Method, device, equipment and medium for optimizing flow field of proton exchange membrane fuel cell

Abstract

The present invention discloses a method, device, equipment and medium for optimizing the flow field of a proton exchange membrane fuel cell. The scheme determines multiple preset objective functions through the utilization rate of the electrochemical active area, the uniformity of gas distribution, the uniformity of temperature distribution, the water management capability and the pressure drop at the inlet and outlet of the flow field. In the preset objective function corresponding to the utilization rate of the electrochemical active area, the proportion of the active area and the distribution area is balanced. In the preset objective function corresponding to the water management capability, the factor of gas flow rate is taken into account, which makes up for the shortcomings of the existing commonly used flow field optimization objectives, and the generated target first design variable and target second design variable are better, thereby comprehensively improving the flow field performance.

Description

Technical Field

[0001] The invention relates to the technical field of proton exchange membrane fuel cells, and in particular to a method, device, equipment and medium for optimizing a flow field of a proton exchange membrane fuel cell. Background Art

[0002] The plate flow field design of the proton exchange membrane fuel cell (PEMFC) is closely related to the mass transfer of the reaction gas and the process of discharging the generated water, which ultimately affects the output performance. Researchers usually optimize the flow field structure to ensure that the flow field has good water and gas management capabilities to avoid the degradation of PEMFC durability and output performance caused by local insufficient gas supply or flooding. As the power density target of automotive PEMFC stacks continues to rise, the active area of ​​the plate flow field is increased to 300cm 2 As mentioned above, the challenges to flow field design are gradually increasing.

[0003] Traditionally, when optimizing the flow field of a proton exchange membrane fuel cell, the optimization objectives designed are all focused on the pressure drop and the flow difference between the flow channels. However, when optimizing using the above method, the effect of the gas flow rate on the flow field is ignored, and the balance between the active area and the distribution area of ​​the proton exchange membrane fuel cell plate is not considered, resulting in poor performance of the optimized proton exchange membrane fuel cell flow field. Summary of the invention

[0004] The present invention aims to at least solve the technical problems existing in the prior art. To this end, the first aspect of the present invention provides a method for optimizing the flow field of a proton exchange membrane fuel cell, the method comprising:

[0005] Based on the fluid dynamics model of the proton exchange membrane fuel cell flow field, a first parameterized geometric model corresponding to the distribution area and a second parameterized geometric model corresponding to the active area of ​​the proton exchange membrane fuel cell plate are constructed; wherein the first parameterized geometric model includes a plurality of initial first design variables, and the second parameterized geometric model includes a plurality of initial second design variables;

[0006] Based on a plurality of initial first design variables, a plurality of initial second design variables and a preset objective function, a current response curve model is constructed; wherein the preset objective function is determined based on the utilization rate of the electrochemical active area, the uniformity of gas distribution, the uniformity of temperature distribution, the water management capability and the pressure drop at the inlet and outlet of the flow field;

[0007] With the goal of minimizing the preset objective function, the preset solution algorithm is used to calculate the current response curve model to generate the target first design variable and the target second design variable.

[0008] In a possible implementation, the preset objective function includes a first objective function corresponding to the utilization rate of the electrochemical active area, a second objective function corresponding to the uniformity of gas distribution, a third objective function corresponding to the uniformity of temperature distribution, a fourth objective function corresponding to the water management capability, and a fifth objective function corresponding to the pressure drop at the inlet and outlet of the flow field. The current response curve model includes a first type of response curve model and a second type of response curve model. Based on multiple initial first design variables, multiple initial second design variables and the preset objective function, a response curve model is constructed, including:

[0009] Fitting the initial first design variable to the first objective function, the second objective function and the third objective function respectively to generate a first type response curve model;

[0010] The initial second design variable is fitted with the fourth objective function and the fifth objective function respectively to generate a second type of response curve model.

[0011] In a possible implementation, the preset objective function includes a first comprehensive objective function and a second comprehensive objective function, the first comprehensive objective function is determined based on a first objective function corresponding to the utilization rate of the electrochemical active area, a second objective function corresponding to the gas distribution uniformity, and a third objective function corresponding to the temperature distribution uniformity, the second comprehensive objective function is determined based on a fourth objective function corresponding to the water management capability and a fifth objective function corresponding to the flow field inlet and outlet pressure drop, the current response curve model includes a first type of response curve model and a second type of response curve model; based on multiple initial first design variables, multiple initial second design variables and the preset objective function, constructing a response curve model, further comprising:

[0012] Fitting the initial first design variable with the first comprehensive objective function to generate a first type response curve model;

[0013] The initial second design variable is fitted with the second comprehensive objective function to generate a second type of response curve model.

[0014] In a possible implementation, the first objective function is determined by the following formula:

[0015]

[0016] in, represents the first objective function, It represents the total area of ​​the proton exchange membrane fuel cell plate excluding the inlet and outlet; W represents the total width of the distribution area; L represents the total length of the distribution area.

[0017] In a possible implementation, the second objective function, the third objective function and the fifth objective function are respectively determined by the following formulas:

[0018]

[0019] in, represents the second objective function, represents the standard deviation of the flow rate between the channels in the cathode and anode flow fields, represents the average flow rate in the cathode and anode flow fields, represents the flow rate of each flow channel in the cathode and anode flow fields, and n represents the number of flow channels in the cathode and anode flow fields;

[0020]

[0021] in, represents the third objective function, Indicates the maximum temperature difference of the flow channel in the cooling flow field; represents the average temperature difference of the flow channel in the cooling flow field, They represent the average flow rate, minimum flow rate, and total flow rate of the coolant in the cooling flow field, respectively. represents the voltage of a single cell in the cooling flow field; I represents the current of a single cell in the cooling flow field; C represents the specific heat capacity of the coolant in the cooling flow field. Indicates the maximum temperature difference limit in the cooling flow field;

[0022]

[0023] in, represents the fifth objective function, They represent the inlet and outlet areas of the flow field respectively, P represents the pressure component of the flow channel section, represents the area-weighted average pressure drop, Indicates the maximum voltage drop limit value.

[0024] In a possible implementation, the fourth objective function is determined by the following formula:

[0025]

[0026] in, represents the fourth objective function, represents the minimum value of the weighted average velocity of the flow channel area, represents the cross-sectional area of ​​the flow channel, represents the velocity component of the flow channel section, Indicates the minimum flow rate limit.

[0027] In a possible implementation, the process of determining the first comprehensive objective function and the second comprehensive objective function includes:

[0028] Respectively obtain a first weight corresponding to the first objective function, a second weight corresponding to the second objective function, a third weight corresponding to the third objective function, a fourth weight corresponding to the fourth objective function, and a fifth weight corresponding to the fifth objective function;

[0029] Perform weighted processing on the first objective function, the second objective function and the third objective function based on the first weight, the second weight and the third weight to generate a first comprehensive objective function;

[0030] The fourth objective function and the fifth objective function are weighted based on the fourth weight and the fifth weight to generate a second comprehensive objective function.

[0031] The second aspect of the present invention provides a device for optimizing the flow field of a proton exchange membrane fuel cell, the device comprising:

[0032] A first construction module is used to construct a first parameterized geometric model corresponding to the distribution area structure and a second parameterized geometric model corresponding to the active area structure based on a fluid dynamics model of a proton exchange membrane fuel cell flow field; wherein the first parameterized geometric model includes a plurality of initial first design variables, and the second parameterized geometric model includes a plurality of initial second design variables;

[0033] A second construction module is used to construct a current response curve model based on a plurality of initial first design variables, a plurality of initial second design variables and a preset objective function; wherein the preset objective function is determined based on the utilization rate of the electrochemical active area, the uniformity of gas distribution, the uniformity of temperature distribution, the water management capability and the pressure drop at the inlet and outlet of the flow field;

[0034] The generation module is used to calculate the current response curve model by using a preset solution algorithm with the goal of minimizing a preset objective function, and to generate a target first design variable and a target second design variable.

[0035] In a possible implementation, the preset objective function includes a first objective function corresponding to the utilization rate of the electrochemical active area, a second objective function corresponding to the uniformity of gas distribution, a third objective function corresponding to the uniformity of temperature distribution, a fourth objective function corresponding to the water management capability, and a fifth objective function corresponding to the inlet and outlet pressure drop of the flow field. The current response curve model includes a first type of response curve model and a second type of response curve model; the second construction module is specifically used for:

[0036] Fitting the initial first design variable to the first objective function, the second objective function and the third objective function respectively to generate a first type response curve model;

[0037] The initial second design variable is fitted with the fourth objective function and the fifth objective function respectively to generate a second type of response curve model.

[0038] In a possible implementation, the preset objective function includes a first comprehensive objective function and a second comprehensive objective function, the first comprehensive objective function is determined based on a first objective function corresponding to the utilization rate of the electrochemical active area, a second objective function corresponding to the gas distribution uniformity, and a third objective function corresponding to the temperature distribution uniformity, the second comprehensive objective function is determined based on a fourth objective function corresponding to the water management capability and a fifth objective function corresponding to the flow field inlet and outlet pressure drop, the current response curve model includes a first type of response curve model and a second type of response curve model; the second construction module is also used for:

[0039] Fitting the initial first design variable with the first comprehensive objective function to generate a first type response curve model;

[0040] The initial second design variable is fitted with the second comprehensive objective function to generate a second type of response curve model.

[0041] In a possible implementation manner, the above-mentioned proton exchange membrane fuel cell flow field optimization device is further used to determine the first objective function by the following formula:

[0042]

[0043] in, represents the first objective function, It represents the total area of ​​the proton exchange membrane fuel cell plate excluding the inlet and outlet; W represents the total width of the distribution area; L represents the total length of the distribution area.

[0044] In a possible implementation, the above-mentioned proton exchange membrane fuel cell flow field optimization device is also used to determine the second objective function, the third objective function and the fifth objective function respectively by the following formulas:

[0045]

[0046] in, represents the second objective function, represents the standard deviation of the flow rate between the channels in the cathode and anode flow fields, represents the average flow rate in the cathode and anode flow fields, represents the flow rate of each flow channel in the cathode and anode flow fields, and n represents the number of flow channels in the cathode and anode flow fields;

[0047]

[0048] in, represents the third objective function, Indicates the maximum temperature difference of the flow channel in the cooling flow field; represents the average temperature difference of the flow channel in the cooling flow field, They represent the average flow rate, minimum flow rate, and total flow rate of the coolant in the cooling flow field, respectively. represents the voltage of a single cell in the cooling flow field; I represents the current of a single cell in the cooling flow field; C represents the specific heat capacity of the coolant in the cooling flow field. Indicates the maximum temperature difference limit in the cooling flow field;

[0049]

[0050] in, represents the fifth objective function, They represent the inlet and outlet areas of the flow field respectively, P represents the pressure component of the flow channel section, represents the area-weighted average pressure drop, Indicates the maximum voltage drop limit value.

[0051] In a possible implementation manner, the above-mentioned proton exchange membrane fuel cell flow field optimization device is further used to determine the fourth objective function by the following formula:

[0052]

[0053] in, represents the fourth objective function, represents the minimum value of the weighted average velocity of the flow channel area, represents the cross-sectional area of ​​the flow channel, represents the velocity component of the flow channel section, Indicates the minimum flow rate limit.

[0054] In a possible implementation, the above-mentioned proton exchange membrane fuel cell flow field optimization device is also used for:

[0055] Respectively obtain a first weight corresponding to the first objective function, a second weight corresponding to the second objective function, a third weight corresponding to the third objective function, a fourth weight corresponding to the fourth objective function, and a fifth weight corresponding to the fifth objective function;

[0056] Perform weighted processing on the first objective function, the second objective function and the third objective function based on the first weight, the second weight and the third weight to generate a first comprehensive objective function;

[0057] The fourth objective function and the fifth objective function are weighted based on the fourth weight and the fifth weight to generate a second comprehensive objective function.

[0058] A third aspect of the present invention proposes an electronic device, comprising a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the proton exchange membrane fuel cell flow field optimization method as described in the first aspect.

[0059] The fourth aspect of the present invention proposes a computer-readable storage medium, which stores at least one instruction, at least one program, a code set or an instruction set. The at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by a processor to implement the proton exchange membrane fuel cell flow field optimization method as described in the first aspect.

[0060] The embodiments of the present invention have the following beneficial effects:

[0061] An optimization method for a proton exchange membrane fuel cell flow field provided in an embodiment of the present invention comprises: constructing a first parameterized geometric model corresponding to a distribution area of ​​a proton exchange membrane fuel cell plate and a second parameterized geometric model corresponding to an active area based on a fluid dynamics model of the proton exchange membrane fuel cell flow field, and constructing a current response curve model based on a plurality of initial first design variables, a plurality of initial second design variables and a preset objective function; wherein the preset objective function is determined based on the utilization rate of the electrochemical active area, the uniformity of gas distribution, the uniformity of temperature distribution, the water management capability and the pressure drop at the inlet and outlet of the flow field, and the current response curve model is calculated using a preset solution algorithm with the goal of minimizing the preset objective function to generate a target first design variable and a target second design variable. This scheme determines multiple preset objective functions through the utilization rate of the electrochemical active area, gas distribution uniformity, temperature distribution uniformity, water management capability and the pressure drop at the inlet and outlet of the flow field. In the preset objective function corresponding to the utilization rate of the electrochemical active area, the proportion of the active area and the distribution area is balanced. In the preset objective function corresponding to the water management capability, the gas flow rate is taken into account, which makes up for the shortcomings of the existing commonly used flow field optimization objectives. The generated target first design variable and target second design variable are better, which comprehensively improves the flow field performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 A block diagram of a computer device provided in an embodiment of the present application;

[0063] Figure 2 A flowchart of the steps of the method for optimizing the flow field of a proton exchange membrane fuel cell provided in an embodiment of the present application;

[0064] Figure 3 A flow chart of the steps of constructing a response curve model provided in an embodiment of the present application;

[0065] Figure 4 A schematic diagram of a fluid dynamics model of a proton exchange membrane fuel cell flow field provided in an embodiment of the present application;

[0066] Figure 5 Another flow chart of steps for constructing a response curve model provided in an embodiment of the present application;

[0067] Figure 6 A flowchart of the steps of determining a first comprehensive objective function and a second comprehensive objective function provided in an embodiment of the present application;

[0068] Figure 7 A structural block diagram of a proton exchange membrane fuel cell flow field optimization device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0069] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0070] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present disclosure, unless otherwise specified, "multiple" means two or more. In addition, the use of "based on" or "according to" means openness and inclusiveness, because the process, steps, calculations or other actions "based on" or "according to" one or more of the conditions or values ​​may be based on additional conditions or values ​​beyond the described values ​​in practice.

[0071] The optimization method of the proton exchange membrane fuel cell flow field provided in the present application can be applied to computer equipment (electronic equipment), and the computer equipment can be a server or a terminal, wherein the server can be a single server or a server cluster composed of multiple servers. The embodiments of the present application do not make specific limitations on this. The terminal can be but is not limited to various personal computers, laptops, smart phones, tablet computers and portable wearable devices.

[0072] Take the computer device as a server as an example. Figure 1 A block diagram of a server is shown, such as Figure 1As shown, the server may include a processor and a memory connected via a system bus. The processor of the server is used to provide computing and control capabilities. The memory of the server includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. When the computer program is executed by the processor, a method for optimizing the flow field of a proton exchange membrane fuel cell is implemented.

[0073] Those skilled in the art will understand that Figure 1 The structure shown in the figure is only a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the server to which the solution of the present application is applied. Optionally, the server may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0074] It should be noted that the execution subject of the embodiments of the present application may be a computer device or a proton exchange membrane fuel cell flow field optimization device. The following method embodiments are described with a computer device as the execution subject.

[0075] Figure 2 A flow chart of the steps of a proton exchange membrane fuel cell flow field optimization method provided by an embodiment of the present invention. Figure 2 As shown, the method comprises the following steps:

[0076] Step 202: Based on the fluid dynamics model of the proton exchange membrane fuel cell flow field, a first parameterized geometric model corresponding to the distribution area and a second parameterized geometric model corresponding to the active area of ​​the proton exchange membrane fuel cell plate are constructed.

[0077] Among them, the fluid dynamics model of the proton exchange membrane fuel cell flow field can include geometric models, grid division, boundary conditions and physical model settings. The geometric model is a three-dimensional characteristic model in the fluid domain, the grid division can use a specific type of grid to divide the fluid dynamics model, the boundary conditions are the inlet and outlet positions when the fluid dynamics model is actually used, and the physical model includes the selection of fluid equations, trigger conditions, media and other contents.

[0078] The first parameterized geometric model corresponding to the distribution area of ​​the proton exchange membrane fuel cell plate is the structural parameters and constraint relationships of the protrusion array in the distribution area. The first parameterized geometric model includes multiple initial first design variables. The multiple initial first design variables may include the number of rows of the array of protrusion structures in the width and length directions of the plate, the size of each protrusion structure, the center position, etc.

[0079] The second parameterized geometric model corresponding to the active area includes multiple initial second design variables, and the multiple initial second design variables may include ridge width ratio, channel groove width, channel depth, draft angle, etc.

[0080] Step 204: construct a current response curve model based on the multiple initial first design variables, the multiple initial second design variables and the preset objective function.

[0081] Among them, the preset objective function is determined based on the utilization rate of the electrochemical active area, gas distribution uniformity, temperature distribution uniformity, water management capability and the pressure drop at the inlet and outlet of the flow field.

[0082] Optionally, the first objective function can be determined by formula (1):

[0083] (1)

[0084] in, represents the first objective function, It represents the total area of ​​the proton exchange membrane fuel cell plate excluding the inlet and outlet, in cm 2 ; W represents the total width of the distribution area, in cm; L represents the total length of the distribution area, in cm.

[0085] Optionally, the second objective function, the third objective function and the fifth objective function can be determined by formula (2) to formula (4) respectively:

[0086] (2)

[0087] in, represents the second objective function, represents the standard deviation of the flow rate between the channels in the cathode and anode flow fields, It represents the average flow rate in the cathode and anode flow fields, in kg / s. It represents the flow rate of each flow channel in the cathode and anode flow fields, and the unit is kg / s. n represents the number of flow channels in the cathode and anode flow fields.

[0088] (3)

[0089] in, represents the third objective function, Indicates the maximum temperature difference of the flow channel in the cooling flow field, in °C; It represents the average temperature difference of the flow channel in the cooling flow field, in °C. They represent the average flow rate, minimum flow rate, and total flow rate of the coolant in the cooling flow field, respectively, in kg / s. represents the voltage of a single cell in the cooling flow field, in V; I represents the current of a single cell in the cooling flow field, in A; C represents the specific heat capacity of the coolant in the cooling flow field, in , Indicates the maximum temperature difference limit in the cooling flow field, in °C.

[0090] (4)

[0091] in, represents the fifth objective function, Respectively represent the inlet and outlet areas of the flow field, in m 2 , P represents the pressure component of the flow channel section, the unit is Pa, It represents the area-weighted average pressure drop in Pa. Indicates the maximum pressure drop limit value, in Pa.

[0092] Optionally, the fourth objective function can be determined by formula (5):

[0093] (5)

[0094] in, represents the fourth objective function, It represents the minimum value of the weighted average flow velocity of the flow channel area, in m / s. Indicates the cross-sectional area of ​​the flow channel, in m 2 , Represents the velocity component of the flow channel section, in m / s. Indicates the minimum flow rate limit in m / s.

[0095] In some optional embodiments, the preset objective function includes a first objective function corresponding to the utilization rate of the electrochemical active area, a second objective function corresponding to the uniformity of gas distribution, a third objective function corresponding to the uniformity of temperature distribution, a fourth objective function corresponding to the water management capability, and a fifth objective function corresponding to the pressure drop at the inlet and outlet of the flow field. The current response curve model includes a first type of response curve model and a second type of response curve model, such as Figure 3 As shown, Figure 3 A flowchart of steps for constructing a response curve model provided in an embodiment of the present application includes:

[0096] Step 302: Fit the initial first design variable to the first objective function, the second objective function and the third objective function respectively to generate a first type response curve model.

[0097] Step 304: Fit the initial second design variable to the fourth objective function and the fifth objective function respectively to generate a second type response curve model.

[0098] Among them, Figure 4 As shown, Figure 4 A schematic diagram of a fluid dynamics model of a proton exchange membrane fuel cell flow field provided in an embodiment of the present application, wherein the fluid dynamics model includes an active area structure and a distribution area structure, the distribution area structure includes an inlet distribution area and an outlet distribution area, and the protruding structure in the distribution area structure can be a cylindrical boss. It should be noted that in actual use, the protruding structure in the distribution area structure can also be other types, and the embodiment of the present application does not specifically limit this.

[0099] In order to save computing resources and time, the active area of ​​the fluid dynamics model can be simplified to a porous medium when optimizing the distribution area. The inertial resistance coefficient of the porous medium is and the viscous drag coefficient It can be calculated according to the coefficients of the fitted flow velocity and pressure drop curve. Among them, the flow velocity v and pressure drop of the porous medium The curve can be expressed as shown in formula (6):

[0100] (6)

[0101] in, Indicates the flow channel pressure drop, in Pa; It represents the pressure jump coefficient, also known as the inertial resistance coefficient, in units of 1 / m; represents gas density, in kg / m3; v represents gas velocity, in m / s; Indicates the dynamic viscosity of the gas, in units of ; Represents the surface permeability coefficient, in m 2 ; Represents the thickness of the porous medium along the flow direction, in meters.

[0102] After the distribution area is optimized, the active area design optimization is continued. The porous medium can be replaced by the actual flow channel structure, that is, replaced by the fluid dynamics model. Then, the hexahedral grid can be selected to divide the fluid dynamics model. The grid size can vary with the size of the convex structure in the distribution area. Among them, the boundary conditions can be set according to the working conditions, including inlet flow rate, outlet pressure, etc. Optionally, the cathode and anode gas inlet flow rates can be calculated by formula (7):

[0103] (7)

[0104] in, Indicates the gas inlet mass flow rate in kg / s; represents the gas excess coefficient; j represents the current density, the unit is A / cm 2 ; Indicates the active area of ​​the flow field, in cm 2 ; It represents the molar composition of hydrogen or oxygen; n represents the number of electrons, which is 4 for oxygen consumption on the cathode side and 2 for hydrogen consumption on the anode side; F represents the Faraday constant, with the unit of ‌C / mol; M represents the molar mass of the gas, with the unit of kg / mol.

[0105] It should be noted that the gas can be regarded as an incompressible gas, the outlet pressure can be set to the atmospheric pressure 101.325 kPa (A), and the gas consumption can be ignored.

[0106] like Figure 4 , Figure 4 The figure on the left shows a schematic diagram of a proton exchange membrane fuel cell plate. Figure 4 The upper figure in the two figures on the right shows a schematic diagram of a separate inlet distribution area or outlet distribution area in a proton exchange membrane fuel cell plate. Figure 4 The lower figure in the two figures on the right shows a partial enlarged schematic diagram of the inlet distribution area or the outlet distribution area, that is, Figure 4 In the two figures on the right, the partially enlarged schematic diagram of the dotted box on the left side of the upper figure shows that the length of the entrance distribution area or the exit distribution area is denoted as L, the width is denoted as W, and the radius of the cylindrical boss is denoted as R. In the length direction of the entrance distribution area or the exit distribution area, the number of lattices formed by the cylindrical boss is m, the distance between the center of the last cylindrical boss and the boundary of the distribution area is a, and the center spacing of the cylindrical boss is x. In the width direction of the entrance distribution area or the exit distribution area, the number of lattices formed by the cylindrical boss is n, the distance between the center of the last cylindrical boss and the boundary of the distribution area is b, and the center spacing of the cylindrical boss is y. It should be noted that the entrance distribution area and the exit distribution area maintain the same constraint relationship.

[0107] Therefore, the multiple initial first design variables may be m, n, x, y, and the length L and the width W may be expressed as shown in formula (8) and formula (9) based on the multiple initial first design variables:

[0108] (8)

[0109] (9)

[0110] After the allocation area structure is determined, multiple initial second design variables of the active area can be defined. Optionally, the flow channel ridge width ratio p, the groove width s, and the groove depth h can be selected as multiple initial second design variables.

[0111] Optionally, a can be designed to be 2 mm, b can be designed to be 3 mm, and R can be designed to be 0.8 mm. The fluctuation range of m is 4-8, the fluctuation range of n is 20-40, the fluctuation range of x is 2-5, the fluctuation range of y is 2-5, the fluctuation range of p is 1-2, the fluctuation range of s is 0.1-0.8, and the fluctuation range of h is 0.2-0.5. The multiple sets of m, n, x, y and the corresponding preset function values ​​obtained here are substituted into formula (10) to obtain the corresponding coefficients by solving the multivariate linear equations; the multiple sets of p, s, h and the corresponding preset function values ​​are substituted into formula (11) to obtain the corresponding coefficients by solving the multivariate linear equations.

[0112] Optionally, the initial first design variable is fitted with the first objective function, the second objective function and the third objective function respectively to generate the first type of response curve model, which can be done by a quadratic polynomial fitting method. Since the initial first design variable corresponding to the distribution area structure is determined by the distribution area design parameters and has nothing to do with the flow channel design parameters, the initial first design variable can be fitted with the first objective function, the second objective function and the third objective function respectively by formula (10), thereby obtaining the corresponding first type of response curve model. It should be noted that when fitting different first-type response curve models, they only differ in other parameters except the initial first design variables m, n, x, and y. The fitting process can be calculated by formula (10).

[0113] Among them, the initial first design variable and the first objective function Perform fitting processing, determine the preset function value corresponding to each group of m, n, x, y through the first objective function, so as to obtain the first type of response curve model ; The initial first design variable and the second objective function The fitting process is performed, and the preset function values ​​corresponding to each group of m, n, x, and y are determined by the second objective function, so that the first type of response curve model can be obtained. ; The initial first design variable and the third objective function The fitting process is performed, and the preset function values ​​corresponding to each group of m, n, x, and y are determined by the third objective function, so that the first type of response curve model can be obtained. .

[0114] (10)

[0115] in, represents the intercept term of the first-type response curve model, represents the coefficient of the first-order term, represents the coefficient of the quadratic term, represents the coefficient of the interaction term, represents the error term, which accounts for the random variation that is not explained by the first type of response curve model.

[0116] Optionally, the initial second design variable is fitted with the fourth objective function and the fifth objective function respectively to generate the second type response curve model. And the fifth objective function It is determined by multiple second initial design variables corresponding to the active area structure. Therefore, the initial second design variables and the fourth objective function and the fifth objective function can be fitted by formula (11) to obtain the corresponding second type response curve model: It should be noted that when fitting different second-type response curve models, they only differ in other parameters except the initial second design variables p, s, and h. The fitting process can be calculated by formula (11).

[0117] Among them, the initial second design variable and the fourth objective function The fitting process is performed, and the preset function values ​​corresponding to each group of p, s, and h are determined by the fourth objective function, so that the second type of response curve model can be obtained. ; The initial second design variable and the fifth objective function The fitting process is performed, and the preset function values ​​corresponding to each group of p, s, and h are determined by the fifth objective function, so that the second type of response curve model can be obtained. .

[0118] (11)

[0119] in, represents the intercept term of the second type response curve model, represents the coefficient of the first-order term, represents the coefficient of the quadratic term, represents the error term, which accounts for the random variation that is not explained by the second-type response curve model.

[0120] In some other optional embodiments, the preset objective function includes a first comprehensive objective function and a second comprehensive objective function, the first comprehensive objective function is determined based on a first objective function corresponding to the utilization rate of the electrochemical active area, a second objective function corresponding to the gas distribution uniformity, and a third objective function corresponding to the temperature distribution uniformity, the second comprehensive objective function is determined based on a fourth objective function corresponding to the water management capability and a fifth objective function corresponding to the flow field inlet and outlet pressure drop, and the current response curve model includes a first type of response curve model and a second type of response curve model, such as Figure 5 As shown, Figure 5 Another step flow chart for constructing a response curve model provided in an embodiment of the present application includes:

[0121] Step 502: Fit the initial first design variable with the first comprehensive objective function to generate a first type response curve model.

[0122] Step 504: Fit the initial second design variable to the second comprehensive objective function to generate a second type of response curve model.

[0123] Wherein, optionally, Figure 6 As shown, Figure 6 A flowchart of steps for determining a first comprehensive objective function and a second comprehensive objective function provided in an embodiment of the present application includes:

[0124] Step 602, respectively obtain a first weight corresponding to the first objective function, a second weight corresponding to the second objective function, a third weight corresponding to the third objective function, a fourth weight corresponding to the fourth objective function, and a fifth weight corresponding to the fifth objective function.

[0125] Step 604: Perform weighted processing on the first objective function, the second objective function and the third objective function based on the first weight, the second weight and the third weight to generate a first comprehensive objective function.

[0126] Step 606: Perform weighted processing on the fourth objective function and the fifth objective function based on the fourth weight and the fifth weight to generate a second comprehensive objective function.

[0127] Among them, the first weight, second weight, third weight, fourth weight and fifth weight can all be customized. For example, the first weight, second weight and third weight can be determined as 0.5, 0.25, and 0.5 respectively, and the fourth weight and fifth weight can be determined as 0.5 and 0.5 respectively.

[0128] Thus, by weighting the first objective function, the second objective function and the third objective function based on the first weight, the second weight and the third weight, a first comprehensive objective function can be generated. The first comprehensive objective function can be obtained by formula (12).

[0129] (12)

[0130] The fourth objective function and the fifth objective function are weighted based on the fourth weight and the fifth weight to generate a second comprehensive objective function. The second comprehensive objective function can be obtained by formula (13).

[0131] (13)

[0132] Step 206 , with the goal of minimizing the preset objective function, a preset solution algorithm is used to calculate the current response curve model to generate a target first design variable and a target second design variable.

[0133] Among them, optionally, the preset solution algorithm can be a fast non-dominated sorting genetic algorithm II (NSGA2) with an elite retention strategy. When the preset objective function includes a first objective function corresponding to the utilization rate of the electrochemical active area, a second objective function corresponding to the uniformity of gas distribution, a third objective function corresponding to the uniformity of temperature distribution, a fourth objective function corresponding to the water management ability, and a fifth objective function corresponding to the pressure drop at the inlet and outlet of the flow field, the preset objective functions can be minimized as the goal, so that the current response curve model can be calculated using the NSGA2 algorithm to obtain the target first design variable and the target second design variable when each preset objective function is minimized. By optimizing the method of minimizing each preset objective function as the goal, the accuracy of generating the target first design variable and the target second design variable can be improved.

[0134] Optionally, the preset solution algorithm can be a genetic algorithm. The embodiment of the present application does not limit the specific framework of the genetic algorithm. When the preset objective function includes a first comprehensive objective function and a second comprehensive objective function, the goal can be to minimize the first comprehensive objective function and the second comprehensive objective function respectively, so that the genetic algorithm can be used to calculate the current response curve model to obtain the target first design variable and the target second design variable when the first comprehensive objective function and the second comprehensive objective function are minimized.

[0135] After experimental verification, the target first design variable and the target second design variable can be designed as m=5, n=25, x=3.5 mm, y=4.5 mm, p=1.5, s=0.4 mm, h=0.2 mm respectively. By optimizing the first comprehensive objective function and the second comprehensive objective function with minimization as the goal, the amount of calculation can be reduced, the efficiency of generating the target first design variable and the target second design variable can be improved, and rapid iterative design can be achieved, saving time and material resources for project development.

[0136] The optimization method of the proton exchange membrane fuel cell flow field provided in this embodiment includes: based on the fluid dynamics model of the proton exchange membrane fuel cell flow field, constructing a first parameterized geometric model corresponding to the distribution area of ​​the proton exchange membrane fuel cell plate and a second parameterized geometric model corresponding to the active area, and constructing a current response curve model based on multiple initial first design variables, multiple initial second design variables and a preset objective function; wherein the preset objective function is determined based on the utilization rate of the electrochemical active area, gas distribution uniformity, temperature distribution uniformity, water management capability and flow field inlet and outlet pressure drop, and with the goal of minimizing the preset objective function, the current response curve model is calculated using a preset solution algorithm to generate a target first design variable and a target second design variable. This scheme determines multiple preset objective functions through the utilization rate of the electrochemical active area, gas distribution uniformity, temperature distribution uniformity, water management capability and the pressure drop at the inlet and outlet of the flow field. In the preset objective function corresponding to the utilization rate of the electrochemical active area, the proportion of the active area and the distribution area is balanced. In the preset objective function corresponding to the water management capability, the gas flow rate is taken into account, which makes up for the shortcomings of the existing commonly used flow field optimization objectives. The generated target first design variable and target second design variable are better, which comprehensively improves the flow field performance.

[0137] Figure 7 A structural block diagram of a proton exchange membrane fuel cell flow field optimization device provided in an embodiment of the present invention.

[0138] like Figure 7 As shown, the proton exchange membrane fuel cell flow field optimization device 700 includes:

[0139] The first construction module 702 is used to construct a first parameterized geometric model corresponding to the distribution area structure and a second parameterized geometric model corresponding to the active area structure based on the fluid dynamics model of the proton exchange membrane fuel cell flow field; wherein the first parameterized geometric model includes multiple initial first design variables, and the second parameterized geometric model includes multiple initial second design variables.

[0140] The second construction module 704 is used to construct a current response curve model based on multiple initial first design variables, multiple initial second design variables and a preset objective function; wherein the preset objective function is determined based on the utilization rate of the electrochemical active area, gas distribution uniformity, temperature distribution uniformity, water management capability and flow field inlet and outlet pressure drop.

[0141] The generation module 706 is used to calculate the current response curve model using a preset solution algorithm with the goal of minimizing a preset objective function, and generate a target first design variable and a target second design variable.

[0142] Regarding the device in the above embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment of the method, and will not be described in detail here. Each module in the above-mentioned proton exchange membrane fuel cell flow field optimization device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations of the above modules.

[0143] In one embodiment of the present application, a computer device is provided, the computer device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the following steps when executing the computer program:

[0144] Based on the fluid dynamics model of the proton exchange membrane fuel cell flow field, a first parameterized geometric model corresponding to the distribution area and a second parameterized geometric model corresponding to the active area of ​​the proton exchange membrane fuel cell plate are constructed; wherein the first parameterized geometric model includes a plurality of initial first design variables, and the second parameterized geometric model includes a plurality of initial second design variables;

[0145] Based on a plurality of initial first design variables, a plurality of initial second design variables and a preset objective function, a current response curve model is constructed; wherein the preset objective function is determined based on the utilization rate of the electrochemical active area, the uniformity of gas distribution, the uniformity of temperature distribution, the water management capability and the pressure drop at the inlet and outlet of the flow field;

[0146] With the goal of minimizing the preset objective function, the preset solution algorithm is used to calculate the current response curve model to generate the target first design variable and the target second design variable.

[0147] In one embodiment of the present application, the preset objective function includes a first objective function corresponding to the utilization rate of the electrochemical active area, a second objective function corresponding to the uniformity of gas distribution, a third objective function corresponding to the uniformity of temperature distribution, a fourth objective function corresponding to the water management capability, and a fifth objective function corresponding to the inlet and outlet pressure drop of the flow field, and the current response curve model includes a first type of response curve model and a second type of response curve model; when the processor executes the computer program, the following steps are also implemented:

[0148] Fitting the initial first design variable to the first objective function, the second objective function and the third objective function respectively to generate a first type response curve model;

[0149] The initial second design variable is fitted with the fourth objective function and the fifth objective function respectively to generate a second type of response curve model.

[0150] In one embodiment of the present application, the preset objective function includes a first comprehensive objective function and a second comprehensive objective function, the first comprehensive objective function is determined based on a first objective function corresponding to the utilization rate of the electrochemical active area, a second objective function corresponding to the uniformity of gas distribution, and a third objective function corresponding to the uniformity of temperature distribution, the second comprehensive objective function is determined based on a fourth objective function corresponding to the water management capability and a fifth objective function corresponding to the inlet and outlet pressure drop of the flow field, the current response curve model includes a first type of response curve model and a second type of response curve model; when the processor executes the computer program, the following steps are also implemented:

[0151] Fitting the initial first design variable with the first comprehensive objective function to generate a first type response curve model;

[0152] The initial second design variable is fitted with the second comprehensive objective function to generate a second type of response curve model.

[0153] In one embodiment of the present application, when the processor executes the computer program, the processor further implements the following steps:

[0154]

[0155] in, represents the first objective function, It represents the total area of ​​the proton exchange membrane fuel cell plate excluding the inlet and outlet; W represents the total width of the distribution area; L represents the total length of the distribution area.

[0156] In one embodiment of the present application, when the processor executes the computer program, the processor further implements the following steps:

[0157]

[0158] in, represents the second objective function, represents the standard deviation of the flow rate between the channels in the cathode and anode flow fields, represents the average flow rate in the cathode and anode flow fields, represents the flow rate of each flow channel in the cathode and anode flow fields, and n represents the number of flow channels in the cathode and anode flow fields;

[0159]

[0160] in, represents the third objective function, Indicates the maximum temperature difference of the flow channel in the cooling flow field; represents the average temperature difference of the flow channel in the cooling flow field, They represent the average flow rate, minimum flow rate, and total flow rate of the coolant in the cooling flow field, respectively. represents the voltage of a single cell in the cooling flow field; I represents the current of a single cell in the cooling flow field; C represents the specific heat capacity of the coolant in the cooling flow field. Indicates the maximum temperature difference limit in the cooling flow field;

[0161]

[0162] in, represents the fifth objective function, They represent the inlet and outlet areas of the flow field respectively, P represents the pressure component of the flow channel section, represents the area-weighted average pressure drop, Indicates the maximum voltage drop limit value.

[0163] In one embodiment of the present application, when the processor executes the computer program, the processor further implements the following steps:

[0164]

[0165] in, represents the fourth objective function, represents the minimum value of the weighted average velocity of the flow channel area, represents the cross-sectional area of ​​the flow channel, represents the velocity component of the flow channel section, Indicates the minimum flow rate limit.

[0166] In one embodiment of the present application, when the processor executes the computer program, the processor further implements the following steps:

[0167] Respectively obtain a first weight corresponding to the first objective function, a second weight corresponding to the second objective function, a third weight corresponding to the third objective function, a fourth weight corresponding to the fourth objective function, and a fifth weight corresponding to the fifth objective function;

[0168] Perform weighted processing on the first objective function, the second objective function and the third objective function based on the first weight, the second weight and the third weight to generate a first comprehensive objective function;

[0169] The fourth objective function and the fifth objective function are weighted based on the fourth weight and the fifth weight to generate a second comprehensive objective function.

[0170] The computer device provided in the embodiment of the present application has similar implementation principles and technical effects to those of the above-mentioned method embodiment, and will not be described in detail here.

[0171] In one embodiment of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0172] Based on the fluid dynamics model of the proton exchange membrane fuel cell flow field, a first parameterized geometric model corresponding to the distribution area and a second parameterized geometric model corresponding to the active area of ​​the proton exchange membrane fuel cell plate are constructed; wherein the first parameterized geometric model includes a plurality of initial first design variables, and the second parameterized geometric model includes a plurality of initial second design variables;

[0173] Based on a plurality of initial first design variables, a plurality of initial second design variables and a preset objective function, a current response curve model is constructed; wherein the preset objective function is determined based on the utilization rate of the electrochemical active area, the uniformity of gas distribution, the uniformity of temperature distribution, the water management capability and the pressure drop at the inlet and outlet of the flow field;

[0174] With the goal of minimizing the preset objective function, the preset solution algorithm is used to calculate the current response curve model to generate the target first design variable and the target second design variable.

[0175] In one embodiment of the present application, the preset objective function includes a first objective function corresponding to the utilization rate of the electrochemical active area, a second objective function corresponding to the uniformity of gas distribution, a third objective function corresponding to the uniformity of temperature distribution, a fourth objective function corresponding to the water management capability, and a fifth objective function corresponding to the inlet and outlet pressure drop of the flow field, and the current response curve model includes a first type of response curve model and a second type of response curve model; when the computer program is executed by the processor, the following steps are also implemented:

[0176] Fitting the initial first design variable to the first objective function, the second objective function and the third objective function respectively to generate a first type response curve model;

[0177] The initial second design variable is fitted with the fourth objective function and the fifth objective function respectively to generate a second type of response curve model.

[0178] In one embodiment of the present application, the preset objective function includes a first comprehensive objective function and a second comprehensive objective function, the first comprehensive objective function is determined based on a first objective function corresponding to the utilization rate of the electrochemical active area, a second objective function corresponding to the uniformity of gas distribution, and a third objective function corresponding to the uniformity of temperature distribution, the second comprehensive objective function is determined based on a fourth objective function corresponding to the water management capability and a fifth objective function corresponding to the inlet and outlet pressure drop of the flow field, the current response curve model includes a first type of response curve model and a second type of response curve model; when the computer program is executed by the processor, the following steps are also implemented:

[0179] Fitting the initial first design variable with the first comprehensive objective function to generate a first type response curve model;

[0180] The initial second design variable is fitted with the second comprehensive objective function to generate a second type of response curve model.

[0181] In one embodiment of the present application, when the computer program is executed by a processor, the following steps are further implemented:

[0182]

[0183] in, represents the first objective function, It represents the total area of ​​the proton exchange membrane fuel cell plate excluding the inlet and outlet; W represents the total width of the distribution area; L represents the total length of the distribution area.

[0184] In one embodiment of the present application, when the computer program is executed by a processor, the following steps are further implemented:

[0185]

[0186] in, represents the second objective function, represents the standard deviation of the flow rate between the channels in the cathode and anode flow fields, represents the average flow rate in the cathode and anode flow fields, represents the flow rate of each flow channel in the cathode and anode flow fields, and n represents the number of flow channels in the cathode and anode flow fields;

[0187]

[0188] in, represents the third objective function, Indicates the maximum temperature difference of the flow channel in the cooling flow field; represents the average temperature difference of the flow channel in the cooling flow field, They represent the average flow rate, minimum flow rate, and total flow rate of the coolant in the cooling flow field, respectively. represents the voltage of a single cell in the cooling flow field; I represents the current of a single cell in the cooling flow field; C represents the specific heat capacity of the coolant in the cooling flow field. Indicates the maximum temperature difference limit in the cooling flow field;

[0189]

[0190] in, represents the fifth objective function, They represent the inlet and outlet areas of the flow field respectively, P represents the pressure component of the flow channel section, represents the area-weighted average pressure drop, Indicates the maximum voltage drop limit value.

[0191] In one embodiment of the present application, when the computer program is executed by a processor, the following steps are further implemented:

[0192]

[0193] in, represents the fourth objective function, represents the minimum value of the weighted average velocity of the flow channel area, represents the cross-sectional area of ​​the flow channel, represents the velocity component of the flow channel section, Indicates the minimum flow rate limit.

[0194] In one embodiment of the present application, when the computer program is executed by a processor, the following steps are further implemented:

[0195] Respectively obtain a first weight corresponding to the first objective function, a second weight corresponding to the second objective function, a third weight corresponding to the third objective function, a fourth weight corresponding to the fourth objective function, and a fifth weight corresponding to the fifth objective function;

[0196] Perform weighted processing on the first objective function, the second objective function and the third objective function based on the first weight, the second weight and the third weight to generate a first comprehensive objective function;

[0197] The fourth objective function and the fifth objective function are weighted based on the fourth weight and the fifth weight to generate a second comprehensive objective function.

[0198] The computer-readable storage medium provided in this embodiment has similar implementation principles and technical effects to those of the above method embodiments, and will not be described in detail here.

[0199] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0200] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0201] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for optimizing the flow field of a proton exchange membrane fuel cell, characterized in that: The method comprises: Based on the fluid dynamics model of the proton exchange membrane fuel cell flow field, a first parameterized geometric model corresponding to the distribution area and a second parameterized geometric model corresponding to the active area of ​​the proton exchange membrane fuel cell plate are constructed; wherein the first parameterized geometric model includes a plurality of initial first design variables, and the second parameterized geometric model includes a plurality of initial second design variables; Based on the multiple initial first design variables, the multiple initial second design variables and the preset objective function, a current response curve model is constructed, including: fitting the initial first design variables with the first objective function, the second objective function and the third objective function respectively to generate a first type of response curve model; fitting the initial second design variables with the fourth objective function and the fifth objective function respectively to generate a second type of response curve model; wherein the preset objective function is determined based on the utilization rate of the electrochemical active area, the uniformity of gas distribution, the uniformity of temperature distribution, the water management capability and the pressure drop at the inlet and outlet of the flow field, and the preset objective function includes the first objective function corresponding to the utilization rate of the electrochemical active area, the second objective function corresponding to the uniformity of gas distribution, the third objective function corresponding to the uniformity of temperature distribution, the fourth objective function corresponding to the water management capability and the fifth objective function corresponding to the pressure drop at the inlet and outlet of the flow field, and the current response curve model includes the first type of response curve model and the second type of response curve model; or, The initial first design variable is fitted with the first comprehensive objective function to generate a first type of response curve model; the initial second design variable is fitted with the second comprehensive objective function to generate a second type of response curve model; the preset objective function includes a first comprehensive objective function and a second comprehensive objective function, the first comprehensive objective function is determined based on the first objective function corresponding to the utilization rate of the electrochemical active area, the second objective function corresponding to the gas distribution uniformity, and the third objective function corresponding to the temperature distribution uniformity, the second comprehensive objective function is determined based on the fourth objective function corresponding to the water management ability and the fifth objective function corresponding to the inlet and outlet pressure drop of the flow field, the current response curve model includes a first type of response curve model and a second type of response curve model; the first objective function is determined by the following formula: in, represents the first objective function, represents the total area of ​​the proton exchange membrane fuel cell plate excluding the inlet and outlet; W represents the total width of the distribution area; L represents the total length of the distribution area; The fourth objective function is determined by the following formula: in, represents the fourth objective function, represents the minimum value of the weighted average velocity of the flow channel area, represents the cross-sectional area of ​​the flow channel, represents the velocity component of the flow channel section, Indicates the minimum flow rate limit; The fifth objective function is determined by the following formula: in, represents the fifth objective function, They represent the inlet and outlet areas of the flow field, respectively, and P represents the pressure component of the flow channel section. represents the area-weighted average pressure drop, Indicates the maximum voltage drop limit; With the goal of minimizing the preset objective function, the current response curve model is calculated using a preset solution algorithm to generate a target first design variable and a target second design variable.

2. The method according to claim 1, characterized in that: The second objective function and the third objective function are determined by the following formulas respectively: in, represents the second objective function, represents the standard deviation of the flow rate between the channels in the cathode and anode flow fields, represents the average flow rate in the cathode and anode flow fields, represents the flow rate of each flow channel in the cathode and anode flow fields, and n represents the number of flow channels in the cathode and anode flow fields; in, represents the third objective function, Indicates the maximum temperature difference of the flow channel in the cooling flow field; represents the average temperature difference of the flow channel in the cooling flow field, They represent the average flow rate, minimum flow rate, and total flow rate of the coolant in the cooling flow field, respectively. represents the voltage of a single cell in the cooling flow field; I represents the current of a single cell in the cooling flow field; C represents the specific heat capacity of the coolant in the cooling flow field. Indicates the maximum temperature difference limit in the cooling flow field.

3. The method according to claim 1 or 2, characterized in that: The process of determining the first comprehensive objective function and the second comprehensive objective function includes: Respectively obtain a first weight corresponding to the first objective function, a second weight corresponding to the second objective function, a third weight corresponding to the third objective function, a fourth weight corresponding to the fourth objective function, and a fifth weight corresponding to the fifth objective function; Perform weighted processing on the first objective function, the second objective function and the third objective function based on the first weight, the second weight and the third weight to generate the first comprehensive objective function; The fourth objective function and the fifth objective function are weighted based on the fourth weight and the fifth weight to generate the second comprehensive objective function.

4. A device for optimizing the flow field of a proton exchange membrane fuel cell, characterized in that: The device comprises: A first construction module is used to construct a first parameterized geometric model corresponding to the distribution area structure and a second parameterized geometric model corresponding to the active area structure based on a fluid dynamics model of a proton exchange membrane fuel cell flow field; wherein the first parameterized geometric model includes a plurality of initial first design variables, and the second parameterized geometric model includes a plurality of initial second design variables; A second construction module is used to construct a current response curve model based on the multiple initial first design variables, the multiple initial second design variables and the preset objective function, including: fitting the initial first design variables with the first objective function, the second objective function and the third objective function respectively to generate a first type of response curve model; fitting the initial second design variables with the fourth objective function and the fifth objective function respectively to generate a second type of response curve model; wherein the preset objective function is determined based on the utilization rate of the electrochemical active area, the uniformity of gas distribution, the uniformity of temperature distribution, the water management capability and the pressure drop at the inlet and outlet of the flow field, and the preset objective function includes the first objective function corresponding to the utilization rate of the electrochemical active area, the second objective function corresponding to the uniformity of gas distribution, the third objective function corresponding to the uniformity of temperature distribution, the fourth objective function corresponding to the water management capability and the fifth objective function corresponding to the pressure drop at the inlet and outlet of the flow field, and the current response curve model includes the first type of response curve model and the second type of response curve model; or, The initial first design variable is fitted with the first comprehensive objective function to generate a first type of response curve model; the initial second design variable is fitted with the second comprehensive objective function to generate a second type of response curve model; the preset objective function includes a first comprehensive objective function and a second comprehensive objective function, the first comprehensive objective function is determined based on the first objective function corresponding to the utilization rate of the electrochemical active area, the second objective function corresponding to the gas distribution uniformity, and the third objective function corresponding to the temperature distribution uniformity, the second comprehensive objective function is determined based on the fourth objective function corresponding to the water management ability and the fifth objective function corresponding to the inlet and outlet pressure drop of the flow field, the current response curve model includes a first type of response curve model and a second type of response curve model; the first objective function is determined by the following formula: in, represents the first objective function, represents the total area of ​​the proton exchange membrane fuel cell plate excluding the inlet and outlet; W represents the total width of the distribution area; L represents the total length of the distribution area; The fourth objective function is determined by the following formula: in, represents the fourth objective function, represents the minimum value of the weighted average velocity of the flow channel area, represents the cross-sectional area of ​​the flow channel, represents the velocity component of the flow channel section, Indicates the minimum flow rate limit; The fifth objective function is determined by the following formula: in, represents the fifth objective function, They represent the inlet and outlet areas of the flow field, respectively, and P represents the pressure component of the flow channel section. represents the area-weighted average pressure drop, Indicates the maximum voltage drop limit; The generation module is used to calculate the current response curve model by using a preset solution algorithm with the goal of minimizing the preset objective function, and generate a target first design variable and a target second design variable.

5. The device according to claim 4, characterized in that The device is also used for: Respectively obtain a first weight corresponding to the first objective function, a second weight corresponding to the second objective function, a third weight corresponding to the third objective function, a fourth weight corresponding to the fourth objective function, and a fifth weight corresponding to the fifth objective function; Perform weighted processing on the first objective function, the second objective function and the third objective function based on the first weight, the second weight and the third weight to generate the first comprehensive objective function; The fourth objective function and the fifth objective function are weighted based on the fourth weight and the fifth weight to generate the second comprehensive objective function.

6. An electronic device, characterized in that: The electronic device includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the proton exchange membrane fuel cell flow field optimization method as described in any one of claims 1 to 3.

7. A computer-readable storage medium, characterized in that: The storage medium stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set are loaded and executed by the processor to implement the proton exchange membrane fuel cell flow field optimization method as described in any one of claims 1 to 3.

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