Intelligent regulation and control method, device and system for hydrogen production by water electrolysis of proton exchange membrane

Abstract

The invention provides an intelligent regulation and control method, device and system for hydrogen production through water electrolysis of a proton exchange membrane, and the method comprises the following steps: achieving the goal of prolonging the service life on the premise of not increasing the preparation process and cost of a device before being put on a machine; state monitoring can be carried out on line in real time, the state is researched and judged through monitoring data, and human experience misjudgment is avoided; electrochemical information of a PEMWE electrolytic cell device for a long time can be collected, and analysis of an aging mechanism of the PEMWE electrolytic cell device can be promoted; when the external environment changes, rapid identification and response can be carried out, and unnecessary performance loss caused by unattended operation and the like is avoided.

Description

Technical Field

[0001] This invention relates to the field of hydrogen production technology through water electrolysis in the field of new energy, and in particular to intelligent control methods, devices and systems for hydrogen production through proton exchange membrane water electrolysis. Background Technology

[0002] Currently, proton exchange membrane water electrolysis (PEMWE) has advantages such as high hydrogen purity, fast system response, and strong environmental adaptability. It can also operate under conditions of high current density and wide fluctuation range, and can be coupled with large power generation systems such as wind power and photovoltaic power.

[0003] To improve the efficiency, reduce costs, and extend the lifespan of PEMWEs, the main research directions include catalyst and proton exchange membrane modification of membrane electrodes, coating and flow field optimization of bipolar plates, and pore structure design of titanium felt and titanium mesh, mainly targeting the material end and the device end, and the corresponding state is before machine operation (before operating conditions).

[0004] On the materials side, methods such as improving the preparation process and introducing elemental modification are used to enhance the electrochemical performance of the proton exchange membrane and the catalyst itself. On the device side, methods such as using anti-corrosion coatings and designing different pore ratios are used to optimize the water distribution in the tank and reduce heat loss during operation.

[0005] Modification of materials and devices requires the addition of new processes, making the preparation or synthesis process more cumbersome and complex, thereby increasing costs. At the same time, PEMWE electrolyzer devices lack online monitoring methods after being installed, resulting in insufficient flexibility under operating conditions and difficulty in proactively adapting to changes in the external environment. Summary of the Invention In view of this, the purpose of this invention is to provide an intelligent control method, device and system for proton exchange membrane electrolysis of water to produce hydrogen, which can improve service life without increasing the pre-installation device preparation process and cost; it can perform online real-time status monitoring and use the monitoring data to judge the status; it can collect electrochemical information of PEMWE electrolyzer devices over a long period of time to help analyze their aging mechanism; and it can quickly identify and respond to.

[0006] In a first aspect, embodiments of the present invention provide a smart control method for hydrogen production via proton exchange membrane water electrolysis, the method comprising: Build a dataset and calculate the rate of voltage change over a specified time period; Determine whether the real-time voltage value in the dataset is greater than or equal to a first preset value; If the real-time voltage value is greater than or equal to the first set value, the operation ends; If the real-time voltage value is less than the first set value, then determine whether the voltage change rate is greater than or equal to the second set value; If the voltage change rate is less than the second set value, data acquisition continues; If the voltage change rate is greater than or equal to the second set value, then the EIS data within the set time period is identified; The ratio is calculated based on the EIS data, and it is determined whether the ratio is greater than or equal to a third set value. If the ratio is greater than or equal to the third set value, the EIS data is adjusted by the control module to generate a first control command; If the ratio is less than the third set value, the EIS data is subjected to DRT fitting, integration and identification processing to obtain the corresponding electrochemical process; The corresponding electrochemical process is regulated by the regulation module to generate a second regulation command; Input the first control command or the second control command into the electrolysis device.

[0007] Furthermore, the ratio is calculated based on the EIS data, including: Calculate the rate of change of HFR based on the EIS data; The rate of change of the potential of the HFR is calculated based on the rate of change of the HFR; The ratio is calculated based on the rate of change of the potential and the rate of change of the voltage of the HFR.

[0008] Furthermore, the EIS data is controlled by the control module to generate a first control command, including: The EIS data is physically decoupled using a neural network model to obtain the corresponding physical signal after decoupling. The physical quantity and physical parameters to be controlled are determined based on the physical signal corresponding to the decoupling. The physical quantity and the physical parameters to be regulated constitute the first regulation command.

[0009] Furthermore, the EIS data is subjected to DRT fitting, integration, and identification processing to obtain the corresponding electrochemical process, including: The EIS data were fitted with DRT to obtain peaks in different time domains; wherein the peaks in different time domains correspond to different electrochemical processes. By integrating the different electrochemical processes, the DRT peak area in each time domain is obtained; Calculate the growth rate of the DRT peak area in each of the respective time domains, and identify the time domain corresponding to the maximum peak area growth rate; The corresponding electrochemical process is determined based on the time domain corresponding to the maximum peak area growth rate.

[0010] Furthermore, the corresponding electrochemical process is regulated by the regulation module to generate a second regulation command, including: The corresponding electrochemical process is decoupled using a neural network model to obtain quantitative indicators of the physical signal. The second control command is generated based on the quantization index of the physical signal.

[0011] Furthermore, the dataset is constructed, including: When the electrolysis device is in operation, parameter data is collected; wherein, the parameter data includes voltage value, current value, electrochemical impedance spectrum, temperature, flow rate and pressure; The parameter data is organized by time to form the dataset.

[0012] Secondly, embodiments of the present invention provide an intelligent control device for hydrogen production via proton exchange membrane water electrolysis, the device comprising: The module is used to build a dataset and calculate the rate of voltage change over a set time period. The first judgment module is used to determine whether the real-time voltage value in the dataset is greater than or equal to a first set value; if the real-time voltage value is greater than or equal to the first set value, the operation ends. The second judgment module is used to determine whether the voltage change rate is greater than or equal to a second set value when the real-time voltage value is less than the first set value; and to continue data acquisition when the voltage change rate is less than the second set value. The identification module is used to identify EIS data within the set time period when the voltage change rate is greater than or equal to the second set value; The third judgment module is used to calculate the ratio based on the EIS data and determine whether the ratio is greater than or equal to a third set value. The first analysis module is used to regulate the EIS data and generate a first regulation command when the ratio is greater than or equal to the third set value. The second analysis module is used to perform DRT fitting, integration, and identification processing on the EIS data when the ratio is less than the third set value to obtain the corresponding electrochemical process; and to regulate the corresponding electrochemical process through the regulation module to generate a second regulation command. The input module is used to input the first control command or the second control command into the electrolysis device.

[0013] Thirdly, embodiments of the present invention provide an intelligent control system for hydrogen production by proton exchange membrane electrolysis of water, including the intelligent control device for hydrogen production by proton exchange membrane electrolysis of water as described above. The system further includes a heating system, a pumping system, a power supply, an electrochemical workstation, an electrolyzer, a thermal signal acquisition device, a fluid dynamics signal acquisition device, an electrochemical signal acquisition device, data acquisition hardware, computing hardware, and display hardware. When the heating system, the pumping system, the power supply and the electrochemical workstation are started, the electrolytic cell begins to operate; When the thermal signal acquisition device is used in conjunction with the heating system, the fluid dynamics signal acquisition device is used in conjunction with the pumping system, and the electrochemical signal acquisition device is used in conjunction with the electrochemical workstation, the acquired data is jointly input into the data set hardware; wherein, the acquired data is constructed into a dataset; When adjusting, the dataset is input into the computing hardware to obtain the output result, which is then displayed through the display hardware to form an adjustment command; The control commands are input to the heating system, the pumping system, and the power supply to form an intelligent control closed loop.

[0014] Fourthly, embodiments of the present invention provide an electronic device, including a memory and a processor, wherein the memory stores a computer program that can run on the processor, and the processor executes the computer program to implement the method described above.

[0015] Fifthly, embodiments of the present invention provide a computer-readable medium having processor-executable non-volatile program code that causes the processor to perform the method described above.

[0016] This invention provides an intelligent control method, apparatus, and system for proton exchange membrane electrolysis of water to produce hydrogen, comprising: constructing a dataset and calculating the voltage change rate within a set time period; determining whether the real-time voltage value in the dataset is greater than or equal to a first set value; if the real-time voltage value is greater than or equal to the first set value, terminating the operation; if the real-time voltage value is less than the first set value, determining whether the voltage change rate is greater than or equal to a second set value; if the voltage change rate is less than the second set value, continuing data acquisition; if the voltage change rate is greater than or equal to the second set value, identifying EIS data within the set time period; calculating a ratio based on the EIS data and determining whether the ratio is greater than or equal to a third set value; if the ratio... If the ratio is greater than or equal to the third set value, the EIS data is regulated by the control module to generate the first control command; if the ratio is less than the third set value, the EIS data is subjected to DRT fitting, integration, and identification processing to obtain the corresponding electrochemical process; the corresponding electrochemical process is regulated by the control module to generate the second control command; the first or second control command is input into the electrolysis device; the goal of improving service life is achieved without increasing the device fabrication process and cost before installation; online real-time status monitoring can be performed, and the status can be judged using the monitoring data; long-term electrochemical information of PEMWE electrolysis cell devices can be collected to help analyze their aging mechanism; rapid identification and response are possible.

[0017] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained in accordance with the structures particularly pointed out in the description, claims and drawings.

[0018] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0019] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0020] Figure 1 This is a flowchart of the intelligent control method for proton exchange membrane electrolysis of water to produce hydrogen provided in Embodiment 1 of the present invention; Figure 2 This is a diagram of the input and output signals of artificial intelligence during regulation provided in Embodiment 1 of the present invention; Figure 3This is a schematic diagram of the EIS curve and its data processing provided in Embodiment 1 of the present invention; Figure 4 This is a schematic diagram of another intelligent control process for hydrogen production via proton exchange membrane electrolysis of water provided in Embodiment 2 of the present invention; Figure 5 This is a schematic diagram of the intelligent control device for proton exchange membrane electrolysis of water to produce hydrogen provided in Embodiment 3 of the present invention. Figure 6 This is a schematic diagram of the intelligent control system for proton exchange membrane electrolysis of water to produce hydrogen provided in Embodiment 4 of the present invention; Figure 7 This is a schematic diagram of the intelligent control system for proton exchange membrane electrolysis of water to produce hydrogen provided in Embodiment 4 of the present invention.

[0021] icon: 1-Water storage tank; 2-Gear pump; 3-Water storage tank; 4-Heating rod; 5-Filter ion column; 6-Gas collecting bottle; 7-Dryer; 8-Water storage bottle; 9-Electrolytic cell; 10-Power supply system; 11-Hardware box; 12-Display screen; 13-Workstation. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] According to the national development strategy, the dual carbon target is to achieve 'carbon peak' before 2030 and 'carbon neutrality' before 2060. Finding alternative energy sources to traditional fuels such as oil has become particularly urgent. Hydrogen, due to its high energy density and pollution-free characteristics, is regarded as an energy carrier with great potential in the future energy system.

[0024] In recent years, the green hydrogen sector has received strong policy support and achieved significant development under this strategic background, including water electrolysis hydrogen production technologies such as solid oxide electrolyzer cells (SOEC), anion exchange membrane water electrolysis (AEMWE), and proton exchange membrane water electrolysis (PEMWE).

[0025] PEMWE boasts advantages such as high hydrogen purity, fast system response, and strong environmental adaptability. It also supports operation under conditions of high current density and wide fluctuations, and can be coupled with large-scale power generation systems such as wind and solar power, making it considered one of the technologies with the potential for rapid commercialization. However, PEMWE currently faces challenges such as high cost and poor long-term operational stability.

[0026] To improve the efficiency, reduce costs, and extend the lifespan of PEMWEs. The main research directions include catalyst and proton exchange membrane modification for membrane electrodes, coating and flow field optimization of bipolar plates, and pore structure design of titanium felt and titanium mesh, primarily targeting both material and device aspects, specifically before installation (before operating conditions).

[0027] On the materials side, methods such as improving the preparation process and introducing elemental modification are used to enhance the electrochemical performance of the proton exchange membrane and the catalyst itself. On the device side, methods such as using anti-corrosion coatings and designing different pore ratios are used to optimize the water distribution in the tank and reduce heat loss during operation.

[0028] Modification of materials and devices requires the addition of new processes, making the preparation or synthesis process more cumbersome and complex, thereby increasing costs. At the same time, PEMWE electrolyzer devices lack online monitoring methods after being installed, resulting in insufficient flexibility under operating conditions and difficulty in proactively adapting to changes in the external environment. This application constructs an intelligent closed-loop control system that achieves the goal of improving service life without increasing the device fabrication process and cost before installation. It can perform real-time online status monitoring and use the monitoring data to judge the status, avoiding misjudgment by human experience. It can collect electrochemical information of PEMWE electrolytic cell devices over a long period of time, helping to analyze their aging and degradation mechanisms. When faced with changes in the external environment, it can quickly identify and respond to them, avoiding unnecessary performance loss due to unattended conditions.

[0029] To facilitate understanding of this embodiment, the embodiments of the present invention will be described in detail below.

[0030] Example 1: Figure 1 This is a flowchart of the intelligent control method for hydrogen production by proton exchange membrane electrolysis of water provided in Embodiment 1 of the present invention.

[0031] Reference Figure 1 The method includes the following steps: Step S101: Construct a dataset and calculate the voltage change rate within a set time period; Here, the electrolytic cell to be operated is installed into the electrolysis unit. After operation begins, all systems of the electrolysis unit are in working condition, and the data acquisition part will record the required parameter information. Then, the parameter information is organized with time as the scale. The time scale can be set as needed to record indicators such as per second, per minute, per hour, and per day to form a dataset.

[0032] Step S102: Determine whether the real-time voltage value in the dataset is greater than or equal to the first set value; Step S103: If the real-time voltage value is greater than or equal to the first set value, then the operation ends; Step S104: If the real-time voltage value is less than the first set value, determine whether the voltage change rate is greater than or equal to the second set value. Specifically, the first judgment instruction mainly determines whether the electrolytic cell is in a state of major failure. The measured real-time voltage value and the calculated voltage change rate are automatically input. If the first judgment instruction is met, it is determined that the electrolytic cell has suffered a major failure and the operation is terminated; if it is not met, the second judgment instruction is executed.

[0033] If the voltage change rate is less than the second set value, then proceed to step S101; Step S105: If the voltage change rate is greater than or equal to the second set value, then identify the EIS data within the set time period; Specifically, the second judgment instruction mainly determines whether the electrolyzer is in a specified voltage decay state. If it does not meet the second judgment instruction, it indicates that it is in a specified voltage decay state and no adjustment is needed. In this case, it jumps to the data acquisition state and continues to execute the data acquisition instruction. If it meets the second judgment instruction, it enters the data analysis section. The data analysis section uses EIS spectrum as the analytical data and is mainly divided into HFR (High Frequency Resistance) section and polarization section.

[0034] Step S106: Calculate the ratio based on EIS data; Step S107: Determine whether the ratio is greater than or equal to the third set value; Step S108: If the ratio is greater than or equal to the third set value, the EIS data is regulated by the regulation module to generate a first regulation command. Step S109: If the ratio is less than the third set value, the EIS data is subjected to DRT fitting, integration and identification processing to obtain the corresponding electrochemical process. Step S110: The corresponding electrochemical process is regulated by the regulation module to generate a second regulation command; Step S111: Input the first control command or the second control command into the electrolysis device.

[0035] Furthermore, step S107 includes the following steps: Step S201: Calculate the rate of change of HFR based on EIS data; Step S202: Calculate the potential change rate of HFR based on the rate of change of HFR; Step S203: Calculate the ratio based on the potential change rate and voltage change rate of HFR.

[0036] Furthermore, step S108 includes the following steps: Step S301: Physically decouple the EIS data using a neural network model to obtain the corresponding physical signal after decoupling; Step S302: Determine the physical quantity and physical parameters to be controlled based on the physical signal corresponding to the decoupling. Step S303: The controlled physical quantity and the controlled physical parameter constitute the first control command.

[0037] Specifically, refer to, for example Figure 2 The diagram shown illustrates the input and output signals of artificial intelligence during regulation. Figure 2 This demonstrates the working principle of artificial intelligence when regulation is required. It primarily emphasizes that when the intelligent proton exchange membrane water electrolysis hydrogen production device meets the regulation conditions, it requires input physicochemical signals. These signals are then processed by a neural network to provide specific values ​​for the physical parameters that need to be regulated. Subsequently, the output signal (the regulated physical parameters and their specific values) is sent to the execution hardware for regulation, completing the closed loop.

[0038] Furthermore, step S109 includes the following steps: Step S401: Perform DRT fitting on the EIS data to obtain peaks in different time domains; wherein, the peaks in different time domains correspond to different electrochemical processes. Step S402: Integrate the peaks in different time domains to obtain the DRT peak area in each time domain; Step S403: Calculate the growth rate of DRT peak area in each time domain and identify the time domain corresponding to the maximum peak area growth rate; Step S404: Determine the corresponding electrochemical process based on the time domain corresponding to the maximum peak area growth rate.

[0039] Furthermore, step S110 includes the following steps: Step S501: Decouple the corresponding electrochemical process signal using a neural network model to obtain the quantitative index of the physical signal; Step S502: Generate a second control command based on the quantization index of the physical signal.

[0040] Furthermore, step S101 includes: Step S601: When the electrolysis device is in operation, collect parameter data; wherein, the parameter data includes voltage value, current value, electrochemical impedance spectrum, temperature, flow rate and pressure; Step S602: After organizing the parameter data with time as the scale, a dataset is formed.

[0041] In addition, the measured EIS curve, DRT data, and DRT peak area are as follows: Figure 3 As shown, (a) is the EIS curve, with the horizontal axis representing the real part, indicating the resistance, and the vertical axis representing the imaginary part, indicating the capacitance. It can intuitively display the overall impedance and obtain HFR information; (b) is the DRT fitting curve, which aims to distinguish information about different electrochemical processes. Peaks in different time domains in the DRT represent different electrochemical processes; (c) is a line graph of different peak areas in the DRT. The peak area represents the resistance of the electrochemical process and is used to determine the main contributing process of voltage decay; (d) is a line graph of different peak positions in the DRT, which is used to distinguish peak information in different time domains to determine the electrochemical process corresponding to the peak.

[0042] This application enables data-driven decision support, improving the efficiency of problem-solving for staff; it allows for the development of appropriate operating condition protocols, extending the service life of PEM electrolyzers and reducing costs; it enables real-time acquisition of the electrochemical kinetic state and interface information of PEM water electrolyzers; it allows for the establishment of the correlation between electrochemical kinetic processes and physical parameters, providing new ideas for optimizing the operating conditions of PEM water electrolyzers; it can prevent potential risks and runaway situations during operation, enhancing safety; it is applicable to different scenarios, promoting scientific research and industrial application development; it reduces maintenance costs, is environmentally friendly, promotes the development of clean energy technologies, and supports sustainable development goals.

[0043] Example 2: Figure 4 This is a schematic diagram of another intelligent control process for hydrogen production by proton exchange membrane electrolysis of water provided in Embodiment 2 of the present invention.

[0044] Reference Figure 4 It includes three parts: data collection, data analysis, and control, as well as two judgment conditions.

[0045] The electrolytic cell to be operated is installed into the electrolysis unit. After operation begins, all systems of the electrolysis unit are in working condition. The data acquisition section will record the required information, including voltage (U), current (I), electrochemical impedance spectroscopy (EIS), temperature (T), flow rate (Q), pressure (P), and other data. These data are organized with time as the scale. The time scale can be set as needed to record indicators such as per second, per minute, per hour, or per day to form a dataset.

[0046] Then, based on the actual set parameters, the rate of change of voltage within a certain time period is calculated. The data acquisition status changes to the first judgment instruction interface. The first judgment instruction mainly distinguishes whether the electrolytic cell is in a state of major failure. The measured real-time voltage value and the calculated rate of change of voltage are automatically input. If the first judgment instruction is met, it is determined that the electrolytic cell has suffered a major failure and the operation ends; if it is not met, the second judgment instruction is executed.

[0047] The second judgment instruction mainly determines whether the electrolytic cell is in a specified voltage decay state. If it does not meet the second judgment instruction, it indicates that it is in a specified voltage decay state and no adjustment is required. In this case, it will jump to the data acquisition state and continue to execute the data acquisition instruction. If it meets the second judgment instruction, it will jump to the data parsing part.

[0048] This application uses EIS spectrum as analytical data, which is mainly divided into HFR (High Frequency Resistance) and polarization. HFR mainly refers to the internal resistance and contact resistance of the device itself. First, the EIS data within the time period used to identify the voltage change rate is identified, and the HFR change rate is calculated. Then, according to Ohm's law, the potential change rate caused by HFR is calculated and compared with the voltage change rate to calculate the ratio of HFR potential change rate to voltage change rate.

[0049] When the data parsing section receives a judgment instruction, it primarily identifies the main contributors to voltage attenuation. If the judgment instruction is met, the main contributor to voltage attenuation is the HFR portion, and the data enters the control section. Relying on a neural network model, the data is physically decoupled. Based on the corresponding physical signals after decoupling, the physical quantities requiring adjustment are identified, and the physical parameters to be controlled are quantified, forming the first control instruction. This instruction is then input to the electrolysis device, forming an intelligent automatic control closed loop. The physical quantities include current input parameters, electrolyte temperature, and electrolytic cell pressure, among other physical parameters.

[0050] If the judgment instruction is not met, the main contributor to the voltage decay is the polarization component. The EIS data within the time period used to identify the voltage change rate is subjected to DRT (Distribution of Relaxation Times) fitting processing to obtain peaks in different time domains, which correspond to different electrochemical processes. The DRT peak area in each time domain is obtained by integration, the peak area growth rate is calculated, and then the time domain corresponding to the maximum peak area growth rate is identified. The electrochemical process in the corresponding time domain is confirmed, and the process enters the regulation part. Similarly, the neural network model is used to decouple the signal of this part of the data to form a quantitative index of the physical signal. The second regulation instruction is sent to the electrolysis device for regulation.

[0051] This application adjusts the operating condition protocol for the real-time working status of the device to achieve long-term high-efficiency operation. The system uses a mature EIS testing method to collect electrochemical information and uses the electrochemical information as a judgment indicator. Therefore, it has a wide range of applications and can be used in fields such as lithium-ion batteries, fuel cells, water electrolysis, and carbon dioxide electrolysis.

[0052] Example 3: Figure 5 This is a schematic diagram of the intelligent control device for proton exchange membrane electrolysis of water to produce hydrogen provided in Embodiment 3 of the present invention.

[0053] Reference Figure 5 The device includes: The module is used to build a dataset and calculate the rate of voltage change over a set time period. The first judgment module is used to determine whether the real-time voltage value in the dataset is greater than or equal to a first set value; if the real-time voltage value is greater than or equal to the first set value, the operation ends. The second judgment module is used to determine whether the voltage change rate is greater than or equal to the second set value when the real-time voltage value is less than the first set value; if the voltage change rate is less than the second set value, data acquisition continues. The identification module is used to identify EIS data within a set time period when the voltage change rate is greater than or equal to a second set value; The third judgment module is used to calculate the ratio based on EIS data and determine whether the ratio is greater than or equal to the third set value. The first analysis module is used to regulate the EIS data and generate a first regulation command when the ratio is greater than or equal to the third set value. The second analysis module is used to perform DRT fitting, integration and identification processing on EIS data when the ratio is less than the third set value to obtain the corresponding electrochemical process; the corresponding electrochemical process is then regulated by the regulation module to generate the second regulation command. The input module is used to input the first or second control command into the electrolysis device.

[0054] Example 4: Figure 6 This is a schematic diagram of the intelligent control system for proton exchange membrane electrolysis of water to produce hydrogen provided in Embodiment 4 of the present invention.

[0055] Reference Figure 6The system includes the intelligent control device for hydrogen production by proton exchange membrane electrolysis of water as described above. The system also includes a heating system, a water pumping system, a power supply, an electrochemical workstation, an electrolyzer, a thermal signal acquisition device, a fluid dynamics signal acquisition device, an electrochemical signal acquisition device, data acquisition hardware, computing hardware, and display hardware. The electrolytic cell begins operation when the heating system, pumping system, power supply, and electrochemical workstation are started. When the thermal signal acquisition device is used in conjunction with a heating system, the fluid dynamics signal acquisition device is used in conjunction with a pumping system, and the electrochemical signal acquisition device is used in conjunction with an electrochemical workstation, the acquired data is input into the data set hardware; among these, the acquired data is constructed into a dataset. When making adjustments, the dataset is input into the computing hardware to obtain the output results, which are then displayed through the display hardware to form the adjustment command; The control commands are input into the heating system, pumping system, and power supply to form an intelligent control closed loop.

[0056] Specifically, the system also includes control hardware. At the start of operation, each system provides initial conditions to ensure the electrolytic cell can carry out the electrolytic reaction smoothly. Then, based on the monitoring situation, the hardware part generates control commands, which are fed back to each system. According to the control commands, the operating conditions are adjusted to ensure that the electrolytic cell is in a suitable and efficient working state for a long time, thereby improving the lifespan and electrolysis efficiency of the electrolytic cell.

[0057] The system connection methods include: before starting operation, ensuring the water tank is full and the water quality meets the requirements, and that all pipes and wires are properly connected; starting the heating system, pumping system, power supply, and electrochemical workstation, and starting the electrolytic cell; using the thermal signal acquisition device in conjunction with the heating system, the fluid dynamics signal acquisition device in conjunction with the pumping system, and the electrochemical signal acquisition device in conjunction with the electrochemical workstation to input the collected data into the data set hardware; when regulation is required, inputting the generated dataset into the computing hardware, then outputting the results to the display hardware for display, and generating regulation commands, which are then input into the heating system, pumping system, and power supply to form an intelligent regulation closed loop.

[0058] Figure 7 This is a schematic diagram of the intelligent control system for proton exchange membrane electrolysis of water to produce hydrogen provided in Embodiment 3 of the present invention.

[0059] Reference Figure 7The system comprises the following components: a water tank 1 for supplying deionized water for electrolysis; a gear pump 2 for supplying deionized water to the water tank; a water tank 3 for supplying deionized water to the anode of the electrolyzer; a heating rod 4 for heating the water in the water tank to a set temperature; a filter column 5 for purifying the reflux water from the anode of the electrolyzer; a gas collecting bottle 6 for collecting hydrogen produced on the cathode side; a dryer 7 for drying hydrogen produced on the cathode side; a water tank 8 for collecting water that has passed through the proton exchange membrane to the cathode side; an electrolyzer 9 for producing hydrogen through water electrolysis; a power system 10 for supplying the necessary power to the equipment; a hardware box 11 including a signal acquisition module, a data processing and calculation module, and an instruction transmission module; a display screen 12 for data display; and a workstation 13 for acquiring and transmitting electrochemical signals.

[0060] a, b, c, d, e, and f are water guide pipes, which connect the water storage tank to the first gear pump, the gear pump to the water storage tank, the water storage tank to the second gear pump, the second gear pump to the electrolytic cell inlet, the electrolytic cell outlet to the filter ion column, and the filter ion column to the water storage tank, respectively. g, h, and i are gas guide pipes, which connect the hydrogen outlet of the electrolyzer to the water storage bottle, the water storage bottle to the dryer, and the dryer to the gas collecting bottle, respectively. k, l, m, n, o, p, q, and r are conductive cables that connect the positive terminal of the power supply to the anode of the electrolytic cell, the negative terminal of the power supply to the cathode of the electrolytic cell, the positive terminal of the power supply to the gear pump, the negative terminal of the power supply to the gear pump, the positive terminal of the power supply to the heating rod, the negative terminal of the power supply to the heating rod, the positive terminal of the power supply to the electrochemical workstation, and the negative terminal of the power supply to the electrochemical workstation, respectively.

[0061] j, s, and t are transmission cables. j connects the electrochemical workstation and the electrolytic cell, and is responsible for collecting electrochemical signals; s connects the temperature and hardware box, and the pump system and computer box, and is responsible for transmitting signals such as temperature and flow rate; t connects the workstation and the hardware box, and is responsible for transmitting electrochemical signals.

[0062] This invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the intelligent control method for proton exchange membrane electrolysis of water to produce hydrogen provided in the above embodiments.

[0063] This invention also provides a computer-readable medium having processor-executable non-volatile program code, on which a computer program is stored. When the computer program is run by a processor, it executes the steps of the intelligent control method for proton exchange membrane electrolysis of water to produce hydrogen as described above.

[0064] The computer program product provided in this embodiment of the invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the preceding method embodiments. For specific implementation details, please refer to the method embodiments, which will not be repeated here.

[0065] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system and apparatus described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0066] Furthermore, in the description of the embodiments of the present invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in the present invention based on the specific circumstances.

[0067] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0068] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0069] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A smart control method for hydrogen production via proton exchange membrane water electrolysis, characterized in that, The method includes: Build a dataset and calculate the rate of voltage change over a specified time period; Determine whether the real-time voltage value in the dataset is greater than or equal to a first preset value; If the real-time voltage value is greater than or equal to the first set value, the operation ends; If the real-time voltage value is less than the first set value, then determine whether the voltage change rate is greater than or equal to the second set value; If the voltage change rate is less than the second set value, data acquisition continues; If the voltage change rate is greater than or equal to the second set value, then the EIS data within the set time period is identified; The ratio is calculated based on the EIS data, and it is determined whether the ratio is greater than or equal to a third set value. If the ratio is greater than or equal to the third set value, the EIS data is adjusted by the control module to generate a first control command; If the ratio is less than the third set value, the EIS data is subjected to DRT fitting, integration and identification processing to obtain the corresponding electrochemical process; The corresponding electrochemical process is regulated by the regulation module to generate a second regulation command; Input the first control command or the second control command into the electrolysis device.

2. The intelligent control method for proton exchange membrane electrolysis of water to produce hydrogen according to claim 1, characterized in that, The ratio is calculated based on the EIS data, including: Calculate the rate of change of HFR based on the EIS data; The rate of change of the potential of the HFR is calculated based on the rate of change of the HFR; The ratio is calculated based on the rate of change of the potential and the rate of change of the voltage of the HFR.

3. The intelligent control method for proton exchange membrane electrolysis of water to produce hydrogen according to claim 1, characterized in that, The EIS data is controlled by the control module to generate a first control command, including: The EIS data is physically decoupled using a neural network model to obtain the corresponding physical signal after decoupling. The physical quantity and physical parameters to be controlled are determined based on the physical signal corresponding to the decoupling. The physical quantity and the physical parameters to be regulated constitute the first regulation command.

4. The intelligent control method for proton exchange membrane electrolysis of water to produce hydrogen according to claim 1, characterized in that, The EIS data are subjected to DRT fitting, integration, and identification processing to obtain the corresponding electrochemical process, including: The EIS data were fitted with DRT to obtain peaks in different time domains; wherein the peaks in different time domains correspond to different electrochemical processes. Integrate the peaks in different time domains to obtain the DRT peak area in each time domain; Calculate the growth rate of the DRT peak area in each of the respective time domains, and identify the time domain corresponding to the maximum peak area growth rate; The corresponding electrochemical process is determined based on the time domain corresponding to the maximum peak area growth rate.

5. The intelligent control method for hydrogen production by proton exchange membrane electrolysis of water according to claim 1, characterized in that, The corresponding electrochemical process is regulated by the regulation module to generate a second regulation command, including: The corresponding electrochemical process is decoupled using a neural network model to obtain quantitative indicators of the physical signal. The second control command is generated based on the quantization index of the physical signal.

6. The intelligent control method for hydrogen production by proton exchange membrane electrolysis of water according to claim 1, characterized in that, Constructing the dataset includes: When the electrolysis device is in operation, parameter data is collected; wherein, the parameter data includes voltage value, current value, electrochemical impedance spectrum, temperature, flow rate and pressure; The parameter data is organized by time to form the dataset.

7. A smart control device for hydrogen production by proton exchange membrane electrolysis of water, characterized in that, The device includes: The module is used to build a dataset and calculate the rate of voltage change over a set time period. The first judgment module is used to determine whether the real-time voltage value in the dataset is greater than or equal to a first set value; if the real-time voltage value is greater than or equal to the first set value, the operation ends. The second judgment module is used to determine whether the voltage change rate is greater than or equal to a second set value when the real-time voltage value is less than the first set value; and to continue data acquisition when the voltage change rate is less than the second set value. The identification module is used to identify EIS data within the set time period when the voltage change rate is greater than or equal to the second set value; The third judgment module is used to calculate the ratio based on the EIS data and determine whether the ratio is greater than or equal to a third set value. The first analysis module is used to regulate the EIS data and generate a first regulation command when the ratio is greater than or equal to the third set value. The second analysis module is used to perform DRT fitting, integration, and identification processing on the EIS data when the ratio is less than the third set value to obtain the corresponding electrochemical process; and to regulate the corresponding electrochemical process through the regulation module to generate a second regulation command. The input module is used to input the first control command or the second control command into the electrolysis device.

8. A smart control system for hydrogen production via proton exchange membrane water electrolysis, characterized in that, The system includes the intelligent control device for hydrogen production by proton exchange membrane electrolysis of water as described in claim 7, and further includes a heating system, a pumping system, a power supply, an electrochemical workstation, an electrolyzer, a thermal signal acquisition device, a fluid dynamics signal acquisition device, an electrochemical signal acquisition device, data acquisition hardware, computing hardware, and display hardware. When the heating system, the pumping system, the power supply and the electrochemical workstation are started, the electrolytic cell begins to operate; When the thermal signal acquisition device is used in conjunction with the heating system, the fluid dynamics signal acquisition device is used in conjunction with the pumping system, and the electrochemical signal acquisition device is used in conjunction with the electrochemical workstation, the acquired data is jointly input into the data set hardware; wherein, the acquired data is constructed into a dataset; When adjusting, the dataset is input into the computing hardware to obtain the output result, which is then displayed through the display hardware to form an adjustment command; The control commands are input into the heating system, the pumping system, and the power supply to form an intelligent control closed loop.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program executable on the processor, characterized in that, When the processor executes the computer program, it implements the method described in any one of claims 1 to 6.

10. A computer-readable medium having processor-executable non-volatile program code, characterized in that, The program code causes the processor to execute the method according to any one of claims 1 to 6.

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