Method and device for determining unstable flow drift interval of parallel evaporators

Abstract

The invention provides a method and device for determining a flow drift unstable interval of parallel evaporators, and the method comprises the steps: connecting any target evaporator in the parallel evaporators into a test system, testing the target evaporator through a first test method based on first flow characteristic data, and obtaining a first unstable interval; verifying the first unstable interval, and if the first unstable interval does not meet a preset precision requirement, adjusting the first flow characteristic data in the first test method to obtain adjusted second flow characteristic data; and a second testing method based on the second flow characteristic data is used for testing the target evaporator to obtain a second unstable interval. According to the method, the evaporator is tested through different methods, the flow drift unstable interval of the evaporator is rapidly determined, and a basis is provided for design optimization and engineering application of a two-phase fluid loop.

Description

Technical Field

[0001] The present application relates to the technical field of pump-driven two-phase fluid circuits, and in particular to a method and device for determining an unstable range of flow drift of parallel evaporators. Background Art

[0002] In a pump-driven two-phase fluid circuit, when multiple evaporators operate in parallel, if the system flow distribution does not match the evaporator's flow resistance characteristics, this can trigger unstable flow drift. Specifically, due to a sudden increase in local resistance or heat load fluctuations, the internal working fluid flow rate of one evaporator drops sharply, while the flow rate of other evaporators increases abnormally. This phenomenon can cause localized drying and overheating of the evaporator, and in severe cases, cause heat dissipation failure and equipment burnout. Therefore, to ensure the normal operation of the pump-driven two-phase fluid circuit heat dissipation system, it is necessary to test and determine the unstable flow drift range of the parallel evaporators. Traditional testing methods make it difficult to accurately define the boundaries of this unstable range. Summary of the Invention

[0003] In view of this, the purpose of the present application is to provide a method, device, equipment and medium for determining the unstable range of flow drift of parallel evaporators, so as to overcome the problems in the prior art.

[0004] In a first aspect, an embodiment of the present application provides a method for determining an unstable range of flow drift of parallel evaporators, the method comprising:

[0005] Connecting any target evaporator in the parallel evaporators to the test system, and testing the target evaporator using a first test method based on first flow characteristic data to obtain a first unstable interval;

[0006] Verifying the first unstable interval, and if the first unstable interval does not meet a preset accuracy requirement, adjusting the first flow characteristic data in the first test method to obtain adjusted second flow characteristic data;

[0007] The target evaporator is tested using a second testing method based on the second flow characteristic data to obtain a second unstable interval.

[0008] In some technical solutions of the present application, the first flow characteristic data includes pressure drop data, and the first unstable interval is obtained by testing the target evaporator using a first testing method based on the first flow characteristic data, including:

[0009] Under a preset first heating power, according to a preset first adjustment method, the flow rate entering the target evaporator is adjusted to obtain pressure drop data corresponding to different flow rates;

[0010] Fitting the pressure drop data based on a first fitting algorithm to obtain a first fitting function;

[0011] The first unstable interval is determined according to the extreme value points in the first fitting function.

[0012] In some technical solutions of the present application, the pressure drop data is fitted based on the first fitting algorithm to obtain a first fitting function, including:

[0013] Fitting the pressure drop data using a check mark function to obtain a first fitting function;

[0014] The determining the first unstable interval according to the extreme value points in the first fitting function includes:

[0015] The first unstable interval is determined according to the target flow data corresponding to the minimum point in the first fitting function.

[0016] In some technical solutions of the present application, the above method verifies the first unstable interval by the following method:

[0017] Acquiring application data of the target evaporator in an application scenario;

[0018] The first unstable interval is verified based on whether abnormal data in the application data appears outside the first unstable interval.

[0019] In some technical solutions of the present application, the second flow characteristic data includes: pressure drop data and pressure drop amplitude data; and the second unstable interval is obtained by testing the target evaporator using a second testing method based on the second flow characteristic data, including:

[0020] Under a preset second heating power, according to a preset second adjustment method, the flow rate entering the target evaporator is adjusted to obtain pressure drop data and pressure drop amplitude data corresponding to different flow rates;

[0021] Fitting the pressure drop data based on a first fitting algorithm to obtain a first fitting function;

[0022] Fitting the pressure drop amplitude data based on a second fitting algorithm to obtain a second fitting function;

[0023] The second unstable interval is determined according to the first fitting function and the second fitting function.

[0024] In some technical solutions of the present application, the voltage drop amplitude data is fitted based on the second fitting algorithm to obtain a second fitting function, including:

[0025] The voltage drop amplitude data is fitted based on a quartic polynomial to obtain a second fitting function.

[0026] In some technical solutions of the present application, determining the second unstable interval according to the first fitting function and the second fitting function includes:

[0027] constructing an unstable function based on the target pressure drop data corresponding to the minimum point in the first fitting function, the first fitting function, and the second fitting function;

[0028] An extreme value solution is performed on the unstable function to determine the second unstable interval.

[0029] In a second aspect, an embodiment of the present application provides a device for determining an unstable range of flow rate drift of parallel evaporators, the device comprising:

[0030] A first testing module is configured to connect any target evaporator in the parallel evaporators to the testing system, and test the target evaporator using a first testing method based on first flow characteristic data to obtain a first unstable interval;

[0031] an adjustment module, configured to verify the first unstable interval, and if the first unstable interval does not meet a preset accuracy requirement, adjust the first flow characteristic data in the first test method to obtain adjusted second flow characteristic data;

[0032] The second testing module is configured to test the target evaporator using a second testing method based on the second flow characteristic data to obtain a second unstable interval.

[0033] In a third aspect, an embodiment of the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the method for determining the unstable interval of flow drift of the parallel evaporator are implemented.

[0034] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the method for determining the unstable interval of flow drift of the parallel evaporator are executed.

[0035] The technical solutions provided by the embodiments of the present application may have the following beneficial effects:

[0036] The method of the present application includes: connecting any target evaporator in the parallel evaporator to a test system, testing the target evaporator using a first test method based on first flow characteristic data to obtain a first unstable interval; verifying the first unstable interval, and if the first unstable interval does not meet the preset accuracy requirements, adjusting the first flow characteristic data in the first test method to obtain adjusted second flow characteristic data; and testing the target evaporator using a second test method based on the second flow characteristic data to obtain a second unstable interval. The present application tests the evaporator using different methods to quickly determine its flow drift unstable interval, providing a basis for the design optimization and engineering application of two-phase fluid circuits.

[0037] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0039] Figure 1 A schematic flow chart of a method for determining an unstable interval of flow rate drift of parallel evaporators provided in an embodiment of the present application is shown;

[0040] Figure 2 A schematic diagram of a test system provided in an embodiment of the present application is shown;

[0041] Figure 3 A schematic diagram of a serpentine flow channel evaporator provided in an embodiment of the present application is shown;

[0042] Figure 4 shows a steady-state pressure drop data diagram of an evaporator provided in an embodiment of the present application;

[0043] Figure 5 A data diagram of the dynamic pressure drop oscillation amplitude of an evaporator provided in an embodiment of the present application is shown;

[0044] Figure 6 A steady-state voltage drop data curve diagram provided by an embodiment of the present application is shown;

[0045] Figure 7 A voltage drop oscillation amplitude curve diagram provided in an embodiment of the present application is shown;

[0046] Figure 8A drift data comparison diagram provided by an embodiment of the present application is shown;

[0047] Figure 9 A schematic diagram of a device for determining an unstable range of flow rate drift of parallel evaporators provided in an embodiment of the present application is shown;

[0048] Figure 10 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the drawings in the present application only serve the purpose of illustration and description and are not used to limit the scope of protection of the present application. In addition, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate the operations implemented according to some embodiments of the present application. It should be understood that the operations of the flowcharts can be implemented out of sequence, and steps without logical context can be reversed or implemented simultaneously. In addition, those skilled in the art, under the guidance of the contents of this application, can add one or more other operations to the flowchart, or remove one or more operations from the flowchart.

[0050] In addition, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present application.

[0051] It should be noted that the term "comprising" will be used in the embodiments of the present application to indicate the existence of the features declared thereafter, but does not exclude the addition of other features.

[0052] The peak heat load of the new generation of airborne electronic equipment, satellite payloads and electric vehicle power batteries continues to increase and has exceeded 100W / cm 2Order of magnitude. Moreover, the above-mentioned heat-generating equipment is usually a plurality of distributed heat sources, which are difficult to be cooled by a single cold plate. The pump-driven fluid circuit heat dissipation technology has gradually become the core solution in the field of high-power distributed heat source heat dissipation due to its characteristics of actively regulating flow and temperature distribution, and its ability to cool multiple distributed heat sources at the same time. Pump-driven fluid circuits are divided into single-phase fluid circuits and two-phase fluid circuits according to whether the flowing working fluid undergoes phase change. The pump-driven single-phase fluid circuit relies on the sensible heat transfer of the working fluid and has the advantages of simple structure and stable flow control. In comparison, the pump-driven two-phase fluid circuit carries away heat in the form of latent heat through the vaporization phase change of the working fluid in the evaporator, which can significantly improve the heat transfer efficiency and temperature uniformity. However, due to the dynamic coupling characteristics of the gas-liquid two-phase flow, the pump-driven two-phase fluid circuit has the problem of flow instability, especially the flow drift phenomenon under the parallel evaporator architecture, which restricts the large-scale engineering application of the pump-driven two-phase fluid circuit.

[0053] In a pump-driven two-phase fluid circuit, when multiple evaporators operate in parallel, a mismatch between the system flow distribution and the evaporator's flow resistance characteristics can trigger unstable flow drift. Specifically, this can manifest as a sudden drop in the working fluid flow rate in one evaporator due to a sudden increase in local resistance or a fluctuating heat load, while the flow rate in other evaporators increases abnormally. This phenomenon can cause localized drying and overheating of the evaporator, and in severe cases, lead to heat dissipation failure and equipment burnout. Therefore, to ensure the proper operation of the cooling system in a pump-driven two-phase fluid circuit, it is necessary to test and determine the unstable flow drift range of the parallel evaporators.

[0054] Existing methods for predicting the unstable flow drift range of parallel evaporators primarily rely on experimental or simulation methods. Experimental testing of this range typically relies on a multi-evaporator parallel test bench, increasing the complexity and cost of the setup. Simulation-based prediction methods for this range rely primarily on empirical formulas or simplified models established by previous researchers, failing to fully consider the dynamic flow characteristics of the evaporator. Furthermore, these simulation-based prediction methods are only applicable to geometrically simple evaporators and struggle to predict the unstable flow drift range for complex evaporator structures.

[0055] Based on this, the present invention provides a method, device, equipment, and medium for determining the unstable range of flow rate drift in parallel evaporators. By testing the flow characteristic curve of a single evaporator and combining it with theoretical criteria, the unstable range of flow rate drift can be quickly determined, providing a basis for the design optimization and engineering application of two-phase fluid circuits. This is described below through an example.

[0056] Figure 1 A flow chart of a method for determining an unstable range of flow drift of parallel evaporators provided in an embodiment of the present application is shown, wherein the method includes steps S101-S103; specifically:

[0057] S101, connecting any target evaporator in the parallel evaporators to a test system, and testing the target evaporator using a first test method based on first flow characteristic data to obtain a first unstable interval;

[0058] S102, verifying the first unstable interval, and if the first unstable interval does not meet the preset accuracy requirement, adjusting the first flow characteristic data in the first test method to obtain adjusted second flow characteristic data;

[0059] S103: Test the target evaporator using a second test method based on the second flow characteristic data to obtain a second unstable interval.

[0060] The following describes some embodiments of the present application in detail. In the absence of conflict, the following embodiments and features in the embodiments may be combined with each other.

[0061] The embodiment of the present application provides a method for determining the unstable interval of an evaporator, which acts on a test system, such as Figure 2 As shown in the figure, the test system is a pump-driven two-phase fluid circuit test bench, specifically including a liquid reservoir, a constant flow pump, a preheater, a heating plate, a DC power supply, a condenser, and a water chiller. Key measuring instruments include a flow meter, a pressure gauge, a thermometer, and a differential pressure sensor. It is important to note that the use of a constant flow pump (such as a plunger pump) can provide a stable working fluid flow during the test, avoiding flow drift in the single evaporator itself. The differential pressure sensor should be fixed at both ends of the evaporator as much as possible to ensure the most accurate pressure drop data measurement results.

[0062] An embodiment of the present application provides a method for determining an unstable interval of an evaporator, and the inventive concept is to measure any target evaporator in parallel evaporators (including multiple identical evaporators) based on different methods to ensure measurement accuracy. Specifically, the embodiment of the present application uses a first test method to test the target evaporator to obtain a first unstable interval, and then verifies the first unstable interval. In actual business scenarios, there are cases where the first unstable interval has met the business accuracy requirements, and there are also cases where the business accuracy requirements are not met. In the case where the first unstable interval does not meet the business accuracy requirements, the embodiment of the present application uses a second test method to test the target evaporator again to determine the second unstable interval.

[0063] In the embodiments of the present application, the first testing method is performed based on first flow characteristic data, while the second testing method is performed based on second flow characteristic data. The amount of second flow characteristic data and first flow characteristic data is greater than the amount of first flow characteristic data. Specifically, the first flow characteristic data includes pressure drop data, while the second flow characteristic data includes pressure drop data and pressure drop amplitude data. In other words, in the embodiments of the present application, the first testing method is performed based on pressure drop data, while the second testing method is performed based on pressure drop data and pressure drop amplitude data.

[0064] During implementation, the present embodiment acquires the first and second flow characteristic data in the following manner: A target evaporator of a certain configuration is connected to a pump-driven two-phase fluid circuit. The temperature within the reservoir is set to the desired saturation temperature, the preheater temperature is set to the desired inlet temperature, and the heater power is maintained at the desired test power (either the first heating power or the second heating power). The pumping flow rate is adjusted to a maximum value to maintain a single-phase liquid at the evaporator outlet. The pumping flow rate is then gradually reduced, and the corresponding pressure drop data and pressure drop amplitude data are recorded for each flow rate.

[0065] When acquiring flow characteristic data, to ensure data accuracy, the pressure drop data corresponding to each flow rate is averaged to obtain steady-state pressure drop data, which is used as the first flow characteristic data or the second flow characteristic data. The pressure drop data corresponding to each flow rate is averaged to eliminate abnormal points and then the extreme value is taken to obtain dynamic pressure drop amplitude data, which is used as the second flow characteristic data.

[0066] For the first test method: Based on a first fitting algorithm, the pressure drop data is fitted to obtain a first fitting function; the first unstable interval is determined based on the extreme value points in the first fitting function. Preferably, a check mark function is used to fit the pressure drop data to obtain the first fitting function; the first unstable interval is determined based on the target flow rate data corresponding to the minimum value points in the first fitting function.

[0067] For example, take the flow rate as the independent variable x and the pressure drop as the dependent variable y1, and arrange the data in ascending order by x. In order to ensure the fitting effect, after sorting, the embodiment of the present application also needs to verify the number of pressure drop data. Fitting is performed only when the number of pressure drop data meets the preset quantity requirements. For example, there are no less than 3 data in the negative slope area (including endpoints) of the pressure drop with respect to the flow rate. For the dependent variable y1, the check mark function is used for data fitting, and the check mark function form is f(x) = ax+b / x+c. For the dependent variable y1, calculate the coordinates x_valley and y_valley of the minimum point corresponding to the zero derivative of the check mark function. The part of x < x_valley is taken as the first unstable interval.

[0068] After obtaining the first unstable interval, actual business operations are tested within the first unstable interval to obtain real business data (including the actual voltage drop at the first heating power). The actual voltage drop data is compared with the first unstable interval to determine whether the first unstable interval is accurate. If the first unstable interval is not accurate enough, the second test method is used for testing.

[0069] When using the second test method, the embodiment of the present application needs to adjust the first flow characteristic data in the first test method to obtain the second flow characteristic data. The basis for adjusting the first flow characteristic data here is to take into account the impact of pressure drop changes on the unstable interval. In particular, for a parallel evaporator combination, when the pressure drop of the two evaporators changes instantaneously, the pressure drop of one evaporator increases instantaneously, and the pressure drop of the other evaporator decreases instantaneously, then the liquid flow medium at the inlet is more inclined to flow into the evaporator on the side with smaller pressure drop at this moment, causing instantaneous flow distribution differences. This difference in flow distribution may cause instability to occur in an interval with larger flow. Considering that the root cause of this phenomenon is the instantaneous change in pressure drop, when the first unstable interval is not accurate enough, pressure drop amplitude data can be introduced to determine the second unstable interval.

[0070] For the second test method: Based on the first fitting algorithm, the pressure drop data is fitted to obtain a first fitting function; based on the second fitting algorithm, the pressure drop amplitude data is fitted to obtain a second fitting function; and the second unstable range is determined based on the first fitting function and the second fitting function. Preferably, based on a quartic polynomial, the pressure drop amplitude data is fitted to obtain a second fitting function, and an unstable function is constructed based on the target pressure drop data corresponding to the minimum point in the first fitting function, the first fitting function, and the second fitting function; the unstable function is solved for the extreme value to determine the second unstable range.

[0071] For example, take the flow rate as the independent variable x, the pressure drop as the dependent variable y1, and the pressure drop amplitude as the dependent variable y2; the embodiments of the present application also need to verify the quantity of the pressure drop data. Only when the quantity of the pressure drop data meets the preset quantity requirement, fitting is performed. For example, the number of data points in the negative slope region (including endpoints) of the pressure drop with respect to the flow rate is not less than 3. Further, in order to improve the data processing efficiency, data with less influence is discarded. For the dependent variable y1, the coordinates x_peak of the maximum value point in the negative slope region of y1 with respect to x are extracted, and data points with x≥x_peak are retained. For the dependent variable y1, a hook function is used for data fitting, and the form of the hook function is f(x) = ax + b / x + c; the coordinates x_valley and y_valley of the minimum value point corresponding to the derivative of the hook function being zero are calculated. Data with less influence is discarded. For the dependent variable y2, data points with x≥x_peak are retained; for the dependent variable y2, a quartic polynomial is used for data fitting to obtain the function g(x); according to the obtained functions f(x) and g(x), take the function h(x) = f(x) - g(x) - y_valley, and calculate the maximum value x_uns of the solution of the function h(x) within the x data range; output the flow rate drift unstable interval of the evaporator at this heating power: flow rate < x_uns. The "flow rate < x_uns" obtained by solving according to the above procedure is the flow rate drift unstable interval of an evaporator of a certain configuration. That is, when the system operates in parallel evaporators, if the flow rate < x_uns, it is very likely that a flow rate drift phenomenon occurs, resulting in a significant uneven flow rate distribution between two or more evaporators.

[0072] Based on the flow characteristic test data of a single evaporator, the present application comprehensively considers the steady-state pressure drop data and the dynamic pressure drop oscillation data, and obtains the flow rate drift unstable interval through function fitting and extreme point calculation by a program, saving the test cost. Moreover, since the test data comes from a specific evaporator configuration, the obtained unstable interval has a higher accuracy and stronger guiding significance for engineering applications.

[0073] In an optional embodiment, a method for determining the flow rate drift unstable interval of parallel evaporators and its implementation details are provided. It includes 6 steps:

[0074] Step 1: At a specific heating power, adjust the flow rate from large to small, and test the flow characteristic data of a single evaporator at different flow rates. [[ID=??]] [[ID=??]]

[0075] Among them, the flow rate is adjusted by a constant flow rate pump (such as a plunger pump). At a larger flow rate, it is necessary to ensure that the outlet of the evaporator is in a single-phase liquid state, and then the flow rate is reduced until a relatively complete pressure drop-flow rate "N-shaped curve" is tested, and it is necessary to ensure that there are at least 3 test working condition points in the negative slope region of the pressure drop with respect to the flow rate during the test.

[0076] It should be noted that there are some tags in the original text like and

[0075] which seem to be incomplete or have some issues in the context. I've translated the text as accurately as possible based on the overall content.Step 2: Average the pressure drop data corresponding to each flow rate to obtain the steady-state pressure drop data.

[0077] In step 2, it is important to note that after adjusting the flow rate, it is necessary to exclude data that fluctuates due to pressure drop caused by system response. For example, wait for the pressure drop data fluctuation to decrease until it stabilizes within a certain range, and then take the average pressure drop data over a period of time.

[0078] Step 3: Eliminate abnormal points and take the extreme value of the pressure drop data corresponding to each flow rate to obtain the dynamic pressure drop oscillation amplitude data.

[0079] Similar to step 2, once the pressure drop data stabilizes within a certain range, take the maximum and minimum values ​​of the pressure drop oscillation data over a period of time and subtract them to obtain the oscillation amplitude. If the pressure drop of some data points is significantly larger or smaller than that of other data points, with a difference exceeding 5%, they can be considered outliers and excluded.

[0080] Step 4: Perform function fitting on the steady-state pressure drop data to obtain a steady-state pressure drop function, and calculate the minimum point of the steady-state pressure drop function.

[0081] Step 5: Fit the dynamic voltage drop oscillation amplitude data to obtain the dynamic voltage drop oscillation amplitude function.

[0082] Step 6: Calculate and determine the flow drift instability interval based on the steady-state pressure drop function, the minimum point coordinates, and the dynamic pressure drop oscillation amplitude function.

[0083] Steps 4, 5, and 6 can be solved by function fitting and calculation using a computer program. The calculation program is:

[0084] (1) After starting the calculation, take the flow rate as the independent variable x, the pressure drop as the dependent variable y1, and the pressure drop oscillation amplitude as the dependent variable y2;

[0085] (2) Arrange the data in ascending order of x, and there should be no less than 3 data in the negative slope region (including the endpoint) of the pressure drop with respect to the flow rate. If there are less than 3, the subsequent function fitting may fail or the accuracy may decrease;

[0086] (3) For the dependent variable y1, extract the coordinate x_peak of the maximum point in the negative slope region of y1 with respect to x, and retain the data points with x ≥ x_peak for subsequent function fitting. The remaining data points have little effect on the determination of the unstable interval;

[0087] (4) For the dependent variable y1, the data is fitted using the check function f(x) = ax + b / x + c, where a, b, and c are constants determined by the fitting;

[0088] (5) For the dependent variable y1, calculate the coordinates x_valley and y_valley of the minimum point corresponding to the zero derivative of the check function;

[0089] (6) For the dependent variable y2, the data points with x ≥ x_peak are retained for subsequent function fitting, and the remaining data points have little effect on the determination of the unstable interval;

[0090] (7) For the dependent variable y2, a quartic polynomial is used to fit the data to obtain the function g(x). The specific form of the quartic polynomial is y = d*x^4 + e*x^3 + f*x^2 + g*x + h, where d, e, f, g, and h are constants determined by fitting;

[0091] (8) Based on the functions f(x) and g(x) fitted in steps 4 and 7, take the function h(x) = f(x) - g(x) - y_valley and calculate the maximum value x_uns of the solution of the function h(x) within the data range of x;

[0092] The function h(x) = 0 means that at this flow rate x, the pressure drop curve may enter the negative slope region to the left of the minimum point of the N-type curve due to the superposition of oscillations, thereby inducing flow drift. Therefore, it is necessary to determine the maximum flow rate that can induce flow drift. The flow rate above this value is the range of stable operation.

[0093] (9) Output the flow rate drift instability range of the evaporator at the heating power: flow rate < x_uns.

[0094] In an optional implementation, based on the above embodiment, this embodiment further provides a process for determining the flow drift instability interval of the serpentine flow channel 4 evaporator to illustrate the implementation details of the present application.

[0095] A serpentine flow channel 4 evaporator structure used in the actual test is as follows Figure 3 As shown, the evaporator comprises a three-layer structure consisting of an aluminum alloy cover plate 1, a transparent PC plate 2, and an aluminum alloy flow channel plate 3. The aluminum alloy flow channel plate 3 is machined with a serpentine flow channel 4 with a width of 5 mm and a depth of 5 mm. Extending from the flow channel are a liquid inlet pipe 5 and a liquid outlet pipe 6.

[0096] The above-mentioned serpentine flow channel 4 evaporator was connected to the test system, and the loop working fluid was selected as HFE-7000. The saturation temperature in the liquid reservoir was controlled at 40°C, and the inlet temperature was controlled at 25°C. The flow characteristic data of the evaporator were obtained under the conditions of heating power of 50W and 100W. Among them, the actual measured steady-state pressure drop data of the evaporator is as follows Figure 4 As shown, the dynamic voltage drop oscillation amplitude data is as follows Figure 5 As shown. Figure 5It can be seen that the change trend of the pressure drop with respect to the flow rate in the steady-state pressure drop data of the evaporator is N-shaped, that is, as the flow rate increases, the pressure drop increases first, decreases in the middle, and then increases again. Figure 5 It can be seen that the oscillation amplitude of the pressure drop of the evaporator shows a trend of first increasing and then decreasing with the increase of flow rate.

[0097] The steady-state pressure drop data of the evaporator under 50W and 100W heating powers are fitted, and the obtained check function fitting results are as follows: Figure 6 The figure also shows the turning point, (x_valley, y_valley). In the range x > x_valley, the tick function fit results are consistent with the measured data trend and have high accuracy.

[0098] The evaporator pressure drop oscillation amplitude data under 50W and 100W heating power were fitted, and the obtained quartic function fitting results were as follows: Figure 7 In the range of x>x_valley, the quartic function fitting results are consistent with the measured data trend and have high accuracy.

[0099] Under a heating power of 50W, the flow rate drift unstable range of the serpentine flow channel 4 evaporator is flow rate <119.8mL / min; similarly, under a heating power of 100W, the flow rate drift unstable range of the serpentine flow channel 4 evaporator is flow rate <221.5mL / min.

[0100] The comparison between the flow rate drift interval determined in this application and the measured flow rate drift data is as follows: Figure 8 As shown in the figure, it can be seen that at a heating power of 50W, the evaporator has flow rate drift when the flow rate is slightly less than 120mL / min, that is, the flow rate difference between the two evaporators increases significantly; at a heating power of 100W, the evaporator has flow rate drift when the flow rate is between 220mL / min and 230mL / min. Figure 8 The dotted line in the figure is the upper limit of the flow drift unstable interval determined by the method of this application. It can be seen that the flow drift unstable interval determined by this application is basically consistent with the interval where flow drift occurs in actual tests, with high accuracy, which can provide guidance for engineering applications.

[0101] Figure 9 A schematic diagram of the structure of a device for determining an unstable range of flow drift of parallel evaporators provided in an embodiment of the present application is shown, the device comprising:

[0102] A first testing module is configured to connect any target evaporator in the parallel evaporators to the testing system, and test the target evaporator using a first testing method based on first flow characteristic data to obtain a first unstable interval;

[0103] an adjustment module, configured to verify the first unstable interval, and if the first unstable interval does not meet a preset accuracy requirement, adjust the first flow characteristic data in the first test method to obtain adjusted second flow characteristic data;

[0104] The second testing module is configured to test the target evaporator using a second testing method based on the second flow characteristic data to obtain a second unstable interval.

[0105] The first flow characteristic data includes pressure drop data, and the first testing method based on the first flow characteristic data is used to test the target evaporator to obtain a first unstable interval, including:

[0106] Under a preset first heating power, according to a preset first adjustment method, the flow rate entering the target evaporator is adjusted to obtain pressure drop data corresponding to different flow rates;

[0107] Fitting the pressure drop data based on a first fitting algorithm to obtain a first fitting function;

[0108] The first unstable interval is determined according to the extreme value points in the first fitting function.

[0109] The step of fitting the pressure drop data based on a first fitting algorithm to obtain a first fitting function includes:

[0110] Fitting the pressure drop data using a check mark function to obtain a first fitting function;

[0111] The determining the first unstable interval according to the extreme value points in the first fitting function includes:

[0112] The first unstable interval is determined according to the target flow data corresponding to the minimum point in the first fitting function.

[0113] The first unstable interval is verified by the following method:

[0114] Acquiring application data of the target evaporator in an application scenario;

[0115] The first unstable interval is verified based on whether abnormal data in the application data appears outside the first unstable interval.

[0116] The second flow characteristic data includes: pressure drop data and pressure drop amplitude data; and the second unstable interval is obtained by testing the target evaporator using a second testing method based on the second flow characteristic data, including:

[0117] Under a preset second heating power, according to a preset second adjustment method, the flow rate entering the target evaporator is adjusted to obtain pressure drop data and pressure drop amplitude data corresponding to different flow rates;

[0118] Fitting the pressure drop data based on a first fitting algorithm to obtain a first fitting function;

[0119] Fitting the pressure drop amplitude data based on a second fitting algorithm to obtain a second fitting function;

[0120] The second unstable interval is determined according to the first fitting function and the second fitting function.

[0121] The step of fitting the voltage drop amplitude data based on a second fitting algorithm to obtain a second fitting function includes:

[0122] The voltage drop amplitude data is fitted based on a quartic polynomial to obtain a second fitting function.

[0123] The determining the second unstable interval according to the first fitting function and the second fitting function includes:

[0124] constructing an unstable function based on the target pressure drop data corresponding to the minimum point in the first fitting function, the first fitting function, and the second fitting function;

[0125] An extreme value solution is performed on the unstable function to determine the second unstable interval.

[0126] like Figure 10 As shown, an embodiment of the present application provides an electronic device for executing the method for determining the unstable interval of flow drift of parallel evaporators in the present application. The device includes a memory, a processor, a bus, and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method for determining the unstable interval of flow drift of parallel evaporators when executing the computer program.

[0127] Specifically, the memory and processor may be general-purpose memory and processor, which are not specifically limited here. When the processor runs the computer program stored in the memory, the method for determining the unstable interval of flow drift of the parallel evaporators can be executed.

[0128] Corresponding to the method for determining the unstable interval of the flow drift of the parallel evaporator in the present application, an embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run by the processor, the steps of the method for determining the unstable interval of the flow drift of the parallel evaporator are executed.

[0129] Specifically, the storage medium can be a general storage medium, such as a mobile disk, a hard disk, etc. When the computer program on the storage medium is run, the above-mentioned method for determining the unstable interval of flow rate drift of the parallel evaporators can be executed.

[0130] In the embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. The system embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interface, indirect coupling or communication connection of the system or unit, which can be electrical, mechanical or other forms.

[0131] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, and may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment as needed.

[0132] In addition, each functional unit in the embodiments provided in the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0133] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0134] It should be noted that similar numbers and letters represent similar items in the following figures. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. In addition, the terms "first", "second", "third", etc. are only used to distinguish the description and are not to be understood as indicating or implying relative importance.

[0135] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The scope of protection of the present application is not limited thereto. Although the present application has been described in detail with reference to the above-described embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-described embodiments within the technical scope disclosed in the present application, or perform equivalent replacements for some of the technical features thereof. However, these modifications, changes, or replacements do not deviate from the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application. They should all be included in the scope of protection of the present application. Therefore, the scope of protection of the present application shall be subject to the scope of protection of the claims.

Claims

1. A method for determining the unstable range of flow drift of parallel evaporators, characterized in that: The method comprises: Connecting any target evaporator in the parallel evaporators to the test system, and testing the target evaporator using a first test method based on first flow characteristic data to obtain a first unstable interval; Verifying the first unstable interval, and if the first unstable interval does not meet a preset accuracy requirement, adjusting the first flow characteristic data in the first test method to obtain adjusted second flow characteristic data; The target evaporator is tested using a second testing method based on the second flow characteristic data to obtain a second unstable interval.

2. The method according to claim 1, characterized in that The first flow characteristic data includes pressure drop data, and the first testing method based on the first flow characteristic data is used to test the target evaporator to obtain a first unstable interval, including: Under a preset first heating power, according to a preset first adjustment method, the flow rate entering the target evaporator is adjusted to obtain pressure drop data corresponding to different flow rates; Fitting the pressure drop data based on a first fitting algorithm to obtain a first fitting function; The first unstable interval is determined according to the extreme value points in the first fitting function.

3. The method according to claim 2, characterized in that The step of fitting the pressure drop data based on a first fitting algorithm to obtain a first fitting function includes: Fitting the pressure drop data using a check mark function to obtain a first fitting function; The determining the first unstable interval according to the extreme value points in the first fitting function includes: The first unstable interval is determined according to the target flow data corresponding to the minimum point in the first fitting function.

4. The method according to claim 1, wherein The method verifies the first unstable interval by the following method: Acquiring application data of the target evaporator in an application scenario; The first unstable interval is verified based on whether abnormal data in the application data appears outside the first unstable interval.

5. The method according to claim 1, wherein The second flow characteristic data includes: pressure drop data and pressure drop amplitude data; and the second unstable interval is obtained by testing the target evaporator using a second testing method based on the second flow characteristic data, including: Under a preset second heating power, according to a preset second adjustment method, the flow rate entering the target evaporator is adjusted to obtain pressure drop data and pressure drop amplitude data corresponding to different flow rates; Fitting the pressure drop data based on a first fitting algorithm to obtain a first fitting function; Fitting the pressure drop amplitude data based on a second fitting algorithm to obtain a second fitting function; The second unstable interval is determined according to the first fitting function and the second fitting function.

6. The method according to claim 5, characterized in that The step of fitting the voltage drop amplitude data based on a second fitting algorithm to obtain a second fitting function includes: The voltage drop amplitude data is fitted based on a quartic polynomial to obtain a second fitting function.

7. The method according to claim 5, characterized in that The determining the second unstable interval according to the first fitting function and the second fitting function includes: constructing an unstable function based on target pressure drop data corresponding to the minimum point in the first fitting function, the first fitting function, and the second fitting function; An extreme value solution is performed on the unstable function to determine the second unstable interval.

8. A device for determining the unstable range of flow drift of parallel evaporators, characterized in that: The device comprises: A first testing module is configured to connect any target evaporator in the parallel evaporators to the testing system, and test the target evaporator using a first testing method based on first flow characteristic data to obtain a first unstable interval; an adjustment module, configured to verify the first unstable interval, and if the first unstable interval does not meet a preset accuracy requirement, adjust the first flow characteristic data in the first test method to obtain adjusted second flow characteristic data; The second testing module is configured to test the target evaporator using a second testing method based on the second flow characteristic data to obtain a second unstable interval.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor and the memory communicate via the bus. When the machine-readable instructions are executed by the processor, the steps of the method for determining the unstable interval of flow drift of parallel evaporators as described in any one of claims 1 to 7 are performed.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, executes the steps of the method for determining the unstable interval of flow rate drift of parallel evaporators according to any one of claims 1 to 7.

Images