Dead-beat high-frequency square wave injection permanent magnet synchronous motor position intelligent prediction method

Abstract

The invention relates to a dead-beat high-frequency square wave injection permanent magnet synchronous motor position intelligent prediction method. The method comprises the steps of performing discrete processing on a voltage equation corresponding to the permanent magnet synchronous motor under a high-frequency square wave injection condition to obtain an actually measured current component of a current beat and a predicted current component of a next beat; performing increment analysis on the actually measured current component and the predicted current component to obtain a high-frequency increment of an adjacent beat, and performing differential operation on the actually measured current component of the current beat and the high-frequency increment of the adjacent beat to obtain a high-frequency current component of the current beat; constructing a high-frequency equivalent network corresponding to the voltage equation according to the high-frequency square wave and the high-frequency current component of the current beat, and performing coordinate conversion to obtain an angle association relationship between the high-frequency current component of the current beat and the electrical angle error; and compensating the electrical angle error according to the angle association relationship, and deducing to obtain an electrical angle predicted value of the next beat. By adopting the method, the position prediction precision and the system operation stability of the permanent magnet synchronous motor can be improved.

Description

Technical Field

[0001] This application relates to the field of motor control technology, and in particular to a method for intelligent position prediction of permanent magnet synchronous motors with deadbeat-free high-frequency square wave injection. Background Technology

[0002] In the field of motor control technology, there is a method to excite a high-frequency current response containing implicit rotor position information by injecting an external high-frequency signal, thereby demodulating the rotor information. Related signal injection methods rely on the previous current sampling value to calculate the rotor position error, causing a delay in the position observation response of at least one control cycle. This amplifies the impact of inverter nonlinearity and noise on the demodulation results, severely affecting the position observation accuracy and system stability of permanent magnet synchronous motors under sensorless conditions. Summary of the Invention

[0003] Therefore, it is necessary to provide a method for intelligent position prediction of permanent magnet synchronous motors with beat-free high-frequency square wave injection to address the above-mentioned technical problems.

[0004] In a first aspect, this application provides a method for intelligent position prediction of a permanent magnet synchronous motor by injecting a beatless high-frequency square wave, including: Under the condition of preset high-frequency square wave injection, the voltage equation corresponding to the preset permanent magnet synchronous motor is discretized to obtain the measured current component of the current step and the predicted current component of the next step corresponding to the discrete equation structure. Incremental analysis is performed on the measured current component of the current beat and the predicted current component of the next beat to obtain the high-frequency increment of the adjacent beat. Differential operation is performed on the measured current component of the current beat and the high-frequency increment of the adjacent beat to obtain the high-frequency current component of the current beat. Based on the preset high-frequency square wave and the high-frequency current component of the current beat, a high-frequency equivalent network corresponding to the voltage equation is constructed. The high-frequency equivalent network is then subjected to coordinate transformation to obtain the angular correlation between the high-frequency current component of the current beat and the electrical angle error. Based on the aforementioned angle correlation, phase compensation is performed on the electrical angle error, and the predicted electrical angle value for the next beat is derived. This is used to intelligently predict the electrical angle position of the permanent magnet synchronous motor in the next beat based on a deadbeat high-frequency square wave.

[0005] Secondly, this application also provides a position intelligent prediction system for a permanent magnet synchronous motor with deadbeat-free high-frequency square wave injection, comprising: The discrete processing module is used to discretize the voltage equation corresponding to the preset permanent magnet synchronous motor under the condition of preset high-frequency square wave injection, so as to obtain the measured current component of the current step and the predicted current component of the next step corresponding to the discrete equation structure. The high-frequency analysis module is used to perform incremental analysis on the measured current component of the current beat and the predicted current component of the next beat to obtain the high-frequency increment of the adjacent beat. It also performs differential operation on the measured current component of the current beat and the high-frequency increment of the adjacent beat to obtain the high-frequency current component of the current beat. An angle analysis module is used to construct a high-frequency equivalent network corresponding to the voltage equation based on a preset high-frequency square wave and the high-frequency current component of the current beat, perform coordinate transformation on the high-frequency equivalent network, and obtain the angle correlation between the high-frequency current component of the current beat and the electrical angle error. The compensation module is used to perform phase compensation on the electrical angle error according to the angle correlation and derive the predicted electrical angle value for the next beat, so as to intelligently predict the electrical angle position of the permanent magnet synchronous motor in the next beat based on the deadbeat high-frequency square wave.

[0006] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the above steps.

[0007] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the above steps.

[0008] The aforementioned intelligent position prediction method, system, computer equipment, and computer-readable storage medium for permanent magnet synchronous motors (PMSMs) with deadbeat-free high-frequency square wave injection firstly derives the voltage equation of the PMSM through discretization, thereby obtaining the correspondence between the current of the current in the current step and the current in the next step without relying on continuous modeling, providing a discretization basis for high-frequency response prediction. Secondly, incremental and differential analysis is performed on the current components of the current in the current step and the current in the next step, thereby extracting the current change characteristics of the PMSM under high-frequency square wave injection conditions into high-frequency current components and eliminating interference from low-frequency steady-state components. Finally, a high-frequency equivalent network is constructed based on the high-frequency square wave and the high-frequency current components, and coordinate transformation is performed to establish a high-frequency... The angular correlation between current and electrical angle error provides constraints for angle compensation calculation. Finally, phase compensation is performed on the high-frequency current component based on the angular correlation to obtain an electrical angle prediction value consistent with the timing of the digital control system. Based on this, the entire technical solution employs a layer-by-layer logic of discrete structure modeling, high-frequency component extraction, angle relationship modeling, and angle phase compensation to enable the electrical angle prediction to have low latency and high dynamic consistency. This effectively eliminates phase lag caused by discrete delay under sensorless conditions, combining the fast response of deadbeat control with the high-precision observation characteristics of high-frequency injection, thereby significantly improving the position prediction accuracy and system operation stability of the permanent magnet synchronous motor. Attached Figure Description

[0009] To more clearly illustrate the technical solutions in the embodiments or related technologies of this application, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 This is a flowchart illustrating an intelligent position prediction method for a permanent magnet synchronous motor with deadbeat-free high-frequency square wave injection in one embodiment. Figure 2 This is a spatial vector diagram of a permanent magnet synchronous motor in different coordinate systems in one embodiment; Figure 3 This is a timing diagram of beatless prediction under high-frequency square wave injection conditions in one embodiment; Figure 4 This is a system control block diagram for beatless prediction under high-frequency square wave injection conditions in one embodiment; Figure 5 This is a block diagram of a permanent magnet synchronous motor position intelligent prediction system with deadbeat-free high-frequency square wave injection in one embodiment. Detailed Implementation

[0011] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0012] In one embodiment, such as Figure 1 As shown, a method for intelligent position prediction of a permanent magnet synchronous motor by injecting a beatless high-frequency square wave is provided. This embodiment illustrates the application of this method to a server. It is understood that this method can also be applied to a terminal, or to a system including a terminal and a server, and can be implemented through the interaction between the terminal and the server. In this embodiment, the method includes the following steps S101 to S104.

[0013] Step S101: Under the condition of preset high-frequency square wave injection, the voltage equation corresponding to the preset permanent magnet synchronous motor is discretized to obtain the measured current component of the current step and the predicted current component of the next step corresponding to the discrete equation structure.

[0014] For example, firstly, based on the voltage equation of the permanent magnet synchronous motor, the differential form in the continuous time domain is discretized through sampling periods to construct a discrete equation structure that conforms to the characteristics of a digital control system. Specifically, during the discretization process, for the dynamic relationship between stator voltage and current, the current rate of change term is discretized and approximated using the Euler forward method, so that the change in current between two adjacent sampling periods is jointly determined by the inductance, resistance, and angular velocity parameters of the permanent magnet synchronous motor. Furthermore, to ensure that the discrete equation structure maintains analytical stability under high-frequency injection conditions, a high-frequency square wave voltage is introduced as an excitation term during the discretization process, so that the instantaneous response of voltage disturbance to current can be reflected in each sampling period.

[0015] Subsequently, based on the measured current component and driving voltage component of the current cycle obtained from sampling, the predicted current component of the next cycle is recursively calculated using a discrete equation structure. At the same time, based on the measured current component and driving voltage component of the previous cycle obtained from sampling, the measured current component of the current cycle is presented correspondingly using a discrete equation structure.

[0016] Based on this, this discretization modeling method can express the variation of motor current during different sampling cycles in the form of a time series without relying on continuous differentiation, thus providing a quantitative calculation basis for subsequent high-frequency response incremental analysis.

[0017] Step S102: Perform incremental analysis on the measured current component of the current beat and the predicted current component of the next beat to obtain the high-frequency increment of the adjacent beat. Perform differential operation on the measured current component of the current beat and the high-frequency increment of the adjacent beat to obtain the high-frequency current component of the current beat.

[0018] For example, firstly, incremental analysis is performed on the measured current component of the current cycle and the predicted current component of the next cycle obtained in the aforementioned steps, under the condition of time index alignment, to obtain the current change between adjacent cycles. Specifically, this current change is used to characterize the dynamic response characteristics of the current changing with the sampling period under high-frequency square wave injection conditions, and can reflect the response sensitivity of the digital control system under high-frequency disturbances. Subsequently, the obtained current change is combined with the corresponding voltage excitation differential to establish the incremental mapping relationship between current and voltage in the high-frequency range, and the high-frequency increment set between adjacent cycles is obtained accordingly.

[0019] Furthermore, to further extract the pure high-frequency response component from the high-frequency increment set, a differential operation is performed on the measured current component of the current pulse and the high-frequency increment of the adjacent pulse to eliminate the residual low-frequency steady-state components in the high-frequency increment and highlight the transient changes caused by high-frequency injection. Finally, by time-aligning and filtering the differentially processed signal, the high-frequency current component of the current pulse is obtained. This high-frequency current component reflects the true instantaneous response characteristics of the permanent magnet synchronous motor under high-frequency square wave injection conditions.

[0020] Based on this, the processing method uses adjacent sampling difference to make the extraction of high-frequency current without additional high-order differential operations, while keeping it synchronized with the sampling period during the calculation process, so as to enable real-time implementation and continuous recursion in the digital control system.

[0021] Step S103: Construct a high-frequency equivalent network corresponding to the voltage equation based on the preset high-frequency square wave and the high-frequency current component of the current beat, perform coordinate transformation on the high-frequency equivalent network, and obtain the angular correlation between the high-frequency current component of the current beat and the electrical angle error.

[0022] For example, firstly, based on a preset high-frequency square wave and the high-frequency current component of the current pulse, a high-frequency equivalent network corresponding to the voltage equation is constructed. Specifically, during the construction process, the stator resistance voltage drop and back electromotive force terms in the voltage equation corresponding to the permanent magnet synchronous motor are treated as low-frequency components and ignored, retaining only the dominant role of the inductance term in high-frequency changes, so that the digital control system can be approximated as a linear inductance network under high-frequency square wave injection conditions. Next, based on this high-frequency equivalent network, using the high-frequency current component of the current pulse as input and the high-frequency voltage component as output, a linear coupling relationship between the two parameters is established, forming an algebraic expression reflecting the high-frequency response characteristics.

[0023] Subsequently, in order to correlate current changes with electrical angle deviations, a rotation coordinate system transformation operation is introduced into the constructed high-frequency equivalent network to transform the high-frequency equivalent network from the real rotation coordinate system to the estimated rotation coordinate system based on the estimated angle, so that coupling terms related to angle errors appear in the high-frequency current components.

[0024] Based on this, the functional relationship between electrical angle error and high-frequency current component can be explicitly expressed in algebraic form through this coordinate transformation, thereby obtaining the angular correlation between the high-frequency current component and electrical angle error of the current beat, providing an analytical basis for subsequent angle compensation and prediction.

[0025] Step S104: Based on the angle correlation, phase compensation is performed on the electrical angle error, and the predicted electrical angle value for the next beat is derived, so as to intelligently predict the electrical angle position of the permanent magnet synchronous motor in the next beat based on the deadbeat high-frequency square wave.

[0026] For example, firstly, based on the angular correlation determined in the preceding steps and combined with the discrete delay characteristics of the digital control system, a differential operation is performed on the high-frequency current component of the current beat and the measured current component of the previous beat to obtain the compensated error electrical angle. This compensated error electrical angle reflects the dynamic phase correction result of the digital control system under a one-beat delay condition, ensuring that the phase of the high-frequency current response remains consistent with the time reference of the digital control system.

[0027] Subsequently, based on the compensated electrical angle error, an electrical angle prediction equation including a phase correction term is derived in the discrete time domain to reflect the electrical angle variation pattern of the current beat. Finally, the predicted electrical angle value for the next beat is output according to this electrical angle prediction equation. This predicted electrical angle value serves as a reference for the electrical angle position in the next sampling period, enabling intelligent recursive prediction of the electrical angle position under the condition of error-free high-frequency square wave injection.

[0028] In this embodiment, in step S101, the voltage equation of the permanent magnet synchronous motor is discretized and derived to obtain the correspondence between the current of the current in the current step and the current in the next step without relying on continuous modeling, thus providing a discretization basis for high-frequency response prediction. In step S102, incremental and differential analysis is performed based on the current components of the current step and the current in the next step to extract the current change characteristics of the permanent magnet synchronous motor under high-frequency square wave injection conditions into high-frequency current components, eliminating interference from low-frequency steady-state components. In step S103, a high-frequency equivalent network is constructed based on the high-frequency square wave and the high-frequency current components, and coordinate transformation is performed to establish the angular correlation between the high-frequency current and the electrical angle error. The system provides constraints for angle compensation calculation; in step S104, phase compensation is performed on the high-frequency current component according to the angle correlation to obtain an electrical angle prediction value consistent with the timing of the digital control system; based on this, in the whole technical solution, through the layer-by-layer logic of discrete structure modeling, high-frequency component extraction, angle relationship modeling and angle phase compensation, the electrical angle prediction has low latency and high dynamic consistency, thereby effectively eliminating the phase lag caused by discrete delay under the condition of no position sensor, and combining the fast response of deadbeat control with the high-precision observation characteristics of high-frequency injection, so as to significantly improve the position prediction accuracy and system operation stability of permanent magnet synchronous motor.

[0029] In an exemplary embodiment, under the condition of preset high-frequency square wave injection, the voltage equation corresponding to the preset permanent magnet synchronous motor is discretized to obtain the measured current component of the current step and the predicted current component of the next step corresponding to the discrete equation structure, including steps S201 to S203.

[0030] Step S201: Determine the voltage equation of the permanent magnet synchronous motor in the preset rotating coordinate system.

[0031] For example, the voltage equation of a permanent magnet synchronous motor in a preset rotating coordinate system can be expressed by referring to equation (1): (1) In equation (1), , These represent the stator voltage components in the direct and quadrature axes of the rotating coordinate system, respectively. , These represent the stator current components along the direct and quadrature axes, respectively. , These represent the equivalent inductance along the direct axis and quadrature axis, respectively. Indicates stator resistance. Represents electric angular velocity. This indicates the magnetic flux linkage of a permanent magnet.

[0032] In the above formula, the stator voltage component in the direct axis It is caused by the stator resistance voltage drop in the direct axis Voltage drop caused by inductance change and quadrature axis current Coupling terms under rotating magnetic field The stator voltage components in the quadrature axis are jointly determined; It is caused by the stator resistance voltage drop in the quadrature axis. Voltage drop caused by inductance change Direct-axis current Coupling terms under rotating magnetic field and the back electromotive force term caused by the permanent magnet flux linkage It was decided jointly.

[0033] Therefore, the above equation describes the voltage-current relationship of the permanent magnet synchronous motor in the rotating coordinate system, that is, it reflects the distribution law of the stator voltage among the three parts of the resistor voltage drop, the inductor energy storage change and the electric angular velocity coupling, so as to reflect the dynamic electrical behavior of the permanent magnet synchronous motor in continuous time and provide a modeling basis for subsequent discretization prediction.

[0034] Step S202: Based on the measured current component of the current step and the high-frequency square wave injected into the direct axis of the rotating coordinate system, the voltage equation is forward discretized to obtain the predicted current component of the next step corresponding to the discretized equation structure and in the preset estimated direct axis and preset estimated intersection axis.

[0035] For example, the expression for the predicted current component corresponding to the discrete equation structure can be found in equation (2): (2) In equation (2), , These represent the predicted current components in the estimated direct axis and estimated quadrature axis of the estimated rotating coordinate system for the next cycle, respectively. , These represent the measured current components currently positioned on the estimated direct axis and the estimated quadrature axis, respectively. , Let represent the equivalent inductance along the direct and quadrature axes of the rotating coordinate system, respectively. Indicates the sampling period. Indicates stator resistance; , This represents the given voltage component that is currently being measured in the estimated direct axis and the estimated quadrature axis. This represents the high-frequency square wave voltage term. , These represent the estimated and actual electric angular velocities of the current shot, respectively. This indicates the magnetic flux linkage of a permanent magnet.

[0036] In the above equation, on the one hand, the predicted current component in the estimated direct axis of the next step... It is the measured current component in the estimated direct axis of the current image. During the sampling period The internal result is a combination of main voltage drive, additional voltage excitation, loss compensation, and magnetic coupling. Together, they constitute the estimated effective voltage input on the direct axis. This is the resistance loss term. This is a cross-axis current coupling term.

[0037] On the other hand, the predicted current component in the estimated cross-axis of the next beat It is the measured current component in the estimated cross-axis of the current image. During the sampling period The internal result is a combination of main voltage drive, loss compensation, magnetic coupling, and flux linkage rotation. This constitutes the estimated effective voltage input of the quadrature axis. This is the resistance loss term. This is a direct-axis current coupling term. This is the back electromotive force term.

[0038] Based on this, the above formula characterizes the forward extrapolation relationship of the current of a permanent magnet synchronous motor in discrete time under the condition of direct-axis injection of high-frequency square wave. Specifically, by using the forward Euler discretization method, the voltage-current change of the permanent magnet synchronous motor is discretized within the sampling period, so that the measured current of the current sampling in the current step is recursively extrapolated to the predicted current of the next step after one time step. Thus, this expression reveals the time evolution law of the current under high-frequency square wave excitation, providing a discretized time update basis for the high-frequency dynamic response of the motor current.

[0039] Step S203: Based on the measured current component of the previous frame, the measured current component of the current frame, and the high-frequency square wave injected into the direct axis of the rotating coordinate system, the voltage equation is subjected to forward discretization processing with time index shifted backward to obtain the measured current component of the current frame corresponding to the discrete equation structure and in the preset estimated direct axis and preset estimated intersection axis.

[0040] (3) In equation (3), , These represent the measured current components currently positioned in the estimated direct axis and estimated quadrature axis of the estimated rotating coordinate system, respectively. , These represent the measured current components in the estimated direct axis and estimated quadrature axis of the previous cycle, respectively. , Let represent the equivalent inductance along the direct and quadrature axes of the rotating coordinate system, respectively. Indicates the sampling period. Indicates stator resistance; , This represents the given voltage component in the estimated direct axis and estimated quadrature axis of the previous step; Represents a symbolic function. This represents a high-frequency square wave voltage signal. This represents the amplitude of a high-frequency square wave. This represents the high-frequency square wave voltage term for the next pulse. , Let these represent the estimated and actual electric angular velocities of the previous pulse, respectively. Indicates permanent magnet flux linkage. This indicates the magnetic flux linkage of a permanent magnet.

[0041] In the above formula, on the one hand, the measured current component in the estimated direct axis of the current shot. It is based on the measured current component in the estimated direct axis from the previous step. During the sampling period The internal result is a combination of main voltage drive, additional voltage excitation, loss compensation, and magnetic coupling. Together, they constitute the estimated effective voltage input on the direct axis. This is the resistance loss term. This is a cross-axis current coupling term.

[0042] On the other hand, the measured current component in the estimated quadrature axis of the current image. The measured current component in the estimated quadrature axis of the previous step is derived from the previous step. During the sampling period The internal result is a combination of main voltage drive, loss compensation, magnetic coupling, and flux linkage rotation. This constitutes the estimated effective voltage input of the quadrature axis. This is the resistance loss term. This is a direct-axis current coupling term. This is the back electromotive force term.

[0043] Based on this, the above equation represents the description of the measured change of current in the manner of shifting the time index under the same discrete equation structure as equation (2). Specifically, by using the forward Euler discretization method, the voltage-current change of the permanent magnet synchronous motor is discretized within the sampling period, so that the measured current sampled in the previous time step is presented as the measured current in the current time step after one time step. Thus, the current response process under the shifted time index is accurately reflected in the discrete equation structure, so as to realize the synchronous discrete expression of the current change in the previous time step, the current time step, the next time step, etc. in equations (2) and (3).

[0044] In this embodiment, in step S201, the coupling relationship between voltage and current is determined based on the voltage equation of the permanent magnet synchronous motor in the rotating coordinate system, thus providing a continuous equation basis for discretization solution; in step S202, the voltage equation is discretized by forward Euler based on the measured current component of the current sampling period and the high-frequency square wave injection condition, thereby obtaining the predicted current component of the next sampling period, realizing the discrete recursion of the current response in the current sampling period; in step S203, the voltage equation is discretized by forward Euler with time index shifted based on the measured current components of the previous and current sampling periods, realizing the discrete presentation of the current response in the historical sampling period; based on this, in the entire technical solution, the current response of the permanent magnet synchronous motor obtains discretization, recursion, and time-domain consistent calculation characteristics under the high-frequency square wave injection condition, providing an accurate basis for subsequent high-frequency response extraction.

[0045] In an exemplary embodiment, incremental analysis is performed on the measured current component of the current beat and the predicted current component of the next beat to obtain the high-frequency increment of the adjacent beat, including step S301.

[0046] Step S301: Under the condition that the angular velocity of the permanent magnet synchronous motor is constant and half of the preset PWM frequency is used as the injection frequency, the measured current component of the current step and the predicted current component of the next step are differentially calculated to obtain the voltage increment and current increment in the preset estimated direct axis and the preset estimated quadrature axis, which are used as the high-frequency increment of the adjacent step.

[0047] For example, on the one hand, when the actual electric angular velocity of the permanent magnet synchronous motor is constant, the value in equation (2) is... With equation (3) Corresponding to the same value; on the other hand, when half of the preset PWM frequency is used as the injection frequency, the value in equation (2) is... With equation (3) The opposite value corresponds to the square wave polarity being exactly reversed between adjacent sampling points.

[0048] Based on this, the first-order difference calculation of equation (2) and equation (3) is performed to realize the increment analysis, that is, the difference between the two equations is taken. The expression of the high-frequency increment of the adjacent beat can be referred to equation (4): (4) In Equation 4, , These represent the predicted current components in the estimated direct axis and estimated quadrature axis of the estimated rotating coordinate system for the next cycle, respectively. , These represent the measured current components currently positioned on the estimated direct axis and the estimated quadrature axis, respectively. , These represent the measured current components in the estimated direct axis and estimated quadrature axis of the previous step, respectively. , Let represent the equivalent inductance along the direct and quadrature axes of the rotating coordinate system, respectively. Indicates the sampling period. Indicates stator resistance. This represents the estimated electric angular velocity of the previous beat. This represents the high-frequency square wave voltage term of the current frame.

[0049] Furthermore, , These represent the voltage increments in the estimated direct axis and estimated quadrature axis of adjacent beats, respectively, which are equivalent to the differences between the voltage components of the current beat and the voltage components of the previous beat. , These represent the current increments in the estimated direct axis and estimated quadrature axis of adjacent cycles, respectively, which are equivalent to the differences between the current component of the current cycle and the current component of the previous cycle.

[0050] In the above formula, on the one hand, the predicted current component in the estimated direct axis of the next step... It is the measured current component on the direct axis estimated by the current beat and the previous beat. , The recursive result is formed by combining discrete differences. This recursive process occurs during the sampling period. The internal design integrates the combined effects of main voltage increment, additional voltage excitation, loss compensation, and magnetic coupling. For direct-axis voltage increment, It is twice the high-frequency square wave voltage term. This is the resistance loss term based on the direct-axis current increment. This is a quadrature-axis current coupling term based on the direct-axis current increment.

[0051] On the other hand, the predicted current component in the estimated cross-axis of the next beat It is the measured current component of the estimated intersection axis between the current beat and the previous beat. , The recursive result is formed by combining discrete differences. This recursive process occurs during the sampling period. The internal design integrates the combined effects of main voltage increment, loss compensation, and magnetic coupling. For quadrature axis voltage increment, This is the resistance loss term based on the quadrature-axis current increment. This is a direct-axis current coupling term based on quadrature-axis current increments.

[0052] As can be seen, the above equation describes the discrete current prediction relationship of a permanent magnet synchronous motor under high-frequency square wave injection conditions. It eliminates the continuous time dependence of the flux linkage parameter through discrete differential form, making the expression of high-frequency dynamic response more in line with the actual sampling characteristics, and providing a discretized and de-fluxed data basis for the prediction of electrical angle of beatless high-frequency response.

[0053] In this embodiment, in step S301, under the condition that the angular velocity of the permanent magnet synchronous motor is constant and half of the preset PWM frequency is used as the injection frequency, the measured current component of the current cycle and the predicted current component of the next cycle are differentially calculated to reflect the dynamic change of the current between adjacent sampling cycles in a discrete form, thereby obtaining the high-frequency increment set under the high-frequency square wave injection condition. Based on this, in the whole technical solution, by performing differential and de-coupling processing on the current change relationship within adjacent sampling cycles, the high-frequency dynamic response expression is more in line with the discrete characteristics of the digital control system, avoiding the cumulative error and time-domain drift of the flux linkage parameter in the high-frequency response derivation process.

[0054] In an exemplary embodiment, the measured current component of the current beat and the high-frequency increment of the adjacent beat are differentially calculated to obtain the high-frequency current component of the current beat, including step S401.

[0055] Step S401: Perform center difference calculation on the measured current component of the current beat and the high frequency increment of the adjacent beat to obtain the high frequency current component of the current beat in the preset estimated direct axis and the preset estimated quadrature axis.

[0056] For example, by performing a central difference operation on equation (4) and equation (3), that is, taking half of the difference between the two equations, the expression of the resulting high-frequency current component can be found in equation (5): (5) In equation (5), , These represent the high-frequency current components currently pulsed along the estimated direct axis and the estimated quadrature axis, respectively. , These represent the current increments in the estimated direct axis and estimated quadrature axis for adjacent pulses, respectively. , These represent the voltage increments in the estimated direct axis and estimated quadrature axis, respectively, for adjacent pulses. Indicates the sampling period. Indicates stator resistance. This represents the estimated electric angular velocity of the previous beat. This represents the high-frequency square wave voltage term of the current frame.

[0057] In the above formula, on the one hand, the high-frequency current component currently in the estimated direct axis is... It is the average change of current in the direct axis The result is formed in conjunction with the main voltage increment, additional voltage excitation, loss compensation, and magnetic coupling, among which, For direct-axis voltage increment, It is twice the high-frequency square wave voltage term. This is the resistance loss term based on the direct-axis current increment. This is a quadrature-axis current coupling term based on the direct-axis current increment.

[0058] On the other hand, the high-frequency current component currently being estimated in the quadrature axis is being tested. It is the average change of current in the quadrature axis The result is formed together with the main voltage increment, loss compensation, and magnetic coupling, among which, For quadrature axis voltage increment, This is the resistance loss term based on the quadrature-axis current increment. This is a direct-axis current coupling term based on quadrature-axis current increments.

[0059] Therefore, although the flux linkage parameter is not explicitly included in equation (4), it is evident that... , The residual low-frequency components that are still indirectly related to the flux linkage change are used to further suppress these low-frequency components and extract the pure high-frequency dynamic response. Therefore, Equation (4) and Equation (3) need to be calculated by center difference. This process is essentially a filtering operation. The slowly changing flux linkage related terms are filtered out by center difference of adjacent beats, and only the high-frequency components excited by the high-frequency square wave injection are retained. The resulting Equation (5) not only continues the discrete prediction structure of Equation (4), but also further eliminates the pseudo high-frequency interference introduced by the slowly changing flux linkage or calculation lag, so that the obtained high-frequency current components can more realistically reflect the high-frequency response characteristics of the permanent magnet synchronous motor under the high-frequency square wave injection condition.

[0060] In this embodiment, in step S401, a center differential operation is performed based on the measured current component of the current beat and the high-frequency increment of the adjacent beat to obtain the high-frequency current component. That is, it is equivalent to using the symmetrical structural relationship of the two beats to balance the high-frequency response of voltage and current, thereby retaining the pure high-frequency dynamic components excited by the high-frequency square wave injection. Based on this, in the whole technical solution, the residual low-frequency and flux linkage related terms are further filtered out through the center differential structure to ensure that the extracted high-frequency current component has better frequency domain purity and timing consistency.

[0061] In an exemplary embodiment, a high-frequency equivalent network corresponding to the voltage equation is constructed based on a preset high-frequency square wave and the high-frequency current component of the current beat, including steps S501 to S502.

[0062] Step S501: Under the condition of preset high-frequency square wave injection, the resistance voltage drop term and the back electromotive force term in the voltage equation are ignored, and the high-frequency voltage component generated by the inductance term in the preset direct axis and preset quadrature axis is retained.

[0063] Step S502: Using the high-frequency current components in the direct axis and quadrature axis as input and the high-frequency voltage components in the direct axis and quadrature axis as output, construct a linear mapping relationship between the high-frequency current components and the high-frequency voltage components to obtain the high-frequency equivalent network corresponding to the voltage equation.

[0064] For example, in equation (1), the electric angular velocity at low speed is... The frequency is relatively small, and the injection frequency is much higher than the fundamental frequency, so the stator voltage can be ignored, thus simplifying equation (1) to equation (6): (6) In equation (6), , These represent the high-frequency voltage components along the direct and quadrature axes, respectively. , These represent the high-frequency current components in the direct axis and quadrature axis, respectively. , These represent the equivalent inductance along the direct axis and quadrature axis, respectively. This indicates that the high-frequency response is independent in both axes. This represents the time differential operator, used to characterize the rate of change of high-frequency current components under high-frequency injection conditions.

[0065] It can be seen that the above equation describes the high-frequency equivalent network relationship of the permanent magnet synchronous motor under high-frequency square wave injection conditions. That is, the voltage and current have a linear mapping relationship in the high-frequency range. The change of the high-frequency voltage component is completely obtained by the change rate of the high-frequency current component through the equivalent inductance, so as to ignore the resistance voltage drop term, magnetic coupling term and back electromotive force term in equation (1). Through this equivalent modeling method, the high-frequency electrical behavior of the permanent magnet synchronous motor can be decoupled from the low-frequency magnetic flux and resistance effect, providing a simplified and linear high-frequency response basis for subsequent angle error analysis and electric angle dynamic estimation.

[0066] In this embodiment, in step S501, the voltage equation is structured under high-frequency square wave injection conditions, ignoring the resistance voltage drop and back electromotive force terms. This allows the voltage equation to retain only the high-frequency components dominated by the inductance term, effectively eliminating low-frequency steady-state components and making the high-frequency dynamic relationship mathematically purer. In step S502, based on the linear mapping relationship between the high-frequency current component and the high-frequency voltage component, a high-frequency voltage-high-frequency current mapping relationship is established using the two-axis equivalent inductance as an intermediate conversion parameter, thereby forming a high-frequency equivalent network that can be used to characterize the high-frequency response of the motor. Based on this, in the entire technical solution, the linearization and decoupling expression of the high-frequency dynamic characteristics of the motor are achieved through the simplification of the voltage equation and the construction of the high-frequency equivalent relationship.

[0067] In an exemplary embodiment, coordinate transformation is performed on the high-frequency equivalent network to obtain the angular correlation between the high-frequency current component and the electrical angle error of the current frame, including steps S601 to S602.

[0068] Step S601 involves converting the high-frequency equivalent network in the preset rotating coordinate system into the target high-frequency equivalent network in the preset estimated rotating coordinate system.

[0069] For example, the high-frequency equivalent network in the rotating coordinate system described by equation (6) is subjected to coordinate transformation to obtain the estimated target high-frequency equivalent network in the rotating coordinate system, the expression of which can be referred to by equation (7): (7) In equation (7), , These represent the high-frequency voltage components in the estimated direct axis and the estimated quadrature axis, respectively. , These represent the high-frequency current components in the estimation of the direct axis and the estimation of the quadrature axis, respectively. , These represent the equivalent inductance along the direct axis and quadrature axis, respectively. Indicates electrical angle error. This represents the time differential operator.

[0070] The above equation as a whole expresses the process of transforming the high-frequency equivalent network in equation (6) from the real rotating coordinate system to the estimated rotating coordinate system, so that the rate of change of the high-frequency current component and the high-frequency voltage component still satisfy the linear mapping relationship in the estimated rotating coordinate system, but their amplitude and phase are subject to electrical angle errors. The modulation establishes an implicit coupling relationship between the electrical angle error and the high-frequency current variation.

[0071] Furthermore, Figure 2 The diagram shows the spatial vector diagram of a permanent magnet synchronous motor in different coordinate systems. The α-β coordinate system represents the stationary coordinate system, which is fixed in space with the stator windings to describe the components of stator voltage and current in the stationary space. The dq coordinate system represents the real rotating coordinate system, which rotates with the rotor magnetic poles to reflect the actual electromagnetic energy conversion of the motor. The coordinate system represents the estimated rotating coordinate system, which is calculated by a pre-defined sensorless algorithm or observer for vector decoupling of the control system.

[0072] Furthermore, in A high-frequency square wave voltage signal is injected into the shaft at this time. The angle between the α-axis and the α-axis is the predicted electrical angle. The angle between the d-axis and the α-axis is the true value of the electrical angle. Therefore, the predicted electrical angle value With the true value of electrical angle The difference between them is the electrical angle error. .

[0073] Step S602: In the target high-frequency equivalent network, based on the high-frequency square wave injected in the direct axis of the rotating coordinate system, the high-frequency current component of the current frame is expanded and decomposed to obtain the angular correlation between the high-frequency current component of the current frame and the electrical angle error.

[0074] For example, according to ,as well as ， Simplifying equation (7), we get equation (8): (8) In equation (8), , These represent the high-frequency current components in the estimation of the direct axis and the estimation of the quadrature axis, respectively. Indicates a high-frequency square wave voltage; This represents the average inductance corresponding to the direct-axis equivalent inductance and the quadrature-axis equivalent inductance. This represents the inductance difference between the direct-axis equivalent inductance and the quadrature-axis equivalent inductance. , Indicates the high-frequency current response as a function of electrical angle error The changing amplitude-phase modulation relationship.

[0075] Therefore, assuming that the high-frequency square wave is injected only into the direct axis, equation (7) can be simplified to obtain an explicit expression for the rate of change of the high-frequency current, namely equation (8). Thus, equation (8) reveals the high-frequency current component under the condition of high-frequency square wave injection. The direct algebraic relationship between electrical angle errors shows that when the electrical angle error changes, both the current amplitude and phase exhibit a periodic modulation pattern, reflecting the angular correlation between the high-frequency current component of the current beat and the electrical angle error.

[0076] In this embodiment, in step S601, the high-frequency equivalent network in the rotating coordinate system is transformed to the target high-frequency equivalent network in the estimated rotating coordinate system, thereby explicitly introducing the electrical angle error variable in the mathematical structure, so that the current response equation can reflect the amplitude and phase modulation characteristics of the electrical angle deviation on the high-frequency current component based on the estimated rotating coordinate system; in step S602, based on the condition that a high-frequency square wave is injected only on the direct axis, the target high-frequency equivalent network is expanded and simplified in coordinates, thereby establishing the mapping relationship between the high-frequency current component and the electrical angle error, and realizing the explicit correlation characterization of the electrical angle error on the high-frequency current response.

[0077] In an exemplary embodiment, phase compensation is performed on the electrical angle error based on the angle correlation, and the predicted electrical angle value for the next step is derived, including step S701.

[0078] Step S701: Based on the discrete delay characteristics of the digital control system corresponding to the permanent magnet synchronous motor, in the angle correlation relationship, the high-frequency current component of the current step and the measured high-frequency current component of the previous step are differentially calculated to obtain the compensated electrical angle error, and the predicted electrical angle value of the current step is derived.

[0079] For example, when in equation (8) When it is small enough, it can be approximated as From this, the error electrical angle can be obtained. The expression: (9) In equation (9), This represents the average inductance corresponding to the direct-axis equivalent inductance and the quadrature-axis equivalent inductance. This represents the inductance difference between the direct-axis equivalent inductance and the quadrature-axis equivalent inductance. This represents the high-frequency square wave voltage term. Indicates the sampling period; This represents the actual high-frequency current component in the estimated quadrature axis of the current beat, which is obtained by the central difference operation performed on the current components in the estimated quadrature axis of the current beat and the previous beat, respectively. This represents the high-frequency current component in the estimated cross axis of the previous beat, which is obtained by performing a central difference operation on the current components in the estimated cross axis of the previous beat and the beat before that.

[0080] Therefore, the above formula establishes a direct linear relationship between the electrical angle error and the high-frequency current response, reflecting the coupling law between the current differential change and the rotor position deviation of the motor under high-frequency square wave injection. Specifically, by performing differential calculation on the high-frequency current components of adjacent sampling periods, and using the average value and difference of the inductance parameters to construct a proportional coefficient, an analytical expression of the error electrical angle can be derived from the current change.

[0081] Furthermore, due to the inherent discrete delay characteristics of digital control systems, the measured high-frequency current component corresponding to the high-frequency current component in the previous cycle is obtained to determine the error electrical angle. The expression for phase compensation is: (10) In equation (10), This represents the high-frequency current component in the estimated quadrature axis of the current beat, which is obtained by the central difference operation of the current components in the estimated quadrature axis of the next beat and the current beat, respectively. This represents the high-frequency current component in the estimated cross axis of the previous beat, which is obtained by performing a central difference operation on the current components in the estimated cross axis of the current beat and the previous beat, respectively.

[0082] It can be seen that Equation (10) introduces the discrete delay characteristic of the digital control system on the basis of Equation (9). By combining the predicted current component with the measured current component of the previous step, the phase compensation of the error electrical angle is achieved. Specifically, this compensation process corrects the timing misalignment between sampling and execution, so that the electrical angle estimation result is aligned with the actual rotor response in time. Thus, Equation (10) can improve the real-time accuracy of the error electrical angle under dynamic operating conditions, providing a key correction basis for the synchronization of high-frequency response and control timing.

[0083] Furthermore, by expanding equation (10), the compensated error electrical angle is obtained. The final expression is: (11) In equation (11), This represents the voltage increment currently in the estimated quadrature axis. This represents the current increment currently in the estimated quadrature axis. This represents the current increment currently measured in the estimated direct axis; Indicates stator resistance. This represents the estimated electric angular velocity in the previous beat. This represents the equivalent inductance in the quadrature axis.

[0084] As can be seen, the above formula further discretizes and engineers the calculation of the error electrical angle, and uses measurable voltage increment, current increment and known motor parameters (inductance, stator resistance, estimated electrical angular velocity, etc.) to construct a complete expression equation for the error electrical angle; specifically, by expanding the difference form of equation (10) into an algebraic combination of voltage increment and current increment, the flux linkage related terms and continuous derivative terms are completely eliminated, thus providing a calculable and low-delay core implementation method for intelligent prediction of electrical angle position under the condition of beatless high-frequency square wave injection.

[0085] In this embodiment, in step S701, based on the discrete delay characteristics of the digital control system, the high-frequency current component of the current frame and the measured high-frequency current component of the previous frame are differentially calculated to obtain the electrical angle error compensation result including the timing delay effect, so that the electrical angle estimation and the control signal are re-aligned in time. Based on this, in the whole technical solution, the electrical angle calculation has real-time performance and timing consistency, effectively eliminating the angle offset caused by the sampling lag of the digital control system, and improving the dynamic accuracy and stability of electrical angle estimation under the condition of no position sensor.

[0086] In one exemplary embodiment, Figure 3 The time series diagram of beatless prediction under high-frequency square wave injection conditions is shown, where (k-1) is contained on the time axis t. k (k+1) (k+2) Four sampling periods, high-frequency square wave acting on the high-frequency voltage component on the direct axis During the sampling period (k-1) With sampling period (k+1) The internal values ​​are respectively represented by voltage values. and in the sampling period k With sampling period (k+2) The internal values ​​are respectively represented by voltage values. .

[0087] Correspondingly, in the high-frequency current component of the direct axis During the sampling period (k-1) With sampling period (k+1) The internal manifestations are respectively from the current value To current value Linear growth, and at sampling period k With sampling period (k+2) The internal manifestations are respectively from the current value To current value The voltage decreases linearly, thus forming a frequency-dependent voltage component. Symmetrical current response with alternating polarities.

[0088] A complete cycle of the PWM carrier corresponds to each sampling cycle, the PWM carrier peak ARR corresponds to the midpoint of each sampling cycle, and each PWM update corresponds to the start time of the next sampling cycle. Let k... Taking the sampling period as an example, in the first half of the period, current loop control calculation is performed; in the second half of the period, current sampling is performed, and (k+1) is adjusted based on the sampling results. The electrical angle state during the sampling period is predicted.

[0089] Based on this, in the current sampling period, both the current sampling of the current sampling period and the state prediction of the next sampling period are completed, so that the prediction result can be used for control output in the PWM update stage of the next period. Therefore, this process advances the calculation step that was originally delayed by one beat to be completed in the current period, realizing feedforward compensation for the one-beat sampling delay in the digital control system, thereby achieving true deadbeat predictive control under high-frequency square wave injection conditions, making voltage injection and current response synchronized in the time domain, and ensuring the real-time performance and dynamic consistency of angle estimation.

[0090] In one exemplary embodiment, Figure 4 The system control block diagram for deadbeat prediction under high-frequency square wave injection conditions is shown, wherein: firstly, the three-phase current signal of the permanent magnet synchronous motor (IPMSM) is used. , , As input, the current components in the two-phase stationary α-β coordinate system are obtained through Clarke transformation. and Combined with the predicted electrical angle value The estimated rotation is obtained through the Park transform. Current components in coordinate system and This serves as the basis for current loop and high-frequency signal extraction.

[0091] Furthermore, the current component and Predicted electrical angle value and quadrature axis voltage components They jointly participate in the prediction process of the next current cycle to obtain the next cycle in the estimated rotation. Predicted current components in the coordinate system and The high-frequency current component is thus extracted. and This reflects the high-frequency response characteristics of the dynamic changes in electrical angle, providing a basis for subsequent error correction and angle compensation.

[0092] Furthermore, the high-frequency current component and The input is fed into a PLL (Phase-locked loop) circuit and combined with the predicted electrical angle value. The compensated electrical angle is constructed, and the predicted value of the compensated electrical angle is derived from it to update the coordinate transformation reference, so that the current vector is aligned with the direction of the rotor magnetic field in real time and the current decoupling is correct.

[0093] Furthermore, the compensated predicted electric angular velocity is derived from the compensated predicted electric angle value. Given an electric angular velocity Compared with the compensated predicted electric angular velocity After the subtraction operation, the quadrature-axis current command is output through the PI controller. Then, the quadrature axis current command Compared with high-frequency current components Extracted equivalent feedback current After the subtraction operation, the quadrature-axis voltage command is output through the PI regulator. At the same time, direct-axis current command Set to zero, direct-axis current command Compared with high-frequency current components The obtained equivalent feedback current After the subtraction operation, the PI controller outputs the initial voltage command, which, combined with a high-frequency signal injection, outputs the direct-axis voltage command. .

[0094] Furthermore, the estimated rotation Cross-axis voltage command in coordinate system With direct axis voltage command Combined with the compensated electrical angle prediction value The voltage components in the two-phase stationary α-β coordinate system are obtained by inverse Park transform. and For voltage components and SVPWM modulation is performed to obtain the three-phase voltage signal. , , Finally, the three-phase voltage signals , , The inverter acts on the IPMSM to achieve a closed-loop control of current and torque.

[0095] Based on this, by combining high-frequency signal injection with deadbeat prediction, the current response and voltage output are updated synchronously within one sampling period, eliminating the one-beat delay in traditional control and enabling precise timing alignment of electrical angle estimation and voltage modulation, thereby significantly improving the dynamic control performance and steady-state accuracy of sensorless IPMSM.

[0096] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0097] Based on the same inventive concept, this application also provides a system for intelligent prediction of permanent magnet synchronous motor position using deadbeat high-frequency square wave injection, which implements the aforementioned method for intelligent prediction of permanent magnet synchronous motor position using deadbeat high-frequency square wave injection. The solution provided by this system is similar to the solution described in the above method. Therefore, the specific limitations of one or more embodiments of the system for intelligent prediction of permanent magnet synchronous motor position using deadbeat high-frequency square wave injection provided below can be found in the limitations of the method for intelligent prediction of permanent magnet synchronous motor position using deadbeat high-frequency square wave injection described above, and will not be repeated here.

[0098] In one exemplary embodiment, such as Figure 5 As shown, a position intelligent prediction system for a permanent magnet synchronous motor with deadbeat-free high-frequency square wave injection is provided, comprising: a discrete processing module 101, a high-frequency analysis module 102, an angle analysis module 103, and a compensation module 104, wherein: Discrete processing module 101 is used to discretize the voltage equation corresponding to the preset permanent magnet synchronous motor under the condition of preset high frequency square wave injection, so as to obtain the measured current component of the current step and the predicted current component of the next step corresponding to the discrete equation structure. The high-frequency analysis module 102 is used to perform incremental analysis on the measured current component of the current beat and the predicted current component of the next beat to obtain the high-frequency increment of the adjacent beat, and to perform differential operation on the measured current component of the current beat and the high-frequency increment of the adjacent beat to obtain the high-frequency current component of the current beat. Angle analysis module 103 is used to construct a high-frequency equivalent network corresponding to the voltage equation based on the preset high-frequency square wave and the high-frequency current component of the current beat, perform coordinate transformation on the high-frequency equivalent network, and obtain the angle correlation between the high-frequency current component of the current beat and the electrical angle error. The compensation module 104 is used to perform phase compensation for electrical angle error based on the angle correlation and derive the predicted electrical angle value for the next beat, so as to make intelligent prediction of electrical angle position of permanent magnet synchronous motor based on deadbeat high-frequency square wave in the next beat.

[0099] In an exemplary embodiment, the discretization module 101 is further configured to: determine the voltage equation of the permanent magnet synchronous motor in a preset rotating coordinate system; perform forward discretization on the voltage equation based on the measured current component of the current step and the high-frequency square wave injected into the direct axis of the rotating coordinate system to obtain the predicted current component of the next step corresponding to the discrete equation structure and in the preset estimated direct axis and preset estimated intersection axis; and perform forward discretization on the voltage equation based on the measured current component of the previous step, the measured current component of the current step, and the high-frequency square wave injected into the direct axis of the rotating coordinate system to obtain the measured current component of the current step corresponding to the discrete equation structure and in the preset estimated direct axis and preset estimated intersection axis.

[0100] In an exemplary embodiment, the high-frequency analysis module 102 is further configured to: perform differential calculation on the measured current component of the current step and the predicted current component of the next step under the condition that the angular velocity of the permanent magnet synchronous motor is constant and half of the preset PWM frequency is used as the injection frequency, to obtain the voltage increment and current increment in the preset estimated direct axis and the preset estimated quadrature axis, so as to serve as the high-frequency increment of the adjacent step.

[0101] In an exemplary embodiment, the high-frequency analysis module 102 is further configured to: perform a center difference operation on the measured current component of the current beat and the high-frequency increment of the adjacent beat to obtain the high-frequency current component of the current beat in the preset estimated direct axis and the preset estimated quadrature axis.

[0102] In an exemplary embodiment, the angle analysis module 103 is further configured to: under the condition of preset high-frequency square wave injection, ignore the resistance voltage drop term, magnetic coupling term and back electromotive force term in the voltage equation, and retain the high-frequency voltage component generated by the inductance term in the preset direct axis and preset quadrature axis; take the high-frequency current component in the direct axis and quadrature axis as input and the high-frequency voltage component in the direct axis and quadrature axis as output, construct a linear mapping relationship between the high-frequency current component and the high-frequency voltage component, so as to obtain the high-frequency equivalent network corresponding to the voltage equation.

[0103] In an exemplary embodiment, the angle analysis module 103 is further configured to: convert the high-frequency equivalent network in the preset rotating coordinate system into a target high-frequency equivalent network in the preset estimated rotating coordinate system; in the target high-frequency equivalent network, according to the high-frequency square wave injected in the direct axis of the rotating coordinate system, perform coordinate expansion and decomposition on the high-frequency current component of the current beat to obtain the angular correlation between the high-frequency current component of the current beat and the electrical angle error.

[0104] In an exemplary embodiment, the compensation module 104 is further configured to: based on the discrete delay characteristics of the digital control system corresponding to the permanent magnet synchronous motor, perform differential calculation on the high-frequency current component of the current step and the measured high-frequency current component of the previous step in the angle correlation relationship, obtain the compensated electrical angle error, and derive the predicted electrical angle value of the next step.

[0105] The modules in the aforementioned deadbeat-free high-frequency square wave injection permanent magnet synchronous motor position prediction system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in hardware within or independently of the processor in a computer device, or stored in software within the computer device's memory, allowing the processor to call and execute the corresponding operations of each module.

[0106] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of any of the above embodiments.

[0107] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the above embodiments.

[0108] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0109] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0110] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A dead-beat high-frequency square-wave injection permanent magnet synchronous motor position intelligent prediction method, characterized in that, The method comprises: Under the condition of preset high-frequency square wave injection, discretely processing a voltage equation corresponding to a preset permanent magnet synchronous motor to obtain a current measured component of a current beat corresponding to a discrete equation structure and a predicted current component of a next beat; Incrementally analyzing the current measured component of the current beat and the predicted current component of the next beat to obtain a high-frequency increment of an adjacent beat, and performing a difference operation on the current measured component of the current beat and the high-frequency increment of the adjacent beat to obtain a high-frequency current component of the current beat; According to the preset high-frequency square wave and the high-frequency current component of the current beat, constructing a high-frequency equivalent network corresponding to the voltage equation, and performing coordinate conversion on the high-frequency equivalent network to obtain an angle correlation between the high-frequency current component of the current beat and an electrical angle error; According to the angle correlation, phase compensating the electrical angle error, and deriving a predicted value of the electrical angle of the next beat for intelligent prediction of the electrical angle position of the permanent magnet synchronous motor based on the high-frequency square wave without the current beat in the next beat.

2. The method of claim 1, wherein, Under the condition of preset high-frequency square wave injection, discretely processing a voltage equation corresponding to a preset permanent magnet synchronous motor to obtain a current measured component of a current beat corresponding to a discrete equation structure and a predicted current component of a next beat, comprising: determining a voltage equation of the permanent magnet synchronous motor in a preset rotating coordinate system; According to the current measured component of the current beat and the high-frequency square wave injected in the direct axis of the rotating coordinate system, performing forward discrete processing on the voltage equation to obtain a predicted current component of the next beat corresponding to a discrete equation structure and in a preset estimated direct axis and a preset estimated quadrature axis; According to the current measured component of the current beat and the high-frequency square wave injected in the direct axis of the rotating coordinate system, performing forward discrete processing on the voltage equation to obtain a predicted current component of the next beat corresponding to a discrete equation structure and in a preset estimated direct axis and a preset estimated quadrature axis.

3. The method of claim 1, wherein, The incrementally analyzing the current measured component of the current beat and the predicted current component of the next beat to obtain a high-frequency increment of an adjacent beat, comprising: Under the condition that the angular velocity of the permanent magnet synchronous motor is constant and half of the preset PWM frequency is used as the injection frequency, performing difference calculation on the current measured component of the current beat and the predicted current component of the next beat to obtain voltage increments and current increments in the preset estimated direct axis and the preset estimated quadrature axis as the high-frequency increment of the adjacent beat.

4. The method of claim 1, wherein, The difference operation on the current measured component of the current beat and the high-frequency increment of the adjacent beat to obtain the high-frequency current component of the current beat, comprising: Performing central difference operation on the current measured component of the current beat and the high-frequency increment of the adjacent beat to obtain the high-frequency current component of the current beat in the preset estimated direct axis and the preset estimated quadrature axis.

5. The method of claim 1, wherein, The high-frequency equivalent network corresponding to the voltage equation is constructed according to the preset high-frequency square wave and the high-frequency current component of the current beat, comprising: Under the condition of preset high-frequency square wave injection, the resistance voltage drop term, the magnetic coupling term and the back electromotive force term in the voltage equation are ignored, and the high-frequency voltage component generated by the inductance term in the preset direct axis and the preset quadrature axis is retained; The linear mapping relationship between the high-frequency current component and the high-frequency voltage component is constructed with the high-frequency current component in the direct axis and the high-frequency current component in the quadrature axis as input and the high-frequency voltage component in the direct axis and the high-frequency voltage component in the quadrature axis as output, so as to obtain the high-frequency equivalent network corresponding to the voltage equation.

6. The method of claim 1, wherein, The coordinate conversion of the high-frequency equivalent network is performed to obtain the angle correlation between the high-frequency current component of the current beat and the electrical angle error. The high-frequency equivalent network in the preset rotating coordinate system is converted into a target high-frequency equivalent network in a preset estimated rotating coordinate system. In the target high-frequency equivalent network, the high-frequency current component of the current beat is coordinate unfolded and decomposed according to the high-frequency square wave injected in the direct axis of the rotating coordinate system, so as to obtain the angle correlation between the high-frequency current component of the current beat and the electrical angle error.

7. The method of claim 1, wherein, The phase compensation of the electrical angle error is performed according to the angle correlation, and the electrical angle prediction value of the next beat is derived. According to the discrete delay characteristics of the digital control system corresponding to the permanent magnet synchronous motor, the high-frequency current component of the current beat and the measured high-frequency current component of the previous beat are differentially calculated in the angle correlation to obtain the compensated electrical angle error, and the electrical angle prediction value of the next beat is derived.

8. A dead-beat high frequency square wave injection based permanent magnet synchronous motor position intelligent prediction system, characterized in that, The system comprises: A discrete processing module is configured to perform discrete processing on a voltage equation corresponding to a preset permanent magnet synchronous motor under the condition of preset high-frequency square wave injection, so as to obtain a measured current component of the current beat and a predicted current component of the next beat corresponding to a discrete equation structure. A high-frequency analysis module is configured to perform incremental analysis on the measured current component of the current beat and the predicted current component of the next beat to obtain a high-frequency increment of the adjacent beat, and perform differential operation on the measured current component of the current beat and the high-frequency increment of the adjacent beat to obtain the high-frequency current component of the current beat. An angle analysis module is configured to construct a high-frequency equivalent network corresponding to the voltage equation according to the preset high-frequency square wave and the high-frequency current component of the current beat, and perform coordinate conversion on the high-frequency equivalent network to obtain the angle correlation between the high-frequency current component of the current beat and the electrical angle error. A compensation module is configured to perform phase compensation on the electrical angle error according to the angle correlation, and derive the electrical angle prediction value of the next beat, so as to intelligently predict the electrical angle position of the permanent magnet synchronous motor based on the beatless high-frequency square wave in the next beat. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-8 when the computer program is executed by the processor. The processor executes the computer program to implement the steps of the method of any one of claims 1 to 7.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method of any one of claims 1 to 7.

Images