JP7025287B2 - Battery state estimation device and battery state estimation method - Google Patents

Description

The present invention relates to a battery state estimation device that estimates the battery state of a secondary battery such as the amount of charged electricity and the battery temperature, and a battery state estimation method.

Nickel-hydrogen secondary batteries and lithium-ion secondary batteries are used as in-vehicle power sources for electric vehicles, hybrid vehicles, and the like because of their high energy density.
In order to determine the battery state of such a secondary battery, a technique for performing complex impedance analysis on the secondary battery has been proposed (see, for example, Patent Document 1).

The apparatus described in Patent Document 1 includes a secondary battery in which the degree of deterioration is measured, a measured frequency and a measured temperature, and an initial limit capacity of one secondary battery having the same specifications as the measured secondary battery. It includes a storage unit for storing information and a temperature measuring unit for measuring the temperature of the secondary battery. In addition, this device has a power supply unit that applies an AC signal with a measurement frequency of 0.5 MHz or more and less than 10 MHz to a secondary battery with a measurement temperature of 40 ° C. or higher and 70 ° C. or lower based on the information in the storage unit, and a power supply. It is provided with a measuring unit for measuring the complex impedance of the secondary battery (see the vertical region dc of the impedance curve L121 in FIG. 12) by the AC signal applied by the unit. Further, this device detects the degree of deterioration by using the limit capacity of the secondary battery calculated by using the measured value of the measuring unit and the initial limit capacity stored in the storage unit.

International Publication No. 2014/054796

By the way, as shown in FIG. 12, the impedance curve L121 in the Nyquist diagram usually has a plurality of regions corresponding to the band of the measurement frequency. Specifically, the impedance curve L121 corresponds to the “region a” corresponding to the circuit resistance and the “region b” corresponding to the solution resistance in response to the band changing from the high frequency side to the low frequency side. It has a "region c" corresponding to the complex impedance due to the reaction resistance and a "diffusion region d" corresponding to the substantially linear diffusion resistance. Then, in the apparatus described in Patent Document 1, in the "diffusion region d", the imaginary component in the "vertical region dc" which is a region on the lower frequency side than the "straight line region da" following the "region c". The degree of deterioration of the secondary battery is measured based on the value. However, the "straight line region da" is a region in which the ratio of the change amount of the imaginary number component to the change amount of the real number component is in the range of a predetermined value close to "1", and the "vertical region dc" is the region with respect to the real number component. This is a region where the change in the imaginary number component is large and changes almost vertically in the Nyquist diagram.

However, since the above-mentioned technique utilizes the "vertical region dc" which is in the "diffusion region d" and is on the lower frequency side, it is inevitable that it takes time to measure the complex impedance, and the battery state can be adjusted in a timely manner. It was difficult to get.

The present invention has been made in view of such circumstances, and an object thereof is a battery state estimation device capable of reducing the time required for estimation of a battery state based on complex impedance, and a battery state estimation method. Is to provide.

The battery state estimation device that solves the above problems is a battery state estimation device that estimates the amount of charging electricity of the secondary battery, and is an impedance measurement that measures the complex impedance of the secondary battery based on the application of power for measurement. The measured angular velocity is the angular velocity corresponding to the diffusion region among the measured complex impedances, and the difference between the measured angular velocities of the two complex impedances having different measured angular velocities and the components of the two complex impedances. A parameter calculation unit that calculates a parameter consisting of a ratio to the difference, information that indicates the relationship between the charge electricity amount of the secondary battery and the parameter, which is preset information, and the parameter calculation unit calculated the information. It is provided with an electricity amount estimation unit that estimates the charge electricity amount of the secondary battery based on the parameters.

As the battery state estimation device, the power for measurement is DC power for measurement or AC power for measurement.
The battery state estimation device that solves the above problems is a battery state estimation device that estimates the amount of charging electricity of the secondary battery, and is an impedance that measures the complex impedance of the secondary battery based on the application of AC power for measurement. A parameter consisting of the ratio between the measurement unit and the difference in the measured angular velocities of the two complex impedances that are within the diffusion region and have different measured angular velocities among the measured complex impedances and the difference in the components of the two complex impedances. Based on the parameter calculation unit for calculating the above, the preset information indicating the relationship between the charge electricity amount of the secondary battery and the parameter, and the parameter calculated by the parameter calculation unit. It is provided with an electricity amount estimation unit that estimates the charge electricity amount of the secondary battery.

The battery state estimation method that solves the above problems is a battery state estimation method that estimates the amount of charging electricity of the secondary battery, and is an impedance measurement that measures the complex impedance of the secondary battery based on the application of power for measurement. Of the steps and the measured complex impedance, the angular velocity corresponding to the diffusion region is the measured angular velocity, and the difference between the measured angular velocities of the two complex impedances having different measured angular velocities and the components of the two complex impedances. It was calculated in the parameter calculation step of calculating the parameter consisting of the ratio with the difference, the information indicating the relationship between the charge electricity amount of the secondary battery and the parameter, which is preset information, and the parameter calculation step. The present invention includes an electricity amount estimation step of estimating the charging electricity amount of the secondary battery based on the parameters.

According to such a configuration or method, the charge electricity amount of the battery can be estimated based on the measurement result of the complex impedance. In a secondary battery, the complex impedance in the diffusion region is measured in a low frequency band of, for example, 0.1 Hz or less, so that it takes a relatively long time to measure, but by using only two points in the low frequency band, The time required to estimate the amount of charging electricity can be reduced. That is, the frequency range in the diffusion region is often 0.1 Hz or less, and for example, even if 0.1 Hz to 0.01 Hz is used for measurement, it is in a practical time range of about 10 seconds to 100 seconds. Measurement is possible.

Further, since the change of the complex impedance is linear, there are few restrictions on the selection of the measurement frequencies of the two complex impedances, and the difference in the components of the complex impedance can be easily obtained.

The preset information may be one model information, or may be selected from a plurality of models set for each temperature of the secondary battery.
Further, of the two complex impedance components in the diffusion region, the imaginary number component can be used to estimate the battery state of the secondary battery, but if there is a correlation between the imaginary number component and the real number component, the imaginary number is used. It is also possible to replace the component with a real number component and use the real number component for estimating the battery state of the secondary battery.

As a preferable configuration, a temperature acquisition unit for acquiring the temperature of the secondary battery is further provided, and the preset information includes information set for each temperature of the secondary battery, and the amount of electricity. The estimation unit selects, among the information set for each temperature of the secondary battery, the information corresponding to the acquired temperature as the preset information.

According to such a configuration, the amount of charging electricity can be estimated with high accuracy in consideration of the temperature of the secondary battery.
As a preferred configuration, the charging electricity amount of the secondary battery estimated when the secondary battery is fully charged and the preset reference electricity amount, which is appropriate charging when the secondary battery is fully charged. It is provided with a first variation determination unit for determining whether or not the charge electricity amount of the secondary battery varies by comparing with the reference electricity amount which is the electricity amount.

According to such a configuration, it is possible to determine whether or not there is a variation in the amount of charging electricity for the secondary battery.
As a preferable configuration, the secondary battery is an assembled battery, and the charged electricity amount estimated by the electric amount estimation unit is acquired for each of the two groups in which the assembled battery is divided so that at least a part of the batteries does not overlap. Further, it is provided with a variation determination unit for determining whether or not there is a variation in the charge electricity amount between the batteries constituting the assembled battery based on the comparison of the charge electricity amount of the two groups.

According to such a configuration, it is possible to determine whether or not there is a variation in the amount of charging electricity for a set battery composed of a plurality of single batteries or a plurality of battery modules.
The battery state estimation device that solves the above-mentioned problems is a battery state estimation device that estimates the temperature of the secondary battery, and is an electricity amount acquisition unit that acquires the charge electricity amount of the secondary battery and a power supply for measurement. The measured angular velocity is the angular velocity corresponding to the diffusion region among the measured complex impedance and the impedance measuring unit that measures the complex impedance of the secondary battery based on the above, and the measured angular velocity is different between the two complex. A parameter calculation unit that calculates a parameter consisting of the ratio of the difference in the measured angular velocity of the impedance and the difference between the two complex impedance components, and the preset information, which is the parameter with respect to the charging electricity amount of the secondary battery. The temperature of the secondary battery is based on applying the amount of charging electricity acquired by the electricity amount acquisition unit and the parameter calculated by the parameter calculation unit to the information indicating the relationship between the electricity and the temperature of the secondary battery. It is provided with a temperature estimation unit for estimating.

The battery state estimation method that solves the above-mentioned problems is a battery state estimation method that estimates the temperature of the secondary battery, that is, an electricity amount acquisition step for acquiring the charging electricity amount of the secondary battery, and power supply for measurement. The measurement angular velocity is the angular velocity corresponding to the diffusion region among the measured complex impedances and the impedance measuring step of measuring the complex impedance of the secondary battery based on the above, and the measured angular velocities are different. A parameter calculation step for calculating a parameter consisting of the ratio of the difference in the measured angular velocity of the impedance and the difference between the two complex impedance components, and the preset information, which is the parameter with respect to the charging electricity amount of the secondary battery. The temperature of the secondary battery is based on applying the amount of charging electricity acquired in the electricity amount acquisition step and the parameter calculated in the parameter calculation step to the information indicating the relationship between the electricity and the temperature of the secondary battery. It is provided with a temperature estimation process for estimating.

According to such a configuration or method, the temperature of the battery can be estimated based on the measurement result of the complex impedance. In a secondary battery, the complex impedance in the diffusion region is measured in a low frequency band of, for example, 0.1 Hz or less, so that it takes a relatively long time to measure, but by using only two points in the low frequency band, The time required to estimate the battery temperature can be reduced.

Further, since the temperature of the battery is usually measured on the surface of the battery, it is not possible to obtain the temperature of the electrode plate group itself, which has a strong influence on charge / discharge. In this respect, according to this configuration, the temperature of the electrode plate group itself is estimated as the temperature of the battery based on the state of the portion where the current flows in the electrode plate group. Therefore, the temperature of the battery can be obtained with high accuracy.

As a preferred configuration, each of the two complex impedance components is an imaginary component of the complex impedance.
With such a configuration, the battery state can be estimated based on the imaginary components of the two complex impedances in the diffusion region. Since the amount of change in the real number component of the complex impedance in the diffusion region tends to be small on the low frequency side, the degree of freedom in selecting the measurement angular velocity of the complex impedance can be increased by using the imaginary number component.

As a preferred configuration, the parameter calculation unit sets the difference between the reciprocals of the measured angular velocities of the two complex impedances as "Δ (ω ^-1 )" and the difference between the imaginary components of the two complex impedances as "ΔZi". When the parameter is " _QD ", it is calculated based on the following formula.

このような構成によれば、測定角速度についてその逆数の差に対する虚数成分の差の割合のさらに逆数をパラメータとすることで、このパラメータと、予め設定された情報であって、二次電池の電池状態とパラメータとの関係を示す情報とに基づいて二次電池の電池状態を推定することができるようになる。また、２つの複素インピーダンスの測定角速度の差として、測定角速度についてその逆数の差を用いることで、傾きの逆数を線形、もしくは線形に近いかたちで得ることができるようになる。

According to such a configuration, by further setting the reciprocal of the ratio of the difference of the imaginary component to the difference of the reciprocal of the measured angular velocity as the parameter, this parameter and the preset information are the batteries of the secondary battery. It becomes possible to estimate the battery state of the secondary battery based on the information indicating the relationship between the state and the parameter. Further, by using the difference between the reciprocals of the measured angular velocities as the difference between the measured angular velocities of the two complex impedances, the reciprocal of the slope can be obtained linearly or in a form close to linear.

As a preferred configuration, the measured angular velocities of the two complex impedances are angular velocities within a range in which the absolute value of the rate of change of the imaginary component with respect to the real component of the two complex impedances is 0.5 or more and 2 or less.

According to such a configuration, of the two complex impedances in the diffusion region, the rate of change of the imaginary component with respect to the real component is in the range close to "1", so that the real component is used instead of the imaginary component. Also, the battery state can be estimated from the complex impedance of the secondary battery.

As a preferred configuration, the secondary battery is a nickel metal hydride secondary battery.
In a nickel-metal hydride secondary battery, since the relationship between voltage and SOC is not proportional, it is difficult to estimate the battery state such as the amount of charging electricity based on the voltage. In this respect, according to such a configuration, since the battery state is estimated based on the change of the complex impedance component in the diffusion region, the battery state is preferably estimated even in the nickel-metal hydride secondary battery. You will be able to do it.

According to the present invention, it is possible to reduce the time required for the measurement of the battery state based on the complex impedance.

The block diagram which shows the schematic structure about the 1st Embodiment which embodied the battery state estimation device. In the same embodiment, the flowchart which shows the procedure of setting the information which shows the relationship between the charge electric energy and a parameter. In the same embodiment, a graph showing an example of a Nyquist diagram created from complex impedance measured for a secondary battery. In the same embodiment, a graph showing an example of the relationship between the reciprocal of the measured angular velocity of complex impedance and the imaginary component. In the same embodiment, the graph which shows the relationship between the parameter based on a complex impedance and the charge electric energy. In the same embodiment, a flowchart showing a procedure for estimating the charge electricity amount from the complex impedance. In the same embodiment, a flowchart showing a procedure for determining a variation in the amount of charged electricity for two groups consisting of batteries constituting an assembled battery. The block diagram which shows the schematic structure about the 2nd Embodiment which embodied the battery state estimation device. In the same embodiment, the graph which shows the relationship between the parameter based on the complex impedance and the charge electric energy separately by the battery temperature. In the same embodiment, a flowchart showing a procedure for setting information indicating a relationship between a battery temperature and a parameter. In the same embodiment, a flowchart showing a procedure for estimating a battery temperature from a parameter based on complex impedance. A graph showing an example of a Nyquist diagram created based on the complex impedance measured for a secondary battery. It is a figure which shows the schematic structure of the 3rd Embodiment which embodies the battery state estimation apparatus, (a) is a graph of current / voltage for measurement, (b) is a graph which frequency-converted (a), respectively. , (C) is a Nyquist diagram created from the impedance calculated from the result of (b). The figure which shows the relationship between the measurement current voltage and the measurement result of the AC current voltage about the other embodiment which embodies the battery state estimation device.

(First Embodiment)
A first embodiment that embodies the battery state estimation device and the battery state estimation method will be described with reference to FIGS. 1 to 7. This battery state estimation device and battery state estimation method are used, for example, to estimate the amount of charging electricity, which is one of the battery states of a battery 10 such as a secondary battery mounted on a vehicle. In this embodiment, the battery 10 is a nickel-metal hydride secondary battery. Further, the charge electricity amount is a value calculated from the total capacity of the battery and the state of charge (SOC), and has a correlation with the value of the SOC. Here, the total capacity of the battery is a predetermined amount of electricity, which is the amount of electricity that can be charged to a new battery. Since the SOC is the ratio [%] of the charging electricity amount to the total battery capacity, it has a relationship of "charging electricity amount = total battery capacity x SOC". In the following, for convenience of explanation, both the charging electric energy and the SOC will be described.

First, with reference to FIG. 1, a configuration of a measurement circuit for measuring the characteristics of the battery 10 and an estimation device 30 as a battery state estimation device for estimating the charge electricity amount of the battery 10 will be described.
As shown in FIG. 1, the measuring circuit for measuring the characteristics of the battery 10 includes the battery 10 and a measuring charge / discharging device 20 for supplying a direct current and an alternating current between the terminals of the battery 10. Further, the measuring circuit includes a voltage measuring device 21 for measuring the voltage between the terminals of the battery 10 and a current measuring device 22 for measuring the current flowing between the charging / discharging device 20 for measurement and the battery 10.

The charging / discharging device 20 for measurement can charge the battery 10 with a DC current of a predetermined amount of current, and can discharge the DC current of a predetermined amount of current from the battery 10. That is, the charging / discharging device 20 for measurement can adjust the SOC (charged electricity amount) of the battery 10.

Further, the charging / discharging device 20 for measurement can supply an alternating current for impedance measurement to the battery 10. The charging / discharging device 20 for measurement generates an alternating current having a predetermined measurement frequency, and outputs the generated alternating current between the terminals of the battery 10. Further, the charging / discharging device 20 for measurement can change the measurement frequency of the alternating current. The charging / discharging device 20 for measurement has an output current and a frequency range of a measurement frequency set, and outputs the alternating current of the set output current as a measurement frequency that changes in the same set frequency range. The frequency range to be set is, for example, a range from 100 kHz as the high frequency side to 1 MHz as the low frequency side. However, the present invention is not limited to this, and the high frequency side may be higher than 100 kHz, and the low frequency side may be lower than 1 kHz. Further, a frequency range for the purpose of the "straight line region da" in the "diffusion region d" shown in FIG. 12, for example, a range from 0.1 Hz to 0.01 Hz may be output. Further, two or more different frequencies in the "diffusion region d", for example, a frequency between 0.1 Hz and 0.01 Hz may be output. As mentioned above, since it is clear that the angular velocity and the frequency have a relationship of "angular velocity = 2π x frequency", both the angular velocity and the frequency will be described for convenience of explanation.

The measurement charging / discharging device 20 outputs each signal regarding the set value of the output AC current and the set value of the measurement frequency to the estimation device 30. Further, the charging / discharging device 20 for measurement switches the output and the stop of the alternating current according to the output start signal and the output stop signal input from the estimation device 30.

The voltage measuring device 21 outputs a voltage signal corresponding to the AC voltage and the DC voltage measured between the electrodes of the battery 10 to the estimation device 30.
The current measuring device 22 outputs a current signal corresponding to the alternating current and the direct current measured between the charging / discharging device 20 for measurement and the battery 10 to the estimation device 30.

A temperature measuring device 23 for measuring the temperature of the battery is attached to the battery 10. The temperature measuring device 23 outputs a temperature signal corresponding to the measured temperature of the battery 10 to the estimation device 30.
The estimation device 30 estimates the amount of electricity charged by the battery 10. The estimation device 30 may display the estimated charge electricity amount of the battery 10 or output it to the outside. For example, the external battery control device (not shown) may perform charge / discharge control on the battery 10 according to the amount of charge electricity of the battery 10 output from the estimation device 30.

The estimation device 30 acquires the voltage between the terminals of the battery 10 based on the voltage signal input from the voltage measuring device 21, and the charging / discharging device 20 for measurement and the battery 10 based on the current signal input from the current measuring device 22. Get the current flowing between them. The estimation device 30 acquires AC current setting information and the like from a signal input from the measurement charge / discharge device 20. The estimation device 30 acquires the temperature of the battery 10 based on the temperature signal input from the temperature measuring device 23.

The estimation device 30 includes a processing unit 40 that performs calculation processing related to estimation of the charge electricity amount of the battery 10, and a storage unit 50 that holds information used for calculation processing of the charge electricity amount of the battery 10.
The storage unit 50 is a non-volatile storage device such as a hard disk or a flash memory, and holds various data. In the present embodiment, the storage unit 50 holds the correlation data 51 between the parameter required for calculating the charging electricity amount and the charging electricity amount, and the calculation data 52. As the calculation data 52, the total capacity of the battery 10 and the like are set.

The processing unit 40 includes a microcomputer composed of a CPU, ROM, RAM, and the like. The processing unit 40 can use information such as voltage, current, and measurement frequency acquired by the estimation device 30. Further, the processing unit 40 can exchange data with and from the storage unit 50. The processing unit 40 executes various processes in the processing unit 40 by, for example, executing various programs held in the ROM or RAM by the CPU.

In the present embodiment, as shown in FIG. 2, the processing unit 40 can acquire the correlation data 51 showing the relationship between the parameter and the charge electricity amount, and can execute the process of storing the correlation data 51 in the storage unit 50. Further, as shown in FIG. 6, the processing unit 40 can execute a process of estimating the charge electricity amount of the battery 10 based on the complex impedance Z acquired from the battery 10. Further, as shown in FIG. 7, it is possible to execute a process of determining the presence or absence of SOC variation in the battery 10. It is not necessary to determine the presence or absence of variation.

The processing unit 40 includes an SOC adjusting unit 41 that adjusts the SOC of the battery 10 and a temperature measuring unit 42 that measures the battery temperature of the battery 10. Further, the processing unit 40 includes an impedance measurement unit 43 for measuring the complex impedance Z, a Nyquist diagram creation unit 44 for creating a Nyquist diagram, a parameter calculation unit 45 for calculating parameters, and electricity for calculating the amount of electricity charged. A quantity calculation unit 46 is provided.

The SOC adjustment unit 41 adjusts the SOC of the battery 10 to a predetermined SOC suitable for acquiring the correlation data 51 when the processing unit 40 acquires the correlation data 51 indicating the relationship between the parameter based on the complex impedance and the charge electricity amount. do. The SOC adjusting unit 41 sequentially adjusts the battery 10 to a predetermined SOC by instructing the charging / discharging device 20 for measurement to charge / discharge the current. For example, the predetermined SOC includes 40%, 45%, 50%, 55%, 60% and the like. Further, the SOC adjusting unit 41 may measure the battery 10 by a well-known method, or may acquire the SOC of the battery 10 from a control device or the like of the battery 10. The SOC measured here requires more time to measure than the SOC estimated in the present embodiment, so that the measurement accuracy is maintained.

The temperature measuring unit 42 measures the temperature of the battery 10. For example, the temperature measuring unit 42 is attached to the housing of the battery 10, or a signal from a well-known temperature measuring unit installed in the battery is input.

The impedance measuring unit 43 performs a process (impedance measuring step) of measuring the complex impedance Z of the battery 10. The impedance measuring unit 43 instructs the charging / discharging device 20 for measurement to start or end the measurement. The impedance measuring unit 43 measures the complex impedance Z of the battery 10 based on the voltage and current acquired from the start to the end of the measurement. The unit of complex impedance Z is [Ω] (ohm). The complex impedance Z is represented by the vector component Zr [Ω] and the imaginary number component Zi [Ω] as shown in the equation (1). Note that "j" is an imaginary unit. Hereinafter, the unit [Ω] is omitted.

ナイキスト線図作成部４４は、複数の測定周波数における複素インピーダンスＺに基づいて、それらのベクトル成分である実数成分Ｚｒと虚数成分Ｚｉとから、ナイキスト線図を作成する。

The Nyquist diagram creation unit 44 creates a Nyquist diagram from the real number component Zr and the imaginary number component Zi, which are vector components thereof, based on the complex impedance Z at a plurality of measurement frequencies.

For example, as shown in FIG. 3, the Nyquist diagram creating unit 44 creates an impedance curve L21 as a Nyquist diagram on a complex plane having a real axis on the horizontal axis and an imaginary axis on the vertical axis. The impedance curve L21 is an example of a Nyquist diagram corresponding to the battery 10 having a predetermined SOC. The impedance curve L21 is a plot of the magnitudes of the real number component Zr and the imaginary number component Zi of the complex impedance Z on the complex plane. This impedance curve L21 is based on the complex impedance Z measured by changing the measurement frequency of the alternating current supplied from the measurement charge / discharge device 20 to the battery 10.

In FIG. 3, each point in the impedance curve L21 indicates one measurement frequency. In FIG. 3, the lower side is the high frequency side and the upper side is the low frequency side. The impedance curve L21 changes depending on the SOC of the battery 10 and the battery temperature. It also changes depending on the battery type such as nickel-metal hydride secondary battery and lithium-ion secondary battery. Furthermore, even if the battery type is the same, it will change if the number of cells, capacity, etc. are different.

Here, the impedance curve L21 of the battery 10 will be described in detail with reference to FIGS. 3 and 12.
As shown in FIG. 3, the impedance curve L21 of the battery 10 is divided into a plurality of regions corresponding to the characteristics of the battery 10. The plurality of regions are divided into "region a", "region b", "region c", and "diffusion region d" from the high frequency side to the low frequency side of the measurement frequency. The “region a” is a circuit resistance region corresponding to the circuit resistance. “Region b” is a solution resistance region corresponding to the solution resistance. The “region c” is a reaction resistance region corresponding to the complex impedance Z caused by the reaction resistance. The “diffusion region d” is a region corresponding to a substantially linear diffusion resistance. The circuit resistance is the impedance of wiring or the like composed of an active material, contact resistance in a current collector, or the like. The solution resistance is the resistance of electrons such as the resistance when ions in the electrolytic solution in the separator move. The reaction resistance is the resistance of charge transfer in the electrode reaction and the like. Diffusion resistance is the impedance in which material diffusion is involved. Since each resistance affects each other, it is difficult to divide each region a, b, c, d into only a portion affected by each resistance, but at least each region a of the impedance curve L21 a. The rough behavior of the curves of, b, c, and d is determined by the resistance component that is most affected by each. For example, the "region c" is greatly influenced by the mode of the negative electrode, and the "diffusion region d" is greatly influenced by the mode of the positive electrode.

Roughly speaking, the impedance curve L21 of the battery 10 is a curve obtained by synthesizing the impedance of the positive electrode and the impedance of the negative electrode. For example, in the frequency range corresponding to the “diffusion region d”, the impedance of the positive electrode changes significantly, while the change in the impedance of the negative electrode is small. That is, it can be said that the “diffusion region d” of the impedance curve L21 is a region that is greatly affected by the impedance of the positive electrode and reflects the state of the positive electrode. On the other hand, in the frequency range corresponding to the "region c", the impedance of the negative electrode changes significantly, while the change in the impedance of the positive electrode is small. That is, it can be said that the “region c” of the impedance curve L21 is a region where the impedance of the negative electrode has a large influence and reflects the state of the negative electrode.

According to the impedance curve L21, in FIG. 3, the frequency range corresponding to the “diffusion region d” is “0.1 Hz” or less, and the measurement results up to “0.01 Hz” are shown. Further, the frequency range corresponding to the "region c" is larger than "0.1 Hz" and less than "100 Hz". Incidentally, the frequency range corresponding to the "region b" is higher than "100 Hz" and its vicinity, and the frequency range corresponding to the "region a" is higher than "100 Hz". The "diffusion region d" may be larger or smaller than "0.1 Hz" or less as long as the frequency region is lower than the "region c".

Further, as shown in FIG. 12, the “diffusion region d” includes a “straight line region da”, a “vertical region dc”, and a “region db”. The "straight line region da" is a region in which the ratio of the change amount of the imaginary number component to the change amount of the real number component is close to "1". That is, in the figure, it is a range close to an angle of 45 °, in other words, a range in which the absolute value of the rate of change of the imaginary component with respect to the real component of the complex impedance Z is 0.5 or more and 2 or less. Therefore, the "straight line region da" has a correlation between the imaginary number component and the real number component. The "vertical region dc" is a region in which the imaginary number component changes significantly with respect to the real number component, and is a region in which the graph changes substantially vertically (at an angle of approximately 90 °) in FIG. The “region db” is a boundary and a peripheral region that changes from the “straight line region da” to the “vertical region dc”.

By the way, in the battery 10, the measurement of the complex impedance Z is generally completed in the "straight line region da" because of the characteristics of the nickel-metal hydride secondary battery and the practicality of the measured values. Further, in the nickel-metal hydride secondary battery, the measurement frequency at which the "vertical region dc" is generated tends to be lower than the frequency at which the "vertical region dc" is generated in the lithium ion secondary battery. Further, in order to measure the "vertical region dc" of the battery 10 more reliably, the measurement environment is prepared by raising the temperature of the battery, and the measurement frequency is measured at a frequency lower than "0.01 Hz". It needs to be a frequency that takes time. Further, since the measurement frequency at which the "vertical region dc" occurs cannot be known in advance, the wasted time required for the measurement may be long. Then, when trying to measure the value of the "vertical region dc", it is difficult to estimate the time required for the measurement. Therefore, let's measure the value of the "vertical region dc" with respect to the battery 10 used in the vehicle or the like. Is not realistic.

The parameter calculation unit 45 shown in FIG. 1 is based on the ratio of the difference between the measurement frequencies of two complex impedances in the “diffusion region d” and having different measurement frequencies and the difference between the components of the two complex impedances. (See FIG. 4) is calculated (parameter calculation step). Here, the two complex impedances are "Z1" and "Z2", the imaginary component of the complex impedance "Z1" is "Zi1", the measurement frequency is "f1", and the imaginary component of the complex impedance "Z2" is "Zi2". The measurement frequency is "f2".

More specifically, the parameter calculation unit 45 determines the difference (change amount) "Δω = 2π × (f1-) of the measured angular velocities of the two complex impedances when the two complex impedances" Z1 "and" Z2 "of the battery 10 are measured. f2) ”and the difference (change amount) of the imaginary component of the two complex impedances“ ΔZi = Zi1-Zi2 ”are calculated.

Then, as shown in the graph L31 of FIG. 4, the difference "ΔZi" of the imaginary component of the two complex impedances is divided by the difference "Δ (ω ^-1 )" of the reciprocals of the measured angular velocities of the two complex impedances. It is a slope possessed by the difference in the imaginary number component, and the slope with respect to the difference in the reciprocal of the measured angular velocity is calculated as the parameter “ _QD ” equation (2). That is, the equation (2) shows that the reciprocal of the slope (ratio) of “ _ΔZi ” with respect to “Δ (ω ^-1 )” is the parameter “QD”. Since it is preferable to calculate the parameter "QD" as a positive value, "Δ (ω ^-1 )" or " _ΔZi " may be used as an absolute value, if necessary.

上述したように、パラメータ「Ｑ_Ｄ」は、式（２）が変形された式（３）に基づいて算出することもできる。パラメータ算出部４５は、パラメータを式（２）及び式（３）のいずれから演算するように設定されていてもよい。

As described above, the parameter " _QD " can also be calculated based on the modified equation (3) of the equation (2). The parameter calculation unit 45 may be set to calculate the parameter from either the equation (2) or the equation (3).

電気量算出部４６は、記憶部５０に予め設定されている情報であるパラメータと充電電気量との相関データ５１と、パラメータ算出部４５で算出したパラメータ「Ｑ_Ｄ」とに基づいて、電池１０に推定される充電電池量を算出する（充電電気量推定工程）。

The electric energy calculation unit 46 is based on the correlation data 51 between the parameter which is the information preset in the storage unit 50 and the charge electric energy amount, and the parameter " _QD " calculated by the parameter calculation unit 45, and the battery 10 Calculate the estimated amount of rechargeable battery (charged electricity amount estimation process).

Here, with reference to FIG. 5, the correlation data 51 between the parameter and the amount of charging electricity will be described. The correlation data 51 between the parameter and the amount of charged electricity is information indicating the relationship between the parameter “QD” in the “diffusion region _d ” and the SOC of the battery 10 with respect to the complex impedance Z of the battery 10.

FIG. 5 shows a graph L51 which is an example of the correlation data 51 between the parameter and the amount of charged electricity. Specifically, the graph L51 shows the relationship between the parameter “QD” (= ( _ΔZi / Δ (ω ^-1 )) ^-1 ) and the charge electricity amount [Ah] of the battery 10. The graph L51 is created based on the complex impedance Z obtained by measuring in advance and the amount of charging electricity at that time with respect to the battery 10 manufactured with the same specifications as the battery 10 as the measurement target. The graph L51 may be created from the measured values, may be created by combining the measured values with theory or experience, or may be information created based on the theory or experience. good. Further, since the graph L51 changes according to the battery temperature, it may be set for each predetermined battery temperature. If the graph L51 is provided to be different for each predetermined battery temperature, the amount of charging electricity of the secondary battery can be estimated more preferably.

That is, the correlation data 51 between the parameter held in the storage unit 50 of FIG. 1 and the amount of charging electricity is information preset in the storage unit 50, and is the “diffusion region d” of the complex impedance Z of the battery 10. This is information indicating the relationship between the parameter “ _QD ” related to the complex impedance Z and the amount of charging electricity of the battery 10.

A procedure for setting the correlation data 51 will be described with reference to FIG. 2. Since the correlation data 51 is created by measuring the complex impedance Z at each of a plurality of different SOCs of the batteries 10 manufactured with the same specifications, the process of setting the correlation data 51 is repeated each time the SOC is changed. Is done. Here, it will be described that the complex impedance Z is measured for one SOC and one of the correlation data 51 is set, and for convenience of explanation, the data of the correlation data 51 is acquired for each of the plurality of SOCs. I will omit the explanation about that.

The processing unit 40 includes a battery temperature adjusting step (step S10 in FIG. 2), an SOC adjusting step (step S11 in FIG. 2), and an impedance measuring step (step S12 in FIG. 2). The processing unit 40 performs a parameter calculation step (step S13 in FIG. 2), a step of calculating correlation data between the parameter and the amount of charged electricity (step S14 in FIG. 2), and a correlation data storage step (step S15 in FIG. 2). Be prepared. The value of the correlation data is affected by the temperature of the battery 10 and the SOC. Therefore, in the process of setting the correlation data 51, first, the battery temperature adjusting step and the SOC adjusting step are performed.

When the setting of the correlation data 51 is started as needed, in the battery temperature adjusting step (step S10), the temperature of the battery 10 is acquired by the temperature measuring unit 42, and the battery 10 is set to the specified temperature as needed. adjust. For example, if the temperature of the battery 10 is appropriate, the process proceeds to the next step, and if necessary, the temperature is adjusted. For example, the temperature of the battery 10 is set to a specified temperature (for example, 25 ° C.) by allowing the battery 10 to stand in an environment of 25 ° C. for a predetermined time. In the battery temperature adjusting step, the processing unit 40 may output a signal indicating that the temperature adjustment is necessary, and an external temperature adjusting device or the like may adjust the ambient temperature according to the signal.

In the SOC adjustment step (step S11), the SOC adjusting unit 41 adjusts the specified SOC of the battery 10. Since the correlation data 51 needs to measure the complex impedance Z in a plurality of SOCs, the SOCs are sequentially changed so that the complex impedances in each SOC are measured.

In the impedance measurement step (step S12), the impedance measuring unit 43 measures the complex impedance Z of the battery 10, and the impedance curve L21 based on the complex impedance Z measured by the Nyquist diagram creating unit 44 is created. Further, the Nyquist diagram creating unit 44 specifies the “diffusion region d” of the impedance curve L21.

In the parameter calculation step (step S13), the parameter calculation unit 45 acquires two complex impedances “Z1” and “Z2” from the “diffusion region d” specified in the impedance curve L21. For example, the complex impedance when the measurement frequency is 0.1 Hz is defined as “Z1”, and the complex impedance when the measurement frequency is 0.01 Hz is defined as “Z2”. Then, the parameter " _QD " is calculated by applying the above equation (3).

In the correlation data calculation step (step S14) between the parameter and the charge electricity amount, basic data for the graph L51 is created based on the relationship between the parameter “ _QD ” and the SOC. That is, the charge electricity amount is calculated based on the SOC, and the parameter " _QD " is associated with the calculated charge electricity amount.

In the correlation data storage step (step S15), the parameter “ _QD ” is stored as basic data for the graph L51 with respect to the calculated charge electricity amount. For example, as shown in FIG. 5, when the amount of charging electricity is about "0Ah", "0.1Ah", "0.9Ah", "1.8Ah", "2.7Ah" and "3.2Ah". Each parameter " _QD " corresponding to is set.

According to the graph L51 created based on the data set in this way, it becomes possible to estimate the charge electricity amount of the battery 10 corresponding to the parameter “ _QD ”.
(Action)
A procedure for estimating the charge electricity amount of the battery 10 will be described with reference to FIG.

The processing unit 40 includes a battery temperature adjusting step (step S20 in FIG. 6), an impedance measuring step (step S21 in FIG. 6), and a parameter calculation step (step S22 in FIG. 6). Further, the processing unit 40 includes a step of comparing correlation data and parameters (step S24 in FIG. 6) and a step of estimating the amount of charged electricity (step S25 in FIG. 6). The battery temperature adjusting step (step S20), the impedance measuring step (step S21), and the parameter calculation step (step S22) shown in FIG. 6 are the battery temperature adjusting step (step S10) and the impedance measurement shown in FIG. 2, respectively. It is the same process as the step (step S12) and the parameter calculation step (step S13). Therefore, duplicate explanations will be omitted for the same steps (steps) described above.

The processing unit 40 adjusts the temperature of the battery 10 to a temperature suitable for estimating the amount of charging electricity in the battery temperature adjusting step (step S20). The processing unit 40 may adjust the temperature of the battery 10, perform temperature correction based on the acquired temperature as a parameter used for calculation, or select correlation data 51 corresponding to the acquired temperature. You may do it. The processing unit 40 measures the two complex impedances in the impedance measurement step (step S21), and then calculates the parameters in the parameter calculation step (step S22).

The processing unit 40 compares the previously calculated parameter with the graph L51 in the electricity amount calculation unit 46 (comparison step between the correlation data and the parameter (step S24)), and charges electricity corresponding to the parameter from the compared graph L51. The amount is acquired, and the acquired charging electricity amount is estimated as the charging electricity amount of the battery 10 (charging electricity amount estimation step (step S25)). For example, referring to FIG. 5, it is estimated that the charging electricity amount is “ _2Ah ” based on the parameter calculated earlier being “QD = 1.0”. Further, for example, it is estimated that the charging electricity amount is "4Ah" based on the parameter calculated earlier being " _QD = 1.8". As a result, the charge electricity amount of the battery 10 is calculated based on the complex impedance Z measured from the battery 10.

The processing unit 40 compares with the case where the measurement frequency of the two complex impedances is selected on the high frequency side of the “diffusion region d” to select the low frequency side such as the “vertical region dc”. It will be possible to reduce the time required to estimate the amount of charging electricity.

Next, the difference in the amount of charging electricity, that is, the determination of the variation, which occurs between the cells constituting the battery 10, will be described based on the estimation of the amount of charging electricity. For example, the battery 10 is an assembled battery composed of a plurality of battery modules and a single battery. In the present embodiment, the processing unit 40 includes a variation determination unit 48 that performs variation determination, and the variation determination unit 48 can perform the first variation determination and the second variation determination. The variation determination unit 48 may perform only one of the first variation determination and the second variation determination.

In the first variation determination, the variation determination unit 48 determines the variation in the charge electricity amount for each battery constituting the battery 10 based on the fact that the battery 10 is fully charged. More specifically, the storage unit 50 holds in advance in the calculation data 52 a reference electric energy that is an appropriate charging electric energy when the battery 10 is fully charged. That is, the reference electric energy is the charging electric energy that should be measured when each battery constituting the battery 10 has an appropriate charging electric energy. Therefore, if the estimated charge electricity amount is smaller than the reference electricity amount, at least one of the batteries constituting the battery 10 is in a state where the charge electricity amount is low, and the charge electricity amount varies in the battery 10. It is judged. The reference electric energy is a value that may be set separately for the battery temperature. Further, the reference electric energy may be a value based on the measurement result, or may be an empirical value or a theoretical value.

The processing procedure of the first variation determination will be described.
In the first variation determination, first, the processing unit 40 fully charges the battery 10. Then, the processing unit 40 estimates the charging electricity amount of the battery 10 fully charged in the above-mentioned procedure for estimating the charging electricity amount (steps S20 to S25 in FIG. 6), and uses the estimated charging electricity amount as the reference electricity amount. Compare with. The processing unit 40 determines that there is no variation in the battery 10 if the estimated charging electric energy is within a predetermined range with respect to the reference electric energy. On the other hand, if the estimated charge electricity amount is out of the predetermined range with respect to the reference electricity amount, it is determined that the battery 10 has a variation. As a result, it is determined that the amount of electricity charged for each battery constituting the battery 10 varies based on the fact that the battery 10 is fully charged.

In the second variation determination, the variation determination unit 48 determines the variation based on comparing the charge electric energy of the cells or battery modules divided into two groups so that the total capacity of the batteries 10 is the same. I do. Here, the case where the cells constituting the battery 10 are divided into a first group and a second group consisting of the same number of cells, and the variation is determined based on comparing the charging electric energy of these two groups. Will be explained.

More specifically, as shown in FIG. 7, when the second variation determination is started, the processing unit 40 estimates the charging electricity amount for the first group in the first charging electricity amount estimation step (step S30). I do. Further, the processing unit 40 performs a second charge electricity amount estimation step (step S31) for estimating the charge electricity amount for the second group. The first and second charging electricity amount estimation steps are the same as the above-mentioned procedure for estimating the charging electricity amount (steps S20 to S25 in FIG. 6).

When the charging electricity amounts of the first and second groups are estimated, the processing unit 40 determines whether or not the two estimated charging electricity amounts are corresponding values (step S32). If the difference between the two charging electricity amounts is within a predetermined range, it is determined that the two charging electricity amounts are the corresponding values, and if the difference is not within the predetermined range, the two charging electricity amounts are not the corresponding values. judge. The predetermined range may be a range defined based on the ratio to the estimated charging electricity amount, or may be a range defined as a predetermined electricity amount. Further, the condition for determining that the two charging electricity amounts correspond is that the charging electricity amount of the other is included in a predetermined range set for the charging electricity amount of one of the two charging electricity amounts. Alternatively, in addition to this condition, a condition that one of the charging electricity amounts is included in a predetermined range set for the other charging electricity amount may be combined.

When it is determined that the two estimated charging electricity amounts are the corresponding values (YES in step S32), the processing unit 40 determines that there is no variation in the battery 10 (step S33). On the other hand, when it is determined that the two estimated charging electricity amounts are not the corresponding values (NO in step S32), the processing unit 40 determines that the battery 10 has variations (step S34). The determination result may be used for display or the like by the processing unit 40, or may be output to the outside.

Then, when the determination is completed, the second variation determination is completed.
As described above, according to the battery state estimation device and the battery state estimation method of the present embodiment, the effects described below can be obtained.

(1) The charge electricity amount of the battery 10 can be estimated based on the measurement result of the complex impedance Z. In the battery 10, the complex impedance Z of the “diffusion region d” is measured in a low frequency band of, for example, 0.1 Hz or less, so that it takes a relatively long time to measure, but only two points in the low frequency band are used. By doing so, the time required for estimating the amount of charging electricity can be suppressed. That is, the frequency range in the diffusion region is often 0.1 Hz or less, and for example, even if 0.1 Hz to 0.01 Hz is used for measurement, it is in a practical time range of about 10 seconds to 100 seconds. Measurement is possible.

Further, since the change of the complex impedance Z is linear, there are few restrictions on the selection of the measurement frequencies of the two complex impedances Z, and the difference between the components of the two complex impedances can be easily obtained.

The preset information may be one model information, or may be selected from a plurality of models set for each temperature of the battery 10.
Further, of the two complex impedance Z components in the diffusion region, the imaginary number component can be used to estimate the battery state of the battery 10, but if there is a correlation between the imaginary number component and the real number component, the imaginary number is used. It is also possible to replace the component with a real number component and use the real number component for estimating the battery state of the secondary battery.

(2) By having the variation determination unit 48, it is possible to determine whether or not there is a variation in the charge electricity amount of the battery 10.
(3) By having the variation determination unit 48, it is possible to determine whether or not there is a variation in the amount of charging electricity for a plurality of single batteries and an assembled battery composed of a plurality of battery modules.

(4) The battery state is estimated based on the imaginary component Zi of the two complex impedances Z in the “diffusion region d”. Since the complex impedance Z in the “diffusion region d” tends to have a smaller change in the real number component Zr on the low frequency side, the imaginary number component Zi can be used to increase the degree of freedom in selecting the measurement angular velocity of the complex impedance Z. Can be high.

(5) Regarding the measured angular velocity, the reciprocal of the ratio of the difference in the imaginary component to the difference in the reciprocal is used as a parameter, and this parameter and preset information indicating the relationship between the battery state of the battery 10 and the parameter. It becomes possible to estimate the battery state of the secondary battery based on the above. Further, by using the difference between the reciprocals of the measured angular velocities as the difference between the measured angular velocities of the two complex impedances Z, the reciprocal of the slope can be obtained linearly or in a form close to linear.

(6) Of the two complex impedances Z in the "diffusion region d", the "straight line region da" has the imaginary number component Zi because the rate of change of the imaginary number component Zi with respect to the real number component Zr is in a range close to "1". It is also possible to use the real number component Zr instead.

(7) In a nickel-metal hydride secondary battery, since the relationship between voltage and SOC is not proportional, it is difficult to estimate the battery state such as the amount of charging electricity based on the voltage. According to the present embodiment, since the battery state is estimated based on the change in the component of the complex impedance Z in the “diffusion region d”, the battery state is preferably estimated even in the nickel-metal hydride secondary battery. You will be able to do it.

(Second embodiment)
A second embodiment that embodies the battery state estimation device and the battery state estimation method will be described with reference to FIGS. 8 to 11. The present embodiment differs from the first embodiment in that the temperature of the battery 10, which is one of the battery states, is estimated based on the parameters calculated from the complex impedance of the battery 10. In the following, the differences will be mainly described, and for convenience of explanation, the same configurations are designated by the same reference numerals and detailed description thereof will be omitted.

As shown in FIG. 8, the measuring circuit for measuring the state of the battery 10 is the same as the measuring circuit of the first embodiment. That is, the measuring circuit is a current measurement connected between the battery 10, the measuring charge / discharging device 20 and the voltage measuring device 21 connected between the terminals of the battery 10, and the measuring charging / discharging device 20 and the battery 10. It is equipped with a vessel 22. Further, a temperature measuring device 23 for measuring the temperature of the battery 10 is attached to the battery 10.

The estimation device 30 acquires a voltage signal from the voltage measuring device 21, acquires a current signal from the current measuring device 22, acquires AC current setting information and the like from the measuring charge / discharging device 20, and measures the temperature from the temperature measuring device 23. Get the signal. Further, the estimation device 30 includes a processing unit 40 and a storage unit 50.

The storage unit 50 holds the correlation data 53 between the parameter and the amount of charging electricity, which is required for calculating the temperature of the battery, and the calculation data 52. The storage unit 50 stores the correlation data 53 between the parameter and the amount of charging electricity for each temperature of the battery 10.

As shown in FIG. 9, the correlation data 53 includes information corresponding to graphs L91 to L94 showing the relationship between the parameter and the amount of charging electricity for each temperature of the battery 10.
The processing unit 40 includes an SOC adjustment unit 41, a temperature measurement unit 42, an impedance measurement unit 43, a Nyquist diagram creation unit 44, a parameter calculation unit 45, and a battery temperature calculation unit 47.

The battery temperature calculation unit 47 is based on the correlation data 53 between the parameter for each temperature of the battery 10 set in the storage unit 50 and the amount of charging electricity, and the parameter " _QD " calculated by the parameter calculation unit 45. The battery temperature estimated for the battery 10 is calculated (temperature estimation step).

As shown in FIG. 9, the correlation data 53 is data including correlation data 51 between each parameter and the amount of charging electricity when the temperature of the battery 10 is 15 ° C, 25 ° C, 35 ° C, and 45 ° C. For example, graph L91 is correlation data 51 when the battery temperature is 15 ° C., graph L92 is correlation data 51 when the battery temperature is 25 ° C., and graph L93 is correlation data 51 when the battery temperature is 35 ° C. The graph L94 is the correlation data 51 when the battery temperature is 45 ° C. For example, the parameters of the battery 10 have the slope shown in the graph L91 when the temperature is 15 ° C., the slope shown in the graph L92 when the temperature is 25 ° C., and the temperature is 35, regardless of the amount of charging electricity. It has the slope shown in the graph L93 when the temperature is 45 ° C, and has the slope shown in the graph L94 when the temperature is 45 ° C.

Therefore, as an example, the temperature of the battery 10 is estimated based on the slopes of the two parameters acquired with different charging electricity amounts and the slopes of the graphs L91 to L94 shown in FIG. 9 under the condition of no temperature change. You can also do it.

In the present embodiment, the position on the graph specified in FIG. 9 specified from one calculated parameter and the charge electricity amount of the battery 10 at that time is compared with the graphs L91 to L94 included in the correlation data 53. The estimated temperature of the battery 10 is acquired based on the above. That is, it is estimated as the temperature of the battery 10 from the parameters and the amount of charging electricity.

With reference to FIGS. 10 and 11, the setting of the correlation data 53 for estimating the battery temperature and the estimation of the battery temperature using the correlation data 53 will be described.
As shown in FIG. 10, the processing unit 40 can acquire the correlation data 53 showing the relationship between the parameter for each temperature and the amount of charged electricity, and can execute the process of storing the correlation data 53 in the storage unit 50. Further, as shown in FIG. 11, the processing unit 40 can execute a process of estimating the temperature of the battery 10 based on the complex impedance Z acquired from the battery 10.

First, a procedure for setting the correlation data 53 will be described with reference to FIG.
The processing unit 40 includes an SOC adjustment step (step S40), a battery temperature measurement step (step S41), an impedance measurement step (step S42), and a parameter calculation step (step S43). Further, the processing unit 40 includes a step of calculating the correlation data between the parameter and the amount of electricity charged for each temperature (step S44) and a step of storing the correlation data (step S45). The impedance measurement step (step S42) and the parameter calculation step (step S43) are the same as the impedance measurement step (step S12 in FIG. 2) and the parameter calculation step (step S13 in FIG. 2, respectively) of the first embodiment. Since it is a process, duplicate explanations are omitted.

As shown in FIG. 10, in the SOC adjustment step (step S40), the SOC adjustment unit 41 acquires the SOC of the battery 10 and adjusts the SOC of the battery 10 if necessary.
In the battery temperature measuring step (step S41), the temperature measuring unit 42 acquires the current temperature of the battery 10 with high accuracy. For example, the surface temperature of the battery 10 which has been allowed to stand in a state where the terminals are open for a predetermined period under a predetermined environmental temperature is acquired. With the battery 10 standing still in this way, the temperature inside the battery such as the electrode plate is also close to the surface temperature, so that the temperature inside the battery, which has a strong influence on the battery characteristics, can be obtained with high accuracy.

The processing unit 40 measures the two complex impedances in the impedance measurement step (step S42), and then calculates the parameters in the parameter calculation step (step S43). The processing unit 40 calculates the correlation data between the battery temperature, the parameter "QD", and the amount of charging electricity (step S44), and the parameter " _QD " for the calculated amount of charging electricity corresponds to the graphs _L91 to L94 for each temperature. The data is stored in the storage unit 50 as data to be stored (step S45).

According to the graphs _L91 to L94 created based on the data set in this way, the temperature of the battery 10 is estimated from the parameter "QD" based on the condition that the charge electric energy (SOC) of the battery 10 is known. You will be able to.

A procedure for estimating the temperature of the battery 10 will be described with reference to FIG.
The processing unit 40 includes an SOC acquisition step (step S50), an impedance measurement step (step S51), and a parameter calculation step (step S52). Further, the processing unit 40 includes a comparison step (step S54) between the correlation data and the parameters, and a temperature estimation step (step S55). The impedance measurement step (step S51) and the parameter calculation step (step S52) are the same as the impedance measurement step (step S12 in FIG. 2) and the parameter calculation step (step S13 in FIG. 2, respectively) of the first embodiment. Since it is a process, duplicate explanations are omitted.

In the SOC acquisition step (step S50), the processing unit 40 acquires the current SOC of the battery 10 by a known technique. The processing unit 40 may measure the SOC of the battery 10 by the SOC adjusting unit 41, or may be set or input from the outside. The charging electricity amount obtained by converting the SOC acquired here is applied in comparison with the correlation data 53 (see FIG. 9) between the parameter for each battery temperature and the charging electricity amount. The processing unit 40 may acquire the charging electricity amount instead of the SOC.

The processing unit 40 measures the two complex impedances in the impedance measurement step (step S51), and then calculates the parameters in the parameter calculation step (step S52).
The processing unit 40 specifies one graph L91 to L94 corresponding to the graphs L91 to L94 by comparing the charge electricity amount and the calculated parameter with the battery temperature calculation unit 47 (correlation data and parameter). Comparison step (step S54)). Then, the processing unit 40 acquires the corresponding temperature of the specified graphs L91 to L94 and estimates the acquired temperature as the temperature of the battery 10 (temperature estimation step (step S55)). For example, referring to FIG. 9, it is estimated that the battery temperature is "15 ° C." based on the parameter "QD = 1.0" and the charge electricity amount " _2Ah ". Further, for example, it is estimated that the battery temperature is "35 ° C." based on the parameter being " _QD = 1.6" and the charging electricity amount being "3Ah". As a result, the temperature of the battery 10 can be estimated based on the complex impedance Z measured from the battery 10 and the SOC (charged electricity amount).

As described above, according to the battery state estimation device and the battery state estimation method of the present embodiment, in addition to the effects of (1) to (7) described in the first embodiment, as described below. The effect will be obtained.

(8) The temperature of the battery 10 can be estimated based on the measurement result of the complex impedance Z. In the battery 10, the complex impedance Z of the “diffusion region d” is measured in a low frequency band of, for example, 0.1 Hz or less, so that it takes a relatively long time to measure, but only two points in the low frequency band are used. This makes it possible to reduce the time required to estimate the battery temperature.

Further, since the temperature of the battery 10 is usually measured on the surface of the battery 10, it is not possible to obtain the temperature of the electrode plate group itself, which has a strong influence on charge / discharge. In this respect, according to this configuration, as the temperature of the battery 10, the temperature of the electrode plate group itself is estimated based on the state of the portion in the electrode plate group through which the current flows. Therefore, the temperature of the battery 10 can be obtained with high accuracy.

(Third embodiment)
A third embodiment that embodies the battery state estimation device and the battery state estimation method will be described with reference to FIG. The present embodiment is different from the first or second embodiment in that the charging / discharging device 20 for measurement supplies a step current for impedance measurement to the battery 10 to measure the complex impedance of the battery 10. In the following, the differences will be mainly described, and for convenience of explanation, the same configurations are designated by the same reference numerals and detailed description thereof will be omitted.

The charging / discharging device 20 for measurement can supply the step current for impedance measurement to the battery 10. The step current constitutes a direct current for measurement. The charging / discharging device 20 for measurement generates a step current of a predetermined cycle, and outputs the generated step current between the terminals of the battery 10. Further, the charging / discharging device 20 for measurement can change the cycle of the step current if necessary. The charging / discharging device 20 for measurement has a step current cycle set, and outputs a step current corresponding to the set cycle. Here, the cycle is composed of a set of on-period and off-period, and a set of positive and negative periods, and the step current is output by repeating the cycle once or a plurality of times. Will be done. The cycle period to be set includes, for example, one of the range from 0.1 Hz to 1 MHz. It is possible to measure the impedance for a frequency of "(2 x n-1) times" (where n is a natural number) with respect to the set cycle.

As shown in FIG. 13A, the measurement charging / discharging device 20 applies a step current (see graph L131) of a predetermined cycle to the battery 10 to be measured. The number of applied cycles may be one or a plurality of times. Further, at this time, the response voltage (see graph L132) corresponding to the step current (see graph L131) of a predetermined cycle is output from the battery 10 to be measured. Then, the step current (see graph L131) and the response voltage (see graph L132) are Fourier transformed by the processing unit 40, respectively.

As shown in FIG. 13B, the frequency response of the current corresponding to the step current (see graph L131) (see graph L133) and the frequency response of the voltage to the response voltage (see graph L132) by the Fourier transform (see graph L134). ) Is obtained. That is, the angular velocity corresponding to the sine wave is determined as the measured angular velocity. Therefore, in the present embodiment, the frequency (angular velocity) characteristic corresponding to the sine wave is obtained by Fourier transforming the step current and the response voltage, and the frequency (angular velocity) obtained at this time is the measured angular velocity, and this measurement is performed. A Nyquist diagram of complex impedance is created based on the angular velocity.

As shown in FIG. 13 (c), the processing unit 40 calculates the complex impedance based on the frequency response of the current (see graph L133) and the frequency response of the voltage (see graph L134), and the calculated complex impedance is a Nyquist diagram. (Refer to graph L135). That is, by analyzing the transient response of the step response, the impedance is measured so that the angular velocity corresponding to the sine wave becomes the measured angular velocity. For example, the impedance at each frequency is obtained from Ohm's law "Z (resistance) = V (voltage) / I (current)" based on the frequency response of the current and the frequency response of the voltage.

The cycle of the step current is set so that the impedance measured from the battery 10 includes the "diffusion region d", more preferably the "straight line region da" of the "diffusion region d".

Then, the calculated impedance can be estimated by comparing the calculated impedance with the information indicating the relationship between the parameter " _QD " related to the complex impedance Z and the charging electricity amount of the battery 10.

Further, the calculated impedance can be used to estimate the temperature of the battery 10 from the parameter " _QD " based on the condition that the charge electricity amount (SOC) of the battery 10 is known.

As described above, according to the battery state estimation device and the battery state estimation method of the present embodiment, in addition to the effects of (1) to (8) described in the first embodiment, as described below. The effect will be obtained.

(9) The impedance of the battery 10 can also be calculated by inputting the step current to the battery 10.
(Other embodiments)
In addition, each of the above-mentioned embodiments can also be carried out in the following embodiments.

-The above embodiments can be combined with each other within a technically consistent range.
In the third embodiment, the load response of the battery 10 for each cycle of the step current is associated with the load response of the battery 10 for each frequency of the alternating current. Then, the load response corresponding to the alternating current may be acquired based on applying the load response to the step current of the battery 10 to this association. This makes it possible to reduce the calculation of the Fourier transform and the like.

For example, as shown in FIG. 14, by setting the relationship between the resistance information for the step current and the resistance information for the alternating current as the graph L141 or the function f (x), the load response to the step current of the battery is acquired. Then, it becomes possible to obtain a load response or the like to an alternating current corresponding to the acquired load response. The resistance information for the step current is information including the cycle of the step, the current value and the voltage value, and the resistance information for the AC current is the information including the AC frequency, the current value, the voltage value and the impedance. ..

-In the third embodiment, the case where one of the ranges from 0.1 Hz to 1 MHz is mentioned as the cycle to be set is illustrated. However, the cycle is not limited to this, and the cycle may be higher than 0.1 Hz or more than 1 MHz as long as the impedance that can be measured in the set cycle includes the “diffusion region d”. It may be lower.

-In the third embodiment, the case where the impedance is calculated by analyzing the transient response of the battery 10 to the step current having a cycle is illustrated. However, the impedance is not limited to this, and the impedance may be calculated by analyzing one or more transient responses when the step goes up and one or more transient responses when the step goes down. For example, if the cycle length of the step is equal to or longer than the convergence time of the transient response, the application of the step current may be regarded as the application of the direct current. On the contrary, if the cycle length of the step is sufficiently shorter than the convergence time of the transient response, the application of the step current may be regarded as the application of the alternating current.

-In the third embodiment, a case where a step current is applied and a voltage response is measured has been illustrated. Not limited to this, a step voltage may be applied and the current response may be measured. In any case, the impedance can be measured.

-In the first and second embodiments, a sinusoidal alternating current is applied, and in the third embodiment, a step current is applied. However, the present invention is not limited to this, and a triangular wave or a current having another waveform shape may be applied as long as the transient response of the battery can be obtained.

-In each of the above embodiments, the case where the battery 10 is connected to the measurement circuit has been illustrated, but the battery is not limited to this, and the battery can be a load, a charger, or the like via a switch (not shown) in addition to the measurement circuit. It may be connected to. For example, in the case of a vehicle-mounted battery, it is possible to estimate the battery state of the battery by measuring the complex impedance as necessary while using the battery as a power source for driving.

-In each of the above embodiments, the case where the battery 10 is a nickel hydrogen secondary battery has been exemplified, but the present invention is not limited to this, and other alkaline secondary batteries such as nickel cadmium batteries and secondary batteries such as lithium ion secondary batteries are used. May be.

In each of the above embodiments, the case where the parameter is calculated using the imaginary number component Zi among the components of the complex impedance Z has been illustrated, but the present invention is not limited to this, and the parameter Q is limited to the case where the real number component Zr among the components of the complex impedance Z is used. _D may be calculated. At this time, if the correlation data is also set based on the parameter using the real number component Zr, the charge electricity amount can be estimated. Further, the battery temperature can be estimated by preparing in advance the correlation data showing the relationship between the charge electricity amount and the parameter for each battery temperature in addition to this parameter. For example, in the "straight line region da", the rate of change of the imaginary number component Zi with respect to the real number component Zr is in a range close to "1". Therefore, even if the real number component Zr is used instead of the imaginary number component Zi, the complex impedance Z of the battery 10 is used. The amount of electricity charged and the battery temperature can be estimated from.

-In the first embodiment, when the second variation determination is performed, a case where the cells and the like constituting the battery 10 are divided into a plurality of groups is illustrated. At this time, some of the cells and battery modules constituting the battery may be grouped into a plurality of groups. This also enables sampling-like inspection.

On the contrary, some cell batteries and the like may be duplicated and included in a plurality of groups. This also makes it possible to narrow down the batteries and the like having a large difference in the amount of charging electricity.
-In the first embodiment, when the second variation determination is performed, the case where the total capacity of the two groups is the same is illustrated. However, the present invention is not limited to this, and the total capacities of the two groups may be different as long as the difference in the total capacities of the two groups can be corrected.

-In the first embodiment, when the second variation determination is performed, a case where the cells and the like constituting the battery 10 are divided into two groups is illustrated. However, the present invention is not limited to this, and the cells and the like may be divided into three or more groups and compared with each other.

-In the first embodiment, the variation determination unit 48 determines the variation in the amount of charged electricity for each battery constituting the battery 10 based on the fact that the battery 10 is fully charged in the first variation determination. Was illustrated. However, the present invention is not limited to this, and the first variation determination may be performed based on the battery having a predetermined SOC. At this time, it may be estimated by a well-known technique that the battery has a predetermined SOC.

-In the first embodiment, the case where the variation determination unit 48 is provided has been illustrated, but the present invention is not limited to this, and if the variation determination is unnecessary, the variation determination unit may not be provided.

-In the first embodiment, the case where the temperature of the battery 10 is set to a predetermined temperature has been illustrated, but the present invention is not limited to this, and as shown in FIG. 9, correlation data is provided for each battery temperature and the battery is provided. By acquiring the temperature, the amount of charging electricity may be acquired from the correlation data corresponding to the temperature of the battery. This makes it possible to estimate the amount of charging electricity with high accuracy in consideration of the temperature of the battery.

-In each of the above embodiments, the case where the parameter " _QD " is calculated from the equations (2) and (3) is illustrated. However, the present invention is not limited to this, and the expression form is not limited to the equation (2) and the equation (3) as long as it is a calculation equation showing the theory expressed in the equation (2).

-In each of the above embodiments, the case where the two complex impedances Z are in the "straight line region da" of the "diffusion region d" has been illustrated. However, not limited to this, if the difference between the measured angular velocities of the two complex impedances and the difference between the imaginary components of the two complex impedances can be obtained, one of the two complex impedances is in the "diffusion region d". It may be in an area such as "area db" or "vertical area dc". This also makes it possible to reduce the time required for acquisition because the other complex impedance is in the "straight line region da".

-In each of the above embodiments, a case where the parameter is obtained linearly or in a form close to linear by using the difference of the reciprocal of the measured angular velocity as the difference between the measured angular velocities of the two complex impedances is illustrated. However, the present invention is not limited to this, and the difference in the measured angular velocities may be used as it is as the difference between the measured angular velocities of the two complex impedances. Although the parameter is obtained in a non-linear manner, a correlation can be obtained between this parameter and the battery state.

-In each of the above embodiments, the case where the battery 10 is mounted on an electric vehicle or a hybrid vehicle has been illustrated, but the present invention is not limited to this, and the battery may be mounted on a vehicle such as a gasoline vehicle or a diesel vehicle. Further, the battery may be used as a power source for a fixed installation of a mobile body such as a railroad, a ship, an aircraft or a robot, or an electric product such as an information processing device.

10 ... Battery, 20 ... Charging / discharging device for measurement, 21 ... Voltage measuring device, 22 ... Current measuring device, 23 ... Temperature measuring device, 30 ... Estimating device, 40 ... Processing unit, 41 ... SOC control unit, 42 ... Temperature measurement Unit, 43 ... impedance measurement unit, 45 ... parameter calculation unit, 46 ... electricity amount calculation unit, 47 ... battery temperature calculation unit, 48 ... variation determination unit, 50 ... storage unit, 51 ... correlation data, 52 ... calculation data, 53 ... Correlation data.

Claims (13)

It is a battery state estimation device that estimates the amount of charge electricity of a secondary battery.
An impedance measuring unit that measures the complex impedance of the secondary battery based on the application of power for measurement, and
Of the measured complex impedances, the angular velocity corresponding to the diffusion region is the measured angular velocity, and the difference between the measured angular velocities of the two complex impedances having different measured angular velocities and the difference between the two complex impedance components. A parameter calculation unit that calculates parameters consisting of ratios, and
The information that is preset and indicates the relationship between the charge electricity amount of the secondary battery and the parameter, and the charge electricity amount of the secondary battery based on the parameter calculated by the parameter calculation unit. A battery state estimation device characterized by having an electricity amount estimation unit for estimation. The battery state estimation device according to claim 1, wherein the power for measurement is DC power for measurement or AC power for measurement. It is a battery state estimation device that estimates the amount of charge electricity of a secondary battery.
An impedance measuring unit that measures the complex impedance of the secondary battery based on the application of AC power for measurement, and
A parameter for calculating a parameter consisting of the ratio of the difference between the measured angular velocities of two complex impedances within the diffusion region and having different measured angular velocities and the difference between the two complex impedance components among the measured complex impedances. Calculation unit and
The information that is preset and indicates the relationship between the charge electricity amount of the secondary battery and the parameter, and the charge electricity amount of the secondary battery based on the parameter calculated by the parameter calculation unit. A battery state estimation device characterized by having an electricity amount estimation unit for estimation. Further provided with a temperature acquisition unit for acquiring the temperature of the secondary battery,
The preset information includes information set for each temperature of the secondary battery.
According to any one of claims 1 to 3, the electric energy estimation unit selects the information corresponding to the acquired temperature from the information set for each temperature of the secondary battery as the preset information. The described battery state estimation device. The charging electricity amount of the secondary battery estimated when the secondary battery is fully charged and the preset reference electricity amount, which is an appropriate charging electricity amount when the secondary battery is fully charged. The battery state according to any one of claims 1 to 4, further comprising a first variation determination unit for determining whether or not the charge electricity amount of the secondary battery varies by comparing with the reference electricity amount. Estimator. The secondary battery is an assembled battery and is
The charging electricity amount estimated by the electricity amount estimation unit is acquired for each of the two groups in which the assembled battery is divided so that at least a part of the batteries does not overlap, and based on the comparison of the charging electricity amount of the two groups. The battery state estimation device according to any one of claims 1 to 4, further comprising a variation determination unit for determining whether or not there is a variation in the amount of charging electricity between the batteries constituting the assembled battery. It is a battery state estimation device that estimates the temperature of the secondary battery.
An electric energy acquisition unit that acquires the charging electric energy of the secondary battery, and
An impedance measuring unit that measures the complex impedance of the secondary battery based on the application of power for measurement, and
Of the measured complex impedances, the angular velocity corresponding to the diffusion region is the measured angular velocity, and the difference between the measured angular velocities of the two complex impedances having different measured angular velocities and the difference between the two complex impedance components. A parameter calculation unit that calculates parameters consisting of ratios, and
The information set in advance and showing the relationship between the parameter with respect to the charge electricity amount of the secondary battery and the temperature of the secondary battery is the charge electricity amount acquired by the electricity amount acquisition unit and the parameter calculation. A battery state estimation device including a temperature estimation unit that estimates the temperature of the secondary battery based on the application of the parameters calculated by the unit. The battery state estimation device according to any one of claims 1 to 7, wherein each of the two complex impedance components is an imaginary component of the complex impedance. The parameter calculation unit sets the difference between the reciprocals of the measured angular velocities of the two complex impedances as "Δ (ω ^-1 )", the difference between the imaginary components of the two complex impedances as "ΔZi", and the parameter as "Q". When " _D " is set, it is calculated based on the following formula.

The battery state estimation device according to claim 8. The measured angular velocities of the two complex impedances are angular velocities within a range in which the absolute value of the rate of change of the imaginary component with respect to the real component of the two complex impedances is 0.5 or more and 2 or less. The battery state estimation device according to any one of the above items. The battery state estimation device according to any one of claims 1 to 10, wherein the secondary battery is a nickel hydrogen secondary battery. It is a battery state estimation method that estimates the amount of charge electricity of a secondary battery.
An impedance measurement step of measuring the complex impedance of the secondary battery based on the application of electric power for measurement, and
Of the measured complex impedances, the angular velocity corresponding to the diffusion region is the measured angular velocity, and the difference between the measured angular velocities of the two complex impedances having different measured angular velocities and the difference between the two complex impedance components. A parameter calculation process that calculates a parameter consisting of a ratio, and
The information that is preset and indicates the relationship between the charge electricity amount of the secondary battery and the parameter, and the charge electricity amount of the secondary battery based on the parameter calculated in the parameter calculation step. A battery state estimation method comprising an estimation process for estimating the amount of electricity. It is a battery state estimation method that estimates the temperature of the secondary battery.
The electricity amount acquisition process for acquiring the charging electricity amount of the secondary battery and
An impedance measurement step of measuring the complex impedance of the secondary battery based on the application of electric power for measurement, and
Of the measured complex impedances, the angular velocity corresponding to the diffusion region is the measured angular velocity, and the difference between the measured angular velocities of the two complex impedances having different measured angular velocities and the difference between the two complex impedance components. A parameter calculation process that calculates a parameter consisting of a ratio, and
The information set in advance and showing the relationship between the parameter with respect to the charging electricity amount of the secondary battery and the temperature of the secondary battery is the charging electricity amount acquired in the electricity amount acquisition step and the parameter calculation. A battery state estimation method comprising a temperature estimation step of estimating the temperature of the secondary battery based on the application of the parameters calculated in the step.

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