78 results about "Motor dynamics" patented technology

The invention discloses a servo motor dynamic overload detection and protection method based on a heat accumulation model, which relates to the technical field of servo system fault protection application, and comprises the steps of constructing a heat accumulation equivalent model, dynamically detecting an overload state, executing a heat dissipation recovery strategy, implementing a multi-stage protection mechanism, self-adaptive environment compensation and a historical data learning function. Through discretization processing of overload curve data and a nonlinear acceleration calculation strategy, the problems of protection lag and false triggering caused by traditional single-parameter detection are avoided, it is ensured that the motor can respond in time in light load, heavy load and load fluctuation scenes, the burn-out risk of the motor is reduced, and through integration of an environment temperature sensor and a heat dissipation condition evaluation unit, the reliability of the motor is improved. The heat accumulation coefficient and the heat dissipation attenuation parameter are dynamically adjusted, the problem of model deviation caused by environment interference is solved, when heat dissipation deterioration and temperature feedback abnormity are detected, the heat dissipation recovery period is automatically prolonged, calculation logic is corrected, and the continuous operation reliability of the system is improved.

The invention discloses a robot dynamics physical information prediction neural network construction method based on motor and external force coupling, and relates to the technical field of robots. Comprising the following steps: embedding a motor kinetic equation into a DeLaN network, and establishing an explicit dynamic mapping relation between a system motion state and a motor current through mapping between the motor current and a joint torque; introducing an external force item by fitting a Jacobian matrix, and constructing approximate mapping of the Jacobian matrix by adopting a data driving method; and an initial model is constructed, and after motor dynamics and external force modeling are incorporated into the initial model, an inverse dynamics model of the mechanical arm is obtained. Compared with an existing most advanced method, the method has higher modeling precision and generalization ability and better control performance. The innovative scheme provides solid technical support for realizing real-time accurate control in the field of robots.

The invention discloses an early warning method and device for climbing instability of a crawler unmanned vehicle and a medium, and relates to the technical field of unmanned vehicle climbing control. The early warning method comprises the steps that a digital twin model of the tracked unmanned vehicle is constructed, the digital twin model fuses a motor dynamic model and a whole vehicle dynamic model, and virtual scene data is generated; real-time data of a multi-source sensor of the tracked unmanned vehicle are obtained, wherein the real-time data comprise vehicle posture data, environment data and driving system data; and constructing a time convolutional network prediction model based on transfer learning, performing pre-training by using virtual scene data as source domain data, and performing fine tuning by using real-time data as target domain data to form a target domain prediction model. And inputting the current data into the target domain prediction model, and outputting a predicted vehicle state parameter prediction sequence. According to the vehicle state parameter prediction sequence and a preset safety threshold value, the instability risk is evaluated, an early warning signal is sent out, and the generation logic of the early warning signal is evaluated and optimized through an early warning performance loss function.

The invention relates to the technical field of motor fault diagnosis, and discloses a multi-degree-of-freedom resonant excitation motor dynamic vibration test system and a test method, the system injects a specific harmonic current into a motor through closed-loop control and calculation and a high-bandwidth harmonic injection driver, so that the actual vibration of the tested motor tracks a preset target vibration profile in real time. In the testing process, the cross-spectral density of multi-point vibration signals is analyzed, and a transmission path and a collection area of vibration energy in a motor structure are calculated; and meanwhile, the electromagnetic impedance and the mechanical impedance of the motor are identified and decoupled on line by superposing a broadband disturbance signal in the driving current. In combination with energy flow analysis and an impedance decoupling result, the method can accurately position a vibration abnormal position, clearly causes whether a fault source is from mechanical structure characteristic change or electromagnetic part performance change from a physical level, and realizes deep and accurate diagnosis of the dynamic characteristics of the motor.

The invention discloses a real machine deployment method and device for a quasi-direct-drive robot for migration from simulation to reality, and the method comprises the steps: S1, driving each joint motor through a PD controller on a real machine of the robot to follow a plurality of groups of reference tracks, and synchronously collecting the real motion track data of each joint; s2, in a parallel simulation environment, performing initialization based on a random frame in a real motion track, randomly endowing a group of motor kinetic parameters, then driving a simulation robot through a PD controller by using the same group of reference tracks, and generating corresponding simulation motion track data; s3, based on a trajectory error between the two types of trajectory data, iteratively updating motor kinetic parameters by using an optimization algorithm until the error converges, thereby obtaining a calibrated simulator; s4, training a control strategy network of the robot through reinforcement learning in the calibrated simulator; and S5, directly deploying the control strategy network obtained by training to a real machine for performance evaluation and security verification.

The invention relates to the technical field of motor control, and discloses a vector control application of a direct drive motor, which comprises the following steps: S1, collecting stator current, rotor speed and bus voltage signals of the motor, and carrying out filtering preprocessing on the collected signals; and S2, constructing a self-adaptive flux linkage observation model, estimating a stator flux linkage in real time based on stator current and bus voltage signals in combination with rotor rotating speed information, and correcting stator resistance and inductance parameters through a model reference self-adaptive algorithm. According to the method, the motor parameters are corrected in real time through the self-adaptive flux linkage observation model, parameter drift caused by factors such as temperature change and magnetic saturation is effectively counteracted, and the accuracy of flux linkage estimation is improved; the improved PI regulator realizes online self-tuning of control parameters through a fuzzy control algorithm, can quickly adapt to changes of dynamic characteristics of the motor, and shortens the regulation response time of flux linkage and torque; and the resistance of the system to external interferences such as load fluctuation, power supply voltage change and the like is enhanced.

The invention relates to the technical field of motor testing, and discloses a motor dynamic characteristic compensation test method and platform based on multi-modal data, the method collects motor data through a multi-modal synchronous test system, and a processing module executes the following steps: constructing a state observer model to estimate winding temperature and loss torque; in the online test, the accuracy of the model is monitored by calculating the residual error between the model prediction and the measured value; and when the residual dynamic characteristic exceeds a threshold value, generating and applying an adaptive excitation sequence according to the residual characteristic, collecting high-resolution data to update model parameters on line, forming a self-optimization closed loop, after the test is finished, adopting a fixed interval smoothing algorithm to be combined with a final model to obtain a global optimal state track, and calculating a dynamic characteristic compensation result according to the global optimal state track. According to the invention, through adaptive excitation of residual error driving and online model updating, accurate identification and compensation of dynamic characteristics of the motor are realized, and the test automation level and accuracy are improved.

The invention relates to a braking control method for a distributed torque electric vehicle, a medium and equipment. The method comprises the steps that a control model of wheel rotation dynamics is established according to a vehicle resistance model and a longitudinal dynamics model, and regenerative braking torque of the electric vehicle is established according to the control model of the wheel rotation dynamics; a driving motor model of the vehicle is established, the regenerative braking torque of the electric vehicle serves as input of the driving motor model, and energy recovery of a driving motor is obtained; a braking system is improved based on motor braking force, and braking torque needed by a vehicle is distributed through energy recovery of a driving motor; and adjusting the braking torque of the front axle of the wheel and the braking torque of the rear axle of the wheel, and introducing a predictive control model. According to the method, the arithmetic optimization algorithm is adopted to optimize the performance index of the first stage and the performance index of the second stage, and real-time control and optimization of prediction errors are achieved.

The invention discloses a motor dynamic efficiency optimization regulation and control system, which relates to the technical field of dynamic efficiency optimization regulation and control and comprises a data acquisition module, an efficiency characteristic module, a health evaluation module, a state evaluation module, an optimization execution module and a parameter updating module. A comprehensive index comprehensively reflecting the running state of the motor is constructed, conversion from single efficiency optimization to system-level comprehensive optimization is achieved, a parameter updating module forms complete closed-loop control, the system can dynamically adjust key parameters according to the actual running effect, the self-learning and self-optimization functions are achieved, and the system reliability is improved. The system can dynamically adjust key parameters according to actual operation effects, has self-learning and self-optimization functions, realizes optimal balance of safety and economy through a multi-mode operation strategy, ensures equipment safety, and can dynamically optimize construction efficiency on the premise of safety.

The invention discloses an electric shovel lifting steel wire rope dynamic control device and method based on bucket lifting lug angle changes. The electric shovel lifting steel wire rope dynamic control device comprises a tilt angle sensor, a lifting motor and a whole vehicle controller. The tilt angle sensor is installed in a lifting lug of a bucket of the electric shovel and used for monitoring the dynamic change conditions of the axial tilt angle and the angular acceleration of the lifting lug in the operation process of the electric shovel in real time. A lifting motor dynamic control model established based on the data of the tilt angle sensor is configured in the vehicle control unit, the lifting motor dynamic control model analyzes the real-time posture information of the lifting lug according to the obtained data of the tilt angle sensor, and the tension state of the lifting steel wire rope is further recognized according to the real-time posture information of the lifting lug. And the lifting motor is dynamically controlled accordingly. The angle change of the lifting lug can be automatically monitored in real time, the lifting motor is dynamically adjusted, the fatigue fracture caused by overload of the lifting steel wire rope and the groove jumping overlying fault caused by looseness are effectively avoided, and the operation safety and reliability of equipment are remarkably improved.

The invention provides a preset performance control method and system under saturation of a train actuator, and relates to the technical field of train control, and the method comprises the following steps: building a train longitudinal motion kinetic equation based on the Newton second law; defining actual control input under saturation constraint of a train actuator, and establishing a dynamic compensation function in combination with a train longitudinal motion kinetic equation; designing a tracking error in the train operation process, and defining a filtering error in combination with a power compensation function; designing a preset performance function based on the train longitudinal motion kinetic equation and the filtering error, and defining an error conversion mechanism; constructing a preset performance control law based on the error conversion mechanism, and designing a parameter adaptive law to update the preset performance control law; and verifying the stability of the updated preset performance control law, and controlling the train operation by using the updated preset performance control law. Under the actual working condition of saturation constraint of the actuator, the tracking precision, the response speed and the overall stability of train operation control are remarkably improved.

The invention provides a shaftless drilling winch and an intelligent cooperative control and thermal management method thereof, and the method is implemented based on an embedded controller and a sensor network, and comprises the following steps: data real-time acquisition, intelligent lubrication heat dissipation control, dual-motor dynamic cooperative control, predictive maintenance management based on a health state, and fault tolerance and degradation operation. According to the system, efficient cooperative driving, on-demand accurate heat management and state-based predictive health maintenance of the winch are achieved, the problems that a traditional winch control system is poor in collaboration, extensive in heat management, lack of health management and the like are solved, and the safety, economical efficiency and modernization level of drilling operation are remarkably improved. According to the invention, the winch is changed from traditional mechanical equipment to intelligent equipment with self-sensing, intelligent decision making and active health management capabilities.

The invention discloses a cross arm and insulator installation robot motor control method based on a T-S fuzzy model, and the method comprises the following steps: building a permanent magnet synchronous motor nonlinear model according to electromagnetism and motor dynamics; based on a sector nonlinear method, establishing a permanent magnet synchronous motor T-S fuzzy model; designing an observer to obtain a load torque estimated value; designing an L-infinity robust controller to ensure that the angular velocity of the motor can track a reference instruction; and an anti-control gain matrix solving criterion is formulated, and it is ensured that the system meets performance indexes. According to the method, the nonlinear control problem of the permanent magnet synchronous motor system is effectively solved, the influence of continuous interference signals on the system can be effectively suppressed, and the robustness of the system is enhanced.

The application provides a motor dynamic control method, device, equipment and vehicle, which can determine different induced electromotive force voltages according to different operation parameters of a target motor, determine a maximum value of the induced electromotive force voltage allowed to appear in the current relay state, and further determine the maximum allowed speed of the target motor. Since the induced electromotive force voltage is constantly changing, the maximum allowed speed is also changing. The switching of the protection mode is performed according to the maximum allowed speed, the dynamic switching is realized, the safety of the motor is ensured, the maximum allowed speed corresponds to a higher vehicle speed, and the normal driving of the vehicle is not affected by limiting the vehicle speed according to the maximum allowed speed.

This application provides an adaptive control method, device, equipment, and medium for a permanent magnet linear synchronous motor, belonging to the field of permanent magnet linear synchronous motor control technology. The method involves: solving a first control law in real time based on motor dynamic characteristic data, motion characteristic data, error characteristic quantities, and a motion error convergence model. This first control law indicates the basic adjustment amount for controlling the motion error convergence of the mover when there is no disturbance, achieving rapid error convergence. Based on the error characteristic quantities and compensation function, compensation coefficients are generated in real time and smoothed using a saturation function to derive a second control law, which provides smooth and effective compensation when disturbances exist. Unlike existing technologies, this application can decouple multiple different control laws through the calculation of the first and second control laws, accommodating control requirements under different operating conditions and ensuring both motor control accuracy and system stability and robustness.

The application belongs to the technical field of motor thermal management and computer simulation, and is a motor dynamic thermal network parameter identification and modeling method for full working conditions, comprising the following steps: S1, constructing an equivalent thermal network model of a motor lumped parameter thermal network structure considering key heat dissipation interfaces; S2, establishing a nonlinear thermal resistance and thermal capacity mathematical model that dynamically changes with temperature; S3, based on virtual and real combination, constructing a combined dataset covering the full working condition domain; S4, using a double-layer hybrid optimization mechanism of sparrow search algorithm combined with a local optimization algorithm to jointly identify unknown parameters to be identified, finally determining the polynomial coefficients of multiple dynamic thermal network parameters, and completing the establishment of the dynamic thermal network model. The application significantly improves the motor full-temperature-zone prediction accuracy, conforms to the physical nature of the motor material and fluid heat dissipation changing with temperature, eliminates the prediction deviation of the traditional constant model in a wide temperature range, and ensures high calculation efficiency by using a simplified model.

The invention discloses a new energy automobile driving motor dynamic load testing method based on a digital twin technology, and relates to the technical field of motor load testing. Monitoring equipment is installed in a driving motor area needing load testing, and a dynamic monitoring network is constructed based on the installed monitoring equipment and a wireless communication mode; meanwhile, historical parameter data in a driving motor area are collected and processed based on the dynamic monitoring network, load test analysis is conducted on the processed historical parameter data after processing is completed, and load data of the driving motor are determined; meanwhile, based on the determined load data of the driving motor, the processed historical parameter data are tested and verified in a data verification mode, a motor load test model is determined, and after the motor load test model is determined, a motor load prediction model is constructed in a digital twinning mode; and carrying out real-time load test on the driving motor based on the motor load prediction model.

This invention relates to a hub-driven electric wheel structure with an integrated disc brake, comprising an electric wheel housing. Within the housing are an outer rotor of a motor, a motor stator, a ventilated brake disc, and an aluminum alloy inner brake caliper. A heat insulation device is provided between the outer circumference of the ventilated brake disc and the electric wheel housing, and a heat insulation baffle is provided between the ventilated brake disc and the motor dynamic seal. The aluminum alloy inner brake caliper is disposed within the inner circumference of the ventilated brake disc, forming a brake assembly. Compared with existing technologies, this invention effectively solves the problem of brake thermal management through structural integration and material innovation, improves motor reliability and system power density, and enables a lightweight, high-thermal-isolation hub-driven electric wheel.

The invention relates to a preset space repeated learning control method for aperiodic speed tracking of a rotating motor, and provides the preset space repeated learning control method for aperiodic speed tracking for the complex and changeable characteristics of speed tracking of the rotating motor, and the method comprises the following steps: introducing a space differential operator to establish a spatial domain rotating motor dynamic model; a speed tracking task is converted into an error tracking task by constructing an expected error trajectory related to a rotor position, and a preset space control law is designed, so that a speed tracking error is converged to an original point neighborhood at a preset position; and further designing a full-amplitude-limiting space repeated learning law, effectively compensating periodic uncertainty caused by the angular position, and realizing rapid and high-precision tracking control on the non-periodic expected angular velocity.

This invention discloses a series-parallel switching hydraulic-gas integrated force-controlled suspension system for automobiles and its usage method, belonging to the field of automotive suspension technology. This invention solves the problem that the adjustable frequency range of suspension systems is relatively low, and that they cannot simultaneously achieve rapid adjustment and wide-frequency vibration damping. Based on electromagnetic levitation technology, this invention sets up a magnetic levitation vibration reduction system, designing a series-parallel switching adjustment device between the hydraulic vibration absorption module and the electromagnetic levitation module. In series operation, the hydraulic vibration absorption module is actively adjusted by adjusting the valve opening size and changing the actuation speed and direction of the electromagnetic levitation module, enhancing its damping effect range. In parallel operation, the electromagnetic levitation module and the hydraulic vibration absorption module work independently. In this case, the electromagnetic levitation module can directly actuate between the sprung and unsprung masses of the vehicle, achieving vertical load-bearing and buffer limiting, and further reducing the output of its force-controlled motor dynamic load, thus improving overall energy efficiency.

The utility model discloses a variable displacement motor dynamic balance hydraulic system which comprises a main control loop and a stable branch, and the main control loop is communicated with an oil tank and a hydraulic cavity of a variable displacement motor and used for circularly supplying oil to drive the variable displacement motor to work. A hydraulic cavity of the variable displacement motor is communicated with the oil tank through the stabilizing branch, and the stabilizing branch is used for communicating an oil outlet of the hydraulic cavity of the variable displacement motor with an oil return connector of the oil tank according to the pressure difference of an oil inlet and an oil outlet of the hydraulic cavity of the variable displacement motor and used for reducing the temperature of flowing oil; the oil tank is further communicated with the oil supply side of the main control loop 1 through an oil supplementing branch. Dynamic balance in the working process of the variable displacement motor hydraulic system can be guaranteed, so that stable working is achieved, and the service life of the motor is prolonged.

The invention discloses a DC motor dynamic event trigger iteration interval generation method based on ellipsoid set membership estimation. According to the method, firstly, a coding-decoding scheme based on an event dynamic event trigger mechanism is designed to meet the limited bit rate limitation during network transmission, and then, an iteration interval generation method based on a trigger sampling signal is designed to estimate the state of the direct current motor and external interference and generate an interval. When the method is applied to the direct current motor, the interference estimation effect is good, the state interval generation is tight, and the limited bit rate limitation during transmission is met.

The invention discloses a multi-motor synchronous transmission cooperative device, which relates to the technical field of motor synchronous driving and comprises a plurality of motor output rods, a first transmission pair, a second transmission pair, a magnetic pole array, a fixed magnetic structure, an inner ring cooperative device and an outer ring cooperative device, according to the invention, efficient cooperation and dynamic adjustment of a multi-motor system are realized through an innovative structural design. The inner and outer ring annular structures are made of high-conductivity materials and cover the axial projection areas of the magnetic pole array magnetic blocks, low-speed motor torque compensation and high-speed motor dynamic loading are achieved through the eddy current effect, and the multi-motor load balancing capacity is remarkably improved. The annular array distribution of the motor output rods is combined with the transmission and cooperation device which is coaxially arranged, so that the symmetry and balance of power output are ensured, and the problem of vibration or unbalance caused by uneven distribution in a traditional multi-motor system is avoided.

The utility model provides a step motor dynamic torque measurement frock relates to electrode measurement equipment technical field, including bearing base and motor main part, bearing base top surface is equipped with L type support frame and telescopic guide frame respectively, and the top surface of L type support frame is equipped with positioning assembly, and the top end side of telescopic guide frame is connected and is equipped with monitoring disc, and the surface of monitoring disc is equipped with torque sensor, and the surface of monitoring disc is embedded and is equipped with guide ball, and the surface of monitoring disc is movably connected and is equipped with transmission torus, and the end of transmission torus away from monitoring disc is hinged and is equipped with flexible coupling, and the end of flexible coupling away from transmission torus is hinged and is equipped with the surface of motor's output shaft, and the multi -point torque sensor on monitoring disc is arranged flexibly through damping telescopic axle, can capture the torque change of different angle, overcomes the limitation of single point measurement, improves precision and data comprehensiveness greatly, provides convenient, efficient technical support for the performance analysis and quality detection of step motor, is especially suitable for research and development and production scene.

The invention provides a motor-oriented dynamic balance deviation adaptive compensation method and system, and relates to the technical field of motors, and the method comprises the steps: collecting a real-time radial vibration time domain signal and a real-time rotating speed signal after a target motor is started and enters a steady-state operation mode; calling a vibration fundamental frequency amplitude reference value and a vibration fundamental frequency phase reference value; amplitude-phase combined comparison is carried out, and the real-time dynamic balance deviation value is quantified; performing deviation time sequence backtracking analysis to obtain a dynamic balance deviation sequence; an intervention compensation decision is made, and a compensation current harmonic component sequence is output; and in the real-time compensation current harmonic injection process of the target motor, tracking closed-loop feedback characteristic parameters to perform dynamic correction. The motor dynamic balance compensation method solves the technical problems that a motor dynamic balance compensation method in the prior art mainly depends on physical static adjustment and cannot respond to dynamic changes of the running state of the motor in real time, vibration of the motor under different working conditions cannot be effectively controlled, and the fault occurrence risk is increased.

The invention discloses a motor dynamic filtering method based on wavelet transform, and relates to the technical field of motor control and signal processing, and the method comprises the following steps: S1, collecting an original angular velocity signal of a motor encoder, and dynamically storing the original angular velocity signal as a data curve; s2, performing frequency analysis on the data curve, and determining a maximum frequency and a target frequency; and S3, selecting a wavelet function, constructing a binary tree-shaped frequency division structure based on the maximum frequency and the target frequency, and performing logarithm and rounding down through the ratio of the maximum frequency to the target frequency. According to the motor dynamic filtering method based on the wavelet transformation, data frequency domain decomposition and reconstruction are achieved through the wavelet transformation, the real-time processing requirement and the data fidelity are effectively balanced, the problems of lagging and data distortion of a traditional filtering method in the aspect of real-time performance are solved, the binary tree-shaped frequency division structure is used for accurately controlling components of all frequency bands, and the filtering efficiency is improved. And the target frequency band is enhanced or weakened by adjusting the wavelet coefficient, so that the frequency domain processing accuracy is improved.

A kind of electromechanical coupling dynamics modeling method of electric vertical take-off and landing aircraft based on differential algebraic equation belongs to electric vertical take-off and landing aircraft technical field.First, the motor dynamics equation in eVTOL electric propulsion system is established according to motor parameters;Second, according to the geometric configuration and inertia parameters of eVTOL, the dynamics equation of fuselage multibody system is established, and the aerodynamic model is applied;Third, the motion driving equation is used to couple based on the general mechanical load calculation scheme of Lagrange multiplier;Finally, the electromechanical coupling dynamics model of eVTOL is established, which is discretized by trapezoidal-Newmark hybrid discrete format, and efficient solution is realized based on Newton iteration method, and it is verified by eVTOL vertical take-off.The invention avoids the defects of traditional simplified model ignoring motor transient characteristics and non-coupling modeling without real-time load feedback, improves the motion response and energy consumption calculation accuracy, and provides reliable dynamics modeling basis for eVTOL energy consumption optimization and commercial design.

The invention relates to the technical field of industrial robot control, in particular to an industrial robot-oriented motor dynamic steering anti-out-of-step control system, which is characterized in that motor operation characteristics are self-learned through an LSTM (Long Short Term Memory) neural network, and rotational inertia is identified in real time by adopting a recursive least square method in combination with multi-sensor data such as vibration, temperature and the like; and the noise covariance is dynamically adjusted in cooperation with improved Kalman filtering. The newly added multi-sensor fusion diagnosis module realizes out-of-step risk pre-judgment based on the D-S evidence theory, and the energy recovery unit improves the braking energy efficiency.

This invention relates to the field of motor dynamic performance technology, specifically disclosing a method for optimizing excitation control parameters based on a high-voltage direct-connected synchronous condenser, comprising: Step S1, defining the excitation control parameters of the high-voltage direct-connected synchronous condenser excitation system; the excitation control parameters include: the gain of the thyristor, the time constant of the integral element of the excitation regulator, the time constant of the differential element of the excitation system, and the coefficient of the thyristor regulation element; Step S2, performing sensitivity analysis based on simulation examples to obtain the influence law of each excitation control parameter on the overvoltage value; Step S3, based on the influence law, constructing a nonlinear coupled mapping model with the excitation control parameters as input and the overvoltage value as output using a neural network; Step S4, using the LMSSA sparrow search algorithm with a leader mechanism, with the minimum overvoltage value output by the mapping model as the optimization objective function, searching and optimizing the combination of excitation control parameters, and outputting the optimized combination of excitation control parameters.

The present invention discloses a method for controlling straight-line driving of four in-wheel hub motors that takes into account differences in the dynamic response of the motors. This method relates to the field of new energy vehicle technology and includes the following steps: obtaining the total required torque of the vehicle based on the vehicle speed and pedal opening of the four in-wheel hub motors; establishing an objective function and constraints based on the total required torque of the vehicle to optimize torque distribution; and, based on the optimization results, performing coordinated straight-line driving control of the four in-wheel hub motors to achieve straight-line driving control of the four in-wheel hub motors that takes into account differences in the dynamic response of the motors. This method solves the problem that existing technologies fail to account for the differences in the dynamic responses of the four motors, making it difficult to ensure the stability of the vehicle's straight-line driving.