A multi-working condition comprehensive evaluation method for proton exchange membrane fuel cell

Abstract

The application discloses a kind of proton exchange membrane fuel cell multi-working condition comprehensive evaluation method, specifically related to the field of proton exchange membrane fuel cell.It includes: obtaining the structural parameters of proton exchange membrane fuel cell, operating boundary parameter and cooling flow channel parameter, and establishing three-dimensional multi-physical field model;Respectively, load current density, cooling liquid inlet temperature and cooling liquid flow rate are used as the variables of three-dimensional multi-physical field model, to construct single-factor multi-working condition group;Simulation is carried out for each working condition, and simulation results including single-cell operating voltage, temperature field, cooling liquid pressure field and volumetric heat source term distribution are obtained;According to the simulation results of each working condition, determine the evaluation index;Weighted sum is carried out to all evaluation indexes, and the comprehensive evaluation score of each working condition is obtained.Based on the above method, quantitative basis can be provided for the reference evaluation before cooling flow channel optimization.

Description

Technical Field

[0001] This invention relates to the field of proton exchange membrane fuel cells, and more particularly to a comprehensive evaluation method for proton exchange membrane fuel cells under multiple operating conditions. Background Technology

[0002] Proton exchange membrane fuel cells (PEMFCs) possess advantages such as high energy conversion efficiency, fast start-up speed, and low operating emissions, making them promising candidates for applications in transportation, distributed energy, and portable power sources. However, as the power density of the fuel cell stack increases, the accumulation of heat due to electrochemical reactions, activation polarization, ohmic heat, and localized mass transfer losses becomes more pronounced. If internal waste heat cannot be dissipated promptly, it can easily lead to localized temperature increases and uneven temperature distribution, thereby affecting the water content of the proton exchange membrane, the electrochemical reaction process, and the operational stability of the fuel cell stack.

[0003] Water-cooled proton exchange membrane fuel cells typically remove internal waste heat through cooling channels located in bipolar plates or cooling plates. The structure of the cooling channels and operating parameters such as coolant inlet temperature and flow rate simultaneously affect the cell's maximum temperature, temperature uniformity, coolant heat-carrying capacity, and flow pressure drop. Simply increasing the coolant flow rate can enhance convective heat transfer, but may increase pressure loss. Using a single indicator such as power density, maximum temperature, or cooling channel pressure drop alone fails to reflect the comprehensive relationship between output performance, thermal safety, cooling benefits, and flow resistance. Furthermore, the total heat generated inside the cell varies significantly under different load current densities. If the cooling effect is directly evaluated using the heat removed by the coolant, high-heat-generating conditions may receive a higher evaluation due to the larger heat carried by the coolant, but this result does not directly reflect the cooling structure's ability to suppress the maximum temperature rise caused by a unit heat load. On the other hand, using only the cooling channel pressure drop to evaluate flow performance does not reflect the flow resistance cost of achieving the corresponding cooling effect. Therefore, the existing evaluation methods for cooling channel structures still have certain limitations and are difficult to comprehensively characterize the integrated relationship between cooling effect, thermal load response capability and flow resistance. Summary of the Invention

[0004] The main objective of this application is to provide a comprehensive evaluation method for proton exchange membrane fuel cells under multiple operating conditions, aiming to solve the problem that existing evaluation methods are unable to fully characterize the comprehensive relationship between cooling effect, thermal load response capability and flow resistance.

[0005] To achieve the above objectives, this application provides a multi-condition comprehensive evaluation method for proton exchange membrane fuel cells, comprising: acquiring the structural parameters, operating boundary parameters, and cooling channel parameters of the proton exchange membrane fuel cell; establishing a three-dimensional multiphysics model based on the structural parameters, operating boundary parameters, and cooling channel parameters; constructing a single-factor multi-condition group by using the load current density, coolant inlet temperature, and coolant flow rate as variables in the three-dimensional multiphysics model; performing simulation operation on each condition to obtain simulation results including the working voltage, temperature field, coolant pressure field, and volumetric heat source term distribution of a single cell; determining evaluation indicators based on the simulation results of each condition; wherein the evaluation indicators include power density, maximum temperature, maximum temperature difference, temperature uniformity index, maximum temperature rise coefficient under unit heat load, and cooling benefit per unit pressure drop; and weighted summing of all evaluation indicators to obtain a comprehensive evaluation score for each condition.

[0006] Optionally, the three-dimensional multiphysics model includes one or more computational regions such as the anode channel, cathode channel, gas diffusion layer, catalyst layer, proton exchange membrane, bipolar plate, and cooling channel.

[0007] Optionally, evaluation metrics are determined based on the simulation results for each operating condition, including determining the power density based on the load current density and the single-cell operating voltage.

[0008] Optionally, based on the simulation results for each working condition, evaluation indicators are determined, including: obtaining the highest and lowest temperatures in the temperature field and determining the maximum temperature difference; obtaining the sampling point temperature, the average temperature of the sampling points, and the number of sampling points in the temperature field, and determining the temperature uniformity index.

[0009] Optionally, evaluation indicators are determined based on the simulation results of each working condition, including: determining the total heat generation inside the battery based on the volumetric heat source item, and determining the maximum temperature rise coefficient under unit heat load based on the maximum temperature, coolant inlet temperature and the total heat generation inside the battery.

[0010] Optionally, evaluation indicators are determined based on the simulation results for each operating condition, including: determining the heat carried away by the coolant based on the coolant mass flow rate, coolant specific heat capacity at constant pressure, coolant outlet temperature, and coolant inlet temperature; obtaining the inlet and outlet pressures of the cooling channel in the coolant pressure field and determining the cooling channel pressure drop; and determining the cooling benefit per unit pressure drop based on the heat carried away by the coolant and the cooling channel pressure drop.

[0011] Optionally, after determining the evaluation indicators based on the simulation results of each operating condition, the method further includes: taking power density, temperature uniformity index, and cooling benefit per unit pressure drop as positive indicators, and taking the highest temperature, maximum temperature difference, and maximum temperature rise coefficient per unit heat load as negative indicators, and performing dimensionless normalization processing on each indicator within the same multi-operating condition group to obtain the normalized evaluation value of each evaluation indicator.

[0012] Optionally, a weighted summation of all evaluation indicators can be performed to obtain the comprehensive evaluation score for each working condition, including: a weighted summation of the normalized evaluation values ​​of all evaluation indicators to obtain the comprehensive evaluation score for each working condition.

[0013] Optionally, the expression for the comprehensive evaluation score is:

[0014] In the formula, Let k be the comprehensive evaluation score for the k-th working condition. , , , , and These are the normalized evaluation values ​​for power density, maximum temperature, maximum temperature difference, temperature uniformity index, maximum temperature rise coefficient per unit heat load, and cooling benefit per unit pressure drop under the k-th operating condition, respectively. , , , , , All are weights.

[0015] To achieve the above objectives, this application also provides a multi-condition comprehensive evaluation device for proton exchange membrane fuel cells, comprising: The model building module is used to obtain the structural parameters, operating boundary parameters, and cooling channel parameters of the proton exchange membrane fuel cell. Based on the structural parameters, operating boundary parameters, and cooling channel parameters, a three-dimensional multiphysics model including electrochemical reaction, mass transfer, heat transfer, and coolant flow is established. The operating condition construction module is used to construct single-factor multi-operating condition groups by taking load current density, coolant inlet temperature and coolant flow rate as variables in the three-dimensional multiphysics model. The simulation module is used to run simulations for each operating condition and obtain simulation results including the operating voltage, temperature field, coolant pressure field, and volumetric heat source distribution of a single cell. The evaluation module is used to determine evaluation indicators based on the simulation results of each working condition; The evaluation indicators include power density, maximum temperature, maximum temperature difference, temperature uniformity index, maximum temperature rise coefficient under unit heat load, and cooling benefit per unit pressure drop. All evaluation indicators are weighted and summed to obtain the comprehensive evaluation score for each operating condition.

[0016] Compared with the prior art, the beneficial effects of this application are as follows: The multi-condition comprehensive evaluation method for proton exchange membrane fuel cells of this invention incorporates power density, temperature field characteristics, thermal load response capability, and flow resistance matching relationship into the same evaluation system. This avoids the one-sidedness caused by using only a single performance index for evaluation, thus comprehensively characterizing the integrated relationship between cooling effect, thermal load response capability, and flow resistance. Introducing the maximum temperature rise coefficient under unit heat load can weaken the impact of the difference in total heat generation within different operating conditions on the evaluation of cooling effect, and more directly reflect the ability of the cooling structure to suppress local heat accumulation. The cooling benefit per unit pressure drop characterizes the matching relationship between cooling benefit and flow resistance, establishing a correlation between the heat carried by the coolant and pressure loss in the same index. By weighted summing of evaluation indices within the same single-factor multi-condition group, a comprehensive evaluation score is obtained, providing a quantitative basis for benchmark evaluation before cooling channel optimization and performance comparison between different structural schemes. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating a multi-condition comprehensive evaluation method for proton exchange membrane fuel cells according to this application. Figure 2 A three-dimensional multiphysics model diagram established for the embodiments of this application.

[0018] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] The first embodiment of the present invention provides a multi-condition comprehensive evaluation method for proton exchange membrane fuel cells, such as... Figure 1 As shown, the specific steps include: Step S1: Obtain the structural parameters, operating boundary parameters, and cooling channel parameters of the proton exchange membrane fuel cell. Based on the structural parameters, operating boundary parameters, and cooling channel parameters, establish a three-dimensional multiphysics model that includes electrochemical reactions, mass transfer, heat transfer, and coolant flow. For example, a three-dimensional multiphysics model includes one or more computational regions selected from anode flow channels, cathode flow channels, gas diffusion layers, catalyst layers, proton exchange membranes, bipolar plates, and cooling flow channels. The three-dimensional multiphysics model is used to simulate reactant transport, charge conduction, electrochemical reactions, heat transfer, and coolant flow processes, and outputs the single-cell operating voltage, local current density distribution, temperature field, coolant pressure field, coolant velocity field, and volumetric heat source term distribution.

[0021] Step S2: Load current density, coolant inlet temperature, and coolant flow rate are used as variables in the three-dimensional multiphysics model to construct a single-factor multi-condition group. Specifically, the multi-condition groups can include a load current density condition group, a coolant inlet temperature condition group, and a single-cell equivalent coolant flow rate condition group. In the load current density condition group, the coolant inlet temperature and the single-cell equivalent coolant flow rate remain constant. This group is used to analyze the impact of changes in electrochemical reaction intensity and internal heat generation intensity on overall performance. In the coolant inlet temperature condition group, the load current density and the single-cell equivalent coolant flow rate remain constant. This group is used to analyze the impact of changes in external thermal boundaries on the battery temperature field and output performance. In the single-cell equivalent coolant flow rate condition group, the load current density and the coolant inlet temperature remain constant. This group is used to analyze the impact of changes in cooling intensity on heat dissipation and flow resistance.

[0022] Step S3: Perform simulation for each operating condition to obtain simulation results including the working voltage, temperature field, coolant pressure field, and volumetric heat source distribution of a single cell. Step S4: Determine the evaluation indicators based on the simulation results of each working condition; among which, the evaluation indicators include power density, maximum temperature, maximum temperature difference, temperature uniformity index, maximum temperature rise coefficient under unit heat load, and cooling benefit per unit pressure drop. Specifically, the methods for determining each evaluation indicator include: Step S41: Determine the power density based on the load current density and the operating voltage of the single cell, using the following expression:

[0023]

[0024]

[0025] In the formula, This is the operating current of a single battery. For load current density, The effective activation area of ​​a single cell. For the output power of a single battery, This is the operating voltage of a single battery. Power density; the higher the power density, the stronger the output capacity per unit activated area.

[0026] Step S42: Obtain the highest and lowest temperatures in the temperature field and determine the maximum temperature difference, expressed as:

[0027] In the formula, This represents the maximum temperature difference in the battery evaluation area. and These are the highest and lowest temperatures in the battery evaluation area, respectively. Step S43: Obtain the temperature of each sampling point, the average temperature of each sampling point, and the number of sampling points in the temperature field, and determine the temperature uniformity index, expressed as:

[0028] In the formula, This represents the maximum temperature difference in the battery evaluation area. and These are the highest and lowest temperatures in the battery evaluation area, respectively. The temperature uniformity index, For the first Temperature at each sampling point, The average temperature at the sampling points. This represents the number of sampling points; Step S44: Determine the total heat generated inside the battery based on the volumetric heat source term. Based on the highest temperature, coolant inlet temperature, and the total heat generated inside the battery, determine the maximum temperature rise coefficient under unit heat load, expressed as:

[0029]

[0030] In the formula, This refers to the coolant inlet temperature. The total heat generated inside the battery, For volumetric heat source term, For the heat generation calculation region, The maximum temperature rise coefficient under unit heat load is introduced as an evaluation index to eliminate the influence of differences in heat generation intensity under different operating conditions on the evaluation of cooling effect. The smaller the index, the lower the maximum temperature rise caused by unit heat load, and the stronger the ability of the cooling structure to suppress local heat accumulation.

[0031] Step S45: Determine the heat carried away by the coolant based on the coolant mass flow rate, coolant specific heat capacity at constant pressure, coolant outlet temperature, and coolant inlet temperature. The expression is:

[0032] In the formula, The heat carried away by the coolant. This refers to the coolant mass flow rate. The specific heat capacity at constant pressure of the coolant. and These are the coolant outlet temperature and inlet temperature, respectively. Step S46: Obtain the inlet and outlet pressures of the cooling channel in the coolant pressure field, and determine the pressure drop of the cooling channel. Based on the heat carried away by the coolant and the pressure drop of the cooling channel, determine the cooling benefit per unit pressure drop, expressed as:

[0033]

[0034] In the formula, To cool the pressure drop in the flow channel, and These are the inlet and outlet pressures of the cooling channel, respectively. This represents the cooling benefit per unit pressure drop; a higher cooling benefit per unit pressure drop indicates a higher cooling benefit per unit flow resistance.

[0035] To transform the simulation results into comparable and quantifiable evaluation parameters, a unified post-processing was performed on the simulation results for each operating condition before determining the evaluation indicators: temperature field-related indicators (maximum temperature difference and temperature uniformity index) were extracted within the same battery evaluation region; coolant inlet and outlet temperature differences and pressure losses were calculated at the same coolant inlet and outlet sections; and total internal heat generation was obtained by integrating the volumetric heat source term within the same heat generation calculation region. This processing does not change the original simulation results but is only used to ensure the comparability of evaluation indicators between different operating conditions. For example, for all operating conditions, the highest and lowest temperatures were sampled and extracted within the same battery evaluation region in the temperature field; and the volumetric heat source term was within the same heat generation calculation region.

[0036] Maximum temperature, minimum temperature, average temperature, maximum temperature difference, and temperature uniformity index are temperature field characteristic indicators used to evaluate the internal temperature level and temperature distribution uniformity of the battery. Single-cell operating current, single-cell output power, and power density are output performance indicators used to characterize the energy conversion capability of a proton exchange membrane fuel cell under different operating conditions. Heat carried away by the coolant, total internal heat generation, and maximum temperature rise coefficient under unit heat load are thermal load response indicators used to evaluate the change in maximum temperature rise of the battery under different heat generation intensities. Cooling benefit per unit pressure drop is a flow resistance matching indicator used to evaluate the pressure loss generated by the coolant flowing within the cooling channels.

[0037] Since different evaluation indicators have different dimensions and numerical ranges, this embodiment performs dimensionless processing on each indicator before calculating the comprehensive evaluation score, as follows.

[0038] Step S5: Power density, temperature uniformity index and cooling benefit per unit pressure drop are used as positive indicators, and maximum temperature, maximum temperature difference and maximum temperature rise coefficient per unit heat load are used as negative indicators. Dimensionless normalization processing is performed on each indicator within the same multi-condition group to obtain the normalized evaluation value of each evaluation indicator. Specifically, positive indicators are normalized using the following formula:

[0039] The following formula is used to normalize the contrarian indicator:

[0040] In the formula, For the first Evaluation indicators under various working conditions The original value, This is the normalized evaluation value of the evaluation indicator. and These are the maximum and minimum values ​​of the evaluation index within the same single-factor multi-condition group, respectively.

[0041] Step S6: The normalized evaluation values ​​of all evaluation indicators are weighted and summed to obtain the comprehensive evaluation score for each working condition. The expression for the comprehensive evaluation score for each working condition is:

[0042] In the formula, Let k be the comprehensive evaluation score for the k-th working condition. , , , , and These are the normalized evaluation values ​​for power density, maximum temperature, maximum temperature difference, temperature uniformity index, maximum temperature rise coefficient per unit heat load, and cooling benefit per unit pressure drop under the k-th operating condition, respectively. , , , , , All values ​​are weights, and the sum of all weights is 1. A higher overall evaluation score indicates better overall performance in terms of output performance, thermal safety, thermal load response capability, and flow resistance matching. For example, the weights can be adjusted according to the cooling channel optimization objectives, but should satisfy 0 ≤ w i ≤1、Σw i =1, and preferably satisfying This constraint ensures that the comprehensive evaluation results focus more on reflecting thermal safety, heat load suppression capability, and flow resistance matching relationship.

[0043] In this embodiment, power density, temperature field characteristics, thermal load response capability, and flow resistance matching relationship are incorporated into the same evaluation system, avoiding the one-sidedness caused by using only a single performance index for evaluation. Introducing the maximum temperature rise coefficient under unit heat load weakens the impact of differences in total heat generation within different operating conditions on the evaluation of cooling effect, and more directly reflects the cooling structure's ability to suppress local heat accumulation. The cooling benefit per unit pressure drop characterizes the matching relationship between cooling benefit and flow resistance, establishing a correlation between the heat carried by the coolant and pressure loss within the same index. Through normalization and weighted summation within the same single-factor multi-operating-condition group, evaluation indicators with different dimensions and numerical ranges can be transformed into a unified comprehensive evaluation score, providing a quantitative basis for benchmark evaluation before cooling channel optimization and performance comparison between different structural schemes. This method can establish a unified quantitative evaluation scale between output performance, thermal safety, thermal load response capability, and the matching relationship between cooling benefit and flow resistance, accurately reflecting the cooling effect of the cooling channel structure. It can serve as a benchmark evaluation index before cooling channel structure optimization and a performance comparison index between different cooling channel structure schemes.

[0044] A second embodiment of the present invention provides a multi-condition comprehensive evaluation device for proton exchange membrane fuel cells, comprising: The model building module is used to obtain the structural parameters, operating boundary parameters, and cooling channel parameters of the proton exchange membrane fuel cell. Based on the structural parameters, operating boundary parameters, and cooling channel parameters, a three-dimensional multiphysics model including electrochemical reaction, mass transfer, heat transfer, and coolant flow is established. The operating condition construction module is used to construct single-factor multi-operating condition groups by taking load current density, coolant inlet temperature and coolant flow rate as variables in the three-dimensional multiphysics model. The simulation module is used to run simulations for each operating condition and obtain simulation results including the operating voltage, temperature field, coolant pressure field, and volumetric heat source distribution of a single cell. The evaluation module is used to determine evaluation indicators based on the simulation results of each working condition; The evaluation indicators include power density, maximum temperature, maximum temperature difference, temperature uniformity index, maximum temperature rise coefficient under unit heat load, and cooling benefit per unit pressure drop. All evaluation indicators are weighted and summed to obtain the comprehensive evaluation score for each operating condition.

[0045] Example In this embodiment, COMSOL Multiphysics software is used for three-dimensional multiphysics coupling calculations.

[0046] Taking a representative single-cell repeating unit in a 1 kW-class proton exchange membrane fuel cell as an example, the 1 kW-class PEMFC stack in this embodiment consists of 18 single cells connected in series. The effective activation region size of a single cell is 130 mm × 130 mm, and the effective activation area is 169 cm². 2 The established three-dimensional multiphysics model is shown below. Figure 2 A load current density of 0.45 A / cm² is selected. 2 The baseline operating conditions were set at a coolant inlet temperature of 293.15 K and an equivalent coolant flow rate of 0.11 L / min for a single cell. The anode and cathode inlet pressures were both 150 kPa, the anode hydrogen excess coefficient was 1.3, the cathode air excess coefficient was 2.0, the cooling medium was deionized water, and the total coolant flow rate of the stack was 2.0 L / min. Based on the load current density and the effective activated area of ​​a single cell, the operating current of a single cell was calculated to be approximately 76 A. Under these baseline conditions, a three-dimensional multiphysics steady-state coupling solution was performed, yielding an operating voltage of approximately 0.75 V for a single cell. Based on the number of cells, an equivalent conversion yielded an operating voltage of approximately 13.5 V for the entire stack, corresponding to an output power of approximately 1.03 kW. The relevant parameters of the example model and the baseline operating conditions are shown in Table 1.

[0047] Table 1. Relevant parameters of the embodiment model and the baseline operating condition.

[0048] Construct single-factor multi-condition groups, as detailed in Table 2: Table 2 Multi-condition simulation parameter settings

[0049] Simulations were performed under the baseline operating conditions, and the calculation results of the relevant parameters are shown in Table 3.

[0050] Table 3 Calculation results of relevant parameters under the reference working condition

[0051] After completing the steady-state simulation of the load current density working condition group, the results of temperature field, heat source term and pressure field were extracted from the unified evaluation area and the unified cross-sectional location. The relevant parameter calculation results are shown in Table 4.

[0052] Table 4 Simulation Results and Index Calculation for Load Current Density Conditions

[0053] Set the weights as follows: =0.25, =0.15, =0.10, =0.10, =0.20, =0.20, and the relevant indicators and their meanings for each working condition are shown in Table 5: Table 5. Comprehensive Evaluation Indicators and Weighting Settings

[0054] This weighting setting ensures that the combined weight of the thermal safety index, thermal load response capability index, and flow resistance matching index is greater than the weight of the output performance index, which is in line with the evaluation principle in cooling channel optimization that does not solely pursue output power as the only objective.

[0055] By combining the normalization process and the comprehensive evaluation function, the normalized results and comprehensive evaluation values ​​of the load current density operating condition group are obtained, as shown in Table 6.

[0056] Table 6. Normalized Results and Comprehensive Evaluation of Load Current Density Operating Conditions

[0057] The above results illustrate that the comprehensive evaluation method of this invention can quantitatively characterize the comprehensive operating status within the same single-factor operating condition group, thereby selecting suitable operating conditions. Similarly, the coolant inlet temperature operating condition group and the single-cell equivalent coolant flow rate operating condition group can be evaluated using the same index extraction, normalization, and weighted scoring rules, which will not be elaborated here.

[0058] Example Effect Description The comprehensive evaluation score obtained using the method of this invention can be used as a benchmark evaluation index before optimizing the cooling channel structure, and can also be used as a performance comparison index between different cooling channel structure schemes. During the structural optimization process, the comprehensive evaluation score can be used as one of the optimization objectives, and the highest temperature, the maximum temperature difference, the maximum temperature rise coefficient under unit heat load, and the cooling channel pressure drop can be used as constraints to achieve a balance between enhancing heat dissipation and controlling flow resistance.

[0059] By employing the method of this invention, normalized index values ​​and comprehensive evaluation scores for each operating condition can be obtained within the same single-factor multi-condition group. Compared to using only the highest temperature or power density as evaluation criteria, this method can more comprehensively reflect the impact of cooling channel structure and operating parameters on the overall operating status of proton exchange membrane fuel cells.

[0060] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A comprehensive evaluation method for proton exchange membrane fuel cells under multiple operating conditions, characterized in that, include: The structural parameters, operating boundary parameters, and cooling channel parameters of the proton exchange membrane fuel cell are obtained, and a three-dimensional multiphysics model is established based on the structural parameters, operating boundary parameters, and cooling channel parameters. Load current density, coolant inlet temperature, and coolant flow rate were used as variables in a three-dimensional multiphysics model to construct a single-factor multi-condition group. Simulations were run for each operating condition to obtain simulation results including the operating voltage, temperature field, coolant pressure field, and volumetric heat source distribution of a single cell. Based on the simulation results for each working condition, the evaluation indicators are determined; The evaluation indicators include power density, maximum temperature, maximum temperature difference, temperature uniformity index, maximum temperature rise coefficient under unit heat load, and cooling benefit per unit pressure drop. The weighted sum of all evaluation indicators is used to obtain the comprehensive evaluation score for each working condition.

2. The multi-condition comprehensive evaluation method for proton exchange membrane fuel cells according to claim 1, characterized in that, The three-dimensional multiphysics model includes one or more computational domains such as the anode channel, cathode channel, gas diffusion layer, catalyst layer, proton exchange membrane, bipolar plate, and cooling channel.

3. The multi-condition comprehensive evaluation method for proton exchange membrane fuel cells according to claim 1, characterized in that, Based on the simulation results for each working condition, evaluation indicators are determined, including: The power density is determined based on the load current density and the single-cell operating voltage.

4. The multi-condition comprehensive evaluation method for proton exchange membrane fuel cells according to claim 1, characterized in that, Based on the simulation results for each working condition, evaluation indicators are determined, including: Obtain the highest and lowest temperatures in the temperature field and determine the maximum temperature difference; Obtain the temperature of the sampling points, the average temperature of the sampling points, and the number of sampling points in the temperature field, and determine the temperature uniformity index.

5. The multi-condition comprehensive evaluation method for proton exchange membrane fuel cells according to claim 1, characterized in that, Based on the simulation results for each working condition, evaluation indicators are determined, including: The total heat generated inside the battery is determined based on the volumetric heat source term. The maximum temperature rise coefficient under unit heat load is determined based on the highest temperature, the coolant inlet temperature, and the total heat generated inside the battery.

6. The multi-condition comprehensive evaluation method for proton exchange membrane fuel cells according to claim 1, characterized in that, Based on the simulation results for each working condition, evaluation indicators are determined, including: The amount of heat carried away by the coolant is determined based on the coolant mass flow rate, coolant specific heat capacity at constant pressure, coolant outlet temperature, and coolant inlet temperature. Obtain the inlet and outlet pressures of the cooling channel in the coolant pressure field, determine the pressure drop of the cooling channel, and determine the cooling benefit per unit pressure drop based on the heat carried away by the coolant and the pressure drop of the cooling channel.

7. The multi-condition comprehensive evaluation method for proton exchange membrane fuel cells according to claim 1, characterized in that, After determining the evaluation indicators based on the simulation results for each working condition, the following also includes: Power density, temperature uniformity index, and cooling benefit per unit pressure drop are used as positive indicators, while maximum temperature, maximum temperature difference, and maximum temperature rise coefficient per unit heat load are used as negative indicators. Dimensionless normalization is performed on each indicator within the same multi-condition group to obtain normalized evaluation values.

8. The multi-condition comprehensive evaluation method for proton exchange membrane fuel cells according to claim 7, characterized in that, The weighted sum of all evaluation indicators yields the comprehensive evaluation score for each working condition, including: The normalized evaluation values ​​of all evaluation indicators are weighted and summed to obtain the comprehensive evaluation score for each working condition.

9. The multi-condition comprehensive evaluation method for proton exchange membrane fuel cells according to claim 8, characterized in that, The expression for the comprehensive evaluation score is: In the formula, Let k be the comprehensive evaluation score for the k-th working condition. , , , , and These are the normalized evaluation values ​​for power density, maximum temperature, maximum temperature difference, temperature uniformity index, maximum temperature rise coefficient per unit heat load, and cooling benefit per unit pressure drop under the k-th operating condition, respectively. , , , , , All are weights.

10. A multi-condition comprehensive evaluation device for proton exchange membrane fuel cells, characterized in that, include: The model building module is used to obtain the structural parameters, operating boundary parameters, and cooling channel parameters of the proton exchange membrane fuel cell. Based on the structural parameters, operating boundary parameters, and cooling channel parameters, a three-dimensional multiphysics model including electrochemical reaction, mass transfer, heat transfer, and coolant flow is established. The operating condition construction module is used to construct single-factor multi-operating condition groups by taking load current density, coolant inlet temperature and coolant flow rate as variables of the three-dimensional multiphysics model. The simulation module is used to run simulations for each operating condition and obtain simulation results including the operating voltage, temperature field, coolant pressure field, and volumetric heat source distribution of a single cell. The evaluation module is used to determine evaluation indicators based on the simulation results of each working condition; The evaluation indicators include power density, maximum temperature, maximum temperature difference, temperature uniformity index, maximum temperature rise coefficient under unit heat load, and cooling benefit per unit pressure drop. All evaluation indicators are weighted and summed to obtain the comprehensive evaluation score for each operating condition.

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