CN112468034A - Permanent magnet synchronous motor weak magnetic area efficiency optimal control current track searching method and online control method - Google Patents

Permanent magnet synchronous motor weak magnetic area efficiency optimal control current track searching method and online control method Download PDF

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CN112468034A
CN112468034A CN202011519783.6A CN202011519783A CN112468034A CN 112468034 A CN112468034 A CN 112468034A CN 202011519783 A CN202011519783 A CN 202011519783A CN 112468034 A CN112468034 A CN 112468034A
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iteration
weak magnetic
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CN112468034B (en
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郑萍
王明峤
乔光远
刘家琦
郎杰文
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Harbin Institute 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
    • H02P6/00—Arrangements for controlling synchronous motors or other dynamo-electric motors using electronic commutation dependent on the rotor position; Electronic commutators therefor
    • H02P6/34—Modelling or simulation for control purposes
    • 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
    • H02P21/0014—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control using neural networks
    • 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
    • H02P21/14—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
    • H02P21/14—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
    • H02P25/022—Synchronous motors
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    • 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
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    • H02P21/0085—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation specially adapted for high speeds, e.g. above nominal speed
    • H02P21/0089—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation specially adapted for high speeds, e.g. above nominal speed using field weakening
    • 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
    • H02P2207/00—Indexing scheme relating to controlling arrangements characterised by the type of motor
    • H02P2207/05—Synchronous machines, e.g. with permanent magnets or DC excitation
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    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
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Abstract

The invention discloses a search method and an online control method for an optimal efficiency control current track of a weak magnetic area of a permanent magnet synchronous motor, belongs to the field of motors, and aims to solve the problems that the current track deviation is large and the accurate optimal efficiency control of the weak magnetic area cannot be realized due to the fact that a traditional optimal efficiency control algorithm of the weak magnetic area uses fixed parameter value calculation. The method comprises the following steps: under the given torque instruction, rotating speed instruction, voltage limit and current limit, obtaining a current working point with the minimum current amplitude as an optimal efficiency control current track of the weak magnetic area; the method comprises the steps of weak magnetic current angle iteration and current amplitude iteration, wherein the weak magnetic current angle iteration is carried out firstly, and the iteration direction is the direction in which the current amplitude is reduced under the voltage limit; in the iteration process, current amplitude iteration is nested to determine the current amplitude corresponding to each current angle, the iteration direction is the direction in which the error between the given torque and the actual torque is reduced, and the current trajectory with the optimal efficiency control in the weak magnetic region is output after iteration convergence.

Description

Permanent magnet synchronous motor weak magnetic area efficiency optimal control current track searching method and online control method
Technical Field
The invention relates to a current track search algorithm for optimal control of efficiency of a weak magnetic area of a permanent magnet synchronous motor, in particular to a nonlinear flux linkage model of the permanent magnet synchronous motor and an optimal online control algorithm for the efficiency of the weak magnetic area of the permanent magnet synchronous motor based on a neural network, and belongs to the field of motors.
Background
In recent years, the traditional automobile has a great amount of conservation, the problem of environmental pollution is becoming more serious, and the environmental pollution becomes one of the important factors for increasing the global warming and the greenhouse effect. Meanwhile, the traditional automobile uses an internal combustion engine, the energy conversion rate is low, the internal combustion engine is very dependent on non-renewable resources such as petroleum, and the dual pressure of environmental pollution and energy crisis prompts the traditional automobile industry to gradually develop towards new energy automobiles. The rare earth permanent magnet synchronous motor has the advantages of high power factor, high power density, high efficiency, high reliability and the like, and is widely applied to the fields of electric automobiles, rail transit, household appliances, aerospace, national defense industry and the like. The rare earth permanent magnet motor can be divided into a surface-mounted permanent magnet synchronous motor and a built-in permanent magnet synchronous motor according to different rotor structures, wherein the built-in permanent magnet synchronous motor has different alternating-axis and direct-axis inductances, and additional reluctance torque can be generated by utilizing the asymmetry of the inductances, so that the torque output capability of the motor is improved.
In order to utilize the reluctance torque to the maximum extent, improve the output torque of the motor, and realize the efficient operation of the motor, the idea of optimal control of the efficiency of the weak magnetic region is generally applied to the interior permanent magnet synchronous motor. By adopting the optimal control method for the efficiency of the weak magnetic area, the reluctance torque of the motor can be utilized to the maximum extent, the torque output capacity of the motor under the unit stator current is improved, and the copper loss of the motor during operation can be effectively reduced and the operation efficiency of the motor is improved only by applying smaller stator current under certain output torque requirement and voltage limit. The traditional weak magnetic region efficiency optimal control algorithm is based on a mathematical model of the permanent magnet synchronous motor, and a current track of the motor under the weak magnetic region efficiency optimal control is calculated according to a torque calculation formula and a voltage calculation formula.
However, the traditional weak magnetic area efficiency optimal control algorithm considers that the parameters of the motor such as the quadrature-direct axis inductance, the permanent magnetic flux linkage and the like are fixed, the equivalent processing mode is unreasonable, the traditional weak magnetic area efficiency optimal control algorithm uses the motor parameters such as the permanent magnetic flux linkage, the quadrature axis inductance, the direct axis inductance and the like, the motor parameters can change along with the change of the saturation degree of the iron core of the motor, the higher the load saturation degree of the motor is, the more obvious the parameter changes such as the motor inductance and the like are, the traditional algorithm uses the fixed parameters to calculate the current track under the weak magnetic area efficiency optimal control, the obtained current track has deviation with the actual weak magnetic area efficiency optimal control current track, and the accurate weak magnetic area efficiency optimal control cannot be realized.
Disclosure of Invention
The invention aims to solve the problems that the traditional weak magnetic area efficiency optimal control algorithm uses fixed parameter value calculation, the current track deviation is large, and the accurate weak magnetic area efficiency optimal control cannot be realized, and provides a permanent magnet synchronous motor weak magnetic area efficiency optimal control current track searching method and an online control method.
The invention relates to a permanent magnet synchronous motor weak magnetic area efficiency optimal control current track searching method, which comprises the following steps: under the given torque instruction, rotating speed instruction, voltage limit and current limit, obtaining a current working point with the minimum current amplitude as an optimal efficiency control current track of the weak magnetic area;
the method comprises a flux weakening current angle iteration circulation step and a current amplitude iteration circulation step, wherein the flux weakening current angle iteration circulation step is firstly carried out, and the current angle iteration direction is the direction of current amplitude reduction under a voltage limit; and in the current angle iteration process, nesting a current amplitude iteration loop step to determine the current amplitude corresponding to each current angle, wherein the iteration direction of the current amplitude is the direction of reducing the error between the given torque and the actual torque, and when the iteration interval of the current angle is smaller than the iteration precision of the given current angle, considering that the current amplitude has converged to the minimum value, and outputting the current track with the optimal efficiency control in the weak magnetic region.
Preferably, the step of iteratively circulating the flux weakening current angle comprises the following steps:
a1, initial current angle range [ a ]1，b1]And calculating initial value lambda of current angle probing point1、β1：
λ1＝a1+0.382(b1-a1)、β1＝a1+0.618(b1-a1)；
A2, judging the target function value U (beta) of the load voltagek) And voltage limit value UlimIf U (β) is large or smallk)＞UlimExecuting the step A6; otherwise, go to step A3;
load voltage objective function value U (β)k) Obtaining by calling a current amplitude iteration loop, wherein the current angle iteration number k is 1,2, 3.:
a3, judging the current amplitude target function value I (lambda) at the probe point of the two current anglesk) And I (. beta.)k) Whether or not the relation I (lambda) existsk)＞I(βk)，
If yes, go to step A4; judging whether to execute the step A6;
current magnitude objective function value I (λ)k) And I (. beta.)k) Obtaining by calling current amplitude iterative loop;
a4, order ak+1＝λk，bk+1＝bk，λk+1＝βk，βk+1＝ak+1+0.618(bk+1-ak+1)，
A5, calling current amplitude iterative loop to obtain current amplitude objective function value I (beta)k+1) Then, step A8 is performed;
a6, order ak+1＝ak，bk+1＝βk，βk+1＝λk，λk+1＝ak+1+0.382(bk+1-ak+1)，
A7, calling current amplitude iteration loopObtaining a current amplitude objective function value I (lambda)k+1) Then, step A8 is performed;
a8, let k be k + 1;
a9, judging whether the iteration converges: if b isk-ak＜L1Executing the step A10; otherwise, return to step A2;
wherein L is1Iteration precision is the current angle;
a10, judging whether the current operating point meets the current limit requirement at the same time: if I (λ)k)≤Ilim，IlimOutputting a current track with optimal efficiency control in a weak magnetic area for a given current limit value; otherwise, the torque and speed commands are input again, and the step A1 is executed again.
Preferably, the current amplitude iterative loop step comprises:
b1, initial value interval of initialization current amplitude: [ c ] is1，d1]And calculating the initial value mu of the current amplitude probing point1、ν1：
μ1＝c1+0.382(d1-c1)、ν1＝c1+0.618(d1-c1)；
B2, calculating a torque error objective function value at the two current amplitude probing points: f (. mu.) (1)、f(v1)，
Torque error objective function f (I)
Figure BDA0002848568820000031
Obtaining, wherein:
Figure BDA0002848568820000032
for a given torque, Te(I, theta) is torque corresponding to the current angle theta, and the current angle theta is a current angle probing point lambda output by the flux-weakening current angle iteration cyclek、βk(ii) a I is the current amplitude;
b3, judging the torque error objective function value f (mu) at the probing point of the two current amplitudesh) And f (v)h) Whether or not the relationship f (μ) existsh)＞f(vh) And the iteration number h of the current amplitude is 1,2 and 3.
If yes, go to step B4; if not, executing the step B5;
b4, order ch+1＝μh，dh+1＝dh，μh+1＝vh，vh+1＝ch+1+0.618(dh+1-ch+1)，
Calculating the value of the objective function f (v)h+1) Then step B6;
b5, order ch+1＝ch，dh+1＝vh，vh+1＝μh，μh+1＝ch+1+0.382(dh+1-ch+1)，
Calculating the value of the objective function f (mu)h+1) Then step B6;
b6, let h be h +1,
b7, judging whether the iteration converges: if d ish-ch＜L2Outputting a current amplitude I (theta) and a voltage amplitude U (theta) corresponding to a given current angle, and outputting a result for an iterative search process of the current angle; otherwise, returning to the step B3; wherein L is2And the current amplitude iteration precision is obtained.
Preferably, the current trajectory for the efficiency optimal control of the weak magnetic region is as follows: current amplitude I ═ I (λ)k) D, the current angle theta is lambdak。
Preferably, the torque TeAnd (I, theta) is calculated and output by a motor nonlinear load quadrature-direct axis flux linkage model, and is obtained according to the following formula:
Te(I，θ)＝p(ψd(I，θ)iq-ψq(I，θ)id)
wherein p is the number of pole pairs of the motor, idIs the direct axis current of the motor iqIs the quadrature axis current of the motor,. psidIs a direct axis flux linkage of the motorqIs the quadrature axis flux linkage of the motor.
Preferably, the establishment process of the motor nonlinear load quadrature-direct axis flux linkage model comprises the following steps:
selecting a series of current working points at equal intervals or at unequal intervals within the current limit range of the motor, wherein the current working points comprise an equal-interval or unequal-interval current amplitude series value and an equal-interval or unequal-interval current angle series value, the interval of the selected current working points is determined by the saturation degree of the motor, the magnetic permeability of an iron core between two adjacent current working points needs to be ensured to be kept unchanged, and the iron core is processed according to linear materials;
calculating motor load alternate and direct axis flux linkage data corresponding to the selected current working point by adopting a simulation or experiment mode, and interpolating the obtained load alternate and direct axis flux linkage data to obtain load alternate and direct axis flux linkage models of all current working points in a current limit range, namely a nonlinear flux linkage model of the permanent magnet synchronous motor:
ψd(I,θ)＝ψd(id,iq)
ψq(I,θ)＝ψq(id,iq)。
preferably, the voltage amplitude U (θ) is obtained as follows:
Figure BDA0002848568820000041
wherein the direct axis voltage
Figure BDA0002848568820000042
Quadrature axis voltage
Figure BDA0002848568820000043
w is the electrical angular velocity of the motor, R1Is the motor resistance.
The invention also provides another technical scheme: the permanent magnet synchronous motor weak magnetic area efficiency optimal on-line control method comprises the steps of obtaining current tracks of a plurality of current working points with the minimum current amplitude values of a permanent magnet synchronous motor under the voltage limit by adopting the permanent magnet synchronous motor weak magnetic area efficiency optimal control current track searching method, training and generating a weak magnetic area efficiency optimal neural network model by taking the current tracks as sample data, inputting the weak magnetic area efficiency optimal neural network model into the rotating speed, the torque, the current limit value and the voltage limit value of the motor, and outputting the current amplitude value and the current angle;
the neural network model with the optimal weak magnetic area efficiency is loaded into a DSP or FPGA controller, the optimal online control of the efficiency of the weak magnetic area of the permanent magnet synchronous motor can be realized, and the current amplitude and the current angle are output in real time according to the rotating speed and the torque of the motor and are used for controlling the motor to operate.
The invention has the beneficial effects that:
(1) the load flux linkage model fully considers the nonlinearity of the motor, fully considers the influence rule of nonlinear factors such as iron core saturation and the like on the motor model under different magnetization states and different load conditions, can accurately simulate the nonlinear characteristics of the motor under different magnetization states and different load conditions, does not need to calculate parameters such as inductance and permanent magnet flux linkage, and can accurately calculate the torque, the load voltage and the like of the motor.
(2) A weak magnetic area efficiency optimal control current track searching method based on a double golden section iteration method is provided, and the method has two iteration loops: the weak magnetic current angle iteration and the current amplitude iteration are performed, a load flux linkage model of the motor is utilized, the iterative convergence speed in the search process is high, the calculated amount is small, the optimal control of the efficiency of the weak magnetic area of the permanent magnet synchronous motor can be quickly and accurately realized, and the running performance of the motor is improved.
(3) An online control algorithm for the optimal efficiency of the weak magnetic region based on a neural network model is provided. The current track obtained by the weak magnetic area efficiency optimal control searching method based on the double golden section iteration method is used as sample data, the neural network model is trained, tested and verified, the neural network model is established, and the weak magnetic area efficiency optimal control neural network model is loaded into a DSP or FPGA controller, so that the permanent magnet synchronous motor weak magnetic area efficiency optimal on-line control can be realized.
The invention is not only applicable to the conventional permanent magnet synchronous motor, but also applicable to a novel permanent magnet synchronous motor, such as an adjustable flux permanent magnet synchronous motor, and the like, the structure of the adjustable flux permanent magnet synchronous motor is similar to that of the conventional permanent magnet synchronous motor, and the magnetization state of the motor can be correspondingly adjusted by applying charging and demagnetizing currents in an armature winding due to the adoption of the low-coercive-force permanent magnet, so that the motor can operate in a plurality of magnetization states, but the operation principle of the motor in each magnetization state is consistent with that of the conventional permanent magnet synchronous motor, and the invention is also applicable to the novel permanent magnet synchronous motor.
Drawings
Fig. 1 is a load flux linkage model after saturation demagnetization of a series-parallel adjustable flux permanent magnet synchronous motor, wherein fig. 1(a) is a load direct-axis flux linkage model, and fig. 1(b) is a load quadrature-axis flux linkage model;
FIG. 2 is a flowchart of a method for searching a current trajectory for optimal efficiency control in a flux weakening zone of a permanent magnet synchronous motor according to the present invention;
FIG. 3 is a MAP of optimal control efficiency MAP of weak magnetic area efficiency of the motor calculated by using a traditional formula method;
FIG. 4 is a MAP of the optimal control efficiency MAP of the weak magnetic area efficiency of the motor calculated by the track search method of the present invention;
FIG. 5 is a schematic diagram of training, testing and verifying errors of a weak magnetic region efficiency optimal control neural network model.
Detailed Description
The existing technical scheme, such as a formula method, a table look-up method and the like, has certain defects in the aspects of accuracy, calculated amount, implementation speed and the like. The traditional weak magnetic area efficiency optimal control algorithm uses motor parameters such as permanent magnet flux linkage, quadrature axis inductance and direct axis inductance, the motor parameters can change along with the change of the saturation degree of a motor core, the higher the load saturation degree of the motor is, the more obvious the change of the parameters such as the motor inductance is, the traditional algorithm uses fixed parameter values to calculate the current track under the weak magnetic area efficiency optimal control, and the obtained current track has deviation with the actual weak magnetic area efficiency optimal control current track.
According to the invention, parameters such as quadrature-direct axis inductance, permanent magnet flux linkage and the like are not calculated, and the searching method is based on the idea of golden section, and under the given torque instruction, rotating speed instruction, voltage limit and current limit, the current working point with the minimum current amplitude under the voltage limit is obtained, so that the optimal control of the efficiency of the weak magnetic area is realized. The search method has two iterative loops: flux weakening current angle iteration and current amplitude iteration. The nonlinearity of the inductance and the permanent magnet flux linkage is considered, the current amplitude is difficult to directly obtain through a torque formula, so that amplitude iteration is nested in the current angle iteration process, a nonlinear load flux linkage model is used for calculating the torque in the amplitude iteration process, the influence of the nonlinearity of the inductance and the permanent magnet flux linkage is considered, and the calculation result is accurate. The nonlinear load flux linkage model can accurately calculate the motor torque, the load voltage and the like, does not need to calculate parameters such as inductance, permanent magnet flux linkage and the like, has small calculated amount and high calculating speed, can accurately simulate the change rule of the iron core saturation degree of the permanent magnet synchronous motor under different magnetization states and different load conditions, and realizes accurate modeling of the motor. The current tracks of the permanent magnet synchronous motor at a plurality of working points are obtained by the searching method, and the current tracks are used as sample data to train, test and verify the neural network model. The input of the weak magnetic region efficiency optimal control neural network model is the rotating speed, the torque, the voltage limit and the current limit of the motor, and the output is the current amplitude and the current angle (or the direct axis current and the quadrature axis current). And loading the weak magnetic region efficiency optimal control neural network model (which can be expressed by input and output functional relations) into a DSP or FPGA controller, so that the permanent magnet synchronous motor weak magnetic region efficiency optimal online control can be realized.
The first embodiment is as follows: the present embodiment is described below with reference to fig. 1 to 4, and the method for searching for an efficiency-optimized control current trajectory in a weak magnetic area of a permanent magnet synchronous motor according to the present embodiment includes a weak magnetic current angle iterative loop step and a current amplitude iterative loop step, and a current amplitude objective function value I (λ) in the weak magnetic current angle iterative loop step is shown in fig. 2k)、I(βk) And a load voltage objective function value U (lambda)k)、U(βk) The objective function value obtained by calling the current amplitude iterative loop is I (λ), where k is 1,2,31)、I(β1)、U(λ1)、U(β1)；I(λ2)、I(β2)、U(λ2)、U(β2)；I(λ3)、I(β3)、U(λ3)、U(β3) .., the parameter output to the current amplitude iteration loop is the current angle probe point lambdak、βkWhen k is 1, θ is λ1And beta1Two values, two current amplitude iteration loops are needed, when k is 2 and 3, the theta is judged to be lambda according to the conditionkOr betakPerforming current amplitude iteration cycle once, and outputting I (theta) and U (theta) through current amplitude iteration, namely outputting U (beta)k) Output I (lambda)k) Or I (. beta.)k) And returning the current angle as an objective function value to the flux weakening current angle iteration loop.
Establishing a motor nonlinear load quadrature-direct axis flux linkage model:
aiming at the characteristics that the saturation degree of an iron core of a permanent magnet synchronous motor is obviously changed under different magnetization states and different loads, and the parameter change of the motor is obvious, firstly, a nonlinear flux linkage model is provided and established to simulate the nonlinear characteristics of the motor under different magnetization states and different loads.
A series of current working points are selected at equal intervals or at unequal intervals within the current limit range of the motor, for example, the current amplitude is selected to be (0, 2, 4.), (0, 5, 10 °,) and the current angle is selected to be (0, 5, 10 °,) and the distance between the selected current working points is determined by the saturation degree of the motor, so that the magnetic permeability of an iron core between two adjacent current working points is required to be kept unchanged, and the iron core can be treated as a linear material. Calculating motor load alternate and direct axis flux linkage data corresponding to the selected current working point by adopting a simulation or experiment mode, and interpolating the obtained load alternate and direct axis flux linkage data to obtain load alternate and direct axis flux linkage models of all current working points in a current limit range, namely a nonlinear flux linkage model of the permanent magnet synchronous motor:
ψd(I,θ)＝ψd(id,iq)
ψq(I,θ)＝ψq(id,iq)
direct axis flux linkage model: psid(I,θ)＝ψd(id,iq) The direct-axis flux linkage psi of the motor can be correspondingly calculated according to the alternating-direct-axis current of the motord。
Quadrature axis flux linkage model: psiq(I,θ)＝ψq(id,iq) The quadrature-axis flux linkage psi of the motor can be correspondingly calculated according to the quadrature-axis and direct-axis currents of the motorq。
According to the obtained nonlinear flux linkage model, the electromagnetic torque, the load voltage and the like of the motor can be accurately calculated, and the calculation formulas of the electromagnetic torque and the load voltage are as follows:
torque calculation formula:
Te(I,θ)＝p(ψd(I,θ)iq-ψq(I,θ)id)
wherein, Te(I, theta) is electromagnetic torque, p is number of pole pairs of the motor, IdIs the direct axis current of the motor iqIs the quadrature axis current of the motor,. psidIs a direct axis flux linkage of the motorqIs the quadrature axis flux linkage of the motor.
Amplitude of voltage
Figure BDA0002848568820000071
Wherein the direct axis voltage
Figure BDA0002848568820000072
Quadrature axis voltage
Figure BDA0002848568820000073
w is the electrical angular velocity of the motor, R1Is the motor resistance.
The model combines the characteristic that the permanent magnet synchronous motor can be processed into a piecewise linear model when the iron core saturation is considered, only load flux linkages corresponding to a small part of current working points in the rated operating current range of the motor need to be calculated, then the load flux linkages of all current working points are obtained by utilizing the piecewise linear characteristic through interpolation, parameters such as inductance and permanent magnet flux linkages do not need to be calculated, the model is small in calculated amount and high in calculation speed, the change rule of the iron core saturation degree of the permanent magnet synchronous motor under different magnetization states and different load conditions can be accurately simulated, and the motor can be accurately modeled.
An example of a model is given below: taking a series-parallel magnetic circuit type permanent magnet synchronous motor with the pole number of 6, the slot number of 45, the rated rotating speed of 2100 revolutions per minute and the rated torque of 12.2Nm after saturation demagnetization as an example, a nonlinear flux linkage model of the motor is obtained by means of finite element simulation. At the moment, the magnetization state of the motor is saturation demagnetization, and the current of the motor is given as follows: direct axis current idThe value is (0, -2, -4, -6, -8, -10, -12) (A), for a total of 7 discrete current points; quadrature axis current iqThe value is (0, 2, 4, 6, 8, 10, 12) (A), and 7 discrete current points are provided; there are 49 discrete current operating points, 7 × 7. Through finite element simulation software, motor direct and alternating axis flux linkages of the motor at the 49 current working points in a saturated demagnetization state are obtained through simulation calculation, and flux linkages corresponding to other current working points between two adjacent current working points are interpolated to obtain direct and alternating axis load flux linkages corresponding to all current working points of the series-parallel permanent magnet synchronous motor in a current limit value range, namely a nonlinear flux linkage model of the motor, as shown in the attached drawing 1.
The weak magnetic area efficiency optimal control current track searching method based on the double golden section iteration method comprises the following steps: the current working point with the minimum current amplitude can be obtained under the given torque instruction, rotation speed instruction, voltage limit and current limit, and the efficiency optimal control of the weak magnetic region is realized, and the method is specifically shown in fig. 2.
The search algorithm has two iterative loops: flux weakening current angle iteration and current amplitude iteration. Firstly, current angle iteration is carried out, and under the given torque instruction, rotating speed instruction, voltage limit and current limit, the current angle iteration direction is the direction in which the current amplitude is reduced under the voltage limit; and nesting iteration of current amplitude while current angle iteration is carried out to determine the current amplitude corresponding to each current angle, wherein the iteration direction of the current amplitude is the direction in which the error between the given torque and the actual torque is reduced. And when the iteration interval of the current angle is smaller than a given value, the current amplitude is considered to be converged to the minimum value, namely the weak magnetic region efficiency optimal control working point.
The nonlinearity of the inductance and the permanent magnet flux linkage is considered, the current amplitude is difficult to directly obtain through a torque formula, so that amplitude iteration is nested in the current angle iteration process, a nonlinear load flux linkage model is used for calculating the torque in the amplitude iteration process, the influence of the nonlinearity of the inductance and the permanent magnet flux linkage is considered, and the current amplitude iteration result is accurate.
The implementation steps of the weak magnetic area efficiency optimal control current track searching method based on the double golden section iteration method are described as follows: the method comprises a flux weakening current angle iteration loop step and a current amplitude iteration loop step.
The weak magnetic current angle iteration loop step comprises:
a1, initial current angle range [ a ]1,b1]And calculating initial value lambda of current angle probing point1、β1：
λ1＝a1+0.382(b1-a1)、β1＝a1+0.618(b1-a1)；
Such as [ a ]1,b1]Take on values of [0 °, 90 ° ]]And simultaneously, setting iteration precision, and considering iteration convergence when the interval length is smaller than the given iteration precision along with the continuous process of the iteration process.
A2, judging the target function value U (beta) of the load voltagek) And voltage limit value UlimIf U (β) is large or smallk)＞UlimExecuting the step A6; otherwise, go to step A3;
load voltage objective function value U (β)k) Obtaining by calling a current amplitude iteration loop, wherein the current angle iteration number k is 1,2 and 3;
invoking current amplitude iterative loop output U (theta) ═ U (beta)k) Or U (lambda)k) In this embodiment, only U (. beta.) is usedk) The input of the load voltage objective function is a current angle, and the output is the load voltage under the given torque and the given rotating speed.
A3, judging the current amplitude target function value I (lambda) at the probe point of the two current anglesk) And I (. beta.)k) Whether or not the relation I (lambda) existsk)＞I(βk)，
If yes, go to step A4; judging whether to execute the step A6;
current magnitude objective function value I (λ)k) And I (. beta.)k) Obtaining by calling current amplitude iterative loop;
the input of the current amplitude target function is a current angle, and the output is a current amplitude under a given torque and a given rotating speed.
A4, order ak+1＝λk，bk+1＝bkThen, then
λk+1＝ak+1+0.382(bk+1-ak+1)
＝ak+0.382(bk-ak)+0.382(bk-ak-0.382(bk-ak))
＝ak+0.618(bk-ak)＝βk
βk+1＝ak+1+0.618(bk+1-ak+1)，
A5, calling current amplitude iterative loop to obtain current amplitude objective function value I (beta)k+1) Then, step A8 is performed;
in this step, no calculation of lambda is performedk+1Because of I (λ)k+1)＝I(βk) I.e. using the result of the last iteration. Because the golden section coefficient is used for determining the tentative point in the next iteration, when the tentative point is selected next time, one tentative point is directly taken from the tentative point in the previous iteration, and only another tentative point needs to be recalculated, so that the calculation resources are saved, the calculation amount is small, and the calculation speed is high.
A6, order ak+1＝ak，bk+1＝βkThen, then
βk+1＝ak+1+0.618(bk+1-ak+1)
＝ak+0.618(ak+0.618(bk-ak)-ak)
＝ak+0.382(bk-ak)＝λk
λk+1＝ak+1+0.382(bk+1-ak+1)，
A7, calling current amplitude iterative loop to obtain current amplitude target function value I (lambda)k+1) Then, step A8 is performed;
without performing the calculation I (beta) in this stepk+1) Because of I (β)k+1)＝I(λk) I.e. using the result of the last iteration. Because the golden section coefficient is used for determining the tentative point in the next iteration, when the tentative point is selected next time, one tentative point is directly taken from the tentative point in the previous iteration, and only another tentative point needs to be recalculated, so that the calculation resources are saved, the calculation amount is small, and the calculation speed is high.
A8, let k be k + 1;
a9, judging whether the iteration converges: if b isk-ak＜L1Executing the step A10; otherwise, return to step A2;
wherein L is1Iteration precision is the current angle;
a10, judging whether the current operating point meets the current limit requirement at the same time: if I (λ)k)≤Ilim，IlimOutputting a current track with optimal efficiency control in a weak magnetic area for a given current limit value; otherwise, inputting the torque and rotating speed commands again, and returning to execute the step A1;
the current track for the optimal efficiency control of the weak magnetic region is as follows: current amplitude I ═ I (λ)k) D, the current angle theta is lambdakA series of working point data can be obtained by inputting different rotating speeds and torques.
When k is 1, the initial value of the probe point is lambda1、β1Inputting the current amplitude iteration, and calculating the objective function value I (lambda) by calling the current amplitude iteration loop1)、I(β1)、U(β1) And returning to the current angle iteration loop, determining which trial point is calculated when k +1 is calculated according to the judgment result of the step A2, wherein the objective function value when k +1 is also called the current amplitude iteration loopFinishing, judging whether the iteration is converged according to the step A8, and continuing the iteration cycle if the iteration is not converged; if the current limit requirement of the step A10 is converged and met, outputting a current track with the optimal efficiency of the weak magnetic region, if the current limit requirement is converged and not met, proving that the parameter deviation input by the system is large, re-inputting a torque instruction and a rotating speed instruction, and re-executing two iteration cycles from the beginning.
The current amplitude iterative loop step comprises:
b1, initial value interval of initialization current amplitude: [ c ] is1，d1]And calculating the initial value mu of the current amplitude probing point1、v1：
μ1＝c1+0.382(d1-c1)、v1＝c1+0.618(d1-c1)；
For example, when the current limit value is 12A, the initial value interval of the current value is set as [0A, 12A ], and the iteration precision is set, and as the iteration process continues, when the interval length is smaller than the given iteration precision, the iteration is considered to be converged.
B2, calculating a torque error objective function value at the two current amplitude probing points: f (. mu.) (1)、f(ν1)，
Torque error objective function f (I)
Figure BDA0002848568820000101
Obtaining, wherein:
Figure BDA0002848568820000102
for a given torque, Te(I, theta) is torque corresponding to the current angle theta, and the current angle theta is a current angle probing point lambda output by the flux-weakening current angle iteration cyclek、βk(ii) a I is the current amplitude;
b3, judging the torque error objective function value f (mu) at the probing point of the two current amplitudesh) And f (v)h) Whether or not the relationship f (μ) existsh)＞f(vh) And the iteration number h of the current amplitude is 1,2 and 3.
If yes, go to step B4; if not, executing the step B5;
b4, order ch+1＝μh，dh+1＝dhThen, then
μh+1＝ch+1+0.382(dh+1-ch+1)
＝ch+0.382(dh-ch)+0.382(dh-ch-0.382(dh-ch))
＝ch+0.618(dh-ch)＝vh
vh+1＝ch+1+0.618(dh+1-ch+1)，
Calculating the value of the objective function f (v)h+1) Then step B6;
b5, order ch+1＝ch，dh+1＝vhThen, then
vh+1＝ch+1+0.618(dh+1-ch+1)＝ch+0.618(ch+0.618(dh-ch)-ch)
＝ch+0.382(dh-ch)＝μh
μh+1＝ch+1+0.382(dh+1-ch+1)，
Calculating the value of the objective function f (mu)h+1) Then step B6;
b6, let h be h +1,
b7, judging whether the iteration converges: if d ish-ch＜L2Outputting a current amplitude I (theta) and a voltage amplitude U (theta) corresponding to a given current angle, and outputting a result for an iterative search process of the current angle; otherwise, returning to the step B3; wherein L is2And the current amplitude iteration precision is obtained.
The current amplitude and the phase which should be applied to any working point (given torque instruction, rotating speed instruction, voltage limit and current limit) in the weak magnetic region efficiency optimal control can be obtained by the weak magnetic region efficiency optimal control current track searching method based on the double-golden section iterative method, the iterative convergence speed of the searching method is high, the calculated amount is small, the influence of nonlinear factors such as iron core saturation is considered, the calculated result is accurate and the like
The searching method is used for calculating the current track when the efficiency of the weak magnetic area of the series-parallel permanent magnet synchronous motor is optimally controlled, calculating the motor efficiency MAP after the corresponding current track is applied, as shown in figure 4, and simultaneously calculating the efficiency MAP when the efficiency of the weak magnetic area of the motor is optimally controlled by using a formula method, as shown in figure 3. The comparison of the two graphs shows that under the same voltage and current limits, the weak magnetic running range of the motor calculated by the iterative search method is larger, the maximum torque corresponding to each rotating speed point after the turning speed is higher, and meanwhile, the high-efficiency area occupation ratio of the MAP calculated by the iterative search method is larger, so that the accuracy of the iterative search method is higher when the full-speed-domain working point is calculated. Meanwhile, according to the calculation process, the calculation amount of the searching method is small, and the calculation speed is high.
The second embodiment is as follows: the following describes the present embodiment with reference to fig. 1 to 5, and the online control method for the efficiency optimization of the flux weakening zone of the permanent magnet synchronous motor according to the present embodiment is described.
The current tracks of the permanent magnet synchronous motor under a series of working points with the minimum current amplitude are obtained by utilizing the searching method in the first embodiment, the current tracks are used as sample data, the neural network model is trained, tested and verified, when the error is smaller than a set value, the training is completed, the neural network structure and the weight and bias parameters of each neuron are determined, the efficiency of the weak magnetic region optimally controls the establishment of the neural network model, the error of the neural network model in the training, testing and verification is shown in figure 5, the model not only can output the current tracks of the corresponding working points in the sample data, but also can output the current tracks of the working points except the sample data, and the current tracks of all the working points can be output. The neural network model has four inputs, namely motor rotating speed, torque, voltage limit and current limit, and two outputs, namely direct-axis current and quadrature-axis current, and adopts a hidden layer with 12 neurons. The weak magnetic area efficiency optimal control neural network model (which can be expressed by input and output functional relations) is loaded into a DSP or FPGA controller, so that the permanent magnet synchronous motor weak magnetic area efficiency optimal on-line control can be realized.

Claims (8)

1. The search method for the current track with optimal efficiency control in the weak magnetic area of the permanent magnet synchronous motor is characterized by comprising the following steps: under the given torque instruction, rotating speed instruction, voltage limit and current limit, obtaining a current working point with the minimum current amplitude as an optimal efficiency control current track of the weak magnetic area;
the method comprises a flux weakening current angle iteration circulation step and a current amplitude iteration circulation step, wherein the flux weakening current angle iteration circulation step is firstly carried out, and the current angle iteration direction is the direction of current amplitude reduction under a voltage limit; and in the current angle iteration process, nesting a current amplitude iteration loop step to determine the current amplitude corresponding to each current angle, wherein the iteration direction of the current amplitude is the direction of reducing the error between the given torque and the actual torque, and when the iteration interval of the current angle is smaller than the iteration precision of the given current angle, considering that the current amplitude has converged to the minimum value, and outputting the current track with the optimal efficiency control in the weak magnetic region.
2. The permanent magnet synchronous motor flux-weakening zone efficiency optimal control current track searching method as claimed in claim 1, wherein the flux-weakening current angle iterative loop step comprises:
a1, initial current angle range [ a ]1,b1]And calculating initial value lambda of current angle probing point1、β1：
λ1＝a1+0.382(b1-a1)、β1＝a1+0.618(b1-a1)；
A2, judging the target function value U (beta) of the load voltagek) And voltage limit value UlimIf U (β) is large or smallk)＞UlimExecuting the step A6; otherwise, go to step A3;
load voltage objective function value U (β)k) Obtaining by calling a current amplitude iteration loop, wherein the current angle iteration number k is 1,2,3 …;
a3, judgmentTarget function value I (lambda) of current amplitude at probe point of two current anglesk) And I (. beta.)k) Whether or not the relation I (lambda) existsk)＞I(βk)，
If yes, go to step A4; judging whether to execute the step A6;
current magnitude objective function value I (λ)k) And I (. beta.)k) Obtaining by calling current amplitude iterative loop;
a4, order ak+1＝λk，bk+1＝bk，λk+1＝βk，βk+1＝ak+1+0.618(bk+1-ak+1)，
A5, calling current amplitude iterative loop to obtain current amplitude objective function value I (beta)k+1) Then, step A8 is performed;
a6, order ak+1＝ak，bk+1＝βk，βk+1＝λk，λk+1＝ak+1+0.382(bk+1-ak+1)，
A7, calling current amplitude iterative loop to obtain current amplitude target function value I (lambda)k+1) Then, step A8 is performed;
a8, let k be k + 1;
a9, judging whether the iteration converges: if b isk-ak＜L1Executing the step A10; otherwise, return to step A2;
wherein L is1Iteration precision is the current angle;
a10, judging whether the current operating point meets the current limit requirement at the same time: if I (λ)k)≤Ilim，IlimOutputting a current track with optimal efficiency control in a weak magnetic area for a given current limit value; otherwise, the torque and speed commands are input again, and the step A1 is executed again.
3. The permanent magnet synchronous motor weak magnetic area efficiency optimal control current track searching method according to claim 2, characterized in that the current amplitude iteration loop step comprises:
b1 initial value interval of initialization current amplitude：[c1，d1]And calculating the initial value mu of the current amplitude probing point1、ν1：
μ1＝c1+0.382(d1-c1)、v1＝c1+0.618(d1-c1)；
B2, calculating a torque error objective function value at the two current amplitude probing points: f (. mu.) (1)、f(v1)，
Torque error objective function f (I)
Figure FDA0002848568810000021
Obtaining, wherein:
Figure FDA0002848568810000022
for a given torque, Te(I, theta) is torque corresponding to the current angle theta, and the current angle theta is a current angle probing point lambda output by the flux-weakening current angle iteration cyclek、βk(ii) a I is the current amplitude;
b3, judging the torque error objective function value f (mu) at the probing point of the two current amplitudesh) And f (v)h) Whether or not the relationship f (μ) existsh)＞f(vh) The number of current amplitude iterations h is 1,2,3 …
If yes, go to step B4; if not, executing the step B5;
b4, order ch+1＝μh，dh+1＝dh，μh+1＝vh，vh+1＝ch+1+0.618(dh+1-ch+1)，
Calculating the value of the objective function f (v)h+1) Then step B6;
b5, order ch+1＝ch，dh+1＝vh，vh+1＝μh，μh+1＝ch+1+0.382(dh+1-ch+1)，
Calculating the value of the objective function f (mu)h+1) Then step B6;
b6, let h be h +1,
b7, judging iterationWhether to converge or not: if d ish-ch＜L2Outputting a current amplitude I (theta) and a voltage amplitude U (theta) corresponding to a given current angle, and outputting a result for an iterative search process of the current angle; otherwise, returning to the step B3; wherein L is2And the current amplitude iteration precision is obtained.
4. The permanent magnet synchronous motor weak magnetic area efficiency optimal control current track searching method according to claim 2 or 3, characterized in that the weak magnetic area efficiency optimal control current track is as follows: current amplitude I ═ I (λ)k) D, the current angle theta is lambdak。
5. The permanent magnet synchronous motor weak magnetic area efficiency optimal control current track searching method according to claim 2 or 3, characterized in that torque TeAnd (I, theta) is calculated and output by a motor nonlinear load quadrature-direct axis flux linkage model, and is obtained according to the following formula:
Te(I,θ)＝p(ψd(I,θ)iq-ψq(I,θ)id)
wherein p is the number of pole pairs of the motor, idIs the direct axis current of the motor iqIs the quadrature axis current of the motor,. psidIs a direct axis flux linkage of the motorqIs the quadrature axis flux linkage of the motor.
6. The method for searching the current track with the optimal efficiency control in the weak magnetic area of the permanent magnet synchronous motor according to claim 5, wherein the establishment process of the motor nonlinear load quadrature-direct axis flux linkage model is as follows:
selecting a series of current working points at equal intervals or at unequal intervals within the current limit range of the motor, wherein the current working points comprise an equal-interval or unequal-interval current amplitude series value and an equal-interval or unequal-interval current angle series value, the interval of the selected current working points is determined by the saturation degree of the motor, the magnetic permeability of an iron core between two adjacent current working points needs to be ensured to be kept unchanged, and the iron core is processed according to linear materials;
calculating motor load alternate and direct axis flux linkage data corresponding to the selected current working point by adopting a simulation or experiment mode, and interpolating the obtained load alternate and direct axis flux linkage data to obtain load alternate and direct axis flux linkage models of all current working points in a current limit range, namely a nonlinear flux linkage model of the permanent magnet synchronous motor:
ψd(I,θ)＝ψd(id,iq)
ψq(I,θ)＝ψq(id,iq)。
7. the method for searching the current trajectory for optimally controlling the efficiency of the flux weakening zone of the permanent magnet synchronous motor according to claim 6, wherein the voltage amplitude U (theta) is obtained according to the following formula:
Figure FDA0002848568810000031
wherein the direct axis voltage
Figure FDA0002848568810000032
Quadrature axis voltage
Figure FDA0002848568810000033
w is the electrical angular velocity of the motor, R1Is the motor resistance.
8. The permanent magnet synchronous motor weak magnetic area efficiency optimal online control method is characterized in that a permanent magnet synchronous motor weak magnetic area efficiency optimal control current track searching method according to any claim 1-7 is adopted to obtain current tracks of a plurality of current working points of a permanent magnet synchronous motor with the minimum current amplitude under the voltage limit, the current tracks are used as sample data, a weak magnetic area efficiency optimal neural network model is generated through training, the input of the weak magnetic area efficiency optimal neural network model is the rotating speed, the torque, the current limit value and the voltage limit value of the motor, and the output is the current amplitude and the current angle;
the neural network model with the optimal weak magnetic area efficiency is loaded into a DSP or FPGA controller, the optimal online control of the efficiency of the weak magnetic area of the permanent magnet synchronous motor can be realized, and the current amplitude and the current angle are output in real time according to the rotating speed and the torque of the motor and are used for controlling the motor to operate.
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