Method and device for detecting self-discharge condition of battery pack

Abstract

The invention provides a method and device for detecting the self-discharge condition of a battery pack, and the method comprises the steps: obtaining the operation data of a battery, and the operation data of the battery comprises the voltage data of at least a part of single cells in the battery pack; determining a group of time points when the battery pack is in a balanced state according to the battery operation data; according to the battery operation data, obtaining information related to a voltage difference between time points of single battery cells in the battery pack in the group of time points; and based on the information, determining whether the self-discharge conditions of the single cells in the battery pack are consistent or not.

Description

Technical Field

[0001] Broadly speaking, the present invention relates to battery technology. Specifically, the present invention relates to a method and apparatus for detecting the self-discharge consistency of individual battery cells within a battery pack. Background Art

[0002] Currently, batteries are increasingly used in many application fields such as automobiles, mobile base stations, energy storage power stations, etc., and these batteries usually appear in the form of battery packs in which multiple batteries are connected in series and / or in parallel to provide sufficient power. The capacity and lifespan of a battery pack are not only related to the individual batteries therein, but also to the consistency among the individual batteries. Poor consistency will lead to a decline in the performance of the entire battery pack. As an important item among the consistency indicators, there are many methods and technologies for measuring or detecting self-discharge consistency.

[0003] However, these methods generally have some deficiencies or limitations. For example, capacity testing, open-circuit voltage testing, and current testing have high requirements for the measurement environment, rely on high-precision instruments, or have limited application ranges.

[0004] Therefore, there is a desire to provide a more simple and efficient method and / or measure for detecting the self-discharge consistency of batteries in a battery pack. Summary of the Invention

[0005] A brief overview of one or more embodiments is given below to provide a basic understanding of these embodiments. This overview is not an all-encompassing generalization of all expected embodiments, nor is it intended to identify key or important elements of all embodiments or to describe the scope of any or all embodiments. Its purpose is only to serve as a preface to the more detailed description provided later, to present some concepts of one or more embodiments in a simplified form.

[0006] In one aspect of the present disclosure, a method for detecting the self-discharge condition of a battery pack is provided, including: obtaining battery operation data, where the battery operation data includes voltage data for at least some of the individual battery cells within the battery pack; determining, based on the battery operation data, a set of time points at which the battery pack is in an equilibrium state; obtaining, based on the battery operation data, information related to the voltage differences between the individual battery cells within the battery pack at the time points in the set; and determining, based on the information, whether the self-discharge conditions of the individual battery cells within the battery pack are consistent.

[0007] In another aspect of the present disclosure, there is provided an apparatus for detecting the self-discharge condition of a battery pack, including: a memory; and one or more processors coupled to the memory, the one or more processors being configured to perform the following operations: obtaining battery operation data, where the battery operation data includes voltage data for at least some of the individual battery cells within the battery pack; determining, based on the battery operation data, a set of time points at which the battery pack is in a balanced state; obtaining, based on the battery operation data, information related to the voltage differences between the individual battery cells within the battery pack at the time points within the set; and determining, based on the information, whether the self-discharge conditions of the individual battery cells within the battery pack are consistent.

[0008] The method proposed in the present disclosure detects the self-discharge condition of a battery pack by using the data during the actual operation of the battery pack, making the detection method more convenient and suitable for use during the actual operation of the battery pack.

[0009] Other aspects or various variations of the present disclosure will become more apparent in view of the following detailed description and the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1A and 1B is a schematic diagram showing a comparison between an individual battery cell with abnormal self-discharge and an individual battery cell with normal self-discharge. The upper line in the figure represents the voltage of the individual battery cell with normal self-discharge, and the lower line represents the voltage of the individual battery cell with abnormal self-discharge.

[0011] Figure 2 is a timing diagram showing an example of battery operation data according to one or more aspects of the present disclosure.

[0012] Figure 3 is a timing diagram showing another example of battery operation data according to one or more aspects of the present disclosure.

[0013] Figure 4 is a schematic diagram showing a method for detecting self-discharge consistency using battery operation data according to one or more aspects of the present disclosure.

[0014] Figure 5 is a flowchart showing a method for detecting the self-discharge condition of a battery pack according to one or more aspects of the present disclosure.

[0015] Figure 6 is a schematic diagram showing a method for detecting the self-discharge condition of a battery pack according to one or more aspects of the present disclosure.

[0016] Figure 7It is a schematic diagram showing an example of a battery pack according to one or more aspects of the present disclosure.

[0017] Figure 8 It is a schematic diagram showing an example of a hardware implementation of a device for detecting the self-discharge consistency of a battery pack according to one or more aspects of the present disclosure. Detailed implementation manners

[0018] Now, multiple embodiments will be described with reference to the accompanying drawings, where the same reference numerals are used to denote the same elements herein. In the following description, for the sake of explanation, numerous specific details are given in order to provide a comprehensive understanding of one or more embodiments. However, it is obvious that the described embodiments can also be implemented without these specific details. In other examples, well-known structures and devices are shown in block diagram form in order to describe one or more embodiments.

[0019] In many current application fields, in order to provide the voltage and capacity required to drive a device (for example, an automobile), it is necessary to connect multiple battery cells in series and / or in parallel. A battery cell (or also referred to as a single battery cell) is the basic unit that constitutes a power battery, and generally uses a lithium-ion battery, with a working voltage of about several volts (for example, 3V to 5V). Connecting multiple single battery cells in series can increase the voltage, while connecting multiple single battery cells in parallel can increase the capacity. For example, dozens to hundreds of single battery cells are usually used in an electric vehicle, and these single battery cells are assembled into a battery pack (or also referred to as a battery module).

[0020] Due to factors such as internal electron leakage caused by local electron conduction of the electrolyte or other internal short circuits, poor insulation of the battery seal or gasket, or insufficient resistance between external lead cases resulting in external electron leakage, electrode or electrolyte reactions, etc., the battery cell inevitably has a self-discharge phenomenon, that is, when the battery cell is in an open-circuit state, the phenomenon of spontaneous capacity loss. The self-discharge rate of a lithium-ion battery is usually small (for example, about 3% per month), which can meet the daily use requirements of a single battery. However, when single battery cells are assembled into a battery pack or a battery module, because the characteristics of each single battery cell are inconsistent (for example, compared with most of the single battery cells in the battery pack or battery module, a few single battery cells have a significantly increased self-discharge rate), after charging or discharging, there may be overcharged or over-discharged single battery cells in the battery pack or battery module, resulting in performance deterioration. In addition, a large difference in the self-discharge rate between single battery cells will lead to a significant difference in the state of charge (SOC) among all single battery cells in a battery pack, and may even lead to a decrease in the available capacity of the battery and an increased safety risk of internal short circuits.

[0021] To measure the self-discharge condition of individual battery cells within a battery pack, traditional methods typically rely on a controlled environment, use special test instruments, and in some cases even require the removal of the battery pack from a device (e.g., a vehicle). However, such existing measurement methods or techniques have the following drawbacks: the actual usage environment of the battery pack on a device (e.g., a vehicle) is uncontrollable, and there are no special instruments for detection on the device (e.g., a vehicle).

[0022] For this reason, the present disclosure provides a more convenient method for detecting the self-discharge condition of a battery pack and adapted to the actual operating environment. This method uses data during the actual operation of the battery pack and takes a series of steps or measures to ensure measurement accuracy and timeliness.

[0023] Figure 1A And 1B is a schematic diagram showing a comparison between an individual battery cell with abnormal self-discharge and an individual battery cell with normal self-discharge. In Figure 1A , after time point 101, for example, the battery pack starts to discharge, and after a period of time until time point 102, the individual battery cell 120 with abnormal self-discharge has a lower voltage compared to the individual battery cell 110 with normal self-discharge. Similarly, in Figure 1B , for example, after the battery pack is charged for a period of time, the individual battery cell 120 with abnormal self-discharge has a lower voltage compared to the individual battery cell 110 with normal self-discharge.

[0024] In one or more aspects of the present disclosure, by using battery operation data generated during the actual use of the battery pack, an individual battery cell with abnormal self-discharge is detected by identifying an individual battery cell with a lower voltage in the battery pack. For example, the battery operation data can be data continuously collected by a battery management system (BMS) within the battery pack during the operation of the battery pack, which can include the voltages of individual battery cells within the battery pack.

[0025] Figure 2It is a timing diagram showing an example of battery operation data according to one or more aspects of the present disclosure. The battery operation data 210, 220, and 230 are data collected when the battery pack starts to start (for example, the circuit is closed and powered on). For example, when an electric vehicle is restarted after stopping driving for a period of time, the BMS can start collecting or gathering operation data about the battery pack. Generally, the battery operation data 211-214, 221-222, and 231-236 during the continuous operation of the battery pack can be collected at a frequency of 0.1 to 10 Hz. The battery operation data 210-214, 220-222, and 230-236 can be stored in the memory of the vehicle, and / or can be sent via a wired or wireless communication link and stored on a remote server (such as a supervision platform and / or a cloud platform). Each of the battery operation data 210-214, 220-222, and 230-236 can include respective single-cell identifiers (cell IDs), timestamps, mileage, vehicle status (for example, it can indicate that the vehicle is in motion, charging, parked, or (re)starting), current, and voltages of at least some of the single cells.

[0026] Since there will be obvious polarization phenomena in the battery during charge and discharge processes, deviating from the equilibrium potential, therefore, in order to ensure the accuracy of measurement, a set of data corresponding to the balanced state of the battery pack can be selected from the battery operation data 210-214, 220-222, and 230-236. For example, according to the vehicle status in the battery operation data, it can be determined that the battery operation data 210, 220, and 230 correspond to the restart state of the vehicle, so as to select the battery operation data 210, 220, and 230 as the data that can be used in the process of detecting the self-discharge consistency.

[0027] According to one aspect of the present disclosure, by calculating the difference between the timestamps in the battery operation data, it can be determined whether the time interval between two adjacent data meets (for example, equals or exceeds) a time threshold. For example, the time threshold can be set to any duration within the range of 6 hours to several days (for example, 30 hours). For example, when the time interval between the current battery operation data 230 and the adjacent battery operation data 220 meets the time threshold, a set of voltage differences 240 for each single cell in the battery operation data 230 and 220 can be calculated to determine the single cell with the largest voltage difference. When the largest voltage difference exceeds the threshold, it can be determined that the single cell with the largest voltage difference has abnormal self-discharge. Or, when the difference or ratio between the largest voltage difference and the normal or average voltage difference exceeds the threshold, it can be determined that the single cell with the largest voltage difference has abnormal self-discharge. The average voltage difference can be the mean of a set of voltage differences 240 of all single cells.

[0028] According to another aspect of the present disclosure, when it is determined that the time interval between the current balance state data and adjacent balance state data (e.g., the battery operation data 230 and 220 shown in Figure 3 ) does not meet the time threshold, it is determined whether the time interval between the current balance state data and the balance state data of the previous one (e.g., the battery operation data 210) meets the time threshold. And when this time interval meets the time threshold, perform the similar operations described with reference to Figure 2 .

[0029] According to one or more aspects of the present disclosure, multiple sets of voltage differences (e.g., with two balance state data as a set) between multiple sets of balance state data can be calculated. By comprehensively considering the multiple sets of voltage differences, the noise existing in the sampled data can be effectively excluded to further improve the measurement accuracy.

[0030] Figure 4 is a schematic diagram showing a method for detecting self-discharge consistency using battery operation data according to one or more aspects of the present disclosure. The voltage difference for each single cell between any two of the battery operation data 210, 220, and 230 can be calculated. For example, the voltage difference for each single cell between the battery operation data 210 and 220 and between the battery operation data 220 and 230 can be calculated to obtain two sets of voltage differences 240-1 and 240-2. When a certain single cell has a maximum voltage difference exceeding the threshold only in one set of voltage differences, due to the influence of noise fluctuations in the sampled data, it may not be sufficient to prove that the single cell has abnormal self-discharge. However, when the single cell has a maximum voltage difference exceeding the threshold in both sets of voltage differences, the probability of abnormal self-discharge of the single cell is greatly increased.

[0031] It should be clear that Figure 4 is only an example provided for clear description. Without departing from the inventive spirit of the present disclosure, the present disclosure may also include other examples. For example, calculate the voltage difference for each single cell between more sets (e.g., more than two sets, or continuously calculate in time) of battery operation data. When the voltage difference of a certain single cell (or the difference or ratio between its voltage difference and the average voltage difference) exceeds the threshold for a threshold number of times, it is determined that the single cell has abnormal self-discharge.

[0032] Figure 5 is a flowchart showing a method 500 for detecting the self-discharge condition of a battery pack according to one or more aspects of the present disclosure. The method 500 can be executed at a device (e.g., an electric vehicle) equipped with the battery pack, or the method 500 can be executed at a remote server.

[0033] In step 510, battery operation data can be obtained. The battery operation data can include the identifiers (cell IDs) of each or at least some of the individual battery cells, a timestamp, and the voltages of each or at least some of the individual battery cells. For example, the battery operation data can be obtained from a battery management system (BMC) in the battery pack (e.g., the BMC 720 shown in Figure 7 ).

[0034] In step 520, based on the battery operation data, a set of time points when the battery pack is in a balanced state can be determined. For example, the battery operation data can be sorted according to the collection time sequence (e.g., the timestamp), and it can be determined that the current timestamp corresponds to a time point when the battery pack is in a balanced state based on the difference between the current timestamp and the previous adjacent timestamp being greater than a timestamp threshold (e.g., 3 to 6 hours). Alternatively, the battery operation data can also include other information (e.g., vehicle status) to indicate the time points when the battery pack is in a balanced state.

[0035] In step 530, based on the battery operation data, information related to the voltage differences between the individual battery cells in the battery pack at the time points in this set can be obtained. For example, step 530 can be performed according to the content described with reference to Figure 2 , 3 or 4. In other examples, the self-discharge characteristic value can be calculated according to the following formula:

[0036] Self-discharge characteristic value = (maximum voltage difference - normal voltage difference) / time interval where the maximum voltage difference refers to the maximum voltage difference between two time points that satisfy a time threshold (e.g., 30 hours) among all the time points determined in step 520 for all the individual battery cells, the normal voltage difference can be equal to the average value of all the corresponding voltage differences of all the individual battery cells between these two time points, and the time interval can be the time difference between these two time points.

[0037] According to one aspect of the present disclosure, the information can include the self-discharge characteristic value and the identifier of the individual battery cell having the maximum voltage difference. According to other aspects of the present disclosure, the information can include the maximum voltage difference described with reference to Figure 2 , 3 or 4, the difference or ratio between the maximum voltage difference and the normal or average voltage difference, and the identifier of the individual battery cell having the maximum voltage difference. The normal voltage difference can be based on empirical values or experimental data, etc.

[0038] In step 540, based on this information, it can be determined whether the self-discharge conditions of the individual battery cells in the battery pack are consistent. For example, step 540 can be performed according to the content described with reference to Figure 2 , 3 or 4. In other examples, reference can be made to Figure 6Step 540 is performed, where the self-discharge eigenvalue 602 is arranged in ascending order according to the corresponding timestamp 601. When the self-discharge eigenvalue 602 is greater than a threshold value (for example, 0.5 mV / h or 0.8 mV / h), it is counted once in the label 603 column (for example, it can be set to "1"), otherwise it is not counted (for example, it can be set to "0"). For a predetermined time period (for example, it can be in windows 1, 2, and 3), the cumulative value 605 of the number of times the self-discharge eigenvalue of the single cell exceeds the threshold value is obtained. For example, in window 1 610, the number of times the self-discharge eigenvalue of the single cell 33 (indicated by the single cell identifier 604, for example) exceeds the threshold value is 1. In window 2 620, the number of times the self-discharge eigenvalue of the single cell 33 exceeds the threshold value is 2. In window 3 630, the number of times the self-discharge eigenvalue of the single cell 33 exceeds the threshold value is 3. It can be determined that the self-discharge of the corresponding single cell (for example, single cell 33) is abnormal based on the number of times the self-discharge eigenvalue exceeds the threshold number of times (for example, 2 or 3).

[0039] According to one aspect of the present disclosure, the predetermined time period can be set according to the characteristics of the measured battery pack (for example, corresponding to 5 to dozens of self-discharge eigenvalues), so as to take into account the battery characteristics while taking into account the timeliness requirements. For example, some types of battery packs may require a long standing time to reach a balanced state (for example, resulting in a small number of self-discharge eigenvalues obtained within a given time period), so a shorter predetermined time period (for example, 5) can be set to judge the self-discharge consistency of the battery pack in a timely manner. In addition, the predetermined time period can be set according to the usage of the battery pack. For example, the degree of use and usage habits of the driver for the electric vehicle.

[0040] Figure 7 is a schematic diagram showing an example of a battery pack 700 according to one or more aspects of the present disclosure. The battery pack 700 can be equipped in an electric vehicle (for example, a hybrid electric vehicle (HEV), a battery electric vehicle (BEV), a non-plug-in hybrid vehicle, a plug-in hybrid vehicle (PHEV), an extended-range electric vehicle, etc.), or other devices. The battery pack 700 can include a plurality of battery modules 710-1, 710-2, and 710-3, and each battery module can include a plurality of single cells 711. The battery pack 700 can also include a battery management system (BMS) 720, which can be configured to collect or gather the battery operation data of the battery pack 700. It can be based on the reference Figure 2 、 3, 4 and 5 are used to detect the self-discharge consistency of the battery pack 700. The detection result may include a self-discharge warning sign for a battery pack with abnormal self-discharge problems. In addition, the detection result may also include a battery identifier (ID), a single cell identifier (cell ID), a timestamp, mileage, and a self-discharge characteristic value. The self-discharge warning sign can be presented to the user through a display system on the car, or an alarm can be given in other ways.

[0041] Figure 8 FIG. 8 is a diagram showing an example of a hardware implementation of an apparatus 800 for detecting self-discharge consistency of a battery pack according to one or more aspects of the present disclosure. The apparatus 800 for detecting self-discharge consistency of a battery pack may include a memory 810 and at least one processor 820. The processor 820 may be coupled to the memory 810 and configured to execute the above-mentioned reference Figure 2 , Figure 3 , Figure 4 and Figure 5 The processor 820 may be a general-purpose processor, or may be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors combined with a DSP core, or other such structures. The memory 810 may store data generated or processed by the processor 820 (e.g., battery operation data, self-discharge characteristic values, threshold values, etc.) and / or instructions executed by the processor 820.

[0042] In one example, a set of time points at which the battery pack is in a substantially balanced state after being left at rest for a sufficiently long time can be obtained, and the battery operation data corresponding to the set of time points can be used to calculate a characteristic value associated with the maximum voltage difference in the battery pack (e.g., between the current time point and the previous time point) for each time point. Based on the statistical characteristics of the characteristic value for each time point, it is determined whether the self-discharge rate of the single cell in the battery pack is abnormal. The statistical characteristics may include accumulation or average, etc.

[0043] In one example, the two time points used to calculate the characteristic value associated with the maximum voltage difference need to be separated by a sufficiently long time (e.g., 6 hours to several days). In another example, the characteristic value can be calculated between any two time points in a set of time points when the battery pack is in a balanced state, and based on the statistical characteristics of these characteristic values, it is determined whether the self-discharge rate of the single cells in the battery pack is abnormal.

[0044] The foregoing description of the present disclosure is provided to enable those skilled in the art to make use of or implement the various embodiments. Various modifications to the above embodiments will be apparent to those skilled in the art, and the basic principles defined herein can be applied to other embodiments without departing from the scope of the present disclosure. Thus, the scope of the claims is not intended to be limited to the embodiments disclosed herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for detecting the self-discharge condition of a battery pack, comprising: obtaining battery operation data, wherein the battery operation data includes voltage data for at least some of the individual battery cells within the battery pack; determining, based on the battery operation data, a set of time points at which the battery pack is in an equilibrium state; obtaining, based on the battery operation data, information related to the voltage differences between the time points within the set of time points for the individual battery cells within the battery pack; and determining, based on the information, whether the self-discharge conditions of the individual battery cells within the battery pack are consistent.

2. The method according to claim 1, wherein, the information includes: a self-discharge characteristic value associated with the maximum voltage difference among all the voltage differences between two time points within the set of time points for all the individual battery cells within the battery pack, wherein the time interval between the two time points is equal to or exceeds a time threshold; and an identifier of the individual battery cell having the maximum voltage difference.

3. The method according to claim 2, further comprising: obtaining, based on another two time points within the set of time points, another self-discharge characteristic value for the individual battery cell having the maximum voltage difference.

4. The method according to claim 3, wherein, determining, based on the information, whether the self-discharge conditions of the individual battery cells within the battery pack are consistent further includes: responsive to a plurality of self-discharge characteristic values for the individual battery cell having the maximum voltage difference exceeding a threshold by a threshold number of times, determining that the self-discharge condition of the individual battery cell having the maximum voltage difference is abnormal.

5. The method according to claim 4, wherein, the plurality of self-discharge characteristic values for the individual battery cell having the maximum voltage difference are determined to be abnormal in terms of self-discharge condition by exceeding the threshold by the threshold number of times within a predetermined time period.

6. The method according to claim 5, wherein, the predetermined time period is set based on at least one of the characteristics of the battery pack or the usage conditions of the battery pack.

7. The method according to claim 1, wherein, the battery operation data is obtained through a battery management system (BMS), and the battery operation data further includes at least one of the following: an identifier (cellID) of each individual battery cell, a timestamp, a mileage, a vehicle state, or a current.

8. A device for detecting the self-discharge condition of a battery pack, comprising: a memory; and one or more processors coupled to the memory, the one or more processors being configured to perform the following operations: obtaining battery operation data, wherein the battery operation data includes voltage data for at least some of the individual battery cells within the battery pack; determining, based on the battery operation data, a set of time points at which the battery pack is in an equilibrium state; obtaining, based on the battery operation data, information related to the voltage differences between the time points within the set of time points for the individual battery cells within the battery pack; and determining, based on the information, whether the self-discharge conditions of the individual battery cells within the battery pack are consistent.

9. The device according to claim 8, wherein, the information includes: A self-discharge characteristic value associated with the maximum voltage difference among all voltage differences between two time points within a set of time points for all individual battery cells within the battery pack, wherein a time interval between the two time points is equal to or exceeds a time threshold; and An identifier of the individual battery cell having the maximum voltage difference.

10. The apparatus according to claim 9, wherein, The one or more processors are further configured to: Obtain another self-discharge characteristic value for the individual battery cell having the maximum voltage difference based on another two time points within the set of time points.

11. The apparatus according to claim 10, wherein, In order to determine whether the self-discharge conditions of the individual battery cells within the battery pack are consistent based on the information, the one or more processors are configured to: Determine that the self-discharge condition of the individual battery cell having the maximum voltage difference is abnormal in response to a plurality of self-discharge characteristic values for the individual battery cell having the maximum voltage difference exceeding a threshold for a threshold number of times.

12. The apparatus according to claim 11, wherein, The plurality of self-discharge characteristic values of the individual battery cell having the maximum voltage difference are determined to be abnormal in terms of self-discharge condition by exceeding the threshold for a threshold number of times within a predetermined time period.

13. The apparatus according to claim 12, wherein, The predetermined time period is set based on at least one of the characteristics of the battery pack or the usage conditions for the battery pack.

14. The apparatus according to claim 8, wherein, The battery operation data is obtained through a battery management system (BMS), and the battery operation data further includes at least one of the following: an identifier (cellID) of each individual battery cell, a timestamp, a mileage, a vehicle state, or a current.

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