Method, device and equipment for detecting self-discharge differences among battery cells in a battery pack

Abstract

The embodiments of the present invention relate to the field of battery technology and disclose a method, device, and detection equipment for detecting the self-discharge differences between cells in a battery pack. The detection method includes determining a complete rest period for a number of cells; obtaining the SOC value of each cell during each complete rest period; determining one cell among the number of cells as a reference cell and the other cells as cells to be tested; obtaining an expected SOC value; calculating a first difference between the SOC value of each cell to be tested and the reference cell, and a second difference between the reference cell and the expected SOC value; constructing an SOC difference mapping model; calculating the SOC difference mapping value of each cell to be tested during each complete rest period; and testing a number of cells to be tested based on the SOC difference mapping value of each cell to be tested. Through the above-mentioned method, the embodiments of the present invention can eliminate the inconsistency of the charge capacity of each cell to detect the self-discharge differences of each cell in the battery pack, thereby improving the accuracy of the detection results.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of battery technology, and in particular to a method, device, and equipment for detecting self-discharge differences among battery cells in a battery pack. Background Art

[0002] With the advocacy of new energy concepts, battery modules, represented by lithium batteries, are becoming increasingly widely used. These modules consist of multiple cells, each of which is connected in series or parallel to create a larger module. This allows for greater battery capacity. However, this combination of multiple cells also poses a number of safety risks. Therefore, it is crucial to keep abreast of the health of each cell.

[0003] During the process of implementing the embodiments of the present invention, the inventors of the embodiments of the present invention discovered that: currently, cells with large self-discharge differences can be identified as unhealthy cells. However, after the battery module has been used for a period of time, due to the inconsistent capacity of each cell and the different percentage status of the remaining power of the cell, the general detection results have a large deviation. Summary of the Invention

[0004] The main technical problem solved by the embodiments of the present invention is to provide a method, device and detection equipment for detecting the self-discharge differences of each battery cell in a battery pack, which can eliminate the inconsistency of the power capacity of each battery cell to detect the self-discharge differences of each battery cell in the battery pack and improve the accuracy of the detection results.

[0005] In order to solve the above technical problems, a technical solution adopted in an embodiment of the present invention is: to provide a method for detecting the self-discharge difference of each battery cell of a battery pack, the detection method comprising: determining M completely static periods in which the plurality of battery cells are simultaneously in a completely static state; obtaining the SOC value of each of the battery cells in each of the completely static periods; determining one of the plurality of battery cells as a reference battery cell, and determining the other battery cells except the reference battery cell as the battery cells to be tested; obtaining the expected SOC value; calculating and determining the difference between the SOC value of each of the battery cells to be tested and the SOC value of the reference battery cell in each of the completely static periods; The difference within the completely static period is a first difference, and the difference between the SOC value of the reference battery cell and the expected SOC value within each completely static period is a second difference; based on the first difference and the second difference, an SOC difference mapping model between the reference battery cell and the battery cell to be tested is constructed; based on the first difference, the second difference and the SOC difference mapping model, the SOC difference mapping value of each battery cell to be tested within each completely static period is calculated; based on the SOC difference mapping value of each battery cell to be tested, the several battery cells to be tested are tested.

[0006] Optionally, the step of constructing an SOC difference mapping model between the reference cell and the cell to be tested based on the first difference and the second difference further includes: determining the first difference and the second difference in each of the completely static periods as a difference group to obtain M difference groups; performing linear fitting on the M difference groups to obtain a fitting function, and calculating the final slope of the fitting function; and constructing an SOC difference mapping model between the reference cell and the cell to be tested based on the final slope and the M difference groups.

[0007] Optionally, the step of performing linear fitting on the M difference groups to obtain a fitting function and calculating the final slope of the fitting function further includes: starting from the first difference group, sequentially selecting the next N adjacent difference groups to perform linear regression fitting functions to obtain P fitting functions, where P=M-N+1; calculating the slope of each fitting function to obtain P fitting slopes; sorting the P fitting slopes from small to large to form a slope queue, and determining the slope in the middle of the slope queue as the final slope.

[0008] Optionally, the SOC difference mapping model is: , where n is the number of the battery cell to be tested in the battery pack, s is the number of the reference battery cell in the battery pack, and b is the expected SOC value; : The SOC difference between the nth test cell and the reference cell s during a completely static period, : The SOC difference between the expected SOC value and the SOC value of the reference cell s during the complete rest period; is the SOC difference mapping value between the nth battery cell to be tested and the reference battery cell s during the completely static period.

[0009] Optionally, the step of determining M completely static periods during which the battery cells are simultaneously in a completely static state further includes: obtaining a time period during which the current of the battery cells is less than a preset current threshold; obtaining the voltage of the battery cells within the time period; fitting the voltage within the time period into a voltage function; judging whether the slope of the voltage function is less than a first preset slope; if so, determining that the time period is a completely static period during which the battery cells are in a completely static state; if not, determining to discard the time period and returning to the step of obtaining the time period during which the current of the battery cells is less than the preset current threshold.

[0010] Optionally, the step of testing the several battery cells to be tested based on the SOC difference mapping value of each of the battery cells to be tested further includes: arranging in sequence the M SOC difference mapping values ​​corresponding to one of the battery cells to be tested in the M completely static periods; calculating in sequence the slopes of the straight lines where two adjacent SOC difference mapping values ​​are located to obtain several slopes; judging whether the several slopes are all within a preset slope range; if so, determining that the self-discharge of the battery cell to be tested is normal; if not, determining that the self-discharge of the battery cell to be tested is abnormal.

[0011] Optionally, the step of testing the several cells to be tested based on the SOC difference mapping value of each cell to be tested also includes: judging whether the SOC difference mapping value of each cell to be tested during the M completely static periods is within a preset difference mapping value range; if so, determining that the self-discharge of the several cells to be tested in the battery pack is normal; if not, determining that the self-discharge of the cell to be tested whose SOC difference mapping value exceeds the preset difference mapping value range is abnormal.

[0012] In order to solve the above technical problems, another technical solution adopted in an embodiment of the present invention is: to provide a device for detecting the self-discharge difference of each battery cell in a battery pack, the device comprising: a first determination module for determining M completely static periods in which the plurality of battery cells are simultaneously in a completely static state; a first acquisition module for acquiring the SOC value of each of the battery cells in each of the completely static periods; a second determination module for determining one of the plurality of battery cells as a reference battery cell, and determining the other battery cells except the reference battery cell as the battery cells to be detected; a second acquisition module for acquiring an expected SOC value; a first calculation module for calculating and determining the SOC value of each of the battery cells to be detected and the reference battery cell. The difference in the SOC value of the battery cell during each of the completely static periods is a first difference, and the difference between the SOC value of the reference battery cell and the expected SOC value during each of the completely static periods is a second difference; a construction module is used to construct an SOC difference mapping model between the reference battery cell and the battery cell to be tested based on the first difference and the second difference; a second calculation module is used to calculate the SOC difference mapping value of each of the battery cells to be tested during each of the completely static periods based on the first difference, the second difference and the SOC difference mapping model; a detection module is used to detect the several battery cells to be tested based on the SOC difference mapping value of each of the battery cells to be tested.

[0013] To solve the above technical problems, another technical solution adopted in an embodiment of the present invention is: providing a detection device, including: a controller, the controller including: at least one processor, and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method as described above.

[0014] To solve the above technical problems, another technical solution adopted in an embodiment of the present invention is: providing a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable the server to execute the method described above.

[0015] The beneficial effects of the embodiments of the present invention are as follows: Different from the prior art, the embodiment of the present invention is a method for detecting the self-discharge difference of each battery cell of a battery pack, which first determines M completely static periods in which the plurality of battery cells are simultaneously in a completely static state; obtains the SOC value of each battery cell in each of the completely static periods; determines one battery cell among the plurality of battery cells as a reference battery cell, and determines the other battery cells except the reference battery cell as the battery cells to be tested; obtains the expected SOC value; calculates and determines the difference between the SOC value of each battery cell to be tested and the SOC value of the reference battery cell in each completely static period; The difference between the SOC value of the reference cell and the expected SOC value in each of the completely idle periods is a first difference, and the difference between the SOC value of the reference cell and the expected SOC value in each of the completely idle periods is a second difference; based on the first difference and the second difference, an SOC difference mapping model is constructed between the reference cell and the cell to be tested; based on the first difference, the second difference and the SOC difference mapping model, the SOC difference mapping value of each of the cells to be tested in each of the completely idle periods is calculated; based on the SOC difference mapping value of each of the cells to be tested, the several cells to be tested are tested. Through the above steps, the embodiment of the present invention can eliminate the inconsistency of the power capacity of each cell to detect the self-discharge difference of each cell in the battery pack, thereby improving the accuracy of the test results. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly describes the drawings required for describing the specific embodiments or the prior art. Similar elements or parts are generally identified by similar reference numerals throughout the drawings. Elements or parts in the drawings are not necessarily drawn to scale.

[0017] Figure 1 2. It is a schematic diagram of the application environment of the method for detecting the self-discharge difference between cells in a battery pack according to an embodiment of the present invention;

[0018] Figure 2 This is a flow chart of a method for detecting self-discharge differences among cells in a battery pack according to an embodiment of the present invention;

[0019] Figure 3 This is a flow chart of step S101 in the method for detecting the self-discharge difference between cells in a battery pack according to an embodiment of the present invention;

[0020] Figure 4 is a flow chart of step S106 in the method for detecting the self-discharge difference between cells in a battery pack according to an embodiment of the present invention;

[0021] Figure 5 is a flow chart of step S1062 in the method for detecting self-discharge differences among cells in a battery pack according to an embodiment of the present invention;

[0022] Figure 6 This is a flow chart of step S108 in the method for detecting the self-discharge difference between cells in a battery pack according to an embodiment of the present invention;

[0023] Figure 7 is a flow chart of step S108 in a method for detecting self-discharge differences among battery cells of a battery pack according to another embodiment of the present invention;

[0024] Figure 8 This is a structural block diagram of a device for detecting self-discharge differences among cells in a battery pack according to an embodiment of the present invention;

[0025] Figure 9 Schematic diagram of a detection device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to facilitate the understanding of the present invention, the present invention will be described in more detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that when an element is described as "fixed on" another element, it can be directly on the other element, or there can be one or more centered elements therebetween. When an element is described as "connected" to another element, it can be directly connected to the other element, or there can be one or more centered elements therebetween. The terms "upper", "lower", "inside", "outside", "vertical", "horizontal" and the like used in this specification indicate an orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "", "", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0027] Unless otherwise defined, all technical and scientific terms used in this specification have the same meanings as those commonly understood by those skilled in the art to which this invention pertains. The terms used in this specification are intended only to describe specific embodiments and are not intended to limit the invention. The term "and / or" as used in this specification includes any and all combinations of one or more of the associated listed items.

[0028] In addition, the technical features involved in different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0029] See Figure 1 , Figure 1 Schematic diagram of an application environment for a method for detecting differences in self-discharge between cells in a battery pack according to an embodiment of the present invention. The application environment includes an electric vehicle 10 and a cloud device 20. The battery vehicle 10 includes a vehicle body 11, a battery pack 12, and a data processor 13. The battery pack 12 and the data processor 13 are disposed within the vehicle body 11. The battery pack 12 is electrically connected to the data processor 13. The data processor 13 is configured to collect and store data related to the battery pack 12. The cloud device 20 obtains data related to the battery pack 12 from the data processor 13 to facilitate the task of detecting differences in self-discharge between cells in the battery pack 12.

[0030] Figure 2 A flow chart of a method for detecting self-discharge differences among cells in a battery pack according to the present invention is shown. Figure 2 As shown, the detection method includes the following steps:

[0031] Step S101 : determining M completely idle periods during which the plurality of battery cells are simultaneously in a completely idle state.

[0032] Wherein M is a natural number greater than zero.

[0033] In the field of new energy vehicles, the energy storage power source equipped in the vehicle is composed of multiple battery packs connected in series, in parallel, or in series and parallel. In the embodiment of the present invention, the battery cells in the battery pack are connected in series.

[0034] A battery cell is in a completely static state when the charge and discharge current of the battery cell is detected. When the charge and discharge current of the battery cell is less than a preset current threshold, the battery cell is considered to be in a completely static state. Since several battery cells in the battery pack are connected in series, it can be considered that when one of the battery cells is in a completely static state, the other battery cells in the battery pack are also in a completely static state. The time period when the battery cell is in a completely static state is the completely static period. The charge and discharge current of the battery cell is detected and collected by a current sensor in the battery pack, and the preset current threshold is a manually set current value. In one embodiment of the present invention, the current threshold is generally preset to 3 amps. When the current sensor collects a charge current or discharge current of the battery cell that is less than or equal to 3 amps, it can be considered that the internal electrochemical environment of the battery cell with such a small current approaches a steady state, and the battery cell can be considered to be in a completely static state.

[0035] In some embodiments, see Figure 3 , step S101 includes:

[0036] Step S1011 , obtaining a time period in which the currents of the plurality of battery cells are less than a preset current threshold.

[0037] The data of several battery cells in the electric vehicle battery pack and the electric vehicle mileage data are obtained through the cloud, and the data of the battery cells are cleaned to eliminate invalid information, wherein the data of the battery cells include current data and voltage data.

[0038] The current for each mileage is traversed. When the current is less than or equal to the absolute value of the current sensor's sampling accuracy, the battery cell is considered to have started resting, and this time is recorded as the rest start time. The current is traversed backwards. When the current is greater than the absolute value of the current sensor's accuracy, the battery cell is considered to have ended resting, and the current time is recorded as the rest end time. The complete rest period is defined as the rest start time to the rest end time.

[0039] Step S1012: obtaining the voltages of the plurality of battery cells within the time period.

[0040] The voltage data corresponds to the current in a one-to-one manner, and the voltage is an open-circuit voltage.

[0041] Step S1013: Fit the voltage within the time period into a voltage function.

[0042] In the embodiment of the present invention, an exponential function is used to perform function fitting on the voltage data. It is understandable that in other embodiments, other functions may be used to perform voltage function fitting, such as a logarithmic function.

[0043] Step S1014 , determining whether the slope of the voltage function is less than a first preset slope.

[0044] The current of the battery cell in the completely static period is still in a changing state, and the voltage corresponding to the current is also in a changing state. When the slope of the fitted voltage function is less than the first preset slope, the current voltage change rate is small enough, that is, it can be considered that the current battery cell is in a completely static state.

[0045] Step S1015: If yes, determine that the time period is a completely idle period in which the battery cells are in a completely idle state.

[0046] Step S1016: If not, determine to discard the time period, and return to the step of obtaining the time period in which the currents of the plurality of battery cells are less than the preset current threshold.

[0047] When the voltage slope is greater than the first preset slope, it is considered that the battery cell in the current time period is still in the charge and discharge state, and the current time period should be discarded, and the current data should be traversed to search for a completely static period.

[0048] Step S102 , obtaining the SOC value of each of the battery cells during each of the completely stationary periods.

[0049] SOC (state of charge) refers to the percentage of remaining battery power, that is, the ratio of the remaining battery power to the current capacity of the battery.

[0050] When the slope of the fitted voltage function is less than the first preset slope, the last voltage value of the fitted voltage function is selected as the open circuit voltage of the battery cell during the current completely static period, and the SOC is queried according to the OCV-SOC table, where the OCV-SOC (Open Circuit Voltage) table refers to a table that corresponds one-to-one between the battery open circuit voltage and the battery state of charge.

[0051] In step S103 , one of the plurality of battery cells is determined as a reference battery cell, and the other battery cells except the reference battery cell are determined as battery cells to be inspected.

[0052] Step S104: Obtain the expected SOC value.

[0053] An SOC value is preset as the expected SOC value, where the expected SOC value is used to align the SOC value of the reference cell at each rest to the expected SOC value using the SOC difference mapping model. At this time, the change in the SOC difference between the cell to be tested and the reference cell between different rests can reflect the self-discharge difference between them. The expected SOC value is generally set to 95% or 100%, which can be adjusted according to actual needs.

[0054] Step S105, calculating and determining that the difference between the SOC value of each of the battery cells to be tested and the SOC value of the reference battery cell in each of the completely static periods is a first difference, and the difference between the SOC value of the reference battery cell and the expected SOC value in each of the completely static periods is a second difference.

[0055] Step S106 : constructing an SOC difference mapping model between the reference cell and the cell to be tested according to the first difference and the second difference.

[0056] The SOC difference mapping model is: , where n is the number of the battery cell to be tested in the battery pack, s is the number of the reference battery cell in the battery pack, and b is the expected SOC value; : The SOC difference between the nth test cell and the reference cell s during a completely static period, : The SOC difference between the expected SOC value and the SOC value of the reference cell s during the complete rest period; is the SOC difference mapping value between the nth test cell and the reference cell s during the completely static period. The working principle of this mapping model is: each time it is static, the SOC of the reference cell is compensated After that, the SOC of the reference cell is aligned to the expected SOC. At this time, by comparing the SOC difference mapping value ( ), we can get the change of the self-discharge difference between the test cell No. n and the reference cell No. s over time.

[0057] In some embodiments, see Figure 4 , step S106 includes:

[0058] Step S1061 : Determine a first difference value and a second difference value in each completely static period as a difference value group, and obtain M difference value groups.

[0059] A first difference value and a second difference value form a difference value group, which is equivalent to X and Y in a rectangular coordinate system determining a coordinate point.

[0060] Step S1062 : Perform linear fitting on the M difference value groups to obtain a fitting function, and calculate the final slope of the fitting function.

[0061] A plurality of difference value groups are placed in a discrete state in a rectangular coordinate system, a linear regression function is fitted to the discrete points, and the slope of the fitting function is calculated.

[0062] In some embodiments, see Figure 5 , step S1062 includes:

[0063] Step S10621 , starting from the first difference group, sequentially select the next N adjacent difference groups to perform linear regression fitting functions to obtain P fitting functions, where P=M-N+1, and P and N are both natural numbers greater than zero.

[0064] Step S10622: Calculate the slope of each fitting function to obtain P fitting slopes.

[0065] Step S10623: sort the P fitting slopes from small to large to form a slope queue, and determine the slope in the middle of the slope queue as the final slope.

[0066] For easier understanding, the following example illustrates the process of step S1062. Assuming that there are 30 completely static periods, there are 30 difference groups. Starting from the first difference group, 20 difference groups are selected in turn for linear regression, that is, the first function is fitted from the 1st group to the 20th group, the second function is fitted from the 2nd group to the 21st group, the third function is fitted from the 3rd group to the 22nd group, and so on, until the 11th function is fitted from the 11th group to the 30th group, and 11 fitting functions are obtained. The slope of each of the 11 fitting functions is calculated to obtain 11 slopes. The 11 slopes are arranged in ascending order, and the slope in the middle of the queue is taken as the final slope, that is, the 6th slope.

[0067] Step S1063 : constructing an SOC difference mapping model between the reference cell and the cell to be tested according to the final slope and the M difference value groups.

[0068] Step S107 : calculating the SOC difference mapping value of each of the battery cells to be tested in each of the completely idle periods according to the first difference, the second difference, and the SOC difference mapping model.

[0069] By substituting the first difference between one of the battery cells and the reference battery cell during a certain completely static period and the second difference between the reference battery cell and the expected SOC value into the SOC difference mapping model, the SOC difference mapping value between the battery cell to be tested and the reference battery cell during the completely static period can be obtained. Similarly, the SOC difference mapping values ​​between other battery cells to be tested and the reference battery cell in the battery pack during the completely static period can be obtained, as well as the SOC difference mapping values ​​between each battery cell to be tested and the reference battery cell in the selected M completely static periods.

[0070] Step S108 : testing the plurality of cells to be tested according to the SOC difference mapping value of each cell to be tested.

[0071] In some embodiments, see Figure 6 , step S108 includes:

[0072] Step S1081 , sequentially arranging the M SOC difference mapping values ​​corresponding to the M completely idle periods of the battery cell to be inspected.

[0073] The SOC difference mapping values ​​are arranged in the order of selection of the completely stationary periods.

[0074] Step S1082 : sequentially calculating the slopes of the straight lines where two adjacent SOC difference mapping values ​​are located, and obtaining a plurality of slopes.

[0075] Step S1083: Determine whether the plurality of slopes are all within a preset slope range.

[0076] When the slope of the straight line between two adjacent SOC difference mapping values ​​is not within the preset slope range, it means that the calculated slope is too large or too small, that is, the difference between the two adjacent SOC difference mapping values ​​is too large. According to experience, the battery cell whose SOC difference mapping value suddenly increases over time is likely to become a problematic battery cell, so it needs to be detected.

[0077] Step S1084: If yes, determine that the self-discharge of the battery cell to be inspected is normal.

[0078] Step S1085: If not, determine that the self-discharge of the battery cell to be inspected is abnormal.

[0079] In some embodiments, see Figure 7 , step S108 further includes:

[0080] Step S1086 , determining whether the SOC difference mapping value of each of the battery cells to be inspected during the M completely idle periods is within a preset difference mapping value range.

[0081] When the SOC difference mapping value of a cell to be tested is not within the preset difference mapping value range, it means that the SOC difference mapping value of the cell to be tested is significantly different from the SOC difference mapping values ​​of other cells to be tested. According to experience, a cell to be tested whose SOC difference mapping value is always greater than that of other cells to be tested is likely to become a problem cell, and therefore needs to be detected.

[0082] Step S1087: If yes, determine that the self-discharge of the plurality of cells to be inspected in the battery pack is normal.

[0083] Step S1088: If not, determining that the SOC difference mapping value exceeds the preset difference mapping value range indicates that the self-discharge of the battery cell to be inspected is abnormal.

[0084] It is understandable that, in some embodiments, the method described in the embodiments of the present invention is not limited to use in cloud devices, but can also be applied to battery data monitoring platforms such as automobile BMS (Battery Management System) and energy storage BMS.

[0085] The beneficial effects of the embodiments of the present invention are as follows: Different from the prior art, the embodiment of the present invention is a method for detecting the self-discharge difference of each battery cell of a battery pack, which first determines M completely static periods in which the plurality of battery cells are simultaneously in a completely static state; obtains the SOC value of each battery cell in each of the completely static periods; determines one battery cell among the plurality of battery cells as a reference battery cell, and determines the other battery cells except the reference battery cell as the battery cells to be tested; obtains the expected SOC value; calculates and determines the difference between the SOC value of each battery cell to be tested and the SOC value of the reference battery cell in each completely static period; The difference between the SOC value of the reference cell and the expected SOC value in each of the completely idle periods is a first difference, and the difference between the SOC value of the reference cell and the expected SOC value in each of the completely idle periods is a second difference; based on the first difference and the second difference, an SOC difference mapping model is constructed between the reference cell and the cell to be tested; based on the first difference, the second difference and the SOC difference mapping model, the SOC difference mapping value of each of the cells to be tested in each of the completely idle periods is calculated; based on the SOC difference mapping value of each of the cells to be tested, the several cells to be tested are tested. Through the above steps, the embodiment of the present invention can eliminate the inconsistency of the power capacity of each cell to detect the self-discharge difference of each cell in the battery pack, thereby improving the accuracy of the test results.

[0086] The present invention also provides an embodiment of a device 60 for detecting the self-discharge difference of each cell in a battery pack, see Figure 8 , Figure 8The functional block diagram of a device 60 for detecting the self-discharge difference of each battery cell of a battery pack according to the present invention is shown. The detection device 60 includes a first determination module 601, a first acquisition module 602, a second determination module 603, a second acquisition module 604, a first calculation module 605, a construction module 606, a second calculation module 607, and a detection module 608. The first determination module 601 is used to determine M completely static periods in which the battery cells are simultaneously in a completely static state; the first acquisition module 602 is used to obtain the SOC value of each of the battery cells in each of the completely static periods; the second determination module 603 is used to determine one of the battery cells as a reference battery cell, and to determine the other battery cells except the reference battery cell as the battery cells to be tested; the second acquisition module 604 is used to obtain the expected SOC value; the first calculation module 605 is used to calculate and determine that the difference between the SOC value of each of the battery cells to be tested and the SOC value of the reference battery cell in each of the completely static periods is a first difference value. value, and the difference between the SOC value of the reference battery cell and the expected SOC value in each of the completely static periods is a second difference; the construction module 606 is used to construct an SOC difference mapping model between the reference battery cell and the battery cell to be tested according to the first difference and the second difference; the second calculation module 607 is used to calculate the SOC difference mapping value of each of the battery cells to be tested in each of the completely static periods according to the first difference, the second difference and the SOC difference mapping model; the detection module 608 is used to detect the several battery cells to be tested according to the SOC difference mapping value of each of the battery cells to be tested.

[0087] The first determination module 601 includes a first acquisition unit 6011, a second acquisition unit 6012, a first fitting unit 6013, a first judgment unit 6014, a first determination unit 6015, and a second determination unit 6016. The first acquisition unit 6011 is configured to acquire a time period during which the currents of the plurality of battery cells are less than a preset current threshold; the second acquisition unit 6012 is configured to acquire the voltages of the plurality of battery cells within the time period; the first fitting unit 6013 is configured to fit the voltages within the time period into a voltage function; the first judgment unit 6014 is configured to determine whether a slope of the voltage function is less than a first preset slope; the first determination unit 6015 is configured to, if so, determine that the time period is a completely idle period during which the plurality of battery cells are in a completely idle state; and the second determination unit 6016 is configured to, if not, discard the time period and return to the step of acquiring a time period during which the currents of the plurality of battery cells are less than the preset current threshold.

[0088] The construction module 606 includes a third determination unit 6061, a second fitting unit 6062, and a first construction unit 6063. The third determination unit 6061 is configured to determine a first difference and a second difference within each completely static period as a difference group, thereby obtaining M difference groups; the second fitting unit 6062 is configured to perform linear fitting on the M difference groups to obtain a fitting function and calculate a final slope of the fitting function; and the first construction unit 6063 is configured to construct an SOC difference mapping model between the reference cell and the cell to be tested based on the final slope and the M difference groups.

[0089] Among them, the second fitting unit 6062 is specifically used to start from the first difference group, and sequentially select the next N adjacent difference groups to perform linear regression fitting functions to obtain P fitting functions, where P=M-N+1; calculate the slope of each fitting function to obtain P fitting slopes; sort the P fitting slopes from small to large to form a slope queue, and determine the slope in the middle of the slope queue as the final slope.

[0090] The detection module 608 includes a first arrangement unit 6081 , a first calculation unit 6082 , a second judgment unit 6083 , a fourth determination unit 6084 , a fifth determination unit 6085 , a third judgment unit 6086 , a sixth determination unit 6087 and a seventh determination unit 6088 . Among them, the first arrangement unit 6081 is used to arrange in sequence the M SOC difference mapping values ​​corresponding to the battery cell to be tested in the M completely static periods; the first calculation unit 6082 is used to calculate in sequence the slopes of the straight lines where two adjacent SOC difference mapping values ​​are located to obtain several slopes; the second judgment unit 6083 is used to judge whether several of the slopes are all within a preset slope range; the fourth determination unit 6084 is used to determine that the self-discharge of the battery cell to be tested is normal if so, and the fifth determination unit 6085 is used to determine that the self-discharge of the battery cell to be tested is abnormal if not; the third judgment unit 6086 is used to judge whether the SOC difference mapping value of each of the battery cells to be tested in the M completely static periods is within the preset difference mapping value range; the sixth determination unit 6087 is used to determine that the self-discharge of several battery cells to be tested in the battery pack is normal if so; and the seventh determination unit 6088 is used to determine that the self-discharge of the battery cell to be tested whose SOC difference mapping value exceeds the preset difference mapping value range is abnormal if not.

[0091] The beneficial effects of the embodiments of the present invention are as follows: Different from the prior art, the embodiment of the present invention is a method for detecting the self-discharge difference of each battery cell of a battery pack, firstly determining, through a first determination module 601, M completely static periods in which the plurality of battery cells are simultaneously in a completely static state; then obtaining, through a first acquisition module 602, the SOC value of each of the battery cells in each of the completely static periods; then determining, through a second determination module 603, one of the plurality of battery cells as a reference battery cell, and determining, through a second determination module 603, the other battery cells except the reference battery cell as the battery cells to be tested; then obtaining, through a second acquisition module 604, an expected SOC value; then calculating and determining, through a first calculation module 605, the difference between the SOC value of each of the battery cells to be tested and the reference battery cell. The difference in the SOC value of the battery cell during each of the completely static periods is a first difference, and the difference between the SOC value of the reference battery cell and the expected SOC value during each of the completely static periods is a second difference; then, a construction module 606 is used to construct an SOC difference mapping model between the reference battery cell and the battery cell to be tested based on the first difference and the second difference; then, a second calculation module 607 is used to calculate the SOC difference mapping value of each of the battery cells to be tested during each of the completely static periods based on the first difference, the second difference, and the SOC difference mapping model; finally, a detection module 608 is used to detect the several battery cells to be tested based on the SOC difference mapping value of each of the battery cells to be tested. Through the above-mentioned device, the embodiment of the present invention can eliminate the inconsistency of the power capacity of each battery cell to detect the self-discharge difference of each battery cell in the battery pack, thereby improving the accuracy of the detection results.

[0092] The present invention also provides an embodiment of the detection device 70, see Figure 9 , Figure 9 is a schematic diagram of an embodiment of a detection device 70 according to an embodiment of the present invention. The controller of the detection device 70 includes: at least one processor 701; and a memory 702 in communication with the at least one processor 701. Figure 9 The memory 702 stores instructions that can be executed by the at least one processor 701, and the instructions are executed by the at least one processor 701 so that the at least one processor 701 can perform the above Figures 2 to 7 The method for detecting the self-discharge difference of each battery cell of a battery pack, and performing the above Figure 8 The processor 701 and the memory 702 can be connected via a bus or other means. Figure 9 The bus connection is taken as an example.

[0093] The memory 702 is a non-volatile computer-readable storage medium that can be used to store non-volatile software programs, non-volatile computer executable programs and modules, such as the program instructions / modules corresponding to the method for detecting the self-discharge difference of each battery cell in a battery pack in an embodiment of the present application, for example, Figure 8 The processor 701 executes various functional applications and data processing of the server by running the non-volatile software programs, instructions and modules stored in the memory 702, that is, implements the above-mentioned method embodiment, a method for detecting the self-discharge difference of each battery cell in a battery pack.

[0094] The memory 702 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created based on the use of a device for detecting differences in self-discharge between cells in a battery pack, etc. In addition, the memory 702 may include a high-speed random access memory and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 702 may optionally include a memory remotely located relative to the processor 701, and these remote memories may be connected to a device for detecting differences in self-discharge between cells in a battery pack via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0095] The one or more modules are stored in the memory 702, and when executed by the one or more processors 701, a method for detecting the self-discharge difference of each cell of a battery pack in any of the above method embodiments is executed, for example, the method described above is executed. Figures 2 to 7 The method steps, and performing the above Figure 8 A device for detecting the self-discharge differences of each battery cell in a battery pack.

[0096] The above-mentioned product can execute the method provided in the embodiment of this application, and has the functional modules and beneficial effects corresponding to the execution method. For technical details not fully described in this embodiment, please refer to the method provided in the embodiment of this application.

[0097] The present application also provides a non-volatile computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, which are executed by one or more processors, for example, to execute the above-described Figures 2 to 7 A method and steps for detecting the self-discharge difference of each battery cell in a battery pack, and performing the above Figure 8 A device for detecting the self-discharge differences of each battery cell in a battery pack.

[0098] The present application also provides a computer program product, including a computer program stored on a non-volatile computer-readable storage medium, wherein the computer program includes program instructions. When the program instructions are executed by a computer, the computer executes a method for detecting the self-discharge difference of each battery cell in a battery pack in any of the above-described method embodiments, for example, executing the above-described Figures 2 to 7 The method steps, and performing the above Figure 8 A device for detecting the self-discharge differences of each battery cell in a battery pack.

[0099] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention's description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for detecting the self-discharge difference of each battery cell in a battery pack, characterized in that: include: Determine M completely idle periods during which a plurality of battery cells are simultaneously in a completely idle state; Obtaining the SOC value of each battery cell during each of the completely static periods; Determining one of the plurality of battery cells as a reference battery cell, and determining the other battery cells except the reference battery cell as battery cells to be tested; Obtain expected SOC value; Calculating and determining a difference between the SOC value of each of the cells to be tested and the SOC value of the reference cell during each of the completely stationary periods as a first difference, and a difference between the SOC value of the reference cell and the expected SOC value during each of the completely stationary periods as a second difference; Constructing an SOC difference mapping model between the reference cell and the cell to be tested according to the first difference and the second difference; Calculating an SOC difference mapping value of each of the battery cells to be tested in each of the completely idle periods according to the first difference, the second difference, and the SOC difference mapping model; Each of the battery cells to be tested is tested according to the SOC difference mapping value of each of the battery cells to be tested.

2. The detection method according to claim 1, wherein The step of constructing an SOC difference mapping model between the reference cell and the cell to be tested based on the first difference and the second difference further includes: Determine the first difference and the second difference in each completely static period as a difference group, to obtain M difference groups; Performing linear fitting on the M difference value groups to obtain a fitting function, and calculating a final slope of the fitting function; An SOC difference mapping model between the reference cell and the cell to be tested is constructed according to the final slope and the M difference value groups.

3. The detection method according to claim 2, characterized in that The step of performing linear fitting on the M difference value groups to obtain a fitting function and calculating a final slope of the fitting function further includes: Starting from the first difference group of the M difference groups, sequentially select the next N adjacent difference groups to perform linear regression fitting functions to obtain P fitting functions, where P = M - N + 1; Calculating the slope of each fitting function to obtain P fitting slopes; The P fitting slopes are sorted from small to large to form a slope queue, and the slope in the middle of the slope queue is determined as the final slope.

4. The detection method according to any one of claims 1 to 3, characterized in that The SOC difference mapping model is: , where n is the number of the battery cell to be tested in the battery pack, s is the number of the reference battery cell in the battery pack, and b is the expected SOC value; : The SOC difference between the nth test cell and the reference cell s during a completely static period, : The SOC difference between the expected SOC value and the SOC value of the reference cell s during the complete rest period; is the SOC difference mapping value between the nth battery cell to be tested and the reference battery cell s during the completely static period.

5. The detection method according to claim 1, wherein The step of determining M completely idle periods during which the plurality of battery cells are simultaneously in a completely idle state further includes: Obtaining a time period in which the current of a plurality of battery cells is less than a preset current threshold; Obtaining the voltages of the plurality of battery cells within the time period; fitting the voltage within the time period into a voltage function; Determining whether the slope of the voltage function is less than a first preset slope; If yes, determining that the time period is a completely static period in which the plurality of battery cells are in a completely static state; If not, it is determined to discard the time period, and the process returns to the step of obtaining a time period in which the currents of the plurality of battery cells are less than the preset current threshold.

6. The detection method according to claim 1, characterized in that The step of testing each of the cells to be tested according to the SOC difference mapping value of each of the cells to be tested further includes: Arrange in sequence the M SOC difference mapping values ​​corresponding to the M completely static periods of the battery cell to be tested; The slopes of the lines where two adjacent SOC difference mapping values ​​are located are calculated in sequence to obtain several slopes; Determining whether the plurality of slopes are all within a preset slope range; If so, it is determined that the self-discharge of the battery cell to be inspected is normal; If not, it is determined that the self-discharge of the battery cell to be inspected is abnormal.

7. The detection method according to claim 1, characterized in that The step of testing each of the cells to be tested according to the SOC difference mapping value of each of the cells to be tested further includes: Determine whether the SOC difference mapping value of each of the battery cells to be tested during the M completely static periods is within a preset difference mapping value range; If so, it is determined that the self-discharge of several cells to be tested in the battery pack is normal; If not, it is determined that the self-discharge of the battery cell to be inspected is abnormal because the SOC difference mapping value exceeds the preset difference mapping value range.

8. A device for detecting the self-discharge difference of each battery cell in a battery pack, characterized in that: The device comprises: A first determining module is used to determine M completely static periods during which a plurality of battery cells are simultaneously in a completely static state; A first acquisition module is used to obtain the SOC value of each battery cell during each completely static period; a second determining module, configured to determine one of the plurality of battery cells as a reference battery cell, and to determine other battery cells except the reference battery cell as battery cells to be tested; A second acquisition module is used to obtain an expected SOC value; a first calculation module, configured to calculate and determine that a difference between the SOC value of each of the cells to be tested and the SOC value of the reference cell during each of the completely stationary periods is a first difference, and a difference between the SOC value of the reference cell and the expected SOC value during each of the completely stationary periods is a second difference; A construction module, configured to construct an SOC difference mapping model between the reference cell and the cell to be tested according to the first difference and the second difference; a second calculation module, configured to calculate an SOC difference mapping value of each of the battery cells to be tested in each of the completely static periods according to the first difference, the second difference, and the SOC difference mapping model; The detection module is used to detect each of the battery cells to be detected according to the SOC difference mapping value of each of the battery cells to be detected.

9. A detection device comprising: A controller comprising: at least one processor, and a memory communicatively connected to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that The non-transitory computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a server to execute the method according to any one of claims 1 to 7.

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