Real-time simulation method and system for energy release device

Abstract

A real-time simulation method and system for an energy release device, which method and system relate to the technical field of power simulation. The method comprises: acquiring a charging pile circuit and an energy release multi-unit circuit of an energy release device, and performing circuit partitioning on the energy release multi-unit circuit, so as to obtain a plurality of parallel sub-circuits; loading the parallel sub-circuits and the charging pile circuit onto a preset parallel simulation platform, so as to obtain an initial simulation model; performing performance optimization on the initial simulation model, so as to obtain a target simulation model; and performing simulation processing on the energy release device by means of the target simulation model, so as to obtain a simulation result corresponding to the energy release device. The technical problem of the operational reliability of an energy release device being reduced is solved, wherein the reduction is caused by the difficulty in meeting performance requirements for microsecond-level electromagnetic transient real-time simulation of a large-scale energy release device because existing electromagnetic transient simulation methods for an energy release device are not adapted to large-scale system simulation in terms of computation, memory, communication, etc.

Description

A real-time simulation method and system for energy release devices

[0001] This application claims priority to Chinese Patent Application No. 202510184977.1, filed on February 19, 2025, entitled "A Real-time Simulation Method and System for an Energy Release Device", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This invention relates to the field of power simulation technology, and in particular to a real-time simulation method and system for energy release devices. Background Technology

[0003] Electromagnetic transient simulation technology for energy release devices is an important tool for studying the dynamic behavior of energy release devices under various operating conditions. It helps engineers predict the response of energy release devices under fault conditions and take measures to prevent and mitigate the impact of faults.

[0004] Existing electromagnetic transient simulation methods for energy release devices are mainly designed for the refined electromagnetic process simulation of DC and other power electronic devices and small-scale systems. They are not adapted for large-scale system simulation in terms of computing, memory and communication, making it difficult to meet the performance requirements of microsecond-level real-time electromagnetic transient simulation for large-scale energy release devices and reducing the reliability of energy release device operation. Summary of the Invention

[0005] This invention provides a real-time simulation method and system for energy release devices, which solves the technical problem that existing electromagnetic transient simulation methods for energy release devices are mainly designed for the refined electromagnetic process simulation of DC and other power electronic devices and small-scale systems, and have not been adapted for large-scale system simulation in terms of computing, memory and communication. As a result, they are difficult to meet the performance requirements of microsecond-level electromagnetic transient real-time simulation of large-scale energy release devices, and reduce the reliability of energy release device operation.

[0006] The first aspect of this invention provides a real-time simulation method for an energy release device, comprising:

[0007] The charging pile circuit and energy release multi-unit circuit of the energy release device are obtained, and the energy release multi-unit circuit is divided into multiple parallel sub-circuits.

[0008] Each of the parallel sub-circuits and the charging pile circuit are loaded onto a preset parallel simulation platform to obtain an initial simulation model;

[0009] The initial simulation model is optimized to obtain the target simulation model;

[0010] The energy release device is simulated using the target simulation model to obtain the simulation results corresponding to the energy release device.

[0011] Optionally, the step of dividing the energy-releasing multi-unit circuit into multiple parallel sub-circuits includes:

[0012] The energy release multi-unit circuit is simplified using the Norton equivalent method to obtain an equivalent energy release multi-unit circuit.

[0013] The equivalent energy release multi-unit circuit is electrically divided using the extremely short transmission line theory to obtain multiple parallel sub-circuits.

[0014] Optionally, the parallel simulation platform includes an ARM processor, a field-programmable gate array (FPGA), and a communication network. The step of loading each of the parallel sub-circuits and the charging pile circuit onto the preset parallel simulation platform to obtain an initial simulation model includes:

[0015] The charging pile circuit is loaded onto the ARM processor to obtain the target charging pile model;

[0016] Each of the parallel sub-circuits is loaded onto the field-programmable gate array to obtain a multi-unit model for target energy release.

[0017] An initial simulation model is obtained by exchanging model parameters between the target charging pile model and the target energy release multi-unit model through the communication network.

[0018] Optionally, the step of optimizing the performance of the initial simulation model to obtain the target simulation model includes:

[0019] Obtain the runtime of each simulation element in the initial simulation model, and determine whether each runtime is less than a preset time threshold.

[0020] When the runtime is greater than or equal to the time threshold, the simulation element is identified as an abnormal element.

[0021] The initial simulation model is tested using a preset performance analysis method to obtain the front-end limit test value and error speculation test value corresponding to each abnormal component.

[0022] The hardware parameters of the initial simulation model are adjusted based on the front-end limit test values ​​and error speculation test values ​​corresponding to each of the abnormal components to obtain the adjusted initial simulation model.

[0023] Jump to the step of obtaining the runtime of each simulation element in the initial simulation model, until each runtime is less than the time threshold;

[0024] When the runtime of each of the above is less than the time threshold, the target simulation model is obtained.

[0025] Optionally, the step of adjusting the hardware parameters of the initial simulation model based on the front-end limit test values ​​and error speculation test values ​​corresponding to each of the abnormal components includes:

[0026] Determine whether the front-end limit test value corresponding to each of the abnormal components is less than a preset first test threshold;

[0027] When the front-end limit test value is greater than or equal to the first test threshold, the first hardware parameter of the abnormal component associated with the front-end limit test value is adjusted.

[0028] Determine whether the error prediction test value corresponding to each of the abnormal components is less than a preset second test threshold;

[0029] When the erroneous prediction test value is greater than or equal to the second test threshold, the second hardware parameter of the abnormal component associated with the erroneous prediction test value is adjusted.

[0030] Optionally, the performance analysis method includes a top-down analysis method.

[0031] Optionally, the parallel simulation platform is a system-on-a-chip.

[0032] A second aspect of the present invention provides a real-time simulation system for an energy release device, comprising:

[0033] The acquisition module is used to acquire the charging pile circuit and the energy release multi-unit circuit of the energy release device, and to divide the energy release multi-unit circuit into multiple parallel sub-circuits.

[0034] The distribution module is used to load each of the parallel sub-circuits and the charging pile circuit onto a preset parallel simulation platform to obtain an initial simulation model;

[0035] The optimization module is used to optimize the performance of the initial simulation model to obtain the target simulation model;

[0036] The simulation module is used to perform simulation processing on the energy release device through the target simulation model to obtain the simulation results corresponding to the energy release device.

[0037] A third aspect of the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the real-time simulation method for an energy release device as described in any of the preceding claims.

[0038] The fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed, implements the real-time simulation method for an energy release device as described in any of the preceding claims.

[0039] As can be seen from the above technical solutions, the present invention has the following advantages:

[0040] By acquiring the charging pile circuit and multi-unit circuit of the energy release device, and dividing the multi-unit circuit into multiple parallel sub-circuits, this invention deploys each parallel sub-circuit and the charging pile circuit on a pre-set parallel simulation platform to obtain an initial simulation model. Through front-end hardware optimization of the initial simulation model, a target simulation model is obtained. This overcomes the technical problem that existing energy release device simulation methods are not adapted to large-scale system simulation in terms of computation, memory, and communication, thus failing to meet the performance requirements of microsecond-level electromagnetic transient real-time simulation for large-scale energy release devices and reducing the reliability of energy release device operation. Compared with traditional simulation methods, this invention improves the simulation efficiency of energy release devices by deploying each parallel sub-circuit and the charging pile circuit on a pre-set parallel simulation platform to obtain an initial simulation model, and then optimizing the performance of the initial simulation model to obtain a target simulation model. This meets the performance requirements of microsecond-level electromagnetic transient real-time simulation for large-scale energy release devices and improves the reliability of energy release device operation. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention 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 the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 is a flowchart of the steps of a real-time simulation method for an energy release device provided in Embodiment 1 of the present invention;

[0043] Figure 2 is a schematic diagram of the energy release device provided in Embodiment 1 of the present invention;

[0044] Figure 3 is a flowchart of the steps of a real-time simulation method for an energy release device provided in Embodiment 2 of the present invention;

[0045] Figure 4 is a schematic diagram of the equivalent circuit of the charging pile circuit provided in Embodiment 2 of the present invention;

[0046] Figure 5 is an equivalent circuit diagram of the energy release multi-unit circuit provided in Embodiment 2 of the present invention;

[0047] Figure 6 is a structural block diagram of a real-time simulation system for an energy release device provided in Embodiment 3 of the present invention;

[0048] Figure 7 is a structural block diagram of an electronic device provided in Embodiment 4 of the present invention. Detailed Implementation

[0049] This invention provides a real-time simulation method and system for energy release devices, addressing the technical problem that existing electromagnetic transient simulation methods for energy release devices are mainly designed for the refined electromagnetic process simulation of small-scale systems such as DC power electronic devices, and are not adapted to large-scale system simulation in terms of computing, memory, and communication. As a result, they cannot meet the performance requirements of microsecond-level real-time electromagnetic transient simulation of large-scale energy release devices, thus reducing the reliability of energy release device operation.

[0050] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0051] Currently, existing electromagnetic transient simulation methods for energy release devices generally rely on personal computers and PSCAD for simulation analysis. These simulations include various electromagnetic transient scenarios. Assuming each scenario takes 6 hours to simulate, considering 100,000 scenarios, it would require 600,000 hours! Traditional electromagnetic transient simulation tools are completely unable to meet the actual simulation analysis needs of energy release devices.

[0052] To address this issue, the present invention provides a real-time simulation method for energy release devices. This method acquires the charging pile circuit and the multi-unit circuit of the energy release device, divides the multi-unit circuit into multiple parallel sub-circuits, and then deploys each parallel sub-circuit and the charging pile circuit on a pre-defined parallel simulation platform to obtain an initial simulation model. By optimizing the initial simulation model with front-end hardware, a target simulation model is obtained. This method overcomes the technical problem that existing energy release device simulation methods do not adapt to large-scale system simulation in terms of computation, memory, and communication, thus failing to meet the performance requirements of microsecond-level electromagnetic transient real-time simulation for large-scale energy release devices and reducing the reliability of energy release device operation.

[0053] Please refer to Figure 1, which is a flowchart of the steps of a real-time simulation method for an energy release device provided in Embodiment 1 of the present invention.

[0054] The present invention provides a real-time simulation method for an energy release device, comprising:

[0055] Step 101: Obtain the charging pile circuit and energy release multi-unit circuit of the energy release device, and divide the energy release multi-unit circuit into multiple parallel sub-circuits;

[0056] In this embodiment of the invention, the charging pile circuit and the energy release multi-unit circuit of the energy release device are obtained according to Thevenin's theorem, and the energy release multi-unit circuit is divided into multiple parallel sub-circuits.

[0057] It should be noted that, referring to Figure 2, the energy release device includes a charging pile circuit and an energy release multi-unit circuit. The charging pile circuit is mainly responsible for charging and discharging the energy release units. According to Thevenin's theorem, it can be organized into a single-node circuit with multiple parallel elements, suitable for highly serial arithmetic execution unit structures, and its computational efficiency is highly linearly related to its operating frequency. The energy release multi-unit circuit includes multiple energy release units, cables, and multiple user loads. The number of parallel units can be appropriately increased according to user needs; the cables connect the user loads to each energy release unit.

[0058] Step 102: Load each parallel sub-circuit and charging pile circuit onto the preset parallel simulation platform to obtain the initial simulation model;

[0059] It should be noted that a system-on-a-chip is used as the parallel simulation platform, which includes an ARM processor, a field-programmable gate array (FPGA), and a communication network.

[0060] In this embodiment of the invention, the charging pile circuit is deployed in an ARM processor to obtain a target charging pile model, and each parallel sub-circuit is deployed in a field-programmable gate array (FPGA) to obtain a target energy release multi-unit model. The interconnection and communication between the target charging pile model and the target energy release multi-unit model are realized through a communication network to obtain an initial simulation model.

[0061] It should be noted that the capacitor in the charging pile circuit is the same capacitor as the capacitors in each parallel sub-circuit, and the internal circuit switches between each other through a switch.

[0062] It's important to note that a System-on-Chip (SoC) is a highly integrated integrated circuit chip that integrates all the functional modules required for a complete electronic system, such as processors, memory, input / output interfaces, and analog circuits, onto a single chip, thus realizing the functionality of the entire system. SoCs can effectively provide a flexible solution for configuring computing resources in the complex and ever-changing computing scenarios of energy release devices.

[0063] Step 103: Optimize the performance of the initial simulation model to obtain the target simulation model;

[0064] In this embodiment of the invention, the initial simulation model is optimized using a preset TMAM tool (Top-down Microarchitecture Analysis Method) to obtain the target simulation model.

[0065] Step 104: Simulate the energy release device using the target simulation model to obtain the simulation results corresponding to the energy release device.

[0066] In this embodiment of the invention, the energy release device is simulated using a target simulation model to obtain the simulation results corresponding to the energy release device.

[0067] In this embodiment of the invention, the charging pile circuit and energy release multi-unit circuit of the energy release device are acquired, and the energy release multi-unit circuit is divided into multiple parallel sub-circuits. Each parallel sub-circuit and the charging pile circuit are then deployed on a preset parallel simulation platform to obtain an initial simulation model. By optimizing the initial simulation model with front-end hardware, a target simulation model is obtained. This overcomes the technical problem that existing energy release device simulation methods are not adapted to large-scale system simulation in terms of computation, memory, and communication, thus failing to meet the performance requirements of real-time electromagnetic transient simulation of large-scale energy release devices at the microsecond level, and reducing the reliability of energy release device operation. Compared with traditional simulation methods, this invention improves the simulation efficiency of energy release devices and meets the performance requirements of real-time electromagnetic transient simulation of large-scale energy release devices at the microsecond level by deploying each parallel sub-circuit and the charging pile circuit on a preset parallel simulation platform to obtain an initial simulation model and then optimizing the performance of the initial simulation model to obtain a target simulation model.

[0068] Please refer to Figure 3, which is a flowchart of the steps of a real-time simulation method for an energy release device provided in Embodiment 2 of the present invention.

[0069] The present invention provides a real-time simulation method for an energy release device, comprising:

[0070] Step 201: Obtain the charging pile circuit and energy release multi-unit circuit of the energy release device, and simplify the energy release multi-unit circuit using the Norton equivalent method to obtain the equivalent energy release multi-unit circuit.

[0071] In this embodiment of the invention, the charging pile circuit and the energy release multi-unit circuit of the energy release device are obtained, and the energy release multi-unit circuit is simplified by Norton equivalent method to obtain an equivalent energy release multi-unit circuit.

[0072] It should be noted that the charging pile circuit adopts a controlled charging method, which may result in a control frequency of over 100kHz. Extremely high simulation efficiency and extremely low simulation latency are required to achieve its real-time simulation effect. Therefore, the Norton equivalent method is used to represent it as a single-node circuit, and its equivalent circuit is shown in Figure 4 below.

[0073] Step 202: The equivalent energy release multi-unit circuit is electrically divided using the extremely short transmission line theory to obtain multiple parallel sub-circuits.

[0074] In this embodiment of the invention, referring to Figure 5, based on the theory of extremely short transmission lines, the equivalent energy release multi-unit circuit is electrically divided according to the connection method of each component in the equivalent energy release multi-unit circuit and the transmission path and distribution in the circuit, to obtain multiple parallel sub-circuits.

[0075] In another embodiment, the equivalent energy release multi-unit circuit is divided into multiple parallel sub-circuits using the power transmission line segmentation theory.

[0076] It should be noted that in the theory of extremely short transmission lines, an extremely short transmission line refers to a transmission line whose length is much shorter than the signal wavelength. In this case, the distributed parameter effects of the transmission line (such as the distributed characteristics of inductance and capacitance) can be ignored, and the transmission line can be approximated as a lumped parameter circuit. For example, in low-frequency circuits (such as audio circuits, where the frequency is generally between 20Hz and 20kHz), the signal wavelength is very long, and the length of the interconnects on a typical circuit board is very short relative to the signal wavelength, which can be regarded as an extremely short transmission line.

[0077] Step 203: Load each parallel sub-circuit and charging pile circuit onto the preset parallel simulation platform to obtain the initial simulation model;

[0078] It should be noted that the parallel simulation platform is a system-on-a-chip.

[0079] Furthermore, the parallel simulation platform includes an ARM processor, a field-programmable gate array (FPGA), and a communication network. Step 203 includes the following sub-steps:

[0080] S11. Load the charging pile circuit onto the ARM processor to obtain the target charging pile model;

[0081] In this embodiment of the invention, the charging pile circuit is deployed in an ARM processor to obtain a target charging pile model. During simulation processing, the target charging pile model performs parallel simulation calculations on the simulation task of the charging pile circuit through the ARM processor.

[0082] S12. Load each parallel sub-circuit onto a field-programmable gate array to obtain a multi-unit model of the target energy release.

[0083] In this embodiment of the invention, each parallel sub-circuit is loaded onto a field-programmable gate array (FPGA) to obtain a target energy release multi-unit model. During simulation, the target energy release multi-unit model performs parallel simulation calculations on the simulation tasks of each parallel sub-circuit through the FPGA.

[0084] It's worth noting that the time to run the charge / discharge circuit on an ARM processor is 7.5 ns, the time to run the energy release multi-cell circuit on an ARM processor is 2510 ns, the time to run the charge / discharge circuit on a Field-Programmable Gate Array (FPGA) is 580 ns, and the time to run the energy release multi-cell circuit (assuming 5 parallel multi-cells) on an FPGA is 1870 ns. This demonstrates that ARM and FPGA each have their strengths and can work together for computation.

[0085] S13. The initial simulation model is obtained by exchanging model parameters between the target charging pile model and the target energy release multi-unit model through the communication network.

[0086] In this embodiment of the invention, an initial simulation model is obtained by connecting the target charging pile model and the target energy release multi-unit model through a communication network.

[0087] In another embodiment, the circuit voltage and current data of the charging pile circuit and each parallel sub-circuit of the previous step are exchanged through a communication network to solve the node voltage of the current step. For example, the energy release multi-unit circuit is equivalent to multiple parallel circuit schemes, where the number of energy release units is M, the user load is N, and there are a total of M+N parallel circuits. In the next step, the node voltage of the circuit network of the current step is solved by exchanging the circuit voltage and current data of the previous step.

[0088] It should be noted that the communication network is used to connect the ARM processor and the field-programmable gate array (FPGA) to enable the exchange of computational information between the segmented energy release device.

[0089] Step 204: Optimize the performance of the initial simulation model to obtain the target simulation model;

[0090] Further, step 204 includes the following sub-steps:

[0091] S21. Obtain the runtime of each simulation element in the initial simulation model, and determine whether each runtime is less than a preset time threshold.

[0092] In this embodiment of the invention, the initial simulation model is tested using pre-acquired historical test data to obtain the runtime of each simulation element in the initial simulation model, and it is determined whether each runtime is less than a preset time threshold.

[0093] S22. When the runtime is greater than or equal to the time threshold, the simulation element is identified as an abnormal element.

[0094] In this embodiment of the invention, when the runtime is greater than or equal to the time threshold, the simulation element (i.e., the target charging pile model or the target energy release multi-unit model) is identified as an abnormal element.

[0095] S23. Use a preset performance analysis method to perform performance testing on the initial simulation model, and obtain the front-end limit test value and error prediction test value corresponding to each abnormal component.

[0096] In this embodiment of the invention, the performance of the initial simulation model is tested using the Top-down Microarchitecture Analysis Method to obtain the front-end limit test value (i.e., Front Bound test value) and the bad speculation test value (i.e., Bad Speculation test value) corresponding to each abnormal component.

[0097] It should be noted that the performance analysis method is a top-down analysis method.

[0098] S24. Adjust the hardware parameters of the initial simulation model according to the front-end limit test value and error speculation test value corresponding to each abnormal component to obtain the adjusted initial simulation model.

[0099] Furthermore, S24 includes the following sub-steps:

[0100] S241. Determine whether the front-end limit test value corresponding to each abnormal component is less than the preset first test threshold.

[0101] In this embodiment of the invention, it is determined whether the Frontend Bound test value corresponding to each abnormal element is less than a preset first test threshold.

[0102] S242. When the front-end limit test value is greater than or equal to the first test threshold, the first hardware parameter of the abnormal component associated with the front-end limit test value is adjusted.

[0103] The first hardware parameter refers to the CPU model deployed by the abnormal component.

[0104] In this embodiment of the invention, when the current Frontend Bound test value is greater than or equal to the first test threshold, the CPU model of the abnormal component associated with the Frontend Bound test value is adjusted.

[0105] S243. Determine whether the error prediction test value corresponding to each abnormal component is less than the preset second test threshold.

[0106] In this embodiment of the invention, it is determined whether the Bad Speculation test value corresponding to each abnormal element is less than a preset second test threshold.

[0107] S244. When the erroneous prediction test value is greater than or equal to the second test threshold, the second hardware parameter of the abnormal component associated with the erroneous prediction test value is adjusted.

[0108] The second hardware parameter refers to the compiler type deployed by the abnormal component.

[0109] In this embodiment of the invention, when the Bad Speculation test value is greater than or equal to the second test threshold, the compiler type of the exception element associated with the Bad Speculation test value is adjusted.

[0110] S25. Jump to the step of obtaining the runtime of each simulation element in the initial simulation model until each runtime is less than the time threshold.

[0111] In this embodiment of the invention, after adjusting each abnormal component, an adjusted initial simulation model is obtained. Based on the adjusted initial simulation model, step S21 is executed until each runtime is less than the time threshold.

[0112] S26. When each runtime is less than the time threshold, the target simulation model is obtained.

[0113] In this embodiment of the invention, when the runtime of each component is less than the time threshold, it indicates that there are no abnormal components, and the target simulation model is obtained.

[0114] Step 205: Simulate the energy release device using the target simulation model to obtain the simulation results corresponding to the energy release device.

[0115] In this embodiment of the invention, a target simulation model is used to perform simulation calculations on the simulation task of the energy release device, and the simulation results corresponding to the energy release device are obtained.

[0116] In this embodiment of the invention, the charging pile circuit and energy release multi-unit circuit of the energy release device are acquired, and the energy release multi-unit circuit is divided into multiple parallel sub-circuits. Each parallel sub-circuit and the charging pile circuit are then deployed on a preset parallel simulation platform to obtain an initial simulation model. By optimizing the initial simulation model with front-end hardware, a target simulation model is obtained. This overcomes the technical problem that existing energy release device simulation methods are not adapted to large-scale system simulation in terms of computation, memory, and communication, thus failing to meet the performance requirements of real-time electromagnetic transient simulation of large-scale energy release devices at the microsecond level, and reducing the reliability of energy release device operation. Compared with traditional simulation methods, this invention improves the simulation efficiency of energy release devices and meets the performance requirements of real-time electromagnetic transient simulation of large-scale energy release devices at the microsecond level by deploying each parallel sub-circuit and the charging pile circuit on a preset parallel simulation platform to obtain an initial simulation model and then optimizing the performance of the initial simulation model to obtain a target simulation model.

[0117] Please refer to Figure 6, which is a structural block diagram of a real-time simulation system for an energy release device provided in Embodiment 3 of the present invention.

[0118] The present invention provides a real-time simulation system for an energy release device, comprising:

[0119] The acquisition module 301 is used to acquire the charging pile circuit and the energy release multi-unit circuit of the energy release device, and to divide the energy release multi-unit circuit into multiple parallel sub-circuits.

[0120] The distribution module 302 is used to load each parallel sub-circuit and the charging pile circuit onto a preset parallel simulation platform to obtain an initial simulation model;

[0121] Optimization module 303 is used to optimize the performance of the initial simulation model to obtain the target simulation model;

[0122] The simulation module 304 is used to simulate the energy release device through the target simulation model and obtain the simulation results corresponding to the energy release device.

[0123] Furthermore, the acquisition module 301 includes:

[0124] The simplification submodule is used to simplify the energy release multi-unit circuit using the Norton equivalent method to obtain an equivalent energy release multi-unit circuit.

[0125] The segmentation submodule is used to perform power segmentation on the equivalent energy release multi-unit circuit using the ultra-short transmission line theory, resulting in multiple parallel sub-circuits.

[0126] Furthermore, the parallel simulation platform includes an ARM processor, a field-programmable gate array (FPGA), and a communication network. The distributed module 302 includes:

[0127] The first loading submodule is used to load the charging pile circuit onto the ARM processor to obtain the target charging pile model.

[0128] The second loading submodule is used to load each parallel sub-circuit onto the field programmable gate array to obtain the target energy release multi-unit model.

[0129] The integration submodule is used to exchange model parameters between the target charging pile model and the target energy release multi-unit model through the communication network to obtain the initial simulation model.

[0130] Furthermore, module 303 is optimized, including:

[0131] The acquisition submodule is used to obtain the runtime of each simulation element in the initial simulation model and determine whether each runtime is less than a preset time threshold.

[0132] The first analysis submodule is used to identify the simulation element as an abnormal element when the runtime is greater than or equal to the time threshold.

[0133] The second analysis submodule is used to perform performance testing on the initial simulation model using a preset performance analysis method, and to obtain the front-end limit test value and error speculation test value corresponding to each abnormal component.

[0134] The third analysis submodule is used to adjust the hardware parameters of the initial simulation model based on the front-end limit test values ​​and error speculation test values ​​corresponding to each abnormal component, so as to obtain the adjusted initial simulation model.

[0135] The jump rotor module is used to jump the execution of the steps to obtain the runtime of each simulation element in the initial simulation model until each runtime is less than the time threshold.

[0136] The fourth analysis submodule is used to obtain the target simulation model when each runtime is less than the time threshold.

[0137] Furthermore, the third analysis submodule includes:

[0138] The first analysis unit is used to determine whether the front-end limit test value corresponding to each abnormal component is less than the preset first test threshold.

[0139] When the front-end limit test value is greater than or equal to the first test threshold, the first hardware parameter of the abnormal component associated with the front-end limit test value is adjusted.

[0140] The second analysis unit is used to determine whether the error prediction test value corresponding to each abnormal component is less than the preset second test threshold.

[0141] When the erroneous test value is greater than or equal to the second test threshold, the second hardware parameter of the abnormal component associated with the erroneous test value is adjusted.

[0142] Furthermore, performance analysis methods include top-down analysis.

[0143] Furthermore, the parallel simulation platform is a system-on-a-chip.

[0144] Please refer to Figure 7, which is a structural block diagram of an electronic device provided in Embodiment 4 of the present invention.

[0145] An electronic device according to an embodiment of the present invention includes: a memory 401 and a processor 402. The memory 402 stores a computer program. When the computer program is executed by the processor 402, the processor 402 executes the real-time simulation method of the energy release device as described in any of the above embodiments.

[0146] Memory 401 may be an electronic memory such as flash memory, EEPROM (Electrically Erasable Programmable Read-Only Memory), EPROM, hard disk, or ROM. Memory 401 has storage space 403 for program code 413 for performing any of the method steps described above. For example, storage space 403 for program code may include individual program codes 413 for implementing the various steps in the methods described above. This program code 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, compact discs (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.

[0147] Embodiment 5 of the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the real-time simulation method of the energy release device as described in any of the above embodiments.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] Furthermore, the functional units in the various embodiments of the present invention 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.

[0152] 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 the present invention, 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 the present invention. 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.

[0153] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention 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 the present invention.

Claims

1. A method for real-time simulation of an energy release device, characterized in that, include: The charging pile circuit and energy release multi-unit circuit of the energy release device are obtained, and the energy release multi-unit circuit is divided into multiple parallel sub-circuits. Each of the parallel sub-circuits and the charging pile circuit are loaded onto a preset parallel simulation platform to obtain an initial simulation model; The initial simulation model is optimized to obtain the target simulation model; The energy release device is simulated using the target simulation model to obtain the simulation results corresponding to the energy release device.

2. The real-time simulation method for the energy release device according to claim 1, characterized in that, The step of dividing the energy-releasing multi-unit circuit into multiple parallel sub-circuits includes: The energy release multi-unit circuit is simplified using the Norton equivalent method to obtain an equivalent energy release multi-unit circuit. The equivalent energy release multi-unit circuit is electrically divided using the extremely short transmission line theory to obtain multiple parallel sub-circuits.

3. The real-time simulation method for the energy release device according to claim 1, characterized in that, The parallel simulation platform includes an ARM processor, a field-programmable gate array (FPGA), and a communication network. The step of loading each of the parallel sub-circuits and the charging pile circuit onto the preset parallel simulation platform to obtain an initial simulation model includes: The charging pile circuit is loaded onto the ARM processor to obtain the target charging pile model; Each of the parallel sub-circuits is loaded onto the field-programmable gate array to obtain a multi-unit model for target energy release. An initial simulation model is obtained by exchanging model parameters between the target charging pile model and the target energy release multi-unit model through the communication network.

4. The real-time simulation method for the energy release device according to claim 1, characterized in that, The step of optimizing the performance of the initial simulation model to obtain the target simulation model includes: Obtain the runtime of each simulation element in the initial simulation model, and determine whether each runtime is less than a preset time threshold. When the runtime is greater than or equal to the time threshold, the simulation element is identified as an abnormal element. The initial simulation model is tested using a preset performance analysis method to obtain the front-end limit test value and error speculation test value corresponding to each abnormal component. The hardware parameters of the initial simulation model are adjusted based on the front-end limit test values ​​and error speculation test values ​​corresponding to each of the abnormal components to obtain the adjusted initial simulation model. Jump to the step of obtaining the runtime of each simulation element in the initial simulation model, until each runtime is less than the time threshold; When the runtime of each of the above is less than the time threshold, the target simulation model is obtained.

5. The real-time simulation method for the energy release device according to claim 4, characterized in that, The step of adjusting the hardware parameters of the initial simulation model based on the front-end limit test values ​​and error speculation test values ​​corresponding to each of the abnormal components includes: Determine whether the front-end limit test value corresponding to each of the abnormal components is less than a preset first test threshold; When the front-end limit test value is greater than or equal to the first test threshold, the first hardware parameter of the abnormal component associated with the front-end limit test value is adjusted. Determine whether the error prediction test value corresponding to each of the abnormal components is less than a preset second test threshold; When the erroneous prediction test value is greater than or equal to the second test threshold, the second hardware parameter of the abnormal component associated with the erroneous prediction test value is adjusted.

6. The real-time simulation method for the energy release device according to claim 4, characterized in that, The performance analysis method includes a top-down analysis method.

7. The real-time simulation method for an energy release device according to any one of claims 1 to 6, characterized in that, The parallel simulation platform is a system-on-a-chip.

8. A real-time simulation system for an energy release device, characterized in that, include: The acquisition module is used to acquire the charging pile circuit and the energy release multi-unit circuit of the energy release device, and to divide the energy release multi-unit circuit into multiple parallel sub-circuits. The distribution module is used to load each of the parallel sub-circuits and the charging pile circuit onto a preset parallel simulation platform to obtain an initial simulation model; The optimization module is used to optimize the performance of the initial simulation model to obtain the target simulation model; The simulation module is used to perform simulation processing on the energy release device through the target simulation model to obtain the simulation results corresponding to the energy release device.

9. An electronic device, characterized in that, The device includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor causes the processor to perform the steps of the real-time simulation method for an energy release device as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it implements the real-time simulation method for the energy release device as described in any one of claims 1-7.

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