Memory motor model predictive current control method considering mode switching

Abstract

The application discloses a memory motor model predictive current control method considering mode switching and relates to the technical field of memory motor control. The application comprises the following steps: collecting information such as inverter bus voltage, memory motor rotor position, rotating speed and winding current; calculating winding current dq-axis components; calculating current q-axis current reference value and giving d-axis current reference value; judging system running state; updating current prediction model parameters according to magnetization state; applying dynamic control or steady-state control according to system running state; and obtaining inverter bridge arm switch tube control signals. The method applies corresponding control algorithms according to system running state, improves system steady-state performance and guarantees fast dynamic response speed. In addition, the problem of large parameter variation range of the memory motor under different magnetization states is considered, and the shortcomings of poor steady-state performance, unfixed switching frequency and dependence on accurate system parameters of the traditional model predictive current control are overcome.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of memory motor control, in particular to a memory motor model predictive current control method considering mode switching. BACKGROUND

[0002] Memory motor has controllable permanent magnet flux characteristics, which is expected to solve the defects of narrow constant power range and high efficiency interval of traditional permanent magnet synchronous motor, so it has attracted widespread attention of many scholars at home and abroad. The magnetization characteristics of memory motor benefit from the application of low coercivity permanent magnet such as aluminum-nickel-cobalt (AlNiCo), which can change the magnetization state of permanent magnet and thus change the air gap flux by applying short-time pulse type magnetizing current, with little excitation loss. The existing technology uses fuzzy PI controller, linear active disturbance rejection control and other methods to realize the control of memory motor, which effectively improves the control effect, but the above linear controller has limited bandwidth and parameter tuning problem, which is difficult to meet the wide speed regulation operation demand of memory motor.

[0003] Model predictive control originated from industrial process control, has the advantages of intuitive control idea, fast dynamic response and easy realization of multi-objective constraint, and is popularized to the field of motor drive. The traditional model predictive control selects one voltage vector in each control period, which can effectively improve the response speed of electromagnetic torque, but also brings inherent problems such as poor steady-state performance and fixed inverter switching frequency. SUMMARY

[0004] The purpose of the present application is to provide a memory motor model predictive current control method considering mode switching for memory motor drive, which is used to improve the steady-state performance of traditional model predictive control.

[0005] To achieve the above purpose, the present application provides the following technical scheme: a memory motor model predictive current control method considering mode switching, comprising the following steps:

[0006] Collecting inverter bus voltage, memory motor rotor position, speed and winding current data;

[0007] Establishing memory motor dq coordinate system, taking the direction of memory motor rotor magnetic field as d-axis and the direction perpendicular to the rotor magnetic field as q-axis, and calculating the dq-axis components of stator winding current according to the collected stator winding current data;

[0008] Calculating the error between the reference speed and the actual speed, and calculating the q-axis current reference value through the speed PI controller, and giving the d-axis current reference value according to the reference speed and using the magnetization state controller;

[0009] According to the memory motor dynamic mathematical model, a reference voltage vector is calculated, and according to the memory motor steady-state mathematical model, a steady-state reference voltage vector is calculated, the distance between the reference voltage vector and the steady-state reference voltage vector is calculated, and then it is judged whether the system is in a steady state or a dynamic state;

[0010] According to the magnetization state, the current prediction model parameters are updated;

[0011] According to the judgment of the system running state, steady-state control or dynamic control is implemented;

[0012] The inverter bridge arm switch control signal is obtained and applied to the inverter switch, thereby improving the steady-state performance and dynamic performance.

[0013] Further, the q-axis current reference value is calculated, which specifically includes the following steps:

[0014] The error between the reference speed and the actual speed is calculated:

[0015] Δn=n ref -n(1)

[0016] In the formula, n ref is the reference speed, and n is the actual speed;

[0017] The q-axis current reference value is calculated by a PI controller:

[0018]

[0019] In the formula, is the q-axis current reference value, K p is the proportional coefficient, and K i is the integral coefficient.

[0020] Further, the d-axis current reference value is given, which specifically includes the following steps:

[0021] According to the reference speed n ref , the reference magnetization state MS ref is given according to the speed interval, specifically:

[0022]

[0023] In the formula, n Δ is the speed threshold, which can be obtained by finite element or experiment;

[0024] According to the current magnetization state MS and the reference magnetization state MS ref , the d-axis current reference value is determined, specifically,

[0025]

[0026] In the formula, is the d-axis current reference value, i dp1 (t) represents a trapezoidal pulse wave, the amplitude of which can be determined by finite element or experiment. dp2 (t) represents a trapezoidal pulse wave, the amplitude of which can be determined by finite element or experiment.

[0027] Further, the reference voltage vector and the stable reference voltage vector and the distance therebetween are calculated, and it is judged whether the system is in a steady state or a dynamic state, which specifically includes the following steps:

[0028] According to the zero-error principle, the reference voltage vector is calculated, and the prediction model of the memory motor in the dq coordinate system can be expressed as:

[0029]

[0030] In the formula, i d and i q are the dq-axis stator currents, u d and u q are the dq-axis voltages output by the inverter, "k" represents the current time value, "k+1" represents the next time value, L d (MS) and L q (MS) are the dq-axis inductances, R is the winding resistance, ψ PM (MS) is the permanent magnet flux linkage, ω e is the electrical angular velocity of the memory motor, T s is the sampling period, and the zero-error control is to be realized, i.e. and The reference voltage vector needs to satisfy:

[0031]

[0032] In the formula, u ref , and are the reference voltage vector and its dq-axis components, respectively;

[0033] In the dq coordinate system, the steady-state mathematical model of the memory motor can be expressed as:

[0034]

[0035] The reference voltage vector u s under the steady-state condition is:

[0036]

[0037] In the formula, and are the dq-axis components of the reference voltage vector under the steady-state condition, respectively;

[0038] The method for calculating the distance between the reference voltage vector and the reference voltage vector under steady state condition is:

[0039] d = ||u ref -u s ||2 (9)

[0040] In the formula, d is the distance between the vectors, and the system operating state can be determined according to the following formula:

[0041]

[0042] In the formula, flag is a state flag bit, and the values of "0" and "1" respectively represent that the system is in steady state and dynamic state, d h is a threshold value.

[0043] Further, the specific way of updating the current prediction model parameters is: obtaining the cross-axis inductance L d (MS) and L q (MS), permanent magnet flux ψ PM (MS) and other parameters corresponding to the current magnetization state by querying the parameter storage table, and then updating the current prediction model parameters. The parameter storage table can be obtained by experiment or finite element method, and contains the cross-axis inductance L d (MS) and L q (MS) and permanent magnet flux ψ PM (MS) under different magnetization states of the memory motor.

[0044] Further, the steady state control is to synthesize the reference voltage vector by using the SVPWM modulation algorithm.

[0045] Further, the dynamic control method is as follows:

[0046] (1) synthesizing the reference voltage vector by using the SVPWM modulation algorithm

[0047] (2) calculating the reference voltage vector angle and determining the sector in which it is located;

[0048] (3) selecting the optimal voltage vector from the reference voltage vector sector in (2).

[0049] Further, the method for calculating the reference voltage vector angle and determining the sector is as follows:

[0050] calculating the voltage vector corresponding to the reference voltage vector under the αβ plane by using the inverse Park transformation That is:

[0051]

[0052] In the formula, and are the alpha and beta axis components, respectively, and e is the electrical rotor angle, and the reference voltage vector angle is further calculated by the arctangent function

[0053]

[0054] When belongs to [0, π / 3), the reference voltage vector is located in sector I; when belongs to [π / 3, 2π / 3), the reference voltage vector is located in sector II; when belongs to [2π / 3, π), the reference voltage vector is located in sector III; when belongs to [π, 4π / 3), the reference voltage vector is located in sector IV; when belongs to [4π / 3, 5π / 3), the reference voltage vector is located in sector V; when belongs to [5π / 3, 2π), the reference voltage vector is located in sector VI.

[0055] Further, the selection method of the optimal voltage vector is specifically:

[0056] The optimal voltage vector is selected by using the following formula:

[0057]

[0058] In the formula, i set is a voltage vector sequence determined by the sector in which the reference voltage vector is located, and specifically, if the reference voltage vector is located in sector I, then i set ={0, 1, 2}; if the reference voltage vector is located in sector II, then i set ={0, 2, 3}; if the reference voltage vector is located in sector III, then i set ={0, 3, 4}; if the reference voltage vector is located in sector IV, then i set ={0, 4, 5}; if the reference voltage vector is located in sector V, then i set ={0, 5, 6}; and if the reference voltage vector is located in sector VI, then i set ={0, 6, 1}.

[0059] Beneficial effects:

[0060] The application provides a memory motor model predictive current control method considering mode switching, corresponding control strategies are applied by judging the operation state of the system, so that the dynamic performance of the system is improved and the steady-state performance is improved, the application of SVPWM to synthesize the reference voltage vector under the steady-state working condition can obtain the beneficial effect of fixed switching frequency, in addition, the application considers the change of the memory motor parameters under different magnetization states of the memory motor, the system model parameters are updated in real time through the table lookup method, and the shortage that the traditional model predictive current control depends on accurate system parameters is overcome. BRIEF DESCRIPTION OF DRAWINGS

[0061] Figure 1 It is a control block diagram of the application;

[0062] Figure 2 It is a magnetomotive current trapezoidal pulse wave schematic diagram of the application;

[0063] Figure 3 It is a stator current waveform of phase A of the application;

[0064] Figure 4 It is a dq-axis current waveform of the application;

[0065] Figure 5 It is an electromagnetic torque waveform of the application;

[0066] Figure 6 It is a motor speed waveform of the application;

[0067] Figure 7 It is a state judgment waveform of the application. DETAILED DESCRIPTION

[0068] Combined Figure 1 As shown in the figure, the application provides a memory motor model predictive current control method considering mode switching, comprising the following steps:

[0069] S1: collecting data such as inverter bus voltage, memory motor rotor position, memory motor speed, stator winding current and the like.

[0070] S2: establishing a memory motor dq coordinate system, taking the memory motor rotor magnetic field direction as the d-axis and the direction perpendicular to the rotor magnetic field direction as the q-axis, calculating the dq-axis components of the stator winding current according to the collected stator winding current data;

[0071] S3: calculating the error between the reference speed and the actual speed, and calculating the q-axis current reference value through the speed PI controller, and giving the d-axis current reference value according to the reference speed and using the magnetization state controller, in the embodiment, the magnetization state controller structure is as shown in the figure, in the figure, the speed threshold n Figure 2 ts ​The setting is 800 rpm, the intense magnetizing current, the three stages of keeping and restoring time setting is 10 ms, the demagnetizing current amplitude is-25.4A, and the magnetizing current amplitude is 32A.

[0072] S31: calculating the q-axis current reference value, specifically comprising the following steps:

[0073] The error between the reference speed and the actual speed is calculated:

[0074] Δn = n ref -n(1)

[0075] In the formula, n ref is the reference speed, and n is the actual speed;

[0076] The q-axis current reference value is calculated by a PI controller:

[0077]

[0078] In the formula, is the q-axis current reference value, K p is the proportional coefficient, and K i is the integral coefficient;

[0079] S32: giving the d-axis current reference value, specifically comprising the following steps:

[0080] According to the reference speed n ref , the reference magnetization state MS ref is given according to the speed interval, specifically:

[0081]

[0082] In the formula, n Δ is the speed threshold, which can be obtained by finite element or experiment;

[0083] According to the current magnetization state MS and the reference magnetization state MS ref , the d-axis current reference value is determined, specifically,

[0084]

[0085] In the formula, is the d-axis current reference value, i dp1 (t) and i dp2 (t) represent trapezoidal pulse waves, and the amplitude can be determined by finite element or experiment.

[0086] S4: calculating the reference voltage vector according to the dynamic mathematical model of the memory motor, calculating the steady-state reference voltage vector according to the steady-state mathematical model of the memory motor, calculating the distance between the reference voltage vector and the steady-state reference voltage vector, and then judging whether the system is in a steady state or a dynamic state, which specifically comprises the following steps:

[0087] S41: calculating the reference voltage vector according to the deadbeat principle, specifically, in the dq coordinate system, the prediction model of the memory motor can be expressed as:

[0088]

[0089] In the formula, i d and i q are the dq-axis stator currents, u d and u q are the dq-axis voltages output by the inverter, “k” represents the current time value, “k+1” represents the next time value, L d and L q are the dq-axis inductances, R is the winding resistance, ψ PM is the permanent magnet flux linkage, ω e is the electrical angular velocity of the memory motor, T s is the sampling period, and the deadbeat control is to be realized, that is, and The reference voltage vector needs to satisfy:

[0090]

[0091] In the formula, u ref , and are the reference voltage vector and its dq-axis components, respectively, and are the d-axis and q-axis current reference values, respectively.

[0092] S42: calculating the distance between the reference voltage vector in S41 and the reference voltage vector under the steady-state condition, and judging the system running state, specifically, in the dq coordinate system, the steady-state mathematical model of the memory motor can be expressed as:

[0093]

[0094] The reference voltage vector u s under the steady-state condition is:

[0095]

[0096] In the formula, and Let d and q be the components of the reference voltage vector under steady-state conditions, respectively; then the method for calculating the distance between the reference voltage vector and the reference voltage vector under steady-state conditions is as follows:

[0097] d = u ref -u s 2(9)

[0098] In the formula, d is the distance between vectors, and the system operating state can be determined according to the following formula:

[0099]

[0100] In the formula, flag is a state flag bit, with a value of "0" and "1" indicating that the system is in steady state and dynamic state, respectively. h As a threshold, in this embodiment, d h Set it to 40.

[0101] S5: Update the current prediction model parameters based on the magnetization state. Specifically, obtain the quadrature and direct axis inductance L corresponding to the current magnetization state by querying the parameter storage table. d (MS) and L q (MS), permanent magnet flux ψ PM Parameters such as (MS) are used to update the current prediction model parameters. The parameter storage table can be obtained experimentally or through finite element analysis and includes the direct and quadrature axis inductance L of the memory motor under different magnetization states. d (MS) and L q (MS) and permanent magnet flux ψ PM (MS), In this embodiment, the parameter storage table is shown in Table 1:

[0102] Table 1

[0103]

[0104] S6: Implement dynamic control or steady-state control based on the system operating state. Specifically, steady-state control involves synthesizing a reference voltage vector using the SVPWM modulation algorithm, while dynamic control also includes the following steps:

[0105] S61: Calculate the reference voltage vector angle and determine its sector. Specifically, use the inverse Park transform to calculate the voltage vector corresponding to the reference voltage vector in the αβ plane. Right now:

[0106]

[0107] In the formula, and These are the α-axis and β-axis components, respectively, θ e The electric angle of the motor rotor is then used to calculate the reference voltage vector angle using the arctangent function.

[0108]

[0109] When belongs to [0, π / 3), the reference voltage vector is located in sector I; when belongs to [π / 3, 2π / 3), the reference voltage vector is located in sector II; when belongs to [2π / 3, π), the reference voltage vector is located in sector III; when belongs to [π, 4π / 3), the reference voltage vector is located in sector IV; when belongs to [4π / 3, 5π / 3), the reference voltage vector is located in sector V; when belongs to [5π / 3, 2π), the reference voltage vector is located in sector VI.

[0110] S62: selecting the optimal voltage vector from the reference voltage vector sector described in S61, specifically, selecting the optimal voltage vector by using the following formula:

[0111]

[0112] In the formula, i set is a voltage vector sequence, determined by the sector where the reference voltage vector is located, specifically, if the reference voltage vector is located in sector I, then i set ={0, 1, 2}; if the reference voltage vector is located in sector II, then i set ={0, 2, 3}; if the reference voltage vector is located in sector III, then i set ={0, 3, 4}; if the reference voltage vector is located in sector IV, then i set ={0, 4, 5}; if the reference voltage vector is located in sector V, then i set ={0, 5, 6}; if the reference voltage vector is located in sector VI, then i set ={0, 6, 1}.

[0113] S7: obtaining the inverter bridge arm switch control signal, applied to the inverter switch, thereby improving the steady-state performance and dynamic performance.

[0114] The simulation conditions of the embodiment of the application are: the load torque is given as 3N·m, the reference speed is initially given as 600rpm, and is stepped to 1000rpm at 0.2s, and the sampling frequency is 10kHz. The simulation result is shown in Figures 3-7 It can be seen that the method provided by the application can accurately judge the dynamic and steady-state conditions of the system, dynamic control can be applied when starting and varying the reference speed, the current and torque pulsation are low under the steady-state condition, and the system responds rapidly under the dynamic condition.

[0115] The above-described embodiments of the application are merely descriptive of its

[0116] For purposes of the USPTO extra-statutory invention, any element in the claim that follows the phrase of “a / an” is defined as the preamble recited before the element and following the phrase of “a / an.” The USPTO extra-statutory invention requires that the claim be in independent form and not dependent upon any other claim. Thus, under the USPTO extra-statutory invention, a preamble recited before the claim is not to be used to limit the claim. Structure of the application

[0117] While embodiments of the application have been shown and described, it is to be understood that various additional modifications and substitutions can be undertaken by one of ordinary skill in the art without departing from the spirit and scope of the application. The scope of the application is not to be understood as being limited to the particular embodiments described and it is specifically intended to cover by the claims any and all modifications, substitutions and equivalents falling within the spirit and scope of the present application.

[0118] In the description of the specification, reference to "one embodiment", "an example", "a specific example" or the like means that a particular feature, structure, material or characteristic is included in at least one embodiment or example of the disclosure. The appearances of the phrases of "in one embodiment", "in an example", "in a specific example" or the like in various places in the specification are not necessarily referring to the same embodiment or example. Furthermore, the particular features, structures, materials or characteristics can be combined in any suitable manner in one or more embodiments or examples.

Claims

1. A memory motor model predictive current control method considering mode switching, characterized in that, It comprises the following steps: Collecting inverter bus voltage, memorizing motor rotor position, speed and winding current data; Establishing a memory motor dq Coordinate system, taking the memory motor rotor magnetic field direction as d Axis, perpendicular to the rotor magnetic field direction q Axis, according to the collected stator winding current data to calculate its dq Axis component; The error between the reference rotational speed and the actual rotational speed is calculated, and the error is calculated by a rotational speed PI controller q The shaft current reference value is given according to the reference rotational speed and by using a magnetization state controller d The shaft current reference value According to the dynamic mathematical model of the motor, the reference voltage vector is calculated, and the steady-state reference voltage vector is calculated according to the steady-state mathematical model of the motor. Then, the distance between the reference voltage vector and the steady-state reference voltage vector is calculated, and then the system running state is judged to be steady or dynamic; Updating the current prediction model parameters according to the magnetization state; According to the system running state judged, steady-state control or dynamic control is implemented; Obtaining inverter bridge arm switch control signal, applied to inverter switch, and then improving the steady-state performance and dynamic performance.

2. The memory motor model predictive current control method considering mode switching according to claim 1, wherein, Computing q The shaft current reference value, in particular comprising the steps of: Calculate the error between the reference speed and the actual speed: (1) In the formula, n ref is the reference rotational speed, n is the actual rotational speed; The PI controller calculates q Shaft current reference value: (2) In the formula, is q axis current reference value, K p is a proportional coefficient, K i is an integral coefficient.

3. The memory motor model predictive current control method considering mode switching according to claim 2, wherein, Given d The shaft current reference value, in particular comprising the steps of: According to the reference rotational speed The reference magnetization state is given for the respective rotational speed interval In particular: (3) In the formula, n Δ is a rotation speed threshold value, which can be obtained by finite element or experiment. According to the current magnetization state MS With reference to the magnetization state , determine d The axis current reference value, specifically, (4) wherein is d the shaft current reference value, i dp1 ( t ) and i dp2 ( t ) represent trapezoidal pulse waves, the amplitudes of which can be determined by finite elements or experimentally.

4. The memory motor model predictive current control method considering mode switching according to claim 1, wherein, Calculate the reference voltage vector and the steady-state reference voltage vector and the distance between them, and judge the system running state to be steady or dynamic, which specifically includes the following steps: The reference voltage vector is calculated according to the principle of no error, and dq In the stationary reference frame, the predictive model of the memory motor can be expressed as: (5) wherein, i d and i q are respectively dq shaft stator current, u d and u q are respectively dq shaft voltage, k denotes the current time value, k +1 denotes the next time value, L d MS ) and L q MS ) are respectively dq shaft inductance, R is winding resistance, ψ PM MS is permanent magnet flux linkage, ω e is memory motor electrical angular velocity, T s is sampling period, to realize zero error control, namely = i d k +1) and = i q k +1), the reference voltage vector needs to satisfy:​​​​​ (6) wherein , and are the reference voltage vector and its dq axis component, respectively; In dq The steady-state mathematical model of the memory motor can be expressed as: (7) Reference voltage vector under steady state conditions u s That is: (8) wherein with are the axis components of the reference voltage vector under steady state conditions; respectively dq are the axis components of the reference voltage vector under steady state conditions; respectively The calculation method of the distance between the reference voltage vector and the reference voltage vector under the steady-state condition is: (9) wherein d is the distance between the vectors, the system operating state can be determined according to the following equation: (10) In the formula, flag is a state flag bit, whose value of "0" and "1" respectively indicates that the system is in steady state and dynamic state, d h is a threshold value.

5. The model predictive current control method of a memory motor considering mode switching according to claim 1, wherein, The specific way to update the current prediction model parameters is: Obtain the cross-axis and direct-axis inductance corresponding to the current magnetization state through the parameter storage table L d ( MS ) and L q ( MS ), permanent magnet flux linkage ( MS ), etc. Then update the current prediction model parameters. The parameter storage table can be obtained through experiments or finite element methods, and contains the cross-axis and direct-axis inductance of the memory motor under different magnetization states L d ( MS ) and L q ( MS ) and permanent magnet flux linkage ( MS ).

6. The model predictive current control method of a memory motor considering mode switching according to claim 1, wherein, The steady-state control method is to synthesize the reference voltage vector by using the space vector pulse width modulation algorithm (SVPWM).

7. The memory motor model predictive current control method considering mode switching according to claim 6, wherein, The dynamic control method is as follows: (1) Synthesize the reference voltage vector by using the SVPWM modulation algorithm (2) Calculate the angle of the reference voltage vector and determine the sector it is in; (3) Select the optimal voltage vector from the reference voltage vector sector in (2).

8. The memory motor model predictive current control method considering mode switching according to claim 7, wherein, The method of calculating the angle of the reference voltage vector and determining the sector it is in is as follows: The reference voltage vector is calculated using an inverse Park transformation αβ corresponding voltage vector under the plane i.e. (11) In the formula, With Respectively α Shaft and β Shaft component, θ e Is the motor rotor electrical angle, and then through the arctangent function to calculate the reference voltage vector angle : (12) When belongs to [0, π / 3), then the reference voltage vector is located in sector I; when belongs to [π / 3, 2π / 3), then the reference voltage vector is located in sector II; when belongs to [2π / 3, π), then the reference voltage vector is located in sector III; when belongs to [π, 4π / 3), then the reference voltage vector is located in sector IV; when belongs to [4π / 3, 5π / 3), then the reference voltage vector is located in sector V; when belongs to [5π / 3, 2π), then the reference voltage vector is located in sector VI.

9. The memory motor model predictive current control method considering mode switching according to claim 8, wherein, The selection method of the optimal voltage vector is as follows: The optimal voltage vector is selected by using the following formula: (13) In the formula, i set is a voltage vector sequence determined by the sector in which the reference voltage vector is located. Specifically, if the reference voltage vector is located in sector I, then i set = {0, 1, 2}. If the reference voltage vector is located in sector II, then i set = {0, 2, 3}; If the reference voltage vector is located in sector III, then i set = {0, 3, 4}; If the reference voltage vector is located in sector IV, then i set = {0, 4, 5}; if the reference voltage vector is located in sector V, then i set = {0, 5, 6}; If the reference voltage vector is located in sector VI, then i set = {0, 6, 1}.

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