Method and system for optimizing standing parameters after battery cell liquid injection
By collecting and fitting OCV data after cell injection, the optimal settling time is determined by differentiation, which solves the problem of cumbersome and safety risks in determining settling parameters in the existing technology, and improves the cell wetting effect and performance.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-18
- Publication Date
- 2026-03-31
AI Technical Summary
In the existing technology, the process of determining the standing parameters after electrolyte injection of the battery cell is cumbersome and poses safety risks, making it difficult to quickly and safely determine the optimal standing parameters.
By collecting data on the change of OCV over time after electrolyte injection into the battery cell, fitting the OCV-time equation, and obtaining the optimal settling time by taking the derivative, an index table is constructed to quickly and safely determine the optimal settling parameters.
The optimal static parameters can be determined efficiently and safely without disassembling the battery cell, improving the cell's wetting effect and cycle and storage performance.
Smart Images
Figure CN121769459A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of battery cell production parameter optimization technology, and particularly relates to a method and system for optimizing battery cell static parameters after electrolyte injection. Background Technology
[0002] Lithium-ion batteries, as a new generation of green, high-energy, and environmentally friendly batteries, have wide applications in daily life and production, and have become a key area for the development of rechargeable batteries. In the lithium-ion battery production process, a settling process is often added after the electrolyte injection step. This process ensures that the electrodes inside the cell are fully absorbed and wetted by the electrolyte after injection, and there should be no obvious areas of insufficient wetting. Otherwise, during subsequent charging and discharging, the SEI film formed in these areas will be incomplete, and lithium plating may even occur due to the inability of lithium ions to intercalate properly, resulting in cycle life loss and safety risks.
[0003] Different battery cells require different designs to meet the needs of different fields and customers. These differences manifest in factors such as electrode areal density, compaction density, group margin, electrolyte selection, and the choice of positive and negative electrode materials. These factors all have varying impacts on the electrolyte wetting rate of the cell electrodes. Therefore, when developing new battery cell products, it is often necessary to develop new settling processes (at different times and temperatures) to match the new design. This development process typically involves disassembling the cell after settling, performing a full charge test, and then visually inspecting the cell interface during the later stages of cycling to determine if the electrodes are fully wetted. This process is lengthy and the disassembly is unfriendly to technical personnel (risks include fire and potential health hazards from electrolyte inhalation). Summary of the Invention
[0004] To overcome the shortcomings of the prior art, the present invention provides a method and system for optimizing the static parameters after cell injection, which can quickly and safely determine the optimal static parameters, thereby solving the problems of long process and safety and health risks associated with relying on cell disassembly and observation in the prior art.
[0005] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions: The first aspect of the present invention provides a method for optimizing the parameters of the battery cell after electrolyte injection and static setting.
[0006] A method for optimizing the parameters of a battery cell after electrolyte filling and settling includes the following steps: Experimental methods were used to obtain raw data on the change of OCV over time during the static settling process after the electrolyte injection of the experimental battery cells; By using a data fitting method and combining the original data of OCV change over time in the experimental cells, the OCV-time fitting equation for the current injection volume and static temperature was obtained. By differentiating the OCV-time fitting equation, the optimal immersion time for the current injection volume and static temperature is obtained.
[0007] The second aspect of the present invention provides a system for optimizing parameters during the static setting period after electrolyte injection of battery cells.
[0008] A system for optimizing parameters during the post-filling and settling period of a battery cell includes: The experimental data acquisition module is configured to: adopt experimental methods to acquire raw data on the change of OCV over time during the static settling process after the electrolyte injection process of the experimental battery cell; The experimental data fitting module is configured to: use a data fitting method, combined with the original data of the experimental cell OCV change over time, to obtain the OCV-time fitting equation at the current injection volume and static temperature; The optimal immersion time calculation module is configured to: differentiate the OCV-time fitting equation to obtain the optimal immersion time at the current injection volume and static temperature.
[0009] A third aspect of the present invention provides a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps in the method for optimizing the parameters of the battery cell after electrolyte injection as described in the first aspect of the present invention.
[0010] The fourth aspect of the present invention provides an electronic device, including a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps in the method for optimizing the static parameters after electrolyte injection of the battery cell as described in the first aspect of the present invention.
[0011] The above one or more technical solutions have the following beneficial effects: This invention provides a method and system for optimizing the static parameters of a battery cell after electrolyte injection. The OCV-time fitting equation y=ax is obtained through data acquisition and data fitting. 2 +bx+c, and then through calculation, x=-b / 2a is obtained as the optimal resting time. Experiments have shown that the battery cells obtained after implementing the method of the present invention generally have higher performance than those obtained without applying this embodiment, proving the effectiveness of the method of the present invention.
[0012] This invention eliminates the need for disassembly and directly obtains optimal resting parameters through data acquisition and calculation, achieving efficient and safe results. Compared to cells produced using existing process parameters, the method employed in this invention provides better wetting effects and improved cycle and storage performance.
[0013] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description
[0014] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.
[0015] Figure 1 This is a flowchart of the method in Example 1.
[0016] Figure 2 This is the OCV-time curve for Example 1.
[0017] Figure 3 This is a comparison chart showing the high-temperature cycle performance test results of a lithium-ion battery obtained using the method of this invention and a lithium-ion battery left to stand with existing parameters.
[0018] Figure 4 This is a comparison chart showing the storage performance test results of a lithium-ion battery obtained using the method of this invention and a lithium-ion battery using existing static parameters. Detailed Implementation
[0019] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.
[0020] It should be noted that the terminology used herein is for the purpose of describing particular implementations only and is not intended to limit the exemplary implementations of the present invention.
[0021] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.
[0022] Example 1 Lithium-ion cells have an initial voltage after electrolyte injection but before formation, which is mainly related to the following three reasons: (1) Ion conduction effect of electrolyte: The electrolyte activates the electrochemical reaction between the positive and negative electrodes, making lithium ion migration and charge separation possible, thereby forming a potential difference between the electrodes. This process is the key step for the battery to change from an "inactive" state to an "electrochemically active" state. (2) Intrinsic potential difference of electrode material: After electrolyte injection, the electrolyte wets the electrode, and the positive and negative electrodes form an ion pathway through the electrolyte. The potential difference of the material directly leads to the generation of open circuit voltage.
[0023] (3) Electric double layer effect on electrode surface: When the electrolyte wets the electrode surface, an electric double layer (charge separation layer) will be formed at the interface between the positive and negative electrode materials and the electrolyte. This charge separation will generate an instantaneous potential difference, contributing to the initial voltage.
[0024] Therefore, as the wettability of the electrolyte increases, the OCV before formation will continuously rise until it stabilizes. Based on this characteristic, this invention proposes a method for optimizing the settling parameters after electrolyte injection into the battery cell. This method can quickly and safely determine the optimal settling parameters.
[0025] like Figure 1 As shown, a method for optimizing the parameters of a battery cell after electrolyte filling and settling includes the following steps: Experimental methods were used to obtain raw data on the change of OCV over time during the static settling process after the electrolyte injection of the experimental battery cells; By using a data fitting method and combining the original data of OCV change over time in the experimental cells, the OCV-time fitting equation for the current injection volume and static temperature was obtained. By differentiating the OCV-time fitting equation, the optimal immersion time for the current injection volume and static temperature is obtained.
[0026] Furthermore, the raw data of OCV changes over time during the settling period after the electrolyte injection process of the experimental cells were obtained, specifically including: Take n experimental cells and complete the electrolyte injection according to the designed electrolyte injection volume; After the electrolyte is injected, the injection port of the experimental cell is plugged with a rubber nail to prevent the electrolyte from evaporating. Set the ambient temperature to T, and let the experimental cell stand for t hours after liquid injection, monitoring the cell voltage during this period.
[0027] Furthermore, the number of experimental battery cells, n, is ≥ 30.
[0028] Furthermore, using a data fitting method, combined with the original data of OCV changes over time in the experimental cells, the OCV-time fitting equations for the current injection volume and static temperature were obtained, specifically including: From the raw data of OCV changes of experimental cells over time, time points are selected at set time intervals, and the data is filtered according to the selected time points to obtain OCV value-time data pairs of multiple experimental cells at each corresponding time point. The average OCV value-time data pair of multiple experimental cells at each corresponding time point is obtained by averaging the OCV values in the OCV value-time data pair. Plot a curve using the average OCV value minus the time data at each corresponding time point, where time is the horizontal axis and the average OCV value is the vertical axis; Based on the plotted curve, fit the quadratic equation y=ax 2 +bx+c, we get the values of parameters a, b, and c.
[0029] Furthermore, by differentiating the OCV-time fitting equation, the optimal immersion time for the current injection volume and settling temperature is obtained, specifically including: Find the fitted quadratic equation y=ax 2 The time derivative of +bx+c; Let the quadratic equation y=ax 2 The derivative of +bx+c with respect to time is 0, so x = -b / 2a is calculated. Based on the obtained values of parameters a and b, the value of x = -b / 2a is obtained, which is the optimal immersion time.
[0030] This also includes, after obtaining the preferred immersion time at the current injection volume and settling temperature: Write the current injection volume, settling temperature, and corresponding preferred soaking time into a table, and create an index table based on the current injection volume and settling temperature; Change the injection volume and / or settling temperature, re-obtain the corresponding preferred immersion time, and update the index table based on the changed injection volume, settling temperature, and corresponding preferred immersion time.
[0031] It also includes, according to the preferred immersion time, allowing the cells to stand at the same liquid injection volume and standing temperature as the experimental cells, specifically including: Obtain the electrolyte injection volume and settling temperature of the battery cell to be settling; Based on the electrolyte injection volume and settling temperature of the cells to be settling, the index numbers in the updated index table are filtered to obtain the corresponding target index numbers; Obtain the preferred immersion time corresponding to the target index number, which is the preferred immersion time for the battery cell to be left to stand. The cells to be placed are placed according to the preferred immersion time.
[0032] The execution process of this embodiment will be explained in detail below with specific implementation steps.
[0033] Figure 1 This embodiment illustrates a flowchart of a method for optimizing parameters during the post-filling and settling period of a battery cell, as provided in this example. This method, applicable to lithium iron phosphate battery cells, is generally completed in three stages: first, data collection; second, data processing; and third, obtaining optimized parameters. The specific steps are as follows: Phase 1: S1: Take n cells and complete the liquid injection according to the designed liquid injection volume, n≥30EA (According to the central limit theorem, when the sample size is ≥30, the distribution of the sample mean is approximately normal). S2: After the lithium iron phosphate cell has been injected with electrolyte, plug the injection port with a rubber nail to prevent the electrolyte from evaporating. Let it stand on the OCV machine for t hours (t≤100h) and set the ambient temperature T (T≤60℃). During this period, use the OCV machine to monitor the cell voltage.
[0034] Phase Two: S3: Take the average value of the OCV data of n cells collected at the same time and plot the curve, where the OCV data of the cells is the vertical axis and the time is the horizontal axis; S4: Fit a quadratic equation y=ax based on the data curve. 2 +bx+c.
[0035] Phase Three: S5: After differentiating the fitted equation, set the derivative to 0 and calculate x = -b / 2a. This x is the optimal immersion time under this condition.
[0036] Furthermore, this also includes, after obtaining the preferred immersion time at the current injection volume and settling temperature: Write the current injection volume, settling temperature, and corresponding preferred soaking time into a table, and create an index table based on the current injection volume and settling temperature; Change the injection volume and / or settling temperature, re-obtain the corresponding preferred immersion time, and update the index table based on the changed injection volume, settling temperature, and corresponding preferred immersion time.
[0037] It also includes, according to the preferred immersion time, allowing the cells to stand at the same liquid injection volume and standing temperature as the experimental cells, specifically including: Obtain the electrolyte injection volume and settling temperature of the battery cell to be settling; Based on the electrolyte injection volume and settling temperature of the cells to be settling, the index numbers in the updated index table are filtered to obtain the corresponding target index numbers; Obtain the preferred immersion time corresponding to the target index number, which is the preferred immersion time for the battery cell to be left to stand. The cells to be placed are placed according to the preferred immersion time.
[0038] Next, we will use a specific application scenario to illustrate the implementation process of this embodiment for optimizing the standing parameters after electrolyte injection in lithium iron phosphate cells. Through experiments, we will demonstrate the effectiveness of using the scheme of this embodiment to determine the electrolyte wetting effect and obtain better standing parameters.
[0039] Phase 1: S1: Take 40 lithium iron phosphate cells and complete the electrolyte injection according to the designed injection volume of 240g; S2: After electrolyte injection, plug the electrolyte injection port of the cell with rubber nails to prevent electrolyte evaporation, let it stand on the OCV machine for 80 hours, set the ambient temperature to 40℃, and monitor the cell voltage with the OCV machine during this period.
[0040] Phase Two: S3: After filtering the collected OCV data of 40 cells at 0, 4, and 8 every 4 hours, take the average value and plot a curve, where the cell OCV data is the vertical axis and time is the horizontal axis. S4: Draw based on data Figure 2 The OCV-time curve was fitted to obtain the OCV-time quadratic equation y = -0.0088x. 2 +0.92x+168.79, where a is -0.0088 and b is 0.92.
[0041] Phase Three: S5: The result is x = -b / 2a = 52, indicating that with an injection volume of 240g and a standing temperature of 40℃, a standing time of 52h is the time for complete immersion.
[0042] Table 1 shows the OCV-time fitting equations and optimal settling times obtained under different injection volumes and settling temperatures. It can be seen that the optimal settling temperature is 240g injection volume and 45℃ settling temperature, at which time the settling time is 48h.
[0043] Table 1. Optimal settling time for different injection volumes and settling temperatures.
[0044] Figure 3 This is a schematic diagram of the high-temperature cycle performance test results of a lithium-ion battery optimized using the static parameter method of this invention and a lithium-ion battery statically ground using existing parameters, provided by an embodiment of the present invention. The more cycles a lithium-ion battery has under the same capacity retention rate, the better its cell cycle performance.
[0045] in, Figure 3 The horizontal axis, Cycles, represents the number of cycles, and the vertical axis, Capacity retention, represents the capacity retention rate. According to... Figure 3 It can be seen that, under the same temperature conditions (taking 45 degrees Celsius as an example), the lithium-ion battery optimized by the static parameter method of the present invention (example) has more cycle cycles than the lithium-ion battery with existing static parameters (comparative example). Therefore, the high-temperature cycle performance of the lithium-ion battery optimized by the static parameter method of the present invention is better than the cycle performance of the lithium-ion battery with existing static parameters.
[0046] Figure 3The original injection parameters were not optimized using this method. For example, the original parameters were an injection volume of 240g, a standing temperature of 45℃, and a standing time of 36h. After verification, the injection parameters of 240g, a standing temperature of 45℃, and a standing time of 48h were adopted, with other conditions remaining unchanged. Under these parameters, the battery cells produced were more completely wetted and had better performance.
[0047] Figure 4 This is a schematic diagram illustrating the storage performance test results of a lithium-ion battery optimized using the static parameter method of this invention and a lithium-ion battery using existing static parameters, provided by an embodiment of the present invention. A higher capacity retention rate indicates a lower self-discharge rate, and a higher capacity recovery rate indicates better cycle performance.
[0048] Figure 4 The horizontal axis represents the experimental groups, including the examples (lithium-ion batteries optimized using the resting parameter method of the present invention) and the comparative examples (lithium-ion batteries using existing resting parameters). The vertical axis represents the capacity retention rate and capacity recovery rate.
[0049] according to Figure 4 It can be seen that, under the same temperature and time conditions (taking the test conditions of 45℃ & 30d as an example), the capacity retention rate and capacity recovery rate of the lithium-ion battery optimized by the static parameter method of the present invention are higher than those of the existing static parameter produced cells. Therefore, the storage performance of the lithium-ion battery optimized by the static parameter method of the present invention is better than that of the lithium-ion battery produced by the existing static parameters.
[0050] Example 2 This embodiment discloses a system for optimizing parameters during the static setting period after electrolyte injection in battery cells.
[0051] A system for optimizing parameters during the post-filling and settling period of a battery cell includes: The experimental data acquisition module is configured to: adopt experimental methods to acquire raw data on the change of OCV over time during the static settling process after the electrolyte injection process of the experimental battery cell; The experimental data fitting module is configured to: use a data fitting method, combined with the original data of the experimental cell OCV change over time, to obtain the OCV-time fitting equation at the current injection volume and static temperature; The optimal immersion time calculation module is configured to: differentiate the OCV-time fitting equation to obtain the optimal immersion time at the current injection volume and static temperature. Example 3 The purpose of this embodiment is to provide a computer-readable storage medium.
[0052] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the method for optimizing the parameters of the battery cell after liquid injection as described in Embodiment 1 of this disclosure.
[0053] Example 4 The purpose of this embodiment is to provide an electronic device.
[0054] An electronic device includes a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the method for optimizing the static parameters after electrolyte injection of a battery cell as described in Embodiment 1 of this disclosure.
[0055] The steps and methods involved in the apparatuses of Embodiments 2, 3, and 4 above correspond to those in Embodiment 1. For specific implementation details, please refer to the relevant description section of Embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood as including any medium capable of storing, encoding, or carrying an instruction set for execution by a processor and enabling the processor to perform any of the methods in this invention.
[0056] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computer device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. The present invention is not limited to any particular combination of hardware and software.
[0057] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.
Claims
1. A method for optimizing the resting parameters of an electrochemical cell after liquid injection, characterized in that, The method comprises the following steps: An experimental method is adopted to obtain the original data of the change of the OCV of the experimental battery with time during the standing process after the liquid injection process; A data fitting method is adopted to obtain the OCV-time fitting equation under the current injection amount and standing temperature, in combination with the original data of the change of the OCV of the experimental battery with time; The OCV-time fitting equation is differentiated to obtain the optimal soaking time under the current injection amount and standing temperature.
2. The method for optimizing the parameters of the battery cell after electrolyte injection as described in claim 1, characterized in that, An experimental method is adopted to obtain the original data of the change of the OCV of the experimental battery with time during the standing process after the liquid injection process, specifically comprising: n experimental batteries are taken, and the liquid injection is completed according to the designed injection amount; The injection port of the experimental battery after the liquid injection is plugged with a rubber pin to prevent the electrolyte from volatilizing; The environmental temperature is set to T, and the experimental battery after the liquid injection is stood for t hours, during which the voltage of the experimental battery is monitored.
3. The method for optimizing the parameters of the battery cell after electrolyte injection and settling as described in claim 2, characterized in that, The number n of the experimental batteries is greater than or equal to 30.
4. The method for optimizing the parameters of the battery cell after electrolyte injection and settling as described in claim 1, characterized in that, A data fitting method is adopted to obtain the OCV-time fitting equation under the current injection amount and standing temperature, in combination with the original data of the change of the OCV of the experimental battery with time, specifically comprising: From the original data of the change of the OCV of the experimental battery with time, time points are selected every set time interval, data filtering is performed according to the selected time points, and the OCV value-time data pairs of the multiple experimental batteries at each corresponding time point are obtained; The OCV values in the OCV value-time data pairs of the multiple experimental batteries at each corresponding time point are averaged to obtain the average OCV value-time data pair at each corresponding time point; A curve is drawn by using the average OCV value-time data pair at each corresponding time point, wherein the time is the horizontal coordinate and the average OCV value is the vertical coordinate; Based on the plotted curve, a quadratic equation y = ax + bx + c is fitted to obtain the values of each parameter a, b, and c. 2 +bx+c, to obtain the values of each parameter a, b, and c.
5. The method for optimizing the parameters of the battery cell after electrolyte injection and settling as described in claim 4, characterized in that, The OCV-time fitting equation is differentiated to obtain the optimal soaking time under the current injection amount and standing temperature, specifically comprising: deriving a derivative of the fitted quadratic equation y = ax 2 + bx + c with respect to time; Let the derivative of the quadratic equation y = ax 2 + bx + c with respect to time be equal to zero, and solve for x = -b / 2a. Based on the obtained a and b parameter values, the value of x=-b / 2a is obtained, which is the optimal soaking time.
6. The method for optimizing the parameters of the battery cell after electrolyte injection and settling as described in claim 1, characterized in that, Further comprising, after obtaining the optimal soaking time under the current injection amount and standing temperature: The current injection amount and standing temperature and the corresponding optimal soaking time are written into a table, an index table is constructed based on the current injection amount and standing temperature, and an index number is formed; The injection amount and / or the standing temperature are changed, the corresponding optimal soaking time is re-obtained, and the index table is updated based on the changed injection amount and standing temperature and the corresponding optimal soaking time.
7. The method for optimizing the parameters of the battery cell after electrolyte injection and settling as described in claim 6, characterized in that, Further comprising, standing the to-be-stood battery with the same injection amount and standing temperature as the experimental battery according to the optimal soaking time, specifically comprising: The injection amount and standing temperature of the to-be-stood battery are obtained; The index number in the updated index table is filtered according to the injection amount and standing temperature of the to-be-stood battery, and the corresponding target index number is obtained; The optimal soaking time corresponding to the target index number is obtained, which is the optimal soaking time of the to-be-stood battery; The to-be-stood battery is stood according to the optimal soaking time of the to-be-stood battery.
8. A system for optimizing parameters during the static settling period after electrolyte injection in a battery cell, characterized in that, It comprises: An experimental data acquisition module configured to adopt an experimental method to obtain the original data of the change of the OCV of the experimental battery with time during the standing process after the liquid injection process; The experimental data fitting module is configured to obtain an OCV-time fitting equation under the current liquid injection amount and the standing temperature by using a data fitting method in combination with original data of OCV change over time of the experimental battery cell; The preferred soaking time calculation module is configured to obtain a preferred soaking time under the current liquid injection amount and the standing temperature by deriving the OCV-time fitting equation.
9. A computer-readable storage medium having stored thereon a program, characterized in that, The program, when executed by the processor, implements the steps in the preferred method for standing parameters after liquid injection of the battery cell according to any one of claims 1-7.
10. An electronic device comprising a memory, a processor, and a program stored on the memory and executable on the processor, characterized in that, The program, when executed by the processor, implements the steps in the preferred method for standing parameters after liquid injection of the battery cell according to any one of claims 1-7.