CN111726046B - Asymmetric six-phase PMSM model prediction flux linkage control method considering duty ratio optimization - Google Patents

Asymmetric six-phase PMSM model prediction flux linkage control method considering duty ratio optimization Download PDF

Info

Publication number
CN111726046B
CN111726046B CN202010735818.3A CN202010735818A CN111726046B CN 111726046 B CN111726046 B CN 111726046B CN 202010735818 A CN202010735818 A CN 202010735818A CN 111726046 B CN111726046 B CN 111726046B
Authority
CN
China
Prior art keywords
vector
flux linkage
virtual voltage
voltage vector
components
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202010735818.3A
Other languages
Chinese (zh)
Other versions
CN111726046A (en
Inventor
於锋
刘兴
胡德林
葛天天
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Nantong University
Original Assignee
Nantong University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Nantong University filed Critical Nantong University
Priority to CN202010735818.3A priority Critical patent/CN111726046B/en
Publication of CN111726046A publication Critical patent/CN111726046A/en
Application granted granted Critical
Publication of CN111726046B publication Critical patent/CN111726046B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/14—Estimation or adaptation of machine parameters, e.g. flux, current or voltage
    • H02P21/141—Flux estimation
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/0003—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control
    • H02P21/0017—Model reference adaptation, e.g. MRAS or MRAC, useful for control or parameter estimation
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/12—Stator flux based control involving the use of rotor position or rotor speed sensors
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P27/00—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage
    • H02P27/04—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage
    • H02P27/06—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage using dc to ac converters or inverters
    • H02P27/08—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage using dc to ac converters or inverters with pulse width modulation

Landscapes

  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Control Of Ac Motors In General (AREA)
  • Inverter Devices (AREA)

Abstract

The invention discloses an asymmetric six-phase PMSM model prediction flux linkage control method considering duty ratio optimization. Firstly, constructing 12 active virtual voltage vectors and 1 zero virtual voltage vector by using a vector synthesis principle, reducing vectors to be evaluated and simultaneously realizing harmonic current suppression of a harmonic sub-plane; secondly, a cost function only related to stator flux linkage is constructed, and the problem of weight coefficient adjustment caused by traditional model prediction torque control is solved; thirdly, evaluating 13 virtual voltage vectors by using a cost function, and calculating corresponding cost function values; and finally, determining an optimal acting vector set, calculating the duty ratio of vectors in the set, and outputting corresponding PWM pulses to act on the inverter. The method of the invention not only can reduce the calculation burden of the system, inhibit the harmonic current of the harmonic sub-plane, improve the steady-state performance of the system and fix the switching frequency of the inverter, but also retains the advantage of fast dynamic response of the traditional model predictive control.

Description

Asymmetric six-phase PMSM model prediction flux linkage control method considering duty ratio optimization
Technical Field
The invention relates to an asymmetric six-phase PMSM model prediction flux linkage control method considering duty ratio optimization, and belongs to the field of motor driving and control.
Background
With the development of power electronics and high performance microprocessors, multi-phase motor drive technology is gradually entering the field of vision of people. Compared with a three-phase motor, the multi-phase motor has a plurality of remarkable advantages, such as high fault-tolerant capability, high power density, low torque ripple, high efficiency, lower single-phase power rating and the like, and is very suitable for high-power application scenes, such as electric vehicles, ship propulsion and the like. In many multi-phase motor topologies, the topology has become a research hotspot for researchers at home and abroad because the asymmetric six-phase PMSM eliminates 6 th order harmonic and torque ripple caused by the harmonic.
The model predictive control has the advantages of simple control idea, fast dynamic response, easy realization of multi-target control and the like, and is widely concerned by the students. However, model predictive control is currently mostly applied to three-phase motor drives. The model predictive control algorithm expanded to the asymmetric six-phase PMSM at the present stage still has the problems of poor steady-state performance, unfixed switching frequency, difficulty in weight coefficient adjustment and the like. Therefore, the research on the asymmetric six-phase PMSM model predictive control system which can improve the steady-state performance of the system, realize the fixation of the switching frequency of the inverter and does not need the adjustment of the weight coefficient has wide application prospect.
Disclosure of Invention
The purpose of the invention is as follows: aiming at the situation, the asymmetric six-phase PMSM model prediction flux linkage control method considering duty ratio optimization is provided, the steady-state performance of a system can be improved, the switching frequency of an inverter is fixed, and an additional weight coefficient is not required to be introduced.
The technical scheme is as follows: a duty ratio optimization-related asymmetric six-phase PMSM model prediction flux linkage control method comprises the following steps:
step 1: sampling main circuit DC bus voltage udcSpeed n, rotor angle theta, six-phase stator current iabcAnd iuvw；
Step 2: calculating stator current i under dq coordinate system by using coordinate transformation moduledAnd iq；
And step 3: obtaining given electromagnetic torque value through rotating speed controller
Figure BDA0002604889620000011
Meanwhile, a given flux linkage vector calculation module is used for calculating a given value of a stator flux linkage vector
Figure BDA0002604889620000012
And 4, step 4: calculating a stator flux linkage vector psi at the (k +1) th time by using a current and flux linkage prediction module for the 13 virtual voltage vectorss(k+1)；
And 5: obtaining 13 virtual voltage vectors vv through a value function evaluation module according to the stator flux linkage given value and the predicted valuejCorresponding value of value g (vv)j)(j＝0,…,12)；
Step 6: comparing the value of the value g (vv)j) Obtaining an optimal action vector set SVV by using an optimal control vector set determining moduleoptThen, the duty ratio calculation module is used for calculating the SVVoptDuty cycle d of medium vector0And dopt；
And 7: collecting SVV according to optimal action vectoroptAnd the duty ratio corresponding to the duty ratio is utilized to generate PWM signals by the PWM generating module so as to control the inverter to work.
Further, in step 3, the stator flux linkage vector set value
Figure BDA0002604889620000021
The calculation method specifically comprises the following steps:
for an asymmetric six-phase permanent magnet synchronous motor, a flux linkage equation and a torque equation are expressed as
Figure BDA0002604889620000022
Te＝3Pn(ψdiq-ψqid) (2)
In the formula, #dAnd psiqRespectively representing d-axis and q-axis components of the flux linkage; l isdAnd LqRespectively representing d-axis and q-axis components of the inductor; psifRepresents a permanent magnet flux linkage; t iseRepresents an electromagnetic torque; pnRepresenting the number of pole pairs;
binding idControl strategy of 0, and substituting formula (2) into formula (1) to eliminate current termThe torque is further expressed as an equation about the flux linkage, i.e.
Figure BDA0002604889620000023
Calculating the given values of the d-axis and q-axis components of the stator flux linkage according to the formula (4), namely
Figure BDA0002604889620000024
In the formula (I), the compound is shown in the specification,
Figure BDA0002604889620000025
and
Figure BDA0002604889620000026
respectively setting values of d-axis and q-axis components of the stator flux linkage; writing equation (4) in vector form, i.e. having
Figure BDA0002604889620000027
In the formula (I), the compound is shown in the specification,
Figure BDA0002604889620000028
representing a stator flux linkage vector given value.
Further, in step 4, the method for synthesizing the 13 virtual voltage vectors includes:
first, an asymmetric six-phase PMSM base voltage vector is defined: using octal numbers [ S ]a Sb Sc]-[Su Sv Sw]Encoding a base voltage vector, wherein S k1 represents that the switching tube of the upper bridge arm of the k phase is conducted, S k0 represents that the switching tubes of the k-phase lower bridge arm are conducted, and k is a, b, c, u, v or w; the basic voltage vector is denoted by v[SaSbSc]-[SuSvSw]；
Based on the definition of the basic voltage vector, the 13 virtual voltage vectors include 1 zero virtual voltage vector and 12An active virtual voltage vector; in particular, a zero virtual voltage vector vv0By v0-0And v7-7Synthesized, and the action time ratio of the two is 1: 1; active virtual voltage vector vv1By v6-5And v4-4Synthesized, and the acting time ratio of the two is 0.269: 0.731; active virtual voltage vector vv2By v4-0、v6-4And v7-6The three components are synthesized, and the acting time ratio of the three components is 0.2115:0.577: 0.2115; active virtual voltage vector vv3By v2-4And v6-6Synthesized, and the acting time ratio of the two is 0.269: 0.731; active virtual voltage vector vv4By v0-2、v2-6And v6-7The three components are synthesized, and the acting time ratio of the three components is 0.2115:0.577: 0.2115; active virtual voltage vector vv5By v3-6And v2-2Synthesized, and the acting time ratio of the two is 0.269: 0.731; active virtual voltage vector vv6By v2-0、v3-2And v7-3The three components are synthesized, and the acting time ratio of the three components is 0.2115:0.577: 0.2115; active virtual voltage vector vv7By v1-2And v3-3Synthesized, and the acting time ratio of the two is 0.269: 0.731; active virtual voltage vector vv8By v0-1、v1-3And v3-7The three components are synthesized, and the acting time ratio of the three components is 0.2115:0.577: 0.2115; active virtual voltage vector vv9By v5-3And v1-1Synthesized, and the acting time ratio of the two is 0.269: 0.731; active virtual voltage vector vv10By v1-0、v5-1And v7-5The three components are synthesized, and the acting time ratio of the three components is 0.2115:0.577: 0.2115; active virtual voltage vector vv11By v4-1And v5-5Synthesized, and the acting time ratio of the two is 0.269: 0.731; active virtual voltage vector vv12By v0-4、v4-5And v5-7The three components are synthesized, and the acting time ratio of the three components is 0.2115:0.577: 0.2115.
Further, in step 4, the stator flux linkage vector ψ at the (k +1) th time pointsThe calculation method of (k +1) is specifically as follows:
the voltage equation of the asymmetric six-phase PMSM is expressed as follows
Figure BDA0002604889620000031
In the formula, vdAnd vqRepresenting d-axis and q-axis components of the stator voltage, respectively; r represents the internal resistance of the winding; omegarIs the electrical angular velocity;
discretizing the formulas (6) and (1) by adopting a first-order Euler method to obtain a prediction model of current and flux linkage, namely
Figure BDA0002604889620000032
Figure BDA0002604889620000041
Wherein (k) represents the kth time, and (k +1) represents the (k +1) th time; the stator flux linkage vector psi at the (k +1) th times(k +1) is represented by
ψs(k+1)＝ψd(k+1)+jψq(k+1) (9)。
Further, in step 5, the cost function only includes flux linkage vector constraints, as shown in formula (10)
Figure BDA0002604889620000042
Further, in step 6, the optimal acting vector set SVVoptIncluding a zero virtual voltage vector and an optimal active virtual voltage vector, i.e.
SVVopt＝{vv0,vvopt} (11)
Wherein the optimal active virtual voltage vector vvoptTo minimize the active virtual voltage vector of the cost function (10), i.e.
g(vvopt)＝ming(vvj)，1≤j≤12 (12)
Further, in step 6, the duty ratio d0And doptRespectively representing virtual voltage zero vector vv0With an optimum active virtual voltage vector vvoptThe duty ratio of (1) is calculated by
Figure BDA0002604889620000043
Has the advantages that: (1) the model prediction control method provided by the invention utilizes flux linkage constraint to eliminate the weight coefficient of the balance torque component and the flux linkage component in the traditional model prediction torque control method;
(2) harmonic current is suppressed by utilizing a virtual voltage vector strategy, and a weighting coefficient for balancing fundamental wave components and harmonic wave components is further eliminated;
(3) the steady-state performance of the system is improved by a duty ratio optimization method;
(4) the switching frequency of the inverter is fixed by combining a virtual vector and a duty ratio optimization method;
(5) the superior dynamic performance of the traditional model predictive control algorithm is reserved.
Drawings
FIG. 1 is a block diagram of an asymmetric six-phase PMSM model predictive flux linkage control method of the present invention that accounts for duty cycle optimization;
fig. 2 is a spatial vector distribution of an asymmetric six-phase PMSM in an α β sub-plane obtained by a vector definition method provided in the present invention;
FIG. 3 is a spatial vector distribution of an asymmetric six-phase PMSM in an xy sub-plane, obtained according to a vector definition method provided by the present invention;
FIG. 4 is a diagram illustrating the spatial distribution of virtual voltage vectors in the α β sub-plane according to the present invention;
FIG. 5 is a simulation result of switching frequency obtained by implementing the present invention;
FIG. 6 is a simulation of stator current, harmonic current, speed and torque obtained by implementing the present invention under steady state conditions of a given speed of 300rpm and a load torque of 10 N.m;
FIG. 7 shows the simulation results of stator current, harmonic current, rotational speed and torque obtained by implementing the present invention under variable load conditions, wherein the load torque is suddenly changed from 10 N.m to 15 N.m at 0.2s, and the rotational speed is maintained at 300 r/min;
fig. 8 shows the simulation results of stator current, harmonic current, rotational speed and torque obtained by implementing the present invention under the condition of variable rotational speed, in this case, the rotational speed is set to 0.4s, and the rotational speed is suddenly changed from 300rpm to 500rpm, while the load is maintained at 15N · m.
Detailed Description
The invention is further explained below with reference to the drawings.
As shown in fig. 1, a method for controlling a flux linkage in a prediction model of an asymmetric six-phase PMSM model with consideration of duty ratio optimization includes the following steps:
step 1: sampling the DC bus voltage u of the main circuit 1dcSpeed n, rotor angle theta, six-phase stator current iabcAnd iuvw。
Step 2: calculating stator current i under dq coordinate system by using coordinate transformation module 2dAnd iq. Specifically, a vector space decoupling matrix T is first usedαβCalculating the fundamental wave sub-plane current iαAnd iβHarmonic sub-plane current ixAnd iyAs follows
Figure BDA0002604889620000051
In the formula io1And io2For the zero sequence sub-plane component, i for the double neutral point asymmetric six-phase PMSM according to the inventiono1And io2Are both 0. Then, the matrix T is transformed by using ParkdqA fundamental sub-plane current iαAnd iβTransforming the data into dq coordinate system, and calculating a direct-axis component idAnd the quadrature component iqAs follows
Figure BDA0002604889620000061
And step 3: obtaining given value of electromagnetic torque through rotating speed controller 3
Figure BDA0002604889620000062
Meanwhile, a given flux linkage vector given value is calculated by a given flux linkage vector calculation module 4
Figure BDA0002604889620000063
Specifically, first, a given rotation speed n is set*Calculating a given torque value by using a PI controller in a way of making difference with the actual rotating speed n
Figure BDA0002604889620000064
As follows
Figure BDA0002604889620000065
In the formula, kpAnd k isiProportional coefficient and integral coefficient, respectively, and it should be noted that, in order to prevent the over-current phenomenon of the system, the present invention sets the torque given amplitude limit to [ -30N · m,30N · m [ -30N · m [ ]]。
For an asymmetric six-phase permanent magnet synchronous motor, a flux linkage equation and a torque equation can be expressed as
Figure BDA0002604889620000066
Te＝3Pn(ψdiq-ψqid) (5)
In the formula, #dAnd psiqRespectively representing d-axis and q-axis components of the flux linkage; l isdAnd LqRespectively representing d-axis and q-axis components of the inductor; psifRepresents a permanent magnet flux linkage; t iseRepresents an electromagnetic torque; pnThe number of pole pairs is indicated.
Binding idThe torque may be further expressed as a square with respect to flux linkage by substituting equation (5) for equation (4) with a control strategy of 0 to eliminate the current termProcedure, i.e.
Figure BDA0002604889620000067
Torque set value obtained by combining with rotating speed controller
Figure BDA0002604889620000068
The given values of the d-axis and q-axis components of the stator flux linkage can be calculated according to the formula (6), namely
Figure BDA0002604889620000069
In the formula (I), the compound is shown in the specification,
Figure BDA00026048896200000610
and
Figure BDA00026048896200000611
and respectively setting values of d-axis components and q-axis components of the stator flux linkage. Writing equation (7) in vector form, i.e. having
Figure BDA00026048896200000612
In the formula (I), the compound is shown in the specification,
Figure BDA0002604889620000071
representing a stator flux linkage vector given value;
and 4, step 4: for the 13 virtual voltage vectors 5, the stator flux linkage vector psi at the (k +1) th time is calculated by the current and flux linkage prediction module 6s(k+1)。
The virtual voltage vector synthesis method specifically comprises the following steps: firstly, describing the definition method of asymmetric six-phase PMSM basic voltage vector, the invention adopts octal number [ S ]a Sb Sc]-[Su Sv Sw]Encoding a base voltage vector, wherein S k1 represents that the switching tube of the upper bridge arm of the k phase is conducted, S k0 represents kThe switching tubes of the lower bridge arm are conducted, k is a, b, c, u, v or w, and the basic voltage vector is expressed as v[SaSbSc]-[SuSvSw]. Such as v4-4The basic voltage vector generated when the upper arm of the a phase and the u phase is conducted and the lower arm of the other 4 phases is conducted is shown. The basic voltage vectors mapped to the fundamental sub-plane and the harmonic sub-plane are respectively shown in fig. 2 and fig. 3, and each plane contains 5 vectors, namely a large vector, a medium-small vector, a small vector and a zero vector according to the magnitude of the vector, and the magnitude is respectively 0.644udc，0.471udc，0.333udc，0.173udcAnd 0.
In order to suppress harmonic current, the invention constructs 13 virtual voltage vectors according to the idea of vector synthesis, wherein the virtual voltage vectors comprise 1 zero virtual voltage vector and 12 active virtual voltage vectors, and the aim of suppressing the voltage acting on a harmonic sub-plane to 0 is achieved, so that the harmonic current is suppressed. In particular, a zero virtual voltage vector vv0By v0-0And v7-7Synthesized, and the action time ratio of the two is 1: 1; active virtual voltage vector vv1By v6-5And v4-4Synthesized, and the acting time ratio of the two is 0.269: 0.731; active virtual voltage vector vv2By v4-0、v6-4And v7-6The three components are synthesized, and the acting time ratio of the three components is 0.2115:0.577: 0.2115; active virtual voltage vector vv3By v2-4And v6-6Synthesized, and the acting time ratio of the two is 0.269: 0.731; active virtual voltage vector vv4By v0-2、v2-6And v6-7The three components are synthesized, and the acting time ratio of the three components is 0.2115:0.577: 0.2115; active virtual voltage vector vv5By v3-6And v2-2Synthesized, and the acting time ratio of the two is 0.269: 0.731; active virtual voltage vector vv6By v2-0、v3-2And v7-3The three components are synthesized, and the acting time ratio of the three components is 0.2115:0.577: 0.2115; active virtual voltage vector vv7By v1-2And v3-3Synthesized, and the acting time ratio of the two is 0.269: 0.731; active virtual voltage vector vv8By v0-1、v1-3And v3-7The three components are synthesized, and the acting time ratio of the three components is 0.2115:0.577: 0.2115; active virtual voltage vector vv9By v5-3And v1-1Synthesized, and the acting time ratio of the two is 0.269: 0.731; active virtual voltage vector vv10By v1-0、v5-1And v7-5The three components are synthesized, and the acting time ratio of the three components is 0.2115:0.577: 0.2115; active virtual voltage vector vv11By v4-1And v5-5Synthesized, and the acting time ratio of the two is 0.269: 0.731; active virtual voltage vector vv12By v0-4、v4-5And v5-7The three components are synthesized, and the acting time ratio of the three components is 0.2115:0.577: 0.2115.
For a zero virtual voltage vector, the magnitudes in the α β and xy sub-planes are calculated as follows
Figure BDA0002604889620000081
For odd term virtual voltage vectors, in vv1For example, the amplitudes in the α β and xy sub-planes are calculated as follows
Figure BDA0002604889620000082
For even term virtual voltage vectors, in vv2For example, the amplitudes in the α β and xy sub-planes are calculated as follows
Figure BDA0002604889620000083
As can be seen from equations (9) - (11), the components of the 13 virtual vectors mapped into the xy-plane are all 0, so that a large harmonic current is not generated, and the suppression of the harmonic current is realized. The distribution of the 13 virtual vectors in the α β sub-plane is shown in fig. 4.
In addition, the voltage equation of the asymmetric six-phase PMSM is expressed as follows
Figure BDA0002604889620000084
In the formula, vdAnd vqRepresenting d-axis and q-axis components of the stator voltage, respectively; r represents the internal resistance of the winding; omegarIs the electrical angular velocity. Discretizing the equations (12) and (4) by using a first-order Euler method to obtain a prediction model of current and flux linkage, namely
Figure BDA0002604889620000085
Figure BDA0002604889620000086
In the formula, (k) represents the kth time, and (k +1) represents the (k +1) th time. The stator flux linkage vector psi at the (k +1) th times(k +1) may be represented as
ψs(k+1)＝ψd(k+1)+jψq(k+1) (15)
And 5: obtaining value function values g (vv) corresponding to 13 virtual voltage vectors through a value function evaluation module 7 according to the stator flux linkage given value and the predicted valuej) (j ═ 0, …, 12). The cost function contains only flux linkage vector constraints, as shown in equation (16).
Figure BDA0002604889620000091
Step 6: comparing the value of the value g (vv)j) Obtaining the optimal acting vector set SVV by utilizing the optimal control vector set determining module 8optThen SVV is calculated by means of a duty cycle calculation module 9optDuty cycle d of medium vector0And dopt. Optimal acting vector set SVVoptIncluding a zero virtual voltage vector and an optimal active virtual voltage vector, i.e.
SVVopt＝{vv0,vvopt} (17)
Wherein the optimal active virtual voltage vector vvoptTo minimize the active virtual voltage vector of the cost function (11), i.e.
g(vvopt)＝ming(vvj)，1≤j≤12 (18)
Further, duty ratio d0And doptRespectively representing the duty ratio of a virtual voltage zero vector and an optimal active virtual voltage vector, and the calculation method comprises the following steps
Figure BDA0002604889620000092
And 7: collecting SVV according to optimal action vectoroptAnd the duty ratio corresponding to the duty ratio, and the PWM generating module 10 is used for generating PWM signals to control the inverter to work.
Fig. 5 shows a waveform of switching frequency of the inverter controlled by model prediction flux linkage disclosed by the invention, wherein the switching frequency is stabilized at 10kHz, and the switching frequency is fixed.
Under the conditions that the load torque is 10 N.m and the rotating speed is given as 300rpm, the model prediction flux linkage control disclosed by the invention is implemented, the stator current, the harmonic current, the rotating speed and the electromagnetic torque waveform are shown in figure 6, and it can be seen that the sine degree of the stator current is high, the harmonic current is well restrained, the rotating speed is stabilized at the given value, the electromagnetic torque pulsation is small, and the system has good steady-state performance.
When the load torque is suddenly changed from 10 N.m to 15 N.m at 0.2s, the rotating speed is set to be kept at 300rpm, the model prediction flux linkage control disclosed by the invention is implemented, the stator current, the harmonic current, the rotating speed and the electromagnetic torque waveform are shown in figure 7, and it can be seen that the stator current still keeps high sine degree after the torque suddenly changes, the electromagnetic torque tracks quickly, the rotating speed quickly reaches 300rpm after the load suddenly changes, and the system has good dynamic performance.
When the rotation speed is set to be suddenly changed from 300rpm to 500rpm in 0.4s, the load torque is kept at 15 N.m, the model prediction flux linkage control disclosed by the invention is implemented, the stator current, the harmonic current, the rotation speed and the electromagnetic torque waveform are shown in figure 8, and it can be seen that the electromagnetic torque reaches 30 N.m after the rotation speed is set to be suddenly changed due to the output amplitude limit of the outer ring rotation speed controller, so that the rotation speed is increased in a linear trend. After the speed reached 500rpm, the electromagnetic torque dropped rapidly back to 15N · m and the system continued to operate under new steady state conditions.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.

Claims (6)

1. The asymmetric six-phase PMSM model prediction flux linkage control method considering duty ratio optimization is characterized by comprising the following steps of:
step 1: sampling the DC bus voltage u of the main circuit (1)dcSpeed n, rotor angle theta, six-phase stator current iabcAnd iuvw；
Step 2: calculating stator current i under dq coordinate system by using coordinate transformation module (2)dAnd iq；
And step 3: the given value of the electromagnetic torque is obtained through a rotating speed controller (3)
Figure FDA0003308781760000011
Meanwhile, a given flux linkage vector calculation module (4) is used for calculating a given value of a stator flux linkage vector
Figure FDA0003308781760000012
And 4, step 4: for the 13 virtual voltage vectors (5), a current and flux linkage prediction module (6) is used for calculating a stator flux linkage vector psi at the (k +1) th moments(k+1)；
And 5: obtaining 13 virtual voltage vectors vv through a value function evaluation module (7) according to the stator flux linkage given value and the predicted valuejCorresponding value of value g (vv)j)(j＝0,…,12)；
Step 6: comparing the value of the value g (vv)j) Using the optimumA control vector set determining module (8) obtains an optimal acting vector set SVVoptThen, SVV is calculated by a duty ratio calculation module (9)optDuty cycle d of medium vector0And dopt；
And 7: collecting SVV according to optimal action vectoroptAnd the duty ratio corresponding to the duty ratio, and a PWM signal is generated by using a PWM generating module (10) to control the inverter to work;
in step 4, the method for synthesizing the 13 virtual voltage vectors includes:
first, an asymmetric six-phase PMSM base voltage vector is defined: using octal numbers [ S ]a Sb Sc]-[Su Sv Sw]Encoding a base voltage vector, wherein Sk1 represents that the switching tube of the upper bridge arm of the k phase is conducted, Sk0 represents that the switching tubes of the k-phase lower bridge arm are conducted, and k is a, b, c, u, v or w; the basic voltage vector is denoted by v[SaSbSc]-[SuSvSw]；
Based on the definition of the base voltage vector, the 13 virtual voltage vectors include 1 zero virtual voltage vector and 12 active virtual voltage vectors; in particular, a zero virtual voltage vector vv0By v0-0And v7-7Synthesized, and the action time ratio of the two is 1: 1; active virtual voltage vector vv1By v6-5And v4-4Synthesized, and the acting time ratio of the two is 0.269: 0.731; active virtual voltage vector vv2By v4-0、v6-4And v7-6The three components are synthesized, and the acting time ratio of the three components is 0.2115:0.577: 0.2115; active virtual voltage vector vv3By v2-4And v6-6Synthesized, and the acting time ratio of the two is 0.269: 0.731; active virtual voltage vector vv4By v0-2、v2-6And v6-7The three components are synthesized, and the acting time ratio of the three components is 0.2115:0.577: 0.2115; active virtual voltage vector vv5By v3-6And v2-2Synthesized, and the acting time ratio of the two is 0.269: 0.731; active virtual voltage vector vv6By v2-0、v3-2And v7-3Synthesis ofThe ratio of the action time of the three is 0.2115:0.577: 0.2115; active virtual voltage vector vv7By v1-2And v3-3Synthesized, and the acting time ratio of the two is 0.269: 0.731; active virtual voltage vector vv8By v0-1、v1-3And v3-7The three components are synthesized, and the acting time ratio of the three components is 0.2115:0.577: 0.2115; active virtual voltage vector vv9By v5-3And v1-1Synthesized, and the acting time ratio of the two is 0.269: 0.731; active virtual voltage vector vv10By v1-0、v5-1And v7-5The three components are synthesized, and the acting time ratio of the three components is 0.2115:0.577: 0.2115; active virtual voltage vector vv11By v4-1And v5-5Synthesized, and the acting time ratio of the two is 0.269: 0.731; active virtual voltage vector vv12By v0-4、v4-5And v5-7The three components are synthesized, and the acting time ratio of the three components is 0.2115:0.577: 0.2115.
2. The method of claim 1, wherein in step 3, the stator flux linkage vector set point value is used as a prediction flux linkage control for an asymmetric six-phase PMSM model with duty cycle optimization taken into account
Figure FDA0003308781760000021
The calculation method specifically comprises the following steps:
for an asymmetric six-phase permanent magnet synchronous motor, a flux linkage equation and a torque equation are expressed as
Figure FDA0003308781760000022
Te＝3Pn(ψdiq-ψqid) (2)
In the formula, #dAnd psiqRespectively representing d-axis and q-axis components of the flux linkage; l isdAnd LqRespectively representing d-axis and q-axis components of the inductor; psifRepresents a permanent magnet flux linkage; t iseRepresents an electromagnetic torque; pnRepresenting the number of pole pairs;
binding id0 control strategy and substituting equation (2) for equation (1) to eliminate the current term, further expressing torque as an equation for flux linkage, i.e.
Figure FDA0003308781760000023
Calculating the given values of the d-axis and q-axis components of the stator flux linkage according to the formula (4), namely
Figure FDA0003308781760000024
In the formula (I), the compound is shown in the specification,
Figure FDA0003308781760000025
and
Figure FDA0003308781760000026
respectively setting values of d-axis and q-axis components of the stator flux linkage; writing equation (4) in vector form, i.e. having
Figure FDA0003308781760000027
In the formula (I), the compound is shown in the specification,
Figure FDA0003308781760000028
representing a stator flux linkage vector given value.
3. The method of claim 2, wherein in step 4, the stator flux linkage vector ψ at the (k +1) th time is calculated by the asymmetric six-phase PMSM model predictive flux linkage control method taking duty cycle optimization into accountsThe calculation method of (k +1) is specifically as follows:
the voltage equation of the asymmetric six-phase PMSM is expressed as follows
Figure FDA0003308781760000031
In the formula, vdAnd vqRepresenting d-axis and q-axis components of the stator voltage, respectively; r represents the internal resistance of the winding; omegarIs the electrical angular velocity;
discretizing the formulas (6) and (1) by adopting a first-order Euler method to obtain a prediction model of current and flux linkage, namely
Figure FDA0003308781760000032
Figure FDA0003308781760000033
Wherein (k) represents the kth time, and (k +1) represents the (k +1) th time; the stator flux linkage vector psi at the (k +1) th times(k +1) is represented by
ψs(k+1)＝ψd(k+1)+jψq(k+1) (9)。
4. The method for controlling the flux linkage of the asymmetric six-phase PMSM model in consideration of duty cycle optimization according to claim 1, wherein in step 5, the cost function only contains flux linkage vector constraints as shown in formula (10)
Figure FDA0003308781760000034
5. The method of claim 4, wherein in step 6, the SVV is the set of optimal acting vectorsoptIncluding a zero virtual voltage vector and an optimal active virtual voltage vector, i.e.
SVVopt＝{vv0,vvopt} (11)
Wherein the optimal active virtual voltage vector vvoptTo minimize the active virtual voltage vector of the cost function (10), i.e.
g(vvopt)＝ming(vvj)，1≤j≤12 (12)。
6. The asymmetric six-phase PMSM model predictive flux linkage control method considering duty cycle optimization of claim 5, wherein in step 6, the duty cycle d0And doptRespectively representing virtual voltage zero vector vv0With an optimum active virtual voltage vector vvoptThe duty ratio of (1) is calculated by
Figure FDA0003308781760000041
CN202010735818.3A 2020-07-28 2020-07-28 Asymmetric six-phase PMSM model prediction flux linkage control method considering duty ratio optimization Active CN111726046B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010735818.3A CN111726046B (en) 2020-07-28 2020-07-28 Asymmetric six-phase PMSM model prediction flux linkage control method considering duty ratio optimization

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010735818.3A CN111726046B (en) 2020-07-28 2020-07-28 Asymmetric six-phase PMSM model prediction flux linkage control method considering duty ratio optimization

Publications (2)

Publication Number Publication Date
CN111726046A CN111726046A (en) 2020-09-29
CN111726046B true CN111726046B (en) 2022-03-04

Family

ID=72573823

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010735818.3A Active CN111726046B (en) 2020-07-28 2020-07-28 Asymmetric six-phase PMSM model prediction flux linkage control method considering duty ratio optimization

Country Status (1)

Country Link
CN (1) CN111726046B (en)

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113078867B (en) * 2021-04-13 2022-07-05 南通大学 Finite control set model prediction control method considering switching frequency optimization
CN113067515B (en) * 2021-04-13 2024-05-17 南通大学 Permanent magnet synchronous motor three-vector model prediction flux linkage control method considering duty ratio constraint
CN114142784B (en) * 2021-07-08 2023-11-21 福州大学 Low-calculation-amount dual-motor series system model prediction torque control method
CN113659907B (en) * 2021-09-02 2023-09-19 大连海事大学 Direct torque control method of six-phase permanent magnet fault-tolerant motor based on torque model prediction
CN114157206B (en) * 2021-11-25 2023-12-15 上大电气科技(嘉兴)有限公司 Model predictive torque control method for double three-phase permanent magnet synchronous motor
CN114400939B (en) * 2021-12-13 2023-07-11 湖南大学 Model prediction current control method and system for double three-phase permanent magnet synchronous motor

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108631672A (en) * 2018-05-07 2018-10-09 南通大学 Meter and the permanent magnet synchronous motor of optimal duty ratio modulation predict flux linkage control method
CN108649855A (en) * 2018-06-14 2018-10-12 天津工业大学 A kind of model prediction method for controlling torque based on duty ratio
CN110460281A (en) * 2019-03-28 2019-11-15 南通大学 The double vector models of three level permanent magnet synchronous motor of one kind predict flux linkage control method
CN110829922A (en) * 2019-11-18 2020-02-21 南通大学 Semi-controlled open winding PMSG dual-vector model prediction flux linkage control method

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7821224B2 (en) * 2008-04-10 2010-10-26 Tesla Motors, Inc. Voltage estimation feedback of overmodulated signal for an electrical vehicle
FR2956537B1 (en) * 2010-02-15 2012-02-24 Schneider Toshiba Inverter METHOD FOR CONTROLLING A MATRIX CONVERTER AND MATRIX CONVERTER CAPABLE OF IMPLEMENTING THE METHOD
CN106788027B (en) * 2016-12-16 2018-11-30 华中科技大学 A kind of model predictive control method and system based on optimal two vectorial combination
CN109039189B (en) * 2018-07-17 2021-11-26 东南大学 Permanent magnet synchronous motor two-vector prediction control method based on geometric method
CN109660160B (en) * 2018-09-28 2022-02-18 天津大学 Switching duty ratio prediction torque control method

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108631672A (en) * 2018-05-07 2018-10-09 南通大学 Meter and the permanent magnet synchronous motor of optimal duty ratio modulation predict flux linkage control method
CN108649855A (en) * 2018-06-14 2018-10-12 天津工业大学 A kind of model prediction method for controlling torque based on duty ratio
CN110460281A (en) * 2019-03-28 2019-11-15 南通大学 The double vector models of three level permanent magnet synchronous motor of one kind predict flux linkage control method
CN110829922A (en) * 2019-11-18 2020-02-21 南通大学 Semi-controlled open winding PMSG dual-vector model prediction flux linkage control method

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
A Flux Constrained Predictive Control for a Six-Phase PMSM Motor With Lower Complexity;yixiao luo 等;<IEEE Transactions on Industrial Electronics>;20180910;第66卷(第7期);第5081-5093页 *
An Enhanced Predictive Current Control Method for Asymmetrical Six-Phase Motor Drives;Fedrico Barrero 等;《IEEE Transactions on Industrial Electronics》;20101028;第58卷(第8期);第3242-3252页 *
Finite-Set Model-Predictive Control Strategies for a 3L-NPC I nver ter Operating With Fixed Switching Fr equency;Felipe Donoso 等;《IEEE Transactions on Industrial Electronics》;20171009;第65卷(第5期);第3954-3965页 *

Also Published As

Publication number Publication date
CN111726046A (en) 2020-09-29

Similar Documents

Publication Publication Date Title
CN111726046B (en) Asymmetric six-phase PMSM model prediction flux linkage control method considering duty ratio optimization
CN110829922B (en) Semi-controlled open winding PMSG dual-vector model prediction flux linkage control method
CN108631672B (en) Permanent magnet synchronous motor prediction flux linkage control method considering optimal duty ratio modulation
CN110995076A (en) Permanent magnet synchronous motor model prediction current control method
CN108667389B (en) Virtual voltage vector model-based prediction fault-tolerant control method
WO2022110277A1 (en) Model predictive decomposition control method and apparatus for open-winding five-phase permanent magnet synchronous motor
Zhao et al. Hybrid modulation fault-tolerant control of open-end windings linear vernier permanent-magnet motor with floating capacitor inverter
CN110504889B (en) Fault-tolerant direct torque control method for five-phase permanent magnet synchronous motor
CN110112979B (en) Permanent magnet synchronous motor non-weight coefficient prediction torque control method based on per unit
CN110011588B (en) Semi-control open winding permanent magnet synchronous generator model prediction flux linkage control method
CN110120763B (en) Permanent magnet synchronous motor non-weight coefficient prediction torque control method
CN103117702B (en) A kind of Speedless sensor method of estimation of high accuracy permagnetic synchronous motor
Zhang et al. Torque ripple RMS minimization in model predictive torque control of PMSM drives
Malla et al. SVM-DTC Permanent magnet synchronous motor driven electric vehicle with bidirectional converter
CN109713976B (en) Speed sensorless control method and device for twelve-phase permanent magnet synchronous motor
CN112260605B (en) Direct torque control method for one-phase-lacking fault of five-phase permanent magnet synchronous motor
CN113162505A (en) Permanent magnet motor torque control method and system
CN108649852B (en) Permanent magnet synchronous motor control method for improving current loop
CN115913038A (en) Model prediction control method for double three-phase permanent magnet synchronous motor
CN107370428B (en) Zero-sequence current 2-degree-of-freedom PI control method for open-winding permanent magnet motor
CN112994565B (en) Permanent magnet synchronous motor three-vector five-sector model prediction current control algorithm
CN112865613B (en) Control method of semi-centralized open winding motor driving system
CN114944803A (en) Dead-beat model prediction current control method for open-winding permanent magnet linear motor
CN109193773B (en) Method and device for controlling predicted power of double feeders
CN111464082A (en) SVPWM control method of six-phase motor with low switching loss and common-mode interference

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant