Method and device for optimizing module with fin needle type bottom plate and medium

Abstract

The invention provides a module optimization method with a fin pin type bottom plate, equipment and a medium, and relates to the technical field of data processing, and the method comprises the steps: obtaining an optimization parameter table which comprises a plurality of optimization parameters, and the optimization parameters comprise the fin pin size, the fin pin distance, the bottom plate thickness and the heat conductivity coefficient of a bottom plate material; each optimization parameter comprises a lower limit value, an upper limit value, a heat dissipation performance influence factor, a variable and a weight thereof; presetting initial configuration information of a fin needle type bottom plate based on the optimization parameter table, and performing simulation calculation on initial thermal resistance and initial flow resistance; according to the initial thermal resistance and the initial flow resistance, respectively determining differences between the initial thermal resistance and the initial flow resistance and between the initial thermal resistance and the initial flow resistance and between target thermal resistance and target flow resistance; and dynamically adjusting each optimization parameter according to the difference so as to iteratively optimize the initial configuration information and then determine the target configuration information, thereby solving the problem that the heat dissipation effect of the module is relatively poor due to the fact that a specific scheme is selected only depending on experience when the fin needle type bottom plate of the module is designed in the prior art.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method, device and medium for optimizing heat dissipation of a module with a fin-pin type bottom plate. Background Art

[0002] Good thermal management is particularly important for the stability and reliability of power modules. Power semiconductor modules used in motor controllers for new energy vehicles face more complex operating environments and special application conditions, so they require better heat dissipation. The complex operating conditions of existing new energy vehicles pose great challenges to the performance and reliability of power module heat dissipation substrates, and heat dissipation substrates need to meet heat dissipation requirements.

[0003] The pin-fin baseplate is a common module heat dissipation baseplate. The high-power module equipped with the pin-fin heat dissipation structure is installed in the external waterway structure, and liquid cooling can be performed by passing water. Most of the existing baseplates only select the appropriate size according to the power module, and the structure of the baseplate itself, such as the arrangement of the fins and the thickness of the baseplate, will affect the heat dissipation effect of the power module. When optimizing the existing heat dissipation baseplate, it is usually based on experience to select several specific solutions for comparative analysis, and will not be optimized based on each parameter. As a result, the baseplate design makes the heat dissipation effect not good enough. Summary of the invention

[0004] In order to overcome the above-mentioned technical defects, the purpose of the present invention is to provide a module heat dissipation optimization method, equipment and medium with a fin-pin type base plate, so as to solve the problem that the existing design of the fin-pin type base plate of the module only relies on experience to select a specific solution, resulting in poor module heat dissipation effect.

[0005] The present invention discloses a method for optimizing heat dissipation of a module with a fin-pin type base plate, comprising:

[0006] Obtain an optimization parameter table, wherein the optimization parameter table includes several optimization parameters, wherein the optimization parameters include fin pin size, fin pin spacing, base plate thickness, and base plate material thermal conductivity, and each optimization parameter includes a lower limit value, an upper limit value, a heat dissipation performance influencing factor, a variable, and its weight;

[0007] Predetermine initial configuration information of the base plate based on the optimization parameter table, and perform simulation calculation of initial thermal resistance and initial flow resistance, wherein the initial configuration information includes at least one optimization parameter;

[0008] Determining the difference between the initial thermal resistance and the initial flow resistance relative to the target thermal resistance and the target flow resistance respectively according to the initial thermal resistance and the initial flow resistance;

[0009] The various optimization parameters are dynamically adjusted according to the difference, so as to determine the target configuration information after iterative optimization of the initial configuration information.

[0010] Preferably, the various optimization parameters are dynamically adjusted, including:

[0011] For each optimization parameter, determining an adjustment amount of the optimization parameter;

[0012] Determining an adjustment ratio of the optimization parameter according to an adjustment amount of the optimization parameter, a lower limit value of the optimization parameter, and an upper limit value of the optimization parameter, and determining a corresponding change of the optimization parameter by multiplying the adjustment ratio of the optimization parameter by a heat dissipation performance influencing factor of the optimization parameter;

[0013] Add the changes corresponding to all optimization parameters to obtain the total amount of change;

[0014] A preset margin is obtained, and the adjustment amount of each optimization parameter is updated so that the total amount of change exceeds the preset margin relative to the difference.

[0015] Preferably, for an optimization parameter having at least two variables, determining an adjustment amount of a variable in a certain optimization parameter;

[0016] Determining an adjustment ratio of the variable according to an adjustment amount of the variable, a lower limit value of the variable and an upper limit value of the variable;

[0017] According to the weight of the variable, determine the weight ratio of the variable relative to all variables included in the optimization parameter, so as to determine the change corresponding to the variable by multiplying the adjustment ratio of the variable, the weight ratio, and the heat dissipation performance influence factor of the optimization parameter;

[0018] The changes corresponding to all variables included in the optimization parameters are added to determine the changes corresponding to the optimization parameters.

[0019] Preferably, the optimization parameters with at least two variables include fin pin size and fin pin spacing;

[0020] The variables of the wing pin spacing include horizontal spacing and vertical spacing;

[0021] The wing pin size includes variables determined according to the cross-sectional shape of the wing pin;

[0022] When the cross section of the wing pin is an ellipse, the variables of the wing pin size include the length of the major semi-axis, the length of the minor plate axis, and the wing pin length;

[0023] When the cross section of the wing pin is circular, the variables of the wing pin size include radius and wing pin length;

[0024] When the cross section of the wing pin is a rhombus, the variables of the wing pin size include a long diagonal, a short diagonal, and a wing pin length.

[0025] Preferably, various optimization parameters are classified in advance to determine optimization parameters respectively associated with thermal resistance and flow resistance.

[0026] Preferably, the difference includes a thermal resistance difference and a flow resistance difference;

[0027] Determine the total amount of thermal resistance change and the total amount of flow resistance change corresponding to the thermal resistance difference and the flow resistance difference, respectively;

[0028] The preset margin includes a first margin associated with the thermal resistance and a second margin associated with the flow resistance, and the adjustment amount of each optimization parameter is updated so that the total amount of thermal resistance change exceeds the first margin relative to the thermal resistance difference, and the total amount of flow resistance change exceeds the second margin relative to the flow resistance difference.

[0029] Preferably, the initial configuration information of the fin-pin type base plate includes configuration information based on the base plate thickness and the lower limit value of the thermal conductivity of the base plate material, the upper limit value of the base plate spacing, and the lower limit value of the base plate size.

[0030] Preferably, the priority of each optimization parameter is preset;

[0031] Adjust each optimization parameter according to its priority.

[0032] The present invention also provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the module heat dissipation optimization method with a fin-pin type base plate are implemented.

[0033] The present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the above-mentioned method for optimizing heat dissipation of a module with a fin-pin type base plate are implemented.

[0034] Compared with the prior art, the above technical solution has the following beneficial effects:

[0035] In the present application, optimization parameters related to the fin-pin type base plate structure and affecting multiple aspects such as heat dissipation effect / cost are obtained, the initial configuration information of the fin-pin type base plate is preset, and the base plate structure is iteratively optimized by dynamically adjusting the optimization parameters. The target configuration information is determined by the target thermal resistance and the target flow resistance, which includes the specific values ​​of each optimization parameter. This can obtain a fin-pin type base plate structure design that meets the use requirements, thereby improving the efficiency and accuracy of the base plate structure optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a flow chart of an embodiment of a method, device and medium for optimizing heat dissipation of a module with a fin-pin type base plate according to the present invention;

[0037] Figure 2The present invention provides a flowchart for dynamically adjusting various optimization parameters in a method, device and medium embodiment for optimizing heat dissipation of a module with a fin-pin type base plate. DETAILED DESCRIPTION

[0038] The advantages of the present invention are further described below in conjunction with the accompanying drawings and specific embodiments.

[0039] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0040] The terms used in this disclosure are for the purpose of describing specific embodiments only and are not intended to limit the disclosure. The singular forms of "a", "said" and "the" used in this disclosure and the appended claims are also intended to include plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0041] It should be understood that although the terms first, second, third, etc. may be used in the present disclosure to describe various information, such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present disclosure, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0042] In the following description, the suffixes such as "module", "component" or "unit" used to represent elements are only used to facilitate the description of the present invention, and have no specific meanings. Therefore, "module" and "component" can be used interchangeably.

[0043] Embodiment: This embodiment discloses a module optimization method with a wing-pin type base plate, in which the structural design of the wing-pin type base plate (specifically, the optimization parameters related to the structure) is optimized to improve the heat dissipation effect of the module. Specifically, considering the intrinsic relationship between the base plate structure and the flow resistance and thermal resistance, the initial configuration information is preset, and the base plate design parameters (including but not limited to the arrangement and shape of the wing pins, the thermal conductivity coefficient, etc.) are used as optimization parameters for iterative optimization until the flow resistance and the thermal resistance meet the preset usage requirements, and the target configuration information is determined, which is different from the existing design that only relies on experience for specific design. Specifically, Figure 1 As shown, the optimization method includes the following steps:

[0044] S1: Obtain an optimization parameter table, wherein the optimization parameter table includes several optimization parameters, wherein the optimization parameters include fin pin size, fin pin spacing, base plate thickness, base plate material thermal conductivity, and each optimization parameter includes a lower limit value, an upper limit value, a heat dissipation performance influencing factor, a variable and its weight;

[0045] In this embodiment, the optimization parameters included in the optimization parameters are parameters included in the base plate design that can affect the heat dissipation effect of the power module, including but not limited to the above, and specific optimization parameters such as wing pin inclination can also be added according to the application scenario. It should be noted that the various optimization parameters in the above optimization parameter table and the heat dissipation performance influencing factors, variables and their weights, etc. included therein can be obtained in advance by establishing a module heat dissipation model calculation / data processing (such as controlling variables or multi-factor analysis of each optimization parameter to determine the heat dissipation performance influencing factors). Furthermore, each optimization parameter can even include other performance influencing factors, which can be manufacturing costs and difficulty factors, etc., which can be preset or obtained according to the scenario.

[0046] In addition, the above-mentioned optimization parameters with at least two variables may include wing pin size, wing pin spacing, etc.; the variables of the wing pin spacing include horizontal spacing, vertical spacing, and may also include spacing in other directions; the variables contained in the wing pin size are determined according to the shape of the wing pin; the wing pin is elliptical, and the variables of the wing pin size include the major semi-axis length, the minor plate axis length, and the wing pin length; the wing pin is circular, and the variables of the wing pin size include radius and wing pin length; the wing pin is rhombus, and the variables of the wing pin size include the long diagonal, the short diagonal, and the wing pin length.

[0047] As mentioned above, the different shapes and distributions (spacing) of the fins are also important factors affecting the base plate design, which will also affect the heat dissipation effect of the module. Therefore, it is used as a variable of the fin pin size, so that the variables can be dynamically adjusted during the optimization process to achieve precise optimization of the base plate design, so as to obtain the base plate with the best design in multiple dimensions such as heat dissipation effect and cost, while maintaining a low preparation cost while improving the heat dissipation effect.

[0048] As an example, taking a base plate with elliptical fin pins as an example, the above optimization parameter table can be as follows:

[0049]

[0050] As a supplement, the thermal conductivity of the Category IV baseboard material in the above table mainly considers the thermal conductivity of the material. As the thermal conductivity increases, the heat dissipation performance will be better. Among the main materials currently used for heat dissipation baseboards, the one with poor thermal conductivity is the three-series aluminum 100W / m·K, and the one with good thermal conductivity is the oxygen-free copper 400W / m·K.

[0051] S2: Preset initial configuration information of the fin-pin type base plate based on the optimization parameter table, and simulate and calculate initial thermal resistance and initial flow resistance, wherein the initial configuration information includes at least one optimization parameter;

[0052] In this embodiment, the initial configuration information can be acquired in advance, and the initial configuration information can also be generated according to preset conditions. The configuration information can selectively include some or all of the optimization parameters. The initial configuration information can be the most preferred based on one of the aspects such as cost and heat dissipation effect, such as considering the lowest cost, considering the best heat dissipation effect, or considering the space limitation of the base plate (such as the minimum thickness). Therefore, as an option, the initial configuration information of the base plate includes configuration information based on the lower limit of the base plate thickness and the thermal conductivity of the base plate material, the upper limit of the base plate spacing, and the lower limit of the base plate size. This combination takes into account the heat dissipation performance while minimizing the cost (the lower limit of the base plate thickness and the thermal conductivity of the base plate material), and uses this as the initial configuration information for subsequent iterative optimization.

[0053] As a special case, if the initial flow resistance and initial thermal resistance determined by the initial configuration information directly meet the preset target flow resistance and target thermal resistance, the initial configuration information can be directly used as the target configuration information, or other restrictions can be further preset for further optimization, such as reducing costs. Therefore, it can be understood that the target configuration information finally determined in this embodiment can be one or more design schemes for the fin-pin type base plate.

[0054] In the above steps, the thermal resistance or flow resistance is determined by simulation. For example, for a module with a fin-type heat sink having a certain configuration information, the upper bridge FRD heating source P D1 , then the thermal resistance of the upper bridge FRD is: Rth D1 =(T vjD1 -T f ) / P D1 ; T vjD1 is the junction temperature, T f is the coolant temperature; the flow resistance is the average pressure drop at the water inlet minus the average pressure drop at the water outlet. S3: Determine the difference between the relative target thermal resistance and the target flow resistance according to the initial thermal resistance and the initial flow resistance;

[0055] In this embodiment, the difference is the percentage difference between thermal resistance and flow resistance ΔRth% / Δp%, which reflects the difference between the initial thermal resistance and the initial flow resistance corresponding to the target thermal resistance and the target flow resistance, that is, the degree to which each optimization parameter needs to be adjusted as described below.

[0056] S4: Dynamically adjust various optimization parameters according to the difference to iteratively optimize the initial configuration information and determine the target configuration information.

[0057] In the above steps, each optimization parameter is adjusted to achieve iterative optimization of the initial configuration information. The optimization parameters adjusted in each iteration can be single or multiple, and the priority can be preset to control the adjustment order and adjustment range of each variable; based on this, the dynamic adjustment of each optimization parameter, see Figure 2 , including the following steps:

[0058] S41: for each optimization parameter, determine the adjustment amount of the optimization parameter; taking the thickness of the bottom plate as an example, the thickness of the bottom plate is d0 under the initial configuration information, and at the i-th iteration, the thickness of the bottom plate is d i , then for the base plate thickness, the adjustment amount is d i -d0.

[0059] S42: According to the adjustment amount of the optimization parameter and the lower limit value d of the optimization parameter min and the upper limit value d of the optimization parameter max Determine an adjustment ratio of the optimization parameter, and determine a corresponding change of the optimization parameter by multiplying the adjustment ratio of the optimization parameter by a heat dissipation performance influence factor A3 of the optimization parameter;

[0060] Based on the above, the adjustment ratio is (d i -d0) / (d max -d min ), then the corresponding change is ((d i -d0) / (d max -d min ))×A3; Similar calculations can be performed on other optimization parameters to obtain corresponding changes.

[0061] It can be understood that for an optimization parameter with at least two variables, that is, the change of the optimization parameter is formed by a combination of various variables, that is, it is necessary to determine the corresponding changes of various variables. Therefore, for an optimization parameter with at least two variables, it is also necessary to perform the following: determine the adjustment amount of a variable in a certain optimization parameter; determine the adjustment ratio of the variable according to the adjustment amount of the variable, the lower limit value of the variable and the upper limit value of the variable; taking the elliptical wing pin as an example, the wing pin size includes, including the major semi-axis length a, the short plate axis length b, and the wing pin length h. Similarly, under the initial configuration information, the major semi-axis length, the short plate axis length, and the wing pin length are a0, b0, and h0 respectively; at the i-th iteration, the major semi-axis length, the short plate axis length, and the wing pin length are a respectively. i 、b i 、h i ; Then the change in the length of the wing pin is h i -h0, its adjustment ratio is (h i -h0) / (h max -h min );h max is the upper limit of the wing needle length, h min It is the lower limit of the wing pin length.

[0062] According to the weight of the variable, determine the weight ratio of the variable relative to all variables included in the optimization parameter, so as to determine the change corresponding to the variable by multiplying the adjustment ratio of the variable, the weight ratio, and the heat dissipation performance influencing factor of the optimization parameter; then assume that the heat dissipation performance influencing factor corresponding to the bottom plate size is A1, and the weights corresponding to the above-mentioned major semi-axis length, minor semi-axis length, and wing pin length are A1_a, A1_b, and A1_c respectively; then the change corresponding to the wing pin length can be expressed as ((h i -h0) / (h max -h min ))×(A1_c / (A1_a+A1_b+A1_c))×A1.

[0063] Add the changes corresponding to all variables included in the optimization parameter to determine the change corresponding to the optimization parameter. Based on the above example of the optimization parameter being the wing pin size (the wing pin is elliptical), the corresponding change is expressed as (a i -a0) / (a max -a min ))×(A1_a / (A1_a+A1_b+A1_c))×A1+((b i -b0) / (b max -b min ))×(A1_b / (A1_a+A1_b+A1_c))×A1+((h i -h0) / (h max -h min))×(A1_c / (A1_a+A1_b+A1_c))×A1.

[0064] S43: Adding the changes corresponding to all optimization parameters to obtain a total change amount;

[0065] Based on the optimization parameter table of the above example (taking flow resistance as an example), the sum of each optimization parameter can be expressed as follows:

[0066]

[0067] It is understandable that the above formula only shows the changes in flow resistance and thermal resistance of the entire structure after adjusting various optimization parameters, which will not affect the changes in other factors, so other factors are not reflected in the formula.

[0068] S44: Obtain a preset margin K so that the total amount of change exceeds the preset margin relative to the difference.

[0069] In the above steps, if the degree of deviation between the total amount of change represented by the preset margin and the difference exceeds the preset margin, resulting in a larger total amount of change, the thermal resistance and flow resistance of the iteratively optimized configuration information can be lower than the target thermal resistance and target flow resistance, thereby determining the target configuration information.

[0070] In this embodiment, the thermal resistance and flow resistance are calculated separately, and the iterative optimization can only be stopped when the target thermal resistance and the target flow resistance are met at the same time, so the difference includes the thermal resistance difference and the flow resistance difference; before dynamically adjusting each optimization parameter, it is necessary to classify each optimization parameter in advance to determine the optimization parameters associated with the thermal resistance and the flow resistance, respectively; specifically, the optimization parameters related to the thermal resistance include but are not limited to: fin pin size, fin pin spacing, base plate thickness, thermal conductivity of the base plate material, etc.; the optimization parameters related to the flow resistance include but are not limited to: fin pin size, fin pin spacing, etc.

[0071] Dynamically adjust each optimization parameter to determine the total amount of change corresponding to the thermal resistance difference and the flow resistance difference; the preset margin can be set to include a first margin K1 associated with the thermal resistance and a second margin K2 associated with the flow resistance, so that the total amount of change corresponding to the thermal resistance difference exceeds the first margin relative to the thermal resistance difference, and the total amount of change corresponding to the flow resistance difference exceeds the second margin relative to the flow resistance difference. The second margin can be the same as the first margin or different. Taking the thermal resistance as an example, the total amount of change obtained in the above step S43 is greater than K1·ΔRth%.

[0072] In this embodiment, as an option, when dynamically adjusting various optimization parameters, the priority of each optimization parameter can also be preset; each optimization parameter is adjusted according to the priority of each optimization parameter, and according to the priority, the adjustment order and adjustment range of each variable can be limited, including but not limited to. As an example, when the thickness of the base plate is adjusted, according to its variation law, it is assumed that the optimal value for the module is between 0.2-0.3mm, then the adjustment of the base plate thickness is implemented within this range; for example, when the thermal conductivity k that has the greatest impact on heat dissipation performance and cost is adjusted, it is adjusted to k i , considering the cost impact, set the adjustment range to be smaller; for example, when adjusting other parameters, adjust them in the order of h1, a1, b1, d11, d21 (pinfin length, ellipse major semi-axis length, ellipse minor semi-axis length, Pinfin horizontal spacing, Pinfin longitudinal spacing d2), and the amplitude gradually decreases.

[0073] Furthermore, information priorities or labels may be configured to further control the dynamic adjustment of various optimization parameters in each iteration process.

[0074] In this embodiment, as described above, it should be noted that the iterative optimization can be stopped only when the target thermal resistance and the target flow resistance are satisfied at the same time, so the determination of the target configuration information includes: performing simulation based on the adjusted optimization parameters, calculating the optimized thermal resistance and flow resistance respectively, and determining the target configuration information by achieving the target thermal resistance and the target flow resistance at the same time. It can be understood that, as described above, the generated target configuration information can include multiple bottom plate structure optimization schemes, and the optimization parameters associated with the thermal resistance and the flow resistance can be iteratively adjusted according to the above optimization parameter table, respectively, and the optimization scheme sets associated with the thermal resistance and the flow resistance can be generated respectively, and then the optimization schemes in the optimization scheme sets associated with the thermal resistance and the flow resistance are obtained as the target configuration information.

[0075] In this embodiment, the target configuration information generates specific values ​​including various optimization parameters. For example, the target configuration information of this embodiment may be: a1=2.7mm, b1=1.2mm, h1=3mm, d1=0.58mm, d2=1.03mm, D1=3mm, k1=385W / m·K. The target configuration information may directly generate a fin-type base plate with accurate values ​​of fin size, fin spacing, base plate thickness, and base plate material thermal conductivity structure, so as to quantitatively and accurately optimize the base plate structure, so that when the optimized base plate structure is used in a module, its thermal resistance and flow resistance are both small (i.e., the target thermal resistance and target flow resistance of the configuration information), which meets the use requirements, thereby improving the heat dissipation effect of the module.

[0076] In this embodiment, based on the above steps S1-S4, an optimization parameter table with optimization parameters related to the wing-pin type base plate structure and affecting multiple aspects such as heat dissipation effect / cost is obtained in advance, and the initial configuration information is preset according to the optimization parameter table, and the base plate under the initial configuration information is simulated to determine the initial thermal resistance and initial flow resistance, and then the base plate structure is iteratively optimized by adjusting the optimization parameters based on the initial configuration information until the flow resistance and thermal resistance meet the preset usage requirements, and the target configuration information is determined. Specifically, each optimization parameter can be dynamically adjusted according to the difference between the initial thermal resistance and the initial flow resistance relative to the target thermal resistance and the target flow resistance, respectively, so that a base plate structure that meets the usage requirements (such as optimizing the heat dissipation effect, optimizing the cost, etc.) can be obtained, thereby improving the efficiency and accuracy of the base plate structure optimization.

[0077] The optimization method provided in this embodiment comprehensively considers multiple dimensions of the wing-pin type base plate, such as the fin distribution structure, base plate thickness, and material, and obtains quantitative heat dissipation performance influencing factors in each dimension as a reference to optimize the base plate structure to improve the matching degree between the obtained target configuration information and the requirements, and realize a multifunctional optimized base plate structure design with higher heat dissipation effect and / or lower cost.

[0078] To achieve the above-mentioned purpose, the present invention also provides a computer device, which may include multiple computer devices. The computer device of this embodiment at least includes but is not limited to: a memory and a processor that can be interconnected through a system bus. It should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Specifically, the memory may include a program storage area and a data storage area, wherein the program storage area may store an application required for the operating system and at least one function; the data storage area may store the above-mentioned optimization parameter table, target thermal resistance, target flow resistance, etc. The processor is generally used to control the overall operation of the computer device. In this embodiment, the processor is used to run the program code stored in the memory or process data, for example, to implement the above-mentioned method.

[0079] To achieve the above purpose, the present invention also provides a computer-readable storage medium, which includes multiple storage media, such as random access memory, static random access memory, read-only memory, etc., on which a computer program is stored, and the program implements the corresponding function when executed by the processor. The computer-readable storage medium of this embodiment is used to store data and programs, and implements the above method when executed by the processor.

[0080] It should be noted that the embodiments of the present invention have better practicability and do not impose any form of limitation on the present invention. Any technician familiar with the field may use the technical content disclosed above to change or modify it into an equivalent effective embodiment. However, any modification or equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention, as long as it does not deviate from the content of the technical solution of the present invention, are still within the scope of the technical solution of the present invention.

Claims

1. A module optimization method with a fin-pin type base plate, characterized in that: include: Obtaining an optimization parameter table, wherein the optimization parameter table includes several optimization parameters, wherein the optimization parameters include fin pin size, fin pin spacing, base plate thickness, and base plate material thermal conductivity, and each optimization parameter includes a lower limit value, an upper limit value, a heat dissipation performance influencing factor, a variable, and its weight; Preset initial configuration information of the fin-pin type base plate based on the optimization parameter table, and simulate and calculate initial thermal resistance and initial flow resistance, wherein the initial configuration information includes at least one optimization parameter; Determining the difference between the initial thermal resistance and the initial flow resistance relative to the target thermal resistance and the target flow resistance respectively; The optimization parameters are dynamically adjusted according to the difference, so as to determine the target configuration information after iterative optimization of the initial configuration information.

2. The optimization method according to claim 1, characterized in that Dynamically adjust various optimization parameters, including: For each optimization parameter, determining an adjustment amount of the optimization parameter; Determining an adjustment ratio of the optimization parameter according to the adjustment amount of the optimization parameter, the lower limit value of the optimization parameter, and the upper limit value of the optimization parameter, and determining a corresponding change of the optimization parameter by multiplying the adjustment ratio of the optimization parameter by a heat dissipation performance influence factor of the optimization parameter; Add up the changes corresponding to all optimized parameters to obtain the total amount of change; A preset margin is obtained, and the adjustment amount of each optimization parameter is updated so that the total amount of change exceeds the preset margin relative to the difference.

3. The optimization method according to claim 2, wherein: For an optimization parameter having at least two variables, determining an adjustment amount of a variable in a certain optimization parameter; Determining an adjustment ratio of the variable according to an adjustment amount of the variable, a lower limit value of the variable, and an upper limit value of the variable; Determining, based on the weight of the variable, the weight ratio of the variable relative to all variables included in the optimization parameter, so as to determine the corresponding change of the variable by multiplying the adjustment ratio of the variable, the weight ratio, and the heat dissipation performance impact factor of the optimization parameter; The changes corresponding to all variables included in the optimization parameters are added to determine the changes corresponding to the optimization parameters.

4. The optimization method according to claim 3, wherein: The optimization parameters with at least two variables include fin pin size and fin pin spacing; The variables of the wing pin spacing include horizontal spacing and vertical spacing; The wing pin size is determined by the variables included in the cross-sectional shape of the wing pin; When the cross section of the wing pin is an ellipse, the variables of the wing pin size include the length of the major axis, the length of the minor axis, and the wing pin length; When the cross section of the wing pin is circular, the variables of the wing pin size include radius and wing pin length; When the cross section of the wing pin is rhombus, the variables of the wing pin size include the long diagonal, the short diagonal, and the wing pin length.

5. The optimization method according to claim 2, characterized in that: The various optimization parameters are classified in advance to determine the optimization parameters associated with the thermal resistance and the flow resistance, respectively.

6. The optimization method according to claim 5, characterized in that: The difference includes thermal resistance difference and flow resistance difference; respectively determining a total amount of thermal resistance change and a total amount of flow resistance change corresponding to the thermal resistance difference and the flow resistance difference; The preset margin includes a first margin associated with the thermal resistance and a second margin associated with the flow resistance. The adjustment amount of each optimization parameter is updated so that the total amount of thermal resistance change exceeds the first margin relative to the thermal resistance difference, and the total amount of flow resistance change exceeds the second margin relative to the flow resistance difference.

7. The optimization method according to claim 1, wherein: The initial configuration information of the fin-pin type base plate includes the lower limit value of the base plate thickness and the thermal conductivity coefficient of the base plate material, the upper limit value of the base plate spacing, and the lower limit value of the base plate size.

8. The optimization method according to claim 1, wherein: Preset the priority of each optimization parameter; Adjust each optimization parameter according to its priority.

9. A computer device, characterized in that: The computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the module optimization method with a fin-pin type base plate as claimed in any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the module optimization method with a fin-pin type base plate according to claims 1 to 8 are implemented.

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