Real-time analysis system and method for impedance state of fuel cell

Abstract

The invention discloses a fuel cell impedance state real-time analysis system and method, and relates to the field of fuel cell detection, the system comprises an AC excitation source, a current and voltage acquisition module and an upper computer; the upper computer is respectively connected with the alternating current excitation source and the current and voltage acquisition module, and is used for controlling the alternating current excitation source to apply sine wave excitation signals with different frequencies to a fuel cell stack; the current and voltage acquisition module is used for acquiring current signals and voltage signals of actual load pulling of the fuel cell under different frequencies; the upper computer is used for calculating an impedance spectrum according to the current signal and the voltage signal, determining an equivalent circuit model of the fuel cell based on the impedance spectrum and performing parameter identification, and the equivalent circuit model after parameter identification is used for analyzing the impedance state of the fuel cell in real time. According to the invention, after the measurement of the impedance spectrum is completed, the impedance data can be processed and analyzed immediately, and the safe and stable operation of the fuel cell is ensured.

Description

Technical Field

[0001] The present application relates to the field of fuel cell detection, and in particular to a system and method for real-time analysis of the impedance state of a fuel cell. Background Art

[0002] Fuel cells have problems such as insufficient reliability and poor durability. These problems not only reduce the performance of the battery, but also greatly shorten its service life. Therefore, it is very important to monitor the status of the fuel cell in real time and adjust the operating conditions to ensure the safe and stable operation of the fuel cell and extend the service life of the fuel cell.

[0003] The impedance of a fuel cell can be used as a sign to indirectly reflect the changes in various parameters inside the fuel cell. After measuring the impedance spectrum of the fuel cell, the impedance spectrum data needs to be analyzed to obtain the internal status information of the fuel cell. Although real-time online measurement of fuel cell impedance is currently possible, due to limitations in the software platform, the impedance data still needs to be processed offline, making it impossible to perform real-time analysis of the impedance state and complete subsequent fault diagnosis and adjustment of operating conditions. Summary of the invention

[0004] Based on the above problems, the present application provides a real-time analysis system and method for the impedance state of a fuel cell.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] In the first aspect, the present application provides a real-time analysis system for the impedance state of a fuel cell, comprising: an AC excitation source, a current and voltage acquisition module, and a host computer; the host computer is respectively connected to the AC excitation source and the current and voltage acquisition module, the host computer is used to control the AC excitation source to apply sinusoidal wave excitation signals of different frequencies to the fuel cell stack, and the current and voltage acquisition module is used to collect the current signal and voltage signal actually pulled by the fuel cell at different frequencies; the host computer is used to calculate the impedance spectrum according to the current signal and the voltage signal, determine the equivalent circuit model of the fuel cell based on the impedance spectrum and perform parameter identification, and the equivalent circuit model after parameter identification is used to analyze the impedance state of the fuel cell in real time.

[0007] In a second aspect, the present application provides a method for real-time analysis of the impedance state of a fuel cell, which is applied to the above-mentioned real-time analysis system for the impedance state of a fuel cell, and the method comprises:

[0008] Applying sinusoidal wave excitation signals of different frequencies to the fuel cell stack;

[0009] Collect the current signal and voltage signal of the actual load of the fuel cell at different frequencies;

[0010] Calculating an impedance spectrum according to the current signal and the voltage signal;

[0011] determining an equivalent circuit model of the fuel cell based on the impedance spectrum;

[0012] Performing parameter identification on the equivalent circuit model;

[0013] The impedance state of the fuel cell is analyzed in real time through the equivalent circuit model after parameter identification.

[0014] According to the specific embodiments provided in this application, this application has the following technical effects:

[0015] The present application provides a real-time analysis system and method for the impedance state of a fuel cell, which integrates commonly used impedance analysis tools into a host computer for impedance measurement. After completing the measurement of the impedance spectrum, the host computer can immediately process and analyze the impedance data, which helps to achieve online fault diagnosis and real-time adjustment of operating conditions of the fuel cell based on the impedance state, ensure the safe and stable operation of the fuel cell, and increase the service life of the fuel cell. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 A structural block diagram of a fuel cell impedance state real-time analysis system provided in one embodiment of the present application;

[0018] Figure 2 A schematic flow chart of a method for real-time analysis of the impedance state of a fuel cell provided in one embodiment of the present application;

[0019] Figure 3 It is a schematic diagram of the relationship between relaxation time distribution and equivalent circuit model;

[0020] Figure 4 Schematic diagram for determining the initial values ​​of parameters of the second-order RC model. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0022] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0023] In an exemplary embodiment, Figure 1 As shown, a fuel cell impedance state real-time analysis system is provided, comprising: an AC excitation source 1, a current and voltage acquisition module 2 and a host computer 3.

[0024] The host computer 3 is connected to the AC excitation source 1 and the current and voltage acquisition module 2 respectively, and the host computer 3 is used to control the AC excitation source 1 to apply sinusoidal wave excitation signals of different frequencies to the fuel cell stack 4. The current and voltage acquisition module 2 is used to collect the current signal and voltage signal of the actual load of the fuel cell at different frequencies. The host computer 3 is used to calculate the impedance spectrum according to the current signal and the voltage signal, determine the equivalent circuit model of the fuel cell based on the impedance spectrum and perform parameter identification, and the equivalent circuit model after parameter identification is used to analyze the impedance state of the fuel cell in real time.

[0025] Furthermore, the host computer 3 includes:

[0026] The impedance spectrum calculation module is connected to the current and voltage acquisition module and is used to calculate the impedance of the fuel cell based on the current signal and the voltage signal to obtain the impedance spectrum of the fuel cell.

[0027] The equivalent circuit model determination module is connected to the impedance spectrum calculation module and is used to determine the equivalent circuit model of the fuel cell based on the impedance spectrum.

[0028] A parameter identification module is connected to the equivalent circuit model determination module and is used to perform parameter identification on the equivalent circuit model.

[0029] Furthermore, the equivalent circuit model determination module specifically includes:

[0030] The relaxation time distribution calculation unit is used to calculate the relaxation time distribution of the impedance spectrum.

[0031] A peak number determination unit is used to determine the peak number in the impedance spectrum based on the relaxation time distribution.

[0032] The equivalent circuit model determination unit is used to determine the equivalent circuit model of the fuel cell according to the number of peaks.

[0033] The present application integrates commonly used impedance analysis tools into the host computer of impedance measurement, so that the host computer can immediately process and analyze the impedance data after completing the measurement of the impedance spectrum, thereby being able to perform online fault diagnosis on the fuel cell based on the impedance state analyzed in real time, and adjust the operating conditions in real time, thereby ensuring the safe and stable operation of the fuel cell and increasing the service life of the fuel cell.

[0034] Based on the same inventive concept, in an exemplary embodiment, a method for real-time analysis of the impedance state of a fuel cell is provided, and the method is applied to the above-mentioned real-time analysis system for the impedance state of a fuel cell.

[0035] like Figure 2 As shown, the method includes:

[0036] S1: Apply sinusoidal wave excitation signals of different frequencies to the fuel cell stack.

[0037] The host computer controls the AC excitation source to inject sinusoidal wave excitation signals of different frequencies into the fuel cell stack.

[0038] S2: Collect the current signal and voltage signal of the actual load of the fuel cell at different frequencies.

[0039] S3: Calculating an impedance spectrum according to the current signal and the voltage signal.

[0040] The actual current signal of the fuel cell load and the feedback voltage signal are collected, and the impedance of the fuel cell at different frequencies is calculated in the host computer to obtain the impedance spectrum.

[0041] S4: Determine the equivalent circuit model of the fuel cell based on the impedance spectrum. Specifically, it includes: S41: calculate the relaxation time distribution of the impedance spectrum; S42: determine the number of peaks in the impedance spectrum based on the relaxation time distribution; S43: determine the equivalent circuit model of the fuel cell according to the number of peaks.

[0042] The present application utilizes the distribution of relaxation time (DRT) analysis to select the equivalent circuit model, which can improve the accuracy of the constructed model and improve the accuracy and interpretability of the parameter identification results.

[0043] In a specific embodiment, step S41 includes: determining a relaxation time distribution function based on the impedance spectrum; and discretizing the relaxation time distribution function to obtain a relaxation time distribution.

[0044] The relaxation time distribution (DRT) of the impedance spectrum is calculated in the host computer. The relaxation time distribution function and impedance have the following functional relationship:

[0045]

[0046] Where γ(lnτ) is the relaxation time distribution function, Z(f) is the impedance of the fuel cell at frequency f, τ is the time constant, and R0 is the ohmic resistance.

[0047] The specific calculation steps are as follows:

[0048] (1) Discretization of γ(lnτ).

[0049]

[0050] Among them, φ μ (|lnτ-lnτ m |) is a central time constant τ m and the discretized basis function of the shape parameter μ, while φ μ (x) can be expressed using the Gaussian function exp(-(μx) 2 ).

[0051]

[0052] Objective function:

[0053]

[0054] in,

[0055]

[0056]

[0057] S is the objective function; n is the current iteration number; N is the total number of frequency points contained in the impedance spectrum; w is the weighting coefficient, subscript r represents the real part; subscript i represents the imaginary part, λ is the regularization parameter, and x is the desired x m The column vector is composed of , B is the regularization matrix, m is the number of discretization iterations, and M is the number of basis functions used in the discretization.

[0058] Join λx T The Mx term is to reduce the DRT oscillation caused by the ill-posed problem by adding an additional penalty function. The objective function involves two parameters λ and μ. The larger the λ, the smaller the DRT oscillation, but it may cause over-smoothing and loss of relevant information; while the parameter μ affects the shape of the DRT peak. Generally speaking, if μ is large, the DRT peak will be very sharp and thin, which may easily lead to oscillation. If μ is small, the DRT peak will be very wide, which may lead to information loss. Therefore, in order to obtain good results, the setting of these two parameters is very important. The default value of λ is generally 1×10 -3 ; μ is 1, and then adjusted at any time according to the results.

[0059] In a specific embodiment, step S43 includes: when the number of the peaks is 2, determining that the equivalent circuit model of the fuel cell is a second-order RC model; when the number of the peaks is 3, determining that the equivalent circuit model of the fuel cell is a third-order RC model.

[0060] According to the DRT results, the number of time constants (peaks) contained in the impedance spectrum is identified. Figure 3 The peaks of DRT in the impedance spectrum shown are 2. Usually, the equivalent circuit model of the fuel cell is a second-order RC model (two time constants) or a third-order RC model (three time constants). If more than three time constants are identified, it is considered that the parameters for calculating DRT are improperly set and need to be reset in the host computer.

[0061] The second-order RC model consists of an ohmic resistor R0 connected in series with two RC links. Its impedance expression is:

[0062]

[0063] The real part is:

[0064]

[0065] The imaginary part is:

[0066]

[0067] The third-order RC model consists of an ohmic resistor R0 connected in series with three RC links. Its impedance expression is:

[0068]

[0069] The real part is:

[0070]

[0071] The imaginary part is:

[0072]

[0073] S5: performing parameter identification on the equivalent circuit model.

[0074] This embodiment adopts the Nelder-Mead simplex algorithm to perform parameter identification on the equivalent circuit model, specifically including: determining the initial values ​​of the parameters of the equivalent circuit model according to the impedance spectrum; constructing an initial simplex according to the initial values ​​of the parameters and the number of parameters to be identified of the equivalent circuit model; calculating the objective function value of each point in the initial simplex; calculating the center of gravity of the remaining points except the point with the minimum objective function value; using the reflection coefficient, reflecting the point with the minimum objective function value in the direction of the center of gravity to obtain a reflection point, and calculating the objective function value of the reflection point; updating the initial simplex based on the objective function value of the reflection point until the convergence condition is met, and completing the parameter identification.

[0075] The Nelder-Mead simplex algorithm is a direct search method for multidimensional unconstrained minimization. The minimized objective function (i.e., the calculation formula for the objective function value) is:

[0076]

[0077] In the formula, Z real and Z imag are the real and imaginary parts of the impedance measurement, respectively, and Z real ' and Z imag ' are respectively the real part and imaginary part of the impedance estimation value of the equivalent circuit model determined in step S4.

[0078] In a specific embodiment, the specific calculation process is as follows:

[0079] (1) Confirm the initial values ​​of the parameters of the equivalent circuit model. The selection of the initial values ​​of the parameters directly affects the results of the subsequent parameter identification algorithm. If the initial values ​​of the parameters are not selected appropriately, the algorithm is likely to fall into a local optimal solution. For a second-order RC model, Figure 4As shown, when ω approaches infinity, the real part Z'(ω) is approximately equal to the ohmic resistance R0, and the imaginary part Z"(ω) is approximately equal to 0. Therefore, the real part corresponding to the point where it intersects with the real axis in the high-frequency band can be used as the initial value of the ohmic resistance R0. When ω approaches 0, the real part Z'(ω) is approximately equal to R0+R1+R2, and the imaginary part Z"(ω) is approximately equal to 0, so the value corresponding to the intersection of the impedance spectrum with the real axis in the low-frequency band can be used as the sum of the initial values ​​of the three resistances. Similarly, at the intersection of the extended arc of the first arc and the real axis, it can be approximately regarded as the initial value of R0+R1. At the highest points P1 and P2 of the arc, the first-order derivative value is 0, and the values ​​of C1 and C2 obtained at the two maximum points can be used as the initial values. For the third-order RC model, in actual tests, the impedance spectrum of the fuel cell does not show obvious three arcs. However, through the analysis of DRT results, the third time constant often appears in the high-frequency band. Therefore, when setting the initial values ​​of the parameters of the third-order RC model, on the basis of the original second-order RC model, the initial value C3 of the newly added RC parallel link is set to be equal to C1 of the high-frequency arc, and the initial value R3 is equal to R1, which can obtain better fitting results.

[0080] (2) Construct an initial simplex. Construct an initial simplex according to the number of parameters to be identified. Take the second-order RC model as an example. The second-order RC model has 5 parameters to be identified, so the initial simplex consists of 6 points in the 5-dimensional space. constitutes and satisfies:

[0081]

[0082] Determined by step (1), the remaining points are generated according to the following formula:

[0083]

[0084] in is a set of unit vectors in 5-dimensional space, which is the space The standard basis of i It is a positive number and its size can be determined according to the scale of the optimization problem.

[0085] (3) Calculate the objective function value for 6 points And sort them in order from small to large according to the objective function value:

[0086]

[0087] The worst point is deduct Then calculate the centroid of the remaining 5 points The calculation formula is as follows:

[0088]

[0089] (4) Using the reflection coefficient ρ>0, Direction to the worst point Reflect and get the reflection point

[0090]

[0091] Reflection coefficient ρ = 1, and calculate the objective function value of the reflection point

[0092] (5) If use Replace the old Construct a new simplex, complete this reflection operation, and jump to step (10).

[0093] (6) If exist Extend the direction to get the extension point

[0094]

[0095] χ>1 is the extension coefficient, take χ=2, and calculate the objective function value of the extension point like Use Replace the old Construct a new simplex, complete this reflection operation, and jump to step (10); if use Replace the old Construct a new simplex, complete this reflection operation, and jump to step (10).

[0096] (7) If Perform external contraction to obtain the contraction point

[0097]

[0098] 0<γ<1 is the contraction coefficient, take γ=0.5, and calculate the objective function value of the contraction point Jump to step (9).

[0099] (8) If Perform internal contraction to obtain the contraction point

[0100]

[0101] 0<γ<1 is the contraction coefficient, take γ=0.5, and calculate the objective function value of the contraction point Jump to step (9).

[0102] (9) If use Replace the old Construct a new simplex and jump to step (10); if It means that the shrinkage failed, and the compression operation is performed, and only the The other points in the simplex are The distance is halved and a new simplex is constructed:

[0103]

[0104] σ=0.5 is the compression coefficient, and the process jumps to step (10).

[0105] S510: Determine whether the convergence condition is met. If it is met:

[0106]

[0107] Then the iteration is stopped, ε is the convergence condition, ε=0.00001, and the output is the final parameter identification result; otherwise, continue iterating and execute step (3).

[0108] S6: Real-time analysis of the impedance state of the fuel cell through the equivalent circuit model after parameter identification.

[0109] The fuel cell impedance state obtained through real-time analysis can be used for online fault diagnosis and real-time operation condition adjustment of the fuel cell, ensuring the safe and stable operation of the fuel cell and extending the service life of the fuel cell.

[0110] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0111] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0112] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0113] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0114] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A fuel cell impedance state real-time analysis system, characterized in that: include: An AC excitation source, a current and voltage acquisition module and a host computer; the host computer is connected to the AC excitation source and the current and voltage acquisition module respectively, the host computer is used to control the AC excitation source to apply sinusoidal wave excitation signals of different frequencies to the fuel cell stack, and the current and voltage acquisition module is used to collect current signals and voltage signals of the actual load of the fuel cell at different frequencies; the host computer is used to calculate an impedance spectrum according to the current signal and the voltage signal, determine an equivalent circuit model of the fuel cell based on the impedance spectrum and perform parameter identification, and the equivalent circuit model after parameter identification is used to analyze the impedance state of the fuel cell in real time.

2. The fuel cell impedance state real-time analysis system according to claim 1, characterized in that: The host computer comprises: An impedance spectrum calculation module, connected to the current and voltage acquisition module, for calculating the impedance of the fuel cell based on the current signal and the voltage signal to obtain an impedance spectrum of the fuel cell; an equivalent circuit model determination module, connected to the impedance spectrum calculation module, and used to determine the equivalent circuit model of the fuel cell based on the impedance spectrum; A parameter identification module is connected to the equivalent circuit model determination module and is used to perform parameter identification on the equivalent circuit model.

3. The fuel cell impedance state real-time analysis system according to claim 2, characterized in that: The equivalent circuit model determination module specifically includes: A relaxation time distribution calculation unit, used for calculating the relaxation time distribution of the impedance spectrum; A peak number determination unit, used to determine the peak number in the impedance spectrum based on the relaxation time distribution; The equivalent circuit model determination unit is used to determine the equivalent circuit model of the fuel cell according to the number of peaks.

4. A method for real-time analysis of the impedance state of a fuel cell, characterized in that: The fuel cell impedance state real-time analysis method is applied to the fuel cell impedance state real-time analysis system according to any one of claims 1 to 3, and the method comprises: Applying sinusoidal wave excitation signals of different frequencies to the fuel cell stack; Collect the current signal and voltage signal of the actual load of the fuel cell at different frequencies; Calculating an impedance spectrum according to the current signal and the voltage signal; determining an equivalent circuit model of the fuel cell based on the impedance spectrum; Performing parameter identification on the equivalent circuit model; The impedance state of the fuel cell is analyzed in real time through the equivalent circuit model after parameter identification.

5. The method for real-time analysis of fuel cell impedance state according to claim 4, characterized in that: Determining an equivalent circuit model of a fuel cell based on the impedance spectrum specifically includes: Calculating the relaxation time distribution of the impedance spectrum; determining the number of peaks in the impedance spectrum based on the relaxation time distribution; An equivalent circuit model of the fuel cell is determined according to the number of peaks.

6. The method for real-time analysis of fuel cell impedance state according to claim 5, characterized in that: Calculating the relaxation time distribution of the impedance spectrum specifically includes: Construct the objective function and use the regression algorithm to solve the basis function; determining a relaxation time distribution function based on the basis functions and the impedance spectrum; A relaxation time distribution is determined based on the relaxation time distribution function.

7. The method for real-time analysis of fuel cell impedance state according to claim 5, characterized in that: Determining an equivalent circuit model of a fuel cell according to the number of wave peaks specifically includes: When the number of the wave peaks is 2, it is determined that the equivalent circuit model of the fuel cell is a second-order RC model, which is composed of an ohmic resistor and two RC links in series; When the number of the wave peaks is 3, it is determined that the equivalent circuit model of the fuel cell is a third-order RC model, which is composed of an ohmic resistor and three RC links connected in series.

8. The method for real-time analysis of fuel cell impedance state according to claim 4, characterized in that: The Nelder-Mead simplex algorithm is used to perform parameter identification on the equivalent circuit model.

9. The method for real-time analysis of fuel cell impedance state according to claim 8, characterized in that: The Nelder-Mead simplex algorithm is used to perform parameter identification on the equivalent circuit model, specifically including: Determining initial values ​​of parameters of the equivalent circuit model according to the impedance spectrum; Constructing an initial simplex according to the initial values ​​of the parameters and the number of parameters to be identified of the equivalent circuit model; Calculating the objective function value of each point in the initial simplex; Calculate the centroid of the remaining points except the point with the minimum objective function value; Using the reflection coefficient, the point with the minimum objective function value is reflected in the direction of the center of gravity to obtain a reflection point, and the objective function value of the reflection point is calculated; The initial simplex is updated based on the objective function value of the reflection point until the convergence condition is met, and the parameter identification is completed.

10. The method for real-time analysis of fuel cell impedance state according to claim 9, characterized in that: The calculation formula of the objective function value is: in, For point The objective function value, Z real and Z imag are the real and imaginary parts of the impedance measurement, respectively, and Z real ' and Z imag ' are the real and imaginary parts of the impedance estimate of the equivalent circuit model, k is the current iteration number, and K is the total number of frequency points included in the impedance spectrum.

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