, and a second rotary to linear stage mechanism (34) connected to the second brake piston; a motor (42) configured to generate torque; a torque distributing assembly (40) configured to receive torque from the motor and then distribute the torque from the motor to the first rotary to linear stage mechanism to move the first brake piston and / or to the second rotary to linear stage mechanism to move the second brake piston; wherein the torque distributing assembly comprises: i) a first driving gear (44) connected to the first rotary to linear stage mechanism; ii) a second driving gear (46) connected to the second rotary to linear stage mechanism; iii) a first set of planet gears (72) supported on respective first axles (74); iv) a second set of planet gears (98) supported on respective second axles; and v) a first carrier plate (88) having a plurality of support features each configured to support a respective one of the first axles and a respective one of the second axles.