466 results about "Voltage vector" patented technology

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 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 is suitable for the technical field of flexible power distribution of a power system, and discloses a modular multilevel converter multi-objective optimization method, system and device based on model predictive control and space vector modulation, and a medium. Obtaining an output current reference value and a circulating current reference value; obtaining a reference voltage vector based on the output voltage reference value, and screening out a plurality of groups of redundant voltage vector sequences through a space vector diagram; performing performance evaluation through rolling optimization by combining each redundant voltage vector sequence with a multi-target cost function to obtain an optimal voltage vector sequence; and on the basis of the optimal voltage vector sequence and the corresponding duty ratio, a switching signal for driving each sub-module switching device of the MMC is generated, and multi-target cooperative control is realized. The three targets of reference output current tracking, circulating current suppression and sub-module capacitor voltage balance are met, and the dynamic response capability, efficiency and reliability of MMC system operation are comprehensively improved.

The invention relates to the field of three-level inverters, and particularly discloses a model-free strong-robustness predictive control method and system for a three-level SNPC inverter, and the method comprises the steps: carrying out the real-time sampling and coordinate transformation of the inverter, and obtaining the current and voltage components under a two-phase static coordinate system; establishing a hyper-local model, enabling the system parameter deviation and the external disturbance to be uniformly equivalent to lumped disturbance, and designing a full-order sliding-mode observer for real-time estimation; calculating a reference voltage vector based on the disturbance estimation value and the extrapolated reference current; and an optimal double-vector combination is selected through space vector optimization, action time is solved, redundant small vectors are selected according to midpoint voltage deviation, and PWM driving signals are generated. According to the method, excellent current tracking performance and low harmonic distortion can still be kept under the conditions of parameter mismatch and working condition change, meanwhile, neutral-point potential balance on the direct-current side is achieved, and the method has the advantages of being small in calculation amount, high in robustness, easy to achieve in engineering and the like.

The invention discloses a high-robustness deadbeat predictive current control method which is suitable for current control of a dual three-phase permanent magnet motor driving system, and belongs to the technical field of permanent magnet motor control. The method mainly comprises the following steps: reconstructing a motor mathematical model by adopting a space vector decoupling matrix and Park transformation to obtain a motor voltage equation under a dqxy axis; designing a linear expansion state observer; a reference value of an output voltage vector is obtained in combination with deadbeat predictive current control; time delay in the digital control system is calculated, and angle delay is compensated; and designing a closed-loop Smith predictor for compensating a time delay link to complete high-robustness dead-beat predictive current control of the dual three-phase permanent magnet motor. The current loop design in the method does not depend on motor parameters, and the method has high parameter change robustness. By introducing the closed-loop Smith predictor, large delay of the system can be effectively compensated, and high-precision current tracking is realized under low switching frequency.

The invention provides a motor vibration noise control method and system based on modal resonance frequency prediction, and belongs to the field of motor control. The method comprises the following steps: acquiring each order of intrinsic mode frequency of the permanent magnet motor; a cost function parameter, a current constraint condition and a control target are set, and a model prediction control method is adopted to drive an inverter to operate, specifically, the current operation state quantity of the permanent magnet motor is collected; predicting a state response in a future finite time domain based on the operation state quantity; constructing a value function, and evaluating and optimizing a state change result; and selecting an optimal voltage vector, generating a pulse signal to drive an inverter to execute, obtaining a motor high-frequency electromagnetic force wave distribution condition, comparing the motor high-frequency electromagnetic force wave distribution condition with the intrinsic mode frequency of the permanent magnet motor, and optimizing an optimal voltage vector selection logic. The problems that harmonic waves are concentrated and resonance is easily caused by a fixed switching frequency modulation method in the prior art, and a passive suppression method is high in cost and poor in flexibility are solved.

The invention relates to the technical field of power grid safety evaluation, in particular to a power system short-circuit parameter prediction method, system and device based on time-space relevance and a storage medium. A multi-dimensional state vector including a node voltage vector, a branch current vector, a short-circuit impedance matrix, spatial position information and a time feature vector is constructed, and a space-time correlation feature vector including a time-dimensional feature, a spatial-dimensional feature, a space-time coupling feature and a state feature is extracted. Wavelet transform, Fourier analysis and graph theory analysis are adopted to identify a parameter change rule and a propagation effect. A multi-level prediction model of a statistical prediction layer, a deep learning layer and a fusion layer is constructed, and comprehensive description of dynamic characteristics of short-circuit parameters is realized through spatio-temporal feature fusion. A staged training strategy is adopted, and comprises the steps of establishing a basic model through offline training, updating parameters in real time through online learning, and quantifying uncertainty through a probability prediction framework. And a prediction correction mechanism and a reliability evaluation system are established, and a complete prediction-evaluation-correction closed loop is formed.

The invention discloses an improved multi-vector combined model predictive control method and device for a permanent magnet synchronous motor. The method comprises the following steps: acquiring a three-phase current of each sampling period, and converting the three-phase current into a d-axis current and a q-axis current; performing one-beat delay compensation on the current, predicting a reference voltage of a next beat, and judging a sector where the reference voltage is located; selecting a corresponding voltage vector output combination in the reconstructed voltage vector selection table by combining the sector and the previous period zero vector; solving a cost function only containing voltage vectors and action time by using the KKT theorem, and calculating the action time of each voltage vector; and generating a pulse signal according to the action time for driving the output of an inverter of the permanent magnet synchronous motor. According to the method, the advantages of fast dynamic response, easy processing of multiple constraints and the like of model prediction control are maintained, and meanwhile, lower calculation complexity, fixed switching frequency and higher reliability are realized, so that the comprehensive performance of a permanent magnet synchronous motor control system is improved.

The invention relates to a high-order analysis power flow and carbon flow tracking method based on full-pure embedding, and the method comprises the specific steps: introducing a complex embedding parameter s, constructing a node voltage vector, an injection power vector and a tracking matrix in a power grid power flow equation into an analysis power series and an analysis power series of the complex embedding parameter s based on the analysis continuation characteristic of full-pure embedding, solving a node voltage initial value when the power grid is in a basic operation state by adopting a Newton-Raphson method; calculating a zero-order line active power vector based on the node voltage initial value, and constructing a zero-order distribution matrix representing a power distribution relation in a basic operation state of the power grid; solving a zero-order power flow tracking matrix based on the zero-order line active power vector and the zero-order power distribution matrix; calculating node indirect total carbon emission based on the zero-order power flow tracking matrix; and replacing the power distribution matrix, the node outflow power and the power flow direction matrix in the zero-order power distribution matrix with power series expansion of corresponding variables.

The invention discloses a current prediction control method and device for a permanent magnet motor, and the method achieves the real-time prediction of a voltage error caused by a dead zone and other non-ideal factors through the powerful nonlinear fitting capability of a feedforward neural network in combination with the learning of historical current time sequence characteristics. And the prediction error is further fed forward and compensated to a future current prediction model to improve the accuracy of current prediction, so that the cost function evaluation is more accurate, the optimal voltage vector is selected, and the steady-state current error and the low-speed torque ripple are effectively inhibited. In this way, precise control over the current of the motor is achieved, and the control precision and operation stability of the driving system are comprehensively improved.

The invention relates to the technical field of fuel cell membrane electrode voltage distribution testing, in particular to a fuel cell membrane electrode voltage distribution testing method and system, and the method comprises the steps: arranging a potential sensor array, and synchronously collecting an original voltage vector through the potential sensor array in the loading operation process of a fuel cell; a reference electrode is arranged in the non-reaction area, a stable reference signal is applied to the reference electrode, and a feedback signal of the reference electrode is collected after preset stable time is delayed; carrying out difference calculation on the feedback signal and the stable reference signal to obtain a system measurement drift distance; and performing joint calibration on the original voltage vector according to the system measurement drift amount and the spatial continuity constraint of the membrane electrode voltage distribution to obtain the voltage distribution vector of the fuel cell membrane electrode. And the authenticity and reliability of the voltage distribution data in the long-period test process of the fuel cell are ensured by continuously compensating the drift of the measurement precision.

The invention relates to a matrix decomposition device and method based on a memristor cross array, which are suitable for efficient hardware implementation of singular value decomposition (SVD), the memristor cross array receives a conductance value mapped by a Grubrum matrix constructed by a to-be-decomposed matrix and a bit line input voltage converted by a bit line column vector, and outputs a corresponding current; converting the corresponding current into a voltage vector; performing normalization processing on the voltage vector to obtain a normalized vector; judging whether convergence occurs or not; performing normalization processing on the steady-state voltage vector to obtain a final output vector; and according to the final output vector, main characteristic values are extracted based on a first normalization circuit, and main singular values and corresponding singular matrixes are calculated. Compared with the prior art, the high parallel computing characteristic of the memristor cross array is utilized, efficient operation and hardware acceleration of matrix decomposition are achieved, the method has the advantages of being low in power consumption, high in speed and good in expansibility, and the method is suitable for application scenes such as artificial intelligence, signal processing and large-scale matrix operation.

The invention belongs to the technical field of electronic power, and particularly relates to an LCL grid-connected inverter model-free predictive current control system and method based on sampling noise compensation, and the system comprises an inverter main circuit, an LCL filter and a controller. The controller is configured to firstly calculate a current gradient and a voltage gradient according to a collected system operation signal; then, a second-order generalized integrator is used for conducting accurate compensation on sampling noise contained in the gradient; and finally, executing a model-free predictive control algorithm based on the compensated gradient, and preferably selecting an optimal voltage vector through a multi-objective value function integrating inverter side current, capacitor voltage and network side current. According to the method, sampling noise interference is effectively suppressed, the control precision and the anti-interference capability of the system are improved, and stable and efficient operation of the LCL grid-connected inverter can be realized without additional damping.

The invention discloses a permanent magnet synchronous motor model prediction control method based on multi-target Pareto optimum, which comprises the following steps: measuring two-phase current, motor rotating speed and rotor position of a permanent magnet synchronous motor, converting the two-phase current into d-axis current and q-axis current according to the rotor position, and converting an alternative voltage vector of an inverter into d-axis voltage and q-axis voltage at the same time; inputting the d-axis current, the q-axis current, the d-axis voltage, the q-axis voltage and the rotating speed of the motor into a current prediction model of the permanent magnet synchronous motor, and predicting a future current state value; establishing a multi-target optimization model including torque ripple, current total harmonic distortion, switching frequency and power loss, calculating by using a multi-target particle swarm algorithm in combination with non-dominated sorting and congestion distance to obtain a Pareto optimal solution set, obtaining an optimal weight factor, and automatically adjusting target weights according to motor operation states under different operation conditions; and constructing a cost function based on the optimal weight factor, and selecting a voltage vector enabling the cost function to be minimum as optimal control output.

The invention belongs to the technical field of motor driving control, and discloses a space vector modulation strategy method for a permanent magnet synchronous motor, which comprises the following steps of: searching a region division and vector arrangement table by using regions in which Vlp and V are positioned to obtain an optimal vector sequence, and arranging vectors based on a principle of eliminating a peak of a CMV and minimizing switching operation times; and finally, calculating the duty ratio of a plurality of effective voltage vectors used for synthesizing the next period according to the amplitude-second balance principle. Compared with a control strategy that only one effective vector or two adjacent effective vectors are used in each control period, the virtual vector synthesized by the method is the same as the reference vector, and common-mode voltage spikes can be eliminated by the method; compared with NSPWM and AZPWM, the method has the advantages that area division and vector sorting are reasonably arranged, so that the switching action times are minimized, the switching loss is reduced, and the inverter efficiency is improved.

The invention discloses a network construction type converter pre-synchronization control method based on Taylor compensation, and the method comprises the steps: collecting the three-phase voltage of an output end of a virtual synchronous generator (VSG) and the three-phase voltage of a power grid side, carrying out the Clark transformation, and extracting a positive sequence voltage component; on the basis of the positive sequence voltage component, calculating a phase difference sine value of the VSG output voltage and the power grid voltage; based on the phase difference sine value, compensating the phase difference sine value through Taylor expansion to obtain a compensated real-time phase difference; and fusing the compensated real-time phase difference into a VSG phase-locked loop-free pre-synchronization control strategy, and driving a PI regulator to dynamically correct the output frequency and phase of the VSG. A phase-locked loop is completely abandoned, and the frequency oscillation risk is eliminated; expanding a phase difference calculation range through third-order Taylor compensation; voltage vector analysis and a dynamic compensation function are fused, phase synchronization is achieved, and grid-connected impact current is reduced.

The invention discloses a model prediction control method for a low-common-mode-voltage dual three-phase motor with improved steady-state performance, and belongs to the technical field of dual three-phase permanent magnet synchronous motor control. The method comprises the following steps: firstly, suppressing harmonic current by synthesizing virtual voltage vectors with a specific duty ratio, and synthesizing a candidate output voltage vector by using two adjacent virtual voltage vectors according to a predefined duty ratio; designing a value function without a weight coefficient to select an optimal voltage vector; designing a dual duty ratio technology to calculate the duty ratios of the two virtual voltage vectors for synthesizing the optimal voltage vector; a specific switching sequence in which virtual zero vectors are arranged on two sides and in the middle of a control period is designed, and the switching sequence is generated by using a phase-shifting carrier method. According to the invention, the common-mode voltage can be effectively reduced without adding any hardware circuit, the current harmonic wave and the torque ripple are obviously reduced by expanding the modulation range, the steady-state performance of the system is improved, and the method is suitable for a dual three-phase motor driving system with high requirements on performance and reliability.

The invention discloses a motor control method, device and equipment and a medium, and relates to the field of motor control, when a mode switching condition is met, switching operation is not executed immediately, and the switching time is set at the commutation time of a motor, so that natural transition of a phase angle of a reference voltage vector is ensured; meanwhile, based on the running state of the motor in the first control mode, an integral initial value of the current regulator in the second control mode is preset, so that smooth connection of the amplitude of the reference voltage vector is realized. Through cooperative control of the phase angle and the amplitude, the problems of unstable motor operation, speed fluctuation, equipment stress damage and the like caused by discontinuous jump of the reference voltage vector at the switching point are solved, and the effect of improving the motor control performance and the system operation reliability is achieved.

The invention discloses a permanent magnet synchronous motor wide speed range model prediction control method and system based on a mean value reduction optimization algorithm, and belongs to the technical field of motor control. According to the method, a discrete mathematical model of the permanent magnet synchronous motor is established under a d-q rotating coordinate system, a q-axis current reference value is generated by an outer ring through a speed PI regulator, and a d-axis current reference value is calculated in combination with a maximum torque per ampere (MTPA) principle and a weak magnetic region voltage constraint; finite control set model prediction control is adopted in an inner ring, enumeration prediction is conducted on candidate voltage vectors of the three-phase voltage source type inverter, a cost function containing a d-axis current error, a q-axis current error and an electromagnetic torque error is constructed, an optimal voltage vector is selected, and a three-phase PWM signal is generated through space vector pulse width modulation to drive a motor. The system is provided with a mean value reduction optimization module, joint optimization is carried out on speed outer ring PI parameters and cost function weight coefficients in the off-line stage, the parameters are stored in a lookup table, and automatic setting of control parameters is achieved. The permanent magnet synchronous motor can improve the dynamic response performance of the rotating speed and the current in the base speed area and the weak magnetic area, reduce the total harmonic distortion of the stator current, improve the voltage utilization rate and the overall operation efficiency of the permanent magnet synchronous motor, and is suitable for occasions such as electric vehicle driving and high-performance servo systems.

The invention provides a current sampling zero offset correction method and device. The current sampling zero-bias correction method comprises the following steps: determining a correction trigger opportunity, wherein the correction trigger opportunity is a moment when an output voltage vector of a power converter is in a zero vector state and a theoretical value of current flowing through a current sampling resistor is zero; sampling a current sampling channel through an analog-to-digital converter at a correction triggering time, and obtaining original sampling data under a zero current condition; processing the original sampling data to obtain a current zero current bias value and updating the stored current bias data variable; a corrected current value is determined based on the updated current bias data variable. By setting the specific correction triggering time and correction mechanism, the current sampling zero bias can be dynamically tracked and corrected online, automatically and in real time in the whole operation process of the driver, adverse effects caused by static deviation and dynamic temperature excursion are overcome, and the control precision and robustness of the system under all working conditions are improved.

The invention discloses a permanent magnet synchronous motor current harmonic suppression method based on model prediction control, and the method comprises the following steps: S1, building a mathematical model of a permanent magnet synchronous motor in a rotating coordinate system, and carrying out the discretization through an Euler discretization method, and obtaining a prediction model for predicting the state of the permanent magnet synchronous motor at a future moment; s2, designing and constructing a cost function including a fundamental current tracking item and a high-order current harmonic suppression item in the prediction model; calculating a current harmonic term factor; s3, traversing voltage vectors corresponding to all switching states of the inverter, calculating predicted current and a cost function under the action of the voltage vectors, selecting an optimal voltage vector enabling the cost function to be minimum, and generating a switching signal to drive the permanent magnet synchronous motor to operate; according to the method, the prediction model containing fundamental wave tracking and high-order harmonic suppression is constructed, and the harmonic suppression factor is optimized in real time by using the Lagrange multiplier method, so that current harmonic suppression and system loss reduction are realized.

The invention provides a network construction type converter fault ride-through control method based on model predictive control and a resonance controller, and the method comprises the following steps: A, obtaining a reference value of power under a fault according to a network construction type converter and a virtual synchronous generator (VSG) mathematical model with the purpose of providing required positive sequence reactive power; step B, extracting a fault transient component through a high-pass filter and generating a capacitor voltage positive sequence reference value by using a resonance controller; step C, selecting different capacitor voltage negative sequence reference values according to different control targets; step D, obtaining a filtering current reference value through the reference values of the positive sequence capacitor voltage and the negative sequence capacitor voltage, and constructing a cost function containing current amplitude limiting; and selecting an optimal voltage vector. Compared with the existing method, the method has the advantages that the transient suppression is faster, the steady-state current is not influenced, the resonant controller specifically suppresses a 50Hz transient component, and the reactive response speed is improved by 43% compared with that of a virtual impedance method.

The invention relates to a model prediction fault-tolerant control method and system for a dual three-phase permanent magnet synchronous motor, and the method comprises the steps: estimating the lumped disturbance in the operation process of the motor in real time based on an extended state observer, and carrying out the feed-forward compensation of the reference voltage of the motor according to the lumped disturbance information; and based on the compensated voltage reference value, constructing a dynamic voltage vector set and correcting an initial voltage vector set, searching an optimal voltage vector in the dynamic voltage vector set, and driving the motor through three-phase decoupling space vector pulse width modulation. According to the field loss fault-tolerant control strategy designed by the invention, phase current harmonics caused by local field loss faults of the dual three-phase permanent magnet synchronous motor can be effectively suppressed, and the steady-state precision and the dynamic response capability of the system under the local field loss faults are enhanced.

The invention discloses a three-level inverter open-circuit fault diagnosis method based on fault feature vector prediction, and the method comprises the steps: reconstructing a theoretical stator current through reference current based on a motor steady-state model, and introducing an amplitude per-unit algorithm to calculate a current residual error, thereby recognizing the fault, and locking a fault phase; collecting a system state at the moment of fault triggering, deducing a modulation switch sequence in a future detection period on line by using a reference voltage vector time sequence prediction model, and generating a dynamic reference value of theoretical action times of each switch state; performing real-time statistics on the actually-measured cutoff times of the fault phase in different switch states by using an edge triggering mechanism, and constructing an actually-measured feature vector; and determining a fault device by calculating the minimum distance between the actual measurement vector and each fault modal theoretical feature. The method can effectively eliminate the influence of the rotating speed and load change of the motor on the diagnosis threshold, solves the problem that the fault features of the inner tube and the clamping diode are overlapped and are difficult to distinguish, and improves the robustness and accuracy of fault diagnosis.

This invention discloses a dynamic weighted adaptive predictive control method and apparatus based on twin model fidelity feedback. The method includes: establishing a digital twin model of the motor to obtain the predicted current of the motor's future state, addressing the impact of motor model uncertainty and time-varying parameters on control performance; calculating the prediction fidelity of the motor's digital twin model in real time based on the predicted current and the measured current of the motor; dynamically adjusting weight factors using a fuzzy logic decision system based on the motor's real-time operating conditions and the prediction fidelity to achieve switching of the control objective; calculating the optimal voltage vector corresponding to minimizing the cost function using model predictive control theory based on the predicted current and the dynamically adjusted weight factors; and achieving operation of the permanent magnet synchronous motor at low switching frequencies based on the optimal voltage vector. This invention can effectively compensate for control delay and model uncertainty at low switching frequencies, significantly improving the high dynamic response performance and robustness of the permanent magnet synchronous motor.

The application provides a driving method of an inverter bridge, a driving circuit, a servo driver and a motor device. In the driving method of the inverter bridge, voltage vector output time and dead time are set, so that a power switch tube of a jth bridge arm is kept in a conduction state in two adjacent voltage vector output times before switching, the power switch tubes kept in the conduction state are changed in turn and staggeredly, in each dead time, two other power switch tubes kept in the conduction state in a previous voltage vector output time are switched off, the corresponding switching bridge arm and winding complete resonance work, the end voltage of the power switch tube to be turned on is clamped to zero potential, zero voltage conduction is realized, a soft switching mode is formed, and the switching loss is reduced and the power conversion efficiency is improved.

The application discloses a high-precision model prediction current control system and control method of a double three-phase motor, and relates to the technical field of multiphase motor control. The application extends the traditional 12 virtual voltage vector control set, designs 24 virtual voltage vectors with equal amplitude and uniform phase angle under the premise of not losing voltage utilization rate, and improves control precision. A duty cycle calculation method based on minimum error is proposed, which can track the currents of d-axis and q-axis at the same time even in the case of a single effective virtual voltage vector, and guarantees optimal output duty cycle. In addition, the process of traversing all voltage vectors in the prediction control is simplified, and the calculation burden of the algorithm is reduced. The application improves the precision of model prediction control by extending the control set and reducing the calculation error of the duty cycle, reduces 5th and 7th harmonics, and improves torque ripple. Moreover, even under the action of 24 voltage vectors, the calculation amount is still low, and the execution efficiency of the algorithm is improved.

This invention relates to a low-current harmonic direct torque control method for a dual three-phase permanent magnet synchronous motor (PMSM), belonging to the field of PMSM control technology. The method is as follows: S1: Establish mathematical models of the fundamental and harmonic subspaces of the dual three-phase PMSM under vector space decoupling, and clarify the voltage vector distribution characteristics of the two subspaces; S2: In the fundamental subspace, design a duty cycle modulation strategy based on the principle of minimizing the error vector, and an improved deadbeat flux linkage torque controller; S3: In the harmonic subspace, design an online learning harmonic canceller, using the least mean square algorithm to update the weight coefficients in real time; S4: Select the D1 vector set as the effective vector of the harmonic subspace and perform sector division; S5: Add the effective voltage vector action time of the fundamental and harmonic subspaces to generate the final switching sequence, which is output to the dual three-phase inverter to effectively suppress torque ripple and harmonic current of the dual three-phase PMSM.

The invention discloses a high fundamental frequency permanent magnet motor low carrier wave ratio control method and device based on an optimal switching vector mode. The method comprises the steps of sampling a motor current and a rotor position, and obtaining a dq-axis reference current; calculating a reference stator flux linkage, a reference modulation ratio and a reference voltage phase angle; looking up the table according to the carrier wave ratio and the reference modulation ratio to obtain an optimal switching vector mode and an optimal flux linkage apocentric distance of offline optimization; determining an optimal switching vector mode of the current control time domain; calculating an optimal reference stator flux linkage; calculating a reference voltage vector according to sampling and calculation delay; calculating a switching vector sequence and action time; a switching signal is generated. Through off-line optimization, on-line table look-up and real-time synthesis calculation of the optimal switching vector mode, low-current harmonic and high-dynamic response control of the permanent magnet motor under a low carrier wave ratio is realized, the complexity of a control algorithm is simplified, and the efficiency and reliability of the system are improved.

The embodiment of the application provides a kind of control method and system of virtual motor based on variable step discrete model, belong to power electronics technical field.The control method includes: judging whether the voltage vector of the motor controller to be measured changes;In the case where it is judged that the voltage vector changes, the input voltage of virtual motor is calculated according to the voltage vector;The corresponding dq voltage is calculated according to the input voltage;The corresponding reference current is calculated according to the dq voltage;The reference voltage is calculated according to the reference current and dq current;The control signal of the virtual motor is determined according to the reference voltage.The control method and system can improve the control bandwidth and simulation accuracy of virtual motor, so that the port characteristics of virtual motor are closer to actual motor.