A method for model predictive current control of permanent magnet synchronous motor without position sensor based on prediction error

Abstract

The application discloses a kind of permanent magnet synchronous motor position sensorless model prediction current control method and device based on prediction error, comprising: determining the target control function of permanent magnet synchronous motor based on MPCC;Determine the back electromotive force error of predicted current, and determine the back electromotive force estimation function based on back electromotive force error;Obtain the operating parameter of k time and the back electromotive force of k-1 time, and based on the operating parameter of k time and the back electromotive force of k-1 time, the back electromotive force estimation value of k time is obtained by back electromotive force estimation function;Based on back electromotive force estimation value, determine motor speed estimation value;Determine control scheme based on motor speed estimation value and target control function, and control permanent magnet synchronous motor based on control scheme.The application reduces the complexity of calculation and simplifies parameter adjustment, improves control accuracy and response speed, effectively overcomes the limitations of existing position sensorless control technology.

Description

Technical Field

[0001] This invention relates to the field of motor control technology, and in particular to a sensorless model predictive current control method and device for permanent magnet synchronous motors based on prediction error. Background Technology

[0002] Currently, permanent magnet synchronous motors (PMSMs) are widely used due to their compact structure, high power density, and strong torque capability. However, achieving precise control of PMSMs using traditional methods requires obtaining accurate real-time information about the rotor position through mechanical position sensors such as optical encoders. These position sensors can lead to increased system cost, larger size, reduced reliability, and susceptibility to environmental interference. Therefore, sensorless control methods can be used to control PMSMs, mitigating these problems.

[0003] In existing technologies, sensorless control methods for PMSMs can include back-EMF estimation methods, high-frequency signal injection methods, or model-based observer control methods. Among these, back-EMF estimation methods typically require special filters and are complex in principle; high-frequency signal injection methods can improve low-speed performance but introduce additional complexity and potential acoustic noise; model-based observers are robust to parameter variations but are computationally intensive and sensitive to model errors. Summary of the Invention

[0004] The present invention aims to at least partially solve one of the technical problems in the related art.

[0005] Therefore, one objective of this invention is to propose a sensorless model predictive current control method for permanent magnet synchronous motors based on prediction error. This method can determine the control scheme based on the back EMF error of the predicted current and the target control function, and control the permanent magnet synchronous motor based on the control scheme. It does not require traditional algorithms (such as sliding mode algorithms) and phase-locked loops (PLLs), which reduces computational complexity, simplifies parameter adjustment, improves control accuracy and response speed, and effectively overcomes the limitations of existing sensorless control technologies.

[0006] Another objective of this invention is to propose a sensorless model predictive current control device for permanent magnet synchronous motors based on prediction error.

[0007] To achieve the above objectives, one embodiment of the present invention proposes a sensorless model predictive current control method for permanent magnet synchronous motors based on prediction error, comprising:

[0008] The target control function of a permanent magnet synchronous motor is determined based on constrained model predictive control (MPCC).

[0009] Determine the back EMF error of the predicted current, and determine the back EMF estimation function based on the back EMF error;

[0010] Obtain the operating parameters at time k and the back electromotive force at time k-1, and based on the operating parameters at time k and the back electromotive force at time k-1, obtain the estimated value of the back electromotive force at time k through the back electromotive force estimation function, wherein time k is the current time;

[0011] Based on the back electromotive force estimate, the motor speed estimate is determined;

[0012] A control scheme is determined based on the estimated motor speed and the target control function, and the permanent magnet synchronous motor is controlled based on the control scheme.

[0013] The sensorless model predictive current control method for permanent magnet synchronous motors based on prediction error in this invention may also have the following additional technical features:

[0014] Furthermore, the constraint-based model predictive control (MPCC) determines the target control function of the permanent magnet synchronous motor, including:

[0015] Determine the first equation of the permanent magnet synchronous motor;

[0016] The first equation is subjected to inverse Park transform and simplification to obtain the corresponding second equation;

[0017] The derivative terms in the second equation are processed using the forward Euler method to obtain the corresponding predicted current equation.

[0018] Determine the conversion relationship between the α-axis and β-axis stator currents and the d-axis and q-axis stator currents;

[0019] Based on the transformation relationship and the predicted current equation, the target control function of the permanent magnet synchronous motor is determined by MPCC.

[0020] Further, determining the back potential estimation function based on the back potential error includes:

[0021] Determine the performance index function;

[0022] The back EMF error is processed based on the performance index function to obtain a third-party process;

[0023] Taking partial derivatives of the third equation yields the fourth equation;

[0024] Based on the fourth equation, the back potential estimation function is obtained through compensation processing.

[0025] Further, determining the estimated motor speed based on the back electromotive force estimate includes:

[0026] Based on the estimated back electromotive force, the electric angle and electric angular velocity are determined by calculation;

[0027] Determine the estimation function for the d-axis back electromotive force;

[0028] Based on the estimation function of the d-axis back electromotive force, the electrical angle compensation is determined by a traversal algorithm;

[0029] Based on the electrical angle, the electrical angular velocity, and the electrical angle compensation, the estimated value of the motor speed is determined.

[0030] Further, determining the control scheme based on the estimated motor speed and the target control function includes:

[0031] Determine the reference value of the electric angular velocity, and based on the estimated motor speed and the reference value of the motor speed, determine the reference value of the q-axis current;

[0032] Determine the reference value for the d-axis current;

[0033] Based on the reference values ​​of the q-axis current and the d-axis current, the reference values ​​of the α-axis and β-axis are determined through the conversion relationship.

[0034] Based on the reference values ​​of the α-axis and β-axis and the target control function, a control scheme for the inverter switching state is determined by a traversal algorithm.

[0035] To achieve the above objectives, another embodiment of the present invention proposes a sensorless model predictive current control device for permanent magnet synchronous motors based on prediction error, the device comprising:

[0036] The first determining module is used to determine the target control function of the permanent magnet synchronous motor based on constrained model predictive control (MPCC).

[0037] The second determining module is used to determine the back EMF error of the predicted current and to determine the back EMF estimation function based on the back EMF error.

[0038] The calculation module is used to obtain the operating parameters at time k and the back electromotive force at time k-1, and based on the operating parameters at time k and the back electromotive force at time k-1, obtain the estimated value of the back electromotive force at time k through the back electromotive force estimation function, wherein time k is the current time;

[0039] The third determining module is used to determine the estimated motor speed based on the back electromotive force estimate.

[0040] The fourth determining module is used to determine a control scheme based on the estimated motor speed and the target control function, and to control the permanent magnet synchronous motor based on the control scheme.

[0041] This invention proposes a sensorless model predictive current control method and device for permanent magnet synchronous motors (PMSMs) based on prediction error. The method involves: determining the target control function of the PMSM based on MPCC; determining the back EMF error of the predicted current and determining a back EMF estimation function based on the back EMF error; acquiring the operating parameters at time k and the back EMF at time k-1, and obtaining the back EMF estimate at time k through the back EMF estimation function based on the operating parameters at time k and the back EMF at time k-1; determining the estimated motor speed based on the back EMF estimate; determining the control scheme based on the estimated motor speed and the target control function; and controlling the PMSM based on the control scheme. Therefore, this invention can determine the control scheme based on the back EMF error of the predicted current and the target control function, and control the PMSM based on the control scheme. It eliminates the need for traditional algorithms (such as sliding mode algorithms) and phase-locked loops (PLLs), reducing computational complexity, simplifying parameter adjustment, improving control accuracy and response speed, and effectively overcoming the limitations of existing sensorless control technologies.

[0042] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0043] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0044] Figure 1 A flowchart of a sensorless model predictive current control method for permanent magnet synchronous motors based on prediction error according to an embodiment of the present invention;

[0045] Figure 2 This is a system structure diagram of a sensorless model predictive current control method for permanent magnet synchronous motors based on prediction error according to an embodiment of the present invention.

[0046] Figure 3 a is a schematic diagram of the experimental results of rotor position angle estimation using the SMO+PLL method at a motor speed of 500 rpm;

[0047] Figure 3 b is a schematic diagram of the experimental results of rotor position angle estimation using the MPCC-SL-PE method at a motor speed of 500 rpm;

[0048] Figure 4 a is a schematic diagram of the speed estimation experiment results of the SMO+PLL method when the motor speed is 500 rpm;

[0049] Figure 4b is a schematic diagram of the speed estimation experimental results of the MPCC-SL-PE method at a motor speed of 500 rpm;

[0050] Figure 5 a is a schematic diagram of the experimental results of rotor position angle estimation using the SMO+PLL method at a motor speed of 1000 rpm;

[0051] Figure 5 b is a schematic diagram of the experimental results of rotor position angle estimation using the MPCC-SL-PE method at a motor speed of 1000 rpm;

[0052] Figure 6 a is a schematic diagram of the speed estimation experiment results of the SMO+PLL method when the motor speed is 1000 rpm;

[0053] Figure 6 b is a schematic diagram of the speed estimation experimental results of the MPCC-SL-PE method at a motor speed of 1000 rpm;

[0054] Figure 7 a is a schematic diagram of the experimental results of rotor position angle estimation using the SMO+PLL method at a motor speed of 2000 rpm;

[0055] Figure 7 b is a schematic diagram of the experimental results of rotor position angle estimation using the MPCC-SL-PE method at a motor speed of 2000 rpm;

[0056] Figure 8 a is a schematic diagram of the speed estimation experimental results of the SMO+PLL method at a motor speed of 2000 rpm;

[0057] Figure 8 b is a schematic diagram of the speed estimation experimental results of the MPCC-SL-PE method at a motor speed of 2000 rpm;

[0058] Figure 9 This is a schematic diagram of a sensorless model predictive current control device for a permanent magnet synchronous motor based on prediction error, according to an embodiment of the present invention. Detailed Implementation

[0059] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0060] The following describes, with reference to the accompanying drawings, a sensorless model predictive current control method and apparatus for permanent magnet synchronous motors based on prediction error, according to an embodiment of the present invention.

[0061] Figure 1 This is a flowchart of a sensorless model predictive current control method for permanent magnet synchronous motors based on prediction error, according to an embodiment of the present invention.

[0062] like Figure 1 As shown, the sensorless model predictive current control method for permanent magnet synchronous motors based on prediction error includes the following steps:

[0063] Step S1: Determine the target control function of the permanent magnet synchronous motor based on MPCC (Model Predictive Control with constraints);

[0064] In one embodiment of the present invention, the method for determining the target control function of a permanent magnet synchronous motor based on MPCC may include the following steps:

[0065] Step S11: Determine the first equation of the permanent magnet synchronous motor;

[0066] Step S12: Perform inverse Park transform and simplification on the first equation to obtain the corresponding second equation;

[0067] Step S13: Perform forward Euler method processing on the derivative terms in the second equation to obtain the corresponding predicted current equation;

[0068] Step S14: Determine the conversion relationship between the α-axis and β-axis stator currents and the d-axis and q-axis stator currents;

[0069] Step S15: Based on the transformation relationship and the predicted current equation, the target control function of the permanent magnet synchronous motor is determined by MPCC.

[0070] In one embodiment of the present invention, the first equation of the PMSM can be the basic mathematical model of the PMSM's dq axis, as shown in Formula 1 below:

[0071]

[0072] Among them, u d and u q Indicates the d-axis and q-axis stator voltages of the PMSM, i d and i q This represents the d-axis and q-axis stator currents of the PMSM, R represents the stator resistance, and ω represents the d-axis and q-axis stator currents. e ψ represents electric angular velocity. f This indicates the stator flux linkage.

[0073] Furthermore, in one embodiment of the present invention, since the control method is sensorless control, the inverse Park transformation is performed on the first equation to obtain the equation for the αβ axis, as shown in Formula 2 below:

[0074]

[0075] Among them, u α and u β i represents the α-axis and β-axis stator voltages of the PMSM. α and i β This represents the α-axis and β-axis stator currents of the PMSM.

[0076] Furthermore, in one embodiment of the present invention, -ω in Formula 2 above e ψ f sinθ e and ω e ψ f cosθ e This includes rotor position information, known as back electromotive force (EMF). Based on this, the equations for the αβ axis can be simplified to obtain the second equation, as shown in Equation 3 below:

[0077]

[0078] Furthermore, in one embodiment of the present invention, in the MPCC method of αβ-axes, the derivative term in the second equation above needs to be processed by the forward Euler method to obtain the corresponding predicted current equation, as shown in Formula 4 below:

[0079]

[0080] The aforementioned predictive current equation can use the parameter value at time k to predict the current of αβ-axes at the next time step, and time k can be the current time step.

[0081] Furthermore, in one embodiment of the present invention, the PMSM-based current control method is to give i d and i q Reference value i* d and i* q Based on this, the conversion relationship between the α-axis and β-axis stator currents and the d-axis and q-axis stator currents is determined, as shown in Formula 5:

[0082]

[0083] Furthermore, in one embodiment of the present invention, a two-level three-phase inverter is used as the driving device for the PMSM, thereby obtaining eight voltage vectors, denoted as u0, u1…u7, based on the inverter's switching states. Based on this, the target control function of the permanent magnet synchronous motor is determined using MPCC as follows:

[0084]

[0085] Among them, J T The total cost function of MPCC is represented. This involves substituting u0, u1…u7 into J. T The cost value obtained in J out This represents the minimum value that the objective control function can achieve.

[0086] Step S2: Determine the back EMF error of the predicted current, and determine the back EMF estimation function based on the back EMF error;

[0087] In one embodiment of the present invention, the MPCC method described above predicts the current at time k+1 to further reduce the error between the predicted value and the actual value of the system current at time k+1. However, the error may persist, thus the aforementioned characteristic can be used to extract rotor position information.

[0088] Furthermore, in one embodiment of the present invention, based on the predicted value of the current at time k+1 and the actual value of the current at time k+1, the back EMF error of the predicted current is determined as shown in Formula 7 below:

[0089]

[0090] Furthermore, i pα (k+1), i pβ (k+1) is the predicted value for the next time step calculated at time k, i α (k+1), i β (k+1) is the detection value at time k+1. And, i α (k+1) contains unknown interference and cannot be calculated using discretized parameters. Therefore, Δi is added to Equation 7 above. α (k+1), Δi β (k+1) and Δe α (k), Δe β (k) represents the unknown disturbance increment, and u β (k) and u α (k) depends on the switching state of the inverter and has no disturbance. Therefore, subtracting the two sets of formulas in Formula 7 above, we get Formula 8:

[0091]

[0092] In Formula 8 above, the back EMF error is extracted and placed on the left side of the equation. Furthermore, unpredictable current disturbances still exist in Formula 8; therefore, a performance index function needs to be determined to handle the back EMF error.

[0093] Specifically, the determined performance index function is shown in Formula 9 below:

[0094]

[0095] Here, ξ represents the step index, which is used to adjust the order of magnitude balance between the back EMF and the αβ axis current.

[0096] Furthermore, the back EMF error (Equation 8) can be substituted into the performance index function to obtain the third process, as shown in Equation 10 below:

[0097]

[0098] Furthermore, due to the characteristics of the control system, Δe in Equation 10 above... α (k),Δe β (k) The derivative exists and is continuous. Based on this, we can apply the Cauchy Mean Value Theorem to Δe in Equation 10. α (k),Δe β (k) Taking the partial derivatives, we obtain the fourth equation, as shown in Formula 11 below:

[0099]

[0100] Furthermore, formula 11 can be simplified using formula 4 above to obtain formula 12:

[0101]

[0102] Based on the necessary condition for the extrema of partial derivatives, Equation 12 can be equal to zero, thus obtaining Equation 13:

[0103]

[0104] Furthermore, after obtaining Formula 13 through the above steps, we can use Formula 13 to back-calculate to time k, and obtain the standard form of the back potential estimate as shown in Formula 14 below:

[0105]

[0106] Among them, e α (k),e β The basic form of (k) is calculated, and e can be further processed. α (k),eβ (k) After compensation processing, the back potential estimation function is obtained as shown in Formula 15 below:

[0107]

[0108] Where η is u α (k) and u β The compensation coefficient of (k), which is determined by u α (k) and u β (k) and e α1 (k), e β1 The order of magnitude of (k) is determined.

[0109] Step S3: Obtain the operating parameters at time k and the back EMF at time k-1, and based on the operating parameters at time k and the back EMF at time k-1, obtain the estimated value of the back EMF at time k through the back EMF estimation function.

[0110] In one embodiment of the present invention, the operating parameters at time k may include the α-axis stator current i at time k. α (k) and β-axis stator current i β (k), α-axis stator voltage u α (k) and β-axis stator voltage u β (k), the predicted current at time k and The back electromotive force at time k-1 is e α1 (k-1) and e β1 (k-1).

[0111] Furthermore, in one embodiment of the present invention, after obtaining the operating parameters at time k and the back EMF at time k-1 through the above steps, the operating parameters at time k and the back EMF at time k-1 can be substituted into Formula 15 corresponding to the back EMF estimation function to obtain the back EMF estimate at time k through the back EMF estimation function.

[0112] Step S4: Determine the estimated motor speed based on the back electromotive force estimate;

[0113] In one embodiment of the present invention, after obtaining the back electromotive force estimate through the above steps, the electric angular velocity compensation amount can be determined based on the back electromotive force estimate.

[0114] Furthermore, in one embodiment of the present invention, the method for determining the electric angular velocity compensation amount based on the back electromotive force estimate may include the following steps:

[0115] Step S41: Based on the back electromotive force estimate, the electric angle and electric angular velocity are determined by calculation;

[0116] Step S42: Determine the estimation function of the d-axis back electromotive force;

[0117] Step S43: Based on the estimation function of the d-axis back electromotive force, determine the electrical angle compensation through a traversal algorithm;

[0118] Step S44: Determine the estimated motor speed based on electrical angle, electrical angular velocity, and electrical angle compensation.

[0119] In one embodiment of the present invention, the electric angle and electric angular velocity are calculated and determined based on the back electromotive force estimate using formula 16, wherein formula 16 is as follows:

[0120]

[0121] Where, θ i (k) is the electrical angle, ω ei For electric angular velocity and n ei The value is the rotational speed.

[0122] Furthermore, in one embodiment of the present invention, the electric angular velocity ω, which can be calculated using the above formula 16, is based on the back electromotive force. ei It exhibits significant fluctuations, which can be further compensated and adjusted by incorporating the back electromotive force. Based on this, the d-axis back electromotive force e is determined. d The estimated function of (k) is shown in Equation 17 below:

[0123]

[0124] Among them, i ds (k), i qs (k), u ds (k) is calculated as follows:

[0125]

[0126] Furthermore, based on the above formulas 17 and 18, a traversal algorithm can be used to process Δθ. i (k) Iterate through the data to obtain the electrical angle compensation Δθ at time k. i (k). Wherein, due to θ i (k) has a small lag, hence Δθ i (k) A lead compensation of no more than 0.1 rad is required. Specifically, the above traversal algorithm can be represented by the following formula 19:

[0127]

[0128] Among them, it can be obtained through Δθ i =0:0.01:0.1, from 0 to 0.1, adjusting Δθ in steps of 0.01. i Perform the traversal and obtain the result that makes ed (k) Electrical angle compensation Δθ closest to 0 i .

[0129] Furthermore, Δθ can be compensated based on electrical angle. i The compensated electric angular velocity is determined using formula 20. Formula 20 is shown below:

[0130]

[0131] Furthermore, the compensated electric angular velocity is obtained through the above steps. Then, the estimated motor speed n can be calculated using a simplified differential estimation formula. i The differential operation estimation formula is shown in Formula 21 below:

[0132]

[0133] Among them, the above and This is to compensate the above electrical angle Δθ i Substitute and The obtained value, Δω, represents the electric angular velocity compensation amount. After compensation with the electric angular velocity compensation amount, the compensated electric angular velocity is obtained. By using a first-order low-pass filter to filter the electric speed, a motor speed estimate n with a smaller error can be obtained. i .

[0134] Step S5: Determine the control scheme based on the estimated motor speed and the target control function, and control the permanent magnet synchronous motor based on the control scheme.

[0135] In one embodiment of the present invention, after obtaining the estimated motor speed through the above steps, a control scheme can be determined based on the estimated motor speed and the target control function, and the permanent magnet synchronous motor can be controlled based on the control scheme.

[0136] Specifically, in one embodiment of the present invention, the method for determining a control scheme based on the estimated motor speed and the target control function, and controlling the permanent magnet synchronous motor based on the control scheme, may include the following steps:

[0137] Step S51: Determine the reference value of the electric angular velocity, and based on the estimated value of the motor speed and the reference value of the motor speed, determine the reference value of the q-axis current;

[0138] Step S52: Determine the reference value for the d-axis current;

[0139] Step S53: Based on the reference values ​​of the q-axis current and the d-axis current, determine the reference values ​​of the α-axis and β-axis through a conversion relationship;

[0140] Step S54: Based on the reference values ​​of the α-axis and β-axis and the target control function, determine the control scheme for the inverter switching state through a traversal algorithm.

[0141] In one embodiment of the present invention, the reference value of electric angular velocity n is determined. * Then, based on the estimated motor speed n i and motor speed reference value n * Determine the reference value for the q-axis current.

[0142] Furthermore, in one embodiment of the present invention, the reference value of the aforementioned d-axis current... It can be 0, that is,

[0143] Furthermore, in one embodiment of the present invention, the reference values ​​of the q-axis current and the d-axis current are compared with the above-mentioned compensated electric angular velocity. The reference values ​​for the α-axis and β-axis can be determined using the conversion relationship corresponding to Formula 5 above. and

[0144] Furthermore, in one embodiment of the present invention, reference values ​​for the α-axis and β-axis are obtained through the above steps. and Then, the target inverter switching state that minimizes the target control function value can be determined by traversing the inverter switching states. The target inverter switching state is then used as the control scheme, and the permanent magnet synchronous motor is controlled based on the control scheme.

[0145] This invention proposes a sensorless model predictive current control method and apparatus for permanent magnet synchronous motors (PMSMs) based on prediction error. The method and apparatus determine the target control function of the PMSM based on MPCC; determine the back EMF error of the predicted current and determine a back EMF estimation function based on the back EMF error; acquire the operating parameters at time k and the back EMF at time k-1, and obtain the back EMF estimate at time k using the back EMF estimation function based on the operating parameters at time k and the back EMF at time k-1; determine the estimated motor speed based on the back EMF estimate; determine a control scheme based on the estimated motor speed and the target control function; and control the PMSM based on the control scheme. Therefore, this invention can determine the control scheme based on the back EMF error of the predicted current and the target control function, and control the PMSM based on the control scheme. It eliminates the need for traditional algorithms (such as sliding mode algorithms) and phase-locked loops (PLLs), reducing computational complexity and simplifying parameter adjustment, improving control accuracy and response speed, and effectively overcoming the limitations of existing sensorless control technologies.

[0146] Based on the above description Figure 2 This is a system structure diagram of a sensorless model predictive current control method for permanent magnet synchronous motors based on prediction error, proposed in an embodiment of the present invention. Figure 2 As shown, the α-axis stator current i at time k is obtained. α (k) and β-axis stator current i β (k), α-axis stator voltage u α (k) and β-axis stator voltage u β (k), the predicted current at time k and The back electromotive force at time k-1 is e α1 (k-1) and e β1 (k-1); Based on the α-axis stator current i at time k α (k) and β-axis stator current i β (k), α-axis stator voltage u α (k) and β-axis stator voltage u β (k), the predicted current at time k and The back electromotive force at time k-1 is e α1 (k-1) and e β1 (k-1), the back EMF estimate based on the predicted current error is obtained through Formula 15 above; based on the back EMF estimate, the electrical angle and electrical angular velocity are obtained through Formula 16 above; based on the electrical angle and electrical angular velocity, the following are obtained through Formulas 19 and 20 above: and based on and The estimated motor speed is obtained using formula 21 above; the estimated motor speed and the reference value of electric angular velocity n are then used to obtain the estimated motor speed. * Determine the reference value for the q-axis current. Reference value based on q-axis current and the reference value of d-axis current The reference values ​​for the α-axis and β-axis are determined using the transformation relationship corresponding to Formula 5 above. and Reference values ​​based on the α and β axes and The target inverter switching state that minimizes the target control function value is determined by traversing the inverter switching states, and the permanent magnet synchronous motor is controlled by the target inverter switching state.

[0147] The embodiments of the present invention can be simulated using Matlab / Simulink. The experimental results of the MPCC-SL-PE method of the present invention and the traditional sliding model (SMO) and phase-locked loop (PLL) method were compared. The experimental parameters are shown in Table 1.

[0148] Table 1

[0149] DC bus voltage <![CDATA[U dc ]]> 310V Stator resistance R 3.18Ω Stator inductor L 0.0085H Extreme logarithm n 2 Rated torque TN 5 N·m Rated speed nN 2000 rad / min Rated power PN 1.25kW

[0150] It should be noted that during debugging in a real engineering environment, to balance the difference in magnitude, the ξ value was set to 6450 and the η value was set to 0.02. To demonstrate the applicability of the method of the present invention at different speeds, comparative experiments were conducted on the method of the present invention and the traditional sliding diaphragm observer and phase-locked loop method (SMO+PLL) at motor speeds of 500 rpm, 1000 rpm, 2000 rpm and 5 N.m.

[0151] in, Figure 3 This is a comparison chart of the rotor position angle estimation results for the MPCC-SL-PE method and the SMO+PLL method at a motor speed of 500 rpm. Figure 3 Figure a shows the experimental results of rotor position angle estimation using the SMO+PLL method at a motor speed of 500 rpm. Figure 3 b is a schematic diagram of the experimental results of rotor position angle estimation using the MPCC-SL-PE method at a motor speed of 500 rpm; Figure 4 This is a comparison chart of the speed estimation results of the MPCC-SL-PE method and the SMO+PLL method at a motor speed of 500 rpm. Figure 4 a is a schematic diagram of the speed estimation experimental results of the SMO+PLL method when the motor speed is 500 rpm. Figure 4b is a schematic diagram of the speed estimation experimental results of the MPCC-SL-PE method at a motor speed of 500 rpm; Figure 5 This is a comparison chart of the rotor position angle estimation results for the MPCC-SL-PE method and the SMO+PLL method at a motor speed of 1000 rpm. Figure 5 Figure a shows the experimental results of rotor position angle estimation using the SMO+PLL method at a motor speed of 1000 rpm. Figure 5 b is a schematic diagram of the experimental results of rotor position angle estimation using the MPCC-SL-PE method at a motor speed of 1000 rpm; Figure 6 This is a comparison chart of the speed estimation results of the MPCC-SL-PE method and the SMO+PLL method at a motor speed of 1000 rpm. Figure 6 a is a schematic diagram of the speed estimation experimental results of the SMO+PLL method at a motor speed of 1000 rpm. Figure 6 b is a schematic diagram of the speed estimation experimental results of the MPCC-SL-PE method at a motor speed of 1000 rpm; Figure 7 This is a comparison chart of the rotor position angle estimation results for the MPCC-SL-PE method and the SMO+PLL method at a motor speed of 2000 rpm. Figure 7 Figure a shows the experimental results of rotor position angle estimation using the SMO+PLL method at a motor speed of 2000 rpm. Figure 7 b is a schematic diagram of the experimental results of rotor position angle estimation using the MPCC-SL-PE method at a motor speed of 2000 rpm; Figure 8 This is a comparison chart of the speed estimation results of the MPCC-SL-PE method and the SMO+PLL method at a motor speed of 2000 rpm. Figure 8 a is a schematic diagram of the speed estimation experimental results of the SMO+PLL method at a motor speed of 2000 rpm. Figure 8 b is a schematic diagram of the speed estimation experimental results of the MPCC-SL-PE method at a motor speed of 2000 rpm.

[0152] The experimental results show that θ ture The accurate value of the rotor angle, θ i_SMO θ represents the estimated rotor angle of the SMO+PLL. i_PCR This represents the rotor angle estimate using the proposed MPCC-SL-PE method, where Δθ represents the angle estimation error, and n... ture Indicates the accurate value of rotational speed, n i_SMO This represents the estimated motor speed of the SMO+PLL, n. i_PCRThe value represents the motor speed estimate using the proposed MPCC-SL-PE method, and Δn represents the speed estimation error. From... Figures 3-8 It can be concluded that, for motors operating at speeds between 500 rpm and 2000 rpm, the angle estimation error obtained using the MPCC-SL-PE method is less than 0.02 rad, significantly lower than the 0.02-0.05 rad angle estimation error of the SMO+PLL method; the speed error obtained using the MPCC-SL-PE method is around 4-6 r, significantly lower than the 10-12 r speed error of the SMO+PLL method.

[0153] Next, referring to the accompanying drawings, a sensorless model predictive current control device for permanent magnet synchronous motors based on prediction error, according to an embodiment of the present invention, is described.

[0154] Figure 9 This is a schematic diagram of a sensorless model predictive current control device for a permanent magnet synchronous motor based on prediction error, according to an embodiment of the present invention.

[0155] like Figure 9 As shown, the sensorless model predictive current control device 10 for permanent magnet synchronous motors based on prediction error includes: a first determining module 901, a second determining module 902, a calculation module 903, a third determining module 904, and a fourth determining module 905, wherein...

[0156] The first determining module 901 is used to determine the target control function of the permanent magnet synchronous motor based on the constrained MPCC;

[0157] The second determining module 902 is used to determine the back EMF error of the predicted current and to determine the back EMF estimation function based on the back EMF error.

[0158] The calculation module 903 is used to obtain the operating parameters at time k and the back electromotive force at time k-1, and based on the operating parameters at time k and the back electromotive force at time k-1, to obtain the back electromotive force estimate at time k through the back electromotive force estimation function, wherein time k is the current time.

[0159] The third determining module 904 is used to determine the estimated motor speed based on the back electromotive force estimate;

[0160] The fourth determining module 905 is used to determine a control scheme based on the estimated motor speed and the target control function, and to control the permanent magnet synchronous motor based on the control scheme.

[0161] Furthermore, the aforementioned first determining module 901 is specifically used for:

[0162] Determine the first equation for the permanent magnet synchronous motor;

[0163] By performing an inverse Park transform and simplification on the first equation, the corresponding second equation is obtained.

[0164] By applying the forward Euler method to the derivative terms in the second equation, the corresponding predicted current equation is obtained.

[0165] Determine the conversion relationship between the α-axis and β-axis stator currents and the d-axis and q-axis stator currents;

[0166] Based on the transformation relationship and the predicted current equation, the target control function of the permanent magnet synchronous motor is determined by MPCC.

[0167] Furthermore, the aforementioned second determining module 902 is specifically used for:

[0168] Determine the performance index function;

[0169] The back EMF error is processed based on the performance index function to obtain a third-party process;

[0170] By taking partial derivatives of the third equation, the fourth equation is obtained.

[0171] Based on the fourth equation, the back potential estimation function is obtained through compensation processing.

[0172] Furthermore, the aforementioned third determining module 904 is specifically used for:

[0173] Based on the back electromotive force estimate, the electric angle and electric angular velocity are determined by calculation.

[0174] Determine the estimation function for the d-axis back electromotive force;

[0175] Based on the estimation function of the d-axis back electromotive force, the electrical angle compensation is determined by a traversal algorithm.

[0176] Based on electrical angle, electrical angular velocity, and electrical angle compensation, the estimated value of motor speed is determined.

[0177] Furthermore, the aforementioned fourth determining module 905 is specifically used for:

[0178] Determine the reference value for the electric angular velocity, and based on the estimated motor speed and the reference value for the motor speed, determine the reference value for the q-axis current;

[0179] Determine the reference value for the d-axis current;

[0180] Based on the reference values ​​of the q-axis current and the d-axis current, the reference values ​​of the α-axis and β-axis are determined through a conversion relationship.

[0181] Based on the reference values ​​of the α-axis and β-axis and the target control function, a control scheme for determining the inverter switching state is obtained through a traversal algorithm.

[0182] The sensorless model predictive current control device for permanent magnet synchronous motors based on prediction error proposed in this embodiment of the invention can determine the control scheme based on the back EMF error of the predicted current and the target control function, and control the permanent magnet synchronous motor based on the control scheme. It does not require traditional algorithms (such as sliding mode algorithm) and phase-locked loop (PLL), which reduces the computational complexity and simplifies parameter adjustment, improves control accuracy and response speed, and effectively overcomes the limitations of existing sensorless control technology.

[0183] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0184] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0185] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A sensorless model predictive current control method for permanent magnet synchronous motors based on prediction error, characterized in that, The method includes: The target control function of a permanent magnet synchronous motor is determined based on constrained model predictive control (MPCC). Determine the back EMF error of the predicted current, and determine the back EMF estimation function based on the back EMF error; Obtain the operating parameters at time k and the back electromotive force at time k-1, and based on the operating parameters at time k and the back electromotive force at time k-1, obtain the estimated value of the back electromotive force at time k through the back electromotive force estimation function, wherein time k is the current time; Based on the back electromotive force estimate, the motor speed estimate is determined; A control scheme is determined based on the estimated motor speed and the target control function, and the permanent magnet synchronous motor is controlled based on the control scheme. The step of determining the back potential estimation function based on the back potential error includes: Determine the performance index function, wherein the performance index function is: ， Among them, i α and i β This represents the α-axis and β-axis stator currents of the PMSM. and Predict the current along the α-axis and β-axis, respectively. and These are the back electromotive forces along the α-axis and β-axis, respectively, and ξ represents the step index, which is used to adjust the order-of-magnitude balance between the back electromotive forces and the αβ-axis currents. The back electromotive force error is processed based on the performance index function to obtain a third process, wherein the third process is: Where L is the stator inductance and R is the stator resistance. , These are the back electromotive force errors along the α-axis and β-axis, respectively. , For unknown disturbance increments; Taking partial derivatives of the third equation yields the fourth equation, which is: Based on the fourth equation, combined with the predicted current equation and the fact that the partial derivative is equal to 0, the standard form of the back electromotive force estimate is as follows: The formula for estimating the back electromotive force is obtained by compensating for the formula as follows: , u α ( k )and u β ( k These are the stator voltages along the α and β axes, respectively. This is the compensation coefficient.

2. The method according to claim 1, characterized in that, The constrained model predictive control (MPCC) determines the target control function of the permanent magnet synchronous motor, including: Determine the mathematical model of the dq axis of the permanent magnet synchronous motor; After performing inverse Park transform and simplification on the dq-axis mathematical model, and then processing it using the forward Euler method, the corresponding predicted current equation is obtained: ; Determine the conversion relationship between the α-axis and β-axis stator currents and the d-axis and q-axis stator currents; Based on the transformation relationship and the predicted current equation, the target control function of the permanent magnet synchronous motor is determined by MPCC.

3. The method according to claim 1, characterized in that, The step of determining the estimated motor speed based on the back electromotive force estimate includes: Based on the estimated back electromotive force, the electric angle and electric angular velocity are determined by calculation; Determine the estimation function for the d-axis back electromotive force; Based on the estimation function of the d-axis back electromotive force, the electrical angle compensation is determined by a traversal algorithm; Based on the electrical angle, the electrical angular velocity, and the electrical angle compensation, the estimated value of the motor speed is determined.

4. The method according to claim 2, characterized in that, The process of determining a control scheme based on the estimated motor speed and the target control function includes: Determine the reference value of the electric angular velocity, and based on the estimated motor speed and the reference value of the motor speed, determine the reference value of the q-axis current; Determine the reference value for the d-axis current; Based on the reference values ​​of the q-axis current and the d-axis current, the reference values ​​of the α-axis and β-axis are determined through coordinate transformation. Based on the reference values ​​of the α-axis and β-axis and the target control function, a control scheme for the inverter switching state is determined.

5. A sensorless model predictive current control device for permanent magnet synchronous motors based on prediction error, characterized in that, The device includes: The first determining module is used to determine the target control function of the permanent magnet synchronous motor based on constrained model predictive control (MPCC). The second determining module is used to determine the back EMF error of the predicted current and to determine the back EMF estimation function based on the back EMF error. The calculation module is used to obtain the operating parameters at time k and the back electromotive force at time k-1, and based on the operating parameters at time k and the back electromotive force at time k-1, obtain the estimated value of the back electromotive force at time k through the back electromotive force estimation function, wherein time k is the current time; The third determining module is used to determine the estimated motor speed based on the back electromotive force estimate. The fourth determining module is used to determine a control scheme based on the estimated motor speed and the target control function, and to control the permanent magnet synchronous motor based on the control scheme; The second determining module is further configured to: Determine the performance index function, wherein the performance index function is: ， Among them, i α and i β This represents the α-axis and β-axis stator currents of the PMSM. and Predict the current along the α-axis and β-axis, respectively. and These are the back electromotive forces along the α-axis and β-axis, respectively, and ξ represents the step index, which is used to adjust the order-of-magnitude balance between the back electromotive forces and the αβ-axis currents. The back electromotive force error is processed based on the performance index function to obtain a third process, wherein the third process is: Where L is the stator inductance and R is the stator resistance. , These are the back electromotive force errors along the α-axis and β-axis, respectively. , For unknown disturbance increments; Taking partial derivatives of the third equation yields the fourth equation, which is: Based on the fourth equation, combined with the predicted current equation and the fact that the partial derivative is equal to 0, the standard form of the back electromotive force estimate is as follows: The formula for estimating the back electromotive force is obtained by compensating for the formula as follows: , u α ( k )and u β ( k These are the stator voltages along the α and β axes, respectively. This is the compensation coefficient.

6. The apparatus according to claim 5, characterized in that, The first determining module is specifically used for: Determine the mathematical model of the dq axis of the permanent magnet synchronous motor; After performing inverse Park transform and simplification on the dq-axis mathematical model, and then processing it using the forward Euler method, the corresponding predicted current equation is obtained: ; Determine the conversion relationship between the α-axis and β-axis stator currents and the d-axis and q-axis stator currents; Based on the transformation relationship and the predicted current equation, the target control function of the permanent magnet synchronous motor is determined by MPCC.

7. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-4.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-4.

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