CN113972870A - Robust type predicted torque control system and method for switched reluctance motor - Google Patents

Robust type predicted torque control system and method for switched reluctance motor Download PDF

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CN113972870A
CN113972870A CN202111293940.0A CN202111293940A CN113972870A CN 113972870 A CN113972870 A CN 113972870A CN 202111293940 A CN202111293940 A CN 202111293940A CN 113972870 A CN113972870 A CN 113972870A
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torque
current
phase
switched reluctance
reluctance motor
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CN113972870B (en
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李存贺
赵博
刘剑
杜钦君
李海涛
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Shandong University of Technology
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    • 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
    • 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
    • H02P21/05—Arrangements 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
    • 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
    • H02P21/13—Observer control, e.g. using Luenberger observers or Kalman filters
    • 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
    • H02P21/18—Estimation of position or speed
    • 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
    • H02P21/20—Estimation of torque
    • 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
    • H02P21/22—Current control, e.g. using a current control loop
    • 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
    • H02P25/00—Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details
    • H02P25/02—Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details characterised by the kind of motor
    • H02P25/08—Reluctance motors
    • 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
    • H02P25/00—Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details
    • H02P25/02—Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details characterised by the kind of motor
    • H02P25/08—Reluctance motors
    • H02P25/098—Arrangements for reducing torque ripple
    • 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
    • H02P2203/00—Indexing scheme relating to controlling arrangements characterised by the means for detecting the position of the rotor
    • H02P2203/03—Determination of the rotor position, e.g. initial rotor position, during standstill or low speed operation

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Abstract

A robust type prediction torque control system and method for a switched reluctance motor belong to the technical field of switched reluctance motor control. The device comprises a torque distribution unit, a torque-current converter, a robust model prediction controller, a power converter and a switched reluctance motor. Also comprises the following steps: step 1, solving a nonlinear torque model; step 2, calculating a phase torque value at the moment k; step 3, converting the total reference torque into a phase reference torque; step 4, obtaining phase reference current; step 5, establishing a robust discrete prediction model; step 6, predicting the current value at the k +1 moment; and 7, outputting the switch state to the power converter. In the robust predicted torque control system and method for the switched reluctance motor, the torque-current conversion error is compensated in real time, and meanwhile, the online correction of a discrete prediction model in the presence of modeling errors and parameter changes is carried out, so that the current control precision is improved, the torque output is further smoothed, and the torque pulsation of the switched reluctance motor is reduced.

Description

Robust type predicted torque control system and method for switched reluctance motor
Technical Field
A robust type prediction torque control system and method for a switched reluctance motor belong to the technical field of switched reluctance motor control.
Background
The switched reluctance motor has the advantages of simple structure, high reliability, wide speed regulation range, good fault-tolerant performance, easy realization of four-quadrant operation, no need of rare earth permanent magnet materials and the like, and has wide application prospect in a plurality of fields such as general industry, aerospace, electric vehicles, household appliances and the like. Although the research on the theory and application of the switched reluctance motor has been greatly developed at present, the defect of the switched reluctance motor that the torque pulsation is serious has not been effectively solved. The torque pulsation not only deteriorates the driving performance of the motor and causes the shafting oscillation of a transmission system, but also seriously causes the damage of the transmission system, and greatly limits the application of the switched reluctance motor in occasions with high quality requirements (such as electric vehicles and servo systems).
In the prior art, the commonly adopted methods for solving the problem of torque ripple of the switched reluctance motor include the following steps:
(1) a torque control method based on torque distribution. The torque control method based on torque distribution is characterized in that a total torque is distributed to each phase by using a torque distribution function, then a phase current instruction is obtained through a torque-current converter, and further phase reference current can be tracked in real time by controlling each phase current, so that each phase torque can track the phase reference torque, and torque control is indirectly realized. Thus, the performance of the torque-to-current converter and the current controller directly determines the final torque control performance.
The existing torque-current converter generally adopts a method of carrying out table lookup interpolation on a nonlinear torque inverse model or carrying out nonlinear compensation on a conversion error based on an iterative learning method (for example, for sorrel, for hulinwei, for plum to be sunny, and the like, and for torque ripple suppression of a switched reluctance motor based on active disturbance rejection iterative learning control, a control theory and application, 2020, 37 (10): 2098-. However, these methods are too complex to be easily engineered.
(2) A model predictive control method. In chinese patent with application number 201710537544.5 and patent name "a three-phase switched reluctance motor predicted torque control system and method", and chinese patent with application number 201911180594.8 and patent name "a switched reluctance motor torque distribution model predictive control method", a switched reluctance motor model predictive control method is respectively disclosed, however, in the actual application of the conventional model predictive control method, the influence of disturbance factors such as modeling error, parameter variation and sampling error on the system controlled quantity prediction accuracy is not considered in the algorithm design, and the robustness of the control system is limited.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the defects of the prior art are overcome, and the switching reluctance motor robustness type prediction torque control system and the method thereof are provided, which can compensate the torque-current conversion error in real time, correct the discrete prediction model with the modeling error and the parameter change on line, improve the current control accuracy, help to further smooth the torque output and reduce the torque pulsation of the switching reluctance motor.
The technical scheme adopted by the invention for solving the technical problems is as follows: the robust predicted torque control system of the switched reluctance motor is characterized in that: the method comprises the following steps:
the torque distribution unit is used for converting the total reference torque accessed by the input end into phase reference torque, and the output end of the torque distribution unit is connected with the input end of the torque-current converter;
the torque-current converter is used for converting the phase reference torque input by the torque distribution unit into phase reference current, and the output end of the torque-current converter is connected with the input end of the robust model predictive controller;
the robust model predictive controller is used for generating a switch state signal, and the output end of the robust model predictive controller is connected with the control signal input end of the power converter;
the input end of a power supply of the power converter is connected with the power supply, and the output end of the power converter is connected with the power supply input end of the switched reluctance motor;
and the input end of the state collector is connected with the switched reluctance motor, and the output end of the state collector is respectively connected with the torque distribution unit, the torque-current converter and the robust model prediction controller.
Preferably, the torque-current converter comprises a first controller with a built-in linear torque inverse model and a second controller with a built-in error compensator, the output end of the torque distribution unit is simultaneously connected with the input ends of the first controller and the second controller, the output ends of the first controller and the second controller are connected with the input end of the robust model predictive controller, and the output end of the state collector is connected with the input end of the second controller.
Preferably, the robust model prediction controller comprises a prediction current controller, a robust discrete prediction model and a disturbance observer which are connected in sequence, the output end of the state collector is connected with the input ends of the prediction current controller and the robust discrete prediction model, the output end of the torque-current converter is connected with the input end of the prediction current controller, and the output end of the prediction current controller is connected with the control signal input end of the power converter.
Preferably, the state collector comprises a plurality of sensors connected with the switched reluctance motor: the rotary transformer is used for collecting the position of a rotor of the switched reluctance motor, the Hall current sensor is used for collecting the phase current of the switched reluctance motor, and the Hall voltage sensor is used for collecting the bus voltage of the switched reluctance motor.
Preferably, the output end of the rotary transformer is respectively connected with the torque distribution unit, the torque-current converter and the robust model predictive controller, and the output ends of the hall current sensor and the hall voltage sensor are connected with the robust model predictive controller.
A robust predicted torque control method for a switched reluctance motor is characterized by comprising the following steps: the method comprises the following steps:
step 1, establishing an analytical model of a flux linkage of the switched reluctance motor in a form of multiplying three-order Fourier series by a five-order polynomial, and further solving a nonlinear torque model through the analytical model of the flux linkage of the switched reluctance motor;
step 2, acquiring sampling values of phase current values and rotor position values of the switched reluctance motor at the moment k in real time through a state acquisition device, substituting the sampling values into the nonlinear torque model in the step 1, and calculating the phase torque value at the moment k;
step 3, converting the total reference torque into a phase reference torque by utilizing a cosine type torque distribution function of the torque distribution unit;
step 4, sending the phase reference torque, the rotor position and the phase torque calculated value into a torque-current converter to obtain phase reference current;
step 5, establishing a robust discrete prediction model containing modeling errors and parameter change lumped disturbance;
step 6, estimating the lumped disturbance through a robust model prediction controller, updating and correcting the robust discrete prediction model in real time, and predicting the current value at the k +1 moment;
and 7, traversing all switch states of the conducting phases in the power converter at the moment k based on a finite set model prediction control principle, and selecting the switch state which enables the value function to be minimum to output to the power converter.
Preferably, the step 4 further comprises the following steps:
step 4-1, transmitting the phase reference torque obtained by the torque distribution unit and the position information of the rotor of the switched reluctance motor collected by the state collector into a linear torque inverse model in the torque-current converter, and converting by using the linear torque inverse model to obtain a phase reference current;
step 4-2, sending the reference torque of the phase at the moment k, the position of a rotor of the switched reluctance motor and the phase current sampling value into an error compensator in the torque-current converter, and obtaining the phase torque value at the moment k by using a nonlinear torque model in the error compensator;
step 4-3, based on a feedback control principle, calculating a phase torque error between a phase torque reference value and a phase torque value by using a phase torque error adjusting unit in the error compensator when the time k is calculated, and multiplying the phase torque error by a conversion error compensation coefficient to obtain a torque-current conversion error compensation value;
and 4-4, adding the phase reference current obtained by conversion based on the linear inductance model at the moment k and the torque-current conversion error compensation value obtained in the step 4-3 to obtain the reference phase current at the moment k + 1.
Preferably, the expression of the robust discrete prediction model including modeling error and parameter change lumped disturbance is as follows:
Figure BDA0003335768580000031
wherein iph(k) For phase current sample values at time k, TsWhich represents the period of the sampling,
Figure BDA0003335768580000032
incremental inductance LincThe nominal value of (a) is,
Figure BDA0003335768580000033
is a back electromotive force coefficient EbmfThe nominal value of (a) is,
Figure BDA0003335768580000034
is the nominal value of the stator phase winding resistance R, omega (k) is the rotational speed at time k, vph(k) Phase voltage of switched reluctance motor for time k, dph(k) Is a lumped perturbation for time k.
Preferably, the expression of the predicted value of the current at the time k +1 is as follows:
Figure BDA0003335768580000035
wherein iph(k) For phase current sample values at time k, TsWhich represents the period of the sampling,
Figure BDA0003335768580000036
incremental inductance LincThe nominal value of (a) is,
Figure BDA0003335768580000037
is a back electromotive force coefficient EbmfThe nominal value of (a) is,
Figure BDA0003335768580000038
is the nominal value of the stator phase winding resistance R, omega (k) is the rotational speed at time k, vph(k) The phase voltage of the switched reluctance motor at time k,
Figure BDA0003335768580000039
for the estimate of the lumped disturbance at time k:
Figure BDA00033357685800000310
wherein the content of the first and second substances,
Figure BDA00033357685800000311
is an incremental inductance LincThe nominal value of (a) is,
Figure BDA00033357685800000312
the derivative of the lumped disturbance estimate is represented,
Figure BDA00033357685800000313
an estimate representing the lumped disturbance, γ being the disturbance observer gain, iph(k) For the phase current sample value at time k,
Figure BDA0003335768580000041
the current is predicted for the previous instant.
Compared with the prior art, the invention has the beneficial effects that:
in the robust predicted torque control system and method for the switched reluctance motor, the torque-current conversion error is compensated in real time in the torque-current converter, and the accurate conversion from phase torque to phase current can be realized without solving a nonlinear torque inverse model, so that the torque control precision of the switched reluctance motor can be further improved, and the torque ripple is reduced. Meanwhile, through the robust model prediction controller, the online correction of the discrete prediction model in the presence of modeling errors and parameter changes is carried out, the influence of disturbance quantities such as the modeling errors and the parameter changes in the operation process on the current prediction value of the system at the future moment is eliminated, the current control precision is improved, the torque output is further smoothed, and the torque ripple of the switched reluctance motor is reduced.
Drawings
Fig. 1 is a block diagram of a switched reluctance motor robustness type predictive torque control system.
Fig. 2 is a schematic diagram of a switched reluctance motor power driver circuit for a robust-type predictive torque control system.
Fig. 3 is a flowchart of a method for controlling the switching reluctance motor by using the robust predicted torque.
Fig. 4-8 are schematic diagrams of the switching states of single-phase bridge arms of a power driver of the switched reluctance motor robust type predicted torque control system.
Detailed Description
Fig. 1 to 8 are preferred embodiments of the present invention, and the present invention will be further described with reference to fig. 1 to 8.
As shown in fig. 1, a robust predicted torque control system for a switched reluctance motor includes a torque distribution unit, a torque-current converter, a robust model prediction controller (hereinafter referred to as a model prediction controller), a power distributor, and a state collector. Externally fed total reference torque Te *The input end of the torque distribution unit is connected with the input end of the torque-current converter, the output end of the torque-current converter is connected with the input end of the model predictive controller, the output end of the model predictive controller is connected with the signal input end of the power converter, a power supply (not shown in the figure) is connected with the power supply input end of the power converter, and the output end of the power converter is connected with the power supply input end of the switched reluctance motorThe source input ends are connected, and the switched reluctance motor is supplied with power through the power converter.
The device is provided with a state collector connected with the switched reluctance motor, the state collector is used for collecting information such as current, voltage, rotor position and the like when the switched reluctance motor runs, and the output end of the state collector is connected with a torque distribution unit, a torque-current converter and a model prediction controller at the same time. The state collector sends collected current and voltage information to the model prediction controller, the state collector simultaneously leads the collected information of the rotor position of the switched reluctance motor to the torque distribution unit, the torque-current converter and the model prediction controller respectively, and the state collector collects phase current iphAnd simultaneously fed into the torque-to-current converter.
The torque distribution unit is realized by adopting a controller with a built-in cosine type torque distribution function, and the total reference torque T sent from the outside is transmitted by the torque distribution unite *Conversion into phase reference torque Tph *. The torque-to-current converter includes a controller with a built-in linear torque inverse model and a controller with a built-in error compensator. Wherein the linear torque inverse model is a torque inverse model based on a linear inductance model
Figure BDA0003335768580000051
The error compensator comprises a non-linear torque model Tph(iphθ) and phase torque error adjustment unit:
Figure BDA0003335768580000052
the linear torque inverse model and the error compensator jointly make the phase reference torque Tph *Converted into a phase reference current iph *，iph *＝i1 *+i2 *，ETPThe error is adjusted for phase torque.
The robustness type model prediction controller comprises a disturbance observer, a robustness type discrete prediction model and a prediction current controller which are connected in sequence. The position signal theta of the rotor of the switched reluctance motor is sent to a disturbance observer and is disturbedThe detector collects phase current sampling values i according to the current time (k time)ph(k) And the current predicted value at the previous moment
Figure BDA0003335768580000053
Lumped disturbance d of modeling error, parameter change, sampling error and the like in robust discrete prediction modelphAnd performing real-time compensation. The robustness type discrete prediction model compensates the value d according to the disturbance of the current time (k time)ph(k) And a phase current sampling value i acquired at the current moment (k moment)ph(k) And the bus voltage v acquired at the current time (k time)dc(k) And the system rotor position theta (k) acquired at the current moment (k moment) is used for predicting the system current value i at the next moment (k +1 moment)ph(k + 1). The prediction current controller traverses all switch states of the current conducting phase of the power converter according to a predefined cost function J, and selects a switch state s which enables the cost function to be minimum*And outputting the output to a power converter.
The power converter adopts a T-shaped five-level power driving circuit as shown in FIG. 2, and the power converter is composed of two electrolytic capacitors: electrolytic capacitor CHAnd an electrolytic capacitor CLThe bridge arm of each phase consists of four switching devices (IGBTs) and two diodes.
Specifically, the method comprises the following steps: the anode of the power supply is connected with an electrolytic capacitor C at the same timeHPositive electrode of (1), IGBT tube GAHCollector electrode of (2), diode DAHCathode of (1), IGBT tube GBHCollector electrode of (2), diode DBHAnd IGBT tube GCHCollector electrode of (2), diode DCHThe negative electrode of the power supply is simultaneously connected with the electrolytic capacitor CLNegative electrode of (1), IGBT tube GALEmitter, diode DALAnode of (2), IGBT tube GBLEmitter, diode DBLAnode and IGBT tube GCHEmitter, diode DCHOf (2) an anode. Electrolytic capacitor CHThe negative electrode of the capacitor is simultaneously connected with an electrolytic capacitor CLPositive electrode of (1), IGBT tube GA1Collector electrode of (1), IGBT tube GA2Emitter electrode of (1), IGBT tube GB1Set of (1)Electrode, IGBT tube GB2Emitter electrode of (1), IGBT tube GC1Collector electrode and IGBT tube GC2An emitter of (1).
IGBT tube GAHThe emitting electrodes are simultaneously connected with an IGBT tube GA1Emitter of (2), one end of the A-phase winding, and diode DALA cathode of (a); IGBT tube GBHThe emitting electrodes are simultaneously connected with an IGBT tube GB1Emitter of (2), one end of the B-phase winding, and diode DBLA cathode of (a); IGBT tube GCHThe emitting electrodes are simultaneously connected with an IGBT tube GC1Emitter of (2), one end of the C-phase winding, diode DCLThe cathode of (1). Diode DAHThe anode of the IGBT is simultaneously connected with the other end of the A-phase winding and the IGBT tube GA2Collector electrode and IGBT tube GALA collector electrode of (a); diode DBHThe anode of the IGBT is simultaneously connected with the other end of the B-phase winding and the IGBT tube GB2Collector electrode and IGBT tube GBLA collector electrode of (a); diode DCHThe anode of the IGBT is simultaneously connected with the other end of the C-phase winding and the IGBT tube GC2Collector electrode and IGBT tube GCLThe collector electrode of (1).
The state collector comprises a plurality of sensors connected with a switched reluctance motor: a resolver for gathering switched reluctance motor rotor position theta, be used for gathering switched reluctance motor phase current iphHall current sensor and method for collecting bus voltage v of switched reluctance motordcThe hall voltage sensor of (1). The installation mode of the rotary transformer, the hall current sensor and the hall voltage sensor is a conventional means in the field, and is not described herein again.
As shown in fig. 3, a robust predicted torque control method for a switched reluctance motor includes the following steps:
step 1, establishing an analytic model and a nonlinear torque model of a switched reluctance motor flux linkage;
an analytic model of the flux linkage of the switched reluctance motor is established in a form of multiplication of a third-order Fourier series and a fifth-order polynomial:
Figure BDA0003335768580000061
wherein N isrIs the number of pole pairs of the rotor, i is the current, theta is the rotor position, lambdan(i) Coefficients representing a fourier series, n representing the order of the fourier series, n being 0, 1, 2, 3, m representing the order of a polynomial, n being 0, 1, 2, 3, 4, 5, amnRepresenting the coefficients of a polynomial.
Further obtaining a nonlinear torque model T according to the motor phase flux linkage analytical model shown in the formula (1)ph(θ, i) is as follows:
Figure BDA0003335768580000062
wherein: theta1×4＝[1cos(Nrθ)cos(2Nrθ)cos(3Nrθ)]，Λ4×1＝[λ0(i)λ1(i)λ2(i)λ3(i)]T， NrIs the number of pole pairs of the rotor, i is the current, theta is the rotor position, lambda0(i)～λ3(i) Coefficients of a Fourier series, T representing the vector inversion, Ψph(θ, i) represents an analytical model of the flux linkage of the off-reluctance motor.
Step 2, obtaining a phase torque value of the switched reluctance motor at the moment k;
the method comprises the steps of collecting sampling values i of current values of all phases of the switched reluctance motor at the current moment (k moment) in real time through a current sensor and a photoelectric encoderph(k) And a rotor position value theta (k), substituting the collected phase current and the rotor position into a nonlinear torque model shown in a formula (2), and calculating a phase torque value T at the moment kph(k)。
Step 3, distributing the total reference torque to each phase through a torque distribution unit to obtain a phase reference torque;
using a cosine type torque distribution function of the torque distribution unit, a total reference torque T obtained from the torque outer ringe *Conversion into phase reference torque Tph *(θ)：
Figure BDA0003335768580000063
Wherein, thetaonTo the opening angle, thetaoffTo the off angle, θovIs the overlap angle of two adjacent phases, NrIs the number of pole pairs of the rotor.
Step 4, obtaining a phase reference current through a torque-current converter;
phase reference torque Tph *Rotor position theta and phase torque calculation value TphFeed-in torque-to-current converter iph *(Tph *θ) to obtain a phase reference current iph *The method specifically comprises the following steps:
step 4-1, obtaining the phase reference torque by the torque distribution function
Figure BDA0003335768580000071
And rotor position obtained by sampling
Figure BDA0003335768580000072
Sending the current into a linear model, and converting the linear model into a phase reference current i by adopting a linear torque inverse model based on linear inductanceph *；
Figure BDA0003335768580000073
Wherein, Tph *(k) Reference torque for time k, Lph(θ) represents a linear inductance model of the switched reluctance motor.
Step 4-2, reference torque is carried out on the k time phase
Figure BDA0003335768580000074
Rotor position theta (k) and phase current sampling value i obtained by samplingph(k) Feeding into an error compensator which utilizes a non-linear torque model T as shown in equation (2)ph(iphTheta) calculating to obtain the phase torque value T at the k momentph(k)。
Step 4-3, based on feedback controlAccording to the principle, when the phase torque error adjusting unit is used for calculating the reference value of the phase torque at the time k
Figure BDA0003335768580000075
And phase torque value Tph(k) Phase torque error E betweenTP(k) Error of phase torque ETP(k) Multiplying the conversion error compensation coefficient lambda to obtain a torque-current conversion error compensation value
Figure BDA0003335768580000076
Figure BDA0003335768580000077
Wherein λ is a conversion error compensation coefficient, ETPAs phase torque reference value Tph *And phase torque value TphThe error between.
Step 4-4, converting the k moment based on a linear inductance model to obtain a phase reference current i1 *(k) And a torque-current conversion error compensation value i2 *(k) Adding to obtain a reference phase current i at the moment k +1ph *(k+1)：
Figure BDA0003335768580000078
Wherein i1 *(k) A phase reference current i obtained by conversion based on a linear inductance model at the moment k2 *(k) Switching error compensator pairs i for time k1 *(k) A torque-to-current conversion error compensation value for the conversion error.
Step 5, establishing a discrete prediction model containing lumped disturbances such as modeling errors, parameter changes and the like;
neglecting the mutual inductance coupling effect between phases, the phase voltage v of the switch reluctance motorphThe equilibrium equation of (a) can be expressed as:
Figure BDA0003335768580000079
wherein iphRepresenting switched reluctance machine phase current values, R representing stator phase winding resistance, ΨphRepresents the phth phase flux linkage of the switched reluctance motor,
Figure BDA00033357685800000710
in order to increase the inductance of the inductor,
Figure BDA00033357685800000711
is the back emf coefficient, Ψph(iphAnd theta) is an analytic model of the magnetic flux linkage of the off reluctance motor.
Incremental inductance LincAnd back electromotive force coefficient EbmfThe method is obtained by calculation through a motor phase flux linkage analytical model shown in formula (1), namely:
Figure BDA0003335768580000081
however, the motor phase flux linkage analytical model shown in the formula (1) inevitably has modeling errors, and in practical application, factors such as temperature, phase current and rotor position measurement errors also cause the parameters of the motor model to change. Therefore, equation (7) can be further rewritten as:
Figure BDA0003335768580000082
wherein the content of the first and second substances,
Figure BDA0003335768580000083
incremental inductance LincThe nominal value of (a) is,
Figure BDA0003335768580000084
is a back electromotive force coefficient EbmfThe nominal value of (a) is,
Figure BDA0003335768580000085
for stator phase winding resistance RCan be obtained by experimental measurement; Δ LincIs an incremental inductance LincIs different from the nominal value, Δ EbmfBack electromotive force coefficient EbmfThe delta R is the difference between the actual value and the nominal value of the stator phase winding resistance R, and comprises modeling errors and parameter changes in the system operation process; dphFor lumped disturbances on the phase voltages equivalent to modeling errors and parameter variations: dph＝ΔRiph+ΔLincdiph/dt+ΔEbmfω。
Based on the euler approximation, equation (9) can be discretized as:
Figure BDA0003335768580000086
nominal value of incremental inductance in a current discrete prediction model (10)
Figure BDA0003335768580000087
And nominal value of back emf coefficient
Figure BDA0003335768580000088
Phase current sampling value i at time kph(k) Substituting the rotor position theta (k) at the moment of k into the formula (8) to obtain a nominal value of the resistance of the stator phase winding
Figure BDA0003335768580000089
The rotation speed omega (k) at the moment k is obtained by measurement of a photoelectric encoder. Obviously, in equation (10) there is only a lumped disturbance dphIs unknown.
Step 6, carrying out online estimation on the lumped disturbance through a disturbance observer, and updating and correcting the robust discrete prediction model of the current of the switched reluctance motor driving system in real time;
designing a disturbance observer to the lumped disturbance dphAnd (3) performing online estimation, and updating and correcting the prediction model shown in the formula (10) in real time to enhance the accuracy of phase current prediction.
In order to accurately predict phase currents under different switch states, the following disturbance observer is designed based on the feedback control principle to realize lumped disturbance dphAnd (3) estimating:
Figure BDA00033357685800000810
wherein gamma is the gain of the disturbance observer,
Figure BDA00033357685800000811
the derivative of the lumped disturbance estimate is represented,
Figure BDA00033357685800000812
estimate representing lumped disturbance, dphRepresenting a lumped perturbation.
According to the euler approximation, equation (11) can be discretized as:
Figure BDA00033357685800000813
wherein, TsWhich represents the period of the sampling,
Figure BDA00033357685800000814
the derivative of the lumped disturbance estimate is represented,
Figure BDA00033357685800000815
estimate representing lumped disturbance, dphRepresenting a lumped perturbation.
Substituting equation (12) into equation (10) can obtain the predicted value of the current at time k + 1:
Figure BDA0003335768580000091
subtracting from equation (10) using equation (13) can yield:
Figure BDA0003335768580000092
substituting equation (14) into equation (12) may result in a lumped disturbance dphThe estimated values of (c) are as follows:
Figure BDA0003335768580000093
at each sampling interval, current sampling value i at the current moment is utilizedph(k) And predicting the current at the previous moment
Figure BDA0003335768580000094
The difference between them drives the disturbance observer to converge. Once the current predicted value of the previous time
Figure BDA0003335768580000095
Sum phase current sampling value iph(k) If they are equal, the disturbance compensation value d outputted by the disturbance observerph(k) The lumped disturbances in the prediction model are accurately compensated without any change. And according to the finally derived formulas (13) and (15), the k +1 time phase current value can be accurately predicted by using the k time state value of the SRM driving system.
And 7, traversing all switch states of the conducting phases in the power converter at the current moment based on a finite set model prediction control principle, and selecting the switch state which enables the predefined cost function to be minimum and outputting the switch state to the power converter.
In the power converter shown in FIG. 2, all five switching states of the single-phase bridge arm are shown in FIGS. 4-8,
traverse s at each sampling periodphFive switching states {2, 1, 0, -1, 2 }. Considering the tube voltage drops of the IGBT and the freewheeling diode, the phase voltages in different switching states can be calculated as follows:
Figure BDA0003335768580000096
wherein v isGIs IGBT tube voltage drop, vDFor a freewheeling diode tube drop，vdcRepresenting the bus voltage.
The primary control objective, considering model prediction, is to make the motor actual phase current track the reference phase current, and the secondary control objective is to minimize the power device switching frequency, so the cost function J is defined as follows:
Figure BDA0003335768580000097
wherein q isswWeight factor, s, being the second term of the cost functionphRepresenting the switch state of the ph phase.
In each sampling period, all switch states of a conducting phase in the power converter at the current moment are traversed, and the switch state s which enables the cost function (17) to be minimum is selectedph *And outputting the output to a power converter.
Figure BDA0003335768580000101
Predicted according to equations (13) and (15). The phase torque tracks the reference phase torque indirectly by accurately tracking the reference phase current through the phase current, and the torque control is indirectly finished.
While the invention has been described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the scope of the invention. However, any simple modification, equivalent change and modification of the above embodiments according to the technical essence of the present invention are within the protection scope of the technical solution of the present invention.

Claims (9)

1. A robust predicted torque control system of a switched reluctance motor is characterized in that: the method comprises the following steps:
the torque distribution unit is used for converting the total reference torque accessed by the input end into phase reference torque, and the output end of the torque distribution unit is connected with the input end of the torque-current converter;
the torque-current converter is used for converting the phase reference torque input by the torque distribution unit into phase reference current, and the output end of the torque-current converter is connected with the input end of the robust model predictive controller;
the robust model predictive controller is used for generating a switch state signal, and the output end of the robust model predictive controller is connected with the control signal input end of the power converter;
the input end of a power supply of the power converter is connected with the power supply, and the output end of the power converter is connected with the power supply input end of the switched reluctance motor;
and the input end of the state collector is connected with the switched reluctance motor, and the output end of the state collector is respectively connected with the torque distribution unit, the torque-current converter and the robust model prediction controller.
2. The switched reluctance machine robust predicted torque control system of claim 1, wherein: the torque-current converter comprises a first controller with a built-in linear torque inverse model and a second controller with a built-in error compensator, the output end of the torque distribution unit is simultaneously connected with the input ends of the first controller and the second controller, the output ends of the first controller and the second controller are connected with the input end of the robust model predictive controller, and the output end of the state collector is connected with the input end of the second controller.
3. The switched reluctance machine robust predicted torque control system of claim 1, wherein: the robust model prediction controller comprises a prediction current controller, a robust discrete prediction model and a disturbance observer which are sequentially connected, the output end of the state collector is connected with the input ends of the prediction current controller and the robust discrete prediction model, the output end of the torque-current converter is connected with the input end of the prediction current controller, and the output end of the prediction current controller is connected with the control signal input end of the power converter.
4. The switched reluctance machine robust predicted torque control system of claim 1, wherein: the state collector comprises a plurality of sensors connected with a switched reluctance motor: the rotary transformer is used for collecting the position of a rotor of the switched reluctance motor, the Hall current sensor is used for collecting the phase current of the switched reluctance motor, and the Hall voltage sensor is used for collecting the bus voltage of the switched reluctance motor.
5. The switched reluctance machine robust predicted torque control system of claim 4, wherein: the output end of the rotary transformer is respectively connected with the torque distribution unit, the torque-current converter and the robust model prediction controller, and the output ends of the Hall current sensor and the Hall voltage sensor are connected with the robust model prediction controller.
6. A robust predicted torque control method of a switched reluctance motor, which is realized by using the robust predicted torque control system of the switched reluctance motor according to claims 1 to 5, is characterized in that: the method comprises the following steps:
step 1, establishing an analytical model of the flux linkage of the switched reluctance motor in a form of multiplying three-order Fourier series by a five-order polynomial, and further solving a nonlinear torque model through the analytical model of the flux linkage of the switched reluctance motor;
step 2, acquiring sampling values of phase current values and rotor position values of the switched reluctance motor at the moment k in real time through a state acquisition device, substituting the sampling values into the nonlinear torque model in the step 1, and calculating the phase torque value at the moment k;
step 3, converting the total reference torque into a phase reference torque by utilizing a cosine type torque distribution function of the torque distribution unit;
step 4, sending the phase reference torque, the rotor position and the phase torque calculated value into a torque-current converter to obtain phase reference current;
step 5, establishing a robust discrete prediction model containing modeling errors and parameter change lumped disturbance;
step 6, estimating the lumped disturbance through a robust model prediction controller, updating and correcting the robust discrete prediction model in real time, and predicting the current value at the k +1 moment;
and 7, traversing all switch states of the conducting phases in the power converter at the moment k based on a finite set model prediction control principle, and selecting the switch state which enables the value function to be minimum to output to the power converter.
7. The switched reluctance motor robustness-type predicted torque control method of claim 6, wherein: the step 4 further comprises the following steps:
step 4-1, transmitting the phase reference torque obtained by the torque distribution unit and the position information of the rotor of the switched reluctance motor collected by the state collector into a linear torque inverse model in the torque-current converter, and converting by using the linear torque inverse model to obtain phase reference current;
step 4-2, sending the reference torque of the phase at the moment k, the position of a rotor of the switched reluctance motor and the phase current sampling value into an error compensator in the torque-current converter, and obtaining the phase torque value at the moment k by using a nonlinear torque model in the error compensator;
step 4-3, based on a feedback control principle, calculating a phase torque error between a phase torque reference value and a phase torque value by using a phase torque error adjusting unit in the error compensator when the time k is calculated, and multiplying the phase torque error by a conversion error compensation coefficient to obtain a torque-current conversion error compensation value;
and 4-4, adding the phase reference current obtained by conversion based on the linear inductance model at the moment k and the torque-current conversion error compensation value obtained in the step 4-3 to obtain the reference phase current at the moment k + 1.
8. The switched reluctance motor robustness-type predicted torque control method of claim 6, wherein: the expression of the robust discrete prediction model containing modeling errors and parameter change lumped disturbance is as follows:
Figure FDA0003335768570000021
wherein iph(k) For phase current sample values at time k, TsRepresenting the sampling period，
Figure FDA0003335768570000022
Incremental inductance LincThe nominal value of (a) is,
Figure FDA0003335768570000023
is a back electromotive force coefficient EbmfThe nominal value of (a) is,
Figure FDA0003335768570000024
is the nominal value of the stator phase winding resistance R, omega (k) is the rotational speed at time k, vph(k) Phase voltage of switched reluctance motor for time k, dph(k) Is a lumped perturbation for time k.
9. The switched reluctance motor robustness-type predicted torque control method of claim 6, wherein: the expression of the predicted value of the current at the k +1 moment is as follows:
Figure FDA0003335768570000031
wherein iph(k) For phase current sample values at time k, TsWhich represents the period of the sampling,
Figure FDA0003335768570000032
incremental inductance LincThe nominal value of (a) is,
Figure FDA0003335768570000033
is a back electromotive force coefficient EbmfThe nominal value of (a) is,
Figure FDA0003335768570000034
is the nominal value of the stator phase winding resistance R, omega (k) is the rotational speed at time k, vph(k) The phase voltage of the switched reluctance motor at time k,
Figure FDA0003335768570000035
is kEstimate of the time-of-day lumped disturbance:
Figure FDA0003335768570000036
wherein the content of the first and second substances,
Figure FDA0003335768570000037
is an incremental inductance LincThe nominal value of (a) is,
Figure FDA0003335768570000038
the derivative of the lumped disturbance estimate is represented,
Figure FDA0003335768570000039
an estimate representing the lumped disturbance, γ being the disturbance observer gain, iph(k) For the phase current sample value at time k,
Figure FDA00033357685700000310
the current is predicted for the previous instant.
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