Permanent magnet linear generator model prediction current control method, device and storage medium

Abstract

The present invention provides a model predictive current control method, device and storage medium for a permanent magnet linear generator, which relates to the field of direct drive wave power generation. The model predictive current control method for the permanent magnet linear generator includes: dividing 12 voltage vector sectors in the αβ coordinate system; solving the cost function J1 of the predictive current model based on 6 basic non-zero voltage vectors to obtain the target sector; dividing the voltage vectors in the target sector into N2 + 1 ones by using a positive integer N2; solving the cost function J2 of the predictive current model based on the N2 + 1 voltage vectors to obtain the sub-optimal voltage vector V N2best ; dividing V N2best into N3 + 1 voltage vectors by using a positive integer N3; solving the cost function J3 of the predictive current model based on the N3 + 1 voltage vectors to obtain the optimal voltage vector V N3best ; outputting V N3best to the switching tubes by using SVPWM. The problem that the current control effect of the permanent magnet linear generator affects the stability of the entire control system, resulting in poor stability of the entire system, is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of direct-drive wave power generation, and in particular to a model-predicted current control method, device and storage medium for a permanent magnet linear generator. Background Art

[0002] Wave energy has the advantages of high energy density, etc., and has received extensive attention and research from scholars at home and abroad. my country's wave energy resources are very rich, and the wave energy resources available for development and utilization are about 70 million to 170 million kW. Therefore, research on wave energy power generation has broad development prospects.

[0003] Normally, direct-drive wave power generation devices often use permanent magnet linear generators as energy converters to convert wave energy into electrical energy. However, the current control effect of the permanent magnet linear generator will affect the stability of the entire control system, resulting in poor stability of the entire system. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the shortcomings of the prior art, the present invention provides a permanent magnet linear generator model prediction current control method, device and storage medium, which solves the problem that direct-drive wave power generation devices often use permanent magnet linear generators as energy converters to convert wave energy into electrical energy, and the current control effect of the permanent magnet linear generator will affect the stability of the entire control system, resulting in poor stability of the entire system.

[0006] (II) Technical solution

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0008] On the one hand, a model predictive current control method for a permanent magnet linear generator is provided, the method comprising:

[0009] Divide the voltage vector into 12 sectors in the αβ coordinate system;

[0010] Based on the six basic non-zero voltage vectors, the cost function J1 of the predicted current model is solved to obtain the target sector;

[0011] The voltage vector in the target sector is divided into N2+1 by using a positive integer N2;

[0012] Based on N2+1 voltage vectors, solve the cost function J2 of the predicted current model to obtain the suboptimal voltage vector V N2best ;

[0013] Use positive integer N3 to convert V N2best Divided into N3+1 voltage vectors;

[0014] Based on N3+1 voltage vectors, solve the cost function J3 of the predicted current model to obtain the optimal voltage vector V N3best ;

[0015] Using SVPWM to N3best Output to the switch tube.

[0016] Preferably, the 12 voltage vector sectors are divided in the αβ coordinate system as follows:

[0017] In the αβ coordinate system, the angle of the α axis is defined as 0°; starting from the α axis, every 30° is divided into a sector in a counterclockwise direction, with a total of 12 sectors; each sector is defined as Sector I to Sector XII according to Roman numerals.

[0018] Preferably, the cost function J1 of the predicted current model is solved based on the six basic non-zero voltage vectors to obtain the target sector as follows:

[0019] In the αβ coordinate system, the voltage vector in the α-axis direction is V1; starting from the α-axis, a voltage vector is defined every 60° in the counterclockwise direction, which are defined as basic non-zero voltage vectors V1 to V6 in turn; the cost function J1 of the predicted current model is:

[0020]

[0021]

[0022]

[0023] in, and are the d-axis and q-axis current reference values ​​at the given time k+1; i d (k+1) and i q (k+1) is the predicted value of the d-axis and q-axis currents at time k+1 calculated by the model; T s is the discrete time, R s is the internal resistance of the motor winding, L d , L q are the motor d-axis and q-axis inductances, i d (k) and i q (k) are the actual values ​​of the d-axis and q-axis currents at time k; v is the motor rotor speed, τ is the motor pole pitch, and u di 、u qi are the voltages of the six basic voltage vectors on the d-axis and q-axis, ψ f It is the permanent magnetic flux.

[0024] Preferably, the use of a positive integer N2 to divide the voltage vector in the target sector into N2+1 is specifically:

[0025] The N2+1 voltage vectors in the target sector are expressed as:

[0026]

[0027] sti=0,1,…,N2

[0028] j=1,2,…,6

[0029] When j∈[1,5], k=j+1; when j=6, k=1

[0030] The values ​​of odd and even sectors are expressed as: 2j-1 and 2j, j = 1, 2...6; n1 and n2 can be expressed as:

[0031]

[0032] Preferably, based on N2+1 voltage vectors, the cost function J2 of the predicted current model is solved to obtain the suboptimal voltage vector V N2best Specifically:

[0033] Based on N2+1 voltage vectors, the cost function J2 of the predicted current model is:

[0034]

[0035]

[0036]

[0037] Among them, u d1 is the voltage vector V N2 Multiply by the d-axis component of n1, u d2 is the voltage vector V N2 Multiply by the d-axis component of n2, and similarly we can get u q1 and u q2 ; Find the voltage vector that minimizes J2, which is the suboptimal voltage vector V N2best .

[0038] Preferably, the positive integer N3 is used to set V N2best The voltage vectors divided into N3+1 are as follows:

[0039] V N2best Divided into N3+1 voltage vectors, expressed as:

[0040] V N3i =n 3i V N2best

[0041] =n 3in1V1+n 3i n2V2,i=0,1,…,N3

[0042] Where n 3i It can be expressed as:

[0043]

[0044] Preferably, based on N3+1 voltage vectors, the cost function J3 of the predicted current model is solved to obtain the optimal voltage vector V N3best Specifically:

[0045] Based on N3+1 voltage vectors, the cost function J3 of the predicted current model is:

[0046]

[0047]

[0048]

[0049] Find the voltage vector that minimizes J3, which is the optimal voltage vector V N3best .

[0050] Preferably, the method uses SVPWM to N3best The output to the switch tube is specifically:

[0051] Using SVPWM modulation, the optimal voltage vector V N3best It is output to the switch tube in the form of duty cycle to complete the control of the motor.

[0052] In another aspect, a device is provided, comprising:

[0053] one or more processors;

[0054] a memory for storing one or more programs,

[0055] When the one or more programs are executed by the one or more processors, the one or more processors execute the permanent magnet linear generator model predictive current control method.

[0056] On the other hand, a computer-readable storage medium storing a computer program is provided, and when the program is executed by a processor, the permanent magnet linear generator model predictive current control method is implemented.

[0057] (III) Beneficial effects

[0058] (1) The permanent magnet linear generator model predictive current control method, device and storage medium of the present invention use improved model predictive current control to complete current tracking control. In the entire control process, the model of permanent magnet linear generator is directly used to complete the calculation of the three-time cost function, and the Lagrange extrapolation method is used to delay the q-axis current reference value, which basically eliminates the phase lag disadvantage in PI regulation. Compared with the control strategy with PI regulator, the dynamic response of the current is improved.

[0059] (2) The model predictive current control method, device and storage medium of the permanent magnet linear generator of the present invention utilizes this control strategy to further optimize the phase angle and length of the output voltage vector. Compared with the traditional model predictive current control, this control strategy reduces the current tracking error and improves the stability of the entire wave power generation system.

[0060] (3) The permanent magnet linear generator model prediction current control method, device and storage medium of the present invention are universal and can solve the current tracking control problem of permanent magnet linear generators and permanent magnet linear motors. Therefore, they can be extended to other working occasions based on permanent magnet linear generators to realize current tracking control of permanent magnet linear generators. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a schematic diagram of the process of the present invention;

[0062] Figure 2 It is a schematic diagram of 12 sectors and 6 non-zero voltage vectors of the present invention;

[0063] Figure 3 A schematic structural diagram of a direct-drive wave power generation device applicable to an embodiment of the present invention;

[0064] Figure 4 This is a comparison diagram of the effects of the improved model predicted current control and the model predicted current control under N2=3, N3=3 of the present invention.

[0065] Among them, 1. buoy device; 2. wave; 3. connecting rod; 4. mover; 5. stator; 6. fixing device; 7. seabed. DETAILED DESCRIPTION

[0066] The following will be combined with the accompanying drawings of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0067] See also Figure 1As an embodiment of the present invention, a model prediction current control method for a permanent magnet linear generator is provided, the method comprising the following steps:

[0068] S1. Divide the voltage vector into 12 sectors in the αβ coordinate system

[0069] S2. Based on the six basic non-zero voltage vectors, solve the cost function J1 of the predicted current model to obtain the target sector

[0070] S3, using the positive integer N2 to divide the voltage vector in the target sector into N2+1

[0071] S4. Based on N2+1 voltage vectors, solve the cost function J2 of the predicted current model to obtain the suboptimal voltage vector V N2best

[0072] S5, use the positive integer N3 to V N2best Divided into N3+1 voltage vectors

[0073] S6. Based on N3+1 voltage vectors, solve the cost function J3 of the predicted current model to obtain the optimal voltage vector V N3best

[0074] S7, use SVPWM to V N3best Output to switch tube

[0075] Furthermore, in step S1, the specific process of dividing the 12 voltage vector sectors in the αβ coordinate system is as follows:

[0076] See also Figure 2 In the αβ coordinate system, the angle of the α axis is defined as 0°. Starting from the α axis, every 30° is divided into a sector in a counterclockwise direction, with a total of 12 sectors. Each sector is defined as Sector I to Sector XII in Roman numerals.

[0077] Furthermore, in step S2, the six non-zero voltage vectors, the cost function J1 of the predicted current model, and the specific method for obtaining the target sector are:

[0078] See also Figure 2 In the αβ coordinate system, the voltage vector in the α-axis direction is V1. Starting from the α-axis, a voltage vector is defined every 60° in a counterclockwise direction, and they are defined as basic voltage vectors V1 to V6.

[0079] In the dq coordinate system, the voltage equation of the permanent magnet linear generator is:

[0080]

[0081] Among them, e d 、eq are the electromotive force generated by the permanent magnet flux in the motor d-axis and q-axis windings respectively, R s is the internal resistance of the motor winding, L d , L q are the inductance of the d-axis and q-axis when the motor is not working, v is the running speed of the motor rotor, τ is the motor pole pitch, and i d 、i q They are the motor d-axis and q-axis winding currents, u d 、u q are the d-axis and q-axis winding terminal voltages respectively. d and e q satisfy:

[0082]

[0083] Among them, ψ f It is the permanent magnetic flux.

[0084] Combining equations (1) and (2), we have

[0085]

[0086] Using the first-order forward Euler discretization method, equation (3) can be written as:

[0087]

[0088] The cost function of the predicted current model can be written as:

[0089]

[0090] In the formula, there are

[0091]

[0092] in, The predicted value of the q-axis current at time k+1 is obtained by using the Lagrange extrapolation method. and are the reference values ​​of the q-axis current at time k-1 and k-2 respectively. Therefore, the cost function J1 of the prediction current model based on 6 non-zero voltage vectors can be written as:

[0093]

[0094]

[0095]

[0096] The cost values ​​corresponding to the six non-zero voltage vectors can be obtained by exhaustive method, and the voltage vector V that minimizes the cost function is selected. min and the next smallest voltage vector Vsubmin To determine the target sector. The target sector is the closest to V min and next to V submin sectors.

[0097] Furthermore, in step S3, the specific method of using the positive integer N2 to divide the voltage vector in the target sector into N2+1 is:

[0098] The N2+1 voltage vectors in the target sector are expressed as:

[0099]

[0100] sti=0,1,…,N2

[0101] j=1,2,…,6

[0102] When j∈[1,5], k=j+1; when j=6, k=1 (8)

[0103] The values ​​of odd and even sectors are expressed as: 2j-1 and 2j, j = 1, 2...6. n1 and n2 can be expressed as:

[0104]

[0105] Furthermore, in step S4, based on N2+1 voltage vectors, the cost function J2 of the predicted current model is solved to obtain the suboptimal voltage vector V N2best The specific method is:

[0106] Based on N2+1 voltage vectors, the cost function J2 of the predicted current model is:

[0107]

[0108]

[0109]

[0110] where u d1 is the voltage vector V N2 Multiply by the d-axis component of n1, u d2 is the voltage vector V N2 Multiply by the d-axis component of n2, and similarly we can get u q1 and u q2 . Find the voltage vector that minimizes J2, which is the suboptimal voltage vector V N2best .

[0111] Furthermore, in step S5, V is converted to N2best The specific method of dividing into N3+1 voltage vectors is:

[0112] V N2best Divided into N3+1 voltage vectors, expressed as:

[0113]

[0114] Where n 3i It can be expressed as:

[0115]

[0116] Furthermore, in step S6, based on N3+1 voltage vectors, the cost function J3 of the predicted current model is solved to obtain the optimal voltage vector V N3best The specific method is:

[0117] Based on N3+1 voltage vectors, the cost function J3 of the predicted current model is:

[0118]

[0119]

[0120]

[0121] Find the voltage vector that minimizes J3, which is the optimal voltage vector V N3best .

[0122] Furthermore, in step S7, SVPWM is used to adjust V N3best The specific method of outputting to the switch tube is:

[0123] Using SVPWM modulation, the optimal voltage vector V N3best The duty cycle is output to the switch tube to complete the motor control. Figure 1 shown.

[0124] See also Figure 4 , a comparison chart of the improved model predictive current control and the traditional model predictive current control under N2=3, N3=3 is given. Through comparative analysis, the improved model predictive current control strategy reduces the current tracking error. It should be pointed out that N2 and N3 can be used in any combination as needed in the application to achieve better control effect. Compared with the traditional model predictive current control, this control strategy reduces the current tracking error and improves the stability of the entire wave power generation system.

[0125] See also Figure 3As another embodiment of the present invention, a direct-drive wave power generation device is provided. The device is placed in the wave 2, and the permanent magnet linear motor is composed of a mover 4 and a stator 5. The permanent magnet linear motor is directly connected to the buoy device 1 via a connecting rod 3, and the bottom of the permanent magnet linear motor is directly connected to the seabed 7 via a fixing device 6. The current control of the permanent magnet linear generator converts wave energy into electrical energy through the control strategy mentioned in the present invention and flows to the DC bus side.

[0126] Another embodiment of the present invention provides a device, comprising:

[0127] one or more processors;

[0128] a memory for storing one or more programs,

[0129] When the one or more programs are executed by the one or more processors, the one or more processors execute the permanent magnet linear generator model predictive current control method.

[0130] Yet another embodiment of the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the permanent magnet linear generator model predictive current control method.

[0131] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

Claims

1. A model predictive current control method for a permanent magnet linear generator, characterized in that: The method comprises: Divide the voltage vector into 12 sectors in the αβ coordinate system; Based on the six basic non-zero voltage vectors, the cost function J1 of the predicted current model is solved to obtain the target sector; The voltage vector in the target sector is divided into N2+1 by using a positive integer N2; Based on N2+1 voltage vectors, solve the cost function J2 of the predicted current model to obtain the suboptimal voltage vector V N2best ; Use positive integer N3 to convert V N2best Divided into N3+1 voltage vectors; Based on N3+1 voltage vectors, solve the cost function J3 of the predicted current model to obtain the optimal voltage vector V N3best ; Using SVPWM to N3best Output to the switch tube; Based on the six basic non-zero voltage vectors, the cost function J1 of the predicted current model is solved to obtain the target sector: In the αβ coordinate system, the voltage vector in the α-axis direction is V1; starting from the α-axis, a voltage vector is defined every 60° in the counterclockwise direction, which are defined as basic non-zero voltage vectors V1 to V6 in turn; the cost function J1 of the predicted current model is: in, and are the d-axis and q-axis current reference values ​​at the given time k+1; i d (k+1) and i q (k+1) is the predicted value of the d-axis and q-axis currents at time k+1 calculated by the model; T s is the discrete time, R s is the internal resistance of the motor winding, L d , L q are the motor d-axis and q-axis inductances, i d (k) and i q (k) are the actual values ​​of the d-axis and q-axis currents at time k; v is the motor rotor speed, τ is the motor pole pitch, and u di 、u qi are the voltages of the six basic voltage vectors on the d-axis and q-axis, ψ f is the permanent magnetic flux linkage; Based on N2+1 voltage vectors, solve the cost function J2 of the predicted current model to obtain the suboptimal voltage vector V N2best Specifically: Based on N2+1 voltage vectors, the cost function J2 of the predicted current model is: Among them, u d1 is the voltage vector V N2 Multiply by the d-axis component of n1, u d2 is the voltage vector V N2 Multiply by the d-axis component of n2, and similarly we can get u q1 and u q2 ; Find the voltage vector that minimizes J2, which is the suboptimal voltage vector V N2best ; Based on N3+1 voltage vectors, the cost function J3 of the predicted current model is solved to obtain the optimal voltage vector V N3best Specifically: Based on N3+1 voltage vectors, the cost function J3 of the predicted current model is: Find the voltage vector that minimizes J3, which is the optimal voltage vector V N3best .

2. A permanent magnet linear generator model prediction current control method according to claim 1, characterized in that: The 12 voltage vector sectors are divided in the αβ coordinate system as follows: In the αβ coordinate system, the angle of the α axis is defined as 0°; starting from the α axis, every 30° is divided into a sector in a counterclockwise direction, with a total of 12 sectors; each sector is defined as Sector I to Sector XII according to Roman numerals.

3. A permanent magnet linear generator model prediction current control method according to claim 1, characterized in that: The method of using a positive integer N2 to divide the voltage vector in the target sector into N2+1 is as follows: The N2+1 voltage vectors in the target sector are expressed as: sti=0,1,…,N2 j＝1,2,…,6 When j∈[1,5], k=j+1; when j=6, k=1 The values ​​of odd and even sectors are expressed as: 2j-1 and 2j, j = 1, 2...6; n1 and n2 are expressed as:

4. A permanent magnet linear generator model prediction current control method according to claim 1, characterized in that: The positive integer N3 is used to set V N2best The voltage vectors divided into N3+1 are as follows: V N2best Divided into N3+1 voltage vectors, expressed as: V N3i =n 3i V N2best =n 3i n1V1+n 3i n2V2,i=0,1,…,N3 Where n 3i It is expressed as:

5. A permanent magnet linear generator model prediction current control method according to claim 1, characterized in that: The SVPWM is used to N3best The output to the switch tube is specifically: Using SVPWM modulation, the optimal voltage vector V N3best It is output to the switch tube in the form of duty cycle to complete the control of the motor.

6. A device, characterized in that: The device comprises: one or more processors; a memory for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors execute the permanent magnet linear generator model predictive current control method as described in any one of claims 1-5.

7. A computer-readable storage medium storing a computer program, characterized in that: When the program is executed by a processor, the permanent magnet linear generator model predictive current control method as described in any one of claims 1 to 5 is implemented.

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