An interface thermal conductivity distribution optimization design method and system for improving assembly interface contact thermal performance

Abstract

The application discloses an interface thermal conductivity coefficient distribution optimization design method and system for improving assembly interface contact thermal performance, acquires the contact heat dissipation surface microscopic morphology characteristics of components of an electronic chip packaging system, and constructs a contact thermal performance numerical analysis model; the contact thermal performance numerical analysis model is used for multiple iterations on the thermal conductivity coefficient distribution of a design area, so that the thermal conductivity coefficient distribution and the contact thermal resistance are obtained; whether each iteration meets the iteration convergence criterion is judged according to the thermal conductivity coefficient distribution and the contact thermal resistance; if the iteration convergence criterion is met, the thermal conductivity coefficient distribution and the contact thermal resistance are output. The application controls the assembly interface temperature transmission path by designing the assembly interface surface thermal conductivity coefficient distribution, and truly realizes the uniformization of temperature gradient distribution by applying the innovative design thinking of the "heterogeneous" thermal conductivity coefficient distribution.

Description

Technical Field

[0001] The present invention belongs to the technical field of mechanical design, and specifically relates to an interface thermal conductivity distribution optimization design method and system for improving the contact thermal performance of an assembly interface. Background Art

[0002] The trend toward miniaturization, integration, and high assembly density in electronic devices leads to significant heat accumulation, resulting in insufficient system heat dissipation, seriously impacting the performance and stability of electronic devices throughout their service life. The journal Nature notes that due to unresolved heat dissipation issues, Moore's Law is on the verge of collapse. Effectively ensuring the heat dissipation performance of electronic devices has become a pressing issue. Electronic devices are functional assemblies composed of components assembled using specific connection methods. Internal loads and physical properties are transmitted between components via assembly interfaces. Assembly interfaces disrupt the continuity of temperature and stress transmission between electronic device components, contributing significantly to the contact thermal resistance (TCR) of the overall thermal resistance, far exceeding the contribution of bulk thermal resistance. TCR, caused by non-ideal contact conditions at assembly interfaces, is the primary cause of insufficient contact thermal performance and overall performance in electronic devices. As a multidisciplinary issue involving mechanics, heat transfer, materials, and other related fields, TCR holds significant research and practical application value. Reducing TCR can effectively improve heat transfer efficiency, prevent device overheating, damage, performance degradation, and problems caused by localized thermal stress and hot spots, thereby improving device reliability and service life. Therefore, finding new and efficient technologies to improve contact heat transfer performance has become a prominent issue in solving the thermal management challenges of heat-sensitive equipment in various fields.

[0003] Existing macro-control and surface treatment technologies for enhancing contact thermal performance are insufficient. Thermal interface materials are difficult to prepare, and their thickness cannot adapt to the trend of integrated development. As a result, existing technologies have reached a technical ceiling in enhancing contact thermal performance. Then, starting from the nature of the formation of contact thermal resistance, its physical nature is that the roughness and unevenness of the contact interface lead to insufficient and uneven contact, resulting in insufficient contact thermal performance. From the perspective of energy dissipation, this is due to the failure to minimize the heat transfer energy dissipation at the assembly interface. Summary of the Invention

[0004] The present invention addresses the bottleneck in improving contact thermal performance caused by the existing "homogeneous" design thinking, and aims to provide a method and system for optimizing the design of interface thermal conductivity distribution to improve the contact thermal performance of the assembly interface. By actively designing the thermal conductivity distribution of the assembly interface, the purpose of reducing the contact thermal resistance of the assembly interface is achieved, effectively ensuring the service life and stability of highly heat-sensitive mechanical equipment such as electronic chip packaging systems.

[0005] In order to achieve the purpose of the present invention, the technical solution adopted is:

[0006] A method for optimizing the distribution of thermal conductivity of an assembly interface to improve the contact thermal performance of the assembly interface comprises the following steps:

[0007] Obtaining the microscopic morphology characteristics of the contact and heat dissipation surfaces of components in electronic chip packaging systems;

[0008] According to the microscopic morphology characteristics of the contact heat dissipation surface of the component, a numerical analysis model of contact heat performance is constructed;

[0009] The contact thermal performance numerical analysis model is used to iterate the thermal conductivity distribution of the design area multiple times to obtain the thermal conductivity distribution and contact thermal resistance;

[0010] Whether each iteration satisfies the iterative convergence criterion is determined based on the thermal conductivity distribution and contact thermal resistance. If the iterative convergence criterion is satisfied, the thermal conductivity distribution and contact thermal resistance are output. If the iterative convergence criterion is not satisfied, the thermal conductivity distribution of the next iteration step is calculated, and the thermal conductivity distribution of the design area in the contact thermal performance numerical analysis model is updated. The process then returns to the step of iterating the thermal conductivity distribution of the design area multiple times using the contact thermal performance numerical analysis model.

[0011] Furthermore, a laser confocal roughness testing system is used to obtain the microscopic morphology characteristics of the contact heat dissipation surface of key components.

[0012] Furthermore, the rough surface is reconstructed by mapping the contact surface mesh unit nodes to the same sampling rate, and then a numerical analysis model of the contact thermal performance considering the real microscopic rough surface is constructed.

[0013] Furthermore, the iterative design criterion for thermal conductivity distribution is the temperature gradient uniformity distribution principle extended from the principle of minimum energy dissipation in the heat transfer process, which can be expressed as follows:

[0014]

[0015] Among them, k n)1 (e t )—the design area mesh element e at the n+1th iteration step t Thermal conductivity, k n (e t )—the design area mesh element e at the nth iteration step t The thermal conductivity, Design area grid cell e t Temperature gradient, λ—regulating factor, k min — Minimum thermal conductivity limit for the design area, k max —The maximum value limit of thermal conductivity in the design area.

[0016] Furthermore, the goal of the iterative design criterion for thermal conductivity distribution is to achieve uniform temperature gradient and minimize contact thermal resistance by optimizing the thermal conductivity distribution.

[0017] Furthermore, the design region is the assembly region with a set thickness in a direction perpendicular to the contact surface, and the design subregion is each grid unit in the design region.

[0018] Furthermore, the contact thermal resistance TCR is calculated by the following formula:

[0019]

[0020] Among them, T up —Average contact surface temperature on the assembly, T down —Average temperature of the contact surface under the assembly, q up —Average heat flux on the contact surface of the assembly, q down —Average heat flux on the lower contact surface of the assembly.

[0021] Furthermore, the iterative convergence criteria include the convergence of the maximum number of iterations, the convergence of the design target optimization rate, and the convergence of the rate of change of two adjacent design targets.

[0022] Furthermore, the iterative convergence criterion is:

[0023]

[0024] Among them, k max —Maximum number of iterations, TCR(k) n-1 、TCR(k) n 、TCR(k) n+1 — TCR settlement results for iterations n-1, n, and n+1, TCR(k) 0 —Initial TCR results before optimization, —convergence threshold of optimization target reduction rate, ξ—convergence threshold of adjacent optimization target change rate.

[0025] An interface thermal conductivity distribution optimization design system for improving the contact thermal performance of an assembly interface includes:

[0026] A micro-morphology feature acquisition module is used to obtain the micro-morphology features of the contact and heat dissipation surface of the component;

[0027] The module for constructing a numerical analysis model of contact thermal performance is used to construct a numerical analysis model of contact thermal performance based on the microscopic morphology characteristics of the contact heat dissipation surface of the component;

[0028] Thermal conductivity distribution and contact thermal resistance calculation module, which uses the contact thermal performance numerical analysis model to perform multiple iterative calculations on the thermal conductivity distribution of the design area to obtain the thermal conductivity distribution and contact thermal resistance;

[0029] The judgment module is used to judge whether each iteration meets the iterative convergence criterion based on the thermal conductivity distribution and the contact thermal resistance; if the iterative convergence criterion is met, the thermal conductivity distribution and the contact thermal resistance are output; if the iterative convergence criterion is not met, the thermal conductivity distribution of the next iteration step is calculated, and the thermal conductivity distribution of the design area in the contact thermal performance numerical analysis model is updated, and the step of using the contact thermal performance numerical analysis model to iterate the thermal conductivity distribution of the design area multiple times is returned.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] The present invention, for the first time, analyzes the physical nature of contact thermal resistance formation from the perspective of the energy dissipation mechanism in the heat transfer process. Aiming at the technical ceiling for enhancing contact thermal performance caused by the inadequate control performance of existing macro-control and surface treatment technologies for enhancing contact thermal performance, as well as the difficulty in preparing thermal interface materials and the inability of their own thickness to adapt to the development trend of integration, the present invention creatively proposes controlling the temperature transfer path of the assembly interface by designing the surface thermal conductivity distribution of the assembly interface, and applying the innovative design thinking of "heterogeneous" thermal conductivity distribution to truly achieve uniform temperature gradient distribution, thus overcoming the problem of uneven temperature gradient distribution caused by the traditional "homogeneous" thermal conductivity distribution of the assembly interface, and further achieving effective reduction of contact thermal resistance by ensuring the minimization of energy dissipation. The present invention can break through the bottleneck of improving contact thermal performance caused by the traditional "homogeneous" design thinking, and fundamentally solves the problem of insufficient contact thermal performance caused by contact thermal resistance in the heat transfer process based on the physical nature of heat transfer, significantly improving the contact thermal performance of highly heat-sensitive mechanical equipment such as electronic chip packaging systems, thereby effectively ensuring their service life and stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A flow chart of the interface thermal conductivity distribution optimization design method for improving the contact thermal performance of the assembly interface of the present invention;

[0033] Figure 2 Schematic diagram of the numerical analysis model;

[0034] Figure 3 Temperature distribution cloud diagram of the master and slave assembly interfaces before optimization design; (a) is the master assembly interface, (b) is the slave assembly interface;

[0035] Figure 4 Temperature distribution cloud diagram of the master and slave assembly interfaces after optimization design; (a) is the master assembly interface, (b) is the slave assembly interface;

[0036] Figure 5 Schematic diagram of the interface thermal conductivity distribution optimization design system for improving the contact thermal performance of the assembly interface according to the present invention. DETAILED DESCRIPTION

[0037] To facilitate understanding of the present invention, the present invention will be described more fully below with reference to the accompanying drawings. The accompanying drawings illustrate preferred embodiments of the present invention. However, the present invention may be implemented in a variety of different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and comprehensive understanding of the disclosure of the present invention.

[0038] By proactively designing the thermal conductivity distribution of the assembly interface to minimize energy dissipation, the authors aim to achieve a uniform temperature gradient distribution, thereby minimizing energy dissipation. This allows for rapid and precise placement of the thermal conductivity of the assembly interface to optimize contact thermal performance. This invention overcomes the bottleneck in improving contact thermal performance caused by traditional "homogenization" design thinking, significantly improving the contact thermal performance of highly heat-sensitive mechanical equipment such as electronic chip packaging systems, thereby effectively ensuring their service life and stability.

[0039] The present invention adopts the innovative design concept of "heterogeneous" thermal conductivity distribution, improves the contact heat performance by actively designing the thermal conductivity distribution of the assembly interface, and effectively ensures the service performance and stability of highly heat-sensitive mechanical equipment such as electronic chip packaging systems.

[0040] See also Figure 1 The present invention proposes an interface thermal conductivity distribution optimization design method for improving the contact thermal performance of the assembly interface, comprising the following steps:

[0041] 1) Constructing a Numerical Analysis Model for Contact Thermal Performance: The primary cause of insufficient heat dissipation in highly heat-sensitive mechanical equipment, such as electronic chip packaging systems, is contact thermal resistance caused by the microscopic roughness of the assembly interface surface. Reconstructing the actual contact surface microtopography is a prerequisite and necessary condition for constructing a numerical analysis model for contact thermal resistance. Therefore, a laser confocal roughness measurement system was first used to obtain the microtopography of the contact heat dissipation surfaces of key components. The rough surface was reconstructed by mapping it to the contact surface grid cells at the same sampling rate. This allowed the construction of a numerical analysis model for contact thermal performance that accounted for the actual microscopic roughness of the surface.

[0042] It should be noted that in order to ensure that the reconstructed rough contact surface can meet the coordinated requirements of computational accuracy and computational time, it is necessary to conduct a mesh-independence analysis of the numerical analysis model that relies on the rough surface sampling rate, and then find the minimum micro-morphology sampling rate requirement that meets the computational accuracy requirements. The constructed numerical analysis model for contact thermal performance is a mechanical-heat transfer dual-iteration sequential coupling analysis that considers secondary thermal effects such as thermal stress and thermal softening. The final contact state in the mechanical analysis is used as the initial state of the heat transfer analysis to achieve the transfer of mechanical analysis results to the heat transfer analysis. The method of defining a predefined temperature field is used to initialize the mechanical analysis of the entire temperature distribution in the heat transfer analysis to achieve the transfer of heat transfer analysis results to the mechanical analysis, thereby achieving high-accuracy analysis of contact thermal performance and can be used for contact thermal performance analysis under various working conditions.

[0043] 2) Defining the design area and design sub-area: The optimization design method of the present invention is to find the thermal conductivity distribution of the assembly interface that satisfies the minimum contact thermal resistance under the thermal conductivity integral constraint. The physical equation can be expressed as:

[0044]

[0045] Where k is the thermal conductivity distribution of the design domain, e1 is the mesh element of the design subdomain, k(e1) is the thermal conductivity of the mesh element of the design subdomain, k0 is the initial thermal conductivity value, and V is the volume of the design domain. Furthermore, to find the optimal thermal conductivity distribution, the original total integral limit for the thermal conductivity of the design domain can be changed to unlimited to find the thermal conductivity distribution that achieves the best contact thermal performance.

[0046] Therefore, it is first necessary to define the assembly area with a certain thickness perpendicular to the contact surface as the design area. Each grid unit in the design area is a design sub-area, the thermal conductivity of each design sub-area is the design sub-variable, and the thermal conductivity distribution in the entire design area is the entire design variable.

[0047] Among them, the thickness of the design area is determined according to the actual manufacturing process and the size of the assembly. Different design area thicknesses have a greater impact on the optimization design results. In theory, increasing the thickness of the design area can improve the optimization design effect. Therefore, it is necessary to determine the optimal design area thickness based on actual needs. In order to ensure the precise regulation of the thermal conductivity distribution, each grid unit in the design area is the smallest design sub-area. Of course, in order to match the actual manufacturing process size limitations, the number of grid units contained in each sub-design area can be defined according to actual needs. The optimal thermal conductivity distribution and the contact thermal performance results after optimization corresponding to the sizes of different sub-design areas are different.

[0048] 3) Define the thermal conductivity distribution of the design area: Define the unit thermal conductivity of each design sub-area, initialize the thermal conductivity distribution to a uniform value consistent with traditional design thinking, and obtain the defined thermal conductivity distribution of the design area. This analysis serves as a reference result before optimizing the design. Subsequently, to find the optimal thermal conductivity distribution, the material thermal conductivity distribution of the design area in the numerical analysis model is redefined based on the updated thermal conductivity distribution at each iterative step.

[0049] 4) Calculate the temperature gradient distribution and contact thermal performance of the design area: Based on the thermal conductivity distribution of the design area defined in step 3), apply the contact thermal performance numerical analysis model to calculate the temperature gradient distribution of the design area for iterative updating of design variables, and solve the design target, i.e., the contact thermal resistance, under the thermal conductivity distribution of the design area defined in step 3) for iterative convergence judgment. The design target, i.e., the contact thermal resistance TCR, is defined as:

[0050]

[0051] Among them, T up —Average contact surface temperature on the assembly, T down —Average temperature of the contact surface under the assembly, q up —Average heat flux on the contact surface of the assembly, q down —The average heat flux on the contact surface under the assembly. Therefore, based on the contact surface temperature and heat flux distribution results obtained from the contact thermal performance numerical analysis, the contact thermal resistance results under the thermal conductivity distribution state in different design areas are calculated.

[0052] 5) Determine whether the convergence condition is met: The iterative design criterion for thermal conductivity distribution is the temperature gradient uniform distribution principle extended from the principle of minimum extreme value of energy dissipation in the heat transfer process. The detailed formula is expressed as follows:

[0053]

[0054] Among them, k n+1 (e t )—the design area mesh element e at the n+1th iteration step t Thermal conductivity, k n (e t )—the design area mesh element e at the nth iteration step t The thermal conductivity, Design area grid cell e t The temperature gradient, λ is the control factor used to determine whether the thermal conductivity distribution meets the total integral limit requirement. If it is equal to 1, the total integral of the thermal conductivity distribution in the design area is limited. If it is greater than 1, the optimal thermal conductivity distribution is found under the condition of no thermal conductivity limit. k min — Minimum thermal conductivity limit for the design area, kmax —The maximum value limit of thermal conductivity in the design area.

[0055] The specific steps of updating the thermal conductivity coefficient are to apply the iterative design criteria and update the thermal conductivity coefficient distribution of the next iteration step based on the temperature gradient distribution and thermal conductivity coefficient distribution obtained in the previous iteration step. The ultimate goal is to achieve temperature gradient homogenization by optimizing the thermal conductivity coefficient distribution and thus ensure the minimization of contact thermal resistance.

[0056] The thermal conductivity distribution k of the design area is iterated multiple times using the iterative design criterion for thermal conductivity distribution to obtain the design target result. The iterative convergence criterion is judged based on the design target result. If the iterative convergence criterion is met, the next step 6) is continued. If the iterative convergence criterion is not met, the thermal conductivity distribution of the next iteration step is calculated based on the iterative design criterion, and the thermal conductivity distribution of the design area in the numerical analysis model is updated, and the step 4) is continued.

[0057] There are three iterative convergence criteria: convergence of the maximum number of iterations, convergence of the design target optimization rate, and convergence of the rate of change of two adjacent design targets. They can be specifically expressed as:

[0058]

[0059] Among them, k max —Maximum number of iterations, TCR(k) n-1 、TCR(k) n 、TCR(k) n+1 — TCR settlement results for iterations n-1, n, and n+1, TCR(k) 0 —Initial TCR results before optimization, —convergence threshold of optimization target reduction rate, ξ—convergence threshold of adjacent optimization target change rate.

[0060] 6) Output the optimized thermal conductivity distribution and contact thermal resistance calculation results that meet the iterative convergence criteria. The output optimized thermal conductivity distribution is set according to the actual optimization design. The thermal conductivity distribution in the vertical direction of the assembly interface is uniformed or differentiated. Differentiated distribution can obtain better contact thermal performance but also brings processing difficulties.

[0061] Example 1

[0062] The present invention is described by taking a concrete key assembly interface in an electronic chip packaging system as an example.

[0063] The overall analysis process of this embodiment is as follows Figure 1 As shown in the figure, it mainly includes 6 steps, and the key assembly interface is selected as the research object. The specific steps are as follows:

[0064] 1) The key assembly interface in the electronic chip packaging system is selected as the specific research object. The laser confocal roughness test system is used to obtain the microscopic morphology characteristics of the contact surface. The rough surface is reconstructed by mapping it to the contact surface grid unit nodes with the same sampling rate, and then a numerical analysis model of the contact thermal performance considering the real microscopic rough surface is constructed. In addition, this numerical analysis model is the optimal numerical model considering the analysis of the independence of the surface micromorphology sampling rate and grid size. Figure 2 As shown in the figure, a uniform pressure load of 3 MPa is applied to the upper surface. The load condition for heat transfer analysis is the different temperature heat sources on the left and right sides of the upper surface, which are T r =573K and T l = 373 K. First, contact mechanical analysis is applied to obtain the initial contact state. This initial contact state is then used as the initial mesh state for contact heat transfer analysis. The obtained temperature history is then used in a predefined temperature field to perform a secondary contact state analysis that considers effects such as thermal stress and thermal softening. Finally, the secondary contact state is used as the initial mesh state for contact heat transfer analysis to obtain the final temperature and heat flux distribution.

[0065] 2) The optimization design method is to find the thermal conductivity distribution of the assembly interface that satisfies the minimum contact thermal resistance under the thermal conductivity integral constraint. Its physical equation can be expressed as:

[0066]

[0067] Where k is the thermal conductivity distribution of the design domain, e1 is the mesh element of the design subdomain, k(e1) is the thermal conductivity of the mesh element of the design subdomain, k0 is the initial thermal conductivity value, and V is the volume of the design domain. Furthermore, to find the optimal thermal conductivity distribution, the original total integral limit for the thermal conductivity of the design domain can be changed to unlimited to find the thermal conductivity distribution that achieves the best contact thermal performance.

[0068] Therefore, according to the machining accuracy and size limitation of the surface coating manufacturing process, the assembly area with a thickness of 0.3mm perpendicular to the contact surface is defined as the design area. Each grid unit in the design area is a design sub-area. The thermal conductivity of each design sub-area is the design sub-variable, and the thermal conductivity distribution in the entire design area is the entire design variable. The detailed size of the numerical analysis model and the division of the design area are as follows: Figure 2 shown.

[0069] 3) A looping algorithm was used to define the unit thermal conductivity of each design subregion. The thermal conductivity distribution was initialized to a uniform value consistent with traditional design thinking, and this analysis was used as a reference for the optimization design. The thermal conductivity value for this design object was initialized to that of HTA material, which is defined as 11 W / mK. Subsequently, to find the optimal thermal conductivity distribution, the material thermal conductivity distribution of the design region in the numerical analysis model was redefined based on the updated thermal conductivity distribution at each iteration.

[0070] 4) Based on the defined design area thermal conductivity distribution, the contact thermal performance numerical analysis model is applied to calculate the design area temperature gradient distribution for the design variable update iteration, and the design target under the thermal conductivity distribution condition, i.e., the contact thermal resistance result, is solved for iterative convergence judgment. Among them, the design target, i.e., the contact thermal resistance TCR, is defined as

[0071]

[0072] Among them, T up —Average contact surface temperature on the assembly, T down —Average temperature of the contact surface under the assembly, q up —Average heat flux on the contact surface of the assembly, q down —The average heat flux on the contact surface under the assembly. Therefore, based on the contact surface temperature and heat flux distribution results obtained from the contact thermal performance numerical analysis, the contact thermal resistance results under the thermal conductivity distribution state in different design areas are calculated.

[0073] 5) Iterative design criterion for thermal conductivity distribution The principle of uniform temperature gradient distribution is extended from the principle of minimum extreme value of energy dissipation in the heat transfer process. The detailed formula is expressed as follows:

[0074]

[0075]

[0076] Among them, k n+1 (e t )—the design area mesh element e at the n+1th iteration step t Thermal conductivity, k n (e t )—the design area mesh element e at the nth iteration step t The thermal conductivity, Design area grid cell e t The temperature gradient, λ is the control factor used to determine whether the thermal conductivity distribution meets the total integral limit requirement. If it is equal to 1, the total integral of the thermal conductivity distribution in the design area is limited. If it is greater than 1, the optimal thermal conductivity distribution is found under the condition of no thermal conductivity limit. k min— Minimum thermal conductivity limit for the design area, k max —The maximum value limit of thermal conductivity in the design area.

[0077] The specific steps of updating the thermal conductivity coefficient are to apply the iterative design criteria and update the thermal conductivity coefficient distribution of the next iteration step based on the temperature gradient distribution and thermal conductivity coefficient distribution obtained in the previous iteration step. The ultimate goal is to achieve temperature gradient homogenization by optimizing the thermal conductivity coefficient distribution and thus ensure the minimization of contact thermal resistance.

[0078] Determine whether this iteration meets the iterative convergence criteria based on the design target results. If so, proceed to the next step 6). If not, calculate the thermal conductivity distribution of the next iteration based on the iterative design criteria, update the thermal conductivity distribution of the design area in the numerical analysis model, and proceed to step 4).

[0079] There are three iterative convergence criteria: convergence of the maximum number of iterations, convergence of the design target optimization rate, and convergence of the rate of change of two adjacent design targets. They can be specifically expressed as:

[0080]

[0081] Among them, k max —Maximum number of iterations, TCR(k) n-1 、TCR(k) n 、TCR(k) n+1 — TCR settlement results for iterations n-1, n, and n+1, TCR(k) 0 —Initial TCR results before optimization, —Optimization target reduction rate convergence threshold, ξ—Adjacent optimization target change rate convergence threshold. The specific iterative convergence criterion for this design object is that the change rate of two adjacent design targets converges, that is, the adjacent optimization target change rate convergence threshold ξ=0.0005.

[0082] 6) Output the optimized thermal conductivity distribution and contact thermal resistance calculation results that meet the iterative convergence criteria. In order to improve the calculation efficiency of this optimization design, the design variables are evenly distributed in the vertical direction of the design area. Therefore, only the thermal conductivity distribution of the contact surface mesh unit needs to be output.

[0083] The beneficial effects of the present invention are further illustrated by taking the key assembly interface in the electronic chip packaging system as an example. Figure 3 As shown in (a) and (b), the temperature distribution cloud diagram of the master and slave assembly interfaces after the “heterogeneous” thermal conductivity distribution design is as follows: Figure 4 As shown in (a) and (b). Figure 3Due to the introduction of the non-uniform temperature load distribution on the upper surface and the existence of the micro-surface roughness, the temperature gradient distribution of the contact surface in the heat transfer process is extremely uneven, resulting in a small real contact thermal conductivity and a high temperature distribution difference between the upper and lower contact surfaces. Starting from energy dissipation and temperature gradient distribution uniformity, the temperature gradient distribution uniformity and the real thermal conductivity are greatly improved by actively designing the thermal conductivity distribution of the assembly interface. By comparing Figure 3 With Figure 4 It can be seen that the temperature distribution uniformity is greatly improved, the temperature distribution difference between the upper and lower contact surfaces is significantly reduced, and the average heat flux is increased. It is found through calculation that the contact thermal resistance TCR is reduced by more than 40%, effectively improving the contact thermal performance.

[0084] Embodiment 2

[0085] Referring to Figure 5 An interface thermal conductivity distribution optimization design system for improving the contact thermal performance of an assembly interface, comprising:

[0086] A micro-topography feature acquisition module for acquiring the micro-topography features of the contact heat dissipation surface of the component;

[0087] A contact thermal performance numerical analysis model construction module for constructing a contact thermal performance numerical analysis model according to the micro-topography features of the contact heat dissipation surface of the component;

[0088] A thermal conductivity distribution and contact thermal resistance calculation module for performing multiple iteration calculations on the thermal conductivity distribution of the design area by using the contact thermal performance numerical analysis model to obtain the thermal conductivity distribution and the contact thermal resistance;

[0089] A judgment module for judging whether each iteration meets the iteration convergence criterion according to the thermal conductivity distribution and the contact thermal resistance; if the iteration convergence criterion is met, the thermal conductivity distribution and the contact thermal resistance are output; if the iteration convergence criterion is not met, the thermal conductivity distribution of the next iteration step is calculated, and the thermal conductivity distribution of the design area in the contact thermal performance numerical analysis model is updated, and the step of performing multiple iterations on the thermal conductivity distribution of the design area by using the contact thermal performance numerical analysis model is returned.

[0090] This invention abandons the traditional design thinking of "homogenization" of the thermal conductivity of the assembly interface and innovatively proposes a "heterogeneous" design concept for heat transfer characteristics such as the thermal conductivity of the assembly interface to precisely control the contact thermal performance. This method takes the numerical analysis model of the contact thermal performance of the assembly interface that takes into account the microscopic roughness of the surface as the design object, minimizes the contact thermal resistance of the assembly interface as the design goal, and uses the contact interface area of ​​the assembly and the grid units within the area as the design area and design sub-area. The thermal conductivity of the grid units in the design area is the design variable. A laser confocal roughness test system is used to obtain the microscopic morphology characteristics of the contact surface, and a numerical analysis model of the contact thermal performance that takes into account the real microscopic rough surface and secondary thermal effects is established, thereby achieving accurate prediction of the contact thermal characteristics. The numerical analysis model of the contact thermal performance of the assembly interface that takes into account the surface micro-roughness is constructed as the design object, minimizing the contact thermal resistance of the assembly interface is the design goal, the assembly contact interface area and the grid units within the area are the design area and design sub-area, and the thermal conductivity of the grid units in the design area is the design variable; the iterative design criteria of the distribution of thermal conductivity of the assembly interface driven by the maximum energy dissipation principle are applied to form a fast and precise control optimization design method for the distribution of thermal conductivity of the assembly interface driven by contact thermal performance, which solves the high computational complexity and weak iterative convergence of traditional group algorithms and realizes the fast and precise layout of the thermal conductivity of the assembly interface that matches the optimal contact thermal performance. The present invention can break through the bottleneck of improving contact thermal performance caused by traditional "homogenization" design thinking, significantly improve the contact thermal performance of highly heat-sensitive mechanical equipment such as electronic chip packaging systems, and solve the problems of excessive operating temperature and premature failure of equipment caused by local thermal stress due to insufficient contact thermal performance of highly heat-sensitive mechanical equipment, thereby effectively ensuring its service life and stability.

[0091] The above description is merely a description of the preferred embodiment of the present invention and is not to be construed as limiting the claims. The present invention is not limited to the above embodiment, and variations in the specific structure are permitted. Any variations made within the scope of the independent claims of the present invention are also within the scope of protection of the present invention.

[0092] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this invention pertains. The terms used herein in the specification of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

Claims

1. A method for optimizing the distribution of thermal conductivity of an interface to improve the contact thermal performance of an assembly interface, characterized in that: The following steps are involved: Obtaining the microscopic morphology characteristics of the contact and heat dissipation surfaces of components in electronic chip packaging systems; According to the microscopic morphology characteristics of the contact heat dissipation surface of the component, a numerical analysis model of contact heat performance is constructed; The contact thermal performance numerical analysis model is used to iterate the thermal conductivity distribution of the design area multiple times to obtain the thermal conductivity distribution and contact thermal resistance; Determine whether each iteration meets the iterative convergence criterion based on the thermal conductivity distribution and contact thermal resistance; If the iterative convergence criteria are met, the thermal conductivity distribution and contact thermal resistance are output; If the iterative convergence criterion is not met, the thermal conductivity distribution of the next iteration step is calculated, and the thermal conductivity distribution of the design area in the contact thermal performance numerical analysis model is updated, and the step of using the contact thermal performance numerical analysis model to iterate the thermal conductivity distribution of the design area multiple times is returned; The iterative design criterion for thermal conductivity distribution is the temperature gradient uniformity distribution principle, which is extended from the principle of minimum energy dissipation in the heat transfer process and can be expressed as follows: (1) (2) in, — No. n +1 design region mesh element for the iteration step The thermal conductivity, — Design domain mesh elements for the nth iteration step The thermal conductivity, Design area grid cells The temperature gradient, — regulatory factors, — Minimum thermal conductivity limit for the design area, — Maximum limit of thermal conductivity in the design area; Contact thermal resistance TCR Calculated by the following formula: (3) in, — average temperature of contact surfaces on the assembly, — Average temperature of the lower contact surface of the assembly, —average heat flux on the contact surface of the assembly, — Average heat flux of the lower contact surface of the assembly; The iterative convergence criterion is: (4) in, — maximum number of iterations, 、 、 — No. n -1. n 、 n +1 iteration TCR settlement result, — Initial TCR results before optimization, — Optimize the target reduction rate convergence threshold, — Convergence threshold of the rate of change of adjacent optimization objectives.

2. The interface thermal conductivity distribution optimization design method for improving the contact thermal performance of the assembly interface according to claim 1 is characterized in that: A laser confocal roughness testing system is used to obtain the microscopic morphology characteristics of the contact heat dissipation surface of key components.

3. The interface thermal conductivity distribution optimization design method for improving the contact thermal performance of the assembly interface according to claim 1, characterized in that: The rough surface is reconstructed by mapping the contact surface mesh unit nodes to the same sampling rate, and then a numerical analysis model of the contact thermal performance considering the real microscopic rough surface is constructed.

4. The interface thermal conductivity distribution optimization design method for improving the contact thermal performance of the assembly interface according to claim 1, characterized in that: The goal of the iterative design criterion for thermal conductivity distribution is to achieve uniform temperature gradient and minimize contact thermal resistance by optimizing the thermal conductivity distribution.

5. The interface thermal conductivity distribution optimization design method for improving the contact thermal performance of the assembly interface according to claim 1, characterized in that: The design region is the assembly region with a set thickness perpendicular to the contact surface, and the design subregion is each grid cell within the design region.

6. The interface thermal conductivity distribution optimization design method for improving the contact thermal performance of the assembly interface according to claim 1, characterized in that: Iterative convergence criteria include the convergence of the maximum number of iterations, the convergence of the design target optimization rate, and the convergence of the rate of change of two adjacent design targets.

7. An interface thermal conductivity distribution optimization design system for improving the contact thermal performance of the assembly interface, characterized in that: include: A micro-morphology feature acquisition module is used to obtain the micro-morphology features of the contact and heat dissipation surface of the component; The module for constructing a numerical analysis model of contact thermal performance is used to construct a numerical analysis model of contact thermal performance based on the microscopic morphology characteristics of the contact heat dissipation surface of the component; Thermal conductivity distribution and contact thermal resistance calculation module, which uses the contact thermal performance numerical analysis model to perform multiple iterative calculations on the thermal conductivity distribution of the design area to obtain the thermal conductivity distribution and contact thermal resistance; A judgment module is used to judge whether each iteration meets the iterative convergence criterion based on the thermal conductivity distribution and the contact thermal resistance; If the iterative convergence criteria are met, the thermal conductivity distribution and contact thermal resistance are output; If the iterative convergence criterion is not met, the thermal conductivity distribution of the next iteration step is calculated, and the thermal conductivity distribution of the design area in the contact thermal performance numerical analysis model is updated, and the step of using the contact thermal performance numerical analysis model to iterate the thermal conductivity distribution of the design area multiple times is returned; The iterative design criterion for thermal conductivity distribution is the temperature gradient uniformity distribution principle, which is extended from the principle of minimum energy dissipation in the heat transfer process and can be expressed as follows: (1) (2) in, — No. n +1 design region mesh element for the iteration step The thermal conductivity, — Design domain mesh elements for the nth iteration step The thermal conductivity, Design area grid cells The temperature gradient, — regulatory factors, — Minimum thermal conductivity limit for the design area, — Maximum limit of thermal conductivity in the design area; Contact thermal resistance TCR Calculated by the following formula: (3) in, — average temperature of contact surfaces on the assembly, — Average temperature of the lower contact surface of the assembly, —average heat flux on the contact surface of the assembly, — Average heat flux of the lower contact surface of the assembly; The iterative convergence criterion is: (4) in, — maximum number of iterations, 、 、 — No. n -1. n 、 n +1 iteration TCR settlement result, — Initial TCR results before optimization, — Optimize the target reduction rate convergence threshold, — Convergence threshold of the rate of change of adjacent optimization objectives.

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