A method, system, device and medium for evaluating the heat dissipation effect of a cabinet electrical cabinet

Abstract

The present application relates to the technical field of robot control evaluation, and particularly relates to a kind of evaluation method, system, equipment and medium of the heat dissipation effect of cabinet electric cabinet, method is executed iteration solution to the numerical calculation model to be solved, generates temperature field distribution data and flow field velocity vector data, to evaluate the heat dissipation effect of cabinet electric cabinet;By obtaining the physical attribute parameter set of cabinet electric cabinet, the original three-dimensional design model is inhibited and geometrically converted to reconstruct the thermal analysis geometric model;Parameter set is mapped to model primitive and boundary conditions are defined to build a numerical calculation model;Finally, execute iteration solution to generate temperature field and flow field data;Realize the digital pre-evaluation of heat dissipation effect in design stage, avoid the dependence on physical prototype test, effectively shorten the development cycle, reduce the research and development cost, and improve the accuracy and efficiency of evaluation.

Description

Technical Field

[0001] This invention relates to the field of robot control evaluation technology, and in particular to a method, system, equipment and medium for evaluating the heat dissipation effect of a chassis and electrical cabinet. Background Technology

[0002] With the rapid evolution of industrial robot technology, the performance requirements for control cabinets, as core components, are becoming increasingly stringent. Modern industrial applications not only require control cabinets to adapt to the driving needs of robots across various power ranges, but also to ensure stable operation under high ambient temperatures, preventing internal joint components from triggering overheat alarms or causing shutdowns. To meet market demands, the development of control cabinets must balance compact internal component layout, appropriate fan selection, and efficient airflow design, while also facing immense pressure to shorten development cycles and increase the success rate of first-time design.

[0003] In the existing technological system, evaluating the heat dissipation effect of industrial robot control cabinets typically relies on physical prototype testing. Specifically, after the physical prototype of the control cabinet is manufactured, designers need to connect it to an industrial robot for actual work cycle operation, and obtain temperature data of the heat-generating components inside the cabinet through on-site measurements. If it is necessary to verify the heat dissipation performance under different ambient temperatures, it is also necessary to use equipment such as constant temperature chambers to simulate specific environments. In this mode, the selection of fans and heat sinks, as well as the design of air ducts, often rely more on the designer's past experience and lack quantitative analysis data support during the design phase. Consequently, it is impossible to conduct an accurate and low-cost pre-assessment of the heat dissipation effect of the control cabinet in the early stages of the design phase. In addition, since the rationality of the thermal design can only be verified after the physical prototype is produced, if the test results are unsatisfactory, the design scheme must be revised and the prototype must be prototyped again. This iterative process not only greatly prolongs the product development cycle, but also significantly increases the company's R&D costs and trial-and-error costs. Summary of the Invention

[0004] The main objective of this invention is to provide a method for evaluating the heat dissipation effect of a chassis and electrical cabinet, aiming to solve the problem that existing technologies make it difficult to accurately pre-evaluate the heat dissipation performance of chassis and electrical cabinets during the design phase.

[0005] To achieve the above objectives, the present invention provides a method for evaluating the heat dissipation effect of a chassis / cabinet, the method comprising the following steps: Obtain the set of physical property parameters of the chassis and electrical cabinet; wherein, the set of physical property parameters includes the heating power of the heating elements inside the chassis and electrical cabinet, fan parameters, and material parameters; The original 3D design model of the chassis and electrical cabinet is obtained, and feature suppression and geometric transformation processing are performed on the original 3D design model to generate a thermal analysis geometric model; wherein, the geometric transformation processing includes converting irregular entities into regular geometric bodies for recognition by thermal analysis tools; The physical property parameter set is mapped and associated to the corresponding primitives of the thermal analysis geometric model, and the fluid domain boundary conditions and contact thermal resistance parameters are defined to obtain the numerical calculation model to be solved. The numerical calculation model to be solved is iteratively solved to generate temperature field distribution data and flow field velocity vector data to evaluate the heat dissipation effect of the chassis and cabinet.

[0006] Optionally, the process of obtaining the heating power includes: Retrieve the electronic device model of the heating element and input the preset operating parameters; Calculate the total power loss data based on the operating state of the electronic device model under the operating parameters. The total power loss data is decomposed into conduction loss data and switching loss data, and the conduction loss data and switching loss data are used as part of the physical attribute parameter set.

[0007] Optionally, generating the thermal analysis geometric model includes the following steps: Identify the suppressed parts in the original 3D design model to obtain suppression instructions to remove the suppressed parts; Extract the geometric features of the heating element and convert the geometric features into regular primitives; wherein, the regular primitives include cuboids, cylinders, or prisms; Preserve the fin structure features of the radiator and generate a radiator primitive with the same shape as the original; The regular primitives are combined with the radiator primitives to form a thermal analysis geometric model.

[0008] Optionally, the step of extracting the geometric features of the heating element, converting the geometric features into regular primitives, and generating a radiator primitive with the same shape as the original radiator by retaining the fin structure features of the radiator, further includes the following steps: Extract the original contact area value between the heating element and the heat sink from the original three-dimensional design model; Calculate the simplified contact area between corresponding primitives in the transformed thermal analysis geometric model; An area correction factor is obtained based on the original contact area value and the simplified contact area value; wherein, the area correction factor is the ratio of the simplified contact area value to the original contact area value, and the area correction factor is used to correct the contact area in the construction of the solution domain.

[0009] Optionally, between obtaining the numerical computation model to be solved and performing iterative solution on the numerical computation model to be solved, the following steps are further included: The numerical computation model to be solved is divided into grids; Identify temperature difference region data in the numerical calculation model after mesh division; wherein, the spatial location corresponding to the temperature difference region data includes the surface of the heating element; Based on the temperature difference region data, a local mesh refinement instruction is generated. Using the computational domain size as a reference, the mesh cell size of the corresponding region is limited and reduced to generate a discretized mesh model. For example, the mesh cell size of the corresponding region is limited to less than 1 / 20 of the computational domain size.

[0010] Optionally, mapping and associating the set of physical property parameters to the corresponding primitives of the thermal analysis geometric model includes the following steps: Load the fan parameters into the fan primitives in the thermal analysis geometric model; The opening area data of the air inlet of the chassis and the opening ratio data of the air outlet grille are loaded into the corresponding boundary primitives to form complete boundary condition constraints.

[0011] Optionally, defining the fluid domain boundary conditions includes the following steps: Calculate the Reynolds number based on the characteristic dimensions of the numerical calculation model to be solved; Flow regime determination data is generated based on the Reynolds number. If the flow is determined to be turbulent, the zero equation or higher-order turbulence model parameters are configured into the numerical calculation model.

[0012] To achieve the above objectives, the present invention also provides an evaluation system, the system comprising: The parameter acquisition module is used to acquire a set of physical property parameters of the chassis and electrical cabinet; wherein, the set of physical property parameters includes the heating power of the heating elements inside the chassis and electrical cabinet, fan parameters, and material parameters; The model processing module is used to acquire the original three-dimensional design model of the chassis and electrical cabinet, perform feature suppression and geometric transformation processing on the original three-dimensional design model, and generate a thermal analysis geometric model; wherein, the geometric transformation processing includes converting irregular entities into regular geometric bodies for recognition by thermal analysis tools; The geometric analysis module is used to map and associate the physical property parameter set to the corresponding primitives of the thermal analysis geometric model, define the fluid domain boundary conditions and contact thermal resistance parameters, so as to obtain the numerical calculation model to be solved. The calculation and evaluation module is used to perform iterative solutions on the numerical calculation model to be solved, and generate temperature field distribution data and flow field velocity vector data to evaluate the heat dissipation effect of the chassis and cabinet.

[0013] To achieve the above objectives, the present invention also provides a computer device, which includes a memory and a processor, wherein the memory stores a computer program and the processor executes the computer program to implement the above-described method.

[0014] To achieve the above objectives, the present invention also provides a computer-readable storage medium storing a computer program, wherein a processor executes the computer program to implement the above-described method.

[0015] The beneficial effects that this invention can achieve are as follows: This invention constructs a complete digital evaluation process to pre-evaluate the heat dissipation effect during the design phase, avoiding reliance on physical prototype testing. This solves the problems of extended development cycles and increased R&D costs in existing technologies. Specifically, by executing data acquisition steps, a set of physical property parameters is obtained. This set of parameters covers the heating power of the heating elements in the chassis and cabinet, fan parameters, and material parameters. These parameters are based on actual data from the design phase rather than empirical estimates, thus providing a real and reliable input basis for subsequent thermal analysis. Furthermore, by implementing a geometric model reconstruction step, the original 3D design model is acquired and subjected to feature suppression and geometric transformation processing. Feature suppression precisely eliminates non-critical parts to avoid redundant calculations, while geometric transformation processing converts irregular entities into regular geometric shapes that can be identified by thermal analysis tools. For example, complex heat dissipation structures are simplified into regular primitives such as cuboids or cylinders. This preserves key heat dissipation features while adapting to the processing requirements of thermal analysis tools, effectively solving the problem of low simulation efficiency caused by the overly complex original CAD model.

[0016] Finally, during the process of constructing the solution domain, the set of physical property parameters is mapped and associated with the corresponding primitives of the thermal analysis geometric model. The parameter mapping ensures that properties such as heat generation power are precisely bound to the primitives. The boundary conditions of the fluid domain are defined, and the contact thermal resistance parameters are set, thereby constructing a high-fidelity numerical calculation model. The Reynolds number is calculated based on the characteristic dimensions to determine the flow state and configure the corresponding turbulence model, making the simulation environment closer to the real heat dissipation scenario. The iterative simulation evaluation step is finally executed, and the numerical calculation model to be solved is iteratively solved. After the iterative solution is completed, the converged residual curve is obtained. This residual curve is used to verify the stability of the solution process. Temperature field distribution data and flow field velocity vector data are generated. These data directly quantify the heat dissipation performance and achieve an objective evaluation of the heat dissipation effect. Attached Figure Description

[0017] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0018] Figure 1 This is a flowchart illustrating the method in Embodiment 1 of the present invention; Figure 2 This is a structural block diagram of the system in Embodiment 2 of the present invention; Figure 3 This is a schematic diagram showing the results of evaluating some components of the control cabinet using the method in Embodiment 1 of the present invention.

[0019] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a specific posture. If the specific posture changes, the directional indication will also change accordingly.

[0022] In this invention, unless otherwise explicitly specified and limited, the terms "connection," "fixed," etc., should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral part; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0023] Furthermore, if the embodiments of this invention involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the meaning of "and / or" throughout the text includes three parallel solutions; for example, "A and / or B" includes solution A, solution B, or a solution where both A and B are satisfied simultaneously. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0024] Example 1: Reference Figure 1 This embodiment provides a method for evaluating the heat dissipation effect of a chassis / cabinet, the method comprising the following steps: Obtain the set of physical property parameters of the chassis and electrical cabinet; wherein, the set of physical property parameters includes the heating power of the heating elements inside the chassis and electrical cabinet, fan parameters, and material parameters; The original 3D design model of the chassis and electrical cabinet is obtained, and feature suppression and geometric transformation processing are performed on the original 3D design model to generate a thermal analysis geometric model; wherein, the geometric transformation processing includes converting irregular entities into regular geometric bodies for recognition by thermal analysis tools; The physical property parameter set is mapped and associated to the corresponding primitives of the thermal analysis geometric model, and the fluid domain boundary conditions and contact thermal resistance parameters are defined to obtain the numerical calculation model to be solved. The numerical calculation model to be solved is iteratively solved to generate temperature field distribution data and flow field velocity vector data to evaluate the heat dissipation effect of the chassis and cabinet.

[0025] It should be noted that in the traditional design process of industrial robot control cabinets, the inability to accurately pre-assess heat dissipation during the design phase forces designers to rely on physical prototype testing to verify the rationality of the thermal design. The essence of this problem lies in the lack of effective quantitative analysis methods during the design phase, making it impossible to identify heat dissipation risks early on. This, in turn, affects product development efficiency and cost control. Specifically, the physical prototype testing model requires actual working cycle operation after the control cabinet is manufactured, obtaining temperature data through on-site measurements. However, fan selection, airflow design, and heat sink configuration mainly rely on design experience, lacking data support from the design phase, thus causing a lag in heat dissipation performance evaluation.

[0026] To address the aforementioned issues, this embodiment provides a method for evaluating the heat dissipation effect of a chassis / cabinet. First, a data acquisition step is performed to obtain a set of physical property parameters. This parameter set covers the heat generation power of the heat-generating components within the chassis / cabinet, fan parameters, and material parameters. These parameters are based on actual data from the design phase rather than empirical estimates, thus providing a reliable input basis for subsequent thermal analysis. Further, a geometric model reconstruction step is implemented. The original 3D design model is acquired and subjected to feature suppression and geometric transformation processing. Feature suppression precisely eliminates non-critical parts to avoid redundant calculations, while geometric transformation converts irregular entities into regular geometric shapes that can be recognized by thermal analysis tools. For example, complex heat dissipation structures are simplified into regular primitives such as cuboids or cylinders. This preserves key heat dissipation features while adapting to the processing requirements of thermal analysis tools, effectively solving the problem of low simulation efficiency caused by overly complex original CAD models. The solution domain construction step is then completed, and the set of physical property parameters is mapped and associated with the corresponding primitives of the thermal analysis geometric model. Parameter mapping ensures that attributes such as heat generation power are precisely bound to the primitives. Fluid domain boundary conditions are defined, and contact thermal resistance parameters are set, thereby constructing a high-fidelity numerical calculation model. This model determines the flow regime and configures the corresponding turbulence model by calculating the Reynolds number based on characteristic dimensions, making the simulation environment closer to the real heat dissipation scenario. The iterative simulation evaluation step is finally executed. The numerical calculation model to be solved is iteratively solved, and the converged residual curve is obtained after the iterative solution is completed. This residual curve is used to verify the stability of the solution process. Temperature field distribution data and flow field velocity vector data are generated. These data directly quantify the heat dissipation performance, achieving an objective evaluation of the heat dissipation effect.

[0027] In some preferred methods, the simulation process includes inputting parameters such as IPM model, DC bus capacitance, load (motor model, resistive and inductive load, etc.), and drive resistance into the simulation tool according to the actual application, initially assuming a junction temperature, running the simulation at that junction temperature, and calculating the losses.

[0028] In some preferred embodiments, geometric model reconstruction can be selected to reasonably simplify the control cabinet model and convert each geometric model therein into an object that can be recognized by thermal analysis tools; when converting ordinary geometric bodies, the level of conversion can be selected, such as converting into cuboids, cylinders, polygons, CAD bodies that basically retain the original shape, etc.

[0029] In some preferred embodiments, since thermally conductive silicone is often present between the heat-generating elements in the control cabinet and the adjacent plates or heat sinks, the modeling of the thermally conductive silicone can be done by creating a surface at the corresponding location and then converting it into a surface that can be recognized by thermal simulation software.

[0030] In some preferred embodiments, the solution process involves observing the residual iteration curve and the temperature change curve at the temperature monitoring point. The temperature results for the 1st, 2nd, 3rd, 4th, 5th, and 6th axis modules and the two rectifiers are referenced. Figure 3 As can be seen in the figure, the temperature of the rectifier on the upper left is relatively high, and the temperature of the two-axis module is also relatively high due to its high heat generation power.

[0031] In some preferred embodiments, the residual curve can be understood as a curve that records how the residual value changes as the number of iterations increases.

[0032] In some preferred embodiments, the Reynolds number (Re) is a dimensionless number used in fluid mechanics to determine the state of fluid flow, representing the ratio of inertial force to viscous force.

[0033] In some preferred embodiments, feature suppression can be understood as the process of removing small features (such as screws, chamfers, nameplates, gaskets, etc.) from the computational model during the conversion of a CAD model to a CAE model.

[0034] In some preferred embodiments, geometric transformation can be understood as simplifying a complex industrial design shape (such as a frequency converter housing with complex bumps and grooves) into a thermally equivalent simple geometry.

[0035] In some preferred embodiments, primitives can be understood as the smallest logical unit representing a specific physical object in simulation software.

[0036] In some preferred embodiments, the thermal analysis tool can be selected from existing conventional tools, such as the widely used Ansys.

[0037] In this embodiment, the process of obtaining the heating power includes: Retrieve the electronic device model of the heating element and input the preset operating parameters; Calculate the total power loss data based on the operating state of the electronic device model under the operating parameters. The total power loss data is decomposed into conduction loss data and switching loss data, and the conduction loss data and switching loss data are used as part of the physical attribute parameter set.

[0038] It should be noted that the above steps, by retrieving the electronic device model and inputting operating condition parameters, enable the heat source modeling to dynamically track the actual electrical behavior of the components, avoiding the limitations of static parameter estimation. On this basis, by decomposing the total power loss into conduction loss and switching loss, the thermal simulation model can distinguish the different heat generation mechanisms of the two types of losses in the time dimension. Among them, conduction loss forms a continuous heat source, while switching loss forms a periodic pulse heat source, thereby accurately depicting the temperature fluctuation characteristics of the surface of the heating element. Finally, the decomposed loss data is used as a component of the physical property parameter set to ensure that the thermal boundary conditions match the dynamic characteristics of the actual working cycle, forming a complete heat source input chain.

[0039] In this embodiment, generating the thermal analysis geometric model includes the following steps: Identify the suppressed parts in the original 3D design model to obtain suppression instructions to remove the suppressed parts; Extract the geometric features of the heating element and convert the geometric features into regular primitives; wherein, the regular primitives include cuboids, cylinders, or prisms; Preserve the fin structure features of the radiator and generate a radiator primitive with the same shape as the original; The regular primitives are combined with the radiator primitives to form a thermal analysis geometric model.

[0040] Understandably, the above steps, through a systematic approach to the geometric model reconstruction process, simplify the model while accurately preserving the core thermal features that affect heat dissipation. First, non-thermal-related components are identified and eliminated, significantly reducing model complexity. Second, the geometric features of heat-generating elements are transformed into regular primitives to ensure the accuracy of heat source simulation. At the same time, the radiator fin structure is fully preserved to accurately reproduce the heat exchange process. Finally, the regular primitives are combined with the radiator primitives to construct a complete model that simplifies non-critical parts while preserving key thermal features, enabling subsequent thermal analysis to truly reflect the interaction between the temperature field and the flow field.

[0041] In this embodiment, the process of extracting the geometric features of the heating element, converting the geometric features into regular primitives, and generating a radiator primitive with the same shape as the original radiator by retaining the fin structure features of the heat sink, further includes the following steps: Extract the original contact area value between the heating element and the heat sink from the original three-dimensional design model; Calculate the simplified contact area between corresponding primitives in the transformed thermal analysis geometric model; An area correction factor is obtained based on the original contact area value and the simplified contact area value; wherein, the area correction factor is the ratio of the simplified contact area value to the original contact area value, and the area correction factor is used to correct the contact area in the construction of the solution domain.

[0042] Understandably, the above steps extract the actual contact area values ​​from the original 3D design model, directly obtaining the true physical state of the complex interface between the heating element and the heat sink based on the unsimplified original model; then, the simplified contact area values ​​in the transformed thermal analysis geometric model are calculated, and quantitative analysis is performed on the regularized primitives to identify the area differences caused by geometric simplification; finally, an area correction factor is generated as the ratio of the two. This factor utilizes the inverse proportionality between contact thermal resistance and effective contact area to dynamically compensate for the area reduction in the simplified model, so that the correction of the contact thermal resistance parameter in the solution domain construction process conforms to the physical laws of heat conduction and adapts to the numerical calculation requirements, thereby ensuring the overall accuracy of the thermal analysis model.

[0043] In this embodiment, between obtaining the numerical computation model to be solved and performing iterative solution on the numerical computation model to be solved, the following steps are further included: The numerical computation model to be solved is divided into grids; Identify temperature difference region data in the numerical calculation model after mesh division; wherein, the spatial location corresponding to the temperature difference region data includes the surface of the heating element; Based on the temperature difference region data, a local mesh refinement instruction is generated. Using the computational domain size as a reference, the mesh cell size of the corresponding region is limited and reduced to generate a discretized mesh model. For example, if the computational domain size is 1, the mesh cell size of the corresponding region can be less than 1 / 20 of the computational domain size, or it can be a proportion that meets the requirements, such as 1 / 20, 1 / 25, or 1 / 30.

[0044] It should be noted that the above steps establish a basic mesh framework through discretization, providing an initial basis for subsequent optimization; the step of identifying temperature difference region data focuses on areas with drastic temperature changes, such as the surface of heating elements, ensuring accurate positioning of the densified region based on actual heat distribution characteristics and avoiding ineffective resource investment in non-critical areas; the step of generating local densified mesh instructions dynamically adjusts the mesh density according to the temperature difference region data, making the mesh refinement closely match the needs of physical phenomena; the size constraint step controls the mesh cell size of critical regions within a reasonable proportion of the computational domain scale, ensuring both local refinement and maintaining global computational efficiency; the finally generated discretized mesh model achieves a balance between accuracy and efficiency in heat dissipation effect evaluation through collaborative optimization of local and global aspects.

[0045] In some specific implementations, after obtaining the numerical calculation model of the chassis and electrical cabinet, a preliminary mesh generation is first performed to form a basic discrete framework. Then, high gradient regions on the surface of the heating element are identified through temperature field pre-calculation. These regions are the main heat source interfaces where the temperature changes most drastically. Based on this identification result, a mesh refinement instruction is generated for the surface region of the heating element, setting the mesh cell size of this region to 1 / 20 of the maximum feature size of the computational domain, or the aforementioned proportional value. The finally generated discrete mesh model is used for simulation calculations in the iterative simulation evaluation step, thereby ensuring accurate capture of the temperature gradient on the surface of the heating element while effectively controlling the overall consumption of computing resources.

[0046] In this embodiment, mapping and associating the physical property parameter set with the corresponding primitives of the thermal analysis geometric model includes the following steps: Load the fan parameters into the fan primitives in the thermal analysis geometric model; The opening area data of the air inlet of the chassis and the opening ratio data of the air outlet grille are loaded into the corresponding boundary primitives to form complete boundary condition constraints.

[0047] It should be noted that the above steps ensure the accurate matching of fan performance data and geometric model by directly loading fan parameters into fan primitives, thereby realistically simulating the inlet conditions of the fluid domain. At the same time, loading the inlet opening area data and the outlet grid opening ratio data into the corresponding boundary primitives respectively accurately quantifies the airflow resistance characteristics, so that the boundary conditions completely constrain the fluid domain behavior, effectively avoiding simulation deviations caused by missing parameters, and finally forming a complete boundary condition constraint system.

[0048] In this embodiment, defining the fluid domain boundary conditions includes the following steps: Calculate the Reynolds number based on the characteristic dimensions of the numerical calculation model to be solved; Flow regime determination data is generated based on the Reynolds number. If the flow is determined to be turbulent, the zero equation or higher-order turbulence model parameters are configured into the numerical calculation model.

[0049] In summary, the above steps provide a geometric basis for Reynolds number calculation by selecting characteristic dimensions. The calculation results of the Reynolds number directly generate flow regime determination data. When turbulence is determined, the applicable turbulence model parameters are automatically called and configured into the numerical calculation model, ensuring the accuracy of the fluid domain boundary condition settings. This enables the numerical calculation model to realistically simulate the fluid behavior inside the chassis and cabinet, thereby providing reliable temperature and flow field data for subsequent iterative simulations.

[0050] Example 2: As attached Figure 2 As shown, this embodiment provides an evaluation system, the system comprising: The parameter acquisition module is used to acquire a set of physical property parameters of the chassis and electrical cabinet; wherein, the set of physical property parameters includes the heating power of the heating elements inside the chassis and electrical cabinet, fan parameters, and material parameters; The model processing module is used to acquire the original three-dimensional design model of the chassis and electrical cabinet, perform feature suppression and geometric transformation processing on the original three-dimensional design model, and generate a thermal analysis geometric model; wherein, the geometric transformation processing includes converting irregular entities into regular geometric bodies for recognition by thermal analysis tools; The geometric analysis module is used to map and associate the physical property parameter set to the corresponding primitives of the thermal analysis geometric model, define the fluid domain boundary conditions and contact thermal resistance parameters, so as to obtain the numerical calculation model to be solved. The calculation and evaluation module is used to perform iterative solutions on the numerical calculation model to be solved, and generate temperature field distribution data and flow field velocity vector data to evaluate the heat dissipation effect of the chassis and cabinet.

[0051] It should be noted that, in the above content, by combining feature suppression and geometric transformation processing in a modular manner, and introducing parameter mapping correlation and iterative solution verification, virtual simulation pre-evaluation of heat dissipation effect can be achieved in the design stage, thereby shortening the development cycle and reducing R&D costs. Specifically, feature suppression accurately eliminates non-critical parts to avoid redundant calculations, geometric transformation processing transforms irregular entities into regular geometries to adapt to the requirements of thermal analysis tools, parameter mapping correlation ensures that physical property parameters are accurately bound to primitives, and iterative solution verification monitors the solution stability through residual curves. In this way, a high-fidelity numerical calculation model is constructed, which enables heat dissipation risks to be identified in the early stages of design and effectively avoids reliance on physical prototype testing.

[0052] It should be noted that each module in this embodiment corresponds one-to-one with each step in the method of the aforementioned embodiment. Therefore, the specific implementation of this embodiment can refer to the implementation of the aforementioned method, and will not be repeated here.

[0053] Example 3: Based on the same inventive concept as the foregoing embodiments, this embodiment provides a computer device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0054] Example 4: Based on the same inventive concept as the foregoing embodiments, this embodiment provides a computer-readable storage medium storing a computer program, and a processor executes the computer program to implement the above-described method.

[0055] Furthermore, in one embodiment, the present invention also provides a computer storage medium storing a computer program, which, when executed by a processor, implements the steps of the methods described in the foregoing embodiments.

[0056] In some embodiments, the computer-readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disk, or CD-ROM; or it may be a device including one or any combination of the above-mentioned memories. The computer may be a variety of computing devices, including smart terminals and servers.

[0057] In some embodiments, executable instructions may take the form of a program, software, software module, script, or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as a standalone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

[0058] As an example, executable instructions may, but do not necessarily, correspond to files in a file system. They may be stored as part of a file that holds other programs or data, for example, in one or more scripts in a Hyper Text Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple collaborating files (e.g., a file that stores one or more modules, subroutines, or code sections).

[0059] As an example, executable instructions can be deployed to execute on a single computing device, or on multiple computing devices located in one location, or on multiple computing devices distributed across multiple locations and interconnected via a communication network.

[0060] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0061] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0062] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory / random access memory, magnetic disk, optical disk) and includes several instructions to cause a multimedia terminal device (which may be a mobile phone, computer, television receiver, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0063] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for evaluating the heat dissipation effect of a chassis / cabinet, characterized in that, The method includes the following steps: Obtain the set of physical property parameters of the chassis and electrical cabinet; wherein, the set of physical property parameters includes the heating power of the heating elements inside the chassis and electrical cabinet, fan parameters, and material parameters; The original 3D design model of the chassis and electrical cabinet is obtained, and feature suppression and geometric transformation processing are performed on the original 3D design model to generate a thermal analysis geometric model; wherein, the geometric transformation processing includes converting irregular entities into regular geometric bodies for recognition by thermal analysis tools; The physical property parameter set is mapped and associated to the corresponding primitives of the thermal analysis geometric model, and the fluid domain boundary conditions and contact thermal resistance parameters are defined to obtain the numerical calculation model to be solved. The numerical calculation model to be solved is iteratively solved to generate temperature field distribution data and flow field velocity vector data to evaluate the heat dissipation effect of the chassis and cabinet.

2. The method for evaluating the heat dissipation effect of a chassis / cabinet as described in claim 1, characterized in that, The process of obtaining the heating power includes: Retrieve the electronic device model of the heating element and input the preset operating parameters; Calculate the total power loss data based on the operating state of the electronic device model under the operating parameters. The total power loss data is decomposed into conduction loss data and switching loss data, and the conduction loss data and switching loss data are used as part of the physical attribute parameter set.

3. The method for evaluating the heat dissipation effect of a chassis / cabinet as described in claim 1, characterized in that, The generation of the thermal analysis geometric model includes the following steps: Identify the suppressed parts in the original 3D design model to obtain suppression instructions to remove the suppressed parts; Extract the geometric features of the heating element and convert the geometric features into regular primitives; wherein, the regular primitives include cuboids, cylinders, or prisms; Preserve the fin structure features of the radiator and generate a radiator primitive with the same shape as the original; The regular primitives are combined with the radiator primitives to form a thermal analysis geometric model.

4. The method for evaluating the heat dissipation effect of a chassis / cabinet as described in claim 3, characterized in that, The process of extracting the geometric features of the heating element, converting these features into regular primitives, and generating a radiator primitive with the same shape as the original by combining them with the retained fin structure features of the heat sink, further includes the following steps: Extract the original contact area value between the heating element and the heat sink from the original three-dimensional design model; Calculate the simplified contact area between corresponding primitives in the transformed thermal analysis geometric model; An area correction factor is obtained based on the original contact area value and the simplified contact area value; wherein, the area correction factor is the ratio of the simplified contact area value to the original contact area value, and the area correction factor is used to correct the contact area in the construction of the solution domain.

5. The method for evaluating the heat dissipation effect of a chassis / cabinet as described in claim 1, characterized in that, Between obtaining the numerical computation model to be solved and performing iterative solution on the numerical computation model to be solved, the following steps are also included: The numerical computation model to be solved is divided into grids; Identify temperature difference region data in the numerical calculation model after mesh division; wherein, the spatial location corresponding to the temperature difference region data includes the surface of the heating element; Based on the temperature difference region data, a local refinement mesh instruction is generated. Using the computational domain size as a reference, the mesh cell size of the corresponding region is limited and reduced to generate a discretized mesh model.

6. The method for evaluating the heat dissipation effect of a chassis / cabinet as described in claim 1, characterized in that, The step of mapping and associating the set of physical property parameters to the corresponding primitives of the thermal analysis geometric model includes the following steps: Load the fan parameters into the fan primitives in the thermal analysis geometric model; The opening area data of the air inlet of the chassis and the opening ratio data of the air outlet grille are loaded into the corresponding boundary primitives to form complete boundary condition constraints.

7. The method for evaluating the heat dissipation effect of a chassis / cabinet as described in claim 1, characterized in that, Defining the fluid domain boundary conditions includes the following steps: Calculate the Reynolds number based on the characteristic dimensions of the numerical calculation model to be solved; Flow regime determination data is generated based on the Reynolds number. If the flow is determined to be turbulent, the zero equation or higher-order turbulence model parameters are configured into the numerical calculation model.

8. An evaluation system, characterized in that, The system includes: The parameter acquisition module is used to acquire a set of physical property parameters of the chassis and electrical cabinet; wherein, the set of physical property parameters includes the heating power of the heating elements inside the chassis and electrical cabinet, fan parameters, and material parameters; The model processing module is used to acquire the original three-dimensional design model of the chassis and electrical cabinet, perform feature suppression and geometric transformation processing on the original three-dimensional design model, and generate a thermal analysis geometric model; wherein, the geometric transformation processing includes converting irregular entities into regular geometric bodies for recognition by thermal analysis tools; The geometric analysis module is used to map and associate the physical property parameter set to the corresponding primitives of the thermal analysis geometric model, define the fluid domain boundary conditions and contact thermal resistance parameters, so as to obtain the numerical calculation model to be solved. The calculation and evaluation module is used to perform iterative solutions on the numerical calculation model to be solved, and generate temperature field distribution data and flow field velocity vector data to evaluate the heat dissipation effect of the chassis and cabinet.

9. A computer device, characterized in that, The computer device includes a memory and a processor, wherein the memory stores a computer program and the processor executes the computer program to implement the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and the processor executes the computer program to implement the method as described in any one of claims 1-7.

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