Method, device, equipment, storage medium and program product for determining water distribution state in fuel cell plane

Abstract

The application relates to a fuel cell in-plane water distribution state determination method, device, equipment, storage medium and program product. The method comprises the following steps: acquiring current density distribution signals and physical prior conditions of different regions in a fuel cell; the physical prior condition represents a physical risk of water management problems occurring under different operating conditions; a characteristic factor corresponding to the current density distribution signal of each region is determined through a pre-established multi-physical field model; the characteristic factor is used to represent the influence direction of the local current density of the corresponding region when the water distribution state parameter changes; a target water distribution state of the fuel cell in-plane is determined based on the characteristic factor and the physical prior condition; the target water distribution state comprises water state change mechanisms of different regions. The method can provide accurate diagnostic basis for fuel cell water management regulation.

Description

Technical Field

[0001] This application relates to the field of fuel cell technology, and in particular to a method, apparatus, device, storage medium, and program product for determining the water distribution state within a fuel cell surface. Background Technology

[0002] With the rapid development of fuel cell technology, the demand for proton exchange membrane fuel cells (PEMFCs) in applications such as long-distance heavy-duty transportation, marine propulsion, and stationary power generation is increasing, which in turn places higher demands on the power density, energy conversion efficiency, and service life of the cells. To improve system power and reduce unit cost, the active area of ​​individual fuel cells is continuously expanding. However, as the fuel cell area increases, the transport paths of reactant gases and liquid water in the long flow channels are significantly lengthened, and the spatial non-uniformity of the in-plane multiphysics field is drastically amplified.

[0003] In existing technologies, the identification of the water distribution state inside fuel cells is mainly done through direct visualization measurement techniques, such as optically transparent cell observation, X-ray imaging, neutron imaging, and nuclear magnetic resonance imaging. These techniques can intuitively present the water distribution state inside the cell and have advanced in-situ visualization value, and are widely used in laboratory research.

[0004] However, direct visualization technology is expensive and requires structural modifications to fuel cells, making it difficult to apply to online monitoring of fuel cells. It also lacks the ability to identify specific issues related to water distribution inside fuel cells. Summary of the Invention

[0005] Therefore, it is necessary to provide a method, apparatus, equipment, storage medium, and program product for determining the water distribution state within a fuel cell surface, addressing the aforementioned technical problems.

[0006] In a first aspect, this application provides a method for determining the water distribution state within a fuel cell surface, including:

[0007] The current density distribution signal and physical prior conditions in different regions of the fuel cell surface are obtained; the physical prior conditions characterize the physical risk of water management problems under different operating conditions.

[0008] By using a pre-established multiphysics model, the characteristic factors corresponding to the current density distribution signals in each region are determined; the characteristic factors are used to characterize the direction of influence of changes in water distribution state parameters on the local current density in the corresponding region.

[0009] Based on characteristic factors and physical prior conditions, the target water distribution state within the fuel cell surface is determined; the target water distribution state includes the water state change mechanism in different regions.

[0010] In one embodiment, the characteristic factors corresponding to the current density distribution signals of each region are determined by a pre-established multiphysics model, including:

[0011] Based on the multiphysics model, the current density distribution signal was obtained in different regions, and the water state parameters in the current density expression were determined. The water state parameters include the liquid water saturation in the flow channel, the liquid water saturation in the catalyst layer, the membrane water content, and the membrane water content in the catalyst layer.

[0012] Based on the current density expression, partial derivatives are calculated with respect to each water state parameter to determine the characteristic factors.

[0013] In one embodiment, the process of determining the physical prior conditions includes:

[0014] Obtain gas-water distribution information of fuel cells under different operating conditions;

[0015] Based on a pre-established discrete model, the fuel cell under various operating conditions is simulated to obtain gas and water distribution information in different regions.

[0016] Based on the gas and water distribution information, the physical risks of water management problems in different regions under different operating conditions are determined, and these physical risks are used as physical prior conditions.

[0017] In one embodiment, determining the target water distribution state within the fuel cell surface based on characteristic factors and physical prior conditions includes:

[0018] To obtain the variation characteristics of current density distribution signals in different regions;

[0019] The target water distribution state is determined based on the change characteristics, characteristic factors, and physical prior conditions.

[0020] In one embodiment, determining the target water distribution state based on change characteristics, characteristic factors, and physical prior conditions includes:

[0021] Based on the variation characteristics, determine the variation characteristics of the current density distribution signal in the gas inlet region and the middle and lower downstream regions of the gas;

[0022] Given that the current density in the gas inlet region is increasing, the membrane water content is dominant among the characteristic factors corresponding to the gas inlet region, and the physical prior conditions indicate that there is a risk of membrane drying in the gas inlet region, the target water distribution state is determined to be improved membrane hydration state.

[0023] Given that the current density in the gas inlet region is decreasing, the membrane water content is dominant among the characteristic factors corresponding to the gas inlet region, and the physical prior conditions characterize that there is a risk of membrane drying in the gas inlet region, the target water distribution state is determined to be membrane drying.

[0024] Given that the current density in the gas inlet region is decreasing, the liquid water saturation in the flow channel is dominant among the characteristic factors corresponding to the gas inlet region, and the physical prior conditions characterize that there is a risk of flooding in the gas inlet transition region, the target water distribution state is determined to be flow channel flooding.

[0025] Given that the current density in the downstream region of the gas shows a decreasing trend, the liquid water saturation is the dominant characteristic factor in the downstream region of the gas, and the physical prior conditions indicate that there is a risk of flooding in the downstream region of the gas, the target water distribution state is determined to be flooding.

[0026] In one embodiment, the feature factors include at least one of the following:

[0027] The first characteristic factor characterizes the effect of the liquid water saturation in the flow channel on the local current density; the first characteristic factor is negative.

[0028] The second characteristic factor characterizes the effect of the liquid water saturation in the flow channel of the porous medium on the local current density; the second characteristic factor is negative.

[0029] The third characteristic factor characterizes the effect of the liquid water saturation in the catalyst layer on the local current density; the third characteristic factor is negative.

[0030] The fourth characteristic factor characterizes the effect of the water content in the catalyst layer on the local current density; the fourth characteristic factor is positive.

[0031] The fifth characteristic factor characterizes the effect of membrane water content in the proton exchange membrane on the local current density; the fifth characteristic factor is positive.

[0032] Secondly, this application also provides a device for determining the water distribution state within a fuel cell surface, comprising:

[0033] The acquisition module is used to acquire the current density distribution signal and physical prior conditions in different regions within the fuel cell surface; the physical prior conditions characterize the physical risks of water management problems occurring under different operating conditions.

[0034] The determination module is used to determine the characteristic factors corresponding to the current density distribution signals of each region through a pre-established multiphysics model; the characteristic factors are used to characterize the direction of influence of changes in water distribution state parameters on the local current density of the corresponding region.

[0035] The distribution module is used to determine the target water distribution state within the fuel cell surface based on characteristic factors and physical prior conditions; the target water distribution state includes the water state change mechanism in different regions.

[0036] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0037] The current density distribution signal and physical prior conditions in different regions of the fuel cell surface are obtained; the physical prior conditions characterize the physical risk of water management problems under different operating conditions.

[0038] By using a pre-established multiphysics model, the characteristic factors corresponding to the current density distribution signals in each region are determined; the characteristic factors are used to characterize the direction of influence of changes in water distribution state parameters on the local current density in the corresponding region.

[0039] Based on characteristic factors and physical prior conditions, the target water distribution state within the fuel cell surface is determined; the target water distribution state includes the water state change mechanism in different regions.

[0040] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0041] The current density distribution signal and physical prior conditions in different regions of the fuel cell surface are obtained; the physical prior conditions characterize the physical risk of water management problems under different operating conditions.

[0042] By using a pre-established multiphysics model, the characteristic factors corresponding to the current density distribution signals in each region are determined; the characteristic factors are used to characterize the direction of influence of changes in water distribution state parameters on the local current density in the corresponding region.

[0043] Based on characteristic factors and physical prior conditions, the target water distribution state within the fuel cell surface is determined; the target water distribution state includes the water state change mechanism in different regions.

[0044] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0045] The current density distribution signal and physical prior conditions in different regions of the fuel cell surface are obtained; the physical prior conditions characterize the physical risk of water management problems under different operating conditions.

[0046] By using a pre-established multiphysics model, the characteristic factors corresponding to the current density distribution signals in each region are determined; the characteristic factors are used to characterize the direction of influence of changes in water distribution state parameters on the local current density in the corresponding region.

[0047] Based on characteristic factors and physical prior conditions, the target water distribution state within the fuel cell surface is determined; the target water distribution state includes the water state change mechanism in different regions.

[0048] The aforementioned method, apparatus, equipment, storage medium, and program products for determining the water distribution state within a fuel cell surface acquire current density distribution signals and physical prior conditions in different regions within the fuel cell surface. These physical prior conditions characterize the physical risks of water management problems under different operating conditions. A pre-established multiphysics model determines the characteristic factors corresponding to the current density distribution signals in each region. These characteristic factors characterize the direction of influence of changes in water distribution state parameters on the local current density of the corresponding region. Based on the characteristic factors and physical prior conditions, the target water distribution state within the fuel cell surface is determined. The target water distribution state includes the water state change mechanism in different regions. This method achieves accurate differentiation of different water management problems such as membrane dryness, flooding, and flooding mitigation. Compared to existing technologies, it does not require special modifications to the fuel cell, offering advantages such as low cost and ease of engineering implementation. Furthermore, the analysis of characteristic factors provides accurate diagnostic basis for fuel cell water management and control, helping to improve the performance maintenance capability and service life of the fuel cell system during long-term operation. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 This is an application environment diagram of a method for determining the water distribution state within a fuel cell surface in one embodiment.

[0051] Figure 2 This is one of the flowcharts illustrating a method for determining the water distribution state within a fuel cell surface in one embodiment;

[0052] Figure 3 This is a second flowchart illustrating a method for determining the water distribution state within a fuel cell surface in one embodiment.

[0053] Figure 4 This is the third flowchart illustrating a method for determining the water distribution state within a fuel cell surface in one embodiment;

[0054] Figure 5 This is the fourth flowchart illustrating a method for determining the water distribution state within a fuel cell surface in one embodiment;

[0055] Figure 6 This is the fifth flowchart illustrating a method for determining the water distribution state within a fuel cell surface in one embodiment;

[0056] Figure 7 This is a diagram showing the three-stage variation of the current density distribution during the steady-state operation of a fuel cell in one embodiment.

[0057] Figure 8 This is a schematic diagram of the water content of the proton exchange membrane in one embodiment;

[0058] Figure 9 This is a schematic diagram of the water content in the cathode catalyst layer in one embodiment;

[0059] Figure 10 This is a schematic diagram of the liquid water saturation in the cathode catalyst layer in one embodiment;

[0060] Figure 11 This is a schematic diagram of the oxygen concentration in the cathode catalyst layer in one embodiment;

[0061] Figure 12 This is a flow field structure diagram that leads to potential flooding problems in the inlet region flow channel in one embodiment.

[0062] Figure 13 This is a structural block diagram of a device for determining the water distribution state within a fuel cell surface in one embodiment. Detailed Implementation

[0063] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0064] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0065] With the rapid development of fuel cell technology, the demand for proton exchange membrane fuel cells (PEMFCs) in applications such as long-distance heavy-duty transportation, marine propulsion, and stationary power generation is increasing, which in turn places higher demands on the power density, energy conversion efficiency, and service life of the cells. To improve system power and reduce unit cost, the active area of ​​individual fuel cells is continuously expanding. However, as the fuel cell area increases, the transport paths of reactant gases and liquid water in the long flow channels are significantly lengthened, and the spatial non-uniformity of the in-plane multiphysics field is drastically amplified.

[0066] In existing technologies, the identification of the water distribution state inside fuel cells is mainly done through direct visualization measurement techniques, such as optically transparent cell observation, X-ray imaging, neutron imaging, and nuclear magnetic resonance imaging. These techniques can intuitively present the water distribution state inside the cell and have advanced in-situ visualization value, and are widely used in laboratory research.

[0067] However, direct visualization technology is expensive and requires structural modifications to fuel cells, making it difficult to apply to online monitoring of fuel cells. It also lacks the ability to identify specific issues related to water distribution inside fuel cells.

[0068] In view of the above-mentioned technical problems, this application provides a method for determining the water distribution state in the fuel cell surface. The following embodiments will specifically illustrate the method for determining the water distribution state in the fuel cell surface.

[0069] The method for determining the water distribution state within the fuel cell surface provided in this application embodiment can be applied to, for example... Figure 1The computer device shown includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When executed by the processor, the computer program implements a method for determining the water distribution state within a fuel cell surface. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0070] Those skilled in the art will understand that Figure 1 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0071] In one exemplary embodiment, such as Figure 2 As shown, a method for determining the water distribution state within a fuel cell surface is provided, which can be applied to... Figure 1 The following explanation uses computer equipment as an example, including:

[0072] S201, acquire the current density distribution signal and physical prior conditions in different regions within the fuel cell surface.

[0073] Among them, physical prior conditions characterize the physical risks of water management problems occurring under different operating conditions. These physical prior conditions can be determined in advance through simulation and stored in computer equipment, or they can be calculated in real time by computer equipment.

[0074] In this embodiment, the computer equipment can acquire the current density distribution signals of different regions through a partitioned current acquisition device installed inside the fuel cell. This partitioned current acquisition device is typically configured as a partitioned current acquisition PCB board, which divides the fuel cell into multiple independent test areas, each corresponding to a location within the cell surface. When the fuel cell is operating in a constant current steady-state condition, each test area outputs local current density data in real time through sampling resistors or current sensors, and transmits this data to the computer equipment. The computer equipment stores and monitors this data in a time-series manner, thereby obtaining the current density distribution signals of different regions within the cell surface and their changing trends over time, which serve as external characteristic criteria for subsequent identification of water state changes.

[0075] For the physical prior conditions, they can be predetermined as follows: First, computer equipment acquires gas-liquid distribution information of the fuel cell under different operating conditions, including at least the fuel cell's operating parameters, structural parameters, and material parameters. Then, the gas-liquid distribution information is input into a pre-established discrete model. Based on this information, the computer equipment performs numerical simulations of the gas-liquid flow and distribution inside the fuel cell under each operating condition, thereby obtaining the gas-liquid distribution state information in different regions. This gas-liquid distribution state information includes the membrane water content. , Catalytic layer membrane water content (i.e., the content of water in the cathode catalyst layer membrane) and the saturation of liquid water in the catalyst layer. (i.e., the liquid water saturation of the cathode catalyst layer) and the oxygen concentration of the catalyst layer. The distribution of oxygen concentration (i.e., in the cathode catalyst layer) and other parameters at different locations within the fuel cell surface. Among these, the membrane water content... Characterizing the water content of the proton exchange membrane in different in-plane regions of the fuel cell; catalytic layer membrane water content. Characterizing the hydration state of the ionomers in the cathode catalyst layer; liquid water saturation of the catalyst layer. Characterizing the degree to which the pores of the catalyst layer are occupied by liquid water; oxygen concentration in the catalyst layer. By characterizing the oxygen concentration levels in different regions of the cathode catalyst layer, and based on the gas-water distribution information, the computer equipment can identify which regions in the fuel cell are prone to membrane drying or flooding under different operating conditions, and use these physical risks as physical prior conditions for that region.

[0076] S202 determines the characteristic factors corresponding to the current density distribution signals in each region by using a pre-established multiphysics model.

[0077] Among them, the characteristic factor is used to characterize the direction of influence of changes in water distribution state parameters on the local current density of the corresponding region; the multiphysics model is a mathematical model that is pre-built and stored in a computer device to describe the coupling relationship between the local current density and water distribution state inside the fuel cell, covering the coupling effects of multiple physical fields such as electrochemical reaction kinetics, gas mass transfer, membrane hydration state and ohmic polarization.

[0078] In this embodiment, the computer device inputs the current density distribution signal into a multiphysics model to obtain the current density expression for each region. This expression characterizes the relationship between the local current density and various physical quantities. Subsequently, the computer device identifies four core parameters related to the water distribution state from these expressions: the liquid water saturation in the flow channel, the liquid water saturation in the catalyst layer, the membrane water content, and the membrane water content in the catalyst layer. Under steady-state operating conditions, the change in local current density can be considered as the superposition of the changes in these four core water state variables. Therefore, by taking the partial derivatives of each water state parameter, the computer device can obtain the characteristic factors corresponding to each water state parameter.

[0079] S203, based on characteristic factors and physical prior conditions, determines the target water distribution state within the fuel cell surface.

[0080] The target water distribution status includes the water state change mechanism in different regions.

[0081] In this embodiment, the computer device first acquires the variation characteristics of the current density distribution signal in the gas inlet region and the downstream region of the gas, i.e., whether the local current density in each region is increasing or decreasing. Then, the computer device comprehensively judges the variation characteristics, characteristic factors, and physical prior conditions to obtain the water state change mechanism in each region.

[0082] The aforementioned method for determining the water distribution state within a fuel cell surface involves acquiring current density distribution signals and physical prior conditions in different regions of the fuel cell surface. These physical prior conditions characterize the physical risks of water management problems under different operating conditions. A pre-established multiphysics model is used to determine the characteristic factors corresponding to the current density distribution signals in each region. These characteristic factors characterize the direction of influence on the local current density of the corresponding region when water distribution state parameters change. Based on the characteristic factors and physical prior conditions, the target water distribution state within the fuel cell surface is determined. The target water distribution state includes the water state change mechanism in different regions. This method achieves accurate differentiation of different water management problems such as membrane dryness, flooding, and flooding mitigation. Compared to existing technologies, it does not require special modifications to the fuel cell, offering advantages such as low cost and ease of engineering implementation. Furthermore, the analysis of characteristic factors provides accurate diagnostic basis for fuel cell water management and control, helping to improve the performance maintenance capability and service life of the fuel cell system during long-term operation.

[0083] In an exemplary embodiment, the phrase "determining the characteristic factors corresponding to the current density distribution signals of each region through a pre-established multiphysics model" in S202 above, such as... Figure 3 As shown, it includes:

[0084] S301, based on a multiphysics model, obtains the current density expression of the current density distribution signal in different regions, and determines the water state parameters in the current density expression.

[0085] The water state parameters include the liquid water saturation in the flow channel, the liquid water saturation in the catalyst layer, the membrane water content, and the membrane water content in the catalyst layer.

[0086] In this embodiment of the application, since the core of the multiphysics model is to establish a quantitative mapping relationship between the local current density of the fuel cell and the water distribution state, the computer device can obtain the expression of the change of current density in each region with each physical quantity based on the multiphysics model. This expression can be represented by the relation (1), which is shown below:

[0087] (1);

[0088] in, Represents the current density distribution signal; Indicates the influence coefficient of water content; Indicates the effective reaction area; Indicates the reference current; Indicates the oxygen concentration in the catalyst layer; Indicates reference oxygen concentration; Indicates the cathode reaction order; Indicates the activation energy of the reaction; Represents the ideal gas constant; Indicates battery temperature; Indicates reference temperature; Indicates the cathode transfer coefficient; Denotes Faraday's constant; This indicates a cathode overpotential.

[0089] Among them, the influence coefficient of water content In general, it is mainly affected by the water content of the catalytic layer membrane. The influence is as follows: When the membrane water content in the cathode catalyst layer increases, more water molecules bind to the sulfonate sites in the ionomers, enhancing proton conductivity and thus favoring the oxygen reduction reaction; consequently, the influence coefficient of water content increases. Conversely, when the membrane water content in the cathode catalyst layer decreases, the ionomers dehydrate, proton conductivity decreases, and the influence coefficient of water content decreases. Therefore, this influence coefficient of water content directly reflects the impact of the hydration state of the ionomers in the catalyst layer on the electrochemical reaction kinetics.

[0090] For effective reaction area In general, it is mainly affected by the saturation of liquid water in the catalyst layer. The impact is as follows: As the saturation of liquid water in the catalyst layer increases, liquid water gradually occupies the pores and reaction sites on the catalyst layer surface, forming a liquid film on the catalyst particle surface. This hinders the diffusion and arrival of reactant gases, thus reducing the effective area for the actual electrochemical reaction. Conversely, when the liquid water saturation decreases, the covered reaction sites are re-exposed, and the effective reaction area recovers. Therefore, this effective reaction area also reflects the impact of the degree of water flooding in the catalyst layer on the usable area for the electrochemical reaction.

[0091] Regarding the oxygen concentration in the catalyst layer In this regard, the saturation of liquid water in the flow channel and porous medium (including the saturation of liquid water in the flow channel) is affected. and the saturation of liquid water in the catalyst layer The effects of these factors are as follows: Firstly, as the liquid water saturation in the flow channel increases, the cross-sectional area for gas flow decreases, reducing the convective mass transfer capacity of oxygen from the flow channel to the porous media layer, thus decreasing the amount of gas entering the catalyst layer. Secondly, as the liquid water saturation in the catalyst layer increases, the effective diffusion coefficient of oxygen in the pores of the catalyst layer decreases, and the diffusion path becomes longer, further exacerbating the difficulty for oxygen to reach the reaction sites. The combined effect of these two factors significantly reduces the oxygen concentration in the catalyst layer, thereby inhibiting the electrochemical reaction rate.

[0092] For cathode overpotential In general, its influence on membrane water content is mainly through ohmic polarization. and the content of water in the catalytic layer membrane The impact is as follows: Membrane water content reflects the degree of hydration within the proton exchange membrane. When the membrane water content decreases, the proton conductivity of the membrane decreases, the impedance increases, and the resulting ohmic polarization overpotential increases. Simultaneously, the membrane water content in the catalyst layer also affects the proton conductivity of the ionomers in the catalyst layer. When the membrane water content in the catalyst layer is insufficient, the impedance of the ionomers increases, further increasing local ohmic polarization losses. Therefore, both the membrane water content and the catalyst layer membrane water content jointly determine the magnitude of the ohmic polarization component in the cathode overpotential.

[0093] In other words, the complete process by which changes in the water state affect the local current can be described by four core water state parameters, five core influence paths, and four indirect parameters. The four core water state parameters are: the saturation of liquid water in the flow channel... (Used to characterize the volume fraction of liquid water in the flow channel), liquid water saturation in the catalyst layer. (Used to characterize the degree to which the pores of the catalyst layer are occupied by liquid water), membrane water content (Used to characterize the number of water molecules bound to each sulfonate site within the proton exchange membrane) and the water content of the catalyst layer membrane. (Used to characterize the water content in the ionomers within the catalyst layer). These water state parameters each influence the local current density through the different physical paths described above, forming the basis for subsequent feature factor extraction and water state diagnosis.

[0094] S302, based on the current density expression, partial derivatives are obtained with respect to each water state parameter to determine the characteristic factor.

[0095] In this embodiment of the application, under steady-state operating conditions, the local current density The change can be regarded as the saturation of liquid water in the flow channel , Catalytic layer liquid water saturation Membrane water content and the content of water in the catalytic layer membrane The total differential. Based on the current density expression, the computer device calculates the partial derivatives of each water state parameter to obtain the characteristic factors corresponding to each water state parameter, i.e., relation (2)-relation (5). Among them, the absolute value of the partial derivative reflects the sensitivity of the local current density to the change of the water state parameter. That is, the larger the absolute value, the more sensitive the current density of the region is to the change of this type of water state. A positive partial derivative indicates that the local current density increases when the water state parameter increases, and a negative partial derivative indicates that the local current density decreases when the water state parameter increases. Relation (2)-relation (5) are shown below:

[0096] (2);

[0097] (3);

[0098] (4);

[0099] (5);

[0100] in, This indicates the oxygen concentration in the cathode catalyst layer; This indicates the resistance to oxygen transport in the gas diffusion layer; This indicates the resistance to oxygen transport in the catalyst layer; An intermediate variable representing water content; The transfer coefficient for the oxygen reduction reaction; Indicates the operating temperature of the fuel cell; This represents an intermediate variable related to voltage; This represents an intermediate variable related to voltage; Indicates the density of dance practice; It represents the equivalent weight of a discrete substance.

[0101] Computer equipment can obtain five characteristic factors, namely the first characteristic factor, of the influence of the effluent state on the local current density through relations (2)-relation (5). Second characteristic factor Third characteristic factor Fourth characteristic factor and the fifth characteristic factor These five characteristic factors can be represented by relations (6) to (10), which are shown below:

[0102] (6);

[0103] (7);

[0104] (8);

[0105] (9);

[0106] (10);

[0107] Among them, the first characteristic factor The effect of liquid water saturation in the flow channel on local current density is characterized by the fact that as the amount of liquid water in the channel increases, the effective oxygen concentration decreases, and the local current density decreases; therefore, the first characteristic factor is negative. The second characteristic factor... The effect of liquid water saturation in a porous medium on local current density is characterized by the following: as the amount of liquid water in the porous medium increases, the oxygen transport resistance increases, and the local current density decreases; therefore, the second characteristic factor is negative. The third characteristic factor... The effect of liquid water saturation in the catalyst layer on local current density is characterized. When the amount of liquid water in the catalyst layer increases, the effective reaction area decreases, and the local current density decreases; therefore, the third characteristic factor is negative. The fourth characteristic factor... The effect of the catalytic layer membrane water content on the local current density was characterized. When the membrane water content in the catalytic layer increased, the oxygen reduction reaction kinetics were promoted, and the local current density increased. Therefore, the fourth characteristic factor was positive; the fifth characteristic factor... The effect of membrane water content in a proton exchange membrane on local current density is characterized. When the membrane water content increases, the membrane impedance decreases, the ohmic polarization decreases, and the local current density increases. Therefore, the fifth characteristic factor is positive.

[0108] Of the five characteristic factors mentioned above, the first characteristic factor Second characteristic factor and the third characteristic factor All values ​​are negative, reflecting the inhibitory effect caused by the accumulation of liquid water; the fourth characteristic factor and the fifth characteristic factor All values ​​are positive, reflecting the promoting effect caused by the increase in film water. By distinguishing between positive and negative values, the computer equipment can determine whether the change in local current density is dominated by changes in film water or liquid water, thus providing a basis for subsequent water state diagnosis.

[0109] For example, under steady-state operating conditions, the local current density The change can be regarded as the total differential of the four core water state variables. Based on the partial derivative relationships of relations (2)-relation (5) and the characteristic factor definitions of relations (6)-relation (10), the complete mathematical expression of the local current change under the influence of water state can be obtained, as shown in relation (11):

[0110] (11);

[0111] In actual diagnostics, when a certain type of water management problem plays a dominant role, the complete expression above can be simplified to the corresponding dominant form, allowing the computer equipment to directly identify the core's internal water state based on real-time changes in local current density. Specifically:

[0112] When the problem of channel flooding is dominant, relation (11) can be simplified to relation (12), which is shown below:

[0113] (12);

[0114] At this time, the computer equipment can obtain data in real time. and already determined The change in the liquid water saturation of the flow channel is obtained by reversing the flow.

[0115] When the problem of catalyst layer flooding is dominant, relation (11) can be simplified to relation (13), which is shown below:

[0116] (13);

[0117] At this time, the computer equipment can obtain data in real time. and already determined and The change in the liquid water saturation of the catalyst layer is obtained by reversing the process.

[0118] When the membrane drying problem is dominant, relation (11) can be simplified to relation (14), which is shown below:

[0119] (14);

[0120] At this time, the computer equipment can obtain data in real time. and already determined and The change in membrane water content is obtained by reversing the process.

[0121] Therefore, once the dominant water management problem is identified, the computer equipment does not need to solve the complete system of partial differential equations each time. Instead, it only needs to use the simplified formulas corresponding to the dominant characteristic factors to identify the changing trends of the core water state parameters from the real-time changes in local current density, significantly reducing the computational complexity of online diagnosis. Furthermore, by using the identified changes in water state parameters, the computer equipment can further determine the degree to which the water state deviates from its initial state, providing a quantitative basis for decision-making regarding whether subsequent water management and control operations are necessary.

[0122] In an exemplary embodiment, the process of determining the "physical prior conditions" in S201 above is as follows: Figure 4 As shown, it includes:

[0123] S401, obtain gas-water distribution information of fuel cell under different operating conditions.

[0124] In this embodiment, the computer device first acquires the operating parameter information of the fuel cell under different operating conditions, including but not limited to the fuel cell's operating parameters (such as current density, inlet humidity, inlet pressure, inlet temperature, etc.), structural parameters (such as flow channel geometry, gas diffusion layer thickness, catalyst layer thickness, etc.), and material parameters (such as membrane weight, ionic conductivity, etc.). Subsequently, the computer device inputs the operating parameter information under different operating conditions into a pre-established and stored discrete model. By numerically solving the internal flow field, concentration field, water distribution, and electrochemical processes of the fuel cell under each operating condition, the gas-water distribution state information in different regions can be obtained. The specific values ​​can be set and adjusted according to the actual application scenario.

[0125] S402, based on a pre-established discrete model, simulates fuel cells under various operating conditions to obtain gas and water distribution information in different regions.

[0126] In this embodiment, the computer device inputs the gas-water distribution state information of different regions into a pre-established discrete model. This discrete model can be a one-dimensional or two-dimensional model that divides the fuel cell into multiple continuous partitions along the gas flow direction, or it can be a two-dimensional model that meshes the fuel cell along the membrane plane. It is used to numerically solve the flow field, concentration field, water distribution, and electrochemical processes inside the fuel cell, thereby obtaining detailed state information of different regions. This discrete model needs to be calibrated with experimental data beforehand to ensure its simulation accuracy. For example, a partitioned discrete model along the flow channel direction for a proton exchange membrane fuel cell. After simulation using the discrete model, the computer device can obtain the gas-water distribution state information of different regions. This gas-water distribution state information can include membrane water content (i.e., the water content of the proton exchange membrane in each region within the plane), catalyst layer membrane water content (i.e., the hydration state of the ionomers in the cathode catalyst layer), catalyst layer liquid water saturation (i.e., the degree to which the pores of the catalyst layer are occupied by liquid water), and catalyst layer oxygen concentration (i.e., the concentration level of oxygen in each region within the cathode catalyst layer).

[0127] The gas-water distribution information can be used by subsequent computer equipment to determine whether there is a risk of membrane dryness or flooding in different areas of the fuel cell. For example, the membrane water content reflects the hydration state of the proton exchange membrane. When the membrane water content is below a preset threshold, it indicates that the membrane is in a dry state and the proton conductivity is reduced. The membrane water content of the catalyst layer reflects the hydration state of the ionomers in the catalyst layer. When the ionomers are dehydrated, ion conduction is hindered. The liquid water saturation of the catalyst layer reflects the degree of liquid water accumulation in the catalyst layer. When the liquid water saturation exceeds a preset threshold, it covers the reactive sites, leading to an increased risk of flooding. The oxygen concentration of the catalyst layer reflects the ability of oxygen to reach the reaction sites. When the oxygen concentration is too low, mass transfer polarization increases, indicating that flooding may have blocked the gas channels.

[0128] S403, based on the gas and water distribution information, determines the physical risk of water management problems occurring in different regions under different operating conditions, and uses the physical risk as a physical prior condition.

[0129] In this embodiment, after the computer device obtains the gas-water distribution information, it determines the physical risk of membrane dryness and / or flooding in different areas of the fuel cell under different operating conditions. For example, the computer device can compare the membrane water content and / or catalyst layer membrane water content with a preset membrane dryness threshold: if the membrane water content and / or catalyst layer membrane water content in a certain area is lower than the preset threshold, the computer device determines that the area has a membrane dryness risk under that operating condition. Similarly, the computer device can compare the catalyst layer liquid water saturation with a preset flooding threshold: if the catalyst layer liquid water saturation in a certain area is higher than the preset threshold, the computer device determines that the area has a flooding risk under that operating condition. Furthermore, the computer device can also combine the distribution of oxygen concentration in the catalyst layer to assist in the judgment; if a certain area simultaneously exhibits high liquid water saturation and low oxygen concentration, the confidence level of the flooding risk in that area is higher.

[0130] It should be noted that the specific values ​​of the first preset threshold and the second preset threshold vary depending on the battery model, membrane electrode material and operating conditions. Those skilled in the art can determine them through a limited number of experimental calibrations or empirical formulas. This application does not impose any specific limitations on them.

[0131] In an exemplary embodiment, the "determining the target water distribution state within the fuel cell surface based on characteristic factors and physical prior conditions" in S203 above, such as Figure 5 As shown, it includes:

[0132] S501 acquires the variation characteristics of current density distribution signals in different regions.

[0133] In this embodiment, the computer device can obtain the trend of local current density change over time in each region based on the time series data of the current density distribution signal. Specifically, the computer device can sample and analyze the current density data according to a preset time window to determine whether the local current density of each region shows an upward or downward trend relative to the previous moment or stage. The areas that the computer device focuses on monitoring include at least the gas inlet area and the downstream gas region.

[0134] S502, based on the change characteristics, characteristic factors and physical prior conditions, determine the target water distribution state.

[0135] When the current density in the gas inlet region shows a decreasing trend, the membrane water content in the corresponding characteristic factor of the gas inlet region is dominant, and the physical prior conditions indicate that there is a risk of membrane drying in the gas inlet region, the target water distribution state is determined to be membrane drying; when the current density in the gas inlet region shows a decreasing trend, the liquid water saturation in the flow channel in the corresponding characteristic factor of the gas inlet region is dominant, and the physical prior conditions indicate that there is a risk of water flooding in the gas inlet transition region, the target water distribution state is determined to be flow channel flooding; when the current density in the gas mid-to-downstream region shows a decreasing trend, the liquid water saturation in the corresponding characteristic factor of the gas mid-to-downstream region is dominant, and the physical prior conditions indicate that there is a risk of water flooding in the gas mid-to-downstream region, the target water distribution state is determined to be flooding.

[0136] In this embodiment, the computer device determines the target water distribution state of the fuel cell by combining the variation characteristics of current density in each region, the characteristic factors of each region, and the physical prior conditions of each region. The computer device first determines the variation trend of the current density distribution signal in the gas inlet region and the downstream gas region of the fuel cell based on the variation characteristics of current density, and then determines the target water distribution state by combining preset diagnostic rules.

[0137] When the computer device detects an upward trend in the gas inlet region of the fuel cell based on the current density distribution signal, the fourth and fifth characteristic factors (corresponding to the positive promoting effect of membrane water content on current) in the gas inlet region are absolutely dominant, and the physical prior conditions characterize the original membrane water content in this region. and the content of water in the catalytic layer membrane The risk of membrane drying is extremely low. Therefore, even with a slight increase in liquid water in the porous medium (i.e., the first, second, and third characteristic factors are negatively inhibited), the positive effect caused by the increase in membrane water content still dominates. Ultimately, the computer equipment determines the target water distribution state in this area as improved membrane hydration.

[0138] When the computer device detects a decreasing trend in the current density distribution signal at the gas inlet region of the fuel cell, it first obtains the current operating humidity conditions of the fuel cell. If the fuel cell is operating under low humidity conditions, the computer device then combines this with the prior physical conditions regarding the inlet region... and The low characteristic indicates that the decrease in current density is caused by membrane electrode drying, which is dominated by the fourth and fifth characteristic factors. Ultimately, the computer equipment determines the target water distribution state in this region as membrane dryness.

[0139] If the fuel cell operates under medium-to-high humidity conditions, the computer equipment, based on prior physical conditions, determines that there is a risk of channel flooding in the inlet transition region. In this case, the accumulation of liquid water in the channel hinders oxygen mass transfer, and the decrease in local current density is dominated by the first characteristic factor (the channel liquid water saturation factor, which has a negative inhibitory effect on current). Ultimately, the computer equipment determines the target water distribution state in this region as channel flooding.

[0140] When the computer equipment detects a decreasing trend in the downstream region of the fuel cell gas based on the current density distribution signal, and because the current density in this region is highly sensitive to reactant consumption and liquid water accumulation (dominated by the first, second, and third characteristic factors—the channel liquid water factor, porous media liquid water factor, and catalyst layer liquid water factor), and prior physical conditions confirm that the downstream gas region is prone to liquid water accumulation, the computer equipment ultimately determines the target water distribution state in this region as flooding.

[0141] When the computer equipment detects an upward trend in the current density distribution signal in the downstream region of the fuel cell gas, the increase in current density indicates that the flooding risk in this region is mitigated, and oxygen mass transfer is restored after the liquid water is discharged, based on the prior physical conditions indicating that the region is at risk of flooding. Ultimately, the computer equipment determines the target water distribution state in this region as flooding mitigation.

[0142] In summary, based on all the above embodiments, a method for determining the water distribution state within a fuel cell surface is also provided, such as... Figure 6 As shown, the method includes:

[0143] S601, acquire the current density distribution signal and physical prior conditions in different regions of the fuel cell surface, and execute S610-S612 to determine the physical prior conditions;

[0144] S602, based on a multiphysics model, obtains the current density expression of the current density distribution signal in different regions, and determines the water state parameters in the current density expression;

[0145] S603, based on the current density expression, calculates the partial derivatives with respect to each water state parameter to determine the characteristic factors;

[0146] S604, acquires the variation characteristics of current density distribution signals in different regions;

[0147] S605, based on the change characteristics, determine the change characteristics of the current density distribution signal in the gas inlet region and the middle and lower downstream regions of the gas, and execute S606-S609 to determine the target water distribution state in the fuel cell surface.

[0148] S606, under the condition that the current density in the gas inlet region is on the rise, the membrane water content in the characteristic factors corresponding to the gas inlet region is dominant, and the physical prior conditions characterize that there is a risk of membrane dryness in the gas inlet region, the target water distribution state is determined to be improved membrane hydration state.

[0149] S607, under the condition that the current density in the gas inlet region is decreasing, the membrane water content in the characteristic factors corresponding to the gas inlet region is dominant, and the physical prior conditions characterize that there is a risk of membrane drying in the gas inlet region, the target water distribution state is determined to be membrane drying.

[0150] S608, under the condition that the current density in the gas inlet region is decreasing, the liquid water saturation in the flow channel is dominant in the characteristic factors corresponding to the gas inlet region, and the physical prior conditions characterize that there is a risk of water flooding in the gas inlet transition region, the target water distribution state is determined to be flow channel flooding.

[0151] S609, under the condition that the current density in the middle and lower reaches of the gas is decreasing, the liquid water saturation in the characteristic factors corresponding to the middle and lower reaches of the gas is dominant, and the physical prior conditions characterize that there is a risk of flooding in the middle and lower reaches of the gas, the target water distribution state is determined to be flooding.

[0152] S610, acquires gas-water distribution information of fuel cell under different operating conditions;

[0153] S611, based on a pre-established discrete model, simulates fuel cells under various operating conditions to obtain gas and water distribution information in different regions;

[0154] S612, based on the gas and water distribution status information, determines the physical risk of water management problems occurring in different regions under different operating conditions, and uses the physical risk as a physical prior condition.

[0155] The methods described in each of the above steps have been described in the foregoing embodiments. For details, please refer to the foregoing descriptions. They will not be repeated here.

[0156] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0157] The above embodiments are explained and illustrated by some examples below, which do not limit the technical solution.

[0158] Example 1: Using an active area of ​​349 A proton exchange fuel cell was used as the test object. This fuel cell integrated a partitioned current density acquisition PCB board. During operation, hydrogen was supplied at the anode and a 60% oxygen-nitrogen mixture was supplied at the cathode, using a co-current flow mode with co-current intake. The fuel cell was tested under the six operating conditions shown in Table 1, at 1A / It operates continuously for 12 hours at a constant current density.

[0159] Table 1

[0160]

[0161] During the constant current steady-state operation of the proton exchange fuel cell, local current density data of each region in the plane are collected in real time by the partitioned current acquisition PCB board. The computer equipment receives and records these data to obtain the current density distribution signal and its trend over time.

[0162] Experimental observations showed that under the above six operating conditions, the current density distribution signal exhibited a three-stage variation pattern, such as... Figure 7As shown. The first stage (initial rapid evolution period, approximately 0-0.1 h): The local current density in the gas inlet region rises rapidly, while the current density in the middle and downstream regions remains relatively stable or decreases slightly. The second stage (mid-term local characteristic manifestation period, approximately 0.1-1 h): The local current density in the middle and downstream regions of the gas exhibits a significant decrease, which is more pronounced under medium- and high-pressure conditions; simultaneously, in some conditions (such as conditions 1 and 2), a slight decrease in current also occurs in the gas inlet region. The third stage (late quasi-steady-state evolution period, approximately 1-12 h): In conditions 1-5, a significant decrease in local current density begins to appear in the gas inlet transition region; condition 6 still shows a continuous decrease in current density in the middle and downstream regions.

[0163] Subsequently, the computer equipment used a discrete model partitioned along the flow channel (this model had been experimentally calibrated beforehand) to continue simulations under the six steady-state operating conditions shown in Table 1, thereby obtaining the membrane water content. , Catalytic layer membrane water content , Catalytic layer liquid water saturation and oxygen concentration in the catalyst layer Distribution results at different locations within the plane, such as Figure 8 (The horizontal axis represents the location of the 8 zones along the flow channel (zone number (dimensionless)); the vertical axis represents the membrane water content.) (dimensionless) Figure 9 (The horizontal axis represents the location of the 8 zones along the flow channel (zone number (dimensionless)); the vertical axis represents the water content of the catalyst layer membrane.) (dimensionless) Figure 10 (The horizontal axis represents the location of the 8 zones along the flow channel (zone number (dimensionless)); the vertical axis represents the liquid water saturation of the catalyst layer.) (dimensionless) and Figure 11 (The horizontal axis represents the location of the 8 zones along the flow channel (zone number (dimensionless)); the vertical axis represents the oxygen concentration in the catalyst layer.) (unit: As shown in the figure.

[0164] Simulation results show that, due to the inherent spatial heterogeneity of gas and water states within the fuel cell surface, the membrane water content in the gas inlet region is high under low cathode inlet humidity conditions. and the content of water in the catalytic layer membrane The minimum value is reached, meaning that there is a significant risk of membrane drying in this region under low humidity conditions; while as the inlet pressure increases, the membrane water content in the gas inlet region decreases. and the content of water in the catalytic layer membrane The temperature gradually increases, thus alleviating the risk of membrane drying to some extent.

[0165] Catalytic layer liquid water saturation Similarly, it shows a trend of gradually increasing along the gas flow direction, in the middle and lower reaches. The concentration reaches its highest level within the surface, a result of the continuous accumulation of water generated by the electrochemical reaction along the flow path. Simultaneously, the oxygen concentration in the catalyst layer... It exhibits a trend of gradually decreasing along the gas flow direction. The increase in intake pressure can significantly increase the oxygen concentration at various locations within the surface, but under high intake pressure conditions, the airflow velocity decreases, the drainage capacity within the flow channel is weakened, and more liquid water may accumulate in the flow channel, which in turn exacerbates the risk of flooding.

[0166] Further considering the flow field structure characteristics of fuel cells, the fuel cell is vertically positioned, with gas and cooling water entering from the top and exiting from the bottom. Its design aims to utilize gravity to assist the discharge of liquid water from parallel channels. Figure 12 As shown. However, after entering the battery, the gas needs to pass through a gas transition zone, which includes a horizontal transport section. In the horizontal transport section, gravity cannot assist in drainage; once liquid water begins to accumulate, the local two-phase flow resistance increases, and the incoming gas tends to bypass the blocked channels, preferentially flowing through adjacent channels with lower resistance, making it more difficult to remove the accumulated liquid water. In addition, the local flow resistance of the gas is even greater at right-angle bends, further increasing the possibility of liquid water retention. These factors make the gas inlet transition area a potential area prone to flooding.

[0167] Based on the above discrete numerical simulation results and flow field geometric characteristics, the computer equipment extracted the following prior physical laws:

[0168] Membrane drying prior rule: The local water content in the gas inlet region is extremely low, which is the region where the proton exchange membrane and ionomer are most prone to dehydration and membrane drying, and the sensitivity is extremely high.

[0169] Flooding Prior Law: Due to the continuous accumulation of water produced by the reaction in the long flow channel in the downstream region of the gas, the liquid water saturation level remains at a high level for a long time, and there is an inherent high risk of flooding in the porous media and flow channel. This prior law cannot be ignored under different operating conditions.

[0170] Prior law of water flooding in the inlet transition area: For parallel DC field structures with distribution transition areas, the limitations of fluid turning resistance and gravity make it very easy for early condensed liquid water to accumulate in the inlet transition area. This prior law is particularly prominent during the battery start-up phase or low-power operation phase.

[0171] Secondly, the computer equipment, based on a multiphysics model, obtains expressions for the variation of current density in each region with various physical quantities, and identifies water state parameters (liquid water saturation in the flow channel, liquid water saturation in the catalyst layer, membrane water content, and membrane water content in the catalyst layer). Under steady-state operating conditions, the change in local current density can be regarded as the total differential of the above four core water state variables. By taking partial derivatives with respect to each water state parameter, five characteristic factors are obtained.

[0172] Computer equipment was used to conduct simulation analysis of the in-plane distribution of the above five characteristic factors under different operating conditions using an experimentally calibrated discrete model along the flow channel, in order to reveal the differentiated response laws of different locations in the in-plane to changes in water state. Simulation results show that the increased liquid water content in the flow channel and catalyst layer has a greater impact on the local current than in other regions (first characteristic factor). Second characteristic factor and the third characteristic factor The effect of relatively high current density is due to the low oxygen concentration and high liquid water content in the mid-to-downstream region of the gas; while near the gas inlet region, the membrane electrode is relatively dry, and the increased membrane water content in the cathode catalyst layer or membrane has a greater impact on the local current density than in other regions (fourth characteristic factor). and the fifth characteristic factor (Significantly higher). From the perspective of the impact on operating conditions, the lower the inlet air humidity, the lower the membrane water content in the catalyst layer and membrane, and the more significant the impact of its change on the local current density in the gas inlet region (fourth characteristic factor). and the fifth characteristic factor (Larger). However, with increased intake pressure, the oxygen concentration in the cathode catalyst layer increases significantly, improving oxygen mass transfer. Therefore, the effect of liquid water accumulation reducing oxygen has a smaller impact on the local current density (first characteristic factor). Second characteristic factor (Smaller).

[0173] Finally, the computer device uses the diagnostic rules provided in the embodiments of this application to identify the water state change mechanism at each stage: In the first stage, the current density in the gas inlet region shows an upward trend. The fourth characteristic factor in the characteristic factors corresponding to this region... and the fifth characteristic factor (The characteristic factor corresponding to the membrane water content is positive) is absolutely dominant, and the physical prior conditions indicate that there is a risk of membrane drying in the inlet area. Therefore, the computer equipment diagnoses that the membrane hydration status in the inlet area has improved.

[0174] In the second stage, the current density in the downstream region of the gas exhibits a decreasing trend. The first characteristic factor in the characteristic factors corresponding to this region... Second characteristic factor and the third characteristic factor The dominant factor is the characteristic factor corresponding to the saturation of liquid water, which is negative. Furthermore, the physical prior conditions indicate that there is a risk of flooding in the downstream area. Therefore, the computer equipment diagnoses the occurrence of flooding in the downstream area.

[0175] In the third stage, under operating conditions 1-5, the current density in the gas inlet transition region shows a decreasing trend. The computer equipment obtains the current operating humidity conditions: operating condition 1 is a low humidity condition, diagnosed as membrane dryness; operating conditions 2-5 are medium to high humidity conditions, and the physical prior conditions indicate that there is a risk of water flooding in the inlet transition region, diagnosed as flow channel flooding.

[0176] In operating condition 6, the current density in the middle and downstream areas continued to decrease, which was diagnosed as a continuous deterioration of flooding. This was due to the weakened drainage capacity under high intake pressure, resulting in more liquid water accumulating in the flow channel.

[0177] The above diagnostic results are consistent with the actual water management status observed in the experiment, verifying that the fuel cell water distribution status determination method provided in this application can effectively identify the water state change mechanism in different regions within a large-area fuel cell during steady-state operation.

[0178] Based on the same inventive concept, this application also provides a device for determining the water distribution state within a fuel cell surface to implement the aforementioned method for determining the water distribution state within a fuel cell surface. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more embodiments of the device for determining the water distribution state within a fuel cell surface provided below can be found in the limitations of the method for determining the water distribution state within a fuel cell surface described above, and will not be repeated here.

[0179] In one exemplary embodiment, such as Figure 13 As shown, a device for determining the water distribution state within a fuel cell surface is provided, comprising:

[0180] The acquisition module 11 is used to acquire the current density distribution signal and physical prior conditions in different regions within the fuel cell surface; the physical prior conditions characterize the physical risks of water management problems occurring under different operating conditions.

[0181] The determination module 12 is used to determine the characteristic factors corresponding to the current density distribution signals of each region through a pre-established multiphysics model; the characteristic factors are used to characterize the direction of influence of changes in water distribution state parameters on the local current density of the corresponding region.

[0182] The distribution module 13 is used to determine the target water distribution state within the fuel cell surface based on characteristic factors and physical prior conditions; the target water distribution state includes the water state change mechanism in different regions.

[0183] The various modules in the aforementioned device for determining the water distribution state within the fuel cell surface can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0184] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0185] The current density distribution signal and physical prior conditions in different regions of the fuel cell surface are obtained; the physical prior conditions characterize the physical risk of water management problems under different operating conditions.

[0186] By using a pre-established multiphysics model, the characteristic factors corresponding to the current density distribution signals in each region are determined; the characteristic factors are used to characterize the direction of influence of changes in water distribution state parameters on the local current density in the corresponding region.

[0187] Based on characteristic factors and physical prior conditions, the target water distribution state within the fuel cell surface is determined; the target water distribution state includes the water state change mechanism in different regions.

[0188] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0189] The current density distribution signal and physical prior conditions in different regions of the fuel cell surface are obtained; the physical prior conditions characterize the physical risk of water management problems under different operating conditions.

[0190] By using a pre-established multiphysics model, the characteristic factors corresponding to the current density distribution signals in each region are determined; the characteristic factors are used to characterize the direction of influence of changes in water distribution state parameters on the local current density in the corresponding region.

[0191] Based on characteristic factors and physical prior conditions, the target water distribution state within the fuel cell surface is determined; the target water distribution state includes the water state change mechanism in different regions.

[0192] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0193] The current density distribution signal and physical prior conditions in different regions of the fuel cell surface are obtained; the physical prior conditions characterize the physical risk of water management problems under different operating conditions.

[0194] By using a pre-established multiphysics model, the characteristic factors corresponding to the current density distribution signals in each region are determined; the characteristic factors are used to characterize the direction of influence of changes in water distribution state parameters on the local current density in the corresponding region.

[0195] Based on characteristic factors and physical prior conditions, the target water distribution state within the fuel cell surface is determined; the target water distribution state includes the water state change mechanism in different regions.

[0196] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0197] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0198] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for determining the water distribution state within a fuel cell surface, characterized in that, The method includes: The current density distribution signal and physical prior conditions in different regions within the fuel cell surface are obtained; the physical prior conditions characterize the physical risk of water management problems occurring under different operating conditions. By using a pre-established multiphysics model, the characteristic factors corresponding to the current density distribution signals in each region are determined; these characteristic factors are used to characterize the direction of influence of changes in water distribution state parameters on the local current density in the corresponding region. Based on the characteristic factors and the physical prior conditions, the target water distribution state within the fuel cell surface is determined; the target water distribution state includes the water state change mechanism in different regions.

2. The method according to claim 1, characterized in that, The process of determining the characteristic factors corresponding to the current density distribution signals in each region through a pre-established multiphysics model includes: Based on the multiphysics model, the current density expression of the current density distribution signal in different regions is obtained, and the water state parameters in the current density expression are determined; the water state parameters include the liquid water saturation of the flow channel, the liquid water saturation of the catalyst layer, the membrane water content, and the membrane water content of the catalyst layer; Based on the current density expression, partial derivatives are taken with respect to each of the water state parameters to determine the characteristic factors.

3. The method according to claim 1, characterized in that, The process of determining the physical prior conditions includes: Obtain gas-water distribution information of the fuel cell under different operating conditions; Based on a pre-established discrete model, the fuel cell under each of the aforementioned operating conditions is simulated to obtain gas and water distribution information in different regions. Based on the gas and water distribution information, the physical risks of water management problems occurring in different regions under different operating conditions are determined, and the physical risks are used as the physical prior conditions.

4. The method according to claim 1, characterized in that, Determining the target water distribution state within the fuel cell surface based on the characteristic factors and the physical prior conditions includes: Obtain the variation characteristics of the current density distribution signal in the different regions; The target water distribution state is determined based on the change characteristics, the characteristic factors, and the physical prior conditions.

5. The method according to claim 4, characterized in that, Determining the target water distribution state based on the change characteristics, the characteristic factors, and the physical prior conditions includes: Based on the aforementioned variation characteristics, the variation characteristics of the current density distribution signal in the gas inlet region and the middle and lower downstream regions of the gas are determined; When the current density in the gas inlet region shows an upward trend, the membrane water content in the characteristic factors corresponding to the gas inlet region is dominant, and the physical prior conditions characterize that there is a risk of membrane dryness in the gas inlet region, the target water distribution state is determined to be an improvement in membrane hydration state. When the current density in the gas inlet region shows a decreasing trend, the membrane water content in the characteristic factors corresponding to the gas inlet region is dominant, and the physical prior conditions characterize that there is a risk of membrane drying in the gas inlet region, the target water distribution state is determined to be membrane drying. When the current density in the gas inlet region shows a decreasing trend, the liquid water saturation in the flow channel is dominant in the characteristic factors corresponding to the gas inlet region, and the physical prior conditions characterize that there is a risk of flooding in the gas inlet transition region, the target water distribution state is determined to be flow channel flooding. When the current density in the downstream region of the gas shows a decreasing trend, the liquid water saturation is dominant among the characteristic factors corresponding to the downstream region of the gas, and the physical prior conditions characterize that there is a risk of flooding in the downstream region of the gas, the target water distribution state is determined to be flooded.

6. The method according to any one of claims 1-5, characterized in that, The characteristic factors include at least one of the following: The first characteristic factor characterizes the effect of the liquid water saturation in the flow channel on the local current density; the first characteristic factor is negative. The second characteristic factor characterizes the effect of the liquid water saturation in the porous medium on the local current density; the second characteristic factor is negative. The third characteristic factor characterizes the effect of the liquid water saturation of the catalyst layer on the local current density; the third characteristic factor is negative. The fourth characteristic factor characterizes the effect of the water content in the catalyst layer membrane on the local current density; the fourth characteristic factor is a positive value. The fifth characteristic factor characterizes the effect of membrane water content in the proton exchange membrane on the local current density; the fifth characteristic factor is a positive value.

7. A device for determining the water distribution state within a fuel cell surface, characterized in that, The device includes: The acquisition module is used to acquire the current density distribution signal and physical prior conditions in different regions within the fuel cell surface; the physical prior conditions characterize the physical risk of water management problems occurring under different operating conditions. The determination module is used to determine the characteristic factors corresponding to the current density distribution signals of each region through a pre-established multiphysics model; the characteristic factors are used to characterize the direction of influence of changes in water distribution state parameters on the local current density of the corresponding region. The distribution module is used to determine the target water distribution state within the fuel cell surface based on the characteristic factors and the physical prior conditions; the target water distribution state includes the water state change mechanism in different regions.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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