Model predictive torque control method for BLDC powered by NPC three-level inverter

Abstract

The present invention proposes a BLDC model prediction torque control method powered by an NPC three-level inverter. First, the three-phase stator current at time k is obtained through a current sensor; then, the rotor position angle at time k is obtained through an encoder, and the three-phase back electromotive force at different rotor positions is calculated; then, the dq axis current prediction value at time k+1 is obtained, and the torque and flux prediction value of the dq axis at time k+1 are calculated; then, the basic voltage vector of the NPC three-level inverter with the minimum output is calculated; finally, the basic voltage vector that is more conducive to the midpoint potential balance is selected as the optimal output through the midpoint potential balance control algorithm, and the optimal output is converted into a switching signal of the NPC three-level inverter to drive the inverter. The present invention applies the model prediction torque control method to the control technology of BLDC, which can effectively improve the dynamic and steady-state performance of BLDC, realize direct control of torque to obtain torque output with smaller pulsation, and at the same time, the present invention also takes into account the balanced control of the midpoint potential.

Description

Technical Field

[0001] The present invention belongs to the field of motor drive and control, and in particular relates to a BLDC model prediction torque control method powered by an NPC three-level inverter. Background Art

[0002] Brushless direct current motor (BLDC) is a mechatronic product consisting of a motor body and a driver. It has the advantages of rapid response, large starting torque, high efficiency, and no commutation sparks. It is widely used in electric vehicles, industrial control, aerospace and other fields. Traditional BLDC control strategies mainly include square wave control, sine wave control and vector control (VC). Square wave control has a simple algorithm and low hardware cost, but has large torque fluctuations and low efficiency; sine wave control has low torque fluctuations and current harmonics, but cannot maximize the efficiency of the motor; and VC has the advantages of small torque fluctuations and high efficiency, but the algorithm is complex and highly dependent on motor parameters. Therefore, in order to further improve the performance of BLDC control systems, a model predictive control (MPC) has received widespread attention from researchers.

[0003] In the field of motor control, MPC is mainly divided into model predictive current control (MPCC) and model predictive torque control (MPTC). The value function of MPCC takes current as the direct controlled object, which has the advantages of simple algorithm and good control effect on current, but there is still large torque pulsation. MPTC obtains the optimal torque and flux control vector by solving the value function containing torque and flux in real time, and combines the control idea of ​​online optimization. Therefore, it can effectively improve the dynamic response of the system and reduce torque pulsation. However, MPTC is currently mainly used in AC motors such as permanent magnet synchronous motors and asynchronous motors. How to apply MPTC to BLDC to obtain better control performance deserves in-depth study. Summary of the invention

[0004] Technical problem: In view of the above technical background, a BLDC model prediction torque control method powered by an NPC three-level inverter is proposed. First, the three-phase stator current at time k is obtained through a current sensor; then, the rotor position angle at time k is obtained through an encoder, and the three-phase back electromotive force at different rotor positions is calculated; then, the dq axis current prediction value at time k+1 is obtained, and the torque and flux prediction value of the dq axis at time k+1 are calculated; then, the basic voltage vector of the NPC three-level inverter with the smallest output is calculated; finally, the basic voltage vector that is more conducive to the midpoint potential balance is selected as the optimal output through the midpoint potential balance control algorithm, and the optimal output is converted into a switching signal of the NPC three-level inverter to drive the inverter. The MPTC algorithm can be used to further reduce the torque pulsation of the BLDC and improve the dynamic response performance of the system, while taking into account the midpoint potential balance of the NPC three-level inverter. The present invention applies the model prediction torque control method to the control technology of BLDC, which can effectively improve the dynamic and steady-state performance of the BLDC, realize direct control of the torque to obtain a torque output with less pulsation, and at the same time, the present invention also takes into account the balanced control of the midpoint potential.

[0005] Technical solution: A BLDC model predictive torque control method powered by an NPC three-level inverter includes the following steps:

[0006] Step 1: Obtain the reference value T of the electromagnetic torque according to the speed loop PI controller e ref ;

[0007] Step 2: Get the electrical angle θ and electrical angular velocity ω of BLDC from the encoder e , and then measure the three-phase stator current i at time k through the current sensor x (k) and calculate the three-way back electromotive force e at different rotor positions x (k)(x=a,b,c), and then through Clark-Park transformation, the dq-axis component i of the stator current at time k is obtained d (k), i q (k) and the dq-axis component of the back electromotive force e d (k), e q (k);

[0008] Step 3: The electrical angle θ and electrical angular velocity ω measured by the encoder e According to the table of back electromotive force at different rotor positions, the three-phase back electromotive force e is obtained. x (k)(x=a,b,c), the back electromotive force e of the dq axis at time k is obtained after calculation d (k) and e q (k);

[0009] Step 4: Obtain the predicted values ​​of electromagnetic torque and stator flux at time k+1;

[0010] Step 5, obtaining a process of minimizing the cost function to output a basic voltage vector that minimizes the cost function;

[0011] Step 6: Obtain a balanced control algorithm combined with the midpoint potential to obtain the optimal switching state of the inverter.

[0012] Furthermore, the specific process of step one is as follows:

[0013] The reference speed N r ref The actual speed N measured by the encoder r The difference between n Input the speed PI controller and obtain the electromagnetic torque reference value T according to formula (1): e ref ;

[0014]

[0015] Among them, k p and k i are the proportional gain and integral gain of the speed PI controller respectively, and s is a complex variable.

[0016] Furthermore, the specific process of step 2 is as follows:

[0017] The electrical angle θ of the BLDC is obtained from the encoder and the electrical angular velocity ω is calculated using the differential equation shown in formula (2). e ; Then the three-phase stator current i of BLDC at time k is measured by the current sensor x (k)(x=a,b,c), and then the stator current component i of the αβ axis at time k is obtained by the Clark transformation shown in formula (3): α (k) and i β (k), and after Park transformation of formula (4), the stator current component i of the dq axis at time k is obtained d (k) and i q (k);

[0018]

[0019]

[0020]

[0021] Furthermore, in step 3, the back electromotive force e of the dq axis at time k is obtained. d (k) and e q The method for obtaining (k) is as follows:

[0022] The back electromotive force e under the dq coordinate at time k d (k) and e q The method for obtaining (k) is as follows: first, the electrical angle θ and electrical angular velocity ω measured by the encoder are e Combined with Table 1, calculate the three-phase back electromotive force e at different rotor positions x (k)(x=a,b,c); Then, the back electromotive force e of the αβ axis at time k is obtained by Clark transformation of formula (5): α (k) and e β (k); Finally, the back electromotive force e at the dq coordinate at time k is obtained by Park transformation of formula (6) d (k) and e q (k);

[0023] Table 1 Back EMF at different rotor positions

[0024] Rotor position <![CDATA[e a ]]> <![CDATA[e b ]]> <![CDATA[e c ]]> 0～π / 3 <![CDATA[m*ω e ]]> <![CDATA[-m*ω e ]]> <![CDATA[m*ω e *(-θ / (π / 6)+1)]]> π / 3～2π / 3 <![CDATA[m*ω e ]]> <![CDATA[m*ω e *((θ-π / 3) / (π / 6)-1)]]> <![CDATA[-m*ω e ]]> 2π / 3～π <![CDATA[m*ω e *((2π / 3-θ) / (π / 6)+1)]]> <![CDATA[m*ω e ]]> <![CDATA[-m*ω e ]]> π～4π / 3 <![CDATA[-m*ω e ]]> <![CDATA[m*ω e ]]> <![CDATA[m*ω e *((θ-π) / (π / 6)-1)]]> 4π / 3～5π / 3 <![CDATA[-m*ω e ]]> <![CDATA[m*ω e *((4π / 3-θ) / (π / 6)+1)]]> <![CDATA[m*ω e <!-- 2 -->]]> 5π / 3～2π <![CDATA[m*ω e *((θ-5π / 3) / (π / 6)-1)]]> <![CDATA[-m*ω e ]]> <![CDATA[m*ω e ]]>

[0025]

[0026]

[0027] Where m = 2pψ f , p represents the number of pole pairs, ψ f Represents the flux linkage of a permanent magnet.

[0028] Furthermore, the calculation method of obtaining the predicted values ​​of the electromagnetic torque and stator flux at time k+1 in step 4 is as follows:

[0029] The calculation method of the electromagnetic torque and stator flux prediction value at the k+1 moment is as follows: first, the current differential equation shown in formula (9) is discretized according to the first-order Euler equation shown in formula (7), and then the stator voltage equation under the dq coordinate at the k moment shown in formula (8) is combined to obtain the prediction equation of the stator current at the k+1 moment shown in formula (10); then, the electromagnetic torque T at the k+1 moment is calculated according to the electromagnetic torque prediction equation shown in formula (11): e (k+1); Finally, the predicted flux value ψ in dq coordinates is calculated according to formula (12): d (k+1) and ψ q (k+1), and then calculate the predicted flux amplitude ψ at time k+1 by formula (13) s (k+1);

[0030]

[0031]

[0032]

[0033]

[0034]

[0035]

[0036]

[0037] Among them, y(k+1) and y(k) represent the states at time k+1 and time k; U dc Indicates the DC bus voltage of the inverter; S x (i) represents the switching state of the inverter (i=1,2,…,27; S x (i) = -1, 0, 1; x = a, b, c); u α (k) and u β (k) represents the stator voltage component of the αβ axis; u d (k) and u q (k) represents the stator voltage component of the dq axis; T s represents sampling time; R represents stator resistance; L s represents the stator inductance; n p Indicates the number of pole pairs of the motor; ψ f Represents the flux linkage of a permanent magnet.

[0038] Furthermore, the method of obtaining the process of minimizing the cost function to output the basic voltage vector that minimizes the cost function in step 5 is as follows:

[0039] First, let the output T of formula (1) at time k be e ref =T e ref(k+1) is used as the torque reference of the value function, and the permanent magnet flux ψ f =ψ s ref (k+1) is used as the magnetic link reference of the value function; then, T e ref (k+1),ψ s ref(k+1),T e (k+1) and ψ s (k+1) is sent to the value function (14) to calculate the value function output g under different i i ; Then use formula (15) to obtain the minimum value function output g min ; The final output satisfies g min The basic voltage vector u opt (u optThe corresponding switch state is S x (g_min), g_min means min{g i} subscript);

[0040]

[0041] g min =min{g i},i=1,2,...,27 (15).

[0042] Furthermore, the method for obtaining the optimal switching state of the inverter in step 6 is specifically as follows:

[0043] The method for obtaining the optimal switching state of the inverter by combining the balance control algorithm of the midpoint potential is as follows: firstly, the voltage vector u obtained in step 5 is determined. opt Is it a small vector? If it is not a small vector, the midpoint potential balance control is not performed and u is directly opt The corresponding switch state is sent to the inverter to drive the motor; if it is a small vector, the current midpoint potential U is detected 0 Status (U 0 It can be expressed as the difference between the lower capacitor voltage and the upper capacitor voltage, U 0 >0 means the midpoint potential is high, U 0 <0 means the midpoint potential is low), and then the switch state S is calculated according to formula (16) x The midpoint current i under the action of (g_min) np , and judge U 0 *i np >=0 is true, if true, use S x (g_min) is used as the final control inverter switching state, otherwise u opt The switch state corresponding to the redundant vector is used as the control output of the inverter;

[0044]

[0045] Beneficial effects: The present invention is based on a brushless DC motor powered by a diode neutral-point-clamped (NPC) three-level inverter. By predicting the torque and flux state at the next moment, a value function with electromagnetic torque and stator flux as control variables is constructed to obtain the optimal control vector of electromagnetic torque and stator flux. Therefore, better torque control performance can be obtained. At the same time, combined with the characteristic that a pair of redundant small vectors have opposite mid-point potential effects, the balance of mid-point potential is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1A schematic diagram of the BLDC model predictive torque control for powering the NPC three-level inverter provided by the present invention;

[0047] Figure 2 A flow chart of the BLDC model prediction torque control for powering the NPC three-level inverter provided by the present invention;

[0048] Figure 3 Steady-state simulation diagram of BLDC model predictive control for powering NPC three-level inverter, Figure 3 (a) is the steady-state performance simulation of the MPCC algorithm. Figure 3 (b) is the steady-state performance simulation of the MPTC algorithm;

[0049] Figure 4 Simulation diagram of midpoint potential balance for BLDC model predictive torque control powering an NPC three-level inverter. DETAILED DESCRIPTION

[0050] The present invention will be further described in detail below with reference to the accompanying drawings and by way of examples. The following examples are intended to explain the present invention but the present invention is not limited to the following examples.

[0051] The schematic diagram of a method for model predictive torque control of BLDC powered by NPC three-level inverter is as follows: Figure 1 As shown, it includes a speed loop PI controller module 1, a minimization value function module 2, a midpoint potential balancing module 3, an NPC three-level inverter module 4, a brushless DC motor module 5, an encoder module 6, a coordinate transformation module 7 and an electromagnetic torque and stator flux prediction module 8. The NPC three-level inverter module 4 is directly connected to the brushless DC motor module 5 to control the rotation of the motor. The encoder module 6 collects the operation information of the brushless DC motor module 5 and transmits the data to the speed loop PI controller module 1, the coordinate transformation module 7, and the electromagnetic torque and stator flux prediction module 8; the coordinate transformation module 7 receives the data transmitted by the encoder, and also collects the stator information of the brushless DC motor module 5, and transmits the data to the electromagnetic torque and stator flux prediction module 8 after processing. The electromagnetic torque and stator flux prediction module 8 processes the transmitted information and transmits it to the minimization value function module 2. The minimization value function module 2 also receives the information sent by the speed loop PI controller module 1. The minimization value function module 2 processes the data and transmits it to the midpoint potential balancing module 3; the midpoint potential balancing module 3 directly sends the processed data to the NPC three-level inverter module 4.

[0052] like Figure 2 As shown, the method comprises the following steps:

[0053] Step 1: Obtain the reference value T of the electromagnetic torque according to the speed loop PI controller eref :

[0054] The reference speed N r ref The actual speed N measured by the encoder r The difference between n Input the speed PI controller and obtain the electromagnetic torque reference value T according to formula (1): e ref ;

[0055]

[0056] Among them, k p and k i are the proportional gain and integral gain of the speed PI controller respectively, and s is a complex variable.

[0057] Step 2: Obtain the BLDC electrical angle θ from the encoder and calculate the electrical angular velocity ω using the differential equation shown in formula (2) e ; Then the three-phase stator current i of BLDC at time k is measured by the current sensor x (k)(x=a,b,c), and the stator current component i of the αβ axis at time k is obtained after the Clark transformation shown in formula (3) α (k) and i β (k), and the stator current component i of the dq axis at time k is obtained by Park transformation of formula (4): d (k) and i q (k);

[0058]

[0059]

[0060]

[0061] Step 3: Back EMF e of dq axis at time k d (k) and e q (k) Acquisition method:

[0062] First, the electrical angle θ and electrical angular velocity ω measured by the encoder e According to Table 1, calculate the three-phase back electromotive force e at different rotor positions x (k)(x=a,b,c); Then, the back electromotive force e of the αβ axis at time k is obtained by Clark transformation of formula (5): α (k) and e β (k); Finally, the back electromotive force e at the dq coordinate at time k is obtained by Park transformation of formula (6) d (k) and e q (k).

[0063] Table 1 Back EMF at different rotor positions

[0064] Rotor position <![CDATA[e a ]]> <![CDATA[e b ]]> <![CDATA[e c ]]> 0～π / 3 <![CDATA[m*ω e ]]> <![CDATA[-m*ω e ]]> <![CDATA[m*ω e *(-θ / (π / 6)+1)]]> π / 3～2π / 3 <![CDATA[m*ω e ]]> <![CDATA[m*ω e *((θ-π / 3) / (π / 6)-1)]]> <![CDATA[-m*ω e ]]> 2π / 3～π <![CDATA[m*ω e *((2π / 3-θ) / (π / 6)+1)]]> <![CDATA[m*ω e ]]> <![CDATA[-m*ω e ]]> π～4π / 3 <![CDATA[-m*ω e ]]> <![CDATA[m*ω e ]]> <![CDATA[m*ω e *((θ-π) / (π / 6)-1)<!-- 5 --> ]]> 4π / 3～5π / 3 <![CDATA[-m*ω e ]]> <![CDATA[m*ω e *((4π / 3-θ) / (π / 6)+1)]]> <![CDATA[m*ω e ]]> 5π / 3～2π <![CDATA[m*ω e *((θ-5π / 3) / (π / 6)-1)]]> <![CDATA[-m*ω e ]]> <![CDATA[m*ω e ]]>

[0065]

[0066]

[0067] Where m = 2pψ f , p represents the number of pole pairs, ψ f Represents the flux linkage of a permanent magnet.

[0068] Step 4: Calculation method of electromagnetic torque and stator flux prediction at time k+1:

[0069] First, the current differential equation shown in formula (9) is discretized according to the first-order Euler equation shown in formula (7), and then the stator voltage equation under the dq coordinates at time k shown in formula (8) is combined to obtain the prediction equation of the stator current at time k+1 shown in formula (10); then, the electromagnetic torque T at time k+1 is calculated according to the electromagnetic torque prediction equation shown in formula (11): e (k+1); Finally, the predicted flux value ψ in dq coordinates is calculated according to formula (12): d (k+1) and ψ q (k+1), and then calculate the predicted flux amplitude ψ at time k+1 by formula (13) s (k+1).

[0070]

[0071]

[0072]

[0073]

[0074]

[0075]

[0076]

[0077] Where y(k+1) and y(k) represent the states at time k+1 and time k; T s Indicates the sampling time; U dc Indicates the DC bus voltage of the inverter; S x (i) represents the switching state of the inverter (i=1,2,…,27; S x(i) = -1, 0, 1; x = a, b, c); u α (k) and u β (k) represents the stator voltage component of the αβ axis; u d (k) and u q (k) represents the stator voltage component of the dq axis; R represents the stator resistance; L s represents the stator inductance; n p Indicates the number of pole pairs of the motor; ψ f Represents the flux linkage of a permanent magnet.

[0078] Step 5: Minimize the cost function process to output the basic voltage vector method that minimizes the cost function:

[0079] First, let the output T of formula (1) at time k be e ref =T e ref (k+1) is used as the torque reference of the value function, and the permanent magnet flux ψ f =ψ s ref (k+1) is used as the magnetic link reference of the value function; then, T e ref (k+1),ψ s ref (k+1), T e (k+1) and ψ s (k+1) is sent to the value function (14) to calculate the value function output g under different i i ; Then use formula (15) to obtain the minimum value function output g min ; The final output satisfies g min The basic voltage vector u opt (u opt The corresponding switch state is S x (g_min), g_min means min{g i}).

[0080]

[0081] g min =min{g i},i=1,2,...,27 (15)

[0082] Step 6: A method for obtaining the optimal switching state of the inverter by combining the balance control algorithm of the midpoint potential:

[0083] First, determine the voltage vector u obtained in step 5 opt Is it a small vector? If it is not a small vector, the midpoint potential balance control is not performed and u is directlyopt The corresponding switch state is sent to the inverter to drive the motor; if it is a small vector, the current midpoint potential U is detected 0 Status (U 0 It can be expressed as the difference between the lower capacitor voltage and the upper capacitor voltage, U 0 >0 means the midpoint potential is high, U 0 <0 means the midpoint potential is low), and then the switch state S is calculated according to formula (16) x The midpoint current i under the action of (g_min) np , and judge U 0 *i np >=0 is true, if true, use S x (g_min) is used as the final control inverter switching state, otherwise u opt The switching state corresponding to the redundant vector is used as the control output of the inverter.

[0084]

[0085] The method of the present invention first obtains the stator three-phase current i at time k through a current sensor. x (k), obtain the rotor electrical angle θ and rotor electrical angular velocity ω through the encoder e , and input the given speed N r ref and permanent magnet flux ψ f , and then calculate the three-phase back electromotive force e x (k)(x=a,b,c); then the reference value T of the electromagnetic torque at time k+1 is calculated by the speed PI regulator e ref (k+1); then the electromagnetic torque and stator flux prediction module is used to calculate the predicted value T of the electromagnetic torque and stator flux at time k+1 e (k+1) and ψ s (k+1); then output the minimized value function g through rolling optimization min And get the corresponding basic voltage vector u opt ; Finally, the optimal inverter switching state is output through the midpoint potential balance control module.

[0086] The steady-state performance simulation results of the BLDC model predictive control powered by the NPC three-level inverter are shown in Figure 3 As shown, it can be seen Figure 3 The BLDC model predictive control algorithm shown in (a) and 3(b) can obtain a three-phase current waveform with a high sinusoidal degree and a smooth speed waveform, but Figure 3 The MPTC algorithm in (b) can achieve smaller torque ripple. Figure 4This is a simulation diagram of the midpoint potential balance of the NPC three-level inverter. It can be seen that the midpoint potential can be effectively suppressed near 0V.

[0087] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A BLDC model predictive torque control method powered by an NPC three-level inverter, characterized in that: The steps include: Step 1: Obtain the reference value T of the electromagnetic torque according to the speed loop PI controller e ref ; Step 2: Get the electrical angle θ and electrical angular velocity ω of BLDC from the encoder e , and then measure the three-phase stator current i at time k through the current sensor x (k) and calculate the three-way back electromotive force e at different rotor positions x (k)(x=a,b,c), and then through Clark-Park transformation, the dq-axis component i of the stator current at time k is obtained d (k), i q (k) and the dq-axis component of the back electromotive force e d (k), e q (k); Step 3: The electrical angle θ and electrical angular velocity ω measured by the encoder e According to the table of back electromotive force at different rotor positions, the three-phase back electromotive force e is obtained. x (k)(x=a,b,c), the back electromotive force e of the dq axis at time k is obtained after calculation d (k) and e q (k); In step 3, the back electromotive force e of the dq axis at time k is obtained. d (k) and e q The method for obtaining (k) is as follows: The back electromotive force e under the dq coordinate at time k d (k) and e q The method for obtaining (k) is as follows: first, the electrical angle θ and electrical angular velocity ω measured by the encoder are e Combined with Table 1, calculate the three-phase back electromotive force e at different rotor positions x (k)(x=a,b,c); Then, the back electromotive force e of the αβ axis at time k is obtained by Clark transformation of formula (5): α (k) and e β (k); Finally, the back electromotive force e at the dq coordinate at time k is obtained by Park transformation of formula (6) d (k) and e q (k); Table 1 Back EMF at different rotor positions Where m = 2pψ f , p represents the number of pole pairs, ψ f represents the flux linkage of permanent magnet; Step 4: Obtain the predicted values ​​of electromagnetic torque and stator flux at time k+1; The calculation method of obtaining the electromagnetic torque and stator flux prediction value at time k+1 in step 4 is as follows: The calculation method of the electromagnetic torque and stator flux prediction value at the k+1 moment is as follows: first, the current differential equation shown in formula (9) is discretized according to the first-order Euler equation shown in formula (7), and then the stator voltage equation under the dq coordinate at the k moment shown in formula (8) is combined to obtain the prediction equation of the stator current at the k+1 moment shown in formula (10); then, the electromagnetic torque T at the k+1 moment is calculated according to the electromagnetic torque prediction equation shown in formula (11): e (k+1); Finally, the predicted flux value ψ in dq coordinates is calculated according to formula (12): d (k+1) and ψ q (k+1), and then calculate the predicted flux amplitude ψ at time k+1 by formula (13) s (k+1); Among them, y(k+1) and y(k) represent the states at time k+1 and time k; U dc Indicates the DC bus voltage of the inverter; S x (i) represents the switching state of the inverter (i=1,2,…,27; S x (i) = -1, 0, 1; x = a, b, c); u α (k) and u β (k) represents the stator voltage component of the αβ axis; u d (k) and u q (k) represents the stator voltage component of the dq axis; T s represents sampling time; R represents stator resistance; L s represents the stator inductance; n p Indicates the number of pole pairs of the motor; ψ f represents the flux linkage of permanent magnet; Step 5, obtaining a process of minimizing the cost function to output a basic voltage vector that minimizes the cost function; The method of obtaining the process of minimizing the cost function to output the basic voltage vector that minimizes the cost function in step 5 is as follows: First, let the output T of formula (1) at time k be e ref =T e ref (k+1) is used as the torque reference of the value function, and the permanent magnet flux ψ f =ψ s ref (k+1) is used as the magnetic link reference of the value function; then, T e ref (k+1),ψ s ref (k+1), T e (k+1) and ψ s (k+1) is sent to the value function (14) to calculate the value function output g under different i i ; Then use formula (15) to obtain the minimum value function output g min ; The final output satisfies g min The basic voltage vector u opt (u opt The corresponding switch state is S x (g_min), g_min means min{g i } subscript); g min =min{g i },i=1,2,...,27 (15); Step 6: Obtain the optimal switching state of the inverter by obtaining a balanced control algorithm combined with the midpoint potential; The method for obtaining the optimal switching state of the inverter in step 6 is specifically as follows: The method for obtaining the optimal switching state of the inverter by combining the balance control algorithm of the midpoint potential is: firstly determine the voltage vector u obtained in step 5 opt Is it a small vector? If it is not a small vector, the midpoint potential balance control is not performed and u is directly opt The corresponding switch state is sent to the inverter to drive the motor; if it is a small vector, the current midpoint potential U0 is detected (U0 can be expressed as the difference between the lower capacitor voltage and the upper capacitor voltage, U0>0 indicates that the midpoint potential is high, and U0<0 indicates that the midpoint potential is low), and then the switch state S is calculated according to formula (16) x The midpoint current i under the action of (g_min) np , and judge U0*i np >=0 is true, if true, use S x (g_min) is used as the final control inverter switching state, otherwise u opt The switch state corresponding to the redundant vector is used as the control output of the inverter; 2. The BLDC model predictive torque control method powered by an NPC three-level inverter according to claim 1, characterized in that: The specific process of step one is as follows: The reference speed N r ref The actual speed N measured by the encoder r The difference between n Input the speed PI controller and obtain the electromagnetic torque reference value T according to formula (1): e ref ; Among them, k p and k i are the proportional gain and integral gain of the speed PI controller respectively, and s is a complex variable.

3. The BLDC model predictive torque control method powered by an NPC three-level inverter according to claim 1, characterized in that: The specific process of step 2 is as follows: The electrical angle θ of the BLDC is obtained from the encoder and the electrical angular velocity ω is calculated using the differential equation shown in formula (2). e ; Then the three-phase stator current i of BLDC at time k is measured by the current sensor x (k)(x=a,b,c), and then the stator current component i of the αβ axis at time k is obtained by the Clark transformation shown in formula (3): α (k) and i β (k), and after Park transformation of formula (4), the stator current component i of the dq axis at time k is obtained d (k) and i q (k);

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