Data analysis system, defect notification system for single battery, data analysis method, data analysis program, and recording medium on which data analysis program is recorded

Abstract

In a data analysis system, an analysis unit analyzes time-series data. The determination unit determines whether each value included in the time-series data is a measured value or a supplementary value. When the time-series data includes a supplemental value, the preprocessing unit can switch whether or not to use the supplemental value for data analysis. The time series data may be battery data including at least a voltage of the secondary battery. The pre-processing unit is capable of deleting the supplemental value from the time series data without using the supplemental value for data analysis.

Description

Technical Field

[0001] The present disclosure relates to a data analysis system for analyzing battery data and the like, a defective cell notification system, a data analysis method, and a data analysis program. Background Art

[0002] In an analysis system for various time-series data of secondary batteries, a process of supplementing data-deficient intervals is sometimes performed. Patent Document 1 relates to data supplementation of image data and discloses the following method: information representing a target of a series of inputs is generated based on the temporal or spatial positional relationship of an input portion that exists externally, a process of supplementing a disappeared target is performed when the target temporarily disappears, and a process of removing an unstable target is performed when an unstable target is generated. In this method, it is necessary to perform a supplementary calculation of disappeared data in order to determine the supplementation or removal of the target, and it is also necessary to perform a quality determination of the supplementary data, resulting in an increased data processing load.

[0003] Prior Art Documents

[0004] Patent Documents

[0005] Patent Document 1: Japanese Unexamined Patent Application Publication No. 2010-238094 Summary of the Invention

[0006] In the time-series data of secondary batteries, supplementing missing data also helps to increase the opportunities for diagnosing or analyzing secondary batteries. However, diagnosis or analysis based on time-series data including supplementary values may cause misdiagnosis, false detection, or omission.

[0007] The present disclosure has been made in view of such circumstances, and an object thereof is to provide a technique for improving the accuracy of data analysis.

[0008] To solve the above problems, a data analysis system according to an aspect of the present disclosure includes: an analysis unit that analyzes time-series data; a discrimination unit that discriminates whether each value included in the time-series data is a measured value or a supplementary value; and a preprocessing unit that can switch whether to use the supplementary value for data analysis when the time-series data includes a supplementary value.

[0009] In addition, any combination of the above components, and a mode obtained by converting the expression of the present disclosure between devices, systems, methods, programs, recording media, etc. is also effective as a mode of the present disclosure.

[0010] According to the present disclosure, the accuracy of data analysis can be improved. Brief Description of the Drawings

[0011] Figure 1It is a diagram for explaining a defective cell notification system and a battery analysis system related to the embodiments.

[0012] Figure 2 It is a diagram showing a structural example of a combined battery system.

[0013] Figure 3A It is a diagram showing an example of the voltage change of a block.

[0014] Figure 3B It is a diagram showing an example of the change in the voltage difference between blocks.

[0015] Figure 4 It shows in a graph Figure 3A , Figure 3B A diagram showing the relationship between the voltage of a normal block and the voltage difference between blocks shown.

[0016] Figure 5 It is a diagram summarizing the setting rules for the threshold to be compared with the voltage failure degree.

[0017] Figure 6A It is a diagram showing in a graph that the voltage failure degree is 1 when the number of parallel cells P in a block is 2 and the number of failed cells F is 1.

[0018] Figure 6B It is a diagram showing in a graph that the voltage failure degree is 1 when the number of parallel cells P in a block is 2 and the number of failed cells F is 1.

[0019] Figure 7 It is a flowchart showing the basic process of detecting a failed cell.

[0020] Figure 8 It is a flowchart showing a specific example of the filtering process for the failed cell detection process performed by the battery analysis system according to the embodiments.

[0021] Figure 9 It is a diagram for explaining the function of a transient response filter.

[0022] Figure 10 It shows for Figure 9 A diagram showing the time series data of the current after interpolating and supplementing the defective interval shown.

[0023] Figure 11 It shows after removing Figure 10 A diagram showing the time series data of the current after removing the supplementary data shown. Detailed implementation mode

[0024] Figure 1FIG. 0 is a diagram for explaining a defective cell notification system 1 and a battery analysis system 10 according to an embodiment. The defective cell notification system 1 according to the embodiment is constructed by a battery analysis system 10 and a control unit 25, a communication unit 26, a display unit 28, etc. mounted on an electric vehicle 20. The battery analysis system 10 according to the embodiment is a system for analyzing a battery pack mounted on the electric vehicle 20. For example, the battery analysis system 10 may be constructed on a company server provided in the company facilities or data center of an operator that provides an analysis service for the battery pack mounted on the electric vehicle 20. Alternatively, the battery analysis system 10 may be constructed on a cloud server utilized based on a cloud service. Alternatively, the battery analysis system 10 may be constructed on a plurality of servers provided in a distributed manner at a plurality of locations (data centers, company facilities). The plurality of servers may be any one of a combination of a plurality of company servers, a combination of a plurality of cloud servers, and a combination of a company server and a cloud server.

[0025] An assembled battery system 21 included in the battery pack mounted on the electric vehicle 20 supplies power to a drive motor (not shown). The assembled battery system 21 includes a plurality of parallel cell blocks connected in series. The parallel cell blocks are each formed by connecting a plurality of cells in parallel to increase the battery capacity.

[0026] Figure 2 FIG. 7 is a diagram showing a structural example of the assembled battery system 21. The assembled battery system 21 includes a plurality of parallel cell blocks Eb1 - Ebm connected in series. Each of the parallel cell blocks Eb1 - Ebm includes a plurality of cells E1a to E1n - Ema to Emn connected in parallel.

[0027] The cell can be a lithium - ion battery cell, a nickel - metal hydride battery cell, a lead - acid battery cell, etc. Hereinafter, an example of using a lithium - ion battery cell (nominal voltage: 3.6 - 3.7V) is assumed in this specification. The number of series - connected parallel cell blocks is determined according to the voltage of the drive motor.

[0028] Voltage sensors 22 measure the voltages at both ends of the parallel cell blocks connected in series, respectively. A shunt resistor is connected in series with the plurality of parallel cell blocks connected in series. A current sensor 23 measures the current flowing through the parallel cell blocks connected in series based on the voltage across the shunt resistor. Alternatively, a Hall element may be used instead of the shunt resistor. A plurality of temperature sensors 24 are provided in the battery pack including the assembled battery system 21. The temperature sensor 24 can use, for example, a thermistor.

[0029] The BMU (Battery Management Unit) and the ECU (Electronic Control Unit) form the control unit 25 in a collaborative manner. The BMU combines the OCV (Open Circuit Voltage) method and the current integration method to estimate the SOC (State Of Charge). The OCV method is a method for estimating the SOC based on the measured OCV of a single battery cell and the SOC-OCV curve of the single battery cell. The SOC-OCV curve of a single battery cell is pre-made based on the characteristic tests of the battery manufacturer and registered in the BMU at the time of factory shipment. The control unit 25 according to the embodiment can display the results detected by the analysis unit 115 described later on the display unit 28.

[0030] The current integration method is a method for estimating the SOC based on the OCV at the start of charge and discharge of a single battery cell and the integrated value of the measured current. In the current integration method, as the charge and discharge time becomes longer, the measurement error of the current accumulates. Therefore, it is preferable to use the SOC estimated by the current integration method and the SOC estimated by the OCV method after weighted averaging.

[0031] The BMU periodically (for example, at intervals of 10 seconds, 1 minute) sends battery data including voltage, current, temperature, and SOC of a plurality of parallel-connected battery cell blocks to the ECU via the in-vehicle network, whereby the ECU samples the battery data in time series. As the in-vehicle network, for example, CAN (Controller Area Network) or LIN (Local Interconnect Network) can be used.

[0032] The communication unit 26 has a function of performing communication signal processing with the communication unit 33 of the charging pile 30 and a 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), wireless LAN, V2I (Vehicle to Infrastructure), V2V (Vehicle to Vehicle), ETC system (Electronic Toll Collection System), or DSRC (Dedicated Short Range Communications).

[0033] The network 5 is a general term for communication lines such as the Internet, dedicated lines, and VPN (Virtual Private Network), regardless of its communication medium and protocol. As the communication medium, for example, a mobile phone network, wireless LAN, wired LAN, optical fiber network, ADSL network, CATV network, etc. can be used. As the communication protocol, for example, TCP (Transmission Control Protocol) / IP (Internet Protocol), UDP (User Datagram Protocol) / IP, Ethernet (registered trademark), etc. can be used.

[0034] The ECU can either send the battery data obtained by sampling to the battery analysis system 10 each time, or accumulate the battery data in the internal memory and send the battery data accumulated in the memory to the battery analysis system 10 in a specified timing. In addition, in a state where the electric vehicle 20 and the charging pile 30 are connected by a charging cable, the ECU can also send the battery data accumulated in the memory to the battery analysis system 10 via the charging pile 30.

[0035] By connecting the electric vehicle 20 and the charging pile 30 using a charging cable, the combined battery system 21 inside the electric vehicle 20 can be charged from the outside. The charging pile 30 is connected to the commercial power system 2 to charge the combined battery system 21.

[0036] Generally speaking, AC is used for charging in the case of normal charging, and DC is used for charging in the case of rapid charging. In the case of charging using AC (for example, single-phase 100 / 200V), the charging voltage or charging current is controlled by a charger (not shown) inside the electric vehicle 20. In the case of charging using 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 rectifier circuit is used to perform full-wave rectification on the AC power supplied from the commercial power system 2 and smooth it using the filter, thereby generating DC power. The DC / DC converter controls the voltage or current of the generated DC power.

[0037] As rapid charging specifications, for example, CHAdeMO (registered trademark), ChaoJi, GB / T, Combo (Combined Charging System) can be used. In CHAdeMO, ChaoJi, and GB / T, CAN is adopted as the communication method. In Combo, PLC (Power Line Communication) is adopted as the communication method.

[0038] In the charging cable adopting the CAN method, in addition to the power line, a communication line is also included. When the electric vehicle 20 and the charging pile 30 are connected through this charging cable, a communication channel is established between the control unit 25 of the electric vehicle 20 and the control unit 32 of the charging pile 30. In addition, in the charging cable adopting the PLC method, the communication signal is transmitted in a manner of being superimposed on the power line.

[0039] The communication unit 33 of the charging pile 30 has a function of performing communication signal processing with the communication unit 26 of the electric vehicle 20 and a function of performing signal processing 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.

[0040] The battery analysis 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 connecting to the network 5 by wire or wirelessly (for example, NIC: Network Interface Card).

[0041] The control unit 11 includes an acquisition unit 111, a first preprocessing unit 112, a discrimination unit 113, a second preprocessing unit 114, an analysis unit 115, and a notification unit 120. The functions of the control unit 11 can be realized by the cooperation of hardware resources and software resources, or only by hardware resources. As hardware resources, a CPU, a ROM, a RAM, a GPU (Graphics Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), and other LSIs can be used. As software resources, programs such as an operating system and an application program can be used. The control unit 11 is realized, for example, by a computer having a CPU (Central Processing Unit) and a memory. By the CPU executing the program stored in the memory, the computer functions as the control unit 11. The program is pre-recorded in the memory of the control unit 11 here, but it can also be provided through a telecommunication line such as the Internet or recorded on a (non-transitory) recording medium such as a memory card.

[0042] The storage unit 12 includes non-volatile recording media such as an HDD and an SSD, and is used to store various data. The storage unit 12 includes a battery data holding unit 121. The 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.

[0043] The analysis unit 115 reads the time-series data of the battery pack held in the battery data holding unit 121 to analyze the battery pack. In the present embodiment, the analysis items of the battery pack include single-cell failure analysis for detecting whether a failed single cell is included in the battery pack.

[0044] A failed single cell is a single cell that causes a functional defect, and is caused by the opening of a gas discharge valve, the operation of a CID (Current Interrupt Device), disconnection of a wire, poor contact of a terminal, lithium precipitation, etc. The opening of the gas discharge valve and the operation of the CID are started when the pressure inside the battery rises abnormally. The opening of the gas discharge valve, the operation of the CID, disconnection of a wire, and lithium precipitation are irreversible failures, and poor contact of a terminal is a reversible failure. In the present embodiment, single-cell failure is assumed to include a significant deterioration in capacity caused by lithium precipitation or the like. If the failed single cell is left unattended, the current load on the remaining single cells in the parallel single-cell block including the failed single cell increases, and it is likely to cause failure of the remaining single cells.

[0045] In single-cell failure detection, the analysis unit 115 detects whether a single-cell failure has occurred in the target block based on the voltage change of a normal parallel single-cell block (hereinafter simply referred to as a normal block) and the change in the voltage difference between the normal block and the target parallel single-cell block (hereinafter referred to as the target block).

[0046] In this analysis item, the purpose is to detect the block including the failed single cell (hereinafter referred to as the failed block) without damage. The notification unit 120 uses the communication unit 13 to send the result detected by the analysis unit 115 to the communication unit 26 of the electric vehicle 20 via the network 5, and the control unit 25 of the electric vehicle 20 displays a display indicating the detected result received by the communication unit 26 on the display unit 28. Thus, it is possible to notify the user of the occurrence of a single-cell failure, prompt the replacement and repair of the battery pack, and prevent the occurrence of an unsafe situation. Hereinafter, a specific description will be given.

[0047] In the present embodiment, an index called voltage failure degree is used to detect the failed block. The voltage failure degree is a unique index that utilizes the fact that the smaller the SOH (State Of Health) of the battery, the greater the change in OCV and SOC when charging or discharging with the same current amount [Ah], and can be used to detect an abnormal capacity of the block.

[0048] Figure 3A An example of the voltage change of the block is shown. Figure 3B An example of the change in the voltage difference between the blocks is shown. Figure 3AThe horizontal axis is the date and time, and the vertical axis is the block voltage [V], showing the voltage variations of the first block Eb1 and the second block Eb2. Figure 3B The horizontal axis is the date and time, and the vertical axis is the voltage difference between blocks [ΔV], showing the voltage difference [ΔV] between the first block Eb1 and the second block Eb2, and the voltage difference [ΔV] between the first block Eb1 and itself.

[0049] Figure 3A , Figure 3B It shows the situation when continuous discharging occurs for about 2 hours starting from around 11:30 on May 9th. As Figure 3A shown, the voltages of both the first block Eb1 and the second block Eb2 decrease. Since the second block (failed block) Eb2 including the failed single-cell battery behaves as a battery with a substantially large SOH drop, its voltage drops rapidly compared to the voltage of the first block Eb1 (normal block).

[0050] As Figure 3B shown, the voltage difference between the first block Eb1 (normal block) and the second block Eb2 (failed block) expands. The index obtained by quantifying the rate of expansion of this voltage difference is the voltage failure degree.

[0051] Figure 4 It shows in the graph Figure 3A , Figure 3B the relationship between the voltage of the normal block shown and the voltage difference between blocks. In Figure 4 the voltage difference between the first block Eb1 and the second block Eb2, and the voltage difference between the first block Eb1 and itself are plotted in the range where the voltage of the normal block is from 3.8V to 3.95V. And, the approximate lines obtained by performing linear regression on the plots of each voltage difference using the least squares method are depicted.

[0052] Each approximate line has a slope that is approximately proportional to the SOH difference between blocks. The slope of the linear regression line of the voltage difference between the first block Eb1 and the second block Eb2 is (-0.1 / 0.15). The slope of the linear regression line of the voltage difference between the first block Eb1 and itself is (0 / 0.15).

[0053] In this embodiment, the value obtained by normalizing the rate of expansion of the voltage difference between blocks using the voltage change of the normal block is set as the voltage failure degree of each target block. The larger the value of the voltage failure degree, the larger the voltage difference between blocks is generated by a smaller charge and discharge. The voltage failure degree with the largest absolute value among the voltage failure degrees of each target block is set as the voltage failure degree of the battery pack. That is, the voltage failure degree of the battery pack is set as the voltage failure degree of the block whose SOH deviates most from the SOH of the normal block. In Figure 4In the example shown, the voltage failure degree of the battery pack is 0.67 (= 0.1 / 0.15). A large value of the voltage failure degree indicates that blocks with a large deviation in SOH are mixed in, and it indicates a high possibility that failed single cells are mixed in.

[0054] Next, the threshold value to be compared with the voltage failure degree will be described. It is desired to determine that the case where more than a specified number of single cells among the parallel single cells included in the block have failed (complete functional defect) is abnormal. However, since the above voltage failure degree is an index indicating the deviation of SOH between blocks, some values are derived even when an SOH deviation occurs. Therefore, it is necessary to set an appropriate threshold value for the voltage failure degree in order to distinguish between failure and the allowable SOH deviation.

[0055] Figure 5 It is a diagram summarizing the setting rules for the threshold value to be compared with the voltage failure degree. In this example, it is assumed that the SOC-OCV curve has a proportional relationship to set the threshold value. That is, if the change amount of SOC is 2 times, it is assumed that the change amount of OCV is also 2 times. In the present embodiment, the voltage failure degree is defined as (voltage change amount of the failed block - voltage change amount of the normal block) / voltage change amount of the normal block.

[0056] Hereinafter, let the number of parallel single cells in the block be P and the number of failed single cells in the block be F. If F single cells out of P parallel single cells have failed, a current load of P amounts is applied to the remaining normal (P - F) single cells. When the voltage change amount during charge and discharge of the normal block is set to ΔV, the voltage change amount of the failed block is ΔV × (P / (P - F)). At this time, the voltage difference between the normal block and the failed block is ΔV - (ΔV × (P / (P - F)) = ΔV × (F / (P - F)). The voltage failure degree is ΔV × (F / (P - F)) / ΔV = F / (P - F).

[0057] For example, when the number of parallel single cells in the block is 4 (P = 4), when 1 has failed (F = 1), the voltage failure degree is 1 / (4 - 1) = 0.333. When 2 have failed (F = 2), the voltage failure degree is 2 / (4 - 2) = 1. In addition, the voltage failure degree is a value determined only based on the ratio of the number of parallel single cells in the block to the number of failed single cells. For example, whether 1 out of 4 parallel ones has failed or 10 out of 40 parallel ones have failed, the voltage failure degree is 0.333.

[0058] The voltage failure degree is an index representing the increment of the current load applied to each remaining normal single cell when a failed single cell occurs, with the current load applied to each single cell in the case of no single cell failure within the block being set to 1. For example, a voltage failure degree of 0.333 means that due to a single cell failure within the block, the current load of each remaining normal single cell increases to 1.333 (1 + 0.333) times.

[0059] As long as the designer detects the case where more than 1 / 4 of the number of parallel single cells in the block fails as abnormal, the threshold is set to 0.333; when detecting the case where more than 1 / 3 of the number fails as abnormal, the threshold is set to 0.5; and when detecting the case where more than 1 / 2 of the number fails as abnormal, the threshold is set to 1. In this way, the designer can arbitrarily adjust the sensitivity of failure detection.

[0060] Figure 6A 、 Figure 3B Figure shows that the voltage failure degree is 1 when the number of parallel single cells P in the block is 2 and the number of failed single cells F is 1. Figure 6A Shows the voltage change of the failed block and the normal block. Figure 6B Shows the relationship between the voltage of the normal block and the voltage difference between the failed block and the normal block.

[0061] When the number of parallel single cells P is 2 and the number of failed single cells F is 1, the SOH of the failed block can be regarded as 1 / 2 of the SOH of the normal block. Therefore, the voltage change amount of the failed block is 2 times (2ΔV) that of the normal block. Thus, the voltage failure degree is (2ΔV - ΔV) / ΔV = 1.

[0062] Figure 7 Is a flowchart showing the basic process of single cell failure detection. The analysis unit 115 performs linear regression on the voltage data at multiple sampling times of each block to calculate the slope of the linear regression line of the voltage change of each block (S10). The analysis unit 115 sets the block with the smallest absolute value among the slopes of the linear regression lines of the voltage changes of the calculated blocks as the normal block (S11). The analysis unit 115 divides the difference between the voltage change amounts of the target block and the normal block by the voltage change amount of the normal block (standardization) to calculate the voltage failure degree of the target block (S12).

[0063] That is, when setting the voltage change amount of the normal block as ΔV and the voltage change amount of the target block as ΔVn, the analysis unit 115 calculates |(ΔVn - ΔV)| / ΔV to calculate the voltage failure degree of the target block.

[0064] When the voltage failure degree is above the threshold value (Yes in S13), the analysis unit 115 determines that the failed single cell is included in the target block (S14). When the voltage failure degree is less than the threshold value (No in S13), the analysis unit 115 determines that the failed single cell is not included in the target block (S15).

[0065] Return to Figure 1 In data analysis, continuous data is basically required. As a preprocessing, generally, the data in the missing interval is supplemented. In many cases, the sampling number is appropriately increased by data supplementation, thereby increasing the analysis opportunity and improving the analysis accuracy.

[0066] The first preprocessing unit 112 can read the time series data of the battery pack held in the battery data holding unit 121 and perform preprocessing on the time series data. The first preprocessing unit 112 determines the missing interval based on the time stamps of the respective records of the time series data. The first preprocessing unit 112 supplements the estimated value to the missing interval.

[0067] The first preprocessing unit 112 can use a general supplementation method to supplement the value of the missing interval. For example, the first preprocessing unit 112 supplements the value of the missing interval with the same value as the value immediately before the missing interval (value retention). For example, the first preprocessing unit 112 supplements the value of the missing interval with the value estimated by linear interpolation based on the values before and after the missing interval (linear interpolation). For example, when the value changes linearly in the interval before or after the missing interval, the first preprocessing unit 112 supplements the value of the missing interval with the value estimated by linear extrapolation based on the slope (linear extrapolation). In addition, a supplementation method using a polynomial such as spline supplementation can also be used.

[0068] The first preprocessing unit 112 generates a file including an ID (e.g., flag) string indicating whether the value of each record of the time series data is a measured value or a supplemented value. The first preprocessing unit 112 saves the time series data after the supplementation process in the battery data holding unit 121.

[0069] In addition, the supplementation process of the missing interval may sometimes be performed by the control unit 25 of the electric vehicle 20. In addition, the supplementation process may sometimes be performed by an external system other than the battery analysis system 10. In these cases, the acquisition unit 111 acquires the time series data including the supplemented value.

[0070] When performing data analysis, the discrimination unit 113 discriminates whether each value included in the time series data of the battery pack read from the battery data storage unit 121 is a measured value or a supplemented value. When the above ID exists, the discrimination unit 113 refers to the ID to discriminate whether each value is a measured value or a supplemented value. When the above ID does not exist, the discrimination unit 113 detects the change pattern of the values included in the time series data to discriminate whether each value is a measured value or a supplemented value.

[0071] For example, the discrimination unit 113 discriminates the values in the interval where the same value continues in the time series data as supplemented values. The measured values detected by the sensor fluctuate, and generally the values below the decimal point will not be the same value. When exactly the same value continues, it is highly likely that the value is obtained by supplementation through the supplementation program.

[0072] For example, the discrimination unit 113 discriminates the values in the interval where the values change linearly in the time series data as supplemented values. The measured values detected by the sensor fluctuate, and even when a phenomenon occurs that causes the voltage and current to change linearly, generally it will not change at the slope of a perfect straight line. The interval where the change is linearly at exactly the same slope is highly likely to be an interval obtained by supplementation through the supplementation program.

[0073] When it is impossible to discriminate whether supplemented values are included in the time series data through the ID, the discrimination unit 113 basically needs to scan the change pattern of the values included in the time series data. However, when scanning the change pattern of the values for the entire interval of the time series data, the processing load increases.

[0074] Therefore, it can also be that when the values included in the time series data satisfy a specified condition (such as the application of the starting current), the discrimination unit 113 performs the discrimination process (i.e., scanning of the change pattern) of whether it is a measured value or a supplemented value in the peripheral interval of the value. The processing load can be reduced by suspending the scanning of the change pattern in other intervals.

[0075] When supplemented values are included in the time series data to be analyzed, the second preprocessing unit 114 can switch whether to use the supplemented values for data analysis. As described above, supplementing the data in the missing interval basically causes an increase in the analysis opportunity and an improvement in the analysis accuracy. In contrast, in extremely rare cases, the analysis accuracy may decrease due to the presence of the supplemented values. In such a special case, the second preprocessing unit 114 deletes the supplemented values from the time series data and does not use the supplemented values in the data analysis.

[0076] In order to ensure the detection accuracy of the above-mentioned single cell failure, it is important to ensure the accuracy of the linear regression line of the voltage difference between blocks, and it is necessary to ensure the accuracy of the voltage data as its basis. Hereinafter, a method for improving the calculation accuracy of the voltage failure degree by filtering the voltage data to be used will be described.

[0077] Figure 8 FIG. 4 is a flowchart showing a specific example of the filtering process for the failed single cell detection process performed by the battery analysis system 10 according to the embodiment. In this specific example, the time series data of the battery pack including the supplementary value preprocessed by the first preprocessing unit 112 or the control unit 25 of the electric vehicle 20 is set as the analysis object.

[0078] The analysis unit 115 extracts the charge / discharge interval (S20) excluding the CV (constant voltage) interval from the time series data of the battery pack. The analysis unit 115 excludes the voltage data less than the set value in the extracted charge / discharge interval (S21). For example, in the case of a battery pack using a ternary system (NMC) cathode material, voltage values less than 3.4 V are excluded, and in the case of a battery pack using a lithium cobalt oxide (LCO) cathode material, voltage values less than 3.8 V are excluded.

[0079] The analysis unit 115 excludes the voltage data of the charge / discharge duration less than the set value (for example, 10 minutes) (S22). The analysis unit 115 excludes the voltage data of the voltage transient response interval corresponding to the current application / stop interval (S23). A specific example of the voltage transient response interval will be described later.

[0080] The analysis unit 115 excludes the voltage data of the charge / discharge interval with excessive current variation (S24). The analysis unit 115 excludes, for example, the voltage data of the charge / discharge interval where the ratio of the maximum current to the minimum current in the charge / discharge interval is equal to or greater than the set value.

[0081] The analysis unit 115 excludes the voltage data of the charge / discharge interval with the data sampling number less than the set value (S25). The analysis unit 115 excludes the voltage data of the charge / discharge interval with the current change less than the set value (S26). More specifically, the analysis unit 115 excludes the voltage data of the charge / discharge interval where the voltage change amplitude of the parallel single cell block with the smallest voltage change among the parallel single cell blocks included in the battery pack is less than the set value.

[0082] The analysis unit 115 excludes the voltage data of the charge / discharge interval where the voltage difference between blocks is equal to or greater than the set value throughout the interval (S27). More specifically, the analysis unit 115 excludes the voltage data of the charge / discharge interval where the difference between the maximum voltage and the minimum voltage of the plurality of parallel single cell blocks included in the battery pack is equal to or greater than the set value throughout the interval.

[0083] The analysis unit 115 calculates the voltage failure degree and the RMSE (Root Mean Square Error) value for each remaining charge-discharge interval (S28). As described above, the voltage failure degree is the maximum absolute value among the voltage failure degrees of the multiple parallel single-cell blocks included in the battery pack. The RMSE value is set to the maximum value among the RMSE values of the linear regression lines of the voltage differences between the blocks within the battery pack.

[0084] In the case where there is voltage difference noise in the charge-discharge interval where the voltage failure degree is above the threshold and the RMSE value is less than the set value, the analysis unit 115 recalculates the voltage failure degree and the RMSE value after removing the voltage difference noise (S29). The voltage difference noise refers to the voltage difference between the voltage of the target block and the voltage of the optimal block with the highest SOH being above the set value, and the voltage difference between the voltage of the target block and a past voltage of the target block being less than the set value, and the voltage difference between the voltage of the target block and a future voltage of the target block being less than the set value. In the case where no voltage difference noise is detected, there is no need to recalculate the voltage failure degree and the RMSE value.

[0085] The analysis unit 115 excludes the voltage data of the charge-discharge intervals where the RMSE value is above the set value (S30). Regarding the remaining charge-discharge intervals, if the voltage failure degree is above the threshold, the analysis unit 115 determines that there is a failure, and if it is less than the threshold, the analysis unit 115 determines that there is no failure (S31). In Figure 8 The set values used in each filtering process in the shown flowchart are set by the designer based on the results of experiments and simulations. Next, the transient response filter in step S23 will be described in detail.

[0086] Figure 9 is a diagram for explaining the operation of the transient response filter. Figure 9 Shows the transition of the current waveform and the voltage waveform when switching from the rest interval to the charging period. The waveforms shown by the solid lines show the actual current waveform and the actual voltage waveform. The black circles show the measured values of the current measured by the current sensor 23 and the measured values of the voltage measured by the voltage sensor 22.

[0087] In addition to having an ohmic resistance component, the secondary battery also has non-ohmic resistance components such as a reaction resistance component and a diffusion resistance component. Therefore, after applying current to the secondary battery, the voltage of the secondary battery changes with a time constant. The voltage data in the transient response interval where the voltage does not change linearly with respect to the current may cause a false determination of single-cell failure detection, so it is desirable to exclude it.

[0088] In order to exclude voltage data in the transient response interval, it is considered to exclude voltage data included in the range from the first current sampling point in the charging interval to the sampling point after a specified period has elapsed. For example, when the specified period is set to 5 minutes and the sampling rate is set to 1 minute, voltage data corresponding to 5 points starting from the first current sampling point in the charging interval becomes the object to be excluded.

[0089] Data deficits often occur between the rest interval and the charging period. In many cases, the microcontroller also rests during the rest interval, and in such cases, the microcontroller cannot sample data.

[0090] Figure 10 Shows the Figure 9 Time-series data of the current after interpolation and supplementation of the shown deficit interval. The first preprocessing unit 112 or the control unit 25 of the electric vehicle 20 uses a straight line (shown by a dashed line in Figure 10 ) to connect the current data before and after the deficit interval to each other, and draws supplementary values (shown by small black circles in Figure 10 ) at a specified sampling rate on the straight line.

[0091] The analysis unit 115 identifies the first sampling point at which the current data changes from 0 to a positive value as the start point of the charging interval. The analysis unit 115 excludes voltage data corresponding to a specified number of samples (e.g., 5 points) from the start point of the charging interval. In the example shown in Figure 10 , the voltage data in the actual transient response interval for which the voltage data cannot be excluded. When the interpolation interval is longer than the exclusion interval, the voltage data in the transient response interval cannot be excluded. Even when the interpolation interval is shorter than the exclusion interval, the voltage data in the later part of the transient response interval cannot be excluded.

[0092] Figure 11 Shows the time-series data of the current after removing the Figure 10 shown supplementary data. The second preprocessing unit 114 deletes the current data in the interpolation interval. As a result, the analysis unit 115 identifies the first measured data that changes to a positive value rather than the first supplementary data at which the current data changes from 0 to a positive value as the start point of the charging interval. Thereby, it is possible to prevent the position of the exclusion interval from deviating significantly from the position of the transient response interval. The analysis unit 115 excludes voltage data corresponding to a specified number of samples from the start point of the charging interval. In the example shown in Figure 11 , the use of voltage data in the transient response interval is avoided.

[0093] In this way, the voltage of the secondary battery is delayed in rising with respect to the increase in current due to the influence of the chemical reaction on the resistance component. In the transient response region of a plurality of parallel single-cell blocks included in the battery pack, the voltages of the plurality of parallel single-cell blocks are likely to deviate. For example, a large voltage difference is caused by the influence of a small SOH difference, temperature difference, or current density difference between the plurality of parallel single-cell blocks. As Figure 11 shown, by excluding the voltage data in the transient response region and determining the presence or absence of single-cell failure based on the voltage data in the stable region, the detection accuracy of single-cell failure can be improved.

[0094] In Figures 9 - 11 , an example of deleting the supplementary data interpolated between the rest period and the charging period is described. However, it is also possible to delete the supplementary data interpolated between the rest period and the discharging period in the same way. In the case where the range for searching for the presence or absence of supplementary data is limited in order to reduce the processing load, the discrimination unit 113 starts the search for supplementary data with the current data rising from 0 to a positive or negative value as a trigger. The search range is set to the range from the sampling point of this positive or negative value to the sampling points traced back to a predetermined period in the past.

[0095] In addition, the analysis unit 115 identifies the first sampling point at which the current data changes from a positive or negative value to 0 as the end point of the charging period or the discharging period. The second preprocessing unit 114 deletes the supplementary data around the end point of the charging period or the discharging period. The analysis unit 115 excludes the voltage data of a predetermined number of samples in the past direction from the end point after the supplementary data of the charging period or the discharging period is deleted.

[0096] The second preprocessing unit 114 can switch whether to delete the supplementary values included in the time-series data according to the content of data analysis. As described above, in the detection of single-cell failure, deleting the supplementary values can improve the detection accuracy. On the other hand, it is desirable not to delete the supplementary values in the SOH diagnosis and directly use these supplementary values.

[0097] The SOH is calculated based on the following (Equation 1) and (Equation 2).

[0098] FCC = ΣI / DOD ··· (Equation 1)

[0099] SOH = current FCC / initial FCC ··· (Equation 2)

[0100] Specifically, the analysis unit 115 calculates the difference (DOD: Depth Of Discharge) between the SOC corresponding to the OCV at the start of charging or discharging and the SOC corresponding to the OCV at the end of charging or discharging, and calculates the integrated current value ΣI during the charging period or the discharging period. The analysis unit 115 estimates the FCC (Full Charge Capacity) based on the depth of discharge DOD and the integrated current value ΣI as shown in the above (Equation 1). The analysis unit 115 estimates the SOH based on the estimated FCC and the initial FCC as shown in the above (Equation 2). The SOH is defined by the ratio of the current FCC to the initial FCC, and the lower the value (the closer to 0%), the more advanced the deterioration is.

[0101] As shown in the above (Equation 1), calculating the SOH requires calculating the integrated current value ΣI, and the lack of current data significantly reduces the calculation accuracy of the integrated current value ΣI. Therefore, it is desirable to use the supplementary value of the current data. In addition, for the voltage data, as long as there are data at the start and end of charging or discharging, that is sufficient. Voltage data for periods other than these are not required, and the accuracy of the voltage data for these periods does not affect the calculation accuracy of the SOH.

[0102] As analysis items of the battery pack, in addition to single cell failure detection and SOH diagnosis, there are also various analysis items such as internal resistance estimation and micro short circuit detection. Based on the calculation algorithms for each analysis item, it is preset in the second preprocessing unit 114 whether to use the supplementary value for each analysis.

[0103] In addition, it is also possible to prepare two sets of time series data of the battery pack, one including the supplementary value supplemented by the first preprocessing unit 112 or the control unit 25 of the electric vehicle 20 and the other not including the supplementary value. When the time series data of the battery pack including the supplementary value supplemented by the control unit 25 of the electric vehicle 20 is sent to the battery analysis system 10, the first preprocessing unit 112 deletes the supplementary value from the time series data to generate time series data not including the supplementary value. The analysis unit 115 distinguishes whether to use the time series data including the supplementary value or the time series data not including the supplementary value according to the content of the data analysis.

[0104] In Figure 8In the flowchart shown, after deleting the supplementary values included in the transient response interval, single-cell failure detection is performed. Regarding this point, the analysis unit 115 can also analyze the time-series data of the supplementary values that have not been deleted to perform single-cell failure detection. When an abnormality is detected in the analysis result, the second preprocessing unit 114 deletes the supplementary values from the time-series data of the battery pack. The analysis unit 115 re-analyzes the time-series data after the supplementary values have been deleted. Since the situation where an abnormality is detected in the single-cell failure analysis is basically rare, it is also possible to use an operation mode in which the supplementary values are deleted only when an abnormality is detected. By re-analyzing using the time-series data after deleting the supplementary values, it is possible to confirm the certainty of the results obtained by analyzing using the time-series data of the supplementary values that have not been deleted.

[0105] As described above according to this embodiment, by switching whether to use the supplementary values included in the time-series data according to the analysis content, it is possible to prepare a data set corresponding to the analysis content and improve the analysis accuracy. Compared with the case of determining whether to use the supplementary values by judging the quality of the supplementary values, the processing load can be reduced. In this embodiment, the conditions for whether to use the supplementary values are clear, and it is possible to simply determine whether to use the supplementary values. In addition, the display unit 28 that displays the occurrence of the detected single-cell failure is not limited to being provided in the electric vehicle 20, and can also be displayed on the analysis system 10 having a display unit or on the display unit of a device connected to the battery analysis system 10 via the network 5.

[0106] As described above, the present disclosure has been described based on the embodiments. Those skilled in the art understand that the embodiments are examples, and various modifications can be made to the combination of their respective constituent elements and processing steps, and such modifications are also within the scope of the present disclosure.

[0107] The battery analysis system 10 according to the present disclosure is not limited to the analysis of the battery pack mounted on the electric vehicle 20. For example, it can also be applied to the analysis of battery packs mounted on electric ships, multi-rotor aircraft (UAVs), electric motorcycles, electric bicycles, stationary energy storage systems, smart phones, tablet computers, notebook PCs, etc.

[0108] The method of switching whether to use the supplementary values included in the time series data according to the analysis content involved in the present disclosure can also be applied to data other than the time series data of the battery pack. For example, in the moving image data captured by a camera, sometimes supplementary frames are inserted between the actually captured frames to make the moving image smooth. For example, sometimes moving image data with a frame rate of 120 Hz or 240 Hz is generated based on moving image data with a frame rate of 60 Hz. When it is desired to purely evaluate the optical hardware performance of the camera (such as the performance of a CMOS image sensor) based on the captured moving image data, the analysis is performed after deleting the supplementary frames. Thus, the possibility of diagnostic errors in the optical hardware performance of the camera is reduced according to the frame images added by software processing.

[0109] In addition, the embodiment can also be determined by the following items.

[0110] [Item 1]

[0111] A data analysis system (10) includes:

[0112] An analysis unit (115) that analyzes time series data;

[0113] A discrimination unit (113) that discriminates whether each value included in the time series data is a measured value or a supplementary value; and

[0114] A preprocessing unit (114) that can switch whether to use the supplementary value for data analysis when the time series data includes a supplementary value.

[0115] Accordingly, the accuracy of data analysis can be improved.

[0116] [Item 2]

[0117] The data analysis system (10) according to Item 1, characterized in that

[0118] The preprocessing unit (114) deletes the supplementary value from the time series data.

[0119] Accordingly, the adverse effects caused by the supplementary value in data analysis can be prevented.

[0120] [Item 3]

[0121] The data analysis system (10) according to Item 1 or 2, characterized in that

[0122] When there is identification information indicating whether each value included in the time series data is a measured value or a supplementary value, the discrimination unit (113) refers to the identification information to discriminate whether each value is a measured value or a supplementary value.

[0123] Accordingly, the supplementary value can be determined simply and accurately.

[0124] [Item 4]

[0125] The data analysis system (10) according to Item 1 or 2, characterized in that

[0126] The discrimination unit (113) detects a change pattern of values included in the time series data to discriminate whether each value is a measured value or a supplementary value.

[0127] Accordingly, even without attaching identification information indicating the supplementary value, the supplementary value can be found from the time series data.

[0128] [Item 5]

[0129] The data analysis system (10) according to Item 4, characterized in that

[0130] The discrimination unit (113) discriminates values in an interval where the same value continues or values in an interval where the values change linearly among the values included in the time series data as supplementary values.

[0131] Accordingly, supplementary values inserted by numerical value retention or linear supplementation can be found.

[0132] [Item 6]

[0133] The data analysis system (10) according to Item 4, characterized in that

[0134] When the value included in the time series data satisfies a specified condition, the discrimination unit (113) performs discrimination processing on whether each value is a measured value or a supplementary value in the peripheral interval of the value.

[0135] Accordingly, the processing load can be reduced.

[0136] [Item 7]

[0137] The data analysis system (10) according to Item 1, characterized in that

[0138] The preprocessing unit (114) switches whether to delete the supplementary value according to the content of the data analysis.

[0139] Accordingly, the processing of the supplementary value can be performed simply and clearly.

[0140] [Item 8]

[0141] The data analysis system (10) according to Item 1, characterized in that

[0142] The analysis unit (115) analyzes the time series data for which the supplementary value has not been deleted,

[0143] When an abnormality is detected in the analysis result, the preprocessing unit (114) deletes the supplementary value from the time-series data.

[0144] The analysis unit (115) re-analyzes the time-series data from which the supplementary value has been deleted.

[0145] Accordingly, the frequency of the deletion process of the supplementary value can be reduced.

[0146] [Item 9]

[0147] According to the data analysis system (10) described in Item 1, characterized in that

[0148] Prepare time-series data including supplementary values and time-series data not including the supplementary values.

[0149] The analysis unit (115) distinguishes whether to use the time-series data including the supplementary value or the time-series data not including the supplementary value according to the content of the data analysis.

[0150] Accordingly, the optimal time-series data can be used according to the content of the data analysis.

[0151] [Item 10]

[0152] According to the data analysis system (10) described in Item 1, wherein

[0153] The time-series data is battery data of the secondary battery (21) including at least voltage.

[0154] Accordingly, the analysis accuracy of the secondary battery can be improved.

[0155] [Item 11]

[0156] According to the data analysis system (10) described in Item 1, characterized in that

[0157] It further includes an acquisition unit (111), and the acquisition unit (111) acquires the voltage data of each parallel single-cell battery block of the battery pack (21) obtained by connecting a plurality of parallel single-cell battery blocks in series, wherein the parallel single-cell battery block is obtained by connecting a plurality of single cells in parallel.

[0158] The analysis unit (115) detects whether a single-cell failure has occurred in the parallel single-cell battery block as the object based on the voltage change of the normal parallel single-cell battery block and the change in the voltage difference between the normal parallel single-cell battery block and the parallel single-cell battery block as the object.

[0159] Accordingly, it is possible to simply and nondestructively detect the failure of the single cells included in the parallel-connected single cell block.

[0160] [Item 12]

[0161] The data analysis system (10) according to Item 11 is characterized in that

[0162] when the voltage change of the normal parallel-connected single cell block is set as ΔV and the voltage change of the parallel-connected single cell block as the object is set as ΔVn,

[0163] the analysis unit (115) calculates |(ΔVn - ΔV)| / ΔV to calculate the voltage failure degree,

[0164] when the voltage failure degree is equal to or higher than the threshold value, the analysis unit (115) determines that a single cell failure has occurred in the parallel-connected single cell block as the object.

[0165] Accordingly, it is possible to determine whether there is a failure of the single cells included in the parallel-connected single cell block based on the quantified index.

[0166] [Item 13]

[0167] A data analysis method is characterized by including the following steps:

[0168] Discriminate whether each value included in the time series data is a measured value or a supplementary value;

[0169] In the case where the time series data includes supplementary values, switch whether to use the supplementary values for data analysis; and

[0170] Analyze the time series data.

[0171] Accordingly, the accuracy of data analysis can be improved.

[0172] [Item 14]

[0173] A data analysis program is characterized by causing a computer to execute the following processing:

[0174] Discriminate whether each value included in the time series data is a measured value or a supplementary value;

[0175] In the case where the time series data includes supplementary values, switch whether to use the supplementary values for data analysis; and

[0176] Analyze the time series data.

[0177] Accordingly, the accuracy of data analysis can be improved.

[0178] Description of Reference Numerals

[0179] 1: Defect notification system for single cells; 2: Commercial power system; 5: Network; 10: Battery analysis system; 11: Control unit; 12: Storage unit; 13: Communication unit; 20: Electric vehicle; 21: Combined battery 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: Acquisition unit; 112: First preprocessing unit; 113: Discrimination unit; 114: Second preprocessing unit; 115: Analysis unit; 121: Battery data holding unit.

Claims

1. A data analysis system, comprising: an analysis unit that analyzes time series data; a discrimination unit that discriminates whether each value included in the time series data is a measured value or a supplementary value; and a preprocessing unit that can switch whether to use the supplementary value for data analysis when the time series data includes a supplementary value.

2. The data analysis system according to claim 1, wherein the preprocessing unit deletes the supplementary value from the time series data.

3. The data analysis system according to claim 1 or 2, wherein when there is identification information indicating whether each value included in the time series data is a measured value or a supplementary value, the discrimination unit refers to the identification information to discriminate whether each value is a measured value or a supplementary value.

4. The data analysis system according to claim 1 or 2, wherein the discrimination unit detects a change pattern of the values included in the time series data to discriminate whether each value is a measured value or a supplementary value.

5. The data analysis system according to claim 4, wherein the discrimination unit discriminates the values in the interval where the same value continues or the values in the interval where the value changes linearly in the time series data as supplementary values.

6. The data analysis system according to claim 4, wherein when the value included in the time series data satisfies a specified condition, the discrimination unit performs discrimination processing on whether each value is a measured value or a supplementary value in the surrounding interval of the value.

7. The data analysis system according to claim 1, wherein the preprocessing unit switches whether to delete the supplementary value according to the content of the data analysis.

8. The data analysis system according to claim 1, wherein the analysis unit analyzes the time series data from which the supplementary value has not been deleted, when an abnormality is detected in the analysis result, the preprocessing unit deletes the supplementary value from the time series data, and the analysis unit re-analyzes the time series data after the supplementary value has been deleted.

9. The data analysis system according to claim 1, wherein time series data including a supplementary value and time series data not including the supplementary value are prepared, and the analysis unit distinguishes whether to use the time series data including the supplementary value or the time series data not including the supplementary value according to the content of the data analysis.

10. The data analysis system according to claim 1, wherein the time series data is battery data of a secondary battery including at least voltage.

11. The data analysis system according to claim 1, wherein it further comprises an acquisition unit that acquires voltage data of each parallel single-cell battery block of a battery pack obtained by connecting a plurality of parallel single-cell battery blocks in series, wherein the parallel single-cell battery block is obtained by connecting a plurality of single cells in parallel, and the analysis unit detects whether a single cell failure has occurred in the parallel single-cell battery block as an object based on the voltage change of a normal parallel single-cell battery block and the change of the voltage difference between the normal parallel single-cell battery block and the parallel single-cell battery block as an object.

12. The data analysis system according to claim 11, wherein When the voltage change of the normal parallel single-cell block is set as ΔV and the voltage change of the target parallel single-cell block is set as ΔVn, the analysis unit calculates |(ΔVn - ΔV)| / ΔV to calculate the voltage failure degree, and when the voltage failure degree is equal to or higher than the threshold value, the analysis unit determines that a single-cell failure has occurred in the target parallel single-cell block.

13. The data analysis system according to claim 11, wherein it includes a notification unit that sends the occurrence of the single-cell failure detected by the analysis unit.

14. The data analysis system according to claim 13, wherein it includes a display unit that displays the occurrence of the single-cell failure sent by the notification unit.

15. A defect notification system for a single cell, including the data analysis system according to claim 13, and including a display unit that displays the occurrence of the single-cell failure sent by the notification unit.

16. A data analysis method, performing the following processes: discriminating whether each value included in the time-series data is a measured value or a supplementary value; when the time-series data includes a supplementary value, switching whether to use the supplementary value for data analysis; and analyzing the time-series data.

17. A data analysis program that causes a computer to perform the following processes: discriminating whether each value included in the time-series data is a measured value or a supplementary value; when the time-series data includes a supplementary value, switching whether to use the supplementary value for data analysis; and analyzing the time-series data.

18. A non-transitory storage medium that stores the data analysis program according to claim 17.

19. The data analysis method according to claim 16, performing the following processes: Obtain voltage data of each parallel monomer battery block of a battery pack obtained by connecting multiple parallel monomer battery blocks in series, where the parallel single-cell block is obtained by connecting a plurality of single cells in parallel; detecting whether a single-cell failure has occurred in the target parallel single-cell block based on the voltage change of the normal parallel single-cell block and the change in the voltage difference between the normal parallel single-cell block and the target parallel single-cell block; sending the occurrence of the single-cell failure detected by the analysis unit; and displaying the occurrence of the sent single-cell failure.

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