Electrolytic bath impedance measurement method and system considering dynamic disturbance

Abstract

The invention provides an electrolytic bath impedance measurement method and system considering dynamic disturbance, and relates to the field of electrochemical equipment, and the system comprises a direct current power supply module which is used for providing a direct current power supply for an electrolytic bath; the parameter optimization module is used for determining an optimal disturbance frequency band and an optimal disturbance parameter according to the working condition of the electrolytic cell and the equivalent circuit model of the electrolytic cell; the alternating current disturbance module is used for injecting a dynamic disturbance signal to the electrolytic cell according to the optimal disturbance frequency band and the optimal disturbance parameter; the feedback acquisition module is used for acquiring feedback data of the electrolytic bath on the dynamic disturbance signal; and the impedance analysis module is used for calculating the impedance of the electrolytic cell based on the feedback data, and has the advantage of realizing accurate measurement of the impedance of the electrolytic cell under the dynamic working condition.

Description

Technical Field

[0001] The present invention relates to the field of electrochemical devices, and particularly to a method and system for measuring the impedance of an electrolytic cell considering dynamic disturbances. Background Art

[0002] An electrolytic cell is a core device that uses electrical energy to drive chemical reactions (electrolysis process), and is widely used in industrial production, energy conversion, and material preparation fields. Its basic principle is to apply an external direct current, so that ions in the electrolyte solution or molten electrolyte undergo oxidation-reduction reactions on the electrode surface, thereby realizing the decomposition or synthesis of substances. The impedance of the electrolytic cell is a key parameter reflecting its electrochemical performance and operating state, and impedance measurement is crucial for optimizing processes, ensuring safety, and extending the service life of the device.

[0003] Existing impedance measurement methods, for example, in the dynamic operating conditions of the electrolytic cell (such as current fluctuations, start-stop transients), it is difficult to accurately separate the DC load and the AC disturbance signal, resulting in an increase in measurement error. For example, during direct parallel testing, the AC signal will interfere with the stability of the constant current power supply, causing noise. Moreover, at ultra-high current densities (such as >1000 A / ㎡), the amplitude of the AC disturbance is limited (usually 5%-10% of the DC current), making it difficult to capture the details of electrode polarization. In addition, using open-loop disturbance injection, it is impossible to dynamically adjust the disturbance parameters (such as frequency, amplitude) according to the real-time state of the electrolytic cell, resulting in low measurement efficiency and being easily affected by the operating conditions.

[0004] Therefore, there is a need to provide a method and system for measuring the impedance of an electrolytic cell considering dynamic disturbances, which is used to achieve accurate measurement of the impedance of the electrolytic cell under dynamic operating conditions. Summary of the Invention

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

[0006] Further, the parameter optimization module determines the optimal perturbation frequency band and optimal perturbation parameters according to the electrolyzer operating conditions and the electrolyzer equivalent circuit model, including: initializing the perturbation parameters, starting the DC power supply module, and injecting an initial perturbation signal into the electrolyzer according to the initialized perturbation parameters; determining the activation polarization resistance, ohmic resistance, mass transfer polarization resistance, real-time current density, and real-time electrolyzer temperature of the electrolyzer; determining the electrolyzer operating conditions based on the activation polarization resistance, ohmic resistance, and mass transfer polarization resistance; determining the optimal perturbation amplitude based on the electrolyzer operating conditions and the real-time current density; determining the initial frequency band based on the real-time electrolyzer temperature and the real-time current density; and determining the optimal scanning frequency band based on the electrolyzer equivalent circuit model and the initial frequency band.

[0007] Further, the electrolyzer operating conditions are 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, determining that the electrolyzer operating conditions are activation polarization-dominated; if the ratio of the mass transfer polarization resistance to the activation polarization resistance is greater than the second ratio threshold, determining that the electrolyzer operating conditions are mass transfer polarization-dominated; 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 the second ratio threshold, determining that the electrolyzer operating conditions are in a mixed polarization state.

[0008] Further, the parameter optimization module determines the optimal perturbation amplitude based on the electrolyzer operating conditions and the real-time current density, including: if the electrolyzer operating conditions are activation polarization-dominated, determining the optimal perturbation amplitude based on the base amplitude and the real-time current density; if the electrolyzer operating conditions are mass transfer polarization-dominated, determining the optimal perturbation amplitude based on the base amplitude and the real-time current density; if the electrolyzer operating conditions are in a mixed polarization state, determining that the optimal perturbation amplitude is the base amplitude.

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

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

[0011] Further, the parameter optimization module determines the optimal scanning frequency band based on the electrolyzer equivalent circuit model and the initial frequency band, including: converting the electrolyzer equivalent circuit model into a discrete state-space equation to establish a prediction model; and determining the optimal scanning frequency band based on the prediction model and the initial frequency band through model predictive control.

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

[0013] Further, 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: separating the time - frequency domain characteristics of the voltage signal and the current signal by using fast Fourier transform, and calculating the impedance spectrum.

[0014] The present invention provides an electrolytic cell impedance measurement system considering dynamic perturbation, which is applied to the above - mentioned electrolytic cell impedance measurement method considering dynamic perturbation, and includes: determining the optimal perturbation frequency band and the optimal perturbation parameters according to the electrolytic cell working conditions and the electrolytic cell equivalent circuit model; injecting a dynamic perturbation signal into the electrolytic cell according to the optimal perturbation frequency band and the optimal perturbation parameters; collecting the feedback data of the electrolytic cell on the dynamic perturbation signal; and calculating the electrolytic cell impedance based on the feedback data.

[0015] Compared with the prior art, the electrolytic cell impedance measurement method and system considering dynamic perturbation provided by the present invention at least have the following beneficial effects: 1. The existing impedance measurement uses a fixed perturbation amplitude (such as 5% DC current), which is prone to insufficient signal - to - noise ratio and decreased measurement accuracy at high current densities. The present invention dynamically adjusts the perturbation amplitude based on the polarization type (activation polarization / mass transfer polarization) of the electrolytic cell to ensure high - signal - to - noise - ratio signals can be obtained under different working conditions. It improves the measurement accuracy and adapts to complex working conditions (such as high current density and low electrolyte concentration).

[0016] 2. In the existing impedance measurement, the low - frequency is fixed at 0.1 Hz without considering the influence of temperature on the diffusion coefficient of the electrolyte, resulting in an increase in measurement error at low temperatures. The low - frequency lower limit is dynamically adjusted with temperature to adapt to the diffusion characteristics of the electrolyte at different temperatures. It enhances the adaptability of the system to temperature changes and improves the measurement stability in the full temperature range.

[0017] 3. The existing impedance measurement with full - frequency band scanning (0.1 Hz - 10 kHz) takes a long time and has low efficiency, and the redundant data causes waste of computing resources. The present invention predicts the key frequency band through the electrolytic cell equivalent circuit model and only scans the predicted frequency band, significantly shortening the measurement time, reducing the computing cost, and improving the real - time performance.

[0018] 4. The dual - loop coupling circuit design realizes physical isolation and low - interference superposition of the DC load and the AC perturbation. Description of the Drawings

[0019] This specification will further illustrate in the form of exemplary embodiments, and these exemplary embodiments will be described in detail through the drawings. These embodiments are not restrictive. In these embodiments, the same numbers represent the same structures, where: Figure 1 is a schematic diagram of modules of an electrolytic cell impedance measurement system considering dynamic disturbances as shown in some embodiments of this specification; Figure 2 is a schematic diagram of a dynamic impedance spectrum as shown in some embodiments of this specification; Figure 3 is a schematic diagram as shown in some embodiments of this specification; Figure 4 is a schematic flowchart of a method for measuring the impedance of an electrolytic cell considering dynamic disturbances as shown in some embodiments of this specification. Detailed implementation manners

[0020] To more clearly illustrate the technical solutions of the embodiments of this specification, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some examples or embodiments of this specification. For those of ordinary skill in the art, without creative efforts, this specification can also be applied to other similar scenarios based on these drawings. Unless obvious from the language context or otherwise stated, the same reference numerals in the figures represent the same structure or operation.

[0021] Figure 1 is a schematic diagram of modules of an electrolytic cell impedance measurement system considering dynamic disturbances as shown in some embodiments of this specification, as Figure 1 shown, an electrolytic cell impedance measurement system considering 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.

[0022] The DC power supply module is used to provide a DC power supply for the electrolytic cell.

[0023] The parameter optimization module is used to determine the optimal disturbance frequency band and optimal disturbance parameters according to the operating conditions of the electrolytic cell and the equivalent circuit model of the electrolytic cell.

[0024] Preferably, the parameter optimization module can determine the optimal disturbance frequency band and optimal disturbance parameters through the following process: Initialize the disturbance parameters (for example, amplitude, frequency band, etc.), and start the DC power supply module. Inject an initial disturbance signal into the electrolytic cell according to the initialized 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 electrolytic cell. Among them, the activation polarization resistance , with the unit of Ω·cm², is the impedance component caused by the kinetic resistance of the electrochemical reaction on the electrode surface, and is obtained by fitting through the equivalent circuit model of the electrolytic cell or calculated by the Tafel equation. The ohmic resistance , with the unit of Ω·cm², defined as the pure resistance component in the total impedance of the electrolytic cell, including the series value of the electrolyte, diaphragm, and plate contact resistance, which can be measured by the high-frequency intercept method, and the mass transfer polarization resistance , with the unit of Ω·cm², defined as the impedance component caused by the insufficient diffusion rate of reactants (H2O, ions), related to the electrolyte flow rate and concentration gradient. The current density (J), with the unit of A / cm², is defined as the current intensity per unit electrode active area, , where is the total current, is the effective area. The base amplitude is the reference perturbation current density, with the unit of A / cm², defined as the amplitude of the initially set AC perturbation signal; Based on the activation polarization resistance, ohmic resistance, and mass transfer polarization resistance, determine the working condition of the electrolytic cell, where the working condition of the electrolytic cell is one of mass transfer polarization-dominated, mixed polarization state, and activation polarization-dominated; Based on the working condition of the electrolytic cell and the real-time current density, determine the optimal perturbation amplitude; Based on the real-time electrolytic cell temperature and the real-time current density, determine the initial frequency band; Based on the equivalent circuit model of the electrolytic cell and the initial frequency band, determine the optimal scanning frequency band.

[0025] Preferably, the parameter optimization module determines the working condition of the electrolytic cell 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, it is determined that the working condition of the electrolytic cell is activation polarization-dominated. For example, ; If the ratio of the mass transfer polarization resistance to the activation polarization resistance is greater than the second ratio threshold, it is determined that the working condition of the electrolytic cell is mass transfer polarization-dominated. For example, ; 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 the second ratio threshold, it is determined that the working condition of the electrolytic cell is in a mixed polarization state.

[0026] Preferably, the parameter optimization module determines the optimal perturbation amplitude based on the working condition of the electrolytic cell and the real-time current density, including: If the working condition of the electrolytic cell is activation polarization-dominated, determine the optimal perturbation amplitude based on the base amplitude and the real-time current density. For example, ; If the working condition of the electrolytic cell is mass transfer polarization-dominated, determine the optimal perturbation amplitude based on the base amplitude and the real-time current density. For example, ; If the working condition of the electrolytic cell is in a mixed polarization state, determine the optimal perturbation amplitude as the base amplitude.

[0027] In some embodiments, the perturbation amplitude can be set to 5% - 15% of the DC current density. For example, . The upper limit of the perturbation amplitude does not exceed the instantaneous fluctuation range that the electrolytic cell can withstand, that is, 15% of the DC current density, to avoid exacerbating the oxygen evolution / hydrogen evolution side reactions.

[0028] Preferably, the parameter optimization module is further configured to: Determine the base amplitude based on the real-time electrolytic cell temperature and / or the characteristics of the electrolytic cell material.

[0029] Specifically, when the electrolytic cell temperature (T) deviates from the standard operating condition (such as 60 °C), the base amplitude is adjusted proportionally.

[0030] For example, the base amplitude can be determined based on the real-time electrolytic cell temperature according to the following formula: , For a PEM (Proton Exchange Membrane) electrolytic cell (high catalyst activity), the base amplitude can be increased to 0.12×J; for an alkaline electrolytic cell (mass transfer limitation), the base amplitude can be reduced to 0.08×J.

[0031] Another example is that for a PEM electrolytic cell, the base amplitude can be determined based on the real-time electrolytic cell temperature and the characteristics of the electrolytic cell material according to the following formula: , For an alkaline electrolytic cell, the base amplitude can be determined based on the real-time electrolytic cell temperature and the characteristics of the electrolytic cell material according to the following formula: , Preferably, the parameter optimization module determines the initial frequency band based on the real-time electrolytic cell temperature and the real-time current density, including: Determine the lower limit of the low frequency based on the real-time electrolytic cell temperature; Determine the upper limit of the high frequency based on the real-time current density; Determine the initial frequency band based on the lower limit of the low frequency and the upper limit of the high frequency.

[0032] For example, the lower limit of the low frequency can be determined according to the following formula: , where is the lower limit of the low frequency.

[0033] If the current density is greater than 2 A / cm², the frequency 10 kHz is selected in the upper limit stage of the frequency, otherwise the frequency 5 kHz is selected Preferably, the parameter optimization module determines the optimal scanning frequency band based on the electrolytic cell equivalent circuit model and the initial frequency band, including: Convert the equivalent circuit model of the electrolytic cell into a discrete state - space equation to establish a prediction model; Based on the prediction model and the initial frequency band, determine the optimal scanning frequency band through model predictive control.

[0034] Specifically, the core role of model predictive control in frequency - band optimization is to dynamically predict the impedance response characteristics of the electrolytic cell, adjust the scanning frequency - band range in real - time, and achieve the maximization of measurement efficiency and the improvement of data value density. The following is an explanation from three dimensions: the construction of the prediction model, the rolling optimization mechanism, and the design of constraint conditions: 1. Construction of the prediction model: Prediction of impedance response based on the equivalent circuit model of the electrolytic cell Discretization and state - space representation of the equivalent circuit model of the electrolytic cell: Convert the equivalent circuit model of the electrolytic cell (such as the Randles model) into a discrete state - space equation as the prediction model of model predictive control (MPC). Among them, the equivalent circuit model of the electrolytic cell includes ohmic resistance , charge - transfer resistance , double - layer capacitance and other parameters: State variables: , Among them, is the double - layer capacitance, is the diffusion capacitance.

[0035] Input variables: , Among them, is the alternating - current perturbation, is the current scanning frequency.

[0036] Output variables: , Among them, is the parameter related to the diffusion process.

[0037] Discretization method: Use numerical integration (such as Euler's method or Runge - Kutta method) to convert the continuous - time model into a discrete - time model.

[0038] Form of the state - space equation: , Among them, A, B, C, and D are system matrices, which need to be obtained through model - parameter fitting or experimental - data identification.

[0039] 2. Rolling optimization mechanism Predicting Future Responses: Based on the current state x(k) and input u(k), use the state-space model to predict the impedance responses y(k+1), y(k+2), …, y(k+N) at the next N time instants.

[0040] Optimization Objectives: Maximizing Information Content: Select the scanning frequency band to maximize the variation in the predicted impedance responses.

[0041] Minimizing Measurement Time: Reduce redundant frequency point measurements while ensuring data quality.

[0042] Optimization Algorithm: Quadratic Programming (QP): The confirmation of the objective function refers to the comprehensive consideration of maximizing information acquisition and minimizing measurement costs. The mathematical expression is for the weighted coefficient ratio: The objective function expression is: , where, is the target value, is the calculated value of information acquisition, is the cost, and represent the weight coefficients of the two respectively; represents the number of wide-frequency scans; k represents the k-th impedance measurement.

[0043] Among them, the functional expression of the calculated value of information acquisition is: , where, represents the impedance value at the i-th frequency point; represents the frequency point weight, which is dynamically adjusted according to the polarization state (higher high-frequency weight when activation is dominant); represents the impedance change rate, reflecting the activity of the dynamic process, is the total number of frequency points.

[0044] The second term, the measurement cost function term: The function of the cost is: , where: represents the scanning time; can be understood as the cost coefficient of frequency, which can be dynamically adjusted, and the default setting is 0.6; represents the scanned frequency.

[0045] The weight coefficients can be dynamically adjusted. For example, in high-dynamic working conditions (such as frequency regulation services): α = 0.8, β = 0.2, with emphasis on information gain; in steady-state operation: α = 0.3, β = 0.7, with emphasis on cost savings.

[0046] Constraint conditions: First: The sampling frequency should be carried out under the condition of hardware support.

[0047] Second: The maximum rate of change of the impedance between the front and back scan cycles should be restricted. Avoid too fast changes so that information is not captured.

[0048] Specifically: Activation polarization resistance: ; Mass transfer polarization resistance: 。

[0049] Third, the rate of change between the front and back cycles of the frequency scan cannot be too large, and the set interval limit is 1 kHz Fourth, the prediction model should be carried out under discrete conditions.

[0050] Frequency range constraint: 。

[0051] The impedance characteristics of the electrolyzer usually have different characteristics at low frequencies (such as 0.01 Hz to 1 kHz) and high frequencies (such as 1 kHz to 1 MHz). MPC needs to dynamically adjust the scan range according to the current state to avoid wasting resources in the invalid frequency band.

[0052] Current perturbation constraint: 。

[0053] The alternating current perturbation needs to be restricted within a safe range to avoid irreversible damage to the electrolyzer.

[0054] Model uncertainty constraint: Introduce robust design and consider model parameter errors (such as the uncertainty of Ract, Cdll).

[0055] The constraint tightening method or robust optimization method can be adopted to ensure that the constraints still hold under model errors.

[0056] Measurement time constraint: The measurement time for each frequency point needs to meet the experimental requirements (such as the total measurement time does not exceed ).

[0057] Rolling optimization process: Initialization: Set the initial state 、reference impedance 、weight matrices Q, R.

[0058] Real-time prediction: Based on the current state x(k) and input u(k), predict the impedance response at the next N time instants.

[0059] Optimization solution: Solve the QP problem to obtain the optimal input sequence .

[0060] Implementation of control: Apply the first control input to the system to update the state x(k+1).

[0061] Rolling update: Move the time window and repeat steps 2 - 4 to achieve dynamic optimization.

[0062] Preferably, the dynamic disturbance signal is a multi-band disturbance signal, and the dynamic disturbance signal is an orthogonal composite waveform.

[0063] Specifically, inject the multi-band disturbance signal once and synchronously collect the voltage and current responses.

[0064] Among them, for the high-frequency band (1 - 10 kHz): 5 equally spaced frequencies with a phase difference of π / 2. For the low-frequency band (0.1 - 1 Hz): 3 characteristic frequencies with a logarithmic distribution.

[0065] Merely by way of example, the optimal disturbance frequency band is: Three characteristic frequencies of the logarithmic fraction, where log10(0.1) = -1; log10(0.316) = -0.5; log10(1) = 0; f = [0.1Hz, 0.316Hz, 1Hz, 1kHz, 3.25kHz, 5.5kHz, 7.75kHz, 10kHz] The optimal disturbance parameters are: A = [5mV, 5mV, 5mV, 2mV, 2mV, 2mV, 2mV, 1mV].

[0066] 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.

[0067] The AC disturbance module is used to inject a dynamic disturbance signal into the electrolytic cell according to the optimal disturbance frequency band and the optimal disturbance parameters.

[0068] Preferably, the DC power supply module and the AC perturbation module are coupled through an impedance converter to achieve physical isolation of DC-AC signals and avoid mutual interference. An LC filter network and a DC-blocking capacitor are used to suppress the influence of DC bus voltage fluctuations on the perturbation signal.

[0069] Preferably, a flyback converter can be used to implement a self-powered perturbation circuit, reducing the dependence on external power supplies. A software-defined radio (SDR) is used to generate the perturbation signal, enhancing flexibility.

[0070] The feedback acquisition module is used to acquire the feedback data of the electrolytic cell on the dynamic perturbation signal, where the feedback data includes at least voltage signals and current signals.

[0071] Specifically, a distributed sensor network (such as HIOKI PW6001 ALDAS-E) can be used to replace the centralized acquisition module, improving scalability but increasing communication complexity.

[0072] The impedance analysis module is used to calculate the impedance of the electrolytic cell based on the feedback data.

[0073] Preferably, the impedance analysis module calculates the impedance of the electrolytic cell based on the feedback data, including: Using the fast Fourier transform to separate the time-frequency domain characteristics of the voltage signal and the current signal, and calculating the impedance spectrum. Directly performing the fast Fourier transform on the voltage signal and the current signal will cause spectral leakage, reducing the frequency domain resolution. Moreover, noise will mask weak signals, resulting in impedance calculation errors. Therefore, a Hanning window function is applied to each signal segment to reduce spectral leakage. Using the dynamic perturbation signal as a reference, the collected voltage and current signals are multiplied coherently with the reference signal to extract the amplitude and phase of the target frequency band. The surf or slice function is used in combination with the time-frequency matrix to generate a dynamic impedance spectrum as shown in Figure 2 Figure [specific figure number].

[0074] In some embodiments, the impedance analysis module is further used to perform performance warning based on the impedance spectrum.

[0075] Specifically, the impedance analysis module can establish an impedance-operation condition correlation map as shown in Figure 3 Figure [specific figure number]. The impedance-operation condition correlation map simulates 24-hour operation data, including the daily cycle fluctuation of the current density (J) and the 6-hour cycle fluctuation of the temperature (T); the impedance parameters (R_act, R_mt) are added with a linear growth trend and random noise. The scatter point color represents the operation time, visually showing the performance degradation trend; logarithmic coordinates: both the X / Y axes use logarithmic scales to better display multi-order magnitude changes. The high current density (J>2.4 A / cm²) and high temperature (T>65°C) operation condition points are marked with red borders and the specific parameter values are displayed.

[0076] Based on the impedance-operation condition correlation map, performance early warning is carried out. Specifically, the threshold values corresponding to the impedance parameters can be set. When the impedance parameters exceed the threshold values, the system automatically generates early warning information. The early warning information includes the type of failure (such as diaphragm aging, catalyst failure), the location of the failure (such as a certain electrolytic cell unit), and the recommended measures (such as replacing the diaphragm, adjusting the current density). Setting of the threshold value corresponding to the impedance parameter: Static threshold: Set the upper and lower limits of the impedance parameter based on historical data or empirical values.

[0077] Dynamic threshold: Dynamically adjust the threshold according to the change of the operation condition parameters (such as the impedance allowable range expands at high temperature).

[0078] Operation condition example 1: Diaphragm aging Characteristic: The real part Re(Z) in the high-frequency band (>1 kHz) rises by more than 50%. Data: Re(Z)@10kHz = 0.12 Ω for the fresh diaphragm → Re(Z)@10kHz = 0.58 Ω after aging.

[0079] Operation condition example 2: Catalyst failure Characteristic: The diameter of the capacitive reactance arc expands in the middle-frequency band (1 - 100 Hz). Data: Normal R_act = 0.8 Ω·cm² → R_act = 2.3 Ω·cm² after failure. Early warning logic: When it is detected that Re(Z)@10kHz > 0.5 Ω or the intermediate-frequency phase angle < -45°, a maintenance alarm is triggered.

[0080] It can be understood that traditional impedance measurement usually uses a sine wave or square wave excitation with a fixed frequency. However, the operation conditions of the electrolytic cell (such as temperature, concentration, electrode state) change with time, resulting in the dynamic drift of the equivalent circuit parameters. It is difficult for the fixed-frequency excitation to accurately reflect the real-time impedance characteristics. Through the parameter optimization module, the operation conditions of the electrolytic cell are analyzed in real time, and the disturbance frequency band and parameters (such as amplitude, frequency range) are dynamically adjusted to ensure that the disturbance signal always matches the sensitive frequency band under the current operation conditions, so as to inject the disturbance in the optimal frequency band, reduce the noise interference, and capture the tiny impedance fluctuations caused by the change of the operation conditions.

[0081] Based on the equivalent circuit model of the electrolytic cell and the real-time operation condition data (such as current, voltage, temperature), the system automatically determines the optimal disturbance frequency band through model predictive control, covering the key dynamic response area of the electrolytic cell, as well as the optimal disturbance parameters, ensuring that the disturbance intensity is within the safe range and maximizing the impedance response at the same time. Through adaptive parameter optimization, the system can avoid the nonlinear distortion caused by too strong disturbance and the signal being submerged in the noise caused by too weak disturbance.

[0082] The system collects in real time the feedback data of the electrolytic cell on dynamic disturbances (such as voltage and current responses), and quickly calculates the impedance value through the impedance analysis module. Combining the feedback data, the system can dynamically adjust the disturbance parameters: if the working conditions change suddenly (such as load change), it automatically optimizes the disturbance strategy; it can identify problems such as electrode aging and electrolyte pollution in advance through abnormal impedance changes (such as sudden change in impedance modulus value and phase shift).

[0083] The impedance characteristics of the electrolytic cell may change significantly with frequency (for example, the low-frequency band reflects the electrode process, and the high-frequency band reflects the electrolyte characteristics). Limited by the single frequency band, traditional methods are difficult to analyze comprehensively. Through the parameter optimization module, the system can cover: Low-frequency band (0.1Hz~100Hz): Monitor the electrode polarization and diffusion processes; Medium-frequency band (100Hz~1kHz): Analyze the electrolyte conductivity and contact resistance; High-frequency band (1kHz~100kHz): Detect the electrode surface morphology and bubble effect.

[0084] The system measures through small-signal disturbances (such as current amplitude <5% of the rated value) to avoid interfering with the normal operation of the electrolytic cell. It is decoupled from the DC power supply module to ensure that the measurement process does not affect the DC power supply of the electrolytic cell; the disturbance signal is automatically cut off under abnormal working conditions (such as overvoltage and overcurrent).

[0085] The system not only calculates the impedance value, but also generates an impedance spectrogram: intuitively display the impedance distribution at different frequencies; evaluate the performance decay of the electrolytic cell through historical data comparison.

[0086] Figure 4 is a schematic flowchart of a method for measuring the impedance of an electrolytic cell considering dynamic disturbances shown in some embodiments of this specification, such as Figure 4 shown, a method for measuring the impedance of an electrolytic cell considering dynamic disturbances may include the following processes: Determine the optimal disturbance frequency band and optimal disturbance parameters according to the working conditions of the electrolytic cell and the equivalent circuit model of the electrolytic cell; Inject a dynamic disturbance signal into the electrolytic cell according to the optimal disturbance frequency band and optimal disturbance parameters; Collect the feedback data of the electrolytic cell on the dynamic disturbance signal; Calculate the impedance of the electrolytic cell based on the feedback data.

[0087] A method for measuring the impedance of an electrolytic cell considering dynamic disturbances can be applied to the above-mentioned system for measuring the impedance of an electrolytic cell considering dynamic disturbances, which will not be elaborated here.

[0088] Finally, it should be understood that the embodiments described in this specification are only used 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 regarded as consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly presented and described in this specification.

Claims

1. An electrolytic cell impedance measurement system considering dynamic disturbances, characterized in that, Comprising: A DC power supply module for providing a DC power supply to the electrolytic cell; A parameter optimization module for determining the optimal perturbation frequency band and the optimal perturbation parameters according to the operating conditions of the electrolytic cell and the equivalent circuit model of the electrolytic cell; An AC perturbation module for injecting a dynamic perturbation signal into the electrolytic cell according to the optimal perturbation frequency band and the optimal perturbation parameters; A feedback acquisition module for acquiring the feedback data of the electrolytic cell on the dynamic perturbation signal; An impedance analysis module for calculating the impedance of the electrolytic cell based on the feedback data.

2. The electrolytic cell impedance measurement system considering dynamic disturbance according to claim 1, characterized in that The parameter optimization module determines the optimal perturbation frequency band and the optimal perturbation parameters according to the operating conditions of the electrolytic cell and the equivalent circuit model of the electrolytic cell, including: Initializing the perturbation parameters, starting the DC power supply module, and injecting an initialization perturbation signal into the electrolytic cell according to the initialization perturbation 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 operating conditions of the electrolytic cell based on the activation polarization resistance, ohmic resistance, and mass transfer polarization resistance; Determining the optimal perturbation amplitude based on the operating conditions of the electrolytic cell and the real-time current density; Determining the initial frequency band based on the real-time electrolytic cell temperature and the real-time current density; Determining the optimal scanning frequency band based on the equivalent circuit model of the electrolytic cell and the initial frequency band.

3. The electrolytic cell impedance measurement system considering dynamic disturbance according to claim 2, characterized in that The operating conditions of the electrolytic cell are one of mass transfer polarization-dominated, mixed polarization state, and activation polarization-dominated; The parameter optimization module determines the operating conditions of the electrolytic cell 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, it is determined that the operating conditions of the electrolytic cell are activation polarization-dominated; If the ratio of the mass transfer polarization resistance to the activation polarization resistance is greater than the second ratio threshold, it is determined that the operating conditions of the electrolytic cell are mass transfer polarization-dominated; 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 the second ratio threshold, it is determined that the operating conditions of the electrolytic cell are in a mixed polarization state.

4. A system for measuring the impedance of an electrolytic cell considering dynamic disturbances according to claim 3, wherein, The parameter optimization module determines the optimal perturbation amplitude based on the operating conditions of the electrolytic cell and the real-time current density, including: If the operating conditions of the electrolytic cell are activation polarization-dominated, determining the optimal perturbation amplitude based on the base amplitude and the real-time current density; If the operating conditions of the electrolytic cell are mass transfer polarization-dominated, determining the optimal perturbation amplitude based on the base amplitude and the real-time current density; If the operating conditions of the electrolytic cell are in a mixed polarization state, determining the optimal perturbation amplitude as the base amplitude.

5. The electrolytic cell impedance measurement system considering dynamic disturbance according to claim 4, characterized in that The parameter optimization module is further configured to: Determine the base amplitude based on the real-time electrolytic cell temperature and / or the material characteristics of the electrolytic cell.

6. The electrolytic cell impedance measurement system considering dynamic disturbance according to claim 1, characterized in that, 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 low-frequency lower limit based on the real-time electrolytic cell temperature; Determining the high-frequency upper limit based on the real-time current density; Determining the initial frequency band based on the low-frequency lower limit and the high-frequency upper limit.

7. The electrolytic cell impedance measurement system considering dynamic disturbance according to claim 1, characterized in that 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 to establish a prediction model; Determining the optimal scanning frequency band based on the prediction model and the initial frequency band through model predictive control.

8. A measurement system for the impedance of an electrolytic cell considering dynamic disturbances, according to any one of claims 1-7, characterized in that The dynamic perturbation signal is a multi-band perturbation signal, and the dynamic perturbation signal is an orthogonal composite waveform.

9. A system for measuring the impedance of an electrolytic cell considering dynamic disturbances according to any one of claims 1-7, characterized in that, The feedback data at least includes a voltage signal and a current signal; Based on the feedback data, the impedance analysis module calculates the electrolytic cell impedance, including: Separating the time-frequency domain characteristics of the voltage signal and the current signal by using fast Fourier transform, and calculating the impedance spectrum.

10. A method for measuring the impedance of an electrolytic cell considering dynamic disturbances, characterized in that, Applied to the electrolytic cell impedance measurement method according to any one of claims 1-9, including: Determining the optimal disturbance frequency band and the optimal disturbance parameters according to the operating conditions of the electrolytic cell and the equivalent circuit model of the electrolytic cell; Injecting a dynamic disturbance signal into the electrolytic cell according to the optimal disturbance frequency band and the optimal disturbance parameters; Collecting the feedback data of the electrolytic cell on the dynamic disturbance signal; Calculating the electrolytic cell impedance based on the feedback data.

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