JP7657172B2 - BATTERY STATE ESTIMATION DEVICE, BATTERY SYSTEM, AND BATTERY STATE ESTIMATION METHOD - Google Patents

Description

The present invention relates to a technology for estimating the state of a battery.

There is a growing demand for diagnostic technology that can quickly estimate the degradation state (State of Health: SOH) of secondary batteries. This technology is important for managing the life cycle of secondary batteries in electric vehicles, power storage systems, and the like. There is an increasing need in the market for technology that can quickly diagnose used storage batteries, and there is a demand for a method to quickly diagnose the degradation state of storage batteries by attaching and detaching the storage batteries to devices equipped with the storage batteries. To achieve this, it is necessary to provide an appropriate diagnostic method for each combination of power supply load device and battery measurement device.

Patent Document 1 describes a technology for diagnosing the deterioration state of a battery. The document aims to "accurately evaluate the state of a storage battery system," and describes a technology called "a storage battery state evaluation system for evaluating the state of a storage battery system consisting of multiple storage battery cells, which has a memory that stores the voltages of at least two storage battery cells that are at different positions in the distribution of the voltages of the multiple storage battery cells, and a deterioration state calculation unit that calculates the slope of the voltage over time during a rest period after discharging the at least two storage battery cells" (see abstract).

JP 2020-169943 A

As in Patent Document 1, high-speed diagnosis using voltage characteristics during rest periods is suitable when voltage measurements are performed at a high sampling rate. This is because in order to diagnose a battery within a short period of time, it is necessary to obtain many measurement points within that short period of time, so a high sampling rate is desirable. In other words, with this technology, if the sampling rate is low, the accuracy of estimating the deterioration state may decrease.

In addition, for example, due to the environment in which the measurement work is performed, there are cases in which it is not possible to secure sufficient sampling points for the battery voltage in the period immediately after charging and discharging are completed (the early stage of the rest period). Since it is not possible to obtain sufficient battery voltage in the early stage of the rest period, it is difficult to perform accurate diagnosis within a short period after charging and discharging are completed. In other words, in this case as well, as in the case where the sampling rate is low, it is considered that the accuracy of diagnosis using the time-dependent fluctuation of the battery voltage in the early stage of the rest period is insufficient.

The present invention was made in consideration of the above problems, and aims to provide a technology for estimating the degradation state of a battery using the voltage characteristics during a rest period after charging and discharging the battery, which allows accurate estimation of the degradation state of the battery even when a sufficient number of sampling values of the battery voltage cannot be obtained at the beginning of the rest period.

The battery state estimation device according to the present invention identifies a baseline voltage of the battery voltage during a period after a predetermined time has elapsed since the start of a rest period, estimates the time derivative of the battery voltage during the predetermined time period based on the difference between the baseline voltage and the battery voltage, and estimates the degradation state of the battery using the time derivative.

The battery state estimation device according to the present invention is a technology for estimating the degradation state of a battery using the voltage characteristics during a rest period after charging and discharging the battery, and can accurately estimate the degradation state of the battery even when a sufficient number of sampling values of the battery voltage cannot be obtained at the beginning of the rest period.

4 is a graph showing the change over time in battery voltage during a rest period after a secondary battery has performed a discharging operation. 1 shows various forms of a battery state estimation device that estimates the state of a secondary battery. 1 shows a functional block diagram of a battery state estimating device 100 according to a first embodiment and a processing flow for estimating a degradation state. 13 shows a functional block diagram of a battery state estimating device according to a second embodiment and a processing flow for estimating a degradation state. FIG. 11 is an example of a first correspondence relationship. 13 is an example of a third correspondence relationship. 11 is an example of a second correspondence relationship. 1 shows an example of the impedance of a battery cell measured using an EIS. 1 shows an example of an equivalent circuit diagram of a secondary battery.

<First embodiment>
As described above, existing techniques for quickly diagnosing the deterioration state of a secondary battery generally require a high sampling rate. The present invention provides a technique for estimating the SOH of a secondary battery at a low sampling rate without removing the secondary battery from a device equipped with the secondary battery.

Figure 1 is a graph showing the time variation of the battery voltage during a rest period after a secondary battery performs a discharge operation. As shown in Figure 1, the rest period can be divided into a period T1 during which the battery voltage changes sharply and a subsequent period T2 during which the battery voltage changes more slowly. By estimating the SOH using the time rate of change (dV/dt) of the battery voltage during period T1, the SOH can be estimated within a short period of time. On the other hand, since the battery voltage changes sharply during period T1, it is necessary to take many sampling points of the battery voltage within a short period of time in order to make an accurate estimation. In other words, a high sampling rate is necessary. Therefore, if it is difficult to sample the battery voltage at a high sampling rate due to limitations in the measuring equipment, for example, the estimation accuracy may decrease.

For example, due to the environment in which the battery voltage is measured, it may not be possible to obtain sufficient time-dependent fluctuations in the battery voltage during period T1. In this case, as in the case where the sampling rate is low, it is not possible to obtain a sufficient number of sampling points for the battery voltage during period T1. Therefore, there is a similar possibility that the estimation accuracy will decrease.

The present invention provides a technology that uses the battery voltage characteristics during period T2 to accurately estimate SOH without using a high sampling rate (even when there are few sampling points during period T1). The baseline voltage shown in Figure 1 and its update will be explained using the flowchart described later.

Figure 2 shows various forms of battery state estimation devices that estimate the state of a secondary battery. For example, the battery voltage (as well as the battery current, battery temperature, etc.) of a secondary battery installed in an electric vehicle (EV) can be acquired by a charging/discharging device, a measuring device, an on-board diagnostic (OBD) device, etc. For large facilities such as stationary energy storage systems, for example, a measuring device communicates with the battery system to acquire measured values such as the battery voltage. These measuring devices can transmit measured values, etc. to the data acquisition unit 110 without being removed from the equipment installed with the battery (in this example, the EV or the energy storage system).

The battery voltage and other measurement values acquired by these devices can be used by the devices themselves to estimate the battery state, or the measurement values can be uploaded to a cloud platform and then used by a server computer to estimate the battery state. The estimation results can be viewed by accessing the cloud platform using a computer (PC) or a mobile terminal. These devices that estimate the battery state can be configured as a battery state estimation device according to the present invention.

Figure 3 shows a functional block diagram of the battery state estimation device 100 according to the first embodiment and a processing flow for estimating the degraded state. The battery state estimation device 100 includes a data acquisition unit 110 and a processor 120. The data acquisition unit 110 acquires data such as the measured value of the battery voltage of the secondary battery and the start and end times of T1 described in Figure 1 from, for example, a measuring device. The processor 120 estimates the degraded state of the secondary battery according to the flowchart shown in Figure 3. Each step in Figure 3 will be described below.

(FIG. 3: Step S301)
A controller (e.g., a battery management unit: BMU) that controls the charging and discharging operation of the secondary battery transmits a command to instruct the secondary battery to perform a charging and discharging operation. The processor 120 judges whether the secondary battery has entered a hibernation period according to the command. If the secondary battery has entered a hibernation period, the following steps are performed, and if not, it is not necessary to perform this flowchart. The controller may be configured as a part of the battery state estimation device 100, or as a part of a battery system including the secondary battery.

(FIG. 3: Step S301: Supplement)
Alternatively, the processor 120 may determine by itself whether the secondary battery has entered a rest period. For example, the processor 120 may determine that the secondary battery has entered a rest period when the charge/discharge current falls below a threshold (typically 0) or when this state continues for a threshold time or longer. Any other appropriate criteria may be used.

(FIG. 3: Step S302: Part 1)
The data acquisition unit 110 acquires data such as the measured value of the battery voltage of the secondary voltage, the start time and end time of T1 described in FIG. 1, and the initial baseline voltage (B0). These values may be acquired, for example, from a charge/discharge controller, or may be acquired by accessing values temporarily stored in a storage device such as cloud storage. Fixed values other than the measured values may be stored in advance as initial values in the storage device of the battery state estimation device. The processor 120 acquires these from the data acquisition unit 110, and sets the periods T1 and T2 and the initial baseline voltage based on the acquired data.

(FIG. 3: Step S302: Part 2)
The processor 120 calculates the difference ΔV between the current baseline voltage (initial baseline voltage B0 when this step is performed for the first time) and the battery voltage. It is desirable to use the sampling point of the battery voltage at a time point when the time-dependent fluctuation of the battery voltage becomes stable. In other words, it is desirable to set the difference ΔV between the sampling point at a time point when the slope of the battery voltage in the period T2 is nearly flat and the baseline voltage.

(FIG. 3: Step S302: Supplement)
In this step, it is sufficient to obtain the measured value of the battery voltage during the period T2, and it is not necessary to obtain the measured value during the period T1, i.e., the measuring device does not need to measure the battery voltage at a high sampling rate during the period T1.

(FIG. 3: Step S302: Part 3)
The processor 120 uses the calculated ΔV to determine the tentative SOH by referring to data describing a first correspondence relationship (described later) between ΔV and the SOH. This correspondence relationship data may be acquired by the data acquisition unit 110 from a controller or cloud storage, or may be stored in advance in a storage device included in the battery state estimation device and acquired by the data acquisition unit 110. The same applies to other correspondence relationship data described later.

(FIG. 3: Step S303: Part 1)
The processor 120 estimates dV/dt during the period T1 by referring to data describing a second correspondence relationship (to be exemplified later) between the time rate of change (dV/dt) of the battery voltage during the period T1 and the SOH, using the SOH provisionally acquired in S302. This step is significant in that it allows dV/dt during the period T1 to be obtained without acquiring a measurement value of the battery voltage during the period T1.

(FIG. 3: Step S303: Part 2)
The processor 120 uses the estimated dV/dt to update the baseline voltage. Specifically, for example, the changed dV/dt is multiplied by a very short time (a very short time of about a few ms if T1 is about several hundred ms). This allows the increment of the battery voltage to be obtained. The baseline voltage can be updated by adding the increment to the current baseline voltage. When the end of T1 is reached by repeating the process described below, the baseline voltage is not updated any more.

(FIG. 3: Step S304)
The processor 120 recalculates ΔV using the updated baseline voltages (e.g., B1 and B2 in FIG. 1 ). The processor 120 reacquires the SOH by referring to the first correspondence relationship using the recalculated ΔV.

(FIG. 3: Step S305)
The processor 120 repeats steps S303 and S304 until the SOH converges. For example, the processor 120 may repeatedly acquire the SOH until the difference between the previous SOH value and the current SOH value becomes less than a threshold value.

<Embodiment 2>
In existing technologies for quickly diagnosing the deterioration state of a secondary battery, it is common to charge and discharge the secondary battery using a high C rate (the current value at which the battery can be fully charged or fully discharged in one hour is defined as 1C.) This is because using a high C rate increases the fluctuation of the battery voltage during the rest period, which improves the estimation accuracy using the battery voltage.

However, due to constraints such as the equipment and measuring devices equipped with the secondary battery, it may be difficult to use a high C rate. Therefore, in the second embodiment of the present invention, in addition to the low sampling rate described in the first embodiment, a method for estimating the SOH when the charging and discharging current is performed at a low C rate is described. That is, the data acquisition unit 110 acquires the measurement value of the battery voltage during the rest period after charging and discharging at the low C rate.

Figure 4 shows a functional block diagram of a battery state estimation device according to embodiment 2 and a processing flow for estimating a degradation state. In this embodiment 2, steps S401 and S402 are performed instead of S303. The other configurations are the same as those of embodiment 1.

(FIG. 4: Step S401)
Processor 120 uses the ΔV calculated in S302 to convert the ΔV in S302 into a value of ΔV at a C rate higher than the actual charge/discharge C rate by referring to data describing a third correspondence relationship (described later) between ΔV, C rate, and SOH.

(FIG. 4: Step S402)
The processor 120 obtains a new tentative SOH by referring to the first correspondence relationship using the ΔV estimated by the conversion in S401. The processor 120 estimates dV/dt in the period T1 by referring to the second correspondence relationship using the tentative SOH. The processor 120 updates the baseline voltage in the same manner as in S303: Part 2.

Figure 5A is an example of the first correspondence relationship. The correspondence relationship between ΔV and SOH can be obtained, for example, by actually measuring ΔV for each value of the SOH of the secondary battery. If the values vary widely, the correspondence relationship may be defined using an approximation function. Figure 5A shows an example of approximation using a linear function.

Figure 5B is an example of a third correspondence relationship. The correspondence relationship between ΔV and C rate can be defined for each SOH value. This correspondence relationship can be obtained, for example, by actually measuring ΔV for each C rate value and SOH value of the secondary battery. It may be defined using an approximation function as in Figure 5A. Figure 5B shows an example of approximation using a linear function. In S401, the processor 120 can obtain a ΔV at a higher C rate within the correspondence relationship by referring to the correspondence relationship in Figure 5B using the current ΔV and SOH. This allows ΔV to be converted to a value at the higher C rate.

Figure 5C is an example of the second correspondence relationship. In the second embodiment, the correspondence relationship between dV/dt and SOH can be defined for each value of the C rate (in the first embodiment, the C rate is a fixed value). This correspondence relationship can be obtained, for example, by measuring dV/dt for each value of the SOH and the C rate. It may be defined using an approximation function as in Figure 5A. Figure 5C shows an example of approximation using a high-order function (second order or higher). In S402, the processor 120 can estimate dV/dt by referring to the correspondence relationship in Figure 5C using the current C rate and SOH.

<Third embodiment>
In the third embodiment of the present invention, a method for determining the length of the period T1 will be described. Other configurations are similar to those of the first and second embodiments. For example, it is conceivable to experimentally determine the length of the period T1 by measuring the impedance of the battery cells using electrochemical impedance spectroscopy (EIS) for a plurality of secondary batteries.

Figure 6 shows an example of the impedance of a battery cell measured using an EIS. By analyzing the impedance characteristics of multiple secondary batteries at different frequencies, it is possible to obtain impedance characteristics for each battery and for each frequency band. From these impedance characteristics, it is possible to obtain the time domain requiring a high sampling rate (to the left of the vertical dotted line in Figure 6) and the time domain for which a low sampling rate is sufficient (to the right of the vertical dotted line in Figure 6). By creating a lookup table or the like for each secondary battery based on this, it is possible to define the length of period T1 for each secondary battery. The data acquisition unit 110 simply acquires data describing this definition.

<Fourth embodiment>
FIG. 7 shows an example of an equivalent circuit diagram of a secondary battery. The upper part of FIG. 7 shows a secondary model, and the lower part of FIG. 7 shows a primary model. By simulating the change over time of the battery voltage after charging and discharging using a circuit model such as that shown in FIG. 7, it is possible to derive specific parameters that can be used to estimate the SOH. However, such a simulation method may require a long calculation time to obtain sufficient estimation accuracy. In addition, when charging and discharging using a low C rate, the fluctuation range of the battery voltage is small, so the accuracy of the fitting process, etc. may be insufficient.

Therefore, it is possible to combine the methods described in the first to third embodiments with a simulation using the circuit model shown in FIG. 7. This is thought to improve the accuracy of SOH estimation compared to using the circuit model method shown in FIG. 7 alone.

<Modifications of the present invention>
The present invention is not limited to the above-described embodiment, and includes various modified examples. For example, the above-described embodiment has been described in detail to clearly explain the present invention, and is not necessarily limited to those having all of the configurations described. In addition, it is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. In addition, it is possible to add, delete, or replace a part of the configuration of each embodiment with another configuration.

In the above embodiment, the SOH is estimated during the pause period after the battery discharge operation. However, if a change over time in the output voltage corresponding to the SOH appears during the pause period after the charge operation, the SOH can be estimated in the same manner as in the above embodiment. Whether a change over time that correlates with the SOH appears during the pause period after the discharge operation, the pause period after the charge operation, or both depends on the characteristics of the battery. Therefore, the SOH can be estimated during any of these periods depending on the characteristics of the battery.

In the above embodiment (FIG. 2), an example of an implementation form of the battery state estimation device has been described, but other implementation forms are also possible. For example, the method according to the present invention can be implemented by acquiring a measured value of the battery voltage via the data acquisition unit 110 from any measuring device incorporated in a device equipped with a secondary battery or any measuring device attached externally to the device.

In the above embodiments, the processor 120 can be configured by hardware such as a circuit device that implements its functions, or alternatively, by a computing device such as a CPU (Central Processing Unit) that executes software that implements its functions.

In the above embodiment, it is assumed that the secondary battery is a lithium ion battery, but the present invention can be applied to other types of secondary batteries. For example, the present invention can be applied to secondary batteries such as lead acid batteries, nickel-cadmium batteries, and electric double layer capacitors.

100: Battery state estimation device 110: Data acquisition unit 120: Processor

Claims (14)

A battery state estimation device that estimates a state of a battery,
a data acquisition unit for acquiring data describing an output voltage from the battery;
a calculation unit for estimating a deterioration state of the battery according to the data;
Equipped with
The calculation unit obtains a voltage value from the data during a rest period after charging or discharging the battery,
The calculation unit identifies a baseline voltage of the voltage value from the voltage value of a period that starts when a predetermined time has elapsed from the start point of the idle period,
The calculation unit calculates a difference between the baseline voltage and the voltage value;
The calculation unit estimates a time derivative of the output voltage within the predetermined time period according to the difference;
The calculation unit estimates the degradation state according to a relationship between the time differential and the degradation state ;
The computing unit updates the baseline voltage according to the estimated time derivative;
The calculation unit recalculates the difference according to the updated baseline voltage;
The calculation unit estimates the degradation state according to a first relationship between the difference and the degradation state.
A battery state estimating device comprising: A battery state estimation device that estimates a state of a battery,
a data acquisition unit for acquiring data describing an output voltage from the battery;
a calculation unit for estimating a deterioration state of the battery according to the data;
Equipped with
The calculation unit obtains a voltage value from the data during a rest period after charging or discharging the battery,
The calculation unit identifies a baseline voltage of the voltage value from the voltage value of a period that starts when a predetermined time has elapsed from the start point of the idle period,
The calculation unit calculates a difference between the baseline voltage and the voltage value;
The calculation unit estimates a time derivative of the output voltage within the predetermined time period according to the difference;
The calculation unit estimates the degradation state according to a relationship between the time differential and the degradation state ;
The calculation unit provisionally estimates the degradation state according to a first relationship between the difference and the degradation state;
The calculation unit provisionally estimates the time derivative according to a second relationship between the time derivative and the deterioration state;
The computing unit updates the baseline voltage according to the estimated time derivative;
The calculation unit recalculates the difference according to the updated baseline voltage;
The calculation unit continues the process until the deterioration state is converged.
estimating the degradation state according to the first relationship;
estimating the time derivative according to the second relationship;
recalculating the difference;
Repeat
A battery state estimating device comprising: A battery state estimation device that estimates a state of a battery,
a data acquisition unit for acquiring data describing an output voltage from the battery;
a calculation unit for estimating a deterioration state of the battery according to the data;
Equipped with
The calculation unit obtains a voltage value from the data during a rest period after charging or discharging the battery,
The calculation unit identifies a baseline voltage of the voltage value from the voltage value of a period that starts when a predetermined time has elapsed from the start point of the idle period,
The calculation unit calculates a difference between the baseline voltage and the voltage value;
The calculation unit estimates a time derivative of the output voltage within the predetermined time period according to the difference;
The calculation unit estimates the degradation state according to a relationship between the time differential and the degradation state ;
the data acquisition unit acquires the data describing the output voltage when the battery is charged or discharged at a first C rate;
The calculation unit converts the difference into a second difference when the battery is charged or discharged at a second C rate,
a third relationship between the difference, the second difference, the first C-rate, and the second C-rate;
Convert according to
The calculation unit re-estimates the time derivative according to the second difference.
A battery state estimating device comprising: The calculation unit estimates the time derivative according to a second relationship between the time derivative and the deterioration state;
The calculation unit updates the baseline voltage according to the time derivative estimated according to the second relationship.
2. The battery state estimating device according to claim 1 . The calculation unit continues the process until the deterioration state is converged.
estimating the degradation state according to the first relationship;
estimating the time derivative according to the second relationship;
recalculating the difference;
The battery state estimating device according to claim 4 , characterized in that the above-mentioned is repeated. The third relationship is defined for each value of the degradation state,
The calculation unit provisionally estimates the deterioration state from the difference,
The battery state estimation device according to claim 3 , wherein the calculation unit converts the difference into the second difference by referring to the third relationship corresponding to the provisionally estimated deterioration state. The relationship between the time derivative and the deterioration state is defined for each value of the C rate,
The calculation unit estimates the degradation state by referring to the relationship corresponding to the second C rate.
4. The battery state estimating device according to claim 3 . The battery state estimation device according to any one of claims 1 to 3, characterized in that the data acquisition unit acquires the data from a measuring device incorporated within an apparatus equipped with the battery or from a measuring device attached externally to the apparatus equipped with the battery. the device equipped with the battery is an electric vehicle,
the measuring device is a charger or an OBD tool for the electric vehicle;
The battery state estimation device according to claim 8 , wherein the data acquisition unit acquires the data from the measuring device without removing the battery from the electric vehicle. The battery state estimation device according to any one of claims 1 to 3 ,
The battery,
A battery system comprising: The battery system further includes a controller for controlling charging and discharging of the battery.
The battery system according to claim 10 , wherein the calculation unit determines the start time of the rest period in accordance with an instruction from the controller to the battery. A battery state estimation method for estimating a state of a battery, comprising:
obtaining data describing an output voltage from the battery;
estimating a state of health of the battery according to the data;
having
In the step of estimating, a voltage value is obtained from the data during a rest period after charging or discharging the battery;
In the estimating step, a baseline voltage of the voltage value is identified from the voltage value of a period that starts when a predetermined time has elapsed from the start point of the idle period;
the estimating step calculating a difference between the baseline voltage and the voltage value;
In the estimating step, a time derivative of the output voltage within the predetermined time period is estimated according to the difference;
In the estimating step, the degradation state is estimated according to a relationship between the time derivative and the degradation state ;
updating the baseline voltage in accordance with the estimated time derivative in the estimating step;
In the estimating step, the difference is recalculated according to the updated baseline voltage;
In the step of estimating, the degradation state is estimated according to a first relationship between the difference and the degradation state.
A battery state estimating method comprising: A battery state estimation method for estimating a state of a battery, comprising:
obtaining data describing an output voltage from the battery;
estimating a state of health of the battery according to the data;
having
In the step of estimating, a voltage value is obtained from the data during a rest period after charging or discharging the battery;
In the estimating step, a baseline voltage of the voltage value is identified from the voltage value of a period that starts when a predetermined time has elapsed from the start point of the idle period;
the estimating step calculating a difference between the baseline voltage and the voltage value;
In the estimating step, a time derivative of the output voltage within the predetermined time period is estimated according to the difference;
In the estimating step, the degradation state is estimated according to a relationship between the time derivative and the degradation state ;
In the estimating step, the degradation state is tentatively estimated according to a first relationship between the difference and the degradation state;
In the estimating step, the time derivative is tentatively estimated according to a second relationship between the time derivative and the deterioration state;
updating the baseline voltage in accordance with the estimated time derivative in the estimating step;
In the estimating step, the difference is recalculated according to the updated baseline voltage;
In the step of estimating, until the deterioration state converges,
estimating the degradation state according to the first relationship;
estimating the time derivative according to the second relationship;
recalculating the difference;
Repeat
A battery state estimating method comprising: A battery state estimation method for estimating a state of a battery, comprising:
obtaining data describing an output voltage from the battery;
estimating a state of health of the battery according to the data;
having
In the step of estimating, a voltage value is obtained from the data during a rest period after charging or discharging the battery;
In the estimating step, a baseline voltage of the voltage value is identified from the voltage value of a period that starts when a predetermined time has elapsed from the start point of the idle period;
the estimating step calculating a difference between the baseline voltage and the voltage value;
In the estimating step, a time derivative of the output voltage within the predetermined time period is estimated according to the difference;
In the estimating step, the degradation state is estimated according to a relationship between the time derivative and the degradation state ;
obtaining data describing the output voltage when the battery is charged or discharged at a first C rate;
In the estimating step, the difference is converted to a second difference when the battery is charged or discharged at a second C rate;
a third relationship between the difference, the second difference, the first C-rate, and the second C-rate;
Convert according to
In the estimating step, the time derivative is re-estimated according to the second difference.
A battery state estimating method comprising:

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