Control device for secondary battery, electronic device, and control method for secondary battery

Abstract

Provided is a control device of a secondary battery, which includes a control section that controls to correct a battery characteristic related to an open-circuit voltage with respect to a remaining capacity of a secondary battery. In the control device of the secondary battery, the control section acquires data of a plurality of open-circuit voltages in the battery characteristic in charging of the secondary battery, the control section corrects the open-circuit voltage between each of data pairs of a combination of at least a part of the data of the plurality of open-circuit voltages at the time of full charging of the secondary battery, and the control section corrects a full charging capacity calculated by the correction of the open-circuit voltage between the data pairs by weighted average of a difference between respective remaining capacities corresponding between the data pairs.

Description

TECHNICAL FIELD

[0001] The present application relates to a control device for a secondary battery such as a lithium-ion secondary battery, a control method thereof, and an electronic device provided with the secondary battery. BACKGROUND

[0002] A secondary battery such as a lithium-ion secondary battery has a problem that a full charge capacity (actual capacity) decreases due to deterioration by repeated charge and discharge. Therefore, a technique of estimating a full charge capacity and characteristics of a secondary battery is known. Herein, terms and abbreviations used below are defined.

[0003] OCV (Open Circuit Voltage): Open circuit voltage (mV)

[0004] SOC (Sum of Charge): Charge amount (mAh)

[0005] RSOC (Relative State of Charge): Residual capacity (%)

[0006] FCC (Full Charge Capacity): Full charge capacity (mAh)

[0007] As a capacity correction of a secondary battery so far, for example, there are the following methods.

[0008] (1) Correction of a secondary battery

[0009] After a secondary battery is once fully charged, a full charge capacity of the secondary battery is corrected by fully discharging it. This method is high in precision, but an electronic device (personal computer or the like) using the secondary battery cannot be used for a prescribed time, so the frequency of implementation is low.

[0010] (2) Two-point OCV correction (for example, refer to Patent Literature 1)

[0011] In the secondary battery capacity correction technique of the prior art example, a full charge capacity of a secondary battery is corrected from OCV data of two points and charge and discharge amount therebetween. Specifically, the following processing is performed.

[0012] (Step SS1) An open circuit voltage OCV1 (mV) when one hour or more elapses without performing charge and discharge is acquired, and a charge and discharge amount AQ (mAh) of a secondary battery during use by a user is measured.

[0013] (Step SS2) An open circuit voltage OCV2 (mV) when the next one hour or more elapses without performing charge and discharge is acquired.

[0014] (Step SS3) The full charge capacity is calculated from the acquired OCV data and the RSOC-OCV characteristic inherent to the secondary battery group.

[0015] Prior Art Documents

[0016] Patent Documents

[0017] Patent Document 1: Japanese Patent Application Publication No. 2018-169238 SUMMARY

[0018] -PROBLEMS TO BE SOLVED BY THE INVENTION-

[0019] Generally, the RSOC at the time when the OCV is acquired is calculated from the RSOC-OCV characteristic of the secondary battery. In particular, when the RSOC-OCV characteristic is not corrected for the deterioration of the secondary battery and the decrease in the full charge capacity, for example, a jump estimate of the full charge capacity (margin) occurs. Specifically, the RSOC-OCV characteristic changes less with respect to the change in the capacity and the temperature, but even if the characteristic deviates, there is a problem that a large deviation occurs in the calculation at two points where data is acquired.

[0020] An object of the present disclosure is to provide a control device of a secondary battery that can correct the full charge capacity of a secondary battery with higher precision than the two-point OCV correction method involved in the prior art.

[0021] - MEANS FOR SOLVING THE PROBLEMS -

[0022] The control device of a secondary battery involved in the present disclosure is a control device of a secondary battery that includes a control section that performs control to correct a battery characteristic involved in the open-circuit voltage with respect to the remaining capacity of a secondary battery,

[0023] The control section acquires data of a plurality of open-circuit voltages in the battery characteristic in charging of the secondary battery,

[0024] The control section performs correction of the open-circuit voltage between each data pair when data of at least a part of the combination among the data of the plurality of open-circuit voltages is full charged in the secondary battery,

[0025] The control section performs correction of the full charge capacity calculated by performing the correction of the open-circuit voltage between the data pairs by weighted average of the difference in the respective remaining capacities corresponding between the data pairs.

[0026] - EFFECT OF THE INVENTION -

[0027] According to the control device of a secondary battery in the present disclosure, the full charge capacity of a secondary battery can be corrected with higher precision than the two-point OCV correction method involved in the prior art. BRIEF DESCRIPTION OF DRAWINGS

[0028] Figure 1 is an appearance view of an electronic device equipped with a lithium-ion secondary battery according to the embodiment.

[0029] Figure 2 is a block diagram showing a functional configuration example of the electronic device of Figure 1

[0030] Figure 3 is a block diagram showing a configuration example of the lithium-ion secondary battery of Figure 2

[0031] Figure 4 is a block diagram showing a configuration example of the OCV prediction unit of Figure 3

[0032] Figure 5 is a flowchart showing a battery characteristic calculation process including a battery capacity correction process performed by the battery characteristic calculation unit of Figure 3

[0033] Figure 6 is a flowchart showing a subprogram of step S1, i.e., an OCV prediction process at the time of battery charging, of Figure 5

[0034] Figure 7 is a graph showing RSOC-OCV characteristics representing the battery capacity correction process according to the embodiment. DETAILED DESCRIPTION

[0035] Hereinafter, the embodiments will be described in detail with appropriate reference to the accompanying drawings. However, unnecessary detailed description can be omitted. For example, detailed description of known matters, repetitive description of substantially the same structure can be omitted. This is to avoid the following description from becoming unnecessarily redundant and to make it easy for those skilled in the art to understand.

[0036] In addition, the inventors provide the accompanying drawings and the following description in order for those skilled in the art to fully understand the present disclosure, and do not intend to limit the subject matter of the claims by these.

[0037] (Embodiment)

[0038] Figure 1 is an appearance view of an electronic device equipped with a lithium-ion secondary battery.

[0039] Figure 1 In the personal computer 100, a lithium-ion secondary battery (not shown in FIG. 1) is equipped in order to perform an operation. Figure 1 Figure 2 Figure 3 ​​​​​​​(300). The lithium-ion secondary battery is stored, for example, on the bottom surface that abuts against the back of the keyboard 101, or on the rear side of the bottom surface of the joint between the keyboard 101 and the display 102.

[0040] In this disclosure, a personal computer is used as an example of an electronic device equipped with a lithium-ion secondary battery. However, this disclosure is not limited to this. If the electronic device operates by equipping itself with a secondary battery such as a lithium-ion secondary battery, it may also be other electronic devices such as smartphones, mobile phones, and tablets.

[0041] Figure 2 This is a block diagram illustrating a functional structure example of an electronic device equipped with the lithium-ion secondary battery according to this embodiment. Figure 2 The personal computer 100 includes a main body 200 and a lithium-ion secondary battery 300. The main body 200 includes a power terminal 201, a control unit 202, and a load circuit 203.

[0042] exist Figure 2 In this embodiment, power terminal 201 is the terminal for connecting power cords, etc., when power is supplied from an external source. The lithium-ion secondary battery 300 is charged using the power supplied here. Control unit 202 controls the load circuit 203 and other hardware of the personal computer 100. Specifically, in this embodiment, control unit 202 controls the lithium-ion secondary battery 300. Control unit 202 may include an MPU (Micro-Processing Unit), a dedicated IC (Integrated Circuit), etc. Furthermore, control unit 202 may include a DSP (Digital Signal Processor), an FPGA (Field Programmable Gate Array), etc.

[0043] The load circuit 203 is an electronic circuit that operates using power input from the power supply terminal 201 or power supplied from the lithium-ion secondary battery 300. In the case of the personal computer 100, this corresponds to various devices that generally constitute a computer, such as the CPU, memory, and display.

[0044] The lithium-ion secondary battery 300 internally comprises one or more lithium-ion secondary battery cells. By charging and discharging these cells, it can store power from the main body 200 or supply power to the main body 200. The lithium-ion secondary battery 300 is electrically connected to the main body 200 via a positive connection terminal, a negative connection terminal (power connection terminal), and a data communication terminal.

[0045] Figure 3 yes Figure 2The diagram shows the structure of a lithium-ion secondary battery 300. The lithium-ion secondary battery 300 includes a battery cell block 310 and a control module 320.

[0046] exist Figure 3 In this embodiment, battery cell block 310 includes battery cells capable of being charged using lithium-ion as the electrolyte. Depending on the required performance of the lithium-ion secondary battery, battery cell block 310 may include one or more battery cells.

[0047] The control module 320 controls the charging and discharging of the battery cell block 310. The control module 320 includes a positive terminal 321, a negative terminal 322, a data terminal 323, a current detection resistor 324, a charging switch 325, a discharging switch 326, a fuse 327, a switch 328, a battery control unit 329, a protection circuit 330, a first temperature sensor 331, and a second temperature sensor 332.

[0048] Positive terminal 321 and negative terminal 322 are terminals used for electrical connection when charging the lithium-ion secondary battery 300 from the main body 200 or discharging the lithium-ion secondary battery 300 to the main body 200. DC power is exchanged between the lithium-ion secondary battery 300 and the main body 200. Data terminal 323 is used for communication between the main body 200 and the lithium-ion secondary battery 300. More specifically, the control unit 202 of the main body 200 and the battery control unit 329 of the lithium-ion secondary battery 300 send and receive data, commands, etc., via this terminal.

[0049] The current sensing resistor 324 is used to detect the current of electricity discharged from the lithium-ion secondary battery 300 or the current of electricity charged to the lithium-ion secondary battery 300. The battery control unit 329 measures the voltage difference across its terminals and calculates the current value.

[0050] The charging switch 325 and the discharging switch 326 are switches used to control the battery cell block 310. These switches are controlled by the battery control unit 329.

[0051] When charging the battery cell block 310, the battery control unit 329 controls the charging switch 325 and the discharging switch 326 to prevent the battery cells constituting the battery cell block 310 from becoming over-voltaged or over-discharged. These switches are implemented, for example, by MOSFETs.

[0052] Fuse 327 is provided to protect battery cell 310 from overcurrent or overcharge (overvoltage). If overcurrent or overvoltage is detected in battery cell 310, protection circuit 330 energizes switch 328, allowing current to flow through the resistor of fuse 327. The resistor of fuse 327 melts due to heating caused by the current. This disconnects battery cell 310 from the overcurrent or overvoltage.

[0053] The battery control unit 329 controls the lithium-ion secondary battery 300 as a whole. The battery control unit 329 communicates with the control unit 202 of the main body 200 via the data terminal 323. The battery control unit 329 calculates the current value based on the voltage difference obtained from the two ends of the current sensing resistor 324. The battery control unit 329 also controls the charging switch 325 and the discharging switch 326. The battery control unit 329 also obtains temperature information from the first temperature sensor 331 and the second temperature sensor 332. In addition to current and temperature, the battery control unit 329 also measures the voltage of the battery cell block 310. Furthermore, when the battery cell block 310 is constructed by connecting multiple battery cells in series, it measures not only the voltage as a whole but also the voltage of each individual battery cell.

[0054] The battery control unit 329 is connected to a non-volatile storage medium (not shown). This can be implemented, for example, using an EEPROM (Electrically Erasable Programmable Read-Only Memory) or a NAND flash memory. The battery control unit 329 records / stores calculated current values, acquired temperature information, and the voltage values ​​of the battery cell block 310 on these storage media as needed. Furthermore, the battery control unit 329 records information instructed by the control unit 202 onto this storage medium.

[0055] The protection circuit 330 is provided for the purpose of protecting the battery cell block 310. The protection circuit 330, independent of the battery control unit 329 controlling the charging switch 325 and the discharging switch 326, turns on the switch 328 when an abnormality is detected in the battery cell block 310, thereby causing the fuse 327 to blow.

[0056] Furthermore, the battery control unit 329 and the protection circuit 330 can be implemented using an MPU (Micro-Processing Unit), a dedicated IC (Integrated Circuit), or the like (structure). Additionally, the battery control unit 329 and the protection circuit 330 can be implemented using a DSP (Digital Signal Processor), an FPGA (Field Programmable Gate Array), or the like.

[0057] The non-volatile storage medium connected to the battery control unit 329 can be provided independently of the battery control unit 329 or it can be provided inside the battery control unit 329.

[0058] The first temperature sensor 331 measures the temperature of the charging switch 325 and the discharging switch 326. The second temperature sensor 332 measures the temperature of the battery cell block 310. When the battery cell block 310 is composed of multiple battery cells, the second temperature sensor 332 can also be configured to measure the temperature of each individual battery cell.

[0059] The battery control unit 329 is characterized by further comprising: a battery characteristic calculation unit 340 having an OCV prediction unit 341, and a battery characteristic memory 342 for storing battery characteristics. Here, the battery characteristic calculation unit 340 uses... Figure 6 OCV prediction processing during battery charging, performing with Figure 5 The battery characteristic calculation process for battery capacity correction involves combining OCV data from multiple points, performing multiple OCV corrections between two points, and taking the average value to reduce the deviation in the calculation of the two points in the RSOC-OCV characteristics described in the prior art.

[0060] Figure 4 It means Figure 3 A block diagram of the structure of the OCV prediction unit 341.

[0061] exist Figure 4 In this configuration, the OCV prediction unit 341 includes a neural network such as a three-layer perceptron 400 that forms what is called artificial intelligence (AI). This three-layer perceptron 400 is configured to have: 11 input layers 10-1 to 10-11 (collectively referred to as 10), 3 intermediate layers 20-1 to 20-3 (collectively referred to as 20), and 1 output layer 30. Each input layer 10 is connected to all intermediate layers 20, and each intermediate layer 20 is connected to all output layers 30.

[0062] During the learning process of the three-layer perceptron 400, the learning data of input items A1 to A11 are input to each input layer 10, and the learning result data of output item B1 is set for the output layer 30. The three-layer perceptron 400 then learns. Next, during the action, the detection data of input items A1 to A11 are input to each input layer 10, thereby obtaining output item B1. An example of input items A1 to A11 and output item B1 is given below.

[0063] A1~A10: To be discussed later Figure 6 The voltage variation value in step S14;

[0064] A11: Battery temperature detected by the second temperature sensor 332;

[0065] B1: OCV(V).

[0066] Figure 4 of Figure 3 The structure of the OCV prediction unit 341 is an example, and it can include neural networks such as various perceptrons. Alternatively, instead of neural networks, it can be implemented using support vector machines as a form of machine learning, or by performing prediction calculations based on linear approximations of the distribution of collected data.

[0067] Figure 5 It indicates that it has the ability to pass Figure 3 The flowchart shows the battery characteristic calculation process performed by the battery characteristic calculation unit to correct the battery capacity.

[0068] exist Figure 5 In step S1, during the charging of the battery cell block 310 containing the secondary battery, "OCV prediction processing using a three-layer sensor 400" is used. Figure 6 S10) is used to obtain OCV data from multiple N points and charge the battery cell block 310 until it is fully charged.

[0069] Next, in step S2, based on the acquired OCV data of multiple N points, the OCV data pairs of each pair of points involved in all combinations of selecting each pair of the multiple N points (preferably all combinations, but in this disclosure it may also be at least a portion of the combinations) are (refer to...). Figure 7 The process involves performing multiple OCV corrections on the RSOC-OCV characteristics (hereinafter referred to as battery characteristics). Further, in step S3, each FCCx obtained through the multiple OCV corrections of the battery characteristics is corrected, for example, by a weighted average using the following formula, thereby averaging the multiple FCCx obtained in the OCV correction between the two points, and estimating and calculating the battery characteristics to reduce the deviation of the measurement location.

[0070] FCC=(ΣFCCx×|RSOCm-RSOCn|) / Σ|RSOCm-RSOCn| (2)

[0071] Here, m, n = 1, 2, ..., N, m ≠ n. N is the maximum number of OCV data points. Furthermore, here a weighted average is performed on the multiple FCCx obtained through OCV correction between two points, but for example, a prescribed statistical processing method, such as using a simple average to obtain reliable values ​​from biased data, can also be performed.

[0072] Next, in step S4, the calculated battery characteristics are stored in the battery characteristic memory 342 and the battery characteristic calculation process is terminated.

[0073] Figure 6 It means Figure 5 The flowchart for step S1 is the subroutine of the OCV prediction process during battery charging.

[0074] exist Figure 6 In step S11, the battery cell block 310 is charged. In step S12, after a predetermined time has elapsed since the start of charging, it is determined whether the remaining capacity of the OCV is to be requested. If yes, proceed to step S13; otherwise, proceed to step S11. Here, the predetermined time in step S12 is determined by the characteristics of each battery, for example, 30 seconds, 1 minute, 3 minutes, 5 minutes, or 10 minutes.

[0075] In step S13, charging is stopped. In step S14, multiple voltage fluctuation values ​​in the OCV before and after the stop are detected, for example at a predetermined time interval of 5 seconds, as well as the temperature detected by the second temperature sensor 332.

[0076] Next, in step S15, based on the plurality of voltage variation values ​​and temperature, using Figure 4 The three-layer sensor 400 is used to predict OCV and store it in the battery characteristic memory 342. In step S16, charging begins and the program returns to the main program.

[0077] Figure 7 This is a graph representing the RSOC-OCV characteristics of the battery capacity correction process in the illustrated implementation. Figure 7 In the diagram, P1 to P10 represent the RSOC-OCV characteristics. Figure 5 The OCV data for each step S2. Furthermore, in Figure 7 In the middle, it represents the OCV data of each pair of points involved in the combination of a portion obtained by selecting every two points from the 10-point OCV data (refer to...). Figure 7 ), and perform OCV correction of RSOC-OCV characteristics (battery characteristics) multiple times.

[0078] In the above Figure 5 as well as Figure 6 The correction process has the following unique effects.

[0079] (1) It can stop charging with the determined remaining capacity.

[0080] (2) The voltage change is less compared to the discharge.

[0081] (3) Thus, the full charge capacity of the secondary battery can be corrected with higher accuracy than the two-point OCV correction method involved in the existing example.

[0082] (Modified example)

[0083] In the above embodiments, the control module 320 includes a battery control unit 329 with an OCV prediction unit 341 and a battery characteristic memory 342. However, this disclosure is not limited to this, and other configurations may also be included. Figure 2 The control unit 202 is equipped with it.

[0084] Example

[0085] In the inventor's experiments, for Figure 4 The three-layer perceptron 400 was used to learn and evaluate experimental data with 375 data sets, 300 training sets, and 75 evaluation sets. The results showed that the average error of each cell of the secondary battery was 4.43mV, the maximum error was 15mV, and the standard deviation was 3.56mV.

[0086] Furthermore, even when incorporating artificial intelligence, constraints such as the data size of the parameters must be considered. Figure 3 The sensor is preferably used efficiently with simple devices.

[0087] Furthermore, in order to reduce the calculation error in the correction process, it is preferable to use only the following data in the calculation of FCC.

[0088] |RSOCm-RSOCn|>Specified value (e.g., 20%) (3)

[0089] Furthermore, in regions with smaller OCV, individual differences are greater, so it is preferable to use only a specified value of the remaining capacity (e.g., 50%) or more.

[0090] Furthermore, since the RSOC-OCV characteristics change at low temperatures, it is preferable to set the lower limit of the secondary battery temperature to a specified temperature (e.g., 10°C).

[0091] Industrial availability

[0092] The technologies described in this disclosure can be industrially applied, for example, in electronic devices such as personal computers, smartphones, mobile phones, and tablet devices that utilize secondary batteries such as lithium-ion secondary batteries.

[0093] -Symbol Explanation-

[0094] 10, 10-1 to 10-11 Input Layer

[0095] 20, 20-1 to 20-3 intermediate layers

[0096] 30 Output Layer

[0097] 100 personal computers

[0098] 101 Keyboard

[0099] 102 monitor

[0100] 200 main body

[0101] 201 Power Terminal

[0102] 202 Control Department

[0103] 203 Load Circuit

[0104] 300 Lithium-ion Secondary Battery

[0105] 310 battery cell block

[0106] 320 control module

[0107] 321 positive terminal

[0108] 322 negative terminal

[0109] 323 data terminal

[0110] 324 current sensing resistor

[0111] 325 charging switch

[0112] 326 Discharge Switch

[0113] 327 fuse

[0114] 328 switch

[0115] 329 Battery Control Unit

[0116] 330 protection circuit

[0117] 331 First Temperature Sensor

[0118] 332 Second Temperature Sensor

[0119] 340 Battery Characteristic Calculation Unit

[0120] 341OCV Prediction Department

[0121] 342 Battery Characteristic Memory

[0122] 400 three-layer perceptron.

Claims

1. A control device of a secondary battery, comprising a control section that corrects a battery characteristic that is a battery characteristic related to an open-circuit voltage with respect to a remaining capacity of a secondary battery, the control section acquires data of a plurality of open-circuit voltages in the battery characteristic in charging of the secondary battery, the control section performs correction of the open-circuit voltage between each data pair in a data pair of a combination of at least a part of the data of the plurality of open-circuit voltages when the secondary battery is fully charged, the control section corrects each full-charge capacity calculated for the correction of the open-circuit voltage between the data pairs by weighted average of a difference between each remaining capacity corresponding to the data pairs.

2. The control device of a secondary battery according to claim 1, wherein the control section acquires data of a plurality of open-circuit voltages in the battery characteristic in charging of the secondary battery by predicting the open-circuit voltage of the secondary battery based on a plurality of voltage variation values of the open-circuit voltage at a prescribed time interval of a period before and after the charging of the secondary battery is stopped for a prescribed time and a temperature of the secondary battery.

3. The control device of a secondary battery according to claim 2, wherein the control section predicts the open-circuit voltage of the secondary battery using a neural network that learns an output of the open-circuit voltage using a prescribed learning set after inputting the plurality of voltage variation values of the open-circuit voltage and the temperature of the secondary battery.

4. The control device of a secondary battery according to claim 3, wherein the neural network is a three-layer perceptron.

5. An electronic device comprising a control device of a secondary battery, the control device of a secondary battery comprising a control section that corrects a battery characteristic that is a battery characteristic related to an open-circuit voltage with respect to a remaining capacity of a secondary battery, the control section acquires data of a plurality of open-circuit voltages in the battery characteristic in charging of the secondary battery, the control section performs correction of the open-circuit voltage between each data pair in a data pair of a combination of at least a part of the data of the plurality of open-circuit voltages when the secondary battery is fully charged, the control section corrects each full-charge capacity calculated for the correction of the open-circuit voltage between the data pairs by weighted average of a difference between each remaining capacity corresponding to the data pairs.

6. A control method of a secondary battery, executed by a control device of a secondary battery, the control device of a secondary battery comprising a control section that corrects a battery characteristic that is a battery characteristic related to an open-circuit voltage with respect to a remaining capacity of a secondary battery, the control method of a secondary battery comprising: a step in which the control section acquires data of a plurality of open-circuit voltages in the battery characteristic in charging of the secondary battery, ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ the control section performing the step of correcting the open-circuit voltage between each data pair, in each data pair of a combination of at least a part of the data of the plurality of open-circuit voltages when the secondary battery is fully charged; and the control section performing the step of correcting each full-charge capacity calculated for the correction of the open-circuit voltage between each data pair by weighted average of a difference between each residual capacity corresponding to each data pair.

7. The control method of a secondary battery according to claim 6, wherein the step of acquiring the data of the plurality of open-circuit voltages in the battery characteristics in charging of the secondary battery includes acquiring the open-circuit voltage of the secondary battery by predicting the open-circuit voltage of the secondary battery based on a plurality of voltage variation values of the open-circuit voltage at a prescribed time interval of a period before and after the charging of the secondary battery is stopped for a prescribed time and a temperature of the secondary battery.

8. The control method of a secondary battery according to claim 7, wherein the step of predicting the open-circuit voltage of the secondary battery includes the control section predicting the open-circuit voltage of the secondary battery using a neural network that learns an output of the open-circuit voltage using a prescribed learning set after inputting the plurality of voltage variation values of the open-circuit voltage and the temperature of the secondary battery.

9. The control method of a secondary battery according to claim 8, wherein the neural network is a three-layer perceptron.

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