Visual detection method and device for flow field of flow battery

Abstract

The invention discloses a visual detection method and device for a flow field of a flow battery, and the method comprises the steps: opening a cold fluid valve and starting a flow control pump, enabling a cold fluid to circularly flow into a flow field in a visual pool at a preset rate of the flow control pump until the temperature of the flow field reaches a preset initial temperature; the cold fluid valve is closed, the hot fluid valve is opened, the hot fluid flows into the flow field at the speed preset by the flow control pump, and the hot fluid and the cold fluid reserved in the flow field are subjected to convective heat exchange; collecting color image data displayed by the thermochromic liquid crystal sheet in the visual pool along with the temperature change of the flow field in a preset time period through a camera; obtaining a plurality of color images corresponding to a plurality of preset moments in the color image data; respectively calculating uniformity coefficients of preset colors in the plurality of color images; and judging the distribution uniformity of the flow field according to the uniformity coefficient. The method aims to represent the fluid distribution state in a flow field by monitoring the temperature distribution of the flow field in real time, so that the in-situ visualization of the flow field is realized.

Description

Technical Field

[0001] The present application relates to the technical field of liquid flow battery energy storage, and in particular to a method and device for visualizing the flow field of a liquid flow battery. Background Art

[0002] Numerical simulation techniques (such as computational fluid dynamics) are currently used to understand the flow behavior of electrolytes within complex flow channels. However, due to computational simplification or limited model accuracy, current simulation methods often overlook excessive flow field details and are inaccurate. For example, the ability to accurately predict key phenomena within the flow channel, such as local dead zones, eddies, and uneven velocity distribution, is limited. This makes it difficult to fully reflect the complex fluid dynamics behavior under real-world operating conditions, limiting the guiding role of simulation results in actual flow field design.

[0003] Compared to numerical simulations, direct experimental methods can better reflect the flow field conditions under real operating conditions. However, existing flow field experimental methods, such as particle image velocimetry, typically require special transparent battery structures, expensive equipment, and specific tracer particles. These methods are complex to operate and difficult to perform with actual battery materials and in realistic electrochemical reaction environments, significantly limiting their practicality.

[0004] Therefore, how to provide a flow field visualization detection method for liquid flow batteries that can intuitively and effectively reveal the fluid distribution state in the flow field and thus realize in-situ visualization of the flow field has become an urgent problem to be solved. Summary of the Invention

[0005] The present application provides a flow field visualization detection method and device for a liquid flow battery, which aims to intuitively and effectively reveal the fluid distribution state in the flow field, thereby realizing in-situ visualization of the flow field.

[0006] On the one hand, an embodiment of the present application provides a flow battery flow field visualization detection method, which is applied to a flow battery flow field visualization device, and the detection method includes the following steps: opening the cold fluid valve and starting the flow control pump, so that the cold fluid circulates into the flow field in the visualization pool at a rate preset by the flow control pump until the temperature of the flow field reaches a preset initial temperature; closing the cold fluid valve and opening the hot fluid valve, so that the hot fluid flows into the flow field at a rate preset by the flow control pump, and the hot fluid undergoes convection heat exchange with the cold fluid retained in the flow field; collecting color image data displayed by the thermochromic liquid crystal film in the visualization pool during a preset time period as the temperature of the flow field changes through a camera; respectively obtaining multiple color images corresponding to multiple preset moments in the color image data; respectively calculating the uniformity coefficients of the preset colors in the multiple color images; and judging the uniformity of the flow field distribution based on the uniformity coefficients.

[0007] Optionally, in some embodiments of the present application, the step of opening the cold fluid valve and starting the flow control pump so that the cold fluid circulates into the flow field in the visualization pool at a rate preset by the flow control pump until the temperature of the flow field reaches a preset initial temperature specifically includes: opening the cold fluid valve and starting the flow control pump so that the cold fluid circulates into the flow field at a rate of 50 ml per minute until the temperature of the flow field reaches a preset initial temperature.

[0008] Optionally, in some embodiments of the present application, the preset initial temperature is the same as the temperature of the cold fluid, and the temperature of the cold fluid is between 28 degrees and 32 degrees.

[0009] Optionally, in some embodiments of the present application, the temperature difference between the hot fluid and the cold fluid is between 9 degrees and 11 degrees.

[0010] Optionally, in some embodiments of the present application, the uniformity of the convective heat transfer rate in different regions within the flow field is positively correlated with the uniformity of the flow velocity in different regions within the flow field and the uniformity of the temperature rise rate in different regions within the flow field.

[0011] Optionally, in some embodiments of the present application, the preset time period ranges from 60 seconds to 100 seconds.

[0012] Optionally, in some embodiments of the present application, the step of collecting color image data displayed by the thermochromic liquid crystal panel in the visualization pool during a preset time period as the temperature changes in the flow field through a camera specifically includes: collecting at least two color images displayed by the thermochromic liquid crystal panel in the visualization pool during a preset time period through a camera; and establishing a correspondence between the duration of convective heat transfer in the flow field and the temperature distribution of the flow field based on at least two of the color images.

[0013] Optionally, in some embodiments of the present application, the step of establishing a correspondence between the duration of convective heat transfer in the flow field and the temperature distribution of the flow field based on at least two of the color images specifically includes: dividing the flow field into multiple regions based on the temperature distribution of the flow field in the first color image; calculating the temperature rise rate of each of the regions based on the change of the temperature of each of the regions in at least two of the color images over time; and judging whether there is an abnormal region based on the temperature rise rate.

[0014] Optionally, in some embodiments of the present application, the abnormal region is a region where the temperature rise rate is less than a median of the temperature rise rates corresponding to a plurality of regions.

[0015] Optionally, in some embodiments of the present application, the temperature rise rate is calculated according to the following formula: : , Where T is the regional fluid temperature, ▽T is the temperature gradient, u is the fluid velocity vector, k is the thermal conductivity of the porous electrode, ρ is the density of the porous electrode, C p is the constant-pressure specific heat capacity of the porous electrode, ▽ 2 is the Laplace operator.

[0016] Optionally, in some embodiments of the present application, the step of respectively obtaining multiple color images corresponding to multiple preset moments in the color image data specifically includes: extracting at least two of the color images corresponding to an interval of 20 seconds in the color image data.

[0017] Optionally, in some embodiments of the present application, the uniformity coefficient U is calculated according to the following formula: , Among them, b is the blue value of a single pixel, b m is the average blue value of the entire color image, S is the area of ​​the color image (which can represent the total number of pixels in the color image), and dS is the area element (which can represent one pixel).

[0018] Optionally, in some embodiments of the present application, the step of judging the uniformity of the flow field distribution based on the uniformity coefficient specifically includes: judging the temperature uniformity of the flow field based on the uniformity coefficient; and judging the uniformity of the flow field distribution based on the temperature uniformity.

[0019] Optionally, in some embodiments of the present application, the value of the uniformity coefficient is positively correlated with the temperature uniformity of the flow field, and the temperature uniformity of the flow field is positively correlated with the uniformity of the flow field distribution.

[0020] On the other hand, the present application provides a liquid flow battery flow field visualization detection device, which uses the liquid flow battery flow field visualization detection method as described above to perform flow field detection, including: a visualization pool, a camera and a circulation component, the visualization pool at least includes stacked flow channel plates, thermochromic liquid crystal films, and transparent observation plates, and the flow channel is provided on the flow channel plate; the camera is arranged above the visualization pool, for collecting the color image presented by the thermochromic liquid crystal film as the temperature changes; the circulation component is arranged on one side of the visualization pool and connected to the visualization pool to control the temperature and flow rate of the fluid flowing into the visualization pool.

[0021] Compared to existing technologies, the flow field visualization detection method and device provided in this application controls the flow of a cold fluid at a preset temperature into the visualization pool, thereby actively establishing a background temperature field within the visualization pool that reaches a preset initial temperature. This facilitates the use of a camera to observe local temperature changes caused by differences in the flow rate of the hot fluid and to capture the color image presented by the thermochromic liquid crystal in response to temperature changes within the flow field. This application utilizes the ease of in-situ, non-invasive temperature measurement to characterize the fluid distribution state within the flow field by monitoring temperature changes within the flow field in real time, thereby achieving in-situ visualization of the flow field. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a flow chart of the flow field visualization detection method for a flow battery provided in this application; Figure 2 This is a schematic diagram of a flow field visualization detection device for a flow battery provided in this application; Figure 3 It is the color image presented by the thermochromic liquid crystal sheet at different times captured by the camera in the flow field visualization detection method of the liquid flow battery provided in the present application; Figure 4 This is a corresponding relationship diagram of the time of the color image captured by the camera, the blue intensity in the image, and the blue uniformity coefficient in the flow field visualization detection method of the liquid flow battery provided in this application; Figure 5 These are the color images corresponding to the flow fields of three flow channels with different cross-sectional widths captured by the camera; Figure 6 yes Figure 5 The corresponding relationship between the shooting time of the color images of the three flow fields and the blue intensity in the images; Figure 7 These are the color images corresponding to the flow fields of three different types of flow channels taken by the camera; Figure 8 yes Figure 7 The corresponding relationship between the shooting time of the color images of the three flow fields and the blue intensity in the images. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application. The described technical solutions are only used to explain and illustrate the ideas of the present application and should not be regarded as limiting the scope of protection of the present application.

[0024] The various embodiments provided in this application are similar, and features in different embodiments may be combined with each other.

[0025] like Figure 1As shown, an embodiment of the present application provides a flow field visualization detection method for a flow battery, which is applied to a flow field visualization device for a flow battery. The detection method includes the following steps: S10, opening the cold fluid valve and starting the flow control pump, so that the cold fluid circulates into the flow field in the visualization pool at a preset rate of the flow control pump until the temperature of the flow field reaches a preset initial temperature.

[0026] In an embodiment of the present application, step S10 specifically includes: opening the cold fluid valve and starting the flow control pump, so that the cold fluid circulates into the flow field at a rate of 50 ml per minute until the temperature of the flow field reaches a preset initial temperature.

[0027] In an embodiment of the present application, the preset initial temperature is the same as the temperature of the cold fluid, which is between 28°C and 32°C. Specifically, the cold fluid temperature ranges from 28°C, 29°C, 30°C, 31°C, and 32°C. Preferably, the cold fluid temperature is 30°C. The cold fluid is made of water.

[0028] In an embodiment of the present application, the temperature difference between the hot fluid and the cold fluid is between 9 and 11 degrees Celsius. Specifically, the temperature difference between the hot fluid and the cold fluid can be 9, 10, and 11 degrees Celsius. The temperature of the hot fluid can be 37, 38, 39, 40, 41, 42, and 43 degrees Celsius. Preferably, the temperature of the hot fluid is 40 degrees Celsius. The hot fluid is made of water.

[0029] S20, closing the cold fluid valve and opening the hot fluid valve, so that the hot fluid flows into the flow field at a rate preset by the flow control pump, and the hot fluid undergoes convective heat exchange with the cold fluid remaining in the flow field.

[0030] In the embodiment of the present application, the uniformity of the convective heat transfer rate in different regions within the flow field is positively correlated with the uniformity of the flow velocity in different regions within the flow field and the uniformity of the temperature rise rate in different regions within the flow field.

[0031] In other words, if the flow velocity uniformity in different areas of the flow field is higher, that is, the difference in flow velocity in different areas is smaller, then the convective heat transfer rate uniformity in different areas of the flow field is higher, that is, the difference in convective heat transfer rate in different areas of the flow field is smaller.

[0032] If the uniformity of the convective heat transfer rate in different areas of the flow field is higher, that is, the difference in the convective heat transfer rate in different areas of the flow field is smaller, then the uniformity of the temperature rise rate in different areas of the flow field is higher, that is, the difference in the temperature rise rate in different areas of the flow field is smaller.

[0033] On the contrary, if the uniformity of the flow velocity in different areas within the flow field is lower, that is, the difference in the flow velocity of at least some areas among the multiple areas within the flow field is greater, then the uniformity of the convective heat transfer rate in different areas within the flow field is lower, that is, the difference in the convective heat transfer rate of at least some areas among the multiple areas within the flow field is greater.

[0034] If the uniformity of the convective heat transfer rate in different areas of the flow field is lower, that is, the difference in the convective heat transfer rate of at least some areas among multiple areas in the flow field is greater, then the uniformity of the temperature rise rate in different areas of the flow field is lower, that is, the difference in the temperature rise rate of at least some areas among multiple areas in the flow field is greater.

[0035] S30, collecting color image data displayed by the thermochromic liquid crystal sheet in the visualization pool during a preset time period as the temperature changes in the flow field through the camera.

[0036] In an embodiment of the present application, the preset time period ranges from 60 seconds to 100 seconds. Specifically, the preset time period includes 60 seconds, 70 seconds, 80 seconds, 90 seconds, and 100 seconds.

[0037] In an embodiment of the present application, the type of color image data includes video.

[0038] Step S30 specifically includes: S301 , collecting at least two color images displayed by the thermochromic liquid crystal panel in the visualization pool within a preset time period through a camera.

[0039] S302: Establish a corresponding relationship between the duration of the convective heat transfer in the flow field and the temperature distribution in the flow field according to at least two of the color images.

[0040] In the embodiment of the present application, step S302 specifically includes: S3021. Divide the flow field into multiple regions according to the temperature distribution of the flow field in the first color image.

[0041] Specifically, positions with the same or similar colors in the color image are divided into one region according to the direction of the flow channel, and positions with colors that are different from or have a large color difference from adjacent regions are divided into one region.

[0042] S3022. Calculate the temperature rise rate of each region according to the change of the temperature of each region in the at least two color images over time.

[0043] For example, to calculate the temperature rise rate of a certain area, it is necessary to calculate the temperature difference (i.e., temperature gradient) of the area in two color images.

[0044] In the embodiment of the present application, the temperature rise rate is calculated according to the following formula: : , Where T is the regional fluid temperature, ▽T is the temperature gradient, u is the fluid velocity vector, k is the thermal conductivity of the porous electrode, ρ is the density of the porous electrode, C p is the constant-pressure specific heat capacity of the porous electrode, ▽ 2 is the Laplace operator.

[0045] S3023. Determine whether there is an abnormal area based on the temperature rise rate.

[0046] In an embodiment of the present application, the abnormal region is a region where the temperature rise rate is less than the median of the temperature rise rates corresponding to multiple regions.

[0047] In the embodiment of the present application, the temperature rise rate of each region is compared, and the region with a temperature rise rate less than the median value is determined to be a "dead zone" where the fluid flows slowly or is stagnant.

[0048] S40: Respectively obtain a plurality of color images corresponding to a plurality of preset moments in the color image data.

[0049] In the embodiment of the present application, step S40 specifically includes: extracting at least two color images corresponding to a 20-second interval from the color image data, that is, the preset time interval is every 20 seconds.

[0050] Exemplary: extracting the initial color image at the 10th second, the initial color image at the 30th second, the initial color image at the 50th second, the initial color image at the 70th second, the initial color image at the 90th second, etc. from the color image data.

[0051] S50: Calculate uniformity coefficients of preset colors in the plurality of color images respectively.

[0052] In the embodiment of the present application, step S50 specifically includes: S501 , cropping the color images one by one, and retaining the portion of the color image corresponding to the effective observation area of ​​the thermochromic liquid crystal panel.

[0053] In an embodiment of the present application, the collected color image data (video) is frame-drawn to obtain color images of temperature distribution at different times, and the color images are cropped to retain only the effective observation area of ​​the temperature-sensitive color-changing liquid crystal panel.

[0054] S502: Calculate the uniformity coefficient of blue in the multiple color images respectively.

[0055] In the embodiment of the present application, since the thermochromic liquid crystal gradually changes from black to blue during the process of temperature increase, in order to facilitate the quantitative evaluation of the uniformity of the temperature distribution, the blue value of the color image will be statistically calculated, and the uniformity coefficient of the blue in the image will be calculated through an image processing program.

[0056] In the embodiment of the present application, the uniformity coefficient U is calculated according to the following formula: , Among them, b is the blue value of a single pixel, b m is the average blue value of the entire color image, S is the area of ​​the color image (which can represent the total number of pixels in the color image), and dS is the area element (which can represent one pixel).

[0057] In the embodiment of the present application, the uniformity coefficient U is used to quantify the uniformity of the temperature distribution in the flow field. The larger the value of the uniformity coefficient U is, the higher the uniformity of the temperature distribution in the flow field is.

[0058] S60. Determine the uniformity of the flow field distribution according to the uniformity coefficient.

[0059] In the embodiment of the present application, step S60 specifically includes: S601. Determine the temperature uniformity of the flow field according to the uniformity coefficient.

[0060] S602: Determine the uniformity of the flow field distribution according to the temperature uniformity.

[0061] In the embodiment of the present application, the value of the uniformity coefficient is positively correlated with the temperature uniformity of the flow field, and the temperature uniformity of the flow field is positively correlated with the uniformity of the flow field distribution.

[0062] In the embodiments of this application, the progress of temperature homogenization can be assessed by analyzing the temporal evolution of this uniformity index (uniformity coefficient U). Ultimately, this temperature field uniformity and evolution data can be used to assess the uniformity of the flow field within the electrode. Furthermore, information such as the time to reach steady state can be used to indirectly infer related characteristics such as flow velocity.

[0063] The flow field visualization detection method for a flow battery provided herein controls the flow of a cold fluid at a preset temperature into a visualization cell, thereby actively establishing a background temperature field within the cell that reaches a preset initial temperature. This facilitates the use of a camera to observe local temperature changes caused by differences in the flow rate of the hot fluid and to capture color images presented by the thermochromic liquid crystal in response to temperature changes within the flow field. This method utilizes the ease of in-situ, non-invasive temperature measurement to characterize the fluid distribution within the flow field by monitoring temperature changes in real time, thereby achieving in-situ visualization of the flow field.

[0064] like Figure 2As shown, the present application provides a flow field visualization detection device 100 for a liquid flow battery, which uses the above-mentioned flow field visualization detection method for a liquid flow battery to perform flow field detection, including: a camera 101, a visualization pool 102 and a circulation component 103.

[0065] Specifically, visualization cell 102 comprises at least a stacked flow channel plate, a porous electrode, a thermochromic liquid crystal panel, and a transparent observation panel (not shown). The flow channel plate is provided with a flow channel. A camera 101 is positioned above visualization cell 102 to capture color images produced by the thermochromic liquid crystal panel as temperature changes. A flow assembly 103 is positioned on one side of the visualization cell and connected to the cell to control the temperature and flow rate of the fluid flowing into the cell.

[0066] The flow field visualization detection device 100 provided herein controls the flow of a cold fluid at a preset temperature into a visualization pool, thereby actively establishing a background temperature field within the pool that reaches a preset initial temperature. This facilitates the use of a camera to observe local temperature changes caused by differences in the flow rate of the hot fluid and to capture color images presented by the thermochromic liquid crystal in response to temperature changes within the flow field. This application utilizes the ease of in-situ, non-invasive temperature measurement to characterize the fluid distribution within the flow field by monitoring temperature changes within the flow field in real time, thereby achieving in-situ visualization of the flow field.

[0067] The flow field visualization detection method and device provided in this application were verified by the following experiments: Experimental verification 1: This experiment uses a visualization cell equipped with a traditional interdigitated flow channel plate. The purpose of the experiment is to visualize the flow field on the surface of the porous electrode.

[0068] Specifically, the flow rate of the flow control pump was set to 50 mL / min, the temperature of the cold water was set to 30°C, and the temperature of the hot water was set to 40°C.

[0069] From the moment the cold water valve is closed and the hot water valve is opened, the temperature change process of the visualization pool is recorded by a camera.

[0070] The temperature distribution map is obtained by extracting frames of the video every 20 seconds. For example, the initial color image of the 10th second, the initial color image of the 30th second, the initial color image of the 50th second, the initial color image of the 70th second, the initial color image of the 90th second (such as Figure 3 (As shown in the figure), observations show that during heat transfer, the area below the channel ribs heats up faster than the area below the channel, consistent with the high flow velocity below the ribs of interdigitated channel ribs. Meanwhile, heat transfer is slower in the center of the channel, indicating a lower flow velocity there, which can easily create a mass transfer "dead zone."

[0071] Furthermore, the video is framed every 10 seconds and the uniformity coefficient of the blue distribution in the color image is calculated (e.g. Figure 4 As shown in Figure 3), the results show that by using the traditional interdigitated flow channel, the surface temperature field of the porous electrode becomes basically uniform in about 60 seconds.

[0072] Experimental verification 2: This experiment uses the visualization pool provided by this application, and the purpose of the experiment is to study the effect of flow channel width on the uniformity of the interdigitating flow field.

[0073] Finger-shaped flow plates with channel cross-sectional widths of 1 mm, 2 mm, and 3 mm were prepared and assembled in a visualization cell. Experimental conditions (e.g., flow rate, temperature, etc.) were consistent with those in Experiment 1.

[0074] From the moment the cold water valve is closed and the hot water valve is opened, the temperature change process of the visualization pool is recorded by a camera.

[0075] Extract the video frame at the 20th second and compare the temperature distribution of the flow field under three flow channel widths (a) / (b) / (c) (e.g. Figure 5 shown).

[0076] The results show that when the channel width is 1 mm, the flow field has lost its typical interdigitating characteristics and the diversion effect is weak.

[0077] When the flow channel width increases to 2mm or 3mm, the interdigitation feature appears.

[0078] When the flow channel width is 3mm, the temperature distribution of the flow field is relatively more uniform at the 20th second. Further calculation of the uniformity coefficient of the flow field temperature distribution under different widths over time (such as Figure 6 As shown in Figure 3 ), experiments show that a flow channel with a width of 3 mm can reach a temperature uniform state the fastest. Accordingly, it can greatly improve the renewal speed and flow field uniformity of the fluid in the porous electrode.

[0079] Experimental verification 3: This experiment used the visualization cell provided by this application. The purpose of the experiment was to compare the effects of traditional interdigitated flow channels, the first type of graded interdigitated flow channels, and the second type of graded interdigitated flow channels on the uniformity of the flow field within the porous electrode. Each of the three flow channel plates was assembled in the visualization cell.

[0080] The experimental conditions (such as flow rate, temperature, etc.) are the same as those in Experiment 1.

[0081] From the moment the cold water valve is closed and the hot water valve is opened, the temperature change process of the visualization pool is recorded by a camera.

[0082] The video frame at the 20th second is extracted for comparison.

[0083] The results show that: (such as Figure 7All three flow channels (a) / (b) / (c) have a “dead zone” with slow flow in the center of the porous electrode.

[0084] Among them, the “dead zone” of the traditional interdigitated flow channel (a) is relatively concentrated.

[0085] The “dead zone” area of ​​the graded interdigitated flow channel (b) / (c) is relatively smaller and more dispersed due to its graded structure (e.g., branched flow channels with more stages).

[0086] Further calculation of the change of uniformity coefficient of flow field temperature distribution with time under different flow channel types (such as Figure 8 shown).

[0087] The results show that the second type of graded interdigitated flow channel takes the shortest time to reach a uniform temperature state. Therefore, the second type of graded interdigitated flow channel can be used as an optimized design to effectively improve the fluid renewal rate and flow field uniformity within the electrode, and is expected to reduce concentration polarization in liquid flow batteries.

[0088] The above is a detailed introduction to a method and device for visualizing the flow field of a liquid flow battery input by the embodiments of the present application. The description of the above embodiments is only used to help understand the core idea of ​​the present application, and the above description should not be understood as limiting the scope of protection of the present application.

Claims

1. A flow field visualization detection method for a liquid flow battery, applied to a flow field visualization device for a liquid flow battery, characterized in that: The detection method comprises the following steps: Opening the cold fluid valve and starting the flow control pump, so that the cold fluid circulates into the flow field in the visualization pool at a rate preset by the flow control pump until the temperature of the flow field reaches a preset initial temperature; Closing the cold fluid valve and opening the hot fluid valve, so that the hot fluid flows into the flow field at a rate preset by the flow control pump, and the hot fluid undergoes convective heat exchange with the cold fluid remaining in the flow field; Collecting color image data displayed by the thermochromic liquid crystal sheet in the visualization pool during a preset time period as the temperature of the flow field changes through a camera; Respectively acquiring a plurality of color images corresponding to a plurality of preset moments in the color image data; Calculating uniformity coefficients of preset colors in the plurality of color images respectively; The uniformity of the flow field distribution is determined according to the uniformity coefficient.

2. The flow field visualization detection method of a flow battery according to claim 1, characterized in that: The step of opening the cold fluid valve and starting the flow control pump so that the cold fluid circulates into the flow field in the visualization pool at a rate preset by the flow control pump until the temperature of the flow field reaches a preset initial temperature specifically includes: The cold fluid valve is opened and the flow control pump is started, so that the cold fluid circulates into the flow field at a rate of 50 ml per minute until the temperature of the flow field reaches a preset initial temperature.

3. The flow field visualization detection method of a flow battery according to claim 1 or 2, characterized in that: The preset initial temperature is the same as the temperature of the cold fluid, and the temperature of the cold fluid is between 28 degrees and 32 degrees.

4. The method for visualizing flow field detection of a flow battery according to claim 1, characterized in that: The temperature difference between the hot fluid and the cold fluid is between 9 degrees and 11 degrees.

5. The method for visualizing flow field detection of a flow battery according to claim 1, characterized in that: The uniformity of the convective heat transfer rate in different areas within the flow field is positively correlated with the uniformity of the flow velocity in different areas within the flow field and the uniformity of the temperature rise rate in different areas within the flow field.

6. The method for visualizing flow field detection of a flow battery according to claim 1, characterized in that: The preset time period ranges from 60 seconds to 100 seconds.

7. The method for visualizing flow field detection of a flow battery according to claim 1, characterized in that: The step of collecting color image data displayed by the thermochromic liquid crystal sheet in the visualization pool during a preset time period as the temperature of the flow field changes, by using a camera, specifically includes: collecting at least two color images displayed by the thermochromic liquid crystal sheet in the visualization pool within a preset time period through a camera; A corresponding relationship between the duration of the convective heat transfer in the flow field and the temperature distribution in the flow field is established based on at least two of the color images.

8. The method for visualizing flow field detection of a flow battery according to claim 1, characterized in that: The step of establishing a corresponding relationship between the duration of the convective heat transfer in the flow field and the temperature distribution in the flow field based on at least two of the color images specifically includes: dividing the flow field into a plurality of regions according to the temperature distribution of the flow field in the first color image; Calculating the temperature rise rate of each of the regions according to the change in temperature of each of the regions over time in at least two of the color images; It is determined whether there is an abnormal area based on the temperature rise rate.

9. The method for visualizing flow field detection of a flow battery according to claim 8, characterized in that: The abnormal region is a region where the temperature rise rate is less than a median of the temperature rise rates corresponding to a plurality of regions.

10. The flow field visualization detection method of a flow battery according to claim 8, characterized in that: The temperature rise rate is calculated according to the following formula : ， Where T is the regional fluid temperature, ▽T is the temperature gradient, u is the fluid velocity vector, k is the thermal conductivity of the porous electrode, ρ is the density of the porous electrode, C p is the constant-pressure specific heat capacity of the porous electrode, ▽ 2 is the Laplace operator.

11. The method for visualizing flow field detection of a flow battery according to claim 1, characterized in that: The step of respectively acquiring a plurality of color images corresponding to a plurality of preset moments in the color image data specifically includes: At least two color images corresponding to a time interval of 20 seconds are extracted from the color image data.

12. The method for visualizing flow field detection of a flow battery according to claim 1, characterized in that: The uniformity coefficient U is calculated according to the following formula: ， Among them, b is the blue value of a single pixel, b m is the average blue value of the entire color image, S is the area of ​​the color image, and dS is the area element.

13. The method for visualizing flow field detection of a flow battery according to claim 1, characterized in that: The step of determining the uniformity of the flow field distribution according to the uniformity coefficient specifically includes: determining the temperature uniformity of the flow field according to the uniformity coefficient; The uniformity of the flow field distribution is determined based on the temperature uniformity.

14. The method for visualizing flow field detection of a flow battery according to claim 1, characterized in that: The value of the uniformity coefficient is positively correlated with the temperature uniformity of the flow field, and the temperature uniformity of the flow field is positively correlated with the uniformity of the flow field distribution.

15. A flow field visualization detection device for a liquid flow battery, which uses the flow field visualization detection method for a liquid flow battery according to any one of claims 1 to 14 to perform flow field detection, characterized in that: include: A visualization pool, the visualization pool comprising at least stacked flow channel plates, a thermochromic liquid crystal sheet, and a transparent observation plate, wherein the flow channel plates are provided with flow channels; A camera is provided above the visualization pool and is used to collect color images of the thermochromic liquid crystal sheet as the temperature changes; A circulation component is arranged at one side of the visualization pool and connected to the visualization pool to control the temperature and flow rate of the fluid flowing into the visualization pool.

Images