Hydrogen purity detection system and method for solid hydrogen storage medium

Abstract

The embodiment of the application discloses a hydrogen purity detection system and method of solid-state hydrogen storage medium, relates to the technical field of solid-state hydrogen storage system monitoring, and the hydrogen purity detection system of the solid-state hydrogen storage medium comprises: a sampling pretreatment unit in communication with an outlet pipeline of a solid-state hydrogen storage system; a multi-parameter coupling detection unit in communication with an output end of the sampling pretreatment unit, comprising a thermal conductivity sensor, an electrochemical sensor group and a miniature Raman spectrum sensor arranged integrally and used for synchronously collecting multi-dimensional detection parameters of hydrogen; and a data processing and linkage control unit in communication connection with the multi-parameter coupling detection unit, a control end of the solid-state hydrogen storage system and a valve control end of a fuel cell respectively, wherein the data processing and linkage control unit is internally provided with a multi-sensing data fusion model, hydrogen purity and impurity component content are obtained, linkage control instructions are output to the valve control end of the solid-state hydrogen storage system and the fuel cell when the detection result is abnormal, and a warning is triggered.

Description

Technical Field

[0001] This application relates to the technical field of monitoring solid hydrogen storage systems, and in particular to a hydrogen purity detection system and method for solid hydrogen storage media. Background Technology

[0002] Solid-state hydrogen storage has become a core technology for hydrogen storage in long-term energy storage systems due to its advantages of high volumetric hydrogen storage density and good safety. However, after multiple hydrogen charging and discharging cycles, solid-state hydrogen storage media are prone to problems such as catalytic performance decay and pipeline sealing leaks, which can lead to a decrease in the purity of the output hydrogen and excessive levels of harmful impurities such as O2, N2, CO, and H2O. If substandard hydrogen enters the fuel cell, it can easily cause catalyst poisoning and seriously affect the reliability of system operation.

[0003] There are two main technical solutions for hydrogen purity detection in existing solid-state hydrogen storage systems, both of which have significant drawbacks: (1) Offline sampling detection: Manual sampling is performed after the hydrogen charging and discharging process is completed and sent to the laboratory for gas chromatography detection. The detection cycle is long and there is a significant lag. It cannot reflect the dynamic changes in hydrogen purity during the charging and discharging process in real time, and it cannot detect the problem of excessive impurities in time, which can easily lead to the continuous supply of unqualified hydrogen to the fuel cell; (2) Online single sensor detection: A single thermal conductivity sensor or electrochemical sensor is set in the hydrogen storage outlet pipeline. It can only detect the total purity of hydrogen or a certain specific impurity. The impurity coverage is narrow, the detection accuracy is low, and it is easily affected by environmental interference. At the same time, the sampling volume of the existing online detection scheme is large, which is an invasive detection method. It will interfere with the stability of the charging and discharging hydrogen pressure of the solid-state hydrogen storage system and affect the normal operation of the hydrogen storage system.

[0004] Furthermore, existing detection schemes lack effective abnormal linkage protection mechanisms, cannot quickly cut off the gas path when impurities exceed the standard, and have not established a correlation analysis between hydrogen purity and the number of hydrogen charging and discharging cycles of the hydrogen storage medium. They cannot provide data support for the maintenance and replacement of the hydrogen storage medium, making it difficult to meet the high reliability and long-cycle operation requirements of solid-state hydrogen storage systems.

[0005] Therefore, a solution is urgently needed to address the above problems. Summary of the Invention

[0006] This application proposes a hydrogen purity detection system and method for solid hydrogen storage media to address the deficiencies of the prior art.

[0007] According to a first aspect of the embodiments of this application, a hydrogen purity detection system for a solid hydrogen storage medium is provided, comprising: The sampling pretreatment unit is connected to the outlet pipeline of the solid hydrogen storage system and is used to perform low-invasive micro-sampling and standardized pretreatment of hydrogen released by the solid hydrogen storage medium during the charging and discharging process. A multi-parameter coupled detection unit, connected to the output of the sampling preprocessing unit, includes an integrated thermal conductivity sensor, an electrochemical sensor group, and a miniature Raman spectroscopy sensor, used to simultaneously acquire multi-dimensional detection parameters of hydrogen. The data processing and linkage control unit is communicatively connected to the multi-parameter coupled detection unit, the control terminal of the solid hydrogen storage system, and the valve control terminal of the fuel cell. The data processing and linkage control unit has a built-in multi-sensor data fusion model, which is used to perform fusion calculation on the multi-dimensional detection parameters to obtain the hydrogen purity and impurity component content. When the detection results are abnormal, it outputs linkage control commands to the valve control terminals of the solid hydrogen storage system and the fuel cell, and triggers early warnings.

[0008] In some embodiments, the sampling preprocessing unit includes a bypass micro-sampling structure and a filter, pressure reduction, and flow stabilization module; the bypass micro-sampling structure includes a bypass branch pipe, a micro-sampling pump, and a flow regulating valve, wherein the sampling flow rate of the micro-sampling pump is not greater than 100 ml / min.

[0009] In some embodiments, the filtration, pressure reduction, and flow stabilization module includes, in sequence along the hydrogen flow direction, a precision filter, a pressure reducing valve, and a flow stabilizing valve; the precision filter has a filtration accuracy of not less than 0.1 micrometers, the pressure reducing valve is used to reduce the hydrogen pressure range from 1 MPa to 10 MPa to 0.1 MPa to 0.2 MPa, and the flow stabilizing valve is used to control the sampling flow rate at a set value.

[0010] In some embodiments, the electrochemical sensor array includes an oxygen sensor, a carbon monoxide sensor, and a water vapor sensor; the multi-sensor data fusion model is a pre-trained BP neural network model.

[0011] In some implementations, the data processing and linkage control unit supports communication and linkage with external devices and is equipped with an audible and visual alarm module.

[0012] According to a second aspect of this application, a method for detecting the purity of hydrogen in a solid hydrogen storage medium is provided, implemented based on the hydrogen purity detection system for a solid hydrogen storage medium as described above, comprising: A standardized hydrogen sample is obtained by bypassing and pre-processing the hydrogen at the outlet of the solid hydrogen storage medium through a sampling pre-processing unit. The multi-parameter coupled detection unit is controlled to acquire multi-dimensional detection parameters of the standardized hydrogen sample at a set sampling frequency; The multi-dimensional detection parameters are input into the multi-sensor data fusion model for weighted fusion calculation to obtain hydrogen purity, impurity types and the content of each impurity. The detection results obtained by fusion calculation are compared with a preset threshold to obtain a comparison result; wherein, when the comparison result is abnormal, an early warning is triggered and a control command for cutting off the relevant gas path is output; when the comparison result is normal, the detection data is updated and stored. The detection results are correlated with the number of hydrogen charging and discharging cycles of the solid hydrogen storage medium and stored for performance analysis.

[0013] In some embodiments, the method further includes: The pressure of the standardized hydrogen sample was controlled to be 0.1 MPa and the flow rate to be 50 mL / min.

[0014] In some implementations, the step of inputting the multi-dimensional detection parameters into a multi-sensor data fusion model for weighted fusion calculation includes: For carbon monoxide and water vapor in the multi-dimensional detection parameters, the weighting coefficient of the electrochemical sensor group is the highest based on the multi-sensor data fusion model. For nitrogen and methane among the multi-dimensional detection parameters, the weighting coefficient of the micro Raman spectroscopy sensor controlled by the multi-sensor data fusion model is the highest.

[0015] In some embodiments, the preset thresholds include, but are not limited to, hydrogen purity not less than 99.97%, carbon monoxide content not greater than 0.2 ppm, oxygen content not greater than 5 ppm, and water vapor content not greater than 5 ppm. The method further includes: The response time from when the comparison result is abnormal to when the linkage control command is output shall not exceed 5 seconds.

[0016] In some embodiments, the method further includes: The detection data is associated with the operating conditions of the hydrogen storage medium and stored, and then uploaded remotely. The storage period for the detection data is no less than one year.

[0017] The beneficial effects of the hydrogen purity detection system and method for solid hydrogen storage media in this application include at least the following: This application embodiment employs a multi-parameter coupled detection unit consisting of a thermal conductivity sensor, an electrochemical sensor group, and a miniature Raman spectroscopy sensor. Combined with a built-in BP neural network multi-sensor data fusion model, it performs weighted fusion calculations on multi-dimensional detection data. This enables simultaneous and accurate identification of multiple components such as hydrogen, oxygen, nitrogen, carbon monoxide, water vapor, and methane. The hydrogen purity detection accuracy reaches 99.999%, the impurity detection limit is as low as 0.1 ppm, and the sampling frequency is 1 Hz with a detection response time of no more than 5 seconds. This completely solves the problems of low detection accuracy, narrow impurity identification range, and large lag in existing technologies, and can reflect the dynamic changes in hydrogen purity during the charging and discharging process in real time and comprehensively. This application embodiment, through the design of a bypass micro-sampling structure including a bypass branch pipe, a micro-sampling pump, and a flow regulating valve, enables the system to sample at an extremely low flow rate of no more than 100 mL / min. The impact on pressure fluctuations during the hydrogen charging and discharging process of the solid-state hydrogen storage system is less than 0.5%, and the impact on flow rate is less than 0.1%. This allows for online detection without interrupting the normal operation of the hydrogen storage system, overcoming the shortcomings of traditional online detection methods, such as large sampling volumes and interference with system stability. This application embodiment, through data processing and linkage control units, can quickly identify anomalies within 5 seconds when hydrogen purity is detected to be below the threshold or any harmful impurities exceed the standard. Simultaneously, it triggers on-site audible and visual alarms and automatically outputs control commands to shut off the charging and discharging control valves of the solid-state hydrogen storage system and the inlet valve of the fuel cell. This multi-protection mechanism effectively prevents substandard hydrogen from entering the fuel cell and causing catalyst poisoning, reducing the probability of related failures by more than 80%, and supports remote early warning, achieving rapid fault response. This application embodiment can store all detection data for a long time and support remote uploading, and accurately correlate hydrogen purity and impurity content data with the number of hydrogen charging and discharging cycles and operating conditions of the solid hydrogen storage medium; through big data analysis, it can generate intuitive hydrogen storage medium performance degradation curves, thereby providing scientific quantitative data support for preventive maintenance, maintenance timing judgment and replacement decisions of hydrogen storage medium, realizing refined management of the entire life cycle of hydrogen storage medium, and extending the service life of the entire hydrogen storage system. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of a hydrogen purity detection system for a solid hydrogen storage medium according to an embodiment of this application. Figure 2 This is a schematic flowchart of a method for detecting the purity of hydrogen in a solid hydrogen storage medium according to an embodiment of this application. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the various embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. However, those skilled in the art will understand that many technical details have been provided in the various embodiments of this disclosure to facilitate a better understanding of the disclosure. However, the technical solutions claimed in this disclosure can be implemented even without these technical details and with various variations and modifications based on the following embodiments. The division of the various embodiments below is for ease of description and should not constitute any limitation on the specific implementation of this disclosure. The various embodiments can be combined with and referenced by each other without contradiction.

[0020] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the claimed embodiments of the present application, but merely to illustrate selected embodiments of the present application. Other embodiments obtained by those skilled in the art based on the embodiments of the present application without inventive effort are all within the scope of protection of the embodiments of the present application.

[0021] This application discloses a hydrogen purity detection system and method for solid-state hydrogen storage media. The method is applied to the hydrogen purity detection system for solid-state hydrogen storage media. This application is applicable to real-time hydrogen purity detection, impurity warning, and abnormal linkage protection during the hydrogen charging and discharging process of titanium-iron-based and magnesium-based solid-state hydrogen storage media in long-term energy storage scenarios. It enables hydrogen purity data traceability and performance monitoring throughout the entire lifecycle of the hydrogen storage media. The purpose of this application is to overcome the shortcomings of existing technologies and solve the technical problems of large detection lag, low detection accuracy, highly invasive sampling, narrow impurity identification range, and lack of effective abnormal linkage protection in solid-state hydrogen storage systems. It achieves low-invasive online micro-sampling, high-precision real-time identification of hydrogen purity and multiple impurity components through multi-parameter coupled detection, and simultaneously possesses rapid abnormal linkage control and data traceability functions, reducing the probability of fuel cell failures caused by hydrogen impurities and providing data support for the full lifecycle management of solid-state hydrogen storage media.

[0022] See attached document Figure 1 As shown, an embodiment of the present application illustrates a hydrogen purity detection system for a solid hydrogen storage medium, comprising: a sampling preprocessing unit, a multi-parameter coupling detection unit, and a data processing and linkage control unit. Each unit is sequentially connected and communicates with each other. The overall structure is a bypass design, which does not hinder the hydrogen charging and discharging operation of the main circuit of the solid hydrogen storage system.

[0023] In some implementations, the sampling pretreatment unit is connected to the outlet pipeline of the solid hydrogen storage system and is used to perform low-invasive micro-sampling and standardized pretreatment of hydrogen released by the solid hydrogen storage medium during the charging and discharging process.

[0024] In some embodiments, the sampling preprocessing unit includes a bypass micro-sampling structure and a filter, pressure reduction and flow stabilization module; the bypass micro-sampling structure includes a bypass branch pipe, a micro-sampling pump and a flow regulating valve, and the sampling flow rate of the micro-sampling pump is not greater than 100 ml / min.

[0025] In some embodiments, the filtration, pressure reduction, and flow stabilization module includes, in sequence along the hydrogen flow direction, a precision filter, a pressure reducing valve, and a flow stabilization valve; the precision filter has a filtration accuracy of not less than 0.1 micrometers, the pressure reducing valve is used to reduce the hydrogen pressure range from 1 MPa to 10 MPa to 0.1 MPa to 0.2 MPa, and the flow stabilization valve is used to control the sampling flow rate at a set value.

[0026] For example, the sampling pretreatment unit is connected to the outlet pipeline of the solid hydrogen storage medium and is located on the bypass of the outlet pipeline. It includes a bypass micro-sampling structure and a filtration, pressure reduction, and flow stabilization module to achieve low-intrusion micro-sampling and standardized pretreatment of hydrogen, meeting the requirements of subsequent sensor detection. The bypass micro-sampling structure consists of a bypass branch pipe, a micro-sampling pump, and a flow regulating valve. The sampling flow rate of the micro-sampling pump is in the range of 10 mL / min to 100 mL / min (sampling volume ≤ 100 sccm), and its impact on the hydrogen charging and discharging pressure fluctuation of the main pipeline of the hydrogen storage system is less than 0.5%, and its impact on the flow rate is less than 0.1%. The filtration, pressure reduction, and flow stabilization module consists of a precision filter, a pressure reducing valve, and a flow stabilizing valve, arranged sequentially along the hydrogen flow direction. The precision filter uses a 0.1μm sintered metal filter element with a filtration accuracy of no less than 0.1μm, effectively filtering powdery solid particles released from the solid hydrogen storage medium. The pressure reducing valve can reduce the high-pressure hydrogen gas at the hydrogen storage outlet from 1MPa to 10MPa to 0.1MPa to 0.2MPa. The flow stabilizing valve uses a thermal mass flow meter to stably control the sampled flow rate within ±1% error range, which is stable at 50sccm under normal operating conditions.

[0027] In some implementations, a multi-parameter coupled detection unit, connected to the output of the sampling preprocessing unit, includes an integrated thermal conductivity sensor, an electrochemical sensor group, and a miniature Raman spectroscopy sensor, for simultaneously acquiring multi-dimensional detection parameters of hydrogen.

[0028] In some embodiments, the electrochemical sensor array includes an oxygen sensor, a carbon monoxide sensor, and a water vapor sensor; the multi-sensor data fusion model is a pre-trained BP neural network model.

[0029] For example, the multi-parameter coupled detection unit is connected to the output of the sampling preprocessing unit, integrating a thermal conductivity sensor, an electrochemical sensor group, and a miniature Raman spectroscopy sensor. This allows for the simultaneous acquisition of multi-dimensional detection parameters of hydrogen, achieving comprehensive detection of total hydrogen purity and various impurities. The thermal conductivity sensor measures from 0% to 100% H2 with an accuracy of ±0.01%, and preliminarily calculates the total hydrogen purity by acquiring the difference in thermal conductivity between hydrogen and the background gas. The electrochemical sensor group includes dedicated electrochemical sensors for O2, CO, and H2O, each with a detection range of 0 ppm to 100 ppm. The detection limits for CO are 0.05 ppm, O2 0.1 ppm, and H2O 1 ppm, respectively detecting the electrochemical response signals of corresponding harmful impurities. The miniature Raman spectroscopy sensor can acquire the characteristic Raman spectral peak intensities of components such as H2, N2, and CH4, with a detection limit of 0.1 ppm, enabling accurate identification of non-electrochemically responsive impurities.

[0030] In some implementations, the data processing and linkage control unit is communicatively connected to the multi-parameter coupled detection unit, the control terminal of the solid hydrogen storage system, and the valve control terminal of the fuel cell, respectively. The data processing and linkage control unit has a built-in multi-sensor data fusion model, which is used to perform fusion calculation on the multi-dimensional detection parameters to obtain the hydrogen purity and impurity component content, and output linkage control commands to the valve control terminals of the solid hydrogen storage system and the fuel cell when the detection results are abnormal, and trigger an early warning.

[0031] In some implementations, the data processing and linkage control unit supports communication and linkage with external devices and is equipped with an audible and visual alarm module.

[0032] For example, the data processing and linkage control unit communicates with the multi-parameter coupling detection unit, the control terminal of the solid-state hydrogen storage system, and the valve control terminal of the fuel cell, respectively. It uses an ARM architecture processor (such as the STM32F4 series), has a storage capacity of ≥64G, supports the MODBUS (MODBUS-RTU) communication protocol, and can seamlessly link with the hydrogen storage system PLC and fuel cell controller. Its core functions are data fusion calculation and abnormal linkage control. Specifically, it uses a built-in pre-trained BP neural network multi-sensor data fusion model to perform weighted fusion calculations on the output data from the thermal conductivity sensor, electrochemical sensor group, and Raman spectroscopy sensor. Based on the detection sensitivity of each sensor for different impurities, it calibrates the weight coefficients, eliminates single-sensor detection errors, and accurately outputs the hydrogen purity, impurity type, and content of each impurity. The detection sensitivity calibration weight coefficients are shown in Table 1 below. Table 1: Weighting Coefficients for Multi-Sensor Weighted Fusion

[0033] Based on this, a linkage control interface and an audible and visual alarm module are configured. When the detection result is abnormal, the linkage control command is output in real time, and the on-site audible and visual alarm is triggered. The abnormal data is also uploaded to the station-level management platform. It supports long-term storage of detection data (storage period ≥ 1 year) and 4G remote data upload. The detection result can be correlated with the number of hydrogen charging and discharging cycles of the solid hydrogen storage medium to generate a medium performance degradation curve.

[0034] This application embodiment employs a multi-parameter coupled detection unit consisting of a thermal conductivity sensor, an electrochemical sensor group, and a miniature Raman spectroscopy sensor. Combined with a built-in BP neural network multi-sensor data fusion model, it performs weighted fusion calculations on multi-dimensional detection data. This enables simultaneous and accurate identification of multiple components such as hydrogen, oxygen, nitrogen, carbon monoxide, water vapor, and methane. The hydrogen purity detection accuracy reaches 99.999%, the impurity detection limit is as low as 0.1 ppm, and the sampling frequency is 1 Hz with a detection response time of no more than 5 seconds. This completely solves the problems of low detection accuracy, narrow impurity identification range, and large lag in existing technologies, and can reflect the dynamic changes in hydrogen purity during the charging and discharging process in real time and comprehensively. This application embodiment, through the design of a bypass micro-sampling structure including a bypass branch pipe, a micro-sampling pump, and a flow regulating valve, enables the system to sample at an extremely low flow rate of no more than 100 mL / min. The impact on pressure fluctuations during the hydrogen charging and discharging process of the solid-state hydrogen storage system is less than 0.5%, and the impact on flow rate is less than 0.1%. This allows for online detection without interrupting the normal operation of the hydrogen storage system, overcoming the shortcomings of traditional online detection methods, such as large sampling volumes and interference with system stability. This application embodiment, through data processing and linkage control units, can quickly identify anomalies within 5 seconds when hydrogen purity is detected to be below the threshold or any harmful impurities exceed the standard. Simultaneously, it triggers on-site audible and visual alarms and automatically outputs control commands to shut off the charging and discharging control valves of the solid-state hydrogen storage system and the inlet valve of the fuel cell. This multi-protection mechanism effectively prevents substandard hydrogen from entering the fuel cell and causing catalyst poisoning, reducing the probability of related failures by more than 80%, and supports remote early warning, achieving rapid fault response. This application embodiment can store all detection data for a long time and support remote uploading, and accurately correlate hydrogen purity and impurity content data with the number of hydrogen charging and discharging cycles and operating conditions of the solid hydrogen storage medium; through big data analysis, it can generate intuitive hydrogen storage medium performance degradation curves, thereby providing scientific quantitative data support for preventive maintenance, maintenance timing judgment and replacement decisions of hydrogen storage medium, realizing refined management of the entire life cycle of hydrogen storage medium, and extending the service life of the entire hydrogen storage system.

[0035] See attached document Figure 2As shown in the embodiments of this application, a method for detecting the purity of hydrogen in a solid hydrogen storage medium is also disclosed. This method is based on the hydrogen purity detection system for a solid hydrogen storage medium described above. This method is a low-intrusion, high-precision, and real-time online method for detecting hydrogen purity. It includes the following steps S1 to S5.

[0036] Step S1: Bypass micro-sampling and preprocessing of hydrogen gas at the outlet of solid hydrogen storage medium through sampling preprocessing unit to obtain standardized hydrogen gas sample.

[0037] In some embodiments, the method further includes controlling the pressure of the standardized hydrogen sample to be 0.1 MPa and the flow rate to be 50 mL / min.

[0038] In some embodiments, the sampling preprocessing unit performs bypass micro-sampling and preprocessing of hydrogen at the outlet of the solid hydrogen storage medium to obtain a standardized hydrogen sample. This includes: during the charging and discharging of hydrogen in the solid hydrogen storage system, the sampling preprocessing unit collects hydrogen samples from the outlet pipeline through a bypass micro-sampling structure. The samples are then subjected to 0.1μm precision filtration, 1MPa-10MPa to 0.1MPa-0.2MPa pressure reduction, and ±1% error stabilization processing by a filtration, depressurization, and flow stabilization module to obtain standardized hydrogen to be tested with a pressure of 0.1MPa and a flow rate of 50sccm. The standardized hydrogen sample is then sent to a multi-parameter coupling detection unit.

[0039] Step S2: Control the multi-parameter coupling detection unit to collect multi-dimensional detection parameters of the standardized hydrogen sample at a set sampling frequency.

[0040] In some embodiments, the control multi-parameter coupling detection unit acquires multi-dimensional detection parameters of the standardized hydrogen sample at a set sampling frequency, including: controlling the thermal conductivity sensor, electrochemical sensor group, and miniature Raman spectroscopy sensor of the control multi-parameter coupling detection unit to work synchronously, acquiring the thermal conductivity parameters, impurity electrochemical response parameters, and spectral characteristic parameters of the hydrogen to be detected at a sampling frequency of 1Hz, and transmitting the acquired data to the data processing and linkage control unit in real time.

[0041] Step S3: Input the multi-dimensional detection parameters into the multi-sensor data fusion model for weighted fusion calculation to obtain the hydrogen purity, impurity types and the content of each impurity.

[0042] In some embodiments, the multi-dimensional detection parameters are input into a multi-sensor data fusion model for weighted fusion calculation to obtain hydrogen purity, impurity types, and the content of each impurity. This includes: inputting the collected three types of multi-dimensional detection parameters into a pre-trained BP neural network multi-sensor data fusion model, performing weighted fusion calculation according to the weight coefficients in Table 1, eliminating single-sensor detection errors, and obtaining the final total hydrogen purity, impurity types, and the precise content of each impurity.

[0043] Step S4: Compare the detection results obtained by fusion calculation with the preset threshold to obtain the comparison result; wherein, if the comparison result is abnormal, trigger an early warning and output a control command to cut off the relevant gas path; if the comparison result is normal, update and store the detection data.

[0044] In some implementations, the multi-dimensional detection parameters are input into a multi-sensor data fusion model for weighted fusion calculation, including: for carbon monoxide and water vapor in the multi-dimensional detection parameters, the weight coefficient of the electrochemical sensor group is controlled to be the highest based on the multi-sensor data fusion model; for nitrogen and methane in the multi-dimensional detection parameters, the weight coefficient of the micro Raman spectroscopy sensor is controlled to be the highest based on the multi-sensor data fusion model.

[0045] In some implementations, the preset thresholds include, but are not limited to, hydrogen purity not less than 99.97%, carbon monoxide content not more than 0.2 ppm, oxygen content not more than 5 ppm, and water vapor content not more than 5 ppm.

[0046] In some implementations, the detection results obtained from the fusion calculation are compared with preset thresholds to obtain a comparison result. When the comparison result is abnormal, an early warning is triggered and a control command to cut off the relevant gas path is output. When the comparison result is normal, the detection data is updated and stored, including: comparing the fusion calculation detection results with preset thresholds for hydrogen used in fuel cells (preset thresholds: hydrogen purity ≥ 99.97%, CO content ≤ 0.2 ppm, O2 content ≤ 5 ppm, H2O content ≤ 5 ppm, N2 and CH4 have no obvious characteristic peaks): If the detection result is normal: the detection data is updated every 1 Hz, stored in real time, and uploaded to the station-level management platform; if the detection result is abnormal (purity below the threshold or any harmful impurity content exceeds the standard): the abnormality is identified within ≤ 5 seconds, an on-site audible and visual alarm is immediately triggered, and a control command is automatically output to cut off the charging and discharging control valve of the solid hydrogen storage system and the inlet valve of the fuel cell to prevent unqualified hydrogen from entering the fuel cell; and the abnormal data and alarm information are uploaded in real time to the station-level management platform and the maintenance personnel's terminal.

[0047] Step S5: The test result is correlated with the number of hydrogen charging and discharging cycles of the solid hydrogen storage medium and stored for performance analysis.

[0048] In some implementations, the test results are associated with the number of hydrogen charging and discharging cycles of the solid hydrogen storage medium for performance analysis. This includes: associating the test results of hydrogen purity and impurity content throughout the cycle with the number of hydrogen charging and discharging cycles and operating conditions of the solid hydrogen storage medium; generating a performance degradation curve of the solid hydrogen storage medium through big data analysis; and providing quantitative data support for the maintenance, upkeep, and replacement of the hydrogen storage medium.

[0049] In some implementations, the method further includes: the response time from when the comparison result is abnormal to when the linkage control command is output is no more than 5 seconds.

[0050] In some embodiments, the method further includes: storing the detection data in association with the operating conditions of the hydrogen storage medium and uploading it remotely, wherein the storage period for the detection data is not less than one year.

[0051] To further illustrate the embodiments of this application, a detailed description is provided below in conjunction with a specific implementation process of this application. This specific implementation process is adapted to a long-term energy storage system for a 100kg-class titanium-iron-based solid-state hydrogen storage array. The hydrogen requirements for its fuel cell are: purity ≥99.97%, CO content ≤0.2ppm, O2 content ≤5ppm, H2O content ≤5ppm, and the solid-state hydrogen storage charging and discharging pressure range is 1 MPa - 3 MPa.

[0052] The system hardware configuration includes: 1) Sampling pretreatment unit: a bypass branch pipe with a diameter of 6mm, connected to the outlet main pipe of the solid hydrogen storage tank array; a micro-sampling pump with a rated sampling flow rate of 50sccm, and a flow regulating valve with an adjustable range of 10mL / min—100mL / min; a precision filter with a 0.1μm sintered metal filter element; a pressure reducing valve to reduce the inlet hydrogen pressure from 1MPa-3MPa to 0.1MPa; and a flow stabilizing valve with a thermal mass flow meter, a flow control error of ±0.5%, and an impact on the main hydrogen flow rate of less than 0.05%. 2) Multi-parameter coupled detection unit: a thermal conductivity sensor with a measurement range of 0%—100%H2 and an accuracy of ±0.01%; an electrochemical sensor array including O2, CO, and H2O sensors, with a detection limit of 0.05ppm for CO, 0.1ppm for O2, and 1ppm for H2O; and a miniature Raman spectroscopy sensor capable of identifying characteristic peaks of H2, N2, and CH4, with a detection limit of 0.1ppm. 3) Data processing and linkage control unit: adopts STM32F4 series ARM processor, storage capacity 64G, supports MODBUS-RTU protocol and 4G remote upload; configured with sound and light alarm module, linkage solid hydrogen storage charging and discharging control valve and fuel cell intake valve; built-in pre-trained BP neural network multi-sensor data fusion model, weighted fusion weight coefficients are set according to Table 1.

[0053] The system operation process includes: 1) Normal operation: During the hydrogen release process of the solid hydrogen storage array, the sampling preprocessing unit performs a bypass micro-sampling at a flow rate of 50 sccm. The hydrogen is filtered through 0.1 μm, reduced in pressure by 0.1 MPa, and then sent to the multi-parameter coupling detection unit after stabilization. Each sensor collects data synchronously at a frequency of 1 Hz. The thermal conductivity sensor initially detects a hydrogen purity of 99.98%. The electrochemical sensor group detects a CO content of 0.1 ppm, an O2 content of 3 ppm, and an H2O content of 2 ppm. The Raman spectroscopy sensor does not detect the characteristic peaks of N2 and CH4. After the data is input into the BP neural network model for weighted fusion calculation, the hydrogen purity is obtained as 99.982%, and the content of all impurities meets the preset threshold. The detection data is updated every 1 Hz, stored in real time, and uploaded to the station-level management platform. 2) Abnormal Operating Condition Interaction: When the solid hydrogen storage medium reaches 500 hydrogen charging and discharging cycles, due to the decay of the medium's sealing performance, the electrochemical sensor group detected an increase in O2 content to 6 ppm during a certain test, and the Raman spectroscopy sensor detected a trace N2 characteristic peak. The data processing and linkage control unit identified the abnormality within 3.2 seconds, immediately triggered the on-site audible and visual alarm, and simultaneously sent a command to the hydrogen storage system PLC to close the charging and discharging control valve and a command to the fuel cell controller to close the inlet valve. The abnormal data (O2 content 6 ppm, trace N2 detected) and alarm information were uploaded in real time to the station-level management platform and the operation and maintenance personnel terminal, effectively preventing unqualified hydrogen from entering the fuel cell and causing catalyst poisoning.

[0054] This application embodiment achieves a hydrogen purity detection accuracy of 99.999% and an impurity detection limit as low as 0.1 ppm through multi-sensor coupled detection and weighted fusion calculation using a BP neural network. It can simultaneously and accurately identify six components: H2, O2, N2, CO, H2O, and CH4. With a sampling frequency of 1 Hz and a detection response time ≤ 5 s, it can reflect the dynamic changes in hydrogen purity during the charging and discharging process of the solid hydrogen storage medium in real time, solving the problems of low detection accuracy, narrow impurity identification range, and large hysteresis in existing technologies. This application embodiment also employs a bypass micro-sampling structure with a sampling volume ≤ 100 sccm, which has less than 0.5% impact on the main charging and discharging pressure fluctuations of the solid hydrogen storage system and less than 0.1% impact on the flow rate. It achieves full-process online detection without interrupting the operation of the hydrogen storage system, solving the problems of strong invasiveness and interference with system operation in existing online detection methods. This application embodiment, through the establishment of a multi-level abnormal linkage control and audible and visual early warning mechanism, can quickly cut off the gas path within seconds when impurities exceed the standard, effectively preventing unqualified hydrogen from entering the fuel cell and reducing the probability of fuel cell failure due to hydrogen impurities by more than 80%. It also supports remote data upload and maintenance early warning, enabling rapid response and handling of faults. This application embodiment, by correlating detection data with the number of hydrogen charging and discharging cycles of the hydrogen storage medium, generates a medium performance degradation curve, providing quantitative data support for the maintenance, upkeep, and replacement of the hydrogen storage medium. This achieves refined management of the entire life cycle of solid-state hydrogen storage media, extending the overall operating life of the hydrogen storage system.

[0055] The above description is merely a specific implementation of the embodiments of this application, but the protection scope of the embodiments of this application is not limited thereto. Any simple modifications, changes, and equivalent changes made by those skilled in the art to the above embodiments based on the technical essence of the embodiments of this application within the technical scope disclosed in the embodiments of this application shall still fall within the protection scope of the technical solution of the embodiments of this application.

Claims

1. A hydrogen purity detection system for a solid hydrogen storage medium, characterized in that, include: The sampling pretreatment unit is connected to the outlet pipeline of the solid hydrogen storage system and is used to perform low-invasive micro-sampling and standardized pretreatment of hydrogen released by the solid hydrogen storage medium during the charging and discharging process. A multi-parameter coupled detection unit, connected to the output of the sampling preprocessing unit, includes an integrated thermal conductivity sensor, an electrochemical sensor group, and a miniature Raman spectroscopy sensor, used to simultaneously acquire multi-dimensional detection parameters of hydrogen. The data processing and linkage control unit is communicatively connected to the multi-parameter coupled detection unit, the control terminal of the solid hydrogen storage system, and the valve control terminal of the fuel cell. The data processing and linkage control unit has a built-in multi-sensor data fusion model, which is used to perform fusion calculation on the multi-dimensional detection parameters to obtain the hydrogen purity and impurity component content. When the detection results are abnormal, it outputs linkage control commands to the valve control terminals of the solid hydrogen storage system and the fuel cell, and triggers early warnings.

2. The hydrogen purity detection system for solid hydrogen storage media according to claim 1, characterized in that, The sampling preprocessing unit includes a bypass micro-sampling structure and a filter, pressure reduction and flow stabilization module; the bypass micro-sampling structure includes a bypass branch pipe, a micro-sampling pump and a flow regulating valve, and the sampling flow rate of the micro-sampling pump is not greater than 100 ml / min.

3. The hydrogen purity detection system for solid hydrogen storage media according to claim 2, characterized in that, The filtration, pressure reduction, and flow stabilization module includes, in sequence along the hydrogen flow direction, a precision filter, a pressure reducing valve, and a flow stabilizing valve; the precision filter has a filtration accuracy of not less than 0.1 micrometers, the pressure reducing valve is used to reduce the hydrogen pressure range from 1 MPa to 10 MPa to 0.1 MPa to 0.2 MPa, and the flow stabilizing valve is used to control the sampling flow rate at a set value.

4. The hydrogen purity detection system for solid hydrogen storage media according to claim 1, characterized in that, The electrochemical sensor group includes an oxygen sensor, a carbon monoxide sensor, and a water vapor sensor; the multi-sensor data fusion model is a pre-trained BP neural network model.

5. The hydrogen purity detection system for solid hydrogen storage media according to claim 1, characterized in that, The data processing and linkage control unit supports communication and linkage with external devices and is equipped with an audible and visual alarm module.

6. A method for detecting the purity of hydrogen in a solid hydrogen storage medium, implemented based on the hydrogen purity detection system for a solid hydrogen storage medium according to any one of claims 1 to 5, characterized in that, include: A standardized hydrogen sample is obtained by bypassing and pre-processing the hydrogen at the outlet of the solid hydrogen storage medium through a sampling pre-processing unit. The multi-parameter coupled detection unit is controlled to acquire multi-dimensional detection parameters of the standardized hydrogen sample at a set sampling frequency; The multi-dimensional detection parameters are input into the multi-sensor data fusion model for weighted fusion calculation to obtain hydrogen purity, impurity types and the content of each impurity. The detection results obtained by fusion calculation are compared with a preset threshold to obtain a comparison result; wherein, when the comparison result is abnormal, an early warning is triggered and a control command for cutting off the relevant gas path is output; when the comparison result is normal, the detection data is updated and stored. The detection results are correlated with the number of hydrogen charging and discharging cycles of the solid hydrogen storage medium and stored for performance analysis.

7. The method for detecting hydrogen purity in a solid hydrogen storage medium according to claim 6, characterized in that, The method further includes: The pressure of the standardized hydrogen sample was controlled to be 0.1 MPa and the flow rate to be 50 mL / min.

8. The method for detecting hydrogen purity in a solid hydrogen storage medium according to claim 6, characterized in that, The step of inputting the multi-dimensional detection parameters into the multi-sensor data fusion model for weighted fusion calculation includes: For carbon monoxide and water vapor in the multi-dimensional detection parameters, the weighting coefficient of the electrochemical sensor group is the highest based on the multi-sensor data fusion model. For nitrogen and methane among the multi-dimensional detection parameters, the weighting coefficient of the micro Raman spectroscopy sensor controlled by the multi-sensor data fusion model is the highest.

9. The method for detecting hydrogen purity in a solid hydrogen storage medium according to claim 6, characterized in that, The preset thresholds include, but are not limited to, hydrogen purity not less than 99.97%, carbon monoxide content not greater than 0.2 ppm, oxygen content not greater than 5 ppm, and water vapor content not greater than 5 ppm. The method further includes: The response time from when the comparison result is abnormal to when the linkage control command is output shall not exceed 5 seconds.

10. The method for detecting the hydrogen purity of a solid hydrogen storage medium according to claim 6, characterized in that, The method further includes: The detection data is associated with the operating conditions of the hydrogen storage medium and stored, and then uploaded remotely. The storage period for the detection data is no less than one year.

Images