Fuel cell online electrochemical impedance spectroscopy measurement method and device and storage medium

Abstract

The invention discloses an on-line electrochemical impedance spectroscopy measurement method and device for a fuel cell and a storage medium, and the method comprises the steps: obtaining an initial value of an influence parameter which influences an EIS test result when the fuel cell is started, the influence parameters at least comprise the stack temperature, the stack voltage, the stack current and the low-frequency impedance; acquiring an actual measurement value of the influence parameter when the fuel cell runs; determining a target output value of each influence parameter according to the initial value of each influence parameter and the measured value of each influence parameter; and coupling the target output values of the influence parameters to obtain a high-frequency impedance value. By adopting the method, accurate online EIS diagnosis can be realized, and the diagnosis reliability of the battery state is improved.

Description

Technical Field

[0001] This invention relates to the field of fuel cell technology, and in particular to a method, apparatus, and storage medium for online electrochemical impedance spectroscopy measurement of fuel cells. Background Technology

[0002] Online electrochemical impedance spectroscopy (EIS) is a key technology for real-time condition diagnosis of fuel cells. However, in actual dynamic operation, EIS test results are easily affected by strong coupling interference from multiple factors such as ambient temperature, stack degradation, flow channel blockage, and variable load conditions, leading to spectral distortion and making it difficult to accurately identify core faults such as water management and catalyst degradation, which seriously restricts its engineering application value. Summary of the Invention

[0003] This invention aims to at least solve one of the technical problems existing in the prior art. Therefore, one objective of this invention is to propose an online electrochemical impedance spectroscopy (EIS) measurement method for fuel cells, which enables accurate online EIS diagnosis and improves the reliability of battery status diagnosis.

[0004] The second objective of this invention is to provide an online electrochemical impedance spectroscopy measurement device for fuel cells.

[0005] The third objective of this invention is to provide an electronic device.

[0006] The fourth objective of this invention is to provide a computer storage medium.

[0007] To address the aforementioned problems, a first aspect of the present invention provides a method for online electrochemical impedance spectroscopy (EIS) measurement of a fuel cell, comprising: acquiring initial values ​​of influencing parameters affecting EIS test results during fuel cell startup, wherein the influencing parameters include at least stack temperature, stack voltage, stack current, and low-frequency impedance; acquiring measured values ​​of the influencing parameters during fuel cell operation; determining target output values ​​of each influencing parameter based on the initial values ​​and measured values ​​of each influencing parameter; and coupling the target output values ​​of each influencing parameter to obtain a high-frequency impedance value.

[0008] The online electrochemical impedance spectroscopy (EIS) measurement method for fuel cells according to embodiments of the present invention no longer directly couples the measured values ​​of the parameters affecting the EIS test results to determine the impedance. Instead, it first performs decoupling analysis on each parameter, that is, determines the target output value of each parameter based on the initial value and the measured value of each parameter, thereby determining the influence of different parameters on the battery impedance state. Then, it couples the target output values ​​of each parameter to obtain a conditioned impedance characteristic value, i.e., a high-frequency impedance value, which is strongly correlated only with the water content in the fuel cell membrane. This enables accurate online condition diagnosis and fault warning, improving the reliability of battery condition diagnosis.

[0009] In some embodiments, the initial value includes an initial value of the fuel cell stack temperature, and the measured value includes a measured value of the fuel cell stack temperature. Determining the target output value of each influencing parameter based on the initial value and the measured value of each influencing parameter includes: determining the temperature difference between the initial value of the fuel cell stack temperature and the measured value of the fuel cell stack temperature; if the temperature difference is within a first preset tolerance range, then determining the target output value of the fuel cell stack temperature as the initial value of the fuel cell stack temperature; if the temperature difference is not within the preset tolerance range, then determining the target output value of the fuel cell stack temperature as the product of a temperature correction factor and the measured value of the fuel cell stack temperature.

[0010] In some embodiments, the initial value includes the stack voltage polarization value, and the measured value includes the measured stack voltage value and the measured stack current value. Determining the target output value of each influencing parameter based on the initial value and the measured value of each influencing parameter includes: determining the voltage difference between the stack voltage polarization value and the measured stack voltage value; determining the current change rate based on the measured stack current value; determining the stack decay state based on the voltage difference; determining the stack operating condition based on the current change rate; and determining the target output value of the stack voltage based on the stack decay state and the operating condition.

[0011] In some embodiments, determining the battery stack attenuation state based on the voltage difference includes: if the voltage difference is within a second preset tolerance range, then determining the battery stack attenuation state as an unattenuated state; if the voltage difference is not within the second preset tolerance range, then determining the battery stack attenuation state as an attenuated state.

[0012] In some embodiments, determining the operating condition of the fuel cell stack based on the current change rate includes: if the current change rate is 0, then determining the operating condition as steady-state operation; if the current change rate is not 0, then determining the operating condition as variable load operation.

[0013] In some embodiments, determining the target output value of the fuel cell voltage based on the fuel cell stack decay state and the operating condition includes: if the fuel cell stack decay state is undecayed and the operating condition is steady-state operation, then the target output value of the fuel cell voltage is determined to be the measured value of the fuel cell voltage; if the fuel cell stack decay state is undecayed and the operating condition is variable load operation, then the target output value of the fuel cell voltage is determined to be the product of the measured value of the fuel cell voltage and the variable load correction factor; if the fuel cell stack decay state is decayed and the operating condition is steady-state operation, then the target output value of the fuel cell voltage is determined to be the product of the measured value of the fuel cell voltage and the lifetime decay factor; if the fuel cell stack decay state is decayed and the operating condition is variable load operation, then the target output value of the fuel cell voltage is determined to be the product of the measured value of the fuel cell voltage, the variable load correction factor, and the lifetime decay factor.

[0014] In some embodiments, the initial value includes an initial value of low-frequency impedance, and the measured value includes a measured value of low-frequency impedance. Determining the target output value of each influencing parameter based on the initial value and the measured value of each influencing parameter includes: if the initial value of low-frequency impedance is consistent with the measured value of low-frequency impedance, then the target output value of the low-frequency impedance is determined to be the initial value of low-frequency impedance; if the initial value of low-frequency impedance is inconsistent with the measured value of low-frequency impedance, then the target output value of the low-frequency impedance is determined to be the product of the measured value of low-frequency impedance and the impedance correction factor.

[0015] A second aspect of the present invention provides an online electrochemical impedance spectroscopy (EIS) measurement device for a fuel cell, comprising: a first acquisition module for acquiring initial values ​​of influencing parameters affecting EIS test results during fuel cell startup, wherein the influencing parameters include at least stack temperature, stack voltage, stack current, and low-frequency impedance; a second acquisition module for acquiring measured values ​​of the influencing parameters during fuel cell operation; a determination module for determining target output values ​​of each influencing parameter based on the initial values ​​and measured values ​​of each influencing parameter; and a coupling module for coupling the target output values ​​of each influencing parameter to obtain a high-frequency impedance value.

[0016] The online electrochemical impedance spectroscopy (EIS) measurement device for fuel cells in this invention does not directly couple the measured values ​​of the parameters affecting EIS test results to determine the impedance. Instead, it first performs a stripping analysis on each parameter, that is, it determines the target output value of each parameter based on the initial value and the measured value of each parameter. This allows it to determine the influence of different parameters on the battery impedance state. Then, it couples the target output values ​​of each parameter to obtain a conditioned impedance characteristic value, i.e., a high-frequency impedance value, which is strongly correlated only with the water content in the fuel cell membrane. This enables accurate online condition diagnosis and fault warning, improving the reliability of battery condition diagnosis.

[0017] A third aspect of the present invention provides an electronic device, comprising: at least one processor; and a memory communicatively connected to at least one of the processors; wherein the memory stores a computer program executable by at least one of the processors, and the at least one processor executes the computer program to implement the online electrochemical impedance spectroscopy measurement method for fuel cells described in the above embodiments.

[0018] The electronic device according to embodiments of the present invention can achieve accurate online EIS diagnosis and improve the reliability of battery status diagnosis.

[0019] A fourth aspect of the present invention provides a computer storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the online electrochemical impedance spectroscopy measurement method for fuel cells described in the above embodiments.

[0020] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0021] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 This is a flowchart of an online electrochemical impedance spectroscopy measurement method for fuel cells according to an embodiment of the present invention; Figure 2 This is a flowchart illustrating the process of determining the target output value of the influencing parameters according to an embodiment of the present invention; Figure 3 This is a flowchart of an online electrochemical impedance spectroscopy measurement method for fuel cells according to another embodiment of the present invention; Figure 4 This is a structural diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0022] The embodiments of the present invention are described in detail below. The embodiments described with reference to the accompanying drawings are exemplary. The embodiments of the present invention are described in detail below.

[0023] Online electrochemical impedance spectroscopy (EIS) is a key technology for real-time condition diagnosis of fuel cells. However, in actual dynamic operation, EIS test results are strongly coupled and interfered with by multiple factors such as ambient temperature, stack degradation, flow channel blockage, and variable load conditions, leading to spectral distortion and making it difficult to accurately identify core faults such as water management and catalyst degradation, severely limiting its engineering application value. Existing solutions typically use fixed thresholds or single parameters for coarse compensation, but this approach cannot decouple the aforementioned multiple interferences. Furthermore, these methods have poor adaptability under complex operating conditions, and the diagnostic results still contain a large number of interfering factors, failing to provide a pure EIS signal reflecting the intrinsic state of the fuel cell stack. This results in ambiguous fault location and insufficient basis for optimizing control strategies.

[0024] To address the aforementioned problems, the first aspect of this invention provides a method for online electrochemical impedance spectroscopy (EIS) measurement of fuel cells. This method enables accurate online EIS diagnosis and improves the reliability of battery status diagnosis.

[0025] The following is for reference. Figure 1 A method for online electrochemical impedance spectroscopy measurement of fuel cells according to embodiments of the present invention is described, such as... Figure 1 As shown, the method includes at least steps S1-S4.

[0026] Step S1: Obtain the initial values ​​of the parameters that affect the EIS test results when the fuel cell is started.

[0027] Specifically, during fuel cell system startup, initial values ​​of parameters affecting EIS test results, i.e., initial reference parameters, are calibrated and obtained. These initial reference parameters may include the initial stack temperature T0, initial stack polarization curve data, initial system load current I0, initial high-frequency impedance HFR0, and initial low-frequency impedance LFR0. The method of obtaining these initial values ​​is not limited. For example, the initial stack temperature T0 or initial system load current I0 can be acquired via sensors; the initial stack polarization curve data can be obtained by performing a polarization test on the stack and stored in memory for direct retrieval during online electrochemical impedance spectroscopy (EIS) measurements; or the initial high-frequency impedance HFR0 and initial low-frequency impedance LFR0 can be obtained through online EIS technology or specific excitation.

[0028] The stack temperature can be either the ambient temperature of the stack or the temperature at a critical point on the stack.

[0029] In the actual dynamic operation of fuel cells, considering that EIS test results are affected by multiple factors such as temperature, stack decay, flow channel blockage and variable load conditions, this application uses parameters such as stack temperature, stack voltage, stack current and low-frequency impedance as analytical features for online electrochemical impedance spectroscopy measurement.

[0030] Step S2: Obtain the measured values ​​of the parameters affecting the fuel cell during operation.

[0031] For example, during the operation of the fuel cell stack, key influencing parameters can be collected synchronously at high frequency through an integrated sensor array. Specifically, the measured values ​​of the fuel cell stack's operating parameters, i.e., the influencing parameters, can be collected in real time. These measured values ​​include the real-time ambient temperature (i.e., the measured value of the fuel cell stack temperature T'), the fuel cell stack operating voltage (i.e., the measured value of the fuel cell stack voltage U'), the fuel cell stack operating current (i.e., the measured value of the fuel cell stack current I'), the real-time high-frequency impedance value HFR', and the real-time low-frequency impedance value (i.e., the measured value of the low-frequency impedance LFR').

[0032] Step S3: Determine the target output value of each influencing parameter based on the initial value and the measured value of each influencing parameter.

[0033] Specifically, in related technologies, the fundamental dilemma of online EIS diagnosis lies in the fact that the measured impedance signal is a comprehensive result of the coupling and superposition of multiple factors such as the intrinsic decay of the fuel cell stack, ambient temperature, flow channel blockage, and dynamic operating conditions. Because the coupling effects of temperature, decay, blockage, and variable load conditions on EIS are not decoupled, it leads to the following inherent technical defects: 1. Because the above-mentioned interference factors are intertwined in dynamic operation, a single compensation method or fixed threshold will fail to measure the results due to the neglect of other variables; 2. The above-mentioned coupled signal is a mixture of multiple influences, which inevitably leads to distorted diagnostic results. It is impossible to accurately distinguish core faults such as membrane flooding, catalyst decay, or gas diffusion restriction, which directly leads to incorrect control strategies and ambiguous fault location. To address the aforementioned issues, this application no longer directly couples the measured values ​​of the parameters affecting EIS test results to determine the impedance. Instead, it first analyzes each parameter and isolates the influence of one or more variables among stack temperature, stack voltage, stack current, low-frequency impedance, and stack polarization state on the high-frequency impedance value. That is, based on the initial and measured values ​​of each parameter, the target output value of each parameter is determined, thereby identifying the impact of different parameters on the battery impedance state and eliminating coupling interference from external and operational variables.

[0034] For example, the method for determining the target output value of each influencing parameter can be found in [reference]. Figure 2 As shown, during the operation of the fuel cell stack, the measured values ​​of parameters affecting the EIS test results are continuously acquired, i.e., the system acquisition values. The real-time measured values ​​are compared with the calibrated initial values ​​to determine their consistency. Based on the comparison results, when the judgment result is consistent, the original signal, i.e., the initial value, is used as the valid output; when the judgment result is inconsistent, the measured values ​​are processed to remove the influence of operating variables such as load and temperature; finally, a conditioned impedance characteristic value, i.e., the target output value, is generated and output, which is strongly correlated only with the water content in the fuel cell stack membrane.

[0035] Step S4: Couple the target output values ​​of each influencing parameter to obtain the high-frequency impedance value.

[0036] For example, by coupling the target output values ​​of each influencing parameter determined in step S3 above, a pure impedance spectrum that only reflects the current water management or reaction kinetics can be obtained. This solves the problem that in actual vehicle or system operation, EIS test results are affected by the coupling of multiple complex factors, resulting in distorted test data that is difficult to use directly for accurate diagnosis. Ultimately, accurate online condition diagnosis is achieved, and fault warnings are executed based on the diagnostic results, thereby improving the reliability of battery use.

[0037] In some embodiments, when coupling the target output values ​​of each influencing parameter, the final high-frequency impedance value is also determined by combining the initial high-frequency impedance value at startup of the fuel cell system and the measured high-frequency impedance value during operation.

[0038] The online electrochemical impedance spectroscopy (EIS) measurement method for fuel cells according to embodiments of the present invention no longer directly couples the measured values ​​of the parameters affecting the EIS test results to determine the impedance. Instead, it first performs a stripping analysis on each parameter, that is, determines the target output value of each parameter based on its initial value and measured value. This allows the determination of the influence of different parameters on the battery impedance state. Then, the target output values ​​of each parameter are coupled to obtain a conditioned impedance characteristic value, i.e., a high-frequency impedance value, which is strongly correlated only with the water content in the fuel cell membrane. This enables accurate online condition diagnosis and fault warning, improving the reliability of battery condition diagnosis.

[0039] In some embodiments, the initial value includes the initial value of the fuel cell stack temperature, and the measured value includes the measured value of the fuel cell stack temperature. The target output value of each influencing parameter is determined based on the initial value and the measured value of each influencing parameter, including: determining the temperature difference between the initial value and the measured value of the fuel cell stack temperature; if the temperature difference is within a first preset tolerance range, the target output value of the fuel cell stack temperature is determined to be the initial value of the fuel cell stack temperature; if the temperature difference is not within the preset tolerance range, the target output value of the fuel cell stack temperature is determined to be the product of the temperature correction factor and the measured value of the fuel cell stack temperature.

[0040] The temperature correction factor is a pre-calibrated value based on the actual conditions, such as multiple tests on the changes in fuel cell performance at different temperatures. It is stored in memory so that it can be directly retrieved and used when performing temperature compensation.

[0041] Specifically, to eliminate the impact of ambient temperature fluctuations on the overall diagnostic model of online electrochemical impedance spectroscopy, this application compares the preprocessed real-time temperature signal, i.e., the measured value of the stack temperature, with the temperature calibration reference value stored in the fuel cell control unit, i.e., the initial value of the stack temperature. If the difference between the two is within the first preset tolerance range, it is determined that the current temperature conditions are consistent with the initial calibration conditions. Therefore, the initial value of the stack temperature can be directly called for subsequent calculations or as the output. Conversely, if the measured value of the stack temperature deviates significantly from the calibrated initial value of the stack temperature, i.e., the difference between the two is not within the first preset tolerance range, the temperature compensation algorithm is activated. This algorithm can determine the target output value based on a preset temperature-performance correlation mapping table, or set a compensation function to dynamically correct the temperature term, such as introducing a temperature correction factor of ε to correct the measured value of the stack temperature. Finally, the product of the temperature correction factor and the measured value of the stack temperature is used as the target output value. In this way, the current state of the stack is standardized to the equivalent level under the calibration conditions, eliminating the coupling effect of the stack temperature on EIS.

[0042] The first preset tolerance range can be set based on actual needs, for example, referring to... Figure 3 As shown, the first preset tolerance range can be directly set to 0. That is, it is determined whether the temperature difference is 0. If it is 0, the target output value T of the stack temperature is determined to be the initial value T0 of the stack temperature. If it is not 0, the target output value T of the stack temperature is determined to be the product of the temperature correction factor ε and the measured value T' of the stack temperature.

[0043] In some embodiments, the initial value includes the stack voltage polarization value, and the measured values ​​include the measured stack voltage and the measured stack current. The target output value of each influencing parameter is determined based on the initial and measured values, including: determining the voltage difference between the stack voltage polarization value and the measured stack voltage; determining the current change rate dI' / dt in real time based on the measured stack current; determining the stack decay state based on the voltage difference; determining the stack operating condition based on the current change rate; and determining the target output value of the stack voltage based on the stack decay state and operating condition. Thus, the measured stack voltage can comprehensively reflect the real-time response state and polarization level of the stack, enabling a two-tiered judgment from both the stack decay state and the stack operating condition, achieving decoupled analysis of the stack health state and dynamic operating condition.

[0044] Among them, the stack voltage polarization value can be understood as being determined based on the current stack operating conditions, such as output power, by consulting the initial stack polarization curve, which is the relationship curve between stack polarization voltage and stack polarization current.

[0045] In some embodiments, determining the battery stack attenuation state based on the voltage difference includes: if the voltage difference is within a second preset tolerance range, then determining the battery stack attenuation state as an unattenuated state; if the voltage difference is not within the second preset tolerance range, then determining the battery stack attenuation state as an attenuated state.

[0046] Specifically, the diagnosis of fuel cell stack lifespan degradation includes comparing the measured voltage value of the fuel cell stack with the voltage polarization value, i.e., calculating the voltage difference. If the absolute value of the voltage fluctuation, i.e. the voltage difference, is within the second preset tolerance range, it indicates that the fuel cell stack performance is stable and no significant lifespan degradation has occurred. Therefore, the fuel cell stack degradation state can be determined as an undegraded state. If the absolute value of the voltage fluctuation is not within the second preset tolerance range, it indicates that the fuel cell stack has entered the degradation state and its performance has undergone observable deterioration. Therefore, the fuel cell stack degradation state can be determined as a degraded state.

[0047] The second preset tolerance range can be set based on actual needs, for example, referring to... Figure 3 As shown, the second preset tolerance range is (-10mV, 10mV). That is, if the voltage difference does not exceed 10mV, the stack is determined to be in an un-degraded state; if the voltage difference exceeds 10mV, the stack is determined to be in a degraded state.

[0048] In some embodiments, determining the operating condition of the fuel cell stack based on the rate of change of current includes: if the rate of change of current is 0, then determining the operating condition as steady-state operation; if the rate of change of current is not 0, then determining the operating condition as variable load operation.

[0049] For example, based on the previous layer's judgment of the fuel cell stack's degradation state, the instantaneous rate of change of current, i.e., the rate of change of current dI' / dt, is further analyzed. The real-time determined rate of change of current is compared with a preset load change judgment threshold to identify whether the fuel cell stack is in a transient process of drastic load change. If the rate of change of current dI' / dt is 0, it is determined to be steady-state operation; if the rate of change of current dI' / dt is not 0, it is determined to be variable load operation.

[0050] In some embodiments, determining the target output value of the fuel cell voltage based on the fuel cell stack decay state and operating conditions includes: if the fuel cell stack decay state is undecayed and the operating condition is steady-state operation, then the target output value of the fuel cell voltage is determined to be the measured value of the fuel cell voltage; if the fuel cell stack decay state is undecayed and the operating condition is variable load operation, then the target output value of the fuel cell voltage is determined to be the product of the measured value of the fuel cell voltage and the variable load correction factor; if the fuel cell stack decay state is decayed and the operating condition is steady-state operation, then the target output value of the fuel cell voltage is determined to be the product of the measured value of the fuel cell voltage and the lifetime decay factor; if the fuel cell stack decay state is decayed and the operating condition is variable load operation, then the target output value of the fuel cell voltage is determined to be the product of the measured value of the fuel cell voltage, the variable load correction factor, and the lifetime decay factor.

[0051] Among them, the variable load correction factor and the lifetime decay factor are values ​​that have been pre-calibrated after multiple tests based on the actual conditions. They are stored in the memory so that they can be directly retrieved and used when performing fuel cell voltage compensation.

[0052] Specific, exemplary, reference Figure 3As shown, if the voltage difference is within the second preset tolerance range and the current change rate dI' / dt is 0, that is, when the fuel cell stack is in an undamaged state and the operating condition is steady-state, the measured value of the fuel cell stack voltage is directly used as the target output value of the fuel cell stack voltage. If the voltage difference is within the second preset tolerance range and the current change rate dI' / dt is not 0, that is, when the fuel cell stack is in an undamaged state and the operating condition is variable load operation, the variable load correction factor µ is called to compensate for the instantaneous polarization caused by the load change, thereby outputting the variable load corrected voltage value. In other words, the product of the measured value of the fuel cell stack voltage and the variable load correction factor is used as the target output value of the fuel cell stack voltage. If the voltage difference is not within the second preset tolerance range and the current change rate dI' / dt is 0, meaning the fuel cell stack is in a decayed state and the operating condition is steady-state, then the lifetime decay factor η is invoked to correct the voltage deviation caused by the degradation of the fuel cell stack's performance, thereby outputting a decay-corrected voltage value. In other words, the product of the measured fuel cell stack voltage and the lifetime decay factor η is used as the target output value of the fuel cell stack voltage. If the voltage difference is not within the second preset tolerance range and the current change rate dI' / dt is not 0, meaning the fuel cell stack is in a decayed state and the operating condition is variable load operation, then the lifetime decay factor η and the variable load correction factor µ are invoked to couple and correct the two effects, outputting a double-corrected voltage value. In other words, the product of the measured fuel cell stack voltage, the lifetime decay factor η, and the variable load correction factor µ is used as the target output value of the fuel cell stack voltage. Based on the above, by combining the judgment results of the stack decay state and operating conditions, different compensation factors are adaptively called to compensate the measured value of the stack voltage for different combined judgment results, so as to achieve accurate stripping of the voltage signal and eliminate the coupling effect of the stack voltage on the EIS.

[0053] In some embodiments, the initial value includes the initial value of low-frequency impedance, and the measured value includes the measured value of low-frequency impedance. The target output value of each influencing parameter is determined based on the initial value and the measured value of each influencing parameter, including: if the initial value of low-frequency impedance is consistent with the measured value of low-frequency impedance, then the target output value of low-frequency impedance is determined to be the initial value of low-frequency impedance; if the initial value of low-frequency impedance is inconsistent with the measured value of low-frequency impedance, then the target output value of low-frequency impedance is determined to be the product of the measured value of low-frequency impedance and the impedance correction factor.

[0054] The impedance correction factor is a pre-calibrated value obtained after multiple tests based on the actual conditions. It is stored in memory so that it can be directly retrieved and used when performing impedance compensation of the fuel cell stack.

[0055] Specifically, the low-frequency impedance signal is strongly correlated with the mass transfer process inside the fuel cell stack, especially the gas diffusion layer and flow channel state. Based on this, refer to Figure 3As shown, by comparing the measured low-frequency impedance value LFR' with the initial low-frequency impedance value LFR0, if they match, it indicates that the flow channel is unobstructed and there is no risk of blockage. Therefore, the low-frequency impedance calibration value can be directly output, with the initial low-frequency impedance value LFR0 used as the target output value. If the measured low-frequency impedance value LFR' deviates significantly from the initial low-frequency impedance value LFR0, a low-frequency impedance compensation algorithm is activated for correction. This involves introducing an impedance correction factor α, and using the product of the impedance correction factor α and the measured low-frequency impedance value LFR' as the target output value of the low-frequency impedance. Thus, the coupling effect of subsequent low-frequency impedance on the EIS is eliminated through this method.

[0056] In summary, the online electrochemical impedance spectroscopy (EIS) measurement method for fuel cells according to embodiments of the present invention establishes a joint EIS response model based on stack temperature, performance degradation, flow channel blockage index, and load change rate through calibration. Figure 3 The stripping algorithm shown in the model treats the coupling effects of multiple factors on impedance as a whole for system identification, rather than viewing them in isolation. Therefore, in practical online applications, the system simultaneously collects current influencing parameters and EIS spectra, and performs a one-time parallel calculation by calling this joint model. This simultaneously strips away interference components attributable to fuel cell temperature, long-term decay, physical blockage, and instantaneous load from the mixed impedance signal, outputting a pure impedance spectrum that reflects only the current water management or reaction kinetics. Ultimately, this achieves accurate online status diagnosis and fault warning. Furthermore, the analytical structure of this method is clear, and the processing is easily implemented on the vehicle controller, enabling online EIS diagnosis to move from vague trend judgments to precise quantitative status analysis, greatly improving the real-time performance and reliability of fault warning and water management optimization.

[0057] A second aspect of the present invention provides an online electrochemical impedance spectroscopy (EIS) measurement device for a fuel cell, comprising: a first acquisition module for acquiring initial values ​​of influencing parameters affecting EIS test results during fuel cell startup, the influencing parameters including at least stack temperature, stack voltage, stack current, and low-frequency impedance; a second acquisition module for acquiring measured values ​​of the influencing parameters during fuel cell operation; a determination module for determining target output values ​​of each influencing parameter based on the initial values ​​and measured values ​​of each influencing parameter; and a coupling module for coupling the target output values ​​of each influencing parameter to obtain a high-frequency impedance value.

[0058] It should be noted that the specific implementation of the fuel cell online electrochemical impedance spectroscopy measurement device in this embodiment of the invention is similar to the specific implementation of the fuel cell online electrochemical impedance spectroscopy measurement method in any of the above embodiments of the invention. For details, please refer to the description of the fuel cell online electrochemical impedance spectroscopy measurement method. To reduce redundancy, it will not be repeated here.

[0059] The online electrochemical impedance spectroscopy (EIS) measurement device for fuel cells in this invention does not directly couple the measured values ​​of the parameters affecting EIS test results to determine the impedance. Instead, it first performs a stripping analysis on each parameter, that is, it determines the target output value of each parameter based on the initial value and the measured value of each parameter. This allows it to determine the influence of different parameters on the battery impedance state. Then, it couples the target output values ​​of each parameter to obtain a conditioned impedance characteristic value, i.e., a high-frequency impedance value, which is strongly correlated only with the water content in the fuel cell membrane. This enables accurate online condition diagnosis and fault warning, improving the reliability of battery condition diagnosis.

[0060] A third aspect of the present invention provides an electronic device, such as... Figure 4 As shown, the electronic device 10 includes at least one processor 1 and a memory 2 communicatively connected to at least one processor 1.

[0061] The memory 2 stores a computer program that can be executed by at least one processor 1. When the at least one processor 1 executes the computer program, it implements the online electrochemical impedance spectroscopy measurement method for fuel cells described in the above embodiment.

[0062] It should be noted that the specific implementation of the electronic device 10 in this embodiment of the invention is similar to the specific implementation of the online electrochemical impedance spectroscopy measurement method for fuel cells in any of the above embodiments of the invention. For details, please refer to the description of the online electrochemical impedance spectroscopy measurement method for fuel cells. To reduce redundancy, it will not be repeated here.

[0063] The electronic device 10 according to an embodiment of the present invention can achieve accurate online EIS diagnosis and improve the reliability of battery status diagnosis.

[0064] A fourth aspect of the present invention provides a computer storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the online electrochemical impedance spectroscopy measurement method for fuel cells described above.

[0065] In the description of this specification, any process or method described in the flowcharts or otherwise herein may be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order according to the functions involved, as will be understood by those skilled in the art to which embodiments of the invention pertain.

[0066] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0067] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any of the following techniques known in the art, or a combination thereof: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0068] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0069] Furthermore, the functional units in the various embodiments of the present invention can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0070] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

[0071] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example.

[0072] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A method for online electrochemical impedance spectroscopy measurement of fuel cells, characterized in that, include: The initial values ​​of the parameters affecting the EIS test results during fuel cell startup are obtained, including at least the stack temperature, stack voltage, stack current, and low-frequency impedance. Obtain the measured values ​​of the influencing parameters during fuel cell operation; The target output value of each influencing parameter is determined based on the initial value and the measured value of each influencing parameter. The target output values ​​of each influencing parameter are coupled to obtain the high-frequency impedance value.

2. The method for online electrochemical impedance spectroscopy measurement of fuel cells according to claim 1, characterized in that, The initial values ​​include the initial value of the fuel cell stack temperature, and the measured values ​​include the measured value of the fuel cell stack temperature. The target output value of each influencing parameter is determined based on the initial values ​​and measured values ​​of each influencing parameter, including: Determine the temperature difference between the initial value of the fuel cell stack temperature and the measured value of the fuel cell stack temperature; If the temperature difference is within the first preset tolerance range, then the target output value of the stack temperature is determined to be the initial value of the stack temperature; If the temperature difference is not within the preset tolerance range, the target output value of the stack temperature is determined to be the product of the temperature correction factor and the measured value of the stack temperature.

3. The method for online electrochemical impedance spectroscopy measurement of fuel cells according to claim 1, characterized in that, The initial values ​​include the stack voltage polarization value, and the measured values ​​include the measured stack voltage value and the measured stack current value. Based on the initial values ​​and measured values ​​of each influencing parameter, the target output value of each influencing parameter is determined, including: Determine the voltage difference between the stack voltage polarization value and the measured stack voltage value; The rate of change of current is determined based on the measured value of the current in the fuel cell stack. The stack decay state is determined based on the voltage difference; The operating conditions of the fuel cell stack are determined based on the current change rate. The target output value of the fuel cell voltage is determined based on the fuel cell decay state and the operating conditions.

4. The method for online electrochemical impedance spectroscopy measurement of fuel cells according to claim 3, characterized in that, Determining the stack degradation state based on the voltage difference includes: If the voltage difference is within the second preset tolerance range, then the stack attenuation state is determined to be an unattenuated state. If the voltage difference is not within the second preset tolerance range, then the stack degradation state is determined to be a degradation state.

5. The method for online electrochemical impedance spectroscopy measurement of fuel cells according to claim 4, characterized in that, The operating conditions of the fuel cell stack are determined based on the current change rate, including: If the rate of change of current is 0, then the operating condition is determined to be steady-state operation; If the current change rate is not 0, then the operating condition is determined to be variable load operation.

6. The method for online electrochemical impedance spectroscopy measurement of fuel cells according to claim 5, characterized in that, Determining the target output value of the fuel cell voltage based on the fuel cell decay state and the operating conditions includes: If the fuel cell stack decay state is undecayed and the operating condition is steady-state operation, then the target output value of the fuel cell stack voltage is determined to be the measured value of the fuel cell stack voltage. If the fuel cell stack decay state is undecayed and the operating condition is variable load operation, then the target output value of the fuel cell stack voltage is determined to be the product of the measured value of the fuel cell stack voltage and the variable load correction factor. If the fuel cell stack is in a decayed state and the operating condition is steady-state operation, then the target output value of the fuel cell stack voltage is determined to be the product of the measured value of the fuel cell stack voltage and the lifetime decay factor. If the fuel cell stack is in a decayed state and the operating condition is variable load operation, then the target output value of the fuel cell stack voltage is determined to be the product of the measured value of the fuel cell stack voltage, the variable load correction factor, and the lifetime decay factor.

7. The method for online electrochemical impedance spectroscopy measurement of fuel cells according to claim 1, characterized in that, The initial values ​​include the initial value of low-frequency impedance, and the measured values ​​include the measured value of low-frequency impedance. The target output value of each influencing parameter is determined based on the initial values ​​and measured values ​​of each influencing parameter, including: If the initial value of the low-frequency impedance is consistent with the measured value of the low-frequency impedance, then the target output value of the low-frequency impedance is determined to be the initial value of the low-frequency impedance. If the initial value of the low-frequency impedance is inconsistent with the measured value of the low-frequency impedance, then the target output value of the low-frequency impedance is determined to be the product of the measured value of the low-frequency impedance and the impedance correction factor.

8. An online electrochemical impedance spectroscopy measurement device for fuel cells, characterized in that, include: The first acquisition module is used to acquire the initial values ​​of the parameters that affect the EIS test results when the fuel cell is started. The parameters include at least the stack temperature, stack voltage, stack current and low-frequency impedance. The second acquisition module is used to acquire the measured values ​​of the influencing parameters during fuel cell operation; The determination module is used to determine the target output value of each influencing parameter based on the initial value and the measured value of each influencing parameter. The coupling module is used to couple the target output values ​​of various influencing parameters to obtain high-frequency impedance values.

9. An electronic device, characterized in that, include: At least one processor; A memory that is communicatively connected to at least one of the processors; The memory stores a computer program that can be executed by at least one of the processors, and when the at least one processor executes the computer program, it implements the online electrochemical impedance spectroscopy measurement method for fuel cells according to any one of claims 1-7.

10. A computer storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the online electrochemical impedance spectroscopy measurement method for fuel cells according to any one of claims 1-7.

Images