3332results about "Electric generator control" patented technology

The invention relates to the technical field of industrial automation control, and discloses a water-based paint production and processing equipment control system, which comprises the following steps: acquiring stator current and rotor angular velocity, and reconstructing total load torque by using a sliding mode algorithm; extracting an input power low-frequency component to construct a heat dissipation slow manifold, and calculating a thermal drift disturbance component and an orthogonal residual component through orthogonal projection; on the basis of a two-component generation superposition instruction closed-loop adjustment driving mechanism, a double-time-scale orthogonal projection mechanism is utilized, non-structural thermal drift interference is automatically stripped under the condition that heat transfer parameters of equipment do not need to be predicted, the problem of control divergence caused by model parameter mismatch is solved, and decoupling control over the real rheological state of materials is achieved.

The invention relates to the technical field of servo control, in particular to a high-precision current closed-loop control system and method for a servo driver, and the method comprises the steps: collecting three-phase current, rotor position, winding temperature and bus voltage, and constructing a state data set; constructing a parameter identification model fusing physical prior and an attention mechanism, deducing inductance and flux linkage parameters influenced by temperature, saturation and cross coupling, and correcting a motor model in real time; the correction parameters are injected into an FOC decoupling and feedforward link, and a self-adaptive PI regulator is linked to set the gain of a current loop on line; calculating a d-q axis voltage command according to the update model to respectively control excitation and torque components; an extended state observer is introduced to estimate load abrupt change and parameter disturbance, feed-forward compensation is carried out, and three-phase PWM is generated through anti-Parker and SVPWM; and an inverter nonlinear compensation model of a dead zone and switch delay is constructed, PWM is pre-distorted and output to a power device, and robust and low-ripple current closed-loop control of the servo motor is realized.

The invention discloses a frequency conversion vector control method for a digital energy-saving pump station, which belongs to the technical field of vector control and comprises the following steps: constructing a coupling vector model, simulating the running states of a pump unit under different working conditions through a virtual test signal, and automatically correcting the coupling vector model; operating data of a pump set are collected in real time, an operating situation feature set is constructed, predictive vector control is carried out, an optimal voltage vector sequence is generated, and meanwhile load fluctuation of a pipe network is predicted; demand pre-judgment is carried out on the starting and stopping time and the action amplitude of the anti-backflow device, a bidirectional disturbance suppression mechanism is constructed, current vector parameters are pre-adjusted, and calculus correction is carried out based on deviation judgment; when multiple pumps operate in parallel, the instantaneous operation efficiency point of the pump set is calculated in real time, the efficiency change trend is predicted, a load distribution scheme is generated, the comprehensive energy efficiency is evaluated, energy efficiency self-optimization is carried out, the comprehensive energy efficiency of the system is improved, and control experience reuse is achieved.

The invention discloses an embedded motor torque ripple real-time compensation system based on deep learning, and relates to the technical field of motor control and artificial intelligence crossing, the system comprises a hardware data acquisition module, a signal feature extraction module, a deep learning compensation model module, an embedded real-time compensation module and a compensation effect verification module; a motor position and a current signal are acquired in real time through the hardware data acquisition module, dynamic analysis and multi-dimensional feature construction are performed on torque ripple related features by combining the signal feature extraction module, and the deep learning compensation model module learns a fluctuation rule in historical data by using a space-time sequence model to generate a high-precision compensation current. The model adapts to an embedded environment through lightweight design, real-time deployment and dynamic optimization of a compensation algorithm are achieved, compared with traditional PID control, the scheme can adapt to changes of motor operation conditions, the influence of torque fluctuation on system stability is reduced, and the smoothness and efficiency of motor operation are improved.

The invention relates to the technical field of motor control, and discloses a voltage compensation stable management system for a vortex oscillator motor, and the system comprises a detection unit which is used for collecting a bus current signal; the processing unit is used for performing differential operation on the bus current signal to determine a current change rate, judging that a load sudden change working condition is entered when the current change rate exceeds a preset threshold value, and further querying a load response coefficient according to a preset feature table and calculating a voltage compensation increment; and the driving unit is used for adjusting the phase shift angle of the excitation voltage according to the voltage compensation increment. According to the invention, by identifying the load working condition in real time and executing feedforward compensation, the instantaneous voltage drop caused by load switching is eliminated, the voltage steady-state characteristic of a motor driving link is maintained, the rotation speed fluctuation is effectively inhibited, and the dynamic response capability of the system under the variable load working condition is enhanced.

The invention discloses a multi-motor parallel control system and method based on an FPGA, and belongs to the technical field of multi-motor parallel control. The FPGA module is in communication connection with the control processing unit, and the FPGA module is internally provided with a global synchronous triggering unit used for generating a periodic synchronous triggering signal; the number of the position acquisition sub-modules corresponds to that of the motors, and each position acquisition sub-module comprises a position counter and a hardware latch register, wherein the position counter is used for carrying out counting and direction decoding on encoder pulses in real time; wherein the global synchronous triggering unit is connected with all the position acquisition sub-modules. According to the multi-motor synchronous control system, the position and other state signals of the multiple motors are collected at the same time through the parallel processing capacity of FPGA hardware, real-time control is achieved in combination with the control processing unit, and therefore the multi-motor synchronous control precision is improved, and the response speed is increased.

An electric motor having a stator and a rotor in which the electric motor is an axial flux motor. The stator has a multiplicity of cores which, along a circumferential direction, are disposed beside on another on a common first diameter and are in each case surrounded by one coil. The rotor has a multiplicity of magnets which, along the circumferential direction, are disposed beside one another on a common second diameter on a support. Each magnet in the circumferential direction extends across a first angular range and the magnets are disposed so as to be mutually spaced apart by a second angular range formed by the support, which support is also heatable by the stator by induction. The second angular range is at least 30% of the first angular range.

The invention provides a bus voltage adjusting method of a compressor, the compressor and electronic equipment. The bus voltage adjusting method of the compressor comprises the steps that the current current of the quadrature axis of a motor corresponding to the compressor and the current rotating speed corresponding to the compressor are collected; determining whether the current meets a first preset condition or not, and determining whether the current rotating speed meets a second preset condition or not; and when one of the first preset condition and the second preset condition is met, increasing the bus voltage of the compressor. According to the bus voltage adjusting method of the compressor, one of the current current of the quadrature axis of the electrode corresponding to the compressor and the current rotating speed of the compressor serves as a reference, so that the bus voltage is increased, the rotating speed of the compressor can be guaranteed, and the overall efficiency and performance are improved.

The invention relates to the technical field of maglev motor dynamics and control, and discloses a bearingless asynchronous motor multi-frequency harmonic vibration cooperative suppression method, which comprises the following steps: acquiring radial displacement signals and mechanical angular velocity of a rotor in an x axis and a y axis under a stator fixed coordinate system, and stacking double-axis displacement signals into an observation vector; calculating a weighting coefficient of the normalized residual error through a Huber robust cost function, and outputting the amplitude, the phase and the confidence of each order of harmonic wave; estimating the total disturbance of the system by using a linear extended state observer with harmonic energy injection, wherein the total disturbance is obtained by weighted summation according to the confidence, order and mechanical angular velocity of each order of harmonic; calculating a feedback control force according to the total disturbance estimated value, and superposing the feedforward compensation force and the feedback control force to generate a total suspension force instruction; and according to the total suspension force instruction, inversely calculating a suspension winding current reference value and outputting a control instruction. According to the invention, a mutually complementary cooperative suppression mechanism is formed, and the suppression precision of multi-frequency vibration is improved.

The invention discloses a permanent magnet synchronous motor rotating speed control method based on composite sliding mode control. The method comprises the steps that a mathematical model of a permanent magnet synchronous motor in a d-q axis synchronous rotating coordinate system is built; designing a layered sliding mode surface according to the mathematical model of the permanent magnet synchronous motor; designing a mixed reaching law containing a barrier function in combination with a sliding mode surface; and estimating periodic and non-periodic disturbances existing in the rotating speed of the permanent magnet synchronous motor and carrying out feed-forward compensation on sliding mode control by adopting a cascaded extended state observer combined with quasi-resonance control. According to the method, the rotating speed precision of the permanent magnet synchronous motor can be effectively improved, the dynamic response is improved, and a better inhibition effect on periodic and non-periodic disturbance is achieved.

The invention discloses a permanent magnet synchronous motor PI double-loop control method based on deep reinforcement learning. The method comprises the following steps: establishing a permanent magnet synchronous motor double-loop coupling mathematical model; a traditional FOC composite controller is constructed; designing a state feedback and reward mechanism of the double-ring TD3; constructing a speed loop and current loop TD3 + PI composite controller; and carrying out system stability analysis. According to the method, a system is divided into an inner ring and an outer ring based on hybrid cooperative control fusing deep reinforcement learning and classical control, the problem that robustness is insufficient under system disturbance through PI control and the problem that tracking precision is reduced due to load sudden change and noise interference in PMSM operation are combined, nonlinear disturbance is dynamically compensated through the strategy learning ability of a TD3 algorithm, and the tracking precision is improved. Meanwhile, soft update is introduced to improve convergence stability, and a compound control strategy based on double-loop TD3 + PI is provided. According to the invention, complex non-linear processing is simplified, and the stability of the system and the accuracy of rotating speed tracking are improved at the same time.

The invention relates to an anti-interference speed control method for a permanent magnet synchronous motor, in particular to the technical field of electrical engineering, and effectively solves the problem that the control performance of the permanent magnet synchronous motor is degraded due to model parameter drift and external load sudden change under complex working conditions. According to the method, the high robustness of sliding mode control and the rolling optimization characteristic of model prediction control are creatively fused, and an adaptive observer is introduced to estimate the system state and lumped disturbance online, so that the real-time feedforward compensation and active suppression of parameter uncertainty and disturbance are realized; according to the method, the dynamic response speed and the steady-state precision of the system are remarkably improved, the rotating speed fluctuation and the torque ripple are effectively inhibited, meanwhile, controller parameters are adaptively adjusted through an intelligent learning mechanism, the stability and the adaptability in long-term operation are ensured, and the method is suitable for large-scale popularization and application. The limitation that a traditional control strategy depends on an accurate model and the disturbance boundary is unknown is overcome fundamentally, and high-performance and high-robustness speed control is achieved.

The invention provides a touch feedback control method and device for a rotary knob, electronic equipment and a medium, and belongs to the technical field of switch control. The method comprises the following steps: converting a current Ia, a current Ib and a current Ic in a three-phase static coordinate system into a current Ialpha and a current Ibeta of a two-phase static coordinate system; the current I alpha and the current I beta of the two-phase static coordinate system are converted into current Id and current Iq under a two-phase rotating coordinate system with rotor flux linkage as orientation; the convergence speed of the driving motor in the dynamic response process is controlled and optimized by adopting a sliding mode variable structure; performing real-time setting through a zebra optimization algorithm to minimize overshoot and optimize convergence time; and the magnitude of the rotation feedback damping force is controlled by adjusting the current Iq. In this way, active rotating tactile feedback and pressing tactile feedback can be provided, and the intelligent interaction degree is improved.

The invention relates to a non-inductive FOC open-loop to closed-loop switching method and device for an electronic water pump and a vehicle. The method comprises the steps that a rotor is pre-positioned; starting an open loop I-F; switching condition judgment; estimating the rotor speed based on an observer, calculating a normalization factor, and obtaining a mixed scale factor through cubic polynomial operation; acquiring an open-loop current instruction of a q axis and a closed-loop current instruction output by a closed-loop speed PI regulator; performing weighted synthesis on the two paths of current instructions according to the mixing scale factor to obtain a temporary target current instruction, and applying a change rate limit to obtain a final current instruction output in the current period; the original angle error of the observer estimation angle and the open-loop slope angle is calculated and normalized, the allowable adjustment step length and direction of the round are dynamically determined, and the angle correction amount of the round is generated and superposed to the open-loop slope angle to update the rotor angle reference value; and closed-loop switching is completed. According to the invention, the problems of electromagnetic torque impact and rotating speed fluctuation caused by instruction step change are solved.

The invention discloses a motor position non-contact sensing system and a signal processing control method. The system comprises a three-dimensional magnet assembly, a magnetic signal acquisition module, a digital signal processing unit, a voltage conversion unit and a cooperative control module. The three-dimensional magnet assembly and the acquisition module are coaxially arranged, magnetic points are in spatial gradient layout, the acquisition module comprises a three-dimensional magnetic field detection unit, a real-time phase calibration unit is arranged in the processing unit, and the cooperative control module adjusts sampling parameters based on the rotating speed. The method comprises the steps of initialization, magnetic signal acquisition, operation processing and voltage conversion output. According to the scheme, the problem of magnetic field signal distortion of an existing system is solved, stable and accurate sensing of the motor position is achieved, and the multi-scene motor control requirement is met.

The invention relates to the technical field of motor control, discloses a direct current brushless motor control method and system based on current prediction, and aims to solve the problems of large torque ripple, low efficiency and poor stability caused by current loop lag in the prior art. The method comprises the following steps: acquiring a motor operation state signal in real time; determining a sector and an electrical angular velocity based on the rotor position and the rotational speed; inputting related parameters into the mixed current prediction model to obtain a three-phase current prediction value of the next period; a prediction error is calculated in combination with a current instruction, and an optimal voltage vector enabling a cost function to be minimum is solved through a model prediction control algorithm; and finally, a space vector pulse width modulation signal is generated to drive an inverter. According to the method, advanced control is realized by fusing a physical model and a data-driven prediction mechanism, the torque ripple is remarkably reduced, and the energy efficiency and robustness are improved.

The invention discloses a self-adaptive brushless motor control method and system, and relates to the field of intelligent control, and the method comprises the steps: collecting the original data of the operation state of a motor through a sensor group, and carrying out the preprocessing; time-varying parameter identification is completed through combination of an extended Kalman filtering algorithm and a radial basis function neural network, an evaluation index system is constructed based on an analytic hierarchy process to obtain a comprehensive evaluation value, and a related trend is predicted through a long and short-term memory neural network; constructing a multi-modal control strategy library, determining an adaptive strategy, optimizing core parameters by using an improved particle swarm optimization algorithm, generating a control instruction, and outputting a corresponding current through a power driving module; and monitoring motor parameters in real time, comparing with a control target value, calculating deviation, correcting an identification result, adjusting a strategy threshold value, and updating and optimizing an objective function. The method has the advantages that by accurately sensing the state of the motor, dynamically adapting the control strategy and optimizing parameters in real time, it is ensured that the motor stably and efficiently operates under the complex working condition, and the characteristics of energy conservation and long service life are achieved.

The invention discloses a PMSM speed regulation method (ILADRC) based on improved RLS identification and dynamic inverse control. According to the method, a layered framework is adopted; a linear expansion observer with fixed parameters is used for a bottom layer to ensure observation stability; the middle layer constructs a parameter identification regression model based on a generalized disturbance observation value by using an improved recursive least square algorithm, introduces an online correction mechanism, and performs online decoupling identification on input gain and pure physical disturbance of a speed ring by using the generalized disturbance observation value and a current instruction; and the upper layer reconstructs an adaptive dynamic inverse control law based on an identification result, weakens an algebraic coupling loop of observation and control, realizes no-static-error and no-overshoot rapid tracking of the system on a rotating speed instruction under a parameter mismatch working condition in combination with an acceleration error integral enhancement item, and effectively improves the dynamic performance and robustness of the motor under a parameter perturbation working condition.

A sensorless method for machine tool chatter detection. A motor torque signal is analyzed in the time domain to determine whether a bit is currently cutting workpiece material. When not cutting material, an air-cut reference signal is stored for later use. When cutting material, the motor torque signal is converted to the frequency domain and filtered in a multi-step process. After removal of the air-cut reference signal via spectral subtraction, and removal of spindle harmonic components, additional filtering is performed to address aliasing and encoder error effects. The aliasing filtering removes artificial peaks in the frequency response spectrum resulting from interaction between sampling frequency and cutting frequency. The encoder error filtering removes frequency response peaks related to encoder design and interaction with motor speed. After filtering, indicator criteria are evaluated to detect chatter, and corrective action is taken when chatter is detected.

The present application relates to the technical field of motors, and discloses a motor control method and apparatus based on harmonic injection, and a device and a storage medium. The method comprises: on the basis of a motor and noise of the motor, determining a specified-order harmonic wave needing to be injected; acquiring a rotational speed and torque of the motor, and determining a voltage magnitude and a phase angle of the specified-order harmonic wave corresponding to the rotational speed and the torque from a preset specified-order harmonic wave table; performing transformation processing on the voltage magnitude and the phase angle to obtain a target voltage value in a three-phase coordinate system; and superimposing the target voltage value onto a fundamental voltage to obtain a control voltage, wherein the control voltage is used for controlling the operating state of the motor. In the present application, torque harmonic waves generated by the driving of a motor are eliminated, thus significantly reducing the noise during the operation of the motor and a load system.

The invention discloses a flux linkage tracking full-speed-domain high-precision predictive current control method for a permanent magnet synchronous motor, and the method comprises the steps: sampling a phase current signal, a position signal and a speed signal of the permanent magnet synchronous motor, and obtaining a dq sampling current through coordinate transformation; calculating a predicted current according to the established tracking discrete model; the sinusoidal variation characteristic and the dynamic transient characteristic of the resistance voltage drop are accurately considered in the current prediction and reference voltage calculation stage, and the resistance voltage drop is accurately represented through accurate feed-forward compensation of predicted current and reference voltage; a driving signal of the inverter is obtained through coordinate transformation and space vector modulation, and full-speed-domain high-precision fast-response current prediction control over the permanent magnet motor is achieved. According to the method, the current flow steady state control error caused by the model error is reduced, the current control precision and the dynamic response performance of the permanent magnet synchronous motor in the full-speed domain are effectively improved, and a high-precision model basis is provided for high-precision position-free control and parameter online identification.

The invention relates to the technical field of logistics warehouse storage equipment, in particular to a speed reduction control method for a high-speed motor driven hydraulic system, which comprises the following steps: S1, the output torque of a high-speed motor is transmitted to a gear pump through a motor shaft, a planetary reducer and a planet carrier in sequence to drive the gear pump to work; s2, acquiring a three-phase current instantaneous signal and a direct current bus voltage signal, and performing preprocessing and frequency spectrum conversion to determine a current frequency spectrum; s3, in the current frequency spectrum, extracting an energy value in a preset frequency band with the meshing frequency and harmonic waves of the planetary gear as the center, and calculating to obtain a disturbance characterization value of the planetary gear; s4, determining a torque smooth adjustment coefficient according to the planet wheel disturbance characterization value; and S5, dynamically adjusting a dynamic response parameter of a torque control ring of the high-speed motor according to the torque smooth adjustment coefficient. The problems that in the prior art, a high-rotating-speed motor and a hydraulic pump are not matched in rotating speed, and mechanical disturbance is difficult to restrain are solved.

The invention discloses a low-harmonic high-voltage speed regulation system based on a multi-pulse phase-shifting transformer, and particularly relates to the field of power electronic technology and motor speed regulation, which is characterized in that the primary side of the multi-pulse phase-shifting transformer is in star connection, and N groups of windings on the secondary side are in extended delta connection, so that phase difference is realized; the multi-path low-voltage alternating current is converted into multi-path low-voltage alternating current and low-order harmonics are High voltage is output through cascade H-bridge topology series connection, and reliable conversion is guaranteed through rectification filtering inversion and device redundancy design; the motor control module collects signals through multiple sensors, and PWM drive signals are generated through a vector control algorithm and coordinate transformation. The harmonic detection and compensation module detects harmonic waves based on an FFT algorithm, and injects a reverse compensation component through a modulation strategy to offset the harmonic waves; and the auxiliary protection module integrally realizes low-harmonic and high-precision high-voltage motor speed regulation through multi-dimensional monitoring and hardware protection.

The invention discloses a permanent magnet synchronous motor sensorless control method based on a dynamic position error. A transition stage is provided, per-unit estimation position errors between a first position error signal obtained based on a high-frequency signal injection method and a second position error signal obtained based on a sliding mode observer are compared, an optimal switching speed point is dynamically determined, smooth fusion is carried out on the two position errors by using a nonlinear weighting function, and the optimal switching speed point is obtained. And finally, the estimated position and rotating speed are obtained through a phase-locked loop. And finally, position tracking is carried out by adopting different error signals according to the estimated rotating speed. According to the method, the problem of estimation value pulsation and jump caused by the fact that a traditional method depends on fixed experience switching points is solved, smooth and self-adaptive switching of the two estimation methods in the full-speed domain range is achieved, the control precision and operation stability of the system are remarkably improved, the structure is simple, and engineering implementation is easy.

The invention provides an efficiency optimization control method of a permanent magnet synchronous motor and related equipment. The method comprises the following steps: acquiring an output current of an inverter; constructing an inverter loss model based on the output current of the inverter and the inverter loss coefficient; constructing a total loss model based on the electromagnetic loss model, the inverter loss model and an equivalent conversion method; constructing a current population by taking the plurality of d-axis current values as individuals; and performing optimization solution based on the total loss model, the current population, a PID search algorithm and an artemisinin optimization algorithm to obtain a global optimal solution and control the permanent magnet synchronous motor. According to the scheme, the driver loss is added into the total loss model, and efficiency optimization can be carried out on the whole motor driving system; in order to solve the problem that a traditional method is not suitable for an IPMSM, a PID search algorithm and an artemisinin optimization algorithm are combined, parameter search is carried out on a motor efficiency optimal point by simulating an incremental PID controller adjusting mechanism, a global optimal solution is obtained, and therefore optimal control over the click efficiency is achieved.

The invention discloses a complex wave-based permanent magnet synchronous motor all-electrical parameter online identification method and device. The method comprises the following steps: analyzing the influence of a voltage error caused by dead zone time on parameter identification, and performing corresponding dead zone compensation; a bias complex wave with a certain amplitude and frequency is injected into the d-axis current, so that the d-axis current meets a parameter identification continuous excitation condition; constructing three groups of effective current slopes through four groups of different input data stored in the steady state of the motor, and identifying three groups of parameters of resistance, direct-axis inductance and quadrature-axis inductance by referring to a d-axis voltage equation and adopting a least square method with a forgetting factor; and finally, updating the identified three groups of parameters as known quantities in a q-axis voltage equation in real time, storing two groups of different input data to construct a group of effective current slopes, and identifying flux linkage parameters by adopting a least square method with a forgetting factor. According to the method, the under-rank problem of all-electrical parameter identification of the motor is solved, the identification precision is high, and the identification error of each parameter is about 3%.

The present invention belongs to the technical field of parameter identification for permanent-magnet synchronous motors. Disclosed are a parameter identification method and apparatus for a permanent-magnet synchronous motor, and a storage medium and a device. The method comprises: using a variable step-size feedback neural network algorithm to solve a voltage equation and a d-q axis current discrete state equation, which take cross-coupled inductance into consideration, of a permanent-magnet synchronous motor in a dq coordinate system, so as to obtain intermediate parameters generated in the process of constructing the d-q axis current discrete state equation; and performing calculation on the basis of the intermediate parameters, so as to obtain the stator resistance, the d-axis inductance, the q-axis inductance, the cross-coupled inductance and the permanent-magnet flux linkage of the permanent-magnet synchronous motor, and thereby completing parameter identification. The present invention takes cross-coupled inductance into consideration and uses the variable step-size feedback neural network algorithm, such that the computational load is extremely small, the degree of complexity is reduced, rapid and effective identification can be realized, and errors can be reduced; in different convergence time periods, the algorithm adjusts the step size on the basis of the magnitude of steady-state errors, such that identification results approach stable values more quickly, thereby improving the speed and stability of convergence.

The invention discloses an electric linear servo system control method based on cascade LESO-DISMC. The method comprises the following steps: firstly, establishing a complete mechanism model of a permanent magnet synchronous motor servo loading system; then designing DOB interference observer real-time compensation by adopting a LuGre friction model and a gap dead zone model; a feedforward control quantity is constructed by utilizing a measurable displacement signal, and redundant torque is inhibited; designing a dynamic integral sliding mode controller to ensure global stability; a high-low bandwidth LESO is constructed, and both fast tracking and smooth filtering are considered; and finally, trajectory optimization is carried out, a smooth trajectory is generated by adopting polynomial interpolation for the step and triangular wave signals, and mechanical vibration is inhibited. According to the method, a LuGre friction model is adopted to compensate nonlinear friction, cascade linear LESO and sliding mode control are combined, a track is optimized through an S-shaped curve, and the problem of'differential explosion 'is solved; according to the method, instruction smoothing, core control and friction compensation are fused, and the anti-interference capability and the loading precision of the system are improved.

The invention relates to the technical field of torque control, in particular to a motor torque control method, system, equipment and medium, and the method comprises the following steps: obtaining a winding temperature rise and rotating speed signal through a temperature and rotating speed sensor, calculating the resistance and flux linkage offset, and filtering to obtain a torque evaluation parameter; the acceleration and inertia reference are compared to obtain inertia disturbance, a least square method is combined to calculate a compensation coefficient, a current component is corrected to synthesize an expected torque, a torque error is calculated to judge whether the torque reaches the standard or not, and a torque control result is output and optimized. Load changes are quickly responded through filtering and inertia disturbance recognition, differential calculation is conducted on the relation between acceleration and a correction coefficient to act on a current component, torque output is stable, coefficient iterative optimization is promoted through error comparison, fluctuation is reduced, efficiency is improved, and reliable control over the motor under the complex working condition is kept.

The invention relates to the technical field of motor control, and particularly provides a control method and system suitable for a one-way running motor of a two-wheeled electric vehicle. The method aims to solve the problems of unstable motor operation and insufficient reliability caused by torque pulsation in the prior art. The method comprises the following steps: executing off-line identification of motor parameters to obtain initialized parameters; multi-source operation state signals are collected, and a vehicle working condition judgment result is obtained through fusion analysis; performing fault diagnosis and grading evaluation to form a fault-tolerant instruction; dynamic dead zone compensation and self-adaptive overmodulation are implemented by combining the parameters and the working conditions, and an optimization control instruction is output; generating a PWM driving signal through space vector modulation; and responding to the fault-tolerant instruction, and fusing a sensorless algorithm and a health sensor signal to realize degraded operation. According to the invention, the smoothness and efficiency of motor operation and the fault-tolerant capability of the system are effectively improved.