A wireless charging system cooling optimization method

Abstract

The present application belongs to the field of wireless charging system heat dissipation, and particularly relates to a cooling optimization method for a wireless charging system. The present application establishes a two-dimensional thermal network composed of multiple heat transfer paths from the heat source to the environment for the wireless charging system. The traditional thermal resistance model only considers the copper material of the coil and the ferrite material of the magnetic core, and the degree of detail is limited, so it cannot accurately reflect the temperature of the heat generating components. The improved thermal model considers the main factors affecting heat conduction and dissipation such as potting material, thermal interface material and fluid state, thereby producing more accurate results while maintaining relatively low computational complexity, suitable for iterative thermal design and optimization algorithm implementation of the wireless charging system. The present application proposes a multi-objective thermal optimization method and process for a magnetic coupler based on the Pareto front, which considers temperature rise, weight and cost as objective functions, and helps the wireless charging system to achieve higher power density and lighter weight.

Description

Technical Field

[0001] This invention belongs to the field of heat dissipation in wireless charging systems, and specifically relates to a method for optimizing the cooling of wireless charging systems. Background Technology

[0002] Wireless power transfer technology, which achieves contactless energy transfer through magnetic field coupling, has garnered significant attention in recent years due to its convenience and safety, particularly in the field of wireless charging for electric vehicles. In the electrified transportation sector, the development trend of wireless chargers is towards higher power and power density; however, induced eddy current losses in magnetic components negatively impact the performance and reliability of chargers. In low-power applications, the thermal design of wireless charging systems requires less attention because the limited heat can be easily dissipated through air cooling. However, for high-power wireless charging systems with limited surface area and compact packaging, heat dissipation becomes a critical issue, necessitating greater focus on the thermal design and optimization of wireless charging systems.

[0003] There are two methods to obtain the temperature of the heat-generating components in a wireless charging system:

[0004] 1) Using the thermal network method to establish a thermal resistance model for analytical calculation has the advantage of being fast and direct. However, existing thermal resistance models have limited accuracy and cannot guide the thermal design of wireless charging systems.

[0005] 2) Use multiphysics coupling solutions based on numerical computation methods. This method is highly accurate, but time-consuming, especially during the optimization process where the computational cost is very high, and automatic optimization cannot be achieved. Summary of the Invention

[0006] This invention proposes a cooling optimization method for wireless charging systems to address the problems in existing technologies, such as the limited accuracy of thermal resistance models, which cannot guide the thermal design of wireless charging systems, and the high computational cost that prevents automatic optimization.

[0007] To achieve the above objectives, the present invention proposes the following technical solution:

[0008] A method for optimizing cooling in a wireless charging system includes the following steps:

[0009] Step 1: Establish a thermal resistance model of the magnetic coupler in the wireless charging system based on the TNM (Thermal Network Method) and quantify the thermal resistance value;

[0010] Step 2: Select cooling equipment based on the thermal resistance model and thermal resistance value obtained in Step 1. Set some parameters of the cooling equipment to fixed values, and determine the remaining parameters as design variables. Also, determine the value range and step size of each design variable.

[0011] Step 3: Obtain multiple design schemes by arranging and combining the values ​​of each design variable;

[0012] Step four: Determine the objective function for optimization;

[0013] Step 5: Plot the objective function values ​​corresponding to each design scheme with one objective function as the horizontal axis and the other objective functions as the vertical axis in turn. Use the Pareto front to select the optimal solution of all objective functions.

[0014] The optimal solution was selected as the cooling design scheme for the wireless charging system, thus completing the cooling optimization of the wireless charging system.

[0015] Preferably, in step one, the calculation formula for the thermal resistance of the magnetic coupler is:

[0016]

[0017] In the formula, the length of the heat conduction path is L. c The equivalent cross-sectional area is A, and the thermal conductivity of the material is k.

[0018] The calculation formula for the thermal convection resistance of a magnetic coupler is as follows:

[0019]

[0020] In the formula, A surf h represents the area of ​​the material exposed to the environment. conv It is the equivalent convective heat transfer coefficient.

[0021] Preferably, the thermal resistance model described in step one is:

[0022] R lw,hs-surf R pc R pt R fe,hs-surf R tp R ag R pt’ R lcp R lcp,cv Series;

[0023] Among them, R lw,hs-surf and R fe,hs-surf R represents the thermal resistance of conduction from the Litz wire hotspot to the surface and from the magnetic core hotspot to the surface, respectively. pc R pt The thermal resistance R of the potting material and the gold finger tape are respectively. ag R represents the conductive thermal resistance of the air gap. pt’ R represents the thermal resistance of the thermal pad. lcp R is the thermal resistance for conduction from the magnetic core to the coolant flow channel. lcp,cv This represents the convective thermal resistance between the magnetic core and the coolant.

[0024] Preferably, in step two, the fixed values ​​include coolant flow rate, liquid cooling plate size, and heat sink height.

[0025] Preferably, in step two, the design variables include the number of flow channels in the liquid cooling plate and the number of heat dissipation fins.

[0026] Preferably, in step four, the objective function corresponding to each design scheme includes the temperature rise Δt of the heating component, the system weight m, and the cost C.

[0027] Preferably, the input to the design scheme is the value of the design variable, and the output of the database is the objective function value.

[0028] Preferably, in step five, before plotting all results using any two objective functions as the horizontal and vertical axes, constraints are set, and data results that meet the constraints are selected for plotting.

[0029] Preferably, the constraints include design size limitations and pressure drop limitations.

[0030] The thermal resistance model proposed based on TNM can significantly reduce computation time. The established thermal resistance model has higher accuracy than traditional models and can also adapt to other coil types, core shapes and heat dissipation methods. After weighing multiple objectives, the Pareto front-based method finds the relatively optimal solution among thousands of schemes in the design space.

[0031] The proposed improved thermal model considers the main factors affecting heat conduction and dissipation, such as potting materials, thermal interface materials, and fluid states, thus producing more accurate results while maintaining relatively low computational complexity. It is suitable for iterative thermal design and optimization algorithm implementation of wireless charging systems. Attached Figure Description

[0032] The accompanying drawings, which form part of this specification, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0033] Figure 1 A schematic diagram of a cooling optimization method for a wireless charging system;

[0034] Figure 2 This is a schematic diagram of the cross-section of a magnetic coupler;

[0035] Figure 3 A schematic diagram of a refined thermal resistance model for a magnetic coupler;

[0036] Figure 4 A simplified schematic diagram of the thermal resistance model of the magnetic coupler;

[0037] Figure 5 This is a schematic diagram showing the fixed parameters and design variables of the liquid cooling plate.

[0038] Figure 6 Plot the results of the feasible solution.

[0039] In the diagram, 1 is the coil support, 2 is the hot melt adhesive, 3 is the Litz wire winding, 4 is the potting material, 5 is the magnetic core support, 6 is the thermal pad, 7 is the air gap, 8 is the gold finger tape, 9 is the magnetic core, 10 is the liquid cooling plate, and 11 is the liquid flow channel. Detailed Implementation

[0040] The present invention will now be described in detail with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0041] The following detailed description is exemplary and intended to provide further detailed explanation of the invention. Unless otherwise specified, all technical terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this invention is for describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention.

[0042] Example 1:

[0043] Please see Figure 1 As shown, the present invention provides a method for optimizing the cooling of a wireless charging system, which specifically includes the following steps:

[0044] As input to the flowchart, the magnetic coupling components have been designed previously, including the materials and dimensions of the Litz wire winding, magnetic core, and shielding plate.

[0045] Step one: Select a suitable cooling method for the wireless charging system and rationally arrange the positions of heat dissipation components (such as radiators, coolant channels, etc.). For example: If the magnetic coupler has a large heat dissipation volume and a small heat dissipation area, and can be connected to a liquid cooling circulation system, then choose liquid cooling, fix the magnetic core on a liquid cooling plate, and rationally design the diameter, number, and length of the coolant channels within the cooling plate. If the magnetic coupler has a small heat dissipation volume and a large heat dissipation area, air cooling can be selected, installing heat dissipation fins on the surface of heat-generating components (such as coils, magnetic cores, aluminum shielding plates), and rationally designing the height, number, and length of the fins.

[0046] The minimum dimensions required for coils of different power ratings vary under different cooling conditions, such as... Figure 6 As shown. For example, for a 60cm diameter coil using natural air cooling, its charging power is limited to 10kW; for a 30kW natural convection coil, its minimum size is 90cm. Therefore, liquid cooling / forced air cooling is necessary for coils of 20kW and above.

[0047] With the same power loss, a higher convective heat transfer coefficient requires a smaller coil size; if the size is insufficient, the coil is prone to overheating and damage. During the design process, the coil size, power rating, and heat dissipation can be considered using... Figure 6 Determine the cooling method qualitatively.

[0048] Step two involves selecting appropriate thermal interface materials, such as thermal pads or thermal grease, between the heat-generating components, such as windings, magnetic cores, and aluminum plates, to achieve insulation, high-temperature resistance, and better thermal conductivity.

[0049] Step 3: Calculate system losses. Use finite element simulation to obtain core losses and eddy current losses of the shielding plate, and use analytical models to calculate the losses of the Litz wire windings.

[0050] This step is used to estimate the heat generated when the magnetic coupler is working, and can be regarded as a parameter of the magnetic coupler.

[0051] Step 4: Analyze the heat transfer path, establish a thermal resistance model of the magnetic coupler, and quantify the thermal resistance value.

[0052] Heat transfer occurs through conduction, convection, and radiation. Radiation has little effect on the temperature rise of the magnetic coupler. Furthermore, the thermal resistance representing radiation is nonlinear, which complicates the calculations; therefore, only conduction and convection are considered. The thermal characteristics and behavior of the magnetic coupler can be represented by the equivalent thermal resistance R. th The following formula is used to represent this.

[0053] For heat conduction, if the length of the heat conduction path is L c If the equivalent cross-sectional area is A and the thermal conductivity of the material is k, then the corresponding thermal resistance formula is: It is important to note that the effective cross-sectional area for heat conduction is not equal to the cross-sectional area of ​​the material. When heat passes sequentially through two materials, if the cross-sectional areas and thermal conductivity of the two materials are different, it is recommended to multiply by an area correlation coefficient during calculation.

[0054] For heat convection, the formula for the thermal resistance between the material surface and the external environment is: Where Asurf is the exposed area of ​​the material to the environment, and hconv is the equivalent convective heat transfer coefficient, which is related to factors such as fluid type, flow state, and material shape.

[0055] According to the above formula, regardless of the structure or shape of the magnetic coupler, whether liquid cooling plates or heat sinks are chosen, or what thermal interface material is used, the equivalent thermal resistance of each material at each location can be calculated using the formula. In other words, the thermal network method is universal, but it is particularly suitable for magnetic couplers with regular shapes, simple structures, and uniform heat dissipation. Therefore, the following design case mainly uses a simple rectangular coil, fully-covered magnetic core, and liquid-cooled aluminum plate magnetic coupler to complete the multi-objective thermal optimization process.

[0056] The cross-section of the magnetic coupler in a wireless charging system is as follows: Figure 2 As shown. The liquid cooling plate 10 of this magnetic coupler serves to support, cool, and shield against magnetic leakage. Several liquid flow channels 11 are rationally arranged inside the liquid cooling plate. At the contact surface between the magnetic core 9 and the liquid cooling plate 10, there are gold finger tape 8, an air gap 7 that may be generated due to inversion, and a thermally conductive pad 6. The magnetic core support 5 serves to fix it. The Litz wire winding 3 is fixed to the coil support 1 using hot melt adhesive 2, and the coil support 1 is fixed to the magnetic core support 5 with screws. There is a potting material 4 between the Litz wire winding and the magnetic core. Among them, the gold finger tape 8, the thermally conductive pad 6, and the potting material 4 are thermally conductive interface materials, which have the characteristics of enhancing thermal conductivity, insulation, and high temperature resistance.

[0057] Existing analytical thermal models often only consider the copper material of the Litz wire winding, the core material, and the aluminum material of the shielding plate, neglecting the influence of the fixing bracket, thermal interface material, and coolant flow state in actual applications. Therefore, they cannot be directly used to calculate the temperature rise of the heat-generating components. The refined thermal resistance model proposed in this invention takes all of the above factors into account and establishes a two-dimensional thermal resistance network after analyzing the heat transfer path, such as... Figure 3 As shown. Where T coil It is the surface temperature of the Litz wire winding, T lw,hs It is the temperature of the hot spot inside the Leeds Line, T fe It is the surface temperature of the magnetic core, T fe,hs It is the temperature of the hot spot inside the magnetic core, T liquid It is the coolant temperature below the magnetic coupling component, T amb It is the ambient temperature. P winding P core and P al These represent coil loss, core loss, and eddy current loss of the aluminum plate, respectively. R cf and R cf,cv R represents the conductive thermal resistance of the coil holder and the convective thermal resistance with respect to the environment, respectively. ff and R ff,cv R represents the conductive thermal resistance of the magnetic core support and the convective thermal resistance with respect to the environment, respectively. lcp and R lcp,cv R represents the conductive thermal resistance from the magnetic core to the coolant flow channel and the convective thermal resistance with the coolant, respectively. hma R pc R pt R tp These represent the thermal resistance of hot melt adhesive, potting compound, gold finger tape, and thermal pad, respectively. lw,hs-surf and R fe,hs-surf These represent the thermal resistance conducted from the Litz wire hot spot to the surface and from the magnetic core hot spot to the surface, respectively.

[0058] R lw R represents the thermal resistance of the Litz line.pc R represents the thermal resistance of the potting material. pt R represents the thermal resistance of the gold finger tape. fe R represents the thermal resistance of the magnetic core. tp R represents the thermal resistance of the thermal pad. ag R represents the conductive thermal resistance of the air gap. pt’ R represents the thermal resistance of the thermal pad. lcp and R lcp,cv R represents the conductive thermal resistance from the magnetic core to the coolant flow channel and the convective thermal resistance with the coolant, respectively. lw-fe R represents the thermal resistance of conduction from the Litz wire to the magnetic core. lw R pc and R pt The sum of the three; R fe-al R represents the thermal resistance of conduction from the magnetic core to the coolant flow path. fe R tp R ag and R pt’ The sum of the four.

[0059] Substituting actual values ​​to quantify thermal resistance, exceptionally large and small thermal resistances can be considered as open circuits and short circuits, respectively. Based on this, a simplified version of the thermal resistance model is obtained, such as... Figure 4 As shown. The data indicates that the error between the two models does not exceed 1%, therefore, using... Figure 4 The simplified model is sufficient to calculate the temperature of the heating component of the magnetic coupler.

[0060] In the simplified model, R lw,hs-surf R pc R pt R fe,hs-surf R tp R ag R pt’ R lcp R lcp,cv Series connection.

[0061] Step 5: Select cooling equipment based on the established magnetic coupler thermal resistance model and quantified thermal resistance value. Set some parameters of the cooling equipment to fixed values, such as coolant flow rate, liquid cooling plate size, and heat sink height. These parameters are not parameters of the magnetic coupler itself, but parameters used to optimize the cooling structure design. Determine the design variables of the cooling equipment and give their respective value ranges and step sizes, such as the number of flow channels in the liquid cooling plate and the number of heat sink fins.

[0062] Step six: After permuting and combining the values ​​of each variable, numerous design schemes are obtained. The parameters corresponding to each design scheme are calculated, such as the convective heat transfer coefficient h. conv Thermal resistance R th Cooling hydraulic pressure drop Δp, etc.

[0063] In this embodiment, the magnetic coupler is thermally designed and optimized from two aspects: the design of the liquid cooling plate and the selection of thermal interface materials.

[0064] Let the length and width of the liquid cooling plate be variables L. o and W o Since a certain space is required between the channel and the edge of the liquid cooling plate, the minimum distance between the channel and the edge of the liquid cooling plate is set to B. In addition, seven decision variables are defined: coolant channel width w, channel height h, number of channels N, bend radius r, straight channel length e, potting compound material p, and thermal pad material q. Each potting compound and thermal pad has different thermal conductivity, weight, and cost. When N=3, the variables and parameters are as follows: Figure 5 As shown.

[0065] Step 7: Determine the objective function, such as temperature rise ΔT, system weight m, system cost C, etc.; establish a database containing information such as the input (values ​​of independent variables) and output (values ​​of objective function) for each design scheme.

[0066] Taking the temperature rise of the heat-generating components, system weight, and cost as objective functions, and providing analytical expressions for the relationship between the objective functions and each parameter (fixed parameters and design variables), and considering the available space of the liquid cooling plate, maximum temperature rise, and cooling pressure drop as constraints, the optimization model is expressed as follows:

[0067]

[0068]

[0069] There are a total of 704,000 possible design combinations. Step eight involves eliminating designs that do not meet the constraints, such as those exceeding the design dimensions or failing to meet the pressure drop limits. The results for the remaining 325,728 combinations, excluding those violating constraints, are as follows.

[0070] Step 9: Select any two objective functions as the x and y axes respectively, and plot all the results of the two objective functions until all objective functions have been selected at least once. Use the Pareto front to select the optimal solution of all objective functions.

[0071] The drawing result in this embodiment is as follows: Figure 6 As shown.

[0072] Any point preceding the Paleto front is considered "Paleto optimal". For example, a Paleto front design can minimize temperature rise at the expense of weight, or it can minimize weight at the expense of temperature rise, but it is impossible to reduce both temperature rise and weight simultaneously; this is described as a trade-off between temperature rise and weight. A similar trade-off exists between temperature rise and system cost.

[0073] Finally, the optimal solution point can be selected using the Pareto front.

[0074] This invention addresses the magnetic coupler in wireless charging systems, establishing a two-dimensional thermal network composed of multiple heat transfer paths from the heat source to the environment. Traditional thermal resistance models only consider the copper material of the coil and the ferrite material of the magnetic core, resulting in limited precision and an inability to accurately reflect the temperature of the heat-generating components. The proposed improved thermal model considers key factors affecting heat conduction and dissipation, such as potting materials, thermal interface materials, and fluid states, thus producing more accurate results while maintaining relatively low computational complexity. This makes it suitable for iterative thermal design and optimization algorithms in wireless charging systems.

[0075] This invention proposes a multi-objective thermal optimization method and process for magnetic couplers based on the Pareto front. It considers objective functions such as temperature rise, weight, and cost, which helps wireless charging systems achieve higher power density and lighter weight.

[0076] The thermal resistance model proposed in this invention, based on TNM (Thermal Network Method, an analytical method for calculating thermal behavior through thermal resistance networks), can significantly reduce computation time; it has higher accuracy than traditional thermal resistance models, with a maximum error of no more than 10% (compared to finite element models and experimental results); the proposed thermal modeling method has good adaptability and is also suitable for other coil types, core shapes, and heat dissipation methods; the proposed optimization process comprehensively weighs multiple design objectives, and the Pareto front-based method can find the relatively optimal solution among thousands of schemes in the design space.

[0077] As is known from common technical knowledge, this invention can be implemented through other embodiments that do not depart from its spirit or essential characteristics. Therefore, the disclosed embodiments described above are merely illustrative in all respects and are not the only ones. All modifications within the scope of this invention or equivalent to the scope of this invention are included in this invention.

[0078] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0079] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0080] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0081] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0082] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A method for optimizing cooling in a wireless charging system, characterized in that, Includes the following steps: Step 1: Establish a thermal resistance model of the magnetic coupler in the wireless charging system based on TNM and quantify the thermal resistance value; Step 2: Select the cooling method based on the power rating, heat dissipation, and heat dissipation area of ​​the magnetic coupler: If the power is ≥20kW or the heat dissipation is large and the heat dissipation area is small, use liquid cooling, fix the magnetic core on the liquid cooling plate, and design the diameter, number, and length of the coolant flow channels; if the heat dissipation is small and the heat dissipation area is large, use air cooling and install heat dissipation fins on the surface of the heat-generating components. Step 3: Fill the space between the winding, magnetic core, and aluminum shielding plate with thermal interface material to enhance thermal conductivity; Step 4: Calculate the core loss and shielding plate eddy current loss through finite element simulation, and calculate the Litz wire winding loss through analytical model. Step 5: Select cooling equipment based on the thermal resistance model and thermal resistance value obtained in Step 1. Set some parameters of the cooling equipment to fixed values, and determine the remaining parameters as design variables. Also, determine the value range and step size of each design variable. Step six: Obtain multiple design schemes by arranging and combining the values ​​of each design variable; Step 7: Determine the objective function for optimization; Step 8: Plot the objective function values ​​corresponding to each design scheme with one objective function as the horizontal axis and the other objective functions as the vertical axis in turn. Use the Pareto front to select the optimal solution of all objective functions. The optimal solution was selected as the cooling design scheme for the wireless charging system, thus completing the cooling optimization of the wireless charging system.

2. The cooling optimization method for a wireless charging system as described in claim 1, characterized in that, In step one, the thermal resistance of the magnetic coupler is calculated using the following formula: In the formula, the length of the heat conduction path is L c The equivalent cross-sectional area is A The thermal conductivity of the material is k ; The calculation formula for the thermal convection resistance of a magnetic coupler is as follows: In the formula, A surf The exposed area of ​​the material to the environment. h conv It is the equivalent convective heat transfer coefficient.

3. The cooling optimization method for a wireless charging system as described in claim 1, characterized in that, The thermal resistance model mentioned in step one is: R lw,hs-surf , R pc , R pt , R fe,hs-surf , R tp R ag R pt’ R lcp R lcp,cv Series; in, R lw,hs-surf and R fe,hs-surf These represent the thermal resistances conducted from the Litz wire hotspot to the surface and from the magnetic core hotspot to the surface, respectively. R pc , R pt The thermal resistance R of the potting material and the gold finger tape are respectively. ag R represents the conductive thermal resistance of the air gap. pt’ R represents the thermal resistance of the thermal pad. lcp R is the thermal resistance for conduction from the magnetic core to the coolant flow channel. lcp,cv The convective thermal resistance between the magnetic core and the coolant. R tp This represents the thermal resistance.

4. The cooling optimization method for a wireless charging system as described in claim 1, characterized in that, In step two, the fixed values ​​include coolant flow rate, liquid cooling plate size, and heat sink height.

5. The cooling optimization method for a wireless charging system as described in claim 1, characterized in that, In step two, the design variables include the number of flow channels in the liquid cooling plate and the number of heat dissipation fins.

6. The cooling optimization method for a wireless charging system as described in claim 1, characterized in that, In step four, the objective function corresponding to each design scheme includes the temperature rise of the heating component. Δt System weight m and cost C .

7. The cooling optimization method for a wireless charging system as described in claim 1, characterized in that, The input to the design scheme is the value of the design variable, and the output to the database is the value of the objective function.

8. The cooling optimization method for a wireless charging system as described in claim 1, characterized in that, In step five, before plotting all results using any two objective functions as the horizontal and vertical axes, constraints are set, and data results that meet the constraints are selected for plotting.

9. The cooling optimization method for a wireless charging system as described in claim 8, characterized in that, The constraints include design size limitations and pressure drop limitations.

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