Weight coefficient-free model prediction control method for alternating-current permanent magnet synchronous motor

Abstract

The invention discloses a weight coefficient-free model prediction control method for an AC permanent magnet synchronous motor, and the method comprises the following steps: collecting motor rotor operation parameters at a moment k, obtaining an electromagnetic torque reference value # imgabs0 # and a stator flux linkage reference value # imgabs1 #, and obtaining an electromagnetic torque T'e (k), a stator flux linkage psi's (k) and a torque angle delta at the moment k; acquiring three groups of voltage vectors from the 2-D lookup table; recalculating the electromagnetic torque Te (k) and the stator flux linkage psi s (k) at the moment k; loading an improved ESO observer, obtaining an electromagnetic torque Te (k + 2) and a stator flux linkage psi s (k + 2) at a k + 2 moment, and predicting a torque angle delta (k + 2) at the k + 2 moment; and reconstructing an optimal cost function for predictive control of the AC permanent magnet synchronous motor. According to the technical scheme, the harmonic components of the torque, the flux linkage pulsation and the current can be effectively reduced, setting of the weight coefficient is not involved in the estimation process, and the calculated amount of the system is greatly simplified.

Description

Technical Field

[0001] The present invention relates to the field of motor control, and in particular to a model predictive control method for an AC permanent magnet synchronous motor without weight coefficients. Background Art

[0002] Permanent magnet synchronous motor (PMSM) has the advantages of low energy consumption and stable operation, and is considered to be a green power source to replace gasoline engines. Motor control is the core control technology of electric drive systems, so it is very important to study high-performance motor control algorithms. With the rapid development of industrial technology, finite control set model predictive control (FCS-MPC) that is easy to achieve multi-objective control and multi-constraint conditions has gradually entered the field of motor control. There are two mainstream control methods for AC permanent magnet synchronous motors, one is vector control (FOC) and the other is direct torque control (DTC). The principle of FOC is to achieve the decoupling of flux and torque through a series of coordinate transformations, and then control the speed and current components respectively through the PI controller to achieve the ideal control target, but its model is relatively simple, with few adjustable parameters, and it is not easy to control and adjust. DTC is a high-performance AC variable frequency control technology. This solution does not rely on complex coordinate transformation and pulse width modulation. It directly controls the flux and torque through a hysteresis controller and selects the voltage vector to control the motor operation according to the error value. This method is simple, practical and easy to implement, but it is limited by the hysteresis width and sampling frequency, and has problems such as large torque pulsation and excessive switching frequency, which restricts its development in high-performance occasions.

[0003] In recent years, due to the rapid development of digital technology and hardware equipment, model predictive control (MPC) has been given full attention in the field of motor drive due to its advantages such as high dynamic performance, simple and easy to implement algorithm, and flexible multi-variable tracking control by value function design. Combining the advantages of MPC and DTC, model predictive torque control (MPTC) directly servo-tracks torque and flux, omits the hysteresis controller, and uses rolling optimization to replace the switch table. It has good dynamic response performance, smaller torque pulsation than DTC, and more precise control. However, the traditional single-vector model predictive torque control (MPC-DTC) has the following disadvantages: First, the traditional MPTC needs to substitute all the feasible 8 voltage vectors (six basic vectors and two zero vectors) into the cost function for traversal optimization calculation in each sampling cycle, and the heavy computational burden limits its application in AC permanent magnet synchronous motors. Second, due to its advantages of multi-objective control, the traditional MPTC includes both electromagnetic torque and stator flux error terms in the constructed cost function. Due to the different dimensions of the two controlled quantities, weight coefficients need to be introduced. In general, in order to select the appropriate weight coefficient, a lot of simulation and experimental exploration are required. And the weight coefficient has a certain range of values. If it exceeds or falls below this range, the control performance will deteriorate. Therefore, it takes a lot of effort to select the optimal weight coefficient to meet the best control performance of the motor. Although there are some improvement methods for MPTC in terms of large amount of calculation and difficult adjustment of weight coefficients, the basic ideas are all focused on how to reduce the amount of calculation, which leads to the reduction of optional voltage vectors and affects the control accuracy of the system, or using intelligent algorithms to eliminate weight factors to improve the accuracy of voltage prediction, while also increasing the calculation burden of the system. There is a lack of torque pulsation suppression methods that can simultaneously reduce the amount of calculation and adjust the weight factor. Summary of the invention

[0004] To solve the above problems, the present application provides a model predictive control method for an AC permanent magnet synchronous motor without weight coefficients, comprising the following steps:

[0005] Collect the motor rotor operating parameters at time k to obtain the electromagnetic torque reference value and stator flux reference value The operating parameters include: electrical angular velocity ω, rotor position θ, three-phase motor current i a (k), i b (k), i c (k), DC bus voltage u dc (k), d, q axis component i d (k), i q (k), α, β axis component i α (k), i β (k);

[0006] Get the electromagnetic torque T' at time k e (k) and stator flux ψ' s (k) and torque angle δ;

[0007] According to the electromagnetic torque T' e (k) and stator flux ψ' s (k) The error values ​​of three sets of voltage vectors are obtained from the 2-D lookup table;

[0008] According to the three sets of voltage vectors, three sets of corresponding operating parameters are obtained, and the electromagnetic torque T at time k is recalculated. e (k) and stator flux ψ s (k);

[0009] Load the improved ESO observer to obtain the electromagnetic torque T at time k+2 e (k+2), stator flux ψ s (k+2), predict the torque angle δ(k+2) at time k+2;

[0010] Reconstruct the optimal cost function, the cost function is used to predict the torque angle δ(k+2) at time k+2 based on the torque angle δ at time k;

[0011] The optimal value function is used for predictive control of AC permanent magnet synchronous motors.

[0012] Among them, the electromagnetic torque T' at time k e (k) and stator flux ψ' s (k) through the d and q axis components i d (k), i q (k) is obtained by:

[0013]

[0014] Among them, i α 、i β , α , β are the current and flux of the α and β axes of the two-phase stationary coordinate system, ψ s is the stator flux, ψ f is the rotor flux;

[0015] and:

[0016]

[0017] Where θ is the rotor angular position, u α ,u β They are the voltages of the α and β axes of the two-phase stationary coordinate system respectively.

[0018] Furthermore, the calculation method of the torque angle is:

[0019] The contents of the 2-D lookup table include the stator flux ψ' at time k s (k) Error with reference stator flux, electromagnetic torque T' e (k) Correspondence with reference electromagnetic torque error and space voltage vector Un.

[0020] The content of the 2-D lookup table is determined by dividing the space voltage vector sector table; the space voltage vector sector table includes 12 sectors, which are respectively marked as S1 to S12, Sn is one of the sectors, 0<n<13; the Sn sector corresponds to the space voltage vector Un; when the stator flux is in the Sn sector, the stator flux and electromagnetic torque error adjustment are achieved by synthesizing the effective voltage vector Un, Um and the zero voltage vector, where m=n+1, and m=1 when n=12.

[0021] Recalculate the electromagnetic torque T at time k e (k) and stator flux ψ s (k), the torque formula is used, according to the d and q axis components i d (k), i q (k) Calculation implementation: the calculation method is:

[0022]

[0023]

[0024]

[0025] Among them, ψ f is the permanent magnet rotor flux value, L d , L q is the d-axis inductance and q-axis inductance, L in the surface-mounted permanent magnet synchronous motor d =L q .

[0026] Furthermore, the improved ESO observer is used to realize the observation of current error and two-step delay compensation; before loading the improved ESO observer, the voltage relationship of the improved ESO observer is defined as:

[0027]

[0028] and:

[0029]

[0030] The method for predicting the torque angle δ(k+2) at time k+2 is:

[0031]

[0032] Furthermore, the optimal cost function does not include the weight coefficient and is expressed as:

[0033] g=[δ ref -δ(k+2)] 2 +I m ,

[0034] Among them, I m is the current limit value, and: Among them, I max is the maximum peak current, i s is the stator current.

[0035] In the present invention, the voltage vector sector diagram is divided into 12 sectors, alternative voltage vectors are added, and a new 2-D lookup table (LUT) is designed. Only according to the torque error and the stator flux error, two effective voltage vectors and a zero vector can be directly selected in one sampling cycle through the new switch table, wherein the two effective voltage vectors are not limited to adjacent voltage vectors. On the other hand, the present invention proposes a value function that eliminates the weight coefficient, and the value function only contains the torque angle, thereby eliminating the design of the weight coefficient in the value function and reducing the complexity of the value function calculation. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is a step diagram of a model predictive control method without weight coefficients provided in an embodiment of the present invention;

[0037] Figure 2 is a block diagram of a non-weighted MPTC control according to an embodiment of the present invention;

[0038] Figure 3 is a spatial voltage vector sector division diagram provided according to an embodiment of the present invention;

[0039] Figure 4 This is a schematic diagram of the simulation results of traditional MPTC;

[0040] Figure 5 It is a schematic diagram of the effect of the model predictive control simulation results provided according to an embodiment of the present invention. DETAILED DESCRIPTION

[0041] The present invention provides an MPTC strategy without weight coefficient for AC permanent magnet synchronous motor. In order to quickly screen voltage vectors, reduce the amount of calculation, and increase the concept of alternative voltage vectors, the voltage vector sector diagram is divided into 12 sectors; on this basis, a new 2-D lookup table (LUT) is designed, which can be used to directly select two effective voltage vectors and a zero vector to output the corresponding motor operating state according to the torque error and the stator flux error in one cycle, and the two effective voltage vectors are not limited to adjacent voltage vectors; the present invention also proposes a prediction model for eliminating weight coefficients, in which the value function only contains the torque angle, thereby eliminating the design of the weight coefficient in the value function and reducing the complexity of the value function calculation. The specific implementation of the present invention is described in detail below in conjunction with the drawings of the specification.

[0042] Figure 1 A method for model predictive control without weight coefficients for an AC permanent magnet synchronous motor is provided, comprising:

[0043] Step S100: Collect the motor rotor operating parameters at time k to obtain the electromagnetic torque reference value and stator flux reference value The operating parameters include: electrical angular velocity ω, rotor position θ, three-phase motor current i a (k), i b (k), i c (k), DC bus voltage u dc (k), d, q axis component i d (k), i q (k), α, β axis component i α (k), i β (k);

[0044] For obtaining running parameters, Figure 2 As shown, the motor rotor electrical angular velocity ω, rotor position θ, and three-phase motor current i at time k are collected through the encoder. a (k),i b (k),i c (k) and DC bus voltage u dc (k), and use Clark transformation to solve the d and q axis components i d (k), i q (k), according to the d and q axis components i d (k), i q (k), using Park transform to get α, β axis components i α (k), i β (k).

[0045] On the other hand, the speed error Δω is adjusted by the PI regulator. e Calculate the electromagnetic torque reference value Obtaining stator flux through MTPA

[0046] Step S110: Obtaining the electromagnetic torque T' at time k e (k) and stator flux ψ' s (k) and torque angle δ;

[0047] The electromagnetic torque T' at time k e (k) and stator flux ψ' s (k) through the d and q axis components i d (k), i q (k) is obtained by:

[0048]

[0049]

[0050] Among them, i α 、i β , α , β are the current and flux of the α and β axes of the two-phase stationary coordinate system, ψ s is the stator flux, ψ f is the rotor flux;

[0051] and:

[0052]

[0053]

[0054]

[0055] Where θ is the rotor angular position, u α ,u β They are the voltages of the α and β axes of the two-phase stationary coordinate system respectively.

[0056] The calculation method of the torque angle is:

[0057] Step S120: According to the electromagnetic torque T' e (k) and stator flux ψ' s (k) The error values ​​of three sets of voltage vectors are obtained from the 2-D lookup table;

[0058] The content of the 2-D lookup table in this step includes the stator flux ψ' at time k s (k) Error dψ with reference stator flux s , electromagnetic torque T' e (k) and reference electromagnetic torque error dT e, the corresponding relationship between the space voltage vector Un.

[0059] In the present invention, a new space voltage vector sector division diagram is established according to the state variables of the control system in the current sampling period, namely, the stator flux, electromagnetic torque, torque angle and rotor position, and then the direction in which the stator flux and electromagnetic torque need to change is obtained according to the electromagnetic torque and stator flux error value, and a 2-D lookup table (LUT) is determined accordingly, as shown in the following table:

[0060]

[0061] In the table, U1 to U6 are non-zero voltage vectors.

[0062] Through the 2-D lookup table (LUT) provided by the present invention, only according to the torque error and the stator flux error, two effective voltage vectors and one zero vector can be directly selected in the table in one sampling cycle, wherein the two effective voltage vectors are not limited to adjacent voltage vectors. On this basis, only three voltage vectors (two basic vectors and one zero vector) need to be substituted into the cost function for traversal optimization calculation, which greatly reduces the subsequent calculation amount, and these three vectors are determined by the torque and flux errors, so they can be used for subsequent analysis of the pulsation level of the torque and flux.

[0063] The space voltage vector sector division diagram established in the present invention is as follows: Figure 3 As shown, in order to quickly screen the voltage vector and reduce the amount of calculation, alternative voltage vectors are added, and the voltage vector sector diagram is divided into 12 sectors, the sectors are marked as S1 to S12, Sn is one of the sectors, 0<n<13; the Sn sector corresponds to the space voltage vector Un; when the stator flux is in the Sn sector, the effective voltage vector Un, Um (where m=n+1, m=1 when n=12) is synthesized with the zero voltage vector to achieve stator flux and electromagnetic torque error adjustment.

[0064] Assume that the stator flux ψ s In such Figure 3 The estimated stator flux and electromagnetic torque are compared with the reference stator flux and electromagnetic torque obtained by MPTA and PI controller to obtain two error values, defined as dψ s and dT e, when the error is greater than 0, it is defined as (+), otherwise it is (-). For the stator flux in sector S1, if the torque and flux need to be increased, two effective voltage vectors U2 and U3 and a zero voltage vector (U0|U7) are usually selected for synthesis. However, due to the limited voltage vectors available in each sector, the electromagnetic torque and flux pulsation are large. Therefore, it is necessary to redesign a new spatial voltage vector sector division diagram and divide it into 12 sectors. Assuming that the stator flux is in sector S1, if the torque and flux need to be increased, the two effective voltage vectors U1 and U2 can be used to act on the lower half of the S1 sector (i.e., the optimized S1), and the two effective voltage vectors U2 and U3 can be used to act on the upper half of the S1 sector (i.e., the optimized S2). Therefore, the number of alternative voltage vectors for each sector is increased. Multiple voltage vector synthesis methods can be added without involving the inverter switching frequency in the cost function. Furthermore, in order to reduce the computational burden, only the zero vector (U0) is selected for synthesis.

[0065] Step S121: According to the three sets of voltage vectors obtained in step S120, three sets of corresponding operating parameters are obtained, and the electromagnetic torque T at time k is recalculated by the three sets of operating parameters. e (k) and stator flux ψ s (k);

[0066] Recalculate the electromagnetic torque T at time k e (k) and stator flux ψ s (k) According to the d and q axis components i d (k), i q (k) is calculated using the torque formula, and the calculation method is:

[0067]

[0068]

[0069]

[0070] Among them, ψ f is the permanent magnet rotor flux value, L d , L q is the d-axis inductance and q-axis inductance, L in the surface-mounted permanent magnet synchronous motor d =L q .

[0071] Step S131: Load the improved ESO observer to obtain the electromagnetic torque T at time k+2 e (k+2), stator flux ψ s (k+2);

[0072] When parameter mismatch is considered, an improved ESO observer is designed to observe and compensate for the current error caused by external parameter disturbances in real time. At the same time, considering the existence of computer instruction cycles, a two-step delay compensation is performed.

[0073] Before loading the improved ESO observer, the voltage relationship of the improved ESO observer is defined as:

[0074]

[0075] and:

[0076]

[0077] On this basis, the prediction of the torque angle δ(k+2) at time k+2 is realized, that is:

[0078]

[0079] Step S140: reconstructing an optimal cost function, wherein the cost function is used to predict the torque angle δ at time k+2 according to the torque angle δ at time k;

[0080] The newly constructed value function in this step only contains the torque angle, but does not include the weight coefficient, which saves the complicated setting process of the weight coefficient and is expressed as:

[0081] g=[δ ref -δ(k+2)] 2 +I m (14)

[0082] Among them, I m is the current limit value, and:

[0083] Among them, I max is the maximum peak current, i s is the stator current.

[0084] Compared with the traditional single-vector MPTC, the strategy of eliminating weight coefficients proposed in this step expands the range of selectable voltage vectors and reduces current harmonics as well as torque and flux pulsation. The optimal value function finally reconstructed is used for predictive control of AC permanent magnet synchronous motor. The overall control process is as follows: Figure 2 shown.

[0085] The predictive control method provided by the present invention can effectively reduce torque and flux pulsation, as well as the harmonic components of current. The present invention provides a simulation experiment as follows: the motor operates stably under a certain working condition, and the steady-state operation is analyzed. The total harmonic distortion (THD) is used to measure the degree of current distortion. In addition, the pulsation root mean square error RMSE is used to measure the pulsation level of its torque and flux ripple. The calculation formula of the evaluation index is as follows:

[0086]

[0087]

[0088]

[0089] Where n is the number of samples in each sampling cycle.

[0090] The simulation results using traditional MPTC are as follows: Figure 4 As shown, the simulation results of the control method provided by the present invention are as follows Figure 5 The comparison of evaluation indicators is shown in the following table:

[0091] Traditional MPTC Improved MPTC <![CDATA[THD eq ]]> 21.67％ 12.84％ <![CDATA[T RMSE ]]> 110.03％ 10.75％ <![CDATA[ψ RMSE ]]> 7.97％ 4.24％

[0092] According to the test, the model predictive control method without weight coefficient provided by the present invention has significantly lower THD and RMSE values ​​than the traditional MPTC, which proves that the control method proposed by the present invention can effectively reduce torque and flux pulsation, as well as the harmonic components of current. And because the estimation process only requires three voltage vectors, the estimation process does not involve the setting of weight coefficients, which greatly simplifies the calculation amount of the system.

[0093] The above disclosures are only several specific embodiments of the present invention; however, the present invention is not limited thereto, and any changes that can be conceived by those skilled in the art should fall within the protection scope of the present invention.

Claims

1. A model predictive control method for an AC permanent magnet synchronous motor without weight coefficients, characterized in that: The following steps are involved: Collect the motor rotor operating parameters at time k to obtain the electromagnetic torque reference value and stator flux reference value The operating parameters include: electrical angular velocity ω, rotor position θ, three-phase motor current i a (k), i b (k), i c (k), DC bus voltage u dc (k), d, q axis component i d (k), i q (k), α, β axis component i α (k), i β (k); Get the electromagnetic torque T' at time k e (k) and stator flux ψ' s (k) and torque angle δ; According to the electromagnetic torque T' e (k) and stator flux ψ' s (k) The error values ​​of three sets of voltage vectors are obtained from the 2-D lookup table; According to the three sets of voltage vectors, three sets of corresponding operating parameters are obtained, and the electromagnetic torque T at time k is recalculated by the three sets of operating parameters. e (k) and stator flux ψ s (k); Load the improved ESO observer to obtain the electromagnetic torque T at time k+2 e (k+2), stator flux ψ s (k+2), predict the torque angle δ(k+2) at time k+2; Reconstructing an optimal cost function, wherein the cost function is used to predict the torque angle δ(k+2) at time k+2 based on the torque angle δ at time k; The optimal value function is used for predictive control of an AC permanent magnet synchronous motor.

2. The model predictive control method according to claim 1, characterized in that: The electromagnetic torque T' at time k e (k) and stator flux ψ' s (k) through the d and q axis components i d (k), i q (k) is obtained by: Among them, i α 、i β , α , β are the current and flux of the α and β axes of the two-phase stationary coordinate system, ψ s is the stator flux, ψ f is the rotor flux; and: Where θ is the rotor angular position, u α ,u β They are the voltages of the α and β axes of the two-phase stationary coordinate system respectively. The calculation method of the torque angle is:

3. The model predictive control method according to claim 1, characterized in that: The content of the 2-D lookup table includes the stator flux ψ' at time k s (k) Error with reference stator flux, electromagnetic torque T' e (k) Correspondence with reference electromagnetic torque error and space voltage vector Un.

4. The model predictive control method according to claim 3, characterized in that: The content of the 2-D lookup table is determined by partitioning the space voltage vector sector table; The space voltage vector sector table includes 12 sectors, which are respectively marked as S1 to S12, Sn is one of the sectors, 0<n<13; the Sn sector corresponds to the space voltage vector Un; when the stator flux is in the Sn sector, the stator flux and electromagnetic torque error adjustment are achieved by synthesizing the effective voltage vectors Un, Um and the zero voltage vector, wherein m=n+1, and m=1 when n=12.

5. The model predictive control method according to claim 1, characterized in that: The recalculated electromagnetic torque T at time k e (k) and stator flux ψ s (k), the torque formula is used, according to the d and q axis components i d (k), i q (k) Calculation implementation: the calculation method is: Among them, ψ f is the permanent magnet rotor flux value, L d , L q is the d-axis inductance and q-axis inductance, L in the surface-mounted permanent magnet synchronous motor d =L q .

6. The model predictive control method according to claim 1, characterized in that: The improved ESO observer is used to realize current error observation and two-step delay compensation; Before loading the improved ESO observer, the voltage relationship of the improved ESO observer is defined as: and: The method for predicting the torque angle δ(k+2) at time k+2 is:

7. The model predictive control method according to claim 1, characterized in that: The optimal cost function does not include weight coefficients and is expressed as: g=[δ ref -δ(k+2)] 2 +I m , Among them, I m is the current limit value, and: Among them, I max is the maximum peak current, i s is the stator current.

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