Battery liquid cooling temperature prediction method based on thermal resistance network

Abstract

The invention relates to a battery liquid cooling temperature prediction method based on a thermal resistance network, and the method comprises the following steps: analyzing the heat dissipation condition of a geometric model, and mastering the overall heat flow direction; node division is carried out on the whole model, and preparation is made for constructing a thermal resistance network; thermal resistance value calculation, wherein a thermal resistance network is divided into battery heat conduction thermal resistance, liquid cooling plate heat conduction thermal resistance, cooling liquid convection thermal resistance and enthalpy change thermal resistance; combing the series-parallel connection relation of the thermal resistance between the network units to form a complete thermal resistance network model; the transient temperature of all nodes can be calculated through a calculation formula by calculating the thermal resistance value between the nodes. According to the method, the temperature distribution of the battery under the liquid cooling effect is rapidly and accurately predicted, a reliable basis is provided for real-time temperature monitoring, the problem that the thermal resistance calculation of the liquid cooling plate is complex is solved, and meanwhile the technical problem that the complex calculation problem caused by follow-up structure and parameter optimization can be rapidly solved through the universality of the method is needed to be solved at present. Compared with the prior art, the device has good market prospect and development space.

Description

Technical Field

[0001] The present invention relates to the technical field of battery temperature prediction, and in particular to a battery liquid cooling temperature prediction method based on a thermal resistance network. Background Art

[0002] With the development of my country's new energy vehicle industry, the market share of batteries has grown rapidly. Among them, lithium-ion batteries are the most widely used batteries at present. They have advantages such as high energy density and no memory effect. They have become a relatively mature technical solution for pure electric vehicles. However, lithium-ion batteries have serious safety problems due to their high heat release characteristics. Since thousands of single cells in the battery pack are connected in series and parallel to form a large voltage and current for the vehicle to use, and the space inside the vehicle is small, the battery pack formed by the close arrangement of battery cells is susceptible to adverse factors such as collision, overcharging, and over-discharging, which ultimately cause the entire battery pack to burn or explode. There are reports on spontaneous combustion accidents of new energy vehicle batteries. Research and optimization of battery heat dissipation performance can reduce the frequency of such accidents and safeguard personal safety.

[0003] At present, the main methods for battery heat dissipation are air cooling, liquid cooling, phase change cooling and heat pipe cooling. Among them, liquid cooling is the preferred cooling method for various companies. It has the advantages of obvious heat dissipation effect, no influence from external factors and low cost. For the prediction of battery liquid cooling temperature, the safety of the system can be evaluated and the temperature can be monitored in real time, and a theoretical basis can be provided for subsequent optimization. Patent CN113671384B uses the total heat generation power, the total heat dissipation power, the delayed total heat generation power and the delayed total heat dissipation power as inputs, and uses the heat balance equation to calculate the battery temperature at the next moment. However, the patent does not determine the specific method of the heat dissipation end and the specific steps for calculating the heat dissipation power. For liquid cooling plates with complex structures, the calculation of heat dissipation power and thermal resistance of liquid cooling plates is complicated. Patent CN111191366A estimates the temperature of the battery cells inside the liquid-cooled power battery pack in real time by experimentally calibrating the relationship between the equivalent heat dissipation parameters between the battery and the coolant and the equivalent heat dissipation parameters between the battery and the air. However, this type of technology can only predict the battery temperature under the size of the liquid cooling plate and is not universal for other sizes.

[0004] How to design a smart, reasonable and feasible method to quickly and accurately predict the temperature distribution of the battery under liquid cooling, provide a reliable basis for real-time temperature monitoring, solve the complex calculation of the thermal resistance of the liquid cooling plate, and quickly solve the complex calculation problems caused by subsequent structure and parameter optimization. This is a technical problem that needs to be solved at present. Summary of the invention

[0005] The present invention provides a battery liquid cooling temperature prediction method based on a thermal resistance network, which can improve the accuracy of battery temperature prediction and reduce the time cost required for the prediction process. The present invention is reasonable and feasible, and can quickly and accurately predict the temperature distribution of the battery under liquid cooling, providing a reliable basis for real-time temperature monitoring. While solving the complex calculation of the thermal resistance of the liquid cooling plate, its versatility can quickly solve the complex calculation problems caused by subsequent structure and parameter optimization.

[0006] A battery liquid cooling temperature prediction method based on a thermal resistance network comprises the following steps:

[0007] Step 1: Analyze the heat dissipation of the geometric model and understand the overall heat flow direction;

[0008] Step 2: Divide the nodes of the entire model to prepare for building a thermal resistance network;

[0009] Step 3: Calculate the thermal resistance numerically. The thermal resistance network is divided into four types of thermal resistance, namely, battery thermal resistance, liquid cooling plate thermal resistance, coolant convection resistance and enthalpy change thermal resistance.

[0010] Step 4: sort out the series and parallel relationships of thermal resistances between network units to form a complete thermal resistance network model;

[0011] Step 5: By calculating the thermal resistance values ​​between each node, the transient temperature of all nodes can be calculated using the calculation formula.

[0012] As a further optimization scheme of the above-mentioned battery liquid cooling temperature prediction method based on thermal resistance network, in the step one, the heat flow is as follows: the battery is located at the top of the entire system, the liquid cooling plate is located at the bottom of the entire system, the coolant exists in the liquid cooling plate, the heat is generated by the battery, transferred to the coolant through the liquid cooling plate, and finally the coolant flows out of the system to take away the heat.

[0013] As a further optimization scheme of the above-mentioned battery liquid cooling temperature prediction method based on thermal resistance network, the node division process of the entire model in step 2 is as follows:

[0014] a, In the vertical direction, according to the different physical parameters of each component of the battery liquid cooling heat dissipation model, it is divided into three layers, from top to bottom, namely the battery layer, the liquid cooling plate layer and the coolant layer; the heat is transferred from the battery layer node to the liquid cooling plate layer node, and finally flows into the fluid layer node;

[0015] b. In the horizontal direction, the flow channel corner plane and the center plane of the liquid cooling plate fin are respectively set as the dividing planes. The number of model nodes in this layer is the number of flow channels * (number of corners + 1).

[0016] As a further optimization scheme of the above-mentioned battery liquid cooling temperature prediction method based on thermal resistance network, the calculation process of various thermal resistance values ​​in step 3 is as follows:

[0017] The battery thermal resistance, coolant convection resistance and enthalpy change resistance are calculated using heat transfer theory and can be calculated based on: Calculate the thermal resistance value,

[0018] In the formula, R heat is the thermal resistance of the battery; R conv is the convection thermal resistance of the coolant; δ is the heat transfer thickness; A is the contact area; k is the thermal conductivity of the material; h is the convection heat transfer coefficient;

[0019] The convective heat transfer coefficient h required to calculate the convective thermal resistance of the coolant needs to be calculated using the following formula:

[0020] In the formula, k l is the thermal conductivity of the coolant, d is the characteristic length, Nu is the Nusselt number,

[0021] Since most flows are laminar, there is a laminar inlet effect. If the inlet section length is not exceeded, the calculate,

[0022] Where Re is the Reynolds number, Pr is the Prandtl number, and L is the flow channel length;

[0023] As for the thermal resistance value between each node of the coolant, the enthalpy change thermal resistance used in most literature is adopted. Calculate the enthalpy change thermal resistance value through ΔT = qR fluid Calculate the temperatures of the two coolant nodes,

[0024] Where q is the heat flux from the cold plate node to the fluid node; R fluid is the enthalpy change thermal resistance; m is the mass flow rate; c p is the specific heat capacity of the coolant, the coolant temperature Tr at the inlet is set to a constant low temperature,

[0025] The thermal resistance of the liquid cooling plate is calculated by CFD simulation, and the accuracy of CFD simulation is verified by experiments.

[0026] Use CFD software to simulate the liquid cooling plate nodes. The structure style of each liquid cooling plate node is consistent, and only the size is different.

[0027] In the vertical direction, the upper surface on the outside of the node model and the four inner surfaces are set to different constant temperatures with a temperature difference of ΔT, and the heat flux Q is monitored. Calculate the vertical thermal resistance, which is the thermal resistance of heat flowing from the battery through the liquid cooling plate.

[0028] In the formula, R l is the thermal resistance of the liquid cooling plate,

[0029] In the horizontal direction, the opposite sides of the node model are set to different constant temperatures. The above formula is also used to calculate the thermal resistance values ​​in the horizontal directions, that is, the thermal resistance in the process of heat transfer from a liquid cooling plate node to the horizontal direction.

[0030] Since the structural style of each liquid cooling plate node is consistent, its dimensions are set as variables, and sample points of different sizes are extracted using optimal Latin cube sampling and other forms. If the number of variables is n, 10n+1 sample points need to be selected. An approximate model is established through an appropriate number of sample points to obtain the corresponding values ​​of different sample points, and finally the thermal resistance values ​​of different directions of each size structure of the liquid cooling plate node are obtained.

[0031] As a further optimization scheme of the above-mentioned battery liquid cooling temperature prediction method based on thermal resistance network, the transient temperature calculation process of all nodes in step 5 is as follows:

[0032] The transient temperature calculation formulas for all nodes can be expressed in the following general format for calculation:

[0033]

[0034] Where, T i，j，k (t) is the temperature of the point with coordinates (i, j, k) at time t; V i，j，k is the volume of the point; Q i，j，k (t) is the heating power, T s With R s is the temperature of the node where heat transfer occurs and the thermal resistance between the two; R s Including battery thermal resistance R heat 、Thermal resistance of liquid cooling plate R l , Coolant convection thermal resistance R conv and enthalpy change thermal resistance R fluid , m i，j，k is the average mass of the point;

[0035] The heat generation power is based on the Bernadi heat generation rate model, Q i，j，k =I 2 R n +IT b k rev ,

[0036] Where I is the operating current of the battery, R n is the internal resistance of the battery, T b is the battery temperature, k rev is the entropy thermal coefficient of the battery. The corresponding value is obtained by testing the battery internal resistance at different temperatures and SOC conditions and the entropy thermal coefficient at different SOCs.

[0037] Beneficial Effects

[0038] Compared with the prior art, the present invention has obvious advantages and beneficial effects, can achieve considerable technical progress and practicality, and has a wide range of utilization value. It has at least the following advantages:

[0039] First, the present invention is divided into three layers by different physical parameters in the vertical direction, and the flow channel corner plane and the fin center plane are cutting planes in the horizontal direction. The number of nodes in each layer is the number of flow channels*(number of corners+1). The number of nodes is small, which reduces the calculation time to a certain extent. The battery temperature distribution can be calculated in real time, the real-time temperature dynamics of the battery can be mastered, the battery thermal safety hazards can be discovered in time, and adjustments can be made in advance to ensure that the battery is maintained within a safe temperature range.

[0040] Secondly, in terms of calculating thermal resistance, the present invention first calculates the thermal resistance value of the component node through CFD simulation for the thermal resistance of nodes with complex shapes (thermal resistance of the liquid cooling plate by thermal conduction), and then randomly samples sample points to establish an approximate model to obtain the thermal resistance values ​​of the nodes of various sizes and structures in different directions of the liquid cooling plate. This method improves the accuracy of the system components, and then improves the accuracy of the entire model. At the same time, this method can solve the problem of complex thermal resistance calculation caused by the structure of the liquid cooling plate and reduce the steps required in the calculation process.

[0041] Third, the present invention establishes an approximate model of the thermal resistance of the liquid cooling plate, which is universal for other sizes of this type of liquid cooling plate, reducing the complex calculation problems caused by subsequent structural and parameter optimization. By deriving an approximate model of the change in thermal resistance due to changes in the liquid cooling plate structure, compared with other articles that establish an approximate model for the entire battery liquid cooling system and derive an approximate model of the final temperature change due to changes in the liquid cooling plate structure, this patent establishes an approximate model for the liquid cooling plate, which is more targeted and more conducive to the research on liquid cooling plate structure optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 The flowchart of the battery liquid cooling temperature prediction method based on thermal resistance network;

[0043] Figure 2 It is a schematic diagram of the partial geometric structure of the system;

[0044] Figure 3 It is the thermal resistance network diagram in the vertical direction, Ta is the battery top temperature, and Ts is the coolant temperature;

[0045] Figure 4 It is the thermal resistance network diagram in the horizontal direction of the battery layer or liquid cooling plate layer, and Tb is the edge temperature;

[0046] Figure 5 It is the thermal resistance network diagram of the coolant in the horizontal direction, Tr is the inlet temperature, and Tc is the outlet temperature;

[0047] Figure 6Schematic diagram of the flow channel corner plane on the liquid cooling plate node and the center plane of the liquid cooling plate fin. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with specific embodiments and drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of protection claimed. Based on the embodiments of the present invention, all other embodiments obtained without creative work, such as formal modifications to the technical solutions recorded in the following embodiments made by ordinary technicians in this field within the inspiration of the ideas of the present invention, or equivalent replacement of some of the technical features therein, shall fall within the scope of protection of the present invention.

[0049] like Figure 1 As shown, Figure 1 A flow chart of a battery liquid cooling temperature prediction method based on a thermal resistance network; A battery liquid cooling temperature prediction method based on a thermal resistance network comprises the following steps:

[0050] Step 1: Analyze the heat dissipation of the geometric model and understand the overall heat flow direction;

[0051] Step 2: Divide the nodes of the entire model to prepare for building a thermal resistance network;

[0052] Step 3: Calculate the thermal resistance numerically. The thermal resistance network is divided into four types of thermal resistance, namely, battery thermal resistance, liquid cooling plate thermal resistance, coolant convection resistance and enthalpy change thermal resistance.

[0053] Step 4: sort out the series and parallel relationships of thermal resistances between network units to form a complete thermal resistance network model;

[0054] Step 5: By calculating the thermal resistance values ​​between each node, the transient temperature of all nodes can be calculated using the calculation formula.

[0055] like Figure 2 As shown, Figure 2 It is a schematic diagram of the partial geometric structure of the system; in the step one, the heat flow is as follows: the battery is located at the top of the entire system, the liquid cooling plate is located at the bottom of the entire system, the coolant exists in the liquid cooling plate, the heat is generated by the battery, transferred to the coolant through the liquid cooling plate, and finally the coolant flows out of the system to take away the heat.

[0056] like Figure 3 and 4 As shown, Figure 3 It is the thermal resistance network diagram in the vertical direction, Ta is the battery top temperature, and Ts is the coolant temperature; Figure 4It is a thermal resistance network diagram of the liquid cooling plate layer (or battery layer) in the horizontal direction of the method model. The process of node division of the entire model in step 2 is as follows:

[0057] a, In the vertical direction, according to the different physical parameters of each component of the battery liquid cooling heat dissipation model, it is divided into three layers, from top to bottom, namely the battery layer, the liquid cooling plate layer and the coolant layer; the heat is transferred from the battery layer node to the liquid cooling plate layer node, and finally flows into the fluid layer node;

[0058] b. In the horizontal direction, the flow channel corner plane and the center plane of the liquid cooling plate fin are respectively set as the dividing planes. The number of model nodes in this layer is the number of flow channels * (number of corners + 1).

[0059] like Figure 5 and 6 As shown, Figure 5 It is the thermal resistance network diagram of the cooling liquid layer in the horizontal direction of the method model. In the horizontal direction, the flow channel corner plane is set as the dividing plane, and the number of nodes is the same as that of the liquid cooling plate layer and the battery layer. Figure 6 Schematic diagram of the flow channel corner plane and the center plane of the liquid cooling plate fin.

[0060] The calculation process of various thermal resistance values ​​in step 3 is as follows:

[0061] The battery thermal resistance, coolant convection resistance and enthalpy change resistance are calculated using heat transfer theory and can be calculated based on: Calculate the thermal resistance value,

[0062] In the formula, R heat is the thermal resistance of the battery; R conv is the convection thermal resistance of the coolant; δ is the heat transfer thickness; A is the contact area; k is the thermal conductivity of the material; h is the convection heat transfer coefficient;

[0063] The convective heat transfer coefficient h required to calculate the convective thermal resistance of the coolant needs to be calculated using the following formula:

[0064] In the formula, k l is the thermal conductivity of the coolant, d is the characteristic length, Nu is the Nusselt number,

[0065] Since most flows are laminar, there is a laminar inlet effect. If the inlet section length is not exceeded, the calculate,

[0066] Where Re is the Reynolds number, Pr is the Prandtl number, and L is the flow channel length;

[0067] As for the thermal resistance value between each node of the coolant, the enthalpy change thermal resistance used in most literature is adopted. Calculate the enthalpy change thermal resistance value through ΔT = qR fluid Calculate the temperatures of the two coolant nodes,

[0068] Where q is the heat flux from the cold plate node to the fluid node; R fluid is the enthalpy change thermal resistance; m is the mass flow rate; c p is the specific heat capacity of the coolant, the coolant temperature Tr at the inlet is set to a constant low temperature,

[0069] The thermal resistance of the liquid cooling plate is calculated by CFD simulation, and the accuracy of CFD simulation is verified by experiments.

[0070] Use CFD software to simulate the liquid cooling plate nodes. The structure style of each liquid cooling plate node is consistent, and only the size is different.

[0071] In the vertical direction, the upper surface on the outside of the node model and the four inner surfaces are set to different constant temperatures with a temperature difference of ΔT, and the heat flux Q is monitored. Calculate the vertical thermal resistance, which is the thermal resistance of heat flowing from the battery through the liquid cooling plate.

[0072] In the formula, R l is the thermal resistance of the liquid cooling plate,

[0073] In the horizontal direction, the opposite sides of the node model are set to different constant temperatures. The above formula is also used to calculate the thermal resistance values ​​in the horizontal directions, that is, the thermal resistance in the process of heat transfer from a liquid cooling plate node to the horizontal direction.

[0074] Since the structural style of each liquid cooling plate node is consistent, its dimensions are set as variables, and sample points of different sizes are extracted using optimal Latin cube sampling and other forms. If the number of variables is n, 10n+1 sample points need to be selected. An approximate model is established through an appropriate number of sample points to obtain the corresponding values ​​of different sample points, and finally the thermal resistance values ​​of different directions of each size structure of the liquid cooling plate node are obtained.

[0075] The transient temperature calculation process of all nodes in step 5 is as follows:

[0076] The transient temperature calculation formulas for all nodes can be expressed in the following general format for calculation:

[0077]

[0078] Where, T i，j，k (t) is the temperature of the point with coordinates (i, j, k) at time t; V i，j，k is the volume of the point; Q i，j，k (t) is the heating power, T s With R s is the temperature of the node where heat transfer occurs and the thermal resistance between the two; R s Including battery thermal resistance Rheat 、Thermal resistance of liquid cooling plate R l , Coolant convection thermal resistance R conv and enthalpy change thermal resistance R fluid , m i，j，k is the average mass of the point;

[0079] The heat generation power is based on the Bernadi heat generation rate model, Q i，j，k =I 2 R n +IT b k rev ,

[0080] Where I is the operating current of the battery, R n is the internal resistance of the battery, T b is the battery temperature, k rev is the entropy thermal coefficient of the battery. The corresponding value is obtained by testing the battery internal resistance at different temperatures and SOC conditions and the entropy thermal coefficient at different SOCs.

[0081] The present invention is divided into three layers by different physical parameters in the vertical direction, and the flow channel corner plane and the fin center plane are used as cutting planes in the horizontal direction. The number of nodes in each layer is the number of flow channels*(number of corners+1). The number of nodes is small, which can reduce the calculation time to a certain extent. The battery temperature distribution can be calculated in real time, the real-time temperature dynamics of the battery can be grasped, the thermal safety hazards of the battery can be discovered in time, and regulation can be carried out in advance to ensure that the battery is maintained within a safe temperature range.

[0082] In terms of calculating thermal resistance, the present invention first calculates the thermal resistance value of the component node through CFD simulation for the node thermal resistance of complex shape (thermal resistance of liquid cooling plate), and then randomly samples sample points to establish an approximate model to obtain the thermal resistance values ​​of the liquid cooling plate nodes in different directions of various size structures. This method improves the accuracy of the system components and then improves the accuracy of the entire model. At the same time, this method can solve the problem of thermal resistance calculation caused by the complex structure of the liquid cooling plate and reduce the steps required in the calculation process.

[0083] The present invention establishes an approximate model of the thermal resistance of the liquid cooling plate, which is universal for other sizes of such liquid cooling plates, reduces the complex calculation problems caused by subsequent structural and parameter optimization, and derives an approximate model of the change in thermal resistance caused by the change in the structure of the liquid cooling plate. Compared with other articles that establish an approximate model for the entire battery liquid cooling system and derive an approximate model of the final temperature change caused by the change in the structure of the liquid cooling plate, this patent establishes an approximate model for the liquid cooling plate, which is more targeted and more conducive to the research on the optimization of the liquid cooling plate structure.

[0084] The present invention is reasonable and feasible, and can quickly and accurately predict the temperature distribution of the battery under liquid cooling, provide a reliable basis for real-time temperature monitoring, and solve the complex calculation of the thermal resistance of the liquid cooling plate. Its versatility can also quickly solve the complex calculation problems caused by subsequent structure and parameter optimization. Compared with the existing technology, it has a good market prospect and development space.

[0085] The preferred specific implementation modes and embodiments of the present invention are described in detail above in conjunction with the accompanying drawings, but the present invention is not limited to the above implementation modes and embodiments, and various changes can be made within the knowledge scope of those skilled in the art without departing from the concept of the present invention.

Claims

1. A battery liquid cooling temperature prediction method based on a thermal resistance network, characterized in that: The following steps are included: Step 1: Analyze the heat dissipation of the geometric model and understand the overall heat flow direction; Step 2: Divide the nodes of the entire model to prepare for building a thermal resistance network; Step 3: Calculate the thermal resistance numerically. The thermal resistance network is divided into four types of thermal resistance, namely, battery thermal resistance, liquid cooling plate thermal resistance, coolant convection resistance and enthalpy change thermal resistance. Step 4: sort out the series and parallel relationships of thermal resistances between network units to form a complete thermal resistance network model; Step 5: By calculating the thermal resistance values ​​between each node, the transient temperature of all nodes can be calculated using the calculation formula.

2. A battery liquid cooling temperature prediction method based on a thermal resistance network as claimed in claim 1, characterized in that: In step 1, the heat flow is as follows: the battery is located at the top of the entire system, the liquid cooling plate is located at the bottom of the entire system, the coolant exists in the liquid cooling plate, the heat is generated by the battery, transferred to the coolant through the liquid cooling plate, and finally the coolant flows out of the system to take away the heat.

3. The battery liquid cooling temperature prediction method based on thermal resistance network according to claim 1, characterized in that: The process of node division of the entire model in step 2 is as follows: a. In the vertical direction, according to the different physical parameters of the components of the battery liquid cooling heat dissipation model, it is divided into three layers, namely, the battery layer, the liquid cooling plate layer and the coolant layer from top to bottom; the heat is transferred from the battery layer node to the liquid cooling plate layer node, and finally flows into the fluid layer node; b. In the horizontal direction, the flow channel corner plane and the center plane of the liquid cooling plate fin are respectively set as the dividing planes. The number of model nodes in this layer is the number of flow channels * (number of corners + 1).

4. The battery liquid cooling temperature prediction method based on thermal resistance network according to claim 1, characterized in that: The calculation process of various thermal resistance values ​​in step 3 is as follows: The battery thermal resistance, coolant convection resistance and enthalpy change resistance are calculated using heat transfer theory and can be calculated based on: Calculate the thermal resistance value, In the formula, R heat is the thermal resistance of the battery; R conv is the convection thermal resistance of the coolant; δ is the heat transfer thickness; A is the contact area; k is the thermal conductivity of the material; h is the convection heat transfer coefficient; The convective heat transfer coefficient h required to calculate the convective thermal resistance of the coolant needs to be calculated using the following formula: In the formula, k l is the thermal conductivity of the coolant, d is the characteristic length, Nu is the Nusselt number, Since most flows are laminar, there is a laminar inlet effect. If the inlet section length is not exceeded, the calculate, Where Re is the Reynolds number, Pr is the Prandtl number, and L is the flow channel length; As for the thermal resistance value between each node of the coolant, the enthalpy change thermal resistance used in most literature is adopted. Calculate the enthalpy change thermal resistance value through ΔT = qR fluid Calculate the temperatures of the two coolant nodes, Where q is the heat flux from the cold plate node to the fluid node; R fluid is the enthalpy change thermal resistance; m is the mass flow rate; c p is the specific heat capacity of the coolant, the coolant temperature Tr at the inlet is set to a constant low temperature, The thermal resistance of the liquid cooling plate is calculated by CFD simulation, and the accuracy of CFD simulation is verified by experiments. Use CFD software to simulate the liquid cooling plate nodes. The structure style of each liquid cooling plate node is consistent, and only the size is different. In the vertical direction, the upper surface on the outside of the node model and the four inner surfaces are set to different constant temperatures with a temperature difference of ΔT, and the heat flux Q is monitored. Calculate the vertical thermal resistance, which is the thermal resistance of heat flowing from the battery through the liquid cooling plate. In the formula, R l is the thermal resistance of the liquid cooling plate, In the horizontal direction, the opposite sides of the node model are set to different constant temperatures. The above formula is also used to calculate the thermal resistance values ​​in the horizontal directions, that is, the thermal resistance in the process of heat transfer from a liquid cooling plate node to the horizontal direction. Since the structural style of each liquid cooling plate node is consistent, its dimensions are set as variables, and sample points of different sizes are extracted using optimal Latin cube sampling and other forms. If the number of variables is n, 10n+1 sample points need to be selected. An approximate model is established through an appropriate number of sample points to obtain the corresponding values ​​of different sample points, and finally the thermal resistance values ​​of different directions of each size structure of the liquid cooling plate node are obtained.

5. The battery liquid cooling temperature prediction method based on thermal resistance network according to claim 1, characterized in that: The transient temperature calculation process of all nodes in step 5 is as follows. The transient temperature calculation formula of all nodes can be expressed in the following general format for calculation: Where, T i，j，k (t) is the temperature of the point with coordinates (i, j, k) at time t; V i，j，k is the volume of the point; Q i，j，k (t) is the heating power, T s With R s is the temperature of the node where heat transfer occurs and the thermal resistance between the two; R s Including battery thermal resistance R heat 、Thermal resistance of liquid cooling plate R l , Coolant convection thermal resistance R conv and enthalpy change thermal resistance R fluid , m i，j，k is the average mass of the point; The heat generation power is based on the Bernadi heat generation rate model, Q i，j，k =I 2 R n +IT b k rev , Where I is the operating current of the battery, R n is the internal resistance of the battery, T b is the battery temperature, k rev is the entropy thermal coefficient of the battery. The corresponding value is obtained by testing the battery internal resistance at different temperatures and SOC conditions and the entropy thermal coefficient at different SOCs.

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