Cooling liquid flow matching method and system and application thereof

Abstract

The invention provides a cooling liquid flow matching method and system and application thereof, and the method comprises the steps: building a double-parameterization model which comprises a heat transfer correlation model between the cooling liquid flow and a heat transfer coefficient, and a flow resistance model between the cooling liquid flow and pressure drop; determining a numerical value interval of a heat transfer coefficient and a numerical value interval of pressure drop in a preset working interval of the cooling liquid flow, and calibrating parameters of a heat transfer correlation model and parameters of a flow resistance model by utilizing multiple groups of cooling liquid flow values, corresponding heat transfer coefficient values and corresponding pressure drop values; and based on the calibrated heat transfer correlation model, the calibrated flow resistance model and the coupling relation between the heat transfer coefficient and the pressure drop, the optimal matching value of the cooling liquid flow is determined. The method solves the problem that in the prior art, due to the fact that test design only covers discrete flow points of a local high heat exchange area, it is difficult to directly fit quantitative rules of cooling liquid flow, heat exchange power and pressure drop, and optimal flow point positioning fails.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of battery thermal management of new energy vehicles, and particularly relates to a coolant flow matching method and system and application thereof. BACKGROUND

[0002] In the battery cooling system of a new energy passenger vehicle, coolant flow is a key factor determining the heat exchange power and pressure drop of the battery. When the refrigerant valve front pressure, valve front subcooling degree, outlet pressure, outlet superheating degree and coolant inlet temperature are maintained constant, the system presents a forced heat balance characteristic: an increase in coolant flow promotes the increase in coolant side heat exchange power, and in order to maintain heat balance, the refrigerant flow needs to be increased, thereby increasing the refrigerant side heat exchange power; under the condition of a fixed inlet pipe diameter, an increase in refrigerant flow will inevitably lead to an increase in flow rate and cause a significant increase in pressure drop.

[0003] It should be emphasized that the above changes have a strict nonlinear critical effect: within a reasonable range, the increase in coolant flow can simultaneously increase the refrigerant heat exchange power and pressure drop; but if it enters an excessive range, the heat exchange power increase will be inhibited and gradually stabilized due to the attenuation effect of the coolant-refrigerant temperature difference, and the growth rate of the frictional pressure drop of the two-phase flow will be sharply slowed down. This nonlinear mechanism reveals the core contradiction that when the coolant flow changes, the refrigerant heat transfer coefficient and the pressure drop present a non-synergistic evolution law, so the essence of flow matching is the trade-off optimization of heat transfer performance improvement and flow resistance cost increase. Limited by the power of the electronic water pump and the flow resistance, the working range of the coolant flow is generally constrained to 0-40 L / min; and the existing method has multiple defects due to the neglect of this contradiction: first, since the test design only covers discrete flow points in the local high heat exchange area, it is difficult to directly fit the quantitative law of coolant flow and heat exchange power and pressure drop, resulting in the failure of positioning the optimal flow point; second, when blindly increasing the flow, the water pump power consumption increases far more than the heat exchange benefit.

[0004] Therefore, it is necessary to improve the existing coolant flow matching scheme to solve the above technical problems. SUMMARY

[0005] The present application aims to provide a coolant flow matching method, system and application thereof to solve the problem that the existing technology fails to directly fit the quantitative law of coolant flow and heat exchange power and pressure drop due to the test design only covering discrete flow points in the local high heat exchange area, resulting in the failure of positioning the optimal flow point.

[0006] At the same time, the present application can achieve an optimized balance between energy consumption and heat transfer through a precise flow matching model to solve the defect that the water pump power consumption increases far more than the heat exchange benefit when the flow is blindly increased.

[0007] To achieve the above-mentioned purpose, in a first aspect, a coolant flow matching method is provided, which comprises: establish a double parameterization model, the double parameterization model includes a heat transfer correlation model between the cooling liquid flow and the heat transfer coefficient, a flow resistance model between the cooling liquid flow and the pressure drop; determine the numerical interval of the heat transfer coefficient and the numerical interval of the pressure drop in the preset working interval of the cooling liquid flow, so as to calibrate the parameters of the heat transfer correlation model and the parameters of the flow resistance model by using multiple groups of cooling liquid flow values, corresponding heat transfer coefficient values and corresponding pressure drop values; Based on the calibrated heat transfer correlation model, the calibrated flow resistance model and the coupling relationship between the heat transfer coefficient and the pressure drop, the optimal matching value of the cooling liquid flow is determined.

[0008] As a further improvement of the application, the numerical interval of the heat transfer coefficient and the numerical interval of the pressure drop in the preset working interval of the cooling liquid flow are determined, including: select multiple flow points in the preset working interval to measure the corresponding heat transfer power and pressure drop of each flow point; determine the heat transfer coefficient corresponding to each flow point based on the heat transfer power, so as to determine the numerical interval of the heat transfer coefficient based on the heat transfer coefficient of each flow point, and determine the numerical interval of the pressure drop based on the pressure drop of each flow point.

[0009] As a further improvement of the application, the parameters of the heat transfer correlation model and the parameters of the flow resistance model are calibrated by using multiple groups of cooling liquid flow values, corresponding heat transfer coefficient values and corresponding pressure drop values, including: Substitute the heat transfer coefficient values corresponding to different flow points into the heat transfer correlation model to obtain the parameter values of the heat transfer correlation model; Substitute the pressure drop values corresponding to different flow points into the flow resistance model to obtain the parameter values of the flow resistance model.

[0010] As a further improvement of the application, the heat transfer correlation model is: , wherein, h ( m ) represents the heat transfer coefficient corresponding to different cooling flow, m represents the cooling liquid flow, a represents the maximum heat transfer coefficient to be calibrated, b represents the heat transfer sensitivity coefficient to be calibrated.

[0011] As a further improvement of the application, the flow resistance model is: , wherein, △p( m ) represents the pressure drop corresponding to different cooling liquid flow, cIndicates the secondary resistance coefficient to be calibrated, d Indicates the secondary correction coefficient to be calibrated, g Indicates the linear resistance coefficient to be calibrated.

[0012] As a further improvement of the present invention, determining the optimal matching value of the coolant flow rate based on the calibrated heat transfer correlation model, the calibrated flow resistance model, and the coupling relationship between the heat transfer coefficient and the pressure drop includes: The optimal matching value of the coolant flow rate is determined by simultaneously solving the calibrated heat transfer correlation model, the calibrated flow resistance model, and the coupling relationship, wherein: The coupling relationship between the heat transfer coefficient and the pressure drop is: , in, h 0 represents the base heat transfer coefficient, Indicates the reference voltage drop, f ( m ) The corresponding coolant flow rate at maximum m As the optimal matching flow.

[0013] In a second aspect, a coolant flow matching system is provided, comprising: A model building unit, configured to build a dual-parameter model, wherein the dual-parameter model includes a heat transfer correlation model between coolant flow rate and heat transfer coefficient, and a flow resistance model between coolant flow rate and pressure drop; a data processing unit, configured to determine a numerical range of the heat transfer coefficient and a numerical range of the pressure drop within a preset operating range of the coolant flow rate, so as to calibrate parameters of the heat transfer correlation model and parameters of the flow resistance model using multiple sets of coolant flow rate values, corresponding heat transfer coefficient values, and corresponding pressure drop values; The flow matching unit is used to determine the optimal matching value of the coolant flow rate according to the calibrated heat transfer correlation model, the calibrated flow resistance model and the coupling relationship between the heat transfer coefficient and the pressure drop.

[0014] In a third aspect, a coolant flow matching method is provided for use in new energy vehicles for achieving thermal balance in the collaborative cooling system of the vehicle power battery pack and the drive motor. The coolant flow matching method for the battery cooler is performed based on the method described in the first aspect.

[0015] In a fourth aspect, a battery cooler for a new energy vehicle is provided, wherein a coolant flow matching method for the battery cooler is performed based on the steps described in the first aspect.

[0016] In a fifth aspect, a terminal device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, which, when executed by the processor, implements the steps of the method according to the first aspect.

[0017] In a sixth aspect, a computer-readable storage medium is provided, which stores a computer program, which, when executed by a processor, implements the steps of the method according to the first aspect.

[0018] The present application has the following beneficial effects: The cooling liquid flow matching method of the present application can precisely locate the optimal cooling liquid flow matching value by constructing a double-parameterized model (a heat transfer correlation model and a flow resistance model) and jointly calibrating the parameters of the two models in a preset working range, and finally combining the calibrated double-parameterized model, the heat transfer coefficient, and the coupling decision function of the pressure drop. In this way, the present application can not only fit the quantitative law of the cooling liquid flow, the heat transfer power, and the pressure drop through the double-parameterized model established in the preset working range of the cooling liquid flow, so as to locate the optimal flow point of the cooling liquid, but also realize the optimal balance of energy consumption and heat transfer through the precise flow matching model, and solve the problem of high test cost of the existing cooling liquid flow matching method. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 A schematic flow chart of the cooling liquid flow matching method of an embodiment of the present application; Figure 2 A schematic flow chart of the cooling liquid flow matching method of another embodiment of the present application; Figure 3 A schematic flow chart of the cooling liquid flow matching method of another embodiment of the present application; Figure 4 A schematic diagram of the relationship between the heat transfer coefficient and the cooling liquid flow; Figure 5 A schematic diagram of the relationship between the pressure drop and the cooling liquid flow; Figure 6 A structural block diagram of the cooling liquid flow matching system of an embodiment of the present application; Figure 7 A schematic structural block diagram of the device for cooling liquid flow matching of a battery cooler of an embodiment of the present application; Figure 8 A topology structure diagram of a computer-readable storage medium disclosed by the present application. DETAILED DESCRIPTION

[0020] The present invention is described in detail below with reference to the various embodiments shown in the accompanying drawings, but it should be noted that these embodiments are not limitations of the present invention, and any equivalent transformations or substitutions in functions, methods, or structures made by ordinary technicians in this field based on these embodiments are all within the scope of protection of the present invention.

[0021] The technical solutions provided by various embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0022] Example 1: like Figure 1 As shown, this embodiment provides a coolant flow matching method to solve the problem in the prior art that the experimental design only covers discrete flow points in a local high heat exchange area, making it difficult to directly fit the quantitative law of coolant flow, heat exchange power, and pressure drop, resulting in failure to locate the optimal flow point. The method includes: Step 101: Establish a dual-parameter model. The dual-parameter model includes a heat transfer correlation model between coolant flow rate and heat transfer coefficient, and a flow resistance model between coolant flow rate and pressure drop.

[0023] It should be understood that the coolant flow rate of the battery cooler has different functional relationships with the heat transfer coefficient and pressure drop, and each functional relationship has its own parameters to be calibrated. The heat transfer correlation model and flow resistance model of the corresponding vehicle model are determined based on the calibrated parameters. The heat transfer correlation model is shown in Formula 1: , (Formula 1), in, h ( m ) represents the heat transfer coefficient corresponding to different cooling flow rates, m Indicates the coolant flow rate, unit L / min ，a represents the maximum heat transfer coefficient to be calibrated, b Indicates the heat transfer sensitivity coefficient to be calibrated.

[0024] The flow resistance model is shown in Formula 2: , (Formula 2), Among them, △p( m ) represents the pressure drop corresponding to different coolant flow rates, c Indicates the secondary resistance coefficient to be calibrated, d Indicates the secondary correction coefficient to be calibrated, g Indicates the linear resistance coefficient to be calibrated.

[0025] Step 102: Determine a numerical range of the heat transfer coefficient and a numerical range of the pressure drop within a preset operating range of the coolant flow rate, and calibrate parameters of the heat transfer correlation model and parameters of the flow resistance model using multiple sets of coolant flow rate values, corresponding heat transfer coefficient values, and corresponding pressure drop values.

[0026] In this embodiment, based on the actual operating range of the battery cooler coolant, a coolant flow point for testing is selected within the range of better heat exchange performance, and the heat exchange power and pressure drop are tested based on the selected coolant flow point. Specifically, the operating range of the battery coolant flow in this embodiment is 0-40L / min, and the heat exchange performance is better in the range of 5-24L / min. It should be noted that the coolant flow operating range of the battery cooler may be different for different models. This embodiment only takes the operating range of the coolant flow of a certain model as an example to illustrate the principle of coolant flow matching. The specific values ​​are not limited to the range defined in this embodiment.

[0027] like Figure 2 As shown, the specific operations of “determining the numerical range of the heat transfer coefficient and the numerical range of the pressure drop within the preset working range of the coolant flow rate” include: Step 201: Select multiple flow points within a preset working range to measure the heat exchange power and pressure drop corresponding to each flow point.

[0028] Under the premise of maintaining constant test parameters such as the refrigerant valve pressure and temperature, outlet pressure and temperature, and coolant inlet temperature, the battery cooler coolant flow rate was tested at evenly spaced flow rates within the flow range with optimal heat exchange performance. In this example, 5, 10, 15, and 20 L / min were selected as coolant flow rates for testing, and each flow rate was measured at least three times. The test results are shown in Table 1.

[0029] Table 1 Average values ​​of heat transfer power and pressure drop at different coolant flow rates: Coolant flow (L / min) 5 10 15 20 Heat exchange power (W) 6210.2 9542.1 11355.1 12577.3 Pressure drop (kPa) -32.6 -71.7 -96.3 -117.3

[0030] Step 202: Determine the heat transfer coefficient corresponding to each flow point based on the heat exchange power, determine the value range of the heat transfer coefficient based on the heat transfer coefficient at each flow point, and determine the value range of the pressure drop based on the pressure drop at each flow point.

[0031] As shown in Table 1, according to the results of the refrigerant heat exchange power corresponding to different coolant flow rates, the heat transfer coefficients of the refrigerants under different coolant flow rates can be calculated to be 3118, 4408, 5060, and 5653 W / (m 2• C), so the numerical interval of the heat transfer coefficient can be determined as [3118, 5653]. Similarly, according to the test results in Table 1, the numerical interval of the pressure drop can be determined as [-117.3, -32.6]. It should be noted that different heat transfer coefficients and pressure drops can be obtained by selecting different flow points in the preset working interval, but they should be located in the heat transfer coefficient numerical interval and the pressure drop numerical interval corresponding to the two end point values of the preset working interval. By limiting the numerical interval of the heat transfer coefficient and the numerical interval of the pressure drop, it is convenient to calculate the parameters of the heat transfer correlation model and the flow resistance model in the subsequent steps without being limited to the several test points defined in the embodiment.

[0032] As shown in FIG. 2, the specific method of step 102 "calibrating the parameters of the heat transfer correlation model and the parameters of the flow resistance model by using multiple sets of coolant flow values, corresponding heat transfer coefficient values, and corresponding pressure drop values" includes: Figure 3 Step 301. Substituting the heat transfer coefficient values corresponding to different flow points into the heat transfer correlation model to obtain the parameter values of the heat transfer correlation model.

[0033] Since the numerical interval of the heat transfer coefficient obtained in step 202 is [3118, 5653], it has 4 point values, that is, the number of heat transfer coefficients (4) is greater than the number of parameters to be calibrated (i.e., the maximum heat transfer coefficient to be calibrated a and the heat transfer sensitivity coefficient to be calibrated b ), so the heat transfer coefficients under different coolant flow rates are combined in pairs, a total of 6 groups, substituted into formula 1, solved respectively, and then arithmetically averaged to obtain the to-be-determined coefficient: a = 5706.2, b = -0.1447, so the calibrated heat transfer correlation model is shown in formula 3: , (formula 3), Accordingly, the relationship between the coolant flow rate and the heat transfer coefficient is fitted according to formula 3, as shown in FIG. 3, the heat transfer coefficient increases with the increase of the coolant flow rate. Figure 4

[0034] Step 302. Substituting the pressure drop values corresponding to different flow points into the flow resistance model to obtain the parameter values of the flow resistance model.

[0035] Similarly, since the number of pressure drop test results in Table 1 (4) is greater than the number of parameters to be calibrated (the quadratic resistance coefficient to be calibrated c , the quadratic correction coefficient to be calibrated d , and the linear resistance coefficient to be calibrated g ), so the pressure drops under different coolant flow rates are combined in three groups, a total of ​​=4 groups, substituting into formula 2, respectively solving and then performing arithmetic average, c=1.1385, d=0.01346, g=2.26 can be obtained, that is, the function relationship of the coolant flow and the pressure drop in the embodiment is shown in formula 4: , (formula 4), In this way, the relationship between the coolant flow and the heat transfer coefficient is fitted according to formula 4, as shown in formula 4, the pressure drop decreases with the increase of the coolant flow. Figure 5

[0036] Step 103. Determine the optimal matching value of the coolant flow based on the calibrated heat transfer correlation model, the calibrated flow resistance model and the coupling relationship between the heat transfer coefficient and the pressure drop. The coupling relationship between the heat transfer coefficient and the pressure drop is: , (formula 5), Wherein, h 0 represents the reference heat transfer coefficient, and the reference pressure drop. In the embodiment, the reference heat transfer coefficient h 0 is the heat transfer coefficient under the coolant flow of 5L / min, and the reference pressure drop is the pressure drop under the coolant flow of 5L / min.

[0037] Since the influence of the coolant flow on the heat transfer coefficient and the pressure drop is opposite, it is necessary to perform collaborative matching, that is, both a larger heat transfer coefficient and a smaller pressure drop under the optimal flow matching value to be determined are ensured, and generally the maximum ratio of the heat transfer coefficient to the pressure drop or the minimum ratio of the pressure drop to the heat transfer coefficient is determined as the condition to establish the coupling relationship between the heat transfer coefficient and the pressure drop.

[0038] In the embodiment, the ratio of the heat transfer coefficient to the pressure drop f is used as an evaluation index, and the coolant flow f when the ratio is the maximum value is the optimal matching flow. The specific operation process is as follows: m (1) Calculate the derivative of ( f ) to m , denoted as m ′( f ); m (2) Set the derivative equal to zero and solve: solve the equation ′( f )=0, and the value of m is obtained. At this time, the value of m is the optimal matching flow. m

[0039] In this way, the battery cooler flow m is 18.21L / min​​f The maximum value is 1.132, and the refrigerant heat exchange power is 5296.95 W, and the pressure drop is 110.26 kPa, that is, in this embodiment, the best cooling liquid flow rate is 18.2 L / min, which can ensure that there is a larger heat transfer coefficient under the optimal flow rate matching value, and the pressure drop is also smaller, so as to accurately realize the optimization balance of energy consumption and heat transfer.

[0040] Therefore, the cooling liquid flow rate matching method of the embodiment can accurately locate the optimal cooling liquid flow rate matching value by constructing a double-parameterized model (a heat transfer correlation model and a flow resistance model) and jointly calibrating the parameters of the two models in the preset working interval, and finally combining the calibrated double-parameterized model, the heat transfer coefficient and the coupling decision function of the pressure drop. In this way, the embodiment can not only fit the relationship between the cooling liquid flow rate and the heat exchange power and the pressure drop based on the double-parameterized model established in the preset working interval of the cooling liquid flow rate, so as to obtain the optimal cooling liquid flow rate with the best comprehensive heat exchange performance, solve the defect that the existing matching scheme is insufficient to locate the optimal flow rate point of the cooling liquid, and accurately realize the optimization balance of energy consumption and heat transfer. At the same time, it can solve the problem of high test cost of the existing cooling liquid flow rate matching method.

[0041] It is worth noting that the "specific numerical value or numerical interval (working range of cooling liquid, numerical interval of heat transfer coefficient, numerical interval of pressure drop, etc.)" involved in the cooling liquid flow rate matching method described in the embodiment is only for the convenience of explaining the matching principle of the cooling liquid flow rate, and the specific value is not limited to the numerical value or range defined in the embodiment.

[0042] Embodiment 2: As shown in Figure 6 The embodiment also provides a cooling liquid flow rate matching system 600, which comprises: a model establishing unit 601, configured to establish a double-parameterized model, the double-parameterized model comprising a heat transfer correlation model 6011 between the cooling liquid flow rate and the heat transfer coefficient, and a flow resistance model 6012 between the cooling liquid flow rate and the pressure drop; a data processing unit 602, configured to determine a numerical interval of the heat transfer coefficient and a numerical interval of the pressure drop in a preset working interval of the cooling liquid flow rate, so as to calibrate the parameters of the heat transfer correlation model and the parameters of the flow resistance model by using multiple groups of cooling liquid flow rate values, corresponding heat transfer coefficient values and corresponding pressure drop values; and a flow rate matching unit 603, configured to determine the optimal matching value of the cooling liquid flow rate according to the calibrated heat transfer correlation model, the calibrated flow resistance model and the coupling relationship between the heat transfer coefficient and the pressure drop.

[0043] The data processing unit 602 includes a data measurement unit 6021 configured to select a plurality of flow points in a preset working range to measure a heat exchange power and a pressure drop corresponding to each flow point; and a data determination unit 6022 configured to determine a heat transfer coefficient corresponding to each flow point according to the heat exchange power, to determine a numerical range of the heat transfer coefficient based on the heat transfer coefficient of each flow point, and to determine a numerical range of the pressure drop based on the pressure drop of each flow point.

[0044] The cooling liquid flow matching system 600 of the embodiment constructs a double-parameterized model (a heat transfer correlation model and a flow resistance model) through the model establishment unit 601, and cooperatively calibrates parameters of the two models in a preset working range through the data processing unit 602. Finally, the flow matching unit 603 combines the calibrated double-parameterized model, the coupling decision function of the heat transfer coefficient and the pressure drop to accurately locate the optimal cooling liquid flow matching value. In this way, the system 600 of the embodiment can not only fit the relationship between the cooling liquid flow and the heat exchange power and the pressure drop based on the double-parameterized model established in the preset working range of the cooling liquid flow by the method of undetermined coefficients, but also obtain the optimal cooling liquid flow with the best comprehensive heat exchange performance, solve the defect that the existing matching scheme is insufficient to locate the optimal flow point of the cooling liquid, accurately realize the optimized balance between energy consumption and heat transfer, and solve the problem of high test cost of the existing cooling liquid flow matching method.

[0045] It should be noted that the technical solutions of the cooling liquid flow matching system 600 of the embodiment are the same as those of the same part in Embodiment 1. Please refer to Embodiment 1 for details, which will not be repeated here.

[0046] Embodiment 3 The embodiment provides an application of a cooling liquid flow matching method in a new energy vehicle to a vehicle power battery pack and a driving motor in a cooperative cooling system to realize thermal balance. The cooling liquid flow matching method of the battery cooler is based on the steps described in Embodiment 1 and can achieve the same technical effect. To avoid repetition, details will not be repeated here.

[0047] Embodiment 4 As Figure 7As shown, the embodiment provides an equipment 700 for matching the coolant flow of a battery cooler, which comprises: a refrigerant circulation system 701 for adjusting the temperature of the battery; a controller 702 for monitoring and adjusting the pressure and power of the battery cooler; and the matching system 600 as described in Embodiment Two. The equipment 700 of the embodiment fits the relationship between the coolant flow, heat exchange power and pressure drop through the double-parameterized model established by the matching system 600 within the preset working range of the coolant flow, so as to obtain the optimal coolant flow with the best comprehensive heat exchange performance, solve the defect that the existing matching scheme is not enough to locate the optimal flow point of the coolant, and also accurately realize the optimized balance between energy consumption and heat transfer, while solving the problem of high test cost of the existing coolant flow matching method.

[0048] Embodiment 5 The embodiment of the application also provides a terminal device, which can include a processor, a memory, a computer program stored on the memory and executable on the processor, and the computer program is executed by the processor to implement the above-mentioned Figures 1-3 The processes of the coolant flow matching method embodiment are shown, and the same technical effects can be achieved. To avoid repetition, they will not be described here.

[0049] Embodiment 6 In combination with Figure 8 As shown, the embodiment also discloses a specific implementation of a computer readable storage medium 800. The computer readable storage medium 800 can be wholly or partially configured in a computer, a server, a cluster server or a data center in a physical form.

[0050] In the embodiment, the computer readable storage medium 800 stores computer program instructions 801, and the computer program instructions 801 are read and executed by a processor 802 to perform the steps in the coolant flow matching method disclosed in Embodiment 1.

[0051] Optionally, the computer readable storage medium 800 can be configured as a server, and the server runs on a physical device that builds a private cloud, a hybrid cloud or a public cloud. Meanwhile, the computer readable storage medium 800 can also be configured as a random access memory (RAM), a read only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), etc.

[0052] The computer readable storage medium 800 is used to store a program, and the processor 802 executes the program after receiving an execution instruction to execute the cooling liquid flow matching method disclosed in Embodiment 1.

[0053] Meanwhile, the processor 802 disclosed in the embodiment can be an integrated circuit chip with a signal processing capability. The processor 802 can be a general processor, including a central processing unit (CPU), a network processor (NP), etc.; or can be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The general processor can be a microprocessor or can also be any conventional processor. The general processor can implement or execute the disclosed methods, steps and logic block diagrams in the embodiments of the present application.

[0054] The technical solution of the same part in the computer readable storage medium 800 disclosed in the embodiment and the embodiments 1 and / or 2 is described in the embodiments 1 and / or 2, which will not be described here.

[0055] The above series of detailed descriptions are only specific descriptions of the feasible implementation manners of the present application, and are not used to limit the protection scope of the present application. Any equivalent implementation manners or changes made without departing from the spirit of the present application should be included in the protection scope of the present application.

[0056] It will be apparent to those skilled in the art that the application is not limited to the details of the above-exemplified embodiments and that the present application can be implemented in other particular forms without departing from the spirit or essential characteristics of the present application. The presently disclosed embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. No feature of the application is to be construed as limiting the scope of the claims to its exact counterpart.

[0057] Furthermore, it should be understood that although the description is made on the basis of the embodiments, not every embodiment contains only one independent technical solution, and the description of the specification is only for the sake of clarity, and those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that those skilled in the art can understand.

Claims

1. A coolant flow matching method, characterized in that: The method comprises: Establishing a dual-parameter model, the dual-parameter model including a heat transfer correlation model between coolant flow rate and heat transfer coefficient, and a flow resistance model between coolant flow rate and pressure drop; Determining a numerical range of the heat transfer coefficient and a numerical range of the pressure drop within a preset working range of the coolant flow rate, so as to calibrate parameters of the heat transfer correlation model and parameters of the flow resistance model using multiple sets of coolant flow rate values, corresponding heat transfer coefficient values, and corresponding pressure drop values; An optimal matching value of the coolant flow rate is determined based on the calibrated heat transfer correlation model, the calibrated flow resistance model, and the coupling relationship between the heat transfer coefficient and the pressure drop.

2. The method according to claim 1, characterized in that Determining the numerical range of the heat transfer coefficient and the numerical range of the pressure drop within a preset working range of the coolant flow rate includes: Selecting multiple flow points within the preset working range to measure the heat exchange power and pressure drop corresponding to each flow point; The heat transfer coefficient corresponding to each flow point is determined based on the heat exchange power, the numerical range of the heat transfer coefficient is determined based on the heat transfer coefficient of each flow point, and the numerical range of the pressure drop is determined based on the pressure drop of each flow point.

3. The method according to claim 2, characterized in that Calibration of the parameters of the heat transfer correlation model and the parameters of the flow resistance model using multiple sets of coolant flow values, corresponding heat transfer coefficient values, and corresponding pressure drop values ​​includes: Substituting the heat transfer coefficient values ​​corresponding to different flow points into the heat transfer correlation model to obtain parameter values ​​of the heat transfer correlation model; The pressure drop values ​​corresponding to different flow points are substituted into the flow resistance model to obtain parameter values ​​of the flow resistance model.

4. The method according to any one of claims 1 to 3, characterized in that The heat transfer correlation model is: ， in, h ( m ) represents the heat transfer coefficient corresponding to different cooling flow rates, m Indicates the coolant flow rate, a represents the maximum heat transfer coefficient to be calibrated, b Indicates the heat transfer sensitivity coefficient to be calibrated.

5. The method according to claim 4, characterized in that The flow resistance model is: ， Among them, △p( m ) represents the pressure drop corresponding to different coolant flow rates, c Indicates the secondary resistance coefficient to be calibrated, d Indicates the secondary correction coefficient to be calibrated, g Indicates the linear resistance coefficient to be calibrated.

6. The method according to claim 5, characterized in that The coupling relationship between the heat transfer coefficient and the pressure drop is: ， in, h 0 represents the base heat transfer coefficient, △p0 represents the base pressure drop, and the coupling relationship f ( m ) The corresponding coolant flow rate at maximum m As the optimal matching flow.

7. A coolant flow matching system, characterized in that: The system comprises: A model building unit, configured to build a dual-parameter model, wherein the dual-parameter model includes a heat transfer correlation model between coolant flow rate and heat transfer coefficient, and a flow resistance model between coolant flow rate and pressure drop; a data processing unit, configured to determine a numerical range of the heat transfer coefficient and a numerical range of the pressure drop within a preset operating range of the coolant flow rate, so as to calibrate parameters of the heat transfer correlation model and parameters of the flow resistance model using multiple sets of coolant flow rate values, corresponding heat transfer coefficient values, and corresponding pressure drop values; The flow matching unit is used to determine the optimal matching value of the coolant flow rate according to the calibrated heat transfer correlation model, the calibrated flow resistance model and the coupling relationship between the heat transfer coefficient and the pressure drop.

8. A coolant flow matching method is used in a new energy vehicle to achieve thermal balance in the coordinated cooling system of the vehicle power battery pack and the drive motor, characterized in that: The coolant flow matching method for a battery cooler is performed based on the method according to any one of claims 1 to 6.

9. A terminal device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program implements the steps of the method according to claims 1 to 6 when executed by the processor.

10. A computer-readable storage medium storing a computer program, wherein the computer-readable storage medium is configured to implement the steps of the method according to any one of claims 1 to 6 when the computer program is executed by a processor.

Images