Sensorless control method and device for asynchronous motor, electronic equipment and storage medium
By acquiring stator voltage and current in the asynchronous motor, and combining low-pass filtering and adaptive rate current model, the rotor flux linkage and angular velocity are estimated in real time. This solves the problems of speed identification accuracy and system stability of asynchronous motors in the full speed range, and achieves higher control accuracy and robustness.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-01-01
- Publication Date
- 2026-03-27
AI Technical Summary
Existing sensorless control methods for asynchronous motors suffer from low speed identification accuracy and insufficient system robustness at both low and high speeds, especially due to poor adaptability caused by changes in motor parameters.
By collecting the stator voltage and current of the asynchronous motor and transforming them into a stationary two-phase coordinate system, and combining the voltage model of the low-pass filter and the current model of the speed state variable, the rotor flux linkage and angular velocity are estimated in real time. The model parameters are adjusted using the adaptive rate, and the synchronous electric angle is obtained and fed back to the control system.
It improves the accuracy of speed and position estimation and system stability across the entire speed range, reduces parameter sensitivity, and enhances the control accuracy and robustness of asynchronous motors.
Smart Images
Figure CN121749833A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of motor control technology, and in particular to a sensorless control method, device, electronic device, and storage medium for asynchronous motors. Background Technology
[0002] As a core system in the field of new energy vehicles, the electric drive system is a key research area for scholars both domestically and internationally, with the drive motor being the most important component. Common motors on the market are AC asynchronous motors and permanent magnet synchronous motors. Permanent magnet synchronous motors use permanent magnets as the rotor excitation power source, giving them a significant advantage in high power density. However, due to the high cost of rare earth materials, many researchers have shifted their focus to asynchronous motors.
[0003] In sensorless control of asynchronous motors, traditional methods typically rely on flux observers that combine voltage and current models. Voltage models are effective at medium to high speeds, but become inaccurate at low speeds due to weak back EMF, integral drift, and stator resistance. While current models are suitable for low speeds, their performance is limited by variations in the rotor time constant. Although hybrid models can complement each other, they still rely excessively on motor parameters, exhibiting poor adaptability to changing operating conditions, leading to decreased speed identification accuracy and insufficient system robustness. Summary of the Invention
[0004] In view of this, the purpose of the present invention is to provide a sensorless control method, device, electronic device and storage medium for asynchronous motors, which reduces parameter sensitivity and improves the accuracy of speed and position estimation and system stability across the entire speed range.
[0005] In a first aspect, embodiments of the present invention provide a sensorless control method for an asynchronous motor, the method comprising: acquiring the stator voltage and stator current of the asynchronous motor and transforming them to a stationary two-phase coordinate system to obtain target stator voltage and target stator current in the stationary coordinate system; based on the target stator voltage and target stator current, obtaining a first rotor flux linkage observation value through a voltage model including a low-pass filter; based on the target stator current, obtaining a second rotor flux linkage observation value through a current model including a speed state variable; determining a rotor flux linkage observation error based on the difference between the first rotor flux linkage observation value and the second rotor flux linkage observation value; determining an estimated value of the rotor angular velocity in real time based on the rotor flux linkage observation error and a pre-set adaptive rate; determining a slip angular frequency based on the estimated value of the rotor angular velocity and the second rotor flux linkage observation value; summing and integrating the estimated value of the rotor angular velocity and the slip angular frequency to obtain the synchronous electrical angle; and feeding back the estimated value of the rotor angular velocity and the synchronous electrical angle to the control system of the asynchronous motor.
[0006] In a preferred embodiment of the present invention, the above-described method for obtaining the first rotor flux linkage observation value based on the target stator voltage and target stator current through a voltage model including a low-pass filter includes: constructing a rotor flux linkage voltage equation in a stationary coordinate system based on the target stator voltage and target stator current; replacing the pure integration operation in the rotor flux linkage voltage equation with a low-pass filter with an adjustable cutoff frequency; inputting the target stator voltage and target stator current into the voltage model including the low-pass filter for calculation, and outputting the first rotor flux linkage observation value.
[0007] In a preferred embodiment of the present invention, the above-mentioned method of obtaining the second rotor flux observation value based on the target stator current and through a current model including the rotational speed state variable includes: establishing a rotor flux current equation including the rotor electric angular velocity state variable based on the target stator current; replacing the rotor electric angular velocity in the rotor flux current equation with the estimated value to be identified to form an adjustable model; inputting the target stator current into the adjustable model and outputting the second rotor flux observation value.
[0008] In a preferred embodiment of the present invention, the above-mentioned method of determining the estimated value of rotor angular velocity in real time based on rotor flux linkage observation error and a pre-set adaptive rate includes: determining an error signal based on a first rotor flux linkage observation value and a second rotor flux linkage observation value; substituting the error signal into a proportional-integral adaptive rate formula containing the adaptive rate to calculate and obtain a formula output; and updating and outputting the estimated value of rotor angular velocity in real time based on the formula output.
[0009] In a preferred embodiment of the present invention, the above-mentioned summing and integration of the estimated rotor angular velocity and slip angular frequency to obtain the synchronous electrical angle includes: calculating the slip angular frequency based on the second rotor flux linkage observation value and the target stator current, according to the rotor magnetic field orientation relationship; adding the estimated rotor angular velocity and slip angular frequency to obtain the synchronous electrical angular frequency; and performing an integral operation on the synchronous electrical angular frequency to obtain the synchronous electrical angle.
[0010] In a preferred embodiment of the present invention, the above method further includes a low-speed start-up enhancement step, specifically: when the asynchronous motor starts or the estimated value of the rotor angular velocity is lower than a preset angular velocity threshold, a high-frequency signal injection method is executed to obtain the initial rotor position, and the initial rotor position is assigned as the initial value of integration to the integrator performing the integration operation, or fused with the synchronous electric angle.
[0011] In a preferred embodiment of the present invention, feeding back the estimated rotor angular velocity and the synchronous electrical angle to the control system of the asynchronous motor includes: using the estimated rotor angular velocity as a speed feedback signal and inputting it to the speed loop regulator; and using the synchronous electrical angle to perform Park transformation and inverse Park transformation to achieve current decoupling control.
[0012] Secondly, embodiments of the present invention also provide a sensorless control device for an asynchronous motor, comprising: a coordinate transformation module for acquiring the stator voltage and stator current of the asynchronous motor and transforming them to a stationary two-phase coordinate system to obtain the target stator voltage and target stator current in the stationary coordinate system; a first rotor flux linkage observation determination module for obtaining the first rotor flux linkage observation value based on the target stator voltage and target stator current through a voltage model including a low-pass filter; and a second rotor flux linkage observation determination module for obtaining the second rotor flux linkage observation value based on the target stator current through a current model including a speed state variable; and a rotor flux linkage observation error determination module. The system comprises the following modules: a difference determination module, used to determine the rotor flux linkage observation error based on the difference between the first and second rotor flux linkage observation values; an estimation value determination module, used to determine the estimated value of the rotor angular velocity in real time based on the rotor flux linkage observation error and a pre-set adaptive rate; a slip angular frequency determination module, used to determine the slip angular frequency based on the estimated value of the rotor angular velocity and the second rotor flux linkage observation value; a synchronous electrical angle determination module, used to sum and integrate the estimated value of the rotor angular velocity and the slip angular frequency to obtain the synchronous electrical angle; and a data feedback module, used to feed back the estimated value of the rotor angular velocity and the synchronous electrical angle to the control system of the asynchronous motor.
[0013] Thirdly, embodiments of the present invention also provide an electronic device, including a processor and a memory, wherein the memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the sensorless control method for asynchronous motors described in the first aspect.
[0014] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing computer-executable instructions. When the computer-executable instructions are invoked and executed by a processor, the computer-executable instructions cause the processor to implement the sensorless control method for asynchronous motors described in the first aspect.
[0015] The embodiments of the present invention bring the following beneficial effects: This invention provides a sensorless control method, device, electronic device, and storage medium for an asynchronous motor. The method involves acquiring the stator voltage and stator current of the asynchronous motor and transforming them to a stationary two-phase coordinate system to obtain target stator voltage and target stator current in the stationary coordinate system. Based on the target stator voltage and target stator current, a first rotor flux linkage observation value is obtained using a voltage model including a low-pass filter. Based on the target stator current, a second rotor flux linkage observation value is obtained using a current model including speed state variables. The rotor flux linkage observation error is determined based on the difference between the first and second rotor flux linkage observation values. Based on the rotor flux linkage observation error and a pre-set adaptive rate, an estimated value of the rotor angular velocity is determined in real time. The slip angular frequency is determined based on the estimated rotor angular velocity and the second rotor flux linkage observation value. The estimated rotor angular velocity and slip angular frequency are summed and integrated to obtain the synchronous electrical angle. The estimated rotor angular velocity and synchronous electrical angle are fed back to the asynchronous motor control system. This method reduces parameter sensitivity and improves the accuracy of speed and position estimation and system stability across the entire speed domain.
[0016] Other features and advantages of this disclosure will be set forth in the following description, or some features and advantages may be inferred from the description or determined without doubt, or may be learned by practicing the techniques described above.
[0017] To make the above-mentioned objects, features and advantages of this disclosure more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description
[0018] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.
[0019] Figure 1 A flowchart of a sensorless control method for an asynchronous motor provided in an embodiment of the present invention; Figure 2 A flowchart of another sensorless control method for an asynchronous motor provided in an embodiment of the present invention; Figure 3 A block diagram of a rotational speed identification observer based on the MRAS algorithm provided in this embodiment of the invention; Figure 4 A flux linkage estimation curve based on a rotor current model is provided for an embodiment of the present invention. Figure 5This is a comparison diagram of the identified rotational speed and the actual motor rotational speed provided in an embodiment of the present invention; Figure 6 The estimated synchronous electrical angle and encoder measured angle comparison curve provided for embodiments of the present invention; Figure 7 This is a schematic diagram of the structure of a sensorless control device for an asynchronous motor provided in an embodiment of the present invention; Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation
[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0021] In recent years, with global warming and increased environmental pollution, my country's energy structure has undergone a major transformation. From the perspective of the automotive industry, due to the limitations of traditional energy sources and constraints on sustainable development, a large number of new energy vehicles have entered the market and are gradually replacing gasoline-powered vehicles. This structural shift has provided important support for the implementation of the "dual-carbon" target.
[0022] Electric drive systems, as the core systems in the field of new energy vehicles, are a key research focus for scholars both domestically and internationally, with the drive motor being the most important component. Common motors on the market are AC asynchronous motors and permanent magnet synchronous motors. Permanent magnet synchronous motors use permanent magnets as the rotor excitation power source, giving them a significant advantage in high power density. However, due to the high cost of rare earth materials, many researchers have shifted their focus to asynchronous motors. Asynchronous motors are low-cost, have good speed regulation performance, and are easier to control compared to DC motors.
[0023] An asynchronous motor is a multivariable, nonlinear, and coupled system. To achieve precise control of an asynchronous motor, the rotor flux linkage must first be estimated. However, the rotor flux linkage cannot be directly obtained in an asynchronous motor; it needs to be acquired using information such as voltage and current, which contain information about the rotor flux linkage. The most common methods for obtaining rotor information are voltage modeling and current modeling. Since the back electromotive force is difficult to estimate at low speeds, voltage-based rotor flux linkage estimation is often used for medium to high speeds. This method introduces a pure integrator, and the voltage drop across the stator resistance has a significant impact on the flux linkage estimation. Therefore, a current-based model is needed to complement the estimation. Current models perform well at low speeds, but the rotor time constant determines the system's degradation, and the rotor time constant changes with the rotational speed.
[0024] To address the above shortcomings, some scholars have adopted a flux estimation method that combines voltage and current models, compensating the difference between the voltage and current models into the back electromotive force. While this hybrid observer avoids the limitations of a single observer, its over-reliance on motor parameters makes the system unable to adapt to changes in operating conditions, leading to inaccurate speed estimation.
[0025] Based on this, the present invention provides a sensorless control method, device, electronic device, and storage medium for an asynchronous motor. This method involves acquiring the stator voltage and stator current of the asynchronous motor and transforming them to a stationary two-phase coordinate system to obtain the target stator voltage and target stator current in the stationary coordinate system. Based on the target stator voltage and target stator current, a first rotor flux linkage observation value is obtained through a voltage model including a low-pass filter. Based on the target stator current, a second rotor flux linkage observation value is obtained through a current model including speed state variables. The rotor flux linkage observation error is determined based on the difference between the first and second rotor flux linkage observation values. Based on the rotor flux linkage observation error and a pre-set adaptive rate, an estimated rotor angular velocity is determined in real time. The slip angular frequency is determined based on the estimated rotor angular velocity and the second rotor flux linkage observation value. The estimated rotor angular velocity and the slip angular frequency are summed and integrated to obtain the synchronous electrical angle. The estimated rotor angular velocity and the synchronous electrical angle are fed back to the asynchronous motor control system. This approach reduces parameter sensitivity and improves the accuracy of speed and position estimation and system stability across the entire speed domain.
[0026] To facilitate understanding of this embodiment, a sensorless control method for an asynchronous motor disclosed in this embodiment of the invention will first be described in detail.
[0027] Example 1 This invention provides a sensorless control method for asynchronous motors. Figure 1 This is a flowchart illustrating a sensorless control method for an asynchronous motor, as provided in an embodiment of the present invention. Figure 1 As shown, the sensorless control method for the asynchronous motor may include the following steps: Step S101: Collect the stator voltage and stator current of the asynchronous motor and transform them to a stationary two-phase coordinate system to obtain the target stator voltage and target stator current in the stationary coordinate system.
[0028] Among them, asynchronous motors refer to induction motors, whose rotor speed and stator rotating magnetic field speed have a slip difference.
[0029] The stator voltage and stator current are the three-phase voltages (Ua, Ub, Uc) applied to the stator windings of the motor and the corresponding three-phase currents (Ia, Ib, Ic) flowing into the windings. They are physical quantities that can be measured directly or indirectly. For example, voltage sensors (such as voltage divider resistors + isolation operational amplifiers) and current sensors (such as Hall current sensors) are used to acquire the three-phase voltage and current signals in real time.
[0030] The stationary two-phase coordinate system (α-β coordinate system) is a mathematical coordinate system that converts three-phase AC quantities into two-phase AC quantities. The α-axis coincides with the a-phase axis, and the β-axis leads the α-axis by 90 electrical degrees. After the transformation, the variables still change in a sinusoidal form, but the coupling between the three-phase variables is eliminated, facilitating analysis and calculation.
[0031] Here, the target stator voltage and target stator current refer to the voltage components (uα, uβ) and current components (iα, iβ) used for subsequent calculations in the α-β coordinate system after coordinate transformation. For example, the Clark transformation formula can be used for transformation.
[0032] Furthermore, after the acquisition stage, a digital filter (such as a moving average filter or a low-pass filter) can be introduced to perform secondary filtering on the transformed target stator voltage and target stator current, so as to further suppress switching noise and high-frequency interference and improve the input signal quality of the observation model.
[0033] Furthermore, signal validity verification logic can be set to address sensor failures or extreme operating conditions. For example, when the detected current amplitude exceeds a set multiple of the motor's rated value, or when there is an abnormal voltage-current phase difference, the protection logic is activated and the system switches to standby observation or open-loop mode to prevent the system from becoming unstable due to erroneous signals.
[0034] Step S102: Based on the target stator voltage and target stator current, the first rotor flux linkage observation value is obtained through a voltage model including a low-pass filter.
[0035] The voltage model is a mathematical model used to estimate the rotor flux linkage. This model does not contain speed information but relies on pure integral calculations.
[0036] In this circuit, the low-pass filter is used to replace the pure integrator in the circuit or algorithm unit. Pure integrators are sensitive to DC bias and low-frequency noise, which can easily lead to output saturation or drift. A first-order low-pass filter approximates an integrator in the frequency domain (at frequencies much higher than its cutoff frequency) while also suppressing low-frequency interference.
[0037] The first rotor flux linkage observation is the rotor flux linkage component estimated in the α-β coordinate system, calculated based on the voltage model and the current electrical signal.
[0038] Step S103: Based on the target stator current, the second rotor flux observation value is obtained through a current model that includes the rotational speed state variable.
[0039] The current model is a mathematical model derived from the electromagnetic relations on the rotor side of the motor (rotor loop equations) and used to estimate the rotor flux linkage. This model explicitly includes the rotor angular velocity as a state variable.
[0040] In the differential equation of the current model, the rotational speed state variable represents the actual electrical angular velocity of the rotor. In sensorless control, this value is unknown and is replaced by its estimated value.
[0041] The second rotor flux linkage observation is a rotor flux linkage component calculated based on the current model, target stator current, and speed estimate.
[0042] Step S104: Determine the rotor flux observation error based on the difference between the first rotor flux observation value and the second rotor flux observation value.
[0043] The rotor flux linkage observation error is the difference between the first rotor flux linkage observation (as a reference) and the second rotor flux linkage observation (as the output of the adjustable model) on the α and β axes. This error reflects the degree of mismatch between the two models due to inaccurate speed estimates used in the current model.
[0044] Step S105: Based on the rotor flux observation error and the pre-set adaptive rate, determine the estimated value of the rotor angular velocity in real time.
[0045] In a Model Reference Adaptive System (MRAS), the adaptive rate is a mathematical rule or algorithm for adjusting the adjustable model parameters based on the error signal. Its goal is to asymptotically approach zero, so that the flux linkage output by the current model tracks the flux linkage output by the voltage model.
[0046] The estimated value of the rotor angular velocity is the rotor electrical angular velocity identified in real time through the MRAS process.
[0047] Step S106: Determine the slip angular frequency based on the estimated value of the rotor angular velocity and the observed value of the second rotor flux linkage.
[0048] The slip angular frequency is the difference between the electric angular velocity of the stator rotating magnetic field and the actual electric angular velocity of the rotor. It reflects the load magnitude and is a key quantity for achieving torque control in vector control.
[0049] Step S107: Summing and integrating the estimated rotor angular velocity with the slip angular frequency to obtain the synchronous electrical angle.
[0050] The synchronous electrical angle is the electrical angular position of the stator's synthesized magnetomotive force (i.e., the rotating magnetic field) in space. It is the key angle information required by the Park converter and SVPWM modules.
[0051] In step S108, the estimated value of the rotor angular velocity and the synchronous electrical angle are fed back to the control system of the asynchronous motor.
[0052] In this context, the control system of an asynchronous motor typically refers to a vector control system based on rotor field orientation. Its core components include modules such as an outer speed loop, an inner current loop (d-axis excitation current loop and q-axis torque current loop), coordinate transformation, and pulse width modulation (e.g., SVPWM).
[0053] The sensorless control method for asynchronous motors provided in this invention can obtain target stator voltage and target stator current in a stationary two-phase coordinate system by acquiring the stator voltage and stator current of the asynchronous motor and transforming them to a stationary two-phase coordinate system. Based on the target stator voltage and target stator current, a first rotor flux linkage observation value is obtained through a voltage model including a low-pass filter. Based on the target stator current, a second rotor flux linkage observation value is obtained through a current model including speed state variables. The rotor flux linkage observation error is determined based on the difference between the first and second rotor flux linkage observation values. Based on the rotor flux linkage observation error and a pre-set adaptive rate, an estimated value of the rotor angular velocity is determined in real time. The slip angular frequency is determined based on the estimated rotor angular velocity and the second rotor flux linkage observation value. The estimated rotor angular velocity and the slip angular frequency are summed and integrated to obtain the synchronous electrical angle. The estimated rotor angular velocity and the synchronous electrical angle are fed back to the control system of the asynchronous motor. This method reduces parameter sensitivity and improves the accuracy of speed and position estimation and system stability across the entire speed domain.
[0054] Example 2 This invention also provides another sensorless control method for asynchronous motors; this method is implemented based on the method described in the above embodiments.
[0055] Figure 2 A flowchart of another sensorless control method for an asynchronous motor provided by an embodiment of the present invention is shown below. Figure 2 As shown, the sensorless control method for the asynchronous motor may include the following steps: Step S201: Collect the stator voltage and stator current of the asynchronous motor and transform them to a stationary two-phase coordinate system to obtain the target stator voltage and target stator current in the stationary coordinate system.
[0056] The Clark transformation formula can be used for this transformation.
[0057] Step S202: Based on the target stator voltage and target stator current, the first rotor flux linkage observation value is obtained through a voltage model including a low-pass filter.
[0058] Specifically, based on the target stator voltage and target stator current, the first rotor flux linkage observation value is obtained through a voltage model including a low-pass filter. This can include: constructing a rotor flux linkage voltage equation in a stationary coordinate system based on the target stator voltage and target stator current; replacing the pure integration operation in the rotor flux linkage voltage equation with a low-pass filter with an adjustable cutoff frequency; inputting the target stator voltage and target stator current into the voltage model including the low-pass filter for calculation, and outputting the first rotor flux linkage observation value.
[0059] Step S203: Based on the target stator current, the second rotor flux observation value is obtained through a current model that includes the rotational speed state variable.
[0060] Specifically, based on the target stator current, the second rotor flux observation value is obtained through a current model that includes the rotational speed state variable. This can include: establishing a rotor flux current equation that includes the rotor electric angular velocity state variable based on the target stator current; replacing the rotor electric angular velocity in the rotor flux current equation with the estimated value to be identified to form an adjustable model; inputting the target stator current into the adjustable model and outputting the second rotor flux observation value.
[0061] Step S204: Determine the rotor flux observation error based on the difference between the first rotor flux observation value and the second rotor flux observation value.
[0062] Step S205: Based on the rotor flux observation error and the pre-set adaptive rate, determine the estimated value of the rotor angular velocity in real time.
[0063] Specifically, the estimated value of the rotor angular velocity is determined in real time based on the rotor flux linkage observation error and the pre-set adaptive rate. This can include: determining the error signal based on the first rotor flux linkage observation value and the second rotor flux linkage observation value; substituting the error signal into the proportional-integral adaptive rate formula containing the adaptive rate to calculate the formula output; and updating and outputting the estimated value of the rotor angular velocity in real time based on the formula output.
[0064] Step S206: Determine the slip angular frequency based on the estimated value of the rotor angular velocity and the observed value of the second rotor flux linkage.
[0065] Step S207: When the asynchronous motor starts or the estimated value of the rotor angular velocity is lower than the preset angular velocity threshold, the high-frequency signal injection method is executed to obtain the initial rotor position, and the initial rotor position is assigned as the initial value of integration to the integrator for integration calculation, or fused with the synchronous electric angle.
[0066] In practical implementation, a complete link needs to be designed, including signal injection (such as rotating high-frequency voltage), response extraction (bandpass filtering or demodulation), and position calculation. The integration strategy with MRAS is crucial. For example, a weighted switching approach can be adopted: initially relying entirely on the high-frequency injection method; once the reliability of the rotational speed estimated by MRAS (which can be judged by the error magnitude) reaches a threshold, the weight of MRAS is gradually increased, smoothly transitioning to a state where MRAS is the primary method, high-frequency injection is secondary, or MRAS operates entirely.
[0067] In step S208, the estimated value of the rotor angular velocity is summed and integrated with the slip angular frequency to obtain the synchronous electrical angle.
[0068] Specifically, the synchronous electrical angle is obtained by summing and integrating the estimated rotor angular velocity and slip angular frequency. This can include: calculating the slip angular frequency based on the second rotor flux linkage observation and the target stator current, according to the rotor magnetic field orientation relationship; adding the estimated rotor angular velocity and slip angular frequency to obtain the synchronous electrical angular frequency; and integrating the synchronous electrical angular frequency to obtain the synchronous electrical angle.
[0069] Step S209: The estimated value of the rotor angular velocity and the synchronous electrical angle are fed back to the control system of the asynchronous motor.
[0070] Specifically, feeding back the estimated rotor angular velocity and synchronous electrical angle to the control system of the asynchronous motor can include: using the estimated rotor angular velocity as a speed feedback signal and inputting it to the speed loop regulator; and using the synchronous electrical angle to perform Park transformation and inverse Park transformation to achieve current decoupling control.
[0071] In one embodiment of the application: 1. Establish the voltage equation and current equation for the asynchronous motor in the stationary coordinate system, respectively; The rotor flux linkage voltage equation is expressed as: (1) in, , They are respectively Rotor flux linkage in the voltage model under coordinate axes , They are respectively Stator voltage under shaft, , They are respectively Stator current under the coordinate axes , , , These are the stator resistance, stator inductance, rotor inductance, and mutual inductance between the stator and rotor of an asynchronous motor. Let be the leakage inductance coefficient, satisfying: The rotor angular velocity will be included. The rotor current equation is expressed as: (2) in, , They are respectively Rotor flux linkage in the current model under coordinate axes For differential operators, Let be the rotor time constant, satisfying: , Let be the rotor electric angular velocity. Since the rotor flux linkage voltage model contains a pure integrator, a DC bias will occur. Furthermore, when the motor operates at low speed, the voltage drop across the stator resistance is small, and using a pure integrator will increase the estimation error of the rotor flux linkage. Considering the bias caused by the integrator, a low-pass filter was designed to replace the pure integrator. Therefore, equation (1) is rewritten as: (3) in, Let be the cutoff angular frequency of the low-pass filter, and ,in, This is the cutoff frequency.
[0072] 2. Since the rotor current model contains rotational speed information, it is used as an adjustable model, and the estimated angular velocity is expressed in terms of observed values. The observation equation for the rotor current is then simplified as follows: (4) In the formula, Representing the observed value, based on the characteristics of the asynchronous motor, when the observed rotor current model is consistent with the rotor current model, the electric angular velocity... Gradually approaching the true value. Assuming that the voltage model in equation (3) is consistent with the current model in equation (2), the difference between equation (4) and equation (2) is taken, and the observation error is defined as: (5) Combining equations (2), (4), and (5), we can obtain: (6) in, Equation (6) can be further written as: (7) in, To estimate the error, , .
[0073] 3. According to the super-Popov superstability theory, for a system to be stable, the following inequality must be satisfied: (8) in, Let be a positive real number that converges. The estimated rotational speed is defined as a function of proportional-integral form, by selecting an adaptive rate to make the identified rotational speed close to the true value: (9) Rearranging equations (8) and (9), the inequalities are: (10) in, , The values are respectively: (11) In the formula, , Let be the coefficient, and satisfy . Substituting equation (11) into equation (10) proves that equation (10) holds true. Therefore, equation (9) can be rewritten as: (12) In the formula, , For the proportional coefficient and integral coefficient in the adaptive rate. As can be seen from Equation (12), the rotor voltage equation of Equation (3) is used as the reference model, and the rotor current model of Equation (4) is used as the adjustable model. Combined with the adaptive rate, the identified speed can track the true value of the system.
[0074] 4. Calculate the slip angular frequency, and combine it with the identified rotor angular velocity to obtain the synchronization angle by integration.
[0075] Rotor field-oriented vector control is adopted to align the d-axis with the magnetic field direction, and the q-axis represents the torque component. To ensure that the d-axis always aligns with the magnetic field direction, the following condition must be met: (13) in, , for Rotor flux linkage in axial coordinates For synchronous electrical angle, , Let be the synchronous electric angular velocity and the slip angular frequency, respectively. According to equation (13), the slip angular frequency can be written as: (14) Replace the actual rotor angular velocity with the estimated value of equation (12), and combine equations (13) and (14) to feed the estimated synchronous electrical angle back into the system.
[0076] Based on the above embodiments, Figure 3 This is a block diagram of a rotational speed identification observer based on the MRAS algorithm, provided for an embodiment of the present invention.
[0077] Figure 3 In this model, the rotor flux linkage voltage equation after low-pass filtering is used as the reference model, and the rotor flux linkage current model is used as the adjustable model, combined with adaptive rate adjustment. and The value of is used to identify the rotational speed, which is also the estimated rotational speed required by the rotor flux linkage model.
[0078] Figure 4 The flux linkage estimation curve based on the rotor current model is provided for an embodiment of the present invention.
[0079] Figure 4 In the model, the rotor flux linkage estimated by the rotor flux linkage current model varies in a sinusoidal form, and its amplitude is consistent with the flux linkage amplitude calculated based on the motor model. Therefore, it can be deduced that the adjustable model selected in this embodiment is consistent with the adjustable model related to motor parameters, proving the feasibility of the proposed algorithm.
[0080] Figure 5 A comparison diagram of the identified rotational speed and the actual rotational speed of the motor provided in an embodiment of the present invention.
[0081] Figure 5 In the comparison between the estimated rotational speed and the actual motor speed, it can be seen that the identified motor speed can follow the actual speed changes very well. Because a low-pass filter is used instead of a pure integrator in the voltage model, the harmonic content of the rotational speed is reduced, allowing the motor to start stably even at low speeds.
[0082] Figure 6 The curve showing the comparison between the estimated synchronous electrical angle and the encoder measured angle provided for embodiments of the present invention.
[0083] Figure 6 As can be seen from the curve, when the motor starts, the rotor angle obtained by the speed integral identified by the MRAS algorithm responds first, and the estimated rotor angle is basically consistent with the angle measured by the mechanical encoder, which further illustrates the accuracy of the speed identification algorithm provided in the embodiments of this application.
[0084] Example 3 Corresponding to the above method embodiments, this invention provides a sensorless control device for asynchronous motors. Figure 7 This is a schematic diagram of the structure of a sensorless control device for an asynchronous motor provided in an embodiment of the present invention, as shown below. Figure 7 As shown, the sensorless control device for the asynchronous motor may include: The coordinate transformation module 301 is used to acquire the stator voltage and stator current of the asynchronous motor and transform them to a stationary two-phase coordinate system to obtain the target stator voltage and target stator current in the stationary coordinate system.
[0085] The first rotor flux linkage observation determination module 302 is used to obtain the first rotor flux linkage observation value based on the target stator voltage and target stator current through a voltage model including a low-pass filter.
[0086] The second rotor flux linkage observation determination module 303 is used to obtain the second rotor flux linkage observation based on the target stator current and through a current model that includes speed state variables.
[0087] The rotor flux linkage observation error determination module 304 is used to determine the rotor flux linkage observation error based on the difference between the first rotor flux linkage observation value and the second rotor flux linkage observation value.
[0088] The estimation module 305 is used to determine the estimated value of the rotor angular velocity in real time based on the rotor flux observation error and the preset adaptive rate.
[0089] The slip angular frequency determination module 306 is used to determine the slip angular frequency based on the estimated value of the rotor angular velocity and the observed value of the second rotor flux linkage.
[0090] The synchronous electrical angle determination module 307 is used to sum and integrate the estimated value of the rotor angular velocity and the slip angular frequency to obtain the synchronous electrical angle.
[0091] The data feedback module 308 is used to feed back the estimated value of the rotor angular velocity and the synchronous electrical angle to the control system of the asynchronous motor.
[0092] The sensorless control device for an asynchronous motor provided in this invention can obtain the target stator voltage and target stator current in the stationary two-phase coordinate system by collecting the stator voltage and stator current of the asynchronous motor and transforming them to a stationary two-phase coordinate system. Based on the target stator voltage and target stator current, a first rotor flux linkage observation value is obtained through a voltage model including a low-pass filter. Based on the target stator current, a second rotor flux linkage observation value is obtained through a current model including a speed state variable. The rotor flux linkage observation error is determined based on the difference between the first and second rotor flux linkage observation values. Based on the rotor flux linkage observation error and a pre-set adaptive rate, the estimated value of the rotor angular velocity is determined in real time. The slip angular frequency is determined based on the estimated value of the rotor angular velocity and the second rotor flux linkage observation value. The estimated value of the rotor angular velocity and the slip angular frequency are summed and integrated to obtain the synchronous electrical angle. The estimated value of the rotor angular velocity and the synchronous electrical angle are fed back to the control system of the asynchronous motor. This method reduces parameter sensitivity and improves the accuracy of speed and position estimation and system stability across the entire speed domain.
[0093] In some embodiments, the first rotor flux linkage observation determination module is further configured to construct a rotor flux linkage voltage equation in a stationary coordinate system based on the target stator voltage and the target stator current; replace the pure integration operation in the rotor flux linkage voltage equation with a low-pass filter with an adjustable cutoff frequency; input the target stator voltage and the target stator current into a voltage model containing a low-pass filter for calculation, and output the first rotor flux linkage observation.
[0094] In some embodiments, the second rotor flux linkage observation determination module is further configured to: construct a rotor flux linkage current equation containing rotor electric angular velocity state variables based on the target stator current; replace the rotor electric angular velocity in the rotor flux linkage current equation with the estimated value to be identified to form an adjustable model; input the target stator current into the adjustable model and output the second rotor flux linkage observation value.
[0095] In some embodiments, the estimation value determination module is further configured to determine an error signal based on the first rotor flux linkage observation value and the second rotor flux linkage observation value; substitute the error signal into a proportional-integral adaptive rate formula containing the adaptive rate to calculate the formula output; and based on the formula output, update and output the estimated value of the rotor angular velocity in real time.
[0096] In some embodiments, the synchronous electric angle determination module is further configured to calculate the slip angular frequency based on the second rotor flux linkage observation value and the target stator current, according to the rotor magnetic field orientation relationship; add the estimated value of the rotor angular velocity to the slip angular frequency to obtain the synchronous electric angular frequency; and perform an integral operation on the synchronous electric angular frequency to obtain the synchronous electric angle.
[0097] In some embodiments, the synchronous electrical angle determination module is further configured to perform a high-frequency signal injection method to obtain the initial rotor position when the asynchronous motor starts or the estimated value of the rotor angular velocity is lower than a preset angular velocity threshold, and assign the initial rotor position as the initial value of integration to the integrator performing the integration operation, or fuse it with the synchronous electrical angle.
[0098] In some embodiments, the data feedback module is further configured to input the estimated value of the rotor angular velocity as a speed feedback signal to the speed loop regulator; and to use the synchronous electrical angle to perform Park transformation and inverse Park transformation to achieve current decoupling control.
[0099] The device provided in this embodiment of the invention has the same implementation principle and technical effect as the aforementioned method embodiment. For the sake of brevity, any parts not mentioned in the device embodiment can be referred to the corresponding content in the aforementioned method embodiment.
[0100] Example 4 This invention also provides an electronic device for running the above-described sensorless control method for asynchronous motors; see [link to related documentation]. Figure 8The diagram shows the structure of an electronic device, which includes a memory 400 and a processor 401. The memory 400 is used to store one or more computer instructions, which are executed by the processor 401 to implement the aforementioned sensorless control method for asynchronous motors.
[0101] Furthermore, Figure 8 The electronic device shown also includes a bus 402 and a communication interface 403. The processor 401, the communication interface 403 and the memory 400 are connected via the bus 402.
[0102] The memory 400 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 403 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc. The bus 402 can be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 8 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.
[0103] Processor 401 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 401 or by instructions in software form. Processor 401 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software module can reside in a readily available storage medium in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory 400, and processor 401 reads information from memory 400 and, in conjunction with its hardware, completes the steps of the method described in the foregoing embodiments.
[0104] This invention also provides a computer-readable storage medium storing computer-executable instructions. When these computer-executable instructions are called and executed by a processor, they cause the processor to implement the aforementioned sensorless control method for asynchronous motors. For specific implementation details, please refer to the method embodiments, which will not be repeated here.
[0105] The computer program product for a sensorless control method for an asynchronous motor provided in this embodiment of the invention includes a computer-readable storage medium storing non-volatile program code executable by a processor. The instructions included in the program code can be used to execute the methods described in the preceding method embodiments. For specific implementation details, please refer to the method embodiments, which will not be repeated here.
[0106] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.
[0107] In the several embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.
[0108] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0109] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.
[0110] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0111] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.
Claims
1. A sensorless control method for an asynchronous motor, characterized in that, The method includes: The stator voltage and stator current of the asynchronous motor are collected and transformed to a stationary two-phase coordinate system to obtain the target stator voltage and target stator current in the stationary coordinate system. Based on the target stator voltage and the target stator current, the first rotor flux linkage observation value is obtained through a voltage model including a low-pass filter. Based on the target stator current, the second rotor flux linkage observation value is obtained through a current model that includes rotational speed state variables; The rotor flux linkage observation error is determined based on the difference between the first rotor flux linkage observation value and the second rotor flux linkage observation value. Based on the rotor flux linkage observation error and the pre-set adaptive rate, the estimated value of the rotor angular velocity is determined in real time; Based on the estimated value of the rotor angular velocity and the observed value of the second rotor flux linkage, the slip angular frequency is determined; The estimated value of the rotor angular velocity is summed and integrated with the slip angular frequency to obtain the synchronous electrical angle; The estimated value of the rotor angular velocity and the synchronous electrical angle are fed back to the control system of the asynchronous motor.
2. The method according to claim 1, characterized in that, The process of obtaining the first rotor flux linkage observation value based on the target stator voltage and the target stator current, through a voltage model including a low-pass filter, includes: Based on the target stator voltage and the target stator current, the rotor flux linkage voltage equation in the stationary coordinate system is constructed; A low-pass filter with an adjustable cutoff frequency is used to replace the pure integration operation in the rotor flux voltage equation. The target stator voltage and the target stator current are input into the voltage model containing a low-pass filter for calculation, and the first rotor flux linkage observation value is output.
3. The method according to claim 1, characterized in that, The process of obtaining the second rotor flux linkage observation value based on the target stator current using a current model that includes speed state variables includes: Based on the target stator current, a rotor flux linkage current equation including rotor electric angular velocity state variables is constructed; The rotor electric angular velocity in the rotor flux current equation is replaced with the estimated value to be identified to form an adjustable model; The target stator current is input into the adjustable model, and the second rotor flux linkage observation value is output.
4. The method according to claim 1, characterized in that, The method of determining the estimated value of the rotor angular velocity in real time based on the rotor flux linkage observation error and the pre-set adaptive rate includes: An error signal is determined based on the first rotor flux linkage observation value and the second rotor flux linkage observation value; Substitute the error signal into the proportional-integral adaptive rate formula that includes the adaptive rate to obtain the formula output; Based on the formula output, the estimated value of the rotor angular velocity is updated and output in real time.
5. The method according to claim 1, characterized in that, The process of summing and integrating the estimated rotor angular velocity with the slip angular frequency to obtain the synchronous electrical angle includes: Based on the second rotor flux linkage observation value and the target stator current, the slip angular frequency is calculated according to the rotor magnetic field orientation relationship; The estimated value of the rotor angular velocity is added to the slip angular frequency to obtain the synchronous electric angular frequency; The synchronous electrical angle is obtained by integrating the synchronous electrical angular frequency.
6. The method according to claim 5, characterized in that, The method also includes a low-speed startup enhancement step, specifically: When the asynchronous motor starts or the estimated value of the rotor angular velocity is lower than the preset angular velocity threshold, the high-frequency signal injection method is executed to obtain the initial rotor position, and the initial rotor position is assigned as the initial value of integration to the integrator that performs the integration operation, or it is fused with the synchronous electric angle.
7. The method according to claim 1, characterized in that, The step of feeding back the estimated rotor angular velocity and the synchronous electrical angle to the control system of the asynchronous motor includes: The estimated value of the rotor angular velocity is used as a speed feedback signal and input to the speed loop regulator; The synchronous electrical angle is used to perform Park transformation and inverse Park transformation to achieve current decoupling control.
8. A sensorless control device for an asynchronous motor, characterized in that, The device includes: The coordinate transformation module is used to collect the stator voltage and stator current of the asynchronous motor and transform them to a stationary two-phase coordinate system to obtain the target stator voltage and target stator current in the stationary coordinate system. The first rotor flux linkage observation value determination module is used to obtain the first rotor flux linkage observation value based on the target stator voltage and the target stator current through a voltage model including a low-pass filter. The second rotor flux linkage observation value determination module is used to obtain the second rotor flux linkage observation value based on the target stator current and through a current model that includes speed state variables. The rotor flux linkage observation error determination module is used to determine the rotor flux linkage observation error based on the difference between the first rotor flux linkage observation value and the second rotor flux linkage observation value. The estimation value determination module is used to determine the estimated value of the rotor angular velocity in real time based on the rotor flux observation error and the preset adaptive rate; The slip angular frequency determination module is used to determine the slip angular frequency based on the estimated value of the rotor angular velocity and the observed value of the second rotor flux linkage. The synchronous electrical angle is determined by summing and integrating the estimated value of the rotor angular velocity with the slip angular frequency to obtain the synchronous electrical angle. The data feedback module is used to feed back the estimated value of the rotor angular velocity and the synchronous electrical angle to the control system of the asynchronous motor.
9. An electronic device, characterized in that, The method includes a processor and a memory, the memory storing computer-executable instructions that can be executed by the processor, the processor executing the computer-executable instructions to implement the sensorless control method for an asynchronous motor according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when invoked and executed by a processor, cause the processor to implement the sensorless control method for an asynchronous motor as described in any one of claims 1 to 7.