Simulation modeling method and system for real-time model of silicon carbide IGBT module
Patent Information
- Application Number
- PCT/CN2025/142508
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2025-02-21
- Filing Date
- 2025-12-15
- Publication Date
- 2026-08-27
Smart Images
Figure CN2025142508_27082026_PF_FP_ABST
Abstract
Description
A simulation modeling method and system for real-time models of silicon carbide IGBT modules
[0001] This application claims priority to Chinese Patent Application No. 202510195027.9, filed on February 21, 2025, entitled "A Simulation Modeling Method and System for Real-Time Model of Silicon Carbide IGBT Module", the entire contents of which are incorporated herein by reference. Technical Field
[0002] This application relates to the field of power electronics technology, and in particular to a simulation modeling method and system for a real-time model of a silicon carbide IGBT module. Background Technology
[0003] With the development of materials science, silicon carbide has gradually entered the field of power semiconductors. It has the characteristics of low device capacitance, small temperature-dependent switching losses, extremely low reverse recovery effect and no threshold voltage for conduction. Its advantages are reflected in high efficiency, low cooling requirements, high operating frequency and increased power density.
[0004] Currently, traditional IGBT power electronic switches have certain limitations in the field of power electronics. With the widespread application of silicon carbide (SiC) IGBTs, the parasitic parameters within SiC IGBT modules are significantly reduced compared to traditional IGBTs, improving the feasibility of switching frequencies. However, SiC IGBT modules also introduce a new oscillating characteristic during switching. Simulating this oscillation characteristic using traditional physical methods would greatly increase the computational load, resulting in low simulation modeling efficiency. Summary of the Invention
[0005] This application provides a simulation modeling method and system for real-time models of silicon carbide IGBT modules, solving the technical problem of how to improve the simulation modeling efficiency of silicon carbide IGBT modules.
[0006] The first aspect of this application provides a simulation modeling method for a real-time model of a silicon carbide IGBT module, including:
[0007] In response to a modeling request for a target IGBT module, the module characteristic parameters of the target IGBT module are obtained through a preset device data table;
[0008] By performing a switching operation on the preset module equivalent circuit, the oscillation characteristic parameters of the target IGBT module during the instantaneous oscillation phase of the switching are obtained.
[0009] An initial real-time model is constructed, and the oscillation characteristic parameters and the module characteristic parameters are input into the initial real-time model to perform real-time oscillation simulation, and the oscillation simulation data is output.
[0010] Compare the oscillation simulation data with the preset standard operating condition data;
[0011] If the oscillation simulation data is consistent with the preset standard operating condition data, then the initial real-time model will be used as the target real-time model of the target IGBT module.
[0012] Optionally, it also includes:
[0013] If the oscillation simulation data is inconsistent with the preset standard operating condition data, then proceed to the step of obtaining the oscillation characteristic parameters of the target IGBT module during the instantaneous oscillation phase by performing a switching operation on the preset module equivalent circuit.
[0014] Optionally, the oscillation characteristic parameters include a first oscillation characteristic parameter and a second oscillation characteristic parameter, the initial real-time model includes an instantaneous on-state oscillation circuit model and an instantaneous off-state oscillation circuit model, and the step of using the oscillation characteristic parameters and the module characteristic parameters to input the initial real-time model for real-time oscillation simulation and outputting oscillation simulation data includes:
[0015] The first oscillation characteristic parameter and the module characteristic parameter are used to input the instantaneous oscillation circuit model for real-time oscillation simulation, and the first oscillation simulation data is output.
[0016] The second oscillation characteristic parameter and the module characteristic parameter are used to input the instantaneous oscillation circuit model for real-time oscillation simulation, and the second oscillation simulation data is output.
[0017] The oscillation simulation data includes the first oscillation simulation data and the second oscillation simulation data.
[0018] Optionally, the first oscillation characteristic parameters include first gate resistance data, first parasitic inductance data, and first parasitic capacitance data. The step of using the first oscillation characteristic parameters and the module characteristic parameters to input the instantaneous oscillation circuit model for real-time oscillation simulation and outputting the first oscillation simulation data includes:
[0019] The first gate resistance data is used as input to the first preset gate total resistance function to determine the first total equivalent resistance simulation data.
[0020] The first parasitic inductance data is used as input to the first preset total parasitic inductance function to determine the first total parasitic inductance simulation data;
[0021] The first parasitic capacitance data is used as input to the first preset total parasitic capacitance function to determine the first total parasitic capacitance simulation data;
[0022] The simulation data of the first total parasitic inductance, the simulation data of the first total parasitic capacitance, and the module characteristic parameters are used to determine the simulation data of the first maximum reverse current.
[0023] The first oscillation simulation data includes the first total equivalent resistance simulation data, the first total parasitic inductance simulation data, the first total parasitic capacitance simulation data, and the first maximum reverse current simulation data.
[0024] Optionally, the second oscillation characteristic parameters include second gate resistance data, second parasitic inductance data, and second parasitic capacitance data. The step of using the second oscillation characteristic parameters and the module characteristic parameters to input the instantaneous oscillation circuit model for real-time oscillation simulation and outputting the second oscillation simulation data includes:
[0025] The second gate resistor data, the second parasitic inductance data, the second parasitic capacitance data, and the module characteristic parameters are used to determine the second-order circuit simulation data;
[0026] The simulation data for the first-order circuit are determined using the module characteristic parameters.
[0027] The second oscillation simulation data includes the first-order circuit simulation data and the second-order circuit simulation data.
[0028] Optionally, the step of determining the second-order circuit simulation data using the second gate resistance data, the second parasitic inductance data, the second parasitic capacitance data, and the module characteristic parameters includes:
[0029] The second gate resistance data is used as input to the second preset gate total resistance function to determine the second total equivalent resistance simulation data.
[0030] The second parasitic inductance data is used as input to the second preset total parasitic inductance function to determine the second total parasitic inductance simulation data;
[0031] The second parasitic capacitance data is used as input to the second preset total parasitic capacitance function to determine the second total parasitic capacitance simulation data;
[0032] The second maximum reverse current simulation data is determined using the second total parasitic inductance simulation data, the second total parasitic capacitance simulation data, and the module characteristic parameters.
[0033] The second-order circuit simulation data includes the second total equivalent resistance simulation data, the second total parasitic inductance simulation data, the second total parasitic capacitance simulation data, and the second maximum reverse current simulation data.
[0034] The second aspect of this application provides a simulation modeling system for a real-time model of a silicon carbide IGBT module, comprising:
[0035] The response module is used to respond to the modeling request for the target IGBT module and obtain the module characteristic parameters of the target IGBT module through a preset device data table.
[0036] The switching operation module is used to obtain the oscillation characteristic parameters of the target IGBT module during the instantaneous oscillation phase of switching by performing switching operations on the preset module equivalent circuit;
[0037] The oscillation simulation module is used to construct an initial real-time model, and to perform real-time oscillation simulation by inputting the oscillation characteristic parameters and the module characteristic parameters into the initial real-time model, and output oscillation simulation data.
[0038] The data comparison module is used to compare the oscillation simulation data with the preset standard operating condition data;
[0039] The model output module is used to use the initial real-time model as the target real-time model of the target IGBT module if the oscillation simulation data is consistent with the preset standard operating condition data.
[0040] The third aspect of this application provides an electronic device, including a memory and a processor. The memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the simulation modeling method for a real-time model of a silicon carbide IGBT module as described in any of the preceding claims.
[0041] The fourth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements a simulation modeling method for a real-time model of a silicon carbide IGBT module as described in any of the preceding claims.
[0042] The fifth aspect of this application provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, wherein, when the program instructions are executed by a computer, the computer performs a simulation modeling method for a real-time model of a silicon carbide IGBT module as described in any of the preceding claims.
[0043] As can be seen from the above technical solutions, this application has the following advantages:
[0044] This application is applied to silicon carbide IGBT modules. Based on the acquired module characteristic parameters and oscillation characteristic parameters, and through targeted data acquisition methods, it can quickly and accurately provide key information for modeling, greatly reducing unnecessary computation and significantly improving modeling efficiency. Based on the constructed initial real-time model, real-time oscillation simulation is performed using the acquired oscillation characteristic parameters and module characteristic parameters. This can more accurately simulate the instantaneous switching oscillation characteristics of silicon carbide IGBT modules in actual operation. By comparing the oscillation simulation data with the preset standard operating condition data, if the two are consistent, the initial real-time model is used as the target real-time model to ensure model accuracy. Attached Figure Description
[0045] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0046] Figure 1 is a flowchart of the simulation modeling method for a real-time model of a silicon carbide IGBT module provided in an embodiment of this application;
[0047] Figure 2 is a schematic diagram of the equivalent circuit of the preset module of this application;
[0048] Figure 3 is a schematic diagram of the oscillation stage when the first silicon carbide IGBT module is turned on and the second silicon carbide IGBT module is turned off in this application.
[0049] Figure 4 is a schematic diagram of the oscillation stage when the first silicon carbide IGBT module is turned off and the second silicon carbide IGBT module is turned on in this application.
[0050] Figure 5 is a schematic diagram of the instantaneous oscillation circuit model of this application;
[0051] Figure 6 is a schematic diagram of the instantaneous oscillation circuit model of this application;
[0052] Figure 7 shows the waveform diagrams of the silicon carbide IGBT module in the turn-on test and the actual working condition in this application.
[0053] Figure 8 shows the waveform diagrams of the silicon carbide IGBT module under turn-off test and the actual working condition in this application.
[0054] Figure 9 is a structural block diagram of a simulation modeling system for a real-time model of a silicon carbide IGBT module provided in an embodiment of this application;
[0055] Figure 10 is a structural block diagram of a computer device provided in an embodiment of this application. Detailed Implementation
[0056] This application provides a simulation modeling method and system for a real-time model of a silicon carbide IGBT module, which addresses the technical problem of improving the simulation modeling efficiency of silicon carbide IGBT modules.
[0057] To make the objectives, features, and advantages of this application more apparent and understandable, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0058] IGBT (Insulated Gate Bipolar Transistor) is a composite, fully controllable, voltage-driven power semiconductor device composed of a BJT (Bipolar Junction Transistor) and a MOS (Metal-Oxide-Semiconductor Field-Effect Transistor). Similar to CPU technology in microelectronics, IGBT chip technology is the "heart" and "brain" of the power electronics industry, controlling and providing high-power power conversion for electrical equipment, effectively improving energy efficiency, automation, and intelligence. IGBT devices, modules, components, and systems composed of IGBT chips are widely used in household appliances such as air conditioners and washing machines, as well as in high-end industries such as rail transportation, smart grids, aerospace, marine propulsion, new energy, and electric vehicles. High-power IGBTs are particularly crucial.
[0059] IGBT models involve the interaction of multiple physical fields, including electricity, magnetism, heat, and force. Multiphysics modeling and analysis are crucial tools for studying their thermal management, electromagnetic compatibility, and mechanical fatigue. However, ordinary users only have access to datasheets from IGBT manufacturers, which lack specific material parameters, doping concentrations, and other detailed information, causing significant confusion and difficulty in using multiphysics modeling tools. If users could directly extract gate turn-on and turn-off parameters from the datasheets and then build behavioral-level modeling methods based on these parameters, it would solve most users' needs for modeling the turn-on and turn-off conditions of this switching device. Furthermore, accelerating the computation of such models and embedding them into hardware-in-the-loop scenarios would greatly improve their versatility and practicality.
[0060] Traditional IGBT circuit simulation employs the following circuit models: 1) analytical models; 2) behavioral models; 3) numerical models; and 4) hybrid models. Analytical models are based on the physical principles of the device, establishing models that accurately describe the steady-state and transient operation of the device. Behavioral models provide good predictions of device performance while ignoring detailed physical characteristics. Numerical models can simulate the electrical, thermal, and optical characteristics of the device using the finite element method without manufacturing the physical device, but their computation is very time-consuming. Hybrid models combine the physical interpretability of analytical models, the low computational cost of behavioral models, and the accurate geometric characteristics of numerical models. Generally, behavioral models offer the best real-time performance and require the fewest computational resources, while other models consume significant resources and execution time.
[0061] Behavioral models can achieve rapid device-level modeling and real-time simulation using only device datasheets. However, analytical, numerical, and hybrid models require specific dimensions and manufacturing descriptions to extract specialized physical parameters. Generally, device datasheets do not provide such detailed manufacturer design specifications, making modeling general devices very difficult. Some physical parameters within power semiconductors cannot be measured or estimated without extensive collaboration with semiconductor manufacturers. High-order nonlinear equations, convergence problems, and sensitivity to initial conditions can lead to incomplete or inaccurate simulations, which are also major challenges for these three types of models. The choice of modeling method depends on the required accuracy, computational resources, convergence properties, validity range, and computational time consumption. Analytical, numerical, and hybrid models consume significant computational resources and are not suitable for real-time simulation scenarios. Therefore, choosing behavioral models with acceptable accuracy and low computational resource consumption for rapid modeling and real-time simulation of IGBTs is a feasible and recommended modeling approach.
[0062] The use of silicon carbide material greatly reduces parasitic parameters in power electronic switches, improving the feasibility of switching frequencies. However, it also introduces new oscillation characteristics at the moment of switching. Modeling and calculating these oscillation characteristics using traditional physical methods would significantly increase the computational load. Therefore, a simplified behavioral model should be proposed based on the actual physical characteristics of the devices to greatly reduce the computational load.
[0063] Therefore, this application proposes a rapid modeling method for real-time models of IGBT modules based on silicon carbide materials. The most time-consuming nonlinear iterative switching oscillation calculation is simplified into an RLC circuit model or an RLC+RC circuit model through physically resolvable circuits, which greatly improves the calculation speed of the model and can achieve real-time calculation results. This improves the efficiency of simulation modeling and solves the problem of meeting the requirements of behavioral modeling and real-time simulation in the absence of semiconductor physical parameters. It also enables hardware-in-the-loop testing of new semiconductor oscillation characteristics under high-frequency switching conditions, and provides an important research tool for scenarios such as forward-looking device-level selection and massive subsequent debugging in the construction of large-scale new power systems.
[0064] Please refer to Figure 1, which is a flowchart of the steps of a simulation modeling method for a real-time model of a silicon carbide IGBT module provided in an embodiment of this application.
[0065] This application provides a simulation modeling method for a real-time model of a silicon carbide IGBT module, including:
[0066] Step 101: Respond to the modeling request for the target IGBT module and obtain the module characteristic parameters of the target IGBT module through the preset device data table.
[0067] The target IGBT module refers to the silicon carbide IGBT module.
[0068] A modeling request is a command to request simulation modeling of a target IGBT module.
[0069] The preset equipment data sheet refers to a set of data that is pre-acquired to record various detailed information and characteristic parameters of the equipment and the target IGBT module.
[0070] Module characteristic parameters refer to a set of data used to describe and characterize the performance and characteristics of a target IGBT module in terms of electrical, thermal, mechanical, and reliability aspects.
[0071] In this embodiment of the application, in response to receiving a request instruction to perform simulation modeling for the target IGBT module, a preset device data table is retrieved to obtain the module characteristic parameters of the target IGBT module for real-time oscillation simulation calculation.
[0072] Step 102: By performing a switching operation on the preset module equivalent circuit, obtain the oscillation characteristic parameters of the target IGBT module during the instantaneous oscillation phase of the switching.
[0073] Oscillation characteristic parameters refer to the real-time data recorded by each component in the equivalent circuit of the preset module during the oscillation phase of switching operation, which is used for real-time oscillation simulation calculation.
[0074] The preset module equivalent circuit refers to the pre-constructed equivalent test circuit of the target IGBT module. By performing switching operations on the preset module equivalent circuit, the oscillation characteristic parameters of the target IGBT module during the oscillation phase at the moment of switching are obtained.
[0075] Please refer to Figure 2. The preset module equivalent circuit includes a first silicon carbide IGBT module, a second silicon carbide IGBT module, an external capacitor, and a module circuit parasitic inductance.
[0076] Among them, the cable line with parasitic inductance mixed in the external capacitor is equivalent to a parasitic inductance, that is, the parasitic inductance of the module circuit.
[0077] It should be noted that the preset module equivalent circuit is applied to the ultra-high voltage flexible DC MMC sub-module circuit.
[0078] The following are the component connection relationships of the preset module equivalent circuit:
[0079] The first silicon carbide IGBT module ① includes a first gate, a first gate external resistance, a first gate internal resistance, and a first gate-collector parasitic capacitance C. GC Parasitic capacitance C of the first collector-emitter junction CE The parasitic capacitance C of the first gate-emitter junction GE The first emitter, the first emitter parasitic inductance, the first parasitic resistor, the first collector parasitic inductance, the first collector, the first diode, and the first capacitor;
[0080] The first gate is connected to one end of the first gate external resistor, and the other end of the first gate external resistor is connected to the first end of the first gate internal resistor.
[0081] The second terminal of the first gate internal resistance is connected to the first gate-collector parasitic capacitance C. GC One end is connected;
[0082] First gate-collector parasitic capacitance C GC The other end is connected to the first parasitic resistor, the first capacitor, and the first collector-emitter parasitic capacitance C. CE With the first diode;
[0083] The first parasitic resistance is far from the first gate-collector parasitic capacitance C. GC One end is connected to one end of the first collector parasitic inductor;
[0084] The other end of the parasitic inductance of the first collector electrode is connected to one end of the first collector electrode;
[0085] The third terminal of the first gate internal resistance and the parasitic capacitance C between the first gate and emitter. GE One end is connected;
[0086] The parasitic capacitance C of the first gate-emitter junction GE The other end is connected to the first emitter parasitic inductance, the first capacitor, and the first collector-emitter parasitic capacitance C. CE With the first diode;
[0087] The parasitic inductance of the first emitter is far from the parasitic capacitance C of the first gate-emitter junction. GE One end is connected to the first emitter;
[0088] The first emitter is connected to the second collector in the second silicon carbide IGBT module.
[0089] The second silicon carbide IGBT module ② includes a second gate, a second gate external resistance, a second gate internal resistance, and a second gate-collector parasitic capacitance C. GC Parasitic capacitance C of the second collector-emitter junction CE The parasitic capacitance C of the second gate-emitter junction GE Second emitter, second emitter parasitic inductance, second parasitic resistance, second collector parasitic inductance, second collector, second diode, and second capacitor;
[0090] The second gate is connected to one end of the second gate external resistor, and the other end of the second gate external resistor is connected to the second end of the second gate internal resistor.
[0091] The second terminal of the second gate internal resistance is related to the parasitic capacitance C of the second gate-collector electrode. GC One end is connected;
[0092] The second gate-collector parasitic capacitance C GC The other end is connected to a second parasitic resistor, a second capacitor, and a second collector-emitter parasitic capacitance C. CE With the second diode;
[0093] The second parasitic resistance is far from the second gate-collector parasitic capacitance C. GC One end is connected to one end of the second collector parasitic inductor;
[0094] The other end of the parasitic inductance of the second collector electrode is connected to one end of the second collector electrode;
[0095] The third terminal of the second gate internal resistance and the parasitic capacitance C between the second gate and emitter. GE One end is connected;
[0096] The parasitic capacitance C of the second gate-emitter junction GE The other end is connected to the second emitter parasitic inductance, the second capacitor, and the second collector-emitter parasitic capacitance C. CE With the second diode;
[0097] The parasitic inductance of the second emitter is far from the parasitic capacitance C of the second gate-emitter junction. GE One end is connected to the second emitter;
[0098] The parasitic inductance of the second emitter is far from the parasitic capacitance C of the second gate-emitter junction. GE One end is also connected to the other end of an external capacitor;
[0099] The other end of the external capacitor is connected to one end of the module circuit's parasitic inductance;
[0100] The other end of the parasitic inductance of the module circuit is connected to the first collector.
[0101] In this embodiment, a controllable current source is used to switch the equivalent circuit of the preset module, simulating the current change during the linear rise or fall phase of the switch, that is, switching the first silicon carbide IGBT module ① and the second silicon carbide IGBT module ② respectively.
[0102] Instantaneous start: The linear rise phase of the current is measured using the preset module equivalent circuit. When the switch of the first silicon carbide IGBT module ① is turned on, the second silicon carbide IGBT module ② is turned off, as shown in Figure 3. At the instant ① is turned on and ② is turned off, there is a linear rise phase followed by an oscillation phase. During the linear rise phase, the current rise is controlled by a controllable current source. The rise time can be extracted from the preset device data table.
[0103] Instantaneous shutdown: The linear descent phase of the current is measured using the preset module equivalent circuit. When the switch of the second silicon carbide IGBT module ② is turned on, the first silicon carbide IGBT module ① is turned off. As shown in Figure 4, at the instant ① is turned off and ② is turned on, there is a linear descent phase followed by an oscillation phase. The linear descent phase also uses a controllable current source to control the current descent. The descent time can also be extracted from the equipment data sheet.
[0104] Through the above switching operation, the oscillation characteristic parameters of each component during the instantaneous oscillation phase of the target IGBT module are obtained.
[0105] Step 103: Construct an initial real-time model, and use the oscillation characteristic parameters and module characteristic parameters as inputs to the initial real-time model to perform real-time oscillation simulation, and output oscillation simulation data.
[0106] In this embodiment of the application, an initial real-time model is constructed, which includes an instantaneous oscillation circuit model for the moment of opening and an instantaneous oscillation circuit model for the moment of closing.
[0107] It is worth mentioning that the simplified circuit form of the instantaneous oscillation circuit model includes a first preset gate total resistance function, a first preset parasitic total inductance function, a first preset parasitic total capacitance function, and a formula for calculating the simulation data of the first maximum reverse current; the simplified circuit form of the instantaneous oscillation circuit model includes a second preset gate total resistance function, a second preset parasitic total inductance function, a second preset parasitic total capacitance function, a formula for calculating the simulation data of the second maximum reverse current, and a formula for calculating the simulation data of the first-order circuit; through the above simplified circuit form of the oscillation circuit model, oscillation simulation data can be obtained quickly through simulation calculation, which greatly reduces the amount of calculation and improves the modeling efficiency compared with traditional physical method modeling.
[0108] Please refer to Figure 5. At the instants ① open and ② close, the oscillating circuit is in the form of an RLC circuit at the instant of opening, and the output is the current at the right end. The RLC circuit is composed of the first total equivalent resistance, the first total parasitic inductance, and the first total parasitic capacitance connected in series, and the output at the right end is the first maximum reverse current.
[0109] Please refer to Figure 6. At the instants ① closed and ② open, the oscillating circuit at the instant of closing is an RLC circuit superimposed with an RC circuit, and the output is the current at the right end. The RLC circuit is composed of the second total equivalent resistance, the second total parasitic inductance, and the second total parasitic capacitance connected in series, and the output at the right end is the second maximum reverse current. The RC circuit is composed of the first-order total equivalent resistance and the first-order total parasitic capacitance connected in series, and the output at the right end is the first-order maximum reverse current.
[0110] In this embodiment, oscillation characteristic parameters and module characteristic parameters are input into the parameter calculation module for calculation, and oscillation simulation data is output. The oscillation simulation data includes first oscillation simulation data and second oscillation simulation data.
[0111] The first oscillation simulation data refers to the oscillation characteristic parameters and module characteristic parameters at the instants of ① opening and ② closing, which are used as the inputs to the initial real-time model through real-time oscillation simulation. The output oscillation simulation data includes the first total equivalent resistance, the first total parasitic inductance, the first total parasitic capacitance, and the first maximum reverse current.
[0112] The second oscillation simulation data refers to the oscillation characteristic parameters and module characteristic parameters at the instants of ① closing and ② opening, which are used as the inputs to the initial real-time model through real-time oscillation simulation. The output oscillation simulation data includes first-order simulation data and second-order simulation data. The first-order simulation data includes the first-order total equivalent resistance, the first-order total parasitic capacitance, and the first-order maximum reverse current. The second-order simulation data includes the second total equivalent resistance, the second total parasitic inductance, the second total parasitic capacitance, and the second maximum reverse current.
[0113] Furthermore, the oscillation characteristic parameters include a first oscillation characteristic parameter and a second oscillation characteristic parameter; the oscillation simulation data includes a first oscillation simulation data and a second oscillation simulation data; the initial real-time model includes an oscillation circuit model at the moment of switching on and an oscillation circuit model at the moment of switching off; and step 103 may include the following sub-steps:
[0114] S31. Using the first oscillation characteristic parameters and module characteristic parameters as input, perform real-time oscillation simulation on the instantaneous oscillation circuit model and output the first oscillation simulation data.
[0115] Furthermore, the first oscillation characteristic parameters include first gate resistance data, first parasitic inductance data, and first parasitic capacitance data; the first oscillation simulation data includes first total equivalent resistance simulation data, first total parasitic inductance simulation data, first total parasitic capacitance simulation data, and first maximum reverse current simulation data; S31 may include the following sub-steps:
[0116] S311. Input the first gate resistance data into the first preset gate total resistance function to determine the first total equivalent resistance simulation data.
[0117] The first preset gate total resistance function is specifically: R ON =R ge1 +R gi1
[0118] In the formula, R ON This represents the simulation data for the first total equivalent resistance, specifically the first total equivalent resistance, R. ge1 R represents the external resistance of the first gate. gi1 This represents the internal resistance of the first gate.
[0119] In the embodiments of this application, during the ① on and ② off phases, the first gate resistance data includes the first gate external resistance and the first gate internal resistance. The first gate external resistance and the first gate internal resistance in the first silicon carbide IGBT module ① are used as inputs to the first preset gate total resistance function for calculation to obtain the first total equivalent resistance simulation data.
[0120] S312. Using the first parasitic inductance data as input, the first preset total parasitic inductance function is determined to obtain the first total parasitic inductance simulation data.
[0121] The first preset parasitic total inductance function is specifically: L ON =L C1 +L C2 +L E1 +L m
[0122] In the formula, L ON This represents the simulation data for the first total parasitic inductance, specifically the first total parasitic inductance, L. C1 L represents the parasitic inductance of the first collector electrode.C2 L represents the parasitic inductance of the second collector electrode. E1 L represents the parasitic inductance of the first emitter. m This indicates the parasitic inductance of the module circuit.
[0123] In this embodiment of the application, during the ① on and ② off phases, the first parasitic inductance data includes the first collector parasitic inductance, the second collector parasitic inductance, the first emitter parasitic inductance, and the module circuit parasitic inductance. The first parasitic inductance data is input into the first preset total parasitic inductance function for calculation to obtain the first total parasitic inductance simulation data.
[0124] S313. Using the first parasitic capacitance data as input to the first preset total parasitic capacitance function, determine the first total parasitic capacitance simulation data.
[0125] The first presupposed parasitic total capacitance function is specifically: C ON =C GC1 +C CE1
[0126] In the formula, C ON This represents the simulation data for the first total parasitic capacitance, specifically the first total parasitic capacitance, C. GC1 C represents the first gate-collector parasitic capacitance. CE1 This represents the parasitic capacitance of the first collector-emitter junction.
[0127] In this embodiment of the application, during the ① on and ② off phases, the first parasitic capacitance data includes the first gate-collector parasitic capacitance and the first collector-emitter parasitic capacitance. The first parasitic capacitance data is input into the first preset total parasitic capacitance function for calculation to obtain the first total parasitic capacitance simulation data.
[0128] S314. Using the simulation data of the first total parasitic inductance, the simulation data of the first total parasitic capacitance, and the module characteristic parameters, determine the simulation data of the first maximum reverse current.
[0129] S314 is encapsulated in the form of a formula, specifically:
[0130] In the formula, I rr1 This represents the simulation data for the first maximum reverse current, specifically the first maximum reverse current, Q. rr It represents the reverse recovery charge, T represents the period, and ω represents the angular velocity.
[0131] In this embodiment, the angular velocity is calculated using the simulation data of the first total parasitic inductance and the simulation data of the first total parasitic capacitance, and the period is calculated using the angular velocity. The module characteristic parameters include reverse recovery charge. The simulation data of the first maximum reverse current can be calculated using the reverse recovery charge and the angular velocity, or the simulation data of the first maximum reverse current can also be calculated using the reverse recovery charge and the period.
[0132] S32. Using the second oscillation characteristic parameters and module characteristic parameters, input the instantaneous oscillation circuit model to perform real-time oscillation simulation and output the second oscillation simulation data.
[0133] Furthermore, the second oscillation characteristic parameters include the second gate resistance data, the second parasitic inductance data, and the second parasitic capacitance data. The second oscillation simulation data includes first-order circuit simulation data and second-order circuit simulation data. S32 may include the following sub-steps:
[0134] S321. Using the second gate resistor data, second parasitic inductance data, second parasitic capacitance data, and module characteristic parameters, determine the simulation data for the second-order circuit.
[0135] Furthermore, the second-order circuit simulation data includes simulation data of the second total equivalent resistance, simulation data of the second total parasitic inductance, simulation data of the second total parasitic capacitance, and simulation data of the second maximum reverse current. S321 may include the following sub-steps:
[0136] S3211. Using the second gate resistance data as input, the second preset gate total resistance function is used to determine the simulation data of the second total equivalent resistance.
[0137] The second preset gate total resistance function is specifically: R OFF1 =R ge2 +R gi2
[0138] In the formula, R OFF1 This represents the simulation data for the second total equivalent resistance, specifically the second total equivalent resistance, R. ge2 R represents the external resistance of the second gate. gi2 This represents the internal resistance of the second gate.
[0139] In this embodiment, during the ①off and ②on phases, the second gate resistance data includes the second gate external resistance and the second gate internal resistance. The second gate external resistance and the second gate internal resistance in the second silicon carbide IGBT module ② are used as inputs to the second preset gate total resistance function for calculation to obtain the second total equivalent resistance simulation data.
[0140] S3212. Using the second parasitic inductance data as input, the second preset parasitic total inductance function is determined to obtain the second total parasitic inductance simulation data.
[0141] The second preset parasitic total inductance function is specifically: L OFF1 =L C1 +L C2 +L E2 +L m
[0142] In the formula, L OFF1 This represents the simulation data for the second total parasitic inductance, specifically the second total parasitic inductance, L. C1 L represents the parasitic inductance of the first collector electrode. C2 L represents the parasitic inductance of the second collector electrode. E2 L represents the parasitic inductance of the second emitter. m This indicates the parasitic inductance of the module circuit.
[0143] In this embodiment of the application, during the ①off and ②on phases, the second parasitic inductance data includes the first collector parasitic inductance, the second collector parasitic inductance, the second emitter parasitic inductance, and the module circuit parasitic inductance. The second parasitic inductance data is input into the second preset total parasitic inductance function for calculation to obtain the second total parasitic inductance simulation data.
[0144] S3213. Using the second parasitic capacitance data as input to the second preset total parasitic capacitance function, determine the second total parasitic capacitance simulation data.
[0145] The second presupposed parasitic total capacitance function is specifically: C OFF1 =C GC2 +C CE2
[0146] In the formula, C OFF1 This represents the simulation data for the second total parasitic capacitance, specifically the second total parasitic capacitance, C. GC2 C represents the second gate-collector parasitic capacitance. CE2 This represents the parasitic capacitance of the second collector-emitter junction.
[0147] In this embodiment of the application, during the ①off and ②on phases, the second parasitic capacitance data includes the second gate-collector parasitic capacitance and the second collector-emitter parasitic capacitance. The second parasitic capacitance data is input into the second preset total parasitic capacitance function for calculation to obtain the second total parasitic capacitance simulation data.
[0148] S3214. Using the simulation data of the second total parasitic inductance, the simulation data of the second total parasitic capacitance, and the module characteristic parameters, determine the simulation data of the second maximum reverse current.
[0149] The formula for 3214 is as follows:
[0150] In the formula, I rr2This represents the simulation data for the second maximum reverse current, specifically the second maximum reverse current.
[0151] In this embodiment, the angular velocity is calculated using the second total parasitic inductance simulation data and the second total parasitic capacitance simulation data, and the period is calculated using the angular velocity. The module characteristic parameters include reverse recovery charge. The second maximum reverse current simulation data can be calculated using the reverse recovery charge and the angular velocity, or the second maximum reverse current simulation data can also be calculated using the reverse recovery charge and the period.
[0152] S322. Use module characteristic parameters to determine the simulation data of the first-order circuit.
[0153] First-order circuit simulation data includes the first-order maximum reverse current;
[0154] S322 is encapsulated in the form of a formula, specifically: T down =2.2τ
[0155] In the formula, I rr3 I represents the first-order maximum reverse current. rrm T represents the maximum current cutoff at the current moment, and t represents the discharge time. down Let τ represent the descent time, and τ represent the time constant.
[0156] In this embodiment, the module characteristic parameters also include fall time, maximum turn-off current at the current moment, and discharge time. The RC circuit uses the fall time from a preset device data sheet as a reference. The fall time is defined as the time from 90% to 10%, which can be considered as the fall time T. down =2.2τ is a first-order process. Using the above formula, the second gate resistance data, the second parasitic capacitance data and the module characteristic parameters are used to calculate the first-order total equivalent resistance, the first-order total parasitic capacitance and the first-order maximum reverse current.
[0157] Step 104: Compare the oscillation simulation data with the preset standard operating condition data.
[0158] Preset standard operating condition data refers to a set of reference standard data that should be exhibited under pre-set ideal operating conditions.
[0159] In this embodiment of the application, the oscillation simulation data is compared with the preset standard operating condition data.
[0160] It should be noted that it is necessary to compare all the simulation data in the oscillation simulation data to see if they are consistent with the preset standard operating condition data.
[0161] Step 105: If the oscillation simulation data is consistent with the preset standard operating condition data, then the initial real-time model is used as the target real-time model of the target IGBT module.
[0162] In this embodiment of the application, if the oscillation simulation data is consistent with the preset standard operating condition data, the initial real-time model is used as the target real-time model of the target IGBT module.
[0163] Furthermore, it also includes:
[0164] Step 106: If the oscillation simulation data is inconsistent with the preset standard operating condition data, proceed to the step of obtaining the oscillation characteristic parameters of the target IGBT module during the instantaneous oscillation stage by performing a switching operation on the preset equivalent circuit of the module.
[0165] In this embodiment, if the oscillation simulation data is inconsistent with the preset standard operating condition data, the process jumps to the step of obtaining the oscillation characteristic parameters of the target IGBT module during the instantaneous oscillation phase by performing a switching operation on the preset equivalent circuit of the module, performing the switching operation again to obtain new oscillation characteristic parameters, and then performing real-time oscillation simulation until the oscillation simulation data is consistent with the preset standard operating condition data.
[0166] In subsequent applications, the oscillation characteristic parameters of the silicon carbide IGBT module to be analyzed and the module characteristic parameters will be input into the constructed target real-time model. The output will be the oscillation data of the silicon carbide IGBT module switching transient process, which can be understood as the oscillation simulation data calculated above. This data will form different types of waveforms to describe the oscillation curve, such as the maximum value, oscillation frequency, and decay method. Corresponding measures can be taken to mitigate the oscillation. For example, if the oscillation process is to decay faster, the resistance value in the subsystem can be increased. Another example is that the maximum protection value of the circuit can be designed based on the maximum value of the current overshoot. If this limit is exceeded, it can be considered that the circuit needs to be protected by the relay protection device. Through these curves, the circuit analysis can be further refined.
[0167] The following is an example test:
[0168] Select a test silicon carbide IGBT module and construct a target real-time model corresponding to the test silicon carbide IGBT module using the modeling method described above. Then, input the oscillation characteristic parameters and module characteristic parameters into the target real-time model and output the oscillation test data.
[0169] Please refer to Figures 7 and 8. Figure 7 is a waveform diagram of the turn-on test silicon carbide IGBT module and the actual operating condition. In the figure, the waveform formed by black dots is the turn-on waveform generated in this test example, and the colored waveform is the actual operating condition waveform generated under different input currents.
[0170] Figure 8 shows the waveform diagrams of the silicon carbide IGBT module under turn-off test and actual operating conditions. In the figure, the waveform formed by black dots is the turn-off waveform generated in this test example, and the colored waveforms are the actual operating waveforms generated under different input currents.
[0171] As shown in Figures 7 and 8 above, the two sets of data are basically consistent, proving the effectiveness of the model.
[0172] It is worth mentioning that the above-mentioned model calculation formulas significantly reduce the computational workload of calculating oscillation currents and can highly match actual equipment datasheets. The entire turn-on or turn-off condition process can be simplified into an RLC circuit or a superposition of RLC and RC circuits, achieving simplified conditions with physical interpretability. This application can achieve rapid modeling of silicon carbide IGBT modules, achieve real-time computational efficiency, and can be integrated with hardware-in-the-loop testing to evaluate the safety and adequacy of the power system and its control system.
[0173] Please refer to Figure 9, which is a structural block diagram of a simulation modeling system for a real-time model of a silicon carbide IGBT module provided in an embodiment of this application.
[0174] This application provides a simulation modeling system for a real-time model of a silicon carbide IGBT module, comprising:
[0175] Response module 201 is used to respond to the modeling request of the target IGBT module and obtain the module characteristic parameters of the target IGBT module through the preset device data table;
[0176] The switching operation module 202 is used to obtain the oscillation characteristic parameters of the target IGBT module during the instantaneous oscillation phase of switching by performing a switching operation on the preset module equivalent circuit.
[0177] The oscillation simulation module 203 is used to build an initial real-time model, and to perform real-time oscillation simulation by inputting oscillation characteristic parameters and module characteristic parameters into the initial real-time model, and output oscillation simulation data.
[0178] The data comparison module 204 is used to compare the oscillation simulation data with the preset standard working condition data.
[0179] The model output module 205 is used to use the initial real-time model as the target real-time model of the target IGBT module if the oscillation simulation data is consistent with the preset standard operating condition data.
[0180] Furthermore, it also includes:
[0181] The jump module 206 is used to jump to the step of obtaining the oscillation characteristic parameters of the target IGBT module during the instantaneous oscillation stage by performing a switching operation on the preset equivalent circuit of the module if the oscillation simulation data is inconsistent with the preset standard operating condition data.
[0182] Furthermore, the oscillation characteristic parameters include a first oscillation characteristic parameter and a second oscillation characteristic parameter; the initial real-time model includes an oscillation circuit model at the instant of switching on and an oscillation circuit model at the instant of switching off; and the oscillation simulation module 203 includes:
[0183] The first oscillation simulation data submodule is used to perform real-time oscillation simulation using the first oscillation characteristic parameters and module characteristic parameters as input to the instantaneous oscillation circuit model, and output the first oscillation simulation data.
[0184] The second oscillation simulation data submodule is used to perform real-time oscillation simulation by inputting the second oscillation characteristic parameters and module characteristic parameters into the instantaneous oscillation circuit model, and output the second oscillation simulation data.
[0185] The oscillation simulation data includes the first oscillation simulation data and the second oscillation simulation data.
[0186] Furthermore, the first oscillation characteristic parameters include the first gate resistance data, the first parasitic inductance data, and the first parasitic capacitance data. The first oscillation simulation data submodule includes:
[0187] The first total equivalent resistance simulation data unit is used to input the first preset gate total resistance function with the first gate resistance data to determine the first total equivalent resistance simulation data;
[0188] The first total parasitic inductance simulation data unit is used to input the first parasitic inductance data into the first preset total parasitic inductance function to determine the first total parasitic inductance simulation data;
[0189] The first total parasitic capacitance simulation data unit is used to input the first parasitic capacitance data into the first preset total parasitic capacitance function to determine the first total parasitic capacitance simulation data.
[0190] The first maximum reverse current simulation data unit is used to determine the first maximum reverse current simulation data by using the first total parasitic inductance simulation data, the first total parasitic capacitance simulation data, and the module characteristic parameters.
[0191] The first oscillation simulation data includes the first total equivalent resistance simulation data, the first total parasitic inductance simulation data, the first total parasitic capacitance simulation data, and the first maximum reverse current simulation data.
[0192] Furthermore, the second oscillation characteristic parameters include the second gate resistance data, the second parasitic inductance data, and the second parasitic capacitance data. The second oscillation simulation data submodule includes:
[0193] The second-order circuit simulation data unit is used to determine the second-order circuit simulation data using the second gate resistor data, the second parasitic inductance data, the second parasitic capacitance data, and the module characteristic parameters.
[0194] The first-order circuit simulation data unit is used to determine the first-order circuit simulation data using module characteristic parameters;
[0195] The second oscillation simulation data includes first-order circuit simulation data and second-order circuit simulation data.
[0196] Furthermore, the second-order circuit simulation data unit includes:
[0197] The second total equivalent resistance simulation data subunit is used to input the second preset gate total resistance function with the second gate resistance data to determine the second total equivalent resistance simulation data.
[0198] The second total parasitic inductance simulation data subunit is used to input the second preset total parasitic inductance function using the second parasitic inductance data to determine the second total parasitic inductance simulation data;
[0199] The second total parasitic capacitance simulation data subunit is used to input the second parasitic capacitance data into the second preset total parasitic capacitance function to determine the second total parasitic capacitance simulation data.
[0200] The second maximum reverse current simulation data subunit is used to determine the second maximum reverse current simulation data by using the second total parasitic inductance simulation data, the second total parasitic capacitance simulation data, and module characteristic parameters.
[0201] The second-order circuit simulation data includes simulation data for the second total equivalent resistance, the second total parasitic inductance, the second total parasitic capacitance, and the second maximum reverse current.
[0202] Please refer to Figure 10, which is a structural block diagram of a computer device provided in an embodiment of this application.
[0203] An electronic device according to an embodiment of this application includes: a memory 301 and a processor 302. The memory 301 stores a computer program. When the computer program is executed by the processor 302, the processor 302 executes a simulation modeling method for a real-time model of a silicon carbide IGBT module as described in any of the above embodiments.
[0204] Memory 301 may be an electronic memory such as flash memory, EEPROM (Electrically Erasable Programmable Read-Only Memory), EPROM, hard disk, or ROM. Memory 301 has storage space 303 for program code 313 for performing any of the method steps described above. For example, storage space 303 for program code may include various program codes 313 for implementing the various steps in the methods described above. These program codes may be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, CDs, memory cards, or floppy disks. The program code may be compressed, for example, in a suitable form. When run by a computing processing device, this code causes the computing processing device to perform the various steps in the methods described above. These program codes may be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, CDs, memory cards, or floppy disks. The program code may be compressed, for example, in a suitable form. When this code is run by a computing device, it causes the computing device to perform the various steps in the simulation modeling method for the real-time model of the silicon carbide IGBT module described above.
[0205] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements a simulation modeling method for a real-time model of a silicon carbide IGBT module as described in any of the above embodiments.
[0206] This application also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions, wherein when the program instructions are executed by a computer, the computer performs a simulation modeling method for a real-time model of a silicon carbide IGBT module as described in any of the above embodiments.
[0207] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.
[0208] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components 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 through some interfaces, or indirect coupling or communication connection between apparatuses or units, and may be electrical, mechanical, or other forms.
[0209] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0210] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.
[0211] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0212] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.
Claims
1. A simulation modeling method for a real-time model of a silicon carbide IGBT module, characterized in that, include: In response to a modeling request for a target IGBT module, the module characteristic parameters of the target IGBT module are obtained through a preset device data table; By performing a switching operation on the preset module equivalent circuit, the oscillation characteristic parameters of the target IGBT module during the instantaneous oscillation phase of the switching are obtained. An initial real-time model is constructed, and the oscillation characteristic parameters and the module characteristic parameters are input into the initial real-time model to perform real-time oscillation simulation, and the oscillation simulation data is output. Compare the oscillation simulation data with the preset standard operating condition data; If the oscillation simulation data is consistent with the preset standard operating condition data, then the initial real-time model will be used as the target real-time model of the target IGBT module.
2. The simulation modeling method for a real-time model of a silicon carbide IGBT module according to claim 1, characterized in that, Also includes: If the oscillation simulation data is inconsistent with the preset standard operating condition data, then proceed to the step of obtaining the oscillation characteristic parameters of the target IGBT module during the instantaneous oscillation phase by performing a switching operation on the preset module equivalent circuit.
3. The simulation modeling method for a real-time model of a silicon carbide IGBT module according to claim 1, characterized in that, The oscillation characteristic parameters include a first oscillation characteristic parameter and a second oscillation characteristic parameter. The initial real-time model includes an instantaneous on-state oscillation circuit model and an instantaneous off-state oscillation circuit model. The step of using the oscillation characteristic parameters and the module characteristic parameters to input the initial real-time model for real-time oscillation simulation and outputting oscillation simulation data includes: The first oscillation characteristic parameter and the module characteristic parameter are used to input the instantaneous oscillation circuit model for real-time oscillation simulation, and the first oscillation simulation data is output. The second oscillation characteristic parameter and the module characteristic parameter are used to input the instantaneous oscillation circuit model for real-time oscillation simulation, and the second oscillation simulation data is output. The oscillation simulation data includes the first oscillation simulation data and the second oscillation simulation data.
4. The simulation modeling method for a real-time model of a silicon carbide IGBT module according to claim 3, characterized in that, The first oscillation characteristic parameters include first gate resistance data, first parasitic inductance data, and first parasitic capacitance data. The step of using the first oscillation characteristic parameters and the module characteristic parameters to input the instantaneous oscillation circuit model for real-time oscillation simulation and outputting the first oscillation simulation data includes: The first gate resistance data is used as input to the first preset gate total resistance function to determine the first total equivalent resistance simulation data. The first parasitic inductance data is used as input to the first preset total parasitic inductance function to determine the first total parasitic inductance simulation data; The first parasitic capacitance data is used as input to the first preset total parasitic capacitance function to determine the first total parasitic capacitance simulation data; The simulation data of the first total parasitic inductance, the simulation data of the first total parasitic capacitance, and the module characteristic parameters are used to determine the simulation data of the first maximum reverse current. The first oscillation simulation data includes the first total equivalent resistance simulation data, the first total parasitic inductance simulation data, the first total parasitic capacitance simulation data, and the first maximum reverse current simulation data.
5. The simulation modeling method for a real-time model of a silicon carbide IGBT module according to claim 3, characterized in that, The second oscillation characteristic parameters include second gate resistance data, second parasitic inductance data, and second parasitic capacitance data. The step of using the second oscillation characteristic parameters and the module characteristic parameters to input the instantaneous oscillation circuit model for real-time oscillation simulation and outputting the second oscillation simulation data includes: The second gate resistor data, the second parasitic inductance data, the second parasitic capacitance data, and the module characteristic parameters are used to determine the second-order circuit simulation data; The simulation data for the first-order circuit are determined using the module characteristic parameters. The second oscillation simulation data includes the first-order circuit simulation data and the second-order circuit simulation data.
6. The simulation modeling method for a real-time model of a silicon carbide IGBT module according to claim 5, characterized in that, The step of determining the second-order circuit simulation data using the second gate resistance data, the second parasitic inductance data, the second parasitic capacitance data, and the module characteristic parameters includes: The second gate resistance data is used as input to the second preset gate total resistance function to determine the second total equivalent resistance simulation data. The second parasitic inductance data is used as input to the second preset total parasitic inductance function to determine the second total parasitic inductance simulation data; The second parasitic capacitance data is used as input to the second preset total parasitic capacitance function to determine the second total parasitic capacitance simulation data; The second maximum reverse current simulation data is determined using the second total parasitic inductance simulation data, the second total parasitic capacitance simulation data, and the module characteristic parameters. The second-order circuit simulation data includes the second total equivalent resistance simulation data, the second total parasitic inductance simulation data, the second total parasitic capacitance simulation data, and the second maximum reverse current simulation data.
7. A simulation modeling system for a real-time model of a silicon carbide IGBT module, based on the simulation modeling method for a real-time model of a silicon carbide IGBT module according to any one of claims 1-6, characterized in that, include: The response module is used to respond to the modeling request for the target IGBT module and obtain the module characteristic parameters of the target IGBT module through a preset device data table. The switching operation module is used to obtain the oscillation characteristic parameters of the target IGBT module during the instantaneous oscillation phase of switching by performing switching operations on the preset module equivalent circuit; The oscillation simulation module is used to construct an initial real-time model, and to perform real-time oscillation simulation by inputting the oscillation characteristic parameters and the module characteristic parameters into the initial real-time model, and output oscillation simulation data. The data comparison module is used to compare the oscillation simulation data with the preset standard operating condition data; The model output module is used to use the initial real-time model as the target real-time model of the target IGBT module if the oscillation simulation data is consistent with the preset standard operating condition data.
8. An electronic device, characterized in that, The system includes a memory and a processor. The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the simulation modeling method for a real-time model of a silicon carbide IGBT module as described in any one of claims 1-6.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it implements the simulation modeling method for a real-time model of a silicon carbide IGBT module as described in any one of claims 1-6.
10. A computer program product, characterized in that, The computer program product includes a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions, wherein when the program instructions are executed by a computer, the computer performs the simulation modeling method for a real-time model of a silicon carbide IGBT module as described in any one of claims 1-6.