Incremental deadbeat current prediction control method for permanent magnet synchronous motor with inductance identification

Abstract

The application relates to a permanent magnet synchronous motor incremental deadbeat current prediction control method with inductance identification, and relates to the technical field of permanent magnet synchronous motor control, and comprises the following steps: step S01: mathematically modeling the voltage in the d, q axis coordinate system of a permanent magnet synchronous motor; step S02: subtracting the predicted current value at the first k +1 moment from the predicted current value at the first k moment to obtain an incremental current value, adding the incremental current value to the current value, deducing the predicted current after eliminating the magnetic flux parameter, and remodeling; step S03: identifying the inductance parameter in the predicted current after eliminating the magnetic flux parameter, feeding back the identified inductance to the current loop control system, and self-adaptively updating the inductance. Through the method, the identified inductance is fed back to the motor control system, the self-adaptive updating of the inductance parameter is realized, the adverse effects caused by the inductance parameter mismatch are solved, and the stability and prediction accuracy of the motor control system are enhanced.

Description

Technical Field

[0001] This invention relates to the field of permanent magnet synchronous motor control technology, and in particular to an incremental deadbeat-free current prediction control method for permanent magnet synchronous motors with inductance identification. Background Technology

[0002] Permanent magnet synchronous motors (PMSMs) are widely used in industries such as new energy vehicles and medical devices due to their advantages of simple structure, low noise, high reliability, and high power factor. PMSMs are multivariable, nonlinear, and strongly coupled systems, highly sensitive to parameter perturbations and external load disturbances. To meet the requirements of high dynamic response, strong robustness, and high efficiency for PMSM systems, research on motor control algorithms has become a key focus. Replacing traditional proportional-integral (PI) control with incremental deadbeat current predictive control (IDPCC) can achieve better control performance and accuracy. However, IDPCC still suffers from reduced prediction accuracy and poor motor control performance due to parameter mismatch. IDPCC can solve the problems of low control accuracy and poor anti-interference in DPCC caused by flux parameter mismatch, but it may lead to inductance parameter mismatch, causing increased motor operating temperature, which in turn reduces motor life and operating efficiency. Using a disturbance observer to address the inductance parameter mismatch problem is complex and difficult to design. Summary of the Invention

[0003] In view of the above-mentioned shortcomings and deficiencies of the prior art, the present invention provides an incremental deadbeat-free current prediction control method for permanent magnet synchronous motors with inductor identification. By feeding back the identified inductance to the motor control system, the inductance parameters are adaptively updated, which solves the adverse effects caused by inductance parameter mismatch and enhances the stability and prediction accuracy of the motor control system.

[0004] To achieve the above objectives, the main technical solutions adopted by the present invention include: An incremental, deadbeat-free predictive current control method for permanent magnet synchronous motors with inductance identification includes the following steps: Step S01: Mathematically model the voltage of the permanent magnet synchronous motor in the d and q axis coordinate system, discretize it using the first-order Taylor formula to obtain the predicted current at time k+1, and replace the current prediction value at time k+2 with the reference current to achieve one-step delay compensation. Step S02: Based on the mathematical modeling in step S01, subtract the predicted current value at time k+1 from the predicted current value at time k to obtain the incremental current value, and then add the incremental current value to the current value to derive the predicted current after eliminating the magnetic flux parameter and remodel it. Step S03: Based on the remodeling, the inductance parameter in the predicted current with the magnetic flux parameter eliminated is identified, and the identified inductance is fed back to the current loop control system to make the inductance update adaptively. Step S04: Add a low-pass filter and determine the coefficient setting range in inductor identification so that the inductor value fed back to the system after identification conforms to the set accuracy range. Step S05: Use the DPCC control method to obtain the current and voltage values ​​at the previous two moments, and substitute them into steps S01-S04 to realize IDPCC control with inductor identification.

[0005] Further, step S01 includes: The mathematical model of the voltage of the permanent magnet synchronous motor in the d- and q-axis coordinate system is as follows: (1); In the formula, , These are the d-axis and q-axis voltages, respectively. For SPMSM stator resistors, , These are the d-axis and q-axis currents, respectively. The angular velocity of the motor. It is an SPMSM stator inductor. Permanent magnetic flux; Discretize equation (1) using the first-order Taylor formula to obtain the predicted d-axis and q-axis currents at time k+1. for: (2); In the formula, , , , , These represent the d-axis current, q-axis voltage, and motor angular velocity at time k, respectively. The sampling period; Predict the current along the d-axis. Predict the current for the q-axis.

[0006] Replace the predicted current value at time k+2 with the reference current, i.e. After one-step delay compensation, the reference current formula is obtained as follows: (4); The formula for obtaining the reference voltage is: (5); in, The d-axis reference current, This is the q-axis reference current. The d-axis reference voltage. This is the q-axis reference voltage.

[0007] Further, step S02 includes subtracting the predicted current value at time k+1 from the predicted current value at time k to obtain the incremental current value as follows: (6); In the formula, The predicted current increment along the d-axis at time k+1. The predicted current increment along the q-axis at time k+1. Let k be the d-axis current increment at time k. Let k be the q-axis current increment at time k. Let k be the voltage increment along the d-axis at time k. The q-axis voltage increment at time k This represents the stator resistance increment of the SPMSM. The sampling period is The angular velocity of the motor. It is an SPMSM stator inductor; Add the incremental current value to the current value to derive the predicted current after eliminating the magnetic flux parameter, and then remodel it as follows: (7); In the formula, Predict the d-axis current at time k+1. Predict the q-axis current at time k+1.

[0008] Furthermore, in step S03, the inductor is identified using the following formula: (14); (16); In the formula, , These are the actual inductance parameter values. The sampling period is For SPMSM stator inductors, Predict the current along the d-axis; For d-axis current, Let d be the voltage along the d-axis, and k be the voltage at time k. Predict the current for the q-axis; For q-axis current, This is the q-axis voltage.

[0009] Furthermore, in step S04, the coefficient setting range in inductor identification satisfies: (19); In the formula, i pre(k) represents the predicted current at time k, and i(k) represents the current at time k. Let k be the voltage increment at time k.

[0010] Furthermore, in step S04, a low-pass filter is added to obtain stable inductor parameters, as follows: (twenty one); In the formula, The inductance parameters after stabilization. Here are the coefficients of the low-pass filter, and k is the value at time k. It is an SPMSM stator inductor.

[0011] The beneficial effects of this invention are as follows: This invention addresses the problems in traditional IDPCC control where inductor parameter mismatch leads to decreased current prediction accuracy, resulting in reduced motor control performance and poor efficiency. It proposes an IDPCC control with inductor identification, which feeds back the identified inductance to the motor control system to achieve adaptive updating of inductor parameters. This effectively solves the adverse effects caused by inductor parameter mismatch and enhances the stability and prediction accuracy of the control system.

[0012] The IDPCC control with inductance identification of the present invention not only achieves new control by changing the control method, but also effectively solves the problem of motor damage caused by sudden changes in inductance during the inductance identification process by using a low-pass filter and setting parameter limiting. Attached Figure Description

[0013] Figure 1 This is a schematic diagram of the incremental deadbeat-free current prediction control method for permanent magnet synchronous motors with inductance identification according to the present invention. Figure 2 This is a simulation result diagram of inductor identification in a specific embodiment of the present invention; Figure 3 This is a simulation result diagram of d-axis current prediction in a specific embodiment of the present invention; Figure 4 This is a simulation result diagram of q-axis current prediction in a specific embodiment of the present invention; Figure 5 This is a diagram showing the torque simulation results in a specific embodiment of the present invention; Figure 6 This is a simulation result diagram of rotational speed in a specific embodiment of the present invention; Figure 7 This is a comparison chart of d-axis current predictions in the comparative examples of the present invention; Figure 8 This is a comparison chart of q-axis current predictions in the comparative examples of this invention; Figure 9The above is a simulation result of inductor identification in a comparative example of the present invention, with an inductor identification time of 0.05s and an initial inductance of 50% of the actual inductance. Figure 10 The above is a simulation result of inductor identification in a comparative example of the present invention, with an initial inductance of 50% of the actual inductance and an initial inductance of 0.15s. Figure 11 The above is a simulation result of inductance identification in a comparative example of the present invention, with the inductance identification start time being 0.15s and the initial inductance set to 50% of the actual inductance. Detailed Implementation

[0014] To better explain and facilitate understanding of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0015] like Figure 1 As shown, this invention provides an incremental deadbeat-free current prediction control method for permanent magnet synchronous motors with inductance identification, comprising the following steps: Step S01: Mathematically model the voltage of the permanent magnet synchronous motor in the d and q axis coordinate system, discretize it using the first-order Taylor formula to obtain the predicted current at time k+1, and replace the current prediction value at time k+2 with the reference current to achieve one-step delay compensation.

[0016] Specifically, a mathematical model is performed on the voltage in the d- and q-axis coordinate systems of the surface-mounted permanent magnet synchronous motor, whereby... The voltage equation is: (1); In the formula, , These are the d-axis and q-axis voltages, respectively. For SPMSM stator resistors, , These are the d-axis and q-axis currents, respectively. The angular velocity of the motor. It is an SPMSM stator inductor. Permanent magnetic flux; Discretizing equation (1) using the first-order Taylor formula yields the predicted d-axis and q-axis currents at time k+1. for: (2); In the formula, , , , and These represent the d-axis current, q-axis voltage, and motor angular velocity at time k, respectively. Indicates the sampling period. Predict the current along the d-axis. Predict the current for the q-axis.

[0017] In practical digital control systems, a one-step delay can occur. To address this issue, a DPCC typically calculates the predicted current value at time k+2, i.e.: (3); Because of the motor's angular velocity Mechanical variables of the motor change very slowly, so the motor's angular velocity is still the value at time k, i.e. It is usually taken as a constant value over several periods.

[0018] After calculating the predicted current value at time k+2, replace the predicted current value at time k+2 with the reference current, that is... To achieve a one-step delay compensation effect, the reference current formula can be derived as follows: (4); By deriving formula (4), the reference voltage equation in the formula can be obtained as follows: (5); in, The d-axis reference current, This is the q-axis reference current. The d-axis reference voltage. This is the q-axis reference voltage.

[0019] Step S02: Based on the mathematical modeling in step S01, subtract the predicted current value at time k+1 from the predicted current value at time k to obtain the incremental current value, and then add the incremental current value to the current value to derive the predicted current after eliminating the magnetic flux parameter and remodel it.

[0020] Specifically, by using IDPCC to calculate the predicted current value required in step S01, it can be seen that the motor angular velocity in equation (3) is... The predicted current remains almost constant across two consecutive time points. IDPCC utilizes this property by subtracting the predicted current value at time k+1 from that at time k, thereby eliminating the inequality in the q-axis predicted current formula. In the parameter section, the predicted current is obtained by adding the incremental current to the current at the current moment, thereby eliminating the influence of flux parameter mismatch in the control. The incremental current is obtained by subtraction: (6); In the formula, The predicted current increment along the d-axis at time k+1. The predicted current increment along the q-axis at time k+1. Let k be the d-axis current increment at time k. Let k be the q-axis current increment at time k. Let k be the voltage increment along the d-axis at time k. The q-axis voltage increment at time k This represents the stator resistance increment of the SPMSM.

[0021] By adding the incremental current to the current at the current moment, the predicted current at time k+1 in the IDPCC for eliminating the magnetic flux parameter can be obtained, i.e.: (7); In the formula, Predict the d-axis current at time k+1. Predict the q-axis current at time k+1.

[0022] As can be seen from the above equation derivation process, the magnetic flux parameter in the predicted current value in formula (7) is eliminated, proving that IDPCC can solve the problems of reduced control performance and poor prediction effect caused by changes in magnetic flux parameter.

[0023] Step S03: Based on the remodeling, the inductance parameter in the predicted current with eliminated magnetic flux parameter is identified, and the identified inductance is fed back to the current loop control system to enable adaptive inductance updates.

[0024] Specifically, after mathematically modeling the IDPCC, an IDPCC with inductance identification is set up based on this, and derivation and mathematical modeling are performed. Due to the short sampling period, even if there is resistance mismatch, and The product of is very small and can be ignored, so the effect of resistance mismatch on control performance can be ignored. Equation (6) can be rewritten as: (8); From equation (8), we can obtain: (9); For equation (9), These are the controller inductance parameters. In practice, the formula for the inductance parameter is: (10); In the formula, These are the actual inductance parameter values.

[0025] Subtracting equation (10) from equation (9) yields: (11); Expanding equation (11) as follows: (12); Further derivation yields: (13); Ultimately, it can be deduced that The expression is: (14); As can be seen from equation (14), the inductance identification calculation requires the voltage and current values ​​at times k-1 and k-2. Therefore, the present invention combines DPCC with IDPCC with inductance identification. When the motor starts, DPCC is used for control first. After running two control cycles, the voltage and current values ​​required by equation (14) are obtained, and then the control is switched to IDPCC to realize IDPCC control with inductance identification.

[0026] Equation (14) can be further derived as follows: (15); In the formula , is the coefficient of inductance variation.

[0027] Further derivation: (16).

[0028] Step S04: Add a low-pass filter and determine the coefficient setting range in inductor identification so that the inductor value fed back to the system after identification conforms to the set accuracy range.

[0029] Specifically, setting inductance tolerance It is ±20%, that is: (17); According to equation (17), the following can be calculated: The value range is [0.833, 1.25]. Considering the actual situation and safety margin, through overall system design and simulation debugging, The value range is determined to be [0.5, 2].

[0030] In determining After determining the range of values, we can conclude that: (18); Under ideal conditions, according to equation (18), the following can be determined: The value range is [0.015, -0.029]. The control method of this invention identifies the inductor when the system experiences dynamic response or poor control accuracy, and feeds back the identified inductor to the system to solve the problem of performance degradation and accuracy reduction caused by external noise. Therefore, when... and If the value exceeds the stable range, inductor identification begins, thereby stabilizing the system. In the control system of this invention, considering safety margins and actual conditions, the coefficient... The value is much smaller than the range limit, so a current error greater than 0.1 and a voltage error greater than 0.5 in the model are considered to indicate system instability. Under this setting, the coefficient is also satisfied. The range of values ​​for is: (19); In the formula, i pre (k) represents the predicted current at time k, and i(k) represents the current at time k. Let k be the voltage increment at time k.

[0031] After obtaining the identified inductance parameters, the identified inductance is fed back to the current loop control system, and the predicted current can be obtained as follows: (20); Simultaneously, a low-pass filter is used to suppress high-frequency oscillations, resulting in stable inductor parameters, which can be expressed as: (twenty one); In the formula, The inductance parameters after stabilization. Set the coefficients of the low-pass filter. .

[0032] Step S05: Use the DPCC control method to obtain the current and voltage values ​​at the previous two moments, and substitute them into steps S01-S04 to realize IDPCC control with inductor identification.

[0033] The designed method was verified by simulation experiments. In order to verify the effectiveness of the IDPCC with inductor identification in improving the steady-state performance and current prediction accuracy of the motor, the method proposed in this invention was simulated and analyzed by Matlab / Simulink. The parameters of the PMSM in the simulation are shown in Table 1.

[0034] Table 1 shows the PMSM parameter table: .

[0035] First, given a rotational speed of 2000 r / min, a sudden load torque of 10 N·m is applied at 0.1 s, and the load is suddenly reduced to 5 N·m at 0.2 s. Simultaneously, the rotational speed is changed to 1000 r / min at 0.3 s, and then restored to 2000 r / min at 0.5 s. Identification is set to begin at 0.05 s, with the initial inductance being 200% of the actual inductance. The operating results are as follows... Figure 2-6As shown in the simulation results, the inductor identification error is very small during sudden load torque application and reduction, and further decreases during acceleration and deceleration. The current prediction accuracy remains good throughout the entire process, with no significant deviation. Furthermore, the torque and speed simulation graphs demonstrate excellent response speed and tracking performance.

[0036] Comparative example: Under the same operating conditions, simulations were performed to compare the existing traditional DPCC and the designed IDPCC with inductor identification. The comparison results are as follows: Figure 7-8 As shown, according to Figure 7 , Figure 8 The comparative simulation results show that the IDPCC control system with inductor identification of the present invention has better prediction accuracy for d-axis and q-axis current prediction and tracking than DPCC.

[0037] To further verify the feasibility and superiority of the proposed method, the starting inductance identification time and the initial value of inductance identification were changed for verification. Simulation experiments were conducted under three conditions: inductance identification time of 0.05s and initial inductance of 50% of the actual inductance; starting inductance identification time of 0.15s and initial inductance of 50% of the actual inductance; and starting inductance identification time of 0.15s and initial inductance of 50% of the actual inductance.

[0038] from Figure 9-11 It can be seen that the designed method achieves good inductance identification accuracy under different operating conditions. Overall, this demonstrates that the designed IDPCC with inductance identification not only improves the prediction accuracy of the control system and increases the anti-interference capability of parameters under different operating conditions, but is also applicable to motors under various working conditions.

[0039] 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. Any modifications, alterations, substitutions, and variations made by those skilled in the art to the above embodiments are within the scope of the present invention.

Claims

1. An incremental deadbeat-free predictive control method for permanent magnet synchronous motors with inductance identification, characterized in that, Includes the following steps: Step S01: Mathematically model the voltage of the permanent magnet synchronous motor in the d and q axis coordinate system, discretize it using the first-order Taylor formula to obtain the predicted current at time k+1, and replace the current prediction value at time k+2 with the reference current to achieve one-step delay compensation. Step S02: Based on the mathematical modeling in step S01, subtract the predicted current value at time k+1 from the predicted current value at time k to obtain the incremental current value, and then add the incremental current value to the current value to derive the predicted current after eliminating the magnetic flux parameter and remodel it. Step S03: Based on the remodeling, the inductance parameter in the predicted current with the magnetic flux parameter eliminated is identified, and the identified inductance is fed back to the current loop control system to make the inductance update adaptively. Step S04: Add a low-pass filter and determine the coefficient setting range in inductor identification so that the inductor value fed back to the system after identification conforms to the set accuracy range. Step S05: Use the DPCC control method to obtain the current and voltage values ​​at the previous two moments, and substitute them into steps S01-S04 to realize IDPCC control with inductor identification.

2. The incremental deadbeat-free current prediction control method for permanent magnet synchronous motors with inductance identification according to claim 1, characterized in that, Step S01 includes: The mathematical model of the voltage of the permanent magnet synchronous motor in the d- and q-axis coordinate system is as follows: （1）； In the formula, , These are the d-axis and q-axis voltages, respectively. For SPMSM stator resistors, , These are the d-axis and q-axis currents, respectively. The angular velocity of the motor. It is an SPMSM stator inductor. Permanent magnetic flux; Discretize equation (1) using the first-order Taylor formula to obtain the predicted d-axis and q-axis currents at time k+1. for: （2）； In the formula, , , , , These represent the d-axis current, q-axis voltage, and motor angular velocity at time k, respectively. The sampling period; Predict the current along the d-axis. Predict the current for the q-axis; Replace the predicted current value at time k+2 with the reference current, i.e. After one-step delay compensation, the reference current formula is obtained as follows: （4）； The formula for obtaining the reference voltage is: （5）； in, The d-axis reference current, This is the q-axis reference current. The d-axis reference voltage. This is the q-axis reference voltage.

3. The incremental deadbeat-free current prediction control method for permanent magnet synchronous motors with inductance identification according to claim 1, characterized in that, Step S02 includes subtracting the predicted current value at time k+1 from the predicted current value at time k to obtain the incremental current value as follows: （6）； In the formula, The predicted current increment along the d-axis at time k+1. The predicted current increment along the q-axis at time k+1. Let k be the d-axis current increment at time k. Let k be the q-axis current increment at time k. Let k be the voltage increment along the d-axis at time k. The q-axis voltage increment at time k This represents the stator resistance increment of the SPMSM. The sampling period is The angular velocity of the motor. It is an SPMSM stator inductor; Add the incremental current value to the current value to derive the predicted current after eliminating the magnetic flux parameter, and then remodel it as follows: （7）； In the formula, Predict the d-axis current at time k+1. Predict the q-axis current at time k+1.

4. The incremental deadbeat-free current prediction control method for permanent magnet synchronous motors with inductance identification according to claim 1, characterized in that, In step S03, the inductor is identified using the following formula: （14）； （16）； In the formula, , These are the actual inductance parameter values. The sampling period is For SPMSM stator inductors, Predict the current along the d-axis; For d-axis current, Let d be the voltage along the d-axis, and k be the voltage at time k. Predict the current for the q-axis; For q-axis current, This is the q-axis voltage.

5. The incremental deadbeat-free current prediction control method for permanent magnet synchronous motors with inductance identification according to claim 1, characterized in that, In step S04, the coefficient setting range in inductor identification satisfies the following: （19）； In the formula, i pre (k) represents the predicted current at time k, and i(k) represents the current at time k. Let k be the voltage increment at time k.

6. The incremental deadbeat-free current prediction control method for permanent magnet synchronous motors with inductance identification according to claim 1, characterized in that, In step S04, a low-pass filter is added to obtain stable inductor parameters, as follows: （21）； In the formula, The inductance parameters after stabilization. Here are the coefficients of the low-pass filter, and k is the value at time k. It is an SPMSM stator inductor.

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