KR102628845B1 - Battery aging analysis device and method, battery management system including the same, and battery analysis model generation method - Google Patents

Abstract

One embodiment includes a sensing unit that senses the voltage of a battery terminal (battery voltage) and senses a current input and output to the battery terminal (battery current); a driving unit that supplies a driving current including a frequency component to the battery terminal; and an analysis unit that analyzes the battery voltage corresponding to the driving current to generate Nyquist plot data, and analyzes the Nyquist plot data to generate battery aging data. .

Description

Battery aging analysis device and method, battery management device including the same, and battery analysis model generation method {BATTERY AGING ANALYSIS DEVICE AND METHOD, BATTERY MANAGEMENT SYSTEM INCLUDING THE SAME, AND BATTERY ANALYSIS MODEL GENERATION METHOD}

This embodiment relates to battery management technology.

BMS (Battery Management System) is a device that plays an important role in battery management by monitoring the voltage, current, and temperature of the battery pack and maintaining it in optimal condition, predicting battery replacement time, and detecting battery problems in advance.

To ensure the safety of battery packs, overcharge/discharge, overcurrent, and overvoltage are currently limited by BMS, and technologies such as cell balancing and temperature alarm are being applied. However, this is an elementary technology to prevent serious battery pack accidents and is used to evaluate the health of the battery. Functions for - for example, functions to estimate state-of-health (SOH), state-of-safety (SOS) - are controlled.

The most reliable methods for estimating SOH and SOH are a method of determining the deterioration state and degree of aging of the electrode and electrolyte through material analysis after disassembling the battery (destructive method), or a method of analyzing the state of the electrode through X-ray photography (non-destructive method). Although known, this method is not recommended because not only is it impossible while the battery pack is in operation, but in the case of a destructive method, the battery pack itself must be discarded after testing.

Due to this problem, indirect estimation methods are currently being used to estimate SOH and SOS through charge/discharge efficiency, remaining capacity, battery pack operation history, and temperature history.

Against this background, the purpose of this embodiment is to provide a technology that can more accurately analyze battery aging.

In order to achieve the above-described object, one embodiment includes a sensing unit that senses the voltage of a battery terminal (battery voltage) and senses a current input and output to the battery terminal (battery current); a driving unit that supplies a driving current including a frequency component to the battery terminal; and an analysis unit that analyzes the battery voltage corresponding to the driving current to generate Nyquist plot data, and analyzes the Nyquist plot data to generate battery aging data. .

The aging data may include lifespan data and aging cause data.

The analysis unit can adjust the ratio of causes caused by vibration according to the size of the semicircle in the Nyquist plot data and adjust the ratio of causes caused by temperature according to the size of the real value in the Nyquist plot data. .

Another embodiment includes supplying a driving current including a frequency component to a battery terminal; Sensing the voltage of the battery terminal (battery voltage) and sensing the current input and output to the battery terminal (battery current); generating Nyquist plot data by analyzing the battery voltage corresponding to the driving current; and analyzing the Nyquist plot data to generate battery aging data.

The battery aging analysis method includes analyzing the Nyquist plot data to generate aging data of the battery, constructing a circuit model of the battery using the Nyquist plot data, and component values of the circuit model. The aging data can be generated using .

In the battery aging analysis method, in the step of generating aging data of the battery by analyzing the Nyquist plot data, the cause of aging of the battery can be determined differently depending on the component value changing among the components of the circuit model. .

The aging data may include lifespan data and aging cause data.

Another embodiment includes a sensing unit that senses the voltage of the battery terminal (battery voltage), senses the current input and output to the battery terminal (battery current), and senses the temperature of the battery (battery temperature); a control unit that blocks the battery current input and output to the battery terminal when the battery voltage exceeds the upper limit voltage or falls below the lower limit voltage, the battery current exceeds the limit current, or the battery temperature exceeds the limit temperature; a driving unit that supplies a driving current including a frequency component to the battery terminal; and an analysis unit that analyzes the battery voltage corresponding to the driving current to generate Nyquist plot data, and analyzes the Nyquist plot data to generate battery aging data.

The battery management device further includes a cutoff switch that blocks input and output of the battery current, and the control unit can control the cutoff switch to cut off the battery current.

The control unit may calculate the remaining capacity of the battery by accumulating the battery current or using the battery voltage.

The aging data may include lifespan data and aging cause data.

The analysis unit can adjust the ratio of causes caused by vibration according to the size of the semicircle in the Nyquist plot data and adjust the ratio of causes caused by temperature according to the size of the real value in the Nyquist plot data. .

Another embodiment includes charging and discharging the first battery N times (N is a natural number of 100 or more) while shaking the first battery at a constant acceleration; At each charge/discharge cycle, a first driving current including a frequency component is supplied to the first battery, and the voltage of the first battery corresponding to the first driving current is analyzed to generate first Nyquist plot data, calculating the capacity of the first battery; Charging and discharging the second battery N times in a constant temperature chamber; At each charge/discharge cycle, a second drive current including a frequency component is supplied to the second battery, and the voltage of the second battery corresponding to the second drive current is analyzed to generate second Nyquist plot data, calculating the capacity of the second battery; And inputting the first Nyquist plot data and the capacity of the first battery, and the second Nyquist plot data and the capacity of the second battery into a machine learning device to calculate the life of the battery according to the Nyquist plot. Provides a battery analysis model creation method that includes the step of creating a battery analysis model that classifies the causes of changes in battery life.

The battery analysis model can be installed in a BMS (Battery Management System).

The causes can be classified into vibration causes and temperature causes.

The first driving current and the second driving current may be supplied while charging and discharging is stopped.

As described above, according to this embodiment, the aging of the battery can be analyzed more accurately.

1 is a configuration diagram of a battery system according to an embodiment.
Figure 2 is a configuration diagram of a BMS device according to an embodiment.
Figure 3 is a configuration diagram of an analysis unit according to an embodiment.
Figure 4 is a diagram showing changes in the Nyquist plot graph depending on temperature.
Figure 5 is a diagram showing changes in the Nyquist plot graph due to vibration.
Figure 6 is a configuration diagram of an impedance model according to one embodiment.
Figure 7 is a flowchart of a battery aging analysis method according to an embodiment.
Figure 8 is a diagram showing the creation of an analysis module through machine learning.
Figure 9 is a flowchart of a method for generating a battery analysis model according to an embodiment.

Hereinafter, some embodiments of the present invention will be described in detail through illustrative drawings. When adding reference numerals to components in each drawing, it should be noted that identical components are given the same reference numerals as much as possible even if they are shown in different drawings. Additionally, in describing the present invention, if it is determined that a detailed description of a related known configuration or function may obscure the gist of the present invention, the detailed description will be omitted.

Additionally, when describing the components of the present invention, terms such as first, second, A, B, (a), and (b) may be used. These terms are only used to distinguish the component from other components, and the nature, sequence, or order of the component is not limited by the term. When a component is described as being “connected,” “coupled,” or “connected” to another component, that component may be directly connected or connected to that other component, but there is another component between each component. It will be understood that elements may be “connected,” “combined,” or “connected.”

1 is a configuration diagram of a battery system according to an embodiment.

Referring to FIG. 1, the battery system 100 may include a battery 120 and a BMS device 110.

Here, the battery 120 may be composed of one battery cell or may be composed of a plurality of battery cells. The battery 120 may further include a protection circuit in addition to the battery cells, and may be referred to as a battery pack in that it includes two or more components.

Battery terminals including a negative terminal and a positive terminal may be formed in the battery 120, and battery current Ib may be input and output through these battery terminals. When the negative terminal is connected to the ground, the voltage at the positive terminal can be viewed as the battery voltage (Vb).

The battery terminal may be connected to the output terminal. And, the output terminal may be connected to an electronic device or a charging device. When the output terminal is connected to an electronic device, battery current (Ib) can be output through the battery terminal, and when the output terminal is connected to a charging device, battery current (Ib) can be input through the battery terminal.

The battery terminal may be further connected to the BMS device 110.

The BMS device 110 is a device that performs the function of a BMS (Battery Management System), and can manage the state of the battery 120 and protect the battery 120 by operating a cutoff switch, etc., when necessary.

When the battery voltage (Vb) exceeds the upper limit voltage or falls below the lower limit voltage, the BMS device 110 can block the input and output of the battery current (Ib) by generating an alarm or operating a cutoff switch.

When the battery current (Ib) exceeds the limit current, for example, when the size of the battery current (Ib) exceeds the size of the limit discharge current, the BMS device 110 limits the size of the battery current (Ib). If the charging current exceeds the size, an alarm can be generated or a cutoff switch can be activated to block the input and output of the battery current (Ib).

If the battery temperature exceeds the limit temperature, the BMS device 110 can block the input and output of the battery current (Ib) by generating an alarm or operating a cutoff switch.

The BMS device 110 can calculate the remaining capacity of the battery 120. The remaining capacity, also expressed as state-of-charge (SOC), may refer to the amount of energy available in the battery 120.

The BMS device 110 can calculate the remaining capacity according to the battery voltage (Vb). When the battery voltage (Vb) is high, the BMS device 110 may calculate the remaining capacity as high, and when the battery voltage (Vb) is low, the BMS device 110 may calculate the remaining capacity as low.

The BMS device 110 can calculate the remaining capacity by accumulating the battery current (Ib). This method is also called the current integration method.

Meanwhile, the BMS device 110 can generate aging data of the battery 120. Aging data may include lifespan data and aging cause data of the battery 120. In terms of generating aging data, the BMS device 110 may be referred to as a battery aging analysis device.

Lifespan data may include values for remaining lifespan, also called state-of-health (SOH). Additionally, the aging cause data may include values for the cause of the decrease in remaining lifespan. The value for the cause may be composed of classification values. The classification values may include, for example, a value representing a vibration cause and a value representing a temperature cause. Because causes may be complex, the value for each cause may be expressed as a ratio. For example, the proportion of vibration causes may be 30% and the proportion of temperature causes may be 70%.

The BMS device 110 can supply a driving current (It) including a frequency component to the battery terminal. Then, the BMS device 110 analyzes the battery voltage (Vb) corresponding to the driving current (It) to generate Nyquist plot data, and analyzes the Nyquist plot data to generate aging data of the battery 120. can be created.

The driving current (It) may include a signal of a specific frequency component. For example, the driving current (It) may include a 1 KHz signal. When this driving current (It) is supplied to the battery 120, the battery voltage (Vb) may change according to the internal impedance to correspond to the signal of the corresponding frequency component, and the BMS device 110 specifies the battery voltage (Vb). The impedance value for a specific frequency can be calculated by dividing the signal by the frequency component. The BMS device 110 can generate a driving current (It) while changing the frequency and measure the impedance of the battery 120.

Impedance can be composed of real values and imaginary values, and the Nyquist plot displays the real values and imaginary values on the Nyquist plane.

When the real and image values of impedances measured in a certain frequency band are displayed on the Nyquist plane, a graph with a certain pattern is drawn. This graph can also be called Nyquist plot data.

This module that can measure the impedance of the battery 120 can be called an EIS (Electrochemical Impedance Spectroscopy) module, and one feature of the BMS device 110 may be that it has a built-in EIS module.

The BMS device 110 can generate Nyquist plot data for the battery 120 using the EIS module. Nyquist plot data can be composed of multiple coordinate data, and can be intuitively recognized as a graph image on the Nyquist plane.

The BMS device 110 can generate aging data of the battery 120 by analyzing Nyquist plot data. For example, the BMS device 110 can calculate the lifespan data included in the aging data according to the size of the semicircular portion in the graph recognized through Nyquist plot data, and to what extent is the percentage of aging caused by vibration You can decide whether to do it or not. As another example, the BMS device 110 can calculate the lifespan data included in the aging data according to the size of the real value (the value of the portion where the graph and the real axis meet) in the graph recognized through Nyquist plot data, and the aging data It is possible to determine what proportion of causes are caused by temperature.

Figure 2 is a configuration diagram of a BMS device according to an embodiment.

Referring to FIG. 2, the BMS device may include a control unit 210, a sensing unit 220, a driving unit 230, and an analysis unit 240.

The control unit 210 can control the operation of the blocking switch and the sensing unit 220, the driving unit 230, and the analysis unit 240.

The control unit 210 may operate a cutoff switch to protect the battery. For example, the control unit 210 may operate the cutoff switch when the battery voltage exceeds the upper limit voltage or falls below the lower limit voltage, when the battery current exceeds the limit current, or when the battery temperature is lowered. If the temperature exceeds the limit, the battery current input and output to the battery terminal can be blocked.

The sensing unit 220 can sense the voltage of the battery terminal (battery voltage), sense the current input and output to the battery terminal (battery current), and sense the temperature of the battery (battery temperature).

The driver 230 may supply a driving current including a frequency component to the battery terminal. The driving current is a small signal and may have a small current level, and may fluctuate between positive and negative values around 0A.

The analysis unit 240 may analyze the battery voltage corresponding to the driving current to generate Nyquist plot data, and analyze the Nyquist plot data to generate battery aging data.

The BMS device 110 may further include a blocking switch that blocks the input and output of battery current, and the control unit 210 may control the blocking switch to block the battery current.

Additionally, the control unit 210 may calculate the remaining capacity of the battery by accumulating battery current or using the battery voltage.

Aging data generated by the analysis unit 240 may include lifespan data and aging cause data.

Figure 3 is a configuration diagram of an analysis unit according to an embodiment.

Referring to FIG. 3, the analysis unit 240 may include a Nyquist plot unit 310 and a plot analysis unit 320.

The Nyquist plot unit 310 can generate Nyquist plot data (Dnp) by analyzing the battery voltage corresponding to the driving current.

Additionally, the plot analysis unit 320 may generate battery aging data (Dsoh) by analyzing the Nyquist plot data (Dnp).

The plot analysis unit 320 may be equipped with a battery analysis model generated by a machine learning device. The battery analysis model may be an artificial intelligence learned model to output aging data (Dsoh) for the input of Nyquist plot data (Dnp). More specific examples of artificial intelligence learning are described later.

Meanwhile, the plot analysis unit 320 can adjust the ratio of causes due to vibration according to the size of the semicircle in the Nyquist plot data, and adjust the ratio of causes due to temperature according to the size of the real value in the Nyquist plot data. there is.

Figure 4 is a diagram showing changes in the Nyquist plot graph depending on temperature.

The inventor charged and discharged the battery 200 times in a high temperature chamber at 60 degrees Celsius, measuring the impedance of the battery with an EIS module for each charge and discharge cycle, and displayed it on the Nyquist plane. The picture completed in this way is the picture shown in Figure 4.

Referring to FIG. 4, it can be seen that as time passes, that is, as the number of charging and discharging increases, the real value (the value of the part where the graph and the real axis meet) increases.

By equipping the BMS device with a battery analysis model learned according to these experimental data, it can accurately find out that the cause of life change is temperature.

Figure 5 is a diagram showing changes in the Nyquist plot graph due to vibration.

The inventor charged and discharged the battery 200 times while shaking it at a constant acceleration, measured the impedance of the battery with an EIS module for each charge and discharge cycle, and displayed it on the Nyquist plane. The picture completed in this way is the picture shown in Figure 5.

Referring to FIG. 5, it can be seen that as time passes, that is, as the number of charging and discharging increases, the size of the semicircle shown in the graph - the size of the radius - increases.

By equipping the BMS device with a battery analysis model learned according to these experimental data, it can accurately find that the cause of the change in lifespan is vibration.

In the actual experiment according to FIG. 4, the inventor confirmed that the electrolyte resistance of the battery was initially 15 mOhm, but after charging and discharging 200 times, it became 40 mOhm. In the actual experiment according to FIG. 5, the electrode resistance of the battery was initially 20 mOhm. , it was confirmed that after charging and discharging 200 times, it became 50m ohm. This may mean that the part where aging occurs varies depending on the cause.

To confirm this by matching it with the Nyquist plot, the BMS device can form an impedance model of the battery and match the Nyquist plot to the impedance model.

Figure 6 is a configuration diagram of an impedance model according to one embodiment.

Referring to FIG. 6, the impedance model may include a charge transfer capacitor (Cct) and a charge transfer resistor (Rct) configured in RC parallel, and a series resistance (Ri). In addition, the impedance model may include diffuser capacitors (Cdif1, Cdif2) and diffuser capacitors (Rdif1, Rdif2) composed of RC parallel, and an open circuit voltage (OCV) capacitor.

The BMS device can find the value of each component of the impedance model by analyzing Nyquist plot data. Additionally, the BMS device can recognize changes in the values of each configuration to generate lifespan data and aging cause data.

For example, when the series resistance (Ri) increases, the BMS device can classify the cause of aging as a temperature cause, and when the charge transfer resistance (Rct) increases, the BMS device can classify the cause of aging as a vibration cause. You can. And, if both become large, the BMS device can display each cause as a ratio.

Figure 7 is a flowchart of a battery aging analysis method according to an embodiment.

Referring to FIG. 7, the BMS device can supply a driving current including a frequency component to the battery terminal (S700). Driving current can be supplied without disconnecting the battery from electronic devices - ESS (Energy Storage System), electric vehicles, etc. In other words, it can be supplied while the electronics are in operation.

The BMS device can sense the voltage of the battery terminal and the current input and output to the battery terminal (S702).

Additionally, the BMS device can generate Nyquist plot data by analyzing the battery voltage corresponding to the driving current (S704).

Additionally, the BMS device can analyze the Nyquist plot data (S706) and use it to generate aging data (S708).

Here, aging data may include lifespan data and aging cause data.

Then, in the step (S706, S708) of analyzing the Nyquist plot data and generating battery aging data, the BMS device constructs a circuit model of the battery using the Nyquist plot data and uses the component values of the circuit model. Thus, aging data can be generated. Here, the BMS device can determine the cause of battery aging differently depending on the configuration of the circuit model in which component values change.

The module that generates battery aging data by analyzing Nyquist plot data can be created using machine learning.

Figure 8 is a diagram showing the creation of an analysis module through machine learning.

Referring to FIG. 8, Nyquist plot data for learning (Dnpm) and aging data for learning (Dsohm) may be supplied to the machine learning device 810. The machine learning device 810 includes multiple neural networks and can learn internal parameters and layers using Nyquist plot data for learning (Dnpm) and aging data for learning (Dsohm).

The battery analysis model (NN) learned in this way can be installed in the plot analysis unit 320. Additionally, the plot analysis unit 320 may generate aging data according to the input Nyquist plot data.

Figure 9 is a flowchart of a method for generating a battery analysis model according to an embodiment.

Referring to FIG. 9, the device can charge and discharge the first battery N times (N is a natural number of 100 or more) while shaking the first battery at a constant acceleration (S900).

Then, at every charge/discharge cycle, the device supplies a first drive current including a frequency component to the first battery, analyzes the voltage of the first battery corresponding to the first drive current, and generates first Nyquist plot data. , the capacity of the first battery can be calculated (S902). Here, the capacity of the first battery can be used as the lifespan value of the first battery.

The device can charge and discharge the second battery N times in a constant temperature chamber (S904).

Then, at every charge/discharge cycle, the device supplies a second drive current including a frequency component to the second battery, analyzes the voltage of the second battery corresponding to the second drive current, and generates second Nyquist plot data. , the capacity of the second battery can be calculated. Here, the capacity of the second battery can be used as the lifespan value of the second battery.

Then, the device inputs the first Nyquist plot data and the capacity of the first battery, and the second Nyquist plot data and the capacity of the second battery into the machine learning device to calculate the lifespan of the battery according to the Nyquist plot and battery life. A battery analysis model can be created to classify the causes of changes in lifespan.

The battery analysis model created in this way can be installed in the BMS device. And, here, the first driving current and the second driving current can be supplied while charging and discharging is stopped.

Terms such as “include,” “comprise,” or “have,” as used above, mean that the corresponding component may be included, unless specifically stated to the contrary, and do not exclude other components. It should be interpreted that it may further include other components. All terms, including technical or scientific terms, unless otherwise defined, have the same meaning as generally understood by a person of ordinary skill in the technical field to which the present invention pertains. Commonly used terms, such as terms defined in a dictionary, should be interpreted as consistent with the meaning in the context of the related technology, and should not be interpreted in an idealized or overly formal sense unless explicitly defined in the present invention.

The above description is merely an illustrative explanation of the technical idea of the present invention, and various modifications and variations will be possible to those skilled in the art without departing from the essential characteristics of the present invention. Accordingly, the embodiments disclosed in the present invention are not intended to limit the technical idea of the present invention, but are for illustrative purposes, and the scope of the technical idea of the present invention is not limited by these embodiments. The scope of protection of the present invention should be interpreted in accordance with the claims below, and all technical ideas within the equivalent scope should be construed as being included in the scope of rights of the present invention.

Claims (16)

A sensing unit that senses the voltage of the battery terminal (battery voltage) and senses the current input and output to the battery terminal (battery current);
a driving unit that supplies a driving current including a frequency component to the battery terminal; and
It includes an analysis unit that analyzes the battery voltage corresponding to the driving current to generate Nyquist plot data, and analyzes the Nyquist plot data to generate battery aging data,
The aging data includes lifespan data and aging cause data, and the aging cause data includes a value representing a vibration cause and a value representing a temperature cause, wherein the value for each aging cause is expressed as a ratio. . delete According to paragraph 1,
The analysis unit,
A battery aging analysis device that adjusts the ratio of causes caused by vibration according to the size of the semicircle in the Nyquist plot data and adjusts the ratio of causes caused by temperature according to the size of the real value in the Nyquist plot data. Supplying a driving current including a frequency component to a battery terminal;
Sensing the voltage of the battery terminal (battery voltage) and sensing the current input and output to the battery terminal (battery current);
generating Nyquist plot data by analyzing the battery voltage corresponding to the driving current; and
It includes generating battery aging data by analyzing the Nyquist plot data,
The aging data includes lifespan data and aging cause data, and the aging cause data includes a value representing a vibration cause and a value representing a temperature cause. A battery aging analysis method in which the values for each aging cause are expressed as a ratio. . According to clause 4,
In the step of analyzing the Nyquist plot data to generate aging data of the battery,
A battery aging analysis method for constructing a circuit model of the battery using the Nyquist plot data and generating the aging data using component values of the circuit model. According to clause 5,
In the step of analyzing the Nyquist plot data to generate aging data of the battery,
A battery aging analysis method that determines the cause of aging of the battery differently depending on the configuration of the circuit model in which component values change. According to clause 4,
The aging data is,
Battery aging analysis method including lifespan data and aging cause data. A sensing unit that senses the voltage of the battery terminal (battery voltage), senses the current input and output to the battery terminal (battery current), and senses the temperature of the battery (battery temperature);
a control unit that blocks the battery current input and output to the battery terminal when the battery voltage exceeds the upper limit voltage or falls below the lower limit voltage, the battery current exceeds the limit current, or the battery temperature exceeds the limit temperature;
a driving unit that supplies a driving current including a frequency component to the battery terminal; and
It includes an analysis unit that analyzes the battery voltage corresponding to the driving current to generate Nyquist plot data, and analyzes the Nyquist plot data to generate battery aging data,
The aging data includes lifespan data and aging cause data, and the aging cause data includes a value representing a vibration cause and a value representing a temperature cause, and the value for each aging cause is expressed as a ratio. According to clause 8,
It further includes a blocking switch that blocks the input and output of the battery current,
The control unit is a battery management device that controls the cutoff switch to cut off the battery current. According to clause 8,
The control unit,
A battery management device that accumulates the battery current or calculates the remaining capacity of the battery using the battery voltage. According to clause 8,
The aging data is,
A battery management device that includes lifespan data and aging cause data. According to clause 8,
The analysis unit,
A battery management device that adjusts the ratio of causes caused by vibration according to the size of a semicircle in the Nyquist plot data and adjusts the ratio of causes caused by temperature according to the size of the real value in the Nyquist plot data. Charging and discharging the first battery N times (N is a natural number of 100 or more) while shaking the first battery at a constant acceleration;
At each charge/discharge cycle, supply a first driving current including a frequency component to the first battery, analyze the voltage of the first battery corresponding to the first driving current, and generate first Nyquist plot data, calculating the capacity of the first battery;
Charging and discharging the second battery N times in a constant temperature chamber;
At each charge/discharge cycle, a second drive current including a frequency component is supplied to the second battery, and the voltage of the second battery corresponding to the second drive current is analyzed to generate second Nyquist plot data, calculating the capacity of the second battery; and
The first Nyquist plot data and the capacity of the first battery, and the second Nyquist plot data and the capacity of the second battery are input into a machine learning device to calculate the lifespan of the battery according to the Nyquist plot and battery life. Steps to create a battery analysis model that classifies the causes of changes in lifespan
Battery analysis model generation method including. According to clause 13,
The battery analysis model is a method of generating a battery analysis model installed in a BMS (Battery Management System). According to clause 13,
A method of generating a battery analysis model in which the causes are classified into vibration causes and temperature causes. According to clause 13,
A method of generating a battery analysis model in which the first driving current and the second driving current are supplied in a state in which charging and discharging are stopped.

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