CN112290858A - A fault-tolerant control method for phase-to-phase short circuit of five-phase permanent magnet synchronous motor based on multi-vector model prediction - Google Patents

Abstract

The invention discloses a five-phase permanent magnet synchronous motor interphase short circuit fault-tolerant control method based on multi-vector model prediction. The method comprises the following steps: detecting motor feedback rotation speed omega_mBy a given rotational speed ω^*Error of (2) to obtain i_qrefSetting i_drefIs 0; calculating the compensation voltage u_α'，u_β' and the compensating current i_α'，i_β'; sampling each phase current i_A，i_B，i_C，i_D，i_EAnd short-circuit current, combined with compensation current i_α'，i_β' and transform the matrix to obtain the feedback d-q axis current i_d(k)，i_q(k) (ii) a Calculating reference voltage value by using dead-beat algorithm, and combining with compensation voltage u_α',u_β' and back-emf compensation to obtain the reference value u of the alpha-beta axis voltage_αref，u_βref(ii) a Derivation baseA cost function of the voltage error; selecting an optimal voltage vector combination according to the shortest distance principle of the cost function; and selecting the optimal voltage vector combination and inputting the corresponding switching state of the optimal voltage vector combination into the PWM module, and inputting the obtained switching signal into the inverter to control the motor, thereby realizing the interphase short circuit fault-tolerant control of the five-phase permanent magnet synchronous motor.

Description

A fault-tolerant control method for phase-to-phase short circuit of five-phase permanent magnet synchronous motor based on multi-vector model prediction

technical field

The invention relates to the technical field of fault-tolerant control of multi-phase motors, realizes fault-tolerant control under interphase short-circuit faults of five-phase permanent magnet motors by injecting compensation voltage and current, and also relates to a novel multi-vector model predictive control. It is suitable for occasions that have high requirements on the reliability of motors, such as aerospace, electric vehicles, and ship propulsion systems.

Background technique

Permanent magnet synchronous motors are more and more widely used in electric vehicles, aerospace and marine cruise systems due to their high torque density, high efficiency and high reliability. At the same time, for some occasions with high reliability requirements such as aircraft and electric vehicles, a stable and reliable motor drive system is particularly important. The three-phase permanent magnet synchronous motor has the disadvantage of insufficient reliability in some special occasions. The multi-phase permanent magnet motor is a research hotspot in the field of motor because of its low torque ripple and high fault tolerance. The existing fault-tolerant methods mainly focus on the open-circuit fault state, and the fault-tolerant analysis of the short-circuit fault is relatively rare. Compared with the open-circuit fault, due to the existence of permanent magnets, after the short-circuit fault of the five-phase permanent magnet synchronous motor, the motor phase current increases sharply in a short time, and the motor torque ripple increases, which is more harmful to the system. The existing short-circuit fault tolerance mainly focuses on the inter-turn short circuit and the single-phase or two-phase center short-circuit of the motor, and there is no fault-tolerant control for the motor-phase short-circuit fault.

In recent years, scholars at home and abroad have carried out in-depth research on model predictive control, and have achieved rich results. Model Predictive Control (MPC) has the characteristics of fast dynamic response, simple and flexible control, and easy handling of nonlinear constraints. Compared with direct torque, MPC is more accurate and effective in vector selection. The optimal voltage vector is selected by substituting the predicted value into the value evaluation function; compared with vector control, MPC does not require current loop parameter tuning and can obtain better dynamic response characteristics. Due to the large error of the model predictive control of a single vector, the current will contain more harmonic currents, and the model predictive control of multiple vectors has become a research hotspot. At present, the multi-vector model predictive control mainly focuses on the normal running state of the motor, and there are few studies on the fault-tolerant state of the motor.

SUMMARY OF THE INVENTION

Aiming at the low accuracy of single-vector model prediction fault-tolerant control and the fault-tolerant operation of the motor under interphase short-circuit faults, the present invention proposes a phase-to-phase short-circuit fault-tolerant control method for a five-phase permanent magnet synchronous motor based on multi-vector model prediction.

For achieving technical purpose, the present invention adopts following technical scheme:

A fault-tolerant control method for phase-to-phase short circuit of a five-phase permanent magnet synchronous motor based on multi-vector model prediction, comprising the following steps:

Step 1, compare the detected feedback speed _ωm of the five-phase permanent magnet synchronous motor with the given speed ω* to obtain the speed error of the motor, and use the PI controller to calculate the five-phase permanent magnet synchronous motor according to the speed error. q-axis current reference value i _qref ; id is the _d -axis current, since id =0 control is adopted, the _d -axis current reference value _idref of the five-phase permanent magnet synchronous motor is set to 0;

Step 2, when the phase-to-phase short-circuit fault occurs in the five-phase permanent magnet synchronous motor, the compensation voltage u _α ', u can be added on the basis of the open-circuit fault of the corresponding phase according to the constraint that the magnetomotive force is constant and the neutral point is 0. _β ' and compensation current i _α ', i _β ' to eliminate the influence of interphase short-circuit current;

Step 3, use the current sensor to sample the A, B, C, D, E phase currents i _A , i _B , i _C , i _D , i _E of the five-phase permanent magnet motor and the short-circuit current i _sc during the interphase short-circuit fault, according to The sampling current determines the reduced-order matrix when the short-circuit fault corresponds to the missing phase, and the selected reduced-order matrix is used to perform matrix transformation on the phase current of the five-phase permanent magnet motor obtained by sampling, and add the previously calculated compensation current i _α ', i _β ', the _dq -axis currents id (k) and i _q (k) fed back by the five-phase permanent magnet synchronous motor during fault can be obtained;

Step 4, according to the dq-axis current and the current reference value fed back by the five-phase motor, use the deadbeat current prediction algorithm to predict the α-β axis voltage reference value, and add the previously calculated compensation voltages u _α ', u _β ' And back EMF compensation can obtain the α-β axis voltage reference values u _αref , u _βref after short-circuit compensation;

Step 5, combining the basic five-phase motor discrete prediction model and the transformation matrix from the stationary coordinate system to the rotating coordinate system, on the basis of the fault-tolerant candidate voltage vector, a value function based on the voltage error can be constructed;

Step 6: According to the previously obtained α-β axis voltage reference values u _αref , u _βref , the voltage error judgment of the candidate vector is carried out in the sector through the principle of the shortest distance, and the optimal voltage vector combination and corresponding effect can be selected. time management;

Step 7, select the optimal voltage vector combination and input its corresponding switch state to the PWM module, and obtain the switch signal of each phase, and input the obtained switch signal into the inverter to control the motor to realize the five-phase permanent magnet synchronous motor. Phase-to-phase short-circuit fault tolerance control.

Further, the derivation method of the compensation voltage and current described in step 2 is: in the case of an interphase short circuit fault, it is necessary to generate a compensation current in the remaining healthy phases to offset the influence of the interphase short circuit current, and the interphase short circuit fault can be divided into adjacent The short-circuit faults between phases and non-adjacent phases need to be analyzed separately. The specific steps are as follows:

Step 2.1, assuming that the short-circuit fault between adjacent phases occurs in the C and D phases, according to the principle that the magnetomotive force remains unchanged before and after the fault, it can be obtained:

Ni _A +γNi _B +γ ² Ni _sc -γ ³ Ni _sc +γ ⁴ i _E =0

Among them, N is the number of turns of the motor winding, γ=2/5π;

When two phases C and D fail, the current compensated in the remaining healthy phases A, B, and E must meet the neutral point current sum of 0:

i _A + i _B + i _E = 0

Assuming that the non-adjacent phase-to-phase short-circuit fault occurs in the B and E phases, according to the principle that the magnetomotive force remains unchanged before and after the fault and the sum of the neutral point current is 0, it can be obtained:

Ni _A +γNi _sc +γ ² Ni _C +γ ³ Ni _D -γ ⁴ i _sc =0

i _A +i _C +i _D =0

Step 2.2, according to the constraints, the compensation currents of the remaining phases based on the short-circuit current i _sc when the phase-to-phase short-circuit fault occurs in the C and D phases can be obtained as:

Then through the Clarke transformation matrix, the compensation current can be transformed to the α-β axis to obtain i _α ', i _β ':

为C、D相缺失下的Clarke变换矩阵；in,

is the Clarke transformation matrix under the absence of C and D phases;

Similarly, when phase-to-phase short-circuit faults occur in phases B and E, the compensation current based on the short-circuit current and the current transformed to the α-β axis can be calculated as:

为B、E相缺失下的Clarke变换矩阵；in,

is the Clarke transformation matrix under the absence of B and E phases;

Step 2.3, in order to generate the compensation current of the remaining healthy phases, the compensation voltage needs to be generated on the feedforward voltage. When the phase-to-phase short-circuit fault occurs in the C and D phases, the mathematical model of the motor is determined;

According to Kirchhoff's voltage law, the voltage equation of each phase winding can be obtained separately, and when the C and D phases fail, the two-phase winding must be regarded as a loop to solve:

Among them, U _xe (x=A, B, C, D, E) is the voltage drop of the winding resistance and inductance of each phase; U _x (x=A, B, C, D, E) is the phase voltage of each phase; e _x (x=A, B, C, D, E) is the back EMF of each phase; R _s is the resistance of each phase winding; L is the inductance of each phase winding;

Combining the compensation current and transformation matrix of the healthy phase, the compensation voltage u _α ', u _β ' on the α-β axis can be obtained:

Similarly, determine the mathematical model of the motor when the B and E phases have a short-circuit fault, and the compensation voltage is as follows:

Further, the calculation of the feedback d-q axis current in step 3 is as follows:

为C、D相缺失的Park变换矩阵，

为C、D相缺失下的Clarke变换矩阵，假如为相邻相相间短路故障：Since the feedback current is used to generate the voltage reference value, and this process is based on the open-circuit fault-tolerant control of the five-phase motor, therefore, the current collected by the current sensor needs to remove the short-circuit current component, and the collected current i of each phase needs to be removed. _A , i _B , i _C , i _D , i _E are transformed to the α-β axis through Clarke matrix, and then the compensation current i _α ', i _β ' is subtracted to eliminate the composition of short-circuit current, and then transformed to dq through Park matrix The currents _{id (k), i q (} k) are obtained on the axis,

is the Park transformation matrix with missing phases C and D,

is the Clarke transformation matrix under the absence of C and D phases, if it is a short-circuit fault between adjacent phases:

Further, the calculation of the α-β axis voltage reference values u _αref and u _βref in step 4 is as follows:

Step 4.1, according to the deadbeat current prediction method, substitute the feedback current and current reference value into the prediction equation to obtain the dq axis voltage reference value:

Among them, u _dref , u _qref are the dq-axis reference voltage, _idref , i _qref are the dq-axis reference current, L _d , L _q are the dq-axis inductance, T _s is the sampling time, ω _e is the electrical angle frequency, _ed ( k), e _q (k) is the _dq -axis back-EMF at time k in the fault-tolerant state, id (k), i _q (k) are the current at time k;

Step 4.2, according to the Park inverse matrix, the dq axis voltage reference value can be transformed to the α-β axis. At this time, the prediction is made on the basis of open circuit fault tolerance. Therefore, it is necessary to add the compensation voltage u _α ', u _β ' into it Obtain the α-β axis voltage reference values u _αref , u _βref , if it is a short-circuit fault between adjacent phases, then:

Step 4.3, according to step 2.3, the obtained α-β axis voltage reference value u _αref , u _βref contains the components of the healthy opposite potential. Taking the short-circuit fault between adjacent phases as an example, the final α-β axis voltage reference value u _αref ^* , u _βref ^* can be calculated as:

Further, the derivation of the value function based on the voltage error in step 5 is as follows:

Step 5.1, the basic model predictive control idea is to sequentially substitute the candidate voltage vectors into the value function for rolling optimization, and screen out the optimal voltage vector according to the error between the current generated by the candidate voltage vector and the current reference value, and the process can be expressed as :

g=|i _dref -i _d (k+1)| ² +|i _qref -i _q (k+1)| ²

Among them, u _d (k), u _q (k) are the dq-axis voltage of the candidate voltage vector at time k, and _id (k+1), i _q (k+1) are the current at time k+1;

In step 5.2, combined with the deadbeat prediction process in step 4.1, the value function based on current error can be transformed into a value function based on voltage error:

Step 5.3, if the deviation of the dq-axis inductance of the five-phase permanent magnet synchronous motor is not large, the weighting factors of the d-axis voltage error and the q-axis voltage error can be ignored, and then the value function based on the voltage error is transformed into α-β through the Park matrix On the axis, the final value function can be obtained:

g=|u _αref −u _α (k)| ² +|u _βref −u _β (k)| ² .

Further, the specific steps for selecting the optimal voltage vector combination in step 6 are as follows:

In case of short-circuit fault between adjacent phases:

Step 6.1, according to the Clarke transformation matrix and switching state after the two-phase missing, the vector distribution map after fault tolerance can be obtained, and the vector distribution map is divided into six sectors according to six non-zero vectors;

In step 6.2, the α-β axis voltage reference value obtained in step 4.3 can determine the amplitude and phase of the reference voltage vector, and then determine the sector where the reference vector is located. Assuming that the reference vector is located in the first sector, according to the value determined in step 5.3 The function can simplify the vector selection into a mathematical problem. Find the composite vector with the smallest voltage error in the sector, that is, find the point closest to the reference vector. The vertex of the reference voltage vector can draw vertical lines to the three sides, and the shortest distance will be Produced in three perpendicular lines;

Step 6.3, the vector combination can be divided into two cases, the combination of a non-zero vector and a zero vector and the combination of two non-zero vectors, the combination 1 contains the vector synthesis of U ₀ , U ₄ and U ₀ , U ₆ respectively;

where r ₁ and r ₂ are the action times of the non-zero vectors U ₄ and U ₆ respectively, which can be calculated as:

Wherein, U _sref =u _αref +ju _βref is the reference voltage, θ _s =arctan(u _βref /u _αref );

Combination 2 is the vector composition of non-zero vectors U ₄ and U ₆ , and the range of the composite vector vertices is the third side of the triangle;

where r ₃ and r ₄ are the action times of the non-zero vectors U ₄ and U ₆ respectively. The vector synthesis will follow the parallelogram law, which can be calculated as:

where d ₁ , d ₂ can be expressed as:

θ ₁ is the angle between d ₁ and U ₄ , and the optimal vector combination will be generated in the above combination, that is, g=min{g ₁ ,g ₂ ,g ₃ }:

g ₁ =|U _sref -r ₁ U ₄ | ²

g ₂ =|U _sref -r ₂ U ₆ | ²

g ₃ =|U _sref -(r ₃ U ₆ +r ₄ U ₄ )| ²

Among them g ₁ , g ₂ , g ₃ are the expressions of the value function in three cases.

The present invention has the following beneficial effects:

1. The present invention divides the influence of interphase short-circuit fault into the influence of open-circuit fault and interphase short-circuit current, and adds compensation voltage and current to the algorithm of open-circuit fault-tolerant control to eliminate the influence of interphase short-circuit current, thereby realizing a five-phase permanent magnet synchronous motor. The fault-tolerant control of phase-to-phase short-circuit fault improves the fault-tolerant performance of the motor, making it suitable for electric vehicles and other application fields that require high reliability and wide speed regulation range, and the method is simple and easy to implement.

2. The multi-vector model predictive control adopted by the present invention can select the optimal vector combination through the principle of the shortest distance in the asymmetric shape sector of the fault-tolerant vector distribution map, which greatly reduces the amount of Computational burden, simple and easy to implement. And the analysis method for the asymmetric shape sector can use the sector in various states, not only limited to the symmetrical shape sector in the normal state, and has wider applicability.

3. The deadbeat control method adopted in the present invention calculates the reference voltage, has faster dynamic response than the PI regulator, and has better tracking performance for the AC signal.

Description of drawings

Figure 1: Mathematical model of adjacent phase-to-phase short-circuit motor (taking C and D phases as examples);

Figure 2: Mathematical model of non-adjacent phase-to-phase short-circuit motor (taking B and E phases as examples);

Figure 3: Vector distribution diagram of short-circuit between adjacent phases;

Figure 4: Distribution of short-circuit sectors between adjacent phases;

Figure 5: Selection principle of optimal vector combination;

Figure 6: U ₀ and U ₄ vector synthesis;

Figure 7: U ₀ and U ₆ vector synthesis;

Figure 8: U ₄ and U ₆ vector synthesis; (a) is mode 1, (b) is mode 2;

Figure 9: Fault-tolerant control block diagram of five-phase permanent magnet synchronous motor based on multi-vector model prediction; (a) fault-tolerant control diagram for short-circuit between adjacent phases; (b) fault-tolerant control diagram for short-circuit between non-adjacent phases;

Figure 10: Current and torque waveforms of five-phase permanent magnet synchronous motor from fault to fault tolerance; (a) fault tolerance for short-circuit between adjacent phases; (b) fault tolerance for short-circuit between non-adjacent phases;

Figure 11: Load mutation current and torque waveform during short-circuit fault-tolerant control of five-phase permanent magnet synchronous motor; (a) short-circuit fault tolerance between adjacent phases (given speed 100r/min, load from 1-2-1Nm); (b) ) fault tolerance of non-adjacent phase-to-phase short circuit (the given speed is 100r/min, and the load is 0-1-0Nm);

Figure 12: Speed mutation current and torque waveform during short-circuit fault-tolerant control of five-phase permanent magnet synchronous motor; (a) short-circuit fault tolerance between adjacent phases (given load 2Nm, speed from 50-100-50r/min); (b) ) Short-circuit fault tolerance between non-adjacent phases (for a given load of 1Nm, the rotational speed is 50-100-50r/min).

Detailed ways

The specific implementation manner and implementation effect of this embodiment will be described in detail below with reference to the accompanying drawings.

It can be seen from the equivalent mathematical models of the motor in Figures 1 and 2 that when adjacent-phase short-circuit and non-adjacent-phase short-circuit faults occur, the influence of short-circuit faults can be divided into the influence of open-circuit faults and the influence of short-circuit current. Therefore, the present invention will On the basis of the open-circuit fault-tolerant control, the compensation voltage u _α ', u _β ' and the compensation current i _α ', i _β ' are input to realize the short-circuit fault-tolerant control.

Taking phases C and D as examples, the Clarke and Park transformation matrices of short-circuit between adjacent phases are:

According to the principle that the magnetomotive force remains unchanged before and after the fault, it can be obtained:

Ni _A +γNi _B +γ ² Ni _sc -γ ³ Ni _sc +γ ⁴ i _E =0

The current compensated in the remaining healthy phases A, B, and E must meet the neutral point current sum of 0:

i _A + i _B + i _E = 0

Assuming that the non-adjacent phase-to-phase short-circuit fault occurs in the B and E phases, according to the principle that the magnetomotive force remains unchanged before and after the fault and the sum of the neutral point current is 0, it can be obtained:

Ni _A +γNi _sc +γ ² Ni _C +γ ³ Ni _D -γ ⁴ i _sc =0

i _A +i _C +i _D =0

According to the constraints, the compensation currents of the remaining phases based on the short-circuit current i _sc when the phase-to-phase short-circuit fault occurs in the C and D phases can be obtained as:

Then through the Clarke transformation matrix under the absence of C and D phases, the compensation current can be transformed to the α-β axis to obtain i _α ', i _β ':

In order to generate the compensation current for the remaining healthy phases, a compensation voltage needs to be generated on the feedforward voltage. According to Kirchhoff's voltage law, the voltage equation of each phase winding can be obtained separately, and when the C and D phases fail, the two-phase winding must be regarded as a loop to solve:

Combining the compensation current and transformation matrix of the healthy phase, the compensation voltage u _α ', u _β ' on the α-β axis can be obtained:

Taking phases B and E as an example, the Clarke and Park transformation matrices of short-circuit between non-adjacent phases are:

Similarly, when phase-to-phase short-circuit faults occur in phases B and E, the compensation current based on the short-circuit current and the current transformed to the α-β axis can be calculated as:

Its compensation voltage is as follows:

The last row of the Clarke transformation matrix is the zero-sequence component, which satisfies the principle that the sum of the neutral points is 0, which is usually ignored in the calculation.

It can be seen from Figures 3 and 4 that when the phase-to-phase short-circuit fault occurs between phases C and D, the non-zero vector divides the vector distribution diagram into six sectors. When the reference voltage vector is solved, the location can be determined according to the phase angle of the reference voltage vector. sector.

Since the situation of each sector is very similar, it is taken as an example that the reference voltage vector is located in the first sector.

It can be seen from the voltage-based cost function derived in conjunction with Fig. 5 that the vector selection is simplified as a mathematical problem, searching for the synthetic vector with the smallest voltage error in the sector, that is, the point closest to the reference vector, which can be determined by the reference voltage. The vertices of the vector are perpendicular to the three sides, and the shortest distance will be generated in the three perpendiculars. Figures 6 and 7 are a combination of a non-zero voltage vector and a zero vector respectively, wherein r ₁ and r ₂ are the action time of the non-zero vectors U ₄ and U ₆ respectively, which can be calculated as:

Figure 8 is a combination of two non-zero voltage vectors, where r ₃ and r ₄ are the action times of the non-zero vectors U ₄ and U ₆ respectively. The vector synthesis will follow the parallelogram law, which can be calculated as:

The optimal vector combination will result in the above combination, i.e. g=min{g ₁ ,g ₂ ,g ₃ }:

g ₁ =|U _sref -r ₁ U ₄ | ²

g ₂ =|U _sref -r ₂ U ₆ | ²

g ₃ =|U _sref -(r ₃ U ₆ +r ₄ U ₄ )| ²

FIG. 9 is a block diagram of fault tolerance control of five-phase permanent magnet synchronous motor phase-to-phase short-circuit based on multi-vector model prediction. Figure 10 shows the switching of five-phase permanent magnet synchronous motor from interphase short-circuit fault to fault-tolerant control. Whether it is adjacent phase or non-adjacent phase-to-phase short circuit, the short-circuit fault-tolerant control proposed by the present invention can reduce the torque ripple caused by the fault, At the same time, the sine of the healthy phase current is restored, and it has good fault tolerance. Figures 11 and 12 respectively verify the dynamic performance of the fault-tolerant control proposed by the present invention, which can respond quickly to sudden changes in load and speed, and the motor can maintain good operating performance under different conditions.

In the description of this specification, reference to the terms "one embodiment," "some embodiments," "exemplary embodiment," "example," "specific example," or "some examples", etc., is meant to incorporate the embodiments A particular feature, structure, material, or characteristic described by an example or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

Although embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, The scope of the invention is defined by the claims and their equivalents.

Claims (6)

1. a five-phase permanent magnet synchronous motor phase-to-phase short-circuit fault-tolerant control method based on multi-vector model prediction, is characterized in that, comprises the steps: Step 1, compare the detected feedback speed _ωm of the five-phase permanent magnet synchronous motor with the given speed ω* to obtain the speed error of the motor, and use the PI controller to calculate the five-phase permanent magnet synchronous motor according to the speed error. q-axis current reference value i _qref ; id is the _d -axis current, since id =0 control is adopted, the _d -axis current reference value _idref of the five-phase permanent magnet synchronous motor is set to 0; Step 2, when the phase-to-phase short-circuit fault occurs in the five-phase permanent magnet synchronous motor, the compensation voltage u _α ', u can be added on the basis of the open-circuit fault of the corresponding phase according to the constraint that the magnetomotive force is constant and the neutral point is 0. _β ' and compensation current i _α ', i _β ' to eliminate the influence of interphase short-circuit current; Step 3, use the current sensor to sample the A, B, C, D, E phase currents i _A , i _B , i _C , i _D , i _E of the five-phase permanent magnet motor and the short-circuit current i _sc during the interphase short-circuit fault, according to The sampling current determines the reduced-order matrix when the short-circuit fault corresponds to the missing phase. Using the selected reduced-order matrix, the phase current of the five-phase permanent magnet motor obtained by sampling is converted into a matrix, and the compensation current i _α ' obtained before is added. i _β ', the _dq -axis currents id (k) and i _q (k) fed back by the five-phase permanent magnet synchronous motor during fault can be obtained; Step 4, according to the dq-axis current and the current reference value fed back by the five-phase motor, use the deadbeat current prediction algorithm to predict the α-β axis voltage reference value, and add the previously calculated compensation voltage u _α ', u _β ' And back EMF compensation can obtain the α-β axis voltage reference values u _αref , u _βref after short-circuit compensation; Step 5, combining the basic five-phase motor discrete prediction model and the transformation matrix from the stationary coordinate system to the rotating coordinate system, on the basis of the fault-tolerant candidate voltage vector, a value function based on the voltage error can be constructed; Step 6: According to the previously obtained α-β axis voltage reference values u _αref , u _βref , the voltage error judgment of the candidate vector is carried out in the sector through the principle of the shortest distance, and the optimal voltage vector combination and corresponding effect can be selected. time management; Step 7, select the optimal voltage vector combination and input its corresponding switch state to the PWM module, and obtain the switch signal of each phase, and input the obtained switch signal into the inverter to control the motor to realize the five-phase permanent magnet synchronous motor. Phase-to-phase short-circuit fault tolerance control. 2. a kind of five-phase permanent magnet synchronous motor phase-to-phase short-circuit fault-tolerant control method based on multi-vector model prediction according to claim 1, is characterized in that, the derivation method of the compensation voltage and current described in step 2 is: In the case of short-circuit fault, compensation current needs to be generated in the remaining healthy phases to offset the influence of inter-phase short-circuit current, and inter-phase short-circuit fault can be divided into adjacent phase and non-adjacent phase-to-phase short-circuit faults, which need to be analyzed separately. The specific steps are as follows: Step 2.1, assuming that the short-circuit fault between adjacent phases occurs in the C and D phases, according to the principle that the magnetomotive force remains unchanged before and after the fault, it can be obtained: Ni _A +γNi _B +γ ² Ni _sc -γ ³ Ni _sc +γ ⁴ i _E =0 Among them, N is the number of turns of the motor winding, γ=2/5π; When two phases C and D fail, the current compensated in the remaining healthy phases A, B, and E must meet the neutral point current sum of 0: i _A + i _B + i _E = 0 Assuming that the non-adjacent phase-to-phase short-circuit fault occurs in the B and E phases, according to the principle that the magnetomotive force remains unchanged before and after the fault and the sum of the neutral point current is 0, it can be obtained: Ni _A +γNi _sc +γ ² Ni _C +γ ³ Ni _D -γ ⁴ i _sc =0 i _A +i _C +i _D =0 Step 2.2, according to the constraints, the compensation currents of the remaining phases based on the short-circuit current i _sc when the phase-to-phase short-circuit fault occurs in the C and D phases can be obtained as:

Then through the Clarke transformation matrix, the compensation current can be transformed to the α-β axis to obtain i _α ', i _β ':

in,

is the Clarke transformation matrix under the absence of C and D phases; Similarly, when phase-to-phase short-circuit faults occur in phases B and E, the compensation current based on the short-circuit current and the current transformed to the α-β axis can be calculated as:

in,

is the Clarke transformation matrix under the absence of B and E phases; Step 2.3, in order to generate the compensation current of the remaining healthy phases, the compensation voltage needs to be generated on the feedforward voltage. When the phase-to-phase short-circuit fault occurs in the C and D phases, the mathematical model of the motor is determined; According to Kirchhoff's voltage law, the voltage equation of each phase winding can be obtained separately, and when the C and D phases fail, the two-phase winding must be regarded as a loop to solve:

Among them, U _xe (x=A, B, C, D, E) is the voltage drop of the winding resistance and inductance of each phase; U _x (x=A, B, C, D, E) is the phase voltage of each phase; e _x (x=A, B, C, D, E) is the back EMF of each phase; R _s is the resistance of each phase winding; L is the inductance of each phase winding; Combining the compensation current and transformation matrix of the healthy phase, the compensation voltage u _α ', u _β ' on the α-β axis can be obtained:

Similarly, determine the mathematical model of the motor when the B and E phases have a short-circuit fault, and the compensation voltage is as follows:

3. a kind of five-phase permanent magnet synchronous motor phase-to-phase short-circuit fault-tolerant control method based on multi-vector model prediction according to claim 1, is characterized in that, the calculation of the d-q axis current of feedback described in step 3 is as follows: Since the feedback current is used to generate the voltage reference value, and this process is based on the open-circuit fault-tolerant control of the five-phase motor, the current collected by the current sensor needs to remove the components of the short-circuit current, and the collected current i of each phase needs to be removed. _A , i _B , i _C , i _D , i _E are transformed to the α-β axis through Clarke matrix, and then the compensation current i _α ', i _β ' is subtracted to eliminate the composition of short-circuit current, and then transformed to dq through Park matrix The currents _{id (k), i q (} k) are obtained on the axis,

is the Park transformation matrix with missing phases C and D,

is the Clarke transformation matrix under the absence of C and D phases, if it is a short-circuit fault between adjacent phases:

4. a kind of five-phase permanent magnet synchronous motor phase-to-phase short-circuit fault-tolerant control method based on multi-vector model prediction according to claim 1, is characterized in that, in step 4, the calculation of α-β axis voltage reference value u _αref , u _βref As follows: Step 4.1, according to the deadbeat current prediction method, substitute the feedback current and current reference value into the prediction equation to obtain the dq axis voltage reference value:

Among them, u _dref , u _qref are the dq-axis reference voltage, _idref , i _qref are the dq-axis reference current, L _d , L _q are the dq-axis inductance, T _s is the sampling time, ω _e is the electrical angle frequency, _ed ( k), e _q (k) is the _dq -axis back-EMF at time k in the fault-tolerant state, id (k), i _q (k) are the current at time k; Step 4.2, according to the Park inverse matrix, the dq axis voltage reference value can be transformed to the α-β axis. At this time, the prediction is made on the basis of open circuit fault tolerance. Therefore, it is necessary to add the compensation voltage u _α ', u _β ' into it Obtain the α-β axis voltage reference values u _αref , u _βref , if it is a short-circuit fault between adjacent phases, then:

Step 4.3, according to step 2.3, the obtained α-β axis voltage reference value u _αref , u _βref contains the components of the healthy opposite potential. Taking the short-circuit fault between adjacent phases as an example, the final α-β axis voltage reference value u _αref ^* , u _βref ^* can be calculated as:

5. a kind of five-phase permanent magnet synchronous motor phase-to-phase short-circuit fault-tolerant control method based on multi-vector model prediction according to claim 1, is characterized in that, in step 5, the derivation based on the value function of voltage error is as follows: Step 5.1, the basic model predictive control idea is to sequentially substitute the candidate voltage vectors into the value function for rolling optimization, and screen out the optimal voltage vector according to the error between the current generated by the candidate voltage vector and the current reference value, and the process can be expressed as :

g=|i _dref -i _d (k+1)| ² +|i _qref -i _q (k+1)| ² Among them, u _d (k), u _q (k) are the dq-axis voltages of the candidate voltage vector at time k, and _id (k+1), i _q (k+1) are the currents at time k+1; In step 5.2, combined with the deadbeat prediction process in step 4.1, the value function based on current error can be transformed into a value function based on voltage error:

Step 5.3, if the deviation of the dq-axis inductance of the five-phase permanent magnet synchronous motor is not large, the weighting factors of the d-axis voltage error and the q-axis voltage error can be ignored, and then the value function based on the voltage error is transformed into α-β through the Park matrix On the axis, the final value function can be obtained: g=|u _αref −u _α (k)| ² +|u _βref −u _β (k)| ² . 6. a kind of five-phase permanent magnet synchronous motor phase-to-phase short-circuit fault-tolerant control method based on multi-vector model prediction according to claim 1, is characterized in that, in step 6, the concrete steps that optimal voltage vector combination is selected are as follows: In case of short-circuit fault between adjacent phases: Step 6.1, according to the Clarke transformation matrix and switching state after the two-phase missing, the vector distribution map after fault tolerance can be obtained, and the vector distribution map is divided into six sectors according to six non-zero vectors; In step 6.2, the α-β axis voltage reference value obtained in step 4.3 can determine the amplitude and phase of the reference voltage vector, and then determine the sector where the reference vector is located. Assuming that the reference vector is located in the first sector, according to the value determined in step 5.3 The function can simplify the vector selection into a mathematical problem. Find the composite vector with the smallest voltage error in the sector, that is, find the point closest to the reference vector. The vertex of the reference voltage vector can draw vertical lines to the three sides, and the shortest distance will be Produced in three perpendicular lines; Step 6.3, the vector combination can be divided into two cases, the combination of a non-zero vector and a zero vector and the combination of two non-zero vectors, the combination 1 contains the vector synthesis of U ₀ , U ₄ and U ₀ , U ₆ respectively; where r ₁ and r ₂ are the action times of the non-zero vectors U ₄ and U ₆ respectively, which can be calculated as:

Wherein, U _sref =u _αref +ju _βref is the reference voltage, θ _s =arctan(u _βref /u _αref ); Combination 2 is the vector composition of non-zero vectors U ₄ and U ₆ , and the range of the composite vector vertices is the third side of the triangle; where r ₃ and r ₄ are the action times of the non-zero vectors U ₄ and U ₆ respectively. The vector synthesis will follow the parallelogram law, which can be calculated as:

where d ₁ , d ₂ can be expressed as:

θ ₁ is the angle between d ₁ and U ₄ , and the optimal vector combination will be generated in the above combination, that is, g=min{g ₁ ,g ₂ ,g ₃ }: g ₁ =|U _sref -r ₁ U ₄ | ² g ₂ =|U _sref -r ₂ U ₆ | ² g ₃ =|U _sref -(r ₃ U ₆ +r ₄ U ₄ )| ² Among them g ₁ , g ₂ , g ₃ are the expressions of the value function in three cases.

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