Induction motor time-varying phase domain modeling method and system based on discrete coordinate system
By using discrete coordinate system transformation and Clark inverse transformation, an electromagnetic transient VBR model of the induction motor is constructed, which solves the problem that the induction motor model and the network model cannot be directly solved together, and realizes efficient and stable multi-machine system simulation.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-02
- Publication Date
- 2026-03-27
Smart Images
Figure CN121744618A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of electromagnetic transient modeling technology for power systems, and more specifically, to a method and system for time-varying phase domain modeling of induction motors based on discrete coordinate systems. Background Technology
[0002] Currently, electromagnetic transient simulation software commonly employs induction motor modeling methods based on a universal coordinate system (such as the dq0 model). However, since the network model typically uses abc phase components, the dq0 model cannot be directly solved in conjunction with the network model; it can only be solved indirectly through the motor-grid interface, which easily introduces computational errors and numerical instability.
[0003] In existing technologies, for rotating equipment such as induction motors, a modeling approach with strong stator-rotor coupling is typically used. This results in complex models, low computational efficiency, and difficulty in adapting to the simulation requirements of multi-machine systems. Furthermore, traditional models contain a large number of time-varying parameters, which further exacerbates numerical oscillations and simulation convergence difficulties. Summary of the Invention
[0004] To address the above problems, this invention proposes a time-varying phase domain modeling method for induction motors based on discrete coordinate systems, comprising:
[0005] The stator and rotor circuits and rotor components of the induction motor are transformed in a discrete coordinate system to construct the mutual inductance matrix between the stator and rotor.
[0006] Based on the mutual inductance matrix, the rotor current component in the stator voltage equation is replaced with the flux linkage equation to obtain the subtransient expression of the stator circuit. Then, the Clark inverse transform is applied to obtain the stator voltage equation suitable for solving the network simultaneously.
[0007] The stator voltage equations suitable for network simultaneous solution are discretized to construct an electromagnetic transient VBR model of the time-varying phase domain of the induction motor.
[0008] Optionally, discrete coordinate system transformations of the induction motor stator and rotor circuits include:
[0009] The stator and rotor circuits of the induction motor are transformed from the abc coordinate system to the stator αβ coordinate system and the rotor αβ coordinate system, respectively.
[0010] Optional, discrete coordinate system transformations of the rotor components include:
[0011] The rotor components are transformed from the rotor αβ coordinate system to the rotor dq coordinate system, and the rotor dq coordinate system is kept relatively stationary with respect to the stator αβ coordinate system.
[0012] Optionally, the mutual inductance matrix can be a constant matrix.
[0013] Optionally, a mutual inductance matrix between the stator and rotor can be constructed to eliminate time-varying parameters.
[0014] Optionally, apply the Clark inverse transform, including:
[0015] The stator voltage equations, which are obtained in the subtransient form of the stator circuit, are transformed from the αβ0 coordinate system to the abc coordinate system.
[0016] Optionally, the induction motor can be equivalent to a Thevenin / Norton circuit, and the electromagnetic transient VBR model can be solved simultaneously using the predicted rotor speed.
[0017] Furthermore, this invention also proposes a time-varying phase domain modeling system for induction motors based on discrete coordinate systems, comprising:
[0018] The first transformation unit is used to perform discrete coordinate system transformation on the stator and rotor circuits and rotor components of the induction motor to construct the mutual inductance matrix between the stator and rotor.
[0019] The second transformation unit is used to replace the rotor current component in the stator voltage equation with the flux linkage equation based on the mutual inductance matrix, obtain the subtransient expression of the stator circuit, and then apply the Clark inverse transformation to obtain the stator voltage equation suitable for network simultaneous solution.
[0020] The modeling unit is used to discretize the stator voltage equations suitable for network simultaneous solution in order to construct the electromagnetic transient VBR model of the time-varying phase domain of the induction motor.
[0021] Optionally, discrete coordinate system transformations of the induction motor stator and rotor circuits include:
[0022] The stator and rotor circuits of the induction motor are transformed from the abc coordinate system to the stator αβ coordinate system and the rotor αβ coordinate system, respectively.
[0023] Optional, discrete coordinate system transformations of the rotor components include:
[0024] The rotor components are transformed from the rotor αβ coordinate system to the rotor dq coordinate system, and the rotor dq coordinate system is kept relatively stationary with respect to the stator αβ coordinate system.
[0025] Optionally, the mutual inductance matrix can be a constant matrix.
[0026] Optionally, a mutual inductance matrix between the stator and rotor can be constructed to eliminate time-varying parameters.
[0027] Optionally, apply the Clark inverse transform, including:
[0028] The stator voltage equations, which are obtained in the subtransient form of the stator circuit, are transformed from the αβ0 coordinate system to the abc coordinate system.
[0029] Optionally, the induction motor can be equivalent to a Thevenin / Norton circuit, and the electromagnetic transient VBR model can be solved simultaneously using the predicted rotor speed.
[0030] In another aspect, the present invention also provides a computing device, comprising: one or more processors;
[0031] A processor is used to execute one or more programs;
[0032] When the one or more programs are executed by the one or more processors, the method described above is implemented.
[0033] In another aspect, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements the method described above.
[0034] Compared with the prior art, the beneficial effects of the present invention are as follows:
[0035] This invention provides a time-varying phase domain modeling method for induction motors based on discrete coordinate systems. The method includes: transforming the stator and rotor circuits and rotor components of the induction motor into discrete coordinate systems to construct a mutual inductance matrix between the stator and rotor; based on the mutual inductance matrix, replacing the rotor current component in the stator voltage equation with a flux linkage equation to obtain the subtransient expression of the stator circuit; applying an inverse Clark transform to obtain a stator voltage equation suitable for network simultaneous solution; and discretizing the stator voltage equation suitable for network simultaneous solution to construct an electromagnetic transient VBR model of the induction motor in the time-varying phase domain. This invention is applicable to multi-machine system simulation, has high computational efficiency, and is easy to implement in engineering. Attached Figure Description
[0036] Figure 1 This is a flowchart of the method of the present invention;
[0037] Figure 2 A schematic diagram of the αβ-dq coordinate system of the induction motor provided by the present invention;
[0038] Figure 3 A flowchart illustrating the calculation rules of the VBR model provided by this invention;
[0039] Figure 4 A simulation comparison diagram of the A-phase armature current provided by this invention;
[0040] Figure 5 Simulation comparison chart of active power provided for this invention;
[0041] Figure 6 Simulation comparison diagram of electromagnetic torque provided for this invention.
[0042] Figure 7 This is a structural diagram of the system of the present invention. Detailed Implementation
[0043] Exemplary embodiments of the invention will now be described with reference to the accompanying drawings. However, the invention may be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided to fully and completely disclose the invention and to fully convey its scope to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the drawings is not intended to limit the invention. In the drawings, the same units / elements are referred to by the same reference numerals.
[0044] Unless otherwise stated, the terms used herein (including technical terms) have their common meaning as understood by one of ordinary skill in the art. Furthermore, it is understood that terms defined in commonly used dictionaries should be understood to have a meaning consistent with the context of their relevant field, and not to be interpreted as having an idealized or overly formal meaning.
[0045] Example 1:
[0046] This invention proposes a time-varying phase domain modeling method S100 for induction motors based on discrete coordinate systems, such as... Figure 1 As shown, it includes:
[0047] S101, the stator and rotor circuits and rotor components of the induction motor are transformed in a discrete coordinate system to construct the mutual inductance matrix between the stator and rotor.
[0048] S102, Based on the mutual inductance matrix, the rotor current component in the stator voltage equation is replaced with the flux linkage equation. After obtaining the subtransient expression of the stator circuit, the Clark inverse transform is applied to obtain the stator voltage equation suitable for network simultaneous solution.
[0049] S103 discretizes the stator voltage equations suitable for network simultaneous solution to construct an electromagnetic transient VBR model of the time-varying phase domain of the induction motor.
[0050] The discrete coordinate system transformation of the stator and rotor circuits of the induction motor includes:
[0051] The stator and rotor circuits of the induction motor are transformed from the abc coordinate system to the stator αβ coordinate system and the rotor αβ coordinate system, respectively.
[0052] The discrete coordinate system transformation of the rotor components includes:
[0053] The rotor components are transformed from the rotor αβ coordinate system to the rotor dq coordinate system, and the rotor dq coordinate system is kept relatively stationary with respect to the stator αβ coordinate system.
[0054] The mutual inductance matrix is a constant matrix.
[0055] Among them, the mutual inductance matrix between the stator and the rotor is constructed to eliminate time-varying parameters.
[0056] The application of the Clark inverse transform includes:
[0057] The stator voltage equations, which are obtained in the subtransient form of the stator circuit, are transformed from the αβ0 coordinate system to the abc coordinate system.
[0058] In this method, the induction motor is equivalent to a Thevenin / Norton circuit, and the electromagnetic transient VBR model is solved simultaneously using the predicted rotor speed.
[0059] The following is combined Figure 2-6 The invention will be further illustrated by specific implementation examples:
[0060] Specific examples include:
[0061] Transform the stator and rotor circuits of the induction motor from the abc coordinate system to the stator αβ coordinate system and the rotor αβ coordinate system, respectively, as follows: Figure 2 As shown;
[0062] Transform the rotor components from the rotor αβ coordinate system to the rotor dq coordinate system, and keep the rotor dq coordinate system relatively stationary with the stator αβ coordinate system;
[0063] The mutual inductance matrix between the stator and rotor is constructed as a constant matrix to eliminate time-varying parameters;
[0064] By replacing the rotor current component in the stator voltage equation with the flux linkage equation, the subtransient expression of the stator circuit is obtained.
[0065] Applying the Clark inverse transformation to the stator voltage equations transforms them from the αβ0 coordinate system to the abc coordinate system, resulting in stator voltage equations suitable for solving simultaneous network problems.
[0066] The stator voltage equation is discretized to construct an electromagnetic transient VBR model of the induction motor.
[0067] The induction motor is equivalent to a Thevenin / Norton circuit, and the rotor speed is predicted to achieve a direct solution in conjunction with the network model. The calculation rules are as follows: Figure 3 As shown, the calculation results are as follows: Figure 4-6 As shown.
[0068] Taking a squirrel-cage induction motor as an example, the specific implementation steps are as follows:
[0069] Step 1: Set motor parameters: stator resistance 1.1936Ω, rotor resistance 0.6258Ω, stator leakage inductance 0.7mH, rotor leakage inductance 5.5mH, mutual inductance 35mH, number of pole pairs 2;
[0070] Step 2: Write a VBR model calculation program in VS2017 and embed it into the ADPSS simulation platform;
[0071] Set the simulation step size to 5e-5s, the simulation duration to 10s, and the voltage source to 500V / 50Hz.
[0072] Step 3: Transform the stator voltage equations to the abc coordinate system using the Clark inverse transform, and solve them simultaneously with the network model;
[0073] Step 4: Compare the Simulink simulation results. The errors in phase A current, active power, and electromagnetic torque are all less than 0.1%, verifying the accuracy of the model.
[0074] This invention transforms the mutual inductance matrix between the stator and rotor from a time-varying matrix to a constant matrix by processing with a discrete coordinate system, which significantly improves the numerical stability of the model.
[0075] After Clark inverse transform, the stator circuit can be directly solved in conjunction with the network model, avoiding interface errors.
[0076] The VBR model has a simple structure, is easy to discretize, and is suitable for electromagnetic transient simulation platforms.
[0077] The simulation results showed an error of less than 0.1% compared with platforms such as Simulink and ADPSS, verifying the accuracy of the model.
[0078] Example 2:
[0079] This invention also proposes a time-varying phase domain modeling system 200 for induction motors based on discrete coordinate systems, such as... Figure 7 As shown, it includes:
[0080] The first transformation unit 201 is used to perform discrete coordinate system transformation on the stator and rotor circuits and rotor components of the induction motor to construct the mutual inductance matrix between the stator and rotor.
[0081] The second transformation unit 202 is used to replace the rotor current component in the stator voltage equation with the flux linkage equation based on the mutual inductance matrix, obtain the subtransient expression of the stator circuit, and then apply the Clark inverse transformation to obtain the stator voltage equation suitable for network simultaneous solution.
[0082] Modeling unit 203 is used to discretize the stator voltage equations suitable for network simultaneous solution in order to construct the electromagnetic transient VBR model of the time-varying phase domain of the induction motor.
[0083] The discrete coordinate system transformation of the stator and rotor circuits of the induction motor includes:
[0084] The stator and rotor circuits of the induction motor are transformed from the abc coordinate system to the stator αβ coordinate system and the rotor αβ coordinate system, respectively.
[0085] The discrete coordinate system transformation of the rotor components includes:
[0086] The rotor components are transformed from the rotor αβ coordinate system to the rotor dq coordinate system, and the rotor dq coordinate system is kept relatively stationary with respect to the stator αβ coordinate system.
[0087] The mutual inductance matrix is a constant matrix.
[0088] Among them, the mutual inductance matrix between the stator and the rotor is constructed to eliminate time-varying parameters.
[0089] The application of the Clark inverse transform includes:
[0090] The stator voltage equations, which are obtained in the subtransient form of the stator circuit, are transformed from the αβ0 coordinate system to the abc coordinate system.
[0091] In this method, the induction motor is equivalent to a Thevenin / Norton circuit, and the electromagnetic transient VBR model is solved simultaneously using the predicted rotor speed.
[0092] This invention is applicable to multi-machine system simulation, has high computational efficiency, and is easy to implement in engineering.
[0093] Example 3:
[0094] Based on the same inventive concept, this invention also provides a computer device, which includes a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to implement corresponding method flows or corresponding functions, thereby implementing the steps of the methods in the above embodiments.
[0095] Example 4:
[0096] Based on the same inventive concept, this invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of the method in the above embodiments.
[0097] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention can be implemented using various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.
[0098] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0099] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.
[0100] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.
[0101] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.
[0102] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.
Claims
1. A method for modeling the time-varying phase domain of an induction motor based on a discrete coordinate system, characterized in that, include: The stator and rotor circuits and rotor components of the induction motor are transformed in a discrete coordinate system to construct the mutual inductance matrix between the stator and rotor. Based on the mutual inductance matrix, the rotor current component in the stator voltage equation is replaced with the flux linkage equation to obtain the subtransient expression of the stator circuit. Then, the Clark inverse transform is applied to obtain the stator voltage equation suitable for solving the network simultaneously. The stator voltage equations suitable for network simultaneous solution are discretized to construct an electromagnetic transient VBR model of the time-varying phase domain of the induction motor.
2. The time-varying phase domain modeling method for induction motors according to claim 1, characterized in that, The discrete coordinate system transformation of the stator and rotor circuits of an induction motor includes: The stator and rotor circuits of the induction motor are transformed from the abc coordinate system to the stator αβ coordinate system and the rotor αβ coordinate system, respectively.
3. The time-varying phase domain modeling method for induction motors according to claim 1, characterized in that, Its features are, Discrete coordinate system transformation of rotor components includes: The rotor components are transformed from the rotor αβ coordinate system to the rotor dq coordinate system, and the rotor dq coordinate system is kept relatively stationary with respect to the stator αβ coordinate system.
4. The time-varying phase domain modeling method for induction motors according to claim 1, characterized in that, Its features are, The mutual inductance matrix is a constant matrix.
5. The time-varying phase domain modeling method for induction motors according to claim 1, characterized in that, Its features are, Construct a mutual inductance matrix between the stator and rotor to eliminate time-varying parameters.
6. The time-varying phase domain modeling method for induction motors according to claim 1, characterized in that, Its features are, Apply the Clark inverse transform, including: The stator voltage equations, which are obtained in the subtransient form of the stator circuit, are transformed from the αβ0 coordinate system to the abc coordinate system.
7. The time-varying phase domain modeling method for induction motors according to claim 1, characterized in that, The induction motor is equivalent to a Thevenin / Norton circuit, and the electromagnetic transient VBR model is solved simultaneously using the predicted rotor speed.
8. A time-varying phase domain modeling system for induction motors based on discrete coordinate systems, characterized in that, include: The first transformation unit is used to perform discrete coordinate system transformation on the stator and rotor circuits and rotor components of the induction motor to construct the mutual inductance matrix between the stator and rotor. The second transformation unit is used to replace the rotor current component in the stator voltage equation with the flux linkage equation based on the mutual inductance matrix, obtain the subtransient expression of the stator circuit, and then apply the Clark inverse transformation to obtain the stator voltage equation suitable for network simultaneous solution. The modeling unit is used to discretize the stator voltage equations suitable for network simultaneous solution in order to construct the electromagnetic transient VBR model of the time-varying phase domain of the induction motor.
9. The time-varying phase domain modeling system for induction motors according to claim 8, characterized in that, The discrete coordinate system transformation of the stator and rotor circuits of an induction motor includes: The stator and rotor circuits of the induction motor are transformed from the abc coordinate system to the stator αβ coordinate system and the rotor αβ coordinate system, respectively.
10. The time-varying phase domain modeling system for induction motors according to claim 8, characterized in that, Its features are, Discrete coordinate system transformation of rotor components includes: The rotor components are transformed from the rotor αβ coordinate system to the rotor dq coordinate system, and the rotor dq coordinate system is kept relatively stationary with respect to the stator αβ coordinate system.
11. The time-varying phase domain modeling system for induction motors according to claim 8, characterized in that, Its features are, The mutual inductance matrix is a constant matrix.
12. The time-varying phase domain modeling method for induction motors according to claim 8, characterized in that, Its features are, Construct a mutual inductance matrix between the stator and rotor to eliminate time-varying parameters.
13. The time-varying phase domain modeling system for induction motors according to claim 8, characterized in that, Its features are, Apply the Clark inverse transform, including: The stator voltage equations, which are obtained in the subtransient form of the stator circuit, are transformed from the αβ0 coordinate system to the abc coordinate system.
14. The time-varying phase domain modeling system for induction motors according to claim 8, characterized in that, The induction motor is equivalent to a Thevenin / Norton circuit, and the electromagnetic transient VBR model is solved simultaneously using the predicted rotor speed.
15. A computer device, characterized in that, include: One or more processors; A processor is used to execute one or more programs; When the one or more programs are executed by the one or more processors, the method described in any one of claims 1-7 is implemented.
16. A computer-readable storage medium, characterized in that, It contains a computer program, which, when executed, implements the method as described in any one of claims 1-7.