A method for judging the surge boundary of a fuel cell air compressor in real time

Abstract

The application discloses a kind of fuel cell air compressor surge boundary multi-source real-time judgment method, belong to fluid compression mechanical system field.The application is introduced after filtering processing to the signal collected by sensor, and surge variance for representing surge fluctuation degree is introduced.Sampling frequency determined by filter is used to determine the length of moving time window.In moving time window, the variance of air compressor pressure and current signal is calculated respectively.The temperature at the beginning of time window is subtracted from the temperature at the end of time window to obtain the temperature rise value in time window, to realize the real-time acquisition and calculation of air compressor pressure signal surge variance, current signal surge variance and temperature rise value.The application constructs a surge identification method combined with redundant multi-source information, and when at least two of the three parameters of air compressor pressure surge variance, current signal surge variance and temperature rise value exceed the corresponding threshold, it is judged that surge occurs, to improve the reliability and real-time performance of air compressor surge online identification.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of fluid compression mechanical system, and relates to a multi-source real-time judgment method for surge boundary of a fuel cell air compressor. BACKGROUND

[0002] The fuel cell air compressor plays a vital role in the fuel cell system, which is mainly responsible for compressing the air entering the fuel cell stack to provide sufficient pressure and flow for the cathode of the stack to ensure that the chemical reaction of the fuel cell can proceed efficiently, and its performance directly affects the performance and life of the entire fuel cell system. Among them, the centrifugal air compressor has the advantages of light weight, simple structure, high pressure ratio, easy maintenance, etc., and is the most widely used form of fuel cell air compressor. However, the centrifugal air compressor also has some obvious shortcomings, such as the surge problem, and the existence of the surge line puts higher requirements on the optimal control of the air compressor.

[0003] When the centrifugal air compressor is at a certain speed, the air flow is reduced to below a certain value, the work becomes unstable, the airflow pulsates strongly, causing the entire air compressor to vibrate violently, and even causing damage, and emitting a sharp periodic noise, which is called surge. The surge phenomenon is extremely harmful to the air compressor and even the entire fuel cell system, and in severe cases, it can cause damage to the air compressor and even threaten personnel safety. Therefore, it is necessary to accurately demarcate the surge boundary during performance testing.

[0004] When testing the performance of the fuel cell air compressor, it is necessary to detect the surge in real time according to the working condition and demarcate the surge boundary, but most of the current performance tests are still manually operated, and the judgment of the surge also relies on the experience of the test personnel, which has a large error and uncertainty; the existing recognition algorithm also has the problem of not being able to balance speed and accuracy, and when encountering sensor failure, changes in environmental factors, or other non-surge failures of the air compressor, etc., it is very likely to cause the pre-designed detection algorithm to fail, misjudge the occurrence of surge, and sacrifice a certain accuracy. In order to improve the accuracy, more complex algorithms are designed to ensure the accuracy of surge recognition, but complex algorithms bring greater computational load, and detection speed cannot be guaranteed. Therefore, in order to balance speed and accuracy, the dimension of the information needs to be increased, which will bring information redundancy, which can be used to eliminate uncertainty. SUMMARY

[0005] In view of the above problems, the purpose of the present application is to provide a multi-source real-time judgment method for the surge boundary of a fuel cell air compressor, which can realize online monitoring of the surge of the fuel cell air compressor, improve the real-time performance and accuracy of the surge recognition of the air compressor, and improve the accuracy of the surge boundary test of the air compressor.

[0006] The purpose of the application is achieved by the following technical solutions:

[0007] The application discloses a multi-source real-time judgment method for surge boundary of a fuel cell air compressor, and comprises the following steps:

[0008] S1: performing a surge test on a fuel cell air compressor measurement and control platform, and collecting compressor inlet pressure, inlet temperature and motor current. Sensors are arranged on double-wire flow meters at the air compressor inlet, wherein the tail probe of the temperature sensor is arranged at the center of the flow meter and faces the air compressor inlet, and the air compressor inlet temperature, pressure and current signals are measured respectively. During the operation of the fuel cell system, the surge boundary of the air compressor is gradually approached by changing the flow and pressure ratio of the air compressor, and the inlet temperature, pressure and current signals of the air compressor are dynamically collected to realize the collection of surge signals.

[0009] S2: Due to the influence of instrument measurement error, environmental factors, electromagnetic interference and signal transmission process during the test, high-frequency noise is generated, which affects the accuracy of signal analysis and processing. The original signals of the current and the inlet pressure are subjected to first-order low-pass filtering processing, and the inlet temperature signal is not processed, so as to obtain the current and the inlet pressure signals subjected to first-order low-pass filtering and reduce the influence of high-frequency noise.

[0010] S2.1: According to the surge signal of the compressor measured in step 1, a complete surge waveform data is intercepted, a complete surge waveform data is defined as consisting of m sampling points, and then an m-dimensional signal vector is formed.

[0011]

[0012] Wherein, s(0), s(1), …, s(m-1) are the values of the m sampling points contained in a complete surge signal waveform.

[0013] S2.2: The original signals of the current and the inlet pressure are subjected to first-order low-pass filtering processing by using a first-order low-pass filter shown in the following formula to obtain the current signal and the inlet pressure signal subjected to first-order low-pass filtering.

[0014] y n =ax n +(1-a)y n-1

[0015] Wherein, y n is the output value of this filtering, y n-1 is the output value of the last filtering, x n is the sampling value, T s is the sampling period, unit: second, f c is the cut-off frequency, unit: hertz, and a is in the range of [0, 1].

[0016] S3: Constructing a surge variance for characterizing the degree of surge fluctuation, respectively calculating the surge variance of the air compressor pressure and current signals within each time window, making the calculation of the surge variance more localized, and improving the recognition accuracy of the surge. The moving time window length ΔX is determined according to the sampling frequency set by the filter. The air compressor pressure and current signal variance is calculated within the moving time window, respectively, to obtain the air compressor pressure signal surge variance S P and the current signal surge variance S I , that is, the fluctuation characteristics of the air compressor pressure and current signals are obtained. The temperature rise value ΔT within the time window is obtained by subtracting the temperature at the beginning of the time window from the temperature at the end of the time window.

[0017] S3.1: When the surge occurs, the air compressor inlet pressure and current will produce a larger surge fluctuation, and the surge variance is introduced to characterize the degree of surge fluctuation. The calculation formula of the surge variance is:

[0018]

[0019] Wherein, c i is the sampling value at time i, m is the number of sampling points in the preset time period, is the average value of the sampling data in this period.

[0020] Select the time window, and the range of each variance statistics m is determined by the length of the time window. The window is a signal range size used for surge variance calculation, that is, the surge variance of the air compressor pressure and current signals within each time window is calculated, making the calculation of the surge variance more localized, and improving the recognition accuracy of the surge.

[0021] S3.2: The moving time window length ΔX is determined according to the sampling frequency set by the filter

[0022]

[0023] Wherein, f is the signal sampling frequency, and m is the number of sampling points contained in a complete surge waveform data.

[0024] S3.3: According to 3.1, the variance of the air compressor pressure and current signals within the time window is calculated, respectively, to obtain the air compressor pressure signal surge variance and the current signal surge variance, that is, the fluctuation characteristics of the air compressor pressure and current signals are obtained.

[0025] S3.4: The temperature signal will not fluctuate obviously when the surge occurs, but there will be a significant temperature rise phenomenon, therefore, the temperature rise value within the time window is calculated, wherein ΔT=T2-T1, T1 represents the temperature at the beginning of the time window, and T2 represents the temperature at the end of the time window.

[0026] S4: According to step S3, the pressure surge variance and the current signal surge variance of the air compressor when the surge occurs at different rotating speeds are measured respectively, and the rotating speed-threshold value relationship of the pressure signal and the current signal is obtained by polynomial fitting. At different rotating speeds, the corresponding pressure signal variance threshold M p and the current signal variance threshold M I for judging whether the surge occurs are obtained. T A fixed temperature threshold M n is set to judge whether the surge occurs.

[0027] S4.1: The threshold value is related to the rotating speed. The greater the rotating speed, the higher the corresponding threshold value should be. In the early performance test stage, the pressure variance and the current variance when the surge occurs at different rotating speeds are measured respectively, and there is a unique polynomial L 2 (x) = b0 + b1x + b2x n +…+b n x n , so that L j (x j ) = y j (j = 1, 2, …, n)

[0028] Where x j represents different rotating speeds, and y p represents the variance value at different rotating speeds.

[0029] The rotating speed-threshold value relationship of the pressure signal and the current signal is obtained, and at different rotating speeds, the corresponding pressure signal variance threshold M I and the current signal variance threshold M T for judging whether the surge occurs are obtained.

[0030] S4.2: When the surge occurs, the change of temperature affected by system vibration can be ignored. A fixed temperature threshold M p is set to judge whether the surge occurs.

[0031] S5: The surge signal described in step S1 is collected in real time by the sensor, the length of the time window is determined by step 2, and the air compressor pressure surge variance, the current signal surge variance and the temperature rise value in the time window are calculated according to step S3. The air compressor pressure surge variance in the time window calculated in step S3 is compared with the pressure signal variance threshold M I ; the current signal surge variance in the time window calculated in step S3 is compared with the current signal variance threshold M TThe comparison is carried out; when at least two of the three parameters of the air compressor pressure surge variance, the current signal surge variance and the temperature rise value exceed the corresponding threshold value, it is judged that the surge occurs, otherwise, the surge does not occur, that is, the multi-source real-time judgment of the fuel cell air compressor surge boundary is realized.

[0032] Beneficial effects:

[0033] 1. The multi-source real-time judgment method of the fuel cell air compressor surge boundary disclosed in the application carries out time domain analysis on the collected air compressor inlet temperature, pressure and current signal, finds that the pressure and current will produce periodic pulsation signals when the electric air compressor surges at each speed, and the temperature will rise at the same time, and it is concluded that the signal characteristics of the pressure and current when surging are low-frequency and large-amplitude pulsation signals. After filtering the signals collected by the sensor, the surge variance used to represent the surge fluctuation degree is introduced, and the surge variance of the air compressor pressure and current signal in each time window is calculated respectively, so that the calculation of the surge variance is more localized, and the identification accuracy of the surge is improved.

[0034] 2. The multi-source real-time judgment method of the fuel cell air compressor surge boundary disclosed in the application, based on the beneficial effect 1, determines the moving time window length ΔX according to the sampling frequency set by the filter. The air compressor pressure and current signal variance is calculated in the moving time window, and the air compressor pressure signal surge variance and current signal surge variance are obtained respectively, that is, the fluctuation characteristics of the air compressor pressure and current signal are obtained. The temperature rise value in the time window is obtained by subtracting the temperature at the beginning of the time window from the temperature at the end of the time window, and the real-time collection and calculation of the air compressor pressure signal surge variance, current signal surge variance and temperature rise value in the time window can be realized.

[0035] 3. The multi-source real-time judgment method of the fuel cell air compressor surge boundary disclosed in the application, based on the beneficial effect 2, obtains the speed-threshold relationship of the pressure signal and the current signal through polynomial fitting, and at different speeds, the corresponding pressure signal variance threshold M p and current signal variance threshold M I for judging whether the surge occurs are obtained according to the speed-threshold relationship, and a fixed temperature threshold M T is set. The redundant multi-source information combined surge identification method is constructed by using the redundant information generated by different sensors measuring the same characteristics, when at least two of the three parameters of the air compressor pressure surge variance, the current signal surge variance and the temperature rise value exceed the corresponding threshold value, it is judged that the surge occurs, and the reliability and real-time performance of the air compressor surge online identification are improved. BRIEF DESCRIPTION OF DRAWINGS

[0036] Figure 1This is a schematic diagram of a multi-source real-time judgment method for surge boundary of a fuel cell air compressor disclosed in this invention.

[0037] Figure 2 This refers to the inlet pressure signal of the air compressor at different speeds.

[0038] Figure 3 This refers to the inlet current signal of the air compressor at different speeds.

[0039] Figure 4 This refers to the inlet temperature signal of the air compressor at different speeds.

[0040] Figure 5 The pressure signal and the variance of the pressure signal when surge occurs.

[0041] Figure 6 The current signal and the variance of the current signal when surge occurs.

[0042] Figure 7 This includes sensor signals and alarm information at 50,000 RPM. Detailed Implementation

[0043] To better illustrate the purpose and advantages of the present invention, the invention will be further described below in conjunction with the accompanying drawings and examples.

[0044] Example 1:

[0045] like Figure 1 As shown in the figure, this embodiment discloses a multi-source real-time judgment method for surge boundary of fuel cell air compressor, and the specific implementation steps are as follows:

[0046] S1: A surge test was conducted on the fuel cell air compressor control platform, and the compressor inlet pressure, inlet temperature, and motor current were collected. Sensors were arranged on the nylon flow meter at the air compressor inlet, with the tail probe of the temperature sensor positioned at the center of the flow meter, facing the air compressor inlet. The air compressor inlet temperature, pressure, and current signals were measured respectively. During the operation of the fuel cell system, the air compressor's flow rate and pressure ratio were changed to gradually approach the surge boundary of the air compressor, and the air compressor inlet temperature, pressure, and current signals were dynamically collected at a sampling frequency of f = 100Hz to achieve surge signal acquisition.

[0047] S2: Due to instrument measurement errors, environmental factors, electromagnetic interference, and the influence of signal transmission during testing, high-frequency noise is generated, affecting the accuracy of signal analysis and processing. The raw inlet pressure and current signals are subjected to a first-order low-pass filter, while the inlet temperature signal remains unprocessed. This yields the first-order low-pass filtered current and inlet pressure signals. The inlet pressure signal is as follows: Figure 2 As shown, the inlet current signal is as follows Figure 3 As shown, the inlet temperature signal is as follows: Figure 4 As shown.

[0048] S2.1: According to the compressor surge signal measured in step 1, a complete surge waveform data is intercepted, and a complete surge waveform data is defined by 50 sampling points, then a 50-dimensional signal vector is formed

[0049]

[0050] Wherein, s(0), s(1), …, s(49) are the values of the 50 sampling points contained in a complete surge signal waveform.

[0051] S2.2 The first-order low-pass filter shown in the following formula is used to perform first-order low-pass filtering on the original signals of the inlet temperature and pressure, and the first-order low-pass filtered inlet temperature signal and inlet pressure signal are obtained.

[0052] y n = ax n +(1-a)y n-1

[0053] Wherein, y n is the output value of this filtering, y n-1 is the output value of the last filtering, x n is the sampling value, T s is the sampling period, unit is second, f c is the cut-off frequency, unit is hertz.

[0054] T s = 0.01s, f c = 275Hz, a = 0.054 is calculated.

[0055] S3: Constructing a surge variance for representing the degree of surge fluctuation, calculating the surge variance of the air compressor pressure and current signal in each time window, making the calculation of the surge variance more localized, and improving the recognition accuracy of the surge. The length of the moving time window ΔX is determined according to the sampling frequency set by the filter. The air compressor pressure and current signal variance is calculated in the moving time window, respectively, to obtain the air compressor pressure signal surge variance S P and the current signal surge variance S I , that is, the fluctuation characteristics of the air compressor pressure and current signal. The temperature rise value ΔT in the time window is obtained by subtracting the temperature at the beginning of the time window from the temperature at the end of the time window.

[0056] S3.1: When surge occurs, the air compressor inlet pressure and current will produce large surge fluctuations, and the surge variance is introduced to represent the degree of surge fluctuation. The calculation formula of the surge variance is:

[0057]

[0058] wherein c i is the sampling value at time i, m is the number of sampling points in the preset time period, is 50, is the average of the sampling data in this period of time.

[0059] The appropriate time window is selected, and the statistical range m of each variance is determined by the length of the time window. The window is the size of the signal range used when calculating the surge variance, i.e. the surge variance is calculated for the air compressor pressure and current signals in each time window, so that the calculation of the surge variance is more localized, and the recognition accuracy of the surge is improved.

[0060] S3.2: Determine the length of the moving time window ΔX according to the sampling frequency set by the filter

[0061]

[0062] wherein f = 100 Hz, m = 50, and the length of the time window is calculated to be in the range of 1.5-2 seconds. In this experiment, the length of the time window ΔX = 1.5 s.

[0063] S3.3: According to 3.1, the variance of the air compressor pressure and current signals in the time window is calculated respectively, and the surge variance of the air compressor pressure and current signals is obtained respectively, as shown in Figure 5 , 6 , i.e. the fluctuation characteristics of the air compressor pressure and current signals are obtained.

[0064] S3.4: The temperature signal does not fluctuate significantly when surge occurs, but there is a significant temperature rise. Therefore, the temperature rise value in the time window is calculated, wherein ΔT = T2-T1, T1 represents the temperature at the beginning of the time window, and T2 represents the temperature at the end of the time window.

[0065] S4: According to step S3, the surge variance of the air compressor pressure and current signals when surge occurs at different speeds is measured, and the speed-threshold relationship of the pressure signal and current signal is obtained by polynomial fitting. At different speeds, the corresponding pressure signal variance threshold M p and current signal variance threshold M I for judging whether surge occurs are obtained according to the speed-threshold relationship. A fixed temperature threshold M T is set to judge whether surge occurs.

[0066] S4.1: The selection of the threshold is related to the speed. The greater the speed, the higher the corresponding threshold should be. In the early performance test stage, the pressure variance and current variance when surge occurs at different speeds are measured, and there is a unique polynomial L n(x) = b0 + b1x + b2x 2 +…+b n x n , so that L n (x j ) = y j (j = 1, 2, …, n)

[0067] where x j represents different rotating speeds, and y j represents variance values at different rotating speeds.

[0068] The function result after fitting of the pressure link is:

[0069] L(x) = 0.000563x 4 + 0.00132x 3 + 0.0024356x 2 + 0.0030659x + 0.002186

[0070] The function result after fitting of the pressure link is:

[0071] L(x) = 5 × 10 -7 x-0.001

[0072] The rotating speed-threshold value relationship of the pressure signal and the current signal is obtained, and at different rotating speeds, corresponding pressure signal variance threshold values M p and current signal variance threshold values M I for judging whether surge occurs are obtained.

[0073] S4.2: When surge occurs, the change of temperature affected by system vibration can be ignored, and a fixed temperature threshold value M T is set, and through multiple comparisons, the threshold value M T = 0.06.

[0074] S5: Real-time acquisition of the surge signal described in step S1 is performed by the sensor, the length of the time window is determined by step 2, the air compressor pressure surge variance, the current signal surge variance and the temperature rise value in the time window are calculated according to step S3; the air compressor pressure surge variance in the time window calculated in step S3 is compared with the pressure signal variance threshold value M p ; the current signal surge variance in the time window calculated in step S3 is compared with the current signal variance threshold value M I ; and the temperature rise value in the time window calculated in step S3 is compared with the temperature threshold value M TThe comparison is made; when at least two of the three parameters of the air compressor pressure surge variance, the current signal surge variance and the temperature rise value exceed the corresponding threshold, it is judged that the surge occurs, otherwise, the surge does not occur, that is, the multi-source real-time judgment of the fuel cell air compressor surge boundary is realized. Figure 7 As shown in the figure, the current link has an alarm signal at the 4.8s, at this time the air compressor is in the normal regulation process, since the pressure and temperature links do not issue an alarm at this time, the redundancy combination module also does not issue an alarm signal, with the gradual closing of the valve opening, the pressure, current and temperature links issue an alarm in turn, and the redundancy combination module timely gives an alarm signal after the surge occurs.

[0075] The above specific description further details the purpose, technical scheme and beneficial effects of the application, and it should be understood that the above description is only a specific embodiment of the application and is not used to limit the protection scope of the application, and any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the application should be included in the protection scope of the application.

Claims

1. A method for real-time multi-source judgment of surge boundary of fuel cell air compressor, characterized in that: Comprising the following steps, S1: The surge test is performed on the fuel cell air compressor control platform, and the compressor inlet pressure, inlet temperature and motor current are collected; the sensors are arranged on the double-wire flow meter at the air compressor inlet, wherein the tail probe of the temperature sensor is placed at the center of the flow meter, facing the air compressor inlet, and the air compressor inlet temperature, pressure and current signals are measured respectively, during the operation of the fuel cell system, the surge boundary of the air compressor is gradually approached by changing the flow and pressure ratio of the air compressor, and the inlet temperature, pressure and current signals of the air compressor are dynamically collected to realize the collection of the surge signal; S2: Due to the influence of instrument measurement error, environmental factors, electromagnetic interference and signal transmission process during the test, high-frequency noise is generated, which affects the accuracy of signal analysis and processing; the original signals of the current and inlet pressure are processed by first-order low-pass filtering, and the inlet temperature signal is not processed, to obtain the first-order low-pass filtered current and inlet pressure signals, and reduce the influence of high-frequency noise; S3: Constructing a surge variance for characterizing the degree of surge fluctuation, respectively calculating the surge variance of the air compressor pressure and current signals in each time window, making the calculation of the surge variance more localized, and improving the recognition accuracy of the surge; determining the length of the moving time window ΔX according to the sampling frequency set by the filter; respectively calculating the air compressor pressure and current signal variance in the moving time window to obtain the air compressor pressure signal surge variance S P and the current signal surge variance S I , that is, the fluctuation characteristics of the air compressor pressure and current signals are obtained; The temperature rise value ΔT in the time window is obtained by subtracting the temperature at the beginning of the time window from the temperature at the end of the time window; S4: According to step S3, the pressure surge variance and the current signal surge variance of the air compressor when the surge occurs at different rotating speeds are measured respectively, the rotating speed-threshold value relationship of the pressure signal and the current signal is obtained through polynomial fitting, and at different rotating speeds, the corresponding pressure signal variance threshold value M p and the current signal variance threshold value M I for judging whether the surge occurs are obtained according to the rotating speed-threshold value relationship; T A fixed temperature threshold value M T is set for judging whether the surge occurs. S5: Real-time acquisition of the surge signal described in step S1 through the sensor, determination of the length of the time window using step 2, calculation of the air compressor pressure surge variance, current signal surge variance and temperature rise value in the time window according to step S3; comparison of the air compressor pressure surge variance in the time window calculated in step S3 with the pressure signal variance threshold M p ; comparison of the current signal surge variance in the time window calculated in step S3 with the current signal variance threshold M I ; comparison of the temperature rise value in the time window calculated in step S3 with the temperature threshold M T ; when at least two of the three parameters of the air compressor pressure surge variance, the current signal surge variance and the temperature rise value exceed the corresponding threshold, it is judged that surge occurs, otherwise, surge does not occur, that is, the fuel cell air compressor surge boundary multi-source real-time judgment is realized.

2. The method of claim 1, wherein the method further comprises: determining the surge margin of the air compressor of the fuel cell power plant. The implementation method of step S2 is S2.1: According to the compressor surge signal measured in step 1, a complete surge waveform data is intercepted, a complete surge waveform data is defined by m sampling points, and then an m-dimensional signal vector is formed Wherein, s(0), s(1), …, s(m-1) are respectively the values of m sampling points contained in a complete surge signal waveform; S2.2: The original signals of the current and inlet pressure are processed by first-order low-pass filtering using the first-order low-pass filter shown in the following formula to obtain the first-order low-pass filtered current signal and inlet pressure signal; y n = ax n +(1-a)y n-1 wherein, y n is the output value of the last filter, y n-1 is the output value of the last filter, x n is the current sample value, T s is the sampling period in seconds, f c is the cut-off frequency in Hertz, a is in the range [0, 1].

3. The method of claim 2, wherein the method further comprises: determining the surge margin of the air compressor of the fuel cell power plant. The implementation method of step S3 is S3.1: When surge occurs, the air compressor inlet pressure and current will produce large surge fluctuations, and the surge variance is introduced to characterize the surge fluctuation degree; the surge variance calculation formula is: Wherein, c i is the sampling value at time i, m is the number of sampling points in the preset time period, is the average of the sampling data in this period. Select a time window, and the statistical range m of each variance is determined by the length of the time window; the window is a signal range size used for surge variance calculation, that is, the surge variance of the air compressor pressure and current signals in each time window is calculated respectively, so that the calculation of the surge variance is more localized, and the recognition accuracy of the surge is improved; S3.2: The moving time window length ΔX is determined according to the sampling frequency of the filter Wherein, f is the signal sampling frequency, and m is the number of sampling points contained in a complete surge waveform data; S3.3: According to 3.1, the variances of the air compressor pressure and current signals in the time window are calculated respectively to obtain the surge variances of the air compressor pressure signal and current signal, that is, the fluctuation characteristics of the air compressor pressure and current signals are obtained; S3.4: The temperature signal will not fluctuate obviously when surge occurs, but there will be obvious temperature rise phenomenon, therefore, the temperature rise value ΔT in the time window is calculated, wherein ΔT=T2-T1, T1 represents the temperature at the beginning of the time window, and T2 represents the temperature at the end of the time window.

4. The method of claim 3, wherein the method further comprises: determining the surge margin of the air compressor of the fuel cell power plant based on the determined surge margin of the air compressor of the fuel cell power plant. The implementation method of step S4 is S4.1: The selection of threshold is related to the speed, the greater the speed, the corresponding threshold should also be improved, in the early performance test stage, respectively, measure the pressure variance, current variance when surge occurs under different speed, there is only a polynomial L n (x) = b0+ b1x + b2x 2 + … + b n x n , so that L n (x j ) = y j (j = 1, 2, …, n) wherein x j represents the variance value at different rotational speeds; y j represents different rotational speeds; The speed-threshold relationship of the pressure signal and the current signal is obtained, and the corresponding pressure signal variance threshold M for judging whether surge occurs is obtained at different speeds p and the current signal variance threshold M I ; S4.2: When surge occurs, the change of temperature can be ignored due to system vibration, and a fixed temperature threshold M is set to determine whether surge occurs. T , for determining whether surge occurs.

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