WO2025013537A1 - Battery analysis system, battery analysis method, and battery analysis program - Google Patents

Abstract

A battery analysis system (10) according to an embodiment comprises a data acquisition unit (111), an invalid value determination unit (118), a correlation determination unit (119), and an invalid value removal unit (116). The data acquisition unit (111) acquires the time-series battery data of a battery pack (20) via a network (5). The invalid value determination unit (118) determines each of the invalid values of the measured values of a plurality of data types included in the battery data. The correlation determination unit (119) determines the synchronization rate of the occurrence of the invalid values of the measured values of the plurality of data types. The invalid value removal unit (116) removes the remaining measured values when one of the measured values of the plurality of data types at the same sampling time is an invalid value in the battery data of the battery pack (20) in which the synchronization rate is equal to or greater than a predetermined value.

Description

Battery analysis system, battery analysis method, and battery analysis program

This disclosure relates to a battery analysis system, a battery analysis method, and a battery analysis program for analyzing the state of a battery.

As the Internet of Things (IoT) of devices such as PCs (Personal Computers) and EVs (Electrified Vehicles) becomes more prevalent, battery analysis systems that store battery data from the battery packs installed in these devices in a cloud database and analyze the battery data are being put to practical use. There are several configurations for supplying power to the sensor system for measuring the battery voltage, current, and temperature: a direct connection from the battery, and a configuration that uses a regulator or a large-capacity capacitor in combination.

Patent document 1 discloses a configuration in which the battery and the sensor power supply are directly connected. In this configuration, if the timing of A/D (Analog-to-Digital) conversion of the analog sensor value overlaps with the start or stop of a data transmission IC (Integrated Circuit), which causes large load fluctuations, the error in the sensor value after A/D conversion will be large. In Patent document 1, the A/D converted sensor value is invalidated when the data transmission IC is started or stopped.

JP 2014-153901 A

If the configuration in which the battery and the power supply for the sensor system are directly connected is known, as described above, it is possible to remove invalid values at startup or shutdown when the load fluctuations are large. However, if the system configuration of the battery and the power supply for the sensor system is unknown, it is not possible to uniformly remove invalid values at startup or shutdown. For example, invalid values at startup or shutdown cannot be removed from battery data sent to the cloud database from a device with an unknown system configuration of the battery and the power supply for the sensor system, and unnatural temperature data and voltage data will be stored in the cloud database as valid data.

This disclosure provides technology that accurately removes invalid values from battery data that should be excluded from analysis.

A battery analysis system according to one aspect of the present disclosure includes an acquisition unit that acquires time-series battery data of a battery pack via a network, and an invalid value determination unit that determines invalid values of each of the measurement values of the multiple data types included in the battery data. The battery analysis system also includes a correlation determination unit that determines the synchronization rate of the occurrence of invalid values of the measurement values of the multiple data types, and a removal unit that removes the remaining measurement values when one of the measurement values of the multiple data types at the same sampling time is an invalid value in the battery data of a battery pack with a synchronization rate equal to or greater than a predetermined value.

In addition, any combination of the above components and conversions of the expressions of this disclosure between devices, systems, methods, computer programs, etc. are also valid aspects of this disclosure.

According to this disclosure, it is possible to accurately remove invalid values from battery data that should be excluded from analysis.

FIG. 1 is a diagram for explaining a battery analysis system according to an embodiment. FIG. 1 is a diagram showing a configuration of a battery pack system including a plurality of unit cells connected in series. FIG. 1 is a diagram showing a configuration of a battery pack system including a plurality of cell blocks connected in series. FIG. 4 is a diagram for explaining a flow of battery data from an electric vehicle to a battery analysis system. FIG. 1 is a diagram showing an example of destructive test data obtained by a nail penetration test. FIG. 11 is a diagram showing an example of temperature transition during natural cooling of a heated object. 5 is a flowchart for explaining a first removal process of an invalid value performed by the battery analysis system according to the embodiment. 11 is a flowchart for explaining a basic example of a second invalid value removal process performed by the battery analysis system according to the embodiment. 10 is a flowchart for explaining an advanced example of a second invalid value removal process performed by the battery analysis system according to the embodiment.

FIG. 1 is a diagram for explaining a battery analysis system 10 according to an embodiment. The battery analysis system 10 is a system for analyzing the state of a battery pack 20 mounted on an electric vehicle 1. In this embodiment, the battery analysis system 10 is constructed on a cloud server installed in a data center managed by a cloud service provider. A battery analysis service provider that provides an analysis service for the battery pack 20 mounted on an electric vehicle 1 uses the cloud server by entering into a contract with the cloud service provider. The battery analysis system 10 may be constructed on the battery analysis service provider's own server installed in its own facility or data center.

The battery pack 20 mounted on the electric vehicle 1 includes a battery pack system 21 that supplies power to a drive motor (not shown). The battery pack system 21 includes multiple single cells or multiple cell blocks connected in series.

FIG. 2A is a diagram showing the configuration of a battery pack system 21 including multiple unit cells E1-Em connected in series. FIG. 2B is a diagram showing the configuration of a battery pack system 21 including multiple cell blocks Eb1-Ebm connected in series. Each cell block Eb1-Ebm includes multiple unit cells E1a-E1n-Ema-Emn connected in parallel.

For example, lithium ion battery cells, nickel metal hydride battery cells, lead battery cells, etc. can be used for the single cells E1-Em and E1a to E1n-Ema to Emn. In the following description, an example is assumed in which lithium ion battery cells (nominal voltage: 3.6-3.7 V) are used as the single cells E1-Em and E1a to E1n-Ema to Emn. The number of single cells or cell blocks connected in series is determined according to the voltage of the drive motor. For example, when the number of series is large, the system configuration shown in FIG. 2A or FIG. 2B is treated as one unit of battery module, and multiple battery modules are connected in series to form the battery pack system 21.

The BMU (Battery Management Unit) 22 manages the state of the battery pack system 21. The BMU 22 monitors the cell voltage of the multiple single cells E1-Em or multiple cell blocks Eb1-Ebm, the current flowing through the battery pack 20, and the temperature at multiple observation points within the battery pack 20. The BMU 22 is composed of a power supply circuit 221 (see Figure 3), a voltage sensor 225 (see Figure 3), a current sensor, a temperature sensor 223 (see Figure 3), an analog front end, a microcontroller, a non-volatile memory, etc. The analog front end includes multiple semiconductor chips such as an amplifier, a multiplexer, an A/D converter, and a filter.

The power supply circuit 221 steps down the voltage of the battery pack system 21 to generate a power supply voltage (e.g., 3.3 to 5.0 V) to be supplied to the various semiconductor chips in the BMU 22. The power supply circuit 221 may be a linear regulator (e.g., a three-terminal regulator or an LDO (Low Drop Out) regulator), or a switching regulator. In general, linear regulators are cheaper and smaller, while switching regulators have lower losses.

The voltage sensor 225 detects the voltages across both ends (hereinafter referred to as cell voltages) of multiple single cells E1-Em or cell blocks Eb1-Ebm connected in series. The analog front end includes a multiplexer and an A/D converter that function as a voltage measurement circuit 226 (see FIG. 3). The multiplexer outputs each measured cell voltage to the A/D converter in a predetermined order. The A/D converter converts the analog cell voltages input from the multiplexer into digital cell voltage values. The voltage measurement circuit 226 transmits each cell voltage value converted into a digital value to the microcontroller.

A shunt resistor that functions as a current sensor is connected in series with the multiple single cells E1-Em or cell blocks Eb1-Ebm that are connected in series. Note that a Hall element may be used instead of the shunt resistor. The analog front end includes an amplifier that functions as a current measurement circuit and an A/D converter. The amplifier measures the value of the current flowing through the single cells E1-Em or cell blocks Eb1-Ebm that are connected in series based on the voltage across the shunt resistor. The A/D converter converts the analog current value input from the amplifier into a digital current value. The current measurement circuit transmits the current value converted into a digital value to the microcontroller.

Temperature sensors 223 are installed at multiple observation points of the battery pack system 21. For example, thermistors T1-Tm are used as the temperature sensors 223, and as shown in FIG. 2A or FIG. 2B, thermistors T1-Tm are installed at multiple points on the surface of the battery pack system 21. The analog front end includes an amplifier and an AD converter that function as the temperature measurement circuit 224 (see FIG. 3). The amplifier measures the temperatures of the multiple observation points based on multiple divided voltages between each thermistor T1-Tm and each voltage dividing resistor. The A/D converter converts the analog temperature value input from the amplifier into a digital temperature value. The temperature measurement circuit 224 transmits the multiple temperature values converted into digital values to the microcontroller.

The microcontroller acquires each monitored cell voltage, current, and temperature at a predetermined sampling period (e.g., 10 seconds, 30 seconds, or 1 minute) and stores them in non-volatile memory. To compress the amount of data stored, the BMU 22 may store only the maximum and minimum cell voltages among the cell voltages. To compress the amount of data stored, the BMU 22 may store only the maximum and minimum temperatures among the temperatures at multiple observation points.

The BMU 22 estimates the SOC (State of Charge) by combining the OCV (Open Circuit Voltage) method and the current integration method. The OCV method estimates the SOC based on the measured cell OCV and the cell's SOC-OCV curve. The cell's SOC-OCV curve is created in advance by the battery manufacturer based on characteristic tests and is registered in the BMU 22 at the time of shipment.

The current integration method is a method for estimating the SOC based on the OCV at the start of charging/discharging the cell and the integrated value of the measured current. With the current integration method, current measurement errors accumulate as the charging/discharging time becomes longer. Therefore, it is preferable to use a weighted average of the SOC estimated by the current integration method and the SOC estimated by the OCV method.

The BMU 22 converts the SOC of each single cell E1-Em or each cell block Eb1-Ebm into an actual capacity, combines these actual capacities to calculate the actual capacity of the battery pack 20, and can estimate the SOC of the battery pack 20 based on this actual capacity and the current full charge capacity of the battery pack 20.

The BMU 22 transmits battery data including each cell voltage or maximum and minimum cell voltages, current, each temperature or maximum and minimum temperatures, and SOC of the battery pack 20 to an ECU (Electronic Control Unit) (not shown) via an in-vehicle network. For example, a CAN (Controller Area Network) or a LIN (Local Interconnect Network) can be used as the in-vehicle network.

The communication unit 23 has a function of performing communication signal processing with the communication unit 33 of the charging stand 3, and a function of performing wireless signal processing for connecting to the network 5. The communication unit 23 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), DSRC (Dedicated Short Range Communications), etc.

Network 5 is a general term for communication paths such as the Internet, dedicated lines, and VPNs (Virtual Private Networks), and the communication medium and protocol can be any. For example, mobile phone networks, wireless LANs (Local Area Networks), wired LANs, optical fiber networks, ADSL (Asymmetric Digital Subscriber Line) networks, and CATV (Community Antenna TeleVision) networks can be used as communication media. For example, TCP (Transmission Control Protocol)/IP (Internet Protocol), UDP (User Datagram Protocol)/IP, Ethernet (registered trademark), etc. can be used as communication protocols.

The client system 4 is a system used by a transportation business operator who owns multiple electric vehicles 1 and operates a transportation business. In this embodiment, the transportation business operator who uses the client system 4 is the client who requests an analysis of the battery pack 20 from the battery analysis service operator. For example, if the transportation business operator is a delivery business operator who owns multiple electric vehicles 1 as delivery vehicles, the client system 4 is composed of a server and a terminal device (e.g., a PC) operated and managed by the delivery business operator.

By connecting the electric vehicle 1 to a terminal device installed at the delivery company's office via cable or wirelessly, the ECU of the electric vehicle 1 can transmit battery data to the delivery company's terminal device. The ECU of the electric vehicle 1 may transmit driving data including vehicle speed and accumulated mileage, in addition to battery data, to the terminal device. The delivery company's terminal device transmits battery data acquired from multiple electric vehicles 1 managed at the office to the delivery company's server. The delivery company's server transmits the battery data of multiple electric vehicles 1 collected from each office in a batch to the battery analysis system 10 via network 5. The battery data may also be transmitted directly from the terminal device at each office to the battery analysis system 10 via network 5.

The client system 4 transmits specification data of the electric vehicle 1 owned by the delivery company and specification data of the battery pack 20 installed in the electric vehicle 1 to the battery analysis system 10 via the network 5.

The ECU of the electric vehicle 1 is wirelessly connected to the network 5 and can transmit the battery data received from the BMU 22 directly to the battery analysis system 10. In this case, the ECU may transmit the data each time, or may store the data in an internal non-volatile memory and transmit the battery data stored in the non-volatile memory to the battery analysis system 10 all at once at a specified timing.

In addition, when the charging stand 3 is connected to the network 5, by connecting the electric vehicle 1 and the charging stand 3 with a charging cable, the ECU of the electric vehicle 1 can transmit the battery data stored in the non-volatile memory to the battery analysis system 10 in a batch via the charging stand 3 connected to the network 5.

When the electric vehicle 1 and the charging stand 3 are connected by a charging cable, the charging stand 3 can charge the battery pack 20 of the electric vehicle 1 with power supplied from the commercial power system 2. Generally, charging is performed with AC for normal charging and with DC for rapid charging. When charging with AC (e.g., single-phase 100/200V), the charging voltage or charging current is controlled by the charger in the electric vehicle 1. When charging with DC, the charging voltage or charging current is controlled by the power supply unit 31 of the charging stand 3. The power supply unit 31 includes a rectifier circuit, a filter, and a DC (Direct Current)/DC converter, and generates DC power by full-wave rectifying the AC power supplied from the commercial power system 2 with the rectifier circuit and smoothing it with a filter. The DC/DC converter controls the voltage or current of the generated DC power.

For example, CHAdeMO (registered trademark), ChaoJi, GB/T, and Combo (Combined Charging System) can be used as fast charging standards. CHAdeMO, ChaoJi, and GB/T use CAN as the communication method. Combo uses PLC (Power Line Communication) as the communication method.

A charging cable that uses the CAN method includes a communication line in addition to a power line. When the electric vehicle 1 and the charging stand 3 are connected with the charging cable, the ECU of the electric vehicle 1 establishes a communication channel with the control unit 32 of the charging stand 3. Note that in a charging cable that uses the PLC method, communication signals are transmitted superimposed on the power line.

The communication unit 33 of the charging stand 3 has a function of performing communication signal processing with the communication unit 23 of the electric vehicle 1, 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, a mobile phone network, etc.

The battery analysis system 10 includes a control unit 11, a memory unit 12, and a communication unit 13. The communication unit 13 is a communication interface (e.g., a Network Interface Card (NIC)) for connecting to the network 5 via a wired or wireless connection.

The control unit 11 includes a data acquisition unit 111, a data extraction unit 112, a power loss estimation unit 113, a heat capacity/thermal resistance estimation unit 114, a threshold setting unit 115, an invalid value removal unit 116, an evaluation/correction unit 117, an invalid value determination unit 118, and a correlation determination unit 119. The functions of the control unit 11 can be realized by a combination of hardware resources and software resources, or by hardware resources alone. As hardware resources, a CPU (Central Processing Unit), ROM (Read Only Memory), RAM (Random Access Memory), GPU (Graphics Processing Unit), ASIC (Application Specific Integrated Circuit), FPGA (Field Programmable Gate Array), and other LSIs (Large-Scale Integration) can be used. As software resources, an operating system, an application, and other programs can be used.

The memory unit 12 includes non-volatile recording media such as a HDD (Hard Disc Drive) and an SSD (Solid State Drive) and stores various data. The memory unit 12 includes a battery data retention unit 121, a vehicle and battery specification retention unit 122, and a test data retention unit 123. The data acquisition unit 111 receives time-series battery data of the battery pack 20 mounted on the electric vehicle 1 from the electric vehicle 1 via the client system 4. The data acquisition unit 111 may receive the battery data directly from the electric vehicle 1 or via the charging stand 3. The data acquisition unit 111 saves the received battery data in the battery data retention unit 121.

The data acquisition unit 111 receives specification data of the electric vehicle 1 held by the client and specification data of the battery pack 20 mounted on the electric vehicle 1 from the client system 4. The data acquisition unit 111 stores the received specification data of the electric vehicle 1 and the battery pack 20 in the vehicle and battery specification storage unit 122.

FIG. 3 is a diagram for explaining the flow of battery data from the electric vehicle 1 to the battery analysis system 10. The temperature data measured by the temperature sensor 223 and temperature measurement circuit 224 of the BMU 22 in the battery pack 20 mounted on the electric vehicle 1 includes valid and invalid values. Hereinafter, the temperature sensor 223 and temperature measurement circuit 224 are collectively referred to as the temperature measurement system. Valid values of the temperature data include normal and abnormal values. Abnormal values of the temperature data are values based on a temperature abnormality that has actually occurred in the battery pack 20. Invalid values of the temperature data are values that indicate an abnormality in the data itself that is not based on the occurrence of an actual abnormality, and include noise, missing values, and large errors from the normal value.

The voltage data measured by the voltage sensor 225 and voltage measurement circuit 226 of the BMU 22 includes valid values and invalid values. Valid values of the voltage data include normal values and abnormal values. Hereinafter, the voltage sensor 225 and voltage measurement circuit 226 are collectively referred to as the voltage measurement system. An abnormal value of the voltage data is a value based on an abnormality (overcharge value, overdischarge value) of the cell voltage that has actually occurred within the battery pack 20. An invalid value of the voltage data is a value that indicates an abnormality in the data itself that is not based on the occurrence of an actual abnormality, and includes noise, missing values, and large errors from the normal value.

The temperature data and voltage data sent from the electric vehicle 1 are collected by the client system 4 and stored in the database of the client system 4. If the client system 4 is equipped with a data interpolation function, the temperature data and voltage data in the missing sections are each interpolated. Due to the interpolation process, some invalid values of the temperature data or voltage data may become valid values. Note that incorrect interpolation may also result in noise.

The client system 4 transmits the temperature data and voltage data collected from the electric vehicle 1 to the battery analysis system 10 and requests an analysis of the battery pack 20. When analyzing the battery pack 20, the battery analysis system 10 removes invalid values that induce false detection before analyzing the battery pack 20. Although not shown in FIG. 3, the BMU 22 also measures current data, and the current data is also transmitted from the electric vehicle 1 to the client system 4 and from the client system 4 to the battery analysis system 10. The current data also includes valid and invalid values.

In this embodiment, the battery analysis service provider performs destructive tests (e.g., nail penetration tests on cells and fire tests on battery packs) in advance on available cells and battery packs, and collects residual heat data at the time of cell and battery pack destruction and, if possible, temperature changes. The battery analysis service provider includes the residual heat data at the time of cell destruction in a destructive test data log for each cell type and stores it in the test data storage unit 123. Each time a destructive test is performed, the destructive test data is accumulated in the test data storage unit 123, and the destructive test data stored in the test data storage unit 123 is continuously improved in accuracy. Note that, if destructive test data is available from the battery manufacturer, the destructive test data obtained from the battery manufacturer is stored in the test data storage unit 123.

The data extraction unit 112 of the battery analysis system 10 extracts residual heat data contained in the destructive test data of the cells contained in the battery pack 20 to be analyzed, which is stored in the test data storage unit 123. The data extraction unit 112 extracts specification data of the battery pack 20 to be analyzed, which is stored in the vehicle and battery specification storage unit 122.

The power loss estimation unit 113 estimates the power loss when the battery pack 20 is destroyed based on the specification data of the battery pack 20 being analyzed and the cell destruction test data. From the heat capacity formula, the temperature change characteristics of an object (heat source) can be described by the following (Equation 1).

T(t)-T(0)=(Rth×P(t))×(exp(-t/(Rth×Cth)))...(Formula 1)
T(t): Object temperature after t seconds [℃]
T(0): Initial temperature of the object [°C]
Rth: Thermal resistance [℃/W]
P: Power loss [W]
t: elapsed time [sec]
Cth: heat capacity [W・sec/℃]
FIG. 4 is a diagram showing an example of destructive test data obtained by a nail penetration test. The residual heat data obtained by the nail penetration test is obtained as a heat generation amount change curve per cell. The heat generation amount [W] at the time of nail penetration is suppressed after a certain time has passed. The power loss estimation unit 113 multiplies the heat generation amount per cell by the number of cells included in the specification data of the battery pack 20. In the case where the specification data of the battery pack 20 does not include the number of cells, if the specification data of the battery pack 20 includes the total capacity of the battery pack 20, the total capacity of the battery pack 20 and the number of cells can be calculated. The number of cells can be estimated from the type of the battery pack 20. The amount of heat generated by the battery pack 20 can also be directly estimated from destructive test data obtained by a fire spread test of the battery pack 20.

The data extraction unit 112 of the battery analysis system 10 extracts battery data (actual usage log) stored in the battery data storage unit 121. The heat capacity/thermal resistance estimation unit 114 estimates the thermal resistance and heat capacity of the battery pack 20 from the transition of temperature data after the end of charging/discharging contained in the extracted battery data, and the transition of temperature data and current data during charging contained in the extracted battery data.

From Newton's law of cooling, when an object with a uniform temperature is placed in a room, and the change in surface temperature is calculated using unsteady heat transfer, the temperature T(t) after t seconds can be expressed by the following (Equation 2).

T(t)=Ta+(T(0)-Ta)×(exp(-α・S/C・ρ・V)・t) ... (Formula 2)
Ta: Outside temperature T(0): Initial temperature of object [℃]
α: Thermal conductivity S: Surface area c: Specific heat of object ρ: Mass density of object V: Volume t: Elapsed time FIG. 5 is a diagram showing an example of temperature transition during natural cooling of a heated object. As shown in FIG. 5, the temperature transition of a heated object during natural cooling approximates a logarithmic curve.

The thermal resistance Rth of an object can be defined as the inverse of the product of the heat transfer coefficient α and the surface area S, as shown in the following (Equation 3).

Rth=1/(α・S)...(Formula 3)
The heat capacity Cth of an object can be defined as the product of the object's mass (ρ·V) and its specific heat c, as shown in the following (Equation 4).

Cth=c・ρ・V...(Formula 4)
The average temperature of the warmed battery pack 20 after charging and discharging approaches the outside air temperature over time, and after t seconds, the temperature T(t) of the battery pack 20 drops to the outside air temperature Ta. Therefore, the above formula (2) is expressed as follows: This can be transformed into (Equation 5).

T(t)=T(t)+(T(0)-T(t))×(exp(-t/(Rth×Cth)))...(Formula 5)
Taking into consideration the possibility that the time t required for the temperature to drop to the outside air temperature Ta is unknown due to a lack of data, or that the heat capacity Cth is large and does not become equal to the outside air temperature Ta, a non-steady equation is used.

The time t, temperature T(0) and temperature T(t) can be identified from the log of natural cooling in a non-energized state after charging and discharging, which is included in the battery data, so the heat capacity/thermal resistance estimation unit 114 can derive the thermal time constant (Rth x Cth), which is the product of the thermal resistance Rth and the thermal capacity Cth. In other words, by regarding the battery pack 20 as a single object, the thermal time constant (Rth x Cth) can be derived from the log of natural cooling after charging and discharging.

In addition, the temperature gradient of the battery pack 20 due to the shape and material of the battery pack 20 or the position of the temperature sensor 223 in the battery pack 20 can be identified by simulation, a correction coefficient for correcting the temperature gradient can be obtained, and the temperature data can be multiplied by the correction coefficient to improve the accuracy of the temperature data.

The amount of temperature change when the battery pack 20 is energized (when charging or discharging) can be calculated using the above formula (1). The power loss P of the battery pack 20 can be calculated using the internal resistance Rb and current value Ib of the battery pack 20 as shown in the following formula (6). Here, the power loss P during constant current charging is calculated. The internal resistance Rb of the battery pack 20 can be estimated from the relationship between the voltage data and current data when energized.

P=Rb×Ib^2 (Formula 6)
By substituting the thermal time constant (Rth·Cth) derived in the above (Equation 5) and the power loss P derived in the above (Equation 6) into the above (Equation 1), the thermal resistance Rth and the thermal capacity Cth are calculated as follows: In this way, two equations are established: one that represents the temperature change based on the log during natural cooling after charging and discharging, and the other that represents the temperature change based on the log during current flow. In addition, when a plurality of logs during natural cooling and logs during energization can be extracted from the battery data storage unit 121 for one battery pack 20, the thermal resistance Rth and the thermal capacity Cth can be derived. In this case, the thermal resistance Rth and the thermal capacity Cth can be derived with higher accuracy.

The heat capacity Cth of the battery pack 20 is determined by the weight m and specific heat c of the battery pack 20. In the case of a battery pack 20 whose specification data includes the weight m and specific heat c, the heat capacity/thermal resistance estimation unit 114 can estimate the heat capacity Cth of the battery pack 20 by multiplying the known weight m and specific heat c. In this case, the thermal resistance Rth and heat capacity Cth can be derived only from the log during natural cooling after charging and discharging.

In the above example, the thermal resistance Rth and thermal capacity Cth were derived from the log during constant current charging contained in the battery data. In this regard, when deriving the thermal resistance Rth and thermal capacity Cth from the log during discharge contained in the battery data, it is necessary to take into account fluctuations in the discharge current and thermal convection. For example, the thermal resistance Rth and thermal capacity Cth can be derived by correlating the thermal resistance Rth with the current value and vehicle speed.

In the above example, the thermal resistance Rth and the thermal capacity Cth were derived based on the battery data of one battery pack 20. In this regard, the thermal resistance Rth and the thermal capacity Cth may be derived based on the battery data of multiple battery packs 20 of the same model number mounted on multiple electric vehicles 1 of the same vehicle type. The battery analysis system 10 may derive the thermal resistance Rth and the thermal capacity Cth for each battery pack 20, and derive their average values as the final thermal resistance Rth and thermal capacity Cth. In this case, it is possible to derive the thermal resistance Rth and the thermal capacity Cth with higher accuracy.

The threshold setting unit 115 obtains an upper limit of the temperature change rate based on the thermal resistance Rth and heat capacity Cth of the battery pack 20 and the power loss P at the time of destruction, and sets the upper limit as a threshold for determining whether the temperature data is invalid. The temperature change rate is defined as the amount of temperature change per unit time. The temperature change transition at the time of ignition of the battery pack 20 can be estimated by substituting the amount of heat generated by the battery pack 20 at the time of destruction test based on the destruction test data into the power loss P in the above (Equation 1). The upper limit of the temperature change rate at the time of ignition can be said to be the theoretical upper limit of the temperature change rate, and can be used as a boundary value for determining whether the temperature data is abnormal or invalid. The upper limit of the temperature change rate at the time of ignition can be derived from the maximum value of the differential curve obtained by time-differentiating the temperature change curve at the time of ignition. Note that if the temperature transition of the cell or battery pack can be measured in advance by a destruction test, the temperature change transition at the time of ignition of the battery pack 20 estimated by the above (Equation 1) and the temperature transition measured in the destruction test can be used in combination to suppress estimation errors and measurement errors, thereby achieving even higher accuracy.

If specification data regarding the shape and material of the battery pack 20 or the position of the temperature sensor 223 inside the battery pack 20 can be obtained, these specifications can be taken into consideration to estimate the temperature change progression at the time of ignition with higher accuracy. Note that high accuracy is not essential since the purpose is to calculate the boundary value between abnormal values and invalid values.

The invalid value removal unit 116 removes temperature data with a temperature change rate exceeding the threshold as an invalid value. The temperature data included in the actual usage log may be the maximum temperature and the minimum temperature at multiple observation points in the battery pack 20 to be analyzed. In this case, the maximum temperature and the minimum temperature may be corrected taking into account the temperature gradient according to the position of the temperature sensor 223 where the maximum temperature was measured and the temperature gradient according to the position of the temperature sensor 223 where the minimum temperature was measured. Furthermore, the temperature data included in the actual usage log may be a representative temperature of multiple observation points in the battery pack 20. The representative temperature is defined, for example, as the average value, median value, or intermediate value between the maximum temperature and the minimum temperature of the temperatures measured at the multiple observation points.

The evaluation and correction unit 117 evaluates the threshold value based on the temperature change rate determined from the battery data when an abnormality occurs in the battery pack 20, and corrects the threshold value according to the evaluation result. For example, if the maximum value of the temperature change rate determined from the battery data when an abnormality occurs in the battery pack 20 exceeds the threshold value, the evaluation and correction unit 117 updates the threshold value to the maximum value of the temperature change rate.

If the battery pack 20 catches fire, it is possible that the temperature sensor 223 inside the battery pack 20 will malfunction, and only invalid values will remain in the actual use log. In that case, analysis by the battery analysis system 10 will be impossible. If the battery pack 20 catches fire, it is basically detected and verified by the on-site remote control system. Therefore, the main purpose of the battery analysis system 10 is to detect logs when a phenomenon that is a precursor to fire (for example, abnormal heat generation due to a micro-short circuit) occurs. However, logs at the time of fire may reach the battery analysis system 10.

The maximum temperature change rate identified from the abnormality log when a phenomenon that is a sign of fire occurs or when a fire actually occurs should not exceed the above threshold, which is the theoretical upper limit of the temperature change rate. If it exceeds the above threshold, it is assumed that there is a problem with the above threshold.

Therefore, when the maximum value of the temperature change rate identified from the abnormality occurrence log exceeds the threshold, the evaluation and correction unit 117 provisionally updates the threshold to the maximum value of the temperature change rate. When the threshold calculated the next time exceeds this provisional threshold, the evaluation and correction unit 117 updates the provisional threshold to the newly calculated threshold. By the time the next threshold is calculated, the destructive test will be performed again, and the measured power loss P at the time of destruction may be significantly different from the previous value. In addition, as the battery deteriorates, the power loss P may also differ significantly from the previous value. The evaluation and correction unit 117 may correct the provisional threshold taking into account the degree of deterioration of the battery. In this case, it is possible to address the above threshold problem caused by battery deterioration without waiting for the next threshold calculation.

FIG. 6 is a flowchart for explaining the first invalid value removal process performed by the battery analysis system 10 according to the embodiment. The data extraction unit 112 extracts residual heat data contained in the nail penetration test data of the battery pack 20 to be analyzed, which is stored in the test data storage unit 123. The power loss estimation unit 113 identifies the power loss per cell from the extracted residual heat data (step S10).

The data extraction unit 112 extracts the specification data of the battery pack 20 to be analyzed that is stored in the vehicle and battery specification storage unit 122. The power loss estimation unit 113 identifies the number of cells included in the extracted specification data (step S11). The power loss estimation unit 113 calculates the power loss when the battery pack 20 to be analyzed is destroyed based on the power loss per cell and the number of cells (step S12).

The data extraction unit 112 extracts the temperature data log during natural cooling after charging and discharging from the actual usage log of the battery pack 20 to be analyzed stored in the battery data storage unit 121 (step S13). The heat capacity/thermal resistance estimation unit 114 substitutes the temperature data log during natural cooling into the above (Equation 5) to calculate the thermal time constant (thermal resistance x heat capacity) of the battery pack 20 during natural cooling (step S14).

The data extraction unit 112 extracts a temperature data log during charging from the actual usage log of the battery pack 20 to be analyzed, stored in the battery data storage unit 121 (step S15). This temperature data log reflects heat generation due to charging. The heat capacity/thermal resistance estimation unit 114 substitutes the power loss during charging into the above (Equation 1) to calculate the thermal time constant (thermal resistance x heat capacity) of the battery pack 20 during charging. The heat capacity/thermal resistance estimation unit 114 calculates the thermal resistance and heat capacity of the battery pack 20 from the relationship between the above (Equation 5), the thermal time constant of the battery pack 20 during natural cooling, the above (Equation 1), and the thermal time constant of the battery pack 20 during charging (step S16). The threshold setting unit 115 sets the above threshold based on the power loss when the battery pack 20 is destroyed, and the thermal resistance and heat capacity of the battery pack 20 (step S17).

The data extraction unit 112 reads out the entire actual usage log of the battery pack 20 to be analyzed from the battery data storage unit 121. When an abnormality occurrence log is detected in the actual usage log, the evaluation and correction unit 117 evaluates the threshold value based on the temperature change rate identified from the abnormality occurrence log, and corrects the threshold value according to the evaluation result (step S18). The invalid value removal unit 116 removes, from the temperature data in the read actual usage log, temperature data whose temperature change rate exceeds the threshold value as an invalid value (step S19). The actual usage log from which the invalid values have been removed is stored in the battery data storage unit 121 as a log for abnormality analysis.

The processes from step S13 to step S19 are periodically executed. When the nail penetration test is performed again, the processes from step S10 to step S12 are executed. The threshold evaluation and correction process in step S18 can be omitted. The threshold evaluation and correction process in step S18 may be executed less frequently than the invalid value removal process in step S19.

The analysis unit (not shown) of the battery analysis system 10 reads the battery data of the abnormality analysis log from the battery data storage unit 121 and analyzes the battery pack 20. For example, the analysis unit estimates the SOC and SOH (State Of Health) of the battery pack 20, predicts the time to replace, and detects signs of abnormality. If driving data of the electric vehicle 1 equipped with the battery pack 20 to be analyzed has also been acquired, the analysis unit may predict the time to replace taking into account the driving data (e.g., accumulated driving distance, etc.).

The analysis unit transmits the analysis results of the battery pack 20 to the client system 4 via the network 5. The client can refer to the received analysis results of the battery pack 20 to determine the timing of replacing the electric vehicle 1, the market value of the electric vehicle 1, etc.

As described above, the first invalid value removal process makes it possible to accurately remove invalid values that should be excluded from analysis from the temperature data included in the battery data. Specifically, by setting the maximum value of the rate of temperature change at the time of destruction or abnormality as the threshold value for determining the boundary between abnormal values and invalid values, it is possible to leave the temperature data (abnormal values) when a phenomenon that is a sign of ignition occurs or when ignition actually occurs, and remove only invalid values such as noise. This makes it possible to perform analysis that includes data when an abnormality occurs.

Even if the weight of the battery pack 20 cannot be obtained from the catalog, the heat capacity and thermal resistance can be estimated by substituting the log during natural cooling and the log during current application into the respective equations and solving the simultaneous equations.

In the flowchart shown in FIG. 6, an example has been described in which the invalid value removal unit 116 of the battery analysis system 10 removes, as an invalid value, temperature data from the actual use log whose temperature change rate exceeds the above threshold. In this regard, the control unit 11 of the battery analysis system 10 may transmit the threshold set by the threshold setting unit 115 to the BMU 22 of the target battery pack 20 via the network 5. In that case, the BMU 22 removes, as an invalid value, temperature data from the temperature data measured by its own temperature measurement system whose temperature change rate exceeds the above threshold.

When the voltage measurement system and the temperature measurement system share the power supply circuit 221 as shown in FIG. 3, the power supply voltage of the voltage measurement system and the power supply voltage of the temperature measurement system are synchronized. Therefore, if the measured value of either the voltage or the temperature is an invalid value, it is possible to determine that the other measured value is also invalid. Since it is known to the BMU 22 in the battery pack 20 that the voltage measurement system and the temperature measurement system are operating on the same power supply system, the BMU 22 can determine that the validity/invalidity of the measured voltage value and the measured temperature value are synchronized.

On the other hand, in the case of a battery pack 20 in which the battery analysis system 10 is unable to grasp the power supply configuration of the BMU 22, the battery analysis system 10 is unable to determine whether the voltage measurement value and the temperature measurement value are synchronized in valid/invalid. Even if one measurement value is invalid, the battery analysis system 10 is unable to remove the other measurement value as an invalid value, and there is a risk of false detection due to an invalid measurement value. For example, during load fluctuations such as when the BMU 22 is started/stopped, the power supply voltage of the voltage measurement system and the power supply voltage of the temperature measurement system are unstable, and measurement errors for both voltage and temperature become large, but these cannot be removed as invalid values.

The data extraction unit 112 extracts battery data (actual usage log) of the battery pack 20 to be analyzed, which is stored in the battery data storage unit 121. The invalid value determination unit 118 determines whether each of the measurement values of the multiple data types contained in the extracted battery data is invalid.

Of the multiple data types, an upper limit voltage and a lower limit voltage are set for the voltage value. The upper limit voltage is a threshold for determining whether a cell has been overcharged, and the lower limit voltage is a threshold for determining whether a cell has been overdischarged. In a typical battery pack 20, the protection circuit in the BMU 22 performs control to stop charging and discharging when the voltage value of any cell exceeds the overcharge threshold or falls below the overdischarge threshold. Therefore, voltage data should essentially be within the range between the upper limit voltage and the lower limit voltage, and the invalid value determination unit 118 determines that voltage data that deviates from the range between the upper limit voltage and the lower limit voltage is an invalid value.

As described above, for temperature values among the multiple data types, the maximum value of the temperature change rate is set as the threshold value. Because temperature is not a physical quantity that changes instantaneously like voltage, there is naturally an upper limit to the temperature change rate. The invalid value determination unit 118 determines that temperature data whose temperature change rate exceeds the threshold value is an invalid value. Note that unless there are special circumstances, such as cooling the battery pack 20 from outside with a special cooler, extremely low temperature data such as -100°C cannot be generated. The invalid value determination unit 118 determines that temperature data below the set lower limit temperature is an invalid value. There is also an upper limit to the temperature at the time of ignition, and the invalid value determination unit 118 determines that temperature data above the set upper limit temperature is an invalid value.

Of the multiple data types, an overcurrent threshold for charging and an overcurrent threshold for discharging are set for the current value. In a typical battery pack 20, the protection circuit in the BMU 22 performs control to stop charging and discharging when the absolute value of the charging current exceeds the overcurrent threshold for charging, or when the absolute value of the discharging current exceeds the overcurrent threshold for discharging. Therefore, the absolute value of the current data should essentially be within the range of the overcurrent threshold for charging and the overcurrent threshold for discharging, and the invalid value determination unit 118 determines that current data that deviates from the range of the overcurrent threshold for charging and the overcurrent threshold for discharging is an invalid value.

The correlation determination unit 119 determines the synchronization rate of invalid value occurrence for measurement values of multiple data types. For example, the correlation determination unit 119 determines the synchronization rate of invalid value occurrence for voltage measurement values and temperature measurement values. If the invalid values of voltage measurement values and temperature measurement values are synchronized, it can be assumed that the battery pack system 21 is configured such that the power supplies of the voltage measurement system and the temperature measurement system are directly connected, or that the voltage measurement system and the temperature measurement system use a common power supply circuit 221. The correlation determination unit 119 may also determine the synchronization rate of invalid value occurrence for voltage measurement values, temperature measurement values, and current measurement values.

The correlation determination unit 119 calculates, for example, the synchronization rate as the ratio of the number of samples in which all measurement values of multiple data types at the same sampling time in a specified period are invalid to the number of samples in which some of the measurement values are invalid (see formula 7).

Synchronization rate = all invalid values / some invalid values (Equation 7)
If the synchronization rate of the measurement values of multiple data types is a predetermined value (e.g., 0.8) or greater, the correlation determination unit 119 determines that the battery pack 20 employs a BMU 22 in which the measurement values of multiple data types are synchronized, and if the synchronization rate is less than the predetermined value, it determines that the battery pack 20 employs a BMU 22 in which the measurement values of multiple data types are not synchronized.

When determining whether the voltage measurement value and the temperature measurement value are synchronized, the correlation determination unit 119 calculates the synchronization rate as the ratio of the number of samples in which both the voltage measurement value and the temperature measurement value at the same sampling time in a specified period are invalid values to the number of samples in which one of the voltage measurement values is invalid (see formula 8).

Synchronization rate=(both the voltage measurement value and the temperature measurement value are invalid)/(one of the voltage measurement value and the temperature measurement value is invalid) (Equation 8)
If the synchronization rate of the voltage measurement value and the temperature measurement value is a predetermined value (e.g., 0.8) or greater, the correlation determination unit 119 determines that the battery pack 20 employs a BMU 22 in which the voltage measurement value and the temperature measurement value are synchronized, and if the synchronization rate is less than the predetermined value, it determines that the battery pack 20 employs a BMU 22 in which the voltage measurement value and the temperature measurement value are not synchronized.

If, in the battery data of a battery pack 20 whose synchronization rate is equal to or greater than a predetermined value, one of the measurement values of multiple data types at the same sampling time is an invalid value, the invalid value removal unit 116 also removes the remaining measurement value even if the remaining measurement value is other than an invalid value (normal value or abnormal value). In the case of a battery pack 20 that employs a BMU 22 in which the voltage measurement value and the temperature measurement value are synchronized, the invalid value removal unit 116 also removes the other measurement value if one of the voltage measurement value and the temperature measurement value at the same sampling time is an invalid value, even if the other measurement value is other than an invalid value.

The correlation determination unit 119 considers that the measurement values of multiple data types are correlated for a battery pack 20 known to share a power source between the voltage measurement system and the temperature measurement system. For a battery pack 20 that is considered to share a power source, if one of the voltage measurement value and the temperature measurement value at the same sampling time is an invalid value, the invalid value removal unit 116 removes the other measurement value even if the other measurement value is not an invalid value. Note that the correlation determination unit 119 may always set the synchronization rate to 1.0 for a battery pack 20 known to share a power source between the voltage measurement system and the temperature measurement system.

The correlation determination unit 119 considers that the measurement values of multiple data types are not correlated for a battery pack 20 known to have a voltage measurement system and a temperature measurement system that do not share a common power source. The invalid value removal unit 116 removes invalid values from the voltage measurement value and the temperature measurement value independently. Note that the correlation determination unit 119 may always set the synchronization rate to 0.0 for a battery pack 20 known to have a voltage measurement system and a temperature measurement system that do not share a common power source.

If the specification data of the battery pack 20 stored in the vehicle/battery specification storage unit 122 includes information on the power supply configuration of the voltage measurement system and the temperature measurement system as design information for the BMU 22, the correlation determination unit 119 can determine whether the power supply of the voltage measurement system and the temperature measurement system is shared.

FIG. 7 is a flowchart for explaining a basic example of the second invalid value removal process performed by the battery analysis system 10 according to the embodiment. The data extraction unit 112 extracts voltage data from the actual usage log of the battery pack 20 to be analyzed, which is stored in the battery data storage unit 121. The invalid value removal unit 116 extracts invalid values from the voltage data (step S20). The data extraction unit 112 extracts temperature data from the actual usage log. The invalid value removal unit 116 extracts invalid values from the temperature data (step S21).

The correlation determination unit 119 calculates the synchronization rate of invalid value occurrence for the voltage measurement value and the temperature measurement value for the target period (step S23). The battery data for the target period must contain a predetermined number (e.g., 10 times) or more of invalid values in at least one of the voltage measurement value or the temperature measurement value. If the battery data for the target period does not contain a predetermined number or more of invalid values, the correlation determination unit 119 does not calculate the synchronization rate for the battery data for that target period. The correlation determination unit 119 calculates the synchronization rate for battery data for a different target period.

For battery packs 20 with a synchronization rate equal to or greater than a predetermined value (Y in step S24), if either the voltage measurement value or the temperature measurement value at the same sampling time is invalid, the invalid value removal unit 116 also removes the other measurement value (step S25). For battery packs 20 with a synchronization rate less than a predetermined value (N in step S24), the invalid value removal unit 116 independently removes the invalid voltage measurement value and the invalid temperature measurement value (step S26). The actual usage log from which the invalid values have been removed is stored in the battery data storage unit 121 as a log for abnormality analysis.

FIG. 8 is a flowchart for explaining an advanced example of the second invalid value removal process by the battery analysis system 10 according to the embodiment. The invalid value removal unit 116 extracts invalid values from the voltage data (step S20). The invalid value removal unit 116 extracts invalid values from the temperature data (step S21). The data extraction unit 112 extracts specification data of the battery pack 20 to be analyzed that is stored in the vehicle and battery specification storage unit 122 (step S22a). The correlation determination unit 119 determines whether or not the specification data includes design information of the BMU 22 (step S22b). If the design information of the BMU 22 is not included (N in step S22b), the process proceeds to step S23.

If the design information of the BMU 22 is included (Y in step S22b), the correlation determination unit 119 determines whether or not the voltage measurement system and the temperature measurement system share a power supply based on the design information of the BMU 22 (step S22c). If the power supply is shared (Y in step S22c), the process proceeds to step S25. If the power supply is not shared (N in step S22c), the process proceeds to step S26. The processing in steps S23-S26 is the same as the basic processing shown in the flowchart of FIG. 7.

As described above, the second invalid value removal process can accurately remove invalid values that should be excluded from the analysis from the battery data. Specifically, for battery data of a battery pack 20 in which the voltage measurement system and the temperature measurement system share a common power source, if one of the voltage measurement value and the temperature measurement value at the same sampling time is an invalid value, the other measurement value is also determined to be an invalid value. Due to a missynchronization of the sampling timing of the voltage and temperature, it is possible that one measurement value is not determined as an invalid value when both measurement values should be determined as invalid values. In such cases, since the data was measured in the same power supply environment, the reliability of the measurement value that was not determined as an invalid value can be said to be low. In this embodiment, the measurement value that was not determined as an invalid value can also be removed as an invalid value, so that data with low reliability can be excluded from the analysis target, and the analysis accuracy can be improved.

The present disclosure has been described above based on the embodiments. The embodiments are merely examples, and it will be understood by those skilled in the art that various modifications are possible in the combination of each component and each processing process, and that such modifications are also within the scope of the present disclosure.

The first and second removal processes described above may be performed during the same maintenance session, or may be performed independently during different maintenance sessions.

In addition, information identifying whether the battery pack 20 is started or stopped may be added to the battery data, and the second removal process may be performed on the battery data when the battery pack 20 is started or stopped. In this case, by narrowing down the battery data used to determine the synchronization rate to the battery data when the battery pack 20 is started or stopped, it is possible to estimate with higher accuracy whether the voltage measurement system and the temperature measurement system share a common power source, and to suppress erroneous detection.

Furthermore, the device in which the battery pack 20 is mounted is not limited to the electric vehicle 1. Devices in which the battery pack 20 is mounted include electric vehicles such as low-speed electric vehicles (golf carts, land cars, etc.), electric ships, railroad cars, and multicopters (drones), stationary power storage systems, and consumer electronic devices (notebook PCs, smartphones).

The embodiment may be specified by the following items:

[Item 1]
The battery analysis system (10) of item 1 includes an acquisition unit (111) that acquires time-series battery data of a battery pack (20) via a network (5), and an invalid value determination unit (118) that determines invalid values of measurement values of multiple data types included in the battery data. The battery analysis system (10) of item 1 also includes a correlation determination unit (119) that determines a synchronization rate of occurrence of invalid values of measurement values of multiple data types. The battery analysis system (10) of item 1 also includes a removal unit (116) that removes the remaining measurement values when one of the measurement values of multiple data types at the same sampling time is an invalid value in battery data of a battery pack (20) whose synchronization rate is equal to or greater than a predetermined value.

This allows invalid values to be accurately removed from the battery data.

[Item 2]
In a battery analysis system (10) of item 2, in the battery analysis system (10) according to item 1, the measurement values of the multiple data types are voltage measurement values and temperature measurement values.

This allows invalid values to be accurately removed from the voltage and temperature data.

[Item 3]
In the battery analysis system (10) of item 3, in the battery analysis system (10) described in item 1, the correlation determination unit (119) considers that the measurement values of the multiple data types are correlated for a battery pack (20) known to share a power source for a voltage measurement system and a temperature measurement system. If one of the measurement values of the multiple data types at the same sampling time in the battery data of the battery pack (20) considered to have the measurement values of the multiple data types correlated is an invalid value, the removal unit (116) also removes the remaining measurement values.

As a result, for a battery pack (20) where it is known that the voltage measurement system and the temperature measurement system share a common power source, it is possible to omit the calculation of the synchronization rate of occurrence of invalid values for voltage data and temperature data.

[Item 4]
The battery analysis system (10) of item 4 is the battery analysis system (10) according to item 1, further comprising a first estimation unit (113) for estimating the power loss at the time of destruction of the battery pack (20) based on the cell test data obtained from a previous destruction test of the cells included in the battery pack (20) and the specifications of the battery pack (20). The battery analysis system (10) of item 4 further comprises a second estimation unit (114) for estimating the thermal resistance and heat capacity of the battery pack (20) from the transition of the temperature data after the end of charging and discharging included in the battery data and the transition of the temperature data and current data during charging included in the battery data. The battery analysis system (10) of item 4 further comprises a threshold setting unit (115) for determining the upper limit of the temperature change rate based on the thermal resistance and heat capacity of the battery pack (20) and the power loss at the time of destruction, and setting the upper limit as a threshold for determining the invalid value of the temperature data. The removal unit (116) removes the temperature data with a temperature change rate exceeding the threshold.

This makes it possible to accurately remove invalid temperature data values from the battery data.

[Item 5]
In the battery analysis system (10) of item 5, in the battery analysis system (10) according to item 1, the battery data includes identification information for when the battery pack (20) was started or stopped. The correlation determination unit (119) determines a synchronization rate of occurrence of invalid values for multiple data types at the time of start-up or stop. If one of the measurement values of the multiple data types at the time of start-up or stop is an invalid value, the removal unit (116) also removes the remaining measurement values.

This allows the power supply configuration of multiple measurement systems to be estimated with high accuracy, and erroneous detections can be suppressed.

[Item 6]
The battery analysis method of item 6 includes a step of acquiring time-series battery data of a battery pack (20) via a network (5) and a step of determining invalid values of measurement values of a plurality of data types included in the battery data. The battery analysis method of item 6 also includes a step of determining a synchronization rate of occurrence of invalid values of measurement values of a plurality of data types. The battery analysis method of item 6 also includes a step of removing the remaining measurement values when one of the measurement values of a plurality of data types at the same sampling time is an invalid value in battery data of a battery pack (20) having a synchronization rate equal to or greater than a predetermined value.

This allows invalid values to be accurately removed from the battery data.

[Item 7]
The battery analysis program of item 7 causes a computer to execute a process of acquiring time-series battery data of a battery pack (20) via a network (5) and a process of determining invalid values of each of a plurality of data types included in the battery data. The battery analysis program of item 7 also causes a computer to execute a process of determining a synchronization rate of occurrence of invalid values of the measurement values of the plurality of data types. The battery analysis program of item 7 also causes a computer to execute a process of removing the remaining measurement values when one of the measurement values of the plurality of data types at the same sampling time is an invalid value in the battery data of a battery pack (20) whose synchronization rate is equal to or greater than a predetermined value.

This allows invalid values to be accurately removed from the battery data.

REFERENCE SIGNS LIST 1 Electric vehicle 2 Commercial power system 3 Charging station 4 Client system 5 Network 10 Battery analysis system 11 Control unit 12 Storage unit 13 Communication unit 20 Battery pack 21 Assembled battery system 22 BMU
23 Communication unit 31 Power supply unit 32 Control unit 33 Communication unit 111 Data acquisition unit (acquisition unit)
112 Data extraction unit 113 Power loss estimation unit (first estimation unit)
114 Heat capacity/thermal resistance estimation section (second estimation section)
115 Threshold setting unit 116 Invalid value removal unit (removal unit)
117 Evaluation/correction unit 118 Invalid value determination unit 119 Correlation determination unit 121 Battery data storage unit 122 Vehicle/battery specification storage unit 123 Test data storage unit 221 Power supply circuit 223 Temperature sensor 224 Temperature measurement circuit 225 Voltage sensor 226 Voltage measurement circuit

Claims (7)

an acquisition unit that acquires time-series battery data of the battery pack via a network;
an invalid value determination unit that determines whether each of a plurality of data types included in the battery data is an invalid value;
a correlation determination unit that determines a synchronization rate of occurrence of invalid values of the measurement values of the plurality of data types;
a removal unit that, when one of the measurement values of a plurality of data types at the same sampling time is an invalid value in the battery data of the battery pack having a synchronization rate equal to or higher than a predetermined value, also removes the remaining measurement values;
A battery analysis system comprising: The battery analysis system according to claim 1, wherein the measurement values of the multiple data types are voltage measurement values and temperature measurement values. the correlation determination unit determines that the measurement values of the plurality of data types are correlated with each other for a battery pack that is known to share a power source between a voltage measurement system and a temperature measurement system,
2. The battery analysis system according to claim 1, wherein when one of the measurement values of the plurality of data types at the same sampling time in the battery data of a battery pack in which the measurement values of the plurality of data types are deemed to be correlated is an invalid value, the removal unit also removes the remaining measurement values. a first estimation unit that estimates a power loss upon breakdown of the battery pack based on test data of the cells obtained from a previous destructive test of the cells included in the battery pack and specifications of the battery pack;
a second estimation unit that estimates a thermal resistance and a thermal capacity of the battery pack from a transition of temperature data after the end of charging/discharging, which is included in the battery data, and a transition of temperature data and current data during charging, which are included in the battery data;
a threshold setting unit that determines an upper limit of a temperature change rate based on the thermal resistance and the heat capacity of the battery pack and the power loss at the time of destruction, and sets the upper limit as a threshold for determining an invalid value of temperature data;
The battery analysis system according to claim 1 , wherein the removal unit removes temperature data having a temperature change rate exceeding the threshold value. The battery data includes identification information for when the battery pack is started or stopped,
The correlation determination unit determines a synchronization rate of occurrence of invalid values of a plurality of data types at the time of the start-up or the time of the stoppage,
The battery analysis system according to claim 1 , wherein when one of the measurement values of the plurality of data types at the time of the start-up or the time of the stop is an invalid value, the removal unit also removes the remaining measurement values. acquiring time-series battery data of the battery pack via a network;
determining whether each of a plurality of data types included in the battery data is an invalid value;
determining a synchronization rate of occurrence of invalid values of the measurement values of the plurality of data types;
removing the remaining measurement values when one of the measurement values of a plurality of data types at the same sampling time is an invalid value in the battery data of the battery pack having a synchronization rate equal to or higher than a predetermined value;
The battery analysis method includes the steps of: A process of acquiring time-series battery data of the battery pack via a network;
A process of determining whether each of measurement values of a plurality of data types included in the battery data is invalid;
A process of determining a synchronization rate of occurrence of invalid values of the measurement values of the plurality of data types;
a process of removing the remaining measurement values when one of the measurement values of a plurality of data types at the same sampling time is an invalid value in the battery data of the battery pack having a synchronization rate equal to or higher than a predetermined value;
A battery analysis program that causes a computer to execute the following:

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