Motor speed regulation method based on model predictive control, inverter and control system

Abstract

The application provides a motor speed regulation method based on model predictive control, an inverter and a control system. The method comprises the following steps: obtaining motor parameters and d, q-axis current reference signals; the motor parameters comprise d, q-axis inductance values; in combination with the motor parameters, a model predictive control mode is used to start tracking the d, q-axis current reference signals, and the output voltage of an inverter connected with the motor is determined; the output voltage is transformed to a dq coordinate system through park transformation, and a finite element set is determined; in the finite element set, all possible switching sequences are traversed to determine the switching signal of the inverter, the switching signal acts on the switching tube of the inverter, and the switching tube is controlled to turn on and off, so that the current of the motor completes the task of tracking the d, q-axis current reference signals. The motor speed regulation method based on model predictive control has fast response speed and is not prone to overshoot.

Description

Technical Field

[0001] This application belongs to the technical field of electrical engineering, and relates to a motor speed control method, and particularly to a motor speed control method, inverter and control system based on model predictive control. Background Technology

[0002] Currently, compared to surface-mounted permanent magnet synchronous motors, embedded permanent magnet synchronous motors can achieve higher energy and torque densities, and are therefore widely used in fields such as electric vehicles. However, due to the salient polarity of embedded motors, the d-axis and q-axis inductances are no longer equal, requiring different algorithms to accommodate different speed ranges.

[0003] At low speeds, the motor needs to reduce current loss by using the maximum torque per ampere (MTPA). As the speed increases, it needs to select the maximum torque per voltage (MTPV) or field weakening to obtain a wider speed range. Furthermore, the motor needs to operate in maximum torque mode during startup to quickly increase speed. In traditional algorithms, motor parameters are fixed, there is no maximum current operating mode, and the inner loop uses a PI controller to generate voltage command signals, resulting in poor speed control accuracy and slow response. Summary of the Invention

[0004] This application provides a motor speed regulation method, inverter, and control system based on model predictive control to solve the problems of poor motor speed regulation accuracy and slow response speed.

[0005] Firstly, this application provides a motor speed control method based on model predictive control. The state and control of the motor are described using a dq coordinate system, which consists of a d-axis and a q-axis. The method includes: acquiring motor parameters and d- and q-axis current reference signals; the motor parameters include d- and q-axis inductance values; combining the motor parameters, using model predictive control to start tracking the d- and q-axis current reference signals to determine the output voltage of the inverter connected to the motor; transforming the output voltage to the dq coordinate system using Park transformation to determine a finite element set; within the finite element set, traversing all possible switching sequences to determine the switching signal of the inverter, the switching signal acting on the inverter's switching transistors to cause the switching transistors to perform on / off switching, so that the motor current completes the task of tracking the d- and q-axis current reference signals.

[0006] In one implementation of the first aspect, the method further includes: determining the motor parameters; determining a 3D lookup table by applying an external voltage excitation under different ambient temperatures based on the stator voltage equation in the dq coordinate system; and determining the motor parameters by using the 3D lookup table in conjunction with the motor motion equation.

[0007] In one implementation of the first aspect, the motor is subjected to d-axis and q-axis current excitation at different ambient temperatures, and the d-axis and q-axis inductance values ​​are measured offline to obtain a 3D lookup table.

[0008] In one implementation of the first aspect, open-loop current is applied at 40℃, 80℃, and 100℃ respectively to measure the d-axis and q-axis inductance values ​​offline; wherein the q-axis current range is 0-10A, the d-axis current range is -10A-10A, and the step size is selected as 0.1A.

[0009] In one implementation of the first aspect, the method further includes: determining the d-axis and q-axis current reference signals; during the motor startup phase, causing the motor to output maximum torque to rapidly increase the speed, at which point the command current is simultaneously limited by the current limiting circle and the voltage limiting ellipse; when the set speed is not high, the motor enters a steady state at low speed, and the maximum torque-to-current ratio curve is used to reduce current loss; if the speed further increases, and the voltage limiting ellipse no longer includes the origin and the command speed is still greater than the current speed, the maximum torque-to-voltage ratio curve is used; when the command speed is equal to the actual speed at high speed, a fixed voltage-to-current curve is selected; a proportional-integral controller is used to generate torque commands, and the d-axis and q-axis current reference signals are generated using the Newton-Raphson method.

[0010] In one implementation of the first aspect, the inverter includes six switching transistors, which can only output seven effective voltages; the switching signal of the inverter is determined by traversing the seven possible switching sequences within the finite set of elements.

[0011] In one implementation of the first aspect, the step of determining the inverter's switching signals by traversing seven possible switching sequences within the finite set of elements includes: discretizing the motor equations based on the output voltage in the dq coordinate system; selecting a cost function to track the d- and q-axis current reference signals; finding the combination of switching signals with the minimum cost function value by traversing the seven possible switching sequences and predicting the current value at the next moment; and using the combination of switching signals to control the switching transistors to enable the motor current to track the d- and q-axis current reference signals.

[0012] Secondly, this application provides an inverter that uses the aforementioned model predictive control-based motor speed regulation method for control.

[0013] Thirdly, this application provides a motor control system, which includes the inverter described above.

[0014] In one implementation of the third aspect, the motor control system further includes an outer loop controller, a model predictive controller, and a motor; the outer loop controller outputs d-axis and q-axis current reference signals according to the received speed command; the model predictive controller determines a switching signal based on the d-axis and q-axis current reference signals and motor parameters derived from a 3D lookup table; and the inverter performs on or off operation according to the switching signal, thereby enabling the motor current to track the d-axis and q-axis current reference signals.

[0015] As described above, the motor speed control method, inverter, and control system based on model predictive control described in this application have the following beneficial effects:

[0016] This application establishes a 3D lookup table to accurately calculate the current curve, and uses the Newton-Raphson method to solve for the intersection of the curve and the command torque, thereby generating d and q current reference signals. Furthermore, it employs the FCS-MPC model predictive control method to track the current signal, resulting in fast response and low overshoot. Attached Figure Description

[0017] Figure 1 The diagram shows an application scenario of the motor speed control method based on model predictive control described in this application.

[0018] Figure 2 The diagram shown illustrates the principle flowchart of the motor speed control method based on model predictive control as described in the embodiments of this application.

[0019] Figure 3 This is another principle flowchart of the motor speed control method based on model predictive control described in the embodiments of this application.

[0020] Figure 4 The flowchart shown is a process for determining motor parameters in the motor speed control method based on model predictive control described in this application embodiment.

[0021] Figure 5 The flowchart shown is a reference signal determination flowchart for the motor speed regulation method based on model predictive control described in the embodiments of this application.

[0022] Figure 6 The diagram shown is a predictive control flowchart of the motor speed regulation method based on model predictive control as described in the embodiments of this application.

[0023] Figure 7 The diagram shown is a schematic diagram of the motor control system based on model predictive control as described in an embodiment of this application.

[0024] Figure 8 The diagram shown illustrates a specific application of the model predictive control-based motor speed regulation method described in this application embodiment.

[0025] Component designation explanation

[0026] 1. Motor control system

[0027] 11 Inverter

[0028] 12 Outer Loop Controller

[0029] 13 Model Predictive Controller

[0030] 14 Motors

[0031] Steps S2A, S2B, and S21-S24

[0032] S2A1~S2A2 Steps

[0033] S2B1~S2B5 Steps Detailed Implementation

[0034] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, unless otherwise specified, the following embodiments and features in the embodiments can be combined with each other.

[0035] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. Therefore, the illustrations only show the components related to this application and are not drawn according to the number, shape and size of the components in actual implementation. In actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0036] The following embodiments of this application provide a motor speed control method, inverter and control system based on model predictive control, including but not limited to applications in a speed control system formed by a controller, inverter and motor. The following description will take this hardware application scenario as an example.

[0037] Please see Figure 1 The diagram shows an application scenario of the motor speed control method based on model predictive control described in this application. Figure 1 As shown in the figure, this embodiment illustrates a motor control speed regulation system, which specifically includes: an outer loop controller such as MTPA and FW, an MPC controller, an inverter, and a motor connected to the inverter.

[0038] Taking a permanent magnet synchronous motor as an example, when the permanent magnet synchronous motor is running at low speed, the motor needs to reduce current loss by using the maximum torque per Ampere (MTPA). When the speed increases, the maximum torque per voltage (MTPV) or field weakening needs to be selected to obtain a wider speed range. In addition, the motor needs to operate in maximum torque mode during the start-up phase to quickly increase the speed.

[0039] The purpose of this application is to obtain a 3D lookup table by applying dq-axis current excitation to the motor at different temperatures and measuring the dq-axis inductance offline. Based on the difference between the set speed and the current speed and the load torque, the motor operating curve is determined, providing a dq-axis current reference signal. Finite set model predictive control is used to turn the inverter on or off, thereby enabling the motor current to track the reference signal.

[0040] The technical solutions in the embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0041] Please see Figure 2 The diagram shows the principle flowchart of the motor speed control method based on model predictive control described in the embodiments of this application. Figure 2 As shown, this embodiment provides a motor speed control method based on model predictive control. The motor state and control are described using a dq coordinate system, which consists of a d-axis and a q-axis. The method specifically includes the following steps:

[0042] S21, acquire motor parameters and d-axis and q-axis current reference signals; the motor parameters include d-axis and q-axis inductance values.

[0043] Specifically, the motor parameters are obtained by exporting a 3D lookup table, and the d-axis and q-axis current reference signals are obtained by outputting from the outer loop controller.

[0044] S22, combining the motor parameters, model predictive control is used to start tracking the d-axis and q-axis current reference signals to determine the output voltage of the inverter connected to the motor.

[0045] Specifically, after the outer loop controller provides the dq-axis current reference signal, finite set model predictive control (FCS-MPC) is used to control the inverter for rapid signal tracking. This is achieved by changing the voltage applied to the motor by the inverter to change the current and track the speed. FCS-MPC is a powerful control technique with advantages such as high precision, flexibility, stability, ease of implementation, and a simple and easy-to-understand concept; all control requirements can be considered simultaneously by a single controller.

[0046] S23, the output voltage is transformed to the dq coordinate system through the Park transformation to determine the finite set of elements.

[0047] In one embodiment, the inverter includes six switching transistors, which can output only seven effective voltages. The switching signals of the inverter are determined by traversing the seven possible switching sequences within the finite set of elements.

[0048] S24, within the finite set of elements, traverse all possible switching sequences to determine the switching signal of the inverter. The switching signal acts on the switching transistor of the inverter, causing the switching transistor to perform on / off switching, so that the current of the motor completes the task of tracking the d-axis and q-axis current reference signals.

[0049] In one embodiment, the motor speed control method based on model predictive control, in addition to steps S21 to S24, further includes: determining the motor parameters and determining the d-axis and q-axis current reference signals. Please refer to [link to relevant documentation]. Figure 3 This is another principle flowchart of the motor speed control method based on model predictive control described in the embodiments of this application. Figure 3 As shown, the motor speed control method based on model predictive control further includes, before the steps of obtaining motor parameters and d-axis and q-axis current reference signals: S2A, determining the motor parameters and S2B, determining the d-axis and q-axis current reference signals.

[0050] Please see Figure 4 The diagram shows a flowchart of the motor parameter determination process in the model predictive control-based motor speed control method described in this application embodiment. Figure 4 As shown, step S2A determines the motor parameters, which specifically includes the following steps.

[0051] S2A1, based on the stator voltage equation in the dq coordinate system, determines the 3d lookup table by external voltage excitation under different ambient temperatures.

[0052] S2A2, using the 3d lookup table and the motor motion equation, the motor parameters are determined.

[0053] In one embodiment, the motor is subjected to d-axis and q-axis current excitation at different ambient temperatures, and the d-axis and q-axis inductance values ​​are measured offline to obtain a 3D lookup table.

[0054] Furthermore, the d-axis and q-axis inductance values ​​were measured offline under open-loop current conditions of 40℃, 80℃, and 100℃, respectively; the q-axis current range was 0-10A, the d-axis current range was -10A-10A, and the step size was selected as 0.1A.

[0055] Specifically, the detailed process for determining the motor parameters is as follows:

[0056] For a three-phase permanent magnet synchronous motor, its stator voltage equation in the dq coordinate system can be expressed as:

[0057]

[0058] Among them, u d ,u q These are the d-axis and q-axis voltages, respectively, i d i q These are the d-axis and q-axis currents, respectively, R s It is the stator resistance of the motor, n p It is the number of pole pairs of the motor, L d ,L q These are the d-axis and q-axis inductances, respectively; ω is the angular velocity of the motor; and ψ... f It is a permanent magnet flux linkage.

[0059] Since the dq-axis inductance is synthesized from the motor phase inductance, and the motor inductance varies with current and temperature conditions, accurate inductance parameters are required for the controller. This invention employs an offline measurement method, applying open-loop currents at 40℃, 80℃, and 100℃. The q-axis current range is 0-10A, and the d-axis current range is -10A to 10A, with a step size of 0.1A. After measuring the inductance parameters, a 3D lookup table is obtained using linear interpolation.

[0060] The equation of motion of the motor is

[0061]

[0062] Where, τ e It is electromagnetic torque. Indicates the electromagnetic torque command value. The derivative of angular velocity, τ m It is the load torque, B mJ is the coefficient of kinetic friction, and J is the sum of the moments of inertia of the motor and the load.

[0063] Please see Figure 5 The flowchart shown is a reference signal determination flowchart for the motor speed control method based on model predictive control described in this application embodiment. In one embodiment, step S2B, determining the d-axis and q-axis current reference signals, specifically includes the following steps:

[0064] S2B1, during the motor start-up phase, the motor is made to output maximum torque so that the speed increases rapidly. At this time, the command current is simultaneously limited by the current limit circle and the voltage limit ellipse.

[0065] S2B2, when the set speed is not high, the motor enters a steady state at low speed and uses the maximum torque-to-current ratio curve to reduce current loss.

[0066] S2B3, if the speed increases further, the voltage limit ellipse no longer includes the origin, and the commanded speed is still greater than the current speed, the maximum torque-voltage ratio curve is used.

[0067] S2B4: When the commanded speed is equal to the actual speed at high speed, a fixed voltage-current curve is selected.

[0068] S2B5 uses a proportional-integral controller to generate torque commands and uses the Newton-Raphson method to generate the d-axis and q-axis current reference signals.

[0069] Specifically, the detailed process for determining the d-axis and q-axis current reference signals is as follows:

[0070] During the motor startup phase, the motor should output maximum torque to rapidly increase the speed. At this time, the command current is simultaneously limited by both the current limiting circle and the voltage limiting ellipse.

[0071]

[0072] Among them, I max It is the maximum current that the motor can withstand, U dc It is the voltage of the DC power supply. These are the reference signals for the dq-axis currents, ω e =n p ω is the electric angular velocity of the motor.

[0073] When the set speed is not high, the motor enters a steady state at low speed. At this time, the MTPA curve needs to be used to reduce current loss.

[0074]

[0075] If the rotational speed increases further, the voltage limit ellipse no longer includes the origin, and the commanded rotational speed is still greater than the current rotational speed, then the MTPV curve needs to be used:

[0076]

[0077] When the commanded speed at high speed is equal to the actual speed, select to use the FW curve:

[0078]

[0079] A PI controller is used to generate torque commands, and the Newton-Raphson method is used to solve the above equations to generate the dq-axis command current.

[0080] Please see Figure 6 The diagram shows the predictive control flowchart of the motor speed regulation method based on model predictive control described in the embodiments of this application. Figure 6 As shown, step S24, which involves traversing seven possible switching sequences within the finite set of elements to determine the switching signal of the inverter, specifically includes the following steps:

[0081] S241, Discretize the motor equations based on the output voltage in the dq coordinate system.

[0082] S242, In order to track the d-axis and q-axis current reference signals, a cost function is selected.

[0083] S243, by traversing 7 possible switching sequences and predicting the current value at the next moment, the combination of switching signals with the minimum cost function value is found. The combination of switching signals is used to control the switching transistor to make the motor current track the d-axis and q-axis current reference signals.

[0084] Specifically, the inverter switches are controlled using the MPC algorithm to track the dq-axis reference current provided by the outer loop.

[0085] After obtaining the dq-axis current reference signal, FCS-MPC is used to track the reference signal. The inverter output voltage is...

[0086]

[0087] Among them U dc It is DC voltage, s i i = a, b, c represent the states of the inverter switching transistors:

[0088]

[0089] The voltage is transformed to the dq coordinate system using the Park transformation, where k is the sampling time:

[0090]

[0091] Where θ is the electrical angle of the motor. Since the inverter's six switches can only output seven effective voltages, the controller input is selected from a finite set of elements at any given sampling time. The motor equations are discretized as follows:

[0092]

[0093] Where T s This is the sampling interval. To track the current signal from the outer loop, the cost function is chosen as:

[0094]

[0095] By iterating through seven possible switching sequences and predicting the current value at the next moment, the combination that minimizes the cost function value G can be found. By manipulating the switching transistors, the motor current can be made to track the reference signal, thereby outputting appropriate torque and achieving good speed regulation performance.

[0096] This application provides an inverter that is controlled using the model predictive control-based motor speed regulation method described above.

[0097] The motor speed control method based on model predictive control describes the state and control of the motor connected to the inverter using a dq coordinate system, which consists of a d-axis and a q-axis. The method includes: acquiring motor parameters and d- and q-axis current reference signals; the motor parameters include d- and q-axis inductance values; combining the motor parameters, using model predictive control to start tracking the d- and q-axis current reference signals to determine the output voltage of the inverter connected to the motor; transforming the output voltage to the dq coordinate system using Park transformation to determine a finite element set; within the finite element set, traversing all possible switching sequences to determine the inverter's switching signal, which acts on the inverter's switching transistors to cause them to switch on and off, enabling the motor current to track the d- and q-axis current reference signals.

[0098] Please see Figure 7 The diagram shown is a schematic diagram of the motor control system based on model predictive control as described in an embodiment of this application. Figure 7 As shown, this embodiment provides a motor control system, including the inverter.

[0099] In one embodiment, the motor control system further includes an outer loop controller, a model predictive controller, and a motor.

[0100] The outer loop controller outputs d-axis and q-axis current reference signals according to the received speed command. The model prediction controller determines the switching signal based on the d-axis and q-axis current reference signals and the motor parameters derived from the 3D lookup table. The inverter performs on or off according to the switching signal, thereby making the motor current track the d-axis and q-axis current reference signals.

[0101] Please see Figure 8 The diagram illustrates a specific application of the model predictive control-based motor speed control method described in this embodiment. Figure 8 As shown, the outer loop controller includes MTPA, MTPV and FW controllers, and the model prediction controller is an MPC controller.

[0102] The MTPA, MTPV, and FW controllers output d-axis and q-axis current reference signals according to the received speed command. The MPC controller determines the switching signal based on the d-axis and q-axis current reference signals and the motor parameters derived from the 3D lookup table. The inverter performs on or off according to the switching signal, thereby enabling the motor current to track the d-axis and q-axis current reference signals.

[0103] Combination Figure 7 and Figure 8 As shown, the operating principle of the motor control system described in this application is as follows:

[0104] (1) Determine the motor parameters.

[0105] For a three-phase permanent magnet synchronous motor, its stator voltage equation in the dq coordinate system can be expressed as:

[0106]

[0107] Among them, u d ,u q These are the d-axis and q-axis voltages, respectively, i d i q These are the d-axis and q-axis currents, respectively, R s It is the stator resistance of the motor, n p It is the number of pole pairs of the motor, L d ,L q These are the d-axis and q-axis inductances, respectively; ω is the angular velocity of the motor; and ψ... f It is a permanent magnet flux linkage.

[0108] Since the dq-axis inductance is synthesized from the motor phase inductance, and the motor inductance varies with current and temperature conditions, accurate inductance parameters are required for the controller. This invention employs an offline measurement method, applying open-loop currents at 40℃, 80℃, and 100℃. The q-axis current range is 0-10A, and the d-axis current range is -10A to 10A, with a step size of 0.1A. After measuring the inductance parameters, a 3D lookup table is obtained using linear interpolation.

[0109] The equation of motion for the electric motor is:

[0110]

[0111] Where, τ e It is electromagnetic torque. Indicates the electromagnetic torque command value. The derivative of angular velocity, τ m It is the load torque, B m J is the coefficient of kinetic friction, and J is the sum of the moments of inertia of the motor and the load.

[0112] (2) The outer loop controller determines the reference current.

[0113] During the motor startup phase, the motor should output maximum torque to rapidly increase the speed. At this time, the command current is simultaneously limited by both the current limiting circle and the voltage limiting ellipse.

[0114]

[0115] Among them, I max It is the maximum current that the motor can withstand, U dc It is the voltage of the DC power supply. These are the reference signals for the dq-axis currents, ω e =n p ω is the electric angular velocity of the motor.

[0116] When the set speed is not high, the motor enters a steady state at low speed. At this time, the MTPA curve needs to be used to reduce current loss.

[0117]

[0118] If the rotational speed increases further, the voltage limit ellipse no longer includes the origin, and the commanded rotational speed is still greater than the current rotational speed, then the MTPV curve needs to be used:

[0119]

[0120] When the commanded speed at high speed is equal to the actual speed, select to use the FW curve:

[0121]

[0122] A PI controller is used to generate torque commands, and the Newton-Raphson method is used to solve the above equations to generate the dq-axis command current.

[0123] (3) The inverter switch is controlled by the MPC algorithm to track the dq axis reference current given by the outer loop.

[0124] After obtaining the dq-axis current reference signal, FCS-MPC is used to track the reference signal. The inverter output voltage is...

[0125]

[0126] Among them U dc It is DC voltage, s i i = a, b, c represent the states of the inverter switching transistors:

[0127]

[0128] The voltage is transformed to the dq coordinate system using the Park transformation, where k is the sampling time:

[0129]

[0130] Since the inverter's six switches can only output seven effective voltages, the controller input is selected from a finite set of elements at any sampling time k. The motor equations are then discretized:

[0131]

[0132] To track the current signal provided by the outer loop, the cost function is chosen as follows:

[0133]

[0134] By iterating through seven possible switching sequences and predicting the current value at the next moment, the combination that minimizes the cost function value is found. By manipulating the switching transistors, the motor current can be made to track the reference signal, thereby outputting appropriate torque and achieving good speed regulation performance.

[0135] The scope of protection for the motor speed regulation method based on model predictive control described in this application is not limited to the execution order of the steps listed in this embodiment. Any solution implemented by adding, subtracting, or replacing steps in the prior art based on the principles of this application is included within the scope of protection of this application.

[0136] The motor control system described in this application embodiment can implement the motor speed regulation method based on model predictive control described in this application. However, the implementation device of the motor speed regulation method based on model predictive control described in this application includes, but is not limited to, the structure of the motor control system listed in this embodiment. All structural modifications and substitutions of the prior art made in accordance with the principles of this application are included within the protection scope of this application.

[0137] In the embodiments provided in this application, it should be understood that the disclosed systems or methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For instance, the division of modules / units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or units may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices, or modules or units, and may be electrical, mechanical, or other forms.

[0138] The modules / units described as separate components may or may not be physically separate. The components shown as modules / units may or may not be physical modules; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules / units can be selected to achieve the objectives of the embodiments of this application, depending on actual needs. For example, the functional modules / units in the various embodiments of this application may be integrated into one processing module, or each module / unit may exist physically separately, or two or more modules / units may be integrated into one module / unit.

[0139] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0140] The descriptions of the processes or structures corresponding to the above figures each have their own emphasis. For parts of a process or structure that are not described in detail, please refer to the relevant descriptions of other processes or structures.

[0141] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in this application should still be covered by the claims of this application.

Claims

1. A motor speed control method based on model predictive control, characterized in that, The state and control of the motor are described using a dq coordinate system, which consists of a d-axis and a q-axis; the method includes: Acquire motor parameters and d-axis and q-axis current reference signals; the motor parameters include d-axis and q-axis inductance values. Based on the motor parameters, model predictive control is used to track the d-axis and q-axis current reference signals to determine the output voltage of the inverter connected to the motor. The output voltage is transformed to the dq coordinate system using the Park transformation to determine a finite set of elements. Within the finite set of elements, all possible switching sequences are traversed to determine the switching signal of the inverter. The switching signal acts on the switching transistor of the inverter, causing the switching transistor to perform on / off switching, so that the current of the motor completes the task of tracking the d-axis and q-axis current reference signals.

2. The method according to claim 1, characterized in that, The method further includes: determining the motor parameters; Based on the stator voltage equation in the dq coordinate system, the 3d lookup table is determined by external voltage excitation under different ambient temperatures; The motor parameters are determined using the 3D lookup table and the motor motion equation.

3. The method according to claim 2, characterized in that: Under different ambient temperatures, d-axis and q-axis current excitations are applied to the motor, and the d-axis and q-axis inductance values ​​are measured offline to obtain a 3D lookup table.

4. The method according to claim 3, characterized in that: Offline measurements of d-axis and q-axis inductance were performed by applying open-loop current at 40℃, 80℃, and 100℃. The q-axis current range was 0-10A, the d-axis current range was -10A to 10A, and the step size was 0.1A.

5. The method according to claim 1, characterized in that, The method further includes: determining the d-axis and q-axis current reference signals; During the motor startup phase, the motor outputs maximum torque to rapidly increase the speed. At this time, the command current is simultaneously limited by the current limit circle and the voltage limit ellipse. When the set speed is not high, the motor enters a steady state at low speed and uses the maximum torque-to-current ratio curve to reduce current loss. If the speed increases further, the voltage limit ellipse no longer includes the origin, and the commanded speed is still greater than the current speed, then the maximum torque-voltage ratio curve is used. When the commanded speed at high speed is equal to the actual speed, a fixed voltage-current curve should be selected. Torque commands are generated using a proportional-integral controller, and the d-axis and q-axis current reference signals are generated using the Newton-Raphson method.

6. The method according to claim 1, characterized in that, The inverter includes 6 switching transistors, which can only output 7 effective voltages; Within the finite set of elements, the switching signals of the inverter are determined by traversing seven possible switching sequences.

7. The method according to claim 6, characterized in that, The step of determining the switching signal of the inverter by traversing seven possible switching sequences within the finite set of elements includes: Discretize the motor equations based on the output voltage in the dq coordinate system; To track the d-axis and q-axis current reference signals, a cost function is selected; By traversing seven possible switching sequences and predicting the current value at the next moment, the combination of switching signals with the minimum cost function value is found. The switching signals are then used to control the switching transistors to make the motor current track the d-axis and q-axis current reference signals.

8. An inverter, characterized in that, The inverter is controlled using the motor speed regulation method based on model predictive control as described in any one of claims 1 to 7.

9. A motor control system, characterized in that, The motor control system includes the inverter as described in claim 8.

10. The motor control system according to claim 9, characterized in that: The motor control system also includes an outer loop controller, a model prediction controller, and a motor; The outer loop controller outputs d-axis and q-axis current reference signals according to the received speed command. The model prediction controller determines the switching signal based on the d-axis and q-axis current reference signals and the motor parameters derived from the 3D lookup table. The inverter performs on or off according to the switching signal, thereby making the motor current track the d-axis and q-axis current reference signals.

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