Operation state monitoring method and system of AEM water electrolysis hydrogen production equipment

Abstract

The invention discloses an operation state monitoring method and system for AEM water electrolysis hydrogen production equipment, particularly relates to the technical field of electrolytic bath operation monitoring control, and aims to solve the problem of efficiency nonlinear fluctuation caused by polarization mode alternating dominance and microstructure degradation under a low current density working condition in the prior art. Extracting polarization fluctuation characteristics by generating a dynamic response sequence and calculating a dynamic coupling degree to identify a polarization alternating dominant mode; analyzing a local blocking probability based on frequency characteristics, positioning an active site sparse region in combination with temperature gradient spatial distribution characteristics, and generating an efficiency fluctuation evaluation coefficient; an active site sparse region and a dynamic compensation factor matrix of a cathode flow field pressure gradient are constructed to cooperatively adjust an anode current density distribution weight and a cathode pressure gradient parameter, so that an adjusting variable is accurately matched with a local blocking probability and a dynamic coupling degree; the multi-scale correlation analysis of the microcosmic degradation state and the macroscopic efficiency fluctuation of the electrolytic cell is realized, and the operation stability under the low current density is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electrolytic cell operation monitoring and control. More specifically, the present invention relates to a method and system for monitoring the operating state of an AEM electrolytic water hydrogen production device. Background Art

[0002] Currently, anion exchange membrane (AEM) electrolytic water hydrogen production technology combines the high efficiency of proton exchange membrane (PEM) and the low cost characteristics of alkaline electrolytic cells (ALK). In the prior art, AEM electrolytic cells conduct hydroxide ions through alkaline anion exchange membranes and can operate in a weakly alkaline environment, adapting to non-precious metal catalysts (such as nickel-based materials), significantly reducing the dependence on precious metals and equipment costs. At the same time, its membrane electrode structure design allows for rapid start-stop and dynamic response, especially suitable for scenarios with volatile input of renewable energy. However, for large-scale applications, AEM electrolytic cells need to operate stably in the low current density range (<0.5 A / cm²) to balance equipment costs and system efficiency.

[0003] In the prior art, when AEM electrolytic cells operate at low current density, due to the sluggish reaction kinetics on the electrode surface and the non-uniform distribution of ion transport paths, the utilization rate of active sites is significantly reduced. At the same time, the alternating dominant effect of ohmic polarization and concentration polarization causes non-linear fluctuations in efficiency, resulting in the efficiency optimization falling into local extrema and unable to achieve global stable control, affecting the reliability of AEM electrolytic cells under low load conditions. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide a method and system for monitoring the operating state of an AEM electrolytic water hydrogen production device to solve the problems proposed in the above background art.

[0005] To achieve the above object, the present invention provides the following technical solutions: A method for monitoring the operating state of an AEM electrolytic water hydrogen production device, comprising the following steps: S1. Real-time collect and perform time-series synchronization calibration on the anode-side voltage fluctuation parameter and the cathode-side hydrogen evolution rate parameter of the electrolytic cell to generate a dynamic response sequence; S2. Extract the anode polarization fluctuation feature and the cathode concentration polarization fluctuation feature from the dynamic response sequence, and calculate the dynamic coupling degree to identify the polarization alternating dominant mode; S3. Determine the local blockage probability of the ion transport path at the membrane electrode interface based on the frequency feature of the polarization alternating dominant mode; S4. Collect and analyze the spatial distribution characteristics of the temperature gradient parameter at the membrane electrode interface, locate the sparse area of active site distribution according to the high-frequency mutation area, and generate an efficiency fluctuation evaluation coefficient in combination with the dynamic coupling degree; S5. Establish the spatial correspondence between the sparse region of active site distribution and the pressure gradient of the cathode flow field, and construct a dynamic compensation factor matrix; S6. According to the change trends of the efficiency fluctuation evaluation coefficient and the dynamic compensation factor matrix, adjust the anode current density distribution weight and the cathode flow field pressure gradient parameters so that the adjustment amount meets the collaborative matching condition of the local blocking probability and the dynamic coupling degree.

[0006] In a preferred embodiment, the voltage fluctuation parameters on the anode side and the hydrogen evolution rate parameters on the cathode side of the electrolytic cell are collected in real time and subjected to time series synchronization calibration to generate a dynamic response sequence, including: Obtain the voltage fluctuation parameters on the anode side and the hydrogen evolution rate parameters on the cathode side through a preset sensor group at a periodic acquisition period; Taking the clock signal of the electrolytic cell controller as the synchronization reference, align the timestamps of the voltage fluctuation parameters on the anode side and the hydrogen evolution rate parameters on the cathode side; Under the synchronization reference, intercept the data segments of the voltage fluctuation parameters on the anode side and the hydrogen evolution on the cathode side with a fixed time window to generate a dynamic response sequence.

[0007] In a preferred embodiment, extract the anode polarization fluctuation characteristics and the cathode concentration polarization fluctuation characteristics from the dynamic response sequence, and calculate the dynamic coupling degree to identify the polarization alternation dominant mode, including: Extract the standard deviation of the anode voltage of the anode polarization fluctuation characteristics and the slope of the change in the hydrogen evolution rate of the cathode concentration polarization fluctuation characteristics from the dynamic response sequence; Normalize the standard deviation of the anode voltage and the slope of the change in the hydrogen evolution rate according to the time window to generate a normalized anode polarization coefficient and a normalized cathode concentration polarization coefficient; Calculate the product of the normalized anode polarization coefficient and the normalized cathode concentration polarization coefficient as the dynamic coupling degree; When the dynamic coupling degree is greater than the preset threshold, it is determined as the ohmic polarization dominant mode, and when it is less than or equal to the preset threshold, it is determined as the concentration polarization dominant mode.

[0008] In a preferred embodiment, determine the local blocking probability of the ion transport path at the membrane electrode interface based on the frequency characteristics of the polarization alternation dominant mode, including: Separate the energy of the high-frequency fluctuation component and the energy of the low-frequency fluctuation component from the frequency characteristics of the polarization alternation dominant mode; Calculate the ratio of the energy of the high-frequency fluctuation component to the energy of the low-frequency fluctuation component as the interaction coefficient of microcrack and pore blockage; Map and generate the local blocking probability of the ion transport path at the membrane electrode interface according to the deviation degree of the interaction coefficient from the preset reference value; The preset reference value is the calibrated ratio of the energy of the high-frequency fluctuation component to the energy of the low-frequency fluctuation component of the electrolytic cell in the unblocked state.

[0009] In a preferred embodiment, the spatial distribution characteristics of the membrane electrode interface temperature gradient parameters are collected and analyzed, the sparse area of the active site distribution is located according to the high-frequency mutation region, and an efficiency fluctuation evaluation coefficient is generated in combination with the dynamic coupling degree, including: Collect the membrane electrode interface temperature gradient parameters, analyze the spatial distribution characteristics of the membrane electrode interface temperature gradient parameters, calculate the temperature gradient change rate between adjacent temperature measurement points, and identify the high-frequency mutation region; Determine the boundary coordinates of the sparse area of the active site distribution according to the continuous distribution area of the high-frequency mutation region and the number of mutations per unit area; Multiply the area ratio of the sparse area of the active site distribution by the dynamic coupling degree according to a preset weight coefficient to generate an efficiency fluctuation evaluation coefficient; The preset weight coefficient is calibrated based on the influence degree of the area ratio of the sparse area and the dynamic coupling degree on the efficiency fluctuation in historical data.

[0010] In a preferred embodiment, a spatial correspondence relationship between the sparse area of the active site distribution and the cathode flow field pressure gradient is established, and a dynamic compensation factor matrix is constructed, including: Map the boundary coordinates of the sparse area of the active site distribution to the spatial distribution grid of the cathode flow field pressure gradient; Quantify the cathode flow field pressure gradient drop amplitude within the grid corresponding to the sparse area boundary coordinates to generate a local pressure compensation coefficient; Construct a dynamic compensation factor matrix according to the local pressure compensation coefficients of all grids corresponding to the sparse area boundary coordinates and the gradient correlation degree with adjacent grids.

[0011] In a preferred embodiment, the gradient correlation degree is the matching degree between the cathode flow field pressure gradient change rate of adjacent grids and the pressure compensation demand of the sparse area.

[0012] In a preferred embodiment, according to the change trends of the efficiency fluctuation evaluation coefficient and the dynamic compensation factor matrix, the anode current density distribution weight and the cathode flow field pressure gradient parameters are adjusted so that the adjustment amount satisfies the cooperative matching condition of the local blocking probability and the dynamic coupling degree, including: Quantify the periodic change amplitude of the efficiency fluctuation evaluation coefficient and the gradient change direction of the dynamic compensation factor matrix; Generate an anode current density distribution weight adjustment instruction and a cathode flow field pressure gradient adjustment instruction according to the periodic change amplitude of the efficiency fluctuation evaluation coefficient and the gradient change direction of the dynamic compensation factor matrix; Based on the cooperative matching condition of the local blocking probability and the dynamic coupling degree, constrain the proportional relationship between the anode current density distribution weight adjustment amount and the cathode flow field pressure gradient adjustment amount.

[0013] In a preferred embodiment, the collaborative matching condition is a linear mapping relationship between the product of the local blocking probability and the dynamic coupling degree and the adjustment amount ratio.

[0014] On the other hand, the present invention provides an operating state monitoring system for an AEM electrolytic water hydrogen production device, including the following modules: The acquisition synchronization module: used to collect in real time and perform time series synchronization calibration on the anode-side voltage fluctuation parameters and the cathode-side hydrogen evolution rate parameters of the electrolytic cell to generate a dynamic response sequence; The feature coupling module: used to extract the anode polarization fluctuation feature and the cathode concentration polarization fluctuation feature from the dynamic response sequence, and calculate the dynamic coupling degree to identify the polarization alternation dominant mode; The frequency resistance determination module: used to determine the local blocking probability of the ion transport path at the membrane electrode interface based on the frequency characteristics of the polarization alternation dominant mode; The temperature analysis and positioning module: used to collect and analyze the spatial distribution characteristics of the temperature gradient parameters at the membrane electrode interface, locate the sparse area of the active site distribution according to the high-frequency mutation area, and generate an efficiency fluctuation evaluation coefficient in combination with the dynamic coupling degree; The air pressure mapping module: used to establish the spatial correspondence between the sparse area of the active site distribution and the cathode flow field pressure gradient, and construct a dynamic compensation factor matrix; The co-state adjustment module: used to adjust the anode current density distribution weight and the cathode flow field pressure gradient parameters according to the change trends of the efficiency fluctuation evaluation coefficient and the dynamic compensation factor matrix, so that the adjustment amount meets the collaborative matching condition of the local blocking probability and the dynamic coupling degree.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. Through the analysis of dynamic coupling polarization characteristics and temperature gradients, the accurate capture and cross-field collaborative regulation of the microscopic deterioration state of the membrane electrode interface are realized. It is constructed based on the time series synchronized dynamic response sequence, effectively identifying the alternating dominant modes of ohmic polarization and concentration polarization. Combining with the positioning of the sparse area of active sites in the high-frequency temperature mutation area, through the joint analysis of the dynamic coupling degree and the local blocking probability, a multi-scale state evaluation model of the physical formation of microscopic structure deterioration (such as microcracks and pore blockages) and macroscopic efficiency fluctuations is established. Compared with the prior art, it can sense the dynamic changes of the ion transport path in real time at low current densities, and significantly improve the utilization rate of active sites through the cross-field mapping of the compensation factor matrix, suppressing the non-linear oscillation of efficiency caused by the polarization mode switching.

[0016] 2. By dynamically adapting the spatial pressure gradient compensation to the current density distribution, the problem of the coupled superposition of local blockage and polarization effect in traditional regulation methods is solved. Based on the spatial correspondence between the sparse region of active sites and the pressure gradient, a dynamic matrix is constructed to match the microscopic blockage state and the flow field mechanical characteristics in real time, realizing the coordinated regulation of the anode current density weight and the cathode pressure gradient. Through the coordinated constraint conditions of the local blockage probability and the dynamic coupling degree, it is ensured that the adjustment amount always matches the actual deterioration degree of the electrolytic cell and the polarization fluctuation intensity, avoiding the control instability caused by over-compensation or under-compensation. While maintaining the stability of the electrolysis efficiency, the risk of membrane electrode failure caused by the accumulation of microscopic structure damage is significantly reduced, ensuring the long-term reliable operation of the AEM electrolytic cell in the scenario of renewable energy fluctuations. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a flowchart of a method for monitoring the operating state of an AEM electrolytic water hydrogen production device of the present invention; Figure 2 is a schematic structural diagram of a system for monitoring the operating state of an AEM electrolytic water hydrogen production device of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0019] Embodiment 1: Figure 1 A method for monitoring the operating state of an AEM electrolytic water hydrogen production device of the present invention is given, which includes the following steps: S1. Real-time collect and perform time-series synchronization calibration on the anode-side voltage fluctuation parameters and the cathode-side hydrogen evolution rate parameters of the electrolytic cell to generate a dynamic response sequence; S2. Extract the anode polarization fluctuation characteristics and the cathode concentration polarization fluctuation characteristics from the dynamic response sequence, and calculate the dynamic coupling degree to identify the polarization alternation dominant mode; S3. Determine the local blockage probability of the ion transport path at the membrane electrode interface based on the frequency characteristics of the polarization alternation dominant mode; S4. Collect and analyze the spatial distribution characteristics of the temperature gradient parameters at the membrane electrode interface, locate the sparse region of active site distribution according to the high-frequency mutation region, and generate an efficiency fluctuation evaluation coefficient in combination with the dynamic coupling degree; S5. Establish the spatial correspondence between the sparse region of active site distribution and the cathode flow field pressure gradient, and construct a dynamic compensation factor matrix; S6. Adjust the anode current density distribution weight and the cathode flow field pressure gradient parameter according to the change trends of the efficiency fluctuation evaluation coefficient and the dynamic compensation factor matrix, so that the adjustment amount meets the collaborative matching condition of the local blocking probability and the dynamic coupling degree.

[0020] S1. Collect in real time and perform time-series synchronization calibration on the anode-side voltage fluctuation parameter and the cathode-side hydrogen evolution rate parameter of the electrolytic cell to generate a dynamic response sequence. The specific implementation is as follows: Obtain the anode-side voltage fluctuation parameter and the cathode-side hydrogen evolution rate parameter of the electrolytic cell through a preset sensor group with a periodic acquisition period. The sensor group includes, but is not limited to, a high-precision voltage sensor on the anode side and a gas mass flow sensor on the cathode side. The acquisition frequency of the anode-side voltage fluctuation parameter and the acquisition frequency of the cathode-side hydrogen evolution rate parameter are both set to a fixed period synchronized with the clock signal of the electrolytic cell controller. For example, the acquisition period of the anode-side voltage fluctuation parameter is set to collect once every 100 milliseconds, and the acquisition period of the cathode-side hydrogen evolution rate parameter is also set to collect once every 100 milliseconds, and the start moments of both acquisition periods are aligned with the rising edge of the clock signal of the electrolytic cell controller.

[0021] Take the clock signal of the electrolytic cell controller as the synchronization reference to align the timestamps of the anode-side voltage fluctuation parameter and the cathode-side hydrogen evolution rate parameter. The synchronization reference is the standard time signal output by the internal clock of the electrolytic cell controller, and the time resolution of this clock signal is 1 microsecond. During the timestamp alignment process, each data point of the anode-side voltage fluctuation parameter and each data point of the cathode-side hydrogen evolution rate parameter are marked with the corresponding clock signal timestamp, and the acquisition time deviation between the anode-side voltage fluctuation parameter and the cathode-side hydrogen evolution rate parameter is controlled within 1 millisecond through the timestamp matching algorithm. For example, if a data point of the anode-side voltage fluctuation parameter is collected at the 1000th millisecond moment of the clock signal, and a corresponding data point of the cathode-side hydrogen evolution rate parameter is collected at the 1000.5th millisecond moment of the clock signal, then the time deviation between the two is corrected to the same clock signal cycle through timestamp alignment.

[0022] Under the synchronous reference, data segments of the anode-side voltage fluctuation parameters and the cathode-side hydrogen evolution rate parameters are intercepted within a fixed time window to generate a dynamic response sequence. The length of the fixed time window is set to an integer multiple of the clock signal period of the electrolyzer controller. For example, 10 consecutive clock cycles (i.e., 1 second) are selected as the time window length. Within each time window, the data segment of the anode-side voltage fluctuation parameters is composed of the collected data of all anode-side voltage fluctuation parameters arranged in chronological order within that time window, and the data segment of the cathode-side hydrogen evolution rate parameters is composed of the collected data of all cathode-side hydrogen evolution rate parameters arranged in chronological order within that time window. The dynamic response sequence is generated by aligning the data segments of the anode-side voltage fluctuation parameters and the cathode-side hydrogen evolution rate parameters within the same time window according to the timestamps and then merging them into a single data sequence. For example, within a time window, the anode-side voltage fluctuation parameters include 10 voltage values arranged in chronological order, and the cathode-side hydrogen evolution rate parameters include 10 gas flow values arranged in chronological order. The dynamic response sequence is generated by combining each voltage value with the flow value corresponding to its timestamp into a data pair, and arranging all data pairs in chronological order to form a dynamic response sequence.

[0023] The setting of the periodic acquisition period is based on the dynamic response characteristics of the electrolyzer operating conditions. For example, in the low current density range (less than 0.5 amperes per square centimeter), the electro-chemical reaction time constant of the electrolyzer is usually in the range of 100 milliseconds to 1 second. Therefore, the acquisition period is set to 100 milliseconds to cover the key frequency band of the reaction dynamic process. The setting of the time window length is based on the switching period of the polarization alternation dominant mode. For example, the alternation dominant period of ohmic polarization and concentration polarization is verified to be 1 to 5 seconds. Therefore, the time window length is set to 1 second to capture at least one complete polarization alternation cycle.

[0024] The time deviation correction method during the timestamp alignment process is the value method. For example, if data points are missing within a certain clock signal period of the anode-side voltage fluctuation parameters, interpolation calculations are performed according to the numerical differences between two adjacent voltage data points in proportion to time to complete the missing values; the data completion method for the cathode-side hydrogen evolution rate parameters is the same as that for the anode-side voltage fluctuation parameters. The data storage format of the dynamic response sequence is a two-dimensional array, where the first dimension is the time axis and the second dimension contains the anode-side voltage fluctuation parameter values and the cathode-side hydrogen evolution rate parameter values. For example, the storage form of the nth data point of the dynamic response sequence is [timestamp n, voltage value n, flow value n], and all data points are arranged in ascending order of timestamps, where n is the number of data points in the dynamic response sequence.

[0025] The calibration method for the sensor group is to regularly perform a comparison with a standard signal source. For example, a standard voltage signal (such as 1.0 V, 1.5 V, 2.0 V) is applied to the anode-side voltage sensor every 24 hours, and the output value of the sensor is recorded. If the deviation between the sensor output value and the standard voltage signal exceeds 0.5%, a calibration alarm is triggered; for the cathode-side gas mass flow sensor, a standard gas with a known flow rate (such as hydrogen with a purity of 99.999%) is introduced, and the output value of the sensor is recorded. If the flow measurement deviation exceeds 1%, a calibration alarm is triggered. During the generation of the dynamic response sequence, if data loss or outliers are detected, the sequence continuity is maintained by repeating the previous valid data point. For example, if the anode-side voltage fluctuation parameter at a certain moment is not collected due to a sensor failure, the voltage value at that moment is filled with the previous valid voltage value.

[0026] The generation method of the dynamic response sequence realizes data caching and arrangement through the memory built into the controller. The memory capacity should at least meet the requirement of storing the dynamic response sequence data for 1 hour continuously. For example, if each data point occupies 16 bytes of storage space and the acquisition period is 100 milliseconds, the total amount of dynamic response sequence data for 1 hour is 16 bytes × 10 data points / second × 3600 seconds = 576,000 bytes. The memory capacity of the controller needs to be configured to be no less than 1 megabyte to support the data caching requirement.

[0027] S2. Extract the anode polarization fluctuation characteristics and cathode concentration polarization fluctuation characteristics from the dynamic response sequence, and calculate the dynamic coupling degree to identify the polarization alternation dominant mode. The specific implementation is as follows: Extract the standard deviation of the anode voltage, which is the anode polarization fluctuation characteristic, and the slope of the change in the hydrogen evolution rate, which is the cathode concentration polarization fluctuation characteristic, from the dynamic response sequence. The calculation method for the standard deviation of the anode voltage is as follows: for the data segment of the anode-side voltage fluctuation parameter in each time window of the dynamic response sequence, calculate the standard deviation of all voltage values in this data segment. For example, in a time window containing 10 anode-side voltage fluctuation parameter values, first calculate the average value of these 10 voltage values, then calculate the square of the difference between each voltage value and the average value, take the average of the squared differences and then take the square root to obtain the standard deviation of the anode voltage. The calculation method for the slope of the change in the hydrogen evolution rate is as follows: for the data segment of the cathode-side hydrogen evolution rate parameter in the same time window of the dynamic response sequence, perform a linear regression analysis with the time stamp as the horizontal axis and the hydrogen evolution rate value as the vertical axis, and take the slope value of the regression line as the slope of the change in the hydrogen evolution rate. For example, if the hydrogen evolution rate value increases with time in the time window, the slope of the change in the hydrogen evolution rate is positive; if it decreases, it is negative.

[0028] Normalize the standard deviation of the anode voltage and the slope of the change in the hydrogen evolution rate according to a time window to generate a normalized anodic polarization coefficient and a normalized cathodic concentration polarization coefficient. The normalization method is as follows: for the standard deviation of the anode voltage within the same time window, divide it by the reference value of the maximum anode voltage standard deviation of the electrolytic cell at the rated current density to obtain the normalized anodic polarization coefficient; for the slope of the change in the hydrogen evolution rate, divide it by the reference value of the maximum slope of the change in the hydrogen evolution rate of the electrolytic cell at the rated current density to obtain the normalized cathodic concentration polarization coefficient. For example, if the reference value of the maximum anode voltage standard deviation at the rated current density is 0.1 V and the standard deviation of the anode voltage in the current time window is 0.05 V, the normalized anodic polarization coefficient is 0.05 / 0.1 = 0.5; if the reference value of the maximum slope of the change in the hydrogen evolution rate is 0.2 L / (min·s) and the slope of the change in the hydrogen evolution rate in the current time window is 0.1 L / (min·s), the normalized cathodic concentration polarization coefficient is 0.1 / 0.2 = 0.5.

[0029] Calculate the product of the normalized anodic polarization coefficient and the normalized cathodic concentration polarization coefficient as the dynamic coupling degree. The calculation method of the product is to directly multiply the normalized anodic polarization coefficient and the normalized cathodic concentration polarization coefficient. If the normalized anodic polarization coefficient is 0.5 and the normalized cathodic concentration polarization coefficient is 0.5, the dynamic coupling degree is 0.5×0.5 = 0.25; if the normalized anodic polarization coefficient is 0.8 and the normalized cathodic concentration polarization coefficient is 0.3, the dynamic coupling degree is 0.8×0.3 = 0.24.

[0030] When the dynamic coupling degree is greater than the preset threshold, it is determined as the ohmic polarization dominant mode; when it is less than or equal to the preset threshold, it is determined as the concentration polarization dominant mode. The setting basis of the preset threshold is the critical value of the dynamic coupling degree when ohmic polarization and concentration polarization alternate in the historical operation data. For example, by analyzing the dynamic coupling degree data during multiple polarization mode switching processes in the low current density range of the electrolytic cell, it is statistically obtained that when the dynamic coupling degree exceeds 0.3, ohmic polarization dominates, and when it is less than or equal to 0.3, concentration polarization dominates. Therefore, the preset threshold is set to 0.3. The historical operation data includes but is not limited to the corresponding relationship data between the dynamic coupling degree and the polarization mode under different current densities, temperatures, and pressures.

[0031] The determination method of the reference value of the maximum standard deviation of the anode voltage and the reference value of the hydrogen evolution rate change slope under the rated current density is as follows: During the stable operation of the electrolytic cell at the rated current density, multiple sets of anode voltage fluctuation parameters and cathode hydrogen evolution rate parameter data are collected. The maximum value of the standard deviation of the anode voltage and the maximum absolute value of the hydrogen evolution rate change slope are used as the reference benchmarks for normalization processing. For example, when the rated current density is 1.0 A / cm², by continuously collecting the anode voltage fluctuation data within 1 hour, the maximum standard deviation of the anode voltage is calculated to be 0.1 V; by continuously collecting the hydrogen evolution rate data in the same period, the maximum hydrogen evolution rate change slope is 0.2 L / min·s.

[0032] In the linear regression analysis, the time stamp interval unit is milliseconds, which is consistent with the acquisition period of the dynamic response sequence. For example, if the acquisition period of the dynamic response sequence is 100 milliseconds, the time stamp interval is 100 milliseconds, and the time difference on the horizontal axis in the regression analysis is calculated by increasing in increments of 100 milliseconds. The calculation process of the linear regression analysis is as follows: According to the least squares principle, the slope value that minimizes the sum of the squares of the residuals between the hydrogen evolution rate value and the predicted value of the regression line is obtained. For example, for the hydrogen evolution rate data points within the time window, the slope is calculated by the least squares formula, and the specific calculation process is well-known technology in the art.

[0033] S3. Determine the local blockage probability of the ion transport path at the membrane electrode interface based on the frequency characteristics of the polarization alternation dominant mode. The specific implementation is as follows: Separate the energy of the high-frequency fluctuation component and the energy of the low-frequency fluctuation component from the frequency characteristics of the polarization alternation dominant mode. The frequency range of the energy of the high-frequency fluctuation component is 3 Hz to 5 Hz, corresponding to the tortuosity effect of the ion transport path caused by microcracks at the membrane electrode interface; the frequency range of the energy of the low-frequency fluctuation component is 0.5 Hz to 2 Hz, corresponding to the effect of the extended reactant diffusion path caused by pore blockage in the catalyst layer. The frequency characteristics are obtained by converting the time-domain signal of the polarization alternation dominant mode through the fast Fourier transform method. Among them, the energy of the high-frequency fluctuation component is the sum of the energies of all frequency components within the frequency band of 3 Hz to 5 Hz, and the energy of the low-frequency fluctuation component is the sum of the energies of all frequency components within the frequency band of 0.5 Hz to 2 Hz. For example, if the sum of the energies of the frequency characteristics of the polarization alternation dominant mode in the frequency band of 3 Hz to 5 Hz is 100 mJ, and the sum of the energies in the frequency band of 0.5 Hz to 2 Hz is 80 mJ, then the energy of the high-frequency fluctuation component is 100 mJ, and the energy of the low-frequency fluctuation component is 80 mJ.

[0034] Calculate the ratio of the energy of the high-frequency fluctuation component to the energy of the low-frequency fluctuation component as the interaction coefficient of microcracks and pore blockage. The ratio is calculated by dividing the energy of the high-frequency fluctuation component by the energy of the low-frequency fluctuation component. For example, if the energy of the high-frequency fluctuation component is 100 millijoules and the energy of the low-frequency fluctuation component is 80 millijoules, the interaction coefficient is 100 / 80 = 1.25; if the energy of the high-frequency fluctuation component is 60 millijoules and the energy of the low-frequency fluctuation component is 120 millijoules, the interaction coefficient is 60 / 120 = 0.5. The physical meaning of the interaction coefficient is the relative strength of the microcrack effect and the pore blockage effect. When the interaction coefficient is greater than 1, it indicates that the microcrack effect dominates; when it is less than 1, it indicates that the pore blockage effect dominates.

[0035] According to the deviation degree of the interaction coefficient from the preset reference value, map and generate the local blockage probability of the ion transport path at the membrane electrode interface. The preset reference value is the calibrated ratio of the energy of the high-frequency fluctuation component to the energy of the low-frequency fluctuation component when the electrolytic cell is in an unblocked state. The determination method is as follows: in the unblocked state after the new installation or cleaning and maintenance of the electrolytic cell, continuously collect multiple groups of frequency characteristic data of the polarization-alternating dominant mode, calculate the ratio of the energy of the high-frequency fluctuation component to the energy of the low-frequency fluctuation component for each group of data, and take the average of all ratios as the preset reference value. For example, if the ratios of the energy of the high-frequency fluctuation component to the energy of the low-frequency fluctuation component measured in three groups when the electrolytic cell is in an unblocked state are 1.2, 1.3, and 1.1 respectively, the preset reference value is (1.2 + 1.3 + 1.1) / 3 = 1.2. The calculation method of the deviation degree is the percentage of the absolute difference between the interaction coefficient and the preset reference value to the preset reference value. For example, if the preset reference value is 1.2 and the current interaction coefficient is 1.25, the deviation degree is (1.25 - 1.2) / 1.2×100% = 4.17%.

[0036] The method for mapping and generating the local blockage probability is as follows: divide different blockage levels according to the magnitude of the deviation degree, and linearly map them to the probability interval from 0 to 1. For example, when the deviation degree is less than or equal to 5%, it is determined as the unblocked state, and the local blockage probability is 0; when the deviation degree is greater than 5% and less than or equal to 20%, the local blockage probability is (deviation degree - 5%) / 15%; when the deviation degree is greater than 20%, the local blockage probability is 1. The basis for dividing the blockage levels is the empirical data of the operation and maintenance of the electrolytic cell. For example, when the deviation degree exceeds 20%, it is necessary to immediately stop the machine for maintenance. The linear mapping relationship is determined by experimental calibration. Specifically, collect the corresponding relationship data between the deviation degree and the actual blockage degree (such as the proportion of the microcrack area observed by electron microscopy and the pore blockage rate) in different blockage states of the electrolytic cell, and establish a linear regression model between the deviation degree and the blockage probability. For example, if the experimental data shows that for every 1% increase in the deviation degree, the actual blockage probability increases by 0.05, the formula for calculating the local blockage probability is 0.05×deviation degree.

[0037] In the above embodiments, the frequency range division basis for the high-frequency and low-frequency fluctuation components is the characteristic frequency response of the microscopic defects at the membrane electrode interface of the electrolytic cell. For example, through electrochemical impedance spectroscopy tests, it is found that the tortuosity effect of the ion transport path caused by microcracks shows significant impedance changes in the frequency band of 3 Hz to 5 Hz, while the diffusion resistance caused by pore blockage is more obvious in the frequency band of 0.5 Hz to 2 Hz. The fast Fourier transform method is a signal processing technique well-known in the art, and its specific application scenario is the frequency-domain energy analysis of the polarization alternation dominant mode. The mapping rule of the local blockage probability is realized by calibrating experimental data. For example, the blockage level division thresholds (such as 5% and 20%) are obtained based on the statistical data of the historical operation faults of the electrolytic cell to ensure the early warning accuracy.

[0038] S4. Collect and analyze the spatial distribution characteristics of the temperature gradient parameters at the membrane electrode interface, locate the sparse area of the active site distribution according to the high-frequency mutation area, and generate an efficiency fluctuation evaluation coefficient in combination with the dynamic coupling degree. The specific implementation is as follows: Collect the temperature gradient parameters at the membrane electrode interface, analyze the spatial distribution characteristics of the temperature gradient parameters at the membrane electrode interface, calculate the temperature gradient change rate between adjacent temperature measurement points and identify the high-frequency mutation area. The temperature gradient parameters at the membrane electrode interface are collected in real time through a temperature measurement point array distributed on the surface of the membrane electrode, and the temperature data of each temperature measurement point is updated according to a preset collection period (for example, 100 milliseconds). The calculation method of the temperature gradient change rate is: for the temperature values of two adjacent temperature measurement points, calculate the ratio of the temperature difference to the physical distance between the two points. For example, if the temperatures of two adjacent temperature measurement points are 80°C and 85°C respectively, and the distance between the two points is 5 mm, then the temperature gradient change rate is (85 - 80) / 5 = 1°C / mm. The identification condition for the high-frequency mutation area is: the absolute value of the temperature gradient change rate exceeds the mutation threshold within three consecutive collection periods at the same temperature measurement point. For example, if the mutation threshold is set to 0.8°C / mm, when the temperature gradient change rate of a certain temperature measurement point is 0.9°C / mm, 1.0°C / mm, and 1.1°C / mm respectively in three consecutive collection values, it is determined that this area is a high-frequency mutation area.

[0039] Determine the boundary coordinates of the sparse region of active site distribution based on the continuous distribution area of high-frequency mutation regions and the number of mutations per unit area. The calculation method for the continuous distribution area is as follows: count the connected regions formed by all adjacent high-frequency mutation regions, and calculate the number of temperature measurement points covered by it multiplied by the physical area represented by a single temperature measurement point. For example, if a single temperature measurement point represents an area of 2 square millimeters and a certain connected region contains 50 temperature measurement points, then the continuous distribution area is 50×2 = 100 square millimeters. The calculation method for the number of mutations per unit area is as follows: count the total number of times all temperature measurement points in this connected region reach the mutation threshold within a unit time (such as 1 minute), and divide it by the area of this connected region. For example, if the area of a certain connected region is 100 square millimeters and 200 mutations are detected within 1 minute, then the number of mutations per unit area is 200 / 100 = 2 times per square millimeter. The rule for determining the boundary coordinates of the sparse region is: when the continuous distribution area is greater than or equal to the preset area threshold (such as 50 square millimeters) and the number of mutations per unit area is greater than or equal to the preset number threshold (such as 1 time per square millimeter), mark the coordinates of the temperature measurement points on the outer contour of this connected region as the boundary coordinates of the sparse region.

[0040] Multiply the area proportion of the sparse region of active site distribution and the dynamic coupling degree by the preset weight coefficient to generate the efficiency fluctuation evaluation coefficient. The calculation method for the area proportion is: the area of the sparse region divided by the total area of the membrane electrode interface. For example, if the area of the sparse region is 100 square millimeters and the total area of the membrane electrode is 500 square millimeters, then the area proportion is 100 / 500 = 0.2. The calibration method for the preset weight coefficient is: statistically analyze the influence weights of the area proportion of the sparse region and the dynamic coupling degree on the efficiency fluctuation through historical operation data. For example, by analyzing multiple groups of historical data, it is found that for every 0.1 increase in the area proportion of the sparse region, the efficiency decreases by 5%, and for every 0.1 increase in the dynamic coupling degree, the efficiency decreases by 3%. Then the weight coefficients are set to 0.5 and 0.3 respectively.

[0041] The generation method of the efficiency fluctuation evaluation coefficient is: efficiency fluctuation evaluation coefficient = area proportion × weight coefficient α + dynamic coupling degree × weight coefficient β. For example, if the area proportion is 0.2, the weight coefficient α is 0.5, the dynamic coupling degree is 0.3, and the weight coefficient β is 0.3, then the efficiency fluctuation evaluation coefficient = 0.2×0.5 + 0.3×0.3 = 0.1 + 0.09 = 0.19.

[0042] The determination basis of the mutation threshold, the preset area threshold, and the preset number threshold is the statistical result of abnormal operating conditions in the historical operation data of the electrolytic cell. For example, through the analysis of membrane electrode failure cases, it is found that when the temperature gradient change rate exceeds 0.8 °C / mm, the corresponding risk of microcrack propagation increases significantly. Therefore, the mutation threshold is set to 0.8 °C / mm. The calibration process of the weight coefficient α and the weight coefficient β is as follows: Under different operating states of the electrolytic cell, the data of the area ratio of the sparse area, the dynamic coupling degree, and the actual efficiency fluctuation are collected, and the contribution weights of each parameter are determined through multiple linear regression analysis. For example, the regression coefficient of the area ratio of the sparse area obtained by regression analysis is 0.5, and the regression coefficient of the dynamic coupling degree is 0.3. Then, the weight coefficient α = 0.5 / (0.5 + 0.3) = 0.625, and the weight coefficient β = 0.3 / (0.5 + 0.3) = 0.375.

[0043] In the above embodiments, the calculation of the temperature gradient change rate, the analysis of the connected region, and the calibration of the weight coefficient are all realized based on the existing data processing methods. For example, the flood filling algorithm in the field of image processing is used for the analysis of the connected region, and the specific application scenario is the boundary recognition of the high-frequency mutation region. The generation process of the efficiency fluctuation evaluation coefficient is realized by the arithmetic logic unit built in the controller, and its calculation rule can be dynamically adjusted according to the type of the electrolytic cell. For example, for different types of electrolytic cells, the characteristics can be adapted by updating the values of the weight coefficients α and β.

[0044] S5. Establish the spatial correspondence relationship between the sparse area of the active site distribution and the cathode flow field pressure gradient, and construct a dynamic compensation factor matrix. The specific implementation is as follows: Map the boundary coordinates of the sparse area of the active site distribution to the spatial distribution grid of the cathode flow field pressure gradient. The spatial distribution grid of the cathode flow field pressure gradient is a Cartesian grid divided based on the flow channel geometric structure. Each grid unit corresponds to the physical area of the flow channel and stores the real-time pressure gradient value of this area. The mapping method is as follows: Convert the sparse area boundary coordinates into grid indices to determine the grid unit where the boundary coordinates are located and the adjacent grid units. For example, if the flow channel is divided into a 10×10 grid and each grid corresponds to a 5 mm×5 mm area, and the sparse area boundary coordinates are (15 mm, 25 mm), then it is mapped to the grid unit corresponding to the grid index (3, 5).

[0045] Quantify the pressure gradient decline amplitude within the grid corresponding to the boundary coordinates of the sparse region to generate a local pressure compensation coefficient. The calculation method of the pressure gradient decline amplitude is as follows: Compare the current pressure gradient value with the reference pressure gradient value in the unobstructed state and calculate its relative decline percentage. For example, if the reference pressure gradient value of a grid cell in the unobstructed state is 0.5 MPa / m and the current pressure gradient value is 0.4 MPa / m, then the decline amplitude is (0.5 - 0.4) / 0.5×100% = 20%. The generation rule of the local pressure compensation coefficient is: for every 1% increase in the decline amplitude, the compensation coefficient increases by 0.01. For example, when the decline amplitude is 20%, the local pressure compensation coefficient is 0.2.

[0046] Construct a dynamic compensation factor matrix based on the local pressure compensation coefficients of all sparse region grids and the gradient correlation degree with adjacent grids. The calculation method of the gradient correlation degree is: Statistically analyze the consistency between the pressure gradient change direction of adjacent grid cells and the pressure compensation demand direction of the sparse region. For example, if the sparse region needs to increase the pressure gradient (positive correlation with the compensation coefficient), and the pressure gradient change direction of the adjacent grid is increasing, then the gradient correlation degree is 1; if the directions are opposite, it is 0. The construction rule of the dynamic compensation factor matrix is: Multiply the local pressure compensation coefficient of each sparse region grid by the sum of its gradient correlation degrees with adjacent grids as the compensation factor for this grid. For example, the local pressure compensation coefficient of a sparse region grid is 0.2, and its gradient correlation degrees with three adjacent grids are 1, 0, and 1 respectively, then the compensation factor is 0.2×(1 + 0 + 1) = 0.4.

[0047] The determination method of the reference pressure gradient value in the unobstructed state is: After the electrolytic cell is newly installed or cleaned and maintained, collect the pressure gradient data of each grid cell and calculate its average value as the reference value. For example, in a 10×10 grid, each grid cell continuously collects 10 pressure gradient data in the unobstructed state, and take the average value of the 10 data as the reference pressure gradient value of this grid. The linear relationship between the compensation coefficient and the decline amplitude is calibrated through historical data. For example, by analyzing the pressure gradient decline amplitude and compensation effect of the electrolytic cell under different obstruction degrees, determine the proportional relationship that for every 1% decline amplitude, the compensation coefficient is 0.01.

[0048] The basis for judging the direction consistency of the gradient correlation degree is the correlation between the pressure gradient change trend and the compensation demand. For example, when the sparse region needs to increase the pressure gradient, if the pressure gradient of the adjacent grid shows an upward trend, it is judged as a positive correlation, and if it shows a downward trend, it is judged as a negative correlation. The update period of the dynamic compensation factor matrix is synchronized with the clock signal of the electrolytic cell controller to ensure the real-time nature of the compensation adjustment. For example, update the compensation factor matrix every 100 milliseconds according to the latest pressure gradient data.

[0049] In the above embodiments, the mesh generation, coordinate mapping, and compensation factor calculation are all implemented based on the physical structure of the flow channel and existing data processing methods. For example, Cartesian mesh generation and index mapping are conventional techniques in the field of computational fluid dynamics, and their specific application scenario is the spatial correlation analysis of the flow field pressure gradient and the sparse area of active sites. The direction determination of the gradient correlation degree is achieved by comparing the change trends of the pressure gradients of adjacent meshes.

[0050] S6. According to the change trends of the efficiency fluctuation evaluation coefficient and the dynamic compensation factor matrix, adjust the anode current density distribution weight and the cathode flow field pressure gradient parameter so that the adjustment amount satisfies the collaborative matching condition of the local blockage probability and the dynamic coupling degree. The specific implementation is as follows: Quantify the periodic change amplitude of the efficiency fluctuation evaluation coefficient and the gradient change direction of the dynamic compensation factor matrix. The calculation method of the periodic change amplitude is as follows: perform a moving window average process on the efficiency fluctuation evaluation coefficient, and calculate the difference between the maximum value and the minimum value within the window as the change amplitude. For example, select the efficiency fluctuation evaluation coefficients of 10 consecutive time windows, and calculate the difference between the maximum value of 0.25 and the minimum value of 0.15 as the change amplitude of 0.1. The method for determining the gradient change direction of the dynamic compensation factor matrix is as follows: compare the change trends of the compensation factor values of adjacent mesh cells. If the compensation factor increases along the flow channel direction, it is determined as a positive gradient; if it decreases, it is a negative gradient. For example, if the compensation factor of mesh A is 0.4, the downstream mesh B is 0.5, and the upstream mesh C is 0.3, then the gradient directions are positive from A to B and negative from A to C.

[0051] Generate an anode current density distribution weight adjustment instruction and a cathode flow field pressure gradient adjustment instruction according to the periodic change amplitude of the efficiency fluctuation evaluation coefficient and the gradient change direction of the dynamic compensation factor matrix. The generation rule of the adjustment instruction is as follows: when the change amplitude of the efficiency fluctuation evaluation coefficient is greater than or equal to the fluctuation threshold and the gradient direction of the dynamic compensation factor matrix is positive, generate an instruction to increase the anode current density distribution weight; when the gradient direction is negative, generate an instruction to decrease the cathode flow field pressure gradient. For example, if the change amplitude is 0.1 (the fluctuation threshold is set to 0.08) and the gradient direction is positive, the anode current density distribution weight is increased by 5%; if the gradient direction is negative, the cathode flow field pressure gradient is decreased by 3%.

[0052] Based on the collaborative matching condition of local blockage probability and dynamic coupling degree, the proportional relationship between the adjustment amount of the anode current density distribution weight and the adjustment amount of the cathode flow field pressure gradient is constrained. The collaborative matching condition is the linear mapping relationship between the product of the local blockage probability and the dynamic coupling degree and the adjustment amount ratio. For example, if the local blockage probability is 0.3 and the dynamic coupling degree is 0.4, the product is 0.12, and the corresponding adjustment amount ratio is anode current density weight adjustment amount: cathode pressure gradient adjustment amount = 0.12:0.08 = 3:2. The mapping rule of the proportional relationship is determined by experimental calibration. The corresponding relationship data of the local blockage probability, dynamic coupling degree and adjustment amount ratio are collected under different operating states of the electrolytic cell, and a linear regression model of the product and the ratio value is established. For example, experimental data shows that for every 0.01 increase in the product, the anode adjustment amount ratio increases by 0.5% and the cathode adjustment amount ratio increases by 0.3%.

[0053] The setting basis of the fluctuation threshold and the adjustment amount ratio is the operating stability requirement of the electrolytic cell. For example, by analyzing the operating data of the electrolytic cell in the range of efficiency fluctuation amplitude from 0.08 to 0.12, it is determined that when the change amplitude exceeds 0.08, an adjustment instruction needs to be triggered to avoid efficiency oscillation. The calibration method of the linear mapping relationship is as follows: under different blockage degrees and polarization states of the electrolytic cell, the anode current density distribution weight and the cathode flow field pressure gradient parameters are gradually adjusted, and the optimal matching ratio of the local blockage probability, dynamic coupling degree and adjustment amount is recorded. The coefficient relationship between the product and the ratio is determined by least squares fitting. For example, the fitting result shows that the relationship between the product and the anode adjustment amount ratio is y = 5x (x is the product value, y is the adjustment amount percentage), and the relationship with the cathode adjustment amount ratio is y = 3x.

[0054] In the above embodiments, the sliding window average processing, gradient direction determination and linear regression model are all existing data processing methods. For example, the sliding window average processing is implemented through a circular buffer built into the controller. The buffer capacity is matched with the window length (such as 10 time windows). Each time an update is made, the earliest data point is removed and the latest data point is added. The gradient direction determination is achieved by comparing the numerical differences of the compensation factors of adjacent grid cells. The execution method of the adjustment instruction is to adjust the current distribution parameters of the anode power supply and the opening degree of the pressure regulating valve of the cathode flow channel through the analog output of the electrolytic cell controller.

[0055] Embodiment 2: Figure 2 The structural schematic diagram of an operating state monitoring system of an AEM electrolytic water hydrogen production device according to the present invention is given. An operating state monitoring system of an AEM electrolytic water hydrogen production device includes the following modules: Acquisition synchronization module: used to collect in real time and perform time series synchronization calibration on the anode side voltage fluctuation parameters and the cathode side hydrogen evolution rate parameters of the electrolytic cell, and generate a dynamic response sequence; Feature coupling module: used to extract the anode polarization fluctuation feature and the cathode concentration polarization fluctuation feature from the dynamic response sequence, and calculate the dynamic coupling degree to identify the polarization alternation dominant mode; Frequency resistance determination module: used to determine the local blockage probability of the ion transport path at the membrane electrode interface based on the frequency feature of the polarization alternation dominant mode; Temperature analysis and positioning module: used to collect and analyze the spatial distribution characteristics of the temperature gradient parameters at the membrane electrode interface, locate the sparse area of the active site distribution according to the high-frequency mutation area, and generate an efficiency fluctuation evaluation coefficient in combination with the dynamic coupling degree; Air pressure mapping module: used to establish the spatial correspondence between the sparse area of the active site distribution and the cathode flow field pressure gradient, and construct a dynamic compensation factor matrix; Covariant regulation module: used to adjust the anode current density distribution weight and the cathode flow field pressure gradient parameters according to the change trends of the efficiency fluctuation evaluation coefficient and the dynamic compensation factor matrix, so that the adjustment amount meets the collaborative matching condition of the local blockage probability and the dynamic coupling degree.

[0056] The above formulas are all dimensionless and take their numerical calculations. The formulas are obtained by collecting a large amount of data for software simulation to obtain a formula closest to the actual situation. The preset parameters and threshold selection in the formulas are set by those skilled in the art according to the actual situation.

[0057] It should be noted that the present invention can be deployed on the device itself to achieve embedded applications, or can also run on a PC or other terminals with a user interface, so as to meet various hardware environments and usage requirements.

[0058] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product.

[0059] Those of ordinary skill in the art can realize that the modules and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application of the technical solution and the invention constraints. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0060] In addition, in each embodiment of the present application, the functional modules can be integrated in a processing module, or each module can exist physically alone, or two or more modules can be integrated in one module.

[0061] In several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the modules is only a logical function division. In actual implementation, there may be other division methods. For example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of the devices or modules can be in electrical, mechanical, or other forms.

[0062] As described above, it is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed in the present application can easily think of changes or substitutions, which should all be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0063] Finally: The above are only the preferred embodiments of the present invention and are not used to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should all be included in the protection scope of the present invention.

Claims

1. A method for monitoring the operating status of an AEM water electrolysis hydrogen production device, characterized in that: The steps include: S1, real-time acquisition and timing synchronization calibration of the voltage fluctuation parameters on the anode side and the hydrogen evolution rate parameters on the cathode side of the electrolytic cell to generate a dynamic response sequence; S2, extracting the anode polarization fluctuation characteristics and cathode concentration polarization fluctuation characteristics from the dynamic response sequence, and calculating the dynamic coupling degree to identify the polarization alternation dominant mode; S3, determining the local blocking probability of the ion transport path at the membrane electrode interface based on the frequency characteristics of the polarization alternating dominant mode; S4. Collect and analyze the spatial distribution characteristics of the temperature gradient parameters at the membrane electrode interface, locate the sparsely distributed area of ​​active sites according to the high-frequency mutation area, and generate the efficiency fluctuation evaluation coefficient in combination with the dynamic coupling degree; S5, establishing the spatial correspondence between the sparsely distributed area of ​​active sites and the pressure gradient of the cathode flow field, and constructing a dynamic compensation factor matrix; S6. According to the changing trends of the efficiency fluctuation evaluation coefficient and the dynamic compensation factor matrix, the anode current density distribution weight and the cathode flow field pressure gradient parameter are adjusted so that the adjustment amount satisfies the coordinated matching conditions of the local blocking probability and the dynamic coupling degree.

2. The operating status monitoring method of an AEM water electrolysis hydrogen production equipment according to claim 1, characterized in that: Real-time acquisition and timing synchronization calibration of the voltage fluctuation parameters on the anode side and the hydrogen evolution rate parameters on the cathode side of the electrolyzer are performed to generate a dynamic response sequence, including: The voltage fluctuation parameters on the anode side and the hydrogen evolution rate parameters on the cathode side are obtained through a preset sensor group in a periodic acquisition cycle; Using the clock signal of the electrolyzer controller as the synchronization reference, the voltage fluctuation parameter on the anode side and the hydrogen evolution rate parameter on the cathode side are time-stamped and aligned; Under the synchronous reference, the data segments of the voltage fluctuation parameters on the anode side and the hydrogen evolution on the cathode side are intercepted in a fixed time window to generate a dynamic response sequence.

3. The method for monitoring the operating status of an AEM water electrolysis hydrogen production equipment according to claim 1, characterized in that: The anode polarization fluctuation characteristics and cathode concentration polarization fluctuation characteristics are extracted from the dynamic response sequence, and the dynamic coupling degree is calculated to identify the polarization alternation dominant mode, including: The anode voltage standard deviation of the anode polarization fluctuation characteristic and the slope of the hydrogen evolution rate change of the cathode concentration polarization fluctuation characteristic are extracted from the dynamic response sequence; The standard deviation of the anode voltage and the slope of the hydrogen evolution rate change are normalized according to the time window to generate a normalized anode polarization coefficient and a normalized cathode concentration polarization coefficient; The product of the normalized anode polarization coefficient and the normalized cathode concentration polarization coefficient is calculated as the dynamic coupling degree; When the dynamic coupling degree is greater than a preset threshold, it is determined to be an ohmic polarization-dominated mode; when it is less than or equal to the preset threshold, it is determined to be a concentration polarization-dominated mode.

4. The method for monitoring the operating status of an AEM water electrolysis hydrogen production equipment according to claim 1, characterized in that: The local blocking probability of the ion transport path at the membrane electrode interface is determined based on the frequency characteristics of the polarization alternating dominant mode, including: Separating high-frequency fluctuation component energy from low-frequency fluctuation component energy from the frequency characteristics of the polarization alternation dominant mode; The ratio of high-frequency fluctuation component energy to low-frequency fluctuation component energy is calculated as the interaction coefficient between microcracks and pore blockage; According to the deviation of the interaction coefficient from the preset reference value, the local blocking probability of the ion transmission path at the membrane electrode interface is mapped and generated; The preset reference value is the calibrated ratio of the high-frequency fluctuation component energy to the low-frequency fluctuation component energy of the electrolytic cell in an unblocked state.

5. The method for monitoring the operating status of an AEM water electrolysis hydrogen production equipment according to claim 1, characterized in that: Collect and analyze the spatial distribution characteristics of the membrane electrode interface temperature gradient parameters, locate the sparse distribution area of ​​active sites according to the high-frequency mutation area, and generate the efficiency fluctuation evaluation coefficient combined with the dynamic coupling degree, including: Collect the membrane electrode interface temperature gradient parameters, analyze the spatial distribution characteristics of the membrane electrode interface temperature gradient parameters, calculate the temperature gradient change rate between adjacent temperature measurement points and identify high-frequency mutation areas; Determine the boundary coordinates of the sparsely distributed active site region based on the continuous distribution area of ​​the high-frequency mutation region and the number of mutations per unit area; The area ratio of the sparsely distributed active site region and the dynamic coupling degree are multiplied by a preset weight coefficient to generate an efficiency fluctuation evaluation coefficient; The preset weight coefficient is calibrated based on the proportion of sparse area in historical data and the influence of dynamic coupling degree on efficiency fluctuation.

6. The method for monitoring the operating status of an AEM water electrolysis hydrogen production equipment according to claim 1, characterized in that: The spatial correspondence between the sparsely distributed area of ​​active sites and the pressure gradient of the cathode flow field is established, and a dynamic compensation factor matrix is ​​constructed, including: Mapping the boundary coordinates of the sparsely distributed active site region to the spatial distribution grid of the cathode flow field pressure gradient; Quantify the pressure gradient drop of the cathode flow field in the grid corresponding to the boundary coordinates of the sparse area to generate a local pressure compensation coefficient; According to the local pressure compensation coefficients of the grids corresponding to the boundary coordinates of all sparse areas and the gradient correlation of the adjacent grids, a dynamic compensation factor matrix is ​​constructed.

7. The method for monitoring the operating status of an AEM water electrolysis hydrogen production equipment according to claim 6, characterized in that: The gradient correlation is the matching degree between the pressure gradient change rate of the cathode flow field of adjacent grids and the pressure compensation requirement of the sparse area.

8. The method for monitoring the operating status of an AEM water electrolysis hydrogen production equipment according to claim 1, characterized in that: According to the changing trend of the efficiency fluctuation evaluation coefficient and the dynamic compensation factor matrix, the anode current density distribution weight and the cathode flow field pressure gradient parameter are adjusted so that the adjustment amount meets the coordinated matching conditions of the local blocking probability and the dynamic coupling degree, including: The periodic variation amplitude of the quantitative efficiency fluctuation evaluation coefficient and the gradient variation direction of the dynamic compensation factor matrix; According to the periodic variation amplitude of the efficiency fluctuation evaluation coefficient and the gradient variation direction of the dynamic compensation factor matrix, an anode current density distribution weight adjustment instruction and a cathode flow field pressure gradient adjustment instruction are generated; Based on the cooperative matching condition of local blocking probability and dynamic coupling degree, the proportional relationship between the anode current density distribution weight adjustment amount and the cathode flow field pressure gradient adjustment amount is constrained.

9. The method for monitoring the operating status of an AEM water electrolysis hydrogen production equipment according to claim 8, characterized in that: The cooperative matching condition is a linear mapping relationship between the product of the local blocking probability and the dynamic coupling degree and the proportion of the adjustment amount.

10. An operating status monitoring system for an AEM water electrolysis hydrogen production device, used to implement an operating status monitoring method for an AEM water electrolysis hydrogen production device according to any one of claims 1 to 9, characterized in that: Includes the following modules: Acquisition synchronization module: used for real-time acquisition and timing synchronization calibration of the voltage fluctuation parameters on the anode side and the hydrogen evolution rate parameters on the cathode side of the electrolyzer to generate a dynamic response sequence; Feature coupling module: used to extract the anode polarization fluctuation characteristics and cathode concentration polarization fluctuation characteristics from the dynamic response sequence, and calculate the dynamic coupling degree to identify the polarization alternation dominant mode; Frequency resistance determination module: used to determine the local blocking probability of the ion transmission path at the membrane electrode interface based on the frequency characteristics of the polarization alternating dominant mode; Temperature analysis and positioning module: used to collect and analyze the spatial distribution characteristics of the temperature gradient parameters at the membrane electrode interface, locate the sparsely distributed area of ​​active sites according to the high-frequency mutation area, and generate the efficiency fluctuation evaluation coefficient in combination with the dynamic coupling degree; Air pressure mapping module: used to establish the spatial correspondence between the sparse distribution area of ​​active sites and the pressure gradient of the cathode flow field, and construct a dynamic compensation factor matrix; Co-state regulation module: It is used to adjust the anode current density distribution weight and cathode flow field pressure gradient parameters according to the changing trend of the efficiency fluctuation evaluation coefficient and the dynamic compensation factor matrix, so that the regulation amount meets the cooperative matching conditions of the local blocking probability and the dynamic coupling degree.

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