Battery abnormality detection system, battery abnormality detection method, battery abnormality detection program, and recording medium on which battery abnormality detection program is recorded

Abstract

The data processing unit calculates, in time series, a voltage difference between a reference voltage and a minimum voltage of a plurality of unit cells or unit cell blocks connected in series included in an assembled battery. When the expansion rate of the voltage difference is equal to or greater than a threshold value, the determination unit determines that a minute short circuit has occurred in the unit cell or the unit cell block having the minimum voltage. The data processing unit calculates the expansion rate of the voltage difference using voltage data during a period in which the state of charge (SOC) of the assembled battery is within a predetermined SOC range.

Description

Technical Field

[0001] The present disclosure relates to a battery abnormality detection system, a battery abnormality detection method, and a battery abnormality detection program for detecting an abnormal state of a battery. Background Art

[0002] In secondary battery cells such as lithium-ion batteries, micro short circuits can sometimes occur due to contact between the positive and negative electrodes caused by separator displacement, or due to the formation of conductive paths caused by foreign matter entering the battery. Micro short circuits can cause overheating, and can also cause a micro short circuit to become a full short circuit due to changes in the orientation of foreign matter.

[0003] Battery packs, often used in applications such as electric vehicles, often consist of multiple battery blocks connected in series. In particular, EVs equipped with large motors tend to have a higher number of battery blocks connected in series. In such battery packs, there is a method for detecting a micro-short circuit in the battery pack by detecting the increasing difference between the maximum and minimum battery block voltages across the multiple battery blocks.

[0004] However, in this method, when there are relatively large differences in SOC (State of Charge) and SOH (State of Health) between the single battery blocks, the voltage difference fluctuates greatly according to the SOC change. Therefore, it is difficult to distinguish the voltage difference caused by the SOC change from the voltage difference caused by a small short circuit, which can easily lead to false detection.

[0005] The applicant of the present application previously disclosed in Patent Document 1 a method for detecting micro-short circuits within a battery pack. This method uses a linear function as a tangent to a specific location on the SOC-OCV curve of a single cell. The cell voltage is input to this linear function to derive a normalized cell voltage, thereby reducing the impact of the SOC range on the cell voltage. In the SOC-OCV curve, the OCV drops sharply in the low SOC range. Therefore, even small capacity fluctuations between cell blocks in this low SOC range can cause significant voltage fluctuations. Using a linear function corresponding to the SOC-OCV curve eliminates differences in the sensitivity of voltage changes due to the SOC range.

[0006] This method assumes the existence of a high-quality SOC-OCV curve for a single battery cell and cannot be used if the SOC-OCV curve is unknown. Furthermore, if the SOC-OCV curve significantly changes from its initial state due to degradation, detection accuracy decreases.

[0007] Prior art literature

[0008] Patent Literature

[0009] Patent Document 1: International Publication No. 20 / 021888 Summary of the Invention

[0010] The present disclosure has been made in view of such circumstances, and an object of the present disclosure is to provide a technology for accurately detecting micro short circuits in a battery pack including a plurality of battery cells or battery blocks connected in series.

[0011] To address the aforementioned issues, a battery abnormality detection system according to one embodiment of the present disclosure includes: a data acquisition unit that acquires time-series data of a plurality of voltages and the SOC of a battery pack, the plurality of voltages including the minimum voltage of a plurality of cells connected in series within the battery pack, or at least the minimum voltage of a plurality of cell blocks connected in series within the battery pack, each cell of the plurality of cell blocks comprising a plurality of cells; a data processing unit that calculates the voltage difference between the minimum voltage of the plurality of cells or cell blocks and a reference voltage in a time-series manner; and a determination unit that determines that a micro-short has occurred in the cell or cell block with the minimum voltage when the expansion rate of the voltage difference is greater than a threshold value. The data processing unit calculates the expansion rate of the voltage difference using voltage data collected during a period when the SOC of the battery pack is within a predetermined SOC range.

[0012] Furthermore, arbitrary combinations of the above-described constituent elements and forms in which the expressions of the present disclosure are converted between devices, systems, methods, computer programs, recording media, and the like may also be additional forms of the present disclosure.

[0013] According to the present disclosure, it is possible to detect a micro short circuit in a battery pack including a plurality of battery cells or battery blocks connected in series with high accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a diagram for explaining a battery abnormality detection system according to an embodiment.

[0015] Figure 2A 1 is a diagram showing the configuration of a battery pack system including a plurality of unit cells connected in series.

[0016] Figure 2B 1 is a diagram showing the configuration of a battery pack system including a plurality of battery blocks connected in series.

[0017] Figure 3A Graphs showing transitions in cell voltage and voltage difference in a battery pack where a micro short circuit has occurred.

[0018] Figure 3BThis is a diagram showing the transition of the cell voltage and the voltage difference of a battery pack in which a large SOC difference occurs.

[0019] Figure 3C This is a diagram showing the transition of the cell voltage and the voltage difference of a battery pack in which a large SOH difference occurs.

[0020] Figure 4 This diagram shows a method of generating a linear straight line that approximates the SOC-OCV curve of a certain cell and normalizing the cell voltage.

[0021] Figure 5 Is shown using Figure 4 A straight line will Figure 3B The graph shown is a graph showing changes in the voltage and voltage difference between a medium SOC cell and a low SOC cell when the voltages are normalized.

[0022] Figure 6 This is a diagram showing an example of a statistical table of the number of sampling data for each SOC range.

[0023] Figure 7A This diagram shows how the SOC range to be used is selected based on the maximum cell voltage, the minimum cell voltage, and the transition of the voltage difference therebetween.

[0024] Figure 7B This is a graph in which voltage data for SOC ranges other than the used SOC range is deleted.

[0025] Figure 7C This is a graph obtained by linearly interpolating the interval where the voltage data was deleted.

[0026] Figure 8 This is a flowchart showing an operation example 1 of the battery abnormality detection system according to the embodiment.

[0027] Figure 9 This is a flowchart showing a second operation example of the battery abnormality detection system according to the embodiment. DETAILED DESCRIPTION

[0028] Figure 1 1 is a diagram for explaining a battery abnormality detection system 10 according to an embodiment. The battery abnormality detection system 10 is a system for detecting whether a micro short circuit has occurred in a single cell in a battery pack mounted on an electric vehicle 20 .

[0029] The battery anomaly detection system 10 can be built, for example, on an in-house server installed at a company's own facility or data center that provides analysis services for battery packs installed in electric vehicles 20. Alternatively, the battery anomaly detection system 10 can be built on a cloud server utilized via a cloud service. Furthermore, the battery anomaly detection system 10 can be built on multiple servers distributed across multiple locations (data centers, in-house facilities). These multiple servers can also be a combination of multiple in-house servers, a combination of multiple cloud servers, or a combination of in-house servers and cloud servers.

[0030] The assembled battery system 21 included in the battery pack mounted on the electric vehicle 20 supplies electric power to a driving motor (not shown). The assembled battery system 21 includes a plurality of battery cells or a plurality of cell blocks connected in series.

[0031] Figure 2A 1 is a diagram showing the configuration of a battery pack system including a plurality of cells E1 to Em connected in series. Figure 2B 1 is a diagram showing the configuration of a battery pack system including a plurality of cell blocks Eb1 to Ebm connected in series. Each cell block Eb1 to Ebm includes a plurality of cells E1a to E1n - Ema to Emn connected in parallel.

[0032] Cells can be lithium-ion batteries, nickel-metal hydride batteries, lead-acid batteries, and other types of batteries. This manual assumes the use of lithium-ion batteries (nominal voltage: 3.6V-3.7V). The number of cells or battery blocks connected in series is determined by the voltage of the drive motor.

[0033] The voltage sensor 22 detects the voltage across each of the multiple cells or battery blocks connected in series. The multiple cells or battery blocks connected in series are connected in series with a shunt resistor. The current sensor 23 detects the current flowing through the series-connected cells or battery blocks based on the voltage across the shunt resistor. Alternatively, a Hall effect element may be used in place of the shunt resistor. Multiple temperature sensors 24 are provided within the battery pack including the battery pack system 21. For example, a thermistor can be used as the temperature sensor 24.

[0034] The control unit 25 is composed of a BMU (Battery Management Unit) and an ECU (Electronic Control Unit) working together. The BMU estimates the SOC using a combination of the OCV (Open Circuit Voltage) method and the current integration method. The OCV method estimates the SOC based on the measured OCV of a single cell and the SOC-OCV curve of the single cell. The SOC-OCV curve of the single cell is pre-created based on characteristic tests conducted by the battery manufacturer and is registered in the BMU at the time of shipment.

[0035] The current integration method estimates the SOC based on the OCV of a single cell at the start of charge or discharge and the cumulative value of the measured current. With the current integration method, current measurement errors accumulate as charge or discharge time increases. Therefore, it is preferable to use a weighted average of the SOC estimated using the current integration method and the SOC estimated using the OCV method.

[0036] The BMU periodically transmits battery data (e.g., every 10 seconds) to the ECU via the in-vehicle network, including the voltage, current, temperature, and SOC of the multiple cells or battery blocks that make up the assembled battery system 21. The ECU then samples the battery data in a time-series manner. Examples of in-vehicle networks include CAN (Controller Area Network) and LIN (Local Interconnect Network).

[0037] The communication unit 26 has the function of performing communication signal processing with the communication unit 33 of the charging station 30, and the function of performing wireless signal processing for connecting to the network 5. The communication unit 26 can access the network 5 using, for example, a mobile phone network (cellular network), a wireless LAN, V2I (Vehicle to Infrastructure), V2V (Vehicle to Vehicle), an ETC system (Electronic Toll Collection System), or DSRC (Dedicated Short Range Communications).

[0038] Network 5 is a general term for communication paths such as the Internet, dedicated lines, and VPNs (Virtual Private Networks). The communication medium and protocol are not limited. Examples of communication media include mobile phone networks, wireless LANs, wired LANs, fiber optic networks, ADSL networks, and CATV networks. Examples of communication protocols include TCP (Transmission Control Protocol) / IP (Internet Protocol), UDP (User Datagram Protocol) / IP, and Ethernet (registered trademark).

[0039] The ECU can transmit the battery data received from the BMU to the battery abnormality detection system 10 individually, or it can store the battery data received from the BMU in an internal memory and, at a predetermined timing, transmit the battery data stored in the memory to the battery abnormality detection system 10 in a batch. Furthermore, when the electric vehicle 20 and the charging station 30 are connected via a charging cable, the ECU can also transmit the battery data stored in the memory to the battery abnormality detection system 10 via the charging station 30.

[0040] The ECU can transmit all or part of the battery data received from the BMU to the battery abnormality detection system 10. For example, the ECU can transmit the maximum and minimum voltages of the multiple cells or battery blocks comprising the assembled battery system 21 as battery pack voltage data to reduce the data volume. Similarly, the ECU can transmit the maximum and minimum temperatures measured at multiple observation locations within the battery pack as battery pack temperature data.

[0041] Alternatively, the ECU may estimate the SOC of the battery pack based on the SOCs of the multiple cells or battery blocks that comprise the assembled battery system 21, with only the SOC of the battery pack being the target for transmission. For example, the ECU may convert the SOCs of the multiple cells or battery blocks into actual capacities, combine these actual capacities to calculate the actual capacity of the battery pack, and estimate the SOC of the battery pack based on this actual capacity and the current full charge capacity of the battery pack.

[0042] By connecting the electric vehicle 20 to the charging station 30 using a charging cable, the assembled battery system 21 in the electric vehicle 20 can be charged from the outside. The charging station 30 is connected to the commercial power system 2 to charge the assembled battery system 21 .

[0043] Generally speaking, in the case of normal charging, charging is performed with AC, and in the case of fast charging, charging is performed with DC. When charging with AC (for example, single-phase 100 / 200V), the charging voltage or charging current is controlled by a charger (not shown) in the electric vehicle 20. When charging with DC, the charging voltage or charging current is controlled by the power supply unit 31 of the charging pile 30. The power supply unit 31 includes a rectifier circuit, a filter, and a DC / DC converter. The AC power supplied from the commercial power system 2 is full-wave rectified by the rectifier circuit and smoothed by the filter, thereby generating DC power. The DC / DC converter controls the voltage or current of the generated DC power.

[0044] Examples of fast charging standards include CHAdeMO (registered trademark), ChaoJi, GB / T, and Combo (Combined Charging System). CHAdeMO, ChaoJi, and GB / T use CAN as the communication method, while Combo uses PLC (Power Line Communication).

[0045] A charging cable using the CAN method includes not only power lines but also communication lines. When the electric vehicle 20 is connected to the charging station 30 via this charging cable, the control unit 25 of the electric vehicle 20 establishes a communication channel with the control unit 32 of the charging station 30. Furthermore, in a charging cable using the PLC method, communication signals are superimposed on the power lines for transmission.

[0046] The communication unit 33 of the charging station 30 has functions for processing communication signals with the communication unit 26 of the electric vehicle 20 and for processing signals for connecting to the network 5. The communication unit 33 can access the network 5 using, for example, a wired LAN, a wireless LAN, or a mobile phone network.

[0047] The battery abnormality detection system 10 includes a control unit 11, a storage unit 12, and a communication unit 13. The communication unit 13 is a communication interface (for example, a NIC: Network Interface Card) for connecting to the network 5 by wire or wirelessly.

[0048] The control unit 11 includes a data acquisition unit 111, a data processing unit 112, and a determination unit 113. The functions of the control unit 11 can be implemented through the collaboration of hardware and software resources, or solely through hardware resources. Hardware resources include a CPU, ROM, RAM, a GPU (Graphics Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), and other LSIs. Software resources include programs such as an operating system and application programs.

[0049] The storage unit 12 includes a non-volatile recording medium such as an HDD and an SSD, which is used to store various data. The storage unit 12 includes a battery data holding unit 121. The data acquisition unit 111 acquires battery data from the electric vehicle 20 or the charging pile 30, and accumulates the acquired battery data in the battery data holding unit 121. In this embodiment, the battery data includes the maximum voltage and minimum voltage of multiple single cells or single cell blocks in the battery pack, the maximum temperature and minimum temperature at multiple observation positions in the battery pack, the current flowing through the battery pack, and the SOC of the battery pack. The program can be pre-recorded in the storage unit 12 here, but it can also be provided through electronic communication lines such as the Internet or in the form of (non-transitory) recording media such as a memory card.

[0050] The data processing unit 112 reads out the time series data of the battery data of the battery pack to be inspected from the battery data storage unit 121. For example, the data processing unit 112 reads out the battery data for one month, which is the analysis target period.

[0051] As a basic process for micro-short circuit detection, data processing unit 112 calculates the voltage difference between the maximum and minimum voltages of multiple cells or cell blocks in a time series. If the rate of increase in this voltage difference exceeds a threshold, determination unit 113 determines that a micro-short circuit has occurred in the cell or cell block with the minimum voltage. This basic process reduces detection accuracy when there are differences in SOC or SOH between multiple cells or cell blocks.

[0052] Figure 3A Graphs showing transitions in cell voltage and voltage difference in a battery pack where a micro short circuit has occurred. Figure 3B This is a diagram showing the transition of the cell voltage and the voltage difference in a battery pack having a large SOC difference. Figure 3C This is a diagram showing the transition of the cell voltage and the voltage difference of a battery pack in which a large SOH difference occurs.

[0053] A single cell with a slight short circuit consumes a small amount of power. Figure 3A As shown in FIG, the voltage difference between the voltage of the short-circuited single cell and the voltage of the normal single cell gradually increases. Figure 3B As shown in FIG. 1 , the voltage of a single cell with a low SOC drops more sharply than the voltage of a single cell with a medium SOC. Figure 4 The SOC-OCV curve shows a sharp drop in the OCV of cells below 15% in the SOC range. For example, if cells with an SOC of 15% or higher are mixed with cells with an SOC of less than 15%, the voltage difference between the two cells will increase even without a micro short circuit.

[0054] like Figure 3C As shown, the voltage of cells with low SOH fluctuates at a higher rate than that of cells with high SOH. Because cells with low SOH have a smaller capacity, small current changes can cause large voltage fluctuations. Consequently, when cells with low SOH and cells with high SOH are mixed, even without a micro-short circuit, there will be periods where the voltage difference between the two cells increases or decreases.

[0055] Figure 4 This diagram shows a method of generating a linear line approximating the SOC-OCV curve of a certain single cell to normalize the cell voltage. Figure 3B In the battery pack with a large SOC difference shown above, the problem of decreased accuracy due to a micro short circuit can be eliminated.

[0056] Figure 5 Is shown using Figure 4 A straight line will Figure 3B The graph shows the transition of the voltage and voltage difference of a medium SOC cell and a low SOC cell when the voltages are normalized. Figure 5 In the example shown, it is possible to suppress the increase in the voltage difference and prevent the erroneous detection of the occurrence of a micro short circuit even though no micro short circuit has occurred.

[0057] However, this method requires that the individual cells included in the battery pack being inspected have high-quality SOC-OCV curves. If the SOC-OCV curves of the individual cells are unknown, this method cannot be used. Furthermore, if the SOC-OCV curves of the individual cells have significantly changed from their initial state due to degradation, the accuracy of detecting micro-shorts decreases.

[0058] In addition, this method is effective for battery packs with relatively low capacity and can detect the expansion of the voltage difference between single cells caused by small short circuits at an early stage, but it is not suitable for battery packs with large capacity and cannot detect the expansion of the voltage difference between single cells caused by small short circuits without multiple charge and discharge cycles.

[0059] Furthermore, this method cannot reduce the impact of inter-cell SOH differences. Furthermore, if the current SOH of each cell is known, inter-cell SOH differences can be corrected. However, while knowing the SOH of the entire battery pack is common, knowing the SOH of each cell in the pack is rare.

[0060] In this embodiment, only the voltage data of the SOC range in which the voltage behavior is stable is used to determine whether there is a micro short circuit, thereby improving the detection accuracy of the micro short circuit. The data processing unit 112 takes the sampling data of the time series included in the analysis object period as the object, and counts the number of sampling data for each SOC range. The SOC range is set to a fixed width (for example, 20%). If the unit width of the SOC range is too narrow, it is difficult to ensure the number of sampling data. If the unit width of the SOC range is too wide, the possibility of mixing in unstable voltage data becomes high. The designer can determine the width of the SOC range based on multiple sampling data of the battery data.

[0061] Figure 6 FIG is a diagram showing an example of a statistical table of the number of sampling data for each SOC range. Figure 6 In the example shown, nine sub-areas are provided as multiple SOC ranges: 100-80%, 90-70%, 80-60%, 70-50%, 60-40%, 50-30%, 40-20%, 30-10%, and 20-0%. Thus, the SOC range of each sub-area includes areas that overlap with the SOC ranges of preceding and following sub-areas. This allows for selection of an appropriate SOC range even when voltage data is concentrated near the boundaries of a simple SOC segment.

[0062] The data processing unit 112 selects the SOC range with the most SOC sampling data during the analysis period from among the multiple SOC ranges as the SOC range used for micro-short circuit detection (hereinafter referred to as the use SOC range). Generally, users often charge the battery pack to full charge and leave it in the electric vehicle 20 until it is used. Therefore, the use SOC range is generally selected from 100% to 80%.

[0063] The data processing unit 112 deletes the voltage data of the interval where the SOC of the battery pack exists in an SOC range other than the used SOC range, and linearly interpolates the voltage data of the deleted interval based on the preceding and following voltage data.

[0064] Figure 7A This diagram shows how the SOC range to be used is selected based on the maximum cell voltage, the minimum cell voltage, and the transition of the voltage difference therebetween. Figure 7B This is a graph in which voltage data for SOC ranges other than the used SOC range is deleted. Figure 7C This is a graph obtained by linearly interpolating the interval where voltage data was deleted.

[0065] exist Figure 7A In the example, the interval surrounded by the dotted line indicates that the SOC of the battery pack exists in the interval of the use SOC range. The change of the voltage data in the interval outside the use SOC range is more intense than the change of the voltage data in the interval of the use SOC range. Figure 7B Delete as shown.

[0066] Data processing unit 112 estimates voltage data at each time point in the deletion interval by performing linear interpolation based on the last voltage data of the used SOC range immediately before the deletion interval and the voltage data at the beginning of the used SOC range immediately after the deletion interval. The estimated voltage data is then interpolated into the deletion interval. If there is no section in the used SOC range before or after the deletion interval, data processing unit 112 may interpolate the voltage data for the deletion interval using linear extrapolation. Alternatively, an interpolation method using a polynomial, such as spline interpolation, may be used.

[0067] Figure 8 This is a flowchart illustrating an operation example 1 of the battery abnormality detection system 10 according to the embodiment. The data processing unit 112 reads the maximum and minimum voltages of a plurality of cells or cell blocks, and the SOC of the battery pack from the battery data storage unit 121 as time series data during the analysis target period of the battery pack to be inspected (S10).

[0068] The data processing unit 112 targets the time-series sampling data included in the analysis target period, confirms the SOC at each sampling time, and counts the number of sampling data for each SOC range (S11). The data processing unit 112 selects the SOC range with the largest number of sampling data as the working SOC range (S12).

[0069] The data processing unit 112 deletes the voltage data for the interval where the battery pack's SOC falls within an SOC range other than the operating SOC range (S13). The data processing unit 112 performs linear interpolation on the voltage data for the deleted interval based on the preceding and following voltage data (S14). The data processing unit 112 calculates the voltage difference between the maximum voltage and the minimum voltage at each sampling time during the analysis target period (S15). At this time, the data processing unit 112 may refer to the cell number of the minimum voltage at each sampling time and calculate only the voltage difference between the minimum voltage of the cell or cell block with the largest cell number and the maximum voltage at the corresponding sampling time. The data processing unit 112 performs linear regression on the voltage differences at multiple sampling times included in the analysis target period to generate a regression line (S16).

[0070] If the slope of the generated regression line is greater than the threshold value ("YES" in S17), the determination unit 113 determines that a micro short circuit has occurred in the cell or cell block with the minimum voltage (S18). If the slope of the regression line is less than the threshold value ("NO" in S17), the determination unit 113 determines that a micro short circuit has not occurred in the cell or cell block with the minimum voltage.

[0071] The analysis period and threshold are determined based on the battery pack's capacity and the short-circuit resistance that determines a minor short circuit. For example, if a 200Ω minor short circuit occurs in a 140Ah battery pack, a voltage difference of approximately 3mV will occur between a normal single cell and the minor short circuit single cell within a day. This voltage difference is difficult to distinguish from voltage differences caused by measurement errors, temperature, and other factors. Therefore, it is desirable to set the analysis period for a 140Ah battery pack to approximately 14 to 30 days. This allows for a shorter analysis period when the battery pack's capacity is small, while a longer analysis period is necessary when the battery pack's capacity is large.

[0072] In the above description, the SOC range with the most recorded sample data among multiple SOC ranges is defined as the active SOC range. This does not necessarily mean that the SOC range with the most recorded sample data is the same as the SOC range with the most stable voltage. For example, in operations where the frequency of full-charge charging is low, a medium SOC range is likely to be selected.

[0073] Basically, there's a tendency for voltage data accuracy to be higher in shallow depths of discharge. In deep depths of discharge, the impact of changes in internal resistance associated with temperature changes becomes greater. If a medium SOC range is selected, the accuracy of voltage and SOC data may be low.

[0074] In Example 2, the data processing unit 112 selects, from among multiple SOC ranges, the SOC range with the longest total of pause periods during which charging and discharging are stopped during the analysis target period as the active SOC range. The pause period is assumed to be a period during which the current data is zero. Furthermore, there are battery packs in which the battery management unit (BMU) enters a standby state when the current value measured by the current sensor 23 is zero for a certain period. When the BMU is in the standby state, battery data is essentially missing. This missing period may be treated as a pause period, or, considering the possibility of missing data due to reasons other than the BMU's standby state (e.g., data loss during transmission), it may not be treated as a pause period. Alternatively, a missing period may be treated as a pause period only when the current data before and after the missing period is zero.

[0075] Figure 9 This is a flowchart illustrating a second example of the operation of the battery abnormality detection system 10 according to the embodiment. The data processing unit 112 reads the maximum and minimum voltages of a plurality of cells or cell blocks, the current of the battery pack, and the SOC of the battery pack from the battery data storage unit 121 as time series data during the analysis target period of the battery pack to be inspected (S10a).

[0076] The data processing unit 112 takes the time series sampling data included in the analysis target period as the target, confirms the current at each sampling time, and counts the rest period for each SOC range (S11a). The data processing unit 112 selects the SOC range with the longest rest period as the use SOC range (S12a). The processing after step S13 is the same as Figure 8 The processing after step S13 shown in the flowchart is the same.

[0077] Alternatively, to select an SOC range where voltage data is stable, the data processing unit 112 may calculate the standard deviation of the voltage data included in each SOC range and select the SOC range with the smallest standard deviation as the active SOC range. In this case, to ensure the number of sampled data, the data processing unit 112 may select the SOC range with the smallest standard deviation of the voltage data as the active SOC range, among SOC ranges where the number of sampled data is greater than or equal to a predetermined value.

[0078] As described above, according to this embodiment, the expansion rate of the voltage difference between the maximum and minimum voltages is calculated using voltage data from the battery pack during periods when the SOC is within the operating SOC range. If the expansion rate exceeds a threshold, a micro short circuit is determined to have occurred. This allows for highly accurate detection of micro short circuits in the battery pack. By using voltage data within the SOC range, where the voltage is stable, the effects of SOC variations on the voltage difference can be suppressed. Even when large SOC or SOH differences exist between multiple cells or cell blocks, the presence of a micro short circuit can be accurately determined. Furthermore, since the SOC-OCV curves of individual cells are not required, the range of battery packs that can be inspected can be expanded.

[0079] The present disclosure has been described above based on the embodiments. The embodiments are merely illustrative, and those skilled in the art will appreciate that various modifications can be made to the combinations of these components and processing steps, and that such modifications are also within the scope of the present disclosure.

[0080] In the above embodiment, the data processing unit 112 calculates the voltage difference between the maximum voltage and the minimum voltage of multiple battery cells or battery blocks connected in series. In this regard, the maximum voltage is an example of a reference voltage used to calculate the difference from the minimum voltage. For example, the data processing unit 112 may use the median or average value of the voltages of the multiple battery cells or battery blocks as a reference voltage instead of the maximum voltage. When calculating the median or average value of multiple voltages, the data processing unit 112 may calculate the median or average value in addition to the maximum and minimum voltages. Furthermore, the median or average value may be generated on the BMU side and transmitted to the battery abnormality detection system 10.

[0081] In the above embodiment, an example is described in which a battery anomaly detection system 10 connected to the network 5 detects a micro short circuit in a battery pack mounted on an electric vehicle 20. In this regard, the battery anomaly detection system 10 may also be embedded in the control unit 25. Furthermore, the battery anomaly detection system 10 may also be embedded in the charging station 30.

[0082] In the above embodiment, a four-wheeled electric vehicle is assumed as the electric vehicle 20. In this regard, an electric motorcycle (electric scooter), an electric bicycle, or an electric kickboard may also be used. Furthermore, electric vehicles include not only full-size electric vehicles but also low-speed electric vehicles such as golf carts and electric scooters. Furthermore, devices equipped with battery packs are not limited to the electric vehicle 20. Devices equipped with battery packs also include electric mobile vehicles such as electric ships, railway vehicles, multi-rotor aircraft (drones), fixed power storage systems, and consumer electronic devices (smartphones, laptops, etc.).

[0083] Furthermore, the embodiment can also be determined by the following items.

[0084] [Project 1]

[0085] A battery abnormality detection system (10) is characterized by comprising:

[0086] a data acquisition unit (111) for acquiring time series data of a plurality of voltages and a SOC of a battery pack, the plurality of voltages including a minimum voltage of a plurality of single battery cells (E1-Em) connected in series in the battery pack, or the plurality of voltages including at least a minimum voltage of a plurality of single battery blocks (Eb1-Ebm) connected in series in the battery pack, the plurality of single battery blocks (Eb1-Ebm) each including a plurality of single battery cells (E1-Em);

[0087] a data processing unit (112) for calculating a voltage difference between a minimum voltage of the plurality of single cells (E1-Em) or the plurality of single cell blocks (Eb1-Ebm) and a reference voltage in a time series manner; and

[0088] The determination unit (113) determines that a micro short circuit has occurred in the cell (E1-Em) or cell block (Eb1-Ebm) of the minimum voltage when the expansion rate of the voltage difference is greater than a threshold value.

[0089] The data processing unit (112) calculates the expansion rate of the voltage difference using voltage data during a period when the SOC of the battery pack is within a predetermined SOC range.

[0090] This allows for highly accurate detection of a micro short circuit in a battery pack including a plurality of battery cells ( E1 -Em) or battery blocks ( Eb1 -Ebm) connected in series.

[0091] [Project 2]

[0092] The battery abnormality detection system (10) according to item 1 is characterized in that:

[0093] The data processing unit (112) selects, from a plurality of SOC ranges, an SOC range having the largest number of SOC sampling data during the analysis target period of the time series data as the predetermined SOC range.

[0094] Thus, the presence or absence of a micro short circuit can be determined based on voltage data in an SOC range in which the voltage behavior is likely to be stable.

[0095] [Item 3]

[0096] The battery abnormality detection system (10) according to item 1 is characterized in that:

[0097] The data acquisition unit (111) acquires time series data of the current of the battery pack,

[0098] The data processing unit (112) selects, from a plurality of SOC ranges, an SOC range having the longest total rest period within an analysis target period of the time series data as the predetermined SOC range.

[0099] Thus, the presence or absence of a micro short circuit can be determined based on voltage data in an SOC range in which the voltage behavior is likely to be stable.

[0100] [Item 4]

[0101] The battery abnormality detection system (10) according to item 2 or 3 is characterized in that:

[0102] The data processing unit (112) deletes the voltage sampling data that exists in the SOC range other than the predetermined SOC range, and performs linear interpolation on the interval of the deleted voltage data.

[0103] This ensures the number of samples of voltage data.

[0104] [Item 5]

[0105] The battery abnormality detection system (10) according to item 2 or 3 is characterized in that:

[0106] The multiple SOC ranges include overlapping areas.

[0107] Thus, even when the voltage data near the boundary is concentrated when the SOC is simply divided, an appropriate SOC range can be selected.

[0108] [Item 6]

[0109] A battery abnormality detection method, characterized by comprising the following steps:

[0110] Acquiring time series data of a plurality of voltages and a SOC of a battery pack, the plurality of voltages including a minimum voltage of a plurality of single battery cells (E1-Em) connected in series in the battery pack, or the plurality of voltages including at least a minimum voltage of a plurality of single battery blocks (Eb1-Ebm) connected in series in the battery pack, the plurality of single battery blocks (Eb1-Ebm) each including a plurality of single battery cells (E1-Em);

[0111] calculating a voltage difference between a minimum voltage of the plurality of single cells (E1-Em) or the plurality of single cell blocks (Eb1-Ebm) and a reference voltage in a time series manner; and

[0112] When the voltage difference expansion rate is equal to or greater than a threshold value, it is determined that a micro short circuit has occurred in the cell (E1-Em) or cell block (Eb1-Ebm) with the minimum voltage.

[0113] Here, in the step of performing the calculation, the expansion rate of the voltage difference is calculated using voltage data during a period when the SOC of the battery pack is within a predetermined SOC range.

[0114] This allows for highly accurate detection of a micro short circuit in a battery pack including a plurality of battery cells ( E1 -Em) or battery blocks ( Eb1 -Ebm) connected in series.

[0115] [Item 7]

[0116] A battery abnormality detection program, characterized in that it causes a computer to execute the following processing:

[0117] Acquiring time series data of a plurality of voltages and a SOC of a battery pack, the plurality of voltages including a minimum voltage of a plurality of single battery cells (E1-Em) connected in series in the battery pack, or the plurality of voltages including at least a minimum voltage of a plurality of single battery blocks (Eb1-Ebm) connected in series in the battery pack, the plurality of single battery blocks (Eb1-Ebm) each including a plurality of single battery cells (E1-Em);

[0118] calculating a voltage difference between a minimum voltage of the plurality of single cells (E1-Em) or the plurality of single cell blocks (Eb1-Ebm) and a reference voltage in a time series manner; and

[0119] When the voltage difference expansion rate is equal to or greater than a threshold value, it is determined that a micro short circuit has occurred in the cell (E1-Em) or cell block (Eb1-Ebm) with the minimum voltage.

[0120] In the calculation process, the voltage difference expansion rate is calculated using voltage data during a period when the SOC of the battery pack is within a predetermined SOC range.

[0121] This allows for highly accurate detection of a micro short circuit in a battery pack including a plurality of battery cells ( E1 -Em) or battery blocks ( Eb1 -Ebm) connected in series.

[0122] Description of Reference Numerals

[0123] 2: Commercial power system; 5: Network; 10: Battery anomaly detection system; 11: Control unit; 12: Storage unit; 13: Communication unit; 20: Electric vehicle; 21: Battery pack system; 22: Voltage sensor; 23: Current sensor; 24: Temperature sensor; 25: Control unit; 26: Communication unit; 30: Charging pile; 31: Power supply unit; 32: Control unit; 33: Communication unit; 111: Data acquisition unit; 112: Data processing unit; 113: Judgment unit; 121: Battery data retention unit.

Claims

1. A battery abnormality detection system, characterized in that: have: a data acquisition unit that acquires time-series data including a plurality of voltage data including a minimum voltage of a plurality of battery cells connected in series and included in the battery pack, or a plurality of voltages including at least a minimum voltage of a plurality of battery blocks connected in series and included in the battery pack, each of the plurality of battery blocks including a plurality of battery cells; a data processing unit that calculates a voltage difference between a minimum voltage of each of the plurality of cells or each of the plurality of cell blocks and a reference voltage in a time series manner to obtain a plurality of voltage difference data; as well as The determination unit determines that a micro short circuit has occurred in the plurality of cells at the minimum voltage or the plurality of cell blocks at the minimum voltage when the rate of expansion of the voltage difference is equal to or greater than a threshold value. The data processing unit calculates the voltage difference expansion rate for each of the plurality of cells or each of the plurality of cell blocks using the plurality of voltage data during a period when the state of charge of the battery pack is within a predetermined state of charge range.

2. The battery abnormality detection system according to claim 1, characterized in that: The data processing unit selects, from a plurality of charge state ranges, a charge state range having the largest number of charge state sampling data during the analysis target period of the time series data as the predetermined charge state range.

3. The battery abnormality detection system according to claim 1, characterized in that: The data acquisition unit acquires time series data of a plurality of currents of the battery pack. The data processing unit selects, from a plurality of state-of-charge ranges, a state-of-charge range having the longest total pause period during the analysis target period of the plurality of current time-series data as the predetermined state-of-charge range.

4. The battery abnormality detection system according to claim 2 or 3, characterized in that: The data processing unit deletes the voltage sampling data that exists in a charging state range other than the predetermined charging state range, and performs linear interpolation on the section of the deleted voltage data.

5. The battery abnormality detection system according to claim 2 or 3, characterized in that: The plurality of state of charge ranges include overlapping regions.

6. A battery abnormality detection method, characterized in that: The steps of acquiring time series data including a plurality of voltage data and a plurality of charge state data of a plurality of charge states of a battery pack, wherein the plurality of voltages include a minimum voltage of a plurality of battery cells connected in series and included in the battery pack, or the plurality of voltages include at least a minimum voltage of a plurality of battery cell blocks connected in series and included in the battery pack, each of the plurality of battery cell blocks including a plurality of battery cells, The voltage difference between the minimum voltage of each of the plurality of single cells or each of the plurality of single cell blocks and the reference voltage is calculated in time series as a plurality of voltage difference data. When the voltage difference expansion rate is equal to or greater than a threshold value, it is determined that a micro short circuit has occurred in the plurality of cells at the minimum voltage or the plurality of cell blocks at the minimum voltage. In the calculation, the voltage difference expansion rate is calculated using voltage data during a period when the state of charge of the battery pack is within a predetermined state of charge range.

7. A battery abnormality detection program, characterized in that: Causes the computer to perform the following processing: Acquiring time series data including a plurality of voltage data and a plurality of charge state data of a plurality of charge states of a battery pack, the plurality of voltages including a minimum voltage of a plurality of battery cells connected in series and included in the battery pack, or the plurality of voltages including at least a minimum voltage of a plurality of battery cell blocks connected in series and included in the battery pack, each of the plurality of battery cell blocks including a plurality of battery cells; calculating a voltage difference between a minimum voltage of each of the plurality of cells or each of the plurality of cell blocks and a reference voltage in a time series manner to obtain a plurality of voltage difference data; as well as When the voltage difference expansion rate is equal to or greater than a threshold value, it is determined that a micro short circuit has occurred in the plurality of cells at the minimum voltage or the plurality of cell blocks at the minimum voltage. In the calculation, the voltage difference expansion rate is calculated using voltage data during a period when the state of charge of the battery pack is within a predetermined state of charge range. 8 . A non-transitory recording medium recording the battery abnormality detection program according to claim 7 .

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