Flow field visualization detection method and device for flow battery

Abstract

The application discloses a liquid flow battery flow field visualization detection method and device, and the method comprises the following steps: opening a cold fluid valve and starting a 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; closing the cold fluid valve and opening a hot fluid valve, so that the hot fluid flows into the flow field at a preset rate of the flow control pump, and the hot fluid and the cold fluid remaining in the flow field are subjected to convection heat exchange; acquiring color image data displayed by a temperature-sensitive color-changing liquid crystal sheet in the visualization pool through a camera within a preset time period, the color image data being displayed due to the temperature change of the flow field; acquiring multiple color images corresponding to multiple preset time points in the color image data respectively; calculating uniformity coefficients of preset colors in the multiple color images respectively; and judging the uniformity of the flow field distribution according to the uniformity coefficients. The purpose is to characterize the fluid distribution state in the flow field by monitoring the temperature distribution of the flow field in real time, so as to realize in-situ visualization of the flow field.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of flow battery energy storage, in particular to a flow field visualization detection method and device for flow battery. BACKGROUND

[0002] In the prior art, numerical simulation (such as computational fluid dynamics) technology is used to understand the flow behavior of electrolyte in a complex flow channel. However, the current simulation method often ignores too much details of the flow field and is not accurate enough for simplifying calculation or limited by model accuracy. For example, the accurate prediction ability of key phenomena such as local dead zone, vortex, uneven velocity distribution in the flow channel is limited, and it is difficult to fully reflect the complex fluid dynamics behavior under real working conditions, which limits the guiding effect of simulation results on actual flow field design.

[0003] Compared with numerical simulation, direct experimental methods can better reflect the flow field situation under real operating conditions. However, existing flow field experimental methods, such as particle image velocimetry, usually require special transparent battery structures, expensive equipment and specific tracer particles, and the operation is complex, and it is difficult to perform in actual battery materials and real electrochemical reaction environment, and the practicality is greatly limited.

[0004] Therefore, how to provide a flow field visualization detection method for flow battery, which can intuitively and effectively reveal the fluid distribution state in the flow field, so as to realize the in-situ visualization of the flow field, has become a problem to be solved. SUMMARY

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

[0006] In one aspect, the embodiment of the present application provides a flow field visualization detection method for flow battery, which is applied to a flow field visualization device for flow battery, and the detection method comprises the following steps: opening a cold fluid valve and starting a flow control pump, so that the cold fluid flows 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; closing the cold fluid valve and opening a hot fluid valve, so that the hot fluid flows into the flow field at a preset rate of the flow control pump, and the hot fluid and the cold fluid remaining in the flow field exchange heat by convection; acquiring color image data displayed by a temperature-sensitive color-changing liquid crystal sheet in the visualization pool in a preset time period through a camera; acquiring a plurality of color images corresponding to a plurality of preset time points in the color image data respectively; calculating a uniformity coefficient of a preset color in a plurality of color images respectively; and judging the uniformity of the flow field distribution according to the uniformity coefficient.

[0007] Optionally, in some embodiments of the application, the step of opening the cold fluid valve and starting the flow control pump to circulate the cold fluid into the flow field in the visualization tank at a preset rate of the flow control pump until the temperature of the flow field reaches a preset initial temperature specifically comprises: opening the cold fluid valve and starting the flow control pump to circulate the cold fluid into the flow field at a rate of 50 milliliters per minute until the temperature of the flow field reaches a preset initial temperature.

[0008] Optionally, in some embodiments of the 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 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 application, the uniformity of the rate of convective heat exchange in different regions of the flow field is positively correlated with the uniformity of the flow rate in different regions of the flow field and the uniformity of the temperature rise rate in different regions of the flow field.

[0011] Optionally, in some embodiments of the application, the preset time period is between 60 seconds and 100 seconds.

[0012] Optionally, in some embodiments of the application, the step of collecting, by the camera, color image data of the temperature-sensitive color-changing liquid crystal sheet in the visualization tank showing temperature changes of the flow field over a preset time period specifically comprises: collecting, by the camera, at least two color images of the temperature-sensitive color-changing liquid crystal sheet in the visualization tank over a preset time period; and establishing a correspondence between the duration of convective heat exchange of the flow field and the temperature distribution of the flow field according to the at least two color images.

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

[0014] Optionally, in some embodiments of the application, the abnormal region is a region with a temperature rise rate less than the median of the temperature rise rates of the multiple regions.

[0015] Optionally, in some embodiments of the application, the temperature rise rate is calculated according to the following formula: :

[0016] ,

[0017] wherein T is the temperature of the region, ∇T is the temperature gradient, u is the velocity vector of the fluid, k is the thermal conductivity of the porous electrode, p is the density of the porous electrode, C p is the specific heat capacity at constant pressure of the porous electrode, and ∇ 2 is the Laplace operator.

[0018] Optionally, in some embodiments of the present application, the step of respectively acquiring a plurality of color images corresponding to a plurality of preset time points in the color image data specifically comprises: extracting at least two color images corresponding to an interval time of 20 seconds in the color image data.

[0019] Optionally, in some embodiments of the present application, the uniformity coefficient U is calculated according to the following formula:

[0020] ,

[0021] wherein b is the blue value of a single pixel point, 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 of the color image), and dS is the area element (which can represent a pixel).

[0022] Optionally, in some embodiments of the present application, the step of judging the uniformity of the flow field distribution according to the uniformity coefficient specifically comprises: judging the temperature uniformity of the flow field according to the uniformity coefficient; and judging the uniformity of the flow field distribution according to the temperature uniformity.

[0023] Optionally, in some embodiments of the present application, the size of the uniformity coefficient value 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.

[0024] In another aspect, the present application provides a liquid flow battery flow field visualization detection device, which adopts the liquid flow battery flow field visualization detection method as described above to detect the flow field, and comprises a visualization cell, a camera, and a flow assembly. The visualization cell at least comprises superimposed flow channel plates, temperature-sensitive color-changing liquid crystal sheets, and transparent observation plates, and the flow channel plates are provided with flow channels. The camera is arranged above the visualization cell and is used to collect color images presented by the temperature-sensitive color-changing liquid crystal sheets with temperature changes. The flow assembly is arranged on one side of the visualization cell and is connected with the visualization cell to control the temperature and flow rate of the fluid flowing into the visualization cell.

[0025] Compared with the prior art, the flow field visualization detection method and device of the liquid flow battery provided by the application can actively establish a background temperature field reaching a preset initial temperature in the visualization pool by controlling the cold fluid of the preset temperature to flow into the visualization pool, so that the local temperature change caused by the flow rate difference of the hot fluid can be observed by the camera and the color image presented by the thermochromic liquid crystal sheet in response to the temperature change in the flow field can be collected. The application utilizes the characteristic that the temperature is easy to be measured in situ and non-invasively, and the fluid distribution state in the flow field is characterized by real-time monitoring of the temperature change in the flow field, so that the in-situ visualization of the flow field is realized. BRIEF DESCRIPTION OF DRAWINGS

[0026] Figure 1 is a flowchart of the flow field visualization detection method of the liquid flow battery provided by the application;

[0027] Figure 2 is a schematic diagram of the flow field visualization detection device of the liquid flow battery provided by the application;

[0028] Figure 3 is the color image presented by the thermochromic liquid crystal sheet at different moments photographed by the camera in the flow field visualization detection method of the liquid flow battery provided by the application;

[0029] Figure 4 is a corresponding relationship diagram of the time, the blue intensity in the image and the blue uniformity coefficient of the color image photographed by the camera in the flow field visualization detection method of the liquid flow battery provided by the application;

[0030] Figure 5 is the color image corresponding to the flow field of the flow channel of three different cross-sectional widths photographed by the camera;

[0031] Figure 6 is Figure 5 is a corresponding relationship diagram of the photographing time and the blue intensity in the color image of the three flow fields in

[0032] Figure 7 is the color image corresponding to the flow field of the flow channel of three different types photographed by the camera;

[0033] Figure 8 is Figure 7 is a corresponding relationship diagram of the photographing time and the blue intensity in the color image of the three flow fields in DETAILED DESCRIPTION

[0034] The technical solutions in the embodiments of the application will be described below with reference to the drawings in the embodiments of the application. The described technical solutions are only used to explain and illustrate the idea of the application, and should not be regarded as a limitation on the protection scope of the application.

[0035] The various embodiments provided in this application are similar, and features in different embodiments may be combined with each other.

[0036] like Figure 1 As 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:

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] 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.

[0042] 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.

[0043] 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.

[0044] 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.

[0045] Conversely, the lower the uniformity of the rate of convective heat transfer of different regions in the flow field, i.e. the greater the difference in the rate of convective heat transfer of at least some of the plurality of regions in the flow field, the lower the uniformity of the temperature rise rate of different regions in the flow field, i.e. the greater the difference in the temperature rise rate of at least some of the plurality of regions in the flow field.

[0046] Conversely, the lower the uniformity of the rate of convective heat transfer of different regions in the flow field, i.e. the greater the difference in the rate of convective heat transfer of at least some of the plurality of regions in the flow field, the lower the uniformity of the temperature rise rate of different regions in the flow field, i.e. the greater the difference in the temperature rise rate of at least some of the plurality of regions in the flow field.

[0047] S30, acquiring, by the camera, color image data of the temperature change of the thermochromic liquid crystal sheet in the visualization tank as the flow field appears within a preset time period.

[0048] In embodiments of the present application, the preset time period is in the range of 60 seconds to 100 seconds. Specifically, the preset time period includes 60 seconds, 70 seconds, 80 seconds, 90 seconds, and 100 seconds.

[0049] In embodiments of the present application, the type of color image data includes video.

[0050] Step S30 specifically includes:

[0051] S301, acquiring, by the camera, at least two color images of the thermochromic liquid crystal sheet in the visualization tank within a preset time period.

[0052] S302, establishing a correspondence between the duration of convective heat transfer of the flow field and the temperature distribution of the flow field according to the at least two color images.

[0053] In embodiments of the present application, step S302 specifically includes:

[0054] S3021, dividing the flow field into a plurality of regions according to the temperature distribution of the flow field in the first color image.

[0055] Specifically, the positions with the same or similar color in the color image are sequentially divided into a region according to the flow path, and the positions with different colors or large color differences from adjacent regions are divided into a region.

[0056] S3022, calculating the temperature rise rate of each region according to the temperature change of each region over time in the at least two color images.

[0057] For example, to calculate the temperature rise rate of a region, the temperature difference (i.e. temperature gradient) of the region in the two color images needs to be calculated.

[0058] In the embodiments of the present application, the temperature rise rate is calculated according to the following formula :

[0059] ,

[0060] wherein T is the temperature of the region fluid, △T is the temperature gradient, u is the velocity vector of the fluid, k is the thermal conductivity of the porous electrode, p is the density of the porous electrode, C p is the specific heat capacity of the porous electrode at constant pressure, △ 2 is the Laplace operator.

[0061] S3023, judging whether there is an abnormal region according to the temperature rise rate.

[0062] In the embodiments of the present application, the abnormal region is a region whose temperature rise rate is less than the median value of the temperature rise rates of the multiple regions.

[0063] In the embodiments of the present application, the temperature rise rates of each region are compared, and the region whose temperature rise rate is less than the median value is determined as a “dead zone” where the fluid flows slowly or stagnates.

[0064] S40, acquiring multiple color images corresponding to multiple preset time points in the color image data, respectively.

[0065] In the embodiments of the present application, step S40 specifically includes: extracting at least two color images corresponding to time intervals of 20 seconds in the color image data. That is, the preset time points are every 20 seconds.

[0066] For example: 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, and the like in the color image data.

[0067] S50, calculating the uniformity coefficients of the preset color in the multiple color images, respectively.

[0068] In the embodiments of the present application, step S50 specifically includes:

[0069] S501, cutting the color images one by one to retain the part corresponding to the effective observation region of the temperature-sensing color-changing liquid crystal sheet in the color images.

[0070] In the embodiments of the present application, the color image data (video) collected is frame-extracted to acquire color images of temperature distribution at different time points. The color images are cut to retain only the effective observation region of the temperature-sensing color-changing liquid crystal sheet.

[0071] S502, calculating the uniformity coefficients of the blue color in the multiple color images, respectively.

[0072] In the embodiments of the present application, since the thermochromic liquid crystal sheet gradually changes from black to blue during the temperature rise, in order to quantitatively evaluate the uniformity of the temperature distribution, the blue value of the color image is calculated statistically, and the uniformity coefficient of blue in the image is calculated through an image processing program.

[0073] In the embodiments of the present application, the uniformity coefficient U is calculated according to the following formula:

[0074] ,

[0075] wherein b is the blue value of a single pixel point, 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 of the color image), and dS is the area infinitesimal (which can represent a pixel).

[0076] In the embodiments of the present application, the uniformity coefficient U is used to quantify the uniformity of the temperature distribution in the flow field, and the greater the value of the uniformity coefficient U, the higher the uniformity of the temperature distribution in the flow field.

[0077] S60, judging the uniformity of the flow field distribution according to the uniformity coefficient.

[0078] In the embodiments of the present application, step S60 specifically comprises:

[0079] S601, judging the temperature uniformity of the flow field according to the uniformity coefficient.

[0080] S602, judging the uniformity of the flow field distribution according to the temperature uniformity.

[0081] In the 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.

[0082] In the embodiments of the present application, by analyzing the change relationship of the uniformity index (uniformity coefficient U) with time, the progress of temperature uniformization can be evaluated. Finally, using these temperature field uniformity and evolution data, the uniformity of the flow field in the electrode is evaluated, and the flow rate and other related characteristics can be indirectly inferred according to the time to reach steady state and other information.

[0083] The flow field visualization detection method provided by the application can flow cold fluid of a preset temperature into the inside of the visualization pool, thereby actively establishing a background temperature field reaching a preset initial temperature in the inside of the visualization pool, so that the local temperature change caused by the flow rate difference of the hot fluid can be observed by the camera and the color image presented by the temperature-sensitive color-changing liquid crystal sheet in response to the temperature change in the flow field can be collected. The application utilizes the characteristic that temperature is easy to be measured in situ and non-invasively, and the fluid distribution state in the flow field is characterized by real-time monitoring of the temperature change in the flow field, so that the in-situ visualization of the flow field is realized.

[0084] As shown in Figure 2 The application provides a flow field visualization detection device 100 for a liquid flow battery, which adopts the flow field visualization detection method as above to detect the flow field, and includes a camera 101, a visualization pool 102, and a flow assembly 103.

[0085] Specifically, the visualization pool 102 at least includes stacked flow channel plates, porous electrodes, temperature-sensitive color-changing liquid crystal sheets, and transparent observation plates (not shown in the figure), and the flow channel plates are provided with flow channels. The camera 101 is arranged above the visualization pool 102 and is used to collect the color image presented by the temperature-sensitive color-changing liquid crystal sheet in response to the temperature change. The flow assembly 103 is arranged on one side of the visualization pool and is connected with the visualization pool 102, so as to control the temperature and flow rate of the fluid flowing into the visualization pool 102.

[0086] The flow field visualization detection device 100 for a liquid flow battery provided by the application can flow cold fluid of a preset temperature into the inside of the visualization pool, thereby actively establishing a background temperature field reaching a preset initial temperature in the inside of the visualization pool, so that the local temperature change caused by the flow rate difference of the hot fluid can be observed by the camera and the color image presented by the temperature-sensitive color-changing liquid crystal sheet in response to the temperature change in the flow field can be collected. The application utilizes the characteristic that temperature is easy to be measured in situ and non-invasively, and the fluid distribution state in the flow field is characterized by real-time monitoring of the temperature change in the flow field, so that the in-situ visualization of the flow field is realized.

[0087] The flow field visualization detection method and device provided by the application are verified through the following experiments:

[0088] Experiment verification 1:

[0089] In this experiment, a visualization pool equipped with a traditional interdigital flow channel plate is used, and the purpose of the experiment is to visualize and detect the flow field on the surface of the porous electrode.

[0090] Specifically, the flow rate of the flow control pump is set to 50 mL / min, the temperature of the cold water is 30℃, and the temperature of the hot water is 40℃.

[0091] From the moment of closing the cold water valve and opening the hot water valve, the temperature change process of the visualization pool is recorded by the camera.

[0092] The temperature distribution is obtained by extracting video frames every 20 seconds, for example: 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, and the initial color image at the 90th second in the color image data (as shown in Figure 3 It is found that the temperature of the area under the flow channel rib rises faster than that of the area below the flow channel during heat exchange, which is consistent with the characteristics of the fast flow speed under the flow channel rib of the traditional interdigital flow channel. At the same time, the heat exchange in the center area of the flow channel is slow, indicating that the flow speed in this area is low, and it is easy to form a mass transfer "dead zone".

[0093] Further, the uniformity coefficient of the blue distribution in the color image is calculated every 10 seconds (as shown in Figure 4 The results show that the temperature field on the surface of the multi-hole electrode reaches a basic uniformity at about 60 seconds using the traditional interdigital flow channel.

[0094] Experimental verification 2:

[0095] In this experiment, the visualization pool provided by the present application is used, and the purpose of the experiment is to study the influence of the flow channel width on the uniformity of the interdigital flow field.

[0096] Interdigital flow channel plates with flow channel cross-sectional widths of 1 mm, 2 mm, and 3 mm are respectively prepared and assembled in the visualization pool. The experimental conditions (such as flow rate, temperature, etc.) are consistent with those of experimental verification 1.

[0097] From the moment of closing the cold water valve and opening the hot water valve, the temperature change process of the visualization pool is recorded by the camera.

[0098] The video frame at the 20th second is extracted, and the temperature distribution of the flow field under three flow channel widths (a) / (b) / (c) is compared (as shown in Figure 5 .

[0099] The results show that when the flow channel width is 1 mm, the flow field has lost the typical interdigital characteristics, and the flow splitting effect is weak.

[0100] When the flow channel width is increased to 2 mm or 3 mm, the interdigital characteristics appear.

[0101] When the flow channel width is 3 mm, the temperature distribution of the flow field at the 20th second is relatively more uniform. Further, the uniformity coefficient of the temperature distribution of the flow field under different widths is calculated with respect to time (as shown in Figure 6 The experiment shows that the flow channel with a width of 3 mm reaches the temperature uniformity state the fastest, and accordingly, it can greatly improve the fluid renewal speed and flow field uniformity in the multi-hole electrode.

[0102] Experimental verification 3:

[0103] The experiment uses the visualization cell provided in the present application. The experimental purpose is to compare the influence of the traditional inserted finger flow channel, the first type of hierarchical inserted finger flow channel and the second type of hierarchical inserted finger flow channel on the uniformity of the flow field in the porous electrode. The three types of flow channel plates are respectively assembled in the visualization cell.

[0104] The experimental conditions (such as flow rate, temperature, etc.) are the same as those in the experimental verification 1.

[0105] From the moment when the cold water valve is closed and the hot water valve is opened, the temperature change process of the visualization cell is recorded by the camera.

[0106] The video frame at the 20th second is extracted for comparison.

[0107] The results show that (as shown in Figure 7 The three types of flow channels (a) / (b) / (c) all have a slow-flowing "dead zone" in the central area of the porous electrode.

[0108] Among them, the "dead zone" of the traditional inserted finger flow channel (a) is more concentrated.

[0109] The hierarchical inserted finger flow channels (b) / (c) have a relatively reduced and more dispersed "dead zone" area due to their hierarchical structure (for example, having more levels of branched flow channels).

[0110] Further calculation of the uniformity coefficient of the temperature distribution of the flow field under different flow channel types with time (as shown in Figure 8 ).

[0111] The results show that the second type of hierarchical inserted finger flow channel requires the shortest time to reach the temperature uniformity state. Therefore, the second type of hierarchical inserted finger flow channel can be used as an optimized design, which can effectively improve the fluid renewal rate in the electrode and the uniformity of the flow field, and is expected to reduce the concentration polarization of the flow battery.

[0112] The above describes in detail a flow field visualization detection method and device for a flow battery of the embodiments of the present application. The above description of the 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 protection scope of the present application.

Claims

1. A method for liquid flow battery flow field visualization detection, applied to a liquid flow battery flow field visualization device, 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; Determining the uniformity of the flow field distribution according to the uniformity coefficient; 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; establishing a corresponding relationship between the duration of convective heat transfer in the flow field and the temperature distribution in the flow field according to at least two of the color images; 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; determining whether there is an abnormal area based on the temperature rise rate; The abnormal area is an area where the temperature rise rate is less than the median of the temperature rise rates corresponding to the plurality of areas; The temperature rise rate is calculated according to the following formula : ， where T is the zone fluid temperature, ∇T is the temperature gradient, u is the fluid velocity vector, k is the thermal conductivity of the porous electrode, p is the density of the porous electrode, C p is the specific heat capacity of the porous electrode at constant pressure, ∇ 2 is the Laplacian operator; The step of respectively calculating uniformity coefficients of preset colors in the plurality of color images specifically includes: cropping the color images one by one, retaining the portion of the color image corresponding to the effective observation area of ​​the thermochromic liquid crystal panel; The uniformity coefficients of blue in the plurality of color images are calculated respectively.

2. The flow field visualization detection method for liquid flow batteries according to claim 1, wherein, 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 claim 1 or 2, wherein, 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 flow field visualization detection method for liquid flow batteries according to claim 1, wherein, The temperature difference between the hot fluid and the cold fluid is between 9 degrees and 11 degrees.

5. The flow field visualization detection method for liquid flow batteries according to claim 1, wherein, 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 flow field visualization detection method for liquid flow batteries according to claim 1, wherein, The preset time period ranges from 60 seconds to 100 seconds.

7. The flow field visualization detection method for liquid flow batteries according to claim 1, wherein, The step of acquiring the multiple color images corresponding to the multiple preset time points in the color image data specifically includes: Extracting at least two color images corresponding to an interval time of 20 seconds in the color image data.

8. The flow field visualization detection method for liquid flow batteries according to claim 1, wherein, The uniformity coefficient U is calculated according to the following formula: ， where 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 an area infinitesimal.

9. The flow field visualization detection method for liquid flow batteries according to claim 1, wherein, The step of judging the uniformity of the flow field distribution according to the uniformity coefficient specifically includes: Judging the temperature uniformity of the flow field according to the uniformity coefficient; Judging the uniformity of the flow field distribution according to the temperature uniformity.

10. The flow field visualization detection method for liquid flow batteries according to claim 1, wherein, The uniformity coefficient value 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.

11. A flow field visualization detection device for flow field detection of a flow battery, which is subjected to flow field visualization detection according to any one of claims 1 to 10, characterized by It comprises: A visualization pool comprising at least a superimposed flow channel plate, a temperature-sensitive color-changing liquid crystal sheet, and a transparent observation plate, wherein the flow channel plate is provided with a flow channel; A camera arranged above the visualization pool for collecting color images presented by the temperature-sensitive color-changing liquid crystal sheet with temperature change; A flow circulation assembly arranged on one side of the visualization pool and connected with the visualization pool to control the temperature and flow rate of the fluid flowing into the visualization pool.

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