Fuel cell membrane dry state online identification method and related products

Abstract

The application discloses a kind of fuel cell membrane dry state online identification method and related products, it is related to fuel cell technical field, comprising: obtaining the first single body voltage, reference impedance value, first ohmic loss and membrane reference moisture content when the first single body voltage is obtained under target current, reference impedance value, first ohmic loss and membrane reference moisture content when the first single body voltage is obtained under target current;Determine critical ohmic impedance value according to reference impedance value and membrane reference moisture content;When single body voltage change and ohmic loss change meet set requirements, compare the impedance value to be compared at any time under target current with critical ohmic impedance value, obtain membrane dry state identification result. Realize early identification and quantitative evaluation to membrane dry state, improve the safety and stability of stack operation.

Description

Technical Field

[0001] This invention relates to the field of fuel cell technology, and in particular to an online method for identifying the dry state of fuel cell membranes and related products. Background Technology

[0002] During the operation of a hydrogen-oxygen fuel cell, the wetting state of the proton exchange membrane (PEM) has a crucial impact on the performance and lifespan of the fuel cell stack. The PEM must be kept adequately hydrated to ensure efficient proton migration through the internal hydration network, thereby maintaining good electrochemical reaction efficiency and output power. If membrane dryness occurs, its proton conductivity will decrease significantly, leading to increased membrane resistance and ohmic losses, ultimately affecting the stack's energy conversion efficiency. Furthermore, frequent or persistent membrane dryness failures can accelerate the chemical degradation and mechanical fatigue of the membrane material, shortening the stack's lifespan.

[0003] Existing methods for diagnosing the membrane condition of fuel cells mostly employ static judgment methods such as fixed thresholds or offline pre-calibrated thresholds. However, fixed thresholds cannot adapt to the dynamic operation of the fuel cell stack. The thresholds do not update dynamically with changes in operating conditions such as coolant temperature and current density, which can easily lead to misjudgments and missed judgments under varying loads, varying temperatures, and long-term operation, resulting in low diagnostic accuracy. On the other hand, pre-calibrated static thresholds need to be recalibrated after the stack performance degrades, resulting in poor lifecycle adaptability and making it impossible to achieve stable and accurate membrane condition monitoring throughout the entire lifecycle. Summary of the Invention

[0004] To address the aforementioned issues, this invention proposes an online identification method and related products for the dry state of fuel cell membranes, enabling early identification and quantitative assessment of membrane dryness, thereby improving the safety and stability of fuel cell stack operation.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides an online method for identifying the dry state of a fuel cell membrane, comprising: Under the target current, the first unit voltage, reference impedance value, first ohmic loss, and membrane reference water content are obtained during normal operation of the fuel cell stack. Obtain the second cell voltage, the impedance value to be compared, and the second ohmic loss at any given time; The critical ohmic impedance value is determined based on the reference impedance value and the membrane reference water content. When the changes in cell voltage and ohmic loss meet the set requirements, the impedance value to be compared at any time under the target current is compared with the critical ohmic impedance value to obtain the membrane dry state identification result.

[0006] As an alternative implementation, the setting requirement for the change in unit voltage and the change in ohmic loss is: calculate the ratio of the change in unit voltage to the change in ohmic loss. :

[0007] in, for The second cell voltage at that moment; The voltage of the first individual cell at time t0 when the fuel cell stack is in normal operating condition; for The second ohmic loss at time 1; This represents the first ohmic loss at time t0 when the fuel cell stack is operating normally. when When the voltage change and ohmic loss change of a single unit meet the set requirements.

[0008] As an alternative implementation method, the membrane reference water content is the inherent water content corresponding to the membrane being in a normal and stable operating state under the target current.

[0009] As an alternative implementation method, the critical ohmic impedance value is:

[0010] in, This is the critical ohmic impedance value; This is the reference impedance value; The membrane reference water content; This refers to the water content of the membrane in its dry state. , It is a constant.

[0011] As an alternative implementation, the membrane dry state water content is defined as follows: under the same target current, the membrane dry state water content is defined as... , .

[0012] As an alternative implementation, the process of membrane dry state identification includes: comparing the impedance value to be compared at any time under the target current with the critical ohmic impedance value; if the impedance value to be compared is greater than the critical ohmic impedance value, it is determined to be in the membrane dry state; otherwise, it is in the non-membrane dry state.

[0013] In a second aspect, the present invention provides an online identification system for the dry state of a fuel cell membrane, comprising: The first acquisition module is configured to acquire the first unit voltage, reference impedance value, first ohmic loss and membrane reference water content under the target current and the normal operating state of the fuel cell stack. The second acquisition module is configured to acquire the second cell voltage, the impedance value to be compared, and the second ohmic loss at any time. The threshold confirmation module is configured to determine the critical ohmic impedance value based on the reference impedance value and the membrane reference water content. The judgment module is configured to compare the impedance value to be compared with the critical ohmic impedance value at any time under the target current when the change in single-cell voltage and the change in ohmic loss meet the set requirements, so as to obtain the membrane dry state identification result.

[0014] Thirdly, the present invention provides an electronic device including a memory and a processor, and computer instructions stored in the memory and running on the processor, wherein the computer instructions, when executed by the processor, perform the method described in the first aspect.

[0015] Fourthly, the present invention provides a computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the method described in the first aspect.

[0016] Fifthly, the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the method described in the first aspect.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention proposes an online method for identifying the dry state of fuel cell membranes. By establishing a mapping relationship between ohmic impedance and membrane water content, the critical ohmic impedance value is determined, enabling quantitative identification of the dry state and improving the scientific rigor and accuracy of the assessment. By comparing the measured impedance value with the critical ohmic impedance value, the trend of membrane dryness can be identified before it causes serious performance degradation, triggering early warnings or control adjustments. This helps prevent serious problems such as the formation of local hot spots and membrane rupture, achieving early identification and quantitative assessment of the dry state and improving the safety and stability of the fuel cell stack operation.

[0018] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0020] Figure 1 This is a flowchart of the online identification method for the dry state of fuel cell membranes provided in Embodiment 1 of the present invention. Detailed Implementation

[0021] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0022] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0023] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, unless the context clearly indicates otherwise, the singular form is intended to include the plural form as well. Furthermore, it should be understood that the terms “comprising” and “including”, and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0024] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0025] Terminology Explanation: Membrane water content: The number of grams of water contained in each gram of dry polymer membrane, or expressed as the number of water molecules present in each sulfonic acid group of the polymer, λ=N(H2O) / N(SO3H).

[0026] Ohmic loss: In proton exchange membrane fuel cells, due to the internal resistance of the cell, electrical energy (converted from chemical energy) is irreversibly converted into heat energy during the transfer process, resulting in voltage drop and energy loss.

[0027] Electrical conductivity: the magnitude of the current density in a material under a unit electric field, reflecting the material's ability to conduct current, and is the reciprocal of resistivity.

[0028] As described in the background section, the water content of the proton exchange membrane fuel cell determines the proton conduction efficiency and stack operational stability. Abnormal conditions such as membrane dryness and flooding significantly reduce stack performance and durability. Existing fuel cell membrane condition diagnosis methods mostly employ static criteria such as fixed ohmic impedance thresholds and offline pre-calibration thresholds to determine membrane dryness.

[0029] For example, existing technologies obtain impedance values ​​by applying high-frequency excitation to DC-DC converters and compare them with a preset fixed membrane dryness threshold to determine the membrane dryness state; or they determine the membrane state by using fixed limits of theoretical and actual pressure differences, or a fixed ratio of average cell voltage; or they use calibration parameters such as preset water content ranges and fixed impedance differences to conduct water content assessment. All these methods rely on offline calibration and static thresholds that remain unchanged throughout the process, failing to establish a quantitative correlation between ohmic impedance and membrane water content at the mechanistic level.

[0030] The above-mentioned traditional methods have the following obvious drawbacks: Fixed thresholds cannot adapt to the dynamic operation of fuel cell stacks. The thresholds are not updated in real time with temperature, current density, operating condition switching and fuel cell stack aging and decay. In scenarios with variable load, variable temperature and long-term operation, it is easy to make misjudgments and omissions, resulting in low diagnostic accuracy.

[0031] Without establishing a physical mapping relationship between ohmic impedance and membrane water content, only qualitative fault identification can be achieved, and the true dryness and wetness of the membrane cannot be quantitatively characterized, resulting in a lack of precise basis for water management and control.

[0032] Some solutions rely on signals such as gas pressure difference and voltage, which are easily affected by operating conditions and sensor drift, resulting in poor robustness and difficulty in meeting the stable diagnostic requirements under complex operating conditions.

[0033] The static threshold needs to be recalibrated after the performance of the fuel cell stack degrades, resulting in poor life cycle adaptability and making it impossible to achieve stable and accurate membrane state monitoring throughout the entire life cycle.

[0034] Therefore, this invention proposes an online identification method for the dry state of fuel cell membranes, overcoming the shortcomings of existing technologies that use fixed or calibrated thresholds to determine the membrane state, such as low diagnostic accuracy, poor adaptability to operating conditions, inability to quantitatively characterize membrane water content, and insufficient robustness. By establishing a mapping relationship between ohmic impedance and membrane water content, the critical ohmic impedance value is dynamically determined for different current densities, replacing the traditional static fixed threshold. This achieves accurate and adaptive identification of the membrane dry state, improving the diagnostic accuracy and adaptability of fuel cell membranes, and supporting the efficient and stable operation of the fuel cell stack.

[0035] Example 1 This embodiment provides an online identification method for the dry state of fuel cell membranes based on dynamic resistance comparison. The method mainly includes: acquiring the first cell voltage, reference impedance value, first ohmic loss, and membrane reference water content under normal operating conditions of the fuel cell stack at a target current; acquiring the second cell voltage, the impedance value to be compared, and the second ohmic loss at any given time; determining the critical ohmic impedance value based on the reference impedance value and the membrane reference water content; and comparing the impedance value to be compared with the critical ohmic impedance value at any given time under the target current when the changes in cell voltage and ohmic loss meet set requirements, thereby obtaining the membrane dry state identification result.

[0036] The following is combined with Figure 1 The process shown below provides a detailed explanation of the method in this embodiment.

[0037] S1: Under the condition that the operating conditions such as temperature, humidity, pressure and flow rate are all within the normal set range, the fuel electric field is operated to a stable state. After the voltage of each cell is stable, the fuel cell is gradually loaded to the target current point; that is, at the target current point, the fluctuation range of the voltage of all cells does not exceed ±5 mV, and the voltage is continuously monitored for at least 5 minutes under this stable state.

[0038] S2: At the target current Under normal operating conditions, the voltage of the first individual cell of the fuel cell at time t0 is obtained. Reference impedance value and coolant inlet temperature (Convert Celsius to Kelvin: Kelvin = Celsius + 273.15), and calculate the first ohmic loss at time t0. ; and the membrane reference water content under normal membrane conditions at the target current point. .

[0039] Among them, the intrinsic water content corresponding to the membrane in a normal and stable operating state at different current points is defined as the membrane reference water content at that current point. , The value will change with the current point and is not a fixed value.

[0040] S3: Record the voltage of the second cell at any subsequent time t. Impedance values ​​to be compared and the second ohm loss .

[0041] Among them, the voltage of the first single cell Second cell voltage All data use average single-cell voltage.

[0042] S4: Determine whether the changes in individual unit voltage and ohmic loss meet the set requirements; specifically: Calculate the ratio of the change in unit voltage to the change in ohmic loss. :

[0043] when When the voltage drop is linearly and strongly correlated with the ohmic loss, the performance degradation of the stack is dominated by ohmic polarization. Therefore, the measured impedance value to be compared with the calculated critical ohmic impedance value is compared to determine the dry state of the membrane.

[0044] when At this time, the voltage drop is mainly caused by activation polarization (such as catalyst poisoning or abnormal supply of reaction gas), ruling out the possibility of membrane drying.

[0045] when When this occurs, it indicates abnormal concentration polarization, with faults such as flow channel blockage or flooding appearing, ruling out the possibility of membrane drying.

[0046] S5: Based on the inverse relationship between membrane resistance and water content, a theoretical model is established: (1); (2); in, This is the critical ohmic impedance value; Indicates film thickness, Indicates membrane proton conductivity, The membrane area is represented by T, which is the coolant inlet temperature at time t. This refers to the water content of the membrane in its dry state. , For each constant, the empirical value of a is typically 0.05139, and the empirical value of b is 0.0326.

[0047] From equations (1) and (2), we can derive: (3); (4).

[0048] Then, through equations (3) and (4), we can derive: (5); Further simplification of equation (5) yields: (6).

[0049] Assuming that the coolant inlet temperature remains constant at the same current point, i.e., T=T0, then simplifying equation (6) yields: .

[0050] Understandable, different film thicknesses The membrane in saturated state All of these can be determined in advance from existing literature or experiments.

[0051] As an alternative implementation method, the membrane dry state water content is defined at the target current point. , ,like , ;or , Wait, no restrictions.

[0052] S6: Determine the impedance value to be compared at time t. With critical ohmic impedance value Does it meet the following requirements: If the conditions are met, the fuel cell stack at the target current point is determined to be in a membrane dry state; if the conditions are not met, the fuel cell stack at the target current point is determined to be in a non-membrane dry state.

[0053] S7: The diagnostic of the target current point is complete. Proceed to the next current point until all current points to be tested are completed.

[0054] The method described in this embodiment can dynamically adjust the humidification strategy, airflow distribution, or load conditions by timely identifying and controlling the membrane dryness, thereby maintaining the membrane's good hydration state, ensuring the stable operation of the fuel cell system, and extending its service life.

[0055] The method described in this embodiment establishes a mapping relationship between ohmic impedance and membrane water content to dynamically determine the critical ohmic impedance value, replacing the traditional static fixed threshold. This eliminates the need for frequent recalibration, addressing the shortcomings of traditional fixed thresholds that cannot adapt to varying operating conditions and degradation scenarios, and significantly reducing false positives and false negatives. Using stable and reliable ohmic impedance as the core criterion, it does not rely on easily disturbed differential pressure signals, exhibiting strong resistance to operating condition interference. Furthermore, by constructing a mapping relationship between ohmic impedance and membrane water content at the mechanistic level, the diagnostic results more closely match the actual state of the fuel cell stack, achieving accurate and adaptive discrimination of the membrane dry state. This improves the accuracy and adaptability of fuel cell membrane condition diagnosis, supporting efficient, stable, and long-life operation of the fuel cell stack.

[0056] Example 2 This embodiment provides an online identification system for the dry state of a fuel cell membrane, including: The first acquisition module is configured to acquire the first unit voltage, reference impedance value, first ohmic loss and membrane reference water content under the target current and the normal operating state of the fuel cell stack. The second acquisition module is configured to acquire the second cell voltage, the impedance value to be compared, and the second ohmic loss at any time. The threshold confirmation module is configured to determine the critical ohmic impedance value based on the reference impedance value and the membrane reference water content. The judgment module is configured to compare the impedance value to be compared with the critical ohmic impedance value at any time under the target current when the change in single-cell voltage and the change in ohmic loss meet the set requirements, so as to obtain the membrane dry state identification result.

[0057] It should be noted that the above modules correspond to the steps described in Embodiment 1, and the examples and application scenarios implemented by the above modules and the corresponding steps are the same, but are not limited to the content disclosed in Embodiment 1. It should also be noted that the above modules, as part of the system, can be executed in a computer system such as a set of computer-executable instructions.

[0058] In further embodiments, the following is also provided: An electronic device includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor, wherein the computer instructions, when executed by the processor, perform the method described in Embodiment 1. For brevity, further details are omitted here.

[0059] It should be understood that in this embodiment, the processor can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc.

[0060] Memory may include read-only memory and random access memory, and provides instructions and data to the processor. A portion of memory may also include non-volatile random access memory. For example, memory may also store information about the device type.

[0061] A computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the method described in Embodiment 1.

[0062] The method in Example 1 can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor. The software modules can reside in readily available storage media in the field, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, a detailed description is not provided here.

[0063] A computer program product includes a computer program that, when executed by a processor, implements the method described in Embodiment 1.

[0064] The present invention also provides at least one computer program product tangibly stored on a non-transitory computer-readable storage medium. The computer program product includes computer-executable instructions, such as instructions included in program modules, which execute in a device on a target real or virtual processor to perform the processes / methods described above. Typically, program modules include routines, programs, libraries, objects, classes, components, data structures, etc., that perform specific tasks or implement specific abstract data types. In various embodiments, the functionality of program modules can be combined or divided among program modules as needed. The machine-executable instructions for the program modules can execute within a local or distributed device. In a distributed device, the program modules can reside in both local and remote storage media.

[0065] The computer program code used to implement the methods of the present invention may be written in one or more programming languages. This computer program code may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the computer or other programmable data processing device, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a computer, partially on a computer, as a stand-alone software package, partially on a computer and partially on a remote computer, or entirely on a remote computer or server.

[0066] In the context of this invention, computer program code or related data may be carried by any suitable carrier to enable a device, apparatus, or processor to perform the various processes and operations described above. Examples of carriers include signals, computer-readable media, and the like. Examples of signals may include electrical, optical, radio, sound, or other forms of propagation signals, such as carrier waves, infrared signals, etc.

[0067] Those skilled in the art will recognize that the units and algorithm steps described in connection with the various examples of this embodiment can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention.

[0068] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for online identification of the dry state of a fuel cell membrane, characterized in that, include: Under the target current, the first unit voltage, reference impedance value, first ohmic loss, and membrane reference water content are obtained during normal operation of the fuel cell stack. Obtain the second cell voltage, the impedance value to be compared, and the second ohmic loss at any given time; The critical ohmic impedance value is determined based on the reference impedance value and the membrane reference water content. When the changes in cell voltage and ohmic loss meet the set requirements, the impedance value to be compared at any time under the target current is compared with the critical ohmic impedance value to obtain the membrane dry state identification result.

2. The method for online identification of the dry state of a fuel cell membrane as described in claim 1, characterized in that, The set requirement for the change in individual unit voltage and the change in ohmic loss is: calculate the ratio of the change in individual unit voltage to the change in ohmic loss. : in, for The second cell voltage at that moment; The voltage of the first individual cell at time t0 when the fuel cell stack is in normal operating condition; for The second ohmic loss at time 1; This represents the first ohmic loss at time t0 when the fuel cell stack is operating normally. when When the voltage change and ohmic loss change of a single unit meet the set requirements.

3. The method for online identification of the dry state of a fuel cell membrane as described in claim 1, characterized in that, The membrane reference water content is the inherent water content corresponding to the membrane being in a normal and stable operating state under the target current.

4. The method for online identification of the dry state of a fuel cell membrane as described in claim 1, characterized in that, The critical ohmic impedance value is: in, This is the critical ohmic impedance value; This is the reference impedance value; The membrane reference water content; This refers to the water content of the membrane in its dry state. , It is a constant.

5. The method for online identification of the dry state of a fuel cell membrane as described in claim 4, characterized in that, The membrane dry state water content is defined as follows: under the same target current, the membrane dry state water content is defined as follows. , .

6. The method for online identification of the dry state of a fuel cell membrane as described in claim 1, characterized in that, The process of identifying the dry state of the membrane includes: comparing the impedance value to be compared at any time under the target current with the critical ohmic impedance value; if the impedance value to be compared is greater than the critical ohmic impedance value, it is determined to be in the dry state of the membrane; otherwise, it is in the non-dry state of the membrane.

7. An online identification system for the dry state of a fuel cell membrane, characterized in that, include: The first acquisition module is configured to acquire the first unit voltage, reference impedance value, first ohmic loss and membrane reference water content under the target current and the normal operating state of the fuel cell stack. The second acquisition module is configured to acquire the second cell voltage, the impedance value to be compared, and the second ohmic loss at any time. The threshold confirmation module is configured to determine the critical ohmic impedance value based on the reference impedance value and the membrane reference water content. The judgment module is configured to compare the impedance value to be compared with the critical ohmic impedance value at any time under the target current when the change in single-cell voltage and the change in ohmic loss meet the set requirements, so as to obtain the membrane dry state identification result.

8. An electronic device, characterized in that, It includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor, which, when executed by the processor, perform the method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, Used to store computer instructions, which, when executed by a processor, perform the method described in any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program, which, when executed by a processor, implements the method described in any one of claims 1-6.

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