Method and system for estimating internal resistance of battery cells, and computer program product

Abstract

The present invention relates to a method for estimating internal resistance of battery cells, where all batteries are constructed identically and each of the batteries is composed of a plurality of cells, and the method comprises the following steps: (S110) obtaining first statistics of the internal resistance of cells of all batteries at one predetermined test point; (S120) obtaining second statistics, at all test points, of the internal resistance of the cells of one of the batteries corresponding to each of the test points; (S130) obtaining a statistical relationship between the one battery and all the batteries from the first statistics and the second statistics that correspond to the predetermined test point; and (S140) obtaining, according to the statistical relationship, the first statistics of all the batteries corresponding to remaining test points from the second statistics of the one battery corresponding to the remaining test points. The present invention further relates to a corresponding system and a computer program product. The present invention can estimate a complete distribution of the internal resistance of all batteries at each of the test points in a simple and reliable manner, reduce the workload and amount of data detection and processing, and save the time and cost for testing.

Description

[0001] METHOD AND SYSTEM FOR ESTIMATING INTERNAL RESISTANCE OF BATTERY CELLS, AND COMPUTER PROGRAM PRODUCT

[0002] TECHNICAL FIELD

[0003] The present invention relates to the field of power batteries, and specifically to a method for estimating internal resistance of battery cells, in particular internal resistance of battery cells of an electric vehicle. In addition, the present invention further relates to a computer program product.

[0004] BACKGROUND ART

[0005] In the manufacturing process of power batteries, such as lithium-ion batteries, direct current resistance (DCR) of the battery is provided as one of the important parameters indicating the battery performance.

[0006] Generally, at different temperatures and states of charge (SoC), the direct current resistance of the battery presents different internal resistance values and thus has an internal resistance distribution associated with temperature and state of charge. For battery products, each battery has a different internal resistance distribution. Therefore, it is particularly important for the battery products per se and the manufacturing of batteries to obtain the maximum internal resistance value of the batteries at each of the temperatures and states of charge.

[0007] The DCR of a battery mainly depends on its cells. The DCR of each cell will be tested during an End-of-line (EoL) test of the battery, but the testing is usually limited to one or more specific test points, where test points of importance or concern are usually freely selected by different battery manufacturers. As an example, the DCR of all the battery cells are tested in a state of charge (SoC) at 50% and a temperature at 25°C, and statistical values and statistical distribution of the DCR of all the battery cells at the specific test point(s) can be thus obtained. However, this cannot accurately and fully reflect the entire DCR distribution of all the battery cells at different temperatures and SoCs. Therefore, it is impossible to accurately determine the “worst condition”, i.e., the maximum internal resistance, of the battery at each SoC and temperature state and distribution thereof.

[0008] Theoretically, the direct current resistance of each cell / battery pack at each SoC and temperature can be tested to obtain a complete internal resistance distribution of all cells of all batteries based on the test data, but this requires a great deal of testing work, which is almost impossible in the actual EoL test.

[0009] For this reason, there is still a need to improve the existing solutions for at least some of the above problems.

[0010] SUMMARY OF THE INVENTION

[0011] To this end, the present invention proposes an efficient solution, which can not only overcome the disadvantages of the existing technical solutions, but also estimate a complete DCR distribution of all cells of all batteries in a particularly simple and comprehensive manner.

[0012] According to a first aspect of the present invention, there is provided a method for estimating internal resistance of battery cells, where all batteries are constructed identically and each of the batteries is composed of a plurality of cells, and the method comprises the following steps: SI 10 obtaining first statistics of the internal resistance of cells of all batteries at one predetermined test point;

[0013] S120 obtaining second statistics, at all test points, of the internal resistance of the cells of one of the batteries corresponding to each of the test points;

[0014] S130 obtaining a statistical relationship between the internal resistance of the cells of the one battery and the internal resistance of the cells of all batteries from the first statistics and the second statistics that correspond to the predetermined test point; and

[0015] S140 obtaining, according to the statistical relationship, the first statistics of the resistance of the cells of all batteries corresponding to remaining test points from the second statistics of the resistance of the cells of the one battery corresponding to the remaining test points.

[0016] The basic concept of the invention is to statistically correlate the DCR distribution data, which is obtained in the EoL test, of the cells of all batteries at a selected test point with the complete DCR distribution data of the cells of one of the batteries obtained at different test points through statistical analysis, so that the internal resistance data of the cells of all batteries at different test points, i.e., different SoCs and temperatures, can be reliably and easily obtained based on the complete DCR distribution of one of the batteries, and the complete DCR distribution of the cells of all batteries can be reliably provided, thereby allowing battery manufacturers or engineers to obtain the maximum internal resistance, i.e., the worst condition, of the cells of all batteries at all the test points. Thus, the test efficiency can be improved, and the workload and cost of the test can be reduced through at least some of the embodiments of the present invention.

[0017] An advantageous configuration of the method for estimating internal resistance of battery cells according to the present invention can be obtained from the following optional embodiments.

[0018] According to an optional embodiment of the method of the present invention, the first statistics include a first mean value and a first standard deviation, wherein the first mean value represents a mean value of the internal resistance of the cells of all batteries, and the first standard deviation represents a degree to which the internal resistance of the cells of all batteries deviates from the first mean value.

[0019] According to an optional embodiment of the method of the present invention, the second statistics include a second mean value and a second standard deviation, wherein the second mean value represents a mean value of the internal resistance of the cells of the one battery, and the second standard deviation represents a degree to which the internal resistance of the cells of the one battery deviates from the second mean value.

[0020] According to an optional embodiment of the method of the present invention, for the predetermined test point, a multiplier factor is obtained from the first standard deviation and the second standard deviation, and wherein the multiplier factor represents a quotient of the first standard deviation and the second standard deviation.

[0021] According to an optional embodiment of the method of the present invention, a multiplier of the first standard deviation is set as an acceptable first standard deviation for the cells of all batteries, so that an acceptable maximum internal resistance value and an acceptable minimum internal resistance value of the cells of all batteries at the predetermined test point are obtained.

[0022] According to an optional embodiment of the method of the present invention, for the predetermined test point, an upper-side factor and a lower-side factor are obtained from the acceptable maximum internal resistance value and the acceptable minimum internal resistance value as well as the second mean value and the first standard deviation.

[0023] According to an optional embodiment of the method of the present invention, for remaining test points, the first statistics of the internal resistance of the cells of all batteries corresponding to the remaining test points are obtained from the multiplier factor, the upper-side factor and the lower-side factor, as well as the second standard deviation corresponding to the remaining test points.

[0024] According to an optional embodiment of the method of the present invention, the predetermined test point is determined and the first statistics of the internal resistance of the cells of all batteries are obtained in an End-of-line, Eol, test of the batteries.

[0025] According to an optional embodiment of the method of the present invention, the internal resistance of the battery corresponds to the direct current resistance of the cells of the battery.

[0026] According to an optional embodiment of the method of the present invention, the predetermined test point is: SoC at 50%, and temperature at 25 degrees Celsius. The selection of the test point depends on different battery manufacturers or testers, and other test points may also be considered.

[0027] According to an optional embodiment of the method of the present invention, a total number of the batteries is 10,000, with each of the batteries including 200 cells.

[0028] According to an optional embodiment of the method of the present invention, a multiplier of the first standard deviation is three. In statistics, the three-sigma rule is used to exclude extremely abnormal fluctuation data.

[0029] According to a second aspect of the present invention, there is provided a system for estimating internal resistance of battery cells, which system is used for implementing the method of the present invention.

[0030] According to a third aspect of the present invention, a computer program product is provided, wherein the computer program product comprises computer instructions, which are at least used for assisting in implementing the method according to the present invention when executed by a processor.

[0031] More features of the present invention become apparent from the claims, the drawings and the description of the drawings. The features and feature combinations mentioned in the preceding description and the features and feature combinations mentioned in the following description of the drawings and / or shown only in the drawings can be used not only in specified combinations, but also in other combinations without departing from the scope of the present invention. Therefore, the following contents are also regarded as being covered and disclosed by the present invention: contents which are not explicitly shown in the drawings and not explicitly explained, but are derived from and produced by a combination of separate features from the explained contents. The following contents and feature combinations are also regarded as being disclosed: contents and feature combinations which do not contain all the features of the originally drafted independent claims. In addition, the following contents and feature combinations are regarded as being disclosed in particular by the preceding text: contents and feature combinations which exceed or deviate from the feature combinations recited in the reference relationships of the claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The principles, characteristics and advantages of the present invention can be better understood through the detailed description below with reference to the accompany drawings, in which:

[0033] FIG. 1 shows a flow chart of an embodiment of a method for estimating internal resistance of battery cells according to the present invention; and

[0034] FIG. 2 shows a schematic diagram of a distribution of the internal resistance of cells of one battery at different test points according to the present invention.

[0035] DETAILED DESCRIPTION OF EMBODIMENTS

[0036] For clearer understanding of the technical problems to be solved, technical solutions and advantageous technical effects of the present invention, the invention will be described below in greater detail in conjunction with the drawings and a number of exemplary embodiments. It is to be understood that specific embodiments described here are merely for explaining the invention, rather than limiting the scope thereof.

[0037] FIG. 1 shows a flow chart of an embodiment of a method 100 for estimating internal resistance of battery cells according to the present invention.

[0038] In the present invention, a battery can be understood as a battery pack, which is composed of a plurality of cells. These cells can be assembled into a battery module, which in turn forms a battery pack. In this case, the battery pack forms a cell-module-battery pack (CTM) in form of three-levels. Alternatively, these cells may be directly integrated into the battery pack and the corresponding module assembling step can be omitted. In this case, the battery pack forms a cell-to-pack battery (CTP) in form of two-levels.

[0039] In battery production, all the batteries are constructed identically and composed of the same number of cells.

[0040] As shown in FIG. 1, the method 100 according to the present invention exemplarily includes method steps S 110 to S140.

[0041] According to this embodiment, in step SI 10, first statistics SI of the internal resistance of cells of all batteries at one predetermined test point is obtained. In this embodiment, in an End-of-line (EOL) test of battery production, for example, the resistance of cells of all the batteries produced (for example, 10,000 batteries) is tested for one test point selected by the battery manufacturer or tester. In step S120, second statistics S2, at all test points, of the internal resistance of the cells of one of the batteries corresponding to each of the test points are obtained. The one battery can be understood as a sample battery in the statistical sense. Next, in step S130, a statistical relationship between the one battery and all the batteries is obtained from the first statistics SI and the second statistics S2 that correspond to the predetermined test point. And in step S140, based on the statistical relationship, the first statistics SI of all batteries corresponding to remaining test points are obtained from the second statistics S2 of the one battery corresponding to the remaining test points. In this way, a distribution of the internal resistance of cells of the battery at all test points, i.e., at different SoCs and temperatures, can be obtained.

[0042] In the present invention, the remaining test points are to be understood as the test points that are different from the predetermined test point or different from the SoC and temperature selected or focused on by the battery manufacturer or tester.

[0043] Next, the method 100 exemplarily shown in FIG. 1 will be described in detail with reference to FIG. 2.

[0044] FIG. 2 shows a schematic diagram of a distribution of the internal resistance of cells of one battery (which is understood as a sample battery in this embodiment) at different test points according to the present invention. The data and test points in FIG. 2 are only exemplary and are only used to describe the method of the present invention.

[0045] As mentioned above, the battery, i.e., battery pack, includes a plurality of cells, and specifically includes 200 cells in this embodiment. The internal resistance of a battery corresponds to the direct current resistance of its cells. In other words, in the present invention, the internal resistance of the battery is substantially understood as the direct current resistance of its cells, and the internal resistance caused by other structural elements, such as electrical connectors, of the battery / battery pack is ignored.

[0046] In this embodiment, as an example, 10,000 batteries are tested in the EoL test. In step SI 10, in the EoL test, a predetermined test point is selected, internal resistance values of the cells of all 10,000 batteries are detected, and the first statistics SI of the internal resistance of the cells of all 10,000 batteries is obtained by statistical methods.

[0047] Here, the predetermined test point is selected as: SoC at 50% and temperature at 25°C. This predetermined test point can be selected differently depending on battery manufacturers and testers. Therefore, in this embodiment, the selection of the predetermined test point is only as an example, rather than a limitation on the selection of the test point of the present invention.

[0048] According to the present invention, the first statistics SI include a first mean value Ml and a first standard deviation Nl, wherein the first mean value Ml represents a mean value of the internal resistance (values) of 2,000,000 cells of a total of 10,000 batteries and is obtained by the following formula: in which n = 2,000,000.

[0049] The first standard deviation Nl represents a degree to which the internal resistance of the 2,000,000 cells of all the 10,000 batteries deviates from the first mean value Ml and is obtained by the following formula:

[0050] Nl = in which n = 2,000,000.

[0051] Accordingly, the first mean value Ml and the first standard deviation N1 of the internal resistance of all 10,000 batteries and 2,000,000 cells at the SoC of 50% and the temperature of 25°C are obtained.

[0052] According to one embodiment, Ml is, for example, 60 milliohms, and Nl is, for example, 0.9 milliohms.

[0053] Then, in step S120, one battery is selected from all 10,000 batteries as a sample battery, and the second statistics S2, at all test points, of the internal resistance of the cells of the sample battery corresponding to each of the test points are obtained.

[0054] As shown in FIG. 2, at the test point, where SoC is 50% and temperature is 25°C, predetermined in the EoL test, the internal resistance of the cells of the sample battery is, for example, 58 milliohms in the diagram of FIG. 2. In this embodiment, 200 items of cell internal resistance distribution are accordingly obtained for the 200 cells of the sample battery, similar to those shown in FIG. 2.

[0055] Based on the test of the sample battery, the second statistics S2 corresponding to each of the test points are obtained from the internal resistance values of the 200 cells at each test point (SoC / temperature). The second statistics S2 include a second mean value M2 and a second standard deviation N2. Similar to the first mean value Ml and the first standard deviation Nl, the second mean value M2 represents a mean value of the internal resistance of the 200 cells of the sample battery, and the second standard deviation N2 represents a degree to which the internal resistance of the 200 cells deviates from the second mean value M2, and they can be obtained similarly by the two formulas above. Thus, the corresponding second statistics S2 (M2, N2) are obtained for each test point (SoC / temperature).

[0056] Next, in step S130, for the test point where SoC is 50% and temperature is 25°C as predetermined in the EoL test, a multiplier factor Fl is obtained from the first standard deviation Nl and the second standard deviation N2, and the multiplier factor Fl represents a ratio of the first standard deviation Nl to the second standard deviation N2 and is obtained by the following formula:

[0057] F1=N1 / N2.

[0058] In this embodiment, at the predetermined test point where SoC is 50% and temperature is 25°C, the second mean value M2 is 59 milliohms and the second standard deviation N2 is 0.6 milliohms.

[0059] It is thus obtained that Fl=Nl / N2=0.9 / 0.6=1.5.

[0060] In addition, in step SI 30, severely abnormal fluctuation data can be excluded by the three-sigma rule. In other words, for all the battery cells, a value of three times the first standard deviation Nl is set as an acceptable first standard deviation.

[0061] Therefore, for all the battery cells, an acceptable range of the internal resistance is 60±2.7 milliohms at the predetermined test point where SoC is 50% and temperature is 25°C.

[0062] Next, for the predetermined test point, for the predetermined test point, an upper-side factor Hl and a lower-side factor LI are obtained from the acceptable maximum internal resistance value and the acceptable minimum internal resistance value as well as the second mean value M2 and the first standard deviation Nl, in which the upper-side factor is:

[0063] In this way, it can be obtained in this embodiment that Hl=4.1, and Ll=1.9.

[0064] Now, in step S140, for remaining test points (SoCs / temperatures), the first statistics SI of the cells of all batteries corresponding to the remaining test points can be obtained using the multiplier factor Fl, the upper-side factor Hl and the lower-side factor LI obtained by statistical calculation in step S130 as well as the second statistics S2 of the internal resistance of the cells of the sample battery corresponding to the remaining test points.

[0065] Specifically, in this embodiment, at a test point where SoC is 20% and temperature is 0°C, for example, M2=82 milliohms and N2=0.8 milliohms are obtained from the internal resistance values of the 200 sample cells obtained in step S120. It thus can be obtained that the first standard deviation of the internal resistance of all the battery cells at this test point is Nl=N2xFl=1.2 milliohms.

[0066] Furthermore, a range of internal resistance values of all the battery cells at this test point is obtained using the upper-side factor Hl and the lower-side factor LI. Specifically: the minimum internal resistance value = M2-N1XL1 = 79.72 milliohms; and the maximum internal resistance value = M2+N1XH1 = 86.92 milliohms.

[0067] In this way, it can be obtained that at the test point where SoC is 20% and temperature is 0°C, the range of internal resistance values is 79.72 milliohms to 86.92 milliohms, or 83.32±3.6 milliohms.

[0068] Similarly, for test points at different SoCs and different temperatures, a corresponding internal resistance distribution of all cells of all batteries at different test points can be obtained from the second statistics S2, i.e., M2 and N2, of the corresponding internal resistance of the 200 cells of one sample battery. In this way, during battery production, it is possible to estimate in a particularly simple and low-cost manner at which test point(s) all the batteries / cells have the “worst condition”. The above embodiments are merely illustrative, and the internal resistance values selected are only used to explain the method of the present invention. The internal resistance values of cells may vary greatly with different types and materials of the battery as well as the number and integration manner of cells. However, the method according to the present invention is applicable to all batteries containing multiple cells.

[0069] In particular, the method according to the present invention is applicable to the estimation of internal resistance of a battery pack of an electric vehicle, in particular an all-electric vehicle, during EoL testing. The present invention can significantly reduce the workload needed, improve the test efficiency, and reliably estimate the corresponding internal resistance values of all the battery cells at different SoCs and temperatures. Thus, it is possible to clearly know at which SoC(s) and temperature(s) the internal resistance of the cells has the maximum internal resistance and may have the worst condition.

[0070] The present invention further protects a system for estimating internal resistance of battery cells, which is used to implement the method according to the present invention. In addition, the present invention further protects a computer program product.

[0071] Other advantages and alternative embodiments of the present invention are obvious to those skilled in the art. Therefore, the present invention in its broader sense is not limited to the specific details, representative structures and exemplary embodiments shown and described herein. On the contrary, various modifications and substitutions can be devised by those skilled in the art without departing from the basic spirit and scope of the invention.

Claims

Claims1. A method (100) for estimating the internal resistance of battery cells, where all batteries are constructed identically and each of the batteries is composed of a plurality of cells, wherein the method (100) comprises the following steps:SI 10 obtaining first statistics (SI) of the internal resistance of cells of all batteries at one predetermined test point;S120 obtaining second statistics (S2), at all test points, of the internal resistance of the cells of one of the batteries corresponding to each of the test points;S130 obtaining a statistical relationship between the cells of the one battery and the cells of all batteries from the first statistics (SI) and the second statistics (S2) that correspond to the predetermined test point; andS140 obtaining, according to the statistical relationship, the first statistics (SI) of the internal resistance of the cells of all batteries corresponding to remaining test points from the second statistics (S2) of the internal resistance of the cells of the one battery corresponding to the remaining test points.

2. The method (100) according to claim 1, wherein the first statistics (SI) include a first mean value (Ml) and a first standard deviation (Nl), wherein the first mean value (Ml) represents a mean value of the internal resistance of the cells of all batteries, and the first standard deviation (Nl) represents a degree to which the internal resistance of the cells of all batteries deviates from the first mean value (Ml); and / or the second statistics (S2) include a second mean value (M2) and a second standard deviation (N2), wherein the second mean value (M2) represents a mean value of the internal resistance of the cells of the one battery, and the second standard deviation (N2) represents a degree to which the internal resistance of the cells of the one battery deviates from the second mean value (M2).

3. The method (100) according to claim 2, wherein for the predetermined test point, a multiplier factor (Fl) is obtained from the first standard deviation (Nl) and the second standard deviation (N2), and wherein the multiplier factor (Fl) represents a quotient of the first standard deviation (Nl) and the second standard deviation (N2).

4. The method (100) according to claim 2 or 3, wherein a multiplier of the first standard deviation (Nl) is set as an acceptable first standard deviation for the cells of all batteries, so that an acceptable maximum internal resistance value and an acceptable minimum internal resistance value of the cells of all batteries at the predetermined test point are obtained.

5. The method (100) according to claim 4, wherein for the predetermined test point, an upper-side factor (Hl) and a lower-side factor (LI) are obtained from the acceptable maximum internal resistance value and the acceptable minimum internal resistance value as well as the second mean value (M2) and the first standard deviation (Nl).

6. The method (100) according to claim 5, wherein for remaining test points, the first statistics (SI) of the internal resistance of the cells of all batteries corresponding to the remaining test points are obtained from the multiplier factor (Fl), the upper-side factor (Hl) and the lower-side factor (LI), as well as the second standard deviation (N2) corresponding to the remaining test points.

7. The method (100) according to any one of claims 1 to 6, wherein the predetermined test point is determined and the first statistics (SI) of the internal resistance of the cells of all batteries are obtained in an End-of-line, Eol, test of the batteries.

8. The method (100) according to any one of claims 1 to 7, wherein the internal resistance of the battery corresponds to the direct current resistance of the cells of the battery.

9. The method (100) according to any one of claims 1 to 8, wherein the predetermined test point is: SOC at 50% and temperature at 25 degrees Celsius; and / or a total number of the batteries is 10,000, with each of the batteries including 200 cells; and / or a multiplier of the first standard deviation (Nl) is three.

10. A system for estimating internal resistance of battery cells, wherein the system is used for implementing the method (100) according to any one of claims 1 to 9.

11. A computer program product, wherein the computer program product comprises computer instructions, which are at least used for assisting in implementing the method (100) according to any one of claims 1 to 9 when executed by a processor.

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