An Electrolyzer Impedance Measurement Method and System Considering Dynamic Disturbance

Abstract

This invention provides a method and system for measuring the impedance of an electrolytic cell considering dynamic disturbances, relating to the field of electrochemical equipment. The system includes: a DC power supply module for providing DC power to the electrolytic cell; a parameter optimization module for determining the optimal disturbance frequency band and optimal disturbance parameters based on the electrolytic cell's operating conditions and its equivalent circuit model; an AC disturbance module for injecting a dynamic disturbance signal into the electrolytic cell based on the optimal disturbance frequency band and optimal disturbance parameters; a feedback acquisition module for acquiring feedback data from the electrolytic cell to the dynamic disturbance signal; and an impedance analysis module for calculating the electrolytic cell impedance based on the feedback data. This method offers the advantage of achieving accurate measurement of the electrolytic cell impedance under dynamic operating conditions.

Description

Technical Field

[0001] This invention relates to the field of electrochemical equipment, and in particular to a method and system for measuring the impedance of an electrolytic cell that takes into account dynamic disturbances. Background Technology

[0002] An electrolytic cell is a core piece of equipment that uses electrical energy to drive a chemical reaction (electrolysis process), and it is widely used in industrial production, energy conversion, and materials preparation. Its basic principle is to use an external direct current to cause ions in the electrolyte solution or molten electrolyte to undergo a redox reaction on the electrode surface, thereby achieving the decomposition or synthesis of substances. The impedance of the electrolytic cell is a key parameter reflecting its electrochemical performance and operating status; impedance measurement is crucial for optimizing processes, ensuring safety, and extending equipment lifespan.

[0003] Existing impedance measurement methods, such as those used in electrolytic cells under dynamic operating conditions (e.g., current fluctuations, start-up and shutdown transients), struggle to accurately separate DC loads from AC disturbance signals, leading to increased measurement errors. For instance, in direct parallel testing, AC signals can interfere with the stability of the constant current power supply, causing noise. Furthermore, at ultra-high current densities (e.g., >1000 A / m²), the amplitude of AC disturbances is limited (typically 5%-10% of the DC current), making it difficult to capture electrode polarization details. Moreover, open-loop disturbance injection cannot dynamically adjust disturbance parameters (e.g., frequency, amplitude) according to the real-time state of the electrolytic cell, resulting in low measurement efficiency and susceptibility to operating condition interference.

[0004] Therefore, there is a need to provide a method and system for measuring the impedance of electrolyzers that takes into account dynamic disturbances, so as to achieve accurate measurement of the impedance of electrolyzers under dynamic operating conditions. Summary of the Invention

[0005] This invention provides a method for measuring the impedance of an electrolytic cell considering dynamic disturbances, comprising: a DC power supply module for providing DC power to the electrolytic cell; a parameter optimization module for determining the optimal disturbance frequency band and optimal disturbance parameters based on the electrolytic cell's operating conditions and equivalent circuit model; an AC disturbance module for injecting a dynamic disturbance signal into the electrolytic cell based on the optimal disturbance frequency band and optimal disturbance parameters; a feedback acquisition module for acquiring feedback data from the electrolytic cell to the dynamic disturbance signal; and an impedance analysis module for calculating the electrolytic cell impedance based on the feedback data.

[0006] Furthermore, the parameter optimization module determines the optimal disturbance frequency band and optimal disturbance parameters based on the electrolytic cell operating conditions and the equivalent circuit model of the electrolytic cell. This includes: initializing the disturbance parameters and starting the DC power supply module to inject an initial disturbance signal into the electrolytic cell according to the initial disturbance parameters; determining the activation polarization resistance, ohmic resistance, mass transfer polarization resistance, real-time current density, and real-time electrolytic cell temperature of the electrolytic cell; determining the electrolytic cell operating conditions based on the activation polarization resistance, ohmic resistance, and mass transfer polarization resistance; determining the optimal disturbance amplitude based on the electrolytic cell operating conditions and real-time current density; determining the initial frequency band based on the real-time electrolytic cell temperature and real-time current density; and determining the optimal scanning frequency band based on the equivalent circuit model of the electrolytic cell and the initial frequency band.

[0007] Furthermore, the electrolytic cell operating condition is one of mass transfer polarization-dominated, mixed polarization, and activation polarization-dominated. The parameter optimization module determines the electrolytic cell operating condition based on the activation polarization resistance, ohmic resistance, and mass transfer polarization resistance, including: if the ratio of activation polarization resistance to ohmic resistance is greater than a first ratio threshold, the electrolytic cell operating condition is determined to be activation polarization-dominated; if the ratio of mass transfer polarization resistance to activation polarization resistance is greater than a second ratio threshold, the electrolytic cell operating condition is determined to be mass transfer polarization-dominated; if the ratio of activation polarization resistance to ohmic resistance is less than or equal to the first ratio threshold and the ratio of mass transfer polarization resistance to activation polarization resistance is less than or equal to the second ratio threshold, the electrolytic cell operating condition is determined to be mixed polarization.

[0008] Furthermore, the parameter optimization module determines the optimal disturbance amplitude based on the electrolytic cell operating conditions and real-time current density, including: if the electrolytic cell operating conditions are dominated by activation polarization, determining the optimal disturbance amplitude based on the base amplitude and real-time current density; if the electrolytic cell operating conditions are dominated by mass transfer polarization, determining the optimal disturbance amplitude based on the base amplitude and real-time current density; if the electrolytic cell operating conditions are in a mixed polarization state, determining the optimal disturbance amplitude as the base amplitude.

[0009] Furthermore, the parameter optimization module is also used to: determine the basic amplitude based on the real-time electrolytic cell temperature and / or the characteristics of the electrolytic cell material.

[0010] Furthermore, the parameter optimization module determines the initial frequency band based on the real-time electrolytic cell temperature and the real-time current density, including: determining the lower limit of low frequency based on the real-time electrolytic cell temperature; determining the upper limit of high frequency based on the real-time current density; and determining the initial frequency band based on the lower limit of low frequency and the upper limit of high frequency.

[0011] Furthermore, the parameter optimization module determines the optimal scanning frequency band based on the equivalent circuit model of the electrolytic cell and the initial frequency band, including: converting the equivalent circuit model of the electrolytic cell into a discrete state-space equation and establishing a prediction model; and determining the optimal scanning frequency band based on the prediction model and the initial frequency band through model prediction control.

[0012] Furthermore, the dynamic disturbance signal is a multi-band disturbance signal, and the dynamic disturbance signal is an orthogonal composite waveform.

[0013] Furthermore, the feedback data includes at least voltage and current signals; the impedance analysis module calculates the electrolytic cell impedance based on the feedback data, including: using fast Fourier transform to separate the time-frequency domain characteristics of the voltage and current signals, and calculating the impedance spectrum.

[0014] This invention provides an electrolytic cell impedance measurement system that considers dynamic disturbances, applied to the aforementioned electrolytic cell impedance measurement method that considers dynamic disturbances. The system includes: determining the optimal disturbance frequency band and optimal disturbance parameters based on the electrolytic cell operating conditions and its equivalent circuit model; injecting a dynamic disturbance signal into the electrolytic cell based on the optimal disturbance frequency band and optimal disturbance parameters; collecting feedback data from the electrolytic cell to the dynamic disturbance signal; and calculating the electrolytic cell impedance based on the feedback data.

[0015] Compared with existing technologies, the electrolytic cell impedance measurement method and system considering dynamic disturbances provided by this invention have at least the following advantages:

[0016] 1. Existing impedance measurements use a fixed perturbation amplitude (e.g., 5% DC current), which can easily lead to insufficient signal-to-noise ratio and decreased measurement accuracy under high current density. This invention dynamically adjusts the perturbation amplitude based on the electrolytic cell polarization type (activation polarization / mass transfer polarization) to ensure a high signal-to-noise ratio signal under various operating conditions. This improves measurement accuracy and adapts to complex operating conditions (e.g., high current density, low electrolyte concentration).

[0017] 2. Existing impedance measurements use a fixed low-frequency limit of 0.1Hz, failing to consider the effect of temperature on the electrolyte diffusion coefficient, leading to increased measurement errors at low temperatures. The low-frequency lower limit is dynamically adjusted with temperature to adapt to the electrolyte diffusion characteristics at different temperatures. This enhances the system's adaptability to temperature changes and improves measurement stability across the entire temperature range.

[0018] 3. Existing impedance measurements involving full-band scanning (0.1Hz-10kHz) are time-consuming, inefficient, and waste computational resources due to redundant data. This invention predicts key frequency bands using an equivalent circuit model of the electrolytic cell, scanning only the predicted frequency band, significantly shortening measurement time, reducing computational costs, and improving real-time performance.

[0019] 4. Dual-loop coupling circuit design to achieve physical isolation and low interference superposition of DC load and AC disturbance. Attached Figure Description

[0020] This specification will be further described by way of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting; in these embodiments, the same reference numerals denote the same structures, wherein:

[0021] Figure 1 This is a schematic diagram of a module of an electrolytic cell impedance measurement system considering dynamic disturbances, according to some embodiments of this specification.

[0022] Figure 2 This is a schematic diagram of the dynamic impedance spectrum according to some embodiments of this specification;

[0023] Figure 3 These are schematic diagrams illustrating some embodiments of this specification;

[0024] Figure 4 This is a schematic flowchart illustrating an electrolytic cell impedance measurement method that takes into account dynamic disturbances, according to some embodiments of this specification. Detailed Implementation

[0025] To more clearly illustrate the technical solutions of the embodiments in this specification, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely some examples or embodiments of this specification. For those skilled in the art, these drawings can be applied to other similar scenarios without creative effort. Unless obvious from the context or otherwise specified, the same reference numerals in the drawings represent the same structures or operations.

[0026] Figure 1 This is a schematic diagram of a module of an electrolytic cell impedance measurement system considering dynamic disturbances, as shown in some embodiments of this specification. Figure 1 As shown, an electrolytic cell impedance measurement system that considers dynamic disturbances may include a DC power supply module, a parameter optimization module, an AC disturbance module, a feedback acquisition module, and an impedance analysis module.

[0027] DC power supply module, used to provide DC power to the electrolytic cell.

[0028] The parameter optimization module is used to determine the optimal disturbance frequency band and optimal disturbance parameters based on the electrolytic cell operating conditions and the equivalent circuit model of the electrolytic cell.

[0029] Preferably, the parameter optimization module can determine the optimal perturbation frequency band and optimal perturbation parameters through the following process:

[0030] Initialize the disturbance parameters (e.g., amplitude, frequency band, etc.) and start the DC power supply module to inject the initial disturbance signal into the electrolytic cell according to the initial disturbance parameters;

[0031] Determine the activation polarization resistance, ohmic resistance, mass transfer polarization resistance, real-time current density, and real-time electrolytic cell temperature of the electrolyzer, among which the activation polarization resistance... The unit is Ω·cm², representing the impedance component caused by the electrochemical reaction kinetic resistance at the electrode surface, obtained through fitting the equivalent circuit model of the electrolytic cell or calculating using the Tafel equation. It represents the ohmic resistance. The unit is Ω·cm², defined as the purely resistive component of the total impedance of an electrolytic cell, including the series resistance of the electrolyte, diaphragm, and electrode contact resistance. It can be measured using the high-frequency intercept method. (Mass transfer polarization resistance) The unit is Ω·cm², defined as the product of reactants (H₂O, ... The impedance component caused by insufficient ion diffusion rate is related to electrolyte flow rate and concentration gradient. Current density (J), in units of A / cm², is defined as the current intensity per unit electrode active area. ,in, For the total current, The effective area is the base amplitude, which is the reference disturbance current density in A / cm², and is defined as the initially set AC disturbance signal amplitude.

[0032] Based on the activation polarization resistance, ohmic resistance and mass transfer polarization resistance, the electrolytic cell operating conditions are determined, wherein the electrolytic cell operating conditions are one of mass transfer polarization-dominated, mixed polarization state and activation polarization-dominated.

[0033] The optimal disturbance amplitude is determined based on the electrolytic cell operating conditions and real-time current density.

[0034] The initial frequency band was determined based on the real-time electrolytic cell temperature and real-time current density.

[0035] Based on the equivalent circuit model of the electrolytic cell and the initial frequency band, the optimal scanning frequency band is determined.

[0036] Preferably, the parameter optimization module determines the electrolyzer operating conditions based on the activation polarization resistance, ohmic resistance, and mass transfer polarization resistance, including:

[0037] If the ratio of the activation polarization resistance to the ohmic resistance is greater than the first ratio threshold, the electrolytic cell is determined to be in activation polarization-dominated operation. For example, ;

[0038] If the ratio of mass transfer polarization resistance to activation polarization resistance is greater than the second ratio threshold, the electrolytic cell is determined to be operating under mass transfer polarization-dominated conditions. For example, ;

[0039] If the ratio of the activation polarization resistance to the ohmic resistance is less than or equal to the first ratio threshold and the ratio of the mass transfer polarization resistance to the activation polarization resistance is less than or equal to the second ratio threshold, the electrolytic cell is determined to be in a mixed polarization state.

[0040] Preferably, the parameter optimization module determines the optimal disturbance amplitude based on the electrolyzer operating conditions and real-time current density, including:

[0041] If the electrolyzer's operating condition is dominated by activation polarization, the optimal perturbation amplitude is determined based on the base amplitude and real-time current density. For example... ;

[0042] If the electrolyzer's operating condition is dominated by mass transfer polarization, the optimal perturbation amplitude is determined based on the base amplitude and real-time current density. For example... ;

[0043] If the electrolyzer is in a mixed polarization state, determine the optimal disturbance amplitude as the base amplitude.

[0044] In some embodiments, the disturbance amplitude can be set to 5% to 15% of the DC current density. For example, The upper limit of the disturbance amplitude shall not exceed the instantaneous fluctuation range that the electrolyzer can withstand, i.e., 15% of the DC current density, to avoid exacerbating the oxygen / hydrogen evolution side reactions.

[0045] Preferably, the parameter optimization module is also used for:

[0046] The base amplitude is determined based on the real-time electrolytic cell temperature and / or the characteristics of the electrolytic cell material.

[0047] Specifically, when the temperature (T) of the electrolytic cell deviates from the standard operating conditions (such as 60℃), the base amplitude is adjusted proportionally.

[0048] For example, the base amplitude can be determined based on the real-time electrolyzer temperature using the following formula:

[0049] ,

[0050] For PEM (Proton Exchange Membrane) electrolyzers (high catalyst activity), the base amplitude can be increased to 0.12×J; for alkaline electrolyzers (mass transfer limited), the base amplitude can be reduced to 0.08×J.

[0051] For example, for a PEM electrolyzer, the base amplitude can be determined based on the real-time electrolyzer temperature and the properties of the electrolyzer material using the following formula:

[0052] ,

[0053] For alkaline electrolyzers, the basic amplitude can be determined based on the real-time electrolyzer temperature and the properties of the electrolyzer materials using the following formula:

[0054] ,

[0055] Preferably, the parameter optimization module determines the initial frequency band based on the real-time electrolyzer temperature and real-time current density, including:

[0056] The lower limit of low frequency is determined based on the real-time electrolytic cell temperature;

[0057] The upper limit of high frequency is determined based on real-time current density;

[0058] The initial frequency band is determined based on the lower limit of low frequency and the upper limit of high frequency.

[0059] For example, the lower limit of low frequency can be determined using the following formula:

[0060] ,

[0061] in, This is the lower limit for low frequency.

[0062] If the current density is greater than 2A / cm², select a frequency of 10kHz for the upper frequency range; otherwise, select a frequency of 5kHz.

[0063] Preferably, the parameter optimization module determines the optimal scanning frequency band based on the equivalent circuit model of the electrolytic cell and the initial frequency band, including:

[0064] The equivalent circuit model of the electrolytic cell is converted into discrete state-space equations to establish a prediction model.

[0065] Model predictive control determines the optimal scanning frequency band based on the predictive model and the initial frequency band.

[0066] Specifically, the core role of model predictive control in frequency band optimization is to dynamically predict the impedance response characteristics of the electrolyzer and adjust the scanning frequency range in real time, thereby maximizing measurement efficiency and increasing data value density. This will be explained from three dimensions: predictive model construction, rolling optimization mechanism, and constraint design.

[0067] 1. Prediction Model Construction: Impedance Response Prediction Based on the Equivalent Circuit Model of an Electrolyzer

[0068] Discretization and state-space representation of the equivalent circuit model of an electrolytic cell:

[0069] The equivalent circuit model of the electrolytic cell (such as the Randle model) is transformed into discrete state-space equations, which serve as the predictive model for Model Predictive Control (MPC). The equivalent circuit model of the electrolytic cell includes ohmic resistance. Charge transfer resistance Double-layer capacitors Parameters:

[0070] State variables:

[0071] ,

[0072] in, It is a double-layer capacitor. It is a diffusion capacitor.

[0073] Input variables:

[0074] ,

[0075] in, For alternating current disturbance, This is the current scanning frequency.

[0076] Output variables:

[0077] ,

[0078] in, These are parameters related to the diffusion process.

[0079] Discretization methods:

[0080] Numerical integration (such as the Euler method or the Runge-Kutta method) can be used to convert continuous-time models into discrete-time models.

[0081] State-space equation form:

[0082] ,

[0083] Among them, A, B, C, and D are system matrices, which need to be identified through model parameter fitting or experimental data.

[0084] 2. Rolling optimization mechanism

[0085] Predicting future responses: Based on the current state x(k) and the input u(k), the impedance response y(k+1), y(k+2), ..., y(k+N) at N future times is predicted using a state-space model.

[0086] Optimization goal:

[0087] Maximize information content: Select scanning frequency band This results in the largest change in the predicted impedance response.

[0088] Minimize measurement time: Reduce redundant frequency point measurements while ensuring data quality.

[0089] Optimization algorithm:

[0090] Quadratic Programming (QP):

[0091] The objective function is determined by maximizing information acquisition and minimizing measurement costs, taking both aspects into consideration. The mathematical expression pertains to the weighting coefficient ratio:

[0092] The objective function expression is:

[0093] ,

[0094] In the formula, For the target value, To obtain calculated values ​​for information, For cost, and These represent the weighting coefficients of the two, respectively. The number of wideband scans is indicated; k represents the k-th impedance measurement.

[0095] The function expression for the information acquisition calculation value is as follows:

[0096] ,

[0097] In the formula, This represents the impedance value at the i-th frequency point; The frequency weights are dynamically adjusted based on the polarization state (higher frequencies have higher weights when activation is dominant). This represents the rate of change of impedance, reflecting the activity of the dynamic process. This represents the total number of frequency points.

[0098] The second item is the measurement cost function term:

[0099] The cost function is:

[0100] ,

[0101] In the formula: Indicates scan time; This can be understood as the cost coefficient of frequency, which can be dynamically adjusted, with a default setting of 0.6; Indicates the scanning frequency.

[0102] The weighting coefficients can be dynamically adjusted. For example, in high-dynamic operating conditions (such as frequency modulation services): α=0.8, β=0.2, focusing on information gain; in steady-state operation: α=0.3, β=0.7, focusing on cost savings.

[0103] Constraints:

[0104] First: The sampling frequency should be within the hardware's capabilities.

[0105] Second, the maximum rate of change of impedance during the preceding and following scan cycles should be limited. This is to prevent the change from being too rapid, which could result in information not being captured.

[0106] Specifically:

[0107] Activation polarization resistance: ;

[0108] Mass transfer polarization resistance: .

[0109] Third, the rate of change of the frequency scan period before and after the scan should not be too large; the limit for the interval between the two scans should be set to 1 kHz.

[0110] Fourth, the prediction model should be performed under discrete conditions.

[0111] Frequency range constraints: .

[0112] The impedance characteristics of an electrolytic cell typically differ at low frequencies (e.g., 0.01 Hz to 1 kHz) and high frequencies (e.g., 1 kHz to 1 MHz). MPC needs to dynamically adjust the scan range based on the current state to avoid wasting resources in ineffective frequency bands.

[0113] Current disturbance constraint: .

[0114] Alternating current disturbances must be limited to a safe range to avoid irreversible damage to the electrolytic cell.

[0115] Model uncertainty constraints:

[0116] Introduce robust design and consider model parameter errors (such as the uncertainty of Ract and Cdll).

[0117] Constraint compression or robust optimization methods can be used to ensure that the constraints still hold under model errors.

[0118] Measurement time constraints:

[0119] The measurement time for each frequency point must meet the experimental requirements (e.g., the total measurement time should not exceed [a certain value]). ).

[0120] Rolling optimization process:

[0121] initialization:

[0122] Set initial state Reference impedance Weight matrices Q and R.

[0123] Real-time prediction:

[0124] Based on the current state x(k) and the input u(k), predict the impedance response at N future time points.

[0125] Optimization solution:

[0126] Solve the QP problem to obtain the optimal input sequence. .

[0127] Implement control:

[0128] The first control input Apply to the system and update the state x(k+1).

[0129] Rolling updates:

[0130] Move the time window and repeat steps 2-4 to achieve dynamic optimization.

[0131] Preferably, the dynamic disturbance signal is a multi-band disturbance signal, and the dynamic disturbance signal is an orthogonal composite waveform.

[0132] Specifically, a single injection of multi-band disturbance signals is performed, and voltage and current responses are collected simultaneously.

[0133] The high-frequency band (1-10kHz) consists of 5 equally spaced frequencies with a phase difference of π / 2. The low-frequency band (0.1-1Hz) uses 3 characteristic frequencies with a logarithmic distribution.

[0134] As an example only, the optimal perturbation frequency band is:

[0135] The three characteristic frequencies of the logarithmic fraction are log10(0.1) = -1; log10(0.316) = -0.5; log10(1) = 0;

[0136] f = [0.1Hz, 0.316Hz, 1Hz, 1kHz, 3.25kHz, 5.5kHz, 7.75kHz, 10kHz]

[0137] The optimal perturbation parameters are:

[0138] A = [5mV, 5mV, 5mV, 2mV, 2mV, 2mV, 2mV,1mV].

[0139] In some embodiments, the optimal scanning frequency band can also be determined by a deep learning model based on the equivalent circuit model of the electrolytic cell and the initial frequency band.

[0140] The AC disturbance module is used to inject dynamic disturbance signals into the electrolytic cell according to the optimal disturbance frequency band and optimal disturbance parameters.

[0141] Preferably, the DC power supply module and the AC disturbance module are coupled through an impedance transformer to achieve physical isolation between DC and AC signals and avoid mutual interference. An LC filter network and a DC blocking capacitor are used to suppress the impact of DC bus voltage fluctuations on the disturbance signal.

[0142] Preferably, a flyback converter can be used to implement a self-powered disturbance circuit, reducing dependence on external power sources. Software-defined radio (SDR) is used to generate the disturbance signal, enhancing flexibility.

[0143] The feedback acquisition module is used to acquire feedback data of the electrolytic cell in response to dynamic disturbance signals. The feedback data includes at least voltage and current signals.

[0144] Specifically, a distributed sensor network (such as HIOKI PW6001 ALDAS-E) can be used to replace the centralized acquisition module, which improves scalability but increases communication complexity.

[0145] The impedance analysis module is used to calculate the impedance of the electrolyzer based on feedback data.

[0146] Preferably, the impedance analysis module calculates the electrolyzer impedance based on feedback data, including:

[0147] The fast Fourier transform (FFT) is used to separate the time-frequency domain characteristics of voltage and current signals, and the impedance spectrum is calculated. However, directly performing FFT on the voltage and current signals leads to spectral leakage, reducing frequency domain resolution. Furthermore, noise can mask weak signals, causing errors in impedance calculation. Therefore, a Hanning window function is applied to each signal segment to reduce spectral leakage. Using a dynamic perturbation signal as a reference, the acquired voltage and current signals are coherently multiplied with the reference signal to extract the amplitude and phase of the target frequency band. The surf or slice function is used in conjunction with the time-frequency matrix to generate the impedance spectrum. Figure 2 The dynamic impedance spectrum is shown.

[0148] In some embodiments, the impedance analysis module is also used to provide performance warnings based on impedance spectra.

[0149] Specifically, the impedance analysis module can establish, based on dynamic impedance spectra, such as... Figure 3 The impedance-operation condition correlation graph shown simulates 24-hour operating data, including daily fluctuations in current density (J) and 6-hour fluctuations in temperature (T). The impedance parameters (R_act, R_mt) are represented by linear growth trends and random noise scatter points, with colors indicating operating time to visually display performance degradation trends. Logarithmic coordinates: Both the X and Y axes use logarithmic scales to better display multi-order-of-magnitude changes. High current density (J>2.4 A / cm²) and high temperature (T>65℃) operating conditions are marked with red borders and display specific parameter values.

[0150] Based on impedance-operating condition correlation graphs, performance early warnings are generated. Specifically, thresholds corresponding to impedance parameters can be set. When the impedance parameter exceeds the threshold, the system automatically generates an early warning message. The early warning message includes the fault type (e.g., diaphragm aging, catalyst failure), fault location (e.g., a specific electrolyzer unit), and recommended measures (e.g., replacing the diaphragm, adjusting the current density).

[0151] Threshold settings corresponding to impedance parameters:

[0152] Static threshold: Sets the upper and lower limits of impedance parameters based on historical data or empirical values.

[0153] Dynamic threshold: The threshold is dynamically adjusted according to changes in operating parameters (such as expanding the allowable impedance range at high temperatures).

[0154] Operating Condition Example 1: Diaphragm Aging

[0155] Feature: The real part Re(Z) increases by more than 50% in the high-frequency range (>1kHz).

[0156] Data: Fresh diaphragm Re(Z)@10kHz=0.12Ω → After aging Re(Z)@10kHz=0.58Ω.

[0157] Operating Condition Example 2: Catalyst Deactivation

[0158] Feature: Increased capacitive arc diameter in the mid-frequency range (1-100Hz)

[0159] Data: Normal R_act = 0.8 Ω·cm² → After failure R_act = 2.3 Ω·cm²

[0160] Early warning logic:

[0161] A maintenance alarm is triggered when Re(Z)@10kHz>0.5Ω or intermediate frequency phase angle<-45° is detected.

[0162] Understandably, traditional impedance measurements typically use fixed-frequency sine or square wave excitation. However, the operating conditions of the electrolyzer (such as temperature, concentration, and electrode state) change over time, causing dynamic drift in the equivalent circuit parameters. Fixed-frequency excitation cannot accurately reflect real-time impedance characteristics. By using a parameter optimization module to analyze the electrolyzer's operating conditions in real time and dynamically adjust the disturbance frequency band and parameters (such as amplitude and frequency range), the system ensures that the disturbance signal always matches the sensitive frequency band under the current operating conditions. This allows for the injection of disturbances at the optimal frequency band, reducing noise interference and capturing minute impedance fluctuations caused by changes in operating conditions.

[0163] Based on the equivalent circuit model of the electrolytic cell and real-time operating data (such as current, voltage, and temperature), the system automatically determines the optimal disturbance frequency band through model predictive control, covering the key dynamic response region of the electrolytic cell, as well as the optimal disturbance parameters, ensuring that the disturbance intensity is within a safe range while maximizing the impedance response. Through adaptive parameter optimization, the system can avoid nonlinear distortion caused by excessively strong disturbances and signal submersion in noise caused by excessively weak disturbances.

[0164] The system collects real-time feedback data (such as voltage and current response) from the electrolytic cell to dynamic disturbances and quickly calculates the impedance value through the impedance analysis module. Based on the feedback data, the system can dynamically adjust the disturbance parameters: if the operating conditions change abruptly (such as load changes), it automatically optimizes the disturbance strategy; and it can identify problems such as electrode aging and electrolyte contamination in advance by detecting abnormal impedance changes (such as sudden changes in impedance magnitude and phase shift).

[0165] The impedance characteristics of an electrolyzer can vary significantly with frequency (e.g., low frequencies reflect electrode processes, while high frequencies reflect electrolyte characteristics). Traditional methods are limited by a single frequency band and cannot provide a comprehensive analysis. Through a parameter optimization module, the system can cover:

[0166] Low frequency band (0.1Hz~100Hz): Monitoring electrode polarization and diffusion processes;

[0167] Mid-frequency band (100Hz~1kHz): Analysis of electrolyte conductivity and contact resistance;

[0168] High frequency band (1kHz~100kHz): Probe electrode surface morphology and bubble effect.

[0169] The system measures using small signal disturbances (such as current amplitude <5% of rated value) to avoid interfering with the normal operation of the electrolytic cell. Its decoupled design from the DC power supply module ensures that the measurement process does not affect the DC power supply to the electrolytic cell; under abnormal operating conditions (such as overvoltage or overcurrent), the disturbance signal is automatically cut off.

[0170] The system not only calculates impedance values ​​but also generates impedance spectra, visually displaying the impedance distribution at different frequencies; and it assesses the performance degradation of the electrolyzer by comparing historical data.

[0171] Figure 4 This is a schematic flowchart illustrating a method for measuring the impedance of an electrolytic cell considering dynamic disturbances, based on some embodiments of this specification. Figure 4 As shown, a method for measuring the impedance of an electrolyzer considering dynamic disturbances may include the following steps:

[0172] Based on the electrolytic cell operating conditions and the equivalent circuit model of the electrolytic cell, the optimal perturbation frequency band and optimal perturbation parameters are determined.

[0173] Based on the optimal perturbation frequency band and optimal perturbation parameters, a dynamic perturbation signal is injected into the electrolytic cell;

[0174] Collect feedback data from the electrolytic cell in response to dynamic disturbance signals;

[0175] The impedance of the electrolytic cell is calculated based on the feedback data.

[0176] An electrolytic cell impedance measurement method that takes into account dynamic disturbances can be applied to the aforementioned electrolytic cell impedance measurement system that takes into account dynamic disturbances, and will not be elaborated further here.

[0177] Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments described herein. Other variations may also fall within the scope of this specification. Therefore, alternative configurations of the embodiments described herein are intended to be illustrative rather than limiting, and should be considered consistent with the teachings of this specification. Accordingly, the embodiments described herein are not limited to those explicitly introduced and described herein.

Claims

1. A system for measuring impedance of an electrolytic cell taking into account dynamic disturbances, characterized by, include: DC power supply module, used to provide DC power to the electrolytic cell; The parameter optimization module is used to determine the optimal disturbance frequency band and optimal disturbance parameters based on the electrolytic cell operating conditions and the equivalent circuit model of the electrolytic cell. An AC disturbance module is used to inject dynamic disturbance signals into the electrolytic cell according to the optimal disturbance frequency band and optimal disturbance parameters; The feedback acquisition module is used to acquire feedback data from the electrolytic cell in response to dynamic disturbance signals. Impedance analysis module, used to calculate the electrolyzer impedance based on feedback data; The parameter optimization module determines the optimal disturbance frequency band and optimal disturbance parameters based on the electrolyzer operating conditions and the equivalent circuit model of the electrolyzer, including: Initialize the disturbance parameters and start the DC power supply module to inject an initialization disturbance signal into the electrolytic cell according to the initialization disturbance parameters; Determine the activation polarization resistance, ohmic resistance, mass transfer polarization resistance, real-time current density, and real-time electrolytic cell temperature of the electrolyzer; The operating conditions of the electrolyzer are determined based on the activation polarization resistance, ohmic resistance, and mass transfer polarization resistance. The optimal disturbance amplitude is determined based on the electrolytic cell operating conditions and real-time current density. The initial frequency band was determined based on the real-time electrolytic cell temperature and real-time current density. Based on the equivalent circuit model of the electrolytic cell and the initial frequency band, the optimal scanning frequency band is determined.

2. The electrolytic cell impedance measurement system considering dynamic disturbances according to claim 1, characterized in that, The electrolytic cell operating condition is one of mass transfer polarization-dominated, mixed polarization state, and activation polarization-dominated; The parameter optimization module determines the electrolyzer operating conditions based on the activation polarization resistance, ohmic resistance, and mass transfer polarization resistance, including: If the ratio of the activation polarization resistance to the ohmic resistance is greater than the first ratio threshold, the electrolytic cell is determined to be in activation polarization-dominated condition. If the ratio of mass transfer polarization resistance to activation polarization resistance is greater than the second ratio threshold, the electrolytic cell is determined to be in mass transfer polarization-dominated condition. If the ratio of the activation polarization resistance to the ohmic resistance is less than or equal to the first ratio threshold and the ratio of the mass transfer polarization resistance to the activation polarization resistance is less than or equal to the second ratio threshold, the electrolytic cell is determined to be in a mixed polarization state.

3. A system for measuring impedance of an electrolytic cell taking into account dynamic disturbances according to claim 2, characterized in that, The parameter optimization module determines the optimal disturbance amplitude based on the electrolyzer operating conditions and real-time current density, including: If the electrolyzer is operating under activation polarization-dominated conditions, the optimal disturbance amplitude is determined based on the base amplitude and real-time current density. If the electrolyzer is operating under mass transfer polarization-dominated conditions, the optimal perturbation amplitude is determined based on the base amplitude and real-time current density. If the electrolyzer is in a mixed polarization state, determine the optimal disturbance amplitude as the base amplitude.

4. The electrolytic cell impedance measurement system considering dynamic disturbances according to claim 3, characterized in that, The parameter optimization module is also used for: The base amplitude is determined based on the real-time electrolytic cell temperature and / or the characteristics of the electrolytic cell material.

5. The electrolytic cell impedance measurement system with dynamic disturbance consideration of claim 1, wherein, The parameter optimization module determines the initial frequency band based on the real-time electrolyzer temperature and real-time current density, including: The lower limit of low frequency is determined based on the real-time electrolytic cell temperature; The upper limit of high frequency is determined based on real-time current density; The initial frequency band is determined based on the lower limit of low frequency and the upper limit of high frequency.

6. The electrolytic cell impedance measurement system with dynamic disturbance consideration of claim 1, wherein, The parameter optimization module determines the optimal scanning frequency band based on the equivalent circuit model of the electrolytic cell and the initial frequency band, including: The equivalent circuit model of the electrolytic cell is converted into discrete state-space equations to establish a prediction model. Model predictive control determines the optimal scanning frequency band based on the predictive model and the initial frequency band.

7. A system for measuring impedance of an electrolytic cell taking into account dynamic disturbances according to any one of claims 1-6, characterized in that, The dynamic disturbance signal is a multi-band disturbance signal, and the dynamic disturbance signal is an orthogonal composite waveform.

8. A system for measuring impedance of an electrolytic cell taking into account dynamic disturbances according to any one of claims 1-6, characterized in that, The feedback data at least includes a voltage signal and a current signal; The impedance analysis module calculates the electrolytic cell impedance based on the feedback data, including: The time-frequency domain characteristics of the voltage signal and the current signal are separated by using fast Fourier transform to calculate the impedance spectrum.

9. A method of measuring the impedance of an electrolytic cell taking into account dynamic perturbations, characterized in that, An electrolytic cell impedance measurement system considering dynamic disturbance is applied to any one of claims 1-8, comprising: According to the working condition of the electrolytic cell and the equivalent circuit model of the electrolytic cell, the optimal disturbance frequency band and the optimal disturbance parameter are determined; According to the optimal disturbance frequency band and the optimal disturbance parameter, a dynamic disturbance signal is injected into the electrolytic cell; The feedback data of the electrolytic cell to the dynamic disturbance signal is collected; Based on the feedback data, the electrolytic cell impedance is calculated.

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