A soft package lithium battery thermal parameter synchronous identification device and method based on local heat flow loading and three-dimensional analytical model

Abstract

The present application relates to a kind of soft package lithium battery thermal parameter synchronous identification device and method based on local heat flow loading and three-dimensional analytical model, method includes: carrying soft package lithium battery thermal parameter synchronous identification device, and the temperature-time curve of thermocouple measuring point in heating process is collected;Establish the three-dimensional transient heat conduction analytical model of battery target area, and set boundary condition;Three-dimensional transient heat conduction analytical model is solved using separation of variables method, and temperature field analytical model is obtained, for calculating the model temperature rise value of each measuring point in different time three-dimensional transient heat conduction analytical model;With the error sum of squares between the experimental measurement temperature rise value of all thermocouple measuring points in different time and model temperature rise value reaches minimum as objective function, by least square fitting the temperature-time curve of all thermocouple measuring points and model temperature rise value, obtain the parameter to be identified.The present application is applicable to the battery thermal characteristic research under different temperature conditions.

Description

Technical Field

[0001] This invention relates to the field of lithium-ion battery thermal characteristic testing technology, and in particular to a device and method for synchronous identification of thermal parameters of soft-pack lithium batteries based on local heat flow loading and a three-dimensional analytical model. Background Technology

[0002] The thermal management performance of lithium-ion batteries is highly dependent on their thermal properties (specific heat capacity, anisotropic thermal conductivity). In existing technologies, destructive methods (such as disassembly and layer-by-layer measurement) can damage the battery and cannot reflect the overall thermal behavior; non-destructive methods mostly use one-dimensional analytical models or two-dimensional numerical models. The former requires multiple experiments to measure the thermal conductivity in different directions, while the latter has high computational cost and numerical discrepancies.

[0003] Therefore, there is an urgent need for a non-destructive testing device and a high-precision analysis method that can simultaneously obtain the anisotropic thermal parameters of a battery through a single local heating experiment. Summary of the Invention

[0004] To address the problems existing in the prior art, the present invention aims to provide a device and method for synchronous identification of thermal parameters of soft-pack lithium batteries based on local heat flow loading and a three-dimensional analytical model. By using local constant heat flow loading, direct heat flow measurement, and multi-point transient temperature acquisition, combined with a three-dimensional analytical thermal model, the specific heat capacity, in-plane thermal conductivity, and through-surface thermal conductivity can be identified simultaneously.

[0005] To achieve the above objectives, the present invention provides the following solution: A device for synchronous identification of thermal parameters of soft-pack lithium battery based on local heat flow loading and three-dimensional analytical model includes: a constant temperature chamber, an extruded polystyrene insulation box is set inside the constant temperature chamber, and a target battery wrapped with a bubble film layer is set inside the extruded polystyrene insulation box. The target battery includes: a stacked soft-pack battery of the target shape, wherein a stacked heating resistor sheet, a thermal pad and a heat flow sensor are sequentially arranged in the central region of the upper surface of the stacked soft-pack battery; Multiple T-shaped thermocouples are attached to different positions on the upper and lower surfaces of the battery according to preset spatial coordinates. At the same time, thermocouple measuring points are set at the edge of the heating zone, along the length of the battery, along the width of the battery, and on the back of the battery.

[0006] To achieve the above objectives, the present invention also provides a method for synchronous identification of thermal parameters of pouch lithium batteries based on local heat flow loading and a three-dimensional analytical model, the method comprising: It is equipped with a device for synchronously identifying the thermal parameters of soft-pack lithium batteries and collects the temperature-time curves of thermocouple measuring points during the heating process; A three-dimensional transient thermal conduction analytical model of the target area of ​​the battery is established, and boundary conditions are set; The three-dimensional transient heat conduction analytical model was solved using the method of separation of variables to obtain the temperature field analytical model, which was used to calculate the model temperature rise value of the three-dimensional transient heat conduction analytical model at each measuring point at different times. The objective function is to minimize the sum of squared errors between the experimentally measured temperature rise values ​​and the model temperature rise values ​​at all thermocouple measuring points at different times. The parameters to be identified are obtained by least-squares fitting of the temperature-time curves of all thermocouple measuring points and the model temperature rise values.

[0007] Optionally, the boundary conditions can be set as follows: boundary conditions of the heated zone, boundary conditions of the non-heated zone, or boundary conditions of the outer surface; The boundary conditions of the heating zone include: ; in, For the battery Thermal conductivity in the direction of For the temperature rise, The constant heat flux density is measured by a heat flux sensor. The equivalent thermal conductivity is The coordinates are the transformed coordinates; The boundary conditions of the unheated zone include: ; in, The coordinate direction; The boundary conditions of the outer surface include: ; in, This represents the global heat transfer coefficient.

[0008] Optionally, obtaining the analytical model of the temperature field includes: The temperature rise function is decomposed into the sum of the products of a spatial characteristic function and a time function using the aforementioned method of separation of variables: ; in, For the first Characteristic functions of the first-order space, For the corresponding time function, These are the spatial coordinates after coordinate transformation. For time; After eigenfunction expansion and Laplace transform, the analytical model of the temperature field is obtained as follows: ; in, Let be a function of the battery's temperature rise. For the normalized characteristic function, The total thermal power of the heating zone, These are the coordinate transformation coefficients. The integral over the heating region, The transformed thermal conductivity is... For the first The time constant of the first mode, It is a natural constant.

[0009] Optionally, the temperature rise function includes: ; ; , , ; in, For battery density, For specific heat capacity, These are the spatial coordinates after coordinate transformation. The equivalent thermal conductivity is For time, These are the coordinate transformation coefficients. For the battery Thermal conductivity in three directions.

[0010] Optionally, the spatial feature function includes: ; in, The total eigenvalue, For spatial characteristic functions, denoted as the order of the eigenvalues.

[0011] Optionally, the total feature value includes: ; in, for eigenvalues ​​of direction for eigenvalues ​​of direction, for eigenvalues ​​of direction, Obtained using boundary conditions.

[0012] Optionally, the method further includes: Determine using the boundary conditions The eigenvalues ​​of the direction include: Determining using boundary conditions of the non-heated zone Eigenvalues ​​of direction: ; ; ; in, The order of the eigenvalues. For half the battery length, The order of the eigenvalues. For battery half-width, The battery is half the thickness. For heat flux density, The coefficients are integral correlation coefficients for the heating zone. For the characteristic function in The value at that location, The eigenvalue is multiplied by the tangent, and it appears in the characteristic equation derived when the heating zone exists under adiabatic boundary conditions. Alternatively, the boundary conditions of the outer surface can be used to determine... Eigenvalues ​​of direction: ; in, Here, hcell-air is the thickness-direction characteristic value, and hcell-air is the global heat transfer coefficient. The equivalent thermal conductivity is It is the tangent function.

[0013] Optionally, the objective function is: ; in, To inversely determine the specific heat capacity, The in-plane thermal conductivity is The thermal conductivity of the penetrating surface, The total number of thermocouples, For thermocouple indexing, The number of time sampling points, The temperature rise value measured in the experiment. The temperature rise value is calculated by the model.

[0014] Optionally, the method further includes: When the three-dimensional transient heat conduction analytical model is in a non-adiabatic condition, the boundary conditions of the outer surface are directly set for the three-dimensional transient heat conduction analytical model, and the conditions are corrected. Eigenvalues ​​of direction: in, These are characteristic values ​​in the thickness direction. The global heat transfer coefficient, The equivalent thermal conductivity is It is the tangent function.

[0015] The beneficial effects of this invention are as follows: This invention directly measures the actual heat flux density entering the battery using a heat flux sensor, thus avoiding the uncertainty of input power caused by heat loss from the heating components themselves.

[0016] This invention uses a three-dimensional analytical model instead of a numerical model, which eliminates mesh errors, has a fast calculation speed, and can simultaneously identify the thermal conductivity and specific heat capacity in both the in-plane and penetrating directions through a single experiment.

[0017] The device of this invention has a simple structure, does not damage the battery, and the battery can still be used normally after testing. It is suitable for the study of thermophysical properties at different temperatures (0-40℃).

[0018] This invention allows for the selection of either adiabatic or convective boundary models to adapt to different adiabatic conditions and improve recognition accuracy. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of the connection of a soft-pack lithium battery thermal parameter synchronous identification device based on local heat flow loading and a three-dimensional analytical model according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the thermocouple distribution on the battery surface according to an embodiment of the present invention; (a) is a top view, and (b) is a bottom view; Figure 3 This is a system block diagram of a soft-pack lithium battery thermal parameter synchronous identification device based on local heat flow loading and a three-dimensional analytical model, according to an embodiment of the present invention. Figure 4 This is an enlarged view of the layered structure of the local heating and heat flow monitoring component according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the temperature-time curves of two typical measuring points on the battery surface obtained by model inversion under the adiabatic boundary conditions at 20°C, according to an embodiment of the present invention. Among them, 1. constant temperature chamber, 2. extruded polystyrene insulation chamber, 3. bubble film layer, 4. stacked soft pack battery, 5. heating resistance sheet, 6. thermal pad, 7. heat flow sensor, 8. heating area, 9-20. thermocouple measuring point, 21. auxiliary thermocouple measuring point. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0023] This embodiment discloses a device for synchronous identification of thermal parameters of soft-pack lithium batteries based on local heat flow loading and a three-dimensional analytical model, including: a constant temperature chamber 1, an extruded polystyrene insulation box 2 set inside the constant temperature chamber 1, and a target battery wrapped with a bubble film layer 3 set inside the extruded polystyrene insulation box 2; the target battery includes: a stacked soft-pack battery 4 of the target shape, with a stacked heating resistance sheet 5, a thermal pad 6 and a heat flow sensor 7 sequentially arranged in the central area of ​​the upper surface of the stacked soft-pack battery 4; multiple T-type thermocouples are attached to different positions on the upper and lower surfaces of the battery according to preset spatial coordinates, and thermocouple measuring points 9-20 are set at the edge of the heating area, along the length direction of the battery, along the width direction of the battery and on the back of the battery.

[0024] Specifically, this embodiment discloses a device for synchronous identification of thermal parameters of a soft-pack lithium battery based on local heat flow loading and a three-dimensional analytical model, including: The soft-pack lithium battery under test: a stacked soft-pack battery 4 with a cuboid shape, including an active material region and tabs; like Figure 4 As shown, the local heating and heat flow monitoring assembly is tightly fitted to the central area of ​​the upper surface of the battery, and includes a heating resistor sheet 5, a thermal pad 6, and a heat flow sensor 7 stacked sequentially from top to bottom; the heating resistor sheet 5 and the heat flow sensor 7 have the same planar dimensions, preferably 30mm×30mm; the thermal pad 6 is used to eliminate contact thermal resistance and make the heat flow uniform. Multi-point temperature acquisition system: includes at least 12 T-type thermocouples, which are attached to different positions on the upper and lower surfaces of the battery according to preset spatial coordinates. Thermocouple measuring points 9-20 are provided near the edge of the heating area, along the length of the battery, along the width of the battery, and on the back of the battery to collect transient temperature rise curves. An auxiliary thermocouple measuring point 21 is used to assist in monitoring whether the heating element is working properly, and does not involve temperature measurement calculations. Thermal insulation and environmental control system: including a bubble film layer 3 enclosing the battery and the local heating and heat flow monitoring components, an extruded polystyrene (XPS) insulation box 2 containing the bubble film layer 3, and a constant temperature box 1 containing the insulation box; the constant temperature box 1 is used to set different initial ambient temperatures (0℃~40℃). Data acquisition and processing unit: connected to the heat flux sensor 7, thermocouple and constant temperature chamber 1, used to record heat flux density, temperature at each measuring point and ambient temperature; and based on the three-dimensional analytical thermal model, to inversely derive the specific heat capacity, in-plane thermal conductivity and through-surface thermal conductivity of the battery through least squares fitting.

[0025] Furthermore, the heating resistor 5 is powered by a DC power supply, and its Joule heat is transferred to the battery surface through the thermal pad 6 and the heat flow sensor 7. The output signal of the heat flow sensor 7 is amplified by the inverting amplifier circuit and recorded by the data acquisition unit to obtain the actual steady-state heat flow density entering the battery, thus avoiding the error caused by calculating the heat flow solely from the electrical power.

[0026] Furthermore, the bubble film layer 3 completely covers all the outer surfaces of the battery, as well as the upper and side surfaces of the local heating and heat flow monitoring components, to reduce heat loss.

[0027] This embodiment also discloses a method for synchronous identification of thermal parameters of pouch lithium batteries based on local heat flow loading and a three-dimensional analytical model. This method is applied to the aforementioned device for synchronous identification of thermal parameters of pouch lithium batteries based on local heat flow loading and a three-dimensional analytical model. The method includes: equipping the device with a synchronous identification device for thermal parameters of pouch lithium batteries and acquiring temperature-time curves of thermocouple measuring points during the heating process; establishing a three-dimensional transient heat conduction analytical model of the target area of ​​the battery and setting boundary conditions; solving the heat conduction control model using the separation of variables method to obtain the temperature field analytical model; and obtaining the parameters to be identified by fitting the temperature-time curves of all thermocouple measuring points with the calculated values ​​of the three-dimensional transient heat conduction analytical model using least squares fitting.

[0028] Specifically, this embodiment also discloses a method for synchronous identification of thermal parameters of soft-pack lithium batteries based on local heat flow loading and a three-dimensional analytical model, including: Step 1: Place the battery under test in a constant temperature chamber and set the initial temperature (a value between 0℃ and 40℃). After the temperature of all parts of the battery is uniform and stable, record the initial open-circuit voltage to monitor the change in state of charge (SOC). After the experiment, measure the open-circuit voltage again. If the change is less than 1mV, it proves that the SOC remained basically unchanged during the experiment, thus eliminating the influence of SOC change on the thermal parameter measurement results.

[0029] Step 2: Apply a constant electrical heating power to the central area of ​​the battery surface using a heating resistor, while a heat flow sensor records the heat flux density entering the battery surface in real time. .

[0030] The heating resistor is powered by a DC power supply, and its Joule thermal power is calculated according to the following formula: in, Heating power (W) The current (A) output by the DC power supply. In this embodiment, the resistance value (Ω) of the heating element at room temperature is given. By adjusting the current (Range 300–380 mA) Different heating powers can be achieved; Step 3: Continuously collect temperature rise data at different locations on the battery surface using multiple thermocouples until the temperature rise of the thermocouple closest to the heating area 8 reaches the predetermined value, then stop heating and record the temperature-time curve throughout the entire heating process.

[0031] Step 4: Establish a three-dimensional transient thermal conduction analytical model of the battery. The specific process is as follows: Simplify the battery into an orthogonal isotropic cuboid, ignore the thickness of the tabs and heating components, and model only one-quarter of the region using symmetry; apply a uniform and constant heat flux density to the heating region 8. All other outer surfaces are set as either adiabatic or convective boundaries (the latter requires the introduction of a global heat transfer coefficient).

[0032] Step 5: Solve the three-dimensional transient heat conduction control equation using the method of separation of variables to obtain the analytical expression of the temperature field. Based on this analytical expression, calculate the temperature rise value of the three-dimensional transient heat conduction analytical model at each measuring point at different times. Use the least squares algorithm to fit the experimental temperature-time curves of all thermocouple measuring points with the model temperature rise value of the three-dimensional transient heat conduction analytical model to derive the specific heat capacity. In-plane thermal conductivity ( ) and thermal conductivity of the penetrating surface ( ).

[0033] Furthermore, when considering non-ideal adiabatic conditions, a convective heat transfer boundary related to the ambient temperature of the constant temperature chamber is applied to all external surfaces of the battery in the model, and the heat transfer coefficient is set to... As an additional calibration parameter.

[0034] In one possible implementation, an NMC622 / graphite pouch cell with a rated capacity of 60Ah and dimensions of 263mm × 93mm × 14mm is used, and the SOC is adjusted to 50%. Figure 1As shown, a heating resistor (30mm×30mm×0.2mm, resistance 9.65Ω), a thermal pad 6 (1mm thickness, thermal conductivity 1.6W / m·K), and a heat flow sensor 7 (30mm×30mm×0.4mm, sensitivity 9.89×10⁻⁶ V·m² / W) are stacked sequentially and attached to the center of the upper surface of the battery. The output of the heat flow sensor is connected to an inverting amplifier circuit (gain -45.9), and the amplified signal is recorded by a multimeter. A DC power supply (0-60V, 0-1.5A) powers the heating resistor.

[0035] like Figure 2 As shown in (a)-(b), 12 T-type thermocouple measuring points are set on the upper and lower surfaces of the battery. Thermocouple measuring points 9-12 are distributed along the length direction, thermocouple measuring points 13-14 are distributed along the width direction, thermocouple measuring points 15-19 are gradually placed away from the heating area, and thermocouple measuring point 20 is located at the farthest corner. Two thermocouples are arranged at corresponding positions on the back. All thermocouples collect temperature at a frequency of 10Hz.

[0036] like Figure 3 As shown, the battery and heating components were tightly wrapped in multi-layer bubble wrap and placed in an insulated box made of 50mm thick XPS board (thermal conductivity 0.034W / m·K). The insulated box was then placed in a constant temperature chamber. The temperatures of the constant temperature chamber were set to 0℃, 10℃, 20℃, 30℃, and 40℃.

[0037] Heating was activated, and the temperatures of each thermocouple and the signals from the heat flux sensor were recorded simultaneously. The experiment was stopped when the temperature rise of thermocouple No. 2, which is closest to the heating zone, reached 5°C. The change in the battery open-circuit voltage before and after the experiment was less than 1mV, indicating that the state of charge (SOC) remained essentially unchanged.

[0038] Model building and parameter identification methods: Based on the above experimental setup, a three-dimensional transient heat conduction analytical model was established, and the thermal parameters of the battery were inverted by least squares fitting.

[0039] (a) The governing equation for heat conduction (temperature rise function): Assume the temperature rise of the battery is ( (assuming an initial uniform temperature), under the assumption of orthogonality and isotropy. satisfy: ; in, For the battery Thermal conductivity in three directions (W / (m·K)), and due to symmetry we have (In-plane thermal conductivity) (Thermal conductivity of the penetrating surface) Battery density (kg / m³). Specific heat capacity (J / (kg·K)).

[0040] (ii) Coordinate transformation: To transform the equation into an isotropic form, we define: ; Introducing new coordinates: ; Then equation (1) is transformed into: ; (III) Boundary conditions: Utilizing symmetry, only a quarter region of the battery ( , , Modeling was performed to obtain a three-dimensional transient heat conduction model. The heating region 8 is located at the center of the upper surface, with an area of... (In this embodiment) The boundary conditions are: Heating zone ( , , ): ; in The constant heat flux density (W / m²) is directly measured by the heat flux sensor.

[0041] Non-heated zone ( (other locations) and all other outer surfaces ( , , ): ; Or in the convective boundary model: ; (iv) Eigenvalue system: Using the method of separation of variables, the temperature rise function is decomposed into the sum of the products of a spatial characteristic function and a time function: The spatial characteristic function satisfies: ; The total eigenvalue It consists of eigenvalues ​​in three directions: ; The eigenvalues ​​in each direction are determined by the boundary conditions: For the adiabatic boundary ( Place ): ; Similarly: .

[0042] For thickness direction( Insulation The conditions in the heating zone are complex and require integration (the final eigenvalues ​​satisfy the following): (12); If a convection boundary is used, then the thickness The directional eigenvalue equation is: ; (V) Analytical Solution of Temperature Field: After characteristic function expansion and Laplace transform, the final analytical expression for temperature rise is: (14); in: The normalized characteristic function; The total thermal power (W) of the heating zone. ; These are the coordinate transformation coefficients. ; The integral over the heating region; The transformed thermal conductivity; For the first The time constant of the first mode.

[0043] In actual calculations, the first 50 eigenvalues ​​are taken ( Sufficient accuracy can be obtained by using this method.

[0044] (vi) Parameter Inversion Objective Function: By fitting the experimental data and model calculations using least squares, the parameters to be identified are... , , (and optional convection coefficient) The objective function is: ; This function is used to find a set of thermal parameters (specific heat capacity). In-plane thermal conductivity Thermal conductivity of the penetrating surface This minimizes the sum of squared errors between the experimentally measured temperature rise values ​​and the model-calculated temperature rise values ​​at all thermocouple measuring points at different times.

[0045] in, cp The specific heat capacity of the battery (J / (kg·K)); is the in-plane thermal conductivity (W / (m·K)). ; The thermal conductivity of the penetrating surface is (W / (m·K)). ; This represents the total number of thermocouples. This represents the number of time sampling points; For thermocouple indexing, Index for a specific time point; For the first A thermocouple in The experimentally measured temperature rise (K) at time 10:00. The value of temperature rise (K) at the corresponding location and time is calculated based on the three-dimensional analytical model.

[0046] In one feasible implementation, if the experiment lasts a long time (more than 8 minutes) and the adiabatic assumption does not hold, then a third-type boundary condition (convective heat transfer) needs to be applied to all external surfaces in the model. In this case, the global heat transfer coefficient needs to be additionally calibrated. And modify the eigenvalue equation in equation (13) to be At the same time, the heating input was changed to total Joule heat power. (Instead of relying solely on heat flux sensor measurements). The heat flux density in the heating zone of the model. Obtained by dividing the total power by the heating area: ,in The area of ​​the heating zone (in this embodiment) The fitting results show that the root mean square error is less than 0.15℃, and the obtained specific heat capacity and thermal conductivity deviate from the adiabatic model by less than 5%.

[0047] Table 1. Battery thermal parameters obtained under different temperatures (convection boundary conditions) Model Fitting Validation (20℃ Adiabatic Boundary Condition): To verify the accuracy of the three-dimensional analytical model and parameter inversion method established in this invention, taking an initial temperature of 20℃ and adiabatic boundary conditions as an example, the thermal parameters corresponding to 20℃ in Table 1 are used ( , , Substituting these values ​​into the model, we obtained the temperature-time curves at two typical measuring points on the battery surface.

[0048] Figure 5 The following two measurement points show the temperature rise data: Measurement point A: Directly above the center of the heating zone ( (i.e., the center of the heating zone on the upper surface of the battery). Measurement point B: Edge of the heating zone ( (i.e., the boundary of the heating zone).

[0049] Calculation conditions: constant heating power corresponding to heat flux density (Corresponding to an input current of 380mA), the heating time continues until the temperature rise at measuring point A is approximately 5℃. The calculated temperature data are shown in Table 2.

[0050] Table 2. Model inversion temperature data under adiabatic boundary conditions at 20℃ From Table 2 and Figure 5 As can be seen, the temperature rise rate at the center measuring point (measuring point A) of the heating zone is significantly higher than that at the edge measuring point (measuring point B), indicating that the heat flow mainly enters the battery along the thickness direction while simultaneously diffusing inwards. The temperature curve calculated by the model is smooth and continuous, consistent with the transient heat conduction law. This result is consistent with the trend of the experimentally measured temperature curve, further verifying the correctness of the model and inversion parameters established in this invention.

[0051] This invention can be widely applied to the thermal characteristic testing of pouch cells and prismatic cells used in electric vehicles, providing key parameters for the design of battery thermal management systems and battery state assessment. The device is low in cost, simple to operate, fast in testing, and does not damage the battery.

[0052] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made to the technical solutions of the present invention by those skilled in the art without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A device for synchronous identification of thermal parameters of a soft-pack lithium battery based on local heat flow loading and a three-dimensional analytical model, characterized in that, include: A constant temperature chamber, in which an extruded polystyrene insulation box is set, and a target battery wrapped with a bubble film layer is set inside the extruded polystyrene insulation box. The target battery includes: a stacked soft-pack battery of the target shape, wherein a stacked heating resistor sheet, a thermal pad and a heat flow sensor are sequentially arranged in the central region of the upper surface of the stacked soft-pack battery; Multiple T-shaped thermocouples are attached to different positions on the upper and lower surfaces of the battery according to preset spatial coordinates. At the same time, thermocouple measuring points are set at the edge of the heating zone, along the length of the battery, along the width of the battery, and on the back of the battery.

2. A method for synchronous identification of thermal parameters of pouch lithium batteries based on local heat flow loading and a three-dimensional analytical model, characterized in that, The method applied to the synchronous identification device for thermal parameters of a soft-pack lithium battery based on local heat flow loading and a three-dimensional analytical model as described in claim 1 includes: It is equipped with a device for synchronously identifying the thermal parameters of soft-pack lithium batteries and collects the temperature-time curves of thermocouple measuring points during the heating process; A three-dimensional transient thermal conduction analytical model of the target area of ​​the battery is established, and boundary conditions are set; The three-dimensional transient heat conduction analytical model was solved using the method of separation of variables to obtain the temperature field analytical model, which was used to calculate the model temperature rise value of the three-dimensional transient heat conduction analytical model at each measuring point at different times. The objective function is to minimize the sum of squared errors between the experimentally measured temperature rise values ​​and the model temperature rise values ​​at all thermocouple measuring points at different times. The parameters to be identified are obtained by least-squares fitting of the temperature-time curves of all thermocouple measuring points and the model temperature rise values.

3. The method for synchronous identification of thermal parameters of soft-pack lithium batteries based on local heat flow loading and a three-dimensional analytical model according to claim 2, characterized in that, The boundary conditions include: boundary conditions for the heated zone, boundary conditions for the non-heated zone, or boundary conditions for the outer surface; The boundary conditions of the heating zone include: ； in, For the battery Thermal conductivity in the direction of For the temperature rise, The constant heat flux density is measured by a heat flux sensor. The equivalent thermal conductivity is The coordinates are the transformed coordinates; The boundary conditions of the unheated zone include: ； in, The coordinate direction; The boundary conditions of the outer surface include: ； in, This represents the global heat transfer coefficient.

4. The method for synchronous identification of thermal parameters of soft-pack lithium batteries based on local heat flow loading and three-dimensional analytical model according to claim 2, characterized in that, The analytical model of the temperature field is obtained by: The temperature rise function is decomposed into the sum of the products of a spatial characteristic function and a time function using the aforementioned method of separation of variables: ； in, For the first Characteristic functions of the first-order space, For the corresponding time function, These are the spatial coordinates after coordinate transformation. For time; After eigenfunction expansion and Laplace transform, the analytical model of the temperature field is obtained as follows: ； in, This is a function of the battery's temperature rise. For the normalized characteristic function, The total thermal power of the heating zone, These are the coordinate transformation coefficients. The integral over the heating region, The transformed thermal conductivity is... For the first The time constant of the first mode, It is a natural constant.

5. The method for synchronous identification of thermal parameters of soft-pack lithium batteries based on local heat flow loading and three-dimensional analytical model according to claim 4, characterized in that, The temperature rise function includes: ； ； ， ， ； in, For battery density, For specific heat capacity, These are the spatial coordinates after coordinate transformation. The equivalent thermal conductivity is For time, These are the coordinate transformation coefficients. For the battery Thermal conductivity in three directions.

6. The method for synchronous identification of thermal parameters of soft-pack lithium batteries based on local heat flow loading and a three-dimensional analytical model according to claim 4, characterized in that, The spatial characteristic functions include: ； in, The total eigenvalue, For spatial characteristic functions, denoted as the order of the eigenvalues.

7. The method for synchronous identification of thermal parameters of soft-pack lithium batteries based on local heat flow loading and a three-dimensional analytical model according to claim 5, characterized in that, The total eigenvalues ​​include: ； in, for eigenvalues ​​of direction for eigenvalues ​​of direction for eigenvalues ​​of direction Obtained using boundary conditions.

8. The method for synchronous identification of thermal parameters of soft-pack lithium batteries based on local heat flow loading and three-dimensional analytical model according to claim 7, characterized in that, The method also includes: Determine using the boundary conditions The eigenvalues ​​of the direction include: Determining using boundary conditions of the non-heated zone Eigenvalues ​​of direction: ； ； ； in, The order of the eigenvalues. For half the battery length, The order of the eigenvalues. For battery half-width, The battery is half the thickness. For heat flux density, The coefficients are integral correlation coefficients for the heating zone. For the characteristic function in The value at that location, The eigenvalue is multiplied by the tangent, and it appears in the characteristic equation derived when the heating zone exists under adiabatic boundary conditions. Alternatively, the boundary conditions of the outer surface can be used to determine... Eigenvalues ​​of direction: ； in, Here, hcell-air is the thickness-direction characteristic value, and hcell-air is the global heat transfer coefficient. The equivalent thermal conductivity is It is the tangent function.

9. The method for synchronous identification of thermal parameters of soft-pack lithium batteries based on local heat flow loading and three-dimensional analytical model according to claim 2, characterized in that, The objective function is: ； in, To inversely determine the specific heat capacity, The in-plane thermal conductivity is The thermal conductivity of the penetrating surface, The total number of thermocouples, For thermocouple indexing, The number of time sampling points, The temperature rise value measured in the experiment. The temperature rise value calculated by the model.

10. The method for synchronous identification of thermal parameters of soft-pack lithium batteries based on local heat flow loading and a three-dimensional analytical model according to claim 2, characterized in that, The method also includes: When the three-dimensional transient heat conduction analytical model is in a non-adiabatic condition, the boundary conditions of the outer surface are directly set for the three-dimensional transient heat conduction analytical model, and the conditions are corrected. Eigenvalues ​​of direction: ； in, These are characteristic values ​​in the thickness direction. The global heat transfer coefficient, The equivalent thermal conductivity is It is the tangent function.

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