A Modeling Method and System for a Thermal Model of a Battery Pack

Abstract

The present invention relates to the technical field of battery data modeling, and particularly relates to a modeling method and system for a battery pack thermal model. The method includes the following steps: determining the positions of battery cells inside the battery pack; identifying the monomer topological structures of the battery cell positions and collecting the monomer electrical temperature parameters of the battery cell positions; calculating the electrical temperature gradient differences of the monomer electrical temperature parameters to generate monomer electrical temperature difference data; through data processing technology and simulation modeling technology, by analyzing the monomer topological structures of the battery cells and combining the monomer electrical temperature parameters to trace the thermal resistance flow path, the present invention constructs a battery pack thermal model and completely presents the thermal state of the battery pack, thereby improving the display accuracy of the battery pack thermal model; based on the characteristics of the thermal imbalance region, targeted heat dissipation optimization of the battery pack is carried out, which can effectively identify and solve the thermal imbalance problem, and significantly improve the thermal management efficiency and performance stability of the battery pack.

Description

Technical Field

[0001] The present invention relates to the technical field of battery data modeling, and particularly to a modeling method and system for a battery pack thermal model. Background Art

[0002] Early battery thermal models mainly adopted lumped parameter models, regarding the battery as a whole and describing the thermal behavior of the battery through simplified assumptions; for example, Hallaj established a one-dimensional lumped parameter lithium-ion battery thermal model to simulate the temperature distribution of enlarged-capacity cylindrical lithium-ion batteries under different cooling conditions; with the in-depth understanding of the internal physical and chemical processes of the battery, the electrochemical-thermal coupling model has gradually become a research hotspot. This model combines the charge, mass, and energy conservation relationships in the electrochemical reaction process with the thermal behavior. However, most existing thermal models adopt lumped parameter models or simplified electrochemical-thermal coupling models, which cannot accurately describe the complex temperature distribution inside the battery pack. In a multi-cell battery pack, it is difficult to accurately reflect the heat transfer and temperature distribution between monomers; and when existing thermal models simulate the operation of the battery pack, it is difficult to identify the thermal imbalance area, ignoring the thermal resistance flow path inside the battery pack, resulting in insufficient model accuracy. Summary of the Invention

[0003] Based on this, it is necessary to provide a modeling method and system for a battery pack thermal model to solve at least one of the above technical problems.

[0004] To achieve the above object, a modeling method for a battery pack thermal model, the method includes the following steps:

[0005] Step S1: Determine the positions of battery cells inside the battery pack; identify the monomer topological structure of the battery cell positions, and collect the monomer electrical and temperature parameters of the battery cell positions;

[0006] Step S2: Calculate the electrical and temperature gradient differences of the monomer electrical and temperature parameters to generate monomer electrical and temperature difference data; use the monomer electrical and temperature difference data to detect the monomer temperature field distribution of the monomer topological structure, and draw a monomer temperature distribution map; identify the monomer thermal resistance flow path of the monomer temperature distribution map; construct an initial thermal model of the battery pack based on the monomer topological structure and the monomer thermal resistance flow path;

[0007] Step S3: Input the battery cell operation parameters into the initial thermal model of the battery pack, and perform an in-group thermal energy state assessment to obtain battery pack thermal energy state data; identify the thermal imbalance area of the battery pack thermal energy state data to generate thermal imbalance area data;

[0008] Step S4: Mark the thermally imbalanced battery cells in the initial thermal model of the battery pack according to the thermal imbalance area data, and perform regional heat dissipation optimization on the thermally imbalanced battery cells to obtain the battery pack thermal model.

[0009] By determining the positions of the battery cells inside the battery pack, the present invention can clarify the specific layout of each cell in the battery pack, providing a basis for subsequent accurate modeling. Identifying the cell topology structure allows for a comprehensive understanding of the connection relationships between the battery cells, and then accurately collecting the electrical temperature parameters of the cells at their positions. This process ensures the accuracy and comprehensiveness of the collected data, providing reliable data support for subsequent operations such as calculating the electrical temperature gradient difference and detecting the temperature field distribution, enabling the subsequent modeling to truly reflect the electrical temperature characteristics inside the battery pack; calculating the electrical temperature gradient difference for the electrical temperature parameters of the cells can generate accurate electrical temperature difference data for the cells, thus clearly presenting the non-uniformity of the electrical temperature distribution between the battery cells. Applying the electrical temperature difference data for the cells to the cell topology structure for detecting the temperature field distribution of the cells and drawing the cell temperature distribution map can visually display the temperature distribution inside the battery pack, helping to discover potential thermal management problems. Identifying the single-cell thermal resistance flow path in the single-cell temperature distribution map can clarify the heat conduction path inside the battery pack, providing a key basis for constructing the initial thermal model of the battery pack. The initial thermal model of the battery pack constructed based on the cell topology structure and the single-cell thermal resistance flow path can relatively accurately reflect the thermal characteristics of the battery pack, providing a basis for subsequent thermal energy state assessment and optimization; inputting the operating parameters of the battery cells into the initial thermal model of the battery pack and conducting an in-pack thermal energy state assessment, the obtained thermal energy state data of the battery pack can comprehensively reflect the thermal energy distribution of the battery pack during actual operation. Identifying the thermal imbalance area for the thermal energy state data of the battery pack and generating the thermal imbalance area data can accurately locate the area with thermal imbalance problems in the battery pack, providing a clear direction for subsequent targeted heat dissipation optimization and helping to improve the overall thermal management performance of the battery pack. Marking the thermally imbalanced battery cells in the initial thermal model of the battery pack according to the thermal imbalance area data and performing regional heat dissipation optimization on the thermally imbalanced battery cells, the finally obtained thermal model of the battery pack can more accurately reflect the actual thermal characteristics of the battery pack. Through this optimization, the temperature in the thermal imbalance area can be effectively reduced, the temperature difference inside the battery pack can be reduced, and the service life and safety of the battery pack can be improved. Therefore, the present invention uses data processing technology and simulation modeling technology, analyzes the cell topology structure, and combines the electrical temperature parameters of the cells to track the thermal resistance flow path to construct a thermal model of the battery pack and fully present the thermal state of the battery pack, thereby improving the display accuracy of the thermal model of the battery pack; targeted battery pack heat dissipation optimization based on the characteristics of the thermal imbalance area can effectively identify and solve the thermal imbalance problem, significantly improving the thermal management efficiency and performance stability of the battery pack.

[0010] Preferably, step S1 includes the following steps:

[0011] Step S11: Use an electromagnetic induction positioning device to perform spatial positioning on each battery cell inside the battery pack, obtain the coordinates of the battery cell in the battery pack, and record them as single-cell coordinate data;

[0012] Step S12: Determine the arrangement order and monomer spacing of battery monomers according to the monomer coordinate data; encode the position information of the battery monomers based on the arrangement order and monomer spacing to obtain the positions of the battery monomers.

[0013] Step S13: Determine the connection relationship between adjacent battery monomers according to the positions of the battery monomers; identify the monomer topology of the battery monomer connection relationship.

[0014] Step S14: Select multiple measurement points in the battery pack, and the measurement points are selected at three fixed positions: the positive electrode, the negative electrode, and the midpoint of the surface of the battery monomer.

[0015] Step S15: Set the parameters of the electrical temperature parameter acquisition device, including the voltage acquisition range of 0 - 5V, the current acquisition range of 0 - 10A, the temperature acquisition range of -20°C to 80°C, and the acquisition accuracies of 0.01V, 0.01A, and 0.1°C respectively.

[0016] Step S16: The first acquisition is carried out at the 1st minute after the battery monomer starts charging and discharging, the second acquisition is carried out at the 5th minute, the third acquisition is carried out at the 10th minute, and the duration of each acquisition is 1 second.

[0017] Step S17: Classify and store the voltage parameters, current parameters, and temperature parameters to form monomer electrical temperature parameters.

[0018] The present invention uses an electromagnetic induction positioning device to spatially locate each battery cell inside a battery pack, capable of accurately obtaining the coordinates of the battery cells within the battery pack and recording them as cell coordinate data, providing an accurate coordinate basis for determining the arrangement order of the battery cells, the cell spacing, and performing position information encoding, ensuring the accuracy and reliability of the position information of the battery cells; determining the arrangement order and cell spacing of the battery cells according to the cell coordinate data, and performing position information encoding on the battery cells based on the arrangement order and cell spacing, can clearly characterize the specific position of each battery cell in the battery pack, clarify the reasonable selection of subsequent measurement points and the precise positioning of electrothermal parameter acquisition; determining the connection relationship between adjacent battery cells according to the position of the battery cells and identifying the monomer topology structure of the battery cell connection relationship can accurately reflect the internal connection layout of the battery pack, clarify the electrical connection and heat transfer relationship between each battery cell, enabling the thermal model to truly reflect the heat conduction and electrochemical behavior inside the battery pack; selecting multiple measurement points in the battery pack, and the measurement points are selected at three fixed positions: the positive electrode, the negative electrode, and the midpoint of the surface of the battery cell. This way of selecting measurement points can comprehensively cover the key parts of the battery cell, ensuring that the collected electrothermal parameters can fully reflect the electrochemical reaction and heat generation of the battery cell during charge and discharge; setting the parameters of the electrothermal parameter acquisition device, including a voltage acquisition range of 0 - 5V, a current acquisition range of 0 - 10A, a temperature acquisition range of -20°C to 80°C, and the acquisition accuracies are 0.01V, 0.01A, and 0.1°C respectively; the first acquisition is carried out at the 1st minute after the battery cell starts charge and discharge, the second acquisition is carried out at the 5th minute, the third acquisition is carried out at the 10th minute, and the duration of each acquisition is 1 second. This acquisition time arrangement can obtain multiple sets of data at the key stage in the initial stage of charge and discharge of the battery cell, capturing the electrothermal characteristic changes of the battery cell at different charge and discharge stages; classifying and storing the voltage parameters, current parameters, and temperature parameters, enabling the required parameters to be quickly and accurately called when constructing the thermal model of the battery pack, improving the efficiency and accuracy of thermal model construction.

[0019] Preferably, the calculation of the electrothermal gradient difference for the monomer electrothermal parameters in step S2 includes:

[0020] Mark the measurement points of the battery cells for the monomer electrothermal parameters, determine the positive and negative electrode regions of the battery cells according to the measurement points of the battery cells, and determine the centroid region on the surface of the battery cells based on the positive and negative electrode regions of the battery cells;

[0021] Calculate the temperature difference of the positive and negative electrode regions of the battery cells to obtain the positive and negative electrode temperature difference value; calculate the voltage difference of the positive and negative electrode regions of the battery cells to obtain the positive and negative electrode voltage difference value; calculate the current difference of the positive and negative electrode regions of the battery cells to obtain the positive and negative electrode current difference value;

[0022] Extract the temperature value, voltage value, and current value of the body-centered region on the surface of the battery cell;

[0023] Compare the temperature difference, voltage difference, and current difference between the positive and negative electrodes with the temperature value, voltage value, and current value of the body-centered region respectively, and arrange them according to the numerical gradient to obtain the electro-thermal gradient difference data.

[0024] The present invention marks the measurement points of the single-cell electro-thermal parameters, which can clarify the specific source positions of each measurement data and provide an accurate spatial positioning basis for subsequent regional division and parameter calculation. Based on the measurement points, the positive and negative electrode regions of the battery are determined, further clarifying the key functional regions inside the battery cell, making the analysis of the electrochemical behavior and thermal characteristics of the battery cell more targeted; calculating the temperature difference, voltage difference, and current difference of the positive and negative electrode regions of the battery can quantify the electro-thermal difference between the positive and negative electrode regions, intuitively reflecting the unevenness of the thermal effect and electrochemical reaction between the positive and negative electrodes during the charge and discharge process of the battery cell; at the same time, extract the temperature value, voltage value, and current value of the body-centered region on the surface of the battery cell; compare the temperature difference, voltage difference, and current difference between the positive and negative electrodes with the temperature value, voltage value, and current value of the body-centered region respectively, and arrange them according to the numerical gradient, which can clearly present the electro-thermal gradient change situation between different regions inside the battery cell; through the electro-thermal gradient difference data, the heat distribution and unevenness of the electrochemical reaction inside the battery cell can be accurately judged.

[0025] Preferably, in step S2, the detection of the single-cell temperature field distribution of the single-cell electro-thermal difference data on the single-cell topology structure and the drawing of the single-cell temperature distribution map include:

[0026] Perform a time series on the single-cell electro-thermal difference data and calculate the electro-thermal change rate of each single-cell battery at different time points to obtain the electro-thermal change rate of the single-cell battery;

[0027] Judge whether the single-cell battery is at the edge or in the middle according to the single-cell topology structure to obtain the position data of the battery;

[0028] Determine the arrangement method of the single-cell topology structure and divide the arrangement method into series batteries and parallel batteries;

[0029] Based on the position data of the battery, calculate the heat dissipation space of the series batteries and parallel batteries for the single-cell battery to obtain the heat dissipation space data of the single-cell battery;

[0030] Determine the local temperature data of the single-cell battery according to the heat dissipation space data of the single-cell battery;

[0031] Perform temperature field statistics on the local temperature data of the single-cell battery and detect the heat distribution data of the temperature field;

[0032] Import the temperature field heat distribution data into a plotting tool, and map the data points to a two-dimensional coordinate system according to the temperature gradient, where the coordinate axes represent the physical position and temperature value of the battery pack respectively, so as to obtain the single-cell temperature distribution map.

[0033] The present invention conducts time series analysis on the single-cell electro-temperature difference data and calculates the electro-temperature change rate, which can accurately capture the dynamic characteristics of the battery cells during charge and discharge, and comprehensively understand the thermal evolution law of the battery under different working conditions; based on the single-cell topological structure to judge the position of the battery, the spatial distribution characteristics of the battery cells in the battery pack can be clarified. There are significant differences in the temperature distribution of the cells at the edge and in the middle due to different heat dissipation conditions; clarifying the arrangement (series or parallel) of the single cells is the basis for understanding the overall thermal behavior of the battery pack. There are differences in the current path and heat distribution between series and parallel batteries; through the calculation of the heat dissipation space, the heat dissipation capacity of each battery cell can be quantified. Edge cells usually have better heat dissipation conditions, while middle cells are limited in heat dissipation; the correlation analysis between the heat dissipation space data and the local temperature data can reveal the actual temperature distribution of the battery cells. Battery cells with a smaller heat dissipation space tend to show higher temperatures; the statistical analysis of the local temperature data and the heat distribution detection can generate the temperature field characteristics of the entire battery pack. By mapping the temperature field data to a two-dimensional coordinate system, the temperature distribution of the battery pack can be intuitively displayed, and the relationship between the temperature gradient and the physical position of the battery can be clearly presented, providing a visual basis for the thermal management optimization of the battery pack.

[0034] Preferably, the single-cell thermal resistance flow path for identifying the single-cell temperature distribution map in step S2 includes:

[0035] Divide the single-cell temperature distribution map into regions according to the temperature range, and set the temperature range of each region to 5°C;

[0036] In each temperature gradient region, measure the temperature difference between adjacent single cells and calculate the ratio of the temperature difference to the distance between adjacent single cells to obtain the temperature-distance difference ratio data;

[0037] If the temperature-distance difference ratio data is greater than 0.3°C / cm, it is preliminarily determined that the single cell corresponding to the temperature-distance difference ratio data is the starting point of the thermal resistance flow path;

[0038] Determine the direction of the thermal resistance flow path based on the starting point of the thermal resistance flow path; if the single cells are connected in parallel, the direction of the thermal resistance flow path is perpendicular to the direction of the current flow; if the single cells are connected in series, the direction of the thermal resistance flow path is along the current flow;

[0039] Compare the temperature differences between the temperature gradient regions to determine the intensity of the thermal resistance flow path. If the temperature difference between the temperature gradient regions is larger, the intensity of the thermal resistance flow path is higher;

[0040] Mark the direction and intensity of the thermal resistance flow path on the monomer temperature distribution map with red lines, and superimpose the marked thermal resistance flow path on the monomer temperature distribution map to form the monomer thermal resistance flow path.

[0041] By dividing the monomer temperature distribution map into regions with a fixed temperature range (5°C), the present invention can clearly identify the distribution of different temperature gradients inside the battery pack; by measuring the temperature difference between adjacent monomer batteries and calculating the temperature-distance difference ratio data, the relationship between temperature change and spatial distance can be quantified. This process provides key parameters for identifying the thermal resistance flow path and accurately locates the obstruction points of heat transfer; setting the threshold value of the temperature-distance difference ratio (0.3°C / cm) as the basis for judging the starting point of the thermal resistance flow path can effectively screen out the key positions where heat transfer is blocked. This judgment criterion provides a clear starting point for the subsequent tracking and analysis of the thermal resistance flow path; determining the direction of the thermal resistance flow path according to the connection mode (series or parallel) of the monomer batteries can accurately reflect the heat transfer path inside the battery pack; by comparing the temperature differences between different temperature gradient regions to determine the intensity of the thermal resistance flow path, the degree of obstruction of heat transfer can be quantified; the greater the temperature difference, the higher the intensity of the thermal resistance flow path; marking the direction and intensity of the thermal resistance flow path on the monomer temperature distribution map in a visual way can intuitively display the heat transfer path and obstruction situation inside the battery pack. This superimposition method provides a comprehensive and intuitive visualization tool for the thermal characteristic analysis of the battery pack, which helps to optimize the thermal management system of the battery pack.

[0042] Preferably, the construction of the initial thermal model of the battery pack based on the monomer topology and the monomer thermal resistance flow path in step S2 includes:

[0043] Convert the monomer topology and the monomer thermal resistance flow path into battery monomer files, and import the battery monomer files into Solidworks software;

[0044] Set the monomer batteries as thermal network nodes according to the monomer topology, and determine the arrangement, connection structure and battery layout of the monomer batteries, and mark the position and size of each monomer battery;

[0045] Set the thermal resistance flow path as the connecting edge between thermal network nodes, and set the thermal resistance parameters between nodes;

[0046] Connect the thermal resistance flow paths of adjacent monomer batteries; for series batteries, connect them in the order of the current direction; for parallel batteries, connect them perpendicular to the parallel current;

[0047] Start the simulation function of Solidworks software to construct the initial thermal model of the battery pack.

[0048] The present invention realizes the digital construction of the thermal model of the battery pack by converting the monomer topology structure and the thermal resistance flow path into battery monomer files and importing them into Solidworks software. The monomer battery is set as a thermal network node, and its arrangement, connection structure, and layout are clarified. At the same time, the position and dimension information are marked, which can accurately reflect the physical structure and electrothermal characteristics of the battery pack; the thermal resistance flow path is set as the connection edge between nodes, and the thermal resistance parameters are configured, which can quantify the heat transfer characteristics inside the battery pack; according to the connection method (series or parallel) of the batteries, the thermal resistance flow path is connected, which can accurately reflect the transfer directions of current and heat, combines the electrical and thermal characteristics of the battery pack, and provides complete path information for the simulation of the thermal model; starting the Solidworks simulation function can perform the simulation analysis of the initial thermal model based on the above-built thermal network model, and can simulate the temperature distribution and heat transfer conditions of the battery pack under different working conditions.

[0049] Preferably, in step S3, inputting the battery monomer operating parameters into the initial thermal model of the battery pack and performing the in-group thermal energy state evaluation includes:

[0050] Input the battery monomer operating parameters into the initial thermal model of the battery pack;

[0051] Set the initial conditions of the battery monomer temperature, and set the initial temperature to 25°C and the coolant temperature to 20°C;

[0052] Set the battery monomer operating mode to intermittent charge and discharge, and set the charge and discharge current to 1A and the charge and discharge voltage to 5V;

[0053] Continuously monitor the temperature values of the middle battery and the two side batteries in the group, and calculate the temperature difference between the temperature value of the middle battery in the group and the temperature values of the two side batteries in the group to obtain the in-group temperature aggregation data;

[0054] Mark the in-group temperature aggregation data for the temperature aggregation space, and divide the temperature aggregation space into temperature aggregation points;

[0055] According to the temperature aggregation points, monitor the thermal energy parameters around the temperature aggregation points with a circle of 0.1 cm radius incrementally to obtain the in-group thermal energy diffusion data;

[0056] Identify the diffusion gradient of the in-group thermal energy diffusion data, and perform the thermal energy state evaluation on the diffusion gradient to obtain the battery pack thermal energy state data.

[0057] By inputting the operating parameters of battery cells into the initial thermal model, the present invention can simulate the dynamic thermal behavior of the battery pack under actual working conditions. Setting the initial temperature conditions (25°C for battery cells and 20°C for the coolant) can provide a clear starting state for the thermal model and ensure that the simulation results are consistent with the actual working conditions. Setting the intermittent charge and discharge mode and specific current and voltage parameters can simulate the working state of the battery pack in actual applications and provide accurate operating conditions for the thermal model. By monitoring the temperature difference between the middle battery and the batteries on both sides, the non-uniformity of the temperature distribution inside the battery pack can be quantified, and the temperature aggregation phenomenon can be identified. Spatially marking the temperature aggregation data and dividing the temperature aggregation points can clarify the specific location of heat aggregation. Conducting incremental monitoring centered on the temperature aggregation points can capture the diffusion process of heat energy in detail. Identifying the gradient and evaluating the state of the heat energy diffusion data can quantify the heat energy distribution and transfer characteristics inside the battery pack, providing a scientific basis for optimizing the thermal management strategy of the battery pack.

[0058] Preferably, the identification of the thermal imbalance region for the thermal energy state data of the battery pack in step S3 includes:

[0059] Calculating the average temperature of the single cells in the battery pack according to the thermal energy state data of the battery pack;

[0060] Statistical analysis is performed on the difference between the temperature of each single cell and the average temperature. When the difference exceeds 2°C, the cell is marked as a temperature anomaly point;

[0061] If there are more than 3 temperature anomaly points in a region and the temperature anomaly points are connected to each other, it is determined that the region is a potential thermal imbalance region;

[0062] Detect the voltage and current of the single cells in the potential thermal imbalance region, and set the voltage threshold to ±10% of the rated voltage of the single cell and the current threshold to ±20% of the rated current;

[0063] When the voltage or current of a single cell exceeds the corresponding threshold, it is recorded as an abnormal state. If a single cell simultaneously exhibits temperature anomaly, voltage anomaly, and current anomaly, it is determined that the single cell has a thermal runaway situation, and the potential thermal imbalance region where the single cell is located is determined as the thermal imbalance region and recorded as the thermal imbalance region data.

[0064] By calculating the average temperature of the single cells within the battery pack, the present invention can provide an overall temperature reference value; by statistically analyzing the difference between the temperature of a single cell and the average temperature and setting a difference threshold (2°C), it can accurately identify the single cells with abnormal temperature and effectively screen out the batteries at risk of thermal runaway; by identifying the number and connection relationship of the abnormal temperature points within the identified area, it can clarify the location of the potential thermal imbalance area, effectively identify the thermal aggregation phenomenon inside the battery pack, and provide a basis for subsequent thermal runaway warning; by detecting the voltage and current of the single cells in the potential thermal imbalance area and setting clear thresholds, it can further evaluate the electrochemical state of the battery and identify the overcharge or over-discharge conditions that may occur during the operation of the battery. By comprehensively evaluating the abnormal conditions of the temperature, voltage, and current of the single cells, it can accurately determine the single cells experiencing thermal runaway and the thermal imbalance area where they are located.

[0065] Preferably, step S4 includes the following steps:

[0066] Step S41: Divide the data of the thermal imbalance area into high-risk areas, medium-risk areas, and normal areas to determine the divided areas of thermal imbalance;

[0067] Step S42: Color-mark the initial thermal model of the battery pack according to the divided areas of thermal imbalance, where red represents high-risk areas, yellow represents medium-risk areas, and green represents normal areas; determine the single cells with thermal imbalance according to the color-mark information of the model;

[0068] Step S43: Increase the cooling air speed and reduce the charge-discharge times for the area of the single cells with thermal imbalance to obtain the optimized parameters for the single cells with thermal imbalance;

[0069] Step S44: Transmit the optimized parameters for the single cells with thermal imbalance back to the initial thermal model of the battery pack to obtain the thermal model of the battery pack.

[0070] The present invention divides the data of the thermal imbalance area into a high-risk area, a medium-risk area, and a normal area, which can clarify the area distribution of different risk levels inside the battery pack, provide a clear area basis for subsequent thermal management strategies, and help optimize the thermal management of the battery pack targeted. According to the areas divided by thermal imbalance, color marking is performed on the initial thermal model of the battery pack, where red represents the high-risk area, yellow represents the medium-risk area, and green represents the normal area. Through color marking, the thermal risk distribution inside the battery pack can be visually displayed, facilitating the rapid identification of thermally imbalanced battery cells. This visualization method provides clear guidance for the formulation of thermal management strategies. Increasing the cooling air speed and reducing the charge and discharge times in the area of the thermally imbalanced battery cell can effectively reduce the temperature in this area and reduce heat accumulation. By adjusting the cooling air speed and the charge and discharge times, the optimized parameters of the thermally imbalanced battery can significantly improve the thermal state of the battery cell and reduce the risk of thermal runaway. Transmitting the optimized parameters of the thermally imbalanced battery back to the initial thermal model of the battery pack to obtain the optimized thermal model of the battery pack. This process can feedback the optimized parameters into the thermal model to further improve the thermal management strategy of the battery pack and ensure that the battery pack maintains a good thermal balance state during operation.

[0071] This specification also provides a modeling system for a battery pack thermal model, which is used to execute the modeling method of the battery pack thermal model as described above. The modeling system for the battery pack thermal model includes:

[0072] A single-cell electrical temperature parameter acquisition module, which is used to determine the positions of the battery cells inside the battery pack; identify the single-cell topological structure of the battery cell positions, and acquire the single-cell electrical temperature parameters of the battery cell positions;

[0073] A battery pack initial thermal model construction module, which is used to calculate the electrical temperature gradient difference of the single-cell electrical temperature parameters to generate single-cell electrical temperature difference data; perform single-cell temperature field distribution detection on the single-cell electrical temperature difference data for the single-cell topological structure, and draw a single-cell temperature distribution map; identify the single-cell thermal resistance flow path of the single-cell temperature distribution map; construct an initial thermal model of the battery pack based on the single-cell topological structure and the single-cell thermal resistance flow path;

[0074] A thermal state area detection module, which is used to input the battery cell operating parameters into the initial thermal model of the battery pack, and perform an in-group thermal energy state evaluation to obtain battery pack thermal energy state data; identify the thermal imbalance area for the battery pack thermal energy state data to generate thermal imbalance area data;

[0075] A thermal imbalance identification and optimization module, which is used to perform thermal imbalance battery cell marking on the initial thermal model of the battery pack according to the thermal imbalance area data, and perform area heat dissipation optimization on the thermally imbalanced battery cells to obtain a thermal model of the battery pack.

[0076] Through the synergistic effects of monomer electric temperature parameter acquisition, initial thermal model construction, thermal state region detection, and thermal imbalance identification optimization, the present invention realizes precise modeling and dynamic optimization of the internal temperature distribution of the battery pack. It can accurately identify the thermal imbalance region and perform targeted heat dissipation optimization, thereby improving the thermal stability of the battery pack, optimizing the thermal management effect of the battery pack, extending the battery life, and ensuring the safety and reliability of the battery pack during operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 It is a schematic flowchart of the steps of a method for modeling a thermal model of a battery pack;

[0078] Figure 2 is Figure 1 a detailed implementation step flowchart of step S1 in

[0079] Figure 3 is Figure 1 a detailed implementation step flowchart of step S4 in

[0080] The realization, functional features, and advantages of the object of the present invention will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0081] The technical method of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0082] In addition, the accompanying drawings are only schematic diagrams of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings represent the same or similar parts, and thus their repeated description will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor methods and / or microcontroller methods.

[0083] It should be understood that although the terms "first", "second", etc. may be used here to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, the first unit can be called the second unit, and similarly the second unit can be called the first unit. The term "and / or" used here includes any and all combinations of one or more of the listed related items.

[0084] To achieve the above object, please refer to Figures 1 to 3 , a modeling method for a thermal model of a battery pack, the method comprising the following steps:

[0085] Step S1: Determine the positions of the battery cells inside the battery pack; identify the monomer topology of the battery cell positions, and collect the monomer electrical temperature parameters of the battery cell positions;

[0086] Step S2: Measure the electrical temperature gradient difference of the monomer electrical temperature parameters to generate monomer electrical temperature difference data; use the monomer electrical temperature difference data to detect the monomer temperature field distribution of the monomer topology, and draw a monomer temperature distribution map; identify the monomer heat resistance flow path of the monomer temperature distribution map; construct an initial thermal model of the battery pack based on the monomer topology and the monomer heat resistance flow path;

[0087] Step S3: Input the battery cell operating parameters into the initial thermal model of the battery pack, and perform an in-group thermal energy state assessment to obtain battery pack thermal energy state data; identify the thermal imbalance area of the battery pack thermal energy state data to generate thermal imbalance area data;

[0088] Step S4: Mark the thermally imbalanced battery cells in the initial thermal model of the battery pack according to the thermal imbalance area data, and perform regional heat dissipation optimization on the thermally imbalanced battery cells to obtain the thermal model of the battery pack.

[0089] By determining the positions of the battery cells inside the battery pack, the present invention can clarify the specific layout of each cell in the battery pack, providing a basis for subsequent accurate modeling. Identifying the cell topology structure allows for a comprehensive understanding of the connection relationships between the battery cells, and then accurately collecting the electrical temperature parameters of the cells at their respective positions. This process ensures the accuracy and comprehensiveness of the collected data, providing reliable data support for subsequent operations such as calculating the electrical temperature gradient differences and detecting the temperature field distribution, enabling the subsequent modeling to truly reflect the electrical temperature characteristics inside the battery pack; calculating the electrical temperature gradient differences for the electrical temperature parameters of the cells can generate accurate electrical temperature difference data for the cells, thus clearly presenting the non-uniformity of the electrical temperature distribution between the battery cells. Applying the electrical temperature difference data for the cells to the cell topology structure for detecting the temperature field distribution of the cells and drawing the cell temperature distribution map can visually display the temperature distribution inside the battery pack, helping to discover potential thermal management problems. Identifying the thermal resistance flow paths of the cells in the cell temperature distribution map can clarify the heat conduction paths within the battery pack, providing a key basis for constructing the initial thermal model of the battery pack. The initial thermal model of the battery pack constructed based on the cell topology structure and the thermal resistance flow paths of the cells can relatively accurately reflect the thermal characteristics of the battery pack, providing a basis for subsequent thermal energy state assessment and optimization; inputting the operating parameters of the battery cells into the initial thermal model of the battery pack and conducting an assessment of the thermal energy state within the pack, the obtained thermal energy state data of the battery pack can comprehensively reflect the thermal energy distribution of the battery pack during actual operation. Identifying the thermal imbalance regions from the thermal energy state data of the battery pack and generating the thermal imbalance region data can accurately locate the regions in the battery pack where there are thermal imbalance problems, providing a clear direction for subsequent targeted heat dissipation optimization and helping to improve the overall thermal management performance of the battery pack. Marking the battery cells with thermal imbalance in the initial thermal model of the battery pack according to the thermal imbalance region data and performing regional heat dissipation optimization on the battery cells with thermal imbalance, the finally obtained thermal model of the battery pack can more accurately reflect the actual thermal characteristics of the battery pack. Through this optimization, the temperature of the thermal imbalance regions can be effectively reduced, the temperature difference inside the battery pack can be decreased, and the service life and safety of the battery pack can be improved. Therefore, the present invention uses data processing technology and simulation modeling technology, analyzes the cell topology structure, and combines the electrical temperature parameters of the cells to trace the thermal resistance flow paths to construct the thermal model of the battery pack and fully present the thermal state of the battery pack, thereby improving the display accuracy of the thermal model of the battery pack; performing targeted heat dissipation optimization on the battery pack based on the characteristics of the thermal imbalance regions can effectively identify and solve the thermal imbalance problems, significantly improving the thermal management efficiency and performance stability of the battery pack.

[0090] In an embodiment of the present invention, referring to Figure 1 as shown, it is a schematic flow chart of the steps of a method for modeling a thermal model of a battery pack according to the present invention. In this example, the method for modeling the thermal model of the battery pack includes the following steps:

[0091] Step S1: Determine the positions of the battery cells inside the battery pack; identify the cell topology of the battery cell positions, and collect the electrical temperature parameters of the battery cell positions.

[0092] In the embodiments of the present invention, first, it is necessary to determine the positions of the battery cells inside the battery pack. By using a high-precision three-dimensional positioning technology, multiple positioning sensors are arranged inside the battery pack, combined with laser scanning or ultrasonic ranging technology, to accurately measure the three-dimensional coordinate positions of each battery cell. The accuracy of the positioning sensors needs to reach the millimeter level to ensure the accuracy of the position information; identify the topology of the battery cells. By using the topology identification technology based on a resistance network, specific identification resistors are connected in series in the battery pack, and the voltage to the ground is collected. Through the change of the voltage difference, combined with the preset mapping relationship between the voltage and the topology, the connection relationship between the battery cells is identified to construct a complete topology; in terms of collecting the electrical temperature parameters of the battery cells, high-precision voltage sensors and temperature sensors are used. The voltage sensor adopts an isolated measurement scheme, with a measurement range of 200V to 1000V, an accuracy class of 0.05%, a linearity of 0.02%, and high stability and accuracy. The temperature sensor uses an NTC thermistor, with a measurement range of -30°C to 100°C and an accuracy of ±0.5°C. The voltage sensor collects the voltage value of each battery cell at a sampling period of 10ms, and the temperature sensor records the temperature data at a sampling period of 100ms. The collected voltage and temperature data are transmitted to the data acquisition system through a CAN bus or an Ethernet communication interface and stored in the system at a storage frequency of 10ms. These data will be used as the basic input parameters for the subsequent thermal model modeling of the battery pack.

[0093] Step S2: Calculate the electrical temperature gradient difference of the electrical temperature parameters of the battery cells to generate electrical temperature difference data of the battery cells; use the electrical temperature difference data of the battery cells to detect the temperature field distribution of the battery cells for the cell topology, and draw a cell temperature distribution map; identify the cell thermal resistance flow path of the cell temperature distribution map; construct an initial thermal model of the battery pack based on the cell topology and the cell thermal resistance flow path.

[0094] In the embodiments of the present invention, the calculation of the temperature gradient difference of the collected single-cell temperature parameters is carried out as follows: For each battery cell in the battery pack, calculate the voltage difference (ΔV) between it and the adjacent cell. The calculation formula for the voltage difference is: ΔV = V_i - V_j, where V_i is the voltage value of the current cell and V_j is the voltage value of the adjacent cell. The accuracy of the voltage sensor is 0.01V, and the sampling frequency is 10ms. Similarly, calculate the temperature difference (ΔT) between each cell and the adjacent cell. The calculation formula for the temperature difference is: ΔT = T_i - T_j, where T_i is the temperature value of the current cell and T_j is the temperature value of the adjacent cell. The accuracy of the temperature sensor is ±0.5°C, and the sampling frequency is 10ms. Store the calculated voltage difference (ΔV) and temperature difference (ΔT) in the data processing system. Next, based on the single-cell temperature difference data and the single-cell topology, perform single-cell temperature field distribution detection and draw a single-cell temperature distribution map; the specific operation is as follows: According to the topology of the battery cells, calculate the heat conduction heat between each cell and other cells. The calculation formula is: Q = (k × ΔT × A) / d, where Q is the heat conduction heat, k is the thermal conductivity of the battery material (the value is 1.2W / (m·K)), ΔT is the temperature difference between the cells, A is the contact area between the cells (the value is 0.01m²), and d is the distance between the cells (the value is 0.005m). Visualize the calculated heat conduction heat data and draw a single-cell temperature distribution map of the battery pack. The temperature distribution map represents the temperature differences of different cells in the form of color gradients, where the high-temperature area is represented by red and the low-temperature area is represented by blue. By analyzing the temperature gradient changes in the single-cell temperature distribution map, identify the single-cell thermal resistance flow path, and the specific operation is as follows: In the temperature distribution map, calculate the temperature gradient of each cell. The calculation formula for the temperature gradient is: ΔT / Δx, where ΔT is the temperature difference and Δx is the distance between the cells. The area with a larger temperature gradient represents the path with a larger thermal resistance; according to the temperature gradient analysis results, determine the heat transfer path within the battery pack. The determination of the thermal resistance flow path is based on the following parameters. The calculation formula for the thermal resistance (R_th) is: R_th = d / (k × A), where d is the distance between the cells (the value is 0.005m), k is the thermal conductivity (the value is 1.2W / (m·K)), and A is the contact area (the value is 0.01m²); by analyzing the heat transfer direction from the high-temperature area to the low-temperature area in the temperature distribution map, determine the thermal resistance flow path; based on the single-cell topology and the single-cell thermal resistance flow path, construct an initial thermal model of the battery pack. The specific operation is as follows: Divide the battery pack into several thermal resistance and heat capacity elements, and establish a thermal circuit model according to the single-cell topology and the thermal resistance flow path.The parameter settings for each component are as follows: Heat capacity (C_th): Calculate the heat capacity based on the material and geometric dimensions of the battery cell. The formula is: C_th = m × c_p, where m is the mass of the single cell (taking a value of 1.5 kg) and c_p is the specific heat capacity (taking a value of 800 J / (kg·K)). Thermal resistance (R_th): Calculate the thermal resistance based on the thermal resistance flow path. The formula is: R_th = d / (k × A), where d is the distance between single cells (taking a value of 0.005 m), k is the thermal conductivity (taking a value of 1.2 W / (m·K)), and A is the contact area (taking a value of 0.01 m²); Set boundary conditions in the thermal model, such as the convective heat transfer coefficient (taking a value of 25 W / (m²·K)) and the ambient temperature (taking a value of 25 °C); Verify the accuracy of the initial thermal model by comparing the actually measured temperature data with the temperature data predicted by the model. If there is a deviation between the model prediction and the actual data, adjust the thermal resistance and heat capacity parameters until the model prediction is consistent with the actual data.

[0095] Step S3: Input the battery cell operating parameters into the initial thermal model of the battery pack, and conduct an assessment of the thermal energy state within the pack to obtain the thermal energy state data of the battery pack; Identify the thermally imbalanced regions from the thermal energy state data of the battery pack to generate thermally imbalanced region data;

[0096] In the embodiments of the present invention, the operating parameters of battery cells are input into the initial thermal model of the battery pack. The operating parameters include data such as the voltage, current, temperature, and charge-discharge rate of each battery cell. These parameters are collected in real time by high-precision sensors and transmitted to the data processing system at a sampling frequency of 10 ms. The voltage and current data are used to calculate the power loss and heat generation rate of the battery, the temperature data is used to evaluate the thermal state of the battery, and the charge-discharge rate is set according to the actual operating conditions of the battery; Next, based on the initial thermal model, the internal thermal energy state of the battery pack is evaluated to obtain the thermal energy state data of the battery pack. The evaluation process uses an electrochemical-thermal coupling model, which comprehensively considers physical processes such as heat generation from electrochemical reactions inside the battery, heat conduction, convective heat transfer, and thermal radiation. Through simulation calculations, thermal energy state data such as the temperature distribution, temperature difference, and heat flow path of the battery pack under different operating conditions are obtained. The specific parameter settings are as follows: The nominal capacity of the battery cell is 2.7 Ah, and the nominal voltage is 3.6 V; In the electrochemical model, the equivalent resistance of the current collector is used to calculate the heat generation of the current collector, and the parameters of the electrode model are input according to the electrode size and material characteristics; In the thermal model, the total heat generation of the battery is calculated by the electrochemical model and coupled to the three-dimensional thermal model to calculate the temperature rise; Subsequently, the thermal imbalance region data of the battery pack thermal energy state data is identified to generate thermal imbalance region data. By analyzing the temperature distribution map and temperature difference data, the region with abnormal temperature rise is identified, that is, the thermal imbalance region. In specific operations, the temperature gradient of each region inside the battery pack is calculated. When the temperature gradient exceeds the set threshold (such as 10 °C / cm), it is determined that this region is a thermal imbalance region. In addition, the region prone to thermal runaway under high-rate charge-discharge conditions can also be identified by comparing the temperature changes at different rates; The identified thermal imbalance region data is stored in the data processing system to provide a basis for subsequent battery pack thermal management strategies.

[0097] Step S4: Mark the battery cells with thermal imbalance in the initial thermal model of the battery pack according to the thermal imbalance region data, and optimize the regional heat dissipation of the battery cells with thermal imbalance to obtain the thermal model of the battery pack.

[0098] In the embodiments of the present invention, first, the initial thermal model of the battery pack is marked with thermally imbalanced battery cells according to the thermally imbalanced area data. The specific operations are as follows: By analyzing the thermally imbalanced area data, determine the positions of the single battery cells with abnormally increased temperatures, and mark these single cells in the initial thermal model; during the marking process, set the temperature threshold of the thermally imbalanced area to be more than 20 °C higher than the ambient temperature as the basis for identifying thermally imbalanced single cells; perform regional heat dissipation optimization on the thermally imbalanced battery cells to obtain an optimized thermal model of the battery pack. The specific technical operations for heat dissipation optimization include the following aspects: For the thermally imbalanced area, adjust the heat dissipation structure of the battery pack. For example, increase the area of the heat sink or change the layout of the heat sink to improve the heat dissipation efficiency. The material of the heat sink is selected as aluminum alloy with a high thermal conductivity, a thickness of 2 mm, and a thermal conductivity of 200 W / (m·K) to ensure efficient heat dissipation. By increasing the distance between single battery cells, improve air circulation and reduce the phenomenon of heat accumulation. According to experimental data, optimizing the battery distance from 5 mm to 10 mm can significantly reduce the temperature of the thermally imbalanced area. For the liquid cooling system, adjust the flow rate of the coolant according to the temperature distribution of the thermally imbalanced area. Experiments show that when the coolant flow rate increases from 5 L / min to 15 L / min, the maximum temperature of the battery pack can be reduced by 4 °C. Therefore, adjust the coolant flow rate to 15 L / min to optimize the heat dissipation effect. Fill high thermal conductivity materials such as graphene or thermal conductive silica gel between the battery cells in the thermally imbalanced area to enhance heat conduction. The thermal conductivity of these materials can reach 1000 W / (m·K), which can effectively reduce the local temperature.

[0099] As an example of the present invention, refer to Figure 2 As shown, in this example, step S1 includes:

[0100] Step S11: Use an electromagnetic induction positioning device to perform spatial positioning on each battery cell inside the battery pack, obtain the coordinates of the battery cell in the battery pack, and record them as single cell coordinate data;

[0101] Step S12: Determine the arrangement order and the distance between single cells according to the single cell coordinate data; perform position information encoding on the battery cells based on the arrangement order and the distance between single cells to obtain the positions of the battery cells;

[0102] Step S13: Determine the connection relationship between adjacent battery cells according to the positions of the battery cells; identify the single cell topological structure of the battery cell connection relationship;

[0103] Step S14: Select multiple measurement points in the battery pack. The measurement points are selected at three fixed positions: the positive electrode, the negative electrode, and the midpoint of the surface of the battery cell;

[0104] Step S15: Set the parameters of the electric temperature parameter acquisition device, including a voltage acquisition range of 0 - 5V, a current acquisition range of 0 - 10A, a temperature acquisition range of -20°C to 80°C, and acquisition accuracies of 0.01V, 0.01A, and 0.1°C respectively;

[0105] Step S16: The first acquisition is carried out at the 1st minute after the battery cell starts charging and discharging, the second acquisition is carried out at the 5th minute, and the third acquisition is carried out at the 10th minute, and the duration of each acquisition is 1 second;

[0106] Step S17: Classify and store the voltage parameters, current parameters, and temperature parameters to form the single - cell electric temperature parameters.

[0107] In the embodiment of the present invention, each battery cell inside the battery pack is spatially located through an electromagnetic induction positioning device, the coordinates of the battery cell within the battery pack are obtained and recorded as single - cell coordinate data; the electromagnetic induction positioning device uses a high - precision three - dimensional positioning sensor with a positioning accuracy of up to 0.1 mm, which can accurately measure the three - dimensional coordinate positions of each battery cell; the arrangement order and the single - cell spacing of the battery cells are determined according to the single - cell coordinate data. By calculating the coordinate difference between adjacent cells, the single - cell spacing is determined, and the position information of the battery cells is encoded based on the arrangement order. The encoding rule is to number the cells according to their arrangement order within the battery pack, and at the same time record the coordinate information of each cell; the connection relationship between adjacent battery cells is determined according to the position of the battery cells, and the single - cell topological structure of the battery cell connection relationship is identified. By analyzing the connection method between cells (such as series or parallel), a single - cell topological structure diagram is constructed to clarify the connection relationship of each cell. Multiple measurement points are selected in the battery pack, and the measurement points are respectively located at three fixed positions: the positive electrode, the negative electrode, and the mid - point on the surface of the battery cell. These measurement points are used for subsequent acquisition of electric temperature parameters to ensure that the thermal state of the battery cell can be comprehensively reflected; set the parameters of the electric temperature parameter acquisition device, with a voltage acquisition range of 0 - 5V, a current acquisition range of 0 - 10A, a temperature acquisition range of -20°C to 80°C, and acquisition accuracies of 0.01V, 0.01A, and 0.1°C respectively; perform the acquisition of electric temperature parameters. The first acquisition is carried out at the 1st minute after the battery cell starts charging and discharging, the second acquisition is carried out at the 5th minute, and the third acquisition is carried out at the 10th minute, and the duration of each acquisition is 1 second. During the acquisition process, the voltage, current, and temperature data are transmitted to the data processing system in real time through high - precision sensors, and the acquired voltage parameters, current parameters, and temperature parameters are classified and stored. The voltage data is stored as a voltage parameter file, the current data is stored as a current parameter file, and the temperature data is stored as a temperature parameter file to form a single - cell electric temperature parameter data set.

[0108] Preferably, the calculation of the electric temperature gradient difference for the single - cell electric temperature parameters in step S2 includes:

[0109] Mark the measurement points of battery cells for the single-cell electrical and temperature parameters, determine the positive and negative electrode regions of the battery based on the measurement points of the battery cells, and determine the centroid region on the surface of the battery cell based on the positive and negative electrode regions of the battery;

[0110] Calculate the temperature difference of the positive and negative electrode regions of the battery to obtain the positive and negative electrode temperature difference value; calculate the voltage difference of the positive and negative electrode regions of the battery to obtain the positive and negative electrode voltage difference value; calculate the current difference of the positive and negative electrode regions of the battery to obtain the positive and negative electrode current difference value;

[0111] Extract the temperature value, voltage value, and current value of the centroid region on the surface of the battery cell;

[0112] Compare the positive and negative electrode temperature difference value, positive and negative electrode voltage difference value, and positive and negative electrode current difference value with the temperature value, voltage value, and current value of the centroid region respectively, and arrange them according to the numerical gradient to obtain the electrical and temperature gradient difference data.

[0113] In the embodiment of the present invention,

[0114] Mark the measurement points of battery cells for the single-cell electrical and temperature parameters, arrange measurement points at the positive electrode, negative electrode, and midpoint position on the surface of the battery cell respectively through high-precision sensors for collecting voltage, current, and temperature data; determine the positive and negative electrode regions of the battery according to the position information of the measurement points, where the positive electrode region corresponds to the positive electrode measurement point and the negative electrode region corresponds to the negative electrode measurement point. Based on the positive and negative electrode regions, further determine the centroid region on the surface of the battery cell, that is, the region where the midpoint measurement point on the surface is located;

[0115] Calculate the temperature difference, voltage difference, and current difference of the positive and negative electrode regions of the battery. The specific operations are as follows: read the temperature values of the positive electrode and negative electrode measurement points respectively, and calculate the positive and negative electrode temperature difference value (ΔT). The formula is: ΔT = T_positive - T_negative; read the voltage values of the positive electrode and negative electrode measurement points, and calculate the positive and negative electrode voltage difference value (ΔV). The formula is: ΔV = V_positive - V_negative; read the current values of the positive electrode and negative electrode measurement points, and calculate the positive and negative electrode current difference value (ΔI). The formula is: ΔI = I_positive - I_negative; extract the temperature value (T_centroid), voltage value (V_centroid), and current value (I_centroid) of the centroid region on the surface of the battery cell, which are collected through the midpoint measurement point on the surface; compare the positive and negative electrode temperature difference value, positive and negative electrode voltage difference value, and positive and negative electrode current difference value with the corresponding parameters of the centroid region respectively, and arrange them according to the numerical gradient to obtain the electrical and temperature gradient difference data. The specific operation is: calculate the ratio of ΔT to T_centroid to obtain the temperature gradient difference. Calculate the ratio of ΔV to V_centroid to obtain the voltage gradient difference. Calculate the ratio of ΔI to I_centroid to obtain the current gradient difference.

[0116] Preferably, in step S2, the detection of the monomer temperature field distribution for the monomer topology using the monomer temperature difference data, and the drawing of the monomer temperature distribution map include:

[0117] Perform a time series on the monomer temperature difference data, and calculate the temperature change rate of each monomer battery at different time points to obtain the temperature change rate of the monomer battery;

[0118] Judge whether the monomer battery is at the edge and the middle position according to the monomer topology to obtain the data of the position where the battery is located;

[0119] Determine the arrangement mode of the monomer topology, and divide the arrangement mode into series batteries and parallel batteries;

[0120] Based on the data of the position where the battery is located, calculate the heat dissipation space of the series batteries and parallel batteries for each monomer battery to obtain the heat dissipation space data of the monomer battery;

[0121] Determine the local temperature data of the monomer according to the heat dissipation space data of the monomer battery;

[0122] Perform temperature field statistics on the local temperature data of the monomer, and detect the heat distribution data of the temperature field;

[0123] Import the heat distribution data of the temperature field into a drawing tool, and map the data points to a two-dimensional coordinate system according to the temperature gradient, where the coordinate axes represent the physical position and temperature value of the battery pack respectively, to obtain the monomer temperature distribution map.

[0124] In the embodiments of the present invention, time series processing is performed on the single-cell temperature difference data, and the temperature change rate of each single cell at different time points is calculated to obtain the temperature change rate of the single cell. In specific operations, the collected single-cell temperature parameters are arranged in chronological order, and the voltage, current, and temperature change rates at adjacent time points are calculated. For example, for the voltage change rate (ΔV / Δt), current change rate (ΔI / Δt), and temperature change rate (ΔT / Δt), the following formulas are used for calculation respectively: ΔV / Δt = (V_t2 - V_t1) / Δt, ΔI / Δt = (I_t2 - I_t1) / Δt, ΔT / Δt = (T_t2 - T_t1) / Δt, where V_t1, I_t1, and T_t1 are the voltage, current, and temperature values at the initial time point, V_t2, I_t2, and T_t2 are the corresponding values at the subsequent time point, and Δt is the time interval; according to the single-cell topology, it is determined whether the single cell is in the edge and middle positions to obtain the data on the position of the battery. By analyzing the arrangement of the battery pack, the position of each single cell in the battery pack is identified. Edge cells are defined as the single cells directly in contact with the external environment, and middle cells are the single cells surrounded by other single cells; further determine the arrangement of the single-cell topology and divide the arrangement into series-connected cells and parallel-connected cells. By analyzing the connection relationship of the battery pack, the series-connected and parallel-connected single cells are identified. The voltages of the series-connected cells are accumulated, and the currents are the same; the currents of the parallel-connected cells are accumulated, and the voltages are the same; based on the data on the position of the battery, the heat dissipation space of the single cells in the series-connected cells and parallel-connected cells is measured to obtain the data on the heat dissipation space of the single cells. For edge cells, the heat dissipation space is larger and the heat dissipation coefficient is higher; for middle cells, the heat dissipation space is limited and the heat dissipation coefficient is lower. The formula for the heat dissipation space is: heat dissipation space = battery surface area × heat dissipation coefficient, where the heat dissipation coefficient is determined according to the battery position and the surrounding environment; according to the data on the heat dissipation space of the single cells, the local temperature data of the single cells are determined. Through the relationship between the heat dissipation space and the temperature, the local temperature of each single cell is calculated. The formula for the local temperature is: local temperature = base temperature + heat dissipation space × heat dissipation coefficient × heat flux density; where the base temperature is the ambient temperature, and the heat flux density is calculated according to the heat generation rate and heat dissipation coefficient of the battery; the local temperature data of the single cells are statistically analyzed for the temperature field, and the heat distribution data of the temperature field are detected. By statistically analyzing the local temperature of each single cell, a temperature field distribution map is drawn to analyze the distribution of heat in the battery pack. The heat distribution data of the temperature field are imported into a drawing tool, and the data points are mapped to a two-dimensional coordinate system according to the temperature gradient, where the coordinate axes represent the physical position and temperature value of the battery pack respectively, so as to obtain the single-cell temperature distribution map. The drawing tool uses professional software (such as MATLAB or ANSYS), and through interpolation and fitting algorithms, the temperature data points are converted into a temperature distribution map to intuitively display the temperature distribution inside the battery pack.

[0125] Particularly importantly, the temperature field statistics of the monomer local temperature data and the detection of the heat distribution data of the temperature field include:

[0126] Dividing the monomer local temperature data into temperature range segments, determining multiple sub-regions of the temperature range segments, and each sub-region contains at least 3 monomer cells;

[0127] Performing weighted average processing on the temperature data in each sub-region, where the weight range of the central region is 0.5 to 0.7, and the weight range of the edge region is 0.3 - 0.5;

[0128] Performing temperature field statistics on the temperature data of each sub-region and calculating the temperature fluctuation coefficient of each sub-region;

[0129] Setting a heat flux sensor in each sub-region, the accuracy range of the heat flux sensor is ±0.005W / m² to ±0.02W / m², collecting the heat inflow and outflow data of each sub-region; calculating the heat balance coefficient of each sub-region;

[0130] Determining the temperature heat field distribution based on the temperature fluctuation coefficient and the heat balance coefficient to obtain the heat distribution data of the temperature field.

[0131] In the embodiments of the present invention, first, the local temperature data of the monomers is divided into temperature range segments, and multiple sub-regions of the temperature range segments are determined. Each sub-region contains at least 3 monomer cells. By analyzing the temperature data of the monomer cells in the battery pack, the temperature range is divided into several segments, for example, each 5°C is a temperature segment, and sub-regions are divided according to the temperature segments. Then, the temperature data in each sub-region is processed by weighted average. The weight range of the central region is 0.5 to 0.7, and the weight range of the edge region is 0.3 to 0.5. The specific operation is as follows: within each sub-region, weights are assigned according to the positions of the battery monomers. The weight of the monomer cell in the central region is taken as 0.6, and the weight of the monomer cell in the edge region is taken as 0.4, and the weighted average temperature is calculated. Then, temperature field statistics are performed on the temperature data of each sub-region, and the temperature fluctuation coefficient of each sub-region is calculated. The temperature fluctuation coefficient is determined by calculating the ratio of the standard deviation of the temperature data in the sub-region to the average temperature. The formula is: temperature fluctuation coefficient = (temperature standard deviation) / (weighted average temperature). Heat flux sensors are set in each sub-region. The accuracy range of the heat flux sensors is from ±0.005 W / m² to ±0.02 W / m², and the heat inflow and outflow data of each sub-region are collected. The heat flux sensors are installed at the boundaries of the sub-regions to monitor the heat flow in real time. According to the collected heat inflow and outflow data, the heat balance coefficient of each sub-region is calculated. The formula is: heat balance coefficient = (heat inflow - heat outflow) / (heat inflow + heat outflow). Finally, based on the temperature fluctuation coefficient and the heat balance coefficient, the temperature thermal field distribution is determined, and the temperature field heat distribution data is obtained. By comprehensively analyzing the temperature fluctuation coefficient and the heat balance coefficient, the thermal field distribution of each sub-region is evaluated, and the result is recorded as the temperature field heat distribution data.

[0132] Preferably, the monomer thermal resistance flow path for identifying the monomer temperature distribution map in step S2 includes:

[0133] The monomer temperature distribution map is divided into regions according to the temperature range, and the temperature range of each region is set to 5°C;

[0134] Within each temperature gradient region, the temperature difference between adjacent monomer cells is measured, and the ratio of the temperature difference to the distance between adjacent monomer cells is calculated to obtain the temperature-distance difference ratio data;

[0135] If the temperature-distance difference ratio data is greater than 0.3°C / cm, it is preliminarily determined that the monomer cell corresponding to the temperature-distance difference ratio data is the starting point of the thermal resistance flow path;

[0136] Based on the starting point of the thermal resistance flow path, the direction of the thermal resistance flow path is determined; if the monomer cells are connected in parallel, the direction of the thermal resistance flow path is the direction perpendicular to the current flow direction; if the monomer cells are connected in series, the direction of the thermal resistance flow path is along the current flow direction;

[0137] The temperature difference between temperature gradient regions is compared to determine the intensity of the thermal resistance flow path. The greater the temperature difference in the temperature gradient region, the higher the intensity of the thermal resistance flow path.

[0138] The direction and intensity of the thermal resistance flow path are marked on the monomer temperature distribution map with red lines, and the marked thermal resistance flow path is superimposed on the monomer temperature distribution map to form the monomer thermal resistance flow path.

[0139] In the embodiment of the present invention, the monomer temperature distribution map is divided into regions according to the temperature range, and the temperature range of each region is set to 5°C. By analyzing the monomer temperature distribution map, the temperature data is divided into several temperature gradient regions at intervals of 5°C. For example, the temperature range from 20°C to 40°C is divided into four regions: 20 - 25°C, 25 - 30°C, 30 - 35°C, and 35 - 40°C; within each temperature gradient region, the temperature difference between adjacent monomer cells is measured, and the ratio of the temperature difference to the distance between adjacent monomer cells is calculated to obtain the temperature - distance difference ratio data. In specific operations, a high-precision temperature sensor is used to measure the temperature difference (ΔT) between adjacent monomer cells, and combined with the actual distance (d) between the monomer cells, the temperature - distance difference ratio (ΔT / d) is calculated, with the unit of °C / cm; if the temperature - distance difference ratio data is greater than 0.3°C / cm, it is preliminarily determined that the monomer cell corresponding to the temperature - distance difference ratio data is the starting point of the thermal resistance flow path. By comparing the calculated temperature - distance difference ratio data, the monomer cells greater than 0.3°C / cm are selected and marked as the starting points of the thermal resistance flow path; the direction of the thermal resistance flow path is determined based on the starting point of the thermal resistance flow path. If the monomer cells are connected in parallel, the direction of the thermal resistance flow path is perpendicular to the current flow direction; if the monomer cells are connected in series, the direction of the thermal resistance flow path is along the current flow direction. By analyzing the topology of the battery pack, the connection method of the monomer cells is identified, and the direction of the thermal resistance flow path is determined accordingly; the temperature difference between temperature gradient regions is compared to determine the intensity of the thermal resistance flow path. The greater the temperature difference in the temperature gradient region, the higher the intensity of the thermal resistance flow path. By calculating the temperature difference between adjacent temperature gradient regions, the intensity of the thermal resistance flow path is evaluated. The greater the temperature difference, the higher the intensity of the thermal resistance flow path; the direction and intensity of the thermal resistance flow path are marked on the monomer temperature distribution map with red lines, and the marked thermal resistance flow path is superimposed on the monomer temperature distribution map to form the monomer thermal resistance flow path. The direction and intensity of the thermal resistance flow path are drawn on the monomer temperature distribution map in the form of red lines using a drawing tool (such as Origin or Tecplot) to complete the visualization of the thermal resistance flow path.

[0140] Preferably, the construction of the initial thermal model of the battery pack based on the monomer topology and the monomer thermal resistance flow path in step S2 includes:

[0141] Convert the monomer topology structure and the monomer thermal resistance flow path into a battery monomer file, and import the battery monomer file into Solidworks software;

[0142] Set the monomer battery as a thermal network node according to the monomer topology structure, determine the arrangement, connection structure and battery layout of the monomer battery, and mark the position and size of each monomer battery;

[0143] Set the thermal resistance flow path as the connecting edge between thermal network nodes, and set the thermal resistance parameters between nodes;

[0144] Connect the thermal resistance flow paths of adjacent monomer batteries; for series batteries, connect them in the order of the current direction; for parallel batteries, the current direction is perpendicular to the parallel current;

[0145] Start the simulation function of Solidworks software to construct an initial thermal model of the battery pack.

[0146] In the embodiments of the present invention, the monomer topology structure and the monomer thermal resistance flow path are converted into a battery monomer file. The specific operation is as follows: According to the monomer topology structure and the thermal resistance flow path of the battery pack, a file including the position, size, connection relationship, and thermal resistance parameters of the monomer battery is generated. This file can adopt a common format supported by Solidworks, such as a STEP or IGES file; Import the battery monomer file into the Solidworks software. Open Solidworks, select "Open" through the "File" menu, browse and select the generated battery monomer file (such as in STEP or IGES format), and click "Open" to complete the import. During the import process, ensure that the correct file format is selected and the appropriate template (such as a part or assembly template) is selected when prompted; According to the monomer topology structure, set the monomer battery as a thermal network node, and determine the arrangement, connection structure, and battery layout of the monomer battery. In Solidworks, through the "Insert Component" function, insert each monomer battery model into the assembly and adjust its position and orientation according to the topology structure. Mark the position and size of each monomer battery to ensure that it is consistent with the actual battery pack design; Set the thermal resistance flow path as the connection edge between the thermal network nodes, and define the heat transfer path by setting the thermal resistance parameters between the nodes. In Solidworks, use the "Assembly" function to add the thermal resistance flow path to between the monomer batteries in the form of a virtual connection part, and specify the thermal resistance parameters for each connection edge; Connect the thermal resistance flow paths of adjacent monomer batteries. For series-connected batteries, connect them in sequence according to the current direction; for parallel-connected batteries, connect them perpendicular to the parallel current direction. In Solidworks, ensure that it conforms to the series or parallel connection rules by adjusting the direction and position of the connection edge; Start the simulation function of the Solidworks software to construct the initial thermal model of the battery pack. Enter the FlowSimulation module of Solidworks, set the simulation parameters, including the initial temperature of the battery pack, the ambient temperature, the heat source power, the material properties (such as the thermal conductivity, specific heat capacity), and the boundary conditions. Run the simulation, observe the temperature distribution and heat transfer path of the battery pack, generate a monomer temperature distribution map, and mark the direction and intensity of the thermal resistance flow path.

[0147] Preferably, in step S3, inputting the battery monomer operating parameters into the initial thermal model of the battery pack and performing the in-group thermal energy state evaluation includes:

[0148] Input the battery monomer operating parameters into the initial thermal model of the battery pack;

[0149] Set the initial condition of the battery monomer temperature, and set the initial temperature to 25°C and the coolant temperature to 20°C;

[0150] Set the operating mode of the battery cell to intermittent charge and discharge, and set the charge and discharge current to 1 A and the charge and discharge voltage to 5 V;

[0151] Continuously monitor the temperature values of the middle battery and the two side batteries in the group, and calculate the temperature difference between the temperature value of the middle battery and the temperature values of the two side batteries in the group to obtain the temperature aggregation data in the group;

[0152] Perform temperature aggregation space marking on the temperature aggregation data in the group, and divide the temperature aggregation space into temperature aggregation points;

[0153] According to the temperature aggregation points, incrementally monitor the thermal energy parameters around the temperature aggregation points with a circle radius of 0.1 cm to obtain the thermal energy diffusion data in the group;

[0154] Perform diffusion gradient identification on the thermal energy diffusion data in the group, and perform thermal energy state evaluation on the diffusion gradient to obtain the thermal energy state data of the battery pack.

[0155] In the embodiment of the present invention, the operating parameters of the battery cell are input into the initial thermal model of the battery pack. The operating parameters include charge and discharge current, voltage, initial temperature, etc. The specific operation is as follows: In the simulation software (such as ANSYS or Solidworks Simulation), set the initial temperature of the battery cell to 25 °C and the coolant temperature to 20 °C. At the same time, set the operating mode of the battery cell to intermittent charge and discharge, the charge and discharge current to 1 A, and the charge and discharge voltage to 5 V; Next, continuously monitor the temperature values of the middle battery and the two side batteries in the group. By setting temperature monitoring points in the simulation model, the temperature changes of the middle battery and the two side batteries are recorded in real time. Calculate the temperature difference between the temperature value of the middle battery and the temperature values of the two side batteries in the group to obtain the temperature aggregation data in the group. The specific operation is as follows: In the simulation software, use the temperature field analysis function to calculate the temperature difference between the middle battery and the two side batteries; Perform temperature aggregation space marking on the temperature aggregation data in the group, and divide the temperature aggregation space into temperature aggregation points. Through the temperature field cloud map analysis, identify the temperature aggregation area, and incrementally monitor the thermal energy parameters around the temperature aggregation points with a circle radius of 0.1 cm; Further, perform diffusion gradient identification on the thermal energy diffusion data in the group, and perform thermal energy state evaluation on the diffusion gradient to obtain the thermal energy state data of the battery pack. The specific operation is as follows: In the simulation software, use the heat flow analysis function to calculate the thermal energy diffusion gradient and evaluate the thermal energy state of the battery pack. By analyzing the distribution law of the temperature field and the temperature difference change, determine whether the thermal energy state of the battery pack is within a reasonable range.

[0156] Preferably, the identification of the thermal imbalance area for the thermal energy state data of the battery pack in step S3 includes:

[0157] Calculate the average temperature of the single battery in the battery pack according to the thermal energy state data of the battery pack;

[0158] Statistically analyze the temperature difference between each single cell temperature and the average temperature. When the difference exceeds 2°C, mark this cell as a temperature anomaly point;

[0159] If there are more than 3 temperature anomaly points in a region and these temperature anomaly points are connected to each other, determine this region as a potential thermal imbalance region;

[0160] Detect the voltage and current of the single cells in the potential thermal imbalance region, and set the voltage threshold to ±10% of the rated voltage of the single cell, and the current threshold to ±20% of the rated current;

[0161] When the voltage or current of a single cell exceeds the corresponding threshold, record it as an abnormal state; if a single cell simultaneously exhibits temperature anomaly, voltage anomaly, and current anomaly, determine that this single cell has a thermal runaway situation, and determine the potential thermal imbalance region where this single cell is located as a thermal imbalance region, and record it as thermal imbalance region data.

[0162] In the embodiment of the present invention, the average temperature of the single cells in the battery pack is calculated based on the thermal energy state data of the battery pack. By collecting the temperature data of all single cells in the battery pack and calculating their arithmetic mean, the average temperature of the battery pack is obtained. The specific operation is as follows: add up the temperature values of all single cells and divide by the total number of single cells; then, statistically analyze the difference between the temperature of each single cell and the average temperature. When the difference exceeds 2°C, mark this cell as a temperature anomaly point. The specific operation is as follows: calculate the difference between the temperature of each single cell and the average temperature one by one, and screen out the single cells with a difference greater than 2°C; if there are more than 3 temperature anomaly points in a region and these temperature anomaly points are connected to each other, determine this region as a potential thermal imbalance region. Identify the region that meets the conditions by analyzing the spatial distribution of the temperature anomaly points; detect the voltage and current of the single cells in the potential thermal imbalance region. Set the voltage threshold to ±10% of the rated voltage of the single cell, and the current threshold to ±20% of the rated current. The specific operation is as follows: use high-precision voltage and current sensors (such as INA226) to measure the voltage and current of the single cells in the potential thermal imbalance region respectively, and compare them with the set thresholds. For example, for a battery with a rated voltage of 3.7V and a rated current of 1A, the voltage threshold range is 3.33V to 4.07V, and the current threshold range is 0.8A to 1.2A; when the voltage or current of a single cell exceeds the corresponding threshold, record it as an abnormal state; if a single cell simultaneously exhibits temperature anomaly, voltage anomaly, and current anomaly, determine that this single cell has a thermal runaway situation, and determine the potential thermal imbalance region where this single cell is located as a thermal imbalance region, and record it as thermal imbalance region data.

[0163] As an example of the present invention, refer to Figure 3 As shown, in this example, step S4 includes:

[0164] Step S41: Divide the data of the thermal imbalance area into a high-risk area, a medium-risk area, and a normal area to determine the thermal imbalance division area;

[0165] Step S42: Perform color marking on the initial thermal model of the battery pack according to the thermal imbalance division area, where red represents the high-risk area, yellow represents the medium-risk area, and green represents the normal area; determine the thermal imbalance battery cells according to the model color marking information;

[0166] Step S43: Increase the cooling air speed in the area of the thermal imbalance battery cells and reduce the charge and discharge times to obtain the optimized parameters of the thermal imbalance battery cells;

[0167] Step S44: Transmit the optimized parameters of the thermal imbalance battery cells back to the initial thermal model of the battery pack to obtain the thermal model of the battery pack.

[0168] In the embodiments of the present invention, the data of the thermal imbalance region is divided into a high-risk region, a medium-risk region, and a normal region to determine the divided regions of the thermal imbalance. The specific operation is as follows: According to the temperature anomaly degree of the single cells in the battery pack, the anomalies of the voltage and current, and in combination with a preset threshold, the thermal imbalance region is classified. For example, when the temperature anomaly of the single cell exceeds 5°C, the voltage anomaly exceeds ±15% of the rated voltage, or the current anomaly exceeds ±30% of the rated current, it is classified as a high-risk region; when the temperature anomaly is between 3°C and 5°C, the voltage anomaly is between ±10% and ±15% of the rated voltage, or the current anomaly is between ±20% and ±30% of the rated current, it is classified as a medium-risk region; in other cases, it is classified as a normal region; The initial thermal model of the battery pack is color-coded according to the divided regions of the thermal imbalance, where red represents the high-risk region, yellow represents the medium-risk region, and green represents the normal region. The specific operation is as follows: In the thermal model of the battery pack, according to the division result of each region, a color-coding tool is used to mark the corresponding region. Through the color mapping function of visualization software (such as ANSYS or Solidworks Simulation), the high-risk region is marked as red, the medium-risk region is marked as yellow, and the normal region is marked as green. Determine the single cells with thermal imbalance according to the color marking information of the model, that is, the single cells in the regions marked as red or yellow; Increase the cooling air speed and reduce the charge and discharge times for the regions of the single cells with thermal imbalance to obtain the optimized parameters for the single cells with thermal imbalance. The specific operation is as follows: For the regions of the single cells marked as having thermal imbalance, adjust the parameters of the cooling system, and increase the cooling air speed from the initial value (such as 5 m / s) to the optimized value (such as 8 m / s). At the same time, adjust the charge and discharge strategy of the battery, and reduce the charge and discharge times from the initial set value (such as 5 times per day) to the optimized value (such as 3 times per day). These adjustments of the optimized parameters are aimed at reducing the temperature of the thermal imbalance region and reducing the heat generation of the battery during the charge and discharge process, thereby alleviating the thermal imbalance phenomenon; Transmit the optimized parameters of the single cells with thermal imbalance back to the initial thermal model of the battery pack to obtain the thermal model of the battery pack. The specific operation is as follows: Input the optimized parameters such as the adjusted cooling air speed and charge and discharge times into the thermal model of the battery pack, and update the relevant parameter settings of the model. By re-running the thermal model simulation, verify the effectiveness of the optimized parameters to ensure that the model can accurately reflect the thermal state of the battery pack after optimization.

[0169] Particularly importantly, step S43 includes the following steps:

[0170] Step S431: Judge the regional imbalance state of the single cells with thermal imbalance to obtain the imbalance state data;

[0171] Step S432: Quantify the urgency of the imbalance state data to generate the urgency data of the imbalance;

[0172] Step S433: Perform a single-cell imbalance priority ranking on the thermally imbalanced battery cells based on the imbalance urgency degree data to obtain single-cell imbalance priority data;

[0173] Step S434: Determine the regional cooling wind speed parameter according to the imbalance urgency degree data, and determine the charge and discharge times according to the imbalance state data;

[0174] Step S435: Match the cooling measures for the thermally imbalanced battery cells through the single-cell imbalance priority data, and optimize the thermal imbalance of the thermally imbalanced battery cells based on the regional cooling wind speed parameter and the charge and discharge times to obtain the optimized parameters of the thermally imbalanced battery cells.

[0175] In the embodiments of the present invention, the regional imbalance state of the thermally imbalanced battery cell is judged to obtain the imbalance state data. By monitoring the changes in the temperature, voltage, and current of the battery cell and combining with the preset thresholds, its imbalance state is judged. For example, when the temperature of the single battery cell exceeds 5°C abnormally, the voltage exceeds ±15% of the rated voltage abnormally, or the current exceeds ±30% of the rated current abnormally, it is determined that the battery cell is in a high imbalance state; when the abnormal temperature is between 3°C and 5°C, the abnormal voltage is between ±10% and ±15% of the rated voltage, or the abnormal current is between ±20% and ±30% of the rated current, it is determined to be in a medium imbalance state; in other cases, it is a low imbalance state; the imbalance state data is quantified for the urgency level to generate the imbalance urgency data. According to the severity of the imbalance state, the urgency level is divided into three levels: high, medium, and low. The specific quantification standard is: the urgency level corresponding to the high imbalance state is high (the value is 3), the urgency level corresponding to the medium imbalance state is medium (the value is 2), and the urgency level corresponding to the low imbalance state is low (the value is 1). By calculating the urgency level value of each battery cell, the imbalance urgency data is obtained. Based on the imbalance urgency data, the single-cell imbalance priority of the thermally imbalanced battery cells is sorted to obtain the single-cell imbalance priority data. The battery cells are sorted according to the urgency level value, and the higher the urgency level value, the higher the priority. For example, the battery cell with an urgency level of 3 has the highest priority, the battery cell with an urgency level of 2 is the second, and the battery cell with an urgency level of 1 is the lowest. The sorting result is used as the single-cell imbalance priority data for subsequent allocation of optimization measures. According to the imbalance urgency data, the regional cooling wind speed parameter is determined, and the charge and discharge times are determined according to the imbalance state data. For the battery cells in the high imbalance state, the cooling wind speed is increased to 8 m / s, and the charge and discharge times are reduced to 2 times per day; for the battery cells in the medium imbalance state, the cooling wind speed is increased to 6 m / s, and the charge and discharge times are reduced to 3 times per day; for the battery cells in the low imbalance state, the cooling wind speed is increased to 4 m / s, and the charge and discharge times remain unchanged. The cooling measures are matched for the thermally imbalanced battery cells through the single-cell imbalance priority data, and the thermal imbalance of the thermally imbalanced battery cells is optimized based on the regional cooling wind speed parameter and the charge and discharge times to obtain the thermal imbalance optimization parameters of the battery cells. According to the priority sorting result, the cooling measures are implemented for the battery cells with high priority in sequence, including adjusting the cooling wind speed and the charge and discharge strategy. The optimized parameters are used as the thermal imbalance optimization parameters of the battery cells for subsequent thermal management of the battery pack.

[0176] This specification also provides a modeling system for a battery pack thermal model, which is used to execute the modeling method of the battery pack thermal model as described above. The modeling system for the battery pack thermal model includes:

[0177] A single-cell electrothermal parameter acquisition module, which is used to determine the positions of the battery cells inside the battery pack; identify the single-cell topology of the battery cell positions, and acquire the single-cell electrothermal parameters of the battery cell positions;

[0178] The battery pack initial thermal model construction module is used to measure the temperature gradient difference of the single-cell temperature parameters to generate single-cell temperature difference data; use the single-cell temperature difference data to detect the single-cell temperature field distribution of the single-cell topology structure and draw a single-cell temperature distribution map; identify the single-cell thermal resistance flow path of the single-cell temperature distribution map; construct the battery pack initial thermal model based on the single-cell topology structure and the single-cell thermal resistance flow path;

[0179] The thermal state region detection module is used to input the battery cell operating parameters into the battery pack initial thermal model and perform the internal energy state evaluation of the battery pack to obtain the battery pack internal energy state data; identify the thermal imbalance region of the battery pack internal energy state data to generate thermal imbalance region data;

[0180] The thermal imbalance identification and optimization module is used to mark the thermally imbalanced battery cells of the battery pack initial thermal model according to the thermal imbalance region data and perform regional heat dissipation optimization on the thermally imbalanced battery cells to obtain the battery pack thermal model.

[0181] Through the synergistic effect of single-cell temperature parameter acquisition, initial thermal model construction, thermal state region detection, and thermal imbalance identification and optimization, the present invention realizes the accurate modeling and dynamic optimization of the internal temperature distribution of the battery pack. It can accurately identify the thermal imbalance region and perform targeted heat dissipation optimization, thereby improving the thermal stability of the battery pack, optimizing the thermal management effect of the battery pack, extending the battery life, and ensuring the safety and reliability of the battery pack during operation.

[0182] Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, it is intended to cover all changes falling within the meaning and scope of the equivalent elements of the application documents within the present invention.

[0183] The above are only the specific embodiments of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for modeling a battery pack thermal model, characterized in that: The following steps are involved: Step S1: determining the battery cell position inside the battery pack; identifying the cell topology structure of the battery cell position, and collecting the cell electrical temperature parameters of the battery cell position, wherein the cell electrical temperature parameters include voltage parameters, current parameters and temperature parameters; Step S2: Calculate the electric temperature gradient difference of the electric temperature parameters of the cells to generate electric temperature difference data of the cells; perform a temperature field distribution detection on the cell topology structure of the cells using the electric temperature difference data of the cells, and draw a temperature distribution diagram of the cells; identify the thermal resistance flow path of the cells in the temperature distribution diagram of the cells; and construct an initial thermal model of the battery pack based on the cell topology structure and the thermal resistance flow path of the cells; Step S3: inputting the battery cell operating parameters into the initial thermal model of the battery pack, and evaluating the thermal energy state within the pack to obtain the thermal energy state data of the battery pack; Identify thermal imbalance areas on the thermal energy status data of the battery pack and generate thermal imbalance area data; The identifying of thermal imbalance regions of the battery pack thermal energy status data includes: Calculate the average temperature of the single cells in the battery pack according to the thermal energy status data of the battery pack; The difference between the temperature of each single battery and the average temperature is counted. When the difference exceeds 2°C, the battery is marked as a temperature abnormal point. If there are more than three temperature anomaly points in an area, and the temperature anomaly points are connected to each other, the area is determined to be a potential thermal imbalance area; Conduct voltage and current detection on cells in potential thermal imbalance areas, and set the voltage threshold to ±10% of the rated voltage of the cell, and the current threshold to ±20% of the rated current; When the voltage or current of a single battery exceeds the corresponding threshold, it is recorded as an abnormal state; if a single battery has abnormal temperature, abnormal voltage and abnormal current at the same time, it is determined that the battery cell has thermal runaway, and the potential thermal imbalance area where the battery cell is located is determined as the thermal imbalance area, and recorded as thermal imbalance area data; Step S4: marking the thermally unbalanced battery cells of the initial thermal model of the battery pack according to the thermally unbalanced region data, and performing regional heat dissipation optimization on the thermally unbalanced battery cells to obtain a thermal model of the battery pack.

2. The method for modeling a battery pack thermal model according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: spatially locating each battery cell inside the battery pack by using an electromagnetic induction positioning device, obtaining the coordinates of the battery cell inside the battery pack, and recording them as cell coordinate data; Step S12: determining the arrangement order and the cell spacing of the battery cells according to the cell coordinate data; encoding the position information of the battery cells based on the arrangement order and the cell spacing to obtain the battery cell position; Step S13: determining the connection relationship of adjacent battery cells according to the battery cell positions; identifying the cell topology of the battery cell connection relationship; Step S14: selecting a plurality of measuring points in the battery pack, wherein the measuring points are selected at three fixed positions of the positive electrode, the negative electrode, and the surface midpoint of the battery cell; Step S15: setting the parameters of the electrical temperature parameter acquisition device, including the voltage acquisition range of 0-5V, the current acquisition range of 0-10A, the temperature acquisition range of -20°C to 80°C, and the acquisition accuracy of 0.01V, 0.01A and 0.1°C respectively; Step S16: The first collection is performed at the first minute after the battery cell starts charging and discharging, the second collection is performed at the fifth minute, and the third collection is performed at the tenth minute, and each collection lasts for 1 second; Step S17: classify and store the voltage parameters, current parameters and temperature parameters to form single-cell electrical and temperature parameters.

3. The method for modeling a battery pack thermal model according to claim 1, characterized in that: The step S2 of calculating the difference in electrical temperature gradient of the electrical temperature parameters of the monomer includes: Marking the battery cell measurement points of the battery cell electrical temperature parameters, determining the positive and negative electrode areas of the battery according to the battery cell measurement points, and determining the body center area of ​​the battery cell surface based on the positive and negative electrode areas of the battery; The temperature difference between the positive and negative regions of the battery is calculated to obtain the temperature difference between the positive and negative regions; the voltage difference between the positive and negative regions of the battery is calculated to obtain the voltage difference between the positive and negative regions; the current difference between the positive and negative regions of the battery is calculated to obtain the current difference between the positive and negative regions; Extract the temperature value, voltage value and current value of the center area of ​​the battery cell surface; The temperature difference between the positive and negative electrodes, the voltage difference between the positive and negative electrodes, and the current difference between the positive and negative electrodes are numerically compared with the temperature value, voltage value, and current value of the body center area, respectively, and arranged according to the numerical gradient to obtain the electrical temperature gradient difference data.

4. The method for modeling a battery pack thermal model according to claim 1, characterized in that: The step S2 of using the cell electrical temperature difference data to detect the cell temperature field distribution of the cell topology structure and drawing a cell temperature distribution diagram includes: The temperature difference data of the single cell is processed in time series, and the temperature change rate of each single cell at different time points is calculated to obtain the temperature change rate of the single cell; According to the monomer topological structure, determine whether the single battery is at the edge or the middle position, and obtain the battery position data; Determine the arrangement of the cell topology and classify the arrangement into series cells and parallel cells; Based on the battery location data, the series batteries and parallel batteries are used to calculate the heat dissipation space of the single battery to obtain the heat dissipation space data of the single battery; Determine the local temperature data of the single cell according to the heat dissipation space data of the single cell; Conduct temperature field statistics on the local temperature data of the monomer and detect the heat distribution data of the temperature field; Import the temperature field heat distribution data into the drawing tool, and map the data points into a two-dimensional coordinate system according to the temperature gradient, where the coordinate axes represent the physical position and temperature value of the battery pack, respectively, to obtain a single cell temperature distribution diagram.

5. The method for modeling a battery pack thermal model according to claim 4, characterized in that: The step S2 of identifying the monomer thermal resistance flow path of the monomer temperature distribution diagram includes: The monomer temperature distribution map is divided into regions according to the temperature range, and the temperature range of each region is set to 5°C; In each temperature gradient region, the temperature difference between adjacent single cells is measured, and the ratio of the temperature difference to the distance between adjacent single cells is calculated to obtain temperature-distance difference ratio data; If the temperature-distance difference ratio data is greater than 0.3°C / cm, it is preliminarily determined that the single cell corresponding to the temperature-distance difference ratio data is the starting point of the thermal resistance flow path; Determine the direction of the thermal resistance flow path based on the starting point of the thermal resistance flow path; if the single cells are connected in parallel, the direction of the thermal resistance flow path is perpendicular to the current flow direction; if the single cells are connected in series, the direction of the thermal resistance flow path is along the current flow direction; The intensity of the thermal resistance flow path is determined by comparing the temperature difference between the temperature gradient regions. The greater the temperature difference between the temperature gradient regions, the higher the intensity of the thermal resistance flow path. The direction and intensity of the thermal resistance flow path are marked on the monomer temperature distribution diagram with red lines, and the marked thermal resistance flow path is superimposed on the monomer temperature distribution diagram to form the monomer thermal resistance flow path.

6. The method for modeling a battery pack thermal model according to claim 1, characterized in that: The step S2 of constructing the initial thermal model of the battery pack based on the cell topology and the cell thermal resistance flow path includes: Convert the cell topology and the cell thermal resistance flow path into a battery cell file, and import the battery cell file into Solidworks software; Set the single cell as a thermal network node according to the single cell topology, determine the arrangement, connection structure and battery layout of the single cell, and mark the position and size of each single cell; The thermal resistance flow path is set as the connecting edge between the thermal network nodes, and the thermal resistance parameters between the nodes are set; Connect the thermal resistance flow paths of adjacent single cells; if they are series cells, the current directions are connected sequentially; if they are parallel cells, the current directions are connected perpendicular to the parallel currents; The Solidworks simulation function is started to build an initial thermal model of the battery pack.

7. The method for modeling a battery pack thermal model according to claim 1, characterized in that: Inputting the battery cell operating parameters into the initial thermal model of the battery pack and evaluating the thermal energy state within the pack in step S3 includes: Inputting the battery cell operating parameters into the initial thermal model of the battery pack; Set the initial conditions of the battery cell temperature, and set the initial temperature to 25°C and the coolant temperature to 20°C; Set the battery cell operation mode to intermittent charge and discharge, and set the charge and discharge current to 1A and the charge and discharge voltage to 5V; Continuously monitor the temperature values ​​of the middle battery and the batteries on both sides of the group, and calculate the temperature difference between the temperature values ​​of the middle battery and the batteries on both sides of the group to obtain the temperature aggregation data within the group; Mark the temperature aggregation space of the temperature aggregation data within the group, and divide the temperature aggregation space into temperature aggregation points; The thermal energy parameters around the temperature gathering point are monitored incrementally with a circle of 0.1 cm radius to obtain the thermal energy diffusion data within the group; The thermal energy diffusion data within the group is subjected to diffusion gradient identification, and the thermal energy state of the diffusion gradient is evaluated to obtain the thermal energy state data of the battery group.

8. The method for modeling a battery pack thermal model according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: dividing the thermal imbalance area data into a high-risk area, a medium-risk area and a normal area to determine the thermal imbalance division area; Step S42: color-marking the initial thermal model of the battery pack according to the thermal imbalance division area, wherein red indicates a high-risk area, yellow indicates a medium-risk area, and green indicates a normal area; and determining the thermally unbalanced battery cell according to the model color marking information; Step S43: increasing the cooling wind speed of the area of ​​the thermally unbalanced battery cell and reducing the number of charge and discharge times to obtain optimized parameters of the thermally unbalanced battery; Step S44: transmitting the thermally unbalanced battery optimization parameters back to the initial thermal model of the battery pack to obtain the thermal model of the battery pack.

9. A modeling system for a battery pack thermal model, characterized in that: A method for modeling a battery pack thermal model according to claim 1, wherein the modeling system of the battery pack thermal model comprises: The cell electrical temperature parameter acquisition module is used to determine the battery cell position inside the battery pack; identify the cell topology structure of the battery cell position, and collect the cell electrical temperature parameters of the battery cell position; The module for constructing the initial thermal model of the battery pack is used to measure the difference in the electrical temperature gradient of the electrical temperature parameters of the cells and generate the data of the electrical temperature difference of the cells; to detect the distribution of the temperature field of the cells on the topological structure of the cells using the electrical temperature difference data of the cells and draw the temperature distribution diagram of the cells; to identify the thermal resistance flow path of the cells in the temperature distribution diagram of the cells; and to construct the initial thermal model of the battery pack based on the topological structure of the cells and the thermal resistance flow path of the cells; The thermal state region detection module is used to input the battery cell operating parameters into the initial thermal model of the battery pack, and to evaluate the thermal energy state within the pack to obtain the thermal energy state data of the battery pack; to identify the thermal imbalance region of the thermal energy state data of the battery pack to generate the thermal imbalance region data; The thermal imbalance identification and optimization module is used to mark the thermally unbalanced battery cells in the initial thermal model of the battery pack according to the thermal imbalance area data, and to perform regional heat dissipation optimization on the thermally unbalanced battery cells to obtain the thermal model of the battery pack.

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