Method, device, storage medium and program product for analyzing exhaust gas of an electric cell

Abstract

The application provides an exhaust analysis method and device of an electric core, a storage medium and a program product, and relates to the technical field of simulation. The exhaust analysis method comprises the following steps: acquiring gas production state data of a bare electric core in a thermal runaway process of the electric core; inputting the gas production state data into a three-dimensional model of the bare electric core to predict gas exhaust state change data of two ends of the bare electric core with time, the three-dimensional model being constructed based on the size of the bare electric core; and inputting the gas exhaust state change data of the two ends of the bare electric core with time into a one-dimensional model of a flow channel between the bare electric core and a shell of the electric core to predict the state of the gas in the flow channel, the one-dimensional model being constructed based on an exhaust path between the bare electric core and the shell.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of simulation, in particular to a method and device for analyzing exhaust of an electric core, a storage medium and a program product. BACKGROUND

[0002] In the process of designing the structure of an electric core, the electric core needs to be tested for safety. The current safety test of the electric core focuses on the failure phenomenon of the electric core, and cannot predict the exhaust process when the electric core is in thermal runaway.

[0003] The above statements are only used to provide background technical information related to the present application, and do not necessarily constitute the prior art. SUMMARY

[0004] One of the technical problems to be solved by the present disclosure is to provide a method and device for analyzing exhaust of an electric core, a storage medium and a program product, which can quickly predict the exhaust process of the electric core.

[0005] According to an aspect of the present disclosure, a method for analyzing exhaust of an electric core is provided, comprising: obtaining gas production state data of a bare electric core in a thermal runaway process of the electric core; inputting the gas production state data into a three-dimensional model of the bare electric core to predict data of exhaust state at both ends of the bare electric core changing with time, the three-dimensional model being constructed based on the size of the bare electric core; inputting the data of exhaust state at both ends of the bare electric core changing with time into a one-dimensional model of a flow channel between the bare electric core and a shell of the electric core to predict the state of the gas in the flow channel, the one-dimensional model being constructed based on the exhaust path between the bare electric core and the shell.

[0006] In the technical scheme of the present application, the three-dimensional model of the bare electric core and the one-dimensional model of the flow channel between the bare electric core and the shell of the electric core are constructed, and then the gas production state data of the bare electric core in the thermal runaway process of the electric core is inputted into the three-dimensional model to predict the data of exhaust state at both ends of the bare electric core changing with time, and the data of exhaust state at both ends of the bare electric core changing with time is inputted into the one-dimensional model to predict the state of the gas in the internal space of the electric core. By combining the one-dimensional model and the three-dimensional model, the exhaust process of the electric core is numerically simulated to predict the state of the gas in the internal space of the electric core. Compared with predicting the state of the gas in the internal space of the electric core only by the three-dimensional model, the computational complexity and the calculation period can be reduced, the redundant processing can be reduced, the scene complementarity can be played, and thus the prediction efficiency of the state of the gas in the internal space of the electric core can be improved.

[0007] In some embodiments, the gas generation state data includes gas generation rate data, inputting the gas generation state data into the three-dimensional model of the bare cell, and predicting the gas generation state at both ends of the bare cell over time includes: inputting the gas generation rate data into the three-dimensional model to predict the gas generation flow rate at both ends of the bare cell over time; inputting the gas generation state at both ends of the bare cell over time into a one-dimensional model of the flow channel between the bare cell and the shell of the cell to predict the state of the gas in the flow channel includes: inputting the gas generation flow rate at both ends of the bare cell over time into a one-dimensional model of the flow channel between the bare cell and the shell of the cell to predict the flow state of the gas in the flow channel. By building a one-dimensional and three-dimensional combined model of the monomer cell level, numerical model simulation of the exhaust process can quickly predict the flow state of the gas in the flow channel before and after the thermal runaway of the cell, and improve the efficiency of simulation.

[0008] In some embodiments, the flow state includes flow velocity, and the exhaust analysis method further includes: determining the pressure distribution of the gas in the flow channel based on the flow velocity of the gas in the flow channel; determining the flow resistance value of each region of the flow channel based on the pressure distribution of the gas in the flow channel; and identifying the risk point of the cell based on the flow resistance value of each region. In this embodiment, the pressure distribution of the gas in the flow channel is used to evaluate the flow resistance value of each region inside the cell, providing data support for identifying the weak area of the cell design.

[0009] In some embodiments, identifying the risk point of the cell based on the flow resistance value of each region of the flow channel includes: identifying the region with a flow resistance value greater than a threshold value as a risk point. In this embodiment, the flow resistance value of each region can identify the pressure holding position, and thus quickly locate the weak area of the mechanical design of the cell. In addition, through the identification of the weak area of the mechanical design of the cell, an optimization direction can be provided for the structural optimization design.

[0010] In some embodiments, the exhaust path includes a bare cell boundary region, a gap region between the bare cell and the bottom of the shell, a corner position region of the shell, a gap region of internal mechanical parts of the shell, and a pressure relief valve region. By determining the exhaust path inside the cell when the cell experiences thermal runaway, a one-dimensional model of the flow channel between the bare cell and the shell of the cell can be constructed.

[0011] In some embodiments, the gas generation state data comprises gas generation temperature data, the inputting of the gas generation state data into the three-dimensional model of the bare cell, and the predicting of the gas state change data at the two ends of the bare cell over time comprises: inputting the gas generation temperature data into the three-dimensional model to predict the gas temperature change data at the two ends of the bare cell over time; inputting the gas state change data at the two ends of the bare cell over time into a one-dimensional model of a flow channel between the bare cell and the shell of the cell to predict the state of the gas in the flow channel, which comprises: inputting the gas temperature change data into the one-dimensional model to predict the temperature distribution of the gas in the flow channel. In this embodiment, the temperature distribution in the flow channel of the cell can be quickly predicted by combining the one-dimensional model and the three-dimensional model.

[0012] In some embodiments, the size of any one or more regions in the one-dimensional model is changed to predict the state of the gas in the flow channel; the performance of the cell is determined based on the state of the gas in the flow channel; and the optimal structure of the cell is determined based on the performance of the cell. In this embodiment, by changing the cross-sectional area of the one-dimensional model, the influence of different cell structures on the exhaust path of the cell thermal runaway can be quickly identified, so as to select the optimal cell structure to improve the safety of the cell.

[0013] According to a second aspect of the present disclosure, an exhaust analysis device for a cell is also provided, comprising: a data acquisition module configured to acquire gas generation state data of a bare cell of the cell during a thermal runaway process; a first prediction module configured to input the gas generation state data into a three-dimensional model of the bare cell to predict gas state change data at two ends of the bare cell over time, the three-dimensional model being constructed based on the size of the bare cell; and a second prediction module configured to input the gas state change data at the two ends of the bare cell over time into a one-dimensional model of a flow channel between the bare cell and a shell of the cell to predict the state of the gas in the flow channel, the one-dimensional model being constructed based on an exhaust path between the bare cell and the shell.

[0014] In the technical scheme of the embodiments of the present application, the three-dimensional model of the bare cell and the one-dimensional model of the flow channel between the bare cell and the shell of the cell are constructed, and then the gas generation state data of the bare cell of the cell during the thermal runaway process is input into the three-dimensional model to predict the gas state change data at the two ends of the bare cell over time, and the gas state change data at the two ends of the bare cell over time is input into the one-dimensional model to predict the state of the gas in the internal space of the cell. By combining the one-dimensional model and the three-dimensional model, the exhaust process of the cell is numerically simulated to predict the state of the gas in the internal space of the cell. Compared with predicting the state of the gas in the internal space of the cell only by the three-dimensional model, the computational complexity and the calculation period can be reduced, the redundant processing can be reduced, the scene complementarity can be played, and thus the prediction efficiency of the flow state of the gas in the internal space of the cell can be improved.

[0015] In some embodiments, the gas production state data comprises gas production rate data, the first prediction module is configured to input the gas production rate data into the three-dimensional model to predict the exhaust flow rate data at both ends of the bare cell over time; and the second prediction module is configured to input the exhaust flow rate data at both ends of the bare cell over time into the one-dimensional model of the flow channel between the bare cell and the shell of the cell to predict the flow state of the gas in the flow channel. By building a one-dimensional and three-dimensional combined model at the level of the single cell, numerical model simulation of the exhaust process can quickly predict the flow state of the gas in the flow channel before and after the thermal runaway of the cell, thereby improving the efficiency of simulation.

[0016] In some embodiments, the flow state comprises flow velocity, and the exhaust analysis device further comprises a processing module configured to determine the pressure distribution of the gas in the flow channel based on the flow velocity of the gas in the flow channel, determine the flow resistance value of each region of the flow channel based on the pressure distribution of the gas in the flow channel, and identify the risk point of the cell based on the flow resistance value of each region. In this embodiment, the pressure distribution of the gas in the flow channel is used to evaluate the flow resistance value of each region inside the cell, thereby providing data support for identifying the weak region of the cell design.

[0017] In some embodiments, the processing module is configured to identify the region with a flow resistance value greater than a threshold value as the risk point. In this embodiment, the flow resistance value of each region can be used to identify the pressure retaining position, thereby quickly locating the weak region of the mechanical design of the cell. In addition, the identification of the weak region of the mechanical design of the cell can also provide an optimization direction for the structural optimization design.

[0018] In some embodiments, the exhaust path comprises a boundary region of the bare cell, a gap region between the bare cell and the bottom of the shell, a corner position region of the shell, a gap region of the internal mechanical part of the shell, and a region of the explosion-proof valve. By determining the exhaust path inside the cell when the cell experiences thermal runaway, a one-dimensional model of the flow channel between the bare cell and the shell of the cell can be built.

[0019] In some embodiments, the gas production state data comprises gas production temperature data, the first prediction module is configured to input the gas production temperature data into the three-dimensional model to predict the exhaust temperature data at both ends of the bare cell over time; and the second prediction module is configured to input the exhaust temperature data over time into the one-dimensional model to predict the temperature distribution of the gas in the flow channel. In this embodiment, the combination of the one-dimensional model and the three-dimensional model can quickly predict the temperature distribution in the flow channel of the cell.

[0020] In some embodiments, the parameter modification module is configured to change the size of any one or more regions in the one-dimensional model so that the second prediction module predicts the state of the gas in the flow channel; the processing module is configured to determine the performance of the battery cell based on the state of the gas in the flow channel, and determine the optimal structure of the battery cell based on the performance of the battery cell. In this embodiment, by changing the cross-sectional area of the one-dimensional model, the influence of different battery cell structures on the battery cell thermal runaway exhaust path can be quickly identified, so that the optimal battery cell structure is selected to improve the safety of the battery cell.

[0021] According to a third aspect of the present disclosure, an exhaust analysis device for a battery cell is also provided, comprising: a processor; and a memory coupled to the processor, configured to store instructions, which, when executed by the processor, cause the processor to perform the exhaust analysis method as described above.

[0022] According to a fourth aspect of the present disclosure, a computer-readable storage medium is also provided, which stores computer instructions, which, when executed by a processor, implement the exhaust analysis method as described above.

[0023] According to a fifth aspect of the present disclosure, a computer program product is also provided, comprising: computer instructions, which, when executed by a processor, implement the exhaust analysis method as described above.

[0024] Other features and advantages of the present disclosure will become apparent from the following detailed description of exemplary embodiments thereof, taken in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0025] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required to be used in the embodiments of the present application will be briefly introduced as follows. Obviously, the drawings described below are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without any creative effort on the basis of the drawings.

[0026] Figure 1 a schematic diagram of the exhaust analysis method for a battery cell according to one or more embodiments;

[0027] Figure 2 a schematic diagram of the exhaust analysis method for a battery cell according to one or more embodiments;

[0028] Figure 3 a schematic diagram of the exhaust analysis method for a battery cell according to one or more embodiments;

[0029] Figure 4 a schematic diagram of the exhaust analysis method for a battery cell according to one or more embodiments;

[0030] Figure 5 a schematic diagram of the exhaust analysis method for a battery cell according to one or more embodiments;

[0031] Figure 6 A schematic diagram of a gas exhaust analysis method for a battery cell according to one or more embodiments;

[0032] Figure 7 A schematic diagram of a gas exhaust analysis method for a battery cell according to one or more embodiments;

[0033] Figure 8 A schematic diagram of a gas exhaust analysis device for a battery cell according to one or more embodiments;

[0034] Figure 9 A schematic diagram of a gas exhaust analysis device for a battery cell according to one or more embodiments;

[0035] Figure 10 A schematic diagram of a gas exhaust analysis device for a battery cell according to one or more embodiments. DETAILED DESCRIPTION

[0036] The embodiments of the present application will be described in further detail below with reference to the accompanying drawings and embodiments. The following detailed description and appended drawings are intended to be illustrative only and are not intended to limit the scope of the present application, that is, the application is not limited to the embodiments described.

[0037] In the description of the present application, it should be noted that, unless otherwise specified, the meaning of "a plurality of" is more than two; the orientation or positional relationship indicated by the terms "upper", "lower", "left", "right", "inner", "outer" and the like is only for the purpose of facilitating the description of the present application and simplifying the description, and does not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application. In addition, the terms "first", "second", "third" and the like are only for the purpose of description and cannot be understood as indicating or implying relative importance. "Vertical" is not strictly vertical, but within the allowable range of error. "Parallel" is not strictly parallel, but within the allowable range of error.

[0038] At the same time, it should be understood that, for the purpose of description, the sizes of the various parts shown in the drawings are not drawn in accordance with the actual proportional relationship.

[0039] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way limiting to the disclosure and its application or uses.

[0040] Techniques, methods, and devices known to those of ordinary skill in the relevant art can not be discussed in detail herein, but should be considered as part of the specification, where appropriate.

[0041] In all examples shown and discussed herein, any specific values should be interpreted as merely exemplary, and not as a limitation. Thus, other examples of the exemplary embodiments can have different values.

[0042] It should be noted that like reference numerals and letters refer to like items throughout the attached drawings, and once an item is defined in one drawing, it is not necessary to discuss it further in subsequent drawings.

[0043] In order to make the purposes, technical solutions and advantages of the present disclosure clearer, the present disclosure is further described in detail below with reference to the specific embodiments and in conjunction with the accompanying drawings.

[0044] In the process of thermal runaway of the battery cell, obtaining the exhaust state of the battery cell is a key link for risk assessment, optimization of safety design, and effective protection. Currently, the battery cell safety thermal runaway evaluation standard is mainly biased towards the test end. Since the battery cell cannot capture the gas state in the gap between the JR (Jelly Roll, bare battery cell) and the shell during the thermal runaway process in real time during the test process, it has certain limitations. And only using a three-dimensional model to predict the gas state in the flow channel between the JR and the shell has low efficiency.

[0045] The present disclosure provides an exhaust analysis scheme for a battery cell, which can improve the prediction efficiency of the state of the gas in the internal space of the battery cell, thereby providing data support for other analysis. The scheme of the present disclosure will be described below in conjunction with specific embodiments.

[0046] Figure 1 A schematic diagram of the exhaust analysis method for a battery cell according to one or more embodiments includes steps S11-S13.

[0047] In step S11, the gas production state data of the bare battery cell during the thermal runaway process of the battery cell is obtained.

[0048] The battery cell is, for example, a lithium ion square can winding battery cell, or a lithium ion cylindrical battery cell, or a lithium ion laminated battery cell, etc. The present disclosure does not limit the type of battery cell.

[0049] In step S12, the gas production state data is input to a three-dimensional model of the bare battery cell to predict the exhaust state change data of both ends of the bare battery cell over time, and the three-dimensional model is constructed based on the size of the bare battery cell.

[0050] In some embodiments, the size information of the bare battery cell can obtain a bare battery cell flow channel simulation model, for example, a bare battery cell three-dimensional CAD (Computer Aided Design) model.

[0051] The input condition of the three-dimensional model is the gas generation state data of the bare cell in the thermal runaway test process of the cell. The three-dimensional model can be used to perform interlayer fluid simulation analysis of the bare cell to obtain data of the exhaust state at both ends of the bare cell changing with time.

[0052] In step S13, the data of the exhaust state at both ends of the bare cell changing with time is input into a one-dimensional model of a flow channel between the bare cell and the shell of the cell, and the state of the gas in the flow channel is predicted. The one-dimensional model is constructed based on the exhaust path between the bare cell and the shell.

[0053] In some embodiments, a flow channel model between the bare cell and the shell is built, and the flow channel model is a one-dimensional model. The one-dimensional model represents a gap between the bare cell and the shell, and the gap constitutes a flow channel. During the thermal runaway exhaust process of the cell, the gas passes through the flow channel. The input condition of the one-dimensional model is the data of the exhaust state at both ends of the bare cell changing with time, and the state of the gas in the flow channel is obtained through simulation.

[0054] In this embodiment, by building a one-dimensional and three-dimensional combined model at the level of the single cell, numerical model simulation is performed on the exhaust process, and the state of the gas in the flow channel before and after the thermal runaway of the cell can be predicted. Compared with predicting the state of the gas in the internal space of the cell only by the three-dimensional model, the calculation complexity and calculation period can be reduced, redundant processing can be reduced, and the scene complementarity can be played, so that the prediction efficiency of the state of the gas in the internal space of the cell can be improved.

[0055] In some embodiments, the gas generation state data includes gas generation rate data, and the exhaust analysis method is as shown in Figure 2 Figure 2 FIG. 1 is a schematic diagram of an exhaust analysis method of a cell according to one or more embodiments, including steps S111-S131.

[0056] In step S111, the gas generation rate data of the bare cell of the cell during the thermal runaway process is obtained.

[0057] For example, the gas generation rate of the bare cell from the beginning of the thermal aging to the end of the thermal aging stage of the cell is obtained, which is used as the input condition for subsequent numerical model simulation.

[0058] The gas generation rate of the bare cell can be obtained by a pressure vessel test. For example, the cell is placed in a pressure vessel, the volume and pressure of the gas in the pressure vessel are collected, and then a gas state equation is used to obtain the gas generation rate of the bare cell.

[0059] In step S121, the gas generation rate data is input into a three-dimensional model of the bare cell to predict the data of the exhaust flow rate at both ends of the bare cell changing with time.

[0060] ​The input condition of the three-dimensional model is the gas generation rate data of the bare cell during the cell thermal runaway test process. Through the three-dimensional model, the interlayer fluid simulation analysis of the bare cell can be performed to obtain the exhaust flow rate data of the two ends of the bare cell varying with time.

[0061] As shown in Figure 3 , the two ends 31 and 32 of the bare cell are the exhaust flow rate statistical positions. By statistically analyzing the exhaust flow rate at the positions, the exhaust flow rate data of the two ends of the bare cell varying with time can be obtained.

[0062] In step S131, the exhaust flow rate data of the two ends of the bare cell varying with time is input to a one-dimensional model of the flow channel between the bare cell and the shell of the cell, and the flow state of the gas in the flow channel is predicted.

[0063] The input condition of the one-dimensional model is the exhaust flow rate data of the two ends of the bare cell varying with time. Through simulation, the flow state of the gas in the flow channel is obtained.

[0064] In this embodiment, by building a one-dimensional and three-dimensional combined model of the single cell level, numerical model simulation of the exhaust process can quickly predict the flow state of the gas in the flow channel before and after the cell thermal runaway, and improve the efficiency of simulation.

[0065] In some embodiments, the exhaust path includes a bare cell boundary region, a gap region between the bare cell and the bottom of the shell, a corner position region of the shell, a gap region of the internal mechanical part of the shell, and a pressure relief valve region.

[0066] Based on the above typical positions of the internal flow channel of the cell, a one-dimensional model can be created for the gap of the flow channel between the bare cell and the shell. As shown in Figure 4 , a one-dimensional model architecture according to one or more embodiments is shown. Figure 4

[0067] Reference numeral 41 represents a bare cell boundary flow input parameter region. The parameters output by the three-dimensional model are input to this region. JR is a bare cell. Reference numeral 411 is a flow monitor. Reference numeral A is a port without input information. Reference numeral 412 is a first display. 4121 displays the pressure information of the bare cell boundary region varying with time, and 4122 displays the pressure information at the current time.

[0068] Reference numeral 42 represents a gap region between the bare cell and the bottom of the shell. The gas in the gap region can exchange heat with the environment. Reference numeral 421 is a second display. 4211 displays the pressure information of the gap region between the bare cell and the bottom of the shell varying with time, and 4212 displays the pressure information at the current time.

[0069] ​Label 43 represents a corner position area of the shell, the gas in this area can also exchange heat with the ambient fluid by convection. Those skilled in the art can know that, similar to the setting of the first display 412 and the second display 421, a display can also be set in this area to display the pressure information of this area at any time and the pressure information at the current time. In order to simplify the drawing, the third display is not drawn in this area.

[0070] Label 44 represents a gap area of the internal mechanical parts of the shell, the gas in this area can also exchange heat with the ambient fluid by convection. The internal mechanical parts are, for example, the tab and the pole. Those skilled in the art can know that, similar to the setting of the first display 412 and the second display 421, a display can also be set in this area to display the pressure information of this area at any time and the pressure information at the current time. In order to simplify the drawing, the fourth display is not drawn in this area.

[0071] Label 45 represents the area of the explosion-proof valve. Those skilled in the art can know that, similar to the setting of the first display 412 and the second display 421, a display can also be set in this area to display the pressure information of this area at any time and the pressure information at the current time. In order to simplify the drawing, the fifth display is not drawn in this area.

[0072] According to different project requirements, displays can be set in different positions.

[0073] Label 46 represents a solver for inputting simulation time, size of each gap, and other information.

[0074] In the above embodiment, based on the typical position of the flow channel inside the battery cell, a one-dimensional model describing the gap between the flow channel of the bare battery cell and the shell is built, so that the one-dimensional model can be used to predict the flow state of the gas in the flow channel.

[0075] In some embodiments, the flow state of the gas in the flow channel includes the flow velocity of the gas in the flow channel. The exhaust analysis method is as shown in Figure 5 Figure 5 The schematic diagram of the exhaust analysis method of the battery cell according to one or more embodiments includes steps S51-S53.

[0076] In step S51, based on the flow velocity of the gas in the flow channel, the pressure distribution of the gas in the flow channel is determined.

[0077] The pressure distribution of the gas in the flow channel is, for example, the pressure of the gas in the boundary area of the bare battery cell, the gap area between the bare battery cell and the bottom of the shell, the corner position area of the shell, the gap area of the internal mechanical parts of the shell, and the explosion-proof valve area. By pressure monitoring, the static pressure curve of the flow channel gap inside the battery cell over time can be viewed.

[0078] ​At step S52, the flow resistance value of each region of the flow channel is determined based on the pressure distribution of the gas in the flow channel.

[0079] During the thermal runaway process of the battery cell, the phenomenon of damage to the battery cell shell is mainly due to the large fluid resistance in this area and the existence of pressure accumulation. By the static pressure difference between each two points, the flow resistance between different regions can be obtained.

[0080] At step S53, the risk point of the battery cell is identified based on the flow resistance value of each region.

[0081] In this embodiment, the flow resistance value of each region of the flow channel is determined based on the pressure distribution of the gas in the flow channel, and then the flow resistance value of each region inside the battery cell is evaluated to provide data support for identifying the weak region of the battery cell design.

[0082] In some embodiments, identifying the risk point of the battery cell based on the flow resistance value of each region of the flow channel includes: identifying the region with a flow resistance value greater than a threshold value as a risk point.

[0083] In this embodiment, the pressure accumulation position can be identified by the flow resistance value of each region, and then the weak region of the mechanical design of the battery cell can be quickly located. In addition, through the identification of the weak region of the mechanical design of the battery cell, an optimization direction can also be provided for the structural optimization design.

[0084] In some embodiments, as shown in Figure 6 , a schematic diagram of a battery cell exhaust analysis method according to one or more embodiments includes steps S61-S62. Figure 6

[0085] At step S61, the size of any one or more regions in the one-dimensional model is changed to predict the state of the gas in the flow channel.

[0086] At step S62, the performance of the battery cell is determined based on the state of the gas in the flow channel.

[0087] At step S63, the optimal structure of the battery cell is determined based on the performance of the battery cell.

[0088] For example, the size of any one or more regions in the one-dimensional model is changed, i.e., the structure of the battery cell is changed, the flow velocity of the gas in the flow channel is predicted, the pressure distribution of the gas in the flow channel is determined based on the flow velocity of the gas in the flow channel, the flow resistance value of each region of the flow channel is determined based on the pressure distribution of the gas in the flow channel, it is judged whether there is a region with a flow resistance value greater than a threshold value, if there is, it means that the battery cell has a risk point, if not, it means that the battery cell does not have a risk point. Select the battery cell structure without a risk point, i.e., determine the optimal battery cell structure.

[0089] ​In this embodiment, by adjusting the size of any one or more regions in the one-dimensional model, the flow area of the fluid can be adjusted, and thus the influence of different battery structures on the battery thermal runaway exhaust path can be quickly identified, so as to select the optimal battery structure to improve the safety of the battery.

[0090] In some embodiments, the gas production state data includes gas production temperature data, for example, gas production heat generation power. The exhaust analysis method is as shown in Figure 7 Figure 7 FIG. 1 is a schematic diagram of an exhaust analysis method of a battery according to one or more embodiments, including steps S112-S132.

[0091] In step S112, the gas production temperature data of the bare battery during the thermal runaway process is obtained.

[0092] In step S122, the gas production temperature data is input into the three-dimensional model to predict the exhaust temperature change data of the two ends of the bare battery over time.

[0093] In step S132, the exhaust temperature change data is input into the one-dimensional model to predict the temperature distribution of the gas in the flow channel. Due to the diffusion of the gas in the flow channel, different temperatures can be obtained in different regions through heat conduction, heat exchange, etc.

[0094] In this embodiment, by combining the one-dimensional model and the three-dimensional model, the temperature distribution of the entire process of the gas generated from the inside of the bare battery and flowing to the position of the explosion-proof valve can be quickly simulated, and thus data support is provided for subsequent safety analysis.

[0095] As shown in Figure 4 The bare battery boundary region in label 41 inputs the gas production temperature data of the bare battery, and then determines the temperature distribution of the gas in the gap region between the bare battery and the bottom of the shell, the corner position region of the shell, the gap region of the internal mechanical parts of the shell, and the explosion-proof valve region in sequence. Among them, the first display 412 displays the temperature data through label 4124, and the second display 421 displays the temperature data through label 4214. Of course, the temperature data of the corresponding regions can also be displayed on the third display, the fourth display, and the fifth display.

[0096] In some embodiments, the size of any one or more regions in the one-dimensional model is changed, the temperature distribution of the gas in the flow channel is predicted, the performance of the battery is determined based on the temperature distribution of the gas in the flow channel, and the optimal structure of the battery is determined based on the performance of the battery.

[0097] ​For example, the size of any one or more regions in the one-dimensional model is changed, that is, the structure of the battery cell is changed, the temperature distribution of the gas in the flow channel is predicted, and then it is determined whether the temperature of a certain region is greater than the temperature threshold. If there is, it means that the structure design of the battery cell is unreasonable and is prone to cause safety failure. If not, it means that the structure design of the battery cell is reasonable, so that the optimal battery cell structure can be quickly identified to improve the safety of the battery cell.

[0098] Alternatively, after predicting the temperature distribution of the gas in the flow channel, the temperature of each region is compared with the temperature threshold of the corresponding region. If there is a region whose temperature exceeds the corresponding temperature threshold, it is identified that the structure of the battery cell has defects. If the temperature of each region meets the temperature threshold requirement of the corresponding region, it means that the structure design of the battery cell is reasonable.

[0099] In determining the optimal structure, the pressure distribution and temperature distribution of the gas in the flow channel can be comprehensively judged to determine the optimal battery cell structure. For example, if there is no region whose flow resistance value is greater than the flow resistance threshold, and no region whose temperature is greater than the temperature threshold, it means that the structure of the battery cell meets the design requirements.

[0100] Those skilled in the art can understand that in the above method of the specific embodiment, the writing order of each step does not mean a strict execution order and does not constitute any limitation on the real-time process. The specific execution order of each step should be determined by its function and possible internal logic.

[0101] The above is a schematic diagram of some embodiments of the battery cell exhaust analysis method. Next, the battery cell exhaust analysis device will be further introduced with reference to the accompanying drawings.

[0102] Figure 8 The schematic diagram of the battery cell exhaust analysis device according to one or more embodiments includes a data acquisition module 81, a first prediction module 82, and a second prediction module 83.

[0103] The data acquisition module 81 is configured to acquire the gas production state data of the bare battery cell during the thermal runaway process; the first prediction module 82 is configured to input the gas production state data into a three-dimensional model of the bare battery cell to predict the exhaust state change data of the bare battery cell at both ends over time, and the three-dimensional model is constructed based on the size of the bare battery cell; the second prediction module 83 is configured to input the exhaust state change data of the bare battery cell at both ends into a one-dimensional model of the flow channel between the bare battery cell and the shell of the battery cell to predict the state of the gas in the flow channel, and the one-dimensional model is constructed based on the exhaust path between the bare battery cell and the shell.

[0104] The exhaust path includes a bare battery cell boundary region, a gap region between the bare battery cell and the bottom of the shell, a corner position region of the shell, a gap region of the internal mechanical part of the shell, and a pressure relief valve region.

[0105] In this embodiment, by building a one-dimensional and three-dimensional combined model at the level of the single battery cell, numerical model simulation is performed on the exhaust process, which can predict the state of the gas in the flow channel before and after the thermal runaway of the battery cell. Compared with predicting the state of the gas in the internal space of the battery cell only by a three-dimensional model, the computational complexity and period can be reduced, redundant processing can be reduced, and the prediction efficiency of the state of the gas in the internal space of the battery cell can be improved.

[0106] In some embodiments, the gas generation state data includes gas generation rate data, the first prediction module is configured to input the gas generation rate data to the three-dimensional model to predict the exhaust flow rate data at both ends of the bare battery cell varying with time; and the second prediction module is configured to input the exhaust flow rate data at both ends of the bare battery cell varying with time to a one-dimensional model of the flow channel between the bare battery cell and the shell of the battery cell to predict the flow state of the gas in the flow channel.

[0107] In this embodiment, by building a one-dimensional and three-dimensional combined model at the level of the single battery cell, numerical model simulation is performed on the exhaust process, which can quickly predict the flow state of the gas in the flow channel before and after the thermal runaway of the battery cell, and improve the efficiency of simulation.

[0108] In some embodiments, the flow state includes flow velocity, such as Figure 9 As shown in the figure, the exhaust analysis device further includes a processing module 91 configured to determine the pressure distribution of the gas in the flow channel based on the flow velocity of the gas in the flow channel, determine the flow resistance value of each region of the flow channel based on the pressure distribution of the gas in the flow channel, and identify the risk point of the battery cell based on the flow resistance value of each region.

[0109] In this embodiment, the flow resistance value of each region of the flow channel is determined based on the pressure distribution of the gas in the flow channel, and then the flow resistance value of each region in the battery cell is evaluated, which provides data support for identifying the weak region of the battery cell design.

[0110] In some embodiments, the processing module is configured to identify the region with a flow resistance value greater than a threshold value as the risk point.

[0111] In this embodiment, the pressure holding position can be identified based on the flow resistance value of each region, and then the weak region of the mechanical design of the battery cell can be quickly located. In addition, through the identification of the weak region of the mechanical design of the battery cell, an optimization direction can be provided for the structural optimization design.

[0112] In some embodiments, the gas generation state data includes gas generation temperature data, the first prediction module is configured to input the gas generation temperature data to the three-dimensional model to predict the exhaust temperature data at both ends of the bare battery cell varying with time; and the second prediction module is configured to input the exhaust temperature data varying with time to the one-dimensional model to predict the temperature distribution of the gas in the flow channel.

[0113] In this embodiment, by combining the one-dimensional model and the three-dimensional model, the temperature distribution of the entire process of the gas generated from the inside of the bare battery and flowing to the explosion-proof valve position can be quickly simulated, and data support is provided for subsequent safety analysis.

[0114] In some embodiments, as shown in Figure 9 The exhaust analysis device also includes a parameter modification module 92 configured to change the size of any one or more regions in the one-dimensional model so that the second prediction module predicts the state of the gas in the flow channel; the processing module 91 is also configured to determine the performance of the battery based on the state of the gas in the flow channel, and determine the optimal structure of the battery based on the performance of the battery.

[0115] For example, changing the size of any one or more regions in the one-dimensional model, i.e. changing the structure of the battery, predicting the flow velocity of the gas in the flow channel, determining the pressure distribution of the gas in the flow channel based on the flow velocity of the gas in the flow channel; based on the pressure distribution of the gas in the flow channel, determine the flow resistance value of each region of the flow channel; determine whether there is a region with flow resistance value greater than the threshold value, if there is, it means that there is a risk point in the battery, if not, it means that there is no risk point in the battery. Select the battery structure without risk point, that is, determine the optimal battery structure.

[0116] Or, change the size of any one or more regions in the one-dimensional model, predict the temperature distribution of the gas in the flow channel, and then determine whether the temperature of a certain region is greater than the threshold value, if there is, it means that the structure design of the battery is unreasonable and is prone to safety failure; if not, it means that the structure design of the battery is reasonable, so as to quickly identify the optimal battery structure to improve the safety of the battery.

[0117] Figure 10 A schematic diagram of an exhaust analysis device of a battery according to one or more embodiments. The exhaust analysis device can be realized by means of an electronic device. The exhaust analysis device 10 includes a memory 1010 and a processor 1020. The memory 1010 can be a disk, a flash memory or any other non-volatile storage medium. The memory is used to store the instructions in the above embodiments. The processor 1020 is coupled to the memory 1010 and can be implemented as one or more integrated circuits, such as a microprocessor or a microcontroller. The processor 1020 is used to execute the instructions stored in the memory.

[0118] In some embodiments, the processor 1020 is coupled to the memory 1010 through the BUS bus 1030. The exhaust analysis device can also be connected to an external storage device 1050 through a storage interface 1040 to call external data, and can also be connected to a network or another computer system (not shown) through a network interface 1060. Details are not described here.

[0119] In this embodiment, the electronic device stores data instructions through the memory, and processes the above instructions through the processor, which can improve the prediction efficiency of the state of the gas in the internal space of the battery cell. On the other hand, it can also quickly locate the weak area of the battery cell design, and quickly evaluate the optimal battery cell structure.

[0120] In some embodiments of the application, a computer program product is also provided, which includes computer program instructions executed by a processor to implement the method of any one of the above embodiments.

[0121] In some embodiments of the application, a computer program product is also provided, which includes computer program instructions executed by a processor to implement the method of any one of the above embodiments.

[0122] The above description of various embodiments tends to emphasize differences between various embodiments, and the same or similar parts can be referred to each other, and for brevity, will not be repeated here.

[0123] So far, the present application has been described in detail. In order to avoid obscuring the concept of the present application, some details known in the art are not described. Those skilled in the art can fully understand how to implement the technical solutions disclosed herein according to the above description.

[0124] The method and system of the present application can be implemented in many ways. For example, the method and system of the present application can be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above order of steps for the method is only for illustration, and the steps of the method of the present application are not limited to the above specific order, unless otherwise specifically stated. In addition, in some embodiments, the present application can also be implemented as programs recorded in recording media, which include machine-readable instructions for implementing the method according to the present application. Therefore, the present application also covers the recording media storing the programs for executing the method according to the present application.

[0125] While certain embodiments of the application have been described herein in detail, those skilled in the art will appreciate that modifications can be made without departing from the scope and spirit of the application. The scope of the application is defined by the appended claims.

Claims

1. A method for analyzing the exhaust gas of a battery cell, characterized in that, include: The gas generation status data of the bare cell during thermal runaway is obtained, and the gas generation status data includes gas generation rate data and gas generation temperature data. The gas production state data is input into the three-dimensional model of the bare cell to predict the change data of the exhaust state at both ends of the bare cell over time. The three-dimensional model is constructed based on the size of the bare cell and includes: inputting the gas production rate data into the three-dimensional model to predict the change data of the exhaust flow rate at both ends of the bare cell over time; inputting the gas production temperature data into the three-dimensional model to predict the change data of the exhaust temperature at both ends of the bare cell over time. The data on the time-varying exhaust state at both ends of the bare cell are input into a one-dimensional model of the flow channel between the bare cell and the cell casing to predict the state of the gas in the flow channel. The one-dimensional model is constructed based on the exhaust path between the bare cell and the casing and includes: inputting the time-varying exhaust flow rate data at both ends of the bare cell into the one-dimensional model to predict the flow state of the gas in the flow channel; and inputting the time-varying exhaust temperature data into the one-dimensional model to predict the temperature distribution of the gas in the flow channel.

2. The exhaust gas analysis method according to claim 1, characterized in that, The flow state includes flow velocity, and the exhaust gas analysis method further includes: The pressure distribution of the gas in the flow channel is determined based on the gas flow velocity in the flow channel; Based on the pressure distribution of the gas in the flow channel, the flow resistance value of each region of the flow channel is determined; Based on the current resistance value of each region, the risk points of the battery cell are identified.

3. The exhaust gas analysis method according to claim 2, characterized in that, Based on the flow resistance value of each region of the flow channel, the risk points of the battery cell are identified, including: The regions where the flow resistance value is greater than the threshold are identified as the risk points.

4. The exhaust gas analysis method according to claim 1, characterized in that, The exhaust path includes the boundary area of ​​the bare battery cell, the gap area between the bare battery cell and the bottom of the housing, the corner area of ​​the housing, the gap area of ​​the internal mechanical parts of the housing, and the explosion-proof valve area.

5. The exhaust gas analysis method according to any one of claims 1 to 4, characterized in that, Also includes: By changing the size of any one or more regions in the one-dimensional model, the state of the gas in the flow channel can be predicted. The performance of the battery cell is determined based on the state of the gas in the flow channel; Based on the performance of the battery cell, the optimal structure of the battery cell is determined.

6. A battery cell exhaust analysis device, characterized in that, include: The data acquisition module is configured to acquire gas generation status data of the bare battery cell during thermal runaway, the gas generation status data including gas generation rate data and gas generation temperature data; The first prediction module is configured to input the gas production state data into the three-dimensional model of the bare cell, and predict the change data of the exhaust state at both ends of the bare cell over time. The three-dimensional model is constructed based on the size of the bare cell, and includes: inputting the gas production rate data into the three-dimensional model, predicting the change data of the exhaust flow rate at both ends of the bare cell over time, inputting the gas production temperature data into the three-dimensional model, and predicting the change data of the exhaust temperature at both ends of the bare cell over time. The second prediction module is configured to input the time-varying data of the exhaust state at both ends of the bare cell into a one-dimensional model of the flow channel between the bare cell and the cell casing, and predict the state of the gas in the flow channel. The one-dimensional model is constructed based on the exhaust path between the bare cell and the casing, and includes: inputting the time-varying data of the exhaust flow rate at both ends of the bare cell into the one-dimensional model to predict the flow state of the gas in the flow channel; and inputting the time-varying data of the exhaust temperature into the one-dimensional model to predict the temperature distribution of the gas in the flow channel.

7. The exhaust gas analysis apparatus according to claim 6, characterized in that, The flow state includes flow velocity, and the exhaust gas analysis device further includes: The processing module is configured to determine the pressure distribution of the gas in the flow channel based on the gas flow velocity in the flow channel, determine the flow resistance value of each region of the flow channel based on the pressure distribution of the gas in the flow channel, and identify the risk points of the battery cell based on the flow resistance value of each region.

8. The exhaust gas analysis apparatus according to claim 7, characterized in that, The processing module is configured to identify areas where the flow resistance value is greater than a threshold as risk points.

9. The exhaust gas analysis device according to claim 6, characterized in that, The exhaust path includes the boundary area of ​​the bare battery cell, the gap area between the bare battery cell and the bottom of the housing, the corner area of ​​the housing, the gap area of ​​the internal mechanical parts of the housing, and the explosion-proof valve area.

10. The exhaust gas analysis apparatus according to any one of claims 6 to 9, characterized in that, Also includes: The parameter modification module is configured to change the size of any one or more regions in the one-dimensional model so that the second prediction module can predict the state of the gas in the flow channel. The processing module is configured to determine the performance of the battery cell based on the state of the gas in the flow channel, and to determine the optimal structure of the battery cell based on the performance of the battery cell.

11. A battery cell exhaust analysis device, characterized in that, include: processor; as well as A memory coupled to the processor is used to store instructions that, when executed by the processor, cause the processor to perform the exhaust gas analysis method as described in any one of claims 1 to 5.

12. A computer-readable storage medium storing computer instructions thereon, characterized in that, When executed by a processor, the computer instructions implement the exhaust gas analysis method according to any one of claims 1 to 5.

13. A computer program product, characterized in that, include: It includes computer instructions that, when executed by a processor, implement the exhaust gas analysis method according to any one of claims 1 to 5.

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