A heat dissipation bottom plate layout rule optimization method and device

Abstract

The application relates to the technical field of radiator layout optimization, and discloses a method and device for optimizing a layout rule of a radiator bottom plate, wherein the method calculates the flow velocity field distribution function of each heat dissipation point by applying a lattice Boltzmann method and a large eddy simulation method, and further combines a preset optimization algorithm to optimize the target layout rule of multiple elliptical regions, so that the optimization speed and accuracy of the radiator bottom plate can be improved.

Description

Technical Field

[0001] This invention relates to the field of radiator layout optimization technology, specifically to a method and apparatus for optimizing the layout rules of a radiator base plate. Background Technology

[0002] A heatsink is a highly efficient heat dissipation structure, particularly suitable for the heat dissipation needs of high-performance electronic components, such as IGBTs (Insulated Gate Bipolar Transistors). In recent years, mainstream products have widely adopted Pinfin heatsinks, which contain numerous cylindrical or needle-like protrusions. These protrusions increase the contact area between the heatsink and the cooling medium flowing across its surface, thereby improving heat exchange efficiency.

[0003] Currently, due to the limitations of standardized packaging, the design research of Pinfin heat sinks is still mainly based on geometric size variations in regular layouts. The size and spacing of the Pinfin heat sink are adjusted according to different application requirements to improve heat dissipation performance. However, in most designs, the parameters of the heat dissipation holes of each Pinfin heat sink are exactly the same, failing to take into account local details such as chip layout and coolant flow direction.

[0004] In related technologies, in the layout scheme of Pinfin heat sink base plates, each Pinfin heat sink base plate has the same size, shape, spacing, rotation angle and other parameters. The layout scheme of Pinfin heat sink base plates is usually optimized by CFD method of thermal simulation, formula method, finite difference method or conventional three-dimensional lattice method. However, these methods are not suitable for the optimization of irregular Pinfin heat sink base plates. In addition, these methods are also difficult to guarantee the optimization speed and accuracy of Pinfin heat sink base plates. Summary of the Invention

[0005] In view of this, the present invention provides a method and apparatus for optimizing the layout rules of a heat dissipation base plate, in order to solve the problems that traditional layout schemes for Pinfin heat dissipation base plates are not suitable for optimizing irregular Pinfin heat dissipation base plates, and that it is difficult to guarantee the optimization speed and accuracy of Pinfin heat dissipation base plates.

[0006] In a first aspect, the present invention provides a method for optimizing the layout rules of a heat dissipation base plate, the method comprising:

[0007] Based on the preset layout rules of multiple elliptical regions of the heat dissipation base plate, the target layout rules of multiple elliptical regions are generated by randomly changing multiple layout parameters.

[0008] According to the target layout rules, multiple heat dissipation points are arranged in each elliptical region, and the velocity field distribution function of each heat dissipation point is calculated using the lattice Boltzmann method and the large eddy simulation method.

[0009] Based on the flow field distribution function of each heat dissipation point, calculate the water flow velocity and water flow pressure at each heat dissipation point;

[0010] Based on the flow velocity field distribution function of each heat dissipation point, the water flow velocity and water flow pressure of each heat dissipation point, the target evaluation temperature of the heat dissipation base plate is calculated.

[0011] The target evaluation temperature is used as the initial value of the preset optimization algorithm. The target layout rules of multiple elliptical regions are iteratively optimized step by step until the target evaluation temperature meets the preset optimization requirements. The iteration stops and the target layout rules of multiple elliptical regions corresponding to the optimal result are output. If the target evaluation temperature does not meet the preset requirements, the preset layout rules of multiple elliptical regions based on the heat dissipation base plate are returned. The steps of generating target layout rules of multiple elliptical regions by randomly changing multiple layout parameters are repeated until the target evaluation temperature meets the preset requirements.

[0012] By implementing the above methods, the velocity field distribution function of each heat dissipation point is calculated using the lattice Boltzmann method and the large eddy simulation method. Furthermore, by combining the preset optimization algorithm to optimize the target layout rules of multiple elliptical regions, the optimization speed and accuracy of the heat dissipation base plate can be improved.

[0013] In some optional implementations, multiple heat dissipation points are arranged in each elliptical region according to the target layout rules, and the velocity field distribution function of each heat dissipation point is calculated using the lattice Boltzmann method and the large eddy simulation method, including:

[0014] According to the target layout rules, multiple heat dissipation points are arranged in each elliptical area to generate a layout scheme for the heat dissipation base plate;

[0015] The velocity field distribution function of each heat dissipation point is calculated using the lattice Boltzmann method and the large eddy simulation method. The velocity field distribution function of each heat dissipation point during the collision process and the flow process is calculated.

[0016] Based on the velocity field distribution function of each heat dissipation point during the collision and flow processes, the velocity field distribution function of the boundary heat dissipation point of each elliptical region is calculated.

[0017] By implementing the above methods, the velocity field distribution function of each heat dissipation point can be calculated using the lattice Boltzmann method and the large eddy simulation method. This allows for the accurate calculation of the velocity field distribution function of each heat dissipation point during the collision and flow processes, as well as the velocity field distribution function of the boundary heat dissipation points of each elliptical region.

[0018] In some alternative implementations, the velocity field distribution function of each heat dissipation point during the collision and flow processes is calculated using the following formula;

[0019]

[0020] Among them, f k Let x be the velocity field distribution function at any heat dissipation point x in each elliptical region at time t. Let be the velocity field equilibrium distribution function at any heat dissipation point x in each elliptical region at time t, k be multiple velocity directions for each heat dissipation point in each elliptical region, and τ be the relaxation time. According to the eddy viscosity model in the large eddy simulation method, τ is...

[0021] v0 is the kinematic viscosity Let C be the eddy current viscosity, C be a constant, and Δ be the filter size. Let be the modulus of the strain rate tensor.

[0022] By implementing the above methods, the velocity field distribution function of each heat dissipation point can be calculated using the lattice Boltzmann method and the large eddy simulation method. This allows for the accurate calculation of the velocity field distribution function of each heat dissipation point during the collision and flow processes.

[0023] In some optional implementations, the velocity field distribution function of the boundary heat dissipation point of each elliptical region is calculated based on the velocity field distribution function of each heat dissipation point during the collision and flow processes, using the following formula:

[0024]

[0025] according to q The size of the heat dissipation point x at the boundary of each elliptical region can be calculated. s The velocity field distribution function;

[0026]

[0027] Where, x w For each elliptical region, the boundary heat dissipation point, x s x distance from the boundary heat dissipation point within each elliptical region w The nearest heat dissipation point, x f x is the distance from the boundary heat dissipation point outside each elliptical region. w The nearest heat dissipation point, x ff The distance x outside each elliptical region f Recent heat dissipation point, x f The distance x outside each elliptical region f The nearest heat dissipation point, q is an intermediate parameter, f k '(x s ,t) is the distance x from the boundary heat dissipation point within each elliptical region. w Recent heat dissipation point x s The distribution function after the collision at time t.

[0028] By implementing the above methods, the velocity field distribution function of the boundary heat dissipation point of each elliptical region can be accurately calculated.

[0029] In some alternative implementations, the water flow velocity and pressure at each heat dissipation point are calculated based on the flow field distribution function of each heat dissipation point, using the following formula:

[0030]

[0031]

[0032] Among them, c k Let u be the unit flow velocity at each heat dissipation point in each elliptical region, p be the water flow velocity at each heat dissipation point in each elliptical region, and f be the water flow pressure at each heat dissipation point in each elliptical region. k Let x be the velocity field distribution function at any heat dissipation point x in each elliptical region at time t.

[0033] By implementing the above methods, the water flow velocity and water flow pressure at each heat dissipation point can be accurately calculated based on the flow velocity field distribution function of each heat dissipation point.

[0034] In some optional implementations, the target evaluation temperature of the heat dissipation base plate is calculated based on the flow field distribution function of each heat dissipation point, the water flow velocity and water flow pressure at each heat dissipation point, including:

[0035] Obtain the cross-sectional area of ​​the water outlet of the heat dissipation base plate, the total water output pressure of the heat dissipation pump, and the total water output flow rate;

[0036] Calculate the total water input flow rate of the heat dissipation base plate based on the water flow velocity and outlet cross-sectional area of ​​each heat dissipation point.

[0037] Calculate the total water input pressure of the heat dissipation base plate based on the water flow pressure at each heat dissipation point.

[0038] Based on the total water input pressure and total water input flow rate of the heat dissipation base plate, the first flow characteristic curve of the heat dissipation base plate is plotted.

[0039] Based on the total output pressure and total output flow rate of the cooling pump, plot the second flow characteristic curve of the cooling pump;

[0040] Obtain the intersection point between the first flow characteristic curve and the second flow characteristic curve, and use the intersection point as the target operating point for the heat dissipation base plate and the heat pump.

[0041] Based on the temperature field distribution function, the target evaluation temperature of the heat dissipation base plate corresponding to the target operating point is calculated.

[0042] By implementing the above methods and considering the target evaluation temperature of the heat sink corresponding to the target operating point, an automatic optimization algorithm for irregular Pinfin layout schemes is proposed, which not only improves heat dissipation performance but also increases optimization speed and accuracy.

[0043] In some optional implementations, the target evaluation temperature of the heat dissipation base plate corresponding to the target operating point is calculated based on the temperature field distribution function, using the following formula:

[0044]

[0045] Among them, g k Let x be the temperature field distribution function at time t, k be the multiple velocity directions at each heat dissipation point in each elliptical region, τ be the relaxation time, and c be the temperature field distribution function at time t. k For each heat dissipation point in each elliptical region, c represents the unit flow velocity. s Let u be the lattice sound velocity in the lattice Boltzmann method, u be the water flow velocity at each heat dissipation point in each elliptical region, T be the target evaluation temperature of the heat dissipation base plate corresponding to the target operating point, and w be the lattice sound velocity in the lattice Boltzmann method. k Δx is the weight of the lattice model in the lattice Boltzmann method, Δx is the distance between adjacent heat dissipation points, and Δt is the time advance interval for each simulation using the lattice Boltzmann method.

[0046] By implementing the above methods, the target evaluation temperature of the heat dissipation base plate corresponding to the target operating point is calculated. In order to propose an automatic optimization algorithm for irregular Pinfin layout schemes, not only is the heat dissipation performance improved, but the optimization speed and accuracy are also increased.

[0047] Secondly, the present invention provides an optimization device for the layout rules of a heat dissipation base plate, the device comprising:

[0048] The layout rule generation module is used to generate target layout rules for multiple elliptical regions based on the preset layout rules of the heat dissipation base plate by randomly changing multiple layout parameters.

[0049] The velocity distribution calculation module is used to arrange multiple heat dissipation points in each elliptical region according to the target layout rules, and to calculate the velocity field distribution function of each heat dissipation point using the lattice Boltzmann method and the large eddy simulation method.

[0050] The water flow parameter calculation module is used to calculate the water flow velocity and water flow pressure at each heat dissipation point based on the flow velocity field distribution function at each heat dissipation point.

[0051] The evaluation temperature calculation module is used to calculate the target evaluation temperature of the heat dissipation base plate based on the flow field distribution function of each heat dissipation point, the water flow velocity and water flow pressure of each heat dissipation point.

[0052] The layout rule optimization module uses the target evaluation temperature as the initial value of the preset optimization algorithm to iteratively optimize the target layout rules of multiple elliptical regions until the target evaluation temperature meets the preset optimization requirements. Then, the iteration stops and the target layout rules of multiple elliptical regions corresponding to the optimal result are output. If the target evaluation temperature does not meet the preset requirements, the module returns the preset layout rules of multiple elliptical regions based on the heat dissipation base plate. The module generates the target layout rules of multiple elliptical regions by randomly changing multiple layout parameters until the target evaluation temperature meets the preset requirements.

[0053] Thirdly, the present invention provides a computer device, including: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the optimization method of the heat dissipation base plate layout rules of the first aspect or any corresponding embodiment described above.

[0054] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the optimization method for the heat dissipation base plate layout rules of the first aspect or any corresponding embodiment described above.

[0055] Fifthly, the present invention provides a computer program product, including computer instructions for causing a computer to execute the optimization method of the heat dissipation base plate layout rules of the first aspect or any corresponding embodiment described above. Attached Figure Description

[0056] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0057] Figure 1 This is a flowchart illustrating a method for optimizing the layout rules of a heat dissipation base plate according to an embodiment of the present invention.

[0058] Figure 2 These are schematic diagrams of different types of Pinfin heat dissipation base plates according to embodiments of the present invention;

[0059] Figure 3 This is a schematic diagram of the preset layout rules of multiple elliptical regions according to an embodiment of the present invention;

[0060] Figure 4 This is a schematic diagram illustrating the change from a preset layout rule to a target layout rule according to an embodiment of the present invention;

[0061] Figure 5 This is a schematic diagram of multiple flow velocity directions at each heat dissipation point according to an embodiment of the present invention;

[0062] Figure 6 This is a schematic diagram of the genetic algorithm optimization process according to an embodiment of the present invention;

[0063] Figure 7 This is a schematic diagram of the random generation of primary DNA and the offspring after crossover mutation according to an embodiment of the present invention;

[0064] Figure 8 This is a flowchart illustrating another method for optimizing the layout rules of a heat dissipation base plate according to an embodiment of the present invention;

[0065] Figure 9 This is a schematic diagram illustrating the processing of the elliptical region boundary according to an embodiment of the present invention;

[0066] Figure 10 This is a flowchart illustrating another method for optimizing the layout rules of a heat dissipation base plate according to an embodiment of the present invention;

[0067] Figure 11 This is a schematic diagram of the intersection point between the first flow characteristic curve and the second flow characteristic curve according to an embodiment of the present invention.

[0068] Figure 12 This is a schematic diagram of the Pinfin heat sink structure according to an embodiment of the present invention;

[0069] Figure 13 This is a structural block diagram of a device for optimizing the layout rules of a heat dissipation base plate according to an embodiment of the present invention;

[0070] Figure 14 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0071] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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 some embodiments of the present invention, not all embodiments. 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.

[0072] According to an embodiment of the present invention, an embodiment of a method for optimizing the layout rules of a heat dissipation base plate is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0073] This embodiment provides an optimization method for the layout rules of a heat dissipation base plate, which can be used in computer devices such as mobile phones, tablets, desktop computers, laptops, servers, etc. Figure 1 This is a flowchart of a method for optimizing the layout rules of a heat dissipation base plate according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps:

[0074] Step S101: Based on the preset layout rules of multiple elliptical regions of the heat dissipation base plate, multiple layout parameters are randomly changed to generate target layout rules for multiple elliptical regions.

[0075] Specifically, in recent years, mainstream products have widely adopted Pinfin heatsinks. These Pinfin heatsinks contain numerous cylindrical or needle-like protrusions, which increase the contact area between the heatsink and the cooling medium flowing over its surface, thereby improving heat exchange efficiency. Currently, due to limitations in standardized packaging, the design research of Pinfin heatsinks mainly focuses on geometric variations in a regular layout. The size and spacing of the Pinfin heatsink are adjusted according to different application requirements to improve heat dissipation performance, such as... Figure 2 The diagram shows different types of Pinfin heat sinks.

[0076] Furthermore, the preset layout rules for multiple elliptical regions are layout schemes formed according to standard and universal rules. For example... Figure 3 The diagram shown illustrates the preset layout rules for multiple elliptical regions. Figure 3 In the text, the parameters of Pinfin are basically the same for each elliptical region. Figure 3 The data includes the center-to-center distance between two adjacent elliptical regions along the X-axis, the center-to-center distance along the Y-axis, the X-axis and Y-axis distances between elliptical regions, and the rotation angle of each elliptical region. Each elliptical region is also equivalent to each pin, and the heatsink also includes the height value of each pin. The target layout rule for multiple elliptical regions is a layout scheme formed by an irregular arrangement.

[0077] In a specific example, based on the preset layout rules of multiple elliptical regions of the heat dissipation base plate, multiple layout parameters are randomly changed to generate target layout rules for multiple elliptical regions, including:

[0078] Step a1: Obtain multiple layout parameters, including: the order weight parameters of the arrangement of multiple elliptical regions, and the X-direction displacement parameters, Y-direction displacement parameters, major axis dimension parameters, and rotation angle parameters of each elliptical region;

[0079] Step a2: Based on the preset layout rules of multiple elliptical regions of the heat dissipation base plate, randomly change the order weight parameters of the arrangement of multiple elliptical regions, the X-direction displacement parameters, the Y-direction displacement parameters, the major axis dimension parameters and the rotation angle parameters of each elliptical region, and then generate the target layout rules of multiple elliptical regions.

[0080] Specifically, such as Figure 4 As shown, the order weight parameters of multiple elliptical regions in the preset layout rule are (1, 2, 3, 4, 5, 6, 7, 8). After randomly changing these order weight parameters, the target layout rule for the multiple elliptical regions in the target layout rule becomes (7, 2, 1, 4, 8, 6, 3, 5). The X-direction displacement parameter of each elliptical region in the preset layout rule is (0, 0, 0, 0, 0, 0, 0, 0). After randomly changing these X-direction displacement parameters to (3, -1, 1, 0, -2, 0, 0, -1), the Y-direction displacement parameter of each elliptical region in the preset layout rule becomes (0, 0, 0, 0, 0, 0). The Y-direction displacement parameter is randomly changed to (1, -1, -1, 0, -2, 0, 0, -1). The major axis dimension parameter of each elliptical region in the preset layout rule is (6, 6, 6, 6, 6, 6, 6, 6). The major axis dimension parameter is randomly changed to (7, 8, 8, 6, 6, 8, 6, 6). The rotation angle of each elliptical region in the preset layout rule is (0, 0, 0, 0, 0, 0, 0, 0). The rotation angle parameter is randomly changed to (150, 0, 135, 90, 30, 0, 45, 150). Several different preset angles are provided for selection.

[0081] In the actual process of generating target layout rules for multiple elliptical regions, the X-direction and Y-direction displacements are performed sequentially according to the order weight parameters of the multiple elliptical regions, followed by changes in the major axis dimension and rotation angle. For simplicity, as the major axis dimension increases, the minor axis dimension also increases accordingly. Several preset rotation angles (150°, 0°, 135°, 90°, 30°) are provided for selection, instead of all angles. When there are elliptical position conflicts, the elliptical region corresponding to the higher order weight is retained.

[0082] Step S102: Arrange multiple heat dissipation points in each elliptical region according to the target layout rules, and calculate the velocity field distribution function of each heat dissipation point using the lattice Boltzmann method and the large eddy simulation method.

[0083] Specifically, the velocity field of each elliptical region (each pinfin) is solved using the Lattice Boltzmann Method and Large Eddy Simulation. The lattice model employs D2Q9 for calculating the convection term, such as... Figure 5 As shown, this is a schematic diagram of the flow direction of each heat dissipation point (each grid) in each elliptical region, where the red dots represent the currently observed target heat dissipation point (target grid).

[0084] The velocity field distribution function of each heat dissipation point is calculated using the lattice Boltzmann method and the large eddy simulation method, in order to further optimize the speed and accuracy of the target layout rules for multiple elliptical regions.

[0085] Step S103: Calculate the water flow velocity and water flow pressure at each heat dissipation point based on the flow velocity field distribution function at each heat dissipation point.

[0086] Specifically, under the constraint of the velocity field distribution function at each heat dissipation point, the accuracy of the calculation of water flow velocity and water flow pressure at each heat dissipation point in each elliptical region can be further guaranteed.

[0087] Step S104: Calculate the target evaluation temperature of the heat dissipation base plate based on the flow velocity field distribution function of each heat dissipation point, the water flow velocity and water flow pressure of each heat dissipation point.

[0088] Specifically, based on the flow field distribution function of each heat dissipation point, the water flow velocity and water flow pressure of each heat dissipation point, the target evaluation temperature of the heat dissipation base plate is further obtained. This target evaluation temperature is the junction temperature of the heat dissipation chip deployed on the heat dissipation base plate. This target evaluation temperature is used as the fitness of the target layout rules for evaluating multiple elliptical regions.

[0089] Step S105: The target evaluation temperature is used as the initial value of the preset optimization algorithm. The target layout rules of multiple elliptical regions are iteratively optimized step by step until the target evaluation temperature meets the preset optimization requirements. The iteration is stopped and the target layout rules of multiple elliptical regions corresponding to the optimal result are output. If the target evaluation temperature does not meet the preset requirements, the preset layout rules of multiple elliptical regions based on the heat dissipation base plate are returned. The steps of generating the target layout rules of multiple elliptical regions by randomly changing multiple layout parameters are repeated until the target evaluation temperature meets the preset requirements.

[0090] Specifically, the preset optimization algorithm here can be a genetic algorithm, or other optimization algorithms. Here, a genetic algorithm is preferred, and the specific flowchart is shown below. Figure 6As shown, the genetic algorithm first randomly generates multiple initial DNA sequences (target layout rules for multiple elliptical regions). Then, starting from the initial generation (using the target evaluation temperature as the initial value), it iterates, selecting the better individuals for reproduction by comparing fitness values, while eliminating those with poor fitness. During crossover, the individuals selected in the previous step undergo a longest common subsequence crossover operation. During mutation, two mutation positions are randomly generated, and the DNA characters at these two positions are swapped. It is worth noting that the mutation probability in the genetic algorithm is extremely low, typically around 1%. When the limit is reached, the optimized result is output. Figure 7 The diagram shown illustrates the random generation of primary DNA and the offspring resulting from crossover mutations.

[0091] The optimization method for the heat dissipation base plate layout rules in this embodiment of the present disclosure calculates the flow velocity field distribution function of each heat dissipation point by applying the lattice Boltzmann method and the large eddy simulation method, and further optimizes the target layout rules of multiple elliptical regions by combining a preset optimization algorithm, which can improve the optimization speed and accuracy of the heat dissipation base plate.

[0092] This embodiment provides an optimization method for the layout rules of a heat dissipation base plate, which can be used in computer devices such as mobile phones, tablets, desktop computers, laptops, servers, etc. Figure 8 This is a flowchart of a method for optimizing the layout rules of a heat dissipation base plate according to an embodiment of the present invention, such as... Figure 8 As shown, in step S102, multiple heat dissipation points are arranged in each elliptical region according to the target layout rules, and the velocity field distribution function of each heat dissipation point is calculated using the lattice Boltzmann method and the large eddy simulation method. This process includes the following steps:

[0093] Step S1021: Arrange multiple heat dissipation points in each elliptical region according to the target layout rules to generate a layout scheme for the heat dissipation base plate.

[0094] Specifically, the target layout rule is an irregular arrangement formed by the sequential weights of multiple elliptical regions, the X-direction displacement parameters, Y-direction displacement parameters, major axis dimension parameters, and rotation angle parameters of each elliptical region. Based on this irregular arrangement, multiple heat dissipation points are arranged in each elliptical region, thereby forming a layout scheme for the heat dissipation base plate.

[0095] Step S1022: Calculate the velocity field distribution function of each heat dissipation point during the collision and flow processes using the lattice Boltzmann method and the large eddy simulation method.

[0096] In a specific example, the velocity field distribution function of each heat dissipation point during the collision and flow processes is calculated using the following formula (1);

[0097]

[0098] Among them, f k Let x be the velocity field distribution function at any heat dissipation point x in each elliptical region at time t. Let be the velocity field equilibrium distribution function at any heat dissipation point x in each elliptical region at time t, and k be multiple velocity directions for each heat dissipation point in each elliptical region. Figure 5 In this context, k represents nine different flow velocity directions, and τ is the relaxation time. According to the eddy viscosity model in large eddy simulation, τ is... v0 is the kinematic viscosity Let C be the eddy current viscosity, C be a constant, and Δ be the filter size. Let be the modulus of the strain rate tensor.

[0099] Step S1023: Based on the velocity field distribution function of each heat dissipation point during the collision and flow processes, calculate the velocity field distribution function of the boundary heat dissipation point of each elliptical region.

[0100] Specifically, when encountering obstacles with curved surfaces, the boundaries of these obstacles need to be replaced by interpolation. Therefore, the elliptical pinfins of each elliptical region require additional surface boundary processing. For example... Figure 9 As shown, the distribution of grid points and walls in a two-dimensional flow is presented.

[0101] In a specific example, based on the velocity field distribution function of each heat dissipation point during the collision and flow processes, the velocity field distribution function of the boundary heat dissipation point of each elliptical region is calculated using the following formula (2):

[0102]

[0103] According to the following formula (3), q The size of the heat dissipation point x at the boundary of each elliptical region can be calculated. s The velocity field distribution function;

[0104]

[0105] Where, x w For each elliptical region, the boundary heat dissipation point, x s x distance from the boundary heat dissipation point within each elliptical region w The nearest heat dissipation point, x f x is the distance from the boundary heat dissipation point outside each elliptical region. w The nearest heat dissipation point, x ff The distance x outside each elliptical region f The nearest heat dissipation point, x f The distance x outside each elliptical region f The nearest heat dissipation point, q is an intermediate parameter, fk '(x s ,t) is the distance x from the boundary heat dissipation point within each elliptical region. w Recent heat dissipation point x s The distribution function after the collision at time t.

[0106] This embodiment processes the boundary of each elliptical region and calculates the distance x from the heat dissipation point at the boundary within each elliptical region. w Recent heat dissipation point x s The distribution function after the collision at time t is still for the purpose of accurately defining the target layout rules for each elliptical region.

[0107] In some alternative implementations, the water flow velocity and water flow pressure at each heat dissipation point are calculated based on the flow velocity field distribution function at each heat dissipation point, and this is performed using the following formula (4):

[0108]

[0109] Among them, c k Let u be the unit flow velocity at each heat dissipation point in each elliptical region, p be the water flow velocity at each heat dissipation point in each elliptical region, and f be the water flow pressure at each heat dissipation point in each elliptical region. k Let x be the velocity field distribution function at any heat dissipation point x in each elliptical region at time t.

[0110] Based on the flow field distribution function of any heat dissipation point in each elliptical region, the embodiments of this disclosure further calculate the water flow velocity and water flow pressure of each heat dissipation point in each elliptical region in order to evaluate whether the target layout rule of multiple elliptical regions is feasible.

[0111] This embodiment provides an optimization method for the layout rules of a heat dissipation base plate, which can be used in computer devices such as mobile phones, tablets, desktop computers, laptops, servers, etc. Figure 10 This is a flowchart of a method for optimizing the layout rules of a heat dissipation base plate according to an embodiment of the present invention, such as... Figure 10 As shown, in step S104, based on the flow velocity field distribution function of each heat dissipation point, the water flow velocity and water flow pressure of each heat dissipation point, the target evaluation temperature of the heat dissipation base plate is calculated. This process includes the following steps:

[0112] Step S1041: Obtain the cross-sectional area of ​​the water outlet of the heat dissipation base plate, the total water output pressure of the heat dissipation pump, and the total water output flow rate.

[0113] Specifically, the cross-sectional area of ​​the outlet of the heat dissipation base plate is represented by S, the total water output pressure of the heat dissipation pump is represented by P1, and the total water output flow rate is represented by Q1.

[0114] Step S1042: Calculate the total water input flow rate of the heat dissipation base plate based on the water flow velocity and outlet cross-sectional area of ​​each heat dissipation point.

[0115] Specifically, the water flow velocity at each heat dissipation point in each elliptical region is represented by u, and is calculated using the formula (4) above. The total water input flow rate of the heat dissipation base plate is represented by Q2.

[0116] In one specific embodiment, the total water input flow rate of the heat dissipation base plate is calculated based on the water flow velocity and outlet cross-sectional area of ​​each heat dissipation point, using the following formula (5).

[0117] Q2=u×S (5)

[0118] Step S1043: Calculate the total water input pressure of the heat dissipation base plate based on the water flow pressure at each heat dissipation point.

[0119] Specifically, the water flow pressure at each heat dissipation point in each elliptical region is represented by p, which is calculated using the formula (4) above. The total water flow input pressure of the heat dissipation base plate is obtained by multiplying the total number of heat dissipation points by the water flow pressure at each heat dissipation point in each elliptical region. Therefore, the total water flow input pressure of the heat dissipation base plate is represented by P2.

[0120] Step S1044: Based on the total water input pressure and total water input flow rate of the heat dissipation base plate, plot the first flow characteristic curve of the heat dissipation base plate.

[0121] Specifically, the total water input pressure of the heat dissipation base plate is P2, and the total water input flow rate of the heat dissipation base plate is Q2.

[0122] Based on the total input pressure and total input flow rate of the water to the heat dissipation base plate, the first flow characteristic curve of the heat dissipation base plate is plotted, as follows: Figure 11 The red line shown.

[0123] Step S1045: Based on the total output pressure and total output flow rate of the cooling pump, plot the second flow characteristic curve of the cooling pump.

[0124] Given that the total output pressure of the cooling pump is P1 and the total output flow rate of the cooling pump is Q1, plot the second flow characteristic curve of the cooling pump, as follows: Figure 11 The black line shown.

[0125] Step S1046: Obtain the intersection point between the first flow characteristic curve and the second flow characteristic curve, and use the intersection point as the target operating point for the heat dissipation base plate and the heat pump.

[0126] Step S1047: Calculate the target evaluation temperature of the heat dissipation base plate corresponding to the target operating point based on the temperature field distribution function.

[0127] Specifically, in Figure 11 In the diagram, the red line represents the characteristic curve of the pipeline, obtained from the relevant parameters of the heat sink base plate; the black line represents the flow characteristic curve of the pump, obtained from the relevant parameters of the pump; and point A is the operating point. Therefore, different heat sink structures will not have the same operating point; it is necessary to first find the operating point and compare the suitability at that point.

[0128] In some optional implementations, the target evaluation temperature of the heat dissipation base plate corresponding to the target operating point is calculated based on the temperature field distribution function, and is performed by the following formula (6):

[0129]

[0130] Among them, g k Let x be the temperature field distribution function at time t, k be the multiple velocity directions at each heat dissipation point in each elliptical region, τ be the relaxation time, and c be the temperature field distribution function at time t. k For each heat dissipation point in each elliptical region, c represents the unit flow velocity. s Let u be the lattice sound velocity in the lattice Boltzmann method, u be the water flow velocity at each heat dissipation point in each elliptical region, T be the target evaluation temperature of the heat dissipation base plate corresponding to the target operating point, and w be the lattice sound velocity in the lattice Boltzmann method. k Δx is the weight of the lattice model in the lattice Boltzmann method, Δx is the distance between adjacent heat dissipation points, and Δt is the time advance interval for each simulation using the lattice Boltzmann method.

[0131] Specifically, using, such as Figure 12 The 2.5D lattice Boltzmann method shown is used to solve for the chip junction temperature. The heat conduction process is simulated using lattice model D3Q7, and the heat convection process is solved using lattice model D2Q9 plus lattice model D2Q5.

[0132] This disclosure aims to reduce the thermal resistance of the power module and minimize the temperature difference between the chip junctions. Taking into account the influence of chip size, location, and coolant flow direction, it proposes an automatic optimization algorithm for irregular pinfin layout schemes, which not only improves heat dissipation performance but also enhances optimization speed and accuracy.

[0133] Furthermore, conventional thermal simulation methods such as CFD, formulaic methods, finite difference methods, and conventional three-dimensional lattice methods are not suitable for efficient evaluation of irregularly laid-out Pinfin schemes, making automatic optimization difficult. This disclosure employs a lattice Boltzmann method, making the optimization results closer to their actual heat dissipation performance, thus solving the problem of conventional heat dissipation simulations struggling to balance simulation accuracy and speed.

[0134] Furthermore, we determined the actual operating point of the Pinfin, focusing on improving the overall heat dissipation of the electric drive system and further enhancing the practicality of the Pinfin layout optimization.

[0135] This embodiment also provides an optimization device for the layout rules of a heat dissipation base plate. This device is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0136] This embodiment provides an optimization device for the layout rules of a heat dissipation base plate, such as... Figure 13 As shown, it includes:

[0137] The layout rule generation module 130 is used to generate target layout rules for the multiple elliptical regions based on the preset layout rules of the heat dissipation base plate by randomly changing multiple layout parameters.

[0138] The velocity distribution calculation module 131 is used to arrange the multiple heat dissipation points in each elliptical region according to the target layout rules, and to calculate the velocity field distribution function of each heat dissipation point using the lattice Boltzmann method and the large eddy simulation method.

[0139] The water flow parameter calculation module 132 is used to calculate the water flow velocity and water flow pressure of each heat dissipation point based on the flow velocity field distribution function of each heat dissipation point.

[0140] The evaluation temperature calculation module 133 is used to calculate the target evaluation temperature of the heat dissipation base plate based on the flow velocity field distribution function of each heat dissipation point, the water flow velocity and water flow pressure of each heat dissipation point.

[0141] The layout rule optimization module 134 is used to take the target evaluation temperature as the initial value of the preset optimization algorithm, iteratively optimize the target layout rules of the multiple elliptical regions until the target evaluation temperature meets the preset optimization requirements, stop the iteration, and output the target layout rules of the multiple elliptical regions corresponding to the optimal result. If the target evaluation temperature does not meet the preset requirements, the preset layout rules of the multiple elliptical regions based on the heat dissipation base plate are returned, and the target layout rules of the multiple elliptical regions are generated by randomly changing multiple layout parameters until the target evaluation temperature meets the preset requirements.

[0142] In some alternative implementations, the velocity distribution calculation module 131 includes:

[0143] The layout scheme generation submodule is used to arrange multiple heat dissipation points in each elliptical area according to the target layout rules, and generate the layout scheme of the heat dissipation base plate.

[0144] The first function calculation submodule is used to calculate the velocity field distribution function of each heat dissipation point during the collision and flow processes using the lattice Boltzmann method and the large eddy simulation method.

[0145] The second function calculation submodule is used to calculate the velocity field distribution function of the boundary heat dissipation point of each elliptical region based on the velocity field distribution function of each heat dissipation point during the collision and flow processes.

[0146] In some alternative implementations, the velocity field distribution function of each heat dissipation point during the collision and flow processes is calculated using the above formula (1).

[0147] In some alternative implementations, the velocity field distribution function of the boundary heat dissipation point of each elliptical region is calculated based on the velocity field distribution function of each heat dissipation point during the collision and flow processes using the above formulas (2)-(3).

[0148] In some alternative implementations, the water flow velocity and water flow pressure at each heat dissipation point are calculated based on the flow velocity field distribution function at each heat dissipation point using the above formula (4).

[0149] In some alternative implementations, the evaluation temperature calculation module 133 includes:

[0150] The first acquisition submodule is used to acquire the cross-sectional area of ​​the water outlet of the heat dissipation base plate, the total water output pressure of the heat dissipation pump, and the total water output flow rate.

[0151] The first calculation submodule is used to calculate the total water input flow rate of the heat dissipation base plate based on the water flow velocity and the cross-sectional area of ​​the outlet at each heat dissipation point.

[0152] The second calculation submodule is used to calculate the total water input pressure of the heat dissipation base plate based on the water flow pressure at each heat dissipation point;

[0153] The first drawing submodule is used to draw the first flow characteristic curve of the heat dissipation base plate based on the total water input pressure and total water input flow rate of the heat dissipation base plate.

[0154] The second plotting submodule is used to plot the second flow characteristic curve of the cooling pump based on the total water output pressure and total water output flow of the cooling pump.

[0155] The second acquisition submodule is used to acquire the intersection point between the first flow characteristic curve and the second flow characteristic curve, and use the curve intersection point as the target operating point of the heat dissipation base plate and the heat pump.

[0156] The third calculation submodule is used to calculate the target evaluation temperature of the heat dissipation base plate corresponding to the target operating point based on the temperature field distribution function.

[0157] In some alternative implementations, the target evaluation temperature of the heat dissipation base plate corresponding to the target operating point is calculated based on the temperature field distribution function using the above formula (6).

[0158] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0159] In this embodiment, the device for optimizing the layout rules of the heat dissipation base plate is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit), a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0160] This invention also provides a computer device having the above-described optimized heat dissipation base plate layout rules.

[0161] Please see Figure 14 , Figure 14 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 14 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 14 Take a processor 10 as an example.

[0162] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GPA), or any combination thereof.

[0163] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0164] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0165] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0166] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0167] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0168] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0169] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for optimizing a heat spreader floor layout rule, the method comprising: determining a heat spreader floor layout rule; and optimizing the heat spreader floor layout rule. The method comprises: Based on the preset layout rule of the plurality of elliptical regions of the heat dissipation bottom plate, a target layout rule of the plurality of elliptical regions is generated by randomly changing a plurality of layout parameters; According to the target layout rule, a plurality of heat dissipation points are arranged in each elliptical region, and the flow velocity field distribution function of each heat dissipation point is calculated by using the lattice Boltzmann method and the large eddy simulation method; Based on the flow velocity field distribution function of each heat dissipation point, the water flow velocity and the water flow pressure of each heat dissipation point are calculated; Based on the flow velocity field distribution function of each heat dissipation point, the water flow velocity and the water flow pressure of each heat dissipation point, the target evaluation temperature of the heat dissipation bottom plate is calculated; The target evaluation temperature is taken as the initial value of the preset optimization algorithm, and the target layout rule of the plurality of elliptical regions is gradually iteratively optimized until the target evaluation temperature meets the preset optimization requirement, the iteration is stopped, and the target layout rule of the plurality of elliptical regions corresponding to the optimal result is output, if the target evaluation temperature does not meet the preset requirement, the step of generating the target layout rule of the plurality of elliptical regions by randomly changing the plurality of layout parameters based on the preset layout rule of the plurality of elliptical regions of the heat dissipation bottom plate is returned until the target evaluation temperature meets the preset requirement.

2. The method of claim 1, wherein, According to the target layout rule, the plurality of heat dissipation points are arranged in each elliptical region, and the flow velocity field distribution function of each heat dissipation point is calculated by using the lattice Boltzmann method and the large eddy simulation method, comprising: According to the target layout rule, the plurality of heat dissipation points are arranged in each elliptical region, and the layout scheme of the heat dissipation bottom plate is generated; The flow velocity field distribution function of each heat dissipation point in the collision process and the flow process is calculated by using the lattice Boltzmann method and the large eddy simulation method; Based on the flow velocity field distribution function of each heat dissipation point in the collision process and the flow process, the flow velocity field distribution function of the boundary heat dissipation point of each elliptical region is calculated.

3. The method of claim 2, wherein, The flow velocity field distribution function of each heat dissipation point in the collision process and the flow process is calculated by the following formula: wherein f k is the flow velocity field distribution function of the heat dissipation point x at any place of the each elliptical region at time t, is the flow velocity field equilibrium distribution function of the heat dissipation point x at any place of the each elliptical region at time t, k is the multiple flow velocity directions of each heat dissipation point in the each elliptical region, τ is the relaxation time, according to the vortex viscosity model in the large eddy simulation mode, τ is, v0 is the kinematic viscosity is the eddy viscosity, C is a constant, Δ is the filter size, is the norm of the strain rate tensor.

4. The method of claim 3, wherein, Based on the flow velocity field distribution function of each heat dissipation point in the collision process and the flow process, the flow velocity field distribution function of the boundary heat dissipation point of each elliptical region is calculated by the following formula: According to q the size of each elliptical region can be obtained within the boundary of the heat point x s the flow field distribution function of the flow rate where x w is the boundary heat point of the each elliptical region, x s is the nearest heat point inside the each elliptical region to the boundary heat point x w is the nearest heat point outside the each elliptical region to the boundary heat point x f is the nearest heat point outside the each elliptical region to x w is the nearest heat point outside the each elliptical region to x ff is the nearest heat point outside the each elliptical region to x f is the nearest heat point outside the each elliptical region to x f is the nearest heat point outside the each elliptical region to x f is the nearest heat point outside the each elliptical region to x k is an intermediate parameter, f s '(x w , t) is the nearest heat point inside the each elliptical region to the boundary heat point x s at time t.

5. The method of claim 1, wherein, Based on the flow velocity field distribution function of each heat dissipation point, the water flow velocity and the water flow pressure of each heat dissipation point are calculated by the following formula: wherein c k is the unit flow rate of each heat dissipation point in each elliptical region, u is the water flow velocity of each heat dissipation point in each elliptical region, p is the water flow pressure of each heat dissipation point in each elliptical region, f k is the flow rate field distribution function of the heat dissipation point x at any place in the elliptical region at time t.

6. The method of claim 1, wherein, Based on the flow velocity field distribution function of each heat dissipation point, the water flow velocity and the water flow pressure of each heat dissipation point, the target evaluation temperature of the heat dissipation bottom plate is calculated, comprising: The water outlet cross-sectional area of the heat dissipation bottom plate, the water flow output total pressure and the water flow total output flow of the heat dissipation pump are obtained; Based on the water flow velocity of each heat dissipation point and the water outlet cross-sectional area, the water flow total input flow of the heat dissipation bottom plate is calculated; Based on the water flow pressure of each heat dissipation point, the water flow input total pressure of the heat dissipation bottom plate is calculated; Based on the water flow input total pressure and the water flow total input flow of the heat dissipation bottom plate, the first flow characteristic curve of the heat dissipation bottom plate is drawn; Based on the water flow output total pressure and the water flow total output flow of the heat dissipation pump, the second flow characteristic curve of the heat dissipation pump is drawn; An intersection point between the first flow characteristic curve and the second flow characteristic curve is obtained, and the intersection point is taken as a target working point of the heat dissipation base plate and the heat dissipation pump; A target evaluation temperature of the heat dissipation base plate corresponding to the target working point is calculated based on a temperature field distribution function.

7. The method of claim 6, wherein, The target evaluation temperature of the heat dissipation base plate corresponding to the target working point is calculated based on a temperature field distribution function, and is executed by the following formula: wherein g k is a temperature field distribution function at time t at x, k is a plurality of flow velocity directions of each heat dissipation point in each elliptical region, τ is a relaxation time, c k is a unit flow velocity of each heat dissipation point in each elliptical region, c s is a lattice sound speed in a lattice Boltzmann method, u is a water flow velocity of each heat dissipation point in each elliptical region, T is a target evaluation temperature of the heat dissipation base plate corresponding to a target working point, w k is a lattice model weight in the lattice Boltzmann method, Δx is a distance of adjacent heat dissipation points, and Δt is a time advancement interval of each simulation by the lattice Boltzmann method.

8. An optimization device for the layout regularity of a heat dissipation base plate, characterized in that, The device comprises: A layout rule generation module is configured to generate a target layout rule of a plurality of elliptical regions of a heat dissipation base plate by randomly changing a plurality of layout parameters based on a preset layout rule of the plurality of elliptical regions of the heat dissipation base plate; A flow velocity distribution calculation module is configured to arrange a plurality of heat dissipation points in each elliptical region according to the target layout rule, and to calculate a flow velocity field distribution function of each heat dissipation point by using a lattice Boltzmann method and a large eddy simulation method; A water flow parameter calculation module is configured to calculate a water flow velocity and a water flow pressure of each heat dissipation point based on the flow velocity field distribution function of each heat dissipation point; An evaluation temperature calculation module is configured to calculate a target evaluation temperature of the heat dissipation base plate based on the flow velocity field distribution function of each heat dissipation point, the water flow velocity and the water flow pressure of each heat dissipation point; A layout rule optimization module is configured to take the target evaluation temperature as an initial value of a preset optimization algorithm, to gradually and iteratively optimize the target layout rule of the plurality of elliptical regions until the target evaluation temperature meets a preset optimization requirement, to stop iteration, and to output a target layout rule of the plurality of elliptical regions corresponding to an optimal result, and to return to the step of generating the target layout rule of the plurality of elliptical regions by randomly changing the plurality of layout parameters based on the preset layout rule of the plurality of elliptical regions of the heat dissipation base plate if the target evaluation temperature does not meet the preset requirement, until the target evaluation temperature meets the preset requirement.

9. A computer device, comprising: Comprise: A memory and a processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the optimization method of the layout rule of the heat dissipation base plate according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions, and the computer instructions are used to make a computer execute the optimization method of the layout rule of the heat dissipation base plate according to any one of claims 1 to 7.

11. A computer program product, characterised in that, The computer instructions are used to make a computer execute the optimization method of the layout rule of the heat dissipation base plate according to any one of claims 1 to 7.

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