Method, apparatus, and computer program for monitoring the condition of a multi-cell electrolytic cell

Abstract

SUMMARY OF THE INVENTION An improved method, apparatus, computer program, and system for monitoring the condition of a multi-cell electrolyzer is provided. Examples of the present invention relate to a method, apparatus, computer program, and system for monitoring the condition of a multi-cell electrolyzer. The method includes a step of acquiring (110) sensor information, the sensor information including at least information about measured temperatures of individual cells of the multi-cell electrolyzer. The method includes a step of predicting (130) a predicted cell temperature value of the multi-cell electrolyzer for each cell of the multi-cell electrolyzer based on the sensor information. The method includes a step of providing (170) a notification when a deviation between the predicted temperature value of a cell and the measured temperature of that cell matches a temperature deviation condition.

Description

[Technical Field]

[0001] Examples of the present invention relate to methods, devices, computer programs and systems for monitoring the condition of multi-cell electrolyzers. [Background technology]

[0002] An electrolyzer is a device that uses electricity to drive otherwise non-naturally occurring chemical reactions, splitting compounds such as water into their constituent elements by electrolysis. For example, hydrogen electrolyzers and chlor-alkali electrolyzers are important tools for the production of hydrogen and chlorine / sodium, respectively. For large-scale applications, electrolyzers often use many individual electrolyzer cells, which are often arranged in a horizontal stack.

[0003] The temperature within an individual electrolyzer cell is an important metric, as it is considered to be important for the overall efficiency of the electrolyzer. In addition, the temperature can indicate problems with the individual cells, which may result in cell problems and these problems may be related to a loss of efficiency or may be caused by cell degradation and lead to cell degradation. Furthermore, in the case of hydrogen electrolyzer cells, leaks can cause external flameless combustion, which can be difficult to detect. However, due to the corrosive environment within the electrolyzer cells, the temperature of the cells is often not measured or is measured inadequately. Summary of the Invention [Problem to be solved by the invention]

[0004] There may be a need for improved concepts for monitoring the condition of multi-cell electrolyzers. [Means for solving the problem]

[0005] The subject matter of the independent claims meets this need.

[0006] Various examples of the present invention are based on the discovery that during normal operation, it is usually possible to predict the temperatures of individual cells in a multi-cell electrolyzer, using, for example, knowledge of the physical and chemical properties of the cells and information about other process parameters, such as stack current and individual cell voltage. While temperature predictions are inherently accurate during normal operation of healthy cells, they can be used to identify faults and degradation within the cells by comparing the predicted temperatures with the measured temperatures of the cells. These measured temperatures can be obtained, for example, using fiber optic temperature sensors. Deviations between predicted and measured temperatures can be used to identify anomalies. In this case, a notification is provided to alert the operator of the multi-cell electrolyzer to the anomaly. When the electrolyzer is considered to be operating normally, the measured and predicted values ​​can be provided in graphical form to allow the operator to visually check that the electrolyzer is operating as expected. The proposed concept applies to various types of electrolyzers, including those with monopolar cells and those with bipolar cells, as well as those with cells arranged in a series configuration and those with cells arranged in parallel, for example, in a parallel stack.

[0007] Some aspects of the present invention relate to a method for monitoring the condition of a multi-cellular electrolyzer. The method includes obtaining sensor information, the sensor information including at least information about measured temperatures of individual cells of the multi-cellular electrolyzer. The method includes predicting, for each cell of the multi-cellular electrolyzer, a predicted temperature value for that cell based on the sensor information. The method includes providing a notification when a deviation between the predicted temperature of a cell and the measured temperature of that cell matches a temperature deviation condition. In this way, an operator of the electrolyzer is notified when the electrolyzer is not operating as expected, for example due to cell deterioration or due to an event such as a flameless combustion caused by a hydrogen leak.

[0008] There are different ways to predict the cell temperature. One option is to derive the predicted temperature from the cell voltage of each cell and from the stack current by means of a model, such as an energy balance-based model. For example, the sensor information may include information about the stack current of a multi-cell electrolyzer and information about the individual cell voltages of the cells of the multi-cell electrolyzer. The predicted temperature value of a cell can be predicted based on the cell voltage of this cell and on the stack current of the multi-cell electrolyzer. In particular, the predicted temperature value of a cell can be predicted based on an energy balance based on the cell voltage of this cell and on the stack current of the multi-cell electrolyzer. In this way, the cell temperature is predicted using a model based on the physical and chemical properties of the cell.

[0009] Instead, the temperatures of other cells can be used as a reference. For example, the expected temperature value of a cell can be predicted based on the measured temperatures of one or more adjacent cells in a multi-cell electrolyzer. Adjacent cells are expected to operate in a similar manner, and therefore any deviations would indicate cell degradation or failure.

[0010] Alternatively, or in addition, the temperature of the cell can be predicted using an average value across other cells (e.g. across all cells in the electrolyzer, or across a selected group of cells). For example, the predicted temperature value of a cell can be predicted based on the average or mean value of the measured temperatures of multiple cells in a multi-cell electrolyzer. This can reduce the influence of a single temperature on the predicted temperature value.

[0011] In some cases, the expected temperature value of a cell can be predicted based on one or more reference cells of a multi-cell electrolyzer. In this way, (only) healthy (e.g. new) cells can be used to determine the expected temperature, which facilitates identifying cells whose deviation from the reference indicates their age.

[0012] Generally, the one or more reference cells can be selected by a user, for example, based on which cells were last replaced. Alternatively, the one or more reference cells can be selected using an automated process. For example, the method can further include selecting the one or more reference cells based on sensor information. In this manner, no user interaction is required to select the one or more reference cells.

[0013] To avoid false alarms due to occasional abnormal measurements or to detect the occurrence of small deviations over time, instead of (or in addition to) using the temperature measurement directly, an integrated or differentiated temperature value can be calculated and compared to the integrated or differentiated predicted temperature value. For example, the predicted temperature value of a cell can correspond to the integrated or differentiated predicted temperature value with respect to time, voltage, or current. The deviation between the predicted temperature of a cell and the measured temperature of the cell can be determined as the difference between the integrated or differentiated predicted temperature value of the cell and the corresponding integrated or differentiated measured temperature value of the cell.

[0014] A major concern when operating a hydrogen electrolyzer is the occurrence of so-called flameless combustion, which is difficult to detect because it is invisible. However, flameless combustion can be detected by detecting a spike in the measured temperature of a cell. The method may therefore include providing notification of a suspected flame when a deviation between the expected temperature value of a cell and the measured temperature of that cell exhibits a spike.

[0015] Another important parameter monitored in a multi-cell electrolyzer is the cell voltage of an individual cell, i.e., the potential difference between the cathode and anode of that cell. Similar to temperature monitoring, expected voltage values ​​can be used to compare with measured cell voltage values ​​to determine whether a cell is behaving as expected. For example, the sensor information can include information about the individual cell voltages of the cells of a multi-cell electrolyzer. The notification can be provided if the deviation between the expected temperature value of a cell and the measured temperature value of that cell matches a temperature deviation condition, and if the deviation between the cell voltage of that cell and the expected voltage value matches a voltage deviation condition. In addition to temperature deviation, voltage deviation can also indicate cell degradation or failure.

[0016] There are various ways of obtaining the expected voltage values. In some cases, the voltage values ​​can be estimated from the stack current and / or other parameters. For example, the sensor information can include information about the stack current of the multi-cell electrolyzer and information about the individual cell voltages of the cells of the multi-cell electrolyzer. The method can include predicting, for each cell of the multi-cell electrolyzer, expected voltage values ​​of the cells of the multi-cell electrolyzer based on the sensor information. Alternatively, the expected voltage values ​​can be user-defined. In other words, the method can include obtaining, as input, expected voltage values ​​of the cells of the multi-cell electrolyzer.

[0017] As outlined above, a voltage deviation consistent with a voltage deviation condition can also indicate cell degradation or failure. Accordingly, the method can include providing a notification when a deviation between an expected voltage value for a cell and the measured voltage for that cell is consistent with a voltage deviation condition. This can be done separately from (e.g., in addition to) a temperature deviation-based notification.

[0018] Generally, individual cell voltages depend on the state of the cell and the current being used to power the cell. To further assess the state of the cell, the response of the cell to load changes, and in particular the time it takes to react to a load change, can be monitored. Thus, the expected voltage value can include an expected voltage and an expected time to reach the expected voltage in response to a load change.

[0019] The cell conditions change over time because the electrolysis performed by the cells causes degradation of the membranes of individual cells. The resulting cell voltage depends on the cell conditions and can be modeled using a multi-parameter regression equation. For example, the predicted voltage value can be based on a multi-parameter regression equation. The multi-parameter regression equation can include a first parameter that models an undesired reaction at the electrodes, a second parameter that models at least one of membrane ruptures, pinholes, and degradation, and a third parameter that models electrode degradation. The method can include determining the deviation between a predicted voltage value for a cell and a measured voltage for the cell. The method can include identifying the contributions of the first, second, and third parameters to the deviation using a multi-parameter regression model. The equation has three parameters: one independent of current, one linearly dependent on current, and one logarithmically dependent on current. By varying the current, the effect of different parameters on the predicted cell voltage can be identified, which improves insight into whether and when a cell needs to be replaced or maintained.

[0020] As explained above in connection with the temperature value, the predicted and measured voltage values ​​also do not necessarily correspond to a single voltage. Instead, each voltage can be integrated or a derivative can be calculated. For example, the predicted voltage value of a cell can correspond to the integration or differentiation of the predicted voltage with respect to time, temperature, or current. The deviation between the predicted voltage value of a cell and the measured voltage of that cell can be determined as the difference between the integration or differentiation of the predicted voltage of that cell and the corresponding integration or differentiation of the measured voltage of that cell. This can help avoid false alarms due to occasional abnormal measurements or detect the occurrence of small deviations over time.

[0021] Another important factor is the evolution of the cell voltages over time. For example, the method may comprise, for each cell of a multi-cell electrolyzer and / or for one or more reference cells, determining a previous voltage value of the cell based on sensor information and comparing the previous voltage value with the current voltage measurement contained in the sensor information. In this way, the effect of degradation of each cell can be measured.

[0022] In some cases, notifications need to be provided to alert an operator to critical or potentially critical cell conditions or incidents. In addition to notifications, the measured and / or calculated values ​​can be visualized, allowing the electrolyzer operator to draw their own conclusions. For example, the method may further include providing a visual representation of at least one of the sensor information, the predicted temperature value of each cell, the predicted voltage value of each cell, and the previous voltage value of each cell.

[0023] As outlined above, one option for measuring the temperature of the cells is to use a fiber optic temperature sensor. Thus, information about the measured temperatures of the cells of a multi-cell electrolyzer can be obtained from the fiber optic temperature sensor. Using the fiber optic temperature sensor, the temperature of the cells can be measured using a single (or a few) fiber optic cables, which can reduce the effort required to measure the temperature.

[0024] Alternatively, information about the measured temperatures of the cells of a multi-cell electrolyzer can be obtained from a camera-based temperature sensor, although this method may require greater computational effort since the temperatures must be derived from image data.

[0025] One aspect of the invention relates to a computer program having a program code for performing the above method when the computer program is run on a computer, on a processor or on a programmable hardware component.

[0026] Some aspects of the invention relate to a corresponding apparatus for monitoring the condition of a multi-cell electrolyzer, the apparatus comprising an interface circuit for acquiring sensor information from one or more sensors, and a processing circuit configured to perform the above method.

[0027] Some examples of apparatus and / or methods will now be described, by way of example only, and with reference to the accompanying drawings in which: [Brief explanation of the drawings]

[0028] [Figure 1a] 1 is a flow chart of an example of a method for monitoring the condition of a multi-cell electrolyzer. [Figure 1b] 1 is a schematic diagram of an example of a device for monitoring the condition of a multi-cell electrolyzer, and a system including such a device. [Figure 2a]1 is a flowchart of an example of measurement and processing of process values ​​of cells of a multi-cell electrolyzer. [Figure 2b] 1 is a flowchart of an example of measurement and processing of process values ​​of cells of a multi-cell electrolyzer. [Figure 3] FIG. 1 is a schematic diagram of an example of an electrolyzer cell surrounded by fiber optic cables. [Figure 4] FIG. 1 is a schematic diagram of an example electrolyzer cell with woven fiber optic cables. [Figure 5] FIG. 1 is a schematic diagram of an example data processing system. DETAILED DESCRIPTION OF THE INVENTION

[0029] Detailed Description Some examples will now be described in more detail with reference to the enclosed drawings. However, other possible examples are not limited to the features of these embodiments described in detail. Other examples may include modifications of features and equivalents, and alternatives to features. Furthermore, the terms used herein to describe particular examples should not limit further possible examples.

[0030] Throughout the description of the figures, the same or similar reference numbers refer to the same or similar elements and / or features, which may be the same or may be implemented in modified form while providing the same or similar functionality. The thickness of lines, layer thicknesses, and / or area sizes in the figures may be exaggerated for clarity.

[0031] When combining two elements A and B using "or," this should be understood as disclosing all possible combinations, i.e., A only, B only, and A and B, unless expressly stated otherwise in individual cases. Other phrases for the same combination may be used: "at least one of A and B" or "A and / or B." This applies equally to combinations of more than two elements.

[0032] Where singular forms such as "a," "an," and "the," are used, and where the use of only a single element is not explicitly or implicitly mandated, additional examples may also implement the same function using multiple elements. Where a function is described below as being implemented using multiple elements, additional examples may implement the same function using a single element or single processing entity. It will be further understood that the terms "include," "including," "comprises," and / or "comprising," when used, describe specified features, numbers, steps, operations, processes, elements, components, and / or groups thereof, but do not exclude the presence or addition of one or more other features, numbers, steps, operations, processes, elements, components, and / or groups thereof.

[0033] Various examples of the present invention relate to methods, devices, and computer programs for monitoring the condition of a multi-cell electrolyzer. Optionally, the device may be part of a system, which may include one or more sensors or processing entities for providing sensor information. In some examples, the system may comprise the multi-cell electrolyzer itself.

[0034] Figure 1a is a flowchart of an example of a method for monitoring the status of a multi-cell electrolyzer 100 (shown in Figure 1b). The method comprises a step 110 of obtaining sensor information, which includes at least information about the measured temperatures of the individual cells of the multi-cell electrolyzer 100. The method comprises a step 130 of predicting, for each cell of the multi-cell electrolyzer, a predicted temperature value for that cell of the multi-cell electrolyzer based on the sensor information. The method comprises a step 170 of providing a notification when a deviation between the predicted temperature value of a cell and the measured temperature of that cell corresponds to a temperature deviation condition.

[0035] In the following, a brief introduction to the various components included or referenced herein is provided. FIG. 1b shows a schematic diagram of an apparatus for monitoring the status of a multi-cell electrolyzer, and a system including such an apparatus. The apparatus 50 comprises an interface circuit 52 for acquiring information from one or more sensors, and a processing circuit 54 configured to perform the method of FIG. 1a. Optionally, the apparatus 50 further comprises a memory circuit 56 for temporarily or permanently storing information such as reference values, previous measurements, etc. The processing circuit 54 is coupled to the interface circuit 52 and to the optional memory circuit 56. The processing circuit 54, together with the interface circuit 52 (e.g., for exchanging information with the temperature processing entity 10 or the fiber optic temperature sensor 20, the cell voltage measurement entity 30, and / or the stack current measurement entity 40) and / or the optional memory circuit 56 (for storing information), provides the functionality of the apparatus 50. For example, the apparatus 50 can provide its functionality by the processing circuit 54 executing machine-readable instructions, which can be stored in the memory circuit 56.

[0036] The above-described method and apparatus 50 and corresponding computer program are used to monitor the status of the multi-cell electrolyzer 100. In the following, monitoring the status of the multi-cell electrolyzer will focus on monitoring the temperature of the individual cells of the electrolyzer and subsequently the cell voltage of the individual cells of the electrolyzer. Both the temperature and the cell voltage of the individual cells depend on the load of the electrolyzer, which in turn depends on the stack current supplied to the cells of the electrolyzer, i.e. the current supplied to the entire stack of cells. Therefore, the sensor information 110 includes at least information about the measured temperatures of the individual cells. In addition, the sensor information 110 may also include information about the stack current of the multi-cell electrolyzer and about the individual cell voltages of the cells of the multi-cell electrolyzer, which information may also be used to monitor the multi-cell electrolyzer. Components of the sensor information 110 may be obtained (e.g. received, requested) from different sensors or processing entities of the system. For example, information about the measured temperature may be obtained from a temperature sensor (such as the fiber optic temperature sensor 20 shown in FIG. 1b). Information about the individual cell voltages may be obtained from a processing circuit 30 that performs or processes cell voltage measurements. Information about the stack current may be obtained from a processing circuit 40 that performs or processes stack current measurements. Typically, the processing entity 40 that performs or processes stack current measurements is part of the control system of the electrolyzer 100.

[0037] While stack current and differential cell voltages are fairly easy to capture, capturing individual temperatures can require more effort. In the following, two different methods are described.

[0038] In a first method, optical fiber temperature sensors are used to provide information about the temperatures of the individual cells. In other words, information about the measured temperatures of the cells of a multi-cell electrolyzer can be obtained from the optical fiber temperature sensors. This method is illustrated in FIGS. 1b, 3, 4 and 5 and described below. In the following, it is assumed that the measurements of the optical fiber temperature sensors are processed by a processing entity 10 and provided to the device 50. However, the processing performed by the processing entity 10 can instead be performed by the device 50 or the optical fiber temperature sensors 20. For example, the processing entity 10 can be realized in the same way as the device 50, and includes an interface for communicating with the optical fiber temperature sensors and the device 50, processing circuitry for performing calculations, and memory circuitry for storing information such as mappings.

[0039] Generally, a fiber optic temperature sensor may be used to provide temperature sensor information, including temperature values ​​measured at multiple sections of a fiber optic cable 25 (shown in FIG. 1b) used by the fiber optic temperature sensor. The temperature sensor data may be used to calculate at least one temperature for each cell of a multi-cell electrolyzer based on the temperature values ​​measured at the multiple sections.

[0040] The first method is based on using optical fiber temperature measurements. Generally, such optical fiber temperature measurements are based on the effect of temperature on the optical fiber cable 25. For example, depending on the temperature, the reflection or scattering of light or sound may differ in different sections of the optical fiber cable. Various technologies exist for realizing such optical fiber temperature sensors. For example, the optical fiber temperature sensor can be a fiber Bragg grating sensor, i.e., a sensor based on detecting temperature-dependent changes in the Bragg wavelength. Alternatively, the optical fiber temperature sensor can be a Raman scattering-based temperature sensor, which is based on the temperature-dependent inelastic scattering of optical phonons. Alternatively, the optical fiber temperature sensor can be an interferometric optical fiber temperature sensor (intrinsic or extrinsic), i.e., a temperature sensor based on temperature-dependent changes in the length of an optical resonator. Alternatively, the optical fiber temperature sensor can be a Brillouin scattering-based distributed temperature sensor (based on temperature-dependent scattering of acoustic phonons). However, the proposed concept is not limited to a specific implementation of an optical fiber temperature sensor.

[0041] Fiber-optic temperature sensors commonly allow temperature measurements over user-defined or system-predetermined intervals. For example, in one example of a fiber-optic temperature sensor used to implement the proposed concept, the fiber-optic temperature sensor provides measurements in one-meter increments, i.e., a separate temperature value for each meter along a multi-kilometer length of fiber-optic cable. In some examples, temperature measurements are obtained at specific points every meter, while in other examples, an average temperature value is measured over a one-meter or specific stretch of fiber-optic cable. These temperature values ​​can then be used to calculate the temperature of individual cells, depending on how the fiber-optic cable is positioned in the electrolyzer cells. Thus, the process begins by obtaining temperature sensor information containing temperature values ​​from the fiber-optic temperature sensor. The temperature sensor information includes multiple temperature values, one temperature value per interval. For example, the multiple intervals can be equidistant intervals (e.g., the one-meter intervals described above) defined by the fiber-optic temperature sensor 20. Alternatively, the sections can be custom sections that are tailored to the geometry of the cells of the multi-cellular electrolyzer and to the pattern used to arrange the fiber optic cable 25 in the cells (or within the cells). The temperature values ​​can then be used to calculate the temperature for the individual cells. For this purpose, information about which temperature value in which cell of the electrolyzer to obtain can be used. In the following, this information is represented as a correspondence between sections of the fiber optic cable and cells of the multi-cellular electrolyzer. For example, multiple sections can be associated with the cells of the multi-cellular electrolyzer. For example, a section (or a subset of sections, if a section is between two cells or is not located at a cell) can be associated with one of the cells. Thus, each cell can have at least one (preferably multiple) sections associated with it, and this correspondence can then be used to calculate the temperature of that cell. This correspondence can be used to perform a selection as to which temperature value to use to calculate the temperature of at least one cell.In other words, one or more temperature values ​​can be selected for each cell of the multi-cellular electrolyzer based on the mapping of the multiple zones to the cells of the multi-cellular electrolyzer. The selected temperature values ​​can be used to calculate at least one temperature of the cell. For example, in some cases, a single temperature can be calculated for each cell based on the multiple zones and thus the multiple temperature values ​​associated with the cell, e.g., using the average or median of these temperature values. Alternatively, multiple temperatures can be calculated for each cell based on the multiple zones and thus the multiple temperature values ​​associated with the cell. Calculating multiple temperatures for each cell is preferred in order to detect flameless combustion in different sections of the cell.

[0042] The correspondence between sections and cells depends on the way in which the fiber optic cable is arranged in the respective cell or cells. In general, two general arrangement options can be distinguished: outside the cell (e.g., attached to the outer shell or outer surface of the cell, or attached between the cell and the insulation) or integrated into the cell. For example, the fiber optic cable can be attached to the outer shell or outer surface of a multi-cell electrolyzer. This method is more suitable for retrofitting existing electrolyzers or for use with third-party electrolyzers. Alternatively, the fiber optic cable can be integrated into the cell, cell wall, heating pipe, or cooling pipe of the multi-cell electrolyzer. This requires more effort. However, the closer proximity allows the measurements to be more accurate than measurements from outside the cell. In either case, the fiber optic cable can cover several cells of the multi-cell electrolyzer. For example, a single fiber optic cable may be sufficient to measure the temperature in all cells of a multi-cell electrolyzer. Alternatively, several fiber optic cables can be used, with several sections extending across the several fiber optic cables. In this case, the complexity of the correspondence between intervals and cells may increase slightly.

[0043] The correspondence between sections and cells depends on the geometry of the electrolysis cell and the pattern used to place the fiber optic cable in the cell or cells. Figures 3 and 4 show two options for placing the fiber optic cable. Figure 3 (and Figure 1b) shows a fiber optic cable surrounding the cells of the electrolysis cell. In other words, the fiber optic cable can be placed in a pattern that surrounds each cell continuously around the periphery of multiple cells (e.g., between the cell wall and the insulation). For example, as shown in Figure 1b, the cells of the electrolysis cell can be arranged in a horizontal stack (or alternatively, a vertical stack). The fiber optic cable can be placed in a pattern that substantially surrounds each individual cell of the stack, for example, so that each cell is surrounded (e.g., enclosed, wrapped) at least once. In some cases, each cell can be surrounded multiple times, for example, multiple small areas per cell, to determine the average temperature over different positions per cell, or to determine a two-dimensional temperature profile of the cell. For example, a spiral or snail pattern (e.g., having mostly straight lines or mostly curved lines (not shown)) can be used. The spiral or snail pattern can be repeated multiple times per cell, with the same (or similar) pattern being used for other cells. Alternatively, or in addition, a serpentine / zigzag pattern can be repeated multiple times per cell, with the same (or similar) pattern being used for other cells. For example, if the diameter of the electrolytic cell is, for example, less than one meter (e.g., less than the measurement accuracy of a fiber optic temperature sensor), or if it is necessary to measure the temperature of different regions on the exterior of the electrolytic cell, wiring can be added, where, for example, one portion of an individual electrolytic cell can be surrounded or covered two or three times in a circle (e.g., by zigzagging up and down over 20 cm, or by using a spiral / snail pattern) before moving to the next spot on the same cell that is further from the exterior wall.More generally, the fiber optic cable is arranged in a pattern (i.e., a pattern around a cell or a serpentine pattern) that includes subpatterns, such as a spiral / snail subpattern or a serpentine / zigzag subpattern, that are repeated multiple times within the pattern. Each subpattern can be located in exactly one of the cells (i.e., a subpattern may not cover multiple cells). Each cell can be covered by multiple repetitions of a subpattern, for example, by repeating a series of subpatterns around each cell. Thus, the correspondence between sections and cells can be based on such circular patterns or patterns that combine circularity with subpattern repetition, for example, based on knowledge of which sections are to be placed in which cells of an electrolytic cell. This can be calculated using three-dimensional computer-aided design drawings or can be determined manually using exterior markings on the fiber optic cable.

[0044] Alternatively, a weave or serpentine pattern can be used, as shown in Figures 4 and 5. In other words, the fiber optic cable can be arranged in a serpentine pattern, whereby the fiber optic cable repeatedly extends along a series of cells of a multi-cellular electrolyzer, turns around, extends in the opposite direction along the series of cells, turns around again, and extends along the series of cells again. With a serpentine pattern, the fiber optic cable passes through each cell multiple times. Depending on the size of the cell and the size of the section, a temperature value can be assigned to the cell each time the fiber optic cable passes through the cell (or for a subset of the number of times it passes through). As with the example shown in connection with the circular pattern, a spiral / weave pattern can be combined with a smaller spiral / snail pattern or a smaller serpentine / zigzag pattern to cover a portion of an individual electrolyzer cell multiple times. Thus, again, the assignment of sections to cells can be based on such a serpentine or weave pattern, e.g., based on knowledge of which sections are to be placed in which cells of the electrolyzer. This can be calculated using three-dimensional computer-aided design drawings, or can be determined manually using exterior markings on the fiber optic cable.

[0045] As outlined in relation to the circular pattern, in some examples, multiple temperature values ​​per cell can be obtained, e.g., using multiple sub-patterns, thereby generating a two-dimensional temperature profile for each cell. For example, the method can include generating a two-dimensional temperature profile for each cell based on the temperature values ​​and based on a correspondence between the multiple zones and the cells of the multi-cellular electrolyzer. In this case, the correspondence between the multiple zones and the cells can include a correspondence between the multiple zones and a plurality of points on each cell of the multi-cellular electrolyzer, e.g., a plurality of points in a two-dimensional grid of points on each cell of the electrolyzer.

[0046] In a second method, information about the measured temperatures of the cells of the multi-cell electrolyzer can be obtained from a camera-based temperature sensor, for example an infrared camera sensor. In this case, the picture elements (pixels) of the (infrared) image data provided by the camera-based temperature sensor can be associated with the cells of the multi-cell electrolyzer, for example by the processing entity 10 or the device 50. The sensor information can thus comprise the (infrared) image data, or cell temperatures derived from the infrared image data.

[0047] The sensor information comprises the measured temperature of the individual cells, and optionally information about the stack current and / or the individual cell current, and is then used to predict temperature values ​​for the cells of the multi-cell electrolyzer. In particular, a separate temperature value is predicted for each cell of the multiple cells of the electrolyzer. This prediction is made using various methods. For example, the physical and chemical properties of the cell can be used together with the cell voltage and the stack current to predict the cell temperature. In other words, the expected temperature value of the cell can be predicted based on the cell voltage of the cell (based on the sensor information) and based on the stack current of the multi-cell electrolyzer. In particular, this can be done by examining the energy balance of the cell. In other words, the expected temperature value of the cell can be predicted based on the energy balance based on the cell voltage of the cell and based on the stack current of the multi-cell electrolyzer. For example, electrochemical and thermal models can be used to calculate hydrogen prediction and oxygen prediction, the temperature rise caused by electrolysis, and to predict the temperatures of the individual cells. In some examples, the prediction of the expected temperature value of the cell based on the cell voltage of the cell and based on the stack current of a multi-cell electrolyzer can take into account the (known or measured) cell conditions with respect to undesired reactions in the electrodes, membrane ruptures, pinholes, degradation, and electrode degradation.

[0048] Alternatively, or in addition, the temperature of a cell can be predicted using the temperatures of other cells. For example, since a multi-cell electrolyzer is driven by a single stack current, all cells are expected to have similar temperatures, with small variations due to aging or external influences. Therefore, the predicted temperature can be predicted based on the (measured) temperatures of one or more other cells. For example, the predicted temperature value of a cell can be predicted based on the measured temperatures of one or more adjacent cells of the multi-cell electrolyzer, i.e., one or more cells located directly adjacent to the cell whose temperature is to be predicted. For example, a single cell can be used to predict the temperature of the adjacent cell. Alternatively, if two adjacent cells are available, both can be used. Alternatively, one or more cells that are known (or assumed) to be healthy can be used as reference cells, for example because they have been recently replaced or because they have been shown to have a "healthy" temperature (or "healthy" cell voltage). In other words, the predicted temperature value of a cell can be predicted based on one or more reference cells of the multi-cell electrolyzer. The one or more reference cells can be user-defined reference cells, or can be automatically determined based on the age of the cells (using the most recently added cell as the reference cell), or based on sensor information determined for the cells. For example, as further shown in FIG. 1a, the method can further include step 120 of selecting one or more reference cells based on the sensor information, e.g., by selection criteria. For example, after selecting one or more reference cells, the method can proceed (directly) to step 135 of determining the deviation between an expected temperature value and a measured temperature value, step 150 of determining the deviation between an expected voltage value and a measured voltage value, and / or step 165 of comparing a previous voltage value with a current voltage measurement. For example, the selection criteria can relate to the difference between the measured temperature (or measured voltage) and a user-defined reference temperature (or user-defined reference voltage), the difference between the measured temperature (or measured voltage) and the average temperature (or average voltage) across all cells, or the difference between the measured temperature (or measured voltage) and the minimum measured temperature (or minimum measured voltage) across all cells.In either case, the prediction of the temperature of the cell may not be based on a single other temperature measurement, but on multiple other temperature measurements, if available. For example, the expected temperature value of the cell may be predicted based on the average or mean value of the measured temperatures of multiple cells of a multi-cell electrolyzer (e.g. of all the cells, of all the other cells, of a reference cell, or of adjacent cells).

[0049] In the preceding discussion, it was assumed that the "temperature value" corresponds to a temperature, e.g., a measured or predicted temperature. In some cases, to filter out spurious fluctuations in the measurements, the temperature can be integrated over time (or current, or voltage), and the respective integrals can be compared with each other. In other words, the predicted temperature value of a cell can correspond to the time integral of the predicted temperature of the cell, and the deviation between the predicted temperature value of a cell and the measured temperature of the cell is determined as the difference between the integral of the predicted temperature of the cell and the corresponding integral of the measured temperature of the cell. In this way, small temperature differences that persist over time can be identified while spurious events (such as invalid measurements) are smoothed out (averaged). Similarly, the first or second derivative of each temperature curve can be taken to identify trend differences between different cells. In other words, the predicted temperature value of a cell can correspond to the derivative (e.g., first or second derivative) of the predicted temperature of the cell, and the deviation between the predicted temperature of a cell and the measured temperature of the cell is determined as the difference between the derivative of the predicted temperature of the cell and the corresponding derivative of the measured temperature of the cell. An example of such a comparison is described in connection with the "fifth model" described in connection with FIG. 5.

[0050] In the proposed concept, a notification is provided when a deviation between a predicted temperature value of a cell and the measured temperature of the cell matches a temperature deviation condition. As a basis for providing a notification 170, the method includes a step 135 of determining the deviation between a predicted temperature value of a cell and the measured temperature of the cell to evaluate the temperature deviation condition. The step of determining the deviation includes comparing the respective temperature values, e.g., the temperature, or the temperature integrated or differentiated with respect to time (or current, or voltage). The result of the comparison is then evaluated for the temperature deviation condition. In some cases, the temperature deviation condition can be a threshold, and a notification is provided if the threshold is exceeded or not (depending on the temperature deviation condition). In some cases, the temperature deviation condition can include a range of acceptable deviation and / or one or more ranges of deviation that result in providing a notification. If the temperature deviation condition is met, a notification is provided. For example, providing a notification can include providing a visual indication via a display device and / or providing a notification packet to a control system or to one or more client devices, the notification packet including the notification. For example, the notification may include an alert for the operator / user of the electrolyzer.

[0051] Below are some examples of deviations, temperature deviation conditions, and other triggers for providing notifications. For example, at least some of the following examples are described in more detail in connection with FIG. 5, where various "models" are introduced and these models serve as the basis for notifications and / or visual representations of different values. In the context of the present invention, a model is a mathematical function or computational task that receives one or more input values ​​and includes a calculation (such as predicting a temperature (or voltage) value and, optionally, comparing and evaluating a deviation condition). In other words, the model introduced in connection with FIG. 5 is an algorithm, computational task, or mathematical function for processing signal information.

[0052] For example, in the first model, individual cell voltages, individual cell temperatures and stack currents are measured and plotted on graphs for manual evaluation by an operator of the electrolyzer. Accordingly, the method may include a step 175 of providing a visual representation of at least one of the sensor information, the predicted temperature value of each cell, the predicted voltage value of each cell and the previous voltage value of each cell.

[0053] The second and third models compare individual cell voltages to each other, to one or more adjacent cells, to one or more reference cells, or to the average or mean temperature of the adjacent cells, the reference cell, or all the cells.

[0054] In the eleventh model, in order to detect H2 leaks (and possible flameless combustion that is not visible), any measured high temperature spike can be considered an H2 flame and an alarm can be generated. In other words, the method can include a step 170 of providing notification of a suspected flame if the deviation between the expected temperature value of a cell and the measured temperature of this cell exhibits a spike. In this context, a spike is a change in the measured temperature over a predetermined time interval that is greater than a threshold, for example, greater than 10°C per minute.

[0055] In addition to the cell temperature, the cell voltage is another key indicator of the health of the cells. Therefore, an expected voltage can be determined for each cell, and the measured cell voltage can be compared with the expected voltage to determine a voltage deviation. This expected voltage can be determined in the same way as the expected temperature. Therefore, the method can include a step 140 of predicting an expected voltage of the multi-cell electrolyzer for each cell of the multi-cell electrolyzer based on sensor information. For example, the expected voltage can be determined based on the stack current of the electrolyzer and on the above-mentioned formula V=A+B·I+C·log(I), where A represents undesired reactions in the electrodes, B represents membrane ruptures, pinholes, or deterioration, and C represents electrode deterioration. Alternatively, or in addition, the expected voltage can be determined based on the voltage of one or more other cells, for example, the voltage of one or more adjacent cells, the voltage of one or more reference cells, the voltage of one or more cells with a similar age, or the voltage of all the cells. The average voltage or the median voltage between two or more other cells can be used for this purpose. As an alternative to determining the voltages of individual cells, the voltage values ​​can be user-defined. In other words, the method can include a step 145 of obtaining as input (by an operator / user of the electrolyzer) expected voltage values ​​for the cells of a multi-cell electrolyzer. Similar to the temperature values, the voltage values ​​can correspond to a single voltage or to the integral or derivative of the voltage with respect to time, current or temperature. For example, the expected voltage value of a cell can correspond to the integral or derivative of the expected voltage of this cell with respect to time (or current or temperature). In other words, the expected voltage value of a cell can correspond to the integral or derivative of the expected voltage of this cell with respect to time, temperature or current. The deviation of the expected voltage value of a cell from the measured voltage of this cell can therefore be determined as the difference between the integral or derivative of the expected voltage of this cell and the corresponding integral or derivative of the measured voltage of this cell.

[0056] For example, even when the deviation between the cell voltage of a certain cell and the predicted voltage value of this cell matches the voltage deviation condition, a notification can be provided in step 170. For example, in the fourth model, a rapid drop in the individual cell voltage below a predetermined threshold can be detected. Therefore, this rapid drop indicates a problem with the membrane, and when a rapid drop (relative to the predicted voltage value of this cell or the previous measured voltage value) is detected, a notification can be provided. In this context, a rapid drop in voltage is a change in the measured voltage over a predetermined time interval that is greater than a threshold value, for example, greater than 1 V per minute. Such a rapid drop in the individual cell voltage can be determined relative to the predicted voltage value of this cell or a reference cell, or relative to the previous measured voltage. Therefore, as further shown in FIG. 1a, the above method includes step 160 of determining the previous voltage value of the cell based on sensor information for each cell of the multi-cell electrolyzer and / or for one or more reference cells, and step 165 of comparing the previous voltage value with the current voltage measurement value included in the sensor information (for the same cell or, when determining the previous voltage value for a reference cell, for any cell). For example, a notification can be provided when a rapid drop is detected between the current voltage value and the predicted voltage value (e.g., according to a predetermined time interval), or between the current voltage value and the previous voltage value.

[0057] In the fifth and sixth models, the respective voltages are used with values obtained by integrating and differentiating with respect to time and current respectively. In other words, the deviation between the predicted voltage value of a certain cell and the measured voltage of this cell can be determined as the difference between the value obtained by integrating or differentiating the predicted voltage of this cell and the corresponding value obtained by integrating or differentiating the measured voltage of this cell. For example, when the voltage deviation of the integrated value is greater than a predetermined average (allowable) voltage deviation over a predetermined period, for example, greater than 10 mV per day, a notification can be provided. In this way, small deviations over a certain period become visible, and individual single deviations do not cause false alarms. Regarding the value obtained by differentiating the voltage, an abnormality in the voltage deviation between different cells or between a certain cell and a reference cell can be detected, and a notification can be provided. Using this, an abnormality in the dynamic behavior between cells can be detected.

[0058] Electrolyzers are dynamic systems with different states and phases, such as a shutdown (non-operational) phase and a startup (start-up) phase. Shutdown can be defined as 0% current, and startup can be defined as a current ramp from 0% to 20% in less than 60 minutes. The time it takes for an individual cell to reach a voltage plateau (i.e., steady state) in response to these conditions is of particular interest for identifying the state (and especially aging-related effects) of an individual cell. Thus, in some examples, an expected voltage value can include an expected voltage and an expected time to reach the expected voltage in response to a load change. As described in connection with the seventh model, the time it takes for a single cell to reach full startup or complete shutdown can be determined, and this time provides an indication of cell efficiency (longer times equate to higher efficiency). Once startup or shutdown is detected, the time t required for the cell to reach a predetermined voltage level can be determined for each individual cell while measuring the voltage. This voltage level can be defined as a simple threshold, where the first derivative is zero or the second derivative is zero. This time t can be compared to an expected time to reach an expected voltage in response to a load change. The expected time can be derived from the time it takes one or more reference cells to undergo the same transition, or the expected time can be user-defined. If the deviation between the time it takes a cell to reach an expected voltage in response to a load change and the expected time matches the corresponding voltage deviation criteria, a notification can be provided. Details of this process are described in conjunction with the ninth model, which is discussed in conjunction with FIG. 5.

[0059] In many cases, it is useful to know how each cell deteriorates over time. To this end, the method may also include a step 160 for each cell of the multi-cell electrolyzer, determining a previous voltage value for that cell based on sensor information and comparing the previous voltage value with a current voltage measurement contained in the sensor information. This difference may be used to measure deterioration over time, as will be described in connection with the twelfth model described in connection with Figure 5. Similarly, the difference between the current voltage measurement and a user-defined / operator-defined or reference voltage derived from a reference cell may be calculated to determine the deviation of an individual cell from a desired reference voltage.

[0060] As outlined above, cell voltage depends primarily on two factors: cell condition and stack current. This is reflected by the multiparameter regression formula / equation mentioned above: V = A + B · I + C · log(I), where V represents cell voltage, A represents undesired reactions at the electrodes, B represents membrane ruptures, pinholes, and degradation, and C represents electrode degradation. Once parameters A, B, and C are known (or at least estimated), this voltage can be used to calculate predicted voltage values ​​for different cells. In other words, predicted voltage values ​​can be based on a multiparameter regression formula that includes a first parameter that models undesired reactions at the electrodes, a second parameter that models at least one of membrane ruptures, pinholes, and degradation, and a third parameter that models electrode degradation. As is clear from this formula / equation, one of these parameters is independent of the current I, while one is linearly dependent and one is logarithmically dependent. By varying the current, the individual contributions of these parameters can be determined. For example, the method can include determining 150 the deviation between the expected voltage of a cell and the measured voltage of that cell, and identifying the contributions of the first, second and third parameters to this deviation using the multi-parameter regression equation described above, e.g., by varying the current / load and calculating the contributions of the first, second and third parameters to this deviation based on the response of the cell to the change in current. The result of such parameterization and monitoring this over time is that changes in the parameters can be observed, making it possible to identify the type of deterioration or failure occurring in the cells of the electrolyzer. More details of this process are provided in relation to the eighth model, which is described in relation to FIG. 5.

[0061] In some examples, both temperature deviation and voltage deviation can be used as a common trigger for triggering the provision of a notification: A notification can be provided when the deviation between a predicted temperature value of a cell and the measured temperature of the cell matches a temperature deviation condition, and when the cell voltage of the cell matches a predicted voltage value.

[0062] Although the present invention is primarily concerned with hydrogen electrolyzers and chlor-alkali electrolyzers, the proposed concept is not limited to a specific type of electrolyzer. For example, the proposed concept can be used for different types of (hydrogen) electrolyzers, such as PEM (proton exchange membrane) electrolyzers, alkaline electrolyzers, solid oxide electrolysis-based electrolyzers, or anion exchange membrane water electrolysis-based electrolyzers. The proposed concept applies to various types of electrolyzers, including electrolyzers with monopolar cells and bipolar cells, as well as electrolyzers with cells arranged in a series configuration and electrolyzers with cells arranged in parallel, e.g., in a parallel stack. Monopolar electrolyzers, also known as "tank-type" electrolyzers, use porous separators (e.g., membranes) to keep the positive and negative electrodes separated. These electrodes are linked in parallel to each other and placed in a single electrolytic bath to form a cell. Multi-cell electrolyzers can be created by connecting cells in series. Bipolar electrolyzers use metal sheets or bipoles to connect adjacent cells in series. For example, one side of a bipole can be coated with a negative electrode electrocatalyst, while the other side can be coated with the positive electrode electrocatalyst of the next cell. In the case of a bipolar cell, the total voltage is a combination of the cell voltages, resulting in a module that operates at higher voltages and lower currents than a monopolar, tank-type design. To form a larger, multi-cell electrolyzer, multiple modules (each with multiple cells) are connected in parallel to increase the current. In general, an electrolyzer uses electricity to drive chemical reactions that would otherwise not occur naturally. In the context of the present invention, an electrolyzer is a device that splits compounds such as water into their constituent elements, such as hydrogen and oxygen, by electrolysis.

[0063] The interface circuitry 12 may represent inputs and / or outputs for receiving and / or transmitting information within a module, between modules, or between modules of different entities, and this information may be digital (bit) values ​​according to a specified code. For example, the interface circuitry 12 may include interface circuits configured to receive and / or transmit information.

[0064] For example, processing circuitry 14 may be implemented using any means for processing, such as one or more processing units, one or more processing devices, processors, computers, or programmable hardware components operable by appropriately adapted software. In other words, the described functionality of processing circuitry 14 may also be implemented in software, which is then executed on one or more programmable hardware components. Such hardware components may include general-purpose processors, digital signal processors (DSPs), microcontrollers, etc.

[0065] For example, storage device 16 may comprise at least one element of the group of computer-readable media such as magnetic or optical storage media, e.g., a hard disk drive, flash memory, a floppy disk, random access memory (RAM), programmable read only memory (PROM), erasable programmable read only memory (EPROM), electrically erasable programmable read only memory (EEPROM), or network storage.

[0066] Further details and aspects of the system, and of the method, apparatus and computer system for monitoring the condition of a multi-cell electrolyzer will be described in relation to the proposed concepts or one or more of the examples described above or below (e.g., Figures 2a-5). The system, and of the method, apparatus and computer system for monitoring the condition of a multi-cell electrolyzer may comprise one or more additional optional features corresponding to one or more of the proposed concepts or one or more of the examples described above or below.

[0067] Various examples of the present invention relate to performance monitoring of individual electrolyzer cells based on V (cell voltage), C (stack current), and T (temperature).

[0068] The present invention relates to the monitoring of electrolytic cells, such as (various types of) chlor-alkali, H2 electrolyzers, or other types of electrolytic cells. In one implementation, the following hardware can be used to capture process-related data (current, individual cell voltage, and individual cell exterior temperature). For example, current measurement can be performed by a local control system (within the electrolytic cell) (current is typically measured and / or controlled by the control system). Alternatively, a separate system for measuring stack current can be used. A cell voltage measurement system can be used to accurately measure individual cell voltages. A temperature measurement device based on fiber optic thermometry can be used to measure the exterior temperature of individual electrolytic cell cells with sufficient accuracy. The fiber optic cable of the fiber optic temperature sensor can be arranged in various ways, e.g., vertically, horizontally, etc., e.g., wrapped. Alternatively, the fiber optic-based temperature measurement device can be replaced by an infrared camera or some other temperature measurement device that measures individual cell temperatures. An additional alternative is to measure the internal cell temperature. However, this is complicated due to the corrosive environment inside the cell.

[0069] The captured data can be received by a monitoring server on which the electrolyzer performance monitoring system runs, as shown for example in Figures 2a, 2b, 3, 4 and 5.

[0070] 2a and 2b show a flowchart of an example of a flow for measuring and processing process values ​​of cells in a multi-cell electrolyzer. The flow includes data acquisition 210 (of temperature measurements) via fiber optic cables or other means, and conversion of the data to temperature values ​​220. The flow also includes acquisition of individual cell voltages 230 and stack currents 240. In block 250, the temperature, cell voltage, and stack current data are processed. For example, as shown in FIG. 2b, process 250 can include steps of comparing individual cell temperatures and voltages to modeled cell temperatures and voltages (250a), comparing individual cell temperatures to optimal cell temperatures (250b), monitoring individual cell temperatures and voltages over time (250c), and checking for high temperature spikes that may indicate a fire (250d). Appropriate follow-up action can then be taken (step 260).

[0071] Figure 3 shows a schematic diagram of an example of electrolyzer cells of a multi-cell electrolyzer 300, which are surrounded by fiber optic cables 25 used to measure the individual cell temperatures. Each electrolyzer cell has a cathode and an anode (shown with different patterns), and the cell voltage (V1...Vn) is measured between the cathode and anode of each cell. In addition, a current measurement probe 40a is used to measure the stack current of the multi-cell electrolyzer. The current measurement probe 40a can be part of the electrolyzer's control system. In Figure 4, the fiber optic cables 25 are arranged in a woven or serpentine pattern instead of surrounding the cells. Figure 4 shows a schematic diagram of an example of an electrolyzer cell with woven fiber optic cables.

[0072] The temperature values, cell voltages and stack current can be evaluated by one or more processing units or entities. Figure 5 shows a schematic diagram of an example of a data processing system comprising such processing units or entities. In Figure 5, process values ​​of a multi-cell electrolyzer 500 are captured by processing units 10, 30 and 40, with processing unit 10 converting measurements (measured by optical fiber cable 25) into temperature values, processing unit 30 capturing the individual cell voltages and processing unit 40 capturing the stack current. The temperatures, voltages and stack currents are processed by processing entity 50 (e.g. a personal computer or server) according to the concepts presented in connection with Figures 1a and / or 1b and / or according to the concepts or models below.

[0073] Monitoring electrolyser performance can be useful for a variety of reasons, such as overall safety (to prevent or detect fires or to prevent explosions), energy costs (which are lowest at optimum operating temperatures, whereas malfunctioning cells are expensive to keep operating), and to make an overall assessment of whether or when maintenance is (or is not) required. These purposes can be met, inter alia, using individual electrolyser cell-based monitoring.

[0074] Algorithms and functions run on the monitoring entity (e.g., a monitoring server) that are able to monitor, on a continuous basis, the performance, maintenance needs, and safety of individual electrolyzer cells. Various examples of the present invention are based on a combination of electrochemical models (based on physical properties and literature) for the electrolyzer and continuously measured values ​​of cell voltage, temperature, and stack current.

[0075] The electrochemical processes in an individual cell can essentially be described by the following equation, which also includes coefficients describing specific performance indicators: V=A+B·I+C·log(I) where A is the undesired reaction at the electrode, B represents membrane rupture, pinholes, and degradation, and C represents electrode degradation. This equation can be expanded with a heat balance, where cell temperature is one of the major factors.

[0076] By measuring cell voltages, stack currents, and cell temperatures, a comparison of the measured values ​​with modeled values ​​(e.g., predicted temperature / voltage values) can be made to detect anomalies. However, in more detailed forms, specific differences in measured individual cell voltages or temperatures and / or the overall performance of the cells can also be determined. Based on the measured data and the models described below, the proposed concept allows for the derivation of individual cell performance and specific cell failure mechanisms.

[0077] Below, several models are described, one or more of which can be used by the entire system. For example, one or more of the following models can be used as part of the method or computer program of FIG. 1a and / or calculated by the apparatus of FIG. 1b. In the context of the present invention, the models are computer tasks, and they can have different types of outputs, such as graphical representations of calculations or notifications. For example, in a first model, individual cell voltages, individual cell temperatures, and stack currents can be measured and plotted in a graphical format for manual evaluation by an electrolyzer operator. In a second model, individual cell temperatures can be compared with each other. Cells with relatively large deviations from what is defined as healthy can be alerted (i.e., an alert notification can be provided). This is achieved by creating and updating a table (or other type of data structure) of each cell and its temperature. In a third model, individual cell temperatures can be compared with adjacent cells. Malfunctioning cells generally produce temperatures that differ from those expected. Results can be presented in a tabular or graphical format, making it easy to detect suspect cells.

[0078] A fourth model detects a rapid drop in individual cell voltage below a predetermined threshold, which would therefore indicate a membrane problem and, in combination with an increase in cell temperature, trigger an alarm. Such behavior can be monitored, and a follow-up alarm can be generated if such behavior occurs.

[0079] In the fifth model, several cells are defined as reference cells known to behave in a healthy mode. The voltage can be measured / monitored over a specific period (e.g., one or two days). The voltage can be integrated over time, and the integrated value can be designated as the reference value for a specific time frame. The integrated value can then be used as the reference value. For each individual cell, the cell voltage can be measured and integrated over a similar time frame, e.g., one to two days. The integrated value of each individual cell can then be compared to the reference value. If the difference is greater than a predetermined average (tolerable) deviation over a given period, e.g., 10 mV per day, an alarm can be generated. In this way, small deviations over long periods of time are visible, and individual, single deviations do not cause false alarms. To check the value of the reference cell, a user-defined reference value can be entered into the system, and a calculation method similar to that described above can be used. This can then be used to check the calculated reference value in a similar manner as described above. The advantage of selecting a limited set of metrics is that a better overall indication of the health of an individual cell compared to the overall health of the cell is achieved compared to integrating all measurements. As with voltage, the same can be done for temperature, and further integrals of parameters other than time can be considered, such as the integral of voltage by current. This model detects anomalies over time.

[0080] In the sixth model, as an alternative to integrating over time in line with the fifth model, especially in the case of load fluctuations (current changes), the differentiated values ​​of voltage and temperature changes can be used as a function of stack current (or differentiated values ​​can be extracted using other parameters), and individual cells can be compared with a reference cell. If an abnormality is found, an alarm can be issued. This can be used to detect abnormalities in the dynamic behavior between cells.

[0081] The seventh model determines the time it takes for a single cell to reach full startup or shutdown, providing an indication of cell efficiency (longer times equate to higher efficiency). Individual times can be compared to identify poorly performing, averagely performing, and well-performing cells. This can be achieved by measuring the individual cell voltages of each electrolyzer cell and collecting control signals that control the current supplied to the electrolyzer as a basis for detecting startup or shutdown behavior. Shutdown can be defined as 0% current, and startup can be defined as a current rising from 0% to 20% in less than 60 minutes. Once startup or shutdown is detected, the time t required for the cell to reach a predetermined voltage level can be determined for each individual cell while measuring the voltage. This voltage level can be defined as a simple threshold, with the first derivative being zero or the second derivative being zero. The collected points can be integrated over time for a selected time frame, which can be derived for each individual cell, so that a weighted average provides an indication of the average time to reach a predetermined voltage level. For each cell, the results can be plotted and the cells can be grouped into groups, such as poorly performing cells (linked to low t numbers), averagely performing cells (linked to average t numbers), and highly performing cells (linked to highest t numbers). A well-behaving reference cell (e.g., a new cell) can be used to compare relative results to an ideal situation.

[0082] In the eighth model, healthy cells can be modeled using multiparameter regression, assigning fault-specific parameters to the regression equation (model), and then modeling them into startup, full-load, shutdown, and load-fluctuation zones (where current varies during normal operation). Individual cells can then be modeled using regression, and individual parameters can be compared to indicate specific faults. Measured inputs include cell voltage, stack current, and cell temperature. To verify whether an individual cell is operating properly or has begun to age, each cell can be fitted to a current-voltage curve constructed for a number of predetermined parameters (see Model 7). This curve can be constructed so that the characteristics of a specific cell are present in the form of coefficients. By placing thresholds on one or more characteristics, conclusions can be drawn about the cell's condition by referencing predetermined reference values. Furthermore, individual parameters of individual cells can be compared to indicate differences in cell performance. This fitting process can be done in four zones - start-up zone (current between 0 and 20%), full load zone (20 to 100%), shutdown zone (current is set to 0) and load variation zone (current is varied). A similar approach can be taken across the electrolyzer unit to determine the electrolyzer characteristics that are useful during operation.

[0083] In the ninth model, several cells known to behave in a healthy mode can be defined as reference cells. In this way, the "best" performing cell can be set as a reference for other cells. The average value of these reference cells can be calculated and assigned as the calculated reference value for a particular instant. This reference value can then be used as the calculated reference value for time t. A user / operator can define a theoretical reference voltage by inputting a reference voltage into the system. This reference voltage can be used as a user input to detect deviations between a first reference value (calculated based on the measured cell voltage of the reference cell) and a second reference value (entered by the user) over time. For each individual cell, the cell voltage can be measured within the same time frame as the reference cell measurement. The results can be compared, and an alarm can be generated if the difference is greater than a certain average deviation, e.g., 10 mV. To verify the quality of the reference calculation, the calculated reference value can be compared to a user-defined reference value each time the reference value is calculated. If the deviation exceeds a certain level, a new set of reference cells can be assigned to the algorithm. For start-up and shutdown, the algorithm can be adapted to include process conditions to prevent false alarms from occurring.

[0084] The tenth model uses the energy balance to predict cell temperature based on stack current and cell voltage as inputs. This cell temperature can be compared to the measured cell surface temperature. Anomalies can be flagged with an alarm.

[0085] In the 11th model, to detect H2 leaks (and possible unseen flameless combustion), any measured high temperature spike can be considered an H2 flame and an alarm can be generated.

[0086] The 12th model can analyze and alert on degradation over time compared to the initial model settings. The equation introduced above, V=A+B·I+C·log(I), can be used to model the expected situation. This equation can be separated into its individual parts (e.g., A, B, C) to identify the causes of degradation.

[0087] In the case of a hydrogen production plant, cell temperatures are useful for prediction and monitoring in order to balance efficiency and overall cell life. A model can be created based on the provided equations, which predict individual cell temperatures and cell voltages. By comparing the predicted voltages and temperatures with measured values, an optimization routine can be used to further iteratively improve or optimize the electrolyzer operating temperature, thus improving running costs (operating expenses) versus production yield.

[0088] By measuring the individual cell voltages and cell temperatures, comparisons can be made on the performance of individual electrolyzer cells based on continuously measured data, with stack current as an input. By measuring cell voltage, stack current, and cell temperature, three key parameters for modeling cell performance are available as measurements, which can then be used to validate predictions against measurements, providing an accurate method for detecting cell problems. Based on these models and measurement data, the cause of anomalies, e.g., undesired reactions in the membrane, electrodes, or electrode degradation, can be identified.

[0089] Cell temperature is an important factor in overall cell performance, especially for hydrogen production. If modeling is used to predict cell temperature, validation can be performed between the model and individual cell temperatures and monitored over time. Deviations can indicate cell degradation or undesirable operating temperatures and can be monitored online, and appropriate follow-up can be taken. If cell temperature is not modeled, measured cell temperatures can be used to improve cell performance. Furthermore, cell temperatures can be monitored over time. Changes in cell temperature of individual cells are an indicator of a cell problem and can be flagged for follow-up action. In the case of a leak, flameless combustion can occur. Temperature spikes can be measured in such cases. An alarm can be generated to inform authorized personnel to take necessary action, for example by shutting down the electrolyzer.

[0090] In the previous examples, it was assumed that individual cell temperatures were measured using fiber optic temperature sensors. Other methods exist for measuring the temperature on the exterior surface of a cell, for example, by a camera that measures the surface temperature. Because cameras generally have a limited viewing angle, multiple cameras or cameras incorporating a moving or rotating mechanism can be used. The data captured by a camera is in a different format compared to a fiber optic cable. Therefore, the exact location of a particular measurement point requires some data processing to be accurately determined. Furthermore, measurements may contain a much larger amount of data, which can be fed into sophisticated algorithms that detect temperature changes in more detail. These details can be processed and compared, for example, to calculated values. In order to detect hydrogen flames, such a camera may need the right characteristics to do so.

[0091] In some examples, the robot may be used to capture similar and / or other electrolytic cell data, such as temperature measurements by devices located on the robot, e.g., infrared cameras or temperature probes, or image capture devices, to detect, for example, specific coloration of the tubes through which the final product is released from the electrolytic cell. Additional data may be input into the described (and highlighted) model or new models for further processing.

[0092] Various examples of the present invention use individual cell temperature measurements, individual cell voltage measurements, and stack current measurements using fiber optic cables or other methods. A processing unit can be used to convert the measured temperatures into a format that can be used to compare them with individual cell temperatures. A processing unit with a model for comparing measurements between cell temperatures can be used to detect anomalies. A processing unit including models for predicting individual cell voltages and temperatures and models for comparing them with measurements can be used. A processing unit further including one or more of the above units can be used. A processing unit for detecting flames based on temperature spikes can be used. For example, the above-mentioned processing units can be implemented as a single processing unit or as separate processing units. Optionally, other means for detecting cell temperatures can be used, such as image-based temperature measurements. Optionally, other means for detecting other relevant cell performance parameters can be used, such as robotically captured cell temperatures and images of transparent pipelines containing the produced products. In the event of a problem occurring inside the electrolyzer, such pipelines can change color.

[0093] Aspects and features described with respect to a particular one of the previous examples may be combined with one or more of the additional examples, replacing the same or similar features in such additional examples, or these features may be additionally introduced into such additional examples.

[0094] Examples of the present invention may further be or relate to a (computer) program, including program code for performing one or more of the above-described methods when the program is executed on a computer, processor, or other programmable hardware component. Accordingly, different method steps, operations, or processes in the above-described methods may also be performed by a programmed computer, processor, or other programmable hardware component. Examples of the present invention may also cover program storage devices, such as digital data storage media, that are machine-readable, processor-readable, or computer-readable and encode and / or contain machine-executable, processor-executable, or computer-executable programs and instructions. The program storage device may include or be, for example, a digital storage device, a magnetic storage medium, such as a magnetic disk or magnetic tape, a hard disk drive, or an optically readable digital data storage medium. Other examples may include a computer, processor, control unit, (Field) Programmable Logic Array ((F)PGA), (Field) Programmable Gate Array ((F)PGA), Graphics Processor Unit (GPU), Application-Specific Integrated Circuit (ASIC), Integrated Circuit (IC) or System-on-a-Chip (SoC) system programmed to perform the steps of the methods described above.

[0095] It is further understood that the disclosure of several steps, processes, operations, or functions disclosed in the detailed description or claims should not be construed as implying that these operations necessarily depend on the order in which they are described, unless expressly stated in individual cases or unless required for technical reasons. Thus, the foregoing description does not limit the performance of several steps or functions to a particular order. Furthermore, in other examples, a single step, function, process, or operation may include several sub-steps, sub-functions, sub-processes, or sub-operations, and / or a single step, function, process, or operation may be divided into several sub-steps, sub-functions, sub-processes, or sub-operations.

[0096] Where aspects are described with respect to an apparatus or system, these aspects should also be understood as descriptions of a corresponding method. For example, a block, device, or functional aspect of such an apparatus or system may correspond to a feature, such as a method step, of a corresponding method. Thus, aspects described with respect to a method should also be understood as descriptions of a corresponding block, element, property, or functional feature of a corresponding apparatus or system.

[0097] The following claims are hereby incorporated into the detailed description, with each claim standing on its own as an independent example. Also, while the claims refer to a specific combination of a dependent claim with one or more other claims, other examples may include combinations of the dependent claim with the subject matter of any other dependent or independent claim. Such combinations are hereby expressly suggested unless it is expressly stated in a particular instance that a particular combination is not intended. Furthermore, features of a claim should also be included in any other independent claim, even if that claim is not directly defined as dependent on any other independent claim. [Explanation of symbols]

[0098] 10 Temperature Processing Entity 20 Optical fiber temperature sensor 25 Fiber Optic Cable 30 Cell Voltage Measurement Entity 40 Stack Current Measurement Entity 40a current measurement probe 50 equipment 52 Interface Circuit 54 Processing circuit 56 Memory circuit 100, 300, 500 Multi-cell electrolyzer

Claims

1. A method for monitoring the status of a multi-cell electrolytic cell, A step (110) of acquiring sensor information using an optical fiber temperature sensor, wherein the sensor information includes at least information about the measured temperature of individual cells of the multi-cell electrolytic cell, The steps include (130) predicting the expected temperature value for each cell of the multi-cell electrolytic cell based on the sensor information, Step (170) provides a notification if the deviation between the predicted temperature value of the cell and the measured temperature of the cell matches the temperature deviation condition. A method that includes this.

2. The method according to claim 1, wherein the predicted temperature value is predicted based on determining the average temperature at different locations for each cell, or determined as a two-dimensional temperature profile of the cell from a plurality of temperature values ​​obtained for the cell.

3. The method according to claim 1 or 2, wherein the sensor information is obtained from at least one optical fiber cable of the optical fiber temperature sensor.

4. The method according to claim 3, wherein the optical fiber cable is arranged in a pattern that continuously surrounds each cell on the outer periphery of a plurality of cells.

5. The method according to claim 3, wherein the optical fiber cable is arranged in a pattern that includes at least one subpattern that is repeated multiple times within the pattern.

6. The method according to claim 5, wherein each subpattern is positioned in exactly one cell such that no single subpattern covers multiple cells.

7. The method of claim 5, wherein the optical fiber cable is arranged such that each cell is covered by multiple repetitions of the subpattern, with each cell repeating a series of subpatterns along the periphery of the respective cell.

8. The method according to claim 4, wherein the pattern includes a circular pattern, a spiral pattern, or a woven pattern combined with a subpattern which includes at least one of a spiral pattern, a snail pattern, a meandering pattern, and a zigzag pattern that covers one portion of an individual electrolytic cell multiple times.

9. The method according to claim 3, wherein the optical fiber cable is arranged between the cell wall and the insulating material.

10. The method according to claim 3, wherein the optical fiber cable surrounds a plurality of small areas for each cell, and determines the average temperature at different locations for each cell, or determines the two-dimensional temperature profile of the cell.

11. The method according to claim 3, wherein the optical fiber cable is arranged in a spiral pattern or snail pattern that is repeated multiple times for each cell.

12. The method according to claim 3, wherein the optical fiber cable is arranged in a meandering or zigzag pattern that is repeated multiple times for each cell.

13. The sensor information includes information about the stack current of the multi-cell electrolytic cell and information about the individual cell voltages of the cells of the multi-cell electrolytic cell, and the method includes the step (140) of predicting the expected voltage value for each cell of the multi-cell electrolytic cell based on the sensor information, or the step of acquiring the expected voltage value of the cells of the multi-cell electrolytic cell as input. The method according to claim 1 or 2, wherein the predicted voltage value is determined based on a multiparameter regression equation, the multiparameter regression equation includes a first parameter for modeling an undesirable reaction in the electrode, a second parameter for modeling at least one of film rupture, pinholes, and degradation, and a third parameter for modeling the degradation of the electrode, and the method includes the steps of determining the deviation between the predicted voltage value of the cell and the measured voltage of the cell (150), and using the multiparameter regression equation to identify the contributions of the first parameter, the second parameter, and the third parameter to the deviation.

14. The method according to claim 13, wherein the multiparameter regression equation is used to assign fault-specific parameters to the multiparameter regression equation in order to model the cell in the form of a startup zone, a zone leading to full load, a shutdown zone, and a load fluctuation zone in which the current changes during normal operation.

15. A computer program having program code for performing the method according to claim 1 or 2 when the computer program is executed on a computer, processor, or programmable hardware component.

16. A device (50) for monitoring the status of a multi-cell electrolytic cell, An interface circuit (52) for acquiring sensor information from one or more sensors, including an optical fiber temperature sensor, A processing circuit (54) configured to perform the method described in claim 1 or 2, and A device equipped with [a certain feature].

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