Self-checking optimization fuel cell air inlet system

Abstract

The invention relates to the technical field of traffic and transportation, and discloses a self-inspection optimization fuel cell air inlet system, which comprises a monitoring module, a control module, a gas inlet control module, a gas inlet control module and a gas outlet control module, the filtering module is composed of a mechanical pre-filtering layer, an efficient particle air filtering layer and an adsorption layer and used for filtering impurities in the air inlet pipeline. The feedback adjusting module is in signal connection with the monitoring module and is used for adjusting the air inlet flow according to the impurity concentration change rate and the voltage fluctuation of the fuel cell stack; the data transmission module is used for sending data acquired by the monitoring module to the data processing module; and the data processing module is used for performing analysis processing according to the data acquired by the monitoring module, judging whether filtering reaches the standard or not, and performing early warning according to the filtering effect. According to the scheme, the composition and content of impurities in the gas inlet pipeline can be monitored in real time, the gas inlet flow can be regulated and controlled in real time, multiple layers of filtering protective barriers are designed, impurity gas entering a galvanic pile is reduced, and the service life of a fuel cell is prolonged.

Description

Technical Field

[0001] The present invention belongs to the technical field of transportation, and particularly relates to a self-checking and optimized fuel cell air intake system. Background Art

[0002] With the adjustment of the energy structure and the continuous improvement of environmental protection requirements, fuel cell vehicles have achieved great development. At the same time, the research on their durability has become increasingly urgent. Among them, the durability of fuel cells is a key factor, and impurities in the air seriously affect their service life and comprehensive performance. Therefore, optimizing the fuel cell air intake system and real-time monitoring and regulating the intake air flow are of great significance for improving the durability of fuel cell vehicles.

[0003] Existing fuel cell air intake systems generally adopt a multi-stage static filtration structure, mainly relying on physical interception and adsorption materials to passively purify air, and have the following deficiencies: Insufficient monitoring ability: Only equipped with pressure / flow sensors, unable to identify key corrosive gases such as sulfur oxides (such as SO2) and nitrogen oxides (NOx) (concentration threshold ≤ 1 ppm may cause poisoning of the stack catalyst); Uncontrollable filtration efficiency: The filtration efficiency of the fixed series filter layer drops by more than 50% when blocked (such as pressure difference ΔP ≥ 3 kPa), and it is unable to sense the adsorption saturation of the filter material in real time (such as continuing to use when the VOCs adsorption capacity of activated carbon drops below 50%); Lagging control strategy: The intake air regulation based on a fixed threshold (such as increasing the flow rate only when PM2.5 > 50 μg / m³) causes the stack voltage to fluctuate by more than ±10 mV, leading to performance degradation.

[0004] In addition, the existing technology generally relies on a rough maintenance mode of regularly replacing the filter element, which can neither accurately predict the service life of the filter material nor optimize the energy consumption according to different environmental conditions, resulting in systematic defects such as accelerated catalyst deactivation due to impurity penetration and low energy efficiency ratio of the air compressor in fuel cells for a long time.

[0005] Therefore, there is an urgent need to develop a self-checking and optimized fuel cell air intake system that can real-time monitor the composition and content of impurities in the intake air pipeline, real-time regulate the intake air flow, and at the same time design a multi-layer filtration protection barrier to reduce the entry of impurity gases into the stack and improve the service life of fuel cells. Summary of the Invention

[0006] In order to solve the above technical problems, the present invention provides a self-checking and optimized fuel cell air intake system that can real-time monitor the composition and content of impurities in the intake air pipeline, real-time regulate the intake air flow, and at the same time design a multi-layer filtration protection barrier to reduce the entry of impurity gases into the stack and improve the service life of fuel cells.

[0007] The present invention provides a self-checking and optimized fuel cell intake system, comprising: a monitoring module, a filtering module, a feedback regulation module, a data transmission module and a data processing module; The monitoring module is used for monitoring impurity parameters in the intake pipeline and operating state parameters of the fuel cell stack; The filtering module consists of a mechanical pre-filtering layer, a high-efficiency particulate air filtering layer and an adsorption layer, and is used for filtering impurities in the intake pipeline; The data transmission module is used for sending the data collected by the monitoring module to the data processing module; The data processing module is used for analyzing and processing the data collected by the monitoring module, judging whether the filtering is up to standard, and giving an early warning according to the filtering effect; The feedback regulation module is signal-connected to the monitoring module, and is used for adjusting the intake air flow through a fuzzy PID algorithm according to the change rate of impurity concentration and the voltage fluctuation of the fuel cell stack.

[0008] Further, the monitoring module includes an impurity component sensor, an impurity concentration sensor, a current sensor, a voltage sensor and an electrochemical impedance spectroscopy analyzer.

[0009] Further, in the filtering module, the mechanical pre-filtering layer adopts a PET gradient density fiber filter cotton, with an initial pressure difference ≤ 0.5 kPa and a dust holding capacity ≥ 150 g / m²; the high-efficiency particulate air filtering layer adopts a borosilicate glass fiber filter material, with a fiber diameter of 1-3 μm and a filtering air velocity of 0.1-0.4 m / s; the adsorption layer includes an acidic gas adsorption sub-layer and a volatile organic compound adsorption sub-layer; the acidic gas adsorption sub-layer adopts activated alumina with a sodium hydroxide loading of 5-8 wt%, a specific surface area ≥ 200 m² / g, and the volatile organic compound adsorption sub-layer adopts a honeycomb activated carbon structure, with an iodine value ≥ 1200 mg / g and a pore size distribution of 80% < 2 nm.

[0010] Further, the filtering module adopts a quick-release structure, and each filter layer can be replaced independently.

[0011] Further, a pressure difference sensor is arranged after each filter layer in the filtering module, and the pressure difference sensor is electrically connected to the data processing module.

[0012] Further, the data processing module analyzes and processes the data collected by the monitoring module, judges whether the filtering is up to standard, and gives an early warning according to the filtering effect, including: Sa. Calculating the outlet concentration of each impurity at the outlet of the intake pipeline according to the inlet concentration of each impurity at the inlet of the intake pipeline collected by the monitoring module and the initial filtering efficiency of each filter layer in the filtering module; Sb. Comparing the outlet concentration of each impurity at the outlet of the intake pipeline with the preset standard limit value of each impurity, and giving an early warning according to the filtering effect.

[0013] Further, in Sa, the calculation formula for the outlet concentration of each impurity at the outlet of the intake pipe according to the inlet concentration of each impurity at the inlet of the intake pipe collected by the monitoring module and the initial filtration efficiency of each filtration layer in the filtration module is as follows: ; Among them, C final,j represents the outlet concentration of the j-th impurity, C 0,j represents the inlet concentration of the j-th impurity, i represents the i-th filtration layer in the filtration module, represents the initial filtration efficiency of the i-th filtration layer in the filtration module, and n represents the total number of filtration layers in the filtration module.

[0014] Further, in Sb, comparing the outlet concentration of each impurity at the outlet of the intake pipe with the preset standard limit value of each impurity, and warning according to the filtration effect includes: If the outlet concentration of all impurities is less than or equal to the first preset percentage of the corresponding preset standard limit value, the filtration effect meets the standard and no warning is given; If the outlet concentration of at least one impurity exceeds the first preset percentage of the preset standard limit value, a first-level warning is given; If the outlet concentration of at least one impurity exceeds the preset standard limit value, a second-level warning is given.

[0015] Further, the data processing module is also used to correct the filtration efficiency of each filtration layer of the filtration module in real time according to the data collected by the monitoring module, and synchronously generate a filter material replacement warning, specifically including: The blockage state of each filtration layer is monitored in real time through a differential pressure sensor. When the differential pressure of a certain filtration layer in the filtration module reaches the second preset percentage of the maximum allowable differential pressure, the filtration efficiency correction calculation is triggered, and a filter material replacement warning is synchronously generated.

[0016] Further, the calculation formula for triggering the filtration efficiency correction calculation is as follows: ; Among them, represents the corrected filtration efficiency of the i-th filtration layer in the filtration module, represents the initial filtration efficiency of the i-th filtration layer in the filtration module, represents the differential pressure data collected by the differential pressure sensor after the i-th filtration layer in the filtration module, represents the maximum allowable differential pressure of the i-th filtration layer in the filtration module.

[0017] The embodiments of the present invention have the following technical effects: The present invention adopts the collaborative monitoring of an impurity component sensor and a concentration sensor to capture the dynamic changes in the concentrations of different impurity components in real time. At the filtration and protection level, based on a three-level barrier structure of mechanical pre-filtration, ultra-fine particle interception, and chemical adsorption, different forms of pollutants are eliminated in a gradient manner. The gradient density fiber layer intercepts large particulate suspensions through a progressive pore structure, the fiberglass filter material forms a dense network to capture sub-micron particles, and the composite adsorption layer eliminates acidic gases relying on the acid-base neutralization characteristics of sodium hydroxide-modified activated alumina, and realizes the efficient adsorption of benzene substances through the huge specific surface area of honeycomb activated carbon; the data acquisition system integrates differential pressure sensing and dynamic correction algorithms to track the clogging status of each filter material in real time and calibrate the filtration efficiency parameters, enabling the intake air flow regulating valve to perform predictive regulation according to the change trend of impurity concentration and the fluctuation characteristics of the stack voltage, and triggering the flow compensation mechanism in advance when the pollutant concentration surges. This system adopts a closed-loop control logic of "monitoring - interception - feedback" to monitor the composition and content of impurities in the intake pipeline in real time, transmits the data to the terminal through the data acquisition system to observe the impact of air impurities on the performance of the fuel cell, and according to the output data, regulates the intake air flow in real time. At the same time, a multi-layer filtration and protection barrier is designed to reduce the entry of impurity gases into the stack and improve the service life of the fuel cell. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for use in the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0019] Figure 1 It is a composition diagram of a self-checking and optimizing fuel cell intake system provided by an embodiment of the present invention; Figure 2 It is a structural diagram of a self-checking and optimizing fuel cell intake pipeline provided by an embodiment of the present invention; Figure 3 It is a working flow diagram of a self-checking and optimizing fuel cell intake system provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

[0021] An embodiment of the present invention provides a self-checking and optimized fuel cell intake system. Figure 1 It is a composition diagram of a self-checking and optimized fuel cell intake system provided by an embodiment of the present invention. Figure 2 It is a structural diagram of a self-checking and optimized fuel cell intake pipeline provided by an embodiment of the present invention. See Figure 1 and Figure 2 , including: A monitoring module, a filtering module, a feedback regulation module, a data transmission module, and a data processing module; The monitoring module is used to monitor the impurity parameters in the intake pipeline and the working state parameters of the fuel cell stack. The filtering module is composed of a mechanical pre-filtering layer, a high-efficiency particulate air filtering layer, and an adsorption layer, and is used to filter the impurities in the intake pipeline. The data transmission module is used to send the data collected by the monitoring module to the data processing module. The data processing module is used to analyze and process the data collected by the monitoring module, judge whether the filtering is up to standard, and give an early warning according to the filtering effect. The feedback regulation module is signal-connected to the monitoring module and is used to adjust the intake air flow through a fuzzy PID algorithm according to the impurity concentration change rate and the voltage fluctuation of the fuel cell stack.

[0022] Among them, the monitoring module includes an impurity component and impurity concentration sensor to monitor the impurities contained in the intake pipeline in real time. It also includes current, voltage sensors, and an electrochemical impedance spectroscopy analyzer to monitor the working state of the fuel cell in real time. Prevent abnormal impurity concentration values and abnormal working states from affecting the performance and lifespan of the fuel cell.

[0023] The filtration module includes a multi-stage filtration device. The first-stage filtration is a mechanical pre-filtration layer, which uses PET gradient density fiber filter cotton with an initial pressure difference ≤ 0.5 kPa and a dust holding capacity ≥ 150 g / m². It captures large particles such as PM10 by physical interception, and the interception rate of particles above 10 μm is ≥ 98%. The second-stage filtration is a high-efficiency particulate air filtration layer, which uses borosilicate glass fiber filter media with a fiber diameter of 1 - 3 μm and a filtration air velocity of 0.1 - 0.4 m / s, meeting the EN1822 standard. It filters fine particles and some aerosols through diffusion and electrostatic adsorption. The third-stage filtration is an adsorption layer, which is divided into two sub-layers. The first sub-layer is an acidic gas adsorption sub-layer, which uses activated alumina with a sodium hydroxide loading of 5 - 8 wt% (specific surface area ≥ 200 m² / g), and the SO2 breakthrough capacity is ≥ 50 mg / g. It removes nitrogen oxides and sulfur oxides by chemical adsorption. The second sub-layer is a volatile organic compounds (VOCs) adsorption sub-layer, which uses honeycomb activated carbon (iodine value ≥ 1200 mg / g, pore size distribution 80% < 2 nm), and the benzene vapor adsorption capacity is ≥ 450 mg / g. It removes VOCs by physical adsorption.

[0024] Furthermore, the filtration module adopts a quick-release structure, and each filter layer can be replaced independently, with the replacement time ≤ 5 minutes.

[0025] Furthermore, to ensure the flow efficiency, differential pressure sensors are installed between each stage of the filtration layer to monitor the clogging status and avoid unsmooth air intake. Differential pressure sensors are set after each stage of the filtration layer in the filtration module, and the differential pressure sensors are electrically connected to the data processing module. The dynamic monitoring system of the differential pressure sensor constructs a three-dimensional evaluation model of the filtration status. The differential pressure signals before and after each filter layer form a pressure gradient matrix, and the noise interference caused by air flow pulsation is eliminated through the Kalman filtering algorithm. When local clogging occurs in a certain stage of the filter material, the ratio of the differential pressure increment of this layer to that of the adjacent layer will exceed the preset threshold, triggering the adaptive compensation mechanism.

[0026] The data transmission module adopts two forms of wired transmission and / or wireless transmission to ensure the effectiveness of data transmission, transmits the data to the terminal and the background processing platform to monitor the air intake status and the working status of the fuel cell in real time, can achieve real-time self-check, and transmits the processed data to the feedback regulation system to achieve self-optimized operation.

[0027] The data processing module includes a data storage sub-module, a data processing and analysis sub-module, and an early warning sub-module. The data storage sub-module saves the transmitted data to the terminal for analyzing the impact of gas impurities on the performance of the fuel cell, and provides suggestions for further optimization of the fuel cell intake module; the data processing and analysis sub-module processes the collected data such as filtering and outlier monitoring, and generates images of the concentration of impurity components in the intake pipeline and the changes in the voltage and current of the fuel cell over time during the operation of the fuel cell vehicle to ensure normal operation and working conditions; the early warning sub-module warns of anomalies to remind the driver and passengers to take measures and actively intervene.

[0028] The data storage sub-module can adopt blockchain distributed storage technology. Each data block stores the data collected by the detection module and the data of the terminal, which is convenient for analyzing the impact of gas impurities on the performance of the fuel cell and provides suggestions for optimizing the intake system.

[0029] Furthermore, the data processing and analysis sub-module in the data processing module analyzes and processes the data collected by the monitoring module, judges whether the filtration is up to standard, and issues early warnings according to the filtration effect, including: Sa. Calculate the outlet concentration of each impurity at the outlet of the intake pipeline based on the inlet concentration of each impurity at the inlet of the intake pipeline collected by the monitoring module and the initial filtration efficiency of each filtration layer in the filtration module.

[0030] In some embodiments, the calculation formula for the outlet concentration of each impurity is as follows: ; where C final,j represents the outlet concentration of the jth impurity, C 0,j represents the inlet concentration of the jth impurity, i represents the ith filtration layer in the filtration module, represents the initial filtration efficiency of the ith filtration layer in the filtration module, and n represents the total number of filtration layers in the filtration module.

[0031] Specifically, the concentration of each impurity at the inlet of the first filtration layer, which is the original air impurity concentration of the entire intake system, can be directly measured by an impurity concentration sensor installed at the front end (initial position of the intake pipeline) of the filtration module. This sensor is part of the monitoring system. The concentration of each impurity at the inlet of the second filtration layer is the concentration of each impurity at the outlet of the first filtration layer, and the concentration of each impurity at the inlet of the third filtration layer is the concentration of each impurity at the outlet of the second filtration layer.

[0032] Exemplarily, assume that the initial concentration of a certain impurity is 100 ppm, and the designed filtration efficiencies of each filtration layer are: The filtration efficiency of the first filtration layer = 80%, which is determined by the physical interception performance of the gradient density fiber filter cotton; Filtration efficiency of the secondary filtration layer = 90%, determined by the filtration performance of fiberglass; Filtration efficiency of the tertiary filtration layer = 95%, determined by the chemisorption performance of activated alumina impregnated with sodium hydroxide and the physical adsorption performance of honeycomb activated carbon); Then the concentration of the impurity at the outlet of the tertiary filtration layer, i.e., the outlet concentration of the impurity, and the calculation formula for the outlet concentration of the impurity is: .

[0033] The filtration efficiency of each layer is calculated by combining the designed efficiency with real-time differential pressure correction. The original data is obtained by using the front-end concentration sensor, and the concentration of the intermediate layer is deduced through the recurrence relationship, which not only reduces the hardware cost but also ensures the accuracy of the efficiency calculation through dynamic correction. Finally, the overall filtration effect is verified through the total outlet concentration, realizing the self-optimization and early warning functions of the system.

[0034] Sb. Compare the outlet concentration of each impurity at the outlet of the intake pipe with the preset standard limit value of each impurity, and give an early warning according to the filtration effect.

[0035] In some embodiments, the hierarchical early warning includes: If the outlet concentration of all impurities is less than or equal to the first preset percentage of the corresponding preset standard limit value, the filtration effect meets the standard and no early warning is given; If the outlet concentration of at least one impurity exceeds the first preset percentage of the preset standard limit value, a first-level early warning is given, and the terminal prompts "The filtration efficiency has decreased. It is recommended to check"; If the outlet concentration of at least one impurity exceeds the preset standard limit value, a second-level early warning is given, and the air compressor is linked to close the intake passage and the standby filtration circuit is started.

[0036] Among them, the first preset percentage can be set to 80%.

[0037] Exemplarily, the preset standard limit value (C std,j ) of each impurity is set as: SO2 ≤ 0.1 ppm, NO x ≤ 5 ppm, NH3 ≤ 3 ppm, VOCs ≤ 0.05 ppm, PM2.5 ≤ 10 μg / m 3 , and this standard limit value is adjusted according to the actual situation.

[0038] In some embodiments, the data processing module is further configured to, according to the data collected by the monitoring module, when the differential pressure of a certain filtration layer is caused by impurity blockage When it rises, the filtration efficiency will decrease. The clogging status of each filtration layer is monitored in real time through a differential pressure sensor. When the differential pressure of a certain filtration layer in the filter module reaches the second preset percentage of the maximum allowable differential pressure, the filtration efficiency correction calculation is triggered, and a filter media replacement warning is generated synchronously; among them, the second preset percentage can be 70%.

[0039] The calculation formula for triggering the filtration efficiency correction calculation is as follows: ; Among them, represents the corrected filtration efficiency of the i-th filtration layer in the filtration module, represents the initial filtration efficiency of the i-th filtration layer in the filtration module, represents the differential pressure data collected by the differential pressure sensor after the i-th filtration layer in the filter module, represents the maximum allowable differential pressure of the i-th filtration layer in the filter module to ensure the real-time nature of efficiency correction.

[0040] When the monitoring module detects an increase in the impurity content in the intake pipe or an abnormal operation of the fuel cell module, the feedback adjustment module can alert the driver and passengers to pay attention to maintenance, and at the same time, it can actively intervene and adjust the intake air flow of the intake module, the working status of the filtration module, and the humidity of the proton membrane based on PID control.

[0041] The feedback adjustment module adjusts the intake air flow (adjustment step size ≤ 5%) according to the stack voltage fluctuation (ΔV≥±5mV) and the impurity concentration change rate (ΔC / Δt≥0.5ppm / s) through the fuzzy PID algorithm; the calculation formula for adjusting the intake air flow through PID control is as follows: ; Among them, K p 、K i 、K d represent the proportional, integral, and differential control parameters respectively. Each control parameter is adjusted according to the concentration change rate and the stack working voltage fluctuation through fuzzy rules. u(t) represents the control signal output to the intake air flow regulating valve, driving the valve body opening to change, thereby adjusting the intake air flow, and e(t) represents the deviation between the real-time impurity concentration and the preset standard limit value.

[0042] The present invention adopts the collaborative monitoring of an impurity component sensor and a concentration sensor to capture the dynamic changes in the concentrations of different impurity components in real time. At the filtration and protection level, based on a three - level barrier structure of mechanical pre - filtration, ultra - fine particle interception, and chemical adsorption, it gradually eliminates pollutants in different forms. The gradient - density fiber layer intercepts large - particle suspended matter through a progressive pore structure, the glass fiber filter material forms a dense network to capture sub - micron - sized particles, the composite adsorption layer relies on the acid - base neutralization characteristics of sodium - hydroxide - modified activated alumina to eliminate acidic gases, and achieves efficient adsorption of benzene - like substances through the extremely large specific surface area of honeycomb activated carbon; the data acquisition system integrates differential pressure sensing and a dynamic correction algorithm to track the clogging status of each filter material in real time and calibrate the filtration efficiency parameters, enabling the intake air flow regulating valve to perform predictive regulation according to the change trend of impurity concentration and the fluctuation characteristics of the stack voltage. When the pollutant concentration surges, it triggers the flow compensation mechanism in advance. This system, through the closed - loop control logic of "monitoring - interception - feedback", monitors the composition and content of impurities in the intake pipeline in real time, transmits the data to the terminal through the data acquisition system to observe the impact of air impurities on the performance of the fuel cell, and according to the output data, regulates the intake air flow in real time. At the same time, a multi - layer filtration and protection barrier is designed to reduce the entry of impurity gases into the stack and improve the service life of the fuel cell.

[0043] Figure 3 It is a flowchart of the working process of a self - checking and optimizing fuel cell intake system provided by an embodiment of the present invention. Refer to Figure 3 An embodiment of the present invention also provides a working method for a self - checking and optimizing fuel cell intake system: S1. Monitor the impurity components and concentrations through the impurity component sensor and concentration sensor of the monitoring module, and monitor the working state of the fuel cell through the current - voltage sensor and impedance spectrum analyzer; S2. Transmit the collected data to the vehicle control system and user terminal respectively through the data transmission module in a wired and / or wireless manner; S3. Store the data of the terminal through the data storage sub - module of the data processing module to facilitate the analysis of the impact of gas impurities on the performance of the fuel cell and provide suggestions for optimizing the intake system; S4. Perform processing and analysis such as filtering and outlier detection on the collected data through the data processing and analysis sub - module of the data processing module, generate the time - change curve of impurities and the change curves of the working voltage and current of the fuel cell, and determine the impact of impurities; S5. Compare the processed data with the preset standard limit values through the warning sub - module of the data processing module. If it exceeds the preset standard limit values, alarm to remind the driver and passengers; S6. Adjust the working state, intake air flow, etc. of the filtration module according to the warning data through the feedback regulation module.

[0044] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention.

Claims

1. A self-checking and optimized fuel cell intake system, characterized in that, Including: A monitoring module, a filtering module, a feedback regulation module, a data transmission module, and a data processing module; The monitoring module is used to monitor the impurity parameters in the intake pipeline and the operating state parameters of the fuel cell stack; The filtering module consists of a mechanical pre-filtering layer, a high-efficiency particulate air filtering layer, and an adsorption layer, and is used to filter the impurities in the intake pipeline; A differential pressure sensor is arranged after each level in the filtering module, and the differential pressure sensor is electrically connected to the data processing module; The data transmission module is used to send the data collected by the monitoring module to the data processing module; The data processing module is used to analyze and process the data collected by the monitoring module, judge whether the filtering is up to standard, and give an early warning according to the filtering effect; Specifically, it includes the following steps: Sa. Calculate the outlet concentration of each impurity at the outlet of the intake pipeline according to the inlet concentration of each impurity at the inlet of the intake pipeline collected by the monitoring module and the initial filtration efficiency of each filtration layer in the filtering module; Sb. Compare the outlet concentration of each impurity at the outlet of the intake pipeline with the preset standard limit value of each impurity, and give an early warning according to the filtering effect; The feedback regulation module is signal-connected to the monitoring module and is used to adjust the intake air flow through a fuzzy PID algorithm according to the impurity concentration change rate and the voltage fluctuation of the fuel cell stack.

2. The self-checking optimized fuel cell intake system according to claim 1, wherein The monitoring module includes an impurity component sensor, an impurity concentration sensor, a current sensor, a voltage sensor, and an electrochemical impedance spectroscopy analyzer.

3. The self-checking optimized fuel cell intake system according to claim 1, characterized in that, In the filtering module, the mechanical pre-filtering layer uses PET gradient density fiber filter cotton, with an initial differential pressure ≤ 0.5 kPa and a dust holding capacity ≥ 150 g / m²; the high-efficiency particulate air filtering layer uses borosilicate glass fiber filter material, with a fiber diameter of 1 - 3 μm and a filtration air velocity of 0.1 - 0.4 m / s; the adsorption layer includes an acidic gas adsorption sub-layer and a volatile organic compound adsorption sub-layer; the acidic gas adsorption sub-layer uses activated alumina with a sodium hydroxide loading of 5 - 8 wt%, a specific surface area ≥ 200 m² / g, and the volatile organic compound adsorption sub-layer uses a honeycomb activated carbon structure, with an iodine value ≥ 1200 mg / g and a pore size distribution of 80% < 2 nm.

4. The self-checking optimized fuel cell intake system according to claim 1, wherein, The filtering module adopts a quick-release structure, and each filter layer can be replaced independently.

5. The self-checking optimized fuel cell intake system according to claim 1, wherein, In the above Sa, the calculation formula for calculating the outlet concentration of each impurity at the outlet of the intake pipeline according to the inlet concentration of each impurity at the inlet of the intake pipeline collected by the monitoring module and the initial filtration efficiency of each filtration layer in the filtering module is as follows: ； Among them, C final,j represents the outlet concentration of the j-th impurity, and C 0,j represents the inlet concentration of the j-th impurity. i represents the i-th filtration layer in the filtration module, represents the initial filtration efficiency of the i-th filtration layer in the filtration module, and n represents the total number of filtration layers in the filtration module.

6. The self-checking optimized fuel cell intake system according to claim 1, wherein In the above Sb, comparing the outlet concentration of each impurity at the outlet of the intake pipeline with the preset standard limit value of each impurity and giving an early warning according to the filtering effect includes: If the outlet concentration of all impurities is less than or equal to the first preset percentage of the corresponding preset standard limit value, the filtering effect is up to standard and no early warning is given; If the outlet concentration of at least one impurity exceeds the first preset percentage of the preset standard limit value, a first-level early warning is given; If the outlet concentration of at least one impurity exceeds the preset standard limit value, a second-level early warning is given.

7. The self-checking optimized fuel cell intake system according to claim 1, characterized in that, The data processing module is further configured to, according to the data collected by the monitoring module, correct the filtration efficiency of each filtration layer of the filtration module in real time and synchronously generate a filter media replacement warning, specifically including: The clogging status of each filtration layer is monitored in real time through a differential pressure sensor. When the differential pressure of a certain filtration layer in the filtration module reaches a second preset percentage of the maximum allowable differential pressure, a filtration efficiency correction calculation is triggered, and a filter media replacement warning is synchronously generated.

8. An optimized fuel cell intake system for self-checking according to claim 7, characterized in that, The calculation formula for triggering the filtration efficiency correction calculation is as follows: ； Among them, represents the corrected filtration efficiency of the i-th filtration layer in the filtration module, represents the initial filtration efficiency of the i-th filtration layer in the filtration module, represents the differential pressure data collected by the differential pressure sensor after the i-th filtration layer in the filtration module, represents the maximum allowable differential pressure of the i-th filtration layer in the filtration module.

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