Active control multi-time scale electrolytic bath impedance detection method

Abstract

The invention provides an active control multi-time scale electrolytic bath impedance detection method, and relates to the field of electrolytic hydrogen production, and the method comprises the following steps: determining at least two time scales corresponding to a current detection target; acquiring electrolytic cell working condition information, and determining an optimal frequency band of a time scale corresponding to the current detection target based on the electrolytic cell working condition information; determining a signal amplitude based on the working condition information of the electrolytic cell; determining a data acquisition interval corresponding to the time scale corresponding to the current detection target based on the working condition information of the electrolytic cell; based on the optimal frequency band, the signal amplitude and the data acquisition interval corresponding to each time scale, performing multi-frequency-band alternate scanning on the electrolytic cell to obtain scanning data; the method and the device have the advantage that the precision and the efficiency of the impedance measurement of the electrolytic cell under the dynamic working condition are improved.

Description

Technical Field

[0001] The present invention relates to the field of electrolytic hydrogen production, and in particular to an actively controlled multi-time-scale electrolytic cell impedance detection method. Background Art

[0002] Electrolyzers are core devices that use electricity to drive chemical reactions (electrolysis), and are widely used in industrial production, energy conversion, and material preparation. Their basic principle is that applied direct current (DC) causes ions in an electrolyte solution or molten electrolyte to undergo redox reactions on the electrode surfaces, thereby decomposing or synthesizing substances. Hydrogen production by electrolysis involves the electrolysis of water into hydrogen and oxygen. Specifically, DC current is passed through an electrolyzer filled with electrolyte, causing water molecules to undergo electrochemical reactions on the electrodes, decomposing them into hydrogen and oxygen. Hydrogen production by electrolysis can be widely used in various applications requiring hydrogen, including fuel cells, chemical feedstocks, and energy storage. By converting other energy sources (such as solar and wind energy) into hydrogen for storage, it can effectively address energy storage and transportation issues. Electrolyzer impedance is a key parameter reflecting its electrochemical performance and operating status. Impedance measurement is crucial for process optimization, ensuring safety, and extending equipment life.

[0003] Existing electrolyzer impedance detection technology requires point-by-point frequency sweeps across a wide frequency range (e.g., 0Hz–100kHz). A single complete measurement takes several minutes or even longer, and the electrolyzer's operating state may change during this period, resulting in reduced accuracy of low-frequency data. It also fails to capture rapid impedance changes under complex operating conditions such as fluctuating loads and start-stop transients. Furthermore, impedance analysis performed on only a single timescale (e.g., high or low frequency) fails to simultaneously correlate short-term transient responses with long-term performance degradation patterns.

[0004] Therefore, it is necessary to provide an actively controlled multi-time-scale electrolytic cell impedance detection method to improve the accuracy and efficiency of electrolytic cell impedance measurement under dynamic conditions. Summary of the Invention

[0005] The present invention provides an actively controlled multi-time-scale electrolytic cell impedance detection method, comprising: determining at least two time scales corresponding to a current detection target; determining an initial frequency band according to a current electrolytic cell type; collecting electrolytic cell operating condition information, and determining an optimal frequency band, signal amplitude, and data acquisition interval for the time scale corresponding to the current detection target based on the electrolytic cell operating condition information and the initial frequency band; performing multi-frequency alternating scanning on the electrolytic cell based on the optimal frequency band, signal amplitude, and data acquisition interval corresponding to each time scale to obtain scanning data; and generating an electrolytic cell impedance test result based on the scanning data.

[0006] Furthermore, at least two time scales are determined based on the current detection target, including: determining multiple preset detection targets; for each preset detection target, determining at least two time scales corresponding to the preset detection target; and determining at least two time scales corresponding to the current detection target based on the at least two time scales corresponding to each preset detection target.

[0007] Furthermore, the initial frequency band is determined according to the current electrolytic cell type, including: determining multiple preset electrolytic cell types; for each preset electrolytic cell type, determining the initial frequency band corresponding to the preset electrolytic cell type; and determining the initial frequency band according to the initial frequency band corresponding to each preset electrolytic cell type and the current electrolytic cell type.

[0008] Furthermore, the electrolytic cell operating condition information includes at least real-time current density, real-time electrolytic cell temperature, real-time activation resistance, real-time mass transfer resistance and real-time ohmic resistance.

[0009] Furthermore, based on the electrolytic cell operating condition information and the initial frequency band, the optimal frequency band of the time scale corresponding to the current detection target is determined, including: determining the polarization state of the electrolytic cell based on the real-time activation resistance, real-time mass transfer resistance and real-time ohmic resistance; determining the maximum frequency threshold or the minimum frequency threshold according to the polarization state, real-time current density and real-time electrolytic cell temperature of the electrolytic cell; and determining the optimal frequency band of the time scale corresponding to the current detection target according to the maximum frequency threshold or the minimum frequency threshold.

[0010] Furthermore, based on the real-time activation resistance, the real-time mass transfer resistance and the real-time ohmic resistance, the polarization state of the electrolytic cell is determined, including: when the ratio of the real-time activation resistance to the real-time ohmic resistance is greater than a first ratio, the polarization state of the electrolytic cell is activation polarization-dominated; when the ratio of the real-time mass transfer resistance to the real-time ohmic resistance is greater than a second ratio, the polarization state of the electrolytic cell is mass transfer polarization-dominated; when the ratio of the real-time activation resistance to the real-time ohmic resistance is less than or equal to the first ratio, and / or the ratio of the real-time mass transfer resistance to the real-time ohmic resistance is greater than or equal to the second ratio, the polarization state of the electrolytic cell is a mixed state.

[0011] Furthermore, the maximum frequency threshold or the minimum frequency threshold is determined according to the polarization state, real-time current density and real-time electrolytic cell temperature of the electrolytic cell, including: when the polarization state of the electrolytic cell is dominated by activation polarization, the real-time maximum frequency is calculated according to the real-time current density and the real-time electrolytic cell temperature, and the larger value of the preset maximum frequency and the real-time maximum frequency is taken as the maximum frequency threshold; when the polarization state of the electrolytic cell is dominated by mass transfer polarization or a mixed state, the minimum frequency threshold is calculated according to the real-time electrolytic cell temperature.

[0012] Furthermore, the signal amplitude is determined based on the electrolytic cell operating condition information and the initial frequency band, including: when the polarization state of the electrolytic cell is dominated by activation polarization, the initial signal amplitude is determined based on the maximum amplitude threshold and the basic amplitude, and the signal amplitude is determined based on the real-time electrolytic cell temperature and the initial signal amplitude; when the polarization state of the electrolytic cell is dominated by mass transfer polarization, the signal amplitude is determined based on the basic amplitude, real-time current density and real-time electrolytic cell temperature; when the polarization state of the electrolytic cell is a mixed state, the signal amplitude is determined based on the real-time electrolytic cell temperature and the basic amplitude.

[0013] Furthermore, based on the electrolytic cell operating condition information and the initial frequency band, the data collection interval corresponding to the time scale corresponding to the current detection target is determined, including: through model predictive control, based on the current impedance state and the electrolytic cell operating condition information, predicting the impedance change in the future time domain; based on the impedance change in the future time domain, determining the data collection interval corresponding to the time scale corresponding to the current detection target.

[0014] Furthermore, based on the scanning data, the electrolytic cell impedance test results are generated, including: determining a performance degradation index; generating an impedance-time correlation graph based on the scanning data; calculating a real-time score of the performance degradation index based on the impedance-time correlation graph; judging whether to issue a performance degradation warning based on the real-time score of the performance degradation index; if not, predicting a periodic score of the performance degradation index in the current detection period based on the impedance-time correlation graph; judging whether to issue a performance degradation warning based on the periodic score of the performance degradation index in the current detection period.

[0015] Compared with the prior art, the present invention provides an active control multi-time scale electrolytic cell impedance detection method, which has at least the following beneficial effects: 1. By determining at least two time scales and dynamically adjusting the optimal frequency band and data collection interval based on the electrolyzer's operating conditions, multi-band alternating scanning is achieved. Compared with traditional single-time-scale or fixed-frequency detection methods, the time required for a single full-band detection can be shortened by over 40%.

[0016] 2. Dynamically adjust the optimal frequency band according to the electrolytic cell operating conditions (such as current, temperature, etc.), avoiding time waste on invalid frequency bands and further improving detection efficiency.

[0017] 3. By optimizing the signal amplitude and data collection interval under dynamic operating conditions, the impedance measurement error is reduced to ±3%, significantly improving measurement accuracy compared to the ±10% of traditional methods. Dynamically adjusting the signal amplitude based on the electrolyzer's operating conditions ensures a high signal-to-noise ratio measurement signal under different operating conditions, reducing noise interference. Dynamically adjusting the data collection interval based on operating condition information avoids oversampling during stable conditions or undersampling during drastic changes, ensuring data accuracy and integrity. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] This specification will be further described in the form of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting, and in these embodiments, like numbers represent like structures, wherein: Figure 1 is a flow chart of an actively controlled multi-time-scale electrolytic cell impedance detection method according to some embodiments of this specification; Figure 2 It is a flowchart of data preprocessing of historical measured data upstream of the basin where the forecast section is located according to some embodiments of this specification. DETAILED DESCRIPTION

[0019] To more clearly illustrate the technical solutions of the embodiments of this specification, the following briefly describes the drawings required for describing the embodiments. Obviously, the drawings described below are merely examples or embodiments of this specification. Those skilled in the art can apply this specification to other similar scenarios based on these drawings without inventive effort. Unless otherwise apparent from the context or otherwise noted, the same reference numerals in the figures represent the same structure or operation.

[0020] Figure 1 is a flow chart of an active controlled multi-time scale electrolytic cell impedance detection method according to some embodiments of this specification, such as Figure 1 As shown, an actively controlled multi-time-scale electrolytic cell impedance detection method may include the following steps.

[0021] Step 110: Determine at least two time scales corresponding to the current detection target.

[0022] In some embodiments, step 110 specifically includes: Determine multiple preset detection targets, such as dynamic response monitoring, aging assessment, fault diagnosis, process optimization, etc.; For each preset detection target, determine at least two time scales corresponding to the preset detection target, for example, the time scales corresponding to dynamic response monitoring: transient scale and steady-state scale; the time scales corresponding to aging assessment: steady-state scale and long-term scale; the time scales corresponding to fault diagnosis: transient scale, steady-state scale and long-term scale; According to the at least two time scales corresponding to each preset detection target, at least two time scales corresponding to the current detection target are determined. Specifically, the user specifies the current detection target through the operation interface, and the at least two time scales corresponding to the current detection target are automatically determined.

[0023] For example, time scales may include: For transient scale, the data acquisition interval ranges from 0.1 to 100 ms, and a high-frequency sweep (1 to 10 kHz) is used to capture the impedance response of the electrolyzer during sudden load changes and start-up and shutdown. At the steady-state scale, the data collection interval ranged from 1 to 10 min, and medium- and low-frequency sweeps (0.1–100 Hz) were used to analyze electrode polarization and electrolyte distribution; On a long-term scale, the data collection interval ranges from 1 to 24 hours, and low-frequency scanning (0.01 to 1 Hz) is used to monitor slow variables such as material corrosion and diaphragm aging.

[0024] The time scale of the electrolytic cell is related to the physical process. The electrolytic cell exhibits different electrochemical behaviors at different time scales: Transient scale: Corresponding process: double-layer charging and discharging, and activation polarization transient response during load mutation or start-stop.

[0025] Frequency band selection: High-frequency signals can capture rapidly changing charge transfer processes.

[0026] Typical phenomenon: instantaneous fluctuation of double layer voltage on the electrode surface during current step.

[0027] Steady-state scale: Corresponding process: electrode polarization is stable and electrolyte concentration gradient is formed.

[0028] Frequency band selection: medium and low frequencies cover the mass transfer polarization characteristic frequencies that reflect the diffusion-limited process.

[0029] Typical phenomenon: balance between electrolyte ion migration rate and reaction rate during steady-state operation.

[0030] Long-term scale: Corresponding processes: slow changes such as material corrosion, diaphragm micropore blockage, and catalyst deactivation.

[0031] Frequency band selection: Ultra-low frequency corresponds to hourly time constants and is sensitive to changes in material structure.

[0032] Typical phenomenon: The ionic conductivity of the diaphragm gradually decreases with the running time.

[0033] As an example only, the preset detection goal is to monitor the dynamic response and long-term stability of the electrolyzer during operation.

[0034] Corresponding time scale 1: transient scale Explanation: At the transient scale, high-frequency sweeps can capture the rapid electrochemical behavior of the electrolyzer during sudden load changes or startup and shutdown, such as double-layer charging and discharging, and activation polarization transient responses. By monitoring these transient phenomena, the dynamic response capability of the electrolyzer can be evaluated, and potential performance issues during startup or load changes can be promptly identified.

[0035] Corresponding time scale 2: Steady-state scale Note: At a steady-state scale, medium and low-frequency sweeps can analyze the electrochemical behavior of electrodes after polarization has stabilized, such as the formation of electrolyte concentration gradients and the balance between ion migration and reaction rates. By monitoring these steady-state phenomena, the performance stability of the electrolyzer under normal operating conditions can be assessed, and potential polarization issues or uneven electrolyte distribution can be promptly identified.

[0036] For example, the preset detection objectives are: evaluating the aging degree of the electrolytic cell and predicting maintenance needs.

[0037] Corresponding time scale 1: Steady-state scale Note: Although steady-state metrics are primarily used to monitor the steady-state operation of an electrolyzer, long-term, continuous steady-state monitoring data can also reflect the aging trend of an electrolyzer. For example, by monitoring the long-term changes in the electrolyte ion migration rate and reaction rate, the degree of electrolyzer aging can be assessed.

[0038] Corresponding time scale 2: long-term scale Explanation: On a long-term scale, low-frequency scanning can monitor changes in slow variables such as material corrosion and diaphragm aging in electrolytic cells. These slow variables are the main manifestations of electrolytic cell aging. Through long-term, sparse monitoring, it is possible to understand the aging trend of the electrolytic cell, predict maintenance needs, and plan repairs or replacements in advance.

[0039] As can be understood, the electrolyzer is optimized for detection at various time scales: the transient scale rapidly responds to sudden load changes; the steady-state scale covers the main polarization processes; and the long-term scale sparsely monitors aging trends. Compared to the traditional method of continuous scanning across the full frequency band (0.01Hz–10kHz) for several hours, the overall detection time is significantly shortened, thereby improving detection efficiency. Furthermore, based on the electrolyzer's behavioral characteristics at different time scales, detection resources are precisely allocated to ensure sufficient detection data at critical time scales while avoiding wasting resources at unnecessary time scales. Targeted monitoring of the electrolyzer's behavioral characteristics at different time scales can more accurately capture key information and improve the accuracy of monitoring results.

[0040] Step 120 : Collect the electrolytic cell operating condition information, and determine the optimal frequency band of the time scale corresponding to the current detection target based on the electrolytic cell operating condition information.

[0041] In some embodiments, determining the optimal frequency band of the time scale corresponding to the current detection target based on the electrolytic cell operating condition information includes: Determine the polarization state of the electrolytic cell based on the real-time activation resistance, real-time mass transfer resistance, and real-time ohmic resistance; Determining a maximum frequency threshold or a minimum frequency threshold according to the polarization state, real-time current density, and real-time electrolytic cell temperature of the electrolytic cell; According to the maximum frequency threshold or the minimum frequency threshold, the optimal frequency band of the time scale corresponding to the current detection target is determined.

[0042] In some embodiments, determining the polarization state of the electrolytic cell based on the real-time activation resistance, the real-time mass transfer resistance, and the real-time ohmic resistance includes: When the ratio of the real-time activation resistance to the real-time ohmic resistance is greater than a first ratio (e.g., 3), the polarization state of the electrolytic cell is activation polarization-dominated; When the ratio of the real-time mass transfer resistance to the real-time ohmic resistance is greater than a second ratio (e.g., 2), the polarization state of the electrolytic cell is mass transfer polarization dominated; When the ratio of the real-time activation resistance to the real-time ohmic resistance is less than or equal to the first ratio, and / or the ratio of the real-time mass transfer resistance to the real-time ohmic resistance is greater than or equal to the second ratio, the polarization state of the electrolytic cell is a mixed state.

[0043] In some embodiments, determining the maximum frequency threshold or the minimum frequency threshold according to the polarization state, real-time current density, and real-time electrolytic cell temperature of the electrolytic cell includes: When the polarization state of the electrolytic cell is dominated by activation polarization, the real-time maximum frequency is calculated according to the real-time current density and the real-time electrolytic cell temperature, and the larger value of the preset maximum frequency and the real-time maximum frequency is taken as the maximum frequency threshold; When the polarization state of the electrolytic cell is mass transfer polarization-dominated or mixed, the minimum frequency threshold is calculated according to the real-time electrolytic cell temperature.

[0044] Specifically, when the polarization state of the electrolytic cell is dominated by activation polarization, the maximum frequency threshold can be determined according to the following formula: , in, is the maximum frequency threshold, is the real-time current density, is the real-time electrolytic cell temperature.

[0045] When the polarization state of the electrolytic cell is mass transfer polarization-dominated or mixed, the minimum frequency threshold can be calculated according to the following formula: , in, is the minimum frequency threshold.

[0046] For each time scale corresponding to the current detection target, if the maximum value of the frequency band corresponding to the time scale is greater than the maximum frequency threshold, the maximum value of the frequency band corresponding to the time scale is replaced by the maximum frequency threshold; if the minimum value of the frequency band corresponding to the time scale is less than the minimum frequency threshold, the minimum value of the frequency band corresponding to the time scale is replaced by the minimum frequency threshold.

[0047] Step 130: Determine the signal amplitude based on the electrolytic cell operating condition information.

[0048] Specifically include: When the polarization state of the electrolytic cell is dominated by activation polarization, the initial signal amplitude is determined based on the maximum amplitude threshold and the basic amplitude, and the signal amplitude is determined based on the real-time electrolytic cell temperature and the initial signal amplitude; When the polarization state of the electrolytic cell is dominated by mass transfer polarization, the signal amplitude is determined based on the basic amplitude, the real-time current density and the real-time electrolytic cell temperature; When the polarization state of the electrolytic cell is a mixed state, the signal amplitude is determined based on the real-time electrolytic cell temperature and the base amplitude.

[0049] Specifically, the calculation formula of the basic amplitude is: , in, is the basic amplitude.

[0050] The maximum amplitude threshold is calculated as: , in, is the maximum amplitude threshold.

[0051] When the polarization state of the electrolytic cell is dominated by activation polarization, the initial signal amplitude can be determined according to the following formula: , in, is the initial signal amplitude.

[0052] The signal amplitude can be determined based on the base amplitude, real-time current density, and real-time electrolyzer temperature according to the following formula: , in, is the signal amplitude.

[0053] When the polarization state of the electrolytic cell is dominated by mass transfer polarization, the signal amplitude can be determined according to the following formula: , The amplitude was reduced to avoid electrolyte turbulence interfering with the diffusion process.

[0054] When the polarization state of the electrolytic cell is a mixed state, the signal amplitude can be calculated according to the following formula: , The conductivity of the electrolyte increases with increasing temperature, and the amplitude needs to be appropriately increased to maintain the signal-to-noise ratio.

[0055] Step 140: Determine the data collection interval corresponding to the time scale corresponding to the current detection target based on the electrolytic cell operating condition information. In some embodiments, determining the data collection interval corresponding to the time scale corresponding to the current detection target based on the electrolytic cell operating condition information and the initial frequency band includes: Model Predictive Control (MPC) is used to predict impedance changes in the future time domain based on the current impedance state and electrolyzer operating conditions. Based on the impedance changes in the future time domain, the data collection interval corresponding to the time scale corresponding to the current detection target is determined.

[0056] Specifically, the following steps may be included: 1. Prediction model construction: Impedance response prediction based on the equivalent circuit model (ECM) (1) ECM model discretization and state space representation State variables: : Double layer voltage, representing the potential difference between the electrode surface and the electrolyte, is an important indicator of the electrochemical behavior of the electrolytic cell.

[0057] : Diffusion capacitance, which reflects the dynamic characteristics of the ion diffusion process in the electrolyte.

[0058] Input variables: : AC current disturbance used to stimulate the impedance response of the electrolyzer.

[0059] : Scanning frequency, that is, the frequency value currently used for detection.

[0060] Output variables: : The predicted impedance value is calculated using the Randles equivalent circuit model and includes parameters such as the ohmic resistance Rohm, the activation polarization resistance Ract, the double-layer capacitance Cdl, and the Warburg impedance (expressed as σ / jω).

[0061] By converting the electrolyzer equivalent circuit model into discrete state-space equations, MPC is able to predict the future impedance response based on the current state and inputs.

[0062] For each time scale, a prediction model corresponding to the time scale can be established.

[0063] (2) Frequency domain response prediction Discrete Fourier Transform: The time domain disturbance signal Convert it into frequency domain excitation to obtain the current amplitude and phase information at different frequencies.

[0064] Impedance response prediction: The state-space model is used to predict the impedance response at each frequency point, including the impedance amplitude and phase.

[0065] MPC evaluates the impedance response at different frequencies to determine the information value of each frequency band, such as whether the characteristic frequency of the electrolyzer is covered and whether the signal-to-noise ratio is high enough.

[0066] 2. Rolling Optimization Mechanism MPC performs the following steps in each control cycle, balancing measurement efficiency and data quality through an objective function: Dynamic condition constraints: Frequency range constraint: limits the range of scanning frequencies to ensure detection within a valid frequency band, avoid invalid or redundant scanning, and perform dynamic adjustment through step 120.

[0067] Disturbance amplitude constraint: controls the amplitude of the AC current disturbance to prevent excessive interference to the electrolytic cell, and performs dynamic adjustment through step 130.

[0068] Scan time constraint: limit the time of each scan to ensure that the detection process will not be too long and affect the normal operation of the electrolyzer.

[0069] Objective function design: The objective function consists of two parts: one part is the data value item (such as signal-to-noise ratio, characteristic frequency coverage, impedance feature capture efficiency, etc.), which is used to measure the contribution of the collected data to the electrolytic cell status assessment. According to the data quality, the weight of the data value in the objective function is dynamically adjusted. If the data quality is low and the interference is large, the weight of the data value in the objective function is increased; the other part is the acquisition cost item, which is used to measure the resource consumption (such as time, energy consumption, etc.) in the data acquisition process.

[0070] MPC obtains the optimal test interval sequence by solving the minimum value of the objective function, achieving a balance between measurement efficiency and data quality.

[0071] 3. Solution Quadratic Programming (QP) Solver: Use a quadratic programming solver such as IPOPT (Interior Point OPTimizer) to optimize the collection time interval online.

[0072] The QP (Quadratic Programming Solver) solver can transform the rolling optimization problem into a standard quadratic programming problem and obtain the optimal solution through iterative solution.

[0073] Online optimization means that the solver can adjust the sampling time interval in real time during the operation of the electrolyzer to adapt to changes in the electrolyzer state.

[0074] Traditional model predictive control (MPC) is commonly used in industrial control for real-time optimization of dynamic systems. However, its design is mostly for general scenarios and is not customized for the multi-timescale characteristics and dynamic operating conditions of electrolyzers. This leads to the following shortcomings: Fixed time scale: The data collection interval is based on fixed rules and cannot be dynamically adjusted according to the different time scales of the electrolyzer (transient, steady state, long-term).

[0075] Single optimization objective: The objective function focuses on controlling stability or energy consumption, without incorporating the value of electrolyzer-specific data (such as impedance feature capture efficiency).

[0076] Static constraints: Parameters such as frequency band and amplitude are fixed and cannot be adjusted in real time based on polarization state or temperature.

[0077] Step 140 has the following targeted improvements: 1. Multi-timescale dynamic modeling The impedance response of the electrolyzer is decomposed into three time scales: transient, steady-state, and long-term, and an independent prediction model is established for each scale to accurately match the dynamic characteristics of the electrolyzer.

[0078] 2. Dynamically adjust the collection interval to achieve working condition adaptation According to the real-time working conditions, polarization state, temperature, and current density, the constraints of MPC, such as frequency band range and disturbance amplitude, are dynamically adjusted.

[0079] 3. Customized design of objective function The data value indicators unique to electrolyzers (such as signal-to-noise ratio, characteristic frequency coverage, and impedance feature capture efficiency) and acquisition cost indicators are introduced into the MPC objective function.

[0080] 4. Collaborative optimization of frequency band and acquisition interval By jointly optimizing frequency band selection and data collection interval rather than processing them independently, resource allocation is more efficient and redundant detection is avoided.

[0081] 5. Online real-time adjustment and feedback loop Dynamically modify MPC model parameters through real-time data feedback to form closed-loop optimization and enhance robustness.

[0082] Step 150 : Based on the optimal frequency band, signal amplitude, and data acquisition interval corresponding to each time scale, the electrolytic cell is scanned alternately in multiple frequency bands to obtain scanning data.

[0083] Specifically, a multi-channel signal generator and high-speed data acquisition equipment can be integrated to support multi-point synchronous measurement and acquire scan data. By coupling the impedance converter with the DC power supply, the AC disturbance signal and DC power supply can be seamlessly superimposed.

[0084] As an example, the transient response of a wind power hydrogen production scenario is captured. 2MW, PEM electrolyzer participates in grid frequency regulation, and the sweep parameters are: Transient scale: Perform a 1–10 kHz frequency sweep every 100 ms to capture the dynamic changes in Ract.

[0085] Steady-state scale: Perform a 0.1–100 Hz frequency sweep every 5 minutes to analyze the electrolyte mass transfer state.

[0086] The corresponding scanning process is: During actual operation, transient and steady-state scaling scans are performed alternately. Specifically, after executing a transient scaling scan every 100 milliseconds, the system waits until the next 5-minute steady-state scaling scan is triggered before executing another steady-state scaling scan. This ensures that the two scans are synchronized, meaning that the transient scaling scan does not interfere with the steady-state scaling scan, and vice versa. The data from the transient and steady-state scaling scans are integrated to form a complete dataset for subsequent comprehensive analysis.

[0087] As another example, in the aging monitoring of the alkaline electrolytic cell diaphragm, a 10MW alkaline electrolytic cell is in continuous operation, and the low-frequency impedance drift caused by diaphragm blockage needs to be monitored.

[0088] Long-term scale: 0.01–1 Hz frequency sweep performed every 1 h.

[0089] Steady-state scale: A frequency sweep of 0.1–100 Hz was performed every 30 min to verify the mass transfer polarization stability.

[0090] Step 160: Generate electrolytic cell impedance test results based on the scan data.

[0091] Specifically include: Determine performance degradation indicators; Generate impedance-time correlation graph based on scanning data; Calculate the real-time score of performance degradation index based on impedance-time correlation graph; Determine whether to issue a performance degradation warning based on the real-time score of the performance degradation indicator; If not, the cycle score of the performance degradation index in the current detection cycle is predicted based on the impedance-time correlation graph; Determine whether to issue a performance degradation warning based on the performance degradation indicator's score in the current detection cycle.

[0092] Specifically, impedance features can be extracted from the scan data, and an impedance-time correlation map can be generated based on the extracted impedance features. For example, transient scale feature extraction: extract the time-varying curve of Ract from high-frequency impedance data. Steady-state scale feature extraction: extract ohmic resistance from low-frequency impedance data to reflect the ion conductivity characteristics of the electrolyte. Due to the large difference in the time intervals between transient and steady-state scans, it is recommended to use dual time axes or sub-graphs to display them separately. The main graph shows the time-varying curve of Ract at the transient scale, with a time axis of 100ms intervals. The sub-graph shows the time-varying curve of key impedance parameters (such as Rohm, Rdiff) at the steady-state scale, with a time axis of 5min intervals.

[0093] The real-time score of the performance degradation indicator can be calculated according to the following formula: , in, is the real-time score of the performance degradation index, To activate the polarization resistor in real time, is the activation polarization resistance in the initial state, It is a real-time diffusion coefficient related term, reflecting the dynamic changes in the diffusion capacity of ions or reactants in the electrolyte. is the diffusion coefficient reference value in the initial state, is the real-time ohmic impedance of the electrolyzer, is the ohmic impedance of the electrolytic cell in the initial state, and is the weight, and greater than 0, .

[0094] if If it is less than 1.1, it is considered normal and no response measures are required; if If the value is between 1.1 and 1.3, the warning level is level one, and measures such as recording logs and increasing the frequency of long-term scale scanning are adopted.

[0095] The performance degradation index score in the current detection cycle is calculated using the following formula: , in, is the predicted value of the performance degradation index at a future time point, is the real-time score of the performance degradation indicator and the time window length of the historical data. For example, p=24 means that the data of the past 24 detection cycles are used. For the The weight coefficient of each historical time point; For historical time points arrive Changes in performance degradation indicators; The random error term is assumed to obey a normal distribution with a mean of 0 and is used to characterize random fluctuations not explained by the model, such as noise interference and unmodeled factors.

[0096] when When it is greater than the threshold, a performance degradation warning is issued.

[0097] Finally, it should be understood that the embodiments described in this specification are intended only to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, by way of example and not limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly described and illustrated in this specification.

Claims

1. An active controlled multi-time scale electrolytic cell impedance detection method, characterized in that: include: Determine at least two time scales corresponding to the current detection target; Collect the electrolytic cell operating condition information, and determine the optimal frequency band for the time scale corresponding to the current detection target based on the electrolytic cell operating condition information; Determine the signal amplitude based on the electrolytic cell operating condition information; Based on the electrolytic cell operating condition information, determine the data collection interval corresponding to the time scale corresponding to the current detection target; Based on the optimal frequency band, signal amplitude and data acquisition interval corresponding to each time scale, the electrolytic cell is scanned alternately in multiple frequency bands to obtain scanning data; Based on the scan data, generate the electrolytic cell impedance test results.

2. The method for detecting electrolytic cell impedance with active control and multiple time scales according to claim 1, characterized in that: Based on the current detection goals, determine at least two time scales, including: Determine multiple preset detection targets; For each preset detection target, determining at least two time scales corresponding to the preset detection target; According to the at least two time scales corresponding to each preset detection target, at least two time scales corresponding to the current detection target are determined.

3. The method for detecting electrolytic cell impedance with active control and multiple time scales according to claim 1 or 2, characterized in that: The electrolytic cell operating condition information includes at least real-time current density, real-time electrolytic cell temperature, real-time activation resistance, real-time mass transfer resistance and real-time ohmic resistance.

4. The method for detecting electrolytic cell impedance with active control and multiple time scales according to claim 3, wherein: Based on the electrolytic cell operating condition information, determine the optimal frequency band for the time scale corresponding to the current detection target, including: Determine the polarization state of the electrolytic cell based on the real-time activation resistance, real-time mass transfer resistance, and real-time ohmic resistance; Determining a maximum frequency threshold or a minimum frequency threshold according to the polarization state, real-time current density, and real-time electrolytic cell temperature of the electrolytic cell; According to the maximum frequency threshold or the minimum frequency threshold, the optimal frequency band of the time scale corresponding to the current detection target is determined.

5. The method for detecting electrolytic cell impedance with active control and multiple time scales according to claim 4, characterized in that: Determine the polarization state of the electrolytic cell based on the real-time activation resistance, real-time mass transfer resistance, and real-time ohmic resistance, including: When the ratio of the real-time activation resistance to the real-time ohmic resistance is greater than a first ratio, the polarization state of the electrolytic cell is activation polarization-dominated; When the ratio of the real-time mass transfer resistance to the real-time ohmic resistance is greater than a second ratio, the polarization state of the electrolytic cell is mass transfer polarization dominated; When the ratio of the real-time activation resistance to the real-time ohmic resistance is less than or equal to the first ratio, and / or the ratio of the real-time mass transfer resistance to the real-time ohmic resistance is greater than or equal to the second ratio, the polarization state of the electrolytic cell is a mixed state.

6. The method for detecting electrolytic cell impedance with active control and multiple time scales according to claim 5, characterized in that: The maximum frequency threshold is determined based on the polarization state, real-time current density, and real-time electrolytic cell temperature of the electrolytic cell, including: When the polarization state of the electrolytic cell is dominated by activation polarization, the real-time maximum frequency is calculated based on the real-time current density and the real-time electrolytic cell temperature, and the larger value of the preset maximum frequency and the real-time maximum frequency is taken as the maximum frequency threshold.

7. The method for detecting electrolytic cell impedance with active control and multiple time scales according to claim 6, characterized in that: The minimum frequency threshold is determined based on the polarization state, real-time current density, and real-time electrolytic cell temperature of the electrolytic cell, including: When the polarization state of the electrolytic cell is mass transfer polarization-dominated or mixed, the minimum frequency threshold is calculated according to the real-time electrolytic cell temperature.

8. The method for detecting electrolytic cell impedance with active control and multiple time scales according to claim 5, characterized in that: Based on the electrolytic cell operating condition information, the signal amplitude is determined, including: When the polarization state of the electrolytic cell is dominated by activation polarization, the initial signal amplitude is determined based on the maximum amplitude threshold and the basic amplitude, and the signal amplitude is determined based on the real-time electrolytic cell temperature and the initial signal amplitude; When the polarization state of the electrolytic cell is dominated by mass transfer polarization, the signal amplitude is determined based on the basic amplitude, the real-time current density and the real-time electrolytic cell temperature; When the polarization state of the electrolytic cell is a mixed state, the signal amplitude is determined based on the real-time electrolytic cell temperature and the base amplitude.

9. The method for detecting electrolytic cell impedance with active control and multiple time scales according to claim 5, characterized in that: Based on the electrolytic cell operating condition information, determine the data collection interval corresponding to the time scale corresponding to the current detection target, including: Through model predictive control, based on the current impedance state and electrolyzer operating conditions, the impedance changes in the future time domain are predicted; Based on the impedance changes in the future time domain, the data collection interval corresponding to the time scale corresponding to the current detection target is determined.

10. The active controlled multi-time scale electrolytic cell impedance detection method according to claim 1 or 2, characterized in that: Generate electrolytic cell impedance test results based on the scan data, including: Determine performance degradation indicators; Generate impedance-time correlation graph based on scanning data; Calculate the real-time score of performance degradation index based on impedance-time correlation graph; Determine whether to issue a performance degradation warning based on the real-time score of the performance degradation indicator; If not, the cycle score of the performance degradation index in the current detection cycle is predicted based on the impedance-time correlation graph; Determine whether to issue a performance degradation warning based on the performance degradation indicator's score in the current detection cycle.

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