Method for estimating full charge capacity of battery and device for estimating full charge capacity

Abstract

The invention provides a full charge capacity estimation method and a full charge capacity estimation device of a battery. The full charge capacity estimation method includes: a step A including acquiring data of a battery and processing the acquired data; step B, extracting data; and a step C for estimating the full charge capacity of the battery to be measured. Step A includes: acquiring battery data including a voltage value, a current value, and a temperature value obtained over time from a battery to be measured; and processing the acquired data. In the step B, n or more pieces of data satisfying a predetermined condition are extracted from at least one of the data acquired in the step A and the data obtained by the processing in the step A. In step C, the full charge capacity of the battery to be measured is estimated on the basis of the data extracted in step B. Wherein n is an integer of 3 or more.

Description

Technical Field

[0001] The invention relates to a method and a device for estimating the full charge capacity of a battery. Background Art

[0002] In International Publication No. 2012 / 105492, a full charge capacity detection method for a battery formed by a capacity change detection process, an open circuit voltage detection process, a remaining capacity determination process, a remaining capacity change value calculation process, and a full charge capacity calculation process is disclosed. In the full charge capacity detection method disclosed in the gazette, the full charge capacity of the battery is calculated based on the capacity change value and the remaining capacity change value when at least one of the capacity change value detected in the capacity change detection process, the remaining capacity change value calculated in the remaining capacity change value calculation process, and the voltage difference between the first open circuit voltage and the second open circuit voltage detected in the open circuit voltage detection process is greater than a pre-set set value. It is believed that according to this full charge capacity detection method, the full charge capacity of the battery can be detected more accurately.

[0003] International Publication No. 2012 / 120620 discloses a battery state estimation method that measures the current value and terminal voltage value of a battery during charging and discharging, and calculates the battery state based on the measured current value and terminal voltage value. In the battery state estimation method disclosed in the bulletin, when the change per second of the measured current value is greater than a specified value, the current and terminal voltage measured during the period from the occurrence of the current change to the lapse of a specified time are not used. The battery state is calculated based on the current value and terminal voltage values ​​measured during the battery charging and discharging period other than the above period. In the battery state estimation method disclosed in the bulletin, at least one of the charging rate, degradation degree, and full charge capacity is calculated as the battery state. It is believed that according to this battery state estimation method, battery states such as capacity and degradation degree can be estimated with higher accuracy during discharge.

[0004] Prior art literature

[0005] Patent Literature

[0006] Patent Document 1: International Publication No. 2012 / 105492

[0007] Patent Document 2: International Publication No. 2012 / 120620 Summary of the invention

[0008] The present inventors intend to improve the accuracy of estimating the full charge capacity of a battery.

[0009] The method for estimating the full charge capacity of a battery disclosed herein includes: step A, including obtaining battery data and processing the obtained data; step B, extracting data; and step C, estimating the full charge capacity of the battery to be measured. Step A includes: obtaining battery data including voltage values, current values, and temperature values ​​obtained from the battery to be measured over time; and processing the obtained data. In step B, at least n data satisfying a predetermined condition are extracted from at least one of the data obtained in step A and the data obtained by processing in step A. In step C, the full charge capacity of the battery to be measured is estimated based on the data extracted in step B. Here, n is an integer greater than 3. According to the method for estimating the full charge capacity of a battery, the accuracy of estimating the full charge capacity of the battery is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 is a schematic diagram showing a battery system 100 .

[0011] Figure 2 : is a flowchart showing a procedure executed in the control device 40 of the full charge capacity estimating device 20 .

[0012] Figure 3 is a circuit diagram showing a voltage behavior model 60 of the battery 1 .

[0013] Figure 4 It is a graph showing the relationship between the open circuit voltage OCV and the SOC.

[0014] Figure 5 : is a graph showing the relationship between the current integrated value of the extracted data D and the SOC.

[0015] Figure 6 : is a flowchart showing a procedure executed in the control device 40 of the full charge capacity estimating device 20 .

[0016] Figure 7 : is a graph showing the relationship between the current integrated value and the SOC of the selected data D1.

[0017] Figure 8 : is a flowchart showing a procedure executed in the control device 40 of the full charge capacity estimating device 20 .

[0018] Fig. 9 It is a graph showing the relationship between the SOC and the current integrated value. DETAILED DESCRIPTION

[0019] Hereinafter, an embodiment of the technology disclosed herein will be described with reference to the accompanying drawings. The embodiments described herein are of course not intended to limit the present invention in particular. Each of the accompanying drawings is a schematic depiction and does not necessarily reflect the actual object. In addition, the same reference numerals are appropriately assigned to components / parts that play the same role, and repeated descriptions are appropriately omitted.

[0020] <Battery System 100>

[0021] Figure 1 is a schematic diagram showing a battery system 100. Figure 1 As shown, the battery system 100 includes a battery 1 and a full charge capacity estimating device 20. The battery 1 is connected to an external load (not shown).

[0022] In this specification, "battery" is a term referring to an electrical storage device that can extract electrical energy. The battery includes a secondary battery that can be repeatedly charged and discharged by the movement of charge carriers between a pair of electrodes (positive and negative electrodes) via an electrolyte, such as a lithium-ion secondary battery. The use of the battery is not particularly limited. The battery includes a battery pack in which a plurality of batteries (single cells) are electrically connected to each other. The battery can be, for example, a so-called vehicle-mounted battery that serves as a power source for an electric vehicle. In the case of using the battery as a vehicle-mounted battery, the battery is appropriately connected to a charging and discharging device and charged. The battery can be discharged in a state connected to the charging and discharging device. The battery can be a so-called fixed-purpose battery installed in general households, commercial places, etc. In the case of using the battery as a fixed-purpose battery, the battery can be connected to a power generation device, system power, etc.

[0023] As the battery 1 is charged and discharged, the full charge capacity F of the battery 1 decreases with time. The full charge capacity F is the battery capacity of the battery 1 charged to 100% SOC (States Of Charge) as the maximum charge capacity until it is fully discharged. The full charge capacity estimation device 20 estimates the full charge capacity F of the battery 1.

[0024] The full charge capacity estimation device 20 includes a sensor 30 and a control device 40. The sensor 30 includes a voltage sensor 31, a current sensor 32, and a temperature sensor 33. The control device 40 includes an acquisition unit 41, a first calculation unit 42, a first estimation unit 43, a first determination unit 44, a second determination unit 45, a third determination unit 46, a second estimation unit 47, a determination unit 48, a second calculation unit 49, a third estimation unit 50, a fourth determination unit 51, a fifth determination unit 52, and a storage unit 53. The control device 40 may be, for example, a computer such as an ECU (Electronic Control Unit) or a microcomputer-mounted circuit board. The computer realizes the required functions, for example, according to a predetermined program. The various functions of the computer are processed by the cooperation of the computer's computing device (also referred to as a processor, CPU (Central Processing Unit), MPU (Micro-Processing Unit)), a storage device (memory, hard disk, etc.), and software. In this embodiment, the control device 40 is realized by the ECU. Each of the components 41 to 53 of the control device 40 may be realized by one or more processors, or may be embedded in a circuit. The control device 40 is configured to be able to communicate with the sensor 30. The storage unit 53 may store previously estimated full charge capacity Fp and the like.

[0025] Hereinafter, a method for estimating the full charge capacity F of the battery 1 in the full charge capacity estimating device 20 will be described together with the structure of the full charge capacity estimating device 20. The method for estimating the full charge capacity F of the battery disclosed herein includes: a step A, including obtaining data of the battery 1 and processing the obtained data; a step B, extracting data D that satisfies a predetermined condition; and a step C, estimating the full charge capacity F of the battery 1. Figure 2 is a flowchart showing a process executed in the control device 40 of the full charge capacity estimating device 20. Figure 2 , a flow of a method for estimating the full charge capacity F of the battery 1 as the vehicle-mounted battery is shown.

[0026] If the vehicle's ignition is on, start Figure 2 In step S1, the current integrated value and the SOC calculated when the ignition switch was last turned on are reset, or part of the stored data is reset.

[0027] <Step A of Acquiring Data of Battery 1 and Processing Acquired Data>

[0028] In this embodiment, step A includes: obtaining data of the battery 1 including current value, voltage value and temperature value ( Figure 2 Step S2); calculating the current accumulation value; and obtaining the estimated value of SOC ( Figure 2Step S3).

[0029] In step S2, the acquisition unit 41 acquires data of the battery 1. The acquisition unit 41 acquires data of the battery 1 when it is charged and discharged during the start of the vehicle (including during the driving process). The acquisition unit 41 acquires data during the start of the vehicle (including the rest state in which the current does not flow through the battery 1). The data of the battery 1 includes a current value, a voltage value, and a temperature value. The acquisition unit 41 acquires the current value, the voltage value, and the temperature value detected by the sensor 30 as data.

[0030] The voltage sensor 31 of the sensor 30 detects the voltage value of the battery 1. The current sensor 32 detects the current value of the battery 1 during charging and discharging. The temperature sensor 33 detects the temperature value of the battery 1. Here, the battery 1 may be a battery pack in which a plurality of cells are electrically connected to each other. When the battery 1 is a battery pack, a plurality of temperature sensors 33 and voltage sensors 31 may be provided. When the battery 1 is a battery pack, one temperature sensor 33 and voltage sensor 31 may be provided for a plurality of cells, or a temperature sensor 33 and voltage sensor 31 may be provided for each cell. When one temperature sensor 33 is provided for a plurality of cells, the temperature value of each cell can be estimated by calculation. When the batteries 1 are connected in parallel, one voltage sensor 31 may be provided for the batteries 1 connected in parallel. When the batteries 1 are connected in parallel, a current sensor 32 may be provided for each battery 1 connected in parallel. The voltage sensor 31, the current sensor 32, and the temperature sensor 33 detect the detected current value, voltage value, and temperature value of the battery 1 as analog signals, respectively.

[0031] Data is detected from the battery 1 that is the object of measurement over time. Here, the voltage sensor 31, the current sensor 32, and the temperature sensor 33 can detect the voltage value, the current value, and the temperature value at predetermined intervals, respectively. It is not particularly limited, but the interval for detecting the voltage value, the current value, and the temperature value can be set to, for example, about 0.001 to 1 second (about 0.01 to 1 second). The interval for detecting the voltage value, the current value, and the temperature value can be set to, for example, a fixed interval. The detected analog signal is converted into a digital signal by an A / D converter and output to the acquisition unit 41 of the control device 40. The acquisition unit 41 acquires the data by associating it with the time.

[0032] In step S3, the first calculation unit 42 calculates the current integrated value based on the data acquired by the acquisition unit 41. The first calculation unit 42 integrates the current values ​​included in the data to calculate the current integrated value. Here, the current integrated value is calculated based on the following formula (1):

[0033] Current integrated value = current integrated value accumulated up to the last time + ΔT × current value (1)

[0034] Here, ΔT is the time between the time when the current value was measured last time and the time when the current value is measured this time. In addition, in step S3, the first estimation unit 43 estimates the SOC from the acquired data. The first estimation unit 43 obtains the estimated value of the SOC based on the data of the battery 1. In this embodiment, the first estimation unit 43 obtains the estimated value of the SOC based on the data of the battery 1 and a predetermined voltage behavior model.

[0035] In the voltage behavior model, an equivalent circuit is used to model the internal resistance of the battery, the behavior of the charge and discharge current, and the behavior of the battery voltage. Here, the SOC of the battery 1 is estimated based on the voltage behavior model from the voltage (closed circuit voltage CCV) of the battery 1 obtained. As a voltage behavior model for estimating the SOC, a previously known battery voltage behavior model such as a CR parallel circuit can be used. In addition, the battery voltage behavior model used is not limited to the method described below. The battery voltage behavior model can be appropriately set according to the structure of the battery 1.

[0036] Figure 3 is a circuit diagram showing a voltage behavior model 60 of the battery 1. Figure 3 In FIG. 6 , arrows are used to indicate the directions of the current I flowing through the voltage source 61, the current Ia flowing through the capacitor 63a, and the current Ib flowing through the internal resistor 63b. Figure 3 As shown, the voltage behavior model 60 includes a voltage source 61, an internal resistor 62, and a CR parallel circuit 63 connected in series. The CR parallel circuit 63 is a circuit in which a capacitor 63a and an internal resistor 63b are connected in parallel. In the voltage behavior model 60, the open circuit voltage OCV (Open Circuit Voltage) of the voltage source 61 is estimated.

[0037] The open circuit voltage OCV of the voltage source 61 is estimated based on the closed circuit voltage CCV (Closed Circuit Voltage) applied to the voltage behavior model 60 and the estimated value (Vp+Vohm) of the polarization voltage consisting of the sum of the estimated value Vohm of the voltage drop generated in the internal resistor 62 and the estimated value Vp of the voltage drop generated in the CR parallel circuit 63. The open circuit voltage OCV of the voltage source 61 can be estimated based on the following formula (2), for example:

[0038] OCV=CCV-Vohm-Vp (2)

[0039] Among them, the estimated value Vohm of the voltage drop generated by the internal resistor 62 can be calculated by the product of the resistance value Rohm of the internal resistor 62 and the current value I flowing through the voltage behavior model 60. The estimated value of the polarization voltage (Vp+Vohm) can be calculated by adding the product of the resistance value Rp of the internal resistor 63b and the current value Ib flowing through the internal resistor 63b and the product of the resistance value Rohm of the internal resistor 62 and the current value I flowing through the internal resistor 62. Other well-known general circuit calculation methods for obtaining the voltage value of the CR circuit can also be used. In this way, the open circuit voltage OCV of the voltage source 61 is estimated.

[0040] In addition, the resistance value Rohm of the internal resistor 62 used in the estimation of the "estimated value Vohm for estimating the voltage drop of the open circuit voltage OCV", the resistance value Rp of the internal resistor 63b used in the estimation of the estimated value Vp of the voltage drop generated in the CR parallel circuit 63, and the capacitance C of the capacitor 63a may vary according to the SOC and temperature value of the battery 1. The resistance value Rohm, the resistance value Rp, and the capacitance C can be appropriately corrected according to the SOC and temperature value of the battery 1. For example, a two-dimensional table of temperature value and SOC can be set for the resistance value Rohm, the resistance value Rp, and the capacitance C, respectively. The resistance value Rohm, the resistance value Rp, and the capacitance C can also be determined based on the temperature value measured by the temperature sensor 33, the SOC calculated separately, and the two-dimensional table of temperature value and SOC, and used for the above-mentioned estimation of the open circuit voltage OCV. Thereby, the accuracy of the estimation of the open circuit voltage OCV can be improved.

[0041] By using the voltage behavior model 60, the open circuit voltage OCV of the battery 1 is estimated based on the voltage value of the battery 1. Next, the SOC of the battery 1 is estimated based on the estimated open circuit voltage OCV. In this embodiment, the SOC of the battery 1 is estimated using an OCV-SOC conversion table pre-stored in the control device 40. The OCV-SOC conversion table can be obtained in advance through experiments, simulations, theoretical calculations, etc. and stored in the control device 40.

[0042] Figure 4 is a graph showing the relationship between the open circuit voltage OCV and the SOC. Figure 4 In the figure, the relationship between the open circuit voltage OCV and SOC is shown in a curve graph. Figure 4 In FIG. 1 , the relationship between the open circuit voltage OCV and the SOC is schematically shown, which may not reflect the actual relationship. Figure 4 In the figure, the open circuit voltage OCV after charging is shown by a solid line, and the open circuit voltage OCV after discharging is shown by a dotted line. Figure 4 As shown in FIG. 1 , in the OCV-SOC conversion table, the open circuit voltage OCV is recorded in association with the SOC. Figure 4In the OCV-SOC conversion table shown, the relationship between the open circuit voltage OCV and SOC after charging is different from the relationship between the open circuit voltage OCV and SOC after discharging. The relationship between the open circuit voltage OCV and SOC used to estimate the SOC can be appropriately selected according to whether the current value obtained is the current value obtained during charging or the current value obtained during discharging. In addition, the estimation of the SOC of the battery 1 is not limited to this method, and a conventionally known method such as the IV method of finding the open circuit voltage V0 from the plot of the current value and CCV can also be used. In addition, the method of estimating the SOC can also be determined according to the use mode of the battery 1. For example, as a battery with a small charge rate (C rate) or fluctuation of the current (for example, a battery for stationary use, etc.), when the relationship between SOC and OCV has a property close to a straight line, the full charge capacity can be estimated from the relationship between the voltage value (estimated value of CCV or OCV) and the power-on time. Similarly, as a battery with a small charge rate or fluctuation of the current, when using data of the SOC section where the relationship between SOC and OCV is close to a straight line, the full charge capacity can be estimated from the relationship between the voltage value and the power-on time.

[0043] <Step B of Extracting Data D of Battery 1>

[0044] Step B of extracting data D of battery 1 includes: determining whether the data obtained in step A satisfies a predetermined condition ( Figure 2 Step S4); and storing data D (which satisfies a predetermined condition) Figure 2 For example, step B of extracting data D of battery 1 may include: determining whether data acquired or processed over time in step A satisfies predetermined conditions at each time; and storing all or part of the data acquired or processed in step A at the time when the predetermined conditions are determined to be satisfied as data D.

[0045] In step S4, the first determination unit 44 (see Figure 1 ) determines whether the data acquired in the acquisition unit 41 satisfies a predetermined condition. The predetermined condition can be set based on a condition that can improve the estimation accuracy of the SOC. As an example, a case where it is determined whether the condition is satisfied based on the acquired current value is described.

[0046] In this embodiment, the predetermined condition is set based on the current value obtained and the time when the current value is obtained. The predetermined condition (hereinafter, also referred to as the "determination condition") is set as follows: the magnitude of the current obtained in step A is below the predetermined threshold value for a predetermined period of time. Here, "the magnitude of the current" refers to the absolute value of the current value. In the determination, the absolute value of the current value during charging and the absolute value of the current value during discharge can be used. It is not particularly limited, but the threshold used in the determination can be set based on the charging rate. The threshold can be set to a charging rate of 0.1, for example, or it can be set to a charging rate of 0.2. As described above, the current value obtained is associated with the time. The determination condition of time can be set to more than 10 seconds, for example. The determination condition of time can be set to less than 30 seconds, for example. In addition, the threshold of the current value and the determination condition of time can be appropriately set according to the structure of the battery 1, the mode of use, etc., and are not limited to the above range. From the perspective of increasing the data D extracted in step B, the current value can be set high and the time can be set short. From the viewpoint of improving the accuracy of the data D extracted in the step B, the current value may be set low and the time may be set long.

[0047] Here, the determination condition is set to whether a current with a charge rate of less than 0.2 has continued for 20 seconds. In the case where it is determined that a current greater than 0.2 in charge rate has flowed at least at any time from a certain moment to 20 seconds ago (No), the first determination unit 44 does not store the data in the storage unit 53, and returns to step S2. In addition, as a countermeasure for inevitable noise, etc., the determination condition can be set so that when a current exceeding a threshold value (in this embodiment, a charge rate of 0.2) is detected only within a very short time (several samples, such as 2 samples), it will not be determined that a current greater than 0.2 in charge rate has flowed. In the case where it is determined that a current with a charge rate of less than 0.2 has flowed from a certain moment to 20 seconds ago (Yes), the first determination unit 44 stores the data of process A at that moment (for example, current value, voltage value, temperature value, current cumulative value, SOC, etc.) as data D ( Figure 2 The data D is stored in the storage unit 53. Here, the storage unit 53 may be, for example, a volatile memory or a nonvolatile memory. If the data D is stored in the storage unit 53, the process proceeds to step S6.

[0048] In addition, the determination condition in step S4 is not limited to one condition. For example, different determination conditions can be set according to the timing of the determination. For example, after the state in which the determination condition is not satisfied becomes the state in which it is satisfied, until the data D is first stored, the determination condition can be set to whether the current with a charging rate of less than 0.2 continues for 10 seconds. After the determination condition is met and the data D is first stored, in the case where the above determination condition continues to be satisfied in this state, the determination condition can be set to whether the current with a charging rate of less than 0.2 continues for 5 seconds. However, in the case where the determination condition set to whether the current with a charging rate of less than 0.2 continues for 10 seconds or 5 seconds is not met once, the determination condition can be reset. Then, the determination condition can be set again to whether the current with a charging rate of less than 0.2 continues for 10 seconds. When the current starts to flow, etc., the detected data is sometimes difficult to stabilize. By setting different determination conditions according to the timing of the determination, the obtained data D is stable, and the reliability of the data D can be improved.

[0049] In addition, when current flows through the battery 1, an error may occur in the open circuit voltage OCV estimated from the detected voltage value. This error may be caused by a voltage drop. The smaller the current flowing through the battery 1, the smaller the error caused by the voltage drop. As described above, by using data D when the absolute value of the current value is low, the accuracy of the open circuit voltage OCV is improved, and as a result, the accuracy of the SOC estimated based on the open circuit voltage OCV is improved. The accuracy of the estimated SOC is improved, thereby improving the accuracy of the estimation of the full charge capacity F in step C.

[0050] In step S6, the second determination unit 45 determines whether the ignition switch is turned off. If the ignition switch is not turned off (No), the process returns to step S2, and the acquisition of data and the storage of data D that meet the predetermined conditions are repeated. If the ignition switch is turned off (Yes), the acquisition and extraction of data are completed, and the process proceeds to step S7.

[0051] In step S7, the third determination unit 46 determines whether the number of the extracted data D (the data D stored in the storage unit 53) is less than n. Here, n is an integer greater than or equal to 3. Although not particularly limited, n can be predetermined from the viewpoint of statistically estimating the full charge capacity F, the storage amount required for estimating the full charge capacity F, and the like. In the case where the number of the extracted data D is less than n (yes), the full charge capacity F of the battery 1 is not estimated, and the process ends. In the case where the number of the extracted data D is not less than n (the number of the extracted data D is n or more) (no), the full charge capacity F of the battery 1 is estimated. In addition, in the determination condition of whether to estimate the full charge capacity F or end the process, an additional condition can be set. For example, an additional condition can be set based on the maximum and minimum values ​​of the SOC of the stored data D. In the case where the number of the extracted data D is not less than n, and also in the case where the difference between the maximum and minimum values ​​of the SOC of the stored data D is less than a predetermined threshold value, the full charge capacity F of the battery 1 can be not estimated and the process ends.

[0052] <Step C of Estimating Full Charge Capacity F of Battery 1>

[0053] In the step C of estimating the full charge capacity F of the battery 1 , the full charge capacity F of the battery 1 to be measured is estimated based on the data D extracted in the step B (step S8 ).

[0054] In step S8, the second estimation unit 47 estimates the full charge capacity F of the battery 1 based on the current integrated value and the estimated SOC included in the data D. The second estimation unit 47 can statistically obtain the full charge capacity F from the current integrated value and the SOC included in the extracted data D. The full charge capacity F can be obtained, for example, by the least square method. In this way, the estimation accuracy of the full charge capacity F can be improved.

[0055] Figure 5 is a graph showing the relationship between the current integrated value and the SOC of the extracted data D. Here, the full charge capacity F is estimated based on the current integrated value and the SOC of the extracted data D. Figure 5 As shown, in the graph, the current integrated value and SOC of the extracted data D are plotted. The full charge capacity F can be calculated by finding the slope of the graph when the horizontal axis is SOC (%) and the vertical axis is the current integrated value (Ah), and multiplying the found slope by 100.

[0056] The full charge capacity F estimated in step S8 may be stored in the storage unit 53. The stored full charge capacity F may be referred to when estimating the full charge capacity next time. The storage unit 53 may also store the full charge capacity estimated last time and the like.

[0057] However, in the opinion of the inventors, the SOC is estimated based on the data obtained at two timing points when the current does not flow through the battery, and the full charge capacity F is estimated. For example, for a battery loaded in an electric vehicle (e.g., an electric vehicle (BEV), a plug-in hybrid electric vehicle (PHEV)), data is obtained before and after driving, before and after charging and discharging at a charging and discharging point, and when the electric vehicle is at rest, and the full charge capacity is estimated. At this time, an attempt is made to improve the estimation accuracy of the full charge capacity by obtaining data at two timing points with a large difference in SOC and estimating the full charge capacity. However, for batteries loaded in electric vehicles such as commercial vehicles with a long operating time and a short rest period between charging and discharging, sometimes sufficient rest time for estimating the SOC at two points cannot be obtained. In this case, sometimes data cannot be obtained stably, and the estimation accuracy of the full charge capacity is reduced. In addition, sometimes when the battery is charged just after the electric vehicle stops, the difference in SOC between the two points becomes smaller, and the estimation accuracy of the full charge capacity is reduced. Furthermore, in a hybrid electric vehicle (HEV) that repeatedly charges and discharges the battery while traveling, the difference in SOC between two points becomes smaller, and the estimation accuracy of the full charge capacity may decrease.

[0058] In this regard, in the above-mentioned embodiment, the method for estimating the full charge capacity of a battery includes: step A, including obtaining battery data D including voltage values, current values, and temperature values ​​obtained from a battery 1 to be measured over time, and processing the obtained data D; step B, extracting n or more data D that satisfy a predetermined condition; and step C, estimating the full charge capacity F of the battery 1 to be measured based on the data D extracted in step B. Here, n is an integer greater than or equal to 3.

[0059] In this full charge capacity estimation method, the full charge capacity F is estimated based on data D of more than 3 points, so the accuracy of the estimation of the full charge capacity F is improved compared with the case where the full charge capacity F is estimated based on data between 2 points. In addition, data D that meets a predetermined condition (in the above embodiment, a condition that can improve the estimation accuracy of the SOC) from the data obtained over time is extracted for the estimation of the full charge capacity F. The data D containing the SOC with relatively good accuracy that meets the above-mentioned judgment condition is used. As a result, the accuracy of the estimation of the full charge capacity F is improved. In addition, data that does not meet the predetermined condition is not extracted. Therefore, compared with the case where the full charge capacity F is estimated by simply increasing the amount of data, the error in the estimation of the full charge capacity F is reduced. In addition, by not making the amount of data too much, the memory used in the processing when estimating the full charge capacity F can be suppressed to a low level.

[0060] Furthermore, as described above, when the full charge capacity F is estimated based on data between two points, if the difference in SOC between the two points is small, the estimation accuracy of the full charge capacity may decrease. Fig. 9 is a graph showing the relationship between SOC and current integrated value. Fig. 9 The relationship between SOC and current integrated value is schematically shown in FIG. 1 , which does not necessarily reflect the actual form. Fig. 9 In FIG. 1 , the possible SOC error is shown by an arrow. Here, the possible SOC error does not depend on the SOC but is set to be fixed. Fig. 9 In the case where the difference in SOC is small ( Fig. 9 The double-dotted line) and the large case ( Fig. 9 The single-point dash line) is used to compare the curve with the case with the maximum slope and the case with no error ( Fig. 9 The solid line) curve Figure 1 As shown above. According to the findings of the present invention, when the difference in SOC is small (ba), the slope of the graph is prone to change compared to when the difference in SOC is large (ca). As a result, the error in the estimated value of the full charge capacity based on the slope of the graph may become larger. For example, in a hybrid vehicle that repeatedly charges and discharges the battery while driving, the difference in SOC between two points is unlikely to become large when the vehicle is parked or resting. However, in the above-mentioned full charge capacity estimation method, data D can be obtained while driving. Thus, data D obtained over a relatively wide range of SOCs while driving can be used. As a result, the accuracy of the estimation of the full charge capacity F can be improved.

[0061] In addition, in the step B of extracting the data D of the battery 1, if the data D extracted in the step B is greater than n, the data D may be further filtered. For example, the data D may be further filtered in descending order of priority based on a predetermined priority. The number of the filtered data D may be n or a predetermined number greater than n. An embodiment including a process of further filtering the data D based on priority is described below.

[0062] Figure 6 is a flowchart showing a process executed in the control device 40 of the full charge capacity estimating device 20. Figure 6 In the example, it is shown that when executing Figure 2 The flowchart for different processing steps shown in the figure. Figure 6 Steps S11 to S17 are respectively Figure 2 Steps S1 to S7 are the same, so detailed description is omitted.

[0063] In step S17, similarly to step S7, the third determination unit 46 determines whether the number of extracted data D is less than n. If the number of extracted data D is less than n (yes), the full charge capacity Fr of the battery 1 is not estimated and the process ends. If the number of extracted data D is greater than n (no), the process proceeds to step S18.

[0064] In step S18, the decision unit 48 determines the priority of the data D based on a predetermined priority. The data D is further screened in order of priority from high to low. The predetermined priority can be set based on a condition that can improve the estimation accuracy of the SOC. The priority can also be determined based on the data D stored in the storage unit 53.

[0065] In this embodiment, the priority is determined in such a way that the greater the change in the open circuit voltage relative to the change in the estimated value of the SOC, the higher the priority. Here, the priority is based on Figure 4 As described above, the SOC is estimated based on the open circuit voltage OCV estimated from the voltage behavior model and the OCV-SOC conversion table. Figure 4 As shown, the relationship between the open circuit voltage OCV and the SOC is not linear. The slope of the graph differs depending on the value of the SOC. For example, on the high SOC side of the graph, the slope of the graph tends to become larger. When the slope of the graph is larger, the error in the conversion from the open circuit voltage OCV to the SOC is smaller. When the slope of the graph is smaller, the error in the conversion from the open circuit voltage OCV to the SOC is larger. By determining the priority in such a way that the greater the change in the open circuit voltage OCV relative to the estimated value of the SOC, the higher the priority, the error in the estimated value of the SOC is reduced, and the full charge capacity Fr can be estimated with higher accuracy.

[0066] In the OCV-SOC conversion table, it can be divided into multiple intervals according to the SOC. For example, the intervals can be divided for each SOC 1% to 5%. The slope of the graph can be calculated for each divided interval. The priority can be determined as follows: the data of the SOC of the interval with a larger slope of the graph has a higher priority. In addition, each SOC (or each open circuit voltage OCV) in the OCV-SOC conversion table can be associated with the slope of the graph. The data D associated with the SOC with a larger slope of the graph can have a higher priority.

[0067] In addition, the data D1 can be extracted by the least square method. The current integrated value and SOC of each data D are plotted on the curve graph, and a least square straight line is drawn. The data D that is farther away from the least square straight line can be set to a lower priority. The data D with a low priority can be deleted in such a way that the number of data D1 determined by the memory capacity of the control device 40 is left.

[0068] A predetermined number of data D1 can be extracted from the data D extracted in process B based on the priority determined in the determination unit 48. The number of data D1 extracted can be a predetermined number, or it can be determined as a ratio relative to the data D extracted in process B. As described above, the number of data D1 is determined according to the memory capacity of the control device 40, so it is not particularly limited. The number of data D1 can be selected from a number of more than 3, or from a number of more than 10. The number of data D1 can be selected from a number of less than 1000, or from a number of less than 500. The number of data D1 can be set to less than 1 / 2 of the data D, or less than 1 / 10. The number of data D1 can be determined based on the memory capacity of the control device 40. In step S18, if data D1 with a high priority is screened out, proceed to step S19.

[0069] In the above-mentioned embodiment, a method of filtering the data D extracted in process B based on the priority is described, but the present invention is not limited to this method. For example, when the priority of all the data D extracted in process B is higher than a predetermined threshold, all the data D can be used for estimating the full charge capacity Fr of process C. For example, by using a large amount of data D with a high priority, the estimation accuracy of the full charge capacity Fr in process C can be improved.

[0070] In step S19, the full charge capacity Fr is estimated based on the data D1 selected from the extracted data D (process C). In step S19, the full charge capacity Fr is estimated by the same method as in step S8 (see step S19). Figure 2 ) The full charge capacity Fr is estimated by the same method as in the above. Here, the full charge capacity Fr is statistically obtained from the current integrated value and SOC included in the data D1.

[0071] Figure 7 is a graph showing the relationship between the current integrated value and the SOC of the filtered data D1. Data D1 is further filtered from the data D based on the priority. Figure 7As shown in FIG. 1 , in the graph plotting the current integrated value and SOC of data D1, the deviation of the data points becomes smaller than that of the graph plotting the current integrated value and SOC of data D. In this way, by using the data D1 with high priority for estimating the full charge capacity, the accuracy of the full charge capacity estimation can be improved. In addition, by filtering the data D based on the priority, the memory used in the process of estimating the full charge capacity can be reduced.

[0072] In this embodiment, the full charge capacity estimation method further includes: step D, according to a predetermined condition, weighting the full charge capacity Fp estimated last time and the full charge capacity Fr estimated in step C to update the full charge capacity. Here, the full charge capacity Fr is the full charge capacity Fr estimated in step S19 of step C.

[0073] <Step D of Weighting Full Charge Capacity Fp and Full Charge Capacity Fr>

[0074] The step D of weighting the full charge capacity Fp and the full charge capacity Fr includes: calculating the weighting coefficient W ( Figure 6 Step S20); and using the weighting coefficient W to estimate the full charge capacity F ( Figure 6 Step S21).

[0075] In step S20, the second calculation unit 49 calculates the weighting coefficient W according to the predetermined conditions. The second calculation unit 49 calculates the weighting coefficient W based on the screened data D1 (or the extracted data D). In this embodiment, the predetermined conditions of process D are set based on the acquisition time, temperature value, estimated value of SOC of the data D1 extracted in process B, and the number of data D1 extracted in process B. In this embodiment, the weighting coefficient W is determined based on the coefficient W1 related to the acquisition time of the data D1, the coefficient W2 related to the temperature value of the battery 1, the coefficient W3 related to the estimated value of the SOC of the battery 1, and the coefficient W4 related to the number of data D1. Here, the weighting coefficient W is calculated based on the following formula (3):

[0076] W=W1×W2×W3×W4 (3)

[0077] Each coefficient W1 to W4 is set to be greater than or equal to 0 and less than or equal to 1. Therefore, the weighting coefficient W can be greater than or equal to 0 and less than or equal to 1. Regarding each coefficient W1 to W4, a value is assigned according to the value of each parameter. Regarding each coefficient W1 to W4, the coefficient corresponding to the value of each parameter can be determined in the form of a table. The following describes each coefficient W1 to W4.

[0078] <Coefficient W1 related to the acquisition time of data D1>

[0079] The acquisition time of data D1 may be, for example, the time taken to acquire data D1 used in estimating the full charge capacity Fr. The data D acquired in process A is acquired in association with the time. Therefore, the data D1 used in process C also contains information about the time. In this embodiment, the time between the first acquired data D1 and the last acquired data D1 among the data D1 selected from the data D is used as the acquisition time of data D1. The longer the acquisition time of data D1 is, the greater the influence on the current cumulative value is, and the shorter the acquisition time of data D1 is, the more the influence on the current cumulative value can be suppressed. The coefficient W1 can be set to be higher when the acquisition time of data D1 is shorter, and lower when the acquisition time of data D1 is longer.

[0080] <Coefficient W2 Related to the Temperature Value of Battery 1>

[0081] The temperature value of the battery 1 may affect the estimation error when estimating the SOC from the open circuit voltage OCV. The lower the temperature value of the battery 1, the lower the internal resistance 62, 63b of the battery 1 (refer to Figure 3 ) is higher, so the estimation error of OCV is larger. As a result, the estimation error of SOC is larger. Therefore, the lower the temperature value of battery 1 is, the larger the estimation error is. The higher the temperature value of battery 1 is, the smaller the estimation error is. The coefficient W2 can be set to be higher as the temperature value of battery 1 is higher, and lower as the temperature value of battery 1 is lower.

[0082] <Coefficient W3 Related to Estimated Value of SOC of Battery 1>

[0083] The range of the estimated value of the SOC of the battery 1 can affect the error in the estimation of the full charge capacity Fr. For example, in the case where the full charge capacity Fr is estimated by data D1 with a wide SOC range, the influence of the errors of the individual data D1 on the error in the estimation of the full charge capacity Fr becomes smaller. On the other hand, in the case where the full charge capacity Fr is estimated by data D1 with a narrow SOC range, the influence of the errors of the individual data D1 on the error in the estimation of the full charge capacity Fr becomes larger. The coefficient W3 can be set according to the difference between the maximum and minimum values ​​of the estimated value of the SOC in the data D1. The coefficient W3 can be set to be higher the wider the range of the estimated value of the SOC (for example, the difference between the maximum and minimum values), and lower the narrower the range of the estimated value of the SOC.

[0084] <Coefficient W4 related to the amount of data D1>

[0085] The amount of data D1 may affect the estimated value of the full charge capacity Fr. When estimating the full charge capacity Fr by the least square method or the like, the smaller the amount of data D1, the larger the estimation error; the larger the amount of data D1, the smaller the estimation error. The coefficient W4 may be set to be higher as the amount of data D1 increases, and lower as the amount of data D1 decreases.

[0086] As described above, the coefficients W1 to W4 can be determined based on the acquisition time of the data D1, the temperature value, the estimated value of SOC, and the number of data D1, and the weighting coefficient W can be calculated by the above formula (3). As described with respect to each coefficient W1 to W4, the value of the weighting coefficient W can be larger when the data with higher reliability of the estimated value of the full charge capacity Fr is used. However, the calculation of the weighting coefficient W is not limited to this method. The weighting coefficient W can also be calculated by, for example, a multidimensional table corresponding to the number of parameters that contribute to the weighting (4 in the above embodiment). In the calculation of the weighting coefficient W based on the multidimensional table, it can be configured so that if each parameter is input, a value of the weighting coefficient W is output. In addition, the parameters used to calculate the weighting coefficient W are not limited to the acquisition time of the data D1, the temperature value, the estimated value of SOC, and the number of data D1 described above. In the calculation of the weighting coefficient W, at least any one of these parameters can be selected. In addition, other parameters other than the acquisition time of the data D1, the temperature value, the estimated value of SOC, and the number of data D1 can be included.

[0087] If the weighting coefficient W is calculated in step S20 , the full charge capacity F is estimated in step S21 .

[0088] In step S21, the third estimation unit 50 estimates the full charge capacity F using the weighting coefficient W calculated in step S20. In this embodiment, the third estimation unit 50 estimates the full charge capacity F based on the full charge capacity Fr estimated in step C, the full charge capacity Fp stored in the storage unit 53, and the weighting coefficient W. Here, the full charge capacity F is estimated based on the following formula (4):

[0089] F=W×Fr+(1-W)×Fp (4)

[0090] The full charge capacity F is estimated as described above. In this embodiment, the full charge capacity estimation method further includes: step D, weighting the full charge capacity Fp estimated last time and the full charge capacity Fr estimated in step C according to a predetermined condition. In the estimation of the full charge capacity F, the full charge capacity Fp estimated last time is used in addition to the full charge capacity Fr estimated in step C, thereby improving the accuracy of the estimation of the full charge capacity F.

[0091] In addition, in the above-mentioned embodiment, the conditions for weighting are set based on the acquisition time of the data D1, the temperature value, the estimated value of SOC, and the number of data D1. These parameters can affect the estimation accuracy of the full charge capacity Fr in process C. In other words, these parameters can affect the reliability of the data D1 used when estimating the full charge capacity Fr in process C. Here, the higher the reliability of the data D1 used when estimating the full charge capacity Fr in process C, the larger the weighting coefficient W. In this case, the weight of the full charge capacity Fr estimated in process C is greater. On the other hand, the lower the reliability of the data D1, the greater the weight of the full charge capacity Fp obtained last time. By determining the weighting conditions based on the acquisition time of the data D1, the temperature value, the estimated value of SOC, and the number of data D1 that can affect the reliability of the data D1, the accuracy of the estimation of the full charge capacity F can be improved.

[0092] In the above-mentioned embodiment, as an example of an embodiment of estimating the full charge capacity F when the external load stops, the case where the battery 1 is used as a vehicle-mounted battery is described. However, it is not limited to this method, and the full charge capacity F can also be estimated when the external load is not stopped. For example, it is also possible not to determine the on and off of the ignition switch in steps S6 and S16, but to estimate the full charge capacity F at the time point when a predetermined number of data D is extracted. In addition, the technology disclosed herein can also be applied to a battery 1 in which current always flows. As the battery 1, for example, a fixed-purpose battery connected to system power, a power generation device, an electrical device, etc. can be cited. The following describes the process of estimating the full charge capacity in the battery 1 used in a method in which current can always flow.

[0093] Figure 8 is a flowchart showing a process executed in the control device 40 of the full charge capacity estimating device 20. Figure 8 In the following description, the method of estimating the full charge capacity F of the battery 1 as a stationary battery is shown. Figure 2 , Figure 6 In the case of the same processing as the process executed in, the detailed description is omitted.

[0094] like Figure 8 The processing shown can be started at a predetermined timing. It is not particularly limited, but the processing can be started at a fixed time during a fixed period, such as once in a few days, once in a week, or once in a few weeks. In addition, the owner can start the processing by operating the terminal that manages the battery 1. In step S31, at least a part of the current integrated value and SOC calculated before the start of the processing can be reset. For example, the old part of the stored current integrated value and SOC can be reset by a fixed amount or a fixed ratio.

[0095] In steps S32 to S34, the Figure 2 The same processing as steps S2 to S4 is performed. In step S32, data D is obtained. In step S33, the current integrated value and the estimated value of SOC are obtained. In step S34, it is determined whether data D meets the predetermined condition. In step S35, if data D meets the predetermined condition, the data D is stored.

[0096] In step S36, the fourth determination unit 51 determines whether any of the following conditions is satisfied: the number of stored data D becomes a predetermined number of N or more; and X hours have passed since step S1. In the case where any of these conditions is satisfied (the number of stored data D becomes N or more, or X hours have passed since step S1) (yes), the process proceeds to step S37. In the case where X hours have not passed and the number of stored data D is less than the predetermined number of N (no), the process returns to step S32, and the acquisition of data and the storage of data D that satisfy the predetermined conditions are repeated. In addition, from the perspective of the number of data required when estimating the full charge capacity F statistically, "N" can be predetermined. "N" is set to a number greater than the above-mentioned "n". Regarding "N", from the perspective of improving the estimation accuracy of the full charge capacity F, it is preferably set to a number as large as possible within the constraints of the storage amount and the calculation amount of the control device 40. However, "N" can be set so as not to make the above-mentioned weight W1 too small.

[0097] In step S37, the fifth determination unit 52 determines whether the number of stored data D is less than n. In the case where the number of stored data D is less than n (yes), the full charge capacity F of the battery 1 is not estimated, and a series of processes are terminated. In the next process, the current integrated value and SOC calculated in a series of processes may be reset, or the old data D may be reset (step S31). In the case where the number of stored data D is not less than n (no), proceed to step S38. If the number of stored data D is n or more, the process of estimating the full charge capacity is started.

[0098] In steps S38 to S41, execute Figure 6 The same processing as steps S18 to S21 of the process is performed. In step S38, the priority of data D is determined, and data D is screened. In step S39, the full charge capacity Fr is estimated by the above method. In step S40, the weighting coefficient W is calculated according to a predetermined condition. In step S41, the full charge capacity F is estimated using the weighting coefficient W. The full charge capacity F is estimated based on the full charge capacity Fr estimated in step C, the last estimated full charge capacity Fp, and the weighting coefficient W. The estimated full charge capacity F is stored in the storage unit 53.

[0099] In addition, in this embodiment, the battery 1 is used in a manner that allows current to flow. Therefore, after the full charge capacity F is estimated in step S41, and when the process is terminated without estimating the full charge capacity F, the current continues to flow through the battery 1. After a series of processes are completed, the process is immediately restarted, and the process of estimating the full charge capacity can be restarted.

[0100] However, in the battery 1 used in a manner in which current can always flow, there is no rest period, so it is difficult to obtain data and estimate the full charge capacity at two timing points where the difference in SOC is large, such as before and after charging or before and after discharging. According to the technology disclosed herein, even for the battery 1 used in a manner in which current can always flow without a rest period, the full charge capacity can be estimated. In addition, the full charge capacities F and Fr are estimated based on data with high reliability (data D that meets predetermined conditions, predetermined data D1 with high priority), so the accuracy of the estimation of the full charge capacities F and Fr is good.

[0101] In addition, the extraction of the data D and the screening of the data D1 in the step B are not limited to the above-mentioned embodiment.

[0102] In the above-mentioned embodiment, the conditions for extracting the data D in step B are set according to whether the magnitude of the current value obtained in step A is below a predetermined threshold value for a predetermined period of time (steps S4, S14, S34). However, the extraction of data D is not limited to this method, and different conditions may be used.

[0103] The predetermined conditions of steps S4, S14, and S34 may be set based on the estimated value of the polarization voltage of battery 1 determined based on data D obtained in step A. For example, the conditions may be set based on whether the ratio of the estimated value of polarization (Vp+Vohm) to the maximum value of polarization (Vohm+Vpmax) is less than a predetermined value (for example, less than 0.1). The conditions may be set so that data D is stored when the estimated value of polarization (Vp+Vohm) is less than the above value. In addition, Vpmax is Figure 3The maximum value of the voltage Vp applied to the CR parallel circuit 63 when the storage capacity of the capacitor 63a is at its maximum can be obtained in advance. The larger the current flowing through the battery 1 in the same direction, and the longer the current flows through the battery 1 in the same direction, the more the polarization of the battery 1 can progress. If the current flowing through the battery 1 is small for a long time (for example, the current flowing through the battery 1 is close to 0A for several seconds to several minutes), the polarization gradually decreases. The reduction in polarization varies depending on the model of the battery 1. In the control device 40, for example, a table can be saved that can refer to the degree of polarization as a numerical value from the data D (for example, the current value and time). In step B, the data D of the polarization hour can be extracted by referring to the table. Regarding the estimated value of polarization, a threshold value for determining whether to extract the data D can be set. In addition, the table used here can be obtained in advance according to the model of the battery 1 through experiments, simulations, theoretical calculations, etc., and saved in the control device 40.

[0104] As described above, for the SOC of the battery 1, the open circuit voltage OCV estimated based on the formula (2) is used. The smaller the estimated value (Vp+Vohm) of the polarization voltage is, the smaller the estimation error of the open circuit voltage OCV is. Therefore, a threshold value of the estimated value (Vp+Vohm) of the polarization voltage can be set, and data D of the estimated value (Vp+Vohm) of the polarization voltage below the threshold value can be stored. By extracting data D with a small estimation error of the open circuit voltage OCV, the estimation error of the full charge capacity F can be reduced.

[0105] The predetermined conditions of steps S4, S14, and S34 can be set based on the fluctuation range of the current value obtained in step A. The fluctuation range of the current value can be determined, for example, based on the difference between the maximum value and the minimum value of the current value contained in the data D obtained multiple times. The smaller the fluctuation range of the current value, the smaller the estimation error of the open circuit voltage OCV. In step B, a threshold value of the fluctuation range of the current value can be set, and data D with the fluctuation range of the current value below the threshold value can be stored. By extracting data D using the fluctuation range of the current value as a condition, the estimation error of the open circuit voltage OCV becomes smaller, and the estimation error of the full charge capacity F can be reduced.

[0106] The predetermined conditions of steps S4, S14, and S34 can be set based on the change in SOC determined based on the data obtained in process A. The change in SOC can be determined, for example, based on the difference between the SOC estimated based on the obtained data D and the SOC estimated based on the data obtained last time. Data D with a small change in SOC suppresses the influence on the estimation error of the full charge capacity F. For example, in the case where the current value flowing through the battery 1 is small, the current balance is close to 0, and the change in SOC becomes smaller. In process B, a threshold value for the change in SOC can be set, and data D with a change in SOC below the threshold value can be stored. By extracting data D as a condition, the estimation error of the open circuit voltage OCV becomes smaller, and the estimation error of the full charge capacity F can be reduced.

[0107] The predetermined conditions of steps S4, S14, and S34 may be set based on the variance of the current values ​​acquired a plurality of times. When the variance of the current value is small, data D including the most recently acquired current value may be stored.

[0108] The predetermined conditions of steps S4, S14, and S34 can be set based on the change in the open circuit voltage OCV relative to the estimated value of the SOC. Figure 4 ), the greater the slope of the graph, the smaller the error in the conversion from the open circuit voltage OCV to the SOC. The data D may be stored when the open circuit voltage OCV (or SOC) belonging to the interval where the slope of the graph becomes greater is estimated.

[0109] In the above embodiment, conditions are set based on the change in open circuit voltage relative to the estimated value of SOC for filtering the data D1 from the extracted data D in step B (steps S18 and S38). However, filtering the data D1 is not limited to this method, and different conditions may be used.

[0110] The priority of steps S18 and S38 can be determined based on the elapsed time when the data D is extracted. For example, when a fixed time has passed since the first extraction of the data D, the priority determination condition can be set in a manner that reduces the priority of the data D after the fixed time has passed. When a long time has passed since the first extraction of the data D, the influence of the error of the current sensor 32 may become greater. As a result, the estimation error of the SOC may become larger. Although not particularly limited, the elapsed time here can be set to about 30 minutes to 1 hour.

[0111] The priority of steps S18 and S38 can be determined based on the battery temperature value when extracting data D. The temperature value of battery 1 can affect the estimation error when estimating SOC from open circuit voltage OCV. The lower the temperature value of battery 1, the larger the estimation error. The higher the temperature value of battery 1, the smaller the estimation error. For example, in the case where the deviation of the temperature value included in data D is large, the priority determination condition can be set in a manner to reduce the priority of data D with a low temperature value.

[0112] The condition for determining the priority may be one of the above conditions, or a plurality of the above conditions may be combined to determine the priority.

[0113] In addition, the estimates of the open circuit voltage OCV, SOC, full charge capacity F, etc., can be appropriately corrected. For example, in the equation (2) for estimating the open circuit voltage OCV, a term for correcting voltage hysteresis can be included. In addition, the magnitude of hysteresis can be different depending on the SOC. Data containing an SOC with large hysteresis can be processed in a manner that reduces the contribution when estimating the full charge capacity.

[0114] The data including the SOC with large hysteresis can be corrected by reducing the weighting coefficient W when calculating the weighting coefficient W. When the number of data D and D1 is large and the range of the SOC included in the data D and D1 is wide but the current integrated value is small, the weighting coefficient W can be corrected by increasing it when calculating the weighting coefficient W. In this case, the battery 1 is charged and discharged in a well-balanced manner, so the estimation error of the full charge capacity can be reduced.

[0115] When estimating the SOC based on the open circuit voltage OCV and the current integrated value, the reliability of each data D can be calculated, and the SOC can be estimated by weighting according to the reliability. Although not particularly limited, the data D can be processed in a manner that improves the reliability when the current value is small, the temperature value of the battery 1 is high, the slope of the open circuit voltage OCV-SOC curve is large, etc. Regarding the current value, the reliability can be determined not only based on the instantaneous current of 0.1 seconds, but also based on the current of about 10 seconds to 300 seconds.

[0116] When estimating the full charge capacity Fr, the reliability interval of the data D and D1 can be obtained, and the weighting coefficient W can be determined according to the width of the reliability interval (the difference between the upper and lower limits of the reliability interval). The smaller the width of the reliability interval, the larger the weighting coefficient W can be set.

[0117] Above, various descriptions have been made to the technology disclosed herein. Unless otherwise mentioned, the embodiments cited herein do not limit the present invention. In addition, the technology disclosed herein can be subjected to various changes, and as long as no special problems are generated, each component and each process mentioned herein can be appropriately omitted or appropriately combined. In addition, this specification includes the disclosures described in the following items.

[0118] Item 1: A method for estimating the full charge capacity of a battery, comprising:

[0119] Step A includes acquiring battery data obtained from a battery to be measured over time and processing the acquired data, wherein the battery data includes a voltage value, a current value, and a temperature value;

[0120] Step B, extracting n or more data satisfying a predetermined condition from at least one of the data acquired in the step A and the data obtained through processing in the step A; and

[0121] Step C, estimating the full charge capacity of the battery to be measured based on the data extracted in Step B,

[0122] Here, n is an integer greater than or equal to 3.

[0123] Item 2: A method for estimating the full charge capacity of a battery as described in Item 1,

[0124] The predetermined condition of the step B is that the magnitude of the current obtained in the step A is less than or equal to a predetermined threshold value for a continuous period of time.

[0125] Item 3: A method for estimating the full charge capacity of a battery as described in Item 1 or 2,

[0126] In the process B, when the number of data extracted in the process B is greater than n, the data extracted in the process B is further screened in descending order of priority based on a predetermined priority.

[0127] Item 4: A method for estimating the full charge capacity of a battery as described in Item 3,

[0128] The step A includes processing the acquired data based on a predetermined battery voltage behavior model to obtain estimated values ​​of the open circuit voltage and the SOC,

[0129] The priority is determined such that the priority becomes higher as the change in the open circuit voltage relative to the change in the estimated value of the SOC becomes larger.

[0130] Item 5: The method for estimating the full charge capacity of a battery according to any one of Items 1 to 4,

[0131] Stores the last estimated full charge capacity.

[0132] The method further includes a step D of weighting the full charge capacity estimated last time and the full charge capacity estimated in the step C according to a predetermined condition to update the full charge capacity.

[0133] Item 6: A method for estimating the full charge capacity of a battery as described in Item 5,

[0134] The predetermined condition of step D is set based on at least one of the acquisition time of the data extracted in step B, the temperature value, the estimated value of SOC, and the amount of data extracted in step B.

[0135] The estimated value of the SOC is estimated based on the data acquired in the step A and a predetermined battery voltage behavior model.

[0136] Item 7: The method for estimating the full charge capacity of a battery according to any one of Items 1 to 6,

[0137] The process A comprises:

[0138] The current value is integrated to calculate the current integrated value up to the time of each of the data of the battery obtained over time; and

[0139] An estimated value of the SOC is obtained based on the data of the battery and a predetermined voltage behavior model.

[0140] Item 8: A method for estimating the full charge capacity of a battery as described in Item 7,

[0141] The full charge capacity of the battery to be measured is estimated based on the current integrated value and the estimated value of the SOC.

[0142] Item 9: A method for estimating the full charge capacity of a battery as described in Item 1,

[0143] The predetermined condition of the step B is determined based on an estimated value of polarization of the battery obtained by processing the data acquired in the step A.

[0144] Item 10: A method for estimating the full charge capacity of a battery as described in Item 1,

[0145] The predetermined condition of the step B is determined based on the fluctuation range of the current value obtained in the step A.

[0146] Item 11: A method for estimating the full charge capacity of a battery as described in Item 1,

[0147] The predetermined condition of the step B is determined based on the change in SOC obtained by processing the data acquired in the step A.

[0148] Item 12: A full charge capacity estimation device comprising:

[0149] Sensors; and

[0150] Control device,

[0151] The sensor has:

[0152] Voltage sensor;

[0153] a current sensor; and

[0154] Temperature sensor,

[0155] The control device is configured to perform:

[0156] A process comprising acquiring battery data including voltage values, current values, and temperature values ​​of a battery to be measured over time and processing the acquired data;

[0157] A process of extracting n or more data satisfying a predetermined condition from at least one of the acquired data and the processed data, wherein n is an integer greater than or equal to 3; and

[0158] A process of estimating the full charge capacity of the battery to be measured based on the extracted data.

[0159] Item 13: The full charge capacity estimating device as described in Item 12,

[0160] The control device is configured to execute a process of further filtering the extracted data in descending order of priority based on a predetermined priority when the extracted data is greater than n.

[0161] Item 14: The full charge capacity estimating device according to Item 12 or 13,

[0162] The control device stores the last estimated full charge capacity.

[0163] The control device is configured to execute a process of weighting the last estimated full charge capacity and the full charge capacity estimated based on the extracted data according to a predetermined condition.

Claims

1. A method for estimating the full charge capacity of a battery, comprising: Step A includes obtaining battery data and processing the obtained data, wherein: The battery data is obtained from the battery to be measured over time, and the battery data includes a voltage value, a current value, and a temperature value; Step B, extracting n or more data satisfying a predetermined condition from at least one of the data acquired in the step A and the data obtained through processing in the step A; and Step C, estimating the full charge capacity of the battery to be measured based on the data extracted in Step B, Here, n is an integer greater than or equal to 3.

2. The method for estimating the full charge capacity of a battery according to claim 1, wherein: The predetermined condition of the step B is that the magnitude of the current obtained in the step A is equal to or smaller than a predetermined threshold value for a predetermined period of time.

3. The method for estimating the full charge capacity of a battery according to claim 1 or 2, wherein: In the process B, when the number of data extracted in the process B is greater than n, the data extracted in the process B is further screened in descending order of priority based on a predetermined priority.

4. The method for estimating the full charge capacity of a battery according to claim 3, wherein: The step A includes processing the acquired data based on a predetermined battery voltage behavior model to obtain estimated values ​​of the open circuit voltage and the SOC, The priority is determined such that the priority becomes higher as the change in the open circuit voltage relative to the change in the estimated value of the SOC becomes larger.

5. The method for estimating the full charge capacity of a battery according to claim 1 or 2, wherein: Stores the last estimated full charge capacity. The method further includes a step D of weighting the full charge capacity estimated last time and the full charge capacity estimated in the step C according to a predetermined condition to update the full charge capacity.

6. The method for estimating the full charge capacity of a battery according to claim 5, wherein: The predetermined condition of step D is set based on at least one of the acquisition time of the data extracted in step B, the temperature value, the estimated value of SOC, and the amount of data extracted in step B. The estimated value of the SOC is estimated based on the data acquired in the step A and a predetermined battery voltage behavior model.

7. The method for estimating the full charge capacity of a battery according to claim 1 or 2, wherein: The process A comprises: The current value is integrated to calculate the current integrated value up to the time of each of the data of the battery obtained over time; and An estimated value of the SOC is obtained based on the data of the battery and a predetermined voltage behavior model.

8. The method for estimating the full charge capacity of a battery according to claim 7, wherein: The full charge capacity of the battery to be measured is estimated based on the current integrated value and the estimated value of the SOC.

9. The method for estimating the full charge capacity of a battery according to claim 1, wherein: The predetermined condition of the step B is determined based on an estimated value of polarization of the battery obtained by processing the data acquired in the step A.

10. The method for estimating the full charge capacity of a battery according to claim 1, wherein: The predetermined condition of the step B is determined based on the fluctuation range of the current value obtained in the step A.

11. The method for estimating the full charge capacity of a battery according to claim 1, wherein: The predetermined condition of the step B is determined based on the change in SOC obtained by processing the data acquired in the step A.

12. A full charge capacity estimation device, comprising: Sensors; and Control device, The sensor has: Voltage sensor; a current sensor; and Temperature sensor, The control device is configured to perform: The method includes acquiring battery data including voltage value, current value and temperature value of the battery to be measured over time and processing the acquired data; A process of extracting n or more data satisfying a predetermined condition from at least one of the acquired data and the processed data, wherein: n is an integer greater than 3; and A process of estimating the full charge capacity of the battery to be measured based on the extracted data.

13. The full charge capacity estimation device according to claim 12, wherein: The control device is configured to execute the following processing: when the extracted data is greater than n, the extracted data is further filtered in descending order of priority based on a predetermined priority.

14. The full charge capacity estimation device according to claim 12 or 13, wherein: The control device stores the last estimated full charge capacity. The control device is configured to execute a process of weighting the last estimated full charge capacity and the full charge capacity estimated based on the extracted data according to a predetermined condition.

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