Negative electrode resistance measurement method, negative electrode structure, state of charge estimation method, battery and battery system

Abstract

The present invention relates to a negative electrode resistance measurement method, a negative electrode structure, a state of charge estimation method, a battery, and a battery system: comprising a negative electrode plate, a conventional tab, and a measuring tab, wherein the conventional tab is provided at one end of the negative electrode plate, and the measuring tab is provided at a measurement position on the other end of the negative electrode plate opposite to the conventional tab, and the measurement position is the position of the standard deviation of the normalized negative electrode current density measured by the measuring tab under a working state and the current density under the average current density of the battery negative electrode surface under the working state. The negative electrode resistance is measured in real time by applying a certain current excitation to the conventional tab and the testing tab; since the resistance of the battery negative electrode changes regularly with the amount of lithium inserted during the battery charging and discharging process, which is closely related to the battery state of charge, the measured negative electrode resistance is combined with a data-driven method to perform SOC estimation, thereby adding a feature dimension that is strongly correlated with SOC to the existing data-driven SOC estimation method, and further improving the accuracy of SOC estimation.

Description

Technical field

[0001] The present invention relates to the technical field of lithium-ion batteries and battery management, and in particular to a negative electrode resistance measurement method, a negative electrode structure, a state of charge estimation method, a battery, and a battery system. [Background Technology]

[0002] In recent years, the widespread adoption of electric vehicles has driven the rapid development of the lithium-ion battery industry. However, due to limitations in battery materials and cell manufacturing processes, it's difficult to guarantee absolute consistency in lithium-ion battery products, which in turn impacts the service life, safety, and reliability of battery systems. Therefore, to ensure safe and efficient operation of battery systems, management and control measures such as battery balancing and thermal management are necessary. The battery's state of charge (SOC) is fundamental to battery energy management and operational control. Accurate SOC (State of Charge) estimation can prevent overcharging or over-discharging of lithium-ion batteries, extending battery life and ensuring the safe operation of battery systems. Existing SOC estimation methods primarily estimate battery SOC by monitoring battery data such as current, voltage, and temperature, using methods such as open-circuit voltage, ampere-hour integration, a battery equivalent circuit model combined with adaptive filtering, or data-driven methods. However, among existing SOC estimation methods, the traditional open-circuit voltage method requires the battery to remain stationary for a long time to obtain an accurate open-circuit voltage, making it unsuitable for online SOC estimation. The ampere-hour integration method's estimation accuracy decreases over long battery cycles, making it difficult to meet the requirements of scenarios where the battery requires long-term operation. Methods based on battery equivalent circuit models are limited by the complex characteristics of the battery system itself, making it difficult to establish an accurate battery model for the entire battery operation cycle. Data-driven methods are limited, on the one hand, by the quality of data acquisition, and on the other hand, by the limited number of directly measurable battery parameters, which only include current, voltage, and temperature. There are also some parameters closely related to the battery's charge and discharge state that could be used to broaden the characteristic dimensions of SOC estimation and improve the accuracy of estimated SOC. However, due to the difficulty of real-time monitoring, they cannot be applied to online SOC estimation using data-driven methods. [Summary of the invention]

[0003] To solve the problems in the existing data-driven method for estimating SOC, the present invention provides a negative electrode resistance measurement method, a negative electrode structure, a state of charge estimation method, a battery, and a battery system.

[0004] In order to solve the above-mentioned technical problems, the present invention provides the following technical solutions: a negative electrode structure, comprising a negative electrode plate, a conventional electrode tab and a measuring electrode tab, wherein the conventional electrode tab is arranged at one end of the negative electrode plate, and the measuring electrode tab is arranged at a measuring position at the other end of the negative electrode plate opposite to the conventional electrode tab, and the measuring position is the position where the standard deviation of the normalized negative electrode current density measured by the measuring electrode in a working state and the current density at the average current density on the negative electrode surface of the battery in the working state is the smallest.

[0005] In order to solve the above technical problems, the present invention provides another technical solution as follows: a method for measuring negative electrode resistance, comprising the following steps: providing a battery negative electrode, one end of which is provided with a conventional tab and the other end of which is provided with a test tab; evaluating the current density distribution on the surface of the battery negative electrode through simulation, selecting the current density values ​​at several typical positions and averaging them as the average current density value of the negative electrode surface; changing the position of the measuring tab at the boundary of the setting end, and obtaining the corresponding average current density value of the negative electrode surface when the measuring tab is set at different positions; comparing the normalized standard deviation of the current density value at each typical position with the average current density value when the measuring tab is set at different positions, and determining the position of the measuring tab corresponding to the minimum normalized standard deviation as the measurement position; collecting the negative electrode resistance data of the measuring tab at the measurement position when the battery is in working state as the resistance of the negative electrode.

[0006] Preferably, a first range is set for the negative electrode resistance data; when the negative electrode resistance data is within the first range, it is determined to be in a stable state, and the negative electrode resistance data is in a measurable state.

[0007] To solve the above technical problems, the present invention provides another technical solution as follows: a method for estimating state of charge, providing initial data for training and constructing a data-driven model, wherein the initial data includes current, voltage parameters and electrode resistance data;

[0008] Acquire test data from the battery under test in real time, use the test data as input to the data-driven model, and output an estimated value of the SOC. The test data includes current parameters, voltage parameters, and negative electrode resistance parameters measured using the negative electrode resistance measurement method described above.

[0009] Preferably, the data-driven model includes but is not limited to at least one of an integrated decision tree model, a support vector regression and a neural network algorithm.

[0010] In order to solve the above technical problems, the present invention provides another technical solution as follows: a battery comprising the above-mentioned negative electrode structure.

[0011] Preferably, the negative electrode plate includes a first current collector layer and an active material layer stacked together, the conventional tab and the measuring tab are respectively connected to the first current collector layer and the active material layer, the positive electrode plate is provided with a second current collector, and the positive electrode tab is fixedly connected to the second current collector; at least one of the negative electrode materials including but not limited to graphite, silicon carbon, alloy, lithium titanate and various oxides is stacked on the active material connection area.

[0012] Preferably, the battery further comprises a positive electrode structure arranged opposite to the negative electrode structure and a separator arranged between the positive and negative electrode structures.

[0013] In order to solve the above technical problems, the present invention provides another technical solution as follows: a battery system, including a negative electrode structure or a battery as described above.

[0014] Compared with the prior art, the negative electrode resistance measurement method, negative electrode structure, state of charge estimation method, battery, and battery system provided by the present invention have the following beneficial effects:

[0015] 1. An embodiment of the present invention also provides a negative electrode structure for use in the negative electrode resistance measurement method as described above, comprising a negative electrode plate, a conventional tab, and a measuring tab, wherein the conventional tab is arranged at one end of the negative electrode plate, and the measuring tab is arranged at a measurement position on the other end of the negative electrode plate opposite to the conventional tab, wherein the measurement position is the position where the standard deviation of the negative electrode current density measured by the measuring tab in the working state and the current density normalized under the average current density of the negative electrode surface of the battery in the working state is the smallest.

[0016] 2. A negative electrode resistance measurement method provided by an embodiment of the present invention includes the following steps: providing a battery negative electrode, one end of which is provided with a conventional tab and the other end of which is provided with a test tab; evaluating the current density distribution on the surface of the battery negative electrode through simulation, selecting the current density values ​​at several typical positions and averaging them as the average current density value of the negative electrode surface; changing the position of the measuring tab at the boundary of the setting end, and obtaining the corresponding average current density values ​​of the negative electrode surface when the measuring tab is set at different positions; comparing the normalized standard deviation of the current density values ​​at each typical position with the average current density value when the measuring tab is set at different positions, and determining the position of the measuring tab corresponding to the minimum normalized standard deviation as the measurement position; collecting the negative electrode resistance data of the measuring tab at the measurement position when the battery is in working state as the resistance of the negative electrode.

[0017] By comparing the normalized standard deviation of the current density values ​​at each typical position with the average current density value, the measurement position selected thereby has the least impact on subsequent steps.

[0018] 3. In this embodiment of the present invention, a first range is set for the negative electrode resistance data; when the negative electrode resistance data is within the first range, it is determined to be in a stable state, and the negative electrode resistance data is in a measurable state. By analyzing the collected data, negative electrode resistance data within the first range is determined to be in a stable state.

[0019] 4. A state of charge estimation method provided by an embodiment of the present invention provides initial data for training and constructing a data-driven model, wherein the initial data includes current, voltage parameters, and electrode resistance data;

[0020] Acquire test data from the battery under test in real time, use the test data as input to the data-driven model, and output an estimated value of the SOC. The test data includes current parameters, voltage parameters, and negative electrode resistance parameters measured using the negative electrode resistance measurement method described above.

[0021] By introducing negative electrode resistance data into the data-driven model to improve the accuracy of SOC data, higher SOC accuracy is conducive to judging the battery status and bringing a better user experience.

[0022] 5. The data-driven model of the present invention includes, but is not limited to, at least one of an integrated decision tree model, support vector regression, and a neural network. The data-driven model is used to identify the underlying mathematical relationship between the negative electrode resistance data and the SOC, thereby improving the accuracy of the SOC estimation.

[0023] 6. An embodiment of the present invention further provides a battery comprising the lithium-ion negative electrode structure as described above.

[0024] 7. In a battery according to an embodiment of the present invention, the negative electrode plate includes a first current collector layer and an active material layer stacked together, and the conventional tab and the measuring tab are connected to the first current collector layer and the active material layer, respectively. The provision of the first current collector layer and the active material layer facilitates connection between the conventional tab and the measuring tab.

[0025] 8. The first current collector layer of this embodiment of the present invention includes an active material connection region and a tab connection region. The active material layer is disposed on the active material connection region, the conventional tab is disposed on the tab connection region, and the measurement tab is connected to the active material layer. The active material connection region is layered with at least one negative electrode material including, but not limited to, graphite, silicon-carbon, alloys, lithium titanate, and various oxides. The measurement tab, which is directly connected to the battery pack, facilitates battery measurement. Traditional measurements require the addition of tabs to the battery, making the measurement process cumbersome.

[0026] 9. A battery according to an embodiment of the present invention includes a positive electrode structure disposed opposite a negative electrode structure, and a separator disposed between the positive and negative electrode structures. This embodiment provides a battery with higher precision and lower error when performing SOC estimation, significantly improving the user's ability to accurately determine battery status and enhancing the user experience.

[0027] 10. Embodiments of the present invention also provide a battery system including a negative electrode structure or a battery as described above. A battery system using such a negative electrode structure or a battery can measure battery resistance data in real time and use this data to estimate the battery SOC, thereby improving the accuracy of the battery system and the user experience.

Brief Description of the Drawings

[0028] Figure 1 This is a flow chart of a method for measuring negative electrode resistance of a battery provided by an embodiment of the present invention.

[0029] Figure 2 This is a test diagram provided by an embodiment of the present invention, in which the first boundary is 2 mm away from the third boundary.

[0030] Figure 3 This is a test diagram provided by an embodiment of the present invention, in which the first boundary is 21 mm away from the third boundary.

[0031] Figure 4 This is a test diagram provided by an embodiment of the present invention, in which the first boundary is 38 mm away from the third boundary.

[0032] Figure 5 It is a scatter diagram of the degree of uniform distribution of current on the negative electrode surface provided by an embodiment of the present invention.

[0033] Figure 6 4 is a graph showing the negative electrode resistance data provided by an embodiment of the present invention.

[0034] Figure 7 This is a diagram of the predicted results of the input characteristic voltage and current provided by an embodiment of the present invention.

[0035] Figure 8 1 is an error diagram of input characteristic voltage and current provided by an embodiment of the present invention.

[0036] Figure 9 This is a diagram showing the predicted results of the input characteristic voltage, current, and negative electrode resistance provided by an embodiment of the present invention.

[0037] Figure 10 1 is an error diagram of input characteristic voltage, current and cathode resistance provided by an embodiment of the present invention.

[0038] Figure 11 Schematic diagram of the negative electrode structure provided by an embodiment of the present invention.

[0039] Figure 12It is a schematic diagram of the battery structure provided by an embodiment of the present invention.

[0040] Description of the accompanying drawings:

[0041] 1. Negative electrode sheet; 2. Positive electrode sheet; 3. Diaphragm; 4. Sealing film;

[0042] 11. Conventional tab; 12. Measurement tab; 13. First current collector layer; 14. First boundary; 15. Second boundary; 16. Third boundary; 17. Fourth boundary; 21. Positive tab; 22. Second current collector.

[0043] 131. Active material connection area; 132. Tab connection area. [Specific implementation method]

[0044] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and implementation examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0045] In the embodiments provided herein, it should be understood that "B corresponding to A" means that B is associated with A and B can be determined based on A. However, it should also be understood that determining B based on A does not mean determining B based solely on A; B can also be determined based on A and / or other information.

[0046] It should be understood that references to "one embodiment" or "an embodiment" throughout this specification mean that specific features, structures, or characteristics associated with the embodiment are included in at least one embodiment of the present invention. Therefore, the phrases "in one embodiment" or "in an embodiment" appearing throughout this specification do not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. Those skilled in the art should also be aware that the embodiments described in this specification are all optional embodiments, and the actions and modules involved are not necessarily required for the present invention.

[0047] In various embodiments of the present invention, it should be understood that the size of the serial numbers of the above-mentioned processes does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0048] The flow charts and block diagrams in the accompanying drawings of the present invention illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementation schemes, the functions marked in the box can also occur in a different order than those marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which is determined based on the functions involved. It should be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0049] See also Figure 1 and Figure 12 , an embodiment of the present invention provides a negative electrode resistance measurement method, comprising the following steps:

[0050] S1: Provide a negative electrode of the battery, one end of which is provided with a conventional tab 11,

[0051] A test tab 12 is provided at the other end;

[0052] S2: Evaluate the current density distribution on the surface of the battery negative electrode through simulation, and take the average of the current density values ​​at several typical locations as the average current density value on the negative electrode surface;

[0053] S3: changing the position of the measuring tab 12 at the setting end boundary, and obtaining the corresponding average current density values ​​on the negative electrode surface when the measuring tab 12 is set at different positions;

[0054] S4: comparing the normalized standard deviations of the current density values ​​at each typical position and the average current density value when the measuring tab 12 is set at different positions, and determining the position of the measuring tab 12 corresponding to the minimum normalized standard deviation as the measuring position;

[0055] S5: When the battery is in working state, the negative electrode resistance data of the tab 12 at the measuring position is measured as the resistance of the negative electrode.

[0056] Specifically, step S1: a conventional tab 11 and a measuring tab 12 are respectively provided at both ends of the battery. The present application mainly utilizes the measuring tab 12 to achieve the technical effect of collecting resistance.

[0057] Step S2: Evaluate the current density distribution on the surface of the battery negative electrode through simulation, select the current density values ​​at several typical positions and take the average as the average current density value on the negative electrode surface. The average current density is measured and / or directly preset to improve the test effect after the tab is connected.

[0058] It should be noted that after the measuring tab 12 is introduced, the current distribution is measured again according to the typical position distance. When the measuring tab 12 is used to measure the negative electrode resistance, the uneven current distribution on the negative electrode surface will be accumulated with the uneven current on the negative electrode surface during the actual operation of the battery, thereby causing local accelerated aging of the battery and affecting the battery service life.

[0059] Step S 3: The conventional measurement method connects a conventional tab to each of the positive and negative poles of the battery to measure the battery. This application adds an additional measuring tab 12 at the negative pole. When the measuring tab 12 is connected to different positions of the negative pole of the battery, different current distribution data will be generated. During the measurement process, the current distribution generated by the measuring tab 12 will be superimposed on the current distribution of the battery itself. When the distribution of the two is more even, the impact on the battery is minimized, and the measured data is more accurate.

[0060] The simulation software was used to test different connection positions of the measuring tab 12. The test results are as follows: Figures 2 to 4 As shown, Figures 2 to 4 Graphs showing current density distribution at different positions are shown. Tests were conducted on the measurement tab 12 connected to different positions of the set end-to-end boundary.

[0061] Specifically, the distance range between the measuring tab 12 and the left boundary of the setting end is selected to be 2mm-38mm. After experiments, it is found that when the distance is 2mm, the current distribution data after connecting the measuring tab 12 is closest to the current distribution data of the battery itself. When the measuring tab 12 is connected at a position of 2mm, the impact on the battery life is minimized and the accuracy of the measured data is the highest.

[0062] Step S4: normalize the obtained current distribution sampling data and the average current density data to obtain the standard deviation. The smaller the standard deviation, the smaller the impact of the connection between the measuring tab 12 and the battery pack on the battery life. At the same time, the data measured in subsequent steps will be more stable and accurate.

[0063] Step S5: When the battery is in working state, the negative electrode resistance data of the tab 12 at the measurement position is measured as the resistance of the negative electrode. It can be understood that by introducing the negative electrode resistance, the accuracy of other battery measurements, such as SOC estimation, is improved. The introduction of the negative electrode resistance data improves the measurement accuracy of SOC.

[0064] See also Figure 5 and Figure 6, Figure 5 The scatter plot of the current distribution uniformity on the negative electrode surface is obtained when the tab 12 is at different positions. The experiment shows that the current distribution uniformity on the negative electrode surface decreases gradually when the position of the tab 12 is from 2 mm to 38 mm from the left edge.

[0065] Optionally, a first range is set for the negative electrode resistance data; when the negative electrode resistance data is within the first range, it is determined to be in a stable state, and the negative electrode resistance data is in a measurable state.

[0066] Specifically, the first range is determined by subtracting each peak value from the average value of the peaks in the negative electrode resistance data curve, and then dividing the difference by the average value. The same applies to valleys and other locations on the curve. The first range is preset to a value less than 5 percent. This determines whether the peak value of the negative electrode resistance data curve is substantially within the first range. Negative electrode resistance data within the first range is considered stable, and this stable negative electrode resistance data is used to estimate the SOC value.

[0067] Figure 6 This is the negative electrode resistance data obtained based on the maximum value of the scatter plot. It can be seen that the negative electrode resistance changes steadily over time, and the data at each point on the curve is generally within the first range. To determine the relationship between negative electrode resistance and battery charging and discharging, and further verify the correlation between charging and discharging and negative electrode resistance, a scatter plot of the current sampling is created to intuitively see the impact of different locations on the average current density.

[0068] Optionally, see Figure 11 The test includes: setting one side of the measuring tab 12 as the first boundary 14, the opposite side thereof as the second boundary 15, the side defining the battery as the third boundary 16, and the opposite side thereof as the fourth boundary 17, adjusting the distance between the first boundary 14 and the third boundary 16 of the measuring tab 12, and / or adjusting the distance from the first boundary 14 to the second boundary 15, and conducting tests based on the adjusted distances to obtain data at different distances, and confirming the preset position corresponding to the minimum standard deviation of the normalized current distribution based on the test results.

[0069] It can be understood that the main consideration is the distance between the first boundary 14 of the measuring tab 12 and the third boundary 16 of the battery pack. The present application uses the measuring tab 12 to measure the battery pack. Therefore, when measuring the negative electrode resistance, the uneven current distribution on the negative electrode surface will accelerate the aging of the local position of the battery, thereby affecting the overall life of the battery. In order to slow down the aging of the battery and increase the service life of the battery, it is necessary to determine the maximum value of the uniformity of the current density distribution, reduce unnecessary battery aging, improve the battery durability, and thus improve the user experience.

[0070] An embodiment of the present invention further provides a battery state of charge estimation method, comprising: providing initial data for training and constructing a data-driven model, the initial data including current, voltage parameters, and resistance data;

[0071] Acquire test data from the battery under test in real time, use the test data as input to the data-driven model, and output an estimated value of the SOC. The test data includes current parameters, voltage parameters, and negative electrode resistance parameters measured using the negative electrode resistance measurement method described above.

[0072] Specifically, the data-driven model will take the discharge current values, discharge voltage values ​​and resistance values ​​of a large number of experimental battery samples as input, and use their SOC values ​​after actual testing as the basis for the data-driven model's evaluation.

[0073] Specifically, the data-driven model includes but is not limited to at least one of various data-driven models such as an integrated decision tree model, support vector regression, and a neural network. The present application adopts a random forest model. There is no restriction on the specific type of the data-driven model, as long as the desired effect can be achieved. The data-driven model searches for the potential mathematical relationship between the input voltage, current, and SOC through repeated iterative calculations. When the data-driven model continuously iterates and calculates, so that the error accuracy of the input and output results is lower than the preset value, the model algorithm of the data-driven model has been completed. The preset value of the error accuracy in this solution is less than 5%.

[0074] After the model algorithm training of the data-driven model is completed, we input the battery's discharge voltage, current and negative electrode resistance value into the model algorithm. The data-driven model predicts the SOC value of this battery based on previous training experience.

[0075] Optionally, a relationship curve between the negative electrode resistance and the SOC is drawn using the negative electrode resistance data, and the correlation between the negative electrode resistance and the battery charge and discharge state is verified through the relationship curve. When the relationship curve is positively correlated, it is a related state.

[0076] The relevant status shows that setting the measuring tab 12 can measure the negative electrode resistance data more stably and reliably.

[0077] Specifically, IR (negative electrode resistance) was added to the feature input of the random forest machine learning algorithm and compared with a conventional battery control group without IR. Considering that in real-life applications, such as electric vehicles and smart terminals, BMS management systems will have errors when measuring current and voltage, Gaussian noise with a variance of 0.025 was added to the cycle data to simulate measurement errors. The data when only voltage and current were input features were compared with the results after inputting negative electrode resistance.

[0078] See also Figures 7 to 10 , Figure 7 and Figure 8 is the result of SOC prediction when the negative electrode resistance is not introduced, where Figure 7 The battery capacity decreases over time, and the curve data comparison between the predicted value and the actual value is shown. Figure 8 For the error graph in this state, it can be found that as time goes by, the error gradually increases and then gradually decreases; Figure 9 and Figure 10 This is the control result when the negative electrode resistance is introduced.

[0079] After introducing the negative electrode resistance as an input feature, both the root mean square error (RMSE) and mean square error (MAE) were reduced by half, and the maximum estimation error was reduced from 0.08 to 0.04. Including the negative electrode resistance as a feature significantly improves the estimation accuracy compared to before adding it.

[0080] Optionally, one side of the measuring tab 12 is set as the first boundary 14, the opposite side thereof is set as the second boundary 15, the side defining the battery is set as the third boundary 16, and the opposite side thereof is set as the fourth boundary 17, and the distance between the first boundary 14 and the third boundary 15 is the position corresponding to the minimum value of the normalized standard deviation of the uniformity of the current distribution on the negative electrode surface.

[0081] Specifically, the present invention employs distances of 2mm, 21mm, and 38mm between the first boundary 14 and the third boundary 16. Experimental simulations show that the normalized standard deviation of the current distribution of the negative electrode structure 1 relative to a preset average current distribution density is minimized when the distance between the first boundary 14 and the third boundary 16 is 2mm. Furthermore, this distance reduces uneven current distribution caused by the connection of the measuring tab 12 to the battery, which can be superimposed on the battery's operation. Long-term uneven current distribution can lead to localized battery aging and shorten the battery's lifespan.

[0082] Furthermore, the distance between the first boundary 14 and the third boundary 16 is not limited here. The position corresponding to the minimum value of the normalized standard deviation of the current distribution uniformity obtained from experiments on different batteries is also different, and the position can achieve the corresponding technical effect.

[0083] An embodiment of the present invention also provides a lithium battery negative electrode structure, including a negative electrode structure 1, a conventional pole tab 11 and a measuring pole tab 12, wherein the conventional pole tab 11 is arranged at one end of the negative electrode structure 1, and the measuring pole tab 12 is arranged at a measurement position at the other end of the negative electrode structure 1 opposite to the conventional pole tab 11, and the measurement position is the position of the minimum standard deviation after normalization of the negative electrode current density measured by the measuring pole tab 12 in the working state and the current density under the average current density of the battery negative electrode surface in the working state.

[0084] Optionally, the first current collector layer 13 includes an active material connection area 131 and a tab connection area 132, the active material connection area 131 is connected to the tab connection area 132; the active material layer is arranged on the active material connection area 131, the conventional tab 11 is arranged in the tab connection area 132, and the measurement tab 12 is connected and arranged on the active material layer.

[0085] It can be understood that directly connecting the measuring tab 12 to the active material connection area 131 can better measure the resistance data on the negative electrode structure 1, while eliminating the need to disassemble the measuring tab 12, making it convenient for continuous battery testing.

[0086] Optionally, the first current collector layer 13 includes an active material connection area 131 and a tab connection area 132 ; the active material layer is disposed on the active material connection area 131 , the conventional tab 11 is disposed in the tab connection area 132 , and the measurement tab 12 is connected to the active material layer.

[0087] Furthermore, at least one of negative electrode materials including but not limited to graphite, silicon carbon, alloy, lithium titanate and various oxides is stacked on the active material connection area 131 .

[0088] The lithium-ion battery provided in this embodiment includes a positive electrode structure 2 disposed opposite to a negative electrode structure 1 and a separator disposed between the positive and negative electrode structures 1. A second current collector 22 is disposed on the positive electrode structure 2, and a positive electrode tab 21 is fixedly connected to the second current collector 22.

[0089] A battery system is also provided in an embodiment of the present invention, including the above-mentioned negative electrode structure or a battery. The battery system includes an AC distribution unit, a rectifier module, a DC distribution unit, a battery, and a monitoring system. By improving the battery part of the battery system, the accuracy of the battery system in estimating the SOC can be improved, thereby increasing the system's available parameters and improving the user experience.

[0090] Compared with the prior art, the negative electrode resistance measurement method, negative electrode structure, state of charge estimation method, battery, and battery system provided by the present invention have the following beneficial effects:

[0091] 1. An embodiment of the present invention also provides a lithium battery negative electrode structure, which is used in the negative electrode resistance measurement method as described above, including a negative electrode plate, a conventional tab and a measuring tab, wherein the conventional tab is arranged at one end of the negative electrode plate, and the measuring tab is arranged at a measurement position on the other end of the negative electrode plate opposite to the conventional tab. The measurement position is the position where the standard deviation of the negative electrode current density measured by the measuring tab in the working state and the current density normalized under the average current density of the battery negative electrode surface in the working state is the smallest.

[0092] 2. A negative electrode resistance measurement method provided by an embodiment of the present invention includes the following steps: providing a battery negative electrode, one end of which is provided with a conventional tab and the other end of which is provided with a test tab; evaluating the current density distribution on the surface of the battery negative electrode through simulation, selecting the current density values ​​at several typical positions and averaging them as the average current density value of the negative electrode surface; changing the position of the measuring tab at the boundary of the setting end, and obtaining the corresponding average current density values ​​of the negative electrode surface when the measuring tab is set at different positions; comparing the normalized standard deviation of the current density values ​​at each typical position with the average current density value when the measuring tab is set at different positions, and determining the position of the measuring tab corresponding to the minimum normalized standard deviation as the measurement position; collecting the negative electrode resistance data of the measuring tab at the measurement position when the battery is in working state as the resistance of the negative electrode.

[0093] By comparing the normalized standard deviation of the current density values ​​at each typical position with the average current density value, the measurement position selected thereby has the least impact on subsequent steps.

[0094] 3. In this embodiment of the present invention, a first range is set for the negative electrode resistance data; when the negative electrode resistance data is within the first range, it is determined to be in a stable state, and the negative electrode resistance data is in a measurable state. By analyzing the collected data, negative electrode resistance data within the first range is determined to be in a stable state.

[0095] 4. A state of charge estimation method provided by an embodiment of the present invention provides initial data for training and constructing a data-driven model, wherein the initial data includes current, voltage parameters, and electrode resistance data;

[0096] Acquire test data from the battery under test in real time, use the test data as input to the data-driven model, and output an estimated value of the SOC. The test data includes current parameters, voltage parameters, and negative electrode resistance parameters measured using the negative electrode resistance measurement method described above.

[0097] By introducing negative electrode resistance data into the data-driven model to improve the accuracy of SOC data, higher SOC accuracy is conducive to judging the battery status and bringing a better user experience.

[0098] 5. The data-driven model of the present invention includes, but is not limited to, at least one of an integrated decision tree model, support vector regression, and a neural network. The data-driven model is used to identify the underlying mathematical relationship between the negative electrode resistance data and the SOC, thereby improving the accuracy of the SOC estimation.

[0099] 6. An embodiment of the present invention further provides a battery comprising the lithium-ion negative electrode structure as described above.

[0100] 7. In a battery according to an embodiment of the present invention, the negative electrode plate includes a first current collector layer and an active material layer stacked together, and the conventional tab and the measuring tab are connected to the first current collector layer and the active material layer, respectively. The provision of the first current collector layer and the active material layer facilitates connection between the conventional tab and the measuring tab.

[0101] 8. The first current collector layer of this embodiment of the present invention includes an active material connection region and a tab connection region. The active material layer is disposed on the active material connection region, the conventional tab is disposed on the tab connection region, and the measurement tab is connected to the active material layer. The active material connection region is layered with at least one negative electrode material including, but not limited to, graphite, silicon-carbon, alloys, lithium titanate, and various oxides. The measurement tab, which is directly connected to the battery pack, facilitates battery measurement. Traditional measurements require the addition of tabs to the battery, making the measurement process cumbersome.

[0102] 9. A battery according to an embodiment of the present invention includes a positive electrode structure disposed opposite a negative electrode structure, and a separator disposed between the positive and negative electrode structures. This embodiment provides a battery with higher precision and lower error when performing SOC estimation, significantly improving the user's ability to accurately determine battery status and enhancing the user experience.

[0103] 10. Embodiments of the present invention also provide a battery system including a negative electrode structure or a battery as described above. A battery system using such a negative electrode structure or a battery can measure battery resistance data in real time and use this data to estimate the battery SOC, thereby improving the accuracy of the battery system and the user experience.

[0104] The above is a detailed introduction to the negative electrode resistance measurement method, battery negative electrode structure, battery and battery estimation method disclosed in the embodiments of the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the ideas of the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on the present invention. Any modifications, equivalent replacements and improvements made within the principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for measuring negative electrode resistance, characterized in that: The following steps are involved: A battery negative electrode is provided, wherein one end of the negative electrode plate is provided with a conventional tab and the other end is provided with a test tab; the negative electrode plate includes a first current collector layer and an active material layer stacked together, and the conventional tab and the test tab are connected to the first current collector layer and the active material layer respectively; The current density distribution on the surface of the battery negative electrode is evaluated through simulation, and the current density values ​​at several typical locations are averaged as the average current density value on the negative electrode surface; Changing the position of the measuring tab at the setting end boundary and obtaining the corresponding average current density values ​​on the negative electrode surface when the measuring tab is set at different positions; Comparing the normalized standard deviations of the current density values ​​at each typical position and the average current density value when the measuring tab is set at different positions, and determining the position of the measuring tab corresponding to the minimum normalized standard deviation as the measurement position; When the battery is in working state, the negative electrode resistance data of the measured tab at the measurement position is collected as the resistance of the negative electrode.

2. A method for measuring negative electrode resistance according to claim 1, characterized in that: A first range is set for the negative electrode resistance data; when the negative electrode resistance data is within the first range, it is determined to be in a stable state, and the negative electrode resistance data is in a measurable state.

3. A method for estimating state of charge, characterized in that: The following steps are involved: Providing initial data for training and building a data-driven model, wherein the initial data includes current, voltage parameters and electrode resistance data; Acquire test data from the battery to be tested in real time, use the test data as input to a data-driven model, and output an estimated value of the SOC, wherein the test data includes current parameters, voltage parameters, and negative electrode resistance parameters measured using the negative electrode resistance measurement method according to any one of claims 1 or 2.

4. The method for estimating state of charge according to claim 3, wherein: The data-driven model includes at least one of an integrated decision tree model, a support vector regression model, and a neural network.

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