Diagnostic method, program product, and fuel cell system for fuel cells

Abstract

The present invention relates to a diagnostic method for a fuel cell, comprising the following steps: applying an excitation signal to the fuel cell, acquiring a response signal of the fuel cell; obtaining a high-frequency resistance of the fuel cell to be processed based on the excitation signal and the response signal; dividing the high-frequency resistance to be processed into a plurality of segments each having a predetermined time length, and detecting the maximum and minimum values of the high-frequency resistance to be processed within each segment; when the range between the maximum and minimum values does not exceed a predetermined threshold, calculating an output value between the maximum and minimum values based on the high-frequency resistance to be processed, and using the output value as the target high-frequency resistance. The humidity level inside the fuel cell is evaluated based on the target high-frequency resistance. The present disclosure further relates to a program product and a fuel cell system. Stable and accurate diagnostic results for the fuel cell can be obtained, thereby avoiding undesired fault misdiagnosis and improving the operational performance of the fuel cell.

Description

[0001] DIAGNOSTIC METHOD, PROGRAM PRODUCT, AND FUEL CELL SYSTEM FOR FUEL CELLS

[0002] Technical Field

[0003] The present disclosure relates to the technical field of fuel cells, and more particularly, to a diagnostic method for fuel cells. The invention further relates to a corresponding computer program product and a corresponding fuel cell system.

[0004] Background

[0005] In recent years, with the development of society and the economy, increasing attention has been paid to issues such as air pollution and energy loss. A fuel cell is a highly efficient power generation device that directly converts the chemical energy of fuel and oxidant into electrical energy via an electrochemical reaction, without undergoing a combustion process. Since the main reaction product is water and virtually no harmful gases are emitted, fuel cells possess significant advantages in terms of cleanliness and environmental protection, and are particularly advantageous for use in the automotive field.

[0006] In a fuel cell, the proton exchange membrane (PEM) serves as a core component, functioning to conduct protons and directly affecting the performance and lifespan of the fuel cell. To maintain optimal output performance of the fuel cell, the proton exchange membrane must be appropriately humidified. Here, the humidity of the proton exchange membrane affects both the proton conductivity and the dissolution and diffusion of oxygen within the membrane. Excessive humidity can cause "flooding" faults, impeding the transport of gaseous reactants to the reaction sites and reducing the active area of the catalyst due to water coverage, thereby significantly increasing activation and concentration losses. Conversely, insufficient humidity can cause "membrane dry-out" faults, leading to increased membrane resistance and greater heat generation during operation, which further reduces energy conversion efficiency and may result in more severe membrane dry-out or even membrane tearing, severely impacting output performance and remaining service life. Therefore, realtime monitoring of the internal humidity level of the fuel cell during operation is necessary.

[0007] In the prior art, to assess the internal humidity level of a fuel cell, in addition to technical solutions employing humidity sensors arranged in the gas circuit, there are also solutions utilizing Electrochemical Impedance Spectroscopy (EIS) technology. In EIS technology, an alternating disturbance signal is applied to the fuel cell and the response signal is analyzed to obtain the high-frequency resistance of the fuel cell. This high-frequency resistance is formed by a combination of factors such as internal contact resistance, diffusion resistance, charge transfer impedance, and parasitic inductance, and is mainly influenced by the membrane conductivity of the proton exchange membrane. The high- frequency resistance thus reflects the humidity level inside the fuel cell.

[0008] However, in the practical application of EIS technology for real-time diagnostics of fuel cells, when the stack current or stack voltage of the fuel cell changes, the high-frequency resistance calculated using EIS technology exhibits significant and non-negligible oscillations. This leads to inaccurate and unstable diagnostic results, and may cause undesired fault inputs, thereby adversely affecting the operational performance of the fuel cell.

[0009] Summary of the Invention

[0010] Therefore, the objective of the present disclosure is to provide an improved diagnostic method for fuel cells, which can effectively reduce the impact caused by changes in operating parameters, thereby obtaining stable and accurate diagnostic results for the fuel cell, avoiding undesired fault misdiagnosis, and improving the operational performance of the fuel cell. A further objective of the present invention is to provide a corresponding computer program product and a corresponding fuel cell system.

[0011] According to a first aspect of the present disclosure, a diagnostic method for a fuel cell is provided, wherein the diagnostic method comprises at least the following steps:

[0012] S1 : applying an excitation signal to the fuel cell and acquiring a response signal from the fuel cell;

[0013] S2: obtaining a high-frequency resistance to be processed of the fuel cell based on the excitation signal and the response signal;

[0014] S3: dividing the high-frequency resistance to be processed into a plurality of segments each having a predetermined time length (At), and detecting the maximum and minimum values of the high-frequency resistance to be processed within each segment; when the range between the maximum value and the minimum value does not exceed a predetermined threshold, calculating an output value between the maximum and minimum values of the high- frequency resistance to be processed in the corresponding segment, and using the output value as the target high-frequency resistance (Rc) of the segment;

[0015] S5: evaluating the humidity level inside the fuel cell based on the target high-frequency resistance.

[0016] Compared with the prior art, in the diagnostic method for a fuel cell according to the present disclosure, the high-frequency resistance to be processed is first obtained using EIS technology based on the excitation and response signals. The high-frequency resistance to be processed is then further divided into multiple segments according to time, and the maximum and minimum values within each segment are detected.

[0017] When the range between the maximum and minimum values does not exceed a predetermined threshold, an output value within the segment is calculated based on the high- frequency resistance to be processed in the corresponding segment, and this output value, which lies between the maximum and minimum values, is used as the target high-frequency resistance for that segment. The internal humidity level of the fuel cell is then evaluated based on the target high-frequency resistance. Thus, even when the stack current or stack voltage of the fuel cell changes, it is possible to reliably eliminate severe transient oscillations in the calculated high-frequency resistance and minimize calculation deviations caused by changes in operating conditions, thereby always accurately assessing the internal humidity level of the fuel cell and avoiding undesired fault misdiagnosis, thus improving the operational performance of the fuel cell.

[0018] According to a second aspect of the present disclosure, a computer program product is provided, comprising a computer program which, when executed by one or more processors, enables the processor(s) to perform the diagnostic method according to the present disclosure.

[0019] According to a third aspect of the present invention, a fuel cell system is provided, characterized in that the fuel cell system comprises at least:

[0020] - a fuel cell stack, the fuel cell stack having a plurality of fuel cell units arranged in a stack;

[0021] - a cathode gas circuit, the cathode gas circuit being in communication with the cathode side of the fuel cell units; an anode gas circuit, the anode gas circuit being in communication with the anode side of the fuel cell units; an excitation unit, the excitation unit being configured to apply an excitation signal to the fuel cell stack;

[0022] - an acquisition unit, the acquisition unit being configured to detect a current signal and / or a voltage signal of the fuel cell stack; and

[0023] - a control unit, the control unit being connected to the excitation unit and the acquisition unit, and being configured to implement the diagnostic method according to the present disclosure using the computer program product of the present disclosure, so as to evaluate the internal humidity level of the fuel cell stack.

[0024] Brief Description of the Drawings

[0025] In the following, the present disclosure is described in greater detail with reference to the accompanying drawings to provide a better understanding of its principles, features, and advantages. The accompanying drawings include the following:

[0026] FIG. 1 is a schematic flowchart illustrating a diagnostic method for a fuel cell according to an exemplary embodiment of the present disclosure;

[0027] FIG. 2 is a schematic graph illustrating various parameters of the diagnostic method according to an exemplary embodiment of the present disclosure;

[0028] FIG. 3 is a schematic block diagram illustrating a fuel cell system according to an exemplary embodiment of the present disclosure.

[0029] Detailed Description of the Embodiments

[0030] To provide a clearer understanding of the technical problems, technical solutions, and beneficial technical effects to be addressed by the present invention, the following detailed description of the present invention will be provided with reference to the accompanying drawings and multiple exemplary examples.

[0031] The present specification provides method operation steps as described in the embodiments or flowcharts; however, based on routine or non-inventive work, more or fewer operation steps may be included. The sequence of steps enumerated in the embodiments is merely one possible order among many for performing the steps and does not represent the sole execution sequence.

[0032] FIG. 1 is a schematic flowchart illustrating a diagnostic method for a fuel cell according to an exemplary embodiment of the present disclosure. FIG. 2 is a schematic graph illustrating various parameters of the diagnostic method according to an exemplary embodiment of the present disclosure. Within the framework of the present disclosure, the term "fuel cell” may refer to either a fuel cell stack or a fuel cell unit.

[0033] As shown in FIGS. 1 and 2, the diagnostic method for a fuel cell according to the present disclosure comprises at least the following steps:

[0034] S1 : applying an excitation signal to the fuel cell by means of an excitation unit, wherein the excitation signal is an alternating current (AC) disturbance signal, such as an AC current or AC voltage, and is superimposed onto the direct current (DC) current or DC voltage of the fuel cell; then acquiring the response signal of the fuel cell, specifically, when the excitation signal is an AC current, the response signal is the output voltage of the fuel cell, and when the excitation signal is an AC voltage, the response signal is the output current of the fuel cell. The excitation signal may, for example, be configured in the form of a single sine wave, a superposition of multiple sine waves, or a pseudo-random binary sequence.

[0035] S2: Based on the excitation signal and the response signal, obtaining a high-frequency resistance of the fuel cell to be processed, wherein, the high-frequency resistance to be processed may be the initial high-frequency resistance Ra, directly calculated from the excitation and response signals, which is particularly applicable in cases where signal noise is low or real-time requirements are high. Alternatively, the high-frequency resistance to be processed may be an intermediate high-frequency resistance Rb obtained by filtering the initial high-frequency resistance Ra, which is directly calculated from the excitation and response signals, thereby eliminating transient oscillations and obtaining a smoothed, denoised high- frequency resistance.

[0036] In particular, a first-order inertial filter, such as a PT1 filter, may be used to filter the initial high- frequency resistance Ra to eliminate high-frequency noise interference in the output signal; of course, other filters considered meaningful by those skilled in the art, such as a first-order low- pass filter or an exponentially weighted moving average filter, may also be considered. To calculate the initial high-frequency resistance Ra, the excitation signal and the response signal are first subjected to Fourier transformation to obtain complex-domain current and voltage values with real and imaginary parts at different frequencies. The initial high-frequency resistance Ra can be directly calculated by dividing the voltage and current values in the high- frequency range. Alternatively, the resistance value at each frequency can be obtained by dividing the voltage and current values at each frequency, and the electrochemical impedance spectrum can be derived from the resistance values at various frequencies. The initial high- frequency resistance Ra can then be selected from the electrochemical impedance spectrum according to the high-frequency range. The electrochemical impedance spectrum, in addition to the high-frequency resistance, also includes medium-frequency and low-frequency resistances. The medium-frequency resistance reflects the kinetic characteristics of the electrode reaction, especially the performance of the catalytic layers of the cathode and anode. When issues such as catalyst layer aging, degradation, or uneven catalyst distribution occur, the medium-frequency resistance increases significantly. The low-frequency resistance reflects reactant transport and water management issues; when there is insufficient reactant supply or flooding, the low-frequency resistance increases significantly.

[0037] S3: dividing the high-frequency resistance to be processed into a plurality of segments each having a predetermined time length (At), and detecting the maximum and minimum values of the high-frequency resistance to be processed within each segment; when the range between the maximum value and the minimum value does not exceed a predetermined threshold, calculating an output value between the maximum and minimum values of the high- frequency resistance to be processed in the corresponding segment, and using the output value as the target high-frequency resistance (Rc) of the segment. Specifically, the output value is selected from the following group: the average of the maximum and minimum values, the median value of the high-frequency resistance to be processed in the segment, or the moving average value of the high-frequency resistance to be processed in the segment. This enables the acquisition of smoothed data for the target high-frequency resistance Rc using different processing methods as needed, further reducing the influence of noise.

[0038] S4: The internal humidity level of the fuel cell is evaluated based on the target high- frequency resistance Rc. A relational model between the high-frequency resistance and the humidity level may be pre-established based on experimental and / or empirical data. This relational model can fit a curve of humidity level versus high-frequency resistance. By inputting the target high-frequency resistance Rc into the relational model, the internal humidity level of the fuel cell can be determined. In particular, the humidity level is inversely proportional to the target high-frequency resistance Rc, meaning that the greater the target high-frequency resistance Rc, the lower the humidity level, and vice versa.

[0039] By way of example, as shown in FIG. 2, taking the DC current I of the fuel cell as an example, when the DC current I changes, for example, increases at a specific slope, the initial high-frequency resistance Ra directly calculated from the excitation and response signals in step S2 exhibits severe oscillations during and shortly after the change in DC current I due to instability in the corresponding electrical signals. This oscillation causes a significant deviation from the actual high-frequency resistance. By filtering the initial high-frequency resistance Ra, an intermediate high-frequency resistance Rb is obtained, which eliminates noise interference and is significantly smoother compared to the initial high-frequency resistance Ra. In this case, the intermediate high-frequency resistance Rb serves as the high-frequency resistance to be processed for the fuel cell. Then, in step S3, the intermediate high-frequency resistance Rb, i.e. , the high-frequency resistance to be processed, is divided into multiple segments by time t, each segment having a predetermined time length At. The predetermined time length may be pre-calibrated based on experimental and / or empirical data. The maximum and minimum values of the intermediate high-frequency resistance Rb are detected within each segment. When the range between the maximum and minimum values does not exceed a predetermined threshold, an output value within the range of the maximum and minimum values is calculated for the corresponding segment based on the high-frequency resistance to be processed in that segment. This output value is used as the target high-frequency resistance Rc for that segment. The target high-frequency resistance remains stable in each segment and avoids undesired excessive deviations caused by sudden changes in the DC current I of the fuel cell. The above description likewise applies to situations where the DC voltage of the fuel cell changes. The predetermined threshold may, for example, be determined according to the magnitude or rate of change of the fuel cell’s DC current or DC voltage.

[0040] By way of example, in step S3, the range between the maximum and minimum values of the intermediate high-frequency resistance Rb in each segment is calculated. If the range between the maximum and minimum values in a segment exceeds the predetermined threshold, the output value of the adjacent segment (immediately preceding in time) is used as the output value for that segment. This avoids erroneous recording of extreme values of high-frequency resistance caused by changes in the operating parameters of the fuel cell.

[0041] By way of example, in step S1 , the amplitude of the excitation signal applied depends on the direct current (DC) or direct voltage of the fuel cell, wherein the amplitude of the excitation signal may be the value of the DC current or DC voltage multiplied by a specific coefficient. For example, when the DC current of the fuel cell is 10A, the amplitude of the applied alternating current (AC) is 1A. Alternatively, when the DC voltage of the fuel cell is 2.5V, the amplitude of the applied AC voltage is 1V. Of course, other proportional relationships deemed meaningful by those skilled in the art may also be considered.

[0042] By way of example, as shown in FIG. 1 , the diagnostic method additionally comprises step S5: Adjusting the supply gas humidity of the fuel cell according to the humidity level obtained in step S4, so as to maintain the internal humidity level of the fuel cell within a desired range, wherein the supply gas humidity may be the humidity of the cathode gas, such as air, or the humidity of the anode gas, such as hydrogen. This enables the fuel cell to maintain optimized operational performance.

[0043] By way of example, the diagnostic method according to the present invention may be implemented in at least one, and in particular all, of the following situations: when the fuel cell is started; when detection of the humidity level of the fuel cell is initiated; when the load of the fuel cell changes; when the fuel cell is shut down. In the above situations, the current and / or voltage applied to the fuel cell will change, which may readily cause oscillations in the calculation results of the high-frequency resistance. By means of the diagnostic method according to the present invention, transient oscillations can be eliminated and calculation deviations can be minimized as much as possible. Of course, it is also possible for the diagnostic method according to the present invention to be continuously implemented during the operation of the fuel cell.

[0044] FIG. 3 illustrates a schematic block diagram of a fuel cell system 100 according to an exemplary embodiment of the present invention. Here, the fuel cell system 100 may, for example, be used in a vehicle.

[0045] As shown in FIG. 3, the fuel cell system 100 comprises a fuel cell stack 10, the fuel cell stack having a plurality of fuel cell units 11 arranged in a stacked manner. These fuel cell units 11 may be connected in series or in parallel as required and the generated electrical energy is output via an external circuit.

[0046] As shown in FIG. 3, the fuel cell system 100 comprises a cathode gas circuit 20 in communication with the cathode side of the fuel cell stack 10 and an anode gas circuit 30 in communication with the anode side of the fuel cell stack 10. The cathode gas circuit 20 is configured to supply cathode gas, such as air, to the cathode of the fuel cell units 11 and, for example, comprises an air compressor 21. The air compressor is configured to drive and pressurize the cathode gas. The anode gas circuit 30 is configured to supply anode gas, such as hydrogen, to the anode of the fuel cell units 11 and, for example, comprises a hydrogen recirculation pump 31. The hydrogen recirculation pump is configured to reintroduce unused hydrogen discharged from the fuel cell stack 10 back into the anode supply line.

[0047] As shown in FIG. 3, the fuel cell system 100 comprises an excitation unit 40, which is configured to apply an excitation signal to the fuel cell stack 10. The excitation signal may be an alternating current or alternating voltage. In particular, the excitation unit 40 is a DC / DC converter, which is capable of converting and stabilizing the output voltage of the fuel cell stack 10 and adjusting the current flowing through the fuel cell stack 10. The excitation signal can be superimposed onto the DC voltage or DC current of the fuel cell stack 10 via the DC / DC converter.

[0048] As shown in FIG. 3, the fuel cell system 100 comprises an acquisition unit 50, which is configured to detect the current signal and / or voltage signal of the fuel cell stack 10. The acquisition unit 50 may be arranged at the current collector plate of the fuel cell stack 10.

[0049] As shown in FIG. 3, the fuel cell system 100 comprises a control unit 60, which is connected to the excitation unit 40 and the acquisition unit 50, respectively, to send instructions regarding the excitation signal to the excitation unit 40 and to obtain response signals from the acquisition unit 50. The control unit 60 is configured to implement the diagnostic method according to the present invention by means of a computer program product, so as to assess the internal humidity level of the fuel cell stack 10. The computer program product comprises a computer program, which, when executed by one or more processors, enables the processor(s) to perform the diagnostic method according to the present invention.

[0050] By way of example, the control unit 60 is configured to adjust the supply gas humidity of the cathode gas circuit 20 and / or the anode gas circuit 30 according to the assessed humidity level. For this purpose, a humidifier may be provided in the cathode gas circuit 20 and / or the anode gas circuit 30, the humidifier receiving control instructions from the control unit 60 to specifically change the supply gas humidity, thereby ensuring optimized operational performance of the fuel cell system 100.

[0051] The foregoing description of embodiments only describes the present disclosure within the framework of the examples. Certainly, as long as it is technically meaningful, the various features of the embodiments may be freely combined with each other without departing from the framework of the present invention.

[0052] For those skilled in the art, other advantages and alternative embodiments of the present invention are apparent. Therefore, in terms of its broader significance, the present invention is not limited to the specific details, representative structures, and exemplary examples shown and described. Conversely, those skilled in the art may make various modifications and alternatives without departing from the essential spirit and scope of the present invention.

Claims

CLAIMS1. A diagnostic method for a fuel cell, characterized in that the diagnostic method comprises at least the following steps:S1 : applying an excitation signal to the fuel cell and acquiring a response signal from the fuel cell;S2: obtaining a high-frequency resistance to be processed of the fuel cell based on the excitation signal and the response signal;S3: dividing the high-frequency resistance to be processed into a plurality of segments each having a predetermined time length (At), and detecting the maximum and minimum values of the high-frequency resistance to be processed within each segment; when the range between the maximum value and the minimum value does not exceed a predetermined threshold, calculating an output value between the maximum and minimum values of the high- frequency resistance to be processed in the corresponding segment, and using the output value as the target high-frequency resistance (Rc) of the segment;S4: evaluating the humidity level inside the fuel cell based on the target high-frequency resistance (Rc).

2. The diagnostic method according to claim 1 , characterized in that, in step S3, when the range does not exceed the predetermined threshold, the output value is selected from the following group: the average of the maximum and minimum values, the median value of the high-frequency resistance to be processed in the segment, the moving average value of the high-frequency resistance to be processed in the segment.

3. The diagnostic method according to claim 1 or 2, characterized in that, in step S3, when the range of a segment is greater than the predetermined threshold, the output value of the preceding segment is used as the output value for the current segment.

4. The diagnostic method according to any one of the preceding claims, characterized in that, in step S2, the high-frequency resistance to be processed is an initial high-frequency resistance (Ra) directly calculated from the excitation signal and the response signal; or in step S2, the high-frequency resistance to be processed is an intermediate high- frequency resistance (Rb) obtained by filtering the initial high-frequency resistance (Ra), wherein the initial high-frequency resistance (Ra) is directly calculated from the excitation signal and the response signal.

5. The diagnostic method according to claim 4, characterized in that, the excitation signal and the response signal are subjected to Fourier transform to obtain current and voltage values in the complex domain at different frequencies, and the initial high-frequency resistance (Ra) is calculated based on the voltage and current values in the high-frequency range; and / or the initial high-frequency resistance (Ra) is filtered based on a first-order inertial filter to obtain the intermediate high-frequency resistance (Rb).

6. The diagnostic method according to any one of the preceding claims, characterized in that, the humidity level is inversely proportional to the target high-frequency resistance (Rc); and / or the diagnostic method further comprises step S5: adjusting the supply gas humidity of the fuel cell according to the humidity level, so as to maintain the humidity level within a desired range.

7. The diagnostic method according to any one of the preceding claims, characterized in that, the diagnostic method is implemented in at least one of the following situations: when the fuel cell is started; when detection of the humidity level of the fuel cell is initiated; when the load of the fuel cell changes; when the fuel cell is shut down; and / or the excitation signal is an alternating current or alternating voltage, wherein the amplitude of the excitation signal depends on the direct current or direct voltage of the fuel cell.

8. A computer program product, comprising a computer program, wherein when the computer program is executed by one or more processors, the processor is enabled to perform the diagnostic method according to any one of claims 1 to 7.

9. A fuel cell system (100), characterized in that the fuel cell system (100) at least comprises:- a fuel cell stack (100), the fuel cell stack (100) having a plurality of fuel cell units (11) arranged in a stack;- a cathode gas circuit (20), the cathode gas circuit (20) being in communication with the cathode side of the fuel cell units (11);- an anode gas circuit (30), the anode gas circuit (30) being in communication with theanode side of the fuel cell units (11);- an excitation unit (40), the excitation unit (40) being configured to apply an excitation signal to the fuel cell stack (10);- an acquisition unit (50), the acquisition unit (50) being configured to detect a current signal and / or a voltage signal of the fuel cell stack (10); and- a control unit (60), the control unit (60) being connected to the excitation unit (40) and the acquisition unit (50), and being configured to implement the diagnostic method according to any one of claims 1 to 7 by using the computer program product according to claim 8, so as to evaluate the humidity level inside the fuel cell stack (10).

10. The fuel cell system (100) according to claim 9, characterized in that, the excitation unit (40) is a DC / DC converter; and / or the control unit (60) is configured to adjust the supply gas humidity of the cathode gas circuit (20) and / or the anode gas circuit (30) according to the humidity level.

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