A method for MTPA control of permanent magnet synchronous motor based on Newton iteration method

Abstract

The application discloses a MTPA control method of a permanent magnet synchronous motor based on a Newton iteration method, and comprises the following steps: obtaining a target torque instruction output by a speed regulator and real-time parameters of the permanent magnet synchronous motor; performing Newton iteration operation according to the target torque instruction output by the speed regulator and the real-time parameters of the permanent magnet synchronous motor, solving an optimal current instruction, and inputting the optimal current instruction into a current regulator to realize MTPA control of the permanent magnet synchronous motor. The application solves the problem that in the existing MTPA control method of the permanent magnet synchronous motor, offline experiments or precalculation of optimal currents corresponding to different torques are mostly adopted, the optimal currents are stored as a query table, and the current instruction is obtained by looking up the table during operation. This method needs to measure and establish the query table in advance, which not only leads to a complicated control strategy deployment process and a long preparation period, but also causes the measurement to be susceptible to equipment precision and environmental interference, and introduces measurement errors.

Description

Technical Field

[0001] This invention relates to the field of permanent magnet synchronous motor technology, specifically to an MTPA control method for permanent magnet synchronous motors based on Newton's iterative method. Background Technology

[0002] Permanent magnet synchronous motors (PMSMs), with their high power density, high efficiency, and excellent dynamic response characteristics, have been widely used in many fields such as home appliances, industrial equipment, and electric vehicles. Vector control (FOC) is currently the mainstream technology for achieving high-performance control of PMSMs. However, within the FOC architecture, the core technical challenge is how to optimally allocate the direct-axis and quadrature-axis currents to minimize stator copper losses while outputting a specified torque. Maximum torque per ampere (MTPA) control is a key solution to this problem. Existing PMSM MTPA control methods often employ offline experiments or pre-calculation of the optimal current for different torques, storing this information in a lookup table. During runtime, the current command is retrieved by looking up the table. However, implementing such methods relies on pre-conducted measurement experiments and lookup table establishment processes. This not only leads to cumbersome deployment of control strategies and long preparation periods, but also makes the measurement process susceptible to factors such as the accuracy of experimental equipment and environmental interference, introducing unavoidable measurement errors and affecting the accuracy of PMSM MTPA control. Summary of the Invention

[0003] To address the aforementioned shortcomings, this invention proposes an MTPA control method for permanent magnet synchronous motors based on Newton's iteration method. The aim is to solve the problem that existing MTPA control methods for permanent magnet synchronous motors often rely on offline experiments or pre-calculation of the optimal current corresponding to different torques and storage in a lookup table. During runtime, the current command is obtained by looking up the table. This method requires pre-measurement and the establishment of the lookup table, which not only leads to a cumbersome control strategy deployment process and a long preparation cycle, but also makes the measurement susceptible to interference from equipment accuracy and the environment, introducing measurement errors.

[0004] To achieve this objective, the present invention adopts the following technical solution: A MTPA control method for permanent magnet synchronous motors based on Newton's iterative method is applied to a permanent magnet synchronous motor control system including a speed regulator and a current regulator, and includes the following steps: Step S1: Input the target speed signal and speed feedback signal into the speed regulator for processing, and output the target torque command. ; Step S2: Obtain the real-time parameters of the permanent magnet synchronous motor, wherein the real-time parameters of the permanent magnet synchronous motor include the flux linkage. Direct-axis inductor and quadrature axis inductance ; Step S3: According to First preset coefficient Second preset coefficient Determine the initial value for the direct-axis current iteration. and the initial value of the quadrature axis current iteration ; Step S4: For and Perform iterative calculations. During the iteration process, execute steps S5-S8 and determine whether the following convergence conditions are met: ; in, Indicates a preset constant; If so, then and As the optimal current command input current regulator; if not, then as and As the current, repeat steps S5-S8 until the convergence condition is met, and input the corresponding optimal current command into the current regulator to complete the control of MTPA. Step S5: Calculate the current direct-axis current based on the real-time parameters of the permanent magnet synchronous motor. and current quadrature axis current constraint function value And the electromagnetic torque constraint function value of the current permanent magnet synchronous motor where k is a positive integer; Step S6: Calculate the value of each element in the Jacobian matrix, and calculate the determinant of the Jacobian matrix based on the value of each element in the Jacobian matrix; Step S7: According to , The values ​​of each element in the Jacobian matrix and the determinant of the Jacobian matrix are calculated to obtain... Iterative increment as well as Iterative increment ; Step S8: According to and The direct-axis current after the (k+1)th iteration is calculated. and cross-axis current ,in, and The specific calculation formula is as follows: ; .

[0005] Preferably, in step S3, when hour, and The calculation formulas are as follows: ; ; when hour, and The calculation formulas are as follows: ; .

[0006] Preferably, in step S5, the current direct-axis current and current quadrature axis current constraint function value The calculation formula is as follows: ; Current electromagnetic torque constraint function value of permanent magnet synchronous motor The calculation formula is as follows: ; Where P represents the number of pole pairs of the permanent magnet synchronous motor.

[0007] Preferably, in step S6, the calculation formulas for each element value in the Jacobian matrix J are as follows: ; ; ; ; Where J11 represents the element value in the first row and first column of the Jacobian matrix J; J12 represents the element value in the first row and second column of the Jacobian matrix J; J21 represents the element value in the second row and first column of the Jacobian matrix J; and J22 represents the element value in the second row and second column of the Jacobian matrix J.

[0008] Preferably, in step S6, the specific formula for calculating the determinant of the Jacobian matrix is ​​as follows: ; in, This represents the determinant value of the Jacobian matrix J.

[0009] Preferably, in step S7, Iterative increment The specific calculation formula is as follows: ; Iterative increment The specific calculation formula is as follows: .

[0010] The technical solution provided by this invention may include the following beneficial effects: This scheme acquires the target torque command output by the speed regulator and the real-time parameters of the permanent magnet synchronous motor (PMSM), and performs Newton's iteration calculations to obtain the optimal current command. This optimal current command is then input into the current regulator to achieve MTPA control of the PMSM. Compared to traditional techniques that use offline experiments or pre-calculate the optimal current for different torques and store it in a lookup table, then retrieve the current command at runtime by looking up the table, this scheme directly solves for the optimal current command using Newton's iteration method. This eliminates the need for prior measurement experiments and lookup tables, effectively simplifying the deployment process of the control strategy and shortening the preparation period. Furthermore, it avoids errors introduced by external factors during measurement, thereby improving the MTPA control accuracy of the PMSM. Attached Figure Description

[0011] Figure 1 This is a flowchart of the steps of an MTPA control method for a permanent magnet synchronous motor based on Newton's iterative method. Detailed Implementation

[0012] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown 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 are only used to explain the present invention, and should not be construed as limiting the present invention.

[0013] A MTPA control method for permanent magnet synchronous motors based on Newton's iterative method is applied to a permanent magnet synchronous motor control system including a speed regulator and a current regulator, and includes the following steps: Step S1: Input the target speed signal and speed feedback signal into the speed regulator for processing, and output the target torque command. ; Step S2: Obtain the real-time parameters of the permanent magnet synchronous motor, wherein the real-time parameters of the permanent magnet synchronous motor include the flux linkage. Direct-axis inductor and quadrature axis inductance ; Step S3: According to First preset coefficient Second preset coefficient Determine the initial value for the direct-axis current iteration. and the initial value of the quadrature axis current iteration ; Step S4: For and Perform iterative calculations. During the iteration process, execute steps S5-S8 and determine whether the following convergence conditions are met: ; in, Indicates a preset constant; If so, then and As the optimal current command input current regulator; if not, then as and As the current, repeat steps S5-S8 until the convergence condition is met, and input the corresponding optimal current command into the current regulator to complete the control of MTPA. Step S5: Calculate the current direct-axis current based on the real-time parameters of the permanent magnet synchronous motor. and current quadrature axis current constraint function value And the electromagnetic torque constraint function value of the current permanent magnet synchronous motor where k is a positive integer; Step S6: Calculate the value of each element in the Jacobian matrix, and calculate the determinant of the Jacobian matrix based on the value of each element in the Jacobian matrix; Step S7: According to , The values ​​of each element in the Jacobian matrix and the determinant of the Jacobian matrix are calculated to obtain... Iterative increment as well as Iterative increment ; Step S8: According to and The direct-axis current after the (k+1)th iteration is calculated. and cross-axis current ,in, and The specific calculation formula is as follows: ; .

[0014] This proposal presents an MTPA control method for permanent magnet synchronous motors based on Newton's iterative method, such as... Figure 1 As shown, the first step is to input the target speed signal and the speed feedback signal into the speed regulator for processing, and output the target torque command. In this embodiment, the target speed signal and the speed feedback signal are input into the speed regulator and a target torque command is output. This ensures the matching of torque command and speed requirement, providing a precise torque reference for optimal current allocation in subsequent MTPA control. Furthermore, when the permanent magnet synchronous motor control system is in motoring mode, the target torque command... It is a positive value; when the permanent magnet synchronous motor control system is in braking state, the target torque command is... The value is negative. The second step is to obtain the real-time parameters of the permanent magnet synchronous motor, which include the flux linkage. Direct-axis inductor and quadrature axis inductance In this embodiment, by acquiring the real-time parameters of the permanent magnet synchronous motor, it is possible to adapt to the changes in parameters with operating conditions during the operation of the permanent magnet synchronous motor, avoiding the low MTPA control accuracy caused by fixed parameters. The third step is based on First preset coefficient Second preset coefficient Determine the initial value for the direct-axis current iteration. and the initial value of the quadrature axis current iteration In this embodiment, by determining the initial values ​​for the direct-axis current and quadrature-axis current iterations, a precise initial data benchmark is provided for the subsequent iterative update process of the direct-axis current and quadrature-axis current, ensuring that the iterative calculation starts from a state closer to the optimal solution. The fourth step is... and Perform iterative calculations. During the iteration process, execute steps S5-S8 and determine whether the following convergence conditions are met: ;in, Indicates a preset constant; if so, then... and As the optimal current command input current regulator; if not, then as and As the current, steps S5-S8 are repeated until the convergence condition is met. The corresponding optimal current command is then input to the current regulator to complete the MTPA control. In this embodiment, a preset constant is used. Set to 0.05 .pass" The convergence condition for determining whether the iteration of the direct-axis current and quadrature-axis current has terminated not only ensures the accuracy of the command current but also avoids over-iteration. The fifth step is to calculate the current direct-axis current based on the real-time parameters of the permanent magnet synchronous motor. and current quadrature axis current constraint function value And the electromagnetic torque constraint function value of the current permanent magnet synchronous motor Where k is a positive integer, in this embodiment, by calculating the constraint function values ​​of the current direct-axis current and the current quadrature-axis current, as well as the electromagnetic torque constraint function value of the current permanent magnet synchronous motor, it is ensured that the subsequent Newton iteration direction always points to the optimal solution where "torque meets the requirements and copper loss is minimized". The sixth step is to calculate the value of each element in the Jacobian matrix, and based on the value of each element in the Jacobian matrix, calculate the determinant of the Jacobian matrix. In this embodiment, by calculating the value of each element in the Jacobian matrix and the determinant, a data basis is provided for the subsequent calculation of the iteration increment of the direct-axis current and the quadrature-axis current, ensuring that the iteration step size and direction are more in line with the nonlinear characteristics of the control system. The seventh step is based on , The values ​​of each element in the Jacobian matrix and the determinant of the Jacobian matrix are calculated to obtain... Iterative increment as well as Iterative increment In this embodiment, through calculation Iterative increment and Iterative increment This achieves stable updates of the direct-axis and quadrature-axis currents, avoiding blind adjustments and ensuring that each iteration progresses towards the optimal solution based on quantization logic. The eighth step is based on... and The direct-axis current after the (k+1)th iteration is calculated. and cross-axis current ,in, and The specific calculation formula is as follows: ; In this embodiment, the direct-axis current and quadrature-axis current are updated by using the "current current + iteration increment" method, which makes the operation logic of the iteration process simple and easy to implement.

[0015] This scheme acquires the target torque command output by the speed regulator and the real-time parameters of the permanent magnet synchronous motor (PMSM), and performs Newton's iteration calculations to obtain the optimal current command. This optimal current command is then input into the current regulator to achieve MTPA control of the PMSM. Compared to traditional techniques that use offline experiments or pre-calculate the optimal current for different torques and store it in a lookup table, then retrieve the current command at runtime by looking up the table, this scheme directly solves for the optimal current command using Newton's iteration method. This eliminates the need for prior measurement experiments and lookup tables, effectively simplifying the deployment process of the control strategy and shortening the preparation period. Furthermore, it avoids errors introduced by external factors during measurement, thereby improving the MTPA control accuracy of the PMSM.

[0016] Preferably, in step S3, when hour, and The calculation formulas are as follows: ; ; when hour, and The calculation formulas are as follows: ; .

[0017] In this embodiment, and Take 1 for all By following the target torque command Given the polarity of the current, calculate the initial value of the corresponding direct-axis current iteration. and the initial value of the quadrature axis current iteration This ensures that the initial current value is precisely matched with the torque direction, guaranteeing that the iteration starts from the current range that matches the current torque requirement, thereby shortening the iteration convergence time.

[0018] Preferably, in step S5, the current direct-axis current and current quadrature axis current constraint function value The calculation formula is as follows: ; Current electromagnetic torque constraint function value of permanent magnet synchronous motor The calculation formula is as follows: ; Where P represents the number of pole pairs of the permanent magnet synchronous motor.

[0019] In this embodiment, the current direct-axis current is calculated. and current quadrature axis current constraint function value This allows for precise quantification of the deviation between the current state and the optimal MTPA condition. It is achieved by calculating the electromagnetic torque constraint function value of the current permanent magnet synchronous motor. This enables the correlation between the current state and the electromagnetic torque.

[0020] Preferably, in step S6, the calculation formulas for each element value in the Jacobian matrix J are as follows: ; ; ; ; Where J11 represents the element value in the first row and first column of the Jacobian matrix J; J12 represents the element value in the first row and second column of the Jacobian matrix J; J21 represents the element value in the second row and first column of the Jacobian matrix J; and J22 represents the element value in the second row and second column of the Jacobian matrix J.

[0021] In this embodiment, the calculation of the J11 element in the Jacobian matrix J is specifically performed by... Regarding direct-axis inductors The partial derivative is obtained. In calculating the J12 elements of the Jacobian matrix J, specifically through... Regarding quadrature inductors The partial derivative is obtained. In calculating the J21 elements in the Jacobian matrix J, specifically through... Regarding direct-axis inductors The partial derivative is obtained. In calculating the J22 elements in the Jacobian matrix J, specifically through... Regarding quadrature inductors The partial derivatives are obtained. The calculation of each element value does not require additional complex mathematical models, which effectively reduces computational complexity and ensures the logical consistency between the Jacobian matrix elements and the constraint functions.

[0022] Preferably, in step S6, the specific formula for calculating the determinant of the Jacobian matrix is ​​as follows: ; in, This represents the determinant value of the Jacobian matrix J.

[0023] Beneficial effects: In this embodiment, the Jacobian matrix determinant is the core parameter for calculating the current iteration increment in the Newton iteration method. This calculation formula can accurately quantify the linear correlation between matrix elements, avoid the interference of determinant calculation error on the iteration increment, and ensure that the iteration direction always fits the optimal goal of "torque meets the requirements and copper loss is minimized".

[0024] Preferably, in step S7, Iterative increment The specific calculation formula is as follows: ; Iterative increment The specific calculation formula is as follows: .

[0025] In this embodiment, by combining the elements of the Jacobian matrix, the determinant of the Jacobian matrix, and the constraint function values ​​for iterative incremental calculation, the local fast convergence characteristic of the Newton iteration method is fully utilized, enabling the iteration of the direct-axis current and the quadrature-axis current to quickly approach the optimal solution, thereby shortening the convergence time and improving the real-time response capability of MTPA control.

[0026] Furthermore, the functional units in the various embodiments of the present invention can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0027] 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 MTPA control method of a permanent magnet synchronous motor based on Newton iteration method, applied to a permanent magnet synchronous motor control system comprising a speed regulator and a current regulator, characterized in that: Includes the following steps: Step S1: input the speed target signal and the speed feedback signal into the speed regulator for processing, output a target torque instruction ; Step S2: Obtain the real-time parameters of the permanent magnet synchronous motor, wherein the real-time parameters of the permanent magnet synchronous motor include the flux linkage. Direct-axis inductor and cross-axis inductance ; Step S3: According to First preset coefficient Second preset coefficient Determine the initial value for the direct-axis current iteration. and the initial value of the quadrature axis current iteration ; Step S4: Iterative operation is performed on and In the iterative process, steps S5-S8 are performed, and it is determined whether the following convergence condition is satisfied: ； wherein, represents a preset constant; If yes, input the and as the optimal current command into the current regulator; if no, input the and as the current, repeat steps S5-S8 until the convergence condition is met, input the corresponding optimal current command into the current regulator to complete the MTPA control; Step S5: Calculate the current direct-axis current based on the real-time parameters of the permanent magnet synchronous motor. and current quadrature axis current constraint function value And the electromagnetic torque constraint function value of the current permanent magnet synchronous motor where k is a positive integer; Step S6: Calculate the value of each element in the Jacobian matrix, and calculate the determinant of the Jacobian matrix based on the value of each element in the Jacobian matrix; Step S7: According to , The values ​​of each element in the Jacobian matrix and the determinant of the Jacobian matrix are calculated to obtain... Iterative increment as well as Iterative increment ; Step S8: According to and , the direct-axis current and the quadrature-axis current after the k+1th iteration operation are calculated, wherein, and The specific calculation formula is as follows: ； ； In step S5, the constraint function value of the current direct-axis current and the current quadrature-axis current is calculated as follows: id * iq + (1 - d) * (id * iq + qd * iq) ； A current permanent magnet synchronous motor electromagnetic torque constraint function value The calculation formula is as follows: ； Where P represents the number of pole pairs of the permanent magnet synchronous motor; In step S6, the formulas for calculating the values ​​of each element in the Jacobian matrix J are as follows: ； ； ； ； Where J11 represents the element value in the first row and first column of the Jacobian matrix J; J12 represents the element value in the first row and second column of the Jacobian matrix J; J21 represents the element value in the second row and first column of the Jacobian matrix J; and J22 represents the element value in the second row and second column of the Jacobian matrix J. In step S7, the iterative increment The specific calculation formula is as follows: ； iterative increments of The specific formula is as follows: ； wherein denotes the determinant value of the Jacobian matrix J.

2. The MTPA control method of a permanent magnet synchronous motor based on Newton iteration method according to claim 1, characterized in that: In step S3, when , and the calculation formulas are as follows, respectively: ； ； when hour, and The calculation formulas are as follows: ； 。 3. The MTPA control method of a permanent magnet synchronous motor based on Newton iteration method according to claim 1, characterized in that: In step S6, the specific formula for calculating the determinant of the Jacobian matrix is ​​as follows: ； wherein denotes the determinant value of the Jacobian matrix J.

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