A self-checking and optimizing fuel cell intake system

Abstract

The present invention relates to the field of transportation technology, and discloses a self-checking and optimizing fuel cell air intake system, comprising a monitoring module for monitoring impurity parameters in the air intake duct and operating status parameters of the fuel cell stack; a filtering module composed of a mechanical pre-filtration layer, a high-efficiency particulate air filtration layer, and an adsorption layer, for filtering impurities in the air intake duct; a feedback regulation module connected to the monitoring module signal, for adjusting the air intake flow rate according to the impurity concentration change rate and the voltage fluctuation of the fuel cell stack; a data transmission module for sending the data collected by the monitoring module to a data processing module; the data processing module for analyzing and processing the data collected by the monitoring module, determining whether the filtration meets the standards, and issuing an early warning based on the filtration effect. This solution can monitor the composition and content of impurities in the air intake duct in real time, regulate the air intake flow in real time, design a multi-layer filtration protection barrier, reduce the amount of impurity gas entering the stack, and increase the service life of the fuel cell.

Description

Technical Field

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

[0002] With the adjustment of energy structures and the continuous improvement of environmental protection requirements, fuel cell vehicles have achieved significant development. At the same time, research on their durability is becoming increasingly urgent. Fuel cell durability is a key factor, and impurities in the air seriously affect their service life and overall performance. Therefore, optimizing the fuel cell intake system and real-time monitoring and control of intake air flow are of great significance to improving the durability of fuel cell vehicles.

[0003] Existing fuel cell air intake systems generally use a multi-stage static filtration structure, which mainly relies on physical interception and adsorption materials to passively purify the air. This has the following shortcomings:

[0004] Insufficient monitoring capabilities: Equipped with only pressure / flow sensors, it cannot identify key corrosive gases such as sulfur oxides (SO2) and nitrogen oxides (NOx) (a concentration threshold of ≤1ppm may cause fuel cell catalyst poisoning);

[0005] Uncontrollable filtration efficiency: When the fixed series filter layer is clogged (e.g., pressure difference ΔP ≥ 3kPa), the filtration efficiency drops by more than 50%, and the adsorption saturation of the filter material cannot be sensed in real time (e.g., continued use of activated carbon when its VOCs adsorption capacity drops below 50%).

[0006] Control strategy lag: Intake regulation based on fixed thresholds (such as increasing flow only when PM2.5 is greater than 50μg / m³) causes stack voltage fluctuations exceeding ±10mV, leading to performance degradation.

[0007] In addition, existing technologies generally rely on a rough maintenance mode of regularly replacing filter elements, which can neither accurately predict the life of the filter material nor optimize energy consumption for different environmental conditions. As a result, fuel cells face long-term systemic defects such as impurity penetration accelerating catalyst deactivation and low air compressor energy efficiency.

[0008] Therefore, there is an urgent need to develop a self-checking and optimizing fuel cell intake system that can monitor the composition and content of impurities in the intake pipe in real time, regulate the intake flow in real time, and design a multi-layer filtering protection barrier to reduce the entry of impurity gases into the stack and improve the service life of the fuel cell. Summary of the Invention

[0009] In order to solve the above technical problems, the present invention provides a self-checking and optimizing fuel cell air intake system, which can monitor the composition and content of impurities in the air intake pipe in real time, regulate the air intake flow in real time, and design a multi-layer filtering protection barrier to reduce the entry of impurity gases into the fuel cell stack, thereby improving the service life of the fuel cell.

[0010] The present invention provides a self-checking and optimizing fuel cell intake system, comprising: a monitoring module, a filtering module, a feedback adjustment module, a data transmission module and a data processing module;

[0011] The monitoring module is used to monitor the impurity parameters in the intake pipe and the working status parameters of the fuel cell stack;

[0012] The filter module consists of a mechanical pre-filter layer, a high-efficiency particulate air filter layer and an adsorption layer, which is used to filter impurities in the air intake duct;

[0013] The data transmission module is used to send the data collected by the monitoring module to the data processing module;

[0014] The data processing module is used to analyze and process the data collected by the monitoring module, determine whether the filtering meets the standards, and issue early warnings based on the filtering effect;

[0015] The feedback regulation module is connected to the monitoring module signal and is used to adjust the intake flow rate through a fuzzy PID algorithm according to the impurity concentration change rate and the voltage fluctuation of the fuel cell stack.

[0016] Furthermore, the monitoring module includes an impurity component sensor, an impurity concentration sensor, a current sensor, a voltage sensor and an electrochemical impedance spectroscopy analyzer.

[0017] Furthermore, in the filtration module, the mechanical pre-filtration layer uses PET gradient density fiber filter cotton, with an initial pressure difference of ≤0.5kPa and a dust holding capacity of ≥150g / m²; the high-efficiency particulate air filtration layer uses borosilicate glass fiber filter material, with a fiber diameter of 1-3μm and a filtration wind speed of 0.1-0.4m / s; the adsorption layer includes an acid gas adsorption sublayer and a volatile organic compound adsorption sublayer; the acid gas adsorption sublayer uses activated alumina with a sodium hydroxide loading of 5-8wt% and a specific surface area of ​​≥200m² / g, and the volatile organic compound adsorption sublayer uses a honeycomb activated carbon structure with an iodine value of ≥1200mg / g and a pore size distribution of 80% <2nm.

[0018] Furthermore, the filter module adopts a quick-detachable structure, and each level of filter layer can be replaced independently.

[0019] Furthermore, a differential pressure sensor is provided after each filter layer in the filter module, and the differential pressure sensor is electrically connected to the data processing module.

[0020] Furthermore, the data processing module analyzes and processes the data collected by the monitoring module to determine whether the filtering meets the standards and issues early warnings based on the filtering effect, including:

[0021] Sa, calculating the outlet concentration of each impurity at the outlet of the intake duct based on the inlet concentration of each impurity at the inlet of the intake duct collected by the monitoring module and the initial filtration efficiency of each filter layer in the filtration module;

[0022] Sb. Compare the outlet concentration of each impurity at the outlet of the intake pipe with the preset standard limit of each impurity, and issue an early warning based on the filtering effect.

[0023] Furthermore, in Sa, the calculation formula for calculating the outlet concentration of each impurity at the outlet of the intake duct is as follows based on the inlet concentration of each impurity at the inlet of the intake duct collected by the monitoring module and the initial filtration efficiency of each filter layer in the filtration module:

[0024] ;

[0025] Among them, 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 i-th filter layer in the filter module, It represents the initial filtration efficiency of the i-th filter layer in the filter module, and n represents the total number of filter layers in the filter module.

[0026] Furthermore, in Sb, the outlet concentration of each impurity at the outlet of the intake pipe is compared with the preset standard limit of each impurity, and an early warning is issued according to the filtering effect, including:

[0027] If the outlet concentration of all impurities is less than or equal to the first preset percentage of the corresponding preset standard limit, the filtration effect meets the standard and no warning is issued;

[0028] If the outlet concentration of at least one impurity exceeds a first preset percentage of the preset standard limit, a first-level warning is issued;

[0029] If the outlet concentration of at least one impurity exceeds the preset standard limit, a second-level warning will be issued.

[0030] Furthermore, the data processing module is also used to correct the filtration efficiency of each filter layer of the filtration module in real time based on the data collected by the monitoring module, and simultaneously generate an early warning for filter material replacement, specifically including:

[0031] The blockage status of each level of filter layer is monitored in real time through the pressure differential sensor. When the pressure differential of a certain level of filter layer in the filter module reaches the second preset percentage of the maximum allowable pressure differential, the filtration efficiency correction calculation is triggered and a filter material replacement warning is generated simultaneously.

[0032] Furthermore, the calculation formula for triggering the filtration efficiency correction calculation is as follows:

[0033] ;

[0034] in, It represents the corrected filtration efficiency of the i-th filter layer in the filtration module, It represents the initial filtration efficiency of the i-th filter layer in the filtration module, It represents the differential pressure data collected by the differential pressure sensor after the i-th filter layer in the filter module. Indicates the maximum allowable pressure difference of the i-th filter layer in the filter module.

[0035] The embodiments of the present invention have the following technical effects:

[0036] The present invention adopts the coordinated monitoring of impurity component sensors and concentration sensors to capture the dynamic changes of the concentrations of different impurity components in real time. At the filtration protection level, based on the three-level barrier architecture of mechanical pre-filtration, ultrafine particle interception and chemical adsorption, different forms of pollutants are eliminated in a gradient manner. The gradient density fiber layer intercepts large suspended particles through a progressive pore structure, and the glass fiber filter material forms a dense network to capture submicron particles. The composite adsorption layer relies on the acid-base neutralization properties of sodium hydroxide-modified activated alumina to eliminate acidic gases, and realizes efficient adsorption of benzene substances through the huge specific surface area of ​​honeycomb activated carbon; the data acquisition system integrates pressure difference sensing and dynamic correction algorithm to track the blockage status of filter materials at all levels in real time and calibrate the filtration efficiency parameters, so that the intake flow control valve can be predictively adjusted according to the impurity concentration change trend and the stack voltage fluctuation characteristics, and the flow compensation mechanism is triggered in advance when the pollutant concentration surges. The system uses the closed-loop control logic of "monitoring-interception-feedback" to monitor the composition and content of impurities in the intake duct in real time, and transmits data to the terminal through the data acquisition system to observe the impact of air impurities on fuel cell performance. Based on the output data, the system adjusts the intake flow in real time. At the same time, it designs multi-layer filtering protection barriers to reduce the entry of impurity gases into the fuel cell stack and increase the service life of the fuel cell. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0038] Figure 1 This is a composition diagram of a self-checking and optimizing fuel cell intake system provided by an embodiment of the present invention;

[0039] Figure 2 This is a structural diagram of a self-checking and optimizing fuel cell intake duct provided by an embodiment of the present invention;

[0040] Figure 3This is a workflow diagram for a self-checking and optimizing fuel cell intake system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0041] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention are described clearly and completely below. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are also within the scope of protection of the present invention.

[0042] The embodiment of the present invention provides a self-checking and optimizing fuel cell intake system. Figure 1 This is a composition diagram of a self-checking and optimizing fuel cell intake system provided by an embodiment of the present invention. Figure 2 This is a self-checking and optimizing fuel cell intake pipe structure diagram provided by an embodiment of the present invention, see Figure 1 and Figure 2 ,include:

[0043] Monitoring module, filtering module, feedback adjustment module, data transmission module and data processing module;

[0044] The monitoring module is used to monitor the impurity parameters in the intake pipe and the working status parameters of the fuel cell stack;

[0045] The filter module consists of a mechanical pre-filter layer, a high-efficiency particulate air filter layer and an adsorption layer, which is used to filter impurities in the air intake duct;

[0046] The data transmission module is used to send the data collected by the monitoring module to the data processing module;

[0047] The data processing module is used to analyze and process the data collected by the monitoring module, determine whether the filtering meets the standards, and issue early warnings based on the filtering effect;

[0048] The feedback regulation module is connected to the monitoring module signal and is used to adjust the intake flow rate through a fuzzy PID algorithm according to the impurity concentration change rate and the voltage fluctuation of the fuel cell stack.

[0049] The monitoring module includes sensors for impurity composition and concentration to monitor impurities in the intake duct in real time. It also includes current and voltage sensors and an electrochemical impedance spectroscopy analyzer to monitor the fuel cell's operating status in real time. This prevents abnormal impurity concentrations and operating conditions from impacting fuel cell performance and lifespan.

[0050] The filtration module includes a multi-stage filtration device. The first stage of filtration is a mechanical pre-filtration layer, which uses PET gradient density fiber filter cotton, with an initial pressure difference of ≤0.5kPa and a dust holding capacity of ≥150g / m². It captures large particles such as PM10 through physical interception, and has an interception rate of ≥98% for particles larger than 10μm. The second stage of filtration is a high-efficiency particulate air filtration layer, which uses borosilicate glass fiber filter material with a fiber diameter of 1-3μm and a filtration wind speed of 0.1-0.4m / s, in compliance with EN1822 standards, and filters fine particles and some aerosols through diffusion and electrostatic adsorption. The tertiary filtration is an adsorption layer, which is divided into two sub-layers. The first sub-layer is the acid gas adsorption sub-layer, which uses activated alumina (specific surface area ≥200m² / g) with a sodium hydroxide loading of 5-8wt%, and a SO2 penetration capacity of ≥50mg / g, and removes nitrogen oxides and sulfur oxides by chemical adsorption; the second sub-layer is the volatile organic compound (VOCs) adsorption sub-layer, which uses honeycomb activated carbon (iodine value ≥1200mg / g, pore size distribution 80% <2nm), with a benzene vapor adsorption capacity ≥450mg / g, and removes VOCs by physical adsorption.

[0051] Furthermore, the filter module adopts a quick-disassembly structure, and each level of filter layer can be replaced independently, with a replacement time of ≤5 minutes.

[0052] Furthermore, to ensure circulation efficiency, differential pressure sensors are installed between each filter layer to monitor blockage conditions and avoid air intake problems. A differential pressure sensor is installed after each filter layer in the filter module, and the differential pressure sensor is 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 constitute a pressure gradient matrix, and the Kalman filter algorithm is used to eliminate noise interference caused by airflow pulsation. When a certain level of filter material is partially blocked, the ratio of the differential pressure increment of this layer to the adjacent layer will exceed the preset threshold, triggering an adaptive compensation mechanism.

[0053] The data transmission module uses wired transmission and / or wireless transmission to ensure the effectiveness of data transmission, and transmits data to the terminal and background processing platform to monitor the intake status and the working status of the fuel cell in real time. It can realize real-time self-inspection and transmit the processed data to the feedback adjustment system to achieve self-optimization operation.

[0054] The data processing module includes a data storage submodule, a data processing and analysis submodule, and a warning submodule. The data storage submodule stores transmitted data to the terminal for analysis of the impact of gas impurities on fuel cell performance and provides recommendations for further optimization of the fuel cell intake module. The data processing and analysis submodule filters the collected data and monitors outliers, generating images of changes over time in the intake duct impurity concentration and fuel cell voltage and current during fuel cell vehicle operation to ensure normal operation and working conditions. The warning submodule issues warnings of anomalies, prompting drivers and passengers to take action and proactively intervene.

[0055] The data storage submodule can adopt blockchain distributed storage technology. Each data block stores the data collected by the detection module and the data of the terminal, which facilitates the analysis of the impact of gas impurities on fuel cell performance and provides suggestions for intake system optimization.

[0056] Furthermore, the data processing and analysis submodule in the data processing module analyzes and processes the data collected by the monitoring module, determines whether the filtering meets the standards, and issues early warnings based on the filtering effect, including:

[0057] Sa. Calculate the outlet concentration of each impurity at the outlet of the intake duct based on the inlet concentration of each impurity at the inlet of the intake duct collected by the monitoring module and the initial filtration efficiency of each filter layer in the filtration module.

[0058] In some embodiments, the calculation formula for the outlet concentration of each impurity is as follows:

[0059] ;

[0060] Among them, 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 i-th filter layer in the filter module, It represents the initial filtration efficiency of the i-th filter layer in the filter module, and n represents the total number of filter layers in the filter module.

[0061] Specifically, the concentration of each impurity at the inlet of the first-stage filter layer is the original air impurity concentration of the entire intake system, which can be directly measured by an impurity concentration sensor installed at the front end of the filter module (at the initial position of the intake duct). This sensor is part of the monitoring system. The concentration of each impurity at the inlet of the second-stage filter layer is the concentration of each impurity at the outlet of the first-stage filter layer, and the concentration of each impurity at the inlet of the third-stage filter layer is the concentration of each impurity at the outlet of the second-stage filter layer.

[0062] For example, assuming that the initial concentration of an impurity is 100 ppm, the design filtration efficiency of each filter layer is:

[0063] Filtration efficiency of the first filter layer =80%, determined by the physical interception performance of gradient density fiber filter cotton;

[0064] Second stage filter layer filtration efficiency =90%, determined by the filtration performance of glass fiber;

[0065] Filtration efficiency of the third filter layer = 95%, determined by the chemical adsorption properties of activated alumina impregnated with sodium hydroxide and the physical adsorption properties of honeycomb activated carbon);

[0066] The concentration of the impurity at the outlet of the third-stage filter layer is the outlet concentration of the impurity. The calculation formula for the outlet concentration of the impurity is:

[0067] .

[0068] The filtration efficiency of each level is calculated by combining design efficiency with real-time pressure differential correction. Using raw data from front-end concentration sensors, the concentration of intermediate levels is derived through recursive relationships. This reduces hardware costs while ensuring the accuracy of efficiency calculations through dynamic corrections. Ultimately, the overall filtration effect is verified through the total outlet concentration, enabling the system's self-optimization and early warning capabilities.

[0069] Sb. Compare the outlet concentration of each impurity at the outlet of the intake pipe with the preset standard limit of each impurity, and issue an early warning based on the filtering effect.

[0070] In some embodiments, the graded warning includes:

[0071] If the outlet concentration of all impurities is less than or equal to the first preset percentage of the corresponding preset standard limit, the filtration effect meets the standard and no warning is issued;

[0072] If the outlet concentration of at least one impurity exceeds the first preset percentage of the preset standard limit, a first-level warning will be issued, and the terminal will prompt "filtration efficiency has decreased, inspection is recommended";

[0073] If the outlet concentration of at least one impurity exceeds the preset standard limit, a secondary warning will be issued, the air compressor will be linked to close the air intake channel, and the backup filter circuit will be started.

[0074] Among them, the first preset percentage can be set to 80%.

[0075] For example, the preset standard limit value (C std,j )for:

[0076] SO2≤0.1ppm, NO x≤5ppm, NH3≤3ppm, VOCs≤0.05ppm, PM2.5≤10μg / m 3 , the standard limit is adjusted according to actual conditions.

[0077] In some embodiments, the data processing module is further used to detect the pressure difference when a filter layer at a certain level is blocked by impurities based on the data collected by the monitoring module. When the pressure rises, the filtration efficiency will decrease. The blockage status of each level of filtration layer is monitored in real time through the pressure difference sensor. When the pressure difference of a certain level of filtration layer in the filter module reaches the second preset percentage of the maximum allowable pressure difference, the filtration efficiency correction calculation is triggered and the filter material replacement warning is generated simultaneously; among which, the second preset percentage can be 70%.

[0078] The calculation formula for triggering the filtration efficiency correction calculation is as follows:

[0079] ;

[0080] in, It represents the corrected filtration efficiency of the i-th filter layer in the filtration module, It represents the initial filtration efficiency of the i-th filter layer in the filtration module, It represents the differential pressure data collected by the differential pressure sensor after the i-th filter layer in the filter module. Indicates the maximum allowable pressure difference of the i-th filter layer in the filter module to ensure the real-time efficiency correction.

[0081] If the monitoring module detects an increase in impurity content in the intake duct or abnormal operation of the fuel cell module, the feedback adjustment module can alert the driver and passengers to pay attention to maintenance. At the same time, it can also actively intervene based on PID control to adjust the intake flow of the intake module, the working status of the filter module and the humidity of the proton membrane.

[0082] The feedback regulation module uses a fuzzy PID algorithm to adjust the intake air flow (adjustment step size ≤ 5%) based on the stack voltage fluctuation (ΔV ≥ ± 5mV) and the impurity concentration change rate (ΔC / Δt ≥ 0.5ppm / s). The calculation formula for adjusting the intake air flow through PID control is as follows:

[0083] ;

[0084] Among them, K p , K i , K d They represent the proportional, integral, and differential control parameters respectively. Each control parameter is adjusted through fuzzy rules according to the concentration change rate and the operating voltage fluctuation of the fuel cell stack. u(t) represents the control signal output to the intake flow control valve, which drives the valve body opening to change, thereby adjusting the intake flow. e(t) represents the deviation between the real-time impurity concentration and the preset standard limit.

[0085] The present invention adopts the coordinated monitoring of impurity component sensors and concentration sensors to capture the dynamic changes of the concentrations of different impurity components in real time. At the filtration protection level, based on the three-level barrier architecture of mechanical pre-filtration, ultrafine particle interception and chemical adsorption, different forms of pollutants are eliminated in a gradient manner. The gradient density fiber layer intercepts large suspended particles through a progressive pore structure, and the glass fiber filter material forms a dense network to capture submicron particles. The composite adsorption layer relies on the acid-base neutralization properties of sodium hydroxide-modified activated alumina to eliminate acidic gases, and realizes efficient adsorption of benzene substances through the huge specific surface area of ​​honeycomb activated carbon; the data acquisition system integrates pressure difference sensing and dynamic correction algorithm to track the blockage status of filter materials at all levels in real time and calibrate the filtration efficiency parameters, so that the intake flow control valve can be predictively adjusted according to the impurity concentration change trend and the stack voltage fluctuation characteristics, and the flow compensation mechanism is triggered in advance when the pollutant concentration surges. The system uses the closed-loop control logic of "monitoring-interception-feedback" to monitor the composition and content of impurities in the intake duct in real time, and transmits data to the terminal through the data acquisition system to observe the impact of air impurities on fuel cell performance. Based on the output data, the system adjusts the intake flow in real time. At the same time, it designs multi-layer filtering protection barriers to reduce the entry of impurity gases into the fuel cell stack and increase the service life of the fuel cell.

[0086] Figure 3 This is a flowchart of a self-checking and optimizing fuel cell intake system provided by an embodiment of the present invention, see Figure 3 , an embodiment of the present invention also provides a method for self-checking and optimizing a fuel cell intake system:

[0087] S1. Monitor the impurity composition and concentration through the impurity composition sensor and concentration sensor of the monitoring module, and monitor the working status of the fuel cell through the current and voltage sensor and impedance spectrum analyzer;

[0088] S2. Transmitting the collected data to the vehicle control system and the user terminal respectively by means of wired and / or wireless means through the data transmission module;

[0089] S3. The data storage submodule of the data processing module stores the terminal data to facilitate analysis of the impact of gas impurities on fuel cell performance and provide suggestions for intake system optimization;

[0090] S4. The data processing and analysis submodule of the data processing module performs filtering, outlier detection and other processing and analysis on the collected data to generate a time variation curve of the impurities and a variation curve of the operating voltage and current of the fuel cell to determine the impact of the impurities;

[0091] S5. The early warning submodule of the data processing module compares the processed data with the preset standard limit value. If the preset standard limit value is exceeded, an alarm is issued to alert the driver and passengers.

[0092] S6. The feedback adjustment module adjusts the working state, air intake flow rate, etc. of the filter module according to the early warning data.

[0093] 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 above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.

Claims

1. A self-checking and optimizing fuel cell intake system, characterized in that: include: Monitoring module, filtering module, feedback adjustment module, data transmission module and data processing module; The monitoring module is used to monitor the impurity parameters in the intake pipe and the working status parameters of the fuel cell stack; The filtration module consists of a mechanical pre-filtration layer, a high-efficiency particulate air filtration layer and an adsorption layer, which is used to filter impurities in the air intake duct; the adsorption layer includes an acid gas adsorption sublayer and a volatile organic compound adsorption sublayer; A pressure differential sensor is provided after each level in the filtering module, and the pressure differential 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, determine whether the filtering meets the standards, and issue an early warning based on the filtering effect; The specific steps include: Sa, calculating the outlet concentration of each impurity at the outlet of the intake duct based on the inlet concentration of each impurity at the inlet of the intake duct collected by the monitoring module and the initial filtration efficiency of each filter layer in the filtration module; The calculation formula for the outlet concentration of each impurity is as follows: ； Among them, 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 i-th filter layer in the filter module, represents the initial filtration efficiency of the i-th filter layer in the filter module, and n represents the total number of filter layers in the filter module; Sb. comparing the outlet concentration of each impurity at the outlet of the intake pipe with the preset standard limit of each impurity, and issuing an early warning based on the filtering effect; The data processing module is also used to correct the filtration efficiency of each filter layer of the filtration module in real time based on the data collected by the monitoring module, and simultaneously generate an early warning for filter material replacement, specifically including: The clogging status of each filter layer is monitored in real time through the pressure differential sensor. When the pressure differential of a filter layer in the filter module reaches the second preset percentage of the maximum allowable pressure differential, the filtration efficiency correction calculation is triggered and a filter material replacement warning is generated simultaneously; The calculation formula for triggering the filtration efficiency correction calculation is as follows: ； in, It represents the corrected filtration efficiency of the i-th filter layer in the filtration module, It represents the initial filtration efficiency of the i-th filter layer in the filtration module, It represents the differential pressure data collected by the differential pressure sensor after the i-th filter layer in the filter module. Indicates the maximum allowable pressure difference of the i-th filter layer in the filter module; The feedback regulation module is connected to the monitoring module signal and is used to adjust the intake air flow rate 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 and optimizing fuel cell air intake system according to claim 1, characterized in that: 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 and optimizing fuel cell air intake system according to claim 1, characterized in that: In the filtration module, the mechanical pre-filtration layer uses PET gradient density fiber filter cotton, with an initial pressure difference of ≤0.5kPa and a dust holding capacity of ≥150g / m²; the high-efficiency particulate air filtration layer uses borosilicate glass fiber filter material, with a fiber diameter of 1-3μm and a filtration wind speed of 0.1-0.4m / s; the acid gas adsorption sublayer uses activated alumina with a sodium hydroxide loading of 5-8wt% and a specific surface area of ​​≥200m² / g; the volatile organic compound adsorption sublayer uses a honeycomb activated carbon structure, with an iodine value of ≥1200mg / g and a pore size distribution of 80% <2nm.

4. The self-checking and optimizing fuel cell air intake system according to claim 1, characterized in that: The filter module adopts a quick-detachable structure, and each level of filter layer can be replaced independently.

5. The self-checking and optimizing fuel cell air intake system according to claim 1, characterized in that: In the above-mentioned Sb, comparing the outlet concentration of each impurity at the outlet of the intake pipe with the preset standard limit of each impurity and issuing an early warning based on 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, the filtration effect meets the standard and no warning is issued; If the outlet concentration of at least one impurity exceeds a first preset percentage of the preset standard limit, a first-level warning is issued; If the outlet concentration of at least one impurity exceeds the preset standard limit, a second-level warning will be issued.

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