JPWO2016059869A1 - Secondary battery charge state estimation apparatus and charge state estimation method thereof - Google Patents

Abstract

Provided are a secondary battery charge state estimation device and a charge state estimation method capable of accurately estimating the state of charge of a secondary battery. Based on the measurement data of the state quantity of the battery cell 1 constituting the secondary battery, the SOH estimating unit 8 that estimates the deterioration state of the secondary battery and at least the deterioration state and the value of the internal state parameter of the secondary battery are associated with each other. An internal state parameter corresponding to the deterioration state estimated by the SOH estimating unit 8 is obtained from the battery characteristic information storage unit 10 storing the obtained battery characteristic information and the battery characteristic table of the battery characteristic information storage unit 10, and the internal state And an SOC estimation unit 11 that calculates the charging rate of the secondary battery based on the parameters.

Description

  Embodiments of the present invention relate to a secondary battery charging state estimation device and a charging state estimation method thereof in a secondary battery system for power storage connected to an electric power system and the like.

  The secondary battery is used as a battery of an electric vehicle or a hybrid electric vehicle or in a stationary secondary battery system for power storage. The state of charge (SOC) of the secondary battery is expressed as a charging rate, and the state in which the secondary battery is discharged to the end-of-discharge voltage (complete discharge) is defined as SOC 0%. The state of charging up to (charging) is defined as SOC 100%. In other words, the charging rate can be said to be the ratio of the current charging amount to the battery capacity.

  The charging rate of the secondary battery is important for estimating the chargeable / dischargeable capacity of the secondary battery, and in the case of a vehicle-mounted secondary battery, it greatly affects the calculation of the cruising range. Further, in the stationary secondary battery system, when an error occurs in the estimated value of the charging rate, problems such as unexpectedly stopping charging / discharging or being unable to use the secondary battery efficiently occur.

  Various methods have been proposed for calculating the charging rate of the secondary battery. For example, there is a current integration method. In this method, the charging / discharging current of the secondary battery is measured by a current sensor, and the charging rate of the secondary battery is calculated by integrating the current values. However, in this current integration method, current sensor measurement errors accumulate, and a large error occurs in the measured charge rate.

  Therefore, there is a method of correcting the charging rate from the open circuit voltage (OCV: Open Circuit Voltage) when there is no current with respect to the charging rate obtained by the current integration method. In this method, the open circuit voltage at each charging rate (for example, every 10% of SOC) of the battery is measured in advance, and the battery characteristics are acquired. During charging, the charging rate is measured by the current integration method, the open-circuit voltage of the battery cell is measured when there is no charging / discharging, and the charging rate of the battery is calculated from the battery characteristics (OCV-SOC characteristics) acquired in advance. It is to correct.

  In addition, simulation is performed with an equivalent circuit model of a secondary battery, the closed circuit voltage (CCV) of the secondary battery is estimated from the charge / discharge current and the battery temperature, and charging is performed using the Kalman filter from the measured battery voltage. There is a way to correct the rate.

Gregory L. Plett, “Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs”, Journal of Power Sources 134 (2004) 277-292.

Japanese Patent No. 5292375

  As described above, when using a secondary battery, it is important to accurately estimate the charging rate of the secondary battery. Various methods have been proposed as a method for calculating the charging rate of the secondary battery. In particular, the method for estimating the charging rate using the battery characteristics takes into account the state of health (SOH) of the battery. There is a need. However, the conventional method of estimating the charging rate using the battery characteristics does not take into account the deterioration of the battery, and the charging rate is calculated using only the initial battery characteristics, so that the estimation error increases. Has occurred.

  The charging state estimation device and the charging state estimation method for a secondary battery according to the present embodiment are made to solve the above-described problems, and can accurately estimate the charging state of the secondary battery. An object of the present invention is to provide a state of charge estimation device and a state of charge estimation method for a secondary battery.

  In order to achieve the above object, the secondary battery charge state estimation device of the present embodiment estimates the deterioration state of the secondary battery based on the measurement data of the state quantities of the battery cells constituting the secondary battery. Estimated by the SOH estimation unit from the SOH estimation unit, the storage unit storing the battery characteristic information in which at least the deterioration state and the value of the internal state parameter of the secondary battery are associated, and the battery characteristic information of the storage unit An SOC estimation unit that obtains an internal state parameter corresponding to the deteriorated state and calculates a charging rate of the secondary battery based on the internal state parameter is provided.

  Further, the method for estimating the state of charge of the secondary battery according to the present embodiment quantitatively calculates an indicator of deterioration of the secondary battery based on the measurement data of the state quantity of the battery cell constituting the secondary battery, and the secondary battery An internal state parameter corresponding to the deterioration state estimated in the SOH estimation step based on an SOH estimation step for estimating the deterioration state of the battery and battery characteristic information in which at least the deterioration state and the value of the internal state parameter of the secondary battery are associated And a SOC estimation step of calculating a charging rate of the secondary battery based on the internal state parameter.

It is a figure which shows the equivalent circuit model of a secondary battery. It is a block diagram which shows the whole structure of the charge condition estimation apparatus of the secondary battery which concerns on 1st Embodiment. It is a figure for demonstrating internal resistance calculation using the constant current pulse method. It is a figure which shows the correlation with an internal resistance ratio and a battery capacity maintenance factor. It is a figure which shows the OCV-SOC characteristic table memorize | stored in the battery characteristic information storage part. It is a figure which shows the reaction resistance characteristic table memorize | stored in the battery characteristic information storage part. It is a detailed block diagram of a SOC estimation part. It is an operation | movement flowchart of the charge condition estimation apparatus of the secondary battery which concerns on 1st Embodiment.

[1. First Embodiment]
Below, the charge condition estimation apparatus of the secondary battery of this embodiment is demonstrated, referring FIGS. First, this embodiment will be schematically described, and then the configuration will be described in detail.

[1-1. Outline]
The secondary battery charge state estimation device of this embodiment always estimates the charge rate of the secondary battery with high accuracy. For this purpose, first, the deterioration state (SOH) of the secondary battery is estimated, and then, from a battery characteristic table prepared in advance and showing a relationship between at least the deterioration state and the value of the internal state parameter of the secondary battery. Then, an internal state parameter of the secondary battery corresponding to the estimated deterioration state is obtained, and the charging rate (SOC) is estimated by using the parameter and the equivalent circuit model and the Kalman filter method.

  The deterioration of the secondary battery refers to a decrease in battery performance that accompanies the passage of time or charge / discharge, or both. The deterioration state of the secondary battery is expressed based on, for example, the current battery performance with respect to the initial battery performance. Examples of the battery performance include battery capacity, internal resistance, charging time for constant current input, and the like.

  In this embodiment, the deterioration state of the secondary battery is estimated by quantitatively calculating an index indicating the deterioration of the secondary battery. The index indicating the deterioration of the secondary battery may be a battery capacity, internal resistance, charging time for constant current injection, or at least one of these. In the present embodiment, attention is paid to the internal resistance as an index indicating the deterioration of the secondary battery.

  For the estimation of the charging rate, an equivalent circuit model of a secondary battery is used. FIG. 1 is a model showing a secondary battery in an equivalent circuit, in which an electromotive force (open voltage (OCV)), a reaction resistance Ra, and a diffusion resistance Rb and a capacitor component C connected in parallel to each other are connected in series. Represented. The reaction resistance Ra is a resistance component that increases instantaneously immediately after application of a current pulse, and is an ion conduction resistance in the separator portion inside the battery and a charge transfer resistance of the positive electrode / negative electrode. The diffusion resistance Rb is a resistance component that gradually increases during current application, and is a resistance component due to the diffusion delay of ions inside the positive and negative electrode active material particles.

  The electromotive force (open circuit voltage (OCV)), reaction resistance Ra, and diffusion resistance Rb shown in the equivalent circuit model are parameters indicating the internal state of the secondary battery, and change depending on the deterioration state of the battery. Therefore, if the charging rate is estimated with the equivalent circuit model using the parameters in the initial state without considering the deterioration state of the battery, the estimation error increases. Therefore, in the present embodiment, the current deterioration state of the battery is estimated, and an internal state parameter corresponding to the estimated deterioration state is obtained. Then, using the internal state parameter according to the current deterioration state, the voltage between the terminals of the battery cells constituting the secondary battery (hereinafter referred to as battery voltage) is estimated, and the difference between the estimated battery voltage and the measured battery voltage Is multiplied by the Kalman gain to estimate the charging rate by the Kalman filter method for correcting the charging rate.

[1-2. Detailed configuration]
The overall configuration of the secondary battery charge state estimation device of the present embodiment will be described. FIG. 2 is a block diagram showing the overall configuration. As shown in FIG. 2, the state-of-charge estimation device according to the present embodiment includes measuring units 3 to 5 for measuring the state quantities of the battery cells 1 constituting the secondary battery.

  Specifically, the voltage measuring unit 3 that measures the voltage between the terminals of each battery cell 1 is connected to the assembled battery 2 that is a target of charge state estimation and is composed of a plurality of battery cells 1 connected in series or in parallel. Has been. The voltage measurement unit 3 includes a voltage measurement sensor, and the voltage measurement sensor measures a terminal voltage (battery voltage) between the positive electrode terminal and the negative electrode terminal of the battery cell 1.

  In addition, a current measuring unit 4 that measures the charge / discharge current to the battery cell 1 is inserted in the current path of the assembled battery 2. The current measuring unit 4 includes a current measurement sensor that measures a charging current to the battery cell 1 or a discharging current of the battery cell 1. Further, a temperature measuring unit 5 that measures the temperature of the battery cell 1 is provided in the vicinity of the assembled battery 2. The temperature measurement unit 5 includes a temperature measurement sensor. The temperature measurement sensor may measure the temperature of the assembled battery 2, and the temperature of the battery cell 1 includes not only the temperature of the battery cell 1 but also the temperature of the assembled battery 2. In addition, the temperature of the battery cell 1 or the assembled battery 2 may also be called battery temperature.

  A monitoring control unit 6 that monitors and controls the assembled battery 2 is connected to these measuring units 3 to 5. The monitoring control unit 6 includes, for example, a computer having a CPU, a memory, and the like. The program is stored in an HDD, an SSD, or the like, appropriately expanded in a RAM, and processed by the CPU, thereby estimating the SOH and SOC. Estimate.

  Specifically, the monitoring control unit 6 includes a battery state acquisition unit 7 that controls acquisition of measurement data from the measurement units 3 to 5, and an SOH estimation unit 8 that estimates the deterioration state of the battery based on each measurement data. A battery state storage unit 9 for storing the battery state, a battery characteristic information storage unit 10 having a characteristic table for each internal state parameter, and an SOC estimation unit 11 for estimating a charging rate (SOC) according to the estimated SOH. . The monitoring control unit 6 is connected to a communication interface unit 12 for performing communication with the outside.

  The battery state acquisition unit 7 includes an interface and a driver, for example, and is connected to the measurement units 3 to 5 via the interface, and acquires measurement data of the measurement units 3 to 5 at a predetermined time interval or timing according to the driver. To do. Further, the battery state acquisition unit 7 outputs the acquired measurement data to the SOH estimation unit 8 and the battery state storage unit 9.

The SOH estimation unit 8 includes a CPU and a program, and quantitatively calculates a secondary battery deterioration index based on measurement data obtained at predetermined time intervals or timings. Estimate the degradation state. In the present embodiment, first, the internal resistance value R of the assembled battery 2 is calculated using the current I and the battery voltage V of the battery state acquisition unit 7 obtained at a predetermined time interval or timing as inputs. That is, since the internal resistance value of the secondary battery increases with the aging of the battery and the charge / discharge cycle, the internal resistance value obtained by dividing the calculated current internal resistance value R by the internal resistance value R _BOL in the initial state. The ratio (R / R _BOL ) is taken as an indicator of battery deterioration, and the battery deterioration state (SOH) is estimated.

  Although there are several methods for obtaining the internal resistance value, two methods will be described here. One is an AC impedance method, and the other is a constant current pulse method. The AC impedance method is a method of extracting an AC component of a current output by connecting a battery to a potentiostat and applying a sine wave voltage. The resistance component for each battery material can be analyzed by changing the frequency of the sine wave. However, it is desirable to use a dedicated measuring device.

  The constant current pulse method does not require a special device. As shown in FIG. 3, this method applies a pulsed constant current to a battery and measures the battery voltage at that time to calculate the internal resistance value from Ohm's law. For example, when the storage battery is used for suppressing fluctuations in photovoltaic power generation, the storage battery is in a standby state at night. In other words, there is no current during standby. A charge / discharge command of a constant current pulse is given to the standby storage battery system, and an internal resistance value is obtained from the applied constant current and the measured battery voltage. Alternatively, a constant current pulse may be applied to the battery, and the internal resistance value may be obtained from a rising voltage change at the time of applying the constant current pulse or a voltage change that gradually increases during the application.

  The constant current pulse method assumes that the internal resistance value of the battery does not depend on the applied current. Although the application time of the constant current pulse depends on the evaluation method, for example, in a battery for an electric vehicle, since the battery output is one of the important characteristics, the voltage 10 seconds after the application of the current pulse is used.

  The internal resistance value of the battery varies depending on the battery temperature and the charging rate (SOC). Therefore, the battery state (battery temperature and SOC) when the constant current pulse is applied is calculated according to the same conditions. However, since the battery temperature is affected by the ambient environment temperature, calculation under the same temperature condition may be difficult. Therefore, the internal resistance value at the reference temperature may be converted using temperature correction.

The temperature correction of the internal resistance value is corrected by the temperature correction coefficient Kt. That is, the ratio of the internal resistance value at each battery temperature to the internal resistance value at a reference temperature (for example, a battery temperature of 25 ° C.) is obtained in advance. This ratio is the temperature correction coefficient Kt and depends on the battery temperature. Then, with respect to the internal resistance calculated by the battery voltage when the battery temperature T _A is measured, by multiplying the temperature correction coefficient Kt (T _A), is converted to the internal resistance value at a reference temperature. In order to make the charging rate (SOC) the same condition when calculating the internal resistance value, the estimated value fed back from the SOC estimation unit 11 is converted into the internal resistance value in the reference SOC.

  A plurality of internal resistance values subjected to temperature correction as described above may be averaged. In this case, an averaging processing unit (not shown) that performs processing for this purpose may be separately provided in the monitoring control unit 6 or may be separately provided in the SOH estimating unit 8. When provided in the SOH estimation unit 8, for example, the program of the SOH estimation unit 8 can be configured by including a program for averaging processing and processing by the CPU. Here, it is assumed that the averaging processing unit is provided in the SOH estimation unit 8 as an example. As the averaging process, an average of a plurality of internal resistance values obtained in a predetermined period such as 1 to 3 weeks may be obtained, a moving average or the like may be obtained, and other known averaging methods are used. May be.

Next, the SOH estimation unit 8 calculates a ratio (R / R _BOL ) of the internal resistance value R at each measurement time point with respect to the initial (BOL: Begin OF Life) internal resistance value R _BOL as a reference. From the correlation between the ratio and the battery capacity retention rate, the battery deterioration state (SOH) is estimated.

That is, as a method of estimating the SOH of the secondary battery, the battery capacity ratio (Cap / Cap _BOL ) of the battery capacity Cap (Ah) at each measurement time with respect to the initial battery capacity Cap _BOL (Ah) is used as an indicator of battery deterioration. Although there is a method to obtain by the formula (1), the secondary battery deteriorates due to the formation of a film on the surface of the positive electrode and the negative electrode, the internal resistance value increases, and the battery capacity decreases as the internal resistance value increases. I will do it.

Therefore, in the present embodiment, the deterioration state (SOH) is estimated from the calculated internal resistance ratio (R / R _BOL ) based on the correlation between the internal resistance ratio and the battery capacity retention rate as shown in FIG. The initial internal resistance value R _BOL and the internal resistance value R during measurement are unified under the same conditions, for example, a reference temperature of 25 ° C. and SOC of 50%. The battery capacity maintenance ratio is the ratio (%) of the current battery capacity Cap (Ah) to the initial battery capacity Cap _BOL (Ah), and is synonymous with the above formula (1).

  For example, as shown in FIG. 4, a plurality of data points of the internal resistance ratio and the battery capacity maintenance ratio are prepared in advance, etc., and the battery capacity maintenance ratio ( That is, SOH) is estimated.

Alternatively, the deterioration state (SOH) is estimated from the calculated internal resistance ratio from the relational expression between the internal resistance ratio and the ionization capacity maintenance ratio obtained by statistical processing or the like for the data points of the internal resistance ratio and the battery capacity maintenance ratio. For example, SOH can be obtained from the following equation (2). α and β are coefficients obtained by, for example, the least square method.

  The correlation between the internal resistance ratio and the battery capacity maintenance rate may be stored in advance by the SOH estimation unit 8 or stored in another component such as the battery state storage unit 9 so that it can be acquired. May be. Further, the relational expression between the internal resistance ratio and the battery capacity maintenance ratio may be updated at a predetermined interval by adding data points.

  In addition, the SOH estimation unit 8 calculates the current battery capacity Cap from the estimated current SOH value and the equation (1) in order to estimate the charging rate (SOC) as will be described later. If the calculation of the internal resistance includes an error, the battery capacity also includes an error. Therefore, the current battery capacity may be obtained by observing the transition of SOH over a long period. That is, you may make it obtain | require the moving average in the unit of one to several weeks or a month.

  The SOH estimation unit 8 is connected to the battery state storage unit 9 and the SOC estimation unit 11 and outputs the SOH obtained as described above to the battery state storage unit 9 and the SOC estimation unit 11.

The battery state storage unit 9 includes a recording medium such as an HDD or an SSD, for example. The battery state storage unit 9 includes measurement data input from the battery state acquisition unit 7, and SOH and SOC estimated by the SOH estimation unit 8 and the SOC estimation unit 11. Stores values sequentially. The battery state storage unit 9 stores in advance the initial battery capacity Cap _BOL used in the SOH estimation unit 8 and the initial internal resistance value R _BOL , and the initial charge rate used in the SOH estimation unit 11. The battery state storage unit 9 outputs data indicating the stored battery state to the SOH estimation unit 8 and the SOC estimation unit 11.

  The battery characteristic information storage unit 10 includes a recording medium such as an HDD or an SSD. The battery characteristic information storage unit 10 stores battery characteristic information in which at least the deterioration state and the value of the internal state parameter of the secondary battery are associated with each other. The battery characteristic information is, for example, a battery characteristic table having values of internal state parameters associated with the deterioration state, battery temperature, and SOC or values of internal state parameters for three variables of deterioration state, battery temperature, and SOC. Is stored for each type of internal state parameter of the secondary battery. In the present embodiment, an electrical characteristic table is stored, which will be specifically described by way of example.

  For example, as shown in FIGS. 5 and 6, the battery characteristic table has values of internal state parameters corresponding to the battery temperature and the SOC. Examples of the battery characteristic table include a characteristic table of electromotive force (open voltage OCV), reaction resistance Ra, and diffusion resistance Rb.

  Each type of battery characteristic table exists for each different deterioration state. For example, in the OCV-SOC characteristic table and the reaction resistance Ra characteristic table shown in FIGS. 5 and 6, an initial (BOL) SOH = 100% table and an end (EOL) SOH = 70% table are stored. . However, the present invention is not limited to this, and a plurality of middle-term (for example, 70% <SOH <100%) tables in which the SOH fills the space between the initial table and the final table may be provided.

  The SOC estimation unit 11 includes a CPU and a program, calculates a current internal state parameter based on the current deterioration state, and estimates a battery voltage and a charging rate (SOC) by an equivalent circuit model. As a configuration for that purpose, the SOC estimation unit 11 includes an internal state parameter specifying unit 11a, a battery voltage simulator 11b, and a Kalman filter 11c, as shown in FIG.

  The internal state parameter specifying unit 11a obtains a current internal state parameter corresponding to the current deterioration state estimated by the SOH estimating unit 8 used in the battery voltage simulator 11b from the battery characteristic information storage unit 10.

  As the method, for example, based on the input measurement data and the current deterioration state estimated by the SOH estimation unit 8, the internal state parameter is acquired from the battery characteristic table of the corresponding deterioration state. Further, the internal state parameter of the corresponding deterioration state may be calculated by interpolation (interpolation) or extrapolation (extrapolation) from two or more characteristic tables having different deterioration states of the internal state parameters. That is, an internal state parameter value corresponding to a current deterioration state that is expected within or outside the range may be obtained from two or more characteristic tables having different known deterioration states. For example, the value of the reaction resistance Ra at the time of EOL increases several times as compared with that at the time of BOL of the secondary battery. Therefore, for example, when a reaction resistance Ra characteristic table at BOL and a reaction resistance Ra characteristic table at EOL are stored, an internal state parameter corresponding to the current deterioration state is calculated by linear interpolation. As described above, when interpolation or extrapolation is performed based on the correlation between the internal state parameter and the deterioration state, which is previously determined by measurement or the like, or the relational expression derived from the correlation, the current internal state parameter is accurately estimated. Can be done.

  When the internal state parameter specifying unit 11a obtains the current internal state parameter, it outputs the parameter to the battery voltage simulator 11b. Thus, the internal state parameter specifying unit 11a can update the internal state parameter from the one corresponding to the past deterioration state to the one corresponding to the current deterioration state.

The battery voltage simulator 11b estimates the battery voltage by using the obtained internal state parameters and the current value, battery temperature, and battery voltage measurement data as inputs. Here, the internal state of the battery at time t is x _t , the system noise is w _t , and the input data u _{t + 1} at the next observation time t + 1, and x _{t + 1} from the internal state x _t of the observation time t to the observation time t + 1 is _expressed as x _{t + 1} . Assuming that the function to be obtained is f, the internal state x _{t + 1} of the battery at the observation time t + 1 is expressed by the following equation (3). That is, based on the input data u _{t + 1 at} the observation time t + 1, the function f for obtaining the internal state of the battery at the next observation time t + 1, and the system noise w _t from the internal state x _t of the battery at the previous observation time t. Thus, the internal state of the battery at the observation time t + 1 is obtained.

When the equivalent circuit model shown in FIG. 1 is discretized, it can be expressed by a state equation such as the following equation (4).
SOC _t : Battery charge rate at time t Δt: Sampling cycle time I _t : Battery charge / discharge current at time t Cap: Battery capacity (Ah)
w1 _t , w2 _t : System noise at time t V _{t + 1} : Battery voltage (closed circuit voltage) at time t + 1
OCV: open circuit voltage Ra: reaction resistance Rb: diffusion resistance C: capacitor component ω: frequency

OCV, Ra, and Rb are functions that change depending on the charging rate, the deterioration state, and the battery temperature (SOC _t , SOH _t , T _t ) at time _t . Since the capacitor component C does not depend on the deterioration state in this embodiment, a constant value is used. However, when the capacitor component C changes with deterioration, the battery characteristic information storage unit 10 stores data having a value corresponding to the deterioration state, The SOC may be calculated by obtaining a value corresponding to the state.

Since the battery capacity Cap changes according to the deterioration state, the current battery capacity estimated by the SOH estimation unit 8 or the average battery capacity value of the sample for a predetermined period is used. Thereby, the estimation accuracy of the SOC can be improved. The system noises w1 _t and w2 _t are measurement noises of the measuring devices 3 to 5, for example.

The battery voltage simulator 11b receives each measurement data and the current internal state parameter, estimates the battery voltage according to the following expression (4), and outputs it to the Kalman filter 11c. The Kalman filter 11c updates the estimated value at the time t using the latest measurement data at the time t + 1 by the state estimation method using the Kalman filter. That is, assuming that the Kalman gain is K and the prediction error w _t , the estimated value at time t + 1 is expressed by the following equation (5).

Specifically, assuming that the battery voltage measured at time t + 1 is Vmes _{(t + 1} ) and the battery voltage calculated (estimated) by Equation (4) is Vest _{(t + 1)} , the difference w is fed back, and at time t + 1 The estimated SOC value is obtained by the following equation (6).

  The Kalman gain K may be stored in the SOC estimation unit 11 or may be stored in advance in the battery state storage unit 9. The Kalman gain K may be a fixed value or may be calculated one by one. The Kalman filter 11c acquires the initial charging rate (SOC) from the battery state storage unit 9.

  The SOC estimation unit 11 outputs the estimated SOC value obtained as described above to the battery state storage unit 9 and the communication interface unit 12. The communication interface unit 12 is a medium for inputting the estimated SOC value to a host device (such as an EMS energy management system or a control system that controls the entire storage battery).

(Function)
Operation | movement of the charge condition estimation apparatus of the secondary battery of this embodiment is demonstrated. FIG. 8 is an operation flowchart of the secondary battery charged state estimation device of the present embodiment.

  First, with respect to the battery cell 1 or the assembled battery 2, the measurement units 3 to 5 measure the charge / discharge current, the battery voltage, and the battery temperature, and the measurement unit 3 to the battery state acquisition unit 7 measure each measurement data at a predetermined timing. Is acquired (step S01). Next, the battery state acquisition unit 7 outputs the acquired measurement data to the SOH estimation unit 8 and the battery state storage unit 9 (step S02). The SOH estimation unit 8 calculates an internal resistance value based on each measurement data (step S03) and performs temperature correction (step S04).

  Here, when a plurality of (for example, five) internal resistance values are not obtained within the predetermined period (NO in step S05), the process returns to step S01. On the other hand, when a plurality of (for example, five) internal resistance values are obtained within a predetermined period (YES in step S05), the average is processed by the averaging processing unit in the SOH estimating unit 8 (step S06), and the SOH estimating unit 8 Performs estimation of the SOH value, and outputs the estimated value to the SOC estimation unit 11 (step S07).

  The internal state parameter specifying unit 11a of the SOC estimation unit 11 receives each measurement data from the battery state storage unit 9 and the SOH input from the SOH estimation unit 8, and stores each measurement data, current SOH, and battery characteristic information. Based on the battery characteristic table of the unit 10, the current internal state parameters (reaction resistance Ra, diffusion resistance Rb, open circuit voltage OCV) are determined (step S08). The determined current internal state parameter is output to the battery voltage simulator 11b.

  The battery voltage simulator 11b estimates the battery voltage Vest based on the current internal state parameter and the equivalent circuit model (step S09). Further, this estimated value Vest is output to the Kalman filter 11c. The Kalman filter 11c multiplies the estimation error between the input estimated value Vest and the measured value Vmes by the Kalman gain K, and estimates the SOC based on the equation (6) (step S10).

(effect)
(1) The charging state estimation device for a secondary battery according to the present embodiment quantitatively calculates an index of deterioration of the secondary battery based on the measurement data of the state quantity of the battery cell 1 constituting the secondary battery. A battery characteristic information storage unit 10 in which a battery characteristic table in which at least the deterioration state and the value of the internal state parameter of the secondary battery are associated is stored; An SOC estimation unit 11 that obtains an internal state parameter corresponding to the deterioration state estimated by the SOH estimation unit 8 from the battery characteristic table of the characteristic information storage unit 10 and calculates a charging rate of the secondary battery based on the internal state parameter; , Was prepared. Thereby, since a charging rate can be estimated with the internal state parameter based on the present battery deterioration state, the charging state of the secondary battery can be estimated with high accuracy.

(2) The SOC estimation unit 8 calculates an internal state parameter corresponding to the deterioration state estimated by the SOH estimation unit 8 by interpolation or extrapolation based on the internal state parameter for different deterioration states in the battery characteristic information storage unit 10. I did it. Thereby, since the internal state parameter according to the present deterioration state can be calculated | required, a charging rate can be estimated more accurately than the case where there is only the battery characteristic table of an initial state.

(3) a voltage measuring unit 3 that measures a voltage between terminals of each battery cell 1 constituting the secondary battery, and a current measuring unit 4 that is inserted in the current path and measures a charge / discharge current to the battery cell 1. The SOH estimating unit 8 calculates the internal resistance of the secondary battery based on the measured values from the voltage measuring unit 3 and the current measuring unit 4, and estimates the deterioration state of the secondary battery based on the internal resistance. I made it. Thereby, compared with the case where the battery capacity is obtained by integrating the current value and the deterioration state is estimated, the measurement noise of the current measuring unit 4 is not accumulated, so that the deterioration state can be estimated with high accuracy. .

(4) When the secondary battery is in a no-current state, the SOH estimation unit 8 calculates the internal resistance by the constant current pulse method. Thereby, the deterioration state of the secondary battery can be estimated by calculating the internal resistance by a simple method.

(5) The temperature measurement unit 5 that measures the temperature of the battery cell 1 is provided, and the SOH estimation unit 8 converts the internal resistance at the temperature measured by the temperature measurement unit 5 into the internal resistance of the reference temperature. Thereby, an accurate degradation state can be estimated.

(6) Based on the calculated internal resistance, the SOH estimation unit 8 estimates the deterioration state of the secondary battery from the correlation between the ratio of the internal resistance to the initial internal resistance and the maintenance rate of the battery capacity to the initial battery capacity. I tried to do it. As a result, since both measurement and statistical correlation are used, an accurate deterioration state can be estimated. Even when the battery capacity cannot be obtained directly, the deterioration state can be estimated from the internal resistance.

[Modification of First Embodiment]
(Constitution)
The modification of the first embodiment relates to the calculation of the internal resistance value of the SOH estimation unit 8. Since the basic configuration is the same as that of the first embodiment, description of the configuration and operation of the same portion will be omitted as appropriate. This modification is effective when it is difficult to calculate the internal resistance by the constant current pulse method shown in the first embodiment, for example, when the storage battery is used for suppressing fluctuations in wind power generation.

The SOH estimation unit 8 of this modification example is the same as the first embodiment in that the current I and the battery voltage V measured within a certain period are input and the internal resistance value R of the secondary battery is calculated. However, in this modification, the charge / discharge current waveform and the battery voltage waveform measured by the measuring units 3 and 4 are converted into signal strengths for each frequency by wavelet transformation, and at a frequency where the correlation of each wavelet coefficient is high, The internal resistance R shown in the following formula (7) is estimated.

Here, (W _Ψ ⁱ ) (a, b) is obtained by wavelet transforming a current measurement waveform, and represents a wavelet coefficient of each analysis level a and shift b. (W _Ψ ^v ) (a, b) is obtained by wavelet transforming the voltage measurement waveform of the battery cell, and represents the wavelet coefficient of each analysis level a and shift b. The internal resistance value calculated here corresponds to the internal resistance value calculated by the constant current pulse method, but the internal resistance value calculated at a low analysis level represents the reaction resistance. Further, depending on the analysis level a, the correlation between current and voltage may be low due to the influence of measurement noise or the like, and the internal resistance value is calculated at the analysis level a having a high correlation. In this case, high correlation means that the determination coefficient is equal to or greater than a predetermined value, and the value is designed in advance.

  The SOH estimator 8 calculates the internal resistance value by using the wavelet transform as described above, and calculates the ratio from the estimation result of the internal resistance at each measurement time with the initial (BOL) internal resistance value as a reference. Further, the SOH value is estimated by the above equation (2).

(Action / Effect)
In this modification, the SOH estimation unit 8 calculates the internal resistance from the voltage measurement waveform and the current measurement waveform measured by the voltage measurement unit 3 and the current measurement unit 4 using wavelet transform. Thereby, even when the storage battery system is operating, the internal resistance value can be estimated, so that it is not necessary to stop the system.

[Other Embodiments]
In the present specification, a plurality of embodiments according to the present invention have been described. However, these embodiments are presented as examples and are not intended to limit the scope of the invention. The above embodiments can be implemented in other various forms, and various omissions, replacements, and changes can be made without departing from the scope of the invention. These embodiments and modifications thereof are included in the invention described in the claims and equivalents thereof, as long as they are included in the scope and gist of the invention.

  For example, in the first embodiment, the deterioration state of the secondary battery is estimated based on the internal resistance. However, the present invention is not limited to this, and a known estimation method can be used. In this case, the characteristic table of the battery characteristic information storage unit 10 is also in accordance with the definition of the deterioration state of the estimation method. As a known estimation method of the deterioration state, for example, the battery capacity can be obtained only from the measured current value or voltage value such as current integration or power integration. That is, as an indicator of deterioration, the battery capacity may be directly obtained without integrating the internal resistance by integrating the measured current value or voltage value, and the deterioration state may be estimated from the above equation (1). In addition, if a relationship (for example, a graph) between the measurement data indicating the state quantity of the secondary battery and the deterioration state of the secondary battery is known by a characteristic test or the like performed in advance, The deterioration state of the secondary battery may be estimated based on the measurement data indicating the state quantity and the relationship.

DESCRIPTION OF SYMBOLS 1 ... Battery cell 2 ... Assembly battery 3 ... Voltage measurement part 4 ... Current measurement part 5 ... Temperature measurement part 6 ... Monitoring control unit 7 ... Battery state acquisition part 8 ... SOH estimation part 9 ... Battery state storage part 10 ... Battery characteristic information Storage unit 11 ... SOC estimation unit 11a ... internal state parameter specifying unit 11b ... battery voltage simulator 11c ... Kalman filter 12 ... communication interface unit

Claims (14)

Based on the measurement data of the state quantities of the battery cells constituting the secondary battery, an SOH estimation unit that estimates the deterioration state of the secondary battery,
A storage unit storing battery characteristic information in which at least a deterioration state and a value of an internal state parameter of the secondary battery are associated;
An SOC estimation unit that calculates an internal state parameter corresponding to the deterioration state estimated by the SOH estimation unit from the battery characteristic information of the storage unit, and calculates a charging rate of the secondary battery based on the internal state parameter;
An apparatus for estimating a charged state of a secondary battery, comprising: The SOC estimation unit calculates an internal state parameter corresponding to the deterioration state estimated by the SOH estimation unit by interpolation or extrapolation based on internal state parameters for different deterioration states of the storage unit;
The state-of-charge estimation device for a secondary battery according to claim 1. A voltage measuring unit for measuring a voltage between terminals of each battery cell constituting the secondary battery;
A current measurement unit that is inserted into a current path and measures a charge / discharge current to the battery cell;
With
The SOH estimating unit calculates an internal resistance of the secondary battery based on each measured value from the voltage measuring unit and the current measuring unit, and estimates a deterioration state of the secondary battery based on the internal resistance;
The charge state estimation apparatus of the secondary battery of Claim 1 or 2 characterized by these. The SOH estimating unit calculates the internal resistance by a constant current pulse method when the secondary battery is in a no-current state;
The charge state estimation apparatus of the secondary battery of Claim 3 characterized by these. The SOH estimation unit calculates the internal resistance by wavelet transform from a voltage measurement waveform and a current measurement waveform measured by the voltage measurement unit and the current measurement unit;
The charge state estimation apparatus of the secondary battery of Claim 3 characterized by these. A temperature measuring unit for measuring the temperature of the battery cell;
The SOH estimation unit converts the internal resistance at the temperature measured by the temperature measurement unit into an internal resistance of a reference temperature;
The state-of-charge estimation device for a secondary battery according to claim 3, wherein: The SOH estimating unit estimates a deterioration state of the secondary battery based on the calculated internal resistance based on a correlation between a ratio of the internal resistance to the initial internal resistance and a maintenance ratio of the battery capacity to the initial battery capacity;
The charge state estimation apparatus of the secondary battery according to any one of claims 3 to 6. An SOH estimation step for estimating the deterioration state of the secondary battery based on the measurement data of the state quantities of the battery cells constituting the secondary battery;
An internal state parameter corresponding to the deterioration state estimated in the SOH estimation step is obtained from battery characteristic information in which at least the deterioration state is associated with the value of the internal state parameter of the secondary battery, and the secondary state is determined based on the internal state parameter. An SOC estimation step for calculating a charging rate of the battery;
A method for estimating a charged state of a secondary battery, comprising: The SOC estimation step calculates an internal state parameter corresponding to the deterioration state estimated in the SOH estimation step by interpolation or extrapolation based on internal state parameters for different deterioration states;
The method for estimating the state of charge of a secondary battery according to claim 8. A voltage measuring step for measuring a voltage between terminals of each battery cell constituting the secondary battery;
A current measuring step that is inserted into a current path and measures a charge / discharge current to the battery cell;
With
The SOH estimating step calculates an internal resistance of the secondary battery based on each measured value from the voltage measuring step and the current measuring step, and estimates a deterioration state of the secondary battery based on the internal resistance;
10. The method for estimating the state of charge of a secondary battery according to claim 8 or 9. The SOH estimating step calculates the internal resistance by a constant current pulse method when the secondary battery is in a no-current state;
The method for estimating a charged state of a secondary battery according to claim 10. The SOH estimating step calculates the internal resistance by wavelet transform from the voltage measurement waveform and the current measurement waveform measured in the voltage measurement step and the current measurement step;
The method for estimating a charged state of a secondary battery according to claim 10. A temperature measuring step for measuring the temperature of the battery cell;
The SOH estimation step converts the internal resistance at the temperature measured in the temperature measurement step into an internal resistance of a reference temperature.
The charging state estimation method of the secondary battery in any one of Claims 10-12 characterized by these. The SOH estimating step estimates a deterioration state of the secondary battery based on the calculated internal resistance based on a correlation between a ratio of the internal resistance to the initial internal resistance and a maintenance ratio of the battery capacity to the initial battery capacity;
The charging state estimation method of the secondary battery in any one of Claims 10-13 characterized by these.