Calculation system, battery characteristic estimation method, and battery characteristic estimation program

Abstract

In a calculation system (1), a data acquiring unit (111) acquires the operation data of a battery including at least voltages, currents, and states of charge (SOCs) at a plurality of times, which are measured by a management device for managing the battery, said SOCs being estimated on the basis of at least one of the voltages and the currents. An extraction unit (112) extracts, as sample data, a combination of SOC and voltage in a period in which a battery specified on the basis of the currents is regarded to be in a resting state from the combinations of the SOCs and the voltages at the plurality of times included in the operation data. An estimation unit (113) estimates the SOC-open circuit voltage (OCV) characteristic of the battery on the basis of the extracted sample data.

Description

Technical Field

[0001] The present disclosure relates to an arithmetic system for estimating characteristics of cells such as lithium - ion batteries, a battery characteristic estimation method, and a battery characteristic estimation program.

Background Art

[0002] In recent years, hybrid vehicles (HV), plug - in hybrid vehicles (PHV), and electric vehicles (EV) have become widespread. As a key device for these electric vehicles, secondary batteries such as lithium - ion batteries are installed. For secondary batteries installed in electric vehicles, it is important to accurately obtain the full charge capacity (FCC). If the FCC can be accurately obtained, the state of health (SOH) can be accurately estimated, and the remaining cruising distance of the electric vehicle, the replacement time of the secondary battery installed in the electric vehicle, and the reuse value at the time of replacement can be accurately predicted.

[0003] Generally, the FCC is calculated based on the SOC - OCV characteristic (SOC - OCV curve) that defines the relationship between the open - circuit voltage (OCV) and the state of charge (SOC), two points of OCV, and the integrated current amount between the two points of OCV.

[0004] There are a wide variety of vehicle types in electric vehicles, and a wide variety of secondary batteries are used. To accurately estimate the FCC of a wide variety of secondary batteries, it is necessary to obtain the SOC - OCV curves of all these types of secondary batteries.

[0005] Business operators such as delivery companies, taxi companies, and car - rental companies that operate using a wide variety of electric vehicles need to accurately grasp the FCC and SOH of the secondary batteries of the multiple electric vehicles they own for business reasons. However, many electric vehicles are not designed to output the SOC - OCV curve, FCC, and SOH externally, making it difficult for business operators to easily grasp the FCC and SOH of the secondary batteries of the multiple electric vehicles they own.

[0006] It is time-consuming and costly for an operator to collect operation data of various secondary batteries and create an in-house SOC-OCV curve for each secondary battery, which is not realistic. Also, even for a battery manufacturer, it is costly to collect operation data of secondary batteries of other companies through acceleration tests of electric vehicles or the like.

[0007] As a related technique, a method has been proposed in which an OCV-full charge capacity characteristic that defines the relationship between OCV and full charge capacity is held in a table for each SOC, and the full charge capacity at a certain SOC is estimated by referring to the OCV-full charge capacity characteristic at that SOC (see, for example, Patent Document 1). Also, a method has been proposed in which an SOC-OCV curve is corrected according to characteristic deterioration (see, for example, Patent Document 2). Both methods require a base SOC-OCV curve, and it is costly to obtain the SOC-OCV curve.

Prior Art Documents

Patent Documents

[0008]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0009] The present disclosure has been made in view of such circumstances, and an object thereof is to provide a technique capable of obtaining battery characteristics at low cost.

Means for Solving the Problems

[0010] To solve the above problems, an arithmetic system according to an aspect of the present disclosure includes a data acquisition unit that acquires operation data of the battery including at least voltages and currents at a plurality of times measured by a management device that manages the battery, and an SOC estimated based on at least one of the voltage and the current; an extraction unit that extracts, as sample data, a set of an SOC and a voltage during a period in which the battery can be regarded as being in a rest state, the set of the SOC and the voltage being specified based on the current, from a set of the SOC and the voltage at a plurality of times included in the operation data; and an estimation unit that estimates an SOC-OCV characteristic of the battery based on the extracted sample data.

[0011] In addition, any combination of the above components, and those obtained by converting the expressions of the present disclosure among methods, apparatuses, systems, computer programs, etc. are also effective as aspects of the present disclosure.

Advantages of the Invention

[0012] According to the present disclosure, the characteristics of the battery can be acquired at low cost.

Brief Description of the Drawings

[0013]

Figure 1

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[0014] FIG. 1 is a diagram for explaining an arithmetic system 1 used by a plurality of operator systems 2 according to an embodiment. A plurality of operators A and B each own a plurality of electric vehicles 3 and conduct business by utilizing the plurality of electric vehicles 3. For example, each operator conducts a delivery business (home delivery business), a taxi business, a car rental business, or a car sharing business by utilizing a plurality of electric vehicles 3. In the present embodiment, a pure EV not equipped with an engine is assumed as the electric vehicle 3. Also in the present embodiment, it is assumed that each operator owns electric vehicles 3 of a plurality of vehicle types.

[0015] Each of the operators A and B is provided with an operator system 2. The operator system 2 is a system for managing the operations of each of the operators A and B. The operator system 2 is composed of one or a plurality of information processing apparatuses (for example, a server, a PC). Part or all of the information processing apparatuses constituting the operator system 2 may exist in a data center. For example, it may be composed of a combination of a server (a company server, a cloud server, or a rental server) in the data center and a client PC within the operator.

[0016] The computing system 1 is composed of one or more information processing devices installed in a data center. The business system 2 can access the computing system 1 via the network 5. The network 5 is a general term for communication channels such as the Internet and dedicated lines, and its communication medium and protocol are not limited.

[0017] When multiple electric vehicles 3 are on standby, they are parked in the parking lots or garages of the business premises of each business operator A and B. The multiple electric vehicles 3 have a wireless communication function and can communicate wirelessly with the business system 2. The multiple electric vehicles 3 transmit driving data including the operation data of the secondary batteries they are equipped with to the business system 2. When the electric vehicle 3 is in motion, it may wirelessly transmit the driving data to the server constituting the business system 2 via the network 5. For example, the driving data may be transmitted each time at a frequency of once every 10 seconds. Also, the driving data for one day may be transmitted in batch at a predetermined timing once a day (for example, at the end of business hours).

[0018] In addition, when the business system 2 is composed of the company's own server or PC installed in the business premises, after the electric vehicle 3 returns to the business premises after the end of business, it may transmit the driving data for one day to the company's own server or PC. In that case, it may be transmitted wirelessly to the company's own server or PC, or it may be connected to the company's own server or PC by wire and transmitted via wire. Also, the data may be transmitted to the company's own server or PC via the recording medium on which the driving data is recorded. In addition, when the business system 2 is composed of a combination of a cloud server and a client PC within the business operator, the electric vehicle 3 may transmit the driving data to the cloud server via the client PC within the business operator.

[0019] FIG. 2 is a diagram for explaining the detailed configuration of a battery system 40 mounted on an electric vehicle 3. The battery system 40 is connected to a motor 34 via a first relay RY1 and an inverter 35. During power running, the inverter 35 converts the DC power supplied from the battery system 40 into AC power and supplies it to the motor 34. During regeneration, the inverter 35 converts the AC power supplied from the motor 34 into DC power and supplies it to the battery system 40. The motor 34 is a three-phase AC motor and rotates according to the AC power supplied from the inverter 35 during power running. During regeneration, the rotational energy due to deceleration is converted into AC power and supplied to the inverter 35.

[0020] The first relay RY1 is a contactor inserted between the wirings connecting the battery system 40 and the inverter 35. During running, the vehicle control unit 30 controls the first relay RY1 to be in the on state (closed state) and electrically connects the battery system 40 and the power system of the electric vehicle 3. During non-running, the vehicle control unit 30 generally controls the first relay RY1 to be in the off state (open state) and electrically disconnects the battery system 40 and the power system of the electric vehicle 3. Note that other types of switches such as semiconductor switches may be used instead of the relay.

[0021] The battery system 40 can be charged from the commercial power system 9 by connecting it to a charger 4 installed outside the electric vehicle 3 with a charging cable 38. The charger 4 is connected to the commercial power system 9 and charges the battery system 40 in the electric vehicle 3 via the charging cable 38. In the electric vehicle 3, a second relay RY2 is inserted between the wirings connecting the battery system 40 and the charger 4. Note that other types of switches such as semiconductor switches may be used instead of the relay. The management unit 42 of the battery system 40 controls the second relay RY2 to be in the on state (closed state) before the start of charging and in the off state (open state) after the end of charging.

[0022] Generally, in the case of normal charging, it is charged with AC, and in the case of rapid charging, it is charged with DC. When charged with AC, the AC power is converted into DC power by an AC / DC converter (not shown) inserted between the second relay RY2 and the battery system 40.

[0023] The battery system 40 includes a battery module 41 and a management unit 42. The battery module 41 includes a plurality of cells E1-En connected in series. Note that the battery module 41 may be configured by connecting a plurality of battery modules in series / series-parallel. As the cell, a lithium-ion battery cell, a nickel-metal hydride battery cell, a lead battery cell, etc. can be used. Hereinafter, an example using a lithium-ion battery cell (nominal voltage: 3.6 - 3.7V) is assumed in this specification. The number of cells in series of E1-En is determined according to the drive voltage of the motor 34.

[0024] A shunt resistor Rs is connected in series with the plurality of cells E1-En. The shunt resistor Rs functions as a current detection element. Note that a Hall element may be used instead of the shunt resistor Rs. Also, a plurality of temperature sensors T1, T2 for detecting the temperatures of the plurality of cells E1-En are installed in the battery module 41. One temperature sensor may be installed in the battery module, or one temperature sensor may be installed for each of the plurality of cells. For example, a thermistor can be used for the temperature sensors T1, T2.

[0025] The management unit 42 includes a voltage measurement unit 43, a temperature measurement unit 44, a current measurement unit 45, and a battery control unit 46. The voltage measurement unit 43 is connected to each node of the plurality of cells E1-En connected in series by a plurality of voltage lines. The voltage measurement unit 43 measures the voltage of each cell E1-En by measuring the voltage between two adjacent voltage lines respectively. The voltage measurement unit 43 transmits the measured voltage of each cell E1-En to the battery control unit 46.

[0026] Since the voltage measurement unit 43 has a high voltage with respect to the battery control unit 46, the voltage measurement unit 43 and the battery control unit 46 are insulated from each other and connected by a communication line. The voltage measurement unit 43 can be composed of an ASIC (Application Specific Integrated Circuit) or a general-purpose analog front-end IC. The voltage measurement unit 43 includes a multiplexer and an A / D converter. The multiplexer outputs the voltages between two adjacent voltage lines to the A / D converter in order from the top. The A / D converter converts the analog voltage input from the multiplexer into a digital value.

[0027] The temperature measurement unit 44 includes a voltage-dividing resistor and an A / D converter. The A / D converter sequentially converts a plurality of analog voltages divided by a plurality of temperature sensors T1, T2 and a plurality of voltage-dividing resistors into digital values and outputs them to the battery control unit 46. The battery control unit 46 estimates the temperatures of the plurality of cells E1-En based on the digital values. For example, the battery control unit 46 estimates the temperatures of the respective cells E1-En based on the values measured by the temperature sensors closest to the respective cells E1-En.

[0028] The current measurement unit 45 includes a differential amplifier and an A / D converter. The differential amplifier amplifies the voltage across the shunt resistor Rs and outputs it to the A / D converter. The A / D converter converts the voltage input from the differential amplifier into a digital value and outputs it to the battery control unit 46. The battery control unit 46 estimates the current flowing through the plurality of cells E1-En based on the digital value.

[0029] If an A / D converter is mounted in the battery control unit 46 and an analog input port is provided in the battery control unit 46, the temperature measurement unit 44 and the current measurement unit 45 may output an analog voltage to the battery control unit 46 and convert it into a digital value by the A / D converter in the battery control unit 46.

[0030] The battery control unit 46 manages the states of the plurality of cells E1-En based on the voltages, temperatures, and currents of the plurality of cells E1-En measured by the voltage measurement unit 43, the temperature measurement unit 44, and the current measurement unit 45. The battery control unit 46 and the vehicle control unit 30 are connected by an in-vehicle network. As the in-vehicle network, for example, CAN (Controller Area Network) or LIN (Local Interconnect Network) can be used.

[0031] The battery control unit 46 can be composed of a microcomputer and a non-volatile memory (for example, EEPROM, flash memory). An SOC-OCV map 46a is held in the non-volatile memory. The SOC-OCV map 46a describes the characteristic data of the SOC-OCV curves of the plurality of cells E1-En. The SOC-OCV curves of the plurality of cells E1-En are pre-created by the battery manufacturer and registered in the non-volatile memory at the time of shipment. The battery manufacturer conducts various tests to derive the SOC-OCV curves of the cells E1-En.

[0032] The battery control unit 46 estimates the SOC, FCC, and SOH of each of the plurality of cells E1-En. The battery control unit 46 estimates the SOC by combining the OCV method and the current integration method. The OCV method is a method of estimating the SOC based on the OCV of each cell E1-En measured by the voltage measurement unit 43 and the characteristic data of the SOC-OCV curve described in the SOC-OCV map 46a. The current integration method is a method of estimating the SOC based on the OCV at the start of charge and discharge of each cell E1-En and the integrated value of the current measured by the current measurement unit 45. In the current integration method, as the charge and discharge time becomes longer, the measurement error of the current measurement unit 45 accumulates. Therefore, it is preferable to correct the SOC estimated by the current integration method using the SOC estimated by the OCV method.

[0033] The battery control unit 46 can estimate the FCC of the cell based on the characteristic data of the SOC-OCV curve described in the SOC-OCV map 46a and the OCV of two points of the cell measured by the voltage measurement unit 43.

[0034] FIG. 3 is a diagram for explaining the method of estimating the FCC. The battery control unit 46 acquires the OCVs at two points of the cell. The battery control unit 46 refers to the SOC-OCV curve, identifies the two points of SOC corresponding to the two points of voltage respectively, and calculates the difference ΔSOC between the two points of SOC. In the example shown in FIG. 3, the two points of SOC are 20% and 75%, and ΔSOC is 55%.

[0035] The battery control unit 46 calculates the current integration amount (= charge and discharge capacity) Q during the period between the two times when the two points of OCV are acquired based on the transition of the current measured by the current measurement unit 45. The battery control unit 46 can estimate the FCC by calculating the following (Equation 1).

[0036] FCC = Q / ΔSOC ···(Equation 1) SOH is defined as the ratio of the current FCC to the initial FCC, and the lower the value (the closer to 0%), the more the deterioration has progressed. The battery control unit 46 can estimate the SOH by calculating the following (Equation 2).

[0037] SOH = current FCC / initial FCC ···(Equation 2) Also, the SOH may be obtained by measuring the capacity by full charge and discharge, or may be obtained by adding up the storage deterioration and the cycle deterioration. The storage deterioration can be estimated based on the SOC, temperature, and storage deterioration rate. The cycle deterioration can be estimated based on the SOC range used, temperature, current rate, and cycle deterioration rate. The storage deterioration rate and the cycle deterioration rate can be derived in advance by experiments or simulations. The SOC, temperature, SOC range, and current rate can be obtained by measurement.

[0038] Also, the SOH can also be estimated based on the correlation with the internal resistance of the cell. The internal resistance can be estimated by dividing the voltage drop generated when a predetermined current flows through the cell for a predetermined time by the current value. The internal resistance decreases as the temperature rises, and increases as the SOH decreases.

[0039] The battery control unit 46 notifies the vehicle control unit 30 of the voltages, currents, temperatures, SOCs, FCCs, and SOHs of the plurality of cells E1-En via the in-vehicle network. The vehicle control unit 30 generates operation data of the plurality of cells E1-En including the identification information, type information, voltages, currents, temperatures, SOCs, and measurement times of the plurality of cells E1-En, and driving data including the identification information of the electric vehicle 3 and the vehicle type information. The FCC and SOH are not included in the operation data of the plurality of cells E1-En. Note that the driving data may include data such as the speed data and driving position data of the electric vehicle 3. Further, the function of estimating the SOC, FCC, and SOH is not limited to being provided in the battery control unit 46. If the battery control unit 46 does not have the function of estimating the SOC, the operation system 1 or the operator system 2 may be provided with the function of estimating the SOC. In this case, it is preferable that the operation system 1 or the operator system 2 has the function of estimating the FCC and SOH.

[0040] The wireless communication unit 36 performs signal processing for wirelessly connecting to the network 5 via the antenna 36a. In the present embodiment, the wireless communication unit 36 wirelessly transmits the driving data acquired from the vehicle control unit 30 to the operator system 2. As a wireless communication network to which the electric vehicle 3 can be wirelessly connected, for example, a mobile phone network (cellular network), wireless LAN, ETC (Electronic Toll Collection System), DSRC (Dedicated Short Range Communications), V2I (Vehicle-to-Infrastructure), and V2V (Vehicle-to-Vehicle) can be used.

[0041] Figure 4 is a diagram showing a configuration example of the operator system 2 and the computing system 1 shown in Figure 1. The operator system 2 includes a processing unit 21, a storage unit 22, a display unit 23, and an operation unit 24. The functions of the processing unit 21 can be realized by the cooperation of hardware resources and software resources, or by hardware resources only. As hardware resources, a CPU, GPU (Graphics Processing Unit), ROM, RAM, ASIC, FPGA (Field Programmable Gate Array), and other LSIs can be used. As software resources, programs such as an operating system and applications can be used. The storage unit 22 includes a driving data holding unit 221 and a driver data holding unit 222. The storage unit 22 includes a non-volatile recording medium such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive), and records various programs and data.

[0042] The driving data holding unit 221 holds driving data collected from a plurality of electric vehicles 3 owned by the operator. The driver data holding unit 222 holds data of a plurality of drivers belonging to the operator. For example, for each driver, the cumulative driving distance for each electric vehicle 3 driven is managed.

[0043] The display unit 23 includes a display such as a liquid crystal display or an organic EL display, and displays an image generated by the processing unit 21. The operation unit 24 is a user interface such as a keyboard, a mouse, or a touch panel, and receives operations from the user of the operator system 2.

[0044] The operator system 2 can provide the computing system 1 with the driving data of a plurality of electric vehicles 3 held in the driving data holding unit 221. This data provision is executed based on a contract between each operator A, B and the operator of the computing system 1. This contract may be a contract in which each operator A, B receives a monetary consideration in return for data provision, or a contract in which each operator A, B receives a privilege regarding service use in return for data provision. Also, each operator A, B may provide the driving data for free.

[0045] The business operator system 2 can request the calculation system 1 to estimate the FCC of the battery module 41 mounted on the electric vehicle 3 owned by the business operator. This FCC estimation service may be provided for a fee or free of charge. For example, it may be a service that the business operator can use free of charge in return for providing data.

[0046] The calculation system 1 includes a processing unit 11 and a memory unit 12. The processing unit 11 includes a data acquisition unit 111, an extraction unit 112, and an estimation unit 113. The functions of the processing unit 11 can be realized by a combination of hardware resources and software resources, or by hardware resources alone. As hardware resources, a CPU, a GPU, a ROM, a RAM, an ASIC, an FPGA, and other LSIs can be used. As software resources, programs such as an operating system and applications can be used. The memory unit 12 includes a driving data storage unit 121 and a SOC-OCV characteristic storage unit 122. The memory unit 22 includes a non-volatile recording medium such as an HDD or SSD, and stores various programs and data.

[0047] The running data storage unit 121 stores running data of the electric vehicle 3 collected from each of the businesses A and B. The SOC-OCV characteristic storage unit 122 stores, for each cell type, the SOC-OCV characteristics of the cells created by the processing unit 11 based on the collected running data.

[0048] The data acquisition unit 111 acquires driving data of the electric vehicle 3 from multiple businesses A and B, and stores the acquired driving data in the driving data storage unit 121. The extraction unit 112 extracts, as sample data, pairs of SOC and voltage at multiple times included in the operation data of at least one cell stored in the driving data storage unit 121. In this case, the extraction unit 112 extracts pairs of SOC and voltage for a period during which the voltage can be considered to be OCV (i.e., a period during which the cell can be considered to be in a resting state).

[0049] Incidentally, a secondary battery is an electrochemical product. When a charging current flows through the secondary battery, the measured voltage increases non-linearly, and when a discharging current flows through the secondary battery, the measured voltage decreases non-linearly. The voltage measured when a current is flowing through the secondary battery is the CCV (Closed Circuit Voltage) including an overvoltage component, which is a value deviated from the OCV. In a general lithium-ion battery cell, after the end of charge and discharge, the measured voltage converges to near the OCV without the overvoltage component in about 30 seconds. Note that the time until convergence to near the OCV varies depending on the material used for the negative electrode. For example, in a negative electrode material mixed with silicon, it takes one hour or more until convergence to near the OCV.

[0050] The extraction unit 112 may extract a set of SOC and voltage included in a period after a predetermined time (for example, 30 seconds) has elapsed since the end of charge and discharge (since the value of the current has become zero) from a set of SOC and voltage at a plurality of times when the value of the current is zero.

[0051] FIG. 5A and FIG. 5B are diagrams each showing an example of running data. FIG. 5A is a diagram showing an example of the transition of voltage and current included in the running data of a certain day. FIG. 5B is a diagram in which the measurement points of the current on a certain day are plotted. The small circles indicate the measurement points of the current measured while the electric vehicle 3 is running. The large circles indicate the measurement points of the current measured while the electric vehicle 3 is stopped. That is, they indicate the rest points where no current is flowing. As shown in FIGS. 5A and 5B, there are many rest points in the running data, and it is possible to obtain a large number of voltages that can be regarded as OCV from the running data.

[0052] Furthermore, in order to increase the number of samples that can be extracted, the extraction conditions may be relaxed. The extraction unit 112 may also target for extraction a set of SOC and voltage in a period in which a current value equal to or less than a set value (for example, 1 A or 0.1 C) continues for a set time (for example, 1 minute) or more. That is, in this case, a period in which a current with a charge and discharge rate of 0.1 C or less or a current of 1 A or less continues for 1 minute in the battery module 41 is regarded as a period that can be regarded as OCV or a period in which the cell can be regarded as being in a rest state.

[0053] Further, in order to increase the number of samples that can be extracted, after charging the cell or discharging from the cell is completed and until the measured voltage converges to the OCV, the extraction unit 112 may correct the measured voltage based on the convergence characteristics of the polarization voltage of the cell and sample the corrected voltage.

[0054] FIG. 6 is a diagram showing an example of the behavior of the measured voltage when charging of the cell stops. When the cell is charged from the charger 4 at a constant current rate, the measured voltage of the cell gradually increases. When charging stops, since the DC resistance when current flows through the solution and the electrodes and the increase in the DC voltage based on the charging current disappear, the measured voltage decreases by the increase in the DC voltage. Thereafter, the polarization voltage (overvoltage component) gradually decreases, and the measured voltage converges to the OCV.

[0055] In the case of discharging, on the contrary, when discharging stops, since the DC resistance when current flows through the solution and the electrodes and the decrease in the DC voltage based on the discharging current disappear, the measured voltage increases by the decrease in the DC voltage. Thereafter, the polarization voltage (overvoltage component) gradually increases, and the measured voltage converges to the OCV.

[0056] The developer of the arithmetic system 1 prepares in advance a convergence curve of the polarization voltage of the cell after charging, with time as a variable. The convergence curve may be described by a function or by a table. The extraction unit 112 estimates the polarization voltage at each time based on the convergence curve of the polarization voltage after charging and the elapsed time since the end of charging, and subtracts the estimated polarization voltage from the measured voltage to derive a voltage that can be regarded as the OCV.

[0057] Similarly, the developer of the arithmetic system 1 also prepares in advance a convergence curve of the polarization voltage of the cell after discharging, with time as a variable. The extraction unit 112 estimates the polarization voltage at each time based on the convergence curve of the polarization voltage after discharging and the elapsed time since the end of discharging, and adds the estimated polarization voltage to the measured voltage to derive a voltage that can be regarded as the OCV.

[0058] The convergence curve of the polarization voltage depends on the negative electrode material, temperature, and degree of degradation. The developer of the arithmetic system 1 may prepare the convergence curve of the polarization voltage by mapping it in at least one of the negative electrode material category, temperature category, and degree of degradation category. Although the SOH is not included in the operation data of each cell, if the operation data of each cell includes identification information for uniquely identifying each cell, the cumulative value of the charge and discharge current of each cell can be calculated. Also, the start date of use of each cell can be specified. The extraction unit 112 can estimate the degree of degradation of the cell based on the usage period of the cell and the cumulative value of the charge and discharge current.

[0059] The estimation unit 113 generates an approximation curve based on a plurality of sample data points extracted by the extraction unit 112, and estimates the SOC-OCV characteristics of the cell. The estimation unit 113 stores the estimated SOC-OCV characteristics in the SOC-OCV characteristic holding unit 122. The estimation unit 113 estimates the SOC-OCV characteristics for each cell type based on the sample data of a plurality of cells of the same type. Note that the estimation unit 113 can also estimate the SOC-OCV of the specific cell based on the sample data of the specific cell. Also, the estimated OCVs of each cell may be totaled and the SOC-OCV of the battery module 41 may be estimated by the estimation unit 113.

[0060] The estimation unit 113 may separately generate the SOC-OCV characteristics for charging the cell and the SOC-OCV characteristics for discharging the cell. In that case, the extraction unit 112 separately extracts the set of SOC and voltage during a period that can be regarded as a rest state after charging of the cell and the set of SOC and voltage during a period that can be regarded as a rest state after discharging from the cell.

[0061] The estimation unit 113 may estimate the SOC-OCV characteristics based on only the sample data of cells with a usage period shorter than a predetermined period (e.g., one year). The SOC estimated by the management unit 42 of the electric vehicle 3 is relatively accurate when the cell is in a state close to new. Generally, as the usage period of the cell becomes longer, the accuracy of the SOC estimated by the management unit 42 decreases. In particular, in the management unit 42 that does not have a mechanism to update the maintained SOC-OCV characteristics according to the usage period of the cell, the accuracy of the SOC is likely to decrease.

[0062] From the above, estimating the SOC-OCV characteristics based on only the sample data of cells with a short usage period results in higher estimation accuracy of the SOC-OCV characteristics than when estimating based on the sample data for the entire period. Note that instead of cells with a usage period shorter than the predetermined period, the SOC-OCV characteristics may be estimated based on only the sample data of cells with a cumulative charge-discharge current value smaller than a predetermined value.

[0063] Also, similar to the estimation of the SOC-OCV characteristics of the cell, the SOC-OCV characteristics of the battery module 41 can be estimated based on the voltage, current, temperature, and SOC of the plurality of cells E1-En. The battery referred to in the claims encompasses both the cell and the battery module 41.

[0064] The SOC-OCV characteristics of the cell depend on the temperature and the degree of degradation. The extraction unit 112 may classify and extract the sample data of the cell based on at least one of the temperature category and the degradation degree category. The estimation unit 113 may map the sample data classified for each category in at least one of the temperature category and the degradation degree category to generate the SOC-OCV characteristics of the cell. As described above, when the operation data of each cell includes identification information for uniquely identifying each cell, the degree of degradation of each cell can be estimated based on the usage period and the cumulative charge-discharge current value of each cell.

[0065] FIG. 7 is a flowchart showing the flow of the estimation process of the SOC-OCV characteristics of the cells by the arithmetic system 1. The data acquisition unit 111 acquires the running data (including the voltage, current, SOC, and temperature of the cells) of the electric vehicle 3 from the operator system 2 (S10). The data acquisition unit 111 stores the acquired running data in the running data holding unit 121. The extraction unit 112 extracts a set of SOC and voltage during a period when the cell can be regarded as in a resting state from the running data held in the running data holding unit 121 (S11). The estimation unit 113 generates an approximation curve based on the extracted multiple sets of SOC and voltage, and estimates the SOC-OCV characteristics (S12). The estimation unit 113 stores the estimated SOC-OCV characteristics in the SOC-OCV characteristics holding unit 122.

[0066] FIG. 8 is a diagram showing an example of actually estimating the SOC-OCV characteristics from the running data of one electric vehicle 3. FIG. 9 is a diagram showing an example of actually plotting the OCV data against the SOC from the running data of one electric vehicle 3. FIG. 10 is a diagram showing an example of actually plotting the OCV data against the SOC from the running data of three electric vehicles 3. FIG. 11 is a diagram showing an example of actually estimating the SOC-OCV characteristics from the running data of three electric vehicles 3.

[0067] As shown in FIG. 9, even when there is little running data for one electric vehicle 3 (vehicle A), when the running data of three electric vehicles 3 (vehicles A, B, and C) are plotted as shown in FIG. 10, the number of sample data increases. As shown in FIG. 11, the SOC-OCV characteristics generated based on the running data of three electric vehicles 3 form a smoother curve than the SOC-OCV characteristics generated based on the running data of one electric vehicle 3 shown in FIG. 8. The SOC-OCV characteristics generated based on the running data of three electric vehicles 3 shown in FIG. 11 fell within an error of within 3% compared with the SOC-OCV characteristics derived by testing.

[0068] In the SOC-OCV characteristic, when a plurality of different sample data (OCV data with respect to SOC) are acquired, the degree of adoption of the acquired sample data may be determined in consideration of the allowable range of the error of the SOC estimated value. For example, for each SOC, the average and standard deviation (σ) of the OCV are calculated, and it is determined whether to reduce the weighting of the sample data depending on whether it is more than 2σ away from the average. Also, for example, there may be a case where the acquired sample data is 10 points for ten electric vehicles 3 at SOC = 50%, while it is 2 points for two electric vehicles 3 at SOC = 10%. In another example, considering such a case, for sample data that is less than 2σ less than the average compared to other SOCs, it may be determined to reduce the weighting of the degree of adoption of the sample data.

[0069] The sample data to be plotted on the SOC-OCV characteristic is obtained, for example, by taking the average value (or median) for each SOC (or OCV), and obtaining it by kernel regression or linear interpolation, or by fitting it to a pre-set function. By weighting or selecting the sample data to be plotted on the SOC-OCV characteristic in this way, a highly accurate SOC-OCV characteristic can be obtained.

[0070] By the way, when the standard deviation (σ) with respect to SOC is determined to be unsuitable for use as sample data to be plotted on the SOC-OCV characteristic because it is larger than a pre-set threshold value, or when the management unit 42 of the electric vehicle 3 does not have a function to estimate the SOC, etc., there may be a case where the SOC of the operation data of the plurality of cells E1-En transmitted from the electric vehicle 3 cannot be used. In such a case, the SOC is estimated by the arithmetic system 1 or the operator system 2 based on the full charge capacity FCC and the charge and discharge capacity Q, and the sample data to be used for the SOC-OCV characteristic may be extracted accordingly. Note that the full charge capacity FCC and the charge and discharge capacity Q are calculated based on the OCV and the current integrated value generated based on the voltage and current measured by the management unit 42.

[0071] FIG. 12 is a flowchart showing the flow of the estimation process of the FCC of the battery module 41 by the arithmetic system 1. When a request for the estimation process of the FCC of a specific battery module 41 is received from the operator system 2 (Y in S20), the extraction unit 112 extracts two voltages during a period in which the cell can be regarded as in a rest state from the operation data of the cells included in the specific battery module 41 (S21).

[0072] At this time, the extraction unit 112 needs to extract the two voltages from two independent periods in which the cell can be regarded as in a rest state, with a charge / discharge period sandwiched therebetween. For example, the extraction unit 112 may extract the voltages from the period in which the cell can be regarded as in a rest state before the start of running of the electric vehicle 3 and the period in which the cell can be regarded as in a rest state after the end of running, respectively. Further, the extraction unit 112 extracts the two voltages from the running data of a day as new as possible (for example, the most recent running day).

[0073] The estimation unit 113 specifies two SOCs corresponding to the two extracted voltages with reference to the SOC-OCV characteristics of the same type as the cell held in the SOC-OCV characteristic holding unit 122. The estimation unit 113 calculates the difference ΔSOC between the two specified SOCs (S22).

[0074] When the SOC-OCV characteristics of the same type as the cell are mapped for at least one of the temperature category and the degradation degree category, the SOC-OCV characteristics corresponding to the temperature condition and the degradation degree condition of the cell are used. As the temperature condition of the cell, for example, the temperature obtained by averaging the temperatures during the period between the two times when the two OCVs are acquired can be used. As the degradation degree condition of the cell, the degradation degree estimated based on the usage period of the cell and the cumulative value of the charge / discharge current can be used.

[0075] The extraction unit 112 extracts the current during the period between the times when the two voltages are extracted from the operation data of the cell (S23). The estimation unit 113 calculates the current integration amount Q during the period between the times when the two voltages are extracted (S24). The estimation unit 113 divides the current integration amount Q by the difference ΔSOC to estimate the FCC (see the above (Equation 1)) (S25).

[0076] The estimation unit 113 synthesizes the FCCs of all the cells included in a specific battery module 41 according to the connection form of all the cells, and estimates the FCC of the battery module 41 (S26). The estimation unit 113 transmits the estimated FCC of the battery module 41 to the requesting operator system 2 (S26).

[0077] The requesting operator system 2 can estimate the SOH of the battery module 41 (see the above (Equation 2)) based on the received FCC of the battery module 41 and the initial FCC of the battery module 41. Note that the SOH of the battery module 41 may also be estimated on the side of the computing system 1.

[0078] As described above, according to the present embodiment, it is possible to easily and inexpensively obtain the SOC-OCV characteristics of cells for which the SOC-OCV characteristics have not been obtained. It is not necessary to obtain the basic data for creating the SOC-OCV characteristics, and the time and monetary costs for obtaining the basic data can be reduced. If the SOC-OCV characteristics can be obtained, the FCC and SOH of the battery module 41 can be estimated with high accuracy. In this way, the FCCs and SOHs of various batteries from various battery manufacturers can be estimated with high accuracy without obtaining basic data. Thereby, the operator can determine an appropriate end-of-life time for the electric vehicle 3. In addition, the operator can estimate the reuse value of the battery module 41 with high accuracy.

[0079] In addition, by merging and using the driving data of a plurality of electric vehicles 3 of the same type, the estimation accuracy of the SOC-OCV characteristics can be improved. For example, even if one electric vehicle 3 does not use all SOC ranges, high-precision SOC-OCV characteristics can be generated. Also, even if there is a lot of noise in the driving data of one electric vehicle 3, high-precision SOC-OCV characteristics can be generated.

[0080] Also, by selecting the data period to be used as sample data, SOC-OCV characteristics corresponding to secular changes can be generated. It is also possible to cope with complex secular deterioration depending on the usage method of the electric vehicle 3. It is not necessary to measure the deterioration characteristics of the cell in advance, and an acceleration test based on a plurality of conventional patterns is also unnecessary.

[0081] As described above, the present disclosure has been described based on the embodiments. It is understood by those skilled in the art that the embodiments are examples, and various modifications are possible for each component and each combination of processing processes, and such modifications are also within the scope of the present disclosure.

[0082] In the above embodiment, an example of feedback of the FCC of the battery module 41 from the arithmetic system 1 to the business operator system 2 has been described. In this regard, the SOC-OCV characteristics corresponding to the degradation degree classification of a specific cell may be fed back to the business operator system 2. In particular, in the case of the battery system 40 in which the management unit 42 that does not have a mechanism for updating the held SOC-OCV characteristics according to the usage period of the cell is used, it is better to update to the SOC-OCV characteristics corresponding to the degradation degree classification acquired from the arithmetic system 1 according to the usage period of the cell, so that the estimation accuracy of the SOC is improved.

[0083] In the above embodiment, an example of estimating the characteristics of the battery cells included in the battery system 40 by the arithmetic system 1 has been described. In this regard, the characteristics of the capacitor cells (for example, electric double layer capacitor cells, lithium ion capacitor cells) included in the capacitor system may be estimated by the arithmetic system 1.

[0084] In the above embodiment, an example of estimating the characteristics of the cells of the battery system 40 mounted on the electric vehicle 3 by the arithmetic system 1 has been described. In this regard, the characteristics of the cells of the battery system or capacitor system mounted on the stationary power storage system may be estimated by the arithmetic system 1.

[0085] Note that the embodiments may be specified by the following items. [Item 1] A data acquisition unit (111) that acquires operation data of the battery (E1, 41) including at least the voltage and current at a plurality of times measured by a management device (42) that manages the battery (E1, 41), and the SOC estimated based on at least one of the voltage and the current. An extraction unit (112) that extracts, as sample data, a set of SOC and voltage during a period in which the battery (E1, 41) can be regarded as being in a rest state, based on the current, from a set of SOC and voltage at a plurality of times included in the operation data. An estimation unit (113) that estimates the SOC-OCV characteristics of the battery (E1, 41) based on the extracted sample data. An arithmetic system (1), characterized by comprising the above. According to this, the SOC-OCV characteristics of the battery (E1, 41) can be created at low cost.

[0086] [Item 2] The data acquisition unit (111) acquires operation data of a plurality of types of batteries (E1, 41) respectively measured by a plurality of the management devices (42). The arithmetic system (1) according to Item 1, wherein the estimation unit (113) estimates the SOC-OCV characteristics for each type of the battery (E1, 41). According to this, the SOC-OCV characteristics of the battery (E1, 41) can be created at low cost and with high accuracy.

[0087] [Item 3] The arithmetic system (1) according to Item 2, wherein the data acquisition unit (111) acquires operation data of a plurality of types of batteries (E1, 41) via a network (5). According to this, the operation data of a plurality of types of batteries (E1, 41) can be easily and efficiently increased.

[0088] [Item 4] The arithmetic system (1) according to Item 1 or 2, wherein the extraction unit (112) extracts a set of SOC and voltage during a period in which a current value equal to or less than a set value continues for a set time or more. According to this, the number of sample data to be extracted can be increased.

[0089] [Item 5] The extraction unit (112) corrects the measured voltage based on the convergence characteristics of the polarization voltage of the battery (E1, 41) during the period from the end of charging or discharging of the battery (E1, 41) until the measured voltage converges to the OCV, and extracts the corrected voltage. The arithmetic system (1) according to item 1 or 2. According to this, the number of sample data to be extracted can be increased.

[0090] [Item 6] The extraction unit (112) separately extracts the set of SOC and voltage during a period that can be regarded as a rest state after the charging of the battery (E1, 41) is completed, and the set of SOC and voltage during a period that can be regarded as a rest state after the discharging of the battery (E1, 41) is completed. The estimation unit (113) separately generates the SOC-OCV characteristics for charging of the battery (E1, 41) and the SOC-OCV characteristics for discharging of the battery (E1, 41). The arithmetic system (1) according to any one of items 1 to 5. According to this, the SOC-OCV characteristics for charging and discharging of the battery (E1, 41) can be generated, and the estimation accuracy of the FCC can be improved.

[0091] [Item 7] When the estimation of the FCC of a specific battery (E1, 41) is required, The extraction unit (112) extracts voltages from two periods of the specific battery (E1, 41) that can be regarded as rest states with a charge-discharge period in between from the operation data of the specific battery (E1, 41), and extracts the current during the period between the two times when the two voltages are extracted. The estimation unit (113) refers to the SOC-OCV characteristics, identifies two SOCs corresponding to the two voltages respectively, calculates the difference between the two SOCs, integrates the current during the period between the two times to calculate the current integration amount, and estimates the FCC of the specific battery (E1, 41) based on the difference in SOC and the current integration amount. The arithmetic system (1) according to any one of claims 1 to 6. According to this, it is possible to obtain a highly accurate FCC of the battery (E1, 41) without creating the SOC-OCV characteristics by oneself.

[0092] [Item 8] A step of obtaining operation data of the battery (E1, 41) including at least voltages and currents at a plurality of times measured by a management device (42) for managing the battery (E1, 41) and an SOC estimated based on at least one of the voltage and the current; A step of extracting, as sample data, a set of SOC and voltage during a period in which the battery (E1, 41) identified based on the current can be regarded as a rest state from a set of SOC and voltage at a plurality of times included in the operation data; A step of estimating the SOC-OCV (Open Circuit Voltage) characteristics of the battery (E1, 41) based on the extracted sample data; A battery characteristic estimation method characterized by comprising: According to this, the SOC-OCV characteristics of the battery (E1, 41) can be created at low cost.

[0093] [Item 9] A process of obtaining operation data of the battery (E1, 41) including at least voltages and currents at a plurality of times measured by a management device (42) for managing the battery (E1, 41) and an SOC estimated based on at least one of the voltage and the current; A process of extracting, as sample data, a set of SOC and voltage during a period in which the battery (E1, 41) identified based on the current can be regarded as a rest state from a set of SOC and voltage at a plurality of times included in the operation data; Based on the extracted sample data, a process for estimating the SOC-OCV (Open Circuit Voltage) characteristics of the battery (E1, 41), A battery characteristic estimation program, characterized in that it is executed by a computer. According to this, the SOC-OCV characteristics of the battery (E1, 41) can be created at low cost.

Explanation of symbols

[0094] 1 computing system, 2 operator system, E1-En cells, T1, T2 temperature sensors, RY1, RY2 relays, 3 electric vehicle, 4 charger, 5 network, 11 processing unit, 111 data acquisition unit, 112 extraction unit, 113 estimation unit, 12 storage unit, 121 driving data holding unit, 122 SOC-OCV characteristic holding unit, 21 processing unit, 22 storage unit, 221 driving data holding unit, 222 driver data holding unit, 23 display unit, 24 operation unit, 30 vehicle control unit, 34 motor, 35 inverter, 36 wireless communication unit, 36a antenna, 38 charging cable, 40 battery system, 41 battery module, 42 management unit, 43 voltage measurement unit, 44 temperature measurement unit, 45 current measurement unit, 46 battery control unit, 46a SOC-OCV map.

Claims

1. A data acquisition unit that acquires operation data of the battery including at least voltage and current at a plurality of times measured by a management device for managing the battery, and SOC (State Of Charge) estimated based on at least one of the voltage and the current; An extraction unit that extracts, as sample data, a set of SOC and voltage during a period in which the battery can be regarded as being in a rest state, which is specified based on the current, from a set of SOC and voltage at a plurality of times included in the operation data; An estimation unit that generates an approximate curve based on the extracted sample data and estimates the SOC-OCV (Open Circuit Voltage) characteristic of the battery based on the operation data obtained by merging the operation data of the battery acquired from a plurality of different battery systems of the same type; An arithmetic system characterized by comprising the above.

2. The data acquisition unit acquires operation data of a plurality of types of batteries respectively measured by a plurality of the management devices, The arithmetic system according to claim 1, wherein the estimation unit estimates the SOC-OCV characteristic for each type of the battery.

3. The arithmetic system according to claim 2, wherein the data acquisition unit acquires operation data of a plurality of types of batteries via a network.

4. The arithmetic system according to claim 1 or 2, wherein the extraction unit extracts a set of SOC and voltage during a period in which a current value equal to or less than a set value continues for a set time or more.

5. The arithmetic system according to claim 1 or 2, wherein the extraction unit corrects the measured voltage based on the convergence characteristic of the polarization voltage of the battery during a period from when charging to the battery or discharging from the battery ends until the measured voltage converges to the OCV, and extracts the corrected voltage.

6. The extraction unit separately extracts a set of SOC and voltage during a period that can be regarded as a rest state after charging to the battery and a set of SOC and voltage during a period that can be regarded as a rest state after discharging from the battery, The arithmetic system according to any one of claims 1 to 5, wherein the estimation unit separately generates the SOC-OCV characteristic for charging of the battery and the SOC-OCV characteristic for discharging of the battery.

7. When estimation of the FCC (Full Charge Capacity) of a specific battery is requested, The extraction unit extracts voltages from two periods in the operation data of the specific battery, where the specific battery can be regarded as in a rest state with a charge-discharge period in between, extracts the current during the period between the two times when the two voltages are extracted, The estimation unit refers to the SOC-OCV characteristics, identifies two SOCs corresponding to the two voltages respectively, calculates the difference between the two SOCs, integrates the current during the period between the two times to calculate the integrated current amount, and estimates the FCC of the specific battery based on the difference in SOC and the integrated current amount. The arithmetic system according to any one of claims 1 to 6, characterized in that.

8. Obtaining operation data of the battery including at least voltages and currents at a plurality of times measured by a management device for managing the battery, and an SOC (State Of Charge) estimated based on at least one of the voltage and the current; Extracting, as sample data, a set of SOC and voltage during a period when the battery identified based on the current can be regarded as in a rest state, from a set of SOC and voltage at a plurality of times included in the operation data; Generating an approximate curve based on the extracted sample data and the operation data obtained by merging the operation data of the battery obtained from a plurality of different battery systems of the same type, and estimating the SOC-OCV (Open Circuit Voltage) characteristics of the battery; A battery characteristic estimation method having.

9. A process of obtaining operation data of the battery including at least voltages and currents at a plurality of times measured by a management device for managing the battery, and an SOC (State Of Charge) estimated based on at least one of the voltage and the current; A process of extracting, as sample data, a set of SOC and voltage during a period when the battery identified based on the current can be regarded as in a rest state, from a set of SOC and voltage at a plurality of times included in the operation data; A process of generating an approximate curve based on the extracted sample data and the operation data obtained by merging the operation data of the battery obtained from a plurality of different battery systems of the same type, and estimating the SOC-OCV (Open Circuit Voltage) characteristics of the battery; A battery characteristic estimation program characterized by causing a computer to execute.

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