A model predictive control method and system for a five-phase fault-tolerant permanent magnet motor

Abstract

This invention relates to a model predictive control method and system for a five-phase permanent magnet fault-tolerant motor, belonging to the field of fault-tolerant motor control technology. It solves the problems of poor real-time performance in existing control methods, difficulty in accurately predicting the dynamic behavior of the permanent magnet fault-tolerant motor in the future, and the need for complex control strategies after a fault occurs. The method includes: obtaining the predicted current values ​​of each phase in the next cycle based on the motor phase current value, speed, and electrical angle of the current cycle; obtaining the output variable of the speed controller for the current cycle based on the motor speed of the current cycle, the output value of the proportional-integral controller for the current cycle and the previous cycle; obtaining the current command for each phase in the next cycle based on the fault state of each phase and the rotor electrical angular velocity of the current cycle; obtaining the evaluation function results for each phase based on the predicted current values ​​and current commands for each phase in the next cycle; and obtaining the switching state of the full-bridge circuit for each phase in the next cycle based on the evaluation function results, thus realizing predictive control of the five-phase permanent magnet fault-tolerant motor.

Description

Technical Field

[0001] This invention relates to the field of fault-tolerant motor control technology, and in particular to a model predictive control method and system for a five-phase permanent magnet fault-tolerant motor. Background Technology

[0002] With the development of multi-electric and all-electric aircraft, as well as hybrid and pure electric vehicles, motor drive systems have ushered in new development opportunities and challenges. Besides high power and high efficiency, high output performance (minimized speed and torque ripple) and high reliability have become crucial for motor drive systems. The emergence of permanent magnet fault-tolerant motors and their control systems has improved system safety and reliability and has been applied in the aviation field. In addition to the characteristics of general permanent magnet motors (small size, high power density, etc.), permanent magnet fault-tolerant motors also possess physical isolation, thermal isolation, magnetic isolation, and electrical isolation. Combined with high-performance control algorithms, the entire permanent magnet fault-tolerant motor control system can achieve strong fault tolerance while minimizing output torque ripple, thus meeting the requirements for high output performance.

[0003] In recent years, fault-tolerant control algorithms have seen some development. Commonly used strategies include optimal torque control. Firstly, based on the characteristics of the H-bridge drive topology, the definition, distribution, and distribution law of the phase and combined voltage space vectors of a permanent magnet fault-tolerant motor are studied, and their selection rules are determined. Then, based on the magnetic isolation characteristics of the permanent magnet fault-tolerant motor, flux linkage observers and torque observers are designed, constructing a direct torque control strategy with fault tolerance. Secondly, an optimal current control strategy is proposed, which enables the motor to achieve strong fault tolerance when one, two, or three phase faults occur in the motor windings or power transistors. Finally, the strategy aims to improve the output performance under fault conditions, minimizing torque ripple during fault states.

[0004] However, existing control methods have poor real-time performance, making it difficult to accurately predict the dynamic behavior of future permanent magnet fault-tolerant motors. They also require complex control strategies after a fault occurs, which cannot meet the increasingly higher requirements for permanent magnet fault-tolerant motors. Summary of the Invention

[0005] Based on the above analysis, the embodiments of the present invention aim to provide a model predictive control method and system for a five-phase permanent magnet fault-tolerant motor, in order to solve the problems of poor real-time performance of existing control methods, difficulty in accurately predicting the dynamic behavior of future permanent magnet fault-tolerant motors, and the need for complex control strategies after a fault occurs.

[0006] On one hand, embodiments of the present invention provide a model predictive control method for a five-phase permanent magnet fault-tolerant motor, comprising the following steps:

[0007] Based on the collected motor phase current values, speed, and electrical angle for the current cycle, the predicted values ​​of each phase current for the next cycle are obtained.

[0008] Based on the collected motor speed of the current cycle, the output values ​​of the proportional-integral controller of the current cycle and the previous cycle, the output variables of the speed controller of the current cycle are obtained according to the proportional-integral control algorithm; then, based on the collected fault status of each phase and rotor electric angular velocity of the current cycle, the current commands of each phase of the five-phase permanent magnet fault-tolerant motor in the next cycle are obtained according to the optimal torque control strategy.

[0009] Based on the predicted values ​​of each phase current and the current command for each phase in the next cycle, the evaluation function for each phase is obtained, and then the evaluation function result for each phase is obtained.

[0010] Based on the evaluation function results of each phase, the switching state of the power switch of each phase full-bridge circuit in the next cycle is obtained, realizing predictive control of the five-phase permanent magnet fault-tolerant motor.

[0011] Furthermore, the evaluation functions for each phase include the first evaluation function f′ for the nth phase. n1 The second evaluation function f′ n2 and the third evaluation function f′ n3 , respectively represented as:

[0012]

[0013]

[0014] f′ n3 =|I′ np3 -I′ n_given |

[0015] In the formula, These represent the first, second, and third predicted current values ​​for the nth phase in the next cycle, respectively; I′ n_given This indicates the current command for the nth phase in the next cycle, where n represents the five phases A, B, C, E, and D of the five-phase permanent magnet fault-tolerant motor.

[0016] Furthermore, the evaluation function result f′ of the nth phase is obtained through the following formula. np :

[0017] f′ np =min{f′ n1 ,f′ n2 ,f′ n3}

[0018] In the formula, f′ n1 f′ n2 f′ n3 Let these represent the first evaluation function, the second evaluation function, and the third evaluation function of the nth phase, respectively.

[0019] Furthermore, the process of obtaining the switching state of the power switches of each phase of the full-bridge circuit in the next cycle based on the evaluation function results includes:

[0020] When f′ np =f′ n1 Then the switching state of the power switch transistor in the nth phase of the full-bridge circuit is S. n1 =S n4 =1,S n2 =S n3 =0;

[0021] When f′ np =f′ n2 Then the switching state of the power switch transistor in the nth phase of the full-bridge circuit is S. n1 =S n4 =S n2 =S n3 =0;

[0022] When f′ np =f′ n3 Then the switching state of the power switch transistor in the nth phase of the full-bridge circuit is S. n1 =S n4 =0, S n2 =S n3 =1;

[0023] Among them, S n1 S n4 S represents the switching state of the positive arm of the H-bridge in the nth phase of the full-bridge circuit. n2 S n3 These represent the switching states of the negative arm of the H-bridge in the full-bridge circuit of phase n; "1" indicates on and "0" indicates off.

[0024] Furthermore, the predicted value of the first current in the nth phase of the next cycle Second current prediction value and the third current prediction value They are represented as follows:

[0025]

[0026]

[0027]

[0028] In the formula, T s Indicates the sampling period, R represents the resistance of the five-phase permanent magnet fault-tolerant motor, L represents the inductance of the five-phase permanent magnet fault-tolerant motor, and I represents the resistance of the five-phase permanent magnet fault-tolerant motor. n U represents the nth phase current value in the current cycle. dc EMF represents the DC bus voltage. nThis represents the nth back electromotive force of the five-phase permanent magnet fault-tolerant motor in the current cycle.

[0029] Furthermore, the nth back electromotive force (EMF) of the five-phase permanent magnet fault-tolerant motor in the current cycle n , is represented as:

[0030] EMF n =k m ω m sin(x+θ en )

[0031] In the formula, k m ω represents the peak back EMF coefficient of a five-phase permanent magnet fault-tolerant motor. m Let θ represent the mechanical speed of the five-phase permanent magnet fault-tolerant motor in the current cycle, x represent the electrical angle of the five-phase permanent magnet fault-tolerant motor in the current cycle, and θ represent the mechanical speed of the five-phase permanent magnet fault-tolerant motor in the current cycle. en This represents the initial electrical angle of the nth phase winding.

[0032] Furthermore, the current command I′ of the nth phase in the next cycle n_given , is represented as:

[0033]

[0034] in,

[0035]

[0036] S N ∪S F ={A,B,C,D,E}

[0037]

[0038] In the formula, T represents the output variable of the speed controller in the current cycle. F This represents the electromagnetic torque generated by the faulty phase winding of the current five-phase permanent magnet fault-tolerant motor; S N S represents the set of non-faulty phase windings of a five-phase permanent magnet fault-tolerant motor in the current cycle; F This represents the set of faulty phase windings in the current cycle of a five-phase permanent magnet fault-tolerant motor; ω e θ represents the current cycle rotor electric angular velocity of the five-phase permanent magnet fault-tolerant motor; eh θ represents the initial electrical angle of the h-th phase winding; ej This represents the initial electrical angle of the j-th phase winding.

[0039] Furthermore, the output variable of the current cycle speed controller Represented as:

[0040]

[0041] in,

[0042] u p =k p e;

[0043] u i =u″ i +k i e;

[0044]

[0045] In the formula, u p u i These represent the output values ​​of the proportional and integral terms of the proportional-integral controller for the current cycle, respectively; u″ i e represents the output value of the integral term of the proportional-integral controller in the previous cycle; e represents the deviation value of the motor speed in the current cycle; k p k i These represent the proportional and integral coefficients of the speed controller, respectively. This indicates the speed command for the five-phase permanent magnet fault-tolerant motor in the current cycle; ω m This indicates the mechanical speed of the five-phase permanent magnet fault-tolerant motor in the current cycle.

[0046] On the other hand, embodiments of the present invention provide a model predictive control system for a five-phase permanent magnet fault-tolerant motor, comprising:

[0047] Phase current prediction calculation module: used to obtain the predicted values ​​of each phase current in the next cycle based on the collected motor phase current values, speed and electrical angle in the current cycle;

[0048] The phase current command calculation module is used to obtain the output variables of the speed controller in the current cycle based on the collected motor speed in the current cycle, the output values ​​of the proportional-integral controller in the current cycle and the previous cycle, according to the proportional-integral control algorithm; and then, based on the collected fault status of each phase and rotor electric angular velocity in the current cycle, it obtains the phase current commands of the five-phase permanent magnet fault-tolerant motor in the next cycle according to the optimal torque control strategy.

[0049] The phase evaluation function result acquisition module is used to obtain the phase evaluation function based on the predicted value of each phase current and the current command of each phase in the next cycle, and then obtain the phase evaluation function result.

[0050] The switching state decision module is used to obtain the switching state of the power switch of each phase full-bridge circuit in the next cycle based on the evaluation function results of each phase, so as to realize the predictive control of the five-phase permanent magnet fault-tolerant motor.

[0051] Furthermore, the phase evaluation function in the phase evaluation function result acquisition module includes the first evaluation function f′ of the nth phase. n1 The second evaluation function f′n2 and the third evaluation function f′ n3 , respectively represented as:

[0052]

[0053]

[0054]

[0055] In the formula, These represent the first, second, and third predicted current values ​​for the nth phase in the next cycle, respectively; I′ n_given This indicates the current command for the nth phase in the next cycle.

[0056] Compared with the prior art, the present invention can achieve the following beneficial effects:

[0057] This invention provides a model predictive control method and system for a five-phase permanent magnet fault-tolerant motor.

[0058] By using the electrical data of the five-phase permanent magnet fault-tolerant motor in the current cycle, the predicted current values ​​of each phase in the next cycle are obtained. Then, based on the proportional-integral control algorithm and the optimal torque control strategy, the current commands of each phase in the next cycle are obtained, and the evaluation function results of each phase are obtained. Based on the evaluation function results of each phase, the switching state of the power switch of each phase full-bridge circuit in the next cycle is obtained, thus realizing the predictive control of the five-phase permanent magnet fault-tolerant motor. It has good real-time performance, low computational load, simple control logic, and is easy to implement in engineering. It has good current tracking control performance under normal motor conditions, open circuit faults, and short circuit faults, and can effectively meet the control requirements of high-reliability fault-tolerant motor systems.

[0059] In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained from what is particularly pointed out in the description and drawings. Attached Figure Description

[0060] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0061] Figure 1 This is a flowchart illustrating the model predictive control method for a five-phase permanent magnet fault-tolerant motor provided in Embodiment 1 of the present invention.

[0062] Figure 2 This is a schematic diagram of the structure of the five-phase H-bridge architecture fault-tolerant power drive circuit provided in Embodiment 1 of the present invention;

[0063] Figure 3 This is a schematic diagram of the overall structure of the five-phase permanent magnet fault-tolerant motor system provided in Embodiment 1 of the present invention;

[0064] Figure 4 This is a schematic diagram of the functional allocation modules of the DSP system and FPGA system provided in Embodiment 1 of the present invention. Detailed Implementation

[0065] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0066] Example 1

[0067] A specific embodiment of the present invention discloses a model predictive control method for a five-phase permanent magnet fault-tolerant motor, such as... Figure 1 As shown, it includes the following steps:

[0068] S1. Based on the collected motor phase current values, speed, and electrical angle of the current cycle, obtain the predicted values ​​of each phase current for the next cycle.

[0069] In practice, the predicted current values ​​for each phase in the next cycle include the first predicted current value for the nth phase. Second current prediction value and the third current prediction value They are represented as follows:

[0070]

[0071]

[0072]

[0073] In the formula, T s Indicates the sampling period, R represents the resistance of the five-phase permanent magnet fault-tolerant motor, L represents the inductance of the five-phase permanent magnet fault-tolerant motor, and I represents the resistance of the five-phase permanent magnet fault-tolerant motor. n U represents the nth phase current value in the current cycle. dc This represents the DC bus voltage; for example, the DC bus voltage is 270V, EMF. n This represents the nth back electromotive force of the five-phase permanent magnet fault-tolerant motor in the current cycle.

[0074] In specific implementation, the nth back electromotive force (EMF) of the five-phase permanent magnet fault-tolerant motor in the current cycle n , is represented as:

[0075] EMF n =k m ωm sin(x+θ en )

[0076] In the formula, k m ω represents the peak back EMF coefficient of a five-phase permanent magnet fault-tolerant motor. m Let θ represent the mechanical speed of the five-phase permanent magnet fault-tolerant motor in the current cycle, x represent the electrical angle of the five-phase permanent magnet fault-tolerant motor in the current cycle, and θ represent the mechanical speed of the five-phase permanent magnet fault-tolerant motor in the current cycle. en This represents the initial electrical angle of the nth phase winding.

[0077] S2. Based on the collected motor speed of the current cycle, the output values ​​of the proportional-integral controller of the current cycle and the previous cycle, the output variables of the speed controller of the current cycle are obtained according to the proportional-integral control algorithm; then, based on the collected fault status of each phase and rotor electric angular velocity of the current cycle, the current commands of each phase of the five-phase permanent magnet fault-tolerant motor in the next cycle are obtained according to the optimal torque control strategy.

[0078] During implementation, in step S2, the output variable T of the current cycle speed controller eref , is represented as:

[0079] T eref =u p +u i

[0080] in,

[0081] u p =k p e;

[0082] u i =u″ i +k i e;

[0083]

[0084] In the formula, u p u i These represent the output values ​​of the proportional and integral terms of the proportional-integral controller for the current cycle, respectively; u″ i e represents the output value of the integral term of the proportional-integral controller in the previous cycle; e represents the deviation value of the motor speed in the current cycle; k p k i These represent the proportional and integral coefficients of the speed controller, respectively. This indicates the speed command for the five-phase permanent magnet fault-tolerant motor in the current cycle; ω m This indicates the mechanical speed of the five-phase permanent magnet fault-tolerant motor in the current cycle. The speed command is issued via the host computer.

[0085] During implementation, in step S2, the current command I′ of the nth phase in the next cycle n_given, is represented as:

[0086]

[0087] in,

[0088]

[0089] S N ∪S F ={A,B,C,D,E}

[0090]

[0091] In the formula, T represents the output variable of the speed controller in the current cycle. F This represents the electromagnetic torque generated by the faulty phase winding of the current five-phase permanent magnet fault-tolerant motor; S N S represents the set of non-faulty phase windings of a five-phase permanent magnet fault-tolerant motor in the current cycle; F This represents the set of faulty phase windings in the current cycle of a five-phase permanent magnet fault-tolerant motor; ω e θ represents the current cycle rotor electric angular velocity of the five-phase permanent magnet fault-tolerant motor; eh θ represents the initial electrical angle of the h-th phase winding; ej Let represent the initial electrical angle of the j-th phase winding, and A, B, C, D, and E represent each of the five phases.

[0092] S3. Based on the predicted current values ​​and current commands of each phase in the next cycle, obtain the evaluation function of each phase, and then obtain the evaluation function results of each phase.

[0093] During implementation, in step S3, the evaluation functions for each phase include the first evaluation function f′ for the nth phase. n1 The second evaluation function f′ n2 and the third evaluation function f′ n3 , respectively represented as:

[0094]

[0095]

[0096]

[0097] In the formula, These represent the first, second, and third predicted current values ​​for the nth phase in the next cycle, respectively; I′ n_given This indicates the current command for the nth phase in the next cycle, where n represents the five phases A, B, C, D, and E of the five-phase permanent magnet fault-tolerant motor.

[0098] During implementation, in step S3, the evaluation function result f′ of the nth phase is obtained using the following formula. np :

[0099] f′ np =min{f′ n1 ,f′ n2 ,f′ n3}

[0100] In the formula, f′ n1 f′ n2 f′ n3 Let these represent the first evaluation function, the second evaluation function, and the third evaluation function of the nth phase, respectively.

[0101] S4. Based on the evaluation function results of each phase, the switching state of the power switch of each phase full-bridge circuit in the next cycle is obtained, so as to realize the predictive control of the five-phase permanent magnet fault-tolerant motor.

[0102] In implementation, obtaining the switching state of each phase full-bridge circuit power switch in the next cycle based on the evaluation function results includes:

[0103] When f′ np =f′ n1 Then the switching state of the power switch transistor in the nth phase of the full-bridge circuit is S. n1 =S n4 =1,S n2 =S n3 =0;

[0104] When f′ np =f′ n2 Then the switching state of the power switch transistor in the nth phase of the full-bridge circuit is S. n1 =S n4 =S n2 =S n3 =0;

[0105] When f′ np =f′ n3 Then the switching state of the power switch transistor in the nth phase of the full-bridge circuit is S. n1 =S n4 =0, S n2 =S n3 =1;

[0106] Among them, S n1 S n4 S represents the switching state of the positive arm of the H-bridge in the nth phase of the full-bridge circuit. n2 S n3 These represent the switching states of the negative arm of the H-bridge in the full-bridge circuit of phase n; "1" indicates on and "0" indicates off.

[0107] Understandably, the above process continues, predicting and setting the switching state for the next cycle in real time, thereby achieving precise predictive control of the permanent magnet fault-tolerant motor.

[0108] It should be noted that this embodiment is based on model predictive control, which is a model-based closed-loop optimization control strategy. It can use predictive models to predict the future dynamic behavior of the system and obtain accurate output through repeated online optimization. This makes the control method applicable to the nonlinear and strongly coupled control system of permanent magnet synchronous motor.

[0109] Compared with existing technologies, this embodiment provides a model predictive control method for a five-phase permanent magnet fault-tolerant motor. It uses the electrical data of the five-phase permanent magnet fault-tolerant motor in the current cycle to obtain the predicted current values ​​of each phase in the next cycle. Then, based on the proportional-integral control algorithm and the optimal torque control strategy, it obtains the current commands for each phase in the next cycle, thereby obtaining the evaluation function results for each phase. Based on the evaluation function results, it obtains the switching state of the power switches in the full-bridge circuit of each phase in the next cycle, realizing predictive control of the five-phase permanent magnet fault-tolerant motor. This method offers good real-time performance, low computational complexity, simple control logic, and ease of engineering implementation. It exhibits excellent current tracking control performance under normal motor conditions, open-circuit faults, and short-circuit faults, effectively meeting the control requirements of a high-reliability fault-tolerant motor system.

[0110] Example 2

[0111] A specific embodiment 2 of the present invention provides a model predictive control system for a five-phase permanent magnet fault-tolerant motor, comprising:

[0112] Phase current prediction calculation module: used to obtain the predicted values ​​of each phase current in the next cycle based on the collected motor phase current values, speed and electrical angle in the current cycle;

[0113] The phase current command calculation module is used to obtain the output variables of the speed controller in the current cycle based on the collected motor speed in the current cycle, the output values ​​of the proportional-integral controller in the current cycle and the previous cycle, according to the proportional-integral control algorithm; and then, based on the collected fault status of each phase and rotor electric angular velocity in the current cycle, it obtains the phase current commands of the five-phase permanent magnet fault-tolerant motor in the next cycle according to the optimal torque control strategy.

[0114] The phase evaluation function result acquisition module is used to obtain the phase evaluation function based on the predicted value of each phase current and the current command of each phase in the next cycle, and then obtain the phase evaluation function result.

[0115] The switching state decision module is used to obtain the switching state of the power switch of each phase full-bridge circuit in the next cycle based on the evaluation function results of each phase, so as to realize the predictive control of the five-phase permanent magnet fault-tolerant motor.

[0116] In implementation, the phase evaluation function results acquisition module includes the first evaluation function f′ of the nth phase. n1 The second evaluation function f′ n2 and the third evaluation function f′ n3 , respectively represented as:

[0117]

[0118]

[0119]

[0120] In the formula, These represent the first, second, and third predicted current values ​​for the nth phase in the next cycle, respectively; I′ n_given This indicates the current command for the nth phase in the next cycle, where n represents the five phases A, B, C, D, and E of the five-phase permanent magnet fault-tolerant motor.

[0121] Specifically, such as Figure 3 As shown, the fault-tolerant motor system includes a five-phase permanent magnet fault-tolerant motor, a fault-tolerant controller, a fault-tolerant power driver, and a signal detection circuit; wherein, the five-phase permanent magnet fault-tolerant motor includes an eight-pole surface-mount rotor and a ten-slot stator assembly.

[0122] More specifically, fault-tolerant controllers include DSP and FPGA systems, such as Figure 4 As shown, the DSP system includes a speed controller, a fault-tolerant controller, and a fault diagnosis module. It is mainly responsible for analyzing and implementing fault states, calculating the electromagnetic torque setpoint based on speed commands and speed feedback for speed loop control, and then calculating the current setpoint command value for the non-faulty windings of the motor based on the rotor position. The FPGA system includes a data transmission module, an A / D sampling control module, a current controller, a PWM generation module, and a resolver control module. It is mainly responsible for calculating the current prediction control strategy, motor speed and position sampling control, current sampling control, and deriving the switching control signals of each phase H-bridge based on current prediction and current commands.

[0123] Preferably, the DSP system uses a high-performance 32-bit floating-point digital processor TMS320F28335 with a main frequency of up to 150MHz. It has a single-precision floating-point arithmetic unit, 256K×16 FLASH, 34K×16 SARAM, 8K×16 boot ROM, supports up to 18 channels of PWM output, and CAN, UART, SPI, and I2C communication interfaces. The FPGA system consists of an FPGA chip and its peripheral circuits. The FPGA chip selected is the Altera Cyclone II series EP2C35F484C8N. The EP2C35F484C8N features low power consumption and low cost, a working clock frequency of up to 400MHz, 33216 logic units, 35 multipliers, and provides up to 328 configurable I / O ports.

[0124] More specifically, the signal detection circuit includes a current sensor, a rotary transformer, a shaft angle converter, a signal conditioning circuit, and an A / D conversion circuit; it is used to acquire the phase current signal of the motor, the motor speed, and rotor position information.

[0125] More specifically, a fault-tolerant power driver consists of an isolation drive circuit and an inverter circuit, such as... Figure 2 As shown, the isolation driver consists of a gate isolation driver chip and its peripheral circuitry, achieving electrical isolation and improving system stability; the inverter circuit consists of five independent full-bridge circuits, each H-bridge circuit consisting of four power transistors (S). n1 S n2 S n3 S n4 Composition, in which S n1 With S n4 The positive arm of the H-bridge, which makes up the n phases, S n2 With S n3 The negative arm of the H-bridge, which consists of n phases, enables individual drive and power supply for each phase winding of the permanent magnet fault-tolerant motor, thus forming an electrical fault-tolerant structure between the phase windings.

[0126] The specific implementation process of this invention can be found in the above method embodiments, and will not be repeated here.

[0127] Since this embodiment is based on the same principle as the above-described method embodiments, this system also has the corresponding technical effects of the above-described method embodiments.

[0128] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware, and the program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0129] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A model predictive control method for a five-phase permanent magnet fault-tolerant motor, characterized in that, Includes the following steps: Based on the collected motor phase current values, speed, and electrical angle for the current cycle, the predicted values ​​of each phase current for the next cycle are obtained. Based on the collected motor speed of the current cycle, the output values ​​of the proportional-integral controller of the current cycle and the previous cycle, the output variables of the speed controller of the current cycle are obtained according to the proportional-integral control algorithm; then, based on the collected fault status of each phase and rotor electric angular velocity of the current cycle, the current commands of each phase of the five-phase permanent magnet fault-tolerant motor in the next cycle are obtained according to the optimal torque control strategy. Based on the predicted values ​​of each phase current and the current command for each phase in the next cycle, the evaluation function for each phase is obtained, and then the evaluation function result for each phase is obtained. Based on the evaluation function results of each phase, the switching state of the power switch of each phase full-bridge circuit in the next cycle is obtained, so as to realize the predictive control of the five-phase permanent magnet fault-tolerant motor. The evaluation functions for each phase include the first... n Phase first evaluation function Second evaluation function and the third evaluation function , respectively represented as: ； ； ； In the formula, , , They represent the next period's number. n The first current prediction value, the second current prediction value, and the third current prediction value of the phase; Indicates the next period Phase current command, This represents the five phases A, B, C, E, and D of a five-phase permanent magnet fault-tolerant motor. The first phase is obtained by the following equation n The phase evaluation function result : ； The method of obtaining the switching state of each phase full-bridge circuit power switch in the next cycle based on the evaluation function results includes: when Then the first The switching states of the power switching transistors in the full-bridge circuit of the phase are as follows: , ; when Then the first The switching states of the power switching transistors in the full-bridge circuit of the phase are as follows: ; When , the first phase full-bridge circuit power switch tube switch state is , ; in, , They represent the first In a full-bridge circuit, the positive arm switching state of the H-bridge is as follows: , They represent the first The switching state of the negative arm of the H-bridge in a full-bridge circuit; "1" indicates on, "0" indicates off; The next cycle n First current prediction value of phase Second current prediction value and the third current prediction value , respectively represented as: ； ； ； In the formula, Indicates the sampling period. This indicates the resistance of a five-phase permanent magnet fault-tolerant motor. This indicates the inductance of a five-phase permanent magnet fault-tolerant motor. Indicates the number of the current period Phase current value, Indicates the DC bus voltage. This indicates the current cycle of the five-phase permanent magnet fault-tolerant motor. Opposite potentials.

2. The model predictive control method of a five-phase fault-tolerant permanent magnet motor according to claim 1, characterized in that, the first phase of the five-phase fault-tolerant permanent magnet motor of the current period n opposite potential is expressed as: ； In the formula, This represents the peak back EMF coefficient of a five-phase permanent magnet fault-tolerant motor. This indicates the mechanical speed of the five-phase permanent magnet fault-tolerant motor in the current cycle. This represents the electrical angle of the five-phase permanent magnet fault-tolerant motor in the current cycle. Indicates the first Initial electrical angle of phase winding.

3. The model predictive control method for a five-phase permanent magnet fault-tolerant motor according to claim 2, characterized in that, the next period phase current command is expressed as: ； in, ； ， ； In the formula, This represents the output variable of the speed controller in the current cycle. This indicates the electromagnetic torque generated by the faulty phase winding of the current five-phase permanent magnet fault-tolerant motor; This represents the set of non-faulty phase windings of a five-phase permanent magnet fault-tolerant motor in the current cycle; This represents the set of faulty phase windings in the current cycle of a five-phase permanent magnet fault-tolerant motor. This indicates the current cycle's rotor electric angular velocity of the five-phase permanent magnet fault-tolerant motor; Indicates the first Initial electrical angle of phase winding; Indicates the first Initial electrical angle of phase winding.

4. The model predictive control method for a five-phase permanent magnet fault-tolerant motor according to claim 3, characterized in that, an output variable of the current cycle speed controller is represented as: ； in, ； ； ； In the formula, , These represent the output values ​​of the proportional and integral terms of the proportional-integral controller for the current cycle, respectively. This indicates the output value of the integral term of the proportional-integral controller in the previous cycle. This indicates the deviation value of the motor speed in the current cycle; , These represent the proportional and integral coefficients of the speed controller, respectively. This command indicates the speed of the five-phase permanent magnet fault-tolerant motor in the current cycle. This indicates the mechanical speed of the five-phase permanent magnet fault-tolerant motor in the current cycle.

5. A model predictive control system of a five-phase fault-tolerant permanent magnet motor based on the model predictive control method of the five-phase fault-tolerant permanent magnet motor according to any one of claims 1-4, characterized in that, include: Phase current prediction calculation module: used to obtain the predicted values ​​of each phase current in the next cycle based on the collected motor phase current values, speed and electrical angle in the current cycle; The phase current command calculation module is used to obtain the output variables of the speed controller in the current cycle based on the collected motor speed in the current cycle, the output values ​​of the proportional-integral controller in the current cycle and the previous cycle, according to the proportional-integral control algorithm; and then, based on the collected fault status of each phase and rotor electric angular velocity in the current cycle, it obtains the phase current commands of the five-phase permanent magnet fault-tolerant motor in the next cycle according to the optimal torque control strategy. The phase evaluation function result acquisition module is used to obtain the phase evaluation function based on the predicted value of each phase current and the current command of each phase in the next cycle, and then obtain the phase evaluation function result. The switching state decision module is used to obtain the switching state of the power switch of each phase full-bridge circuit in the next cycle based on the evaluation function results of each phase, so as to realize the predictive control of the five-phase permanent magnet fault-tolerant motor.

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