WO2024065986A1 - 一种双三相电机高精度模型预测电流控制系统及控制方法 - Google Patents

一种双三相电机高精度模型预测电流控制系统及控制方法 Download PDF

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WO2024065986A1
WO2024065986A1 PCT/CN2022/132829 CN2022132829W WO2024065986A1 WO 2024065986 A1 WO2024065986 A1 WO 2024065986A1 CN 2022132829 W CN2022132829 W CN 2022132829W WO 2024065986 A1 WO2024065986 A1 WO 2024065986A1
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voltage vector
module
current
vector
phase
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PCT/CN2022/132829
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English (en)
French (fr)
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赵文祥
崔佳
吉敬华
黄林森
杜育轩
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江苏大学
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Priority to GB2314081.7A priority Critical patent/GB2623189A/en
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • 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
    • H02P29/00—Arrangements for regulating or controlling electric motors, appropriate for both AC and DC motors
    • H02P29/02—Providing protection against overload without automatic interruption of supply
    • H02P29/024—Detecting a fault condition, e.g. short circuit, locked rotor, open circuit or loss of load
    • H02P29/028—Detecting a fault condition, e.g. short circuit, locked rotor, open circuit or loss of load the motor continuing operation despite the fault condition, e.g. eliminating, compensating for or remedying the fault
    • 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
    • H02P6/10—Arrangements for controlling torque ripple, e.g. providing reduced torque ripple
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P6/00—Arrangements for controlling synchronous motors or other dynamo-electric motors using electronic commutation dependent on the rotor position; Electronic commutators therefor
    • H02P6/28—Arrangements for controlling current

Definitions

  • the present invention belongs to the technical field of multi-phase motor predictive control, and in particular relates to a high-precision model predictive current control system and a control method for a dual three-phase motor.
  • Multiphase permanent magnet motors have the advantages of high power density, high efficiency, and good fault tolerance, and have become the first choice for advanced motor systems.
  • the dual three-phase permanent magnet synchronous motor with center point isolation and two sets of windings connected with a phase shift of 30° has been widely used due to its special structure, which eliminates six torque pulsations.
  • the model predictive control strategy has good performance in power converter applications due to its advantages of multivariable control, easy handling of nonlinear constraints, and intuitive and easy implementation, and gradually reflects good engineering application value.
  • it has the disadvantages of large calculation amount and high torque pulsation.
  • the Chinese invention patent "A low-computation model predictive torque control method for dual-motor series system” discloses a low-computation model predictive control method, which only needs to calculate the value function of two voltage vectors, which relatively reduces the calculation amount, but the method needs to calculate the position of the reference voltage vector, so two observers are added, making the system complicated.
  • the Chinese invention patent "A model predictive control method for reducing PMSM torque pulsation and flux fluctuation” discloses a method for reducing the torque pulsation and flux pulsation of a permanent magnet synchronous motor. This method uses multiple voltage vectors in a single cycle to broaden the modulation range.
  • the calculation is complex.
  • the model predictive control algorithm When the model predictive control algorithm is applied to the field of multi-phase motors, its alternative voltage vectors also increase exponentially, and the amount of calculation is relatively increased.
  • the multi-phase motor contains a harmonic plane, which must be controlled during the operation of the system, otherwise it will be detrimental to the performance of the motor and will produce large losses. Therefore, in order to enhance the application of model predictive control in the field of multi-phase motors, it is urgently necessary to carry out relevant research on reducing the computational burden of the algorithm, or related technologies combined with improving torque and flux pulsation.
  • the control set is redesigned.
  • the traditional 12 virtual voltage vector control set is expanded, and 24 virtual voltage vectors with equal amplitude and uniform phase angle are designed without losing voltage utilization to improve control accuracy.
  • a duty cycle calculation method based on minimum error is proposed, which can simultaneously track the current of the d-axis and q-axis even in the case of a single valid virtual voltage vector to ensure the output of the optimal duty cycle.
  • the process of traversing all voltage vectors in predictive control is simplified to reduce the computational burden of the algorithm.
  • the present invention strongly improves the accuracy of model predictive control by expanding the control set and reducing the duty cycle calculation error, reduces the 5th and 7th harmonics, and improves torque pulsation. It also ensures that even under the action of 24 voltage vectors, the amount of calculation is still low, thereby improving the execution efficiency of the algorithm.
  • a dual three-phase motor high-precision model prediction current control system including system hardware and system software (implemented in programming), the system hardware includes dual three-phase permanent magnet motor, DC power supply, PWM module, inverter, position sensor, current sensor; the system software includes: synthetic 24 virtual voltage vector module, speed controller, coordinate conversion module, delay module, prediction module, duty cycle calculation module, simplification module and value function module;
  • the dual three-phase permanent magnet motor is composed of two sets of three-phase windings with a spatial phase shift of 30°; the inverter input end is connected to a DC power supply, and the inverter signal end is connected to a PWM module; the inverter is a six-phase two-level topology structure, and the inverter output end is connected to the dual three-phase motor A, B, C, D, E, and F phases, responsible for converting the PWM signal into the six-phase sinusoidal alternating current required to drive the motor; the position sensor adopts a rotary transformer, which is coaxially connected to the dual three-phase permanent magnet motor, and the current sensor is connected to the inverter, responsible for sampling the six-phase current of the motor;
  • the coordinate conversion module has an input end connected to a current sensor and an output end connected to a delay compensation module, and is used to convert the six-phase current in the natural coordinate system into the current in the rotating coordinate system to achieve decoupling control;
  • the input end of the delay module is connected to the coordinate transformation module, and the output end is connected to the prediction model to compensate for the "one-shot delay" problem caused by digital system sampling;
  • the input end of the prediction model module is connected to the delay compensation module, the 24 virtual voltage vector module and the position sensor, and is responsible for outputting the position change of the dq axis current under the action of different voltage vectors;
  • the speed controller is controlled by PI to obtain the q-axis reference current, the input of which is the error between the given speed and the actual speed, and the output of which is the reference value of the q-axis current;
  • the input end of the duty cycle calculation module is connected to the speed controller and the prediction model module to calculate the position of the optimal voltage vector and its duty cycle under the action of each voltage vector;
  • the input ends of the simplification module and the value function module are connected to the duty cycle calculation module to reduce the number of iterations of the algorithm and select the optimal vector and its duty cycle; the input end of the PWM module is connected to the value function module to convert the optimal vector and duty cycle obtained by the software system into a corresponding PWM signal, which is output to the inverter to complete the modulation, thereby driving the motor to operate.
  • a control method for a high-precision model prediction current control system for a dual three-phase motor comprises the following steps:
  • Step 1) constructing 24 virtual voltage vectors
  • Step 2) optimizing the switching order of the voltage vector to standardize it
  • Step 3) obtaining the rotation speed and position angle through the position sensor, obtaining the six-phase current through the current sensor, and then obtaining the current in the rotating coordinate system through the coordinate transformation module;
  • Step 4) deriving a prediction model for a dual three-phase permanent magnet motor
  • Step 5 Calculate the duty cycle of the voltage vector action using the minimum error method
  • Step 6 Simplify the traversal optimization process
  • Step 7) The optimal voltage vector and its duty cycle are selected through the value function and output to the PWM module.
  • the corresponding voltage vector is output through inverter modulation to complete the entire control.
  • step 1) includes:
  • the 64 voltage vectors corresponding to the conversion switch are determined by the following formula:
  • a e j30°
  • s A ⁇ s F represent the switch state of each bridge arm respectively
  • u ⁇ represents the voltage vector of the ⁇ plane
  • u xy represents the voltage vector of the xy plane
  • U dc represents the DC bus voltage
  • the upper bridge arm is turned on as "1”
  • the upper bridge arm is turned off as "0”
  • the basic voltage vector is numbered in the order of ABC and DEF
  • the switch state combination is represented in octal
  • the virtual voltage vector principle requires that the sum of the effects of the vector on the harmonic plane is zero.
  • the synthesis principle is as follows:
  • Di represents the duty cycle of each basic voltage vector
  • the 12 large vectors and 1 zero vector on the outermost edge of the fundamental wave plane are selected as the basic voltage vectors of the synthetic virtual voltage vector.
  • the adjacent three-vector principle is used to synthesize a new virtual voltage vector control set. The synthesis principle is as follows:
  • each basic voltage vector is 0.59Udc
  • the starting position is 0°
  • the angle between two adjacent voltage vectors is 15°
  • 24 virtual voltage vectors are synthesized in the ⁇ plane, whose component in the xy plane is zero.
  • step 2) includes:
  • the switching order of the synthesized 24 virtual voltage vectors is optimized to make them all standardized.
  • the inner and outer two-layer voltage vector synthesis method is used at V 2 , V 6 , V 10 , V 14 , V 18 and V 22 instead of the adjacent three-vector synthesis method.
  • the final synthesized 24 virtual voltage vectors are shown in Table 1;
  • u 1 , ...u 0 , ...u 11 , ...u 66 , ...u 12 , ...u 64 respectively represent corresponding basic voltage vectors.
  • step 3 includes:
  • the position sensor measures the angular displacement and angular velocity of the rotor shaft, converts it into an electrical signal and transmits it to the controller, which obtains the motor speed and rotor position angle information after decoding;
  • the phase currents of the motor sampled by 6 current sensors are recorded as: iA , iB , iC , iD , iE and iF .
  • the VSD coordinate transformation method is used to transform the variables of the natural coordinate system into the stationary coordinate system.
  • the transformation matrix is:
  • i ⁇ , i ⁇ , i x , i y , i o1 and i o2 represent the currents of the ⁇ -axis, ⁇ -axis, x-axis, y-axis, o1-axis and o2-axis of the stationary coordinate system;
  • ⁇ is the rotor position angle
  • i d and i q are the currents of the d-axis and q-axis respectively;
  • the coordinate conversion module calculates the current i dq (k) of the motor at time k in the dq rotating coordinate system.
  • step 4 includes:
  • the harmonic plane can be ignored, so only the relevant variables of the dual three-phase permanent magnet motor in the fundamental wave plane need to be considered and converted into the rotating coordinate system to obtain the voltage equation of the motor:
  • ud and q are the components of Us in the d-axis and q-axis respectively
  • Rs is the stator resistance
  • Ld , Lq , id and iq are the dq-axis inductance and current respectively
  • ⁇ f is the permanent magnet flux amplitude
  • ⁇ e is the electrical angular velocity
  • the superscript "k” represents the real-time value of the dq axis current and voltage at time k; the superscript "k+1” represents the predicted value of the dq axis current at time k+1; Ts is the control period;
  • the superscript “pre” indicates the final predicted value of the dq axis current
  • the value function is defined as:
  • step 5 includes:
  • the optimal duty cycle of the voltage vector can be obtained as:
  • step 6 includes:
  • the ⁇ plane is divided into four equal regions with V 4 , V 10 , V 16 , and V 22 as boundaries, and named G 1 , G 2 , G 3 , and G 4 ;
  • V 1 , V 7 , V 13 and V 19 Substitute V 1 , V 7 , V 13 and V 19 into (5) to obtain the values of the cost functions of the four voltage vectors: J(V 1 ), J(V 7 ), J(V 13 ), J(V 19 ); select the vector V 1st with the smallest cost function, and then determine the optimal region;
  • step 7) include: bringing the 24 virtual voltage vectors VV into the prediction model one by one, selecting the optimal voltage vector and its duty cycle through the simplified module, outputting them to the PWM module, modulating them through the inverter, outputting the corresponding voltage vector, and completing the entire control.
  • the present invention provides a dual three-phase motor high-precision model prediction current control system and control method, which increases the number of traditional 12 virtual voltage vectors to 24, thereby broadening the modulation range without sacrificing voltage utilization.
  • the duty cycle solution method proposed in the present invention considers the d-axis and q-axis tracking currents at the same time, reduces the minimum error, and the value function obtained is also the smallest among all value functions, thereby improving the control accuracy.
  • the amplitude of each voltage vector can be flexibly changed, which improves the control accuracy, reduces the 5th and 7th harmonics, and improves the torque pulsation and flux pulsation.
  • the simplified vector selection method proposed in the present invention reduces the execution time of the model predictive control algorithm, improves the efficiency of the algorithm, and can be extended to other multi-phase motor predictive control systems.
  • FIG1 is a schematic diagram of the control principle of the method according to an embodiment of the present invention.
  • FIG2 is a topological structure diagram of a six-phase voltage source inverter using a method according to an embodiment of the present invention
  • FIG3 is a spatial voltage vector diagram of the present invention. (a) ⁇ plane; (b) xy plane;
  • FIG4 is a schematic diagram of the maximum three-vector virtual voltage vector structure designed by the present invention. (a) ⁇ plane; (b) xy plane;
  • FIG5 is a switching sequence diagram designed by the present invention; (a) before V 2 correction; (b) after V 2 correction;
  • FIG6 is a schematic diagram of the structure of the inner and outer two-layer virtual voltage vector designed by the present invention. (a) ⁇ plane; (b) xy plane;
  • FIG7 is a 24 virtual voltage vector designed by the present invention.
  • FIG8 is a schematic diagram of a method for calculating a minimum duty cycle error proposed by the present invention.
  • FIG9 is a simplified schematic diagram of the design process of the present invention.
  • (a) is a schematic diagram of region division;
  • (b) is a schematic diagram of the optimal region;
  • (c) is a schematic diagram of the optimal voltage vector;
  • FIG10 is an experimental waveform diagram of a conventional 12-bit virtual voltage vector under the effect of a deadbeat duty cycle
  • FIG11 is an experimental waveform diagram of the present invention.
  • Figure 1 is a schematic diagram of the control box principle of the present invention, and its control system hardware includes: dual three-phase permanent magnet motor, DC power supply, PWM module, inverter, position sensor, current sensor.
  • the control system software includes: synthetic 24 virtual voltage vectors, speed controller, coordinate transformation module, delay module, prediction module, duty cycle calculation module and simplification module.
  • the dual three-phase permanent magnet motor is composed of two sets of three-phase windings with a spatial phase shift of 30°; the inverter input terminal is connected to the DC The power supply is connected, and the signal end is connected to the PWM module of the software system; the inverter is a six-phase two-level topology structure, and the output end is connected to the dual three-phase motors A, B, C, D, E, and F, which is responsible for converting the PWM signal output by the software system into the six-phase sinusoidal alternating current required to drive the motor; the position sensor adopts a rotary transformer, which is coaxially connected to the motor, and the collected information is transmitted to the software system; the current sensor is connected to the inverter and is responsible for sampling the six-phase current of the motor; the input end of the coordinate conversion module is connected to the current sensor, and the output end is connected to the delay compensation module, whose function is to convert the six-phase current in the natural coordinate system into the current in the rotating coordinate system to achieve decoupling control; the input
  • Step 1 Construct 24 virtual voltage vectors (24 virtual voltage vector modules).
  • the 64 voltage vectors corresponding to the conversion switch are determined by the following formula:
  • a e j30°
  • s A ⁇ s F represent the switch state of each bridge arm
  • u ⁇ represents the voltage vector of the ⁇ plane
  • u xy represents the voltage vector of the xy plane
  • Udc represents the DC bus voltage
  • Figure 3 is the voltage vector of the ⁇ plane, which is responsible for participating in the electromechanical energy conversion.
  • the 48 effective voltage vectors are divided into four layers, and the amplitudes from the inside to the outside are: 0.173Udc, 0.333Udc, 0.471Udc, 0.644Udc.
  • (b) is the xy plane, which is the harmonic plane responsible for generating losses.
  • the amplitudes from the inside to the outside are: 0.173Udc, 0.333Udc, 0.471Udc, 0.644Udc.
  • the present invention proposes a novel virtual voltage vector synthesis method.
  • the virtual voltage vector principle requires that the sum of the effects of the vector on the harmonic plane is zero, and its synthesis principle is as follows:
  • Di represents the duty cycle of each basic voltage vector.
  • the present invention selects the 12 large vectors and 1 zero vector at the outermost edge of the fundamental wave plane as the basic voltage vectors for synthesizing the virtual voltage vector, and adopts the adjacent three-vector principle to synthesize a new virtual voltage vector control set.
  • the target voltage vector is V 3.
  • the angle between V 3 and the ⁇ axis is 30°, and the three basic voltage vectors adjacent to it are: u 66 , u 64 and u 44.
  • the virtual voltage vector synthesis principle it can be obtained that:
  • u 1st , u 2nd , and u 3rd represent the first, second, and third basic voltage vectors, respectively;
  • the superscripts " ⁇ ", “ ⁇ ", "x”, and "y” represent the components of the voltage vector on the corresponding coordinate axis.
  • D 1 , D 2 , D 3 , and D 0 represent the duty ratios of the first, second, third basic voltage vectors, and the zero vector, respectively.
  • Step 2 Optimize the switching order of the voltage vector and standardize it.
  • FIG5(a) is a switching sequence diagram of the virtual voltage vector V2 (with an angle of 15° to the ⁇ axis) which is still synthesized using the adjacent three-vector principle. It can be seen from the figure that the switching sequence of the F phase needs to act twice in one cycle, which is not conducive to the implementation of digital processors in industrial applications. For this reason, it is necessary to make local adjustments to the vector at a specific position of V2 .
  • the method is as follows: As shown in FIG6 , V2 is synthesized using two inner and outer layers of two voltage vectors with the same direction in the ⁇ plane and opposite directions in the xy plane. The synthesized switching sequence is shown in FIG5(b), which meets industrial requirements. Similarly, the inner and outer two-layer voltage vector synthesis method is used at V2 , V6, V10 , V14 , V18 and V22 instead of the adjacent three-vector synthesis method.
  • Step 3 Obtain the rotation speed and position angle through the position sensor, obtain the six-phase current through the current sensor, and then obtain the current in the rotating coordinate system through the coordinate transformation module.
  • the position sensor measures the angular displacement and angular velocity of the rotor shaft, converts it into electrical signals and transmits it to the controller, which obtains the motor speed and rotor position angle information after decoding.
  • the present invention uses 6 current sensors to sample the phase currents of the motor and records them as: i A , i B , i C , i D , i E and i F .
  • the VSD coordinate transformation method is used to transform each variable of the natural coordinate system into the stationary coordinate system, and the transformation matrix is:
  • i ⁇ , i ⁇ , ix , i y , i o1 and i o2 represent the currents of the ⁇ -axis, ⁇ -axis, x-axis, y-axis, o1-axis and o2-axis of the stationary coordinate system.
  • ⁇ is the rotor position angle
  • the coordinate conversion module calculates the current i dq (k) of the motor at time k in the dq rotating coordinate system.
  • Step 4 Derive the prediction model of dual three-phase permanent magnet motor.
  • the present invention is a model predictive control system based on virtual voltage vector, and the harmonic plane can be ignored. Therefore, only the relevant variables of the dual three-phase permanent magnet motor in the fundamental wave plane need to be considered. By converting it into the rotating coordinate system, the voltage equation of the motor is obtained as follows:
  • ud and q are the components of Us in the d-axis and q-axis respectively
  • Rs is the stator resistance
  • Ld , Lq , id and iq are the dq-axis inductance and current respectively
  • ⁇ f is the permanent magnet flux amplitude
  • ⁇ e is the electrical angular velocity.
  • the superscript “k” represents the real-time values of the dq axis current and voltage at time k; the superscript “k+1” represents the predicted values of the dq axis current at time k+1; and Ts is the control period.
  • the superscript “pre” represents the final predicted value of the dq-axis current.
  • the value function is defined as:
  • Step 5 Calculate the duty cycle of the voltage vector action using the minimum error method (duty cycle calculation module).
  • Figure 8 is a schematic diagram of the minimum error duty cycle calculation. Taking the dq coordinate system as a reference, the predicted values of id and iq under the action of the zero voltage vector are denoted as point A ( x1 , y1 ), the predicted values of id and iq under the action of the effective voltage vector are denoted as point B ( x2 , y2 ), and the position of the reference current is C ( x0 , y0 ). Therefore, the blue dotted line is the action range of the voltage vector under duty cycle adjustment.
  • the point where the predicted value is located (i d pre , i q pre ) and the point where the reference current is located ( i q * ) represents the value of the cost function. If the duty cycle adjustment technology is not used, a complete voltage vector is applied within one control cycle, and its cost function is represented by an orange line. When the traditional q-axis current zero-beat duty cycle calculation is adopted, the ordinate of the target point of the predicted value is i q * . At this time, the intersection of the line parallel to the i d axis through point C and the straight line AB is the predicted point of the zero-beat duty cycle, and the value of its cost function is represented by a green line segment.
  • the value of the cost function of the duty cycle determined by these two methods is not the smallest.
  • the distance from point C to the straight line AB is the point with the smallest value of the cost function and the point with the smallest error.
  • the intersection of the straight line through point C and perpendicular to AB and AB can be obtained to obtain the required voltage vector, and then the corresponding duty cycle can be obtained.
  • the optimal duty cycle of the voltage vector can be obtained as:
  • Step 6 Simplify the traversal optimization process.
  • the ⁇ plane is divided into four equal regions with V 4 , V 10 , V 16 , and V 22 as boundaries, named G 1 , G 2 , G 3 , and G 4 .
  • the virtual voltage vectors contained in each region are shown in the following table:
  • V 1 , V 7 , V 13 and V 19 Substitute V 1 , V 7 , V 13 and V 19 into (5) to obtain the value of the cost function of each of the four voltage vectors: J(V 1 ), J(V 7 ), J(V 13 ), J(V 19 ). Select the vector V 1st with the smallest cost function, and then determine the optimal region.
  • V2nd determined in the second step is V1
  • the value of the cost function of V1 and the value of the cost functions of the two adjacent voltage vectors V24 and V2 are determined, and the optimal cost function is selected to determine the final voltage vector number.
  • Step 7 Bring the 24 virtual voltage vectors VV into the prediction model one by one, select the optimal voltage vector and its duty cycle through the simplified module, output them to the PWM module, modulate them through the inverter, output the corresponding voltage vector, and complete the entire control.
  • FIG10 is an experimental waveform diagram of the traditional 12 virtual voltage vector under the effect of the deadbeat duty cycle technology, with a THD of 19.8% and a torque ripple of 10.2 Nm .
  • the current ripples of id , iq, ix and iy are 0.86A, 0.35A, 0.89A and 0.71A respectively.
  • FIG11 is an experimental waveform diagram under the effect of the method proposed in the present invention, with a THD of 7.5% and a torque ripple of 5.29 Nm.
  • the current ripples of id , iq, ix and iy are 0.33A, 0.18A, 0.43A and 0.46A respectively.
  • the present invention significantly improves the performance of the motor.

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Abstract

本发明公开了一种双三相电机高精度模型预测电流控制系统及控制方法，涉及多相电机控制技术领域。本发明将传统12虚拟电压矢量控制集进行扩展，在不损失电压利用率的前提下，设计了24个幅值相等，相角均匀的虚拟电压矢量，提高控制精度。提出一种基于最小误差的占空比计算方法，即使在单一有效虚拟电压矢量的情况下，也能同时跟踪d轴和q轴的电流，保证输出最优的占空比。此外，简化预测控制中遍历所有电压矢量的过程，降低算法的计算负担。本发明通过扩展控制集和降低占空比计算误差两方面强有力的提升了模型预测控制的精度，降低了5、7次谐波，改善转矩脉动。且保证即使在24个电压矢量作用下，计算量依然较低，提升算法的执行效率。

Description

一种双三相电机高精度模型预测电流控制系统及控制方法 技术领域
本发明属于多相电机预测控制技术领域，尤其涉及一种双三相电机高精度模型预测电流控制系统及控制方法。
背景技术
随着交通运输、航天航空和国防军工等高端领域的飞速发展，电机系统作为装备的核心部件，对其要求进一步提高。多相永磁电机具有功率密度高、效率高和良好的容错能力等优势，已成为先进电机系统的首选。其中，中心点隔离，两套绕组相移30°连接的双三相永磁同步电机，因其特殊的结构，进而消除了6次转矩脉动，得到了广泛的应用。模型预测控制策略因具有多变量控制、易于处理非线性约束以及直观易实现的优点在功率变换器应用场合中具有良好的性能表现，逐步体现出良好的工程应用价值。但其存在计算量大以及转矩脉动高等缺点。中国发明专利《一种低计算量的双电机串联系统模型预测转矩控制方法》(专利号：202110774817.4)公开了一种低计算量的模型预测控制方法，该方法只需计算两个电压矢量的价值函数，相对减小了计算量，但是该方法需要计算参考电压矢量所在的位置，因此增加了两个观测器，使得系统变得复杂。中国发明专利《一种减小PMSM转矩脉动和磁链波动的模型预测控制方法》(专利号：202210499366.2)公开了一种减小永磁同步电机转矩脉动和磁链脉动的方法，该方法通过在单个周期内使用多个电压矢量拓宽调制范围，虽取得一定效果，但计算复杂。当模型预测控制算法应用到多相电机领域时，其备选电压矢量也呈指数倍增长，计算量也相对增大。同时，多相电机包含谐波平面，在系统运行过程中，必须对其加以控制，否则不利于电机性能，且产生较大的损耗。因此，为了提升模型预测控制在多相电机领域的应用，急需开展减少算法计算负担的相关研究，亦或是与改善转矩及磁链脉动相结合的有关技术。
发明内容
发明目的：针对双三相永磁电机模型预测控制具有转矩脉动大及计算负担重等问题，对控制集进行重新设计。将传统12虚拟电压矢量控制集进行扩展，在不损失电压利用率的前提下，设计了24个幅值相等，相角均匀的虚拟电压矢量，提高控制精度。进一步的，提出一种基于最小误差的占空比计算方法，即使在单一有效虚拟电压矢量的情况下，也能同时跟踪d轴和q轴的电流，保证输出最优的占空比。此外，简化预测控制中遍历所有电压 矢量的过程，降低算法的计算负担。本发明通过扩展控制集和降低占空比计算误差两方面强有力的提升了模型预测控制的精度，降低了5、7次谐波，改善转矩脉动。且保证即使在24个电压矢量作用下，计算量依然较低，提升算法的执行效率。
技术方案：为实现上述发明目的，本发明所采用的技术方案如下：一种双三相电机高精度模型预测电流控制系统，包括系统硬件和系统软件(在编程中实现)，系统硬件包括双三相永磁电机、直流电源、PWM模块、逆变器、位置传感器、电流传感器；系统软件包括：合成的24虚拟电压矢量模块、转速控制器、坐标转换模块、延时模块、预测模块、占空比计算模块、简化模块和价值函数模块；
所述双三相永磁电机由两套三相绕组空间相移30°构成；所述逆变器输入端与直流电源连接，逆变器信号端与PWM模块连接；逆变器为六相两电平拓扑结构，逆变器输出端与双三相电机A、B、C、D、E、F相连接，负责将PWM信号转换为驱动电机所需的六相正弦交流电；所述位置传感器采用旋转变压器，与双三相永磁电机同轴连接，所述电流传感器与逆变器连接，负责采样电机六相电流；
所述的坐标转换模块输入端连接电流传感器，输出端连接延时补偿模块，用于将自然坐标系下的六相电流转换为旋转坐标系下的电流，实现解耦控制；
所述延时模块输入端连接坐标变换模块，输出端连接预测模型，用以弥补数字系统采样带来的“一拍延时”问题；
所述预测模型模块输入端连接延时补偿模块、24虚拟电压矢量模块以及位置传感器，负责输出不同电压矢量作用下dq轴电流变化位置；
所述转速控制器由PI控制用以获取q轴参考电流，其输入端为给定转速与实际转速的误差，输出端为q轴电流的参考值；
所述的占空比计算模块输入端连接所述转速控制器以及预测模型模块，用以计算各电压矢量作用下最优电压矢量所在位置及其占空比；
所述的简化模块及价值函数模块输入端连接占空比计算模块，用以降低算法的迭代次数并选出最优矢量及其占空比；所述PWM模块输入端连接价值函数模块，将软件系统获得的最优矢量及占空比转换为相应的PWM信号，输出至逆变器，完成调制，从而驱动电机运行。
本发明的一种双三相电机高精度模型预测电流控制系统的控制方法，所述控制方法包括如下步骤：
步骤1)构造24个虚拟电压矢量；
步骤2)优化电压矢量的开关次序，使其标准化；
步骤3)通过位置传感器获得转速及位置角、通过电流传感器获得六相电流，再经坐标变换模块获得旋转坐标系下的电流；
步骤4)推导双三相永磁电机的预测模型；
步骤5)使用最小误差的方法计算电压矢量作用的占空比；
步骤6)简化遍历寻优的过程；
步骤7)通过价值函数选出最优电压矢量及其占空比，并输出至PWM模块，通过逆变器调制，输出相应的电压矢量，完成整个控制。
进一步，步骤1)的具体步骤包括：
双三相永磁电机配置成中性点隔离的方式，采用六相两电平电压源逆变器进行驱动，由于每个桥臂的上下两个开关器件都工作在互补导通状态，所以每个桥臂都有两个开关状态，整个逆变器共有2 6＝64个开关状态，与转换开关对应的64个电压矢量由下式决定：
Figure PCTCN2022132829-appb-000001
其中，a＝e j30°，s A～s F分别代表各个桥臂的开关状态，u αβ代表αβ平面的电压矢量，u xy代表xy平面的电压矢量，U dc表示直流母线电压，上桥臂开通为“1”，上桥臂关断则为“0”，基本电压矢量的编号按照ABC和DEF的顺序，将开关状态组合用八进制来进行表示；
虚拟电压矢量原则要求矢量在谐波平面的作用之和为零，其合成原则如下：
Figure PCTCN2022132829-appb-000002
其中，
Figure PCTCN2022132829-appb-000003
表示基本电压矢量在x轴和y轴的分量，D i表示各基本电压矢量作用的占空比；
为保证电压利用率，选用基波平面最外围的12个大矢量及1个零矢量作为合成虚拟电压矢量的基本电压矢量，采用相邻三矢量原则进行合成新的虚拟电压矢量控制集，其合成原则如下：
Figure PCTCN2022132829-appb-000004
其中，V i表示第i个待合成的虚拟电压矢量，其中i＝1,2,3…24；u 1st、u 2nd、和u 3rd分别 表示第一个、第二个和第三个基本电压矢量；上标“α”、“β”、“x”和“y”表示电压矢量在对应坐标轴的分量，D 1、D 2、D 3和D 0分别表示第一个、第二个、第三个基本电压矢量和零矢量作用的占空比；
规定每个基本电压矢量的幅值为0.59Udc，起始位置为0°，相邻两个电压矢量之间的夹角为15°，最终在αβ平面合成24个虚拟电压矢量，其在xy平面的分量为零。
进一步，步骤2)的具体步骤包括：
为了保证所合成的虚拟电压矢量能够在工业应用中实现，针对合成的24个虚拟电压矢量的开关次序进行优化，使其全部标准化，在V 2、V 6、V 10、V 14、V 18和V 22处采用内外两层电压矢量合成的方法代替相邻三矢量合成方法，最终合成的24个虚拟电压矢量如表1所示；
表1 24虚拟电压矢量分布情况
Figure PCTCN2022132829-appb-000005
其中，u 1、…u 0、…u 11、…u 66、…u 12、…u 64分别表示相应的基本电压矢量。
进一步，步骤3)的具体步骤包括：
位置传感器的测量转子的转轴角位移以及角速度，将其转换成电信号传输至控制器，经解码后获得电机的转速及转子的位置角信息；
6个电流传感器采样电机的相电流记为：i A、i B、i C、i D、i E和i F，采用VSD坐标变换法， 将自然坐标系的各个变量转换到静止坐标系，其变换矩阵为：
Figure PCTCN2022132829-appb-000006
其中，i α、i β、i x、i y、i o1和i o2表示静止坐标系α轴、β轴、x轴、y轴、o1轴、o2轴的电流；
对于双三相永磁电机，仅有αβ子空间的基波分量参与机电能量转换，为了便于简化分析，将静止坐标系变换到同步旋转坐标系，其变换矩阵为：
Figure PCTCN2022132829-appb-000007
其中，θ为转子位置角，i d和i q分别为d轴和q轴的电流；
经上述坐标转换模块计算出电机在k时刻，dq旋转坐标系下的电流i dq(k)。
进一步，步骤4)的具体步骤包括：
在基于虚拟电压矢量的模型预测控制系统中，谐波平面可以忽略不计，因此只需考虑双三相永磁电机在基波平面的相关变量，将其转换到旋转坐标系中，得到电机的电压方程为：
Figure PCTCN2022132829-appb-000008
式中，u d、u q分别为U s在d轴和q轴的分量，R s为定子电阻，L d、L q、i d和i q分别为dq轴电感和电流，ψ f为永磁磁链幅值，ω e为电角速度；
采用欧拉前向公式对(6)进行离散化处理，得：
Figure PCTCN2022132829-appb-000009
其中，上标“k”表示k时刻的dq轴电流及电压的实时值；上标“k+1”表示k+1时刻的dq 轴电流预测值；T s为控制周期；
为弥补数字控制器存在“一拍延时”缺点，采用两步预测法进行延时补偿，将(7)再次进行预测，获得最终的预测模型为：
Figure PCTCN2022132829-appb-000010
其中，上标“pre”表示dq轴电流的最终预测值；
价值函数定义为：
Figure PCTCN2022132829-appb-000011
其中，上标“*”表示dq轴电流给定参考值，采用i d *＝0控制。
进一步，步骤5)的具体步骤包括：
以dq坐标系为参考，记零电压矢量作用下i d和i q的预测值为点A(x 1,y 1)，有效电压矢量作用下i d和i q的预测值为点B(x 2,y 2)，参考电流所在的位置为C(x 0,y 0)，则点C到直线AB的距离即为价值函数值最小的点，也是误差最小的点，求出过C点与AB垂直的直线与AB的交点便可得到所需的电压矢量，进而得出相应的占空比；
(5)AB的直线方程：
Figure PCTCN2022132829-appb-000012
(6)过C点与AB垂直的直线方程：
Figure PCTCN2022132829-appb-000013
(7)联立(10)和(11)求出两直线相交的点的坐标为：
Figure PCTCN2022132829-appb-000014
其中，
Figure PCTCN2022132829-appb-000015
和
Figure PCTCN2022132829-appb-000016
表示占空比修正后dq轴电流的预测值；
Figure PCTCN2022132829-appb-000017
(8)根据交点位置可求出电压矢量最优占空比为：
Figure PCTCN2022132829-appb-000018
进一步，步骤6)的具体步骤包括：
(6)以V 4、V 10、V 16、V 22为边界将αβ平面等分为四个区域，命名为G 1，G 2，G 3和G 4；
每个区域包含的虚拟电压矢量如下表所示：
表1 虚拟电压矢量分区规则
Figure PCTCN2022132829-appb-000019
(7)将V 1，V 7，V 13和V 19带入(5)获得四个电压矢量作用下各自的价值函数的值：J(V 1)，J(V 7)，J(V 13)，J(V 19)；选出价值函数最小的矢量V 1st，进而确定最优区域；
(8)假设第二步确定的V 1st是V 1，则最优区域为G 1，再次计算G 1中的V 13和V 13的价值函数的值，选出价值函数最小的矢量V 2nd，确定第二个最优区域；
(9)假设第二步确定的V 2nd是V 1，则判断与V 1的价值函数的值与相邻的两个电压矢量V 24和V 2的价值函数的值，选出最优的价值函数即可确定最终的电压矢量序号；
(10)其他情况以此类推，所有区域的组合如表二所示；
表2 所有最优电压矢量选择情况组合
Figure PCTCN2022132829-appb-000020
经过上述简化过程，原先的预测过程需要遍历24个电压矢量，现在只需遍历8个，降低了算法的计算负担，提升效率。
进一步，步骤7)的具体步骤包括：将24个虚拟电压矢量VV逐个带入预测模型，通过简化模块，选出最优的电压矢量及其作用的占空比，输出至PWM模块，通过逆变器调制，输出相应的电压矢量，完成整个控制。
本发明的有益效果
1)本发明一种双三相电机高精度模型预测电流控制系统及控制方法，将传统12虚拟电压矢量的个数增加至24个，再不损耗电压利用率的基础上，拓宽了调制范围。
2)本发明所提的占空比的求解方法，同时考虑d轴和q轴跟踪电流，减小最低误差，且所求的价值函数也是所有价值函数中最小的，提高控制精度。
3)各电压矢量在所提占空比技术的作用下，幅值可以灵活改变，提高控制精度，降低5、7次谐波，改善了转矩脉动及磁链脉动。
4)本发明所提的简化选取矢量的方法，降低了模型预测控制算法的执行时间，提高算法效率，且能扩展到其他多相电机预测控制系统。
附图说明
图1为本发明实施例方法的控制原理示意图；
图2为应用本发明实施例方法的六相电压源逆变器拓扑结构图；
图3为本发明的空间电压矢量图；(a)αβ平面；(b)xy平面；
图4为本发明设计的最大三矢量虚拟电压矢量构造示意图；(a)αβ平面；(b)xy平面；
图5为本发明设计的开关次序图；(a)V 2修正前；(b)V 2修正后；
图6为本发明设计的内外两层虚拟电压矢量构造示意图；(a)αβ平面；(b)xy平面；
图7为本发明设计的24虚拟电压矢量；
图8为本发明提出的误差最小占空比计算方法示意图；
图9为本发明设计的简化过程示意图；(a)为区域划分示意图；(b)为最优区域示意图；(c)为最优电压矢量示意图；
图10为传统12虚拟电压矢量在无差拍占空比作用下的实验波形图；
图11为本发明的实验波形图；
具体实施方式
为了使本发明的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本发明进行进一步详细说明。应当理解，此处所描述的具体实施例仅用于解释本发明，并不用于限定本发明。
图1为本发明的控制框原理示意图，其控制系统硬件包括：双三相永磁电机、直流电源、PWM模块、逆变器、位置传感器、电流传感器。控制系统软件包括：合成的24虚拟电压矢量、转速控制器、坐标变换模块、延时模块、预测模块、占空比计算模块和简化模块。所述的双三相永磁电机由两套三相绕组空间相移30°构成；所述逆变器输入端与直流 电源连接，信号端与软件系统的PWM模块连接；所述逆变器为六相两电平拓扑结构，输出端与双三相电机A、B、C、D、E、F相连接，负责将软件系统输出的PWM信号转换为驱动电机所需的六相正弦交流电；所述位置传感器采用旋转变压器，与电机同轴连接，所采集的信息传送至软件系统；所述电流传感器与逆变器连接，负责采样电机六相电流；所述的坐标转换模块输入端连接电流传感器，输出端连接延时补偿模块，其作用在于将自然坐标系下的六相电流转换为旋转坐标系下的电流，实现解耦控制；所述延时模块输入端连接坐标变换模块，输出端连接预测模型，用以弥补数字系统采样带来的“一拍延时”问题；所述预测模型模块输入端连接延时补偿模块、24虚拟电压矢量模块以及位置传感器，负责输出不同电压矢量作用下dq轴电流变化位置；所述转速控制器由PI控制用以获取q轴参考电流，其输入端为给定转速与实际转速的误差，输出端为q轴电流的参考值；所述的占空比计算模块输入端连接所述转速控制器以及预测模型模块，用以计算各电压矢量作用下最优电压矢量所在位置及其占空比；所述的简化模块及价值函数模块输入端连接占空比计算模块，用以降低算法的迭代次数并选出最优矢量及其占空比；所述PWM模块输入端连接价值函数模块，将软件系统获得的最优矢量及占空比转换为相应的PWM信号，输出至逆变器，完成调制，从而驱动电机运行。方法的实现步骤主要分为以下几个步骤：
第一步：构造24个虚拟电压矢量(24虚拟电压矢量模块)。
如图2所示，本发明的双三相永磁电机配置成中性点隔离的方式，采用六相两电平电压源逆变器进行驱动。由于每个桥臂的上下两个开关器件都工作在互补导通状态，所以每个桥臂都有两个开关状态，整个逆变器共有2 6＝64个开关状态。与转换开关对应的64个电压矢量由下式决定：
Figure PCTCN2022132829-appb-000021
其中，a＝e j30°，s A～s F其中代表每个桥臂的开关状态，u αβ代表αβ平面的电压矢量，u xy代表xy平面的电压矢量，Udc表示直流母线电压。现规定上桥臂开通为“1”，上桥臂关断则为“0”，基本电压矢量的编号按照ABC和DEF的顺序，将开关状态组合用八进制来进行表示。
最终形成的电压矢量如图3所示，图3(a)为αβ平面的电压矢量，负责参与机电能量转换。48个有效电压矢量分成四层，由内到外的幅值分别为：0.173Udc、0.333Udc、0.471Udc、0.644Udc。(b)为xy平面，为谐波平面负责产生损耗。同样的由内到外的幅值 分别为：0.173Udc、0.333Udc、0.471Udc、0.644Udc。
为了抑制逆变器在谐波平面产生的电压矢量，本发明提出一种新型的虚拟电压矢量合成方法。虚拟电压矢量原则要求矢量在谐波平面的作用之和为零，其合成原则如下：
Figure PCTCN2022132829-appb-000022
其中，
Figure PCTCN2022132829-appb-000023
表示基本电压矢量在x轴和y轴的分量。D i表示各基本电压矢量作用的占空比。
本发明为保证电压利用率，选用基波平面最外围的12个大矢量及1个零矢量作为合成虚拟电压矢量的基本电压矢量，采用相邻三矢量原则进行合成新的虚拟电压矢量控制集。如图4所示，假设目标电压矢量为V 3。V 3与α轴的夹角为30°，与其相邻的三个基本电压矢量为：u 66，u 64和u 44，则根据虚拟电压矢量合成原则可以得出：
Figure PCTCN2022132829-appb-000024
根据方程(3)可以求出D 1，D 2，D 3，D 0。
以此类推，其他的虚拟电压矢量都可以按照此原则求出。其合成原则总结如下：
Figure PCTCN2022132829-appb-000025
其中，V i表示第i个待合成的虚拟电压矢量(i＝1,2,3…24)；u 1st、u 2nd、和u 3rd分别表示第一个、第二个和第三个基本电压矢量；上标“α”、“β”、“x”和“y”表示电压矢量在对应坐标轴的分量。D 1、D 2、D 3和D 0分别表示第一个、第二个、第三个基本电压矢量和零矢量作用的占空比。
第二步：优化电压矢量的开关次序，使其标准化。
图5(a)为虚拟电压矢量V 2(与α轴的夹角为15°)依然采用相邻三矢量原则合成的开关序列图，从图中可以看出F相的开关序列在一个周期内需要动作两次，在工业应用中不利于数字处理器的实现。为此需要针对V 2这中特定位置的矢量进行局部调整。方法如下：如图6所示，V 2采用内外两层，在αβ平面方向相同，在xy平面方向相反的两个电压矢量 进行合成。其合成后的开关次序如图5(b)所示，符合工业要求。类似的，在V 2、V 6、V 10、V 14、V 18和V 22处采用内外两层电压矢量合成的方法代替相邻三矢量合成方法。
经过前两步的方法，最终合成的24个标准的虚拟电压矢量如表1所示。
表1 24虚拟电压矢量分布情况
Figure PCTCN2022132829-appb-000026
其分布图如图7所示。
第三步：通过位置传感器获得转速及位置角、通过电流传感器获得六相电流，再经坐标变换模块获得旋转坐标系下的电流。
位置传感器的测量转子的转轴角位移以及角速度，将其转换成电信号传输至控制器，经解码后获得电机的转速及转子的位置角信息。
本发明使用6个电流传感器采样电机的相电流记为：i A、i B、i C、i D、i E和i F。采用VSD坐标变换法，将自然坐标系的各个变量转换到静止坐标系，其变换矩阵为：
Figure PCTCN2022132829-appb-000027
其中，i α、i β、i x、i y、i o1和i o2表示静止坐标系α轴、β轴、x轴、y轴、o1轴、o2轴的电流。
对于双三相永磁电机，仅有αβ子空间的基波分量参与机电能量转换，为了便于简化分析，将静止坐标系变换到同步旋转坐标系，其变换矩阵为：
Figure PCTCN2022132829-appb-000028
其中，θ为转子位置角。
经上述坐标转换模块计算出电机在k时刻，dq旋转坐标系下的电流i dq(k)。
第四步：推导双三相永磁电机的预测模型。
本发明为基于虚拟电压矢量的模型预测控制系统，谐波平面可以忽略不计。因此只需考虑双三相永磁电机在基波平面的相关变量。将其转换到旋转坐标系中，得到电机的电压方程为：
Figure PCTCN2022132829-appb-000029
式中，u d、u q分别为U s在d轴和q轴的分量，R s为定子电阻，L d、L q、i d和i q分别为dq轴电感和电流，ψ f为永磁磁链幅值，ω e为电角速度。
采用欧拉前向公式对(7)进行离散化处理，得：
Figure PCTCN2022132829-appb-000030
其中，上标“k”表示k时刻的dq轴电流及电压的实时值；上标“k+1”表示k+1时刻的dq 轴电流预测值；T s为控制周期。
为弥补数字控制器存在“一拍延时”缺点，采用两步预测法进行延时补偿(延时模块)，将(8)再次进行预测，获得最终的预测模型(预测模块)为：
Figure PCTCN2022132829-appb-000031
其中，上标“pre”表示dq轴电流的最终预测值。
价值函数定义为：
Figure PCTCN2022132829-appb-000032
其中，上标“*”表示dq轴电流给定参考值，本发明采用i d *＝0控制。
第五步：使用最小误差的方法计算电压矢量作用的占空比(占空比计算模块)。
图8为最小误差占空比计算的示意图，以dq坐标系为参考，记零电压矢量作用下i d和i q的预测值为点A(x 1,y 1)，有效电压矢量作用下i d和i q的预测值为点B(x 2,y 2)，参考电流所在的位置为C(x 0,y 0)。故蓝色虚线即为占空比调节情况下电压矢量的作用范围。
根据价值函数J(价值函数模块)的形式可知，预测值所在的点(i d pre，i q pre)和参考电流所在的点(
Figure PCTCN2022132829-appb-000033
i q *)之间的距离代表了价值函数的值。若未使用占空比调节技术，则在一个控制周期内施加一个完整的电压矢量，其价值函数用橙色的线表示。当采用传统的q轴电流无差拍占空比计算时，则预测值的目标点的纵坐标为i q *。此时，过C点作i d轴的平行线与直线AB的交点即为无差拍占空比的预测点，其价值函数的值用绿色线段表示。由集合知识可知，这两种方法所确定的占空比，其价值函数的值都不是最小的。点C到直线AB的距离即为价值函数值最小的点，也是误差最小的点。求出过C点与AB垂直的直线与AB的交点便可得到所需的电压矢量，进而得出相应的占空比。
(1)AB的直线方程：
Figure PCTCN2022132829-appb-000034
(2)过C点与AB垂直的直线方程：
Figure PCTCN2022132829-appb-000035
(3)联立(11)和(12)求出两直线相交的点的坐标为：
Figure PCTCN2022132829-appb-000036
其中，其中，
Figure PCTCN2022132829-appb-000037
和
Figure PCTCN2022132829-appb-000038
表示占空比修正后dq轴电流的预测值；
Figure PCTCN2022132829-appb-000039
(4)根据交点位置可求出电压矢量最优占空比为：
Figure PCTCN2022132829-appb-000040
第六步：简化遍历寻优的过程。
(1)如图9(a)所示，以V 4、V 10、V 16、V 22为边界将αβ平面等分为四个区域，命名为G 1，G 2，G 3和G 4。每个区域包含的虚拟电压矢量如下表所示：
表1 虚拟电压矢量分区规则
Figure PCTCN2022132829-appb-000041
(2)将V 1，V 7，V 13和V 19带入(5)获得四个电压矢量作用下各自的价值函数的值：J(V 1)，J(V 7)，J(V 13)，J(V 19)。选出价值函数最小的矢量V 1st，进而确定最优区域。
(3)如图9(b)所示，假设第二步确定的V 1st是V 1，则最优区域为G 1。再次计算G 1中的V 13和V 13的价值函数的值，选出价值函数最小的矢量V 2nd，确定第二个最优区域。
(4)如图9(c)所示，假设第二步确定的V 2nd是V 1，则判断与V 1的价值函数的值与相邻的两个电压矢量V 24和V 2的价值函数的值，选出最优的价值函数即可确定最终的电压矢量序号。
(5)其他情况以此类推，所有区域的组合如表二所示。
表2 所有最优电压矢量选择情况组合
Figure PCTCN2022132829-appb-000042
Figure PCTCN2022132829-appb-000043
经过上述简化过程(简化模块)，原先的预测过程需要遍历24个电压矢量，现在只需遍历8个，降低了算法的计算负担，提升效率。
第七步：将24个虚拟电压矢量VV逐个带入预测模型，通过简化模块，选出最优的电压矢量及其作用的占空比，输出至PWM模块，通过逆变器调制，输出相应的电压矢量，完成整个控制。
图10为传统12虚拟电压矢量在无差拍占空比技术的作用下的实验波形图，其THD为19.8％，转矩脉动为10.2Nm。i d，i q，i x和i y的电流脉动分别为：0.86A，0.35A，0.89A和0.71A。图11为本发明所提方法作用下的实验波形图，其THD为7.5％，转矩脉动为5.29Nm。i d，i q，i x和i y的电流脉动分别为：0.33A，0.18A，0.43A和0.46A。相对于传统方法，本发明使得电机性能显著提升。
以上实施例仅用于说明本发明的设计思想和特点，其目的在于使本领域内的技术人员能够了解本发明的内容并据以实施，本发明的保护范围不限于上述实施例。所以，凡依据本发明所揭示的原理、设计思路所作的等同变化或修饰，均在本发明的保护范围之内。

Claims (9)

  1. 一种双三相电机高精度模型预测电流控制系统，其特征在于，包括系统硬件和系统软件，系统硬件包括双三相永磁电机、直流电源、PWM模块、逆变器、位置传感器、电流传感器；
    系统软件包括：合成的24虚拟电压矢量模块、转速控制器、坐标转换模块、延时模块、预测模块、占空比计算模块、简化模块和价值函数模块；
    所述双三相永磁电机由两套三相绕组空间相移30°构成；所述逆变器输入端与直流电源连接，逆变器信号端与PWM模块连接；逆变器为六相两电平拓扑结构，逆变器输出端与双三相电机A、B、C、D、E、F相连接，负责将PWM信号转换为驱动电机所需的六相正弦交流电；所述位置传感器采用旋转变压器，与双三相永磁电机同轴连接，所述电流传感器与逆变器连接，负责采样电机六相电流；
    所述的坐标转换模块输入端连接电流传感器，输出端连接延时补偿模块，用于将自然坐标系下的六相电流转换为旋转坐标系下的电流，实现解耦控制；
    所述延时模块输入端连接坐标变换模块，输出端连接预测模型，用以弥补数字系统采样带来的“一拍延时”问题；
    所述预测模型模块输入端连接延时补偿模块、24虚拟电压矢量模块以及位置传感器，负责输出不同电压矢量作用下dq轴电流变化位置；
    所述转速控制器由PI控制用以获取q轴参考电流，其输入端为给定转速与实际转速的误差，输出端为q轴电流的参考值；
    所述的占空比计算模块输入端连接所述转速控制器以及预测模型模块，用以计算各电压矢量作用下最优电压矢量所在位置及其占空比；
    所述的简化模块及价值函数模块输入端连接占空比计算模块，用以降低算法的迭代次数并选出最优矢量及其占空比；所述PWM模块输入端连接价值函数模块，将软件系统获得的最优矢量及占空比转换为相应的PWM信号，输出至逆变器，完成调制，从而驱动电机运行。
  2. 根据权利要求1所述的一种双三相电机高精度模型预测电流控制系统的控制方法，其特征在于，所述控制方法包括如下步骤：
    步骤1)构造24个虚拟电压矢量；
    步骤2)优化电压矢量的开关次序，使其标准化；
    步骤3)通过位置传感器获得转速及位置角、通过电流传感器获得六相电流，再经坐 标变换模块获得旋转坐标系下的电流；
    步骤4)推导双三相永磁电机的预测模型；
    步骤5)使用最小误差的方法计算电压矢量作用的占空比；
    步骤6)简化遍历寻优的过程；
    步骤7)通过价值函数选出最优电压矢量及其占空比，并输出至PWM模块，通过逆变器调制，输出相应的电压矢量，完成整个控制。
  3. 根据权利要求2所述的一种双三相电机高精度模型预测电流控制系统的控制方法，其特征在于，步骤1)的具体步骤包括：
    双三相永磁电机配置成中性点隔离的方式，采用六相两电平电压源逆变器进行驱动，由于每个桥臂的上下两个开关器件都工作在互补导通状态，所以每个桥臂都有两个开关状态，整个逆变器共有2 6＝64个开关状态，与转换开关对应的64个电压矢量由下式决定：
    Figure PCTCN2022132829-appb-100001
    其中，a＝e j30°，s A～s F分别代表各个桥臂的开关状态，u αβ代表αβ平面的电压矢量，u xy代表xy平面的电压矢量，U dc表示直流母线电压，上桥臂开通为“1”，上桥臂关断则为“0”，基本电压矢量的编号按照ABC和DEF的顺序，将开关状态组合用八进制来进行表示；
    虚拟电压矢量原则要求矢量在谐波平面的作用之和为零，其合成原则如下：
    Figure PCTCN2022132829-appb-100002
    其中，
    Figure PCTCN2022132829-appb-100003
    表示基本电压矢量在x轴和y轴的分量，D i表示各基本电压矢量作用的占空比；
    为保证电压利用率，选用基波平面最外围的12个大矢量及1个零矢量作为合成虚拟电压矢量的基本电压矢量，采用相邻三矢量原则进行合成新的虚拟电压矢量控制集，其合成原则如下：
    Figure PCTCN2022132829-appb-100004
    其中，V i表示第i个待合成的虚拟电压矢量，其中i＝1,2,3…24；u 1st、u 2nd、和u 3rd分别表示第一个、第二个和第三个基本电压矢量；上标“α”、“β”、“x”和“y”表示电压 矢量在对应坐标轴的分量，D 1、D 2、D 3和D 0分别表示第一个、第二个、第三个基本电压矢量和零矢量作用的占空比；
    规定每个基本电压矢量的幅值为0.59Udc，起始位置为0°，相邻两个电压矢量之间的夹角为15°，最终在αβ平面合成24个虚拟电压矢量，其在xy平面的分量为零。
  4. 根据权利要求3所述的一种双三相电机高精度模型预测电流控制系统的控制方法，其特征在于，步骤2)的具体步骤包括：
    为了保证所合成的虚拟电压矢量能够在工业应用中实现，针对合成的24个虚拟电压矢量的开关次序进行优化，使其全部标准化，在V 2、V 6、V 10、V 14、V 18和V 22处采用内外两层电压矢量合成的方法代替相邻三矢量合成方法，最终合成的24个虚拟电压矢量如表1所示；
    表1 24虚拟电压矢量分布情况
    Figure PCTCN2022132829-appb-100005
    其中，u 1、…u 0、…u 11、…u 66、…u 12、…u 64分别表示相应的64个基本电压矢量。
  5. 根据权利要求2所述的一种双三相电机高精度模型预测电流控制系统的控制方法，其特征在于，步骤3)的具体步骤包括：
    位置传感器的测量转子的转轴角位移以及角速度，将其转换成电信号传输至控制器，经解码后获得电机的转速及转子的位置角信息；
    6个电流传感器采样电机的相电流记为：i A、i B、i C、i D、i E和i F，采用VSD坐标变换法，将自然坐标系的各个变量转换到静止坐标系，其变换矩阵为：
    Figure PCTCN2022132829-appb-100006
    其中，i α、i β、i x、i y、i o1和i o2表示静止坐标系α轴、β轴、x轴、y轴、o1轴、o2轴的电流；
    对于双三相永磁电机，仅有αβ子空间的基波分量参与机电能量转换，为了便于简化分析，将静止坐标系变换到同步旋转坐标系，其变换矩阵为：
    Figure PCTCN2022132829-appb-100007
    其中，θ为转子位置角，i d和i q分别为d轴和q轴的电流；
    经上述坐标转换模块计算出电机在k时刻，dq旋转坐标系下的电流i dq(k)。
  6. 根据权利要求2所述的一种双三相电机高精度模型预测电流控制系统的控制方法，其特征在于，步骤4)的具体步骤包括：
    在基于虚拟电压矢量的模型预测控制系统中，谐波平面可以忽略不计，因此只需考虑双三相永磁电机在基波平面的相关变量，将其转换到旋转坐标系中，得到电机的电压方程为：
    Figure PCTCN2022132829-appb-100008
    式中，u d、u q分别为U s在d轴和q轴的分量，R s为定子电阻，L d、L q、i d和i q分别为dq轴电感和电流，ψ f为永磁磁链幅值，ω e为电角速度；
    采用欧拉前向公式对(6)进行离散化处理，得：
    Figure PCTCN2022132829-appb-100009
    其中，上标“k”表示k时刻的dq轴电流及电压的实时值；上标“k+1”表示k+1时刻的dq轴电流预测值；T s为控制周期；
    为弥补数字控制器存在“一拍延时”缺点，采用两步预测法进行延时补偿，将(7)再次进行预测，获得最终的预测模型为：
    Figure PCTCN2022132829-appb-100010
    其中，上标“pre”表示dq轴电流的最终预测值；
    价值函数定义为：
    Figure PCTCN2022132829-appb-100011
    其中，上标“*”表示dq轴电流给定参考值，采用i d *＝0控制。
  7. 根据权利要求2所述的一种双三相电机高精度模型预测电流控制系统的控制方法，其特征在于，步骤5)的具体步骤包括：
    以dq坐标系为参考，记零电压矢量作用下i d和i q的预测值为点A(x 1,y 1)，有效电压矢量作用下i d和i q的预测值为点B(x 2,y 2)，参考电流所在的位置为C(x 0,y 0)，则点C到直线AB的距离即为价值函数值最小的点，也是误差最小的点，求出过C点与AB垂直的直线与AB的交点便可得到所需的电压矢量，进而得出相应的占空比；
    (1)AB的直线方程：
    Figure PCTCN2022132829-appb-100012
    (2)过C点与AB垂直的直线方程：
    Figure PCTCN2022132829-appb-100013
    (3)联立(10)和(11)求出两直线相交的点的坐标为：
    Figure PCTCN2022132829-appb-100014
    其中，
    Figure PCTCN2022132829-appb-100015
    和
    Figure PCTCN2022132829-appb-100016
    表示占空比修正后dq轴电流的预测值；
    Figure PCTCN2022132829-appb-100017
    x 1＝i d k+1+T s·[-R si d k+1+ω eL qi q k+1]/L d
    y 1＝i q k+1+T s·[-R si q k+1-ω eL di d k+1-ω eψ f]/L q
    Figure PCTCN2022132829-appb-100018
    Figure PCTCN2022132829-appb-100019
    (4)根据交点位置可求出电压矢量最优占空比为：
    Figure PCTCN2022132829-appb-100020
  8. 根据权利要求2所述的一种双三相电机高精度模型预测电流控制系统的控制方法，其特征在于，步骤6)的具体步骤包括：
    (1)以V 4、V 10、V 16、V 22为边界将αβ平面等分为四个区域，命名为G 1，G 2，G 3和G 4；
    每个区域包含的虚拟电压矢量如下表所示：
    表1虚拟电压矢量分区规则
    Figure PCTCN2022132829-appb-100021
    (2)将V 1，V 7，V 13和V 19带入(5)获得四个电压矢量作用下各自的价值函数的值：J(V 1)，J(V 7)，J(V 13)，J(V 19)；选出价值函数最小的矢量V 1st，进而确定最优区域；
    (3)假设第二步确定的V 1st是V 1，则最优区域为G 1，再次计算G 1中的V 13和V 13的价值函数的值，选出价值函数最小的矢量V 2nd，确定第二个最优区域；
    (4)假设第二步确定的V 2nd是V 1，则判断与V 1的价值函数的值与相邻的两个电压矢量V 24和V 2的价值函数的值，选出最优的价值函数即可确定最终的电压矢量序号；
    (5)其他情况以此类推，所有区域的组合如表二所示；
    表2所有最优电压矢量选择情况组合
    Figure PCTCN2022132829-appb-100022
    经过上述简化过程，原先的预测过程需要遍历24个电压矢量，现在只需遍历8个，降低了算法的计算负担，提升效率。
  9. 根据权利要求2所述的一种双三相电机高精度模型预测电流控制系统的控制方法，其特 征在于，步骤7)的具体步骤包括：将24个虚拟电压矢量VV逐个带入预测模型，通过简化模块，选出最优的电压矢量及其作用的占空比，输出至PWM模块，通过逆变器调制，输出相应的电压矢量，完成整个控制。
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