Joint estimation method for radial and axial heat conductivity of cylindrical battery

Abstract

The invention provides a joint estimation method for radial and axial thermal conductivity of a cylindrical battery, and aims to synchronously estimate the radial and axial thermal conductivity of the battery with high precision by forming a temperature gradient through charge and discharge heat production and forced cooling of the battery and combining a transient thermal simulation and optimization algorithm. The method comprises the following specific steps: performing constant-current discharge on a battery under a natural cooling condition, laying aside, and calculating a natural cooling heat transfer coefficient; forced cooling is applied to one end of the battery, constant-current charging is carried out, and terminal voltage, temperature and environment data are collected; and establishing a transient thermal simulation model of the charging process, inputting time-varying heat production power and boundary conditions, traversing a thermal conductivity combination for simulation, and determining an optimal thermal conductivity estimated value by taking a minimum temperature error quadratic sum as an optimization target. An external heating device is not needed, operation is safe and convenient, the thermal conductivity decoupling identification capacity is enhanced through the axial temperature gradient difference, and low-cost and high-precision nondestructive testing is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of batteries, and in particular to a method for jointly estimating radial and axial thermal conductivities of cylindrical batteries. Background Art

[0002] Cylindrical batteries, represented by 18650, 26650, and 2480 lithium-ion batteries, are widely used in various fields, including electric vehicles and power tools, due to their advantages such as high standardization and consistency, excellent heat dissipation performance, and flexible combination and expansion. To better design and optimize battery pack cooling devices and thermal management strategies, it is necessary to understand the thermal characteristics of cylindrical batteries, such as specific heat capacity and thermal conductivity. While specific heat capacity can be measured or estimated using relatively simple and mature methods, the thermal conductivity of cylindrical batteries is more difficult to obtain conveniently and accurately.

[0003] Since cylindrical batteries have a wound pole core, their radial and axial thermal conductivities differ significantly and need to be measured separately. For example, Chinese patents 201811610644.7 and 201910641508.2 disclose methods for obtaining the radial thermal conductivity of cylindrical batteries, and 202011180603.6 discloses a method for obtaining the axial thermal conductivity of cylindrical batteries. However, current known technologies often have the following disadvantages:

[0004] (1) Some methods require destructive measures on the battery, such as installing a heating rod and a temperature sensor inside the battery. This not only damages the battery, but also affects the internal structure and thermal characteristics of the battery. There are also problems such as high cost, inconvenience in operation, and easy to cause battery leakage;

[0005] (2) Some methods require external heat sources to heat the battery, but cylindrical batteries are generally small and irregular in shape. It is difficult for the external heat source device to form a good fit with the surface of the battery to be heated. There is thermal resistance and it is difficult to heat it safely and evenly as needed.

[0006] Therefore, it is urgent to propose new technical means to complete the joint estimation of the radial and axial thermal conductivities of cylindrical batteries in a low-cost, simple, easy, safe and non-destructive manner. Summary of the Invention

[0007] The present invention provides a low-cost, simple, easy to operate, safe and lossless method for jointly estimating the radial and axial thermal conductivities of cylindrical batteries. The method comprises the following steps:

[0008] S1. Test, perform the following test sequence in a constant room temperature environment:

[0009] Constant current discharge under natural cooling conditions;

[0010] Shelf under natural cooling conditions;

[0011] Implementing constant current charging with forced cooling on the first end face;

[0012] During the test, the terminal voltage, ambient temperature, the temperature of the center points of the two end faces and the temperature of at least one monitoring point on the side are synchronously collected at a fixed sampling frequency;

[0013] S2. Calculation of natural convection coefficient: Based on the data from the shelf phase, the natural convection coefficient is calculated using the formula h = (c·m·ΔT) / (a·S·Δt), where c, m, and S are the battery specific heat capacity, mass, and surface area, respectively; a is the shelf duration; ΔT is the change in the mean battery surface temperature before and after the shelf phase; and Δt is the time-series average of the difference between the surface temperature and the ambient temperature during the shelf phase.

[0014] S3. Thermal simulation modeling: Construct a transient thermal simulation model that includes the following elements:

[0015] 3D battery geometry model and meshing;

[0016] Input parameters: density, specific heat capacity, axial thermal conductivity λa and radial thermal conductivity λr to be estimated;

[0017] Time-varying heat source term: determined by multiplying the difference between the open circuit voltage and the terminal voltage during the charging phase by the charging current;

[0018] Boundary conditions: The first end surface is set to the measured temperature, and the remaining surfaces are set to natural convection boundaries. The convection coefficient is the h value obtained in step S2;

[0019] S4. Parameter identification: solving the thermal conductivity combination that minimizes the objective function in the thermal simulation model through multivariable parameter scanning. The objective function is the sum of the root mean square errors between the actual temperature values ​​and the simulated values ​​at each measuring point.

[0020] Optionally, the constant current discharge rate of the battery in step S1 is between 0.2C and 3C, the battery is in a fully charged state at the initial moment, and the battery terminal voltage is equal to the discharge cut-off voltage at the end moment.

[0021] Optionally, the termination condition for the battery storage in step S1 is that the real-time difference between the battery surface temperature and the room temperature is less than a preset threshold, and the battery surface temperature is the average temperature of each measuring point on the battery surface.

[0022] Optionally, the constant current charging rate of the battery in step S1 is between 0.2C and 3C, and the termination condition is that the battery terminal voltage reaches the charging cut-off voltage.

[0023] Optionally, the forced cooling applied to the first end face in step S1 is any one of directional blowing by a hair dryer, cooling by a liquid cooling plate, and cooling by a thermoelectric cooling device.

[0024] Optionally, during the process of applying forced cooling to the first end surface in step S1, the remaining surfaces of the battery are still maintained in a natural cooling condition of contact with indoor air.

[0025] Optionally, if a blower is used to force cool the first end surface in step S1, the first end surface is separated from the remaining surfaces of the battery by a partition to prevent the airflow from interfering with the cooling of the remaining surfaces.

[0026] Optionally, the simulation model of step S3 further includes the following initial conditions: assigning the battery surface temperature value at the end of the suspension to the entire calculation domain, and taking the battery surface temperature as the average value of the measurements at each measuring point.

[0027] Optionally, the method for obtaining the battery open circuit voltage at each moment in step S3 is:

[0028] The state of charge at each moment is obtained by integrating the battery state of charge at the start of charging and the current over time during the test process;

[0029] The battery open circuit voltage at each moment is obtained according to a preset battery state of charge-open circuit voltage curve.

[0030] Optionally, in step S3, the sum of the root mean square errors between the measured temperature values ​​and the simulated temperature values ​​at each measuring point is the sum of the square errors corresponding to all time steps, wherein the square error sum of the temperature acquisition values ​​and the calculated values ​​at all measuring points at a certain time step is calculated by the following formula:

[0031]

[0032] The above τ is the sum of squares of the temperature acquisition values ​​and calculated values ​​of all measurement points at a certain time step, n is the total number of temperature measurement points, i is the number of each temperature measurement point, α i and β i are the temperature collection value and calculated value of the temperature measurement point numbered i at this time step.

[0033] The beneficial effects of the technical solution of the present invention are introduced below in conjunction with the principle thereof.

[0034] The technical solution of the present invention is mainly divided into an experimental test part and a simulation calculation part.

[0035] The experimental test section does not use the common external heat source heating method used in the prior art. Instead, it relies on the heat generated by the battery during its own charge and discharge process to achieve battery heating. This method is low-cost, easy to operate, heats evenly, and is safe and reliable. First, the battery is discharged and, using the heat generated by the battery itself during the discharge process, is uniformly heated to a high temperature under natural convection conditions. Then, in a non-heating standby state, the battery is allowed to cool naturally. The convection heat transfer coefficient h under natural cooling is estimated based on information such as the battery's specific heat capacity, mass, surface area, standby time, the difference in battery surface temperature before and after standby, and the time-averaged difference between the surface temperature and room temperature during standby. Finally, forced cooling is applied to the first end face of the battery while maintaining the natural cooling state of the other battery surfaces, and constant current charging is performed. Throughout the experimental test process, the terminal voltage, room temperature, the center temperature of the two end faces, and the temperature of at least one side location are synchronously collected at a fixed sampling frequency. In addition to being used to estimate the convection heat transfer coefficient h under natural cooling, this is also used for data comparison in the simulation calculation process.

[0036] In the simulation calculation phase, a transient thermal simulation model for the charging process is established. The battery geometry, density, specific heat capacity, time-varying heat generation power, boundary conditions, and initial conditions are all directly or indirectly known. However, the battery's axial and radial thermal conductivities are unknown, so their estimated values ​​are input into the model's material thermal properties. Multiple combinations of axial and radial thermal conductivity estimates are set and simulated across these different combinations. Using the least squares method, the sum of squared errors between the collected and calculated temperature values ​​at all measurement points at each time step is calculated. The combination with the minimum total sum of squared errors is used as the final thermal conductivity estimate.

[0037] Therefore, the radial and axial thermal conductivity estimation method of cylindrical batteries proposed in the present invention has the following significant advantages over the existing technology:

[0038] (1) The battery's own charging and discharging heat is used to replace external heating devices, which not only eliminates the temperature unevenness and safety hazards introduced by traditional external heat sources, but also greatly reduces equipment costs and operation complexity, achieving safe and economical non-destructive testing;

[0039] (2) Through the thermal boundary design of "natural cooling heat transfer coefficient calculation + single-end forced cooling and determining the first end surface temperature based on the collected results", while simplifying the analysis process, the natural convection heat transfer coefficient is accurately calculated using the shelving stage data. Combined with forced cooling, a significant axial temperature gradient difference is formed, effectively enhancing the decoupling and identification capabilities of radial and axial heat conduction characteristics;

[0040] (3) Innovatively construct a transient thermal simulation model based on time-varying heat generation power and time-varying boundaries, dynamically linking the difference between open-circuit voltage and terminal voltage to internal heat generation, and traversing and screening the optimal thermal conductivity combination through the least squares optimization algorithm, breaking through the limitations of traditional single-direction thermal conductivity measurement and achieving synchronous high-precision estimation of bidirectional thermal conductivity;

[0041] (4) Partitions are used to isolate interference from forced cooling airflow, and local measurement errors are corrected based on the average temperature of multiple measuring points, significantly improving data reliability.

[0042] In summary, this method does not require professional heating / detection equipment, so the testing cost is low; it only requires conventional charging and discharging equipment, so the operation is convenient; the entire process is non-destructive testing, so the safety, reliability and accuracy are high, and the joint estimation of radial and axial thermal conductivity is scientifically and rationally achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 Flowchart of a method for jointly estimating radial and axial thermal conductivities of cylindrical batteries in an embodiment of the present invention.

[0044] Figure 2 This is a grid diagram of the transient thermal simulation model of a cylindrical battery in an embodiment of the present invention.

[0045] Figure 3 Surface distribution cloud diagram at a certain beam moment in a certain calculation example of the transient thermal simulation model of a cylindrical battery in an embodiment of the present invention. DETAILED DESCRIPTION

[0046] The present invention will be further described below with reference to the accompanying drawings and examples.

[0047] like Figure 1 As shown, a joint estimation method of radial and axial thermal conductivity of a cylindrical battery comprises the following steps:

[0048] S1. Test, perform the following test sequence in a constant room temperature environment:

[0049] Constant current discharge under natural cooling conditions;

[0050] Shelf under natural cooling conditions;

[0051] Implementing constant current charging with forced cooling on the first end face;

[0052] During the test, the terminal voltage, ambient temperature, the temperature of the center points of the two end faces and the temperature of at least one monitoring point on the side are synchronously collected at a fixed sampling frequency;

[0053] S2. Calculation of natural convection coefficient: Based on the data from the shelf phase, the natural convection coefficient is calculated using the formula h = (c·m·ΔT) / (a·S·Δt), where c, m, and S are the battery specific heat capacity, mass, and surface area, respectively; a is the shelf duration; ΔT is the change in the mean battery surface temperature before and after the shelf phase; and Δt is the time-series average of the difference between the surface temperature and the ambient temperature during the shelf phase.

[0054] S3. Thermal simulation modeling: Construct a transient thermal simulation model that includes the following elements:

[0055] 3D battery geometry model and meshing;

[0056] Input parameters: density, specific heat capacity, axial thermal conductivity λa and radial thermal conductivity λr to be estimated;

[0057] Time-varying heat source term: determined by multiplying the difference between the open circuit voltage and the terminal voltage during the charging phase by the charging current;

[0058] Boundary conditions: The first end surface is set to the measured temperature, and the remaining surfaces are set to natural convection boundaries. The convection coefficient is the h value obtained in step S2;

[0059] S4. Parameter identification: solving the thermal conductivity combination that minimizes the objective function in the thermal simulation model through multivariable parameter scanning. The objective function is the sum of the root mean square errors between the actual temperature values ​​and the simulated values ​​at each measuring point.

[0060] Specifically, the surface of a cylindrical battery consists of a first end face, a second end face, and a side face. During testing, the temperature measurement points on the battery surface include the center of the first end face, the center of the second end face, and at least one point on the side face. In addition, a temperature sensor is placed in the air at a certain distance from the battery to measure the room temperature in real time.

[0061] In one embodiment, a temperature measuring point is arranged at the center of the side surface of the cylindrical battery in the vertical direction; in another embodiment, a temperature measuring point is arranged at the upper, middle, and lower positions of the side surface in the vertical direction.

[0062] In order to collect the temperature of each measuring point on the surface of the cylindrical battery in real time, contact and / or non-contact measurement methods can be adopted. In one embodiment, infrared measurement is adopted to collect the temperature of multiple measuring points on the surface of the cylindrical battery in real time.

[0063] Specifically, the terminal voltage and temperature are sampled synchronously during the test process, and the sampling time interval may be between 0.1s and 60s.

[0064] Figure 2 A mesh diagram showing a transient thermal simulation model of a cylindrical battery in one embodiment.

[0065] Figure 3The temperature distribution cloud diagram at a certain moment in a certain example corresponding to the transient thermal simulation model of a cylindrical battery in a certain embodiment is shown. Figure 3 The value in represents the temperature in °C.

[0066] Preferably, in the above-mentioned joint estimation method of radial and axial thermal conductivities of cylindrical batteries, the constant current discharge rate of the battery in step S1 is between 0.2C and 3C, the battery is in a fully charged state at the initial moment, and the battery terminal voltage is equal to the discharge cut-off voltage at the end moment.

[0067] Specifically, before step S1 begins, the battery is fully charged according to the charging method specified by the battery manufacturer and left alone for more than 1 hour.

[0068] Preferably, in the above-mentioned joint estimation method of radial and axial thermal conductivity of cylindrical batteries, the end condition of the battery shelving in step 1 is that the real-time difference between the battery surface temperature and the room temperature is less than a preset threshold, and the battery surface temperature is the average temperature of each measuring point on the battery surface.

[0069] Specifically, the preset threshold may be between 0.5°C and 2°C.

[0070] Preferably, in the above-mentioned method for jointly estimating radial and axial thermal conductivities of cylindrical batteries, the constant current charging rate of the battery in step S1 is between 0.2C and 3C, and the termination condition is that the battery terminal voltage reaches the charging cut-off voltage.

[0071] Preferably, in the above-mentioned method for jointly estimating radial and axial thermal conductivities of cylindrical batteries, the forced cooling applied to the first end face in step S1 is any one of directional blowing by a hair dryer, cooling by a liquid cooling plate, and cooling by a thermoelectric cooling device.

[0072] Preferably, in the above-mentioned method for jointly estimating radial and axial thermal conductivities of cylindrical batteries, during the process of applying forced cooling to the first end face in step S1, the remaining surfaces of the battery are still maintained in a natural cooling condition of contact with indoor air.

[0073] Preferably, in the above-mentioned joint estimation method of radial and axial thermal conductivities of cylindrical batteries, if a blower is used in a directional blowing manner to apply forced cooling to the first end face in step S1, the first end face and the remaining surfaces of the battery are separated by a partition to avoid cooling interference of the remaining surfaces caused by the airflow.

[0074] Specifically, when forced cooling is applied to the first end surface by adopting a directional blowing method of a hair dryer, the hair dryer draws room temperature air from the natural environment without heating the air.

[0075] Furthermore, in the above-mentioned joint estimation method of radial and axial thermal conductivities of cylindrical batteries, the simulation model of step S3 also includes the following initial conditions: the battery surface temperature value at the end of the shelving time is assigned to the entire calculation domain, and the battery surface temperature is taken as the measurement average of each measuring point.

[0076] Preferably, in the above-mentioned joint estimation method of radial and axial thermal conductivity of cylindrical batteries, the total duration of the transient thermal simulation model of the charging process in step S3 is equal to the duration of constant current charging in step S1, and its time step is equal to the sampling time interval in step S1.

[0077] Preferably, in the above-mentioned method for jointly estimating radial and axial thermal conductivities of cylindrical batteries, the method for obtaining the open circuit voltage of the battery at each moment in step S3 is:

[0078] The state of charge at each moment is obtained by integrating the battery state of charge at the start of charging and the current over time during the test process;

[0079] The battery open circuit voltage at each moment is obtained according to a preset battery state of charge-open circuit voltage curve.

[0080] Specifically, in the above-mentioned joint estimation method of radial and axial thermal conductivity of cylindrical batteries, in step S3, the sum of the root mean square errors of the measured temperature values ​​and the simulated values ​​at each measuring point is the sum of the square errors corresponding to all time steps, wherein the square error sum of the temperature acquisition values ​​and the calculated values ​​at all measuring points at a certain time step is calculated by the following formula:

[0081]

[0082] The above τ is the sum of squares of the temperature acquisition values ​​and calculated values ​​of all measurement points at a certain time step, n is the total number of temperature measurement points, i is the number of each temperature measurement point, α i and β i are the temperature collection value and calculated value of the temperature measurement point numbered i at this time step.

[0083] Preferably, in step S4, first, the upper and lower limits of the axial and radial thermal conductivities are determined empirically, thereby forming a feasible domain of the combination of axial and radial thermal conductivity estimation values. Then, evenly distributed combination points are set in the feasible domain, and one combination point corresponds to one combination of axial and radial thermal conductivity estimation values. Finally, different combinations of axial and radial thermal conductivity estimation values ​​are traversed for simulation, and the sum of squared errors between the temperature acquisition values ​​and the calculated values ​​at all measuring points at each time step is calculated. The combination corresponding to the minimum total sum of squared errors is used as the final thermal conductivity estimation value.

[0084] Specifically, the transient thermal simulation model for the charging process can be a three-dimensional model or, based on the geometric symmetry of cylindrical batteries, a simplified two-dimensional axisymmetric model. If a three-dimensional model is used, a cylindrical coordinate system is established that includes the axial, radial, and circumferential directions, and the circumferential thermal conductivity is set equal to the axial thermal conductivity based on the structural characteristics of the cylindrical battery. If a two-dimensional axisymmetric model is used, a coordinate system that includes both the axial and radial directions is established.

[0085] Example

[0086] Please refer to Figures 1 to 3 Let's take a look at a more specific embodiment. The cylindrical battery model in this embodiment is LFP18650, the battery diameter and height are 18mm and 65mm respectively, the positive electrode material is lithium iron phosphate, the negative electrode material is graphite, the rated capacity is 1.5Ah, the charging cut-off voltage is 3.65V, and the discharge cut-off voltage is 2V. The test process is in a room temperature environment of 20±1°C and there are no obstructions around the battery to maintain natural air flow around it. In this embodiment, the battery surface has three temperature measuring points on the center of the first end face, the center of the second end face and the side, and the temperature measuring point on the side is equidistant from the two end faces. In this embodiment, the constant current charge and discharge rate of the battery is 1C, that is, the current is 1.5A, and the sampling interval is 1s.

[0087] During the test, the fully charged battery is first discharged at a constant current of 1C to the discharge cut-off voltage, and then left until the real-time difference between the battery surface temperature and the room temperature is less than 0.5°C. Then, forced cooling is applied to the first end face and the battery is charged at a constant current of 1C to the charge cut-off voltage.

[0088] The specific heat capacity of the battery in this embodiment is c = 860 J / (kg·K), the mass m = 0.048 kg, and the surface area S = 4.2×10 -3 m 2 , the shelf time a=2500s, the difference in battery surface temperature before and after shelf time ΔT=8.2K, the average value of the difference between the surface temperature and room temperature during shelf time Δt=3.3K, so the natural cooling heat transfer coefficient h=cmΔT / (aSΔt)=9.8W / (m 2 ·K).

[0089] Based on experience, the upper and lower limits of axial thermal conductivity are determined to be 25 W / (m·K) and 10 W / (m·K), respectively, and the upper and lower limits of radial thermal conductivity are determined to be 2.5 W / (m·K) and 1.0 W / (m·K), respectively. The feasible values ​​for axial thermal conductivity are 10 W / (m·K), 11 W / (m·K), …, and 25 W / (m·K), and the feasible values ​​for radial thermal conductivity are 1.0 W / (m·K), 1.1 W / (m·K), …, and 2.5 W / (m·K). Therefore, the feasible domain of the estimated axial and radial thermal conductivity values ​​forms 16 × 16, or 256, combinations.

[0090] The simulation was then run through each of the 256 combinations of axial and radial thermal conductivity estimates. The sum of squared errors between the collected and calculated temperatures at all measurement points at each time step was calculated. The combination with the minimum total sum of squared errors was used as the final thermal conductivity estimate. The optimal radial and axial thermal conductivity estimates were 1.2 W / (m·K) and 21 W / (m·K), respectively.

[0091] It should be noted that compared to thermal conductivity, the specific heat capacity of cylindrical batteries is easier to obtain. For example, it can be measured using known technical solutions, or it can be calculated by taking a mass-weighted average of the specific heat capacities of the various materials that make up the cylindrical battery based on its material composition. However, current known technologies do not provide a good estimation method for the thermal conductivity of cylindrical batteries. Furthermore, because the radial and axial thermal conductivities of cylindrical batteries are closely related to process control during the manufacturing process, they cannot be accurately estimated using design solutions.

[0092] In this embodiment, the first end surface is the bottom surface of the cylindrical battery, and the second end surface is the top surface of the cylindrical battery. By applying forced cooling to the first end surface to make it form a significantly lower temperature than the side surface, an axial temperature gradient difference of the battery can be formed, which helps to enhance the decoupling and identification capability of radial and axial heat conduction characteristics. Figure 3 As shown, this is the temperature distribution cloud at a certain moment in a certain example corresponding to the transient thermal simulation model of a cylindrical battery. Figure 3 The value in represents the temperature in °C. Figure 3 It can be seen that there is a significant axial temperature gradient from bottom to top.

[0093] The technical solution in this embodiment only requires conventional charging and discharging devices and forced cooling devices. The external heating device in the known solution is replaced by the heat generated by the battery's own charging and discharging, eliminating the temperature unevenness and safety hazards of the traditional external heat source, reducing costs and operational difficulties. The natural cooling heat transfer coefficient calculation and the single-end forced cooling design are combined, the natural convection heat transfer coefficient is inferred using the shelving stage data, and the bidirectional thermal conductivity decoupling identification capability is enhanced by the axial temperature gradient difference. An innovative transient thermal simulation model of time-varying heat generation power and boundary is constructed, dynamically correlating the voltage difference with internal heat generation, and using the least squares algorithm to screen the optimal thermal conductivity combination to achieve simultaneous high-precision estimation of radial and axial thermal conductivities. Therefore, it has the characteristics of low cost, convenient operation, non-destructive testing, high safety and excellent accuracy, and scientifically realizes the simultaneous estimation of radial and axial thermal conductivities of cylindrical batteries.

Claims

1. A method for jointly estimating radial and axial thermal conductivity of a cylindrical battery, wherein the battery has a first end face, a second end face, and a side face, characterized in that include: S1. Test, perform the following test sequence in a constant room temperature environment: Constant current discharge under natural cooling conditions; Shelf under natural cooling conditions; Implementing constant current charging with forced cooling on the first end face; During the test, the terminal voltage, ambient temperature, the temperature of the center points of the two end faces and the temperature of at least one monitoring point on the side are synchronously collected at a fixed sampling frequency; S2. Calculation of natural convection coefficient: Based on the data from the shelf phase, the natural convection coefficient is calculated using the formula h = (c·m·ΔT) / (a·S·Δt), where c, m, and S are the battery specific heat capacity, mass, and surface area, respectively; a is the shelf duration; ΔT is the change in the mean battery surface temperature before and after the shelf phase; and Δt is the time-series average of the difference between the surface temperature and the ambient temperature during the shelf phase. S3. Thermal simulation modeling: Construct a transient thermal simulation model that includes the following elements: 3D battery geometry model and meshing; Input parameters: density, specific heat capacity, axial thermal conductivity λa and radial thermal conductivity λr to be estimated; Time-varying heat source term: determined by multiplying the difference between the open circuit voltage and the terminal voltage during the charging phase by the charging current; Boundary conditions: The first end surface is set to the measured temperature, and the remaining surfaces are set to natural convection boundaries. The convection coefficient is the h value obtained in step S2; S4. Parameter identification: solving the thermal conductivity combination that minimizes the objective function in the thermal simulation model through multivariable parameter scanning. The objective function is the sum of the root mean square errors between the actual temperature values ​​and the simulated values ​​at each measuring point.

2. The method for jointly estimating radial and axial thermal conductivity of cylindrical batteries according to claim 1, characterized in that: In step S1 , the constant current discharge rate of the battery is between 0.2C and 3C. The battery is fully charged at the initial moment, and the battery terminal voltage is equal to the discharge cut-off voltage at the end moment.

3. The method for jointly estimating radial and axial thermal conductivity of cylindrical batteries according to claim 1, characterized in that: The termination condition of the battery storage in step S1 is that the real-time difference between the battery surface temperature and the room temperature is less than a preset threshold, and the battery surface temperature is the average temperature of each measuring point on the battery surface.

4. The method for jointly estimating radial and axial thermal conductivity of cylindrical batteries according to claim 1, characterized in that: The constant current charging rate of the battery in step S1 is between 0.2C and 3C, and the termination condition is that the battery terminal voltage reaches the charging cut-off voltage.

5. The method for jointly estimating radial and axial thermal conductivity of cylindrical batteries according to claim 1, characterized in that: In step S1 , forced cooling is applied to the first end face, which is any one of directional blowing by a hair dryer, cooling by a liquid cooling plate, and cooling by a thermoelectric cooling device.

6. The method for jointly estimating radial and axial thermal conductivities of cylindrical batteries according to claim 1 or 5, characterized in that: During the process of applying forced cooling to the first end surface in step S1, the remaining surfaces of the battery are still kept in a natural cooling condition of contact with indoor air.

7. The method for jointly estimating radial and axial thermal conductivities of cylindrical batteries according to claim 5, characterized in that: If a blower is used to forcefully cool the first end surface in step S1, the first end surface is separated from the remaining surfaces of the battery by a partition to prevent the airflow from interfering with the cooling of the remaining surfaces.

8. The method for jointly estimating radial and axial thermal conductivities of cylindrical batteries according to claim 1, characterized in that: The simulation model of step S3 also includes the following initial conditions: the battery surface temperature value at the end of the suspension is assigned to the entire calculation domain, and the battery surface temperature is the average value of the measurements at each measuring point.

9. The method for jointly estimating radial and axial thermal conductivities of cylindrical batteries according to claim 1, characterized in that: The method for obtaining the battery open circuit voltage at each moment in step S3 is: The state of charge at each moment is obtained by integrating the battery state of charge at the start of charging and the current over time during the test process; The battery open circuit voltage at each moment is obtained according to a preset battery state of charge-open circuit voltage curve.

10. The method for jointly estimating radial and axial thermal conductivities of cylindrical batteries according to claim 1, characterized in that: In step S3, the sum of the root mean square errors between the actual temperature values ​​and the simulated values ​​at each measuring point is the sum of the square errors corresponding to all time steps, where the square error sum of the temperature acquisition values ​​and the calculated values ​​at all measuring points at a certain time step is calculated by the following formula: The above τ is the sum of squares of the temperature acquisition values ​​and calculated values ​​of all measurement points at a certain time step, n is the total number of temperature measurement points, i is the number of each temperature measurement point, α i and β i are the temperature collection value and calculated value of the temperature measurement point numbered i at this time step.

Images