Setting method of runner structure and electronic equipment

Abstract

The invention provides a flow channel structure setting method which can be applied to the field of liquid cooling plate design and comprises the steps that a two-dimensional conjugate heat transfer-laminar flow rectangular topological optimization model is constructed, and the two-dimensional conjugate heat transfer-laminar flow rectangular topological optimization model describes heat transfer of a heat source received by a liquid cooling plate; cooling liquid flows in a flow channel of a to-be-optimized rectangular area in the liquid cooling plate, the water temperature is increased due to heat absorption, then the change of the flow speed is influenced by the increase of the water temperature, and the change of the flow speed also influences the process of the flowing state of the cooling liquid; setting constraint conditions of the two-dimensional conjugate heat transfer-laminar rectangular topological optimization model, wherein the constraint conditions comprise volume fraction constraint conditions; and in combination with constraint conditions, multi-objective optimization is carried out on the flow channel of the to-be-optimized rectangular area, and multiple objectives comprise maximization of heat transfer efficiency of the liquid cooling plate and minimization of pressure drop at the inlet and the outlet of the flow channel. The invention further provides electronic equipment, a storage medium and a program product.

Description

Technical Field

[0001] This application relates to the field of liquid cooling plate design, specifically to a method for setting up a flow channel structure and an electronic device. Background Technology

[0002] Power batteries continuously generate heat during charging and discharging, and liquid cooling plates are widely used due to their strong heat exchange capacity and good temperature control uniformity. However, existing liquid cooling plate flow channel structures mostly rely on empirical serpentine, parallel straight channel, or a small number of parametric channel designs, which often make it difficult to simultaneously achieve "low temperature rise / high uniformity" and "low pressure drop / low pump power". When the heat source is non-uniform or the cooling plate area is limited, problems such as uneven flow distribution, dead zones, and concentrated hot spots can easily occur, resulting in large maximum temperatures and temperature variances, and increased pump power.

[0003] Tesla valves utilize asymmetric backflow paths to exhibit varying flow resistances under different flow directions, enabling them to enhance heat transfer through disturbance and mixing. However, traditional Tesla valves often have fixed geometries or only minor parametric variations. When directly applied to liquid cooling plates, they may encounter problems such as large local losses at branch / merge points, dead zones caused by local backflow stagnation, high overall pressure drop, and difficulty in adaptively generating curved transition details for specific operating conditions. Existing parameter optimization methods typically search only within a limited geometric parameter space, easily getting trapped in local optima, and struggle to generate complex yet manufacturable channel networks, further limiting the potential for pressure drop reduction and temperature uniformity improvement. Summary of the Invention

[0004] In view of the above problems, this application provides a method for setting up a flow channel structure and an electronic device.

[0005] According to a first aspect of this application, a method for setting up a flow channel structure is provided. The method includes constructing a two-dimensional conjugate heat transfer-laminar flow rectangular topology optimization model, wherein the two-dimensional conjugate heat transfer-laminar flow rectangular topology optimization model describes the heat transfer of a liquid cooling plate receiving a heat source, and the coolant flowing in the flow channel of the rectangular region to be optimized in the liquid cooling plate. Due to the absorption of heat, the water temperature rises, and the rise in water temperature subsequently affects the flow velocity, which in turn affects the flow state of the coolant. Constraints are set for the two-dimensional conjugate heat transfer-laminar flow rectangular topology optimization model, including volume fraction constraints. Based on the constraints, multi-objective optimization is performed on the flow channel of the rectangular region to be optimized. The multi-objectives include maximizing the heat transfer efficiency of the liquid cooling plate and minimizing the pressure drop at the inlet and outlet of the flow channel when the heat transfer process and the flow velocity change process of the two-dimensional conjugate heat transfer-laminar flow rectangular topology optimization model are balanced.

[0006] According to embodiments of this application, the volume fraction constraint includes: , in, To design the values ​​of variables, For the design domain, This represents the initial flow channel fraction.

[0007] According to embodiments of this application, the flow channel structure obtained through multi-objective optimization should have a flow splitting zone, a main flow channel, a secondary flow channel, and a return flow confluence zone.

[0008] According to an embodiment of this application, in conjunction with the constraints, multi-objective optimization of the flow channel in the rectangular region to be optimized includes: setting variables of the minimum design unit within the rectangular region to be optimized, wherein the values ​​of the variables include fluid domain and solid domain; setting the Tesla valve unit configuration as the initial variable distribution, and performing multi-objective optimization.

[0009] According to an embodiment of this application, setting the Tesla valve unit configuration as the initial variable distribution and performing multi-objective optimization includes: performing Helmholtz density filtering and hyperbolic tangent projection on the first variable distribution obtained during multi-objective optimization to obtain a second variable distribution.

[0010] According to an embodiment of this application, the method further includes: setting parameters for the smallest design unit within the rectangular region to be optimized, based on the values ​​of the smallest design unit, the parameters including reverse osmosis rate, thermal conductivity, density, and heat capacity; and using the finite element method to determine the temperature distribution of the liquid cooling plate and the coolant flow of the flow channel structure based on the smallest design unit with set parameters in the region to be optimized and the value distribution of the smallest design unit.

[0011] According to an embodiment of this application, setting the Tesla valve unit configuration as the initial variable distribution and performing multi-objective optimization further includes: determining the heat transfer efficiency of the liquid cooling plate and the pressure drop at the inlet and outlet of the flow channel based on the temperature distribution of the liquid cooling plate and the coolant flow of the flow channel structure; modifying the second variable distribution at least once to obtain a third variable distribution, so that the heat transfer efficiency and pressure drop corresponding to the third variable distribution reach the optimal values.

[0012] A second aspect of this application provides an electronic device, comprising: one or more processors; and a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the method described above.

[0013] A third aspect of this application also provides a computer-readable storage medium having a computer program or instructions stored thereon, which, when executed by a processor, implement the steps of the above-described method.

[0014] A fourth aspect of this application also provides a computer program product, including a computer program or instructions that, when executed by a processor, implement the steps of the above-described method.

[0015] Compared with the prior art, the technical solution provided in this application has at least the following beneficial technical effects: 1. This application adopts a conjugate heat transfer-flow coupling model and performs multi-objective optimization. During the optimization process, the heat transfer performance of the liquid cooling plate and the pressure drop at the inlet and outlet of the flow channel are considered simultaneously. This is beneficial to balance heat dissipation capacity and pump power requirements under laminar flow conditions, thereby improving the engineering applicability of the liquid cooling plate structure.

[0016] 2. Compared with traditional geometric parameter optimization which has strong locality, the topology optimization used in this application has globality and objectivity, and the optimization effect is better than that of traditional optimization methods.

[0017] 3. Compared with topology optimization without initial configuration, this application uses a Tesla valve with high heat transfer as the initial configuration, which ensures the rationality of the optimization results.

[0018] 4. Compared with the unoptimized configuration, the positive optimization results of this application show a 79% reduction in inlet pressure drop, a 1.1-degree reduction in average surface temperature, and a 0.8-degree reduction in maximum surface temperature. Attached Figure Description

[0019] The above-mentioned contents, other objects, features and advantages of this application will become clearer from the following description of embodiments with reference to the accompanying drawings, in which: Figure 1 A flowchart illustrating a method for setting a flow channel structure according to an embodiment of this application is shown schematically. Figure 2 A schematic diagram of a liquid cooling plate substrate according to an embodiment of this application is shown. Figure 3 A schematic diagram of the rectangular region to be optimized according to an embodiment of this application is shown; Figure 4 The schematic diagram illustrates the main flow channel, secondary flow channel, diversion zone, and return flow confluence zone according to an embodiment of this application; Figure 5 A schematic diagram illustrating the initial Tesla valve structure parameters according to an embodiment of this application is shown. Figure 6a This schematic diagram illustrates a two-dimensional structure after forward optimization according to an embodiment of this application. Figure 6b This illustration schematically shows a two-dimensional structure after reverse optimization according to an embodiment of this application; Figure 7a This schematically illustrates a surface temperature before forward optimization according to an embodiment of this application; Figure 7b This schematically illustrates a surface temperature after forward optimization according to an embodiment of this application; Figure 7cA schematic diagram illustrating the surface temperature before reverse optimization according to an embodiment of this application is shown. Figure 7d This schematic diagram illustrates the surface temperature after reverse optimization according to an embodiment of this application. Figure 8 The diagram illustrates a comparison of performance indicators for different structures before and after optimization. Figure 9 The diagram illustrates the mesh independence test data for the 3D model. Detailed Implementation

[0020] The embodiments of this application will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of this application. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of this application for ease of explanation. However, it will be apparent that one or more embodiments may be implemented without these specific details. Furthermore, descriptions of well-known structures and technologies are omitted in the following description to avoid unnecessarily obscuring the concepts of this application.

[0021] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0022] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0023] Figure 1 A flowchart illustrating a method for setting up a flow channel structure according to an embodiment of this application is shown schematically; as follows: Figure 1 As shown, step 110 is executed first to construct a two-dimensional conjugate heat transfer-laminar flow rectangular topology optimization model. The two-dimensional conjugate heat transfer-laminar flow rectangular topology optimization model describes the heat transfer of the liquid cooling plate receiving the heat source. The coolant flows in the flow channel of the rectangular region to be optimized in the liquid cooling plate. The water temperature rises due to the absorption of heat. Subsequently, the rise in water temperature affects the flow velocity, and the flow velocity change affects the flow state of the coolant.

[0024] According to one embodiment, the liquid cooling plate is made of aluminum alloy as the substrate material and water as the cooling medium. The liquid cooling plate can be configured with heat flux or bulk heat source according to the heat source distribution of the battery module, and forms a circulation loop with external pumps and heat exchangers.

[0025] Figure 2A schematic diagram of a liquid cooling plate substrate according to an embodiment of this application is shown, such as... Figure 2 As shown, a cooling channel is formed within the liquid-cooled plate substrate 210. The cooling channel includes an inlet section, an outlet section, and a Tesla-like valve unit located therebetween. The liquid-cooled plate substrate material is aluminum or aluminum alloy; the cooling medium is water; the channel cross-section is rectangular; the channel thickness is 2–5 mm, and the wall thickness is 1–3 mm. The Tesla-like valve units are arranged in series along the flow direction and / or in parallel perpendicular to the flow direction within the liquid-cooled plate.

[0026] The design domain of the two-dimensional conjugate heat transfer-flow model is a planar rectangle, with the inlet / outlet being a rectangular segment outside the design domain. The inlet velocity is 0.015 m / s, and the outlet pressure is set to 0. The plate thickness is 10 mm. A surface heat source of 1000 W / m is applied to the design domain. 2 .

[0027] A two-dimensional conjugate heat transfer-flow model is used to accurately calculate the flow and heat dissipation of coolant within the channels of a liquid cooling plate. The two-dimensional aspect means that the thickness of the liquid cooling plate is not ignored (it can be as thin as 10mm), but rather it is treated as a thin sheet for calculation. This means that only the water flow and heat dissipation within the "length × width" plane are considered, ignoring minor differences in the thickness direction (such as temperature and velocity differences across the thickness). The aim is to simplify the calculations without affecting the core results (the heat dissipation and resistance of the liquid cooling plate are mainly determined by the shape of the channels within the plane).

[0028] Flow refers to the movement of coolant in the flow channel of a Tesla-like valve. The flow model addresses the water velocity; the generation of vortices in the flow channel (e.g., whether the water in the secondary flow channel will swirl); and the pressure drop of the water from the inlet to the outlet. Flow refers to the flow of coolant, which directly affects the pump consumption of the liquid cooling plate. In this application, the Reynolds number Re for laminar flow conditions is in the range of 50 to 500, preferably Re is about 225.

[0029] The heat transfer model calculates the heat removal process, how the generated heat (e.g., 1000W / m²) is transferred to the aluminum alloy wall of the liquid cooling plate; how the heat on the wall is transferred to the water flow; the temperature rise after the water flow removes the heat; and whether there are hot spots on the surface of the liquid cooling plate. These heat transfer processes are related to the "heat dissipation effect" of the liquid cooling plate. Flow and heat transfer are not calculated separately, but rather they correct each other: where the water flows fast, heat dissipation is fast, and the water temperature rises slowly; where the water temperature rises slowly, the viscosity of the water does not decrease, and the flow velocity does not increase; where there are vortices in the flow channel, the water flow and the wall have more contact, resulting in better heat dissipation, and the vortex intensity will slightly change after the water temperature rises; until the two reach equilibrium, the calculated "temperature distribution" and "pressure drop" are the results under the actual working conditions.

[0030] The two-dimensional conjugate heat transfer-flow model serves as the "foundation for channel optimization." This application first determines the initial Tesla valve channel (with a main channel and a secondary channel) in the model; inputs actual operating parameters: water density / viscosity, thermal conductivity of the liquid cooling plate, heat generation of the battery, and inlet water velocity; the model automatically calculates the velocity distribution and vortex position of the water flow in the channel, as well as the temperature distribution of the liquid cooling plate and the inlet and outlet pressure drop; then, based on the calculation results, the channel shape is adjusted (e.g., changing the split point to a curve, optimizing the length of the secondary channel), and the calculation is repeated; this process is iterated repeatedly until the optimal channel with "lowest temperature, smallest pressure drop, and no dead water zone" is found.

[0031] The advantages of using a two-dimensional conjugate heat transfer-flow model are as follows: If only the flow process is calculated without considering the heat transfer process, it's impossible to know where the heat dissipation is poor in the flow channel. The optimized flow channel may have hot spots, and the battery will still overheat. If only "heat transfer" is calculated without "flow," water flow resistance is ignored, and the designed flow channel may have too much resistance, preventing the pump from moving the water and causing the cooling system to fail directly. If the conjugate process is not considered, assuming a fixed flow velocity for heat dissipation calculation or a fixed temperature for resistance calculation will yield unreliable results. In reality, water temperature affects flow velocity, and flow velocity affects heat dissipation; calculating them separately will lead to incorrect optimization direction. Using a "three-dimensional model" would result in an excessive amount of computation. The core value of the model lies in its accuracy and efficiency. The two-dimensional model simplifies the computation, and the conjugate calculation method ensures the accuracy of the results. Ultimately, it provides reliable data for the optimization of "Tesla-like valve flow channels," ensuring that the designed liquid cooling plate can truly meet the heat dissipation requirements of new energy vehicle batteries.

[0032] Subsequently, step 120 is executed to set the constraints of the two-dimensional conjugate heat transfer-laminar rectangular topology optimization model, including volume fraction constraints.

[0033] Volume fraction constraints include: , in, The design area (design domain) of the entire liquid cooling plate is, in this application, a rectangular area to be optimized, such as a rectangle of 100mm × 50mm. The smallest design unit in the design area, such as a "micro-grid" (e.g., 1mm x 1mm). The design variable can be set to a value (e.g., 1 for a fluid domain and 0 for a solid domain). The sum of all "fluid domain lattices" → total area / total volume of the flow channel; The sum of all grid cells → total area / total volume of the liquid cooling plate; The volume fraction threshold can be set as the initial flow channel fraction (0.417 in this application), ensuring that the proportion of the flow channel to the liquid cooling plate does not exceed [a certain threshold]. This avoids excessive flow channels that could lead to insufficient strength and water leakage in the aluminum plate.

[0034] Figure 3 A schematic diagram of the rectangular region to be optimized according to an embodiment of this application is shown.

[0035] According to one implementation, the flow channel structure obtained by multi-objective optimization should have a flow splitting zone, a main flow channel, a secondary flow channel, and a return flow confluence zone; the flow channel structure can be specifically implemented as a Tesla valve-like structure.

[0036] Figure 4 A schematic diagram illustrating the main flow channel, secondary flow channel, branching zone, and return flow confluence zone according to an embodiment of this application is provided. Figure 4 As shown, when the coolant flows through the entire flow channel structure, it can first flow through the diversion zone 410, and then split into two parts. One part flows into the main flow channel 420, and the other part flows into the secondary flow channel 430. Finally, the coolant in the main flow channel 420 and the secondary flow channel 430 merge in the return flow confluence zone 440.

[0037] Finally, step 130 is executed. Based on the constraints, multi-objective optimization is performed on the flow channel within the rectangular region to be optimized. The multi-objectives include maximizing the heat transfer efficiency of the liquid cooler and minimizing the pressure drop at the inlet and outlet of the flow channel while balancing the heat transfer process and velocity variation process in the two-dimensional conjugate heat transfer-laminar rectangular topology optimization model. The heat transfer efficiency of the liquid cooler can be represented by the average temperature of the design domain.

[0038] According to one implementation, this application also provides a multi-objective optimization function, specifically implemented as a multi-objective weighted optimization function: ; in, and The weighting factor can be 0.65 or 0.35. For the design domain normalized average temperature integral, The pressure drop difference between the inlet and outlet. To optimize the objective; , , in For temperature, For temperature variables, For inlet temperature, For the initial temperature, For pressure reduction, For the entrance boundary, For export borders, , The initial value of the target is used for normalization to optimize it.

[0039] According to one implementation, multi-objective optimization of the flow channel in the rectangular region to be optimized, in conjunction with constraints, includes: setting variables of the minimum design unit within the rectangular region to be optimized, the values ​​of which include fluid domain and solid domain; setting the Tesla valve unit configuration as the initial variable distribution; and performing multi-objective optimization.

[0040] According to one implementation method, design variables are defined. , Represents fluid domain, Representing the solid domain; mapping the initial configuration of the Tesla valve unit to the distribution of initial design variables. .

[0041] Figure 5 The diagram illustrates the initial Tesla valve structure parameters according to an embodiment of this application. This application can optimize the aforementioned initial Tesla valve structure.

[0042] According to one implementation, setting the Tesla valve unit configuration as the initial variable distribution and performing multi-objective optimization includes: using the first variable distribution obtained during multi-objective optimization. The distribution of the second variable is obtained by performing Helmholtz density filtering and hyperbolic tangent projection. .

[0043] Specifically, we can first analyze the distribution of the first variable. Helmholtz density filtering is used to obtain the distribution of intermediate variables. .

[0044] , in The grid filter radius, This is the gradient operator.

[0045] Subsequently, the distribution of intermediate variables was analyzed. The distribution of the second variable is obtained by performing hyperbolic tangent projection. .

[0046] , Hyperbolic tangent projection makes the flow channel boundaries clearer, such as >0.5 is set to approximately equal to 1 (fluid domain); <0.5 is set to approximately equal to 0 (solid domain). It refers to the hyperbolic tangent function.

[0047] in For the grid filter radius, The projection slope, The projection base point can be taken as: =2mm, =8, =0.5. The core logic of Helmholtz density filtering is to sweep a circle with a radius of 2mm across the design domain, smoothing out channels thinner than 2mm and sharp burrs, ensuring a minimum channel width ≥ 2mm. The effect is, for example, on a certain grid... (Approaching solid), but surrounded by... (Approaching a fluid) will cause it to The value was revised to 0.8 to avoid abrupt, unsightly fine details.

[0048] According to one embodiment, the minimum design unit within the rectangular area to be optimized is further configured with parameters including reverse osmosis rate, thermal conductivity, density, and heat capacity. Based on the minimum design unit with configured parameters in the area to be optimized and the value distribution of the minimum design unit, the temperature distribution of the liquid cooling plate and the coolant flow of the flow channel structure are determined using the finite element method.

[0049] After each solution The distribution of physical fields such as temperature and velocity is obtained by using the interpolation equations of physical properties such as reverse osmosis and thermal conductivity through the finite element method. , For reverse osmosis rate, This is the maximum value of the volume force. As the Darcy penalty factor, and Can be taken as and .

[0050] , k is the thermal conductivity. , , , , These are thermal conductivity, density, and heat capacity, respectively, with subscripts. Indicates physical properties belonging to solids, subscript Indicates physical properties belonging to fluids, such as Indicates the thermal conductivity of a solid. This represents the thermal conductivity of the fluid. It can be taken as... , , , , , ; , These are the penalty factors for each property, used to push the variable distribution towards 0 / 1 and reduce intermediate values; they can be taken as follows: , , .

[0051] When calculating the physical field using the finite element method, the design domain is decomposed into countless tiny grids (i.e., the smallest design unit). For each grid, the four properties mentioned above are substituted, and combined with operating parameters (including inlet velocity and heat source), the "temperature" and "flow velocity" of each grid are calculated. The output results include: temperature distribution: where the hotspots are (maximum temperature T). max ), average temperature T ave Temperature variance T σ (The smaller the value, the more uniform the flow); Flow distribution: where the water flows fast, where there are eddies, inlet-outlet pressure drop ΔP (resistance magnitude).

[0052] According to one embodiment, the heat transfer efficiency of the liquid cooling plate and the pressure drop at the inlet and outlet of the flow channel are determined based on the temperature distribution of the liquid cooling plate and the coolant flow of the flow channel structure; the second variable distribution is modified at least once to obtain a third variable distribution, so that the heat transfer efficiency and pressure drop corresponding to the third variable distribution reach the optimal values.

[0053] According to one implementation, this application can use the conjugate gradient descent algorithm, based on the calculated T... max T ave ΔP automatically adjusts each grid. Value. The optimization logic is to calculate the total score of the current flow path. The algorithm adjusts automatically. (For example, changing the flow channel in hotspot areas to a curve to enhance turbulence; widening the flow channel in areas with high resistance); repeat the steps of filtering projections, assigning values, calculating, and adjusting. ,until Reduce to the minimum (convergence), or reach the maximum number of iterations.

[0054] According to one embodiment, this application sets forward and reverse operating conditions for the same Tesla valve unit design domain, taking into account the huge difference between its forward and reverse flow. The forward operating condition includes coolant input from the forward direction, and the reverse operating condition includes coolant input from the reverse direction. Figure 6a This schematic diagram illustrates a two-dimensional structure after forward optimization according to an embodiment of this application. Figure 6b The schematic diagram illustrates a two-dimensional structure after reverse optimization according to an embodiment of this application.

[0055] According to one implementation, the final design domain variable distribution is projected using a 0 / 1 bound at 0.5 to extract a two-dimensional CAD file. Further three-dimensional steady-state / transient conjugate heat transfer verification and mesh independence testing can then be performed.

[0056] In an example operating condition, the cooling medium is water (density approximately 1000 kg / m³, dynamic viscosity approximately 0.001 Pa·s, thermal conductivity approximately 0.6 W / (m·K), specific heat approximately 4200 J / (kg·K)), the thermal conductivity of the solid matrix material can be taken as approximately 170 W / (m·K); the inlet velocity can be taken as 0.015 m / s; the plate thickness is 10 mm; the heat source can be equivalent to an area heat flux of approximately 1000 W / m²; the filter radius is 2 mm; the projection slope β=8; and the temperature and pressure drop weights are w_T=0.35 and w_P=0.65, respectively. For the three-dimensional model, the channel thickness is taken as 3 mm and the wall thickness as 2 mm.

[0057] Figure 7a This schematically illustrates a surface temperature before forward optimization according to an embodiment of this application; Figure 7b This schematically illustrates a surface temperature after forward optimization according to an embodiment of this application; Figure 7c A schematic diagram illustrating the surface temperature before reverse optimization according to an embodiment of this application is shown. Figure 7d A schematic diagram of the surface temperature after reverse optimization according to an embodiment of this application is shown.

[0058] Figure 8 A schematic diagram illustrating the performance comparison of different structures before and after optimization is provided. , , ΔP and ΔP represent the highest surface temperature, the average surface temperature, the surface temperature variance, and the inlet / outlet pressure drop, respectively.

[0059] Figure 9 The diagram illustrates the mesh independence test data of the 3D model. The optimized diversion zone and recirculation confluence zone are transitioned with a quasi-curved transition to reduce local losses and weaken stagnant areas. The design method in this application is based on density-based topology optimization. Within the design domain, the fluid / solid distribution is characterized by the design variable θ. Clear boundaries are obtained through density filtering and projection, and the Darcy penalty term of volume force is combined to characterize the high blockage in the solid region. A weighted objective function containing the average temperature of the design domain and the pressure drop difference between the inlet and outlet is constructed, and the optimized Tesla valve unit flow channel topology is obtained by iterative solution under volume fraction constraints. This structure and method can achieve simultaneous reductions in pressure drop, average temperature, maximum temperature, and temperature variance under the same flow rate and heat dissipation area, and is suitable for thermal management scenarios such as liquid cooling plates for power batteries.

[0060] This application provides a liquid-cooled plate flow channel structure and its design method based on Tesla valve unit topology optimization. By introducing density-type topology optimization (combining filtration-projection and Darcy penalty) within the Tesla valve unit, temperature and pressure drop indices are synergistically optimized under given constraints. This results in a valve body flow channel that exhibits both low pressure drop and good heat transfer / temperature uniformity under a preset working flow direction. Beneficial effects include: using the Tesla valve unit itself as the topology optimization object, it can automatically generate curved flow splitting / merging details while maintaining the mechanism framework of "main-sub-channel splitting, return flow re-merging," reducing local losses; through the weighted construction of temperature and pressure drop targets, it can achieve synergistic optimization of heat dissipation and resistance; the use of filtration and projection strategies improves the clarity of flow channel boundaries and enhances manufacturability; under the example conditions, the optimized structure can significantly reduce pressure drop and improve temperature field distribution. Optimization and selective output for forward and reverse operating conditions can achieve better overall temperature-pressure drop performance under different flow direction requirements. It should be noted that the storage medium (computer-readable medium) described above in this invention can be a computer-readable signal medium, a non-transitory computer-readable storage medium, or any combination thereof. A non-transitory computer-readable storage medium can be, for example,, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a non-transitory computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0061] In this invention, a non-transitory computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can also be any computer-readable medium other than a non-transitory computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination thereof.

[0062] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0063] The above description is merely a partial embodiment of the present invention and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of disclosure in this invention is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-disclosed concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this invention.

[0064] Furthermore, although the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in sequential order. Multitasking and parallel processing may be advantageous in certain environments. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the invention. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0065] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.

Claims

1. A method for setting up a flow channel structure, the method comprising: A two-dimensional conjugate heat transfer-laminar flow rectangular topology optimization model is constructed. The two-dimensional conjugate heat transfer-laminar flow rectangular topology optimization model describes the heat transfer of the liquid cooling plate receiving the heat source. The coolant flows in the flow channel of the rectangular region to be optimized in the liquid cooling plate. The water temperature rises due to the absorption of heat. Subsequently, the rise in water temperature affects the change of flow velocity, and the change of flow velocity affects the flow state of the coolant. Set the constraints for the two-dimensional conjugate heat transfer-laminar rectangular topology optimization model, including volume fraction constraints. Based on the constraints, the flow channel of the rectangular region to be optimized is optimized in a multi-objective manner. The multi-objective includes maximizing the heat transfer efficiency of the liquid cooling plate and minimizing the pressure drop at the inlet and outlet of the flow channel when the heat transfer process and the flow velocity change process are balanced in the two-dimensional conjugate heat transfer-laminar flow rectangular topology optimization model.

2. The method as described in claim 1, wherein, The volume fraction constraint conditions include: ， in, To design the values ​​of variables, For the design domain, This represents the initial flow channel fraction.

3. The method as described in claim 1 or 2, wherein, The flow channel structure obtained by the multi-objective optimization should have a flow splitting zone, a main flow channel, a secondary flow channel, and a return flow confluence zone.

4. The method of claim 3, wherein, The multi-objective optimization of the flow channel in the rectangular region to be optimized, in conjunction with the aforementioned constraints, includes: Within the rectangular area to be optimized, set the variables of the smallest design unit, the values ​​of which include fluid domain and solid domain; Set the Tesla valve unit configuration as the initial variable distribution and perform multi-objective optimization.

5. The method of claim 4, wherein, The process of setting the Tesla valve unit configuration as the initial variable distribution and performing multi-objective optimization includes: The distribution of the first variable obtained during multi-objective optimization is subjected to Helmholtz density filtering and hyperbolic tangent projection to obtain the distribution of the second variable.

6. The method of claim 5, further comprising: For the smallest design unit within the rectangular region to be optimized, the parameters of the smallest design unit are set according to its values, including reverse osmosis rate, thermal conductivity, density, and heat capacity. The temperature distribution of the liquid cooling plate and the coolant flow of the flow channel structure are determined by the finite element method based on the minimum design unit with parameters set in the region to be optimized and the value distribution of the minimum design unit.

7. The method of claim 6, wherein setting the Tesla valve unit configuration as the initial variable distribution and performing multi-objective optimization further includes: The heat transfer efficiency of the liquid cooling plate and the pressure drop at the inlet and outlet of the flow channel are determined based on the temperature distribution of the liquid cooling plate and the coolant flow of the flow channel structure. The second variable distribution is modified at least once to obtain the third variable distribution, so that the heat transfer efficiency and pressure drop corresponding to the third variable distribution reach the optimal values.

8. An electronic device, comprising: One or more processors; Memory, used to store one or more computer programs. The characteristic feature is that the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1-7.

9. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, When the computer program or instructions are executed by a processor, they implement the steps of the method according to any one of claims 1-7.

10. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by a processor, they implement the steps of the method according to any one of claims 1-7.

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