CN111313789A - Dual-fuzzy control-based direct torque control method for permanent magnet synchronous motor - Google Patents

Dual-fuzzy control-based direct torque control method for permanent magnet synchronous motor Download PDF

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CN111313789A
CN111313789A CN202010089122.8A CN202010089122A CN111313789A CN 111313789 A CN111313789 A CN 111313789A CN 202010089122 A CN202010089122 A CN 202010089122A CN 111313789 A CN111313789 A CN 111313789A
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torque
fuzzy
error
control
flux linkage
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CN111313789B (en
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李耀华
秦玉贵
秦辉
苏锦仕
赵承辉
周逸凡
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Changan University
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    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02PCONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/24Vector control not involving the use of rotor position or rotor speed sensors
    • H02P21/28Stator flux based control
    • H02P21/30Direct torque control [DTC] or field acceleration method [FAM]
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02PCONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/0003Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control
    • H02P21/001Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control using fuzzy control
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02PCONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/05Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation specially adapted for damping motor oscillations, e.g. for reducing hunting
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02PCONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P6/00Arrangements for controlling synchronous motors or other dynamo-electric motors using electronic commutation dependent on the rotor position; Electronic commutators therefor
    • H02P6/10Arrangements for controlling torque ripple, e.g. providing reduced torque ripple

Abstract

The invention discloses a direct torque control method of a permanent magnet synchronous motor based on double fuzzy control, which comprises the steps of inputting a current torque error, a stator flux linkage error and a stator flux linkage angular position into a fuzzy controller, and outputting a selected basic voltage vector after three input quantities are subjected to fuzzification, fuzzy reasoning and deblurring processing in the fuzzy controller; inputting the current torque error, the torque error change rate and the stator flux linkage error into a fuzzy controller, and outputting the duty ratio corresponding to the selected basic voltage vector after fuzzification, fuzzy reasoning and deblurring processing; six basic voltage vectors V from the origin to six vertexes of a hexagon are determined according to a voltage vector diagram of the permanent magnet synchronous motor inverter1~V6And 1 zero voltage vector, selecting a basic voltage vector through a fuzzy controller, determining an amplitude value corresponding to the voltage vector according to the fuzzy controller, and then outputting the amplitude value to the permanent magnet synchronous motor through space vector modulation to complete direct torque control. The invention can effectively reduce torque pulsation.

Description

Dual-fuzzy control-based direct torque control method for permanent magnet synchronous motor
Technical Field
The invention belongs to the technical field of motor control, and particularly relates to a direct torque control method of a permanent magnet synchronous motor based on double fuzzy control.
Background
The direct torque control technology is based on a stator flux linkage coordinate system and directly takes the torque as a control object, so that a large amount of calculation and dependency on motor parameters during rotation coordinate transformation are avoided, the dynamic performance is good, and the torque response time is short.
In the direct torque control system of the surface permanent magnet synchronous motor, six basic voltage vectors and a zero voltage vector exist, and because two discrete hysteresis controllers are adopted for torque and flux linkage adjustment in conventional direct torque control, the same voltage vector is easy to select when the errors of the torque and the flux linkage are large and small, so that the torque response of the system is slow, and the torque pulsation is easy to increase. The invention uses a fuzzy controller to output basic voltage vector by introducing fuzzy control.
The applied voltage vector of the traditional permanent magnet synchronous motor direct torque control system based on the switching table in each sampling period is fixed, and the duty ratio of the voltage vector is also fixed to be 1. The angle and the amplitude of a voltage vector output in each sampling period are fixed, so that the torque ripple is large, and therefore another fuzzy controller is adopted to adjust the action time of the voltage vector, namely the duty ratio of the output voltage vector is not fixed to 1, but is a continuously changing quantity in [0, 1] determined by fuzzy control, namely the amplitude of the output voltage vector is changed.
Therefore, the direct torque control method based on the double-fuzzy permanent magnet synchronous motor is provided, one fuzzy controller outputs a basic voltage vector, and the other fuzzy controller outputs the duty ratio (namely the amplitude value) of the basic voltage vector, so that the performance of a control system is optimized.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide a method for controlling a direct torque of a permanent magnet synchronous motor based on dual fuzzy control, so as to effectively reduce torque ripple.
The invention adopts the following technical scheme:
a permanent magnet synchronous motor direct torque control method based on double fuzzy control comprises the following steps:
s1, inputting the current torque error, the stator flux linkage error and the stator flux linkage angular position into a fuzzy controller, and outputting the selected basic voltage vector after fuzzification, fuzzy reasoning and deblurring processing of the three input quantities in the fuzzy controller;
s2, inputting the current torque error, the torque error change rate and the stator flux linkage error into a fuzzy controller, and outputting the duty ratio corresponding to the selected basic voltage vector after fuzzification, fuzzy reasoning and deblurring processing;
s3, determining six basic voltage vectors V from the origin to six vertexes of a hexagon according to the voltage vector diagram of the permanent magnet synchronous motor inverter1~V6And 1 zero voltage vector, selecting a basic voltage vector through the fuzzy controller in the step S1, determining the amplitude corresponding to the voltage vector according to the fuzzy controller in the step S2, and outputting the amplitude to the permanent magnet synchronous motor through space vector modulation to complete direct torque control.
Specifically, in step S1, a fuzzy rule is set according to the rule of influence of the basic voltage vector on the torque and flux linkage.
Specifically, in step S2, when the flux linkage error is Z, the voltage vector duty ratio ZL is selected, without considering the influence of the flux linkage error, but only the torque error and the torque error change rate, and when the torque error ET is Z; selecting a voltage vector duty ratio VL when the torque error ET is NB and the torque error change rate is NB; when the torque error is NB and the torque error change rate is PB, the voltage vector duty ratio SL is selected.
Further, when the flux linkage error is Z, the fuzzy control rule is as follows:
specifically, in step S2, ZL is changed to ML to satisfy the control demand when the flux linkage error is N or P, and the minimum duty ratio is set to ML when the torque error ET is in the PS or PB range.
Further, the fuzzy control rule with flux linkage error N or P is:
specifically, in step S3, the torque ripple root mean square error Trip_RMSEComprises the following steps:
wherein, TeIn order to be the actual torque,is a reference torque;
stator flux linkage ripple root mean square error psirip_RMSEComprises the following steps:
wherein n is the number of sampling points, #sIn order to be the actual flux linkage,is a reference flux linkage;
average switching frequency faveComprises the following steps:
wherein N isswitchingTo the total switching frequency, t is the sampling time.
Compared with the prior art, the invention has at least the following beneficial effects:
the invention relates to a permanent magnet synchronous motor direct torque control method based on double fuzzy control.A fuzzy controller selects a voltage vector angle to be applied, and determines a basic voltage vector angle applied at the next moment according to the existing control experience of a direct torque control system through the torque error, flux linkage error and stator flux linkage angle; selecting, by another fuzzy controller, a voltage vector duty cycle (i.e., magnitude) to be applied; and determining the vector magnitude of the basic voltage applied at the next moment according to the existing control experience of the direct torque control system through the torque error, the torque error change rate and the flux linkage error.
Furthermore, a series of evaluation indexes are provided for the direct torque control system, fuzzy control and traditional switch table direct torque control are compared on the control performance, and the fact that the control system based on double fuzzy control can obtain smaller torque pulsation is verified.
Further, when the purpose or benefit set by the fuzzy control rule is that flux linkage error is Z, no adjustment is needed to be made on flux linkage, so that the set duty ratio is small, namely, a voltage vector with a small amplitude is applied, so that the torque change and the flux linkage change at the moment are small, and the torque ripple is reduced.
Further, when the purpose or benefit of the fuzzy control rule setting is flux linkage error N or P, the flux linkage needs to be adjusted, and the set rule tends to reduce the torque, so when the flux linkage error is N or P, when the torque is PS or PB, that is, the flux linkage needs to be adjusted, and when the torque is increased, the minimum duty ratio is set to ML, so that sufficient amplitude is ensured to adjust the flux linkage, and the torque is increased.
In conclusion, the torque ripple can be effectively reduced.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
FIG. 1 is a diagram of a direct torque control system of a permanent magnet synchronous motor based on double fuzzy control;
FIG. 2 is a flow chart of a permanent magnet synchronous motor direct torque control based on double fuzzy control;
FIG. 3 is a graph of a torque error membership function;
FIG. 4 is a graph of membership function for flux linkage error of a stator;
FIG. 5 is a graph of membership functions for angular positions of stator flux linkages;
FIG. 6 is a graph of voltage vector angle membership function;
FIG. 7 is a graph of a torque error membership function;
FIG. 8 is a graph of a membership function for the rate of change of torque error;
FIG. 9 is a graph of membership function for stator flux linkage error;
FIG. 10 is a graph of a voltage vector duty cycle membership function;
FIG. 11 is a voltage vector diagram of a permanent magnet synchronous motor;
FIG. 12 is a diagram of a stator flux linkage waveform of a conventional switching meter;
FIG. 13 is a graph of a conventional torque waveform for a switching gauge;
FIG. 14 is a dual fuzzy control stator flux linkage waveform diagram;
FIG. 15 is a dual fuzzy control torque waveform;
FIG. 16 is a graph of dual-fuzzy control a-phase stator current;
fig. 17 is a diagram of a dual fuzzy control stator flux linkage track.
Detailed Description
Referring to fig. 1 and 2, the present invention provides a method for controlling direct torque of a permanent magnet synchronous motor based on double-fuzzy, which comprises inputting three input quantities, namely a current torque error, a stator flux error and a stator flux angular position, into a fuzzy controller, wherein the input quantities are subjected to fuzzification, fuzzy inference and fuzzy solution in the fuzzy controller, and outputting a voltage vector selected by the fuzzy controller; and then inputting the current torque error, the torque error change rate and the stator flux linkage error into a second fuzzy controller, and outputting the voltage vector amplitude selected by the fuzzy controller through three parts of fuzzification, fuzzy reasoning and fuzzy solution of the input quantity in the fuzzy controller.
The PMSM measures the actual rotation speed through a rotation speed sensor, andafter subtracting the reference rotating speed, obtaining a reference torque through a PI regulator,the voltage and the current of the inverter are measured and then 3/2 conversion is carried out to obtain UabcAnd IabcThen, calculating the angular positions of the flux linkage, the torque and the stator flux linkage to obtain the actual angular positions of the stator flux linkage, the torque and the angular positions of the stator flux linkage at the current moment, subtracting the actual torque from the reference torque to obtain a torque error, subtracting the actual flux linkage from the reference flux linkage to obtain a flux linkage error, and inputting the torque error, the flux linkage error and the angular positions of the stator flux linkage into a fuzzy controller to output a basic voltage vector angle; the torque error, the torque error change rate and the flux linkage error are input into another fuzzy controller, the action time (namely the duty ratio) of a voltage vector is output, the angle and the action time of the voltage vector are obtained, and an inverter is driven to control the motor through a space vector modulation technology.
The invention relates to a permanent magnet synchronous motor direct torque control method based on double fuzzy control, which comprises the following steps:
s1, inputting the current torque error, the stator flux linkage error and the stator flux linkage angular position into a fuzzy controller, and outputting the selected basic voltage vector through three parts of fuzzification, fuzzy reasoning and fuzzy solution in the fuzzy controller;
the torque error membership function is shown in FIG. 3, the fuzzy quantity E of the torque errorTThe domain of discourse is [ -0.5N.m, 0.5N.m]The method is divided into 5 fuzzy subsets { PL, PS, Z, NS, NL }, the membership function of the stator flux linkage error is shown in FIG. 4, and the fuzzy quantity E of the flux linkage errorψThe universe of discourse is [ -0.01Wb, 0.01Wb]The method is divided into three fuzzy subsets { P, Z and N }, the membership function of the angular position of the stator flux linkage is shown in FIG. 5, and the theory domain of the fuzzy quantity of the angular theta of the stator flux linkage is [ -pi, pi }]Can be divided into 6 fuzzy subsets theta1,θ2,θ3,θ4,θ5,θ6The basic voltage vector membership function is shown in FIG. 6, and the output of the fuzzy controller is 7 discrete voltage vectors { V } of the inverter0,V1,V2…V6Adopting successive membershipThe degree function replaces the discrete point set, and a fuzzy rule set used in the fuzzy inference process is shown in table 1.
TABLE 1 fuzzy control rules Table
S2, inputting three input quantities of the current torque error, the torque error change rate and the stator flux linkage error into a fuzzy controller, and outputting the duty ratio (amplitude) corresponding to the selected basic voltage vector through three parts of fuzzification, fuzzy reasoning and fuzzy solution in the fuzzy controller;
the torque error membership function is shown in FIG. 7, the fuzzy quantity E of the torque errorTDiscourse domain is [ -0.5 Nm, 0.5 Nm]The method is divided into 5 fuzzy subsets (NB, NS, Z, PS, PB), the membership function of the torque error change rate is shown in figure 8, and the torque error change rate dETDiscourse domain of [ -2, 2]The fuzzy vector is divided into 5 fuzzy subsets (NB, NS, Z, PS, PB), the membership function of the flux linkage error of the stator is shown in FIG. 9, and the fuzzy vector E psi of the flux linkage error has a argument range of [ -0.01Wb, 0.01Wb ]]The fuzzy logic vector is divided into 3 fuzzy subsets { N, Z, P }, the voltage vector duty ratio membership function is shown in FIG. 10, and the discourse domain of the voltage vector duty ratio delta is [0, 1]]The fuzzy inference method is divided into 5 fuzzy subsets { ZL, SL, ML, RL, VL }, and fuzzy rule sets used in the fuzzy inference process are shown in tables 2 and 3.
TABLE 2 fuzzy control rule table (flux linkage error Z)
TABLE 3 fuzzy control rule table (flux linkage error N or P)
S3, referring to fig. 11, six basic voltage vectors V from the origin to six vertices of a hexagon are determined according to the pm synchronous motor inverter voltage vector diagram1~V6And 1 zero voltage vector, selecting a basic voltage vector through a first fuzzy controller, determining an amplitude value corresponding to the voltage vector according to a second fuzzy controller, and outputting through a space vector modulation technology;
the torque ripple root mean square error is shown in formula (1):
the stator flux linkage pulsation root mean square error is shown as formula (2):
the average switching frequency is shown in equation (3):
and S4, comparing the direct torque control of the permanent magnet synchronous motor based on the double fuzzy control with the direct torque control of the traditional switch meter on the aspect of control performance, wherein the direct torque control comprises a torque root mean square error, a stator flux linkage root mean square error and an average switching frequency.
The direct torque control of the permanent magnet synchronous motor based on the fuzzy logic is verified to be capable of effectively reducing torque ripple compared with the direct torque control of a traditional switch meter.
The fuzzy rule of the direct torque control of the permanent magnet synchronous motor based on the fuzzy logic is obtained based on the existing control experience of a direct torque control system, and a required fuzzy rule set is analyzed and obtained.
In the fuzzy controller of step S1, a fuzzy rule table is set according to the rule of influence of the basic voltage vector on the torque and flux linkage.
In the fuzzy controller of step S2, when the flux linkage error is Z, only the torque error and the rate of change of the torque error are considered without considering the influence of the flux linkage error.
When the torque error ET is Z, indicating that the torque needs to be kept unchanged, selecting a voltage vector duty ratio ZL, selecting a torque error ET as NB, and selecting a voltage vector duty ratio VL when the torque error change rate is NB, namely, when the torque needs to be greatly reduced, and when the torque error change rate is greatly reduced, selecting the maximum duty ratio to meet the requirement.
When the torque error is NB and the torque error change rate is PB, the voltage vector duty ratio SL is selected, that is, the torque needs to be reduced greatly, but when the torque error change rate is increased greatly, the torque error change rate cancels a part of the torque demand, and at this time, the smaller voltage vector duty ratio SL is selected to meet the demand, so that other rules are derived.
When the flux linkage error is N or P, the influence of the flux linkage error cannot be ignored, and at this time, the applied voltage vector duty ratio ZL causes the situation that the flux linkage demand cannot be met only by meeting the torque demand, and large fluctuation of the flux linkage is caused, and all ZL is converted into ML to meet the control demand. And the basic voltage vector selected by the double fuzzy control system considers the requirement of flux linkage when the torque needs to be increased, and the torque cannot be greatly increased, so that when the torque error ET is in the range of PS or PB, the minimum duty ratio is ML to meet the requirement of the torque.
From this, a fuzzy control rule table can be obtained:
when the flux linkage error is Z, the fuzzy rule table is shown as table 2;
when the flux linkage error is N or P, the fuzzy rule table is shown in table 3.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The simulation parameters of the surface permanent magnet synchronous motor system are as follows:
a direct torque control simulation model of the surface permanent magnet synchronous motor is established based on MATLAB/Simulink.
The simulation model is a discrete model with a sampling period of 5 × 10-5s。
The dc bus voltage is 312V.
The parameters of the rotating speed PI regulator are as follows: KP is 5, KI is 100, and PI regulator outputs are [ -35, 35 ].
The reference speed was 50rpm, stepped to-50 rpm at 1 s.
The load torque was initially 15n.m, stepped to-15 n.m at 0.5s, and stepped to 15n.m at 1.5 s.
The reference stator flux linkage amplitude is 0.3 Wb.
The simulation total duration is 2 s.
The parameters of the surface-mounted permanent magnet synchronous motor for simulation are shown in table 4.
TABLE 4 simulation surface-mounted PMSM parameters
A series of performance indexes are compared for a traditional direct control switch table and double fuzzy direct torque control.
The stator flux linkage and the torque of the permanent magnet synchronous motor controlled by the traditional direct torque control switch table are shown in figures 12-13, wherein the traditional switch table is shown in table 5, and phi and tau are output results of the stator flux linkage and the torque hysteresis comparator respectively.
TABLE 5 conventional switch watch
The stator flux linkage and torque of the permanent magnet synchronous motor adopting the double fuzzy control are shown in fig. 14 and 15.
Simulation results show that the simulation waveforms under the two strategies are stable, the control effect is stable and good, the stator flux linkage track under the dual fuzzy control static coordinate system is shown in the figures 16 and 17, and the a-phase stator current is shown in the figures 17.
The performance indexes include: torque ripple root mean square error, flux linkage ripple root mean square error, average switching frequency. The simulation evaluation results are shown in tables 6 to 8.
TABLE 6 Steady State Torque ripple RMSE/N.m under different control strategies
TABLE 7 Steady-State flux linkage ripple RMSE/Wb under different control strategies
TABLE 8 average switching frequency/kHz under different control strategies
Control strategy Average switching frequency/kHz
Conventional direct torque control 3.295
Dual fuzzy control 6.026
A series of evaluation indexes were compared from the simulation evaluation results in tables 6 to 8. The performance of the double fuzzy control is superior to that of the traditional switch table control, and lower torque ripple can be obtained.
In summary, the following conclusions are drawn:
1. the dual fuzzy control performance is superior to the conventional switch table (DTC).
2. The double fuzzy control reasonably classifies the torque error and the flux linkage error in a fuzzy way, outputs a proper basic voltage vector, reasonably classifies the torque error, the torque error change rate and the flux linkage error, outputs a proper voltage vector duty ratio, and effectively reduces the torque ripple but increases the average switching frequency after the space vector modulation.
3. In summary, fuzzy output voltage vector duty cycle control is a better and ideal control method.
The above-mentioned contents are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modification made on the basis of the technical idea of the present invention falls within the protection scope of the claims of the present invention.

Claims (7)

1. A direct torque control method of a permanent magnet synchronous motor based on double fuzzy control is characterized by comprising the following steps:
s1, inputting the current torque error, the stator flux linkage error and the stator flux linkage angular position into a fuzzy controller, and outputting the selected basic voltage vector after fuzzification, fuzzy reasoning and deblurring processing of the three input quantities in the fuzzy controller;
s2, inputting the current torque error, the torque error change rate and the stator flux linkage error into a fuzzy controller, and outputting the duty ratio corresponding to the selected basic voltage vector after fuzzification, fuzzy reasoning and deblurring processing;
s3 according to voltage vectors of permanent magnet synchronous motor inverterThe quantity map determines six basic voltage vectors V from the origin to six vertices of a hexagon1~V6And 1 zero voltage vector, selecting a basic voltage vector through the fuzzy controller in the step S1, determining the amplitude corresponding to the voltage vector according to the fuzzy controller in the step S2, and outputting the amplitude to the permanent magnet synchronous motor through space vector modulation to complete direct torque control.
2. The double-fuzzy-control-based permanent magnet synchronous motor direct torque control method according to claim 1, characterized in that in step S1, fuzzy rules are set according to the influence rule of basic voltage vectors on torque and flux linkage.
3. The method of claim 1, wherein in step S2, when the flux linkage error is Z, the voltage vector duty ratio ZL is selected, only the torque error and the torque error change rate are considered, without considering the influence of the flux linkage error, and when the torque error ET is Z; selecting a voltage vector duty ratio VL when the torque error ET is NB and the torque error change rate is NB; when the torque error is NB and the torque error change rate is PB, the voltage vector duty ratio SL is selected.
4. The dual-fuzzy control based direct torque control method of the permanent magnet synchronous motor according to claim 3, wherein when the flux linkage error is Z, the fuzzy control rule is as follows:
5. the double-fuzzy-control-based permanent magnet synchronous motor direct torque control method according to claim 1, characterized in that in step S2, ZL is changed to ML to meet the control requirement when the flux linkage error is N or P, and the minimum duty ratio is ML when the torque error ET is in the PS or PB range.
6. The method for controlling the direct torque of the permanent magnet synchronous motor based on the double fuzzy control as claimed in claim 5, wherein the fuzzy control rule with flux linkage error of N or P is as follows:
7. the double-fuzzy-control-based direct torque control method for the PMSM according to claim 1, wherein in step S3, the torque ripple root mean square error Trip_RMSEComprises the following steps:
wherein, TeIn order to be the actual torque,is a reference torque;
stator flux linkage ripple root mean square error psirip_RMSEComprises the following steps:
wherein n is the number of sampling points, #sIn order to be the actual flux linkage,is a reference flux linkage;
average switching frequency faveComprises the following steps:
wherein N isswitchingTo the total switching frequency, t is the sampling time.
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Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20070073685A (en) * 2007-06-12 2007-07-10 순천대학교 산학협력단 Maximum torque control system for induction motor
CN202034939U (en) * 2011-05-17 2011-11-09 蒋雪峰 Direct torque control device for novel asynchronous motor based on fuzzy control
CN105048896A (en) * 2015-07-08 2015-11-11 河南科技大学 Brushless DC motor direct torque adaptive fuzzy control method
CN105515455A (en) * 2016-01-28 2016-04-20 湖南科技大学 Synchronous control method and device for biswitch reluctance motors
CN106959612A (en) * 2017-04-12 2017-07-18 江苏大学 A kind of ribbon conveyer twin-engined drives power balancing method based on fuzzy control
CN107332490A (en) * 2017-08-30 2017-11-07 西安科技大学 A kind of fuzzy direct Instantaneous torque control method of switched reluctance machines
CN107425780A (en) * 2017-08-10 2017-12-01 华北电力大学(保定) A kind of system and method for brushless dual-feed motor Direct Torque Control
CN109910863A (en) * 2019-04-17 2019-06-21 苏州赫行新能源汽车科技有限公司 A kind of control method based on plug-in hybrid car dedicated transmission
CN110572108A (en) * 2019-09-12 2019-12-13 桂林电子科技大学 Method and system for nonlinear compensation and control of inductance model of switched reluctance motor

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20070073685A (en) * 2007-06-12 2007-07-10 순천대학교 산학협력단 Maximum torque control system for induction motor
CN202034939U (en) * 2011-05-17 2011-11-09 蒋雪峰 Direct torque control device for novel asynchronous motor based on fuzzy control
CN105048896A (en) * 2015-07-08 2015-11-11 河南科技大学 Brushless DC motor direct torque adaptive fuzzy control method
CN105515455A (en) * 2016-01-28 2016-04-20 湖南科技大学 Synchronous control method and device for biswitch reluctance motors
CN106959612A (en) * 2017-04-12 2017-07-18 江苏大学 A kind of ribbon conveyer twin-engined drives power balancing method based on fuzzy control
CN107425780A (en) * 2017-08-10 2017-12-01 华北电力大学(保定) A kind of system and method for brushless dual-feed motor Direct Torque Control
CN107332490A (en) * 2017-08-30 2017-11-07 西安科技大学 A kind of fuzzy direct Instantaneous torque control method of switched reluctance machines
CN109910863A (en) * 2019-04-17 2019-06-21 苏州赫行新能源汽车科技有限公司 A kind of control method based on plug-in hybrid car dedicated transmission
CN110572108A (en) * 2019-09-12 2019-12-13 桂林电子科技大学 Method and system for nonlinear compensation and control of inductance model of switched reluctance motor

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
刘军 等: "基于模糊控制调节电压矢量作用时间策略的永磁同步电机直接转矩控制仿真研究", 《中国电机工程学报》 *

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