Batch simulation analysis method and system for DC charging piles of new energy vehicles and related equipment
By batch setting of simulation parameters and automated processing, the problems of low efficiency in parameter setting and difficulty in result processing in DC charging pile simulation are solved. It realizes efficient and reliable simulation result export and data sharing, and supports rapid optimization of charging pile design.
Patent Information
- Application Number
- CN202511077123.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-01
- Publication Date
- 2025-11-14
AI Technical Summary
In the current simulation process of DC charging piles, parameter setting relies on manual operation, which is inefficient and prone to errors. Simulation result processing depends on third-party platforms, resulting in poor file readability and difficulty in cross-platform integration, thus hindering the efficiency of large-scale simulation and optimization.
By programming the Fluent solver using a general-purpose programming language, key simulation parameters can be set in batches and automated for simulation. The results can be exported as highly readable simulation files. Combined with the automatic generation and analysis of parameter design points, the standardization and efficient processing of simulation results can be ensured.
It significantly improves the efficiency of simulation parameter setting, shortens the simulation cycle, reduces human error, ensures the readability and reliability of results, facilitates cross-platform data sharing, and supports rapid design optimization.
Smart Images
Figure CN120951577A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of charging pile simulation technology, and in particular to a method, system and related equipment for mass simulation analysis of DC charging piles for new energy vehicles. Background Technology
[0002] With the accelerated development of a global green transportation system, new energy vehicles are gradually becoming an important part of future transportation due to their significant advantages in emission reduction, energy conservation, and lower operating costs. Correspondingly, the widespread application of new energy vehicles has driven the rapid expansion of charging infrastructure, with charging piles, as their core supporting equipment, being deployed on a large scale. During the research and development phase of DC charging piles, their long-term stability and safety under various environmental conditions must be comprehensively considered. In DC charging piles, batteries and electronic equipment generate a large amount of heat during operation; a reasonable heat dissipation design is crucial to ensuring equipment reliability and extending its service life. Poor heat dissipation will cause components to operate in high-temperature environments for extended periods, leading to accelerated aging of circuit boards and other parts, damaging the overall lifespan and reliability of the equipment. In-depth analysis of the impact of temperature changes on charging piles not only helps optimize heat dissipation design and material selection but also effectively extends equipment life, improves overall safety and reliability, and provides a solid guarantee for the long-term development of new energy vehicles.
[0003] Currently, the pre-processing and post-processing operations in the numerical simulation stage of DC charging piles have not been batch-processed, resulting in inefficiency in several key aspects. Specifically, important simulation parameters such as ambient temperature, input and output power, and fan cooling performance still need to be set manually and cannot be automated in batch processing. This not only increases workload but also easily leads to human error, compromising the consistency and accuracy of the simulation. Furthermore, the export of key data after simulation is also not batch-processed; researchers must manually operate or rely on third-party post-processing platforms (such as Tecplot) to extract the required data. This inefficient post-processing method is time-consuming and labor-intensive, increasing the risk of data omissions or errors, affecting the reproducibility and overall progress of the research. More importantly, there is currently a lack of a universal, unified programming language or tool capable of fully automating the aforementioned pre-processing, simulation execution, and post-processing processes. Each stage often relies on different software platforms (such as ANSYS Fluent, Heeds, Tecplot, etc.) and programming languages (such as TUI, APDL, etc.), and without post-processing, the exported file formats (such as .plt, .dat, .cas, etc.) are usually not universally readable. This increases the complexity of learning and use, and also limits the integration and sharing of cross-platform data. This technological gap severely restricts the efficiency of large-scale simulation and optimization, hindering the rapid, batch evaluation and improvement of charging pile designs. Summary of the Invention
[0004] The purpose of this application is to provide a method, system and related equipment for batch simulation analysis of DC charging piles for new energy vehicles, which can solve the problems of manual parameter setting, low efficiency and large error in traditional simulation, as well as the problems of result processing relying on third-party platforms, poor file readability and difficulty in cross-platform integration, and significantly improve the efficiency of large-scale simulation.
[0005] To achieve the above objectives, this application provides the following solution:
[0006] Firstly, this application provides a method for mass simulation analysis of DC charging piles for new energy vehicles, including the following steps:
[0007] The Fluent solver is launched by programming with a general-purpose programming language, allowing for the batch setting of key simulation parameter boundaries and simulation solution conditions in a pre-built DC charging pile simulation model definition file. The pre-built DC charging pile simulation model definition file is a model file obtained by modeling the DC charging pile, defining key simulation parameters, meshing and geometric generation, setting the physical model, and preset model simulation solution conditions. Through programming with a general-purpose programming language, various key simulation parameters and model simulation solution conditions in the model file can be modified.
[0008] The key simulation parameters of the DC charging pile simulation model are defined as parameter design points. The input parameters of the parameter design points are set in batches according to the boundaries of the key simulation parameters, generating several parameter design points and exporting them as parameter design point project files. The parameter design points are combinations of key simulation parameters in subsequent individual simulation cases.
[0009] Based on a pre-built DC charging pile simulation model, batch-configured simulation solution conditions, and parameter design point project files, batch simulations are automatically performed.
[0010] The batch simulation results are processed using a general-purpose programming language, and the 3D coordinate values of key surfaces or key nodes and the target parameter simulation result files with readable parameters at each design point are exported and stored.
[0011] Based on the simulation results of each parameter design point and the engineering requirements, the optimal simulation results and the corresponding parameter design points are determined.
[0012] Optionally, the model file obtained by performing simulation modeling and key simulation parameter definition, mesh and geometry generation, physical model setting, and model simulation solution condition preset for DC charging piles specifically includes the following steps:
[0013] A simulation model of a DC charging pile is created, and the key simulation parameters of the simulation model are defined to obtain the DC charging pile simulation model file.
[0014] Import the DC charging pile simulation model file into Fluent Meshing to perform mesh and geometry generation, and then export the DC charging pile simulation model mesh file.
[0015] Based on the heat flow and current transfer characteristics of DC charging piles, the physical model of the DC charging pile simulation model mesh file is set in Fluent GUI.
[0016] Based on the established physical model, the simulation solution conditions for the DC charging pile simulation model mesh file are defined and preset, and then saved as the DC charging pile simulation model definition file.
[0017] Optionally, the DC charging pile simulation model file is imported into FluentMeshing for mesh and geometry generation, and then the DC charging pile simulation model mesh file is exported. This includes the following steps:
[0018] Open the FluentMeshing tool and import the DC charging pile simulation model file.
[0019] The geometry cleanup tool was used to repair errors in the DC charging pile simulation model.
[0020] The surface of the repaired DC charging pile simulation model is divided into regions based on the solid / liquid plane.
[0021] Based on the division of the surface of the DC charging pile simulation model, a geometric surface mesh of the DC charging pile is generated.
[0022] For the surface mesh of the DC charging pile geometry, select a hexahedral mesh to generate the DC charging pile geometry mesh.
[0023] Boundary layer meshes were added to key simulation regions of the DC charging pile simulation model to capture details of heat flow and current.
[0024] Based on the liquid and solid components, the DC charging pile simulation model is divided into regions, and each region is named.
[0025] After using the inspection tool to inspect the DC charging pile simulation model after the area division, the DC charging pile simulation model mesh file is exported.
[0026] Optionally, based on the heat flow and current transfer characteristics in the DC charging pile, the physical model of the DC charging pile simulation model mesh file is set in Fluent GUI, specifically including the following steps:
[0027] To address the heat flow and current transfer characteristics in DC charging piles, select the physical model in the Fluent GUI interface and enable the energy equation, momentum equation, and mass equation.
[0028] Set the material properties of the interior and shell of the DC charging pile simulation model.
[0029] The DC charging pile simulation model is divided into a structural domain and an air domain to ensure conjugate heat transfer between the air domain and the structural domain; the structural domain is the area of power generation components and heat generation devices, and the air domain is the fluid area.
[0030] Set the power consumption parameters and surface heat transfer coefficients of the power generation components and heat generation devices in the structural domain.
[0031] Set the initial values of inlet and outlet velocity, pressure, and temperature at the boundary of the fluid region in the air domain.
[0032] The internal heat transfer mode of the DC charging pile simulation model is set to natural convection.
[0033] Optionally, the Fluent solver can be launched using a general-purpose programming language to batch set key simulation parameter boundaries and simulation solution conditions for the pre-built DC charging pile simulation model definition file. This includes the following steps:
[0034] The Fluent solver is launched by programming in a general-purpose programming language, which reads the pre-built DC charging pile simulation model definition file and loads the pre-completed simulation settings.
[0035] Enable Fluent's parameterization feature to define key simulation parameter boundaries in batches using named expression functions.
[0036] Simulation solution conditions can be set in batches using a general-purpose programming language; simulation solution conditions include the number of iterations and residual thresholds.
[0037] Optionally, the batch simulation results are processed using a general-purpose programming language to export and store readable 3D coordinate values of key surfaces or key nodes and target parameter simulation result files at each parameter design point. This specifically includes the following steps:
[0038] Locate the simulation results directory and check if the folder corresponding to each parameter design point exists.
[0039] Search for simulation results folders that meet preset criteria; the preset criteria are that the folder contains one file each with the extension ".cas.h5" and ".dat.h5".
[0040] Batch load and export readable simulation result files containing 3D coordinate values and target parameters of key surfaces or key nodes.
[0041] Secondly, this application provides a batch simulation analysis system for DC charging piles for new energy vehicles, including the following functional modules:
[0042] The parameter condition batch preset module is used to start Fluent's solver through programming in a general programming language, and to batch set key simulation parameter boundaries and simulation solution conditions for pre-built DC charging pile simulation model definition files. The pre-built DC charging pile simulation model definition files are model files obtained by modeling DC charging piles, defining key simulation parameters, meshing and geometric generation, setting physical models, and preset model simulation solution conditions. Through programming in a general programming language, various key simulation parameters and model simulation solution conditions in the model file can be modified.
[0043] The parameter design point batch generation module is used to define the key simulation parameters of the DC charging pile simulation model as parameter design points. Based on the boundary of the key simulation parameters, the input parameters of the parameter design points are set in batches, generating a number of parameter design points and exporting them as parameter design point project files. The parameter design points are combinations of key simulation parameters in subsequent individual simulation cases.
[0044] The parameter design point batch simulation module automatically performs batch simulations based on a pre-built DC charging pile simulation model, batch-set simulation solution conditions, and parameter design point project files.
[0045] The batch simulation result processing module is used to process batch simulation results through programming in a general programming language, export readable 3D coordinate values of key surfaces or key nodes and target parameter simulation result files at each parameter design point, and store them.
[0046] The optimal parameter design point determination module is used to analyze the simulation results and engineering requirements based on the parameter design points to determine the optimal simulation results and the corresponding parameter design points.
[0047] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the batch simulation analysis method for DC charging piles for new energy vehicles described above.
[0048] Fourthly, this application provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the batch simulation analysis method for DC charging piles for new energy vehicles described above.
[0049] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the aforementioned method for batch simulation analysis of DC charging piles for new energy vehicles.
[0050] According to the specific embodiments provided in this application, the following technical effects are disclosed:
[0051] This application provides a method, system, and related equipment for batch simulation analysis of DC charging piles for new energy vehicles. In this method: First, the Fluent solver is started using a general-purpose programming language, allowing modification of parameters in a pre-built model definition file. Compared to traditional manual settings, this effectively reduces human error while standardizing simulation parameter configuration, significantly improving parameter setting efficiency in large-scale simulation scenarios and laying a high-efficiency, consistent foundation for subsequent batch simulations. Then, by batch generating parameter design points, a unified benchmark for parameter settings across simulation cases is ensured, avoiding inconsistencies caused by manual individual settings. This also facilitates systematic comparison of simulation effects for different parameter combinations, improving the comprehensiveness and reliability of the simulation scheme. Finally, batch simulations are automatically performed through programming control, requiring no manual intervention. This enables continuous and efficient completion of large-scale simulation tasks, significantly shortening the simulation cycle. Compared to traditional single-case manual simulation, this method better adapts to the needs of multi-scenario, multi-parameter combination simulations in DC charging pile design, significantly improving the overall efficiency of simulation work. Subsequently, the batch simulation results were processed using a general-purpose programming language, achieving automated extraction and standardized storage of the results. This avoided the tedious process of manually extracting data using third-party platforms, while ensuring that the exported results had a consistent format and readability, facilitating rapid review, analysis, and sharing, and reducing the risk of data omissions or errors. Finally, based on the simulation results at each parameter design point and engineering requirements, the optimal parameter combination that meets the engineering design requirements can be quickly identified. This provides a direct and reliable basis for structural optimization and heat dissipation design improvements of DC charging piles, effectively supporting design verification and iterative optimization, and helping to improve the performance stability and service life of charging piles. Attached Figure Description
[0052] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments 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.
[0053] Figure 1 This is a flowchart illustrating the construction of a DC charging pile simulation model definition file in a batch simulation analysis method for DC charging piles of new energy vehicles, provided as an embodiment of this application.
[0054] Figure 2 This is a flowchart illustrating a batch simulation analysis method for DC charging piles for new energy vehicles, provided as an embodiment of this application.
[0055] Figure 3 This is a schematic diagram of the functional modules of a mass simulation analysis system for DC charging piles for new energy vehicles, provided as an embodiment of this application.
[0056] Figure 4 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation
[0057] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.
[0058] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.
[0059] This application provides a batch simulation analysis method for DC charging piles for new energy vehicles, the process of which is as follows: Figures 1-2 As shown, in an exemplary embodiment, an experimental verification is performed using a physical field simulation model of the convective heat transfer device in a DC charging pile. Before performing batch simulations via programming control using a general-purpose programming language, a model file is first obtained by modeling the DC charging pile, defining key simulation parameters, meshing and geometric generation, setting the physical model, and presetting the model simulation solution conditions, as shown in the example. Figure 1 As shown, the process of constructing the DC charging pile simulation model definition file specifically includes the following steps:
[0060] A1. Model a simulation model for the DC charging pile and define the key simulation parameters of the simulation model to obtain the DC charging pile simulation model file.
[0061] In this embodiment, a simulation model is created for the convective heat exchange device in a DC charging pile, including the following steps:
[0062] A11. Establish the main water cooling pipeline model:
[0063] A111 Define the center point coordinates, pipe diameter, length, and pipe inclination angle parameters of the main water-cooled pipeline.
[0064] A112. Based on the diameter and length of the pipe, establish the corresponding cylindrical solid at the origin of the coordinate system.
[0065] A113. Rotate the pipe model along the z-axis by a predefined angle between the pipe axis and the x-axis.
[0066] A114. Rotate the pipeline model along the z-axis and x-axis sequentially according to the pipeline tilt angle defined in step A111, so that it conforms to the actual posture in the equipment.
[0067] A115. Translate the model to the corresponding position according to the center point coordinate parameters of the water cooling pipeline.
[0068] A12. Establish the sub-model of the coolant inlet and outlet connectors:
[0069] A121. Define parameters such as the center point coordinates, connector diameter, and connector length of the coolant inlet and outlet connectors.
[0070] A122. Based on the joint diameter, create a solid with a circular cross-section at the origin of the coordinate system, and translate the created circular solid to the corresponding position based on the coordinates of the center point.
[0071] A123. Adjust the connection method and installation angle of the pipe joint according to the design requirements.
[0072] A13. Establish the sub-model of pipe support and protection frame:
[0073] A131. Define the diameter, length, support point coordinates, and support tilt angle parameters of the bracket.
[0074] A132. Based on the dimensions of the support and the location of the support points, draw half of the support at the origin of the coordinate system, so that the bottom of the support points coincides with the origin of the coordinate system.
[0075] A133. Scan the cross section along the axis to generate a 3D support model.
[0076] A134. Rotate the support model along the z-axis by an angle equal to the angle between the support axis and the x-axis predefined in step A131.
[0077] A135. Rotate the support model along the x-axis by an angle equal to the angle parameter between the projection of the support axis on the xz plane and the y-axis, as defined in step A131.
[0078] A136. Translate the model to the corresponding position according to the coordinate parameters of the support end point.
[0079] A14. Model data collection for subsequent batch parameter setting: Based on the sub-models established in steps A11 to A13, and based on design drawings or physical objects, collect the specific values of each parameter required for modeling each typical water-cooled pipeline device, including:
[0080] A141. For cylindrical entities such as water-cooled pipeline mains, collect the center point coordinates, pipe diameter, length, and pipe inclination angle parameters of the water-cooled pipeline mains.
[0081] A142. For circular entities such as coolant inlet and outlet connectors, collect parameters such as the center point coordinates of the connector, the connector diameter, and the connector length.
[0082] A143. For axisymmetric entities such as pipe supports and protective frames, collect parameters such as the diameter, length, coordinates of support points, and tilt angle of the supports.
[0083] A144. Collect the number of each type of entity to be created.
[0084] A2. Import the DC charging pile simulation model file into FluentMeshing for mesh and geometry generation, and then export the DC charging pile simulation model mesh file. In this embodiment, step A2 specifically includes the following steps:
[0085] A21. Open the FluentMeshing tool and import the DC charging pile simulation model file.
[0086] A22. Use the geometry cleanup tool to repair errors in the DC charging pile simulation model. Ensure the correctness of the geometry.
[0087] A23. The surface of the repaired DC charging pile simulation model is divided into regions based on solid / liquid planes. In this embodiment, multiple pipe walls, inlet / outlet planes, and several monitoring sections are divided. In some implementations, the division is based on solid / liquid planes in actual applications. For example, the pipe wall is a solid plane, and the inlet / outlet is a liquid plane for liquid entry and exit. These are all solid entities before the entity properties are defined for simulation and need to be manually cut. Furthermore, due to their unsteady characteristics, the simulation results differ at different spatial geometric locations, so other monitoring areas are also defined.
[0088] A24. Based on the surface division of the DC charging pile simulation model, generate a mesh for the geometric surface of the DC charging pile. When generating the mesh, it is necessary to ensure its regularity and quality.
[0089] A25. For the surface mesh of the DC charging pile geometry, select hexahedral mesh to generate the DC charging pile geometry mesh.
[0090] A26. Add boundary layer meshes to the key simulation areas of the DC charging pile simulation model to capture the details of heat flow and flow, ensuring higher accuracy.
[0091] A27. Based on the liquid and solid components, divide the DC charging pile simulation model into regions and name each region. When dividing the regions, ensure that the definitions of each boundary surface and region of the model are clear and unambiguous.
[0092] A28. After checking the DC charging pile simulation model after the area division using the inspection tool, export the DC charging pile simulation model mesh file.
[0093] A3. Based on the heat flow and current transfer characteristics of the DC charging pile, the physical model of the DC charging pile simulation model mesh file is set in Fluent GUI. In this embodiment, step A3 specifically includes the following steps:
[0094] A31. To address the heat flow and current transfer characteristics in DC charging piles, select the physical model in the Fluent GUI interface and enable the Energy, Momentum, and Mass equations.
[0095] A32. Set the material properties of the interior and shell of the DC charging pile simulation model. In one implementation, input the material properties of the interior region and shell of the simulation model, such as thermal conductivity, specific heat capacity, density, etc.
[0096] A33. Divide the DC charging pile simulation model into structural domain and air domain to ensure conjugate heat transfer between the air domain and structural domain; the structural domain is the area of power generation components and heat generation devices, and the air domain is the fluid area.
[0097] A34. Set the power consumption parameters and surface heat transfer coefficient of the power generation components and heat generation devices in the structural domain.
[0098] A35. Set the initial values of inlet and outlet velocity, pressure, and temperature at the boundary of the fluid region in the air domain.
[0099] A36. Set the internal heat transfer mode of the DC charging pile simulation model to a natural convection model. This design can simulate the thermal convection effect when there is no external forced flow.
[0100] A4. Based on the established physical model, define and preset the simulation solution conditions for the DC charging pile simulation model mesh file, and save it as the DC charging pile simulation model definition file. Specifically, step A4 includes the following steps:
[0101] A41. When setting the DC charging pile simulation model in step A31, select the steady-state solution mode in the solver settings of the physical model.
[0102] A42. Set the pressure-velocity coupling method and select SIMPLE for an algorithm suitable for steady-state flow.
[0103] A43. Preset convergence parameters in the solution process, including the solver's tolerance and the number of iterations, to ensure simulation convergence.
[0104] A44. Pre-set monitoring items in Fluent to monitor residuals, speed, temperature, and pressure to track simulation progress in real time.
[0105] A45. Set the residual threshold to 10. -3 If the result is less than the threshold, the simulation result can be considered to meet the accuracy requirements.
[0106] A46. Save the single simulation model after all the above steps as a file with the extension ".cas.h5", and use it as the DC charging pile simulation model definition file.
[0107] After obtaining the DC charging pile simulation model definition file, the above-mentioned method for batch simulation analysis of new energy vehicle DC charging piles provided in this embodiment, such as... Figure 2 As shown, it includes the following steps:
[0108] B1. Start the Fluent solver using a general-purpose programming language to batch set key simulation parameter boundaries and simulation solution conditions for the pre-built DC charging pile simulation model definition file. The pre-built DC charging pile simulation model definition file is the model file obtained through steps A1 to A4. Using a general-purpose programming language, various key simulation parameters and model simulation solution conditions in the model file can be modified. In this embodiment, step B1 specifically includes the following steps:
[0109] B11. Start the Fluent solver programmatically using a general-purpose programming language, read the pre-built DC charging pile simulation model definition file, and load the pre-completed simulation settings. In an exemplary embodiment, the Fluent startup process can be controlled programmatically through the Python interface (pyfluent). Use the solver_session.settings.file.read_case() function to read the file with the ".cas.h5" extension already saved in A4 to load the simulation settings previously completed in the Fluent IDE. This allows simulation processing to continue directly in Python without having to reset all parameters.
[0110] B12. Enable Fluent's parameterization feature and define key simulation parameter boundaries in batches using named expression functions. Specifically, enable Fluent's parameterization feature in the Python IDE and define key simulation parameters (such as inlet temperature) in the A4 simulation file. These parameters are defined in batches using the named expression function `named_expressions`, specifying their names, units, and initial values. Subsequently, these parameters are applied to the temperature settings in the boundary conditions. In this embodiment, the key simulation parameters set are the inlet temperature (`inlet1_temp`) and the outlet temperature (`inlet2_temp`). The unit of the parameters is Kelvin (K), and the initial value for both is 293K.
[0111] B13. Simulation solution conditions are set in batches using a general-purpose programming language; simulation solution conditions include the number of iterations and the residual threshold. In this embodiment, the number of iterations is set to 100 to ensure the accuracy and convergence of the solution, and convergence condition checking is enabled, with the convergence condition set as the absolute value criterion. During the simulation, it is determined whether the monitored residual is lower than the specified residual threshold to ensure that the solution converges to the expected accuracy.
[0112] B14. Save all simulation settings and boundary conditions from steps B11 to B13 as a file with the extension ".cas.h5" for future loading, simulation continuation, or analysis.
[0113] B2. Define the key simulation parameters of the DC charging pile simulation model as parameter design points. Based on the boundaries of the key simulation parameters, batch set the input parameters for the parameter design points, generating several parameter design points and exporting them as parameter design point project files. Parameter design points are combinations of key simulation parameters in subsequent individual simulation cases. Specifically, step B2 includes the following steps:
[0114] B21. Use Python commands to initialize the parametric design point project in Fluent, preparing to begin multi-design point simulation. The specified project file is loaded and the basic framework of the parametric design points is set up using the initialization parameter setting function `solver_session.settings.parametric_studies.initialize()`.
[0115] B22. By accessing the parameter design points, modify their input parameters (such as inlet temperature). This step ensures that subsequently generated design points can be adjusted based on these parameters.
[0116] B23. Use advanced Latin hypercube sampling to generate design points in batches as defined in S5. By specifying the number of design points, parameter upper and lower bounds, etc., generate design points that meet the requirements for subsequent simulation.
[0117] Specifically, in this embodiment, step B23 calls the "Automatic Design Point Generation" interface provided by Fluent, with its sequence number 13 corresponding to Advanced Latin Hypercube Sampling. The total number of generated design points is set to 2000, the minimum inlet temperature is 278K and the maximum is 350K, the minimum outlet temperature is 278K and the maximum is 330K, and existing design points are not deleted. The specific steps in this embodiment are as follows: the automatic design point creation function `tui.parametric_study.design_points.auto_create.create_design_points` is called, and the values 13, 2000, 278, 350, 278, 330, and no are entered in sequence.
[0118] B24. Export the several parameter design points generated in B23 as a table file with the extension ".csv" for further data analysis or report generation. In this embodiment, the design point export function `export_design_table` is called to write all generated design points to a CSV file. In this embodiment, one set of parameter design points is, for example: Case 1, initial coolant temperature 1, flow rate 1.
[0119] B3. Based on a pre-built DC charging pile simulation model, batch-configured simulation solution conditions, and parameter design point project files, batch simulation is automatically performed. Specifically, in this embodiment, the design point update function `design_points.update_all()` is executed to start batch simulation calculations. Any simulation result will be: Case 1, wall temperature 1 (cooling effect). After the batch simulation is completed, to ensure subsequent reuse or backup, the entire parameterized project needs to be saved or saved as. In this embodiment, `save()` is executed in the project setting function `settings.file.parametric_project` to save the project, and `save_as(project_filename=full path)` is used to back up the project as a new project.
[0120] B4. Process the batch simulation results using a general-purpose programming language, export the 3D coordinate values of key surfaces or key nodes at each parameter design point, and store the target parameter simulation result files. In this embodiment, step B4 specifically includes the following steps:
[0121] B41. Locate the simulation results directory and check if the folder corresponding to each parameter design point exists. In this embodiment, the calculation results of all parameter design points are stored in subfolders named DP1, DP2, ..., DP2000 (the parent path is denoted as output_dir). Iterate through each subdirectory in sequence; if a directory is found to be missing, simply print a reminder message and continue to prevent the script from being interrupted due to path errors.
[0122] B42. Search for simulation result folders that meet preset conditions: the folder contains one file each with the extension ".cas.h5" and ".dat.h5". Within each existing subdirectory, search for one file each with the extensions ".cas.h5" and ".dat.h5". If both types of files are found, add their full paths as a tuple to the list `case_data_files`; if only one is found, ignore that entry and continue to the next loop.
[0123] B43. Batch load and export readable simulation result files of 3D coordinate values and target parameters for key surfaces or key nodes. Specifically, in this embodiment, for each pair of files collected in case_data_files: first, call Fluent's command-line interface read_case_data to load the corresponding file with the suffix ".cas.h5" and the file with the suffix ".dat.h5" simultaneously; then execute the export.ascii command to export the node coordinates and temperatures on the specified target surface or component (multiple pipe walls, inlet / outlet planes, and several monitoring sections) as ASCII text.
[0124] During the above processing, a progress message is printed after each pair of files is processed to facilitate confirmation of the script's running status. After all design points have been processed, the Fluent session is exited normally by calling the exit function solver_session.exit() to release resources.
[0125] B5. Analyze the simulation results and engineering requirements based on the design points of each parameter to determine the optimal simulation results and corresponding parameter design points. Specifically, use the `os` command to extract the result files in the DP1, DP2...DP1000 folders, analyze and extract the optimal simulation results according to the engineering requirements, and find the design point parameter values of the optimal simulation results in the exported parameter design point table file with the extension ".csv" according to the index.
[0126] The above embodiments of this application provide a batch simulation analysis method for DC charging piles for new energy vehicles. First, by programming with a general programming language, key simulation parameters and model simulation solution conditions in the model file can be modified. This step eliminates the need for manual parameter setting, effectively reducing human error, achieving standardized configuration of key parameters, and significantly improving the efficiency of parameter setting in large-scale simulation scenarios. This solves the problems of high workload and poor consistency in traditional manual setting. Second, by batch generating parameter design points, the systematicity and uniformity of parameter combinations in each simulation case are ensured, facilitating multi-scenario comparative analysis and avoiding parameter confusion caused by manual setting, thus providing a foundation for comprehensive evaluation of charging pile performance. Furthermore, based on the pre-built DC charging pile simulation model, batch-set simulation solution conditions, and parameter design point project files, batch simulation is automatically performed. This process requires no manual intervention, can continuously and efficiently complete large-scale simulation tasks, significantly shorten the simulation cycle, and solve the problems of low efficiency and inability to meet the needs of large-scale evaluation in traditional single-case simulation. Secondly, by processing batch simulation results using a general-purpose programming language, dependence on third-party platforms is eliminated, enabling automated extraction and standardized storage of results. This ensures universal readability of the files, facilitates cross-platform data integration and sharing, reduces the risk of data omissions or errors, and improves post-processing efficiency. Finally, by analyzing batch results, the system can quickly identify the optimal parameter combination that meets engineering requirements, providing direct evidence for optimizing charging pile heat dissipation design and material selection. This accelerates the design verification and iteration process, solving the problems of slow traditional evaluation methods and their inability to support rapid improvements.
[0127] Based on the same inventive concept, this application also provides a system for implementing the above-mentioned method for batch simulation analysis of DC charging piles for new energy vehicles. The solution provided by this system is similar to the solution described in the above method. In an exemplary embodiment, such as... Figure 3 As shown, a mass simulation analysis system for DC charging piles for new energy vehicles is provided, including the following functional modules:
[0128] The parameter condition batch preset module is used to start Fluent's solver through programming in a general programming language, and to batch set key simulation parameter boundaries and simulation solution conditions for pre-built DC charging pile simulation model definition files. The pre-built DC charging pile simulation model definition files are model files obtained by modeling DC charging piles, defining key simulation parameters, meshing and geometric generation, setting physical models, and preset model simulation solution conditions. Through programming in a general programming language, various key simulation parameters and model simulation solution conditions in the model file can be modified.
[0129] The parameter design point batch generation module is used to define the key simulation parameters of the DC charging pile simulation model as parameter design points. Based on the boundary of the key simulation parameters, the input parameters of the parameter design points are set in batches, generating a number of parameter design points and exporting them as parameter design point project files. The parameter design points are combinations of key simulation parameters in subsequent individual simulation cases.
[0130] The parameter design point batch simulation module automatically performs batch simulations based on a pre-built DC charging pile simulation model, batch-set simulation solution conditions, and parameter design point project files.
[0131] The batch simulation result processing module is used to process batch simulation results through programming in a general programming language, export readable 3D coordinate values of key surfaces or key nodes and target parameter simulation result files at each parameter design point, and store them.
[0132] The optimal parameter design point determination module is used to analyze the simulation results and engineering requirements based on the parameter design points to determine the optimal simulation results and the corresponding parameter design points.
[0133] certainly, Figure 3 The architecture shown is merely exemplary; it can be omitted as needed when implementing different functionalities. Figure 3 One or at least two components of the system shown.
[0134] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 4 As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it can implement the batch simulation analysis method for DC charging piles for new energy vehicles provided in the above embodiment.
[0135] Those skilled in the art will understand that Figure 4The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.
[0136] In one exemplary embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.
[0137] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.
[0138] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.
[0139] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.
[0140] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).
[0141] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.
[0142] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0143] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.
Claims
1. A batch simulation analysis method for DC charging piles for new energy vehicles, characterized in that, include: The Fluent solver is launched by programming with a general-purpose programming language to batch set key simulation parameter boundaries and simulation solution conditions for a pre-built DC charging pile simulation model definition file. The pre-built DC charging pile simulation model definition file is a model file obtained by modeling the DC charging pile simulation model, defining key simulation parameters, meshing and geometric body generation, setting the physical model, and preset model simulation solution conditions. The key simulation parameters and model simulation solution conditions in the model file can be modified by programming with a general-purpose programming language. The key simulation parameters of the DC charging pile simulation model are defined as parameter design points. The input parameters of the parameter design points are set in batches according to the boundaries of the key simulation parameters, generating several parameter design points and exporting them as parameter design point project files. The parameter design points are combinations of key simulation parameters in subsequent individual simulation cases. Based on the pre-built DC charging pile simulation model, the batch-set simulation solution conditions, and the parameter design point project file, batch simulation is automatically performed. The batch simulation results are processed by programming in a general programming language, and the 3D coordinate values of key surfaces or key nodes and the target parameter simulation result files with readable parameters at each parameter design point are exported and stored. Based on the simulation results of each parameter design point and the engineering requirements, the optimal simulation results and the corresponding parameter design points are determined.
2. The method for batch simulation analysis of DC charging piles for new energy vehicles according to claim 1, characterized in that, The model file obtained by performing simulation modeling of DC charging piles, defining key simulation parameters, meshing and geometry generation, setting physical models, and pre-setting simulation solution conditions specifically includes: A simulation model of a DC charging pile is created, and the key simulation parameters of the simulation model are defined to obtain the DC charging pile simulation model file. Import the DC charging pile simulation model file into Fluent Meshing to perform mesh and geometry generation, and then export the DC charging pile simulation model mesh file. Based on the heat flow and current transfer characteristics of DC charging piles, the physical model of the DC charging pile simulation model mesh file is set in Fluent GUI. Based on the established physical model, the simulation solution conditions for the DC charging pile simulation model mesh file are defined and preset, and then saved as the DC charging pile simulation model definition file.
3. The method for batch simulation analysis of DC charging piles for new energy vehicles according to claim 2, characterized in that, The DC charging pile simulation model file is imported into FluentMeshing for mesh and geometry generation, and then the DC charging pile simulation model mesh file is exported, specifically including: Open the FluentMeshing tool and import the DC charging pile simulation model file; Errors in the DC charging pile simulation model were repaired using a geometry cleanup tool. The surface of the repaired DC charging pile simulation model is divided into regions based on the solid / liquid plane. Based on the division of the surface of the DC charging pile simulation model, a geometric surface mesh of the DC charging pile is generated; For the surface mesh of the DC charging pile geometry, select a hexahedral mesh to generate the DC charging pile geometry mesh; Boundary layer meshes were added to key simulation regions of the DC charging pile simulation model to capture details of heat flow and flow. Based on the liquid and solid components, the DC charging pile simulation model is divided into regions, and each region is named. After using the inspection tool to inspect the DC charging pile simulation model after the area division, the DC charging pile simulation model mesh file is exported.
4. The method for batch simulation analysis of DC charging piles for new energy vehicles according to claim 2, characterized in that, Based on the heat flow and current transfer characteristics of DC charging piles, the physical model of the DC charging pile simulation model mesh file is set in Fluent GUI, specifically including: To address the heat flow and current transfer characteristics in DC charging piles, select the physical model in the Fluent GUI interface and enable the energy equation, momentum equation, and mass equation. Set the material properties of the interior and shell of the DC charging pile simulation model; The DC charging pile simulation model is divided into a structural domain and an air domain to ensure conjugate heat transfer between the air domain and the structural domain; the structural domain is the area of power generation components and heat generation devices, and the air domain is the fluid region. Set the power consumption parameters and surface heat transfer coefficients of the power generation components and heat generation devices in the structural domain; Set the initial values of inlet and outlet velocity, pressure, and temperature at the boundary of the fluid region in the air domain; The internal heat transfer mode of the DC charging pile simulation model is set to natural convection.
5. The method for batch simulation analysis of DC charging piles for new energy vehicles according to claim 1, characterized in that, By programming in a general-purpose programming language to launch Fluent's solver, key simulation parameter boundaries and simulation solution conditions are set in batches for pre-built DC charging pile simulation model definition files. Specifically, this includes: The Fluent solver is launched by programming in a general programming language, which reads the pre-built DC charging pile simulation model definition file and loads the pre-completed simulation settings. Enable Fluent's parameterization feature to define the boundaries of key simulation parameters in batches using named expression functions; The simulation solution conditions are set in batches using a general-purpose programming language; the simulation solution conditions include the number of iterations and the residual threshold.
6. The method for batch simulation analysis of DC charging piles for new energy vehicles according to claim 1, characterized in that, The batch simulation results are processed using a general-purpose programming language to export and store readable 3D coordinate values of key surfaces or key nodes and target parameter simulation result files at each parameter design point. Specifically, this includes: Locate the simulation results directory and check if the folder corresponding to each parameter design point exists; Search for simulation results folders that meet preset criteria; the preset criteria are that the folder contains one file each with the extension ".cas.h5" and ".dat.h5"; Batch load and export readable simulation result files containing 3D coordinate values and target parameters of key surfaces or key nodes.
7. A batch simulation analysis system for DC charging piles for new energy vehicles, characterized in that, include: The parameter condition batch preset module is used to start the Fluent solver through programming in a general programming language, and to batch set the key simulation parameter boundaries and simulation solution conditions of the pre-built DC charging pile simulation model definition file. The pre-built DC charging pile simulation model definition file is a model file obtained by performing simulation model modeling and key simulation parameter definition, mesh and geometry generation, physical model setting and model simulation solution condition preset of DC charging pile. Through programming in a general programming language, various key simulation parameters and model simulation solution conditions in the model file can be modified. The parameter design point batch generation module is used to define key simulation parameters of the DC charging pile simulation model as parameter design points, set the input parameters of the parameter design points in batches according to the boundaries of the key simulation parameters, generate a number of parameter design points and export them as parameter design point project files; the parameter design points are combinations of key simulation parameters in subsequent individual simulation cases; The parameter design point batch simulation module automatically performs batch simulations based on a pre-built DC charging pile simulation model, the batch-set simulation solution conditions, and the parameter design point project file. The batch simulation result processing module is used to process batch simulation results through programming in a general programming language, export readable three-dimensional coordinate values of key surfaces or key nodes and target parameter simulation result files under each parameter design point, and store them. The optimal parameter design point determination module is used to analyze the simulation results and engineering requirements based on each parameter design point to determine the optimal simulation results and the corresponding parameter design points.
8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the batch simulation analysis method for DC charging piles for new energy vehicles 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 executed by a processor, the computer program implements the batch simulation analysis method for DC charging piles for new energy vehicles as described in any one of claims 1-6.
10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the batch simulation analysis method for DC charging piles for new energy vehicles as described in any one of claims 1-6.