Lithium ion battery charging strategy optimization method

Abstract

The invention discloses a lithium ion battery charging strategy optimization method comprising the following steps: carrying out SOC-OCV test on a lithium ion battery to obtain an SOC-OCV-T matrix table; performing three-electrode different-temperature charging test on the lithium ion battery to form an I-SOC-U-Tmax matrix table at different temperatures; the I-SOC-U-Tmax matrix table is integrated to form a 0-100% SOC charging matrix table; according to the SOC-OCV-T matrix table, the discharging end voltage and the SOC state are searched, and charging is carried out in combination with the SOC state and the 0-100% SOC charging matrix table; and a charging strategy that the charging current I of the single lithium ion battery changes in real time along with the SOC and the temperature T is obtained in a circulating charging and discharging mode. According to the method, the matrix table is constructed through multiple tests, and dynamic cyclic charging and discharging are performed, so that a quick charging strategy that the charging current I of the single lithium ion battery changes in real time along with the SOC and the temperature T is realized, and the charging efficiency and the safety of the lithium ion battery are effectively improved.

Description

Technical Field

[0001] This invention relates to the field of lithium-ion battery charging strategy technology, and in particular to an optimization method for lithium-ion battery charging strategy. Background Technology

[0002] In recent years, against the backdrop of global efforts to limit climate change and reduce air pollution, lithium-ion batteries have seen rapid development in the application of pure electric vehicles due to their advantages such as high energy density and long cycle life, becoming one of the core driving forces for the advancement of the new energy vehicle industry.

[0003] However, compared to traditional gasoline-powered vehicles, electric vehicles still face many pressing issues during their development, with range anxiety and excessively long charging times being key factors hindering their further widespread adoption. Therefore, improving the fast-charging capability of lithium-ion batteries and shortening charging time has become a crucial research and development goal pursued by both battery manufacturers and vehicle manufacturers.

[0004] Currently, most conventional fast-charging methods for lithium-ion battery cells employ a constant current charging to a specified SOC (State of Charge) or voltage. This method has significant limitations: firstly, it does not fully consider the impact of cell temperature changes during high-current charging on the SOC-OCV (State of Charge-Open Circuit Voltage) characteristics of individual cells. Temperature changes often alter the battery's electrochemical performance, thus affecting charging efficiency and safety. Secondly, this method does not incorporate the dynamic control factors of the charging current by the BMS (Battery Management System) in actual usage scenarios.

[0005] For example, invention application No. 202411708148.0 discloses a method for determining a lithium-ion battery charging strategy and a charging method. The solution in this application improves the accuracy and efficiency of the charging strategy formulation. However, its solution also has the problem of affecting charging efficiency and safety by using a constant current to charge to a specified SOC (state of charge) or voltage.

[0006] These limitations make the relationship between the performance of individual battery cells in testing and their actual degradation rate after integration into a battery pack unclear. Many charging strategies that have proven effective in individual battery cell testing often exhibit problems such as uneven temperature distribution and inconsistent current density when applied to a pack composed of multiple individual cells. This not only fails to achieve the expected fast charging effect but may also adversely affect the battery pack's lifespan and safety.

[0007] Therefore, in order to make the fast charging test of individual cells more in line with actual application scenarios, improve the effectiveness and feasibility of its application in the pack, reduce the testing cost of the overall R&D project, and optimize the integration of individual cells and pack design, it is urgent to develop a new lithium-ion battery charging strategy that can comprehensively consider multiple influencing factors. Summary of the Invention

[0008] To address the aforementioned problems, the present invention aims to provide an optimization method for lithium-ion battery charging strategies. By employing methods such as SOC-OCV testing and single-cell three-electrode testing, a SOC-OCV-T matrix table for lithium-ion batteries is constructed, forming a 0-100% SOC charging matrix table, thereby optimizing the charging strategy that optimizes the real-time variation of charging current I with SOC and temperature T.

[0009] The objective of this invention can be achieved through the following technical solution: an optimization method for lithium-ion battery charging strategy, comprising:

[0010] S1. Perform SOC-OCV tests on lithium-ion batteries at different temperatures, and derive the SOC-OCV-T matrix table based on the test data;

[0011] S2. Conduct three-electrode charging tests on lithium-ion batteries at different temperatures to determine the current I and temperature T at different SOC stages under different temperatures. max Forming I-SOC-UT at different temperatures max Matrix table;

[0012] S3, Integrated I-SOC-UT max The matrix table forms a charging matrix table from 0-100% SOC;

[0013] S4. Find the discharge end voltage and SOC status according to the SOC-OCV-T matrix table, and charge according to the SOC status and the 0-100% SOC charging matrix table.

[0014] S5 and S4 cyclic charging and discharging modes are used to obtain the real-time charging strategy of lithium-ion battery cell charging current I as a function of SOC and temperature T.

[0015] As a further embodiment of the present invention, the step of obtaining the SOC-OCV-T matrix table in S1 includes:

[0016] S11. Determine the capacity C at room temperature by performing at least 3 charge-discharge cycles with a standard current at room temperature;

[0017] S12. Adjust the state of charge (SOC) of the lithium-ion battery to the target value by discharging with standard current.

[0018] S13. Adjust the ambient temperature of the lithium-ion battery, let it stand for no less than 2 hours, and measure the OCV value at the current temperature until the target temperature is reached.

[0019] S14. Repeat steps S12 and S13 until the SOC-OCV-T matrix table is obtained.

[0020] As a further embodiment of the present invention, in the SOC-OCV test, the test gradient includes a 1% gradient, a 2% gradient, a 5% gradient, or a 10% gradient.

[0021] As a further embodiment of the present invention, in S2, I-SOC-UT max The steps to obtain the matrix table include:

[0022] With a reference voltage greater than 10mV, constant current and constant voltage charging was performed at different test temperatures until the upper limit cutoff voltage was reached, and the SOC charging stage temperature T was recorded at different test temperatures. max Forming I-SOC-UT at different temperatures max Matrix table.

[0023] As a further embodiment of the present invention, the reference voltage is the voltage between the negative electrode and the reference electrode, wherein when the voltage measuring device is connected to the negative electrode and the reference electrode, the reference electrode is the negative electrode.

[0024] As a further aspect of the present invention, obtaining I-SOC-UT max When using a matrix table, constant current and constant voltage charging is performed using different multiplier currents I1.

[0025] As a further embodiment of the present invention, the cyclic S4 charge-discharge method includes the following steps:

[0026] S41. Perform standard charge and discharge on the battery to determine its standard discharge capacity C0;

[0027] S42. Based on the current SOC value and battery surface temperature T, determine the charging current I by referring to the 0-100% SOC charging matrix table;

[0028] S43. After discharging the battery, determine the current discharge capacity as C. n Given the current voltage U, determine the SOC value corresponding to the current voltage U based on the SOC-OCV-T matrix table;

[0029] S44. Repeat S41-S43 until the target battery cycle life or cycle number is reached, and obtain the charging strategy of real-time change of lithium-ion battery cell charging current I with SOC and temperature T.

[0030] As a further embodiment of the present invention, the battery is charged with reference to a 0-100% SOC charging matrix table, and the battery charging capacity C is monitored during the charging process. x And the battery surface temperature T, through the charging capacity C x The ratio of the current state of charge (SOC) to the standard discharge capacity C0 confirms the current state of charge (SOC), i.e., SOC = C0. x / C0*100%.

[0031] As a further embodiment of the present invention, in S42, the battery is left to stand for at least 30 minutes after charging is completed, and in S43, the battery is left to stand for at least 30 minutes after discharging.

[0032] As a further aspect of the present invention, the BMS in the Pack package implements a charging strategy in which the reference lithium-ion battery cell charging current I changes in real time with SOC and temperature T.

[0033] The beneficial effects of this invention are:

[0034] 1. The optimized strategy of this invention, through SOC-OCV testing, three-electrode testing, and extreme charging current testing, can simulate the current control logic of the BMS on the pack. Compared with the traditional constant current fast charging method, it fully considers the impact of cell temperature changes on SOC-OCV during high-current charging, as well as the control role of the BMS in actual use. This makes the fast charging test data of individual cells more consistent with the actual application scenarios of the pack, effectively solving the problem that while individual cells are effective, the pack application is prone to uneven temperature and current density distribution under the traditional strategy. This makes the application of individual cell fast charging performance in the pack more valuable for reference.

[0035] 2. The optimization strategy of this invention integrates multi-dimensional tests to form a standardized matrix table, such as the SOC-OCV-T matrix table and the 0-100% SOC charging matrix table. This eliminates the need for extensive and repetitive matching tests on individual cells and packs, and can directly guide fast charging testing and design based on the matrix table. At the same time, by clarifying the dynamic change law of individual cell charging current with SOC and temperature, it can optimize the battery cell integration scheme and pack structure design in a targeted manner, reducing the repeated adjustments and testing costs caused by unreasonable design, and significantly reducing the time and financial investment of the overall R&D project.

[0036] 3. The optimized strategy of this invention adopts a dynamic matrix fast charging mode, where the charging current I changes in real time with SOC and temperature T. Furthermore, it rigorously monitors the negative electrode potential through a three-electrode test, stopping charging when the voltage between the negative electrode and the reference electrode falls below 10mV to avoid overcharging risks. Combined with the SOC-OCV-T matrix table, it accurately determines the cell status, ensuring that the cell voltage and temperature remain within safe ranges during charging and discharging. This testing method, which aligns with the actual usage scenarios of new energy vehicles, can expose potential problems of individual cells under complex operating conditions in advance, ensuring the fast charging safety and cycle life reliability of the battery in practical applications. Attached Figure Description

[0037] Figure 1 This is a flowchart illustrating the principle of the optimized lithium-ion battery charging strategy of the present invention. Detailed Implementation

[0038] Embodiments of the present invention are described in detail below. Examples of these embodiments are illustrated in the accompanying drawings, wherein the same or similar symbols denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0039] Current conventional fast charging methods for individual battery cells do not consider the impact of cell temperature changes during high-current charging on the SOC-OCV of individual cells, nor do they take into account the BMS's current control during actual use. This leads to an unclear relationship between the degradation rate of individual cells and the battery pack. While many charging strategies are effective on individual cells, their application to the battery pack may result in uneven temperature and current density distribution. Therefore, new fast charging testing methods for individual battery cells that are more closely aligned with real-world application scenarios are needed.

[0040] Example 1: Regarding the problems mentioned above, such as... Figure 1 As shown in the figure, this embodiment discloses an optimization method for lithium-ion battery charging strategy, including the following steps:

[0041] S1. Perform SOC-OCV tests on lithium-ion batteries at different temperatures, and derive the SOC-OCV-T matrix table based on the test data.

[0042] SOC-OCV tests were conducted on lithium-ion batteries at different temperatures. Based on the test data, an SOC-OCV-T matrix table was obtained. The SOC range can be adjusted according to requirements, such as 1% gradient, 2% gradient, 5% gradient, or 10% gradient. For example, Table 1 shows the SOC-OCV-T matrix table of a certain battery with a gradient of 5%.

[0043] Table 1 Battery SOC-OCV-T Matrix

[0044]

[0045] Specifically, obtaining the SOC-OCV-T matrix table includes the following steps:

[0046] S11, determine the capacity C at room temperature by performing at least 3 charge-discharge cycles with a standard current at room temperature (e.g., 25°C).

[0047] S12, adjust the state of charge (SOC) of the lithium-ion battery to the target value (e.g., 30.00%) by discharging with a standard current.

[0048] S13. With the SOC at the target value, adjust the ambient temperature of the lithium-ion battery (e.g., -25°C, -10°C, 0°C, 10°C, etc. as shown in Table 1), and let it stand for no less than 2 hours each time. Measure the OCV value at the current ambient temperature (e.g., as shown in Table 1: when the SOC is 30.00% and the ambient temperature is -25°C, the OCV value is 3.297) until the target temperature is reached.

[0049] S14, change the battery SOC state to the new target value, repeat step S13 until the SOC-OCV-T matrix table is obtained.

[0050] S2. Conduct three-electrode charging tests on lithium-ion batteries at different temperatures to determine the current I and temperature T at different SOC stages under different temperatures. max Forming I-SOC-UT at different temperatures max Matrix table.

[0051] The lithium-ion battery was charged at different rates and currents (I1) at different electrode temperatures. The reference voltages of the negative electrode and the reference electrode were recorded in real time. Charging was stopped when the reference voltage between the negative electrode and the reference electrode was less than 10mV. If the reference voltage was greater than 10mV during charging, the upper limit cutoff voltage was used, and the temperature T at the current charging stage was recorded. max .

[0052] Through data integration and analysis, the current I and temperature T at different SOC stages under different temperatures were determined. max Forming I-SOC-UT at different temperatures max Matrix table, for example: Table 2 shows the I-SOC-UT of a certain battery. max Matrix table.

[0053] Table 2 Battery I-SOC-UT max Matrix

[0054]

[0055] Obtaining I-SOC-UT maxThe specific process of creating a matrix table includes:

[0056] With a reference voltage greater than 10mV, constant current and constant voltage charging was performed at different test temperatures using different rate currents (I1) until the upper limit cutoff voltage was reached. The SOC charging stage temperature (T) was recorded at different test temperatures. max Forming I-SOC-UT at different temperatures max Matrix table.

[0057] Among them, the three electrodes refer to the positive electrode, the negative electrode, and the reference electrode, and the reference voltage refers to the voltage between the negative electrode and the reference electrode.

[0058] The voltage measuring device is connected to the negative electrode and the reference electrode, with the reference electrode being the negative electrode. Constant current and constant voltage charging is performed at different rates (I1) at different temperatures. Taking the real-time recording of the reference voltage between the negative electrode and the reference electrode as an example, charging stops when the reference voltage between the negative electrode and the reference electrode is less than 10mV. If both are greater than 10mV, charging continues until the upper limit cutoff voltage is reached, and the temperature T at the current charging stage is recorded. max .

[0059] S3, Integrated I-SOC-UT max The matrix table forms a charging matrix table from 0-100% SOC.

[0060] Refine and integrate I-SOC-UT max The matrix table forms a 0-100% SOC charging matrix table. For example, Table 3 shows a certain battery cell integrating I-SOC-UT. max The matrix table forms a charging matrix table from 0-100% SOC.

[0061] Table 3 Battery 0-100% SOC Charging Matrix

[0062]

[0063] S4. Find the discharge end voltage and the current SOC state of the cell according to the SOC-OCV-T matrix table, and charge the cell by combining the SOC state and the 0-100% SOC charging matrix table.

[0064] The current battery SOC is determined based on the SOC-OCV-T matrix table. Dynamic charging and standard discharging are performed according to the 0-100% SOC charging matrix table. Then, the voltage at the end of discharging and the current SOC state of the cell are found again according to the SOC-OCV-T matrix table. Then, charging is performed again by combining the SOC state and the 0-100% SOC charging matrix table. By repeating the above charging and discharging methods, a fast charging test method is achieved that shows the real-time change of lithium-ion cell charging current I with SOC and temperature T matrix.

[0065] The specific steps include:

[0066] S41. Perform standard charge and discharge on the battery to determine its standard discharge capacity C0;

[0067] S42. Based on the current SOC value and battery surface temperature T, determine the charging current I by referring to the 0-100% SOC charging matrix table. After charging is completed, let the battery stand for at least 30 minutes.

[0068] S43. After discharging the battery, let it rest for at least 30 minutes to determine the current discharge capacity as C. n Given the current voltage U, determine the SOC value corresponding to the current voltage U based on the SOC-OCV-T matrix table;

[0069] S44. Repeat S41-S43 until the target battery cycle life or cycle number is reached, and obtain the charging strategy of real-time change of lithium-ion battery cell charging current I with SOC and temperature T.

[0070] Specifically, the battery is charged with reference to the 0-100% SOC charging matrix table, and the battery charging capacity C is monitored during the charging process. x And the battery surface temperature T, through the charging capacity C x The ratio of the current state of charge (SOC) to the standard discharge capacity C0 confirms the current state of charge (SOC), i.e., SOC = C0. x / C0*100%.

[0071] Furthermore, the charging strategy of the reference lithium-ion battery cell charging current I, which varies in real time with SOC and temperature T, is considered in the BMS of the Pack for current control. This allows for the simulation of the BMS's current control logic for the Pack. Compared to traditional constant current fast charging methods, this approach fully considers the impact of cell temperature changes on SOC-OCV during high-current charging, as well as the control role of the BMS in actual use. This makes the fast charging test data for individual cells more consistent with the actual application scenarios of the Pack, effectively solving the problem that while individual cells are effective under traditional strategies, the Pack application is prone to uneven temperature and current density distribution. This makes the application of individual cell fast charging performance in the Pack more valuable for reference.

[0072] This optimization method, through the above series of steps, can effectively optimize the charging strategy of lithium-ion batteries. In practical applications, this method can significantly improve the charging efficiency and safety of lithium-ion batteries.

[0073] In terms of charging efficiency, through a precise SOC-OCV-T matrix table and I-SOC-UT... max The matrix table can dynamically adjust the charging current based on the current state of the battery and the ambient temperature.

[0074] For example, when the battery level is low and the temperature is suitable, a larger charging current can be used for fast charging, thereby shortening the overall charging time. At the same time, because the charging current is dynamically adjusted according to the battery's actual state of charge (SOC), overcharging and undercharging are avoided, helping to extend the battery's lifespan.

[0075] In terms of safety, this optimization method is of great significance. During charging, considering the reference voltage between the negative electrode and the reference electrode, charging is stopped when the voltage falls below 10mV. This effectively prevents lithium metal deposition on the negative electrode surface, reducing the risk of battery short circuits and thermal runaway. Furthermore, by recording the temperature T at different charging stages... max It can promptly detect abnormal heating of the battery during the charging process, so that corresponding measures can be taken to ensure the safe use of the battery.

[0076] Furthermore, this optimization method also exhibits good versatility and scalability. Different types and specifications of lithium-ion batteries can be adapted through corresponding testing and data integration to generate suitable SOC-OCV-T matrix tables and I-SOC-UT tables. max This matrix table enables personalized charging strategy optimization. Furthermore, with the continuous development of battery technology and the increasing diversification of battery application scenarios, this method can be further improved and refined based on new needs and data to adapt to different usage environments and requirements.

[0077] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

[0078] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "over," and "on top" of the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

Claims

1. An optimization method for lithium-ion battery charging strategy, characterized in that, include: S1. Perform SOC-OCV tests on lithium-ion batteries at different temperatures, and derive the SOC-OCV-T matrix table based on the test data; S2. Conduct three-electrode charging tests on lithium-ion batteries at different temperatures to determine the current I and temperature T at different SOC stages under different temperatures. max Forming I-SOC-UT at different temperatures max Matrix table; S3, Integrated I-SOC-UT max The matrix table forms a charging matrix table from 0-100% SOC; S4. Find the discharge end voltage and SOC status according to the SOC-OCV-T matrix table, and charge according to the SOC status and the 0-100% SOC charging matrix table. S5 and S4 cyclic charging and discharging modes are used to obtain the real-time charging strategy of lithium-ion battery cell charging current I as a function of SOC and temperature T.

2. The optimization method according to claim 1, characterized in that, The steps for obtaining the SOC-OCV-T matrix table in S1 include: S11. Determine the capacity C at room temperature by performing at least 3 charge-discharge cycles with a standard current at room temperature; S12. Adjust the state of charge (SOC) of the lithium-ion battery to the target value by discharging with standard current. S13. Adjust the ambient temperature of the lithium-ion battery, let it stand for no less than 2 hours, and measure the OCV value at the current temperature until the target temperature is reached. S14. Repeat steps S12 and S13 until the SOC-OCV-T matrix table is obtained.

3. The optimization method according to claim 2, characterized in that, In the SOC-OCV test, the test gradient includes 1% gradient, 2% gradient, 5% gradient or 10% gradient.

4. The optimization method according to claim 1, characterized in that, The I-SOC-UT in S2 max The steps to obtain the matrix table include: With a reference voltage greater than 10mV, constant current and constant voltage charging was performed at different test temperatures until the upper limit cutoff voltage was reached, and the SOC charging stage temperature T was recorded at different test temperatures. max Forming I-SOC-UT at different temperatures max Matrix table.

5. The optimization method according to claim 4, characterized in that, The reference voltage is the voltage between the negative electrode and the reference electrode, wherein when the voltage measuring device is connected to the negative electrode and the reference electrode, the reference electrode is the negative electrode.

6. The optimization method according to claim 4, characterized in that, Obtaining I-SOC-UT max When using a matrix table, constant current and constant voltage charging is performed using different multiplier currents I1.

7. The optimization method according to claim 1, characterized in that, The S4 cyclic charge-discharge method includes the following steps: S41. Perform standard charge and discharge on the battery to determine its standard discharge capacity C0; S42. Based on the current SOC value and battery surface temperature T, determine the charging current I by referring to the 0-100% SOC charging matrix table; S43. After discharging the battery, determine the current discharge capacity as C. n Given the current voltage U, determine the SOC value corresponding to the current voltage U based on the SOC-OCV-T matrix table; S44. Repeat S41-S43 until the target battery cycle life or cycle number is reached, and obtain the charging strategy of real-time change of lithium-ion battery cell charging current I with SOC and temperature T.

8. The optimization method according to claim 7, characterized in that, Refer to the 0-100% SOC charging matrix table to charge the battery, and monitor the battery charging capacity C during the charging process. x And the battery surface temperature T, through the charging capacity C x The ratio of the current state of charge (SOC) to the standard discharge capacity C0 confirms the current state of charge (SOC), i.e., SOC = C0. x / C0*100%.

9. The optimization method according to claim 7, characterized in that, After the battery is fully charged in S42, it should be left to stand for at least 30 minutes. After the battery is discharged in S43, it should be left to stand for at least 30 minutes.

10. The optimization method according to any one of claims 1 to 9, characterized in that, The pack includes a BMS that controls the charging strategy of a reference lithium-ion battery cell, where the charging current I varies in real time with SOC and temperature T.

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