Thermal simulation analysis method, equipment and storage medium for liquid-cooled energy storage system

Abstract

The present invention discloses a thermal simulation analysis method, device, and storage medium for a liquid-cooled energy storage system, relating to the field of modeling and simulation technology, and is applied to liquid-cooled energy storage systems. The method includes: establishing a liquid-cooling plate simulation model based on preset battery cell data; establishing a battery cluster flow simulation model based on the liquid-cooling plate simulation model and preset battery cluster data; establishing a battery stack flow simulation model based on the battery cluster flow simulation model and preset battery stack data; calculating the flow distribution differences at multiple pipeline inlets in the liquid-cooled energy storage system based on the battery cluster flow simulation model and the battery stack flow simulation model; obtaining a temperature difference fitting curve based on the multiple flow distribution differences and the corresponding multiple maximum temperatures; and calculating the maximum temperature difference of the battery stack in the liquid-cooled energy storage system based on the temperature difference fitting curve. This simulation analysis method provides risk point assessment for early thermal management design, reducing system revision design and project development cycle time.

Description

Technical Field

[0001] The present invention relates to the field of modeling and simulation technology, and in particular to a thermal simulation analysis method, device, and storage medium for a liquid-cooled energy storage system. Background Art

[0002] Energy storage technology is a crucial component of smart grids and one of their supporting technologies. Numerous battery cells form battery modules, which in turn form battery clusters, which in turn form battery stacks, which ultimately form the entire liquid-cooled energy storage system. The battery cell is the fundamental unit of a liquid-cooled energy storage system. Temperature differences within a liquid-cooled energy storage system significantly impact system lifespan, SOH, and system balance. To minimize these temperature differences and extend system lifespan, the temperature differences between different cells within the system must be controlled within a reasonable range.

[0003] As liquid-cooled energy storage systems develop towards higher rates and higher energy densities, traditional air cooling is no longer sufficient to dissipate heat from the system's battery cells. High-efficiency liquid cooling is needed. Liquid cooling offers low power consumption, low noise, and excellent cell temperature uniformity. Given the high heat generation and high temperature uniformity requirements of battery cells, liquid cooling will gradually become widely used in the thermal management of liquid-cooled energy storage systems. Currently, thermal management risks for liquid-cooled energy storage systems remain largely in the testing phase. Since the system has already been finalized, there is little room for improvement, resulting in long temperature control testing cycles. Summary of the Invention

[0004] The present invention aims to address at least one of the technical problems existing in the prior art. To this end, the present invention proposes a thermal simulation analysis method, device, and storage medium for a liquid-cooled energy storage system. These methods provide risk assessment for early thermal management design, reducing system redesign and project development cycle time.

[0005] The thermal simulation analysis method for a liquid-cooled energy storage system according to the first embodiment of the present invention is applied to the liquid-cooled energy storage system. The simulation analysis method includes:

[0006] Establish a liquid cooling plate simulation model based on the preset battery cell data;

[0007] Establishing a battery cluster flow simulation model based on the liquid cooling plate simulation model and preset battery cluster data;

[0008] Establishing a battery stack flow simulation model according to the battery cluster flow simulation model and preset battery stack data;

[0009] Calculating flow distribution differences at multiple pipeline inlets in the liquid-cooled energy storage system based on the battery cluster flow simulation model and the battery stack flow simulation model;

[0010] Calculating, based on the liquid cooling plate simulation model, a plurality of maximum temperatures corresponding to the plurality of flow distribution differences;

[0011] Obtaining a temperature difference fitting curve according to the plurality of flow distribution differences and the corresponding plurality of maximum temperatures;

[0012] The maximum temperature difference of the battery stack in the liquid-cooled energy storage system is calculated based on the temperature difference fitting curve.

[0013] According to one or more technical solutions provided in the embodiments of the present invention, there are at least the following beneficial effects: the present invention establishes a liquid cooling plate simulation model based on preset battery cell data, establishes a battery cluster flow simulation model based on the liquid cooling plate simulation model and preset battery cluster data, and establishes a battery stack flow simulation model based on the battery cluster flow simulation model and preset battery stack data; calculates the flow distribution differences of multiple pipeline inlets in the liquid-cooled energy storage system based on the battery cluster flow simulation model and the battery stack flow simulation model; calculates multiple maximum temperatures corresponding to the multiple flow distribution differences; obtains a temperature difference fitting curve based on the multiple flow distribution differences and the corresponding multiple maximum temperatures; calculates the maximum temperature difference of the battery stack in the liquid-cooled energy storage system based on the temperature difference fitting curve; and evaluates whether the design of the liquid-cooled energy storage system meets the standards based on the maximum temperature difference of the battery stack in the liquid-cooled energy storage system. Through this setting, risk point assessment is provided for early thermal management design, reducing system revision design and project development cycle time, while improving the reliability of thermal management of the liquid-cooled energy storage system.

[0014] According to some embodiments of the present invention, the cell data includes cell heating parameters, cell distribution parameters, and cell demand parameters. Establishing a liquid cooling plate simulation model based on the preset cell data includes:

[0015] Obtaining a preliminary liquid cooling plate simulation model according to the battery cell heating parameters, the battery cell distribution parameters, and the battery cell demand parameters;

[0016] The liquid cooling plate simulation model is obtained by continuously optimizing the flow rate and the flow channel form of the preliminary liquid cooling plate simulation model until the preliminary liquid cooling plate simulation model meets the preset liquid cooling conditions.

[0017] According to some embodiments of the present invention, the liquid cooling condition includes at least one of the following:

[0018] The maximum simulated temperature of the battery module in the preliminary liquid cooling plate simulation model is less than or equal to the preset maximum temperature value of the battery module;

[0019] The maximum simulated temperature difference of the battery module in the preliminary liquid cooling plate simulation model is less than or equal to the preset maximum temperature difference value of the battery module;

[0020] The simulated pressure drop value of the liquid cooling plate inlet and outlet in the preliminary liquid cooling plate simulation model is less than the preset pressure drop value of the liquid cooling plate inlet and outlet;

[0021] In the preliminary liquid cooling plate simulation model, the simulated temperature difference between the inlet and outlet of the liquid cooling plate is less than or equal to the preset temperature difference between the inlet and outlet of the liquid cooling plate.

[0022] According to some embodiments of the present invention, the battery cluster data includes battery module distribution parameters and battery module demand parameters. A battery cluster flow simulation model is established based on the liquid cooling plate simulation model and preset battery cluster data, including:

[0023] According to the liquid cooling plate simulation model, obtaining a plurality of inlet and outlet pipe diameter data of the battery module;

[0024] Obtaining a preliminary battery cluster flow simulation model based on the battery module distribution parameters, the battery module demand parameters, and multiple battery module inlet and outlet pipe diameter data;

[0025] The battery cluster flow simulation model is obtained by continuously optimizing the flow tube size and flow tube type of the preliminary battery cluster flow simulation model until the preliminary battery cluster flow simulation model meets the preset battery cluster conditions.

[0026] According to some embodiments of the present invention, the battery cluster condition includes at least one of the following:

[0027] The simulated inlet flow distribution difference of each battery module in the preliminary battery cluster flow simulation model is less than or equal to the preset inlet flow distribution difference of each battery module;

[0028] The simulated pressure drop value of the battery cluster inlet and outlet in the preliminary battery cluster flow simulation model is less than the preset pressure drop value of the battery cluster inlet and outlet.

[0029] According to some embodiments of the present invention, the battery stack data includes battery cluster distribution parameters and battery cluster demand parameters. Establishing a battery stack flow simulation model based on the battery cluster flow simulation model and preset battery stack data includes:

[0030] According to the battery cluster flow simulation model, obtaining a plurality of inlet and outlet pipe diameter data of the battery cluster;

[0031] Obtaining a preliminary battery stack flow simulation model based on the battery cluster distribution parameters, the battery cluster demand parameters, and multiple battery cluster inlet and outlet pipe diameter data;

[0032] The battery stack flow simulation model is obtained by continuously optimizing the flow tube size and flow tube type of the preliminary battery stack flow simulation model until the preliminary battery stack flow simulation model meets the preset battery stack conditions.

[0033] According to some embodiments of the present invention, the battery stack condition includes at least one of the following:

[0034] The simulated inlet flow distribution difference of each battery cluster in the preliminary battery stack flow simulation model is less than or equal to the preset inlet flow distribution difference of each battery cluster;

[0035] The simulated pressure drop value at the inlet and outlet of the battery stack in the preliminary battery stack flow simulation model is less than the preset pressure drop value at the inlet and outlet of the battery stack.

[0036] According to some embodiments of the present invention, calculating the maximum temperature difference of the battery stack in the liquid-cooled energy storage system according to the temperature difference fitting curve includes:

[0037] Calculating a first difference value of inlet flow distribution between battery modules in each battery cluster in the liquid-cooled energy storage system according to the battery cluster flow simulation model;

[0038] calculating, based on the battery stack flow simulation model, a second difference value of the inlet flow distribution between the battery clusters in the battery stack;

[0039] Calculating a third difference value of inlet flow distribution between a plurality of battery modules in the battery stack based on the first difference value and the second difference value;

[0040] The maximum temperature difference corresponding to the third difference value is calculated based on the temperature difference fitting curve.

[0041] According to an embodiment of the second aspect of the present invention, a liquid-cooled energy storage system thermal simulation and analysis device includes: 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 liquid-cooled energy storage system thermal simulation and analysis method described in the first aspect above is implemented.

[0042] According to a computer-readable storage medium of an embodiment of the third aspect of the present invention, the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the thermal simulation analysis method of the liquid-cooled energy storage system as described in the first aspect above.

[0043] Additional aspects and advantages of the present invention will be set forth in part in the description which follows and, in part, will be obvious from the description which follows, or may be learned by practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings are used to provide a further understanding of the technical solution of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the technical solution of the present invention and do not constitute a limitation to the technical solution of the invention.

[0045] Figure 1 1 is a flow chart of a thermal simulation analysis method for a liquid-cooled energy storage system provided by an embodiment of the present invention;

[0046] Figure 2 1 is a flow chart of a thermal simulation analysis method for a liquid-cooled energy storage system provided by an embodiment of the present invention;

[0047] Figure 3 1 is a flow chart of a thermal simulation analysis method for a liquid-cooled energy storage system provided by an embodiment of the present invention;

[0048] Figure 4 This is a schematic diagram of the process of designing a liquid cooling plate simulation model provided by an embodiment of the present invention;

[0049] Figure 5 1 is a schematic structural diagram of a battery module provided by an embodiment of the present invention;

[0050] Figure 6 1 is a flow chart of a thermal simulation analysis method for a liquid-cooled energy storage system provided by an embodiment of the present invention;

[0051] Figure 7 1 is a flow chart of a thermal simulation analysis method for a liquid-cooled energy storage system provided by an embodiment of the present invention;

[0052] Figure 8 This is a schematic diagram of a flow chart for designing a battery cluster flow simulation model according to an embodiment of the present invention;

[0053] Figure 9 Schematic diagram of the structure of the battery cluster current collector provided by an embodiment of the present invention;

[0054] Figure 10 1 is a flow chart of a thermal simulation analysis method for a liquid-cooled energy storage system provided by an embodiment of the present invention;

[0055] Figure 11 Schematic diagram of the thermal simulation analysis method for a liquid-cooled energy storage system provided in an embodiment of the present invention.

[0056] Figure 12 This is a schematic diagram of a flow chart for designing a battery cluster flow simulation model according to an embodiment of the present invention;

[0057] Figure 13 Schematic diagram of the structure of the battery stack current collector provided by an embodiment of the present invention;

[0058] Figure 14 1 is a flow chart of a thermal simulation analysis method for a liquid-cooled energy storage system provided by an embodiment of the present invention;

[0059] Figure 15 Schematic diagram of the structure of the liquid-cooled energy storage system provided by an embodiment of the present invention;

[0060] Figure 16 Schematic diagram of a temperature difference fitting curve provided by an embodiment of the present invention.

[0061] Reference numerals:

[0062] Battery cell positive electrode 110 , battery cell negative electrode 120 , battery cell 130 , liquid cooling plate 140 , battery module external connector 150 , battery cluster branch pipe 160 , battery cluster collecting pipe 170 , battery stack collecting pipe 180 , battery cluster 190 . DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0064] It should be noted that although the device schematics illustrate functional module divisions and the flowcharts illustrate logical sequences, in certain circumstances, the steps shown or described may be performed in a sequence that differs from the module divisions in the device or the sequence in the flowcharts. The terms "first," "second," and so on, in the specification, claims, and drawings, are used to distinguish similar items and are not necessarily used to describe a specific sequence or precedence.

[0065] Energy storage technology is a crucial component of smart grids and one of their supporting technologies. Numerous battery cells form battery modules, which in turn form battery clusters, which in turn form battery stacks, which ultimately form the entire liquid-cooled energy storage system. The battery cell is the fundamental unit of a liquid-cooled energy storage system. Temperature differences within a liquid-cooled energy storage system significantly impact system lifespan, SOH, and system balance. To minimize these temperature differences and extend system lifespan, the temperature differences between different cells within the system must be controlled within a reasonable range.

[0066] As liquid-cooled energy storage systems develop towards higher rates and higher energy densities, traditional air cooling is no longer sufficient to dissipate heat from the system's battery cells. High-efficiency liquid cooling is needed. Liquid cooling offers low power consumption, low noise, and excellent cell temperature uniformity. Given the high heat generation and high temperature uniformity requirements of battery cells, liquid cooling will gradually become widely used in the thermal management of liquid-cooled energy storage systems. Currently, thermal management risks for liquid-cooled energy storage systems remain largely in the testing phase. Since the system has already been finalized, there is little room for improvement, resulting in long temperature control testing cycles.

[0067] Based on this, the embodiments of the present invention provide a liquid-cooled energy storage system thermal simulation analysis method, device and storage medium, which provide risk point assessment for early thermal management design and reduce system revision design and project development cycle time.

[0068] It should be noted that, referring to Figure 15 Numerous battery cells 130 form a battery module, the battery modules form a battery cluster 190, the battery cluster 190 forms a battery stack, and the battery stack ultimately forms the entire liquid-cooled energy storage system.

[0069] The embodiments of the present invention are further described below with reference to the accompanying drawings.

[0070] The first embodiment of the present invention specifically provides a thermal simulation analysis method for a liquid-cooled energy storage system, such as Figure 1 The thermal simulation analysis method of the liquid-cooled energy storage system according to the embodiment of the present invention is applied to the liquid-cooled energy storage system, and the simulation analysis method includes but is not limited to the following steps:

[0071] Step S100, establishing a liquid cooling plate simulation model according to preset battery cell data;

[0072] It should be noted that the cell data is used to characterize the performance parameters of the cell 130 and the distribution parameters of the cell 130. For example, refer to Figure 4 The preset battery cell data includes the number of battery cells 130 in the battery module and the arrangement of the battery cells 130, the inlet and outlet coolant temperature rise requirements and the maximum temperature rise requirements of the battery cells 130, and the heating parameters of the battery cells 130, wherein the heating parameters of the battery cells 130 include the material properties, thermal conductivity, density, specific heat capacity of the battery cells 130 and the heating power of the battery cells 130 obtained according to experimental test results.

[0073] Step S200, establishing a battery cluster flow simulation model based on the liquid cooling plate simulation model and preset battery cluster data;

[0074] It should be noted that the battery cluster data is used to characterize the battery module distribution parameters and battery module demand parameters in the battery cluster 190. For example, refer to Figure 8 and Figure 9 The preset battery cluster data includes the number of battery modules in the battery cluster 190, the arrangement of the battery modules, and the battery module inlet flow requirements. In step S200, the inlet and outlet pipe diameters of the battery modules can be obtained according to the liquid cooling plate simulation model. The type and size of the battery cluster manifold 170 are obtained according to the number of battery modules in the battery cluster 190, the arrangement of the battery modules, the inlet and outlet pipe diameter data of the battery modules, and the battery module inlet flow requirements, and a battery cluster flow simulation model is established accordingly.

[0075] Step S300, establishing a battery stack flow simulation model based on the battery cluster flow simulation model and preset battery stack data;

[0076] It should be noted that the battery stack data is used to characterize the distribution parameters of the battery cluster 190 in the battery stack and the required parameters of the battery cluster 190. For example, refer to Figure 12 and Figure 13The preset battery stack data includes the number of battery clusters 190 in the battery stack, the arrangement of the battery clusters 190 and the inlet flow requirements of each battery cluster 190. In step S300, the inlet pipe diameter data of the battery cluster 190 can be obtained according to the battery cluster flow simulation model. The type and size of the battery stack collecting pipe 180 are obtained according to the number of battery clusters 190 in the battery stack, the arrangement of the battery clusters 190, the inlet pipe diameter data of the battery cluster 190 and the inlet flow requirements of each battery cluster 190, and the battery stack flow simulation model is established accordingly.

[0077] Step S400, calculating flow distribution differences at multiple pipeline inlets in the liquid-cooled energy storage system based on the battery cluster flow simulation model and the battery stack flow simulation model;

[0078] It should be noted that the flow distribution differences at multiple pipeline inlets include differences in the inlet flow distribution between battery modules within a battery cluster 190 and between battery clusters 190 within a battery stack. Flow distribution differences refer to differences in the inlet flow distribution between different battery modules and between different battery clusters 190.

[0079] Step S500, calculating a plurality of maximum temperatures corresponding to flow distribution differences based on the liquid cooling plate simulation model;

[0080] Step S600, obtaining a temperature difference fitting curve according to a plurality of flow distribution differences and a corresponding plurality of maximum temperatures;

[0081] It should be noted that the temperature difference fitting curve is used to represent the inlet flow rate difference values between different battery modules within the battery cluster 190, the inlet flow rate difference values between different battery clusters 190 within the battery stack, and the maximum temperature change value ΔT corresponding to the inlet flow rate difference values between different battery modules within the battery stack. Specifically, through steps S400 and S500, during the battery module simulation phase, it is necessary to simulate and analyze the maximum temperature corresponding to the inlet flow rates of each different pipeline inlet to obtain the maximum temperature change value ΔT corresponding to different inlet flow rate difference values α. Based on the differences in inlet flow rate distribution between different battery modules within the battery cluster 190 and the differences in inlet flow rate distribution between different battery clusters 190 within the battery stack, the differences in inlet flow rate distribution between different battery modules within the battery stack are calculated, and the temperature difference fitting curve is established accordingly.

[0082] It should be noted that, based on the battery cluster flow simulation model, the differences in the inlet flow distribution between the battery modules in the battery cluster 190 can be preliminarily determined, and the first inlet flow distribution difference data of the inlet flow distribution between the battery modules in the battery cluster 190 can be obtained by the following calculation formula:

[0083] α i1 =(Q i1 -Qi2 ) / Q i2 ,

[0084] Among them, α i1 The first inlet flow rate distribution difference data, Q, represents the inlet flow rate distribution between the battery modules in the same battery cluster 190. i1 represents the inlet flow of a battery module in the same battery cluster 190, Q i2 represents the inlet flow of another battery module in the same battery cluster 190, where Q i1 >Q i2 .

[0085] In addition, based on the battery stack flow simulation model, the difference in inlet flow distribution between the battery clusters 190 in the battery stack can be preliminarily determined, and the second inlet flow distribution difference data of the inlet flow distribution between the battery clusters 190 in the battery stack can be obtained by the following calculation formula:

[0086] α i2 =(Q i3 -Q i4 ) / Q i4 ,

[0087] Among them, α i2 The second inlet flow rate distribution difference data, Q, represents the inlet flow rate distribution between the battery clusters 190 in the battery stack. i3 Indicates the inlet flow of a battery cluster 190 in the battery stack, Q i4 Indicates the inlet flow of another battery cluster 190 in the battery stack, Q i3 >Q i4 Based on the designed first inlet flow distribution difference data of the inlet flow distribution between each battery module in the battery cluster 190 and the second inlet flow distribution difference data of the inlet flow distribution on each battery cluster 190 between the battery stacks, the third inlet flow distribution difference data corresponding to the inlet flow distribution difference between all battery modules in the entire battery stack can be obtained by the following calculation formula:

[0088] α i3 =α i1 +α i2 ,

[0089] Among them, α i3 The third inlet flow distribution difference data represents the inlet flow distribution between each battery module in the battery stack.

[0090] Step S700: Calculate the maximum temperature difference of the battery stack in the liquid-cooled energy storage system based on the temperature difference fitting curve.

[0091] It should be noted that, after comparing the plurality of first inlet flow rate distribution difference data, the maximum inlet flow rate distribution difference data of the inlet flow rate distribution between the battery modules in the battery cluster 190 is obtained, which is also the first difference value. The calculation formula of the first difference value is as follows:

[0092] α1=(Q1-Q2) / Q2,

[0093] Wherein, α1 represents the first difference value of the inlet flow distribution between battery modules in the same battery cluster 190 , Q1 represents the maximum inlet flow of the battery modules in the same battery cluster 190 , and Q2 represents the minimum inlet flow of the battery modules in the same battery cluster 190 .

[0094] In addition, multiple second inlet flow distribution difference data are compared to obtain the maximum inlet flow distribution difference data of the inlet flow distribution between each battery cluster 190 in the battery stack, that is, the second difference value. The calculation formula of the second difference value is as follows:

[0095] α2=(Q3-Q4) / Q4,

[0096] Wherein, α2 represents the second difference value of the inlet flow rate distribution between battery clusters 190 within the battery stack, Q3 represents the maximum inlet flow rate of the battery cluster 190 within the battery stack, and Q4 represents the minimum inlet flow rate of the battery cluster 190 within the battery stack. Based on the designed first difference value of the inlet flow rate distribution between battery modules within the battery cluster 190 and the second difference value of the inlet flow rate distribution between battery clusters 190 within the battery stack, the maximum difference data of the inlet flow rate distribution difference between each battery module in the entire battery stack can be obtained by the following calculation formula, and this difference data is represented by the third difference value:

[0097] α3=α1+α2,

[0098] Here, α3 represents the third difference value. Based on the third difference value, the maximum temperature difference of the battery stack can be obtained from the temperature difference fitting curve. Furthermore, based on the differences in the inlet flow distribution of each battery module, it can be determined whether the temperature difference and maximum temperature within the entire battery stack meet the preset requirements. In this embodiment, the maximum temperature difference between each battery module is required to be less than or equal to 3°C, and the maximum temperature of the battery module must be less than or equal to the value of the ambient temperature plus 10°C. In other embodiments, the required values for the maximum temperature difference between battery modules and the maximum temperature of the battery module can also be set to other values and are not limited to the embodiments of the present invention.

[0099] The present invention establishes a liquid cooling plate simulation model based on preset battery cell data, establishes a battery cluster flow simulation model based on the liquid cooling plate simulation model and preset battery cluster data, and establishes a battery stack flow simulation model based on the battery cluster flow simulation model and preset battery stack data; calculates the flow distribution differences of multiple pipeline inlets in the liquid-cooled energy storage system based on the battery cluster flow simulation model and the battery stack flow simulation model; calculates multiple maximum temperatures corresponding to the multiple flow distribution differences; obtains a temperature difference fitting curve based on the multiple flow distribution differences and the corresponding multiple maximum temperatures; calculates the maximum temperature difference of the battery stack in the liquid-cooled energy storage system based on the temperature difference fitting curve; and evaluates whether the design of the liquid-cooled energy storage system meets the standards based on the maximum temperature difference of the battery stack in the liquid-cooled energy storage system. Through this setting, risk point assessment is provided for early thermal management design, reducing system revision design and project development cycle time, while improving the reliability of thermal management of the liquid-cooled energy storage system.

[0100] In related technologies, thermal management risks for liquid-cooled energy storage systems often remain in the testing phase. Since the system has already been finalized, there's little room for improvement, the system temperature control testing cycle is long, and revisions are labor-intensive and resource-intensive. Therefore, this invention utilizes a thermal simulation analysis method for liquid-cooled energy storage systems to provide risk assessment and improvement solutions for early-stage thermal management design. This reduces system revision design and project development cycle time, saves costs, and improves the reliability of system thermal management.

[0101] It should be noted that, referring to Figure 5 、 Figure 9 and Figure 13 The thermal management simulation of the liquid-cooled energy storage system of the present invention is mainly divided into three levels: the design of the bottom battery module liquid cooling plate 140 is to establish a liquid cooling plate simulation model, the design of the middle battery cluster manifold 170 is to establish a battery cluster flow simulation model, and the design of the top battery stack manifold 180 is to establish a battery stack flow simulation model.

[0102] In this embodiment, during the battery module simulation phase, it is necessary to simulate and analyze the maximum temperature change of the battery module corresponding to the inlet flow rate between different battery modules, obtain the maximum temperature change value ΔT of the battery module corresponding to different flow rate difference values α, and obtain the maximum temperature difference of the battery stack in the liquid-cooled energy storage system, that is, the maximum temperature change value ΔT3, based on the maximum inlet flow difference value α3 of the battery modules in the battery stack in the liquid-cooled energy storage system. The maximum temperature difference of the battery stack in the liquid-cooled energy storage system is then used to evaluate whether the design of the liquid-cooled energy storage system meets the standards. This setting provides risk point assessment for early thermal management design, reduces system revision design and project development cycle time, and improves the reliability of the thermal management of the liquid-cooled energy storage system.

[0103] Reference Figure 2 、 Figure 4 and Figure 5It is understood that the cell data includes the heating parameters of the cell 130, the distribution parameters of the cell 130, and the demand parameters of the cell 130. Step S100 includes but is not limited to the following steps:

[0104] Step S110 , obtaining a preliminary liquid cooling plate simulation model according to the heating parameters of the battery cell 130 , the distribution parameters of the battery cell 130 , and the required parameters of the battery cell 130 ;

[0105] Step S120 , obtaining a liquid cooling plate simulation model by continuously optimizing the flow rate and flow channel form of the preliminary liquid cooling plate simulation model until the preliminary liquid cooling plate simulation model meets the preset liquid cooling conditions.

[0106] It should be noted that the heating parameters of the battery cell 130 include the material properties, thermal conductivity, density, specific heat capacity and heating power of the battery cell 130; the distribution parameters of the battery cell 130 include: the number of battery cells 130 in the battery module and the arrangement of the battery cells 130; the demand parameters of the battery cell 130 include: the inlet and outlet coolant temperature rise requirements and the maximum temperature rise requirements of the battery cell 130.

[0107] It should be noted that the module weight can be determined based on the number and arrangement of battery cells 130 in the battery module, and the structural parameters of the liquid cooling plate 140, such as the dimensions and thickness, can be established based on this. The total heat generation of the battery module is determined from the heat generation parameters of the battery cells 130. The inlet flow rate of the battery module is then determined based on the total heat generation of the battery module, the temperature rise requirements of the inlet and outlet coolant, and the maximum temperature rise requirements of the battery cells 130. The resulting preliminary liquid cooling plate simulation model simulates the maximum simulated battery module temperature, the maximum simulated battery module temperature difference, the simulated pressure drop between the inlet and outlet of the liquid cooling plate 140, and the simulated temperature difference between the inlet and outlet of the liquid cooling plate 140, based on the input flow rate data, to determine whether the preset liquid cooling conditions are met. If so, the preliminary liquid cooling plate simulation model that meets the liquid cooling conditions is used as the liquid cooling plate simulation model. If not, the preliminary liquid cooling plate simulation model is continuously optimized until the preliminary liquid cooling plate simulation model meets the preset liquid cooling conditions, and the preliminary liquid cooling plate simulation model that meets the liquid cooling conditions is used as the liquid cooling plate simulation model.

[0108] It should be noted that when the preliminary liquid cooling plate simulation model does not meet the liquid cooling conditions, the maximum simulated temperature of the battery module, the maximum simulated temperature difference of the battery module, the simulated pressure drop value of the inlet and outlet of the liquid cooling plate 140, and the simulated temperature difference of the inlet and outlet of the liquid cooling plate 140 obtained according to the preliminary liquid cooling plate simulation model are compared with the liquid cooling conditions to obtain the first optimization parameters. According to the first optimization parameters, the flow channel form and flow rate of the liquid cooling plate 140 are optimized until the preliminary liquid cooling plate simulation model meets the preset liquid cooling conditions.

[0109] It should be noted that the flow channel form of the liquid cooling plate simulation model is the flow channel form of the liquid cooling plate 140 , and the flow channel form of the liquid cooling plate 140 includes a series type and a parallel type.

[0110] It should be noted that, referring to Figure 5 The battery module simulation model formed by the liquid cooling plate simulation model includes a battery cell positive electrode 110 , a battery cell negative electrode 120 , a battery cell 130 , a liquid cooling plate 140 and a battery module external connector 150 .

[0111] Reference Figure 3 、 Figure 4 and Figure 5 It is understood that the liquid cooling conditions in step S102 include but are not limited to at least one of the following steps:

[0112] Step S121, the maximum simulated temperature of the battery module in the preliminary liquid cooling plate simulation model is less than or equal to the preset maximum temperature value of the battery module;

[0113] Step S122, the maximum simulated temperature difference of the battery module in the preliminary liquid cooling plate simulation model is less than or equal to the preset maximum temperature difference value of the battery module;

[0114] Step S123: In the preliminary liquid cooling plate simulation model, the simulated pressure drop value at the inlet and outlet of the liquid cooling plate 140 is less than the preset pressure drop value at the inlet and outlet of the liquid cooling plate 140;

[0115] In step S124 , the simulated temperature difference between the inlet and outlet of the liquid cooling plate 140 in the preliminary liquid cooling plate simulation model is less than or equal to a preset temperature difference between the inlet and outlet of the liquid cooling plate 140 .

[0116] For example, the preset maximum temperature of the battery module = ambient temperature + 10°C. If the ambient temperature is 25°C, the maximum simulated temperature of the battery module must be less than or equal to 35°C. The preset maximum temperature difference of the battery module = maximum temperature of the battery module - minimum temperature of the battery module = 3°C. In this case, the maximum simulated temperature difference of the battery module must be less than or equal to 3°C. The preset pressure drop at the inlet and outlet of the liquid cooling plate 140 is 20 kPa. In this case, the simulated pressure drop at the inlet and outlet of the liquid cooling plate 140 must be less than 20 kPa. The preset temperature difference at the inlet and outlet of the liquid cooling plate 140 = outlet temperature of the liquid cooling plate 140 - inlet temperature of the liquid cooling plate 140 = 2°C. In this case, the simulated temperature difference at the inlet and outlet of the liquid cooling plate 140 must be less than or equal to 2°C. If the simulation results do not meet the above liquid cooling conditions, the preliminary liquid cooling plate simulation model must be repeatedly optimized until it meets the preset liquid cooling conditions. The preliminary liquid cooling plate simulation model that meets the liquid cooling conditions will be used as the liquid cooling plate simulation model for battery module testing and verification.

[0117] Reference Figure 6 、 Figure 8 and Figure 9It is understood that the battery cluster data includes battery module distribution parameters and battery module demand parameters. Step S200 includes but is not limited to the following steps:

[0118] Step S210, obtaining inlet and outlet pipe diameter data of multiple battery modules according to the liquid cooling plate simulation model;

[0119] Step S220 , obtaining a preliminary battery cluster flow simulation model based on battery module distribution parameters, battery module demand parameters, and multiple battery module inlet and outlet pipe diameter data;

[0120] Step S230 , obtaining a battery cluster flow simulation model by continuously optimizing the flow tube size and flow tube type of the preliminary battery cluster flow simulation model until the preliminary battery cluster flow simulation model meets the preset battery cluster conditions.

[0121] It should be noted that battery module distribution parameters include the number and arrangement of battery modules within battery cluster 190, while battery module demand parameters include the required battery module inlet flow rate. Based on the number and arrangement of battery modules within battery cluster 190, the inlet and outlet pipe diameters of multiple battery modules, and the required battery module inlet flow rate, the type and size of the battery cluster manifold 170 are determined, and a battery cluster flow simulation model is established based on these parameters.

[0122] It should be noted that it is necessary to judge whether the simulated import flow distribution differences of each battery module and the simulated pressure drop values of the inlet and outlet of the battery cluster 190 obtained according to the preliminary battery cluster flow simulation model meet the preset battery cluster conditions. If so, the preliminary battery cluster flow simulation model that meets the battery cluster conditions will be used as the battery cluster flow simulation model; if the battery cluster conditions are not met, the preliminary battery cluster flow simulation model will be polled and optimized until the preliminary battery cluster flow simulation model meets the battery cluster conditions, and the preliminary battery cluster flow simulation model that meets the battery cluster conditions will be used as the battery cluster flow simulation model.

[0123] It should be noted that when the preliminary battery cluster flow simulation model does not meet the battery cluster conditions, the differences in the simulated inlet flow distribution of each battery module and the simulated inlet and outlet pressure drop values of the battery cluster 190 obtained by simulation of the preliminary battery cluster flow simulation model are compared with the battery cluster conditions to obtain second optimization parameters. According to the second optimization parameters, the size of the battery cluster collector 170 and the type of the battery cluster collector 170 are optimized until the preliminary battery cluster flow simulation model meets the preset battery cluster conditions.

[0124] It should be noted that the battery cluster manifold 170 may be in the shape of a circle, a square, a polygon or a triangle, and the flow distribution corresponding to the battery cluster manifold 170 of different shapes is also different.

[0125] Reference Figure 7 、 Figure 8 and Figure 9 It is understood that the battery cluster conditions in step S230 include but are not limited to at least one of the following steps:

[0126] Step S231: The simulated inlet flow distribution difference of each battery module in the preliminary battery cluster flow simulation model is less than or equal to the preset inlet flow distribution difference of each battery module;

[0127] In step S232 , the simulated pressure drop value at the inlet and outlet of the battery cluster 190 in the preliminary battery cluster flow simulation model is smaller than the preset pressure drop value at the inlet and outlet of the battery cluster 190 .

[0128] For example, if the preset inlet flow rate distribution difference between each battery module is 5%, then the simulated inlet flow rate distribution difference between each battery module must be less than or equal to 5%; if the preset inlet and outlet pressure drop value of battery cluster 190 is 25 kPa, then the simulated inlet and outlet pressure drop value of battery cluster 190 must be less than 25 kPa. If the simulation results of the preliminary battery cluster flow rate simulation model do not meet the above battery cluster conditions, it is necessary to poll and optimize the preliminary battery cluster flow rate simulation model until the preliminary battery cluster flow rate simulation model meets the battery cluster conditions. The preliminary battery cluster flow rate simulation model that meets the battery cluster conditions will be used as the battery cluster flow rate simulation model for battery cluster 190 testing and verification.

[0129] It should be noted that, referring to Figure 9 The size of the battery cluster branch pipe 160 is smaller than that of the battery cluster collecting pipe 170 , but the volume of the battery cluster branch pipe 160 can be larger than or smaller than the area of the battery cluster collecting pipe 170 .

[0130] Reference Figure 10 、 Figure 12 and Figure 13 It is understood that the battery stack data includes the distribution parameters of the battery cluster 190 and the demand parameters of the battery cluster 190. Step S300 includes but is not limited to the following steps:

[0131] Step S310 , obtaining inlet and outlet diameter data of multiple battery clusters 190 according to the battery cluster flow simulation model;

[0132] Step S320 , obtaining a preliminary battery stack flow simulation model based on the battery cluster 190 distribution parameters, the battery cluster 190 demand parameters, and the inlet and outlet pipe diameter data of the plurality of battery clusters 190 ;

[0133] Step S330 , obtaining a battery stack flow simulation model by continuously optimizing the flow tube size and flow tube type of the preliminary battery stack flow simulation model until the preliminary battery stack flow simulation model meets the preset battery stack conditions.

[0134] It should be noted that the distribution parameters of the battery cluster 190 include the number of battery clusters 190 in the battery stack and the arrangement of the battery clusters 190, and the demand parameters of the battery cluster 190 include the inlet flow requirements of the battery cluster 190; based on the number of battery clusters 190 in the battery stack, the arrangement of the battery clusters 190, the inlet and outlet pipe diameter data of multiple battery clusters 190 and the inlet flow requirements of each battery cluster 190, the type and size of the battery stack collecting pipe 180 are obtained, and a battery stack flow simulation model is established accordingly.

[0135] It should be noted that it is necessary to judge whether the simulated inlet flow distribution differences of each battery cluster 190 and the simulated pressure drop values at the inlet and outlet of the battery stack obtained based on the preliminary battery stack flow simulation model meet the preset battery stack conditions. If so, the preliminary battery stack flow simulation model that meets the battery stack conditions will be used as the battery stack flow simulation model; if the battery stack conditions are not met, the preliminary battery stack flow simulation model will be polled and optimized until the preliminary battery stack flow simulation model meets the battery stack conditions, and the preliminary battery stack flow simulation model that meets the battery stack conditions will be used as the battery stack flow simulation model.

[0136] It should be noted that when the preliminary battery stack flow simulation model does not meet the battery stack conditions, the simulated inlet flow distribution differences of each battery cluster 190 and the simulated pressure drop values at the inlet and outlet of the battery stack obtained by simulation according to the preliminary battery stack flow simulation model are compared with the battery stack conditions to obtain the third optimization parameters. According to the third optimization parameters, the size of the battery stack collector 180 and the type of the battery stack collector 180 are optimized until the preliminary battery stack flow simulation model meets the preset battery stack conditions.

[0137] Reference Figure 11 、 Figure 12 and Figure 13 It is understood that the battery stack conditions in step S330 include but are not limited to at least one of the following steps:

[0138] Step S331 , the simulated inlet flow distribution difference of each battery cluster 190 in the preliminary battery stack flow simulation model is less than or equal to the preset inlet flow distribution difference of each battery cluster 190 ;

[0139] Step S332: The simulated pressure drop value at the inlet and outlet of the battery stack in the preliminary battery stack flow simulation model is less than the preset pressure drop value at the inlet and outlet of the battery stack.

[0140] For example, if the preset difference in inlet flow distribution for each battery cluster 190 is 15%, the simulated difference in inlet flow distribution for each battery cluster 190 must be less than or equal to 15%. If the preset pressure drop at the battery stack inlet and outlet is 30 kPa, the simulated pressure drop at the battery stack inlet and outlet must be less than 30 kPa. If the simulation results of the preliminary battery stack flow simulation model do not meet the above battery stack conditions, the preliminary battery stack flow simulation model must be polled and optimized until it meets the battery stack conditions. The preliminary battery stack flow simulation model that meets the battery stack conditions will be used as the battery stack flow simulation model for battery stack testing and verification.

[0141] It should be noted that, referring to Figure 13 The size of the battery stack collecting tube 180 is larger than that of the battery cluster collecting tube 170 , but the volume of the battery stack collecting tube 180 may be larger than or smaller than the area of the battery cluster collecting tube 170 .

[0142] Reference Figure 14 It is understood that step S700 includes but is not limited to the following steps:

[0143] Step S710, calculating a first difference value of inlet flow distribution between each battery module in each battery cluster 190 in the liquid-cooled energy storage system according to the battery cluster flow simulation model;

[0144] Step S720 , calculating a second difference value of the inlet flow distribution between each battery cluster 190 in the battery stack according to the battery stack flow simulation model;

[0145] Step S730, calculating a third difference value of the inlet flow distribution between the plurality of battery modules in the battery stack based on the first difference value and the second difference value;

[0146] Step S740: Calculate the maximum temperature difference corresponding to the third difference value according to the temperature difference fitting curve.

[0147] It should be noted that the calculation formula for the first difference value of the inlet flow distribution on each battery module in the battery cluster 190 is as follows:

[0148] α1=(Q1-Q2) / Q2,

[0149] Where α1 represents the first difference in inlet flow rate distribution between battery modules within the same battery cluster 190, Q1 represents the maximum inlet flow rate of the battery modules within the same battery cluster 190, and Q2 represents the minimum inlet flow rate of the battery modules within the same battery cluster 190. The second difference in inlet flow rate distribution between battery clusters 190 within a battery stack is calculated as follows:

[0150] α2=(Q3-Q4) / Q4,

[0151] Wherein, α2 represents the second difference value of the inlet flow rate distribution between the battery clusters 190 in the battery stack, Q3 represents the maximum inlet flow rate of the battery cluster 190 in the battery stack, and Q4 represents the minimum inlet flow rate of the battery cluster 190 in the battery stack. The calculation formula for the third difference value of the inlet flow rate distribution between each battery module in the battery stack is as follows:

[0152] α3=α1+α2,

[0153] Among them, α3 represents the third difference value of the inlet flow distribution of each battery module in the battery stack, that is, the maximum difference data of the inlet flow distribution difference between each battery module in the entire battery stack. Based on the maximum inlet flow difference value α3 between the battery modules in the battery stack in the liquid-cooled energy storage system and the temperature difference fitting curve, the maximum temperature difference of the battery stack in the liquid-cooled energy storage system, that is, the maximum temperature change value ΔT3, is obtained. Then, the maximum temperature difference of the battery stack in the liquid-cooled energy storage system is used to evaluate whether the design of the liquid-cooled energy storage system meets the standards. Through this setting, risk point assessment is provided for early thermal management design, reducing the system revision design and project development cycle time, while improving the reliability of the thermal management of the liquid-cooled energy storage system.

[0154] In addition, the second embodiment of the present invention further provides a liquid-cooled energy storage system thermal simulation and analysis device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor.

[0155] The processor and the memory may be connected via a bus or other means.

[0156] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0157] The non-transient software program and instructions required to implement the liquid-cooled energy storage system thermal simulation analysis method of the first embodiment are stored in the memory. When executed by the processor, the liquid-cooled energy storage system thermal simulation analysis method of the above embodiment is executed, for example, the above-described Figure 1 Method steps S100 to S700, Figure 2 Steps S110 to S120 of the method, Figure 3 Steps S121 to S124 of the method, Figure 6 Steps S210 to S230 of the method, Figure 7 Steps S231 to S232 of the method, Figure 10 Steps S310 to S330 of the method, Figure 11 Steps S331 to S332 of the method, Figure 14 Method steps S710 to S740.

[0158] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.

[0159] In addition, an embodiment of the present invention further provides a computer-readable storage medium, which stores computer-executable instructions. The computer-executable instructions are executed by a processor or controller, for example, by a processor in the above-mentioned device embodiment, so that the above-mentioned processor can execute the liquid-cooled energy storage system thermal simulation analysis method in the above-mentioned embodiment, for example, to execute the above-mentioned Figure 1 Method steps S100 to S700, Figure 2 Steps S110 to S120 of the method, Figure 3 Steps S121 to S124 of the method, Figure 6 Steps S210 to S230 of the method, Figure 7 Steps S231 to S232 of the method, Figure 10 Steps S310 to S330 of the method, Figure 11 Steps S331 to S332 of the method, Figure 14 Method steps S710 to S740.

[0160] Those skilled in the art will appreciate that all or some of the steps and systems in the method disclosed above can be implemented as software, firmware, hardware, and appropriate combinations thereof. Some physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, and the computer-readable medium can include computer storage media (or non-transitory media) and communication media (or temporary media). As known to those skilled in the art, the term computer storage media is included in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data) and is volatile and non-volatile, removable, and non-removable. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory, or other memory technology, CD-ROM, digital versatile disks (DVD), or other optical disk storage, magnetic cassettes, magnetic tapes, disk storage, or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, as is well known to those skilled in the art, communication media typically embodies computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0161] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the above implementation. Those skilled in the art can make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present invention.

Claims

1. A thermal simulation analysis method for a liquid-cooled energy storage system, characterized in that: Applied to a liquid-cooled energy storage system, the simulation analysis method includes: Establish a liquid cooling plate simulation model based on the preset battery cell data; A battery cluster flow simulation model is established based on the liquid cooling plate simulation model and preset battery cluster data; a battery stack flow simulation model is established based on the battery cluster flow simulation model and preset battery stack data; and flow distribution differences at multiple pipeline inlets in the liquid-cooled energy storage system are calculated based on the battery cluster flow simulation model and the battery stack flow simulation model; Calculating, based on the liquid cooling plate simulation model, a plurality of maximum temperatures corresponding to the plurality of flow distribution differences; Obtaining a temperature difference fitting curve based on the plurality of flow distribution differences and the corresponding plurality of maximum temperatures; and calculating the maximum temperature difference of the battery stack in the liquid-cooled energy storage system based on the temperature difference fitting curve; Calculating the maximum temperature difference of the battery stack in the liquid-cooled energy storage system according to the temperature difference fitting curve includes: Calculating a first difference value of inlet flow distribution between battery modules in each battery cluster in the liquid-cooled energy storage system according to the battery cluster flow simulation model; calculating, based on the battery stack flow simulation model, a second difference value of the inlet flow distribution between the battery clusters in the battery stack; Calculating a third difference value of inlet flow distribution between a plurality of battery modules in the battery stack based on the first difference value and the second difference value; The maximum temperature difference corresponding to the third difference value is calculated based on the temperature difference fitting curve.

2. The thermal simulation analysis method for a liquid-cooled energy storage system according to claim 1, characterized in that: The battery cell data includes battery cell heating parameters, battery cell distribution parameters, and battery cell demand parameters. The liquid cooling plate simulation model is established based on the preset battery cell data, including: Obtaining a preliminary liquid cooling plate simulation model according to the battery cell heating parameters, the battery cell distribution parameters, and the battery cell demand parameters; The liquid cooling plate simulation model is obtained by continuously optimizing the flow rate and the flow channel form of the preliminary liquid cooling plate simulation model until the preliminary liquid cooling plate simulation model meets the preset liquid cooling conditions.

3. The thermal simulation analysis method for a liquid-cooled energy storage system according to claim 2, characterized in that: The liquid cooling condition includes at least one of the following: The maximum simulated temperature of the battery module in the preliminary liquid cooling plate simulation model is less than or equal to the preset maximum temperature value of the battery module; The maximum simulated temperature difference of the battery module in the preliminary liquid cooling plate simulation model is less than or equal to the preset maximum temperature difference value of the battery module; The simulated pressure drop value of the liquid cooling plate inlet and outlet in the preliminary liquid cooling plate simulation model is less than the preset pressure drop value of the liquid cooling plate inlet and outlet; In the preliminary liquid cooling plate simulation model, the simulated temperature difference between the inlet and outlet of the liquid cooling plate is less than or equal to the preset temperature difference between the inlet and outlet of the liquid cooling plate.

4. The thermal simulation analysis method for a liquid-cooled energy storage system according to claim 1, characterized in that: The battery cluster data includes battery module distribution parameters and battery module demand parameters. Based on the liquid cooling plate simulation model and the preset battery cluster data, a battery cluster flow simulation model is established, including: According to the liquid cooling plate simulation model, obtaining a plurality of inlet and outlet pipe diameter data of the battery module; Obtaining a preliminary battery cluster flow simulation model based on the battery module distribution parameters, the battery module demand parameters, and multiple battery module inlet and outlet pipe diameter data; The battery cluster flow simulation model is obtained by continuously optimizing the flow tube size and flow tube type of the preliminary battery cluster flow simulation model until the preliminary battery cluster flow simulation model meets the preset battery cluster conditions.

5. The thermal simulation analysis method for a liquid-cooled energy storage system according to claim 4, characterized in that: The battery cluster condition includes at least one of the following: The simulated inlet flow distribution difference of each battery module in the preliminary battery cluster flow simulation model is less than or equal to the preset inlet flow distribution difference of each battery module; The simulated pressure drop value of the battery cluster inlet and outlet in the preliminary battery cluster flow simulation model is less than the preset pressure drop value of the battery cluster inlet and outlet.

6. The thermal simulation analysis method for a liquid-cooled energy storage system according to claim 1, characterized in that: The battery stack data includes battery cluster distribution parameters and battery cluster demand parameters. A battery stack flow simulation model is established based on the battery cluster flow simulation model and preset battery stack data, including: According to the battery cluster flow simulation model, obtaining a plurality of inlet and outlet pipe diameter data of the battery cluster; Obtaining a preliminary battery stack flow simulation model based on the battery cluster distribution parameters, the battery cluster demand parameters, and multiple battery cluster inlet and outlet pipe diameter data; The battery stack flow simulation model is obtained by continuously optimizing the flow tube size and flow tube type of the preliminary battery stack flow simulation model until the preliminary battery stack flow simulation model meets the preset battery stack conditions.

7. The thermal simulation analysis method for a liquid-cooled energy storage system according to claim 6, characterized in that: The battery stack condition includes at least one of the following: The simulated inlet flow distribution difference of each battery cluster in the preliminary battery stack flow simulation model is less than or equal to the preset inlet flow distribution difference of each battery cluster; The simulated pressure drop value at the inlet and outlet of the battery stack in the preliminary battery stack flow simulation model is less than the preset pressure drop value at the inlet and outlet of the battery stack.

8. A liquid-cooled energy storage system thermal simulation analysis device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the thermal simulation analysis method for a liquid-cooled energy storage system according to any one of claims 1 to 7 is implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the thermal simulation analysis method for a liquid-cooled energy storage system according to any one of claims 1 to 7.

Images