WO2015075814A1 - Secondary battery remaining life diagnosis method, remaining life diagnosis device, and battery system provided with same - Google Patents

Secondary battery remaining life diagnosis method, remaining life diagnosis device, and battery system provided with same Download PDF

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Publication number
WO2015075814A1
WO2015075814A1 PCT/JP2013/081529 JP2013081529W WO2015075814A1 WO 2015075814 A1 WO2015075814 A1 WO 2015075814A1 JP 2013081529 W JP2013081529 W JP 2013081529W WO 2015075814 A1 WO2015075814 A1 WO 2015075814A1
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Prior art keywords
secondary battery
remaining life
discharge
current value
battery
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PCT/JP2013/081529
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French (fr)
Japanese (ja)
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裕 奥山
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株式会社日立製作所
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Priority to PCT/JP2013/081529 priority Critical patent/WO2015075814A1/en
Publication of WO2015075814A1 publication Critical patent/WO2015075814A1/en

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    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/48—Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/392—Determining battery ageing or deterioration, e.g. state of health
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/10—Energy storage using batteries

Definitions

  • the present invention relates to a technique for predicting the remaining life of a secondary battery, and more specifically, a remaining life diagnosis method and a remaining life diagnosis apparatus for estimating a discharge capacity maintenance rate, a DC resistance increase rate, and an output maintenance rate of a secondary battery. And a battery system including the same.
  • Secondary batteries such as lithium ion secondary batteries, are known to deteriorate in performance with storage or use. Therefore, in portable devices for consumer use such as notebook personal computers and mobile phones, or in hybrid vehicles and electric vehicles equipped with a motor driven by a secondary battery as a driving force source, the secondary battery as a power source deteriorates. It is necessary to notify the user of the degree.
  • a discharge capacity when discharged from a fully charged state and a direct current resistance (DCR) in a specified state of charge (SOC: State of Charge).
  • DCR direct current resistance
  • SOC specified state of charge
  • the output is an index.
  • the discharge capacity maintenance rate As the deterioration progresses, the discharge capacity decreases, the DC resistance increases, and the output decreases.
  • the deterioration diagnosis uses a discharge capacity maintenance rate, a direct current resistance increase rate, and an output maintenance rate that are normalized by the respective values before deterioration and displayed as percentages.
  • Patent Document 1 the voltage, current, and temperature during battery operation are detected, and the battery charge rate and DC resistance change rate are estimated using a parameter characteristic map and a battery model equation at the time of a new product.
  • a method of performing a deterioration diagnosis from the rate of change is disclosed.
  • Patent Document 2 discloses a method for performing life prediction on the assumption that the capacity maintenance rate is proportional to the square root of time.
  • Non-Patent Document 1 discloses a method of performing a numerical analysis on an ion movement phenomenon in a process in which a lithium ion battery repeats charging and discharging.
  • the current capacity maintenance rate and the DC resistance increase rate of a battery are calculated by simultaneously solving a plurality of battery model equations including differential equations using characteristics during battery operation. Prediction, that is, remaining life cannot be predicted.
  • a typical object of the present invention is to determine the life of a secondary battery in a technique for predicting the remaining life of a secondary battery.
  • the method for diagnosing the remaining life of a secondary battery stores a parameter of an initial state of the secondary battery in a memory, and discharges at a first current value and the parameter of the initial state stored in the memory after a predetermined time has elapsed.
  • the remaining life regarding the discharge capacity and DC resistance of the secondary battery is calculated based on the characteristics and the discharge characteristics at the second current value larger than the first current value.
  • the secondary battery remaining life diagnosis apparatus of the present invention includes an arithmetic unit for calculating the remaining life.
  • the battery system of the present invention includes a secondary battery, a control unit, and the remaining life diagnosis apparatus.
  • discharge of two different discharge currents is performed with respect to a discharge capacity maintenance rate, a DC resistance increase rate, and an output maintenance rate, which are indices for determining the life of the secondary battery.
  • the remaining life can be calculated by predicting from the characteristics or the charging characteristics of two different charging currents.
  • FIG. 3 is a flowchart illustrating a flow of calculation in a calculation unit according to the first embodiment. It is a block diagram which shows the detail of the calculating part in the remaining life diagnostic apparatus of Example 2.
  • FIG. 6 is a flowchart illustrating a flow of calculation in a calculation unit according to the second embodiment.
  • a representative secondary battery remaining life diagnosis method includes a detection step of detecting a battery voltage and a battery current of a secondary battery by a detector, and a secondary battery based on detection of the detector by a calculation unit.
  • a typical secondary battery remaining life diagnosis method includes a detection step of detecting a battery voltage and a battery current of a secondary battery by a detector, and a secondary battery based on detection of the detector by a calculation unit.
  • An extraction step for extracting a parameter representing the state of the secondary battery from the charging characteristics for the two types of currents, and estimating the time dependence of the parameter from the history of the parameter at a plurality of times, and the parameter at a desired time A predicting step of predicting the output by determining the remaining life of the secondary battery from the output maintenance rate.
  • the calculation unit estimates the deterioration parameter with reference to a model expression representing the history and time dependency of the deterioration parameter, and calculates the discharge capacity, the discharge DC resistance, and the output.
  • the representative effect is that the degradation parameter describing the degradation state of the secondary battery is extracted from the discharge or charge characteristics for two different types of currents, and the future value of the degradation parameter is estimated, thereby determining the discharge capacity.
  • the maintenance rate and the DC resistance increase rate or the output maintenance rate can be calculated, and the remaining life diagnosis of the secondary battery can be performed.
  • the constituent elements are not necessarily indispensable unless otherwise specified and clearly considered essential in principle. Needless to say.
  • the shapes, positional relationships, etc. of the components, etc. when referring to the shapes, positional relationships, etc. of the components, etc., the shapes are substantially the same unless otherwise specified, or otherwise apparent in principle. And the like are included. The same applies to the above numerical values and ranges.
  • 1A to 1C are diagrams for explaining the discharge characteristics of the secondary battery.
  • FIG. 1A and 1B show the open circuit voltage (OCV) characteristics of the positive electrode and the negative electrode.
  • FIG. 1C shows the relationship between voltage and capacity during discharge at the low current limit of the battery.
  • 1A to 1C schematically show discharge characteristics of a secondary battery, for example, a lithium ion battery. It assumes a low current limit state before deterioration and with a small discharge current and negligible resistance.
  • the discharge characteristic (low discharge current) of FIG. 1C shows the battery terminal voltage on the vertical axis and the discharge capacity on the horizontal axis.
  • the terminal voltage V of the battery changes with discharge, but the battery voltage is given by the difference between the positive electrode potential and the negative electrode potential.
  • the value of the discharge capacity when the voltage is discharged from the charged state of V high and discharged to a predetermined lower limit voltage V low is called the discharge capacity of the low discharge current.
  • the change in the potential of the positive electrode and the change in the potential of the negative electrode during discharge are determined from the OCV characteristics of the single electrode of the positive electrode active material in FIG. 1A and the OCV characteristics of the single electrode of the negative electrode active material in FIG. 1B.
  • the vertical axis represents the potential (voltage) with respect to metallic lithium
  • the horizontal axis represents the Li stoichiometric ratio, that is, the occupation ratio of Li.
  • m p and mn are an effective positive electrode active material amount and an effective negative electrode active material amount, respectively
  • C p and C n are a positive electrode specific capacity and a negative electrode specific capacity, respectively.
  • the change in the discharge capacity Q of the battery at time ⁇ t after the start of discharge is equal to ⁇ x p ⁇ m p ⁇ C p and ⁇ x n ⁇ m n ⁇ C n . Accordingly, the discharge characteristics of the low discharge current, four parameters x n or more with respect to the discharge start state, by specifying the x p, y n and y p, is determined only from the OCV characteristics of each positive and negative electrodes.
  • FIG. 2A and 2B are diagrams for explaining the discharge characteristics of the secondary battery.
  • FIG. 2A shows the relationship between voltage and capacity during discharging at the low current limit of the battery
  • FIG. 2B shows the relationship between voltage and capacity during discharging at a high current.
  • These drawings schematically show changes in discharge characteristics when the discharge current is increased.
  • the vertical axis represents the battery terminal voltage
  • the horizontal axis represents the discharge capacity.
  • the discharge capacity for an arbitrary discharge current depends on the resistance R in addition to the above four parameters.
  • the resistance R depends on the design value of the battery, the material property value, the resistance of the active material surface coating, and the like. For this reason, in order to obtain the discharge characteristics with respect to an arbitrary discharge current, it is necessary to use a calculation program that numerically solves an equation describing electron / ion conduction inside the battery, that is, a battery simulator.
  • Non-Patent Document 1 A list of equations and input parameters used in the battery simulator is disclosed in Non-Patent Document 1, for example.
  • the equation is roughly as follows.
  • ⁇ is the volume fraction of the electrolyte
  • c is the electrolyte concentration
  • t is the time
  • D is the diffusion coefficient of lithium ions in the electrolyte
  • j n is the pore wall flux
  • t 0 + is the transport.
  • z + is the number of charges
  • ⁇ + is the number of dissociated cations per mole of electrolyte
  • F is the Faraday constant
  • L is the battery cell thickness
  • a is the specific surface area of the active material
  • I is the total current density
  • i 1 is the current density of the electrolyte phase
  • i 2 is the current density of the solid phase
  • ⁇ 1 is the potential of the solid phase
  • ⁇ is the conductivity of the solid phase
  • ⁇ 2 is the potential of the electrolyte
  • ⁇ is the conductivity of the electrolyte
  • R is the gas constant
  • T is the temperature
  • f A is the salt activity coefficient
  • s i is the stoichiometric coefficient of component i in the electrode reaction
  • r is the radial axis in the active material particle
  • c s is the lithium in the solid phase
  • D s is the diffusion coefficient of lithium in the active material particles
  • R s is the radius of the active
  • Batteries can be stored with repeated use of charge / discharge, or even if they are stored without being used, the discharge capacity decreases and the discharge DC resistance increases.
  • One of the causes of deterioration is a decrease in the amount of effective active material that can be used for charging and discharging, and the other is that the amount of lithium that can be used for charging and discharging decreases due to the growth of the active material surface coating. And the film resistance is increased.
  • FIG. 3A shows the discharge characteristics at a low discharge current before deterioration
  • FIG. 3B shows the discharge characteristics at a low discharge current after deterioration. Therefore, the effect of increasing resistance due to deterioration is ignored in the figure.
  • the positive electrode potential characteristics and the negative electrode potential characteristics during discharge are reduced with respect to the capacity on the horizontal axis. Further, since the amount of lithium available is reduced, the x p and x n in the voltage V high deviates from the value before deterioration.
  • FIG. 3B shows a case where xn greatly increases due to deterioration.
  • Reduction of first causes a is the amount of active material deterioration phenomenon can be described by a reduction in the effective amount of the active material ratio y p and y n in the input parameter of the simulator.
  • the decrease in the amount of lithium among the decrease in the amount of lithium and the increase in resistance, which are the second cause, can be described by the deviation of the Li stoichiometric ratios x p and x n at the discharge start voltage V high from the values before deterioration.
  • the increase in resistance can be described by an increase in the film resistance Rf.
  • the electrolytic solution resistance may be used as the deterioration parameter.
  • these five parameters are the minimum necessary parameters to describe the deterioration state of the battery, and the discharge capacity for any discharge current after deterioration is calculated by inputting these five parameters into the simulator. Can be predicted.
  • FIG. 4A shows the fitting results of the discharge characteristics of the initial battery at low current (0.1 C rate) and high current (10 C rate). In the calculation of the low current and the high current, parameters other than the discharge current are common.
  • FIG. 4B shows the fitting results of the discharge characteristics at low current and high current of the battery after deterioration.
  • Both the initial discharge characteristics and the characteristics after deterioration can be fitted by using the above five parameters as fitting parameters.
  • four other than the film resistance are extracted from the fitting of the low current discharge characteristic with a small resistance component.
  • an appropriate value or 0 is input for the input parameter Rf.
  • the obtained four parameters are fixed, and the film resistance is extracted from the fitting of the high current discharge characteristics.
  • the secondary battery used for the actual measurement is a 18650 type battery (lithium ion secondary battery), the negative electrode is carbon-based, and the positive electrode is ternary (Ni, Mn, Co).
  • Table 1 shows an example of five deterioration parameters of the pre-deterioration battery and the post-deterioration battery extracted by parameter fitting. In the same procedure, a set of five deterioration parameters corresponding to different deterioration states is obtained.
  • the future discharge characteristics can be predicted by using the parameter as an input value of the simulator.
  • FIG. 5 is an explanatory diagram showing the change over time in the effective active material amount ratio y.
  • the horizontal axis represents the battery usage time t.
  • the extracted value shows a monotonous time dependence and can be fitted with a simple function expression.
  • This figure shows an example of fitting using the following formula (15) having time dependence of the exponential function.
  • y (0) is the initial value of the effective active material amount ratio. If the coefficients A and B are determined, the effective active material amount ratio after a long time can be predicted using the equation (4).
  • FIG. 6 is an explanatory diagram showing the change over time in the Li stoichiometric ratio x at the start of discharge.
  • the extracted value shows a monotonous time dependence and can be fitted with a simple function expression.
  • This figure shows an example of fitting using the following formula (16) having time dependence of the exponential function.
  • x (0) is the initial value of the Li stoichiometry at the start of discharge. If the coefficients C and D are determined, the Li stoichiometry after a long time can be predicted using the above equation (16).
  • FIG. 7 is an explanatory diagram showing the change over time of the film resistance Rf.
  • the extracted value shows a monotonous time dependence and can be fitted with a simple function expression.
  • Rf (0) is the film resistance before deterioration. If the coefficient E is determined, the film resistance after a long time can be predicted using the above equation (17).
  • FIG. 8 shows a calculation of deterioration parameters using the above equations (15) to (17), and discharge simulation of low current (0.1 C rate) and high current (10 C rate) using the obtained deterioration parameters as input parameters. It is explanatory drawing which shows the result compared with the measured value about the discharge capacity maintenance factor calculated
  • the prediction result shows a good agreement with the actual measurement value. Assuming that the life criterion for the capacity maintenance rate is 60%, for example, the time when the capacity maintenance rate falls below 60% is the life, and the differences t 0.1C and t 10C from the current time t 0 are 0.1C discharge and The remaining life for 10 C discharge is obtained.
  • discharge capacity maintenance rates of 0.1 C and 10 C are shown, but the discharge capacity maintenance rate and remaining life for an arbitrary discharge rate are calculated simply by changing the discharge current that is the input value of the simulation. be able to.
  • FIG. 9 shows the results of calculating the degradation parameter using the above equations (15) to (17) and comparing the DC resistance increase rate at 50% SOC obtained using the obtained degradation parameter as an input parameter with the actual measurement value. It is shown. For verification of the prediction accuracy, the measured values after the battery use period used for extracting the deterioration parameters are also plotted.
  • the prediction result shows a good agreement with the actual measurement value.
  • Life criteria for the DC resistance increase rate for example, to 150%, the time that the DC resistance increase rate is more than 150% is the life, the difference t DCR between the current time t 0 is the remaining life.
  • FIG. 10 shows the result of calculating the degradation parameter using the above formulas (15) to (17), and comparing the output retention rate obtained using the obtained degradation parameter as the input parameter with the actual measurement value.
  • the output P was defined with respect to SOC 50%, and was calculated by the following formula (18).
  • V low is a set lower limit voltage
  • R DCR is a direct current resistance.
  • the output maintenance ratio is a value obtained by normalizing the output after deterioration with the output before deterioration. Assuming that the life criterion for the output maintenance ratio is 60%, for example, the time when the output maintenance ratio falls below 60% is the life, and the difference t power from the current time is the remaining life.
  • the deterioration state of the battery can be described by the above five deterioration parameters, and these five deterioration parameters show a monotonous time dependency, and the value after a long time can be predicted if the time dependency is determined.
  • the remaining life related to the discharge capacity maintenance rate, discharge DC resistance increase rate, or output maintenance rate is predicted by calculating the discharge characteristics for any discharge current after deterioration by simulation using five deterioration parameters as input parameters.
  • FIG. 11 is a block diagram showing an example of a schematic configuration of a secondary battery remaining life diagnosis apparatus according to the present embodiment.
  • the apparatus includes a secondary battery 10, a control unit 20, a voltage sensor 30, a current sensor 40, a calculation unit 50, a display unit 60, and a timer 70.
  • the voltage sensor 30 measures the battery voltage output from the secondary battery 10.
  • the current sensor 40 measures the battery current output from the secondary battery 10. These voltage sensor 30 and current sensor 40 function as a detector.
  • the measurement value obtained by the voltage sensor 30 is denoted as V
  • the measurement value obtained by the current sensor 40 is denoted as I.
  • the battery voltage V and the battery current I measured by the voltage sensor 30 and the current sensor 40 are sent to the calculation unit 50.
  • FIG. 12 is a block diagram showing an example of a schematic configuration of the calculation unit 50 of FIG.
  • the arithmetic unit 50 includes an arithmetic unit 80, a non-volatile memory 90 for storing deterioration parameter history and coefficients A to E of the deterioration parameter function, material parameters, structure parameters, deterioration parameter function expressions, deterioration parameter initial values, ROM 100 for storing measured current values I 1 , I 2 (I 1 ⁇ I 2 ), life estimation current value list, discharge capacity initial value corresponding to life estimation current value list, DC resistance initial value, diagnosis time, and time increment ⁇ t (Also simply referred to as “memory”).
  • the life estimation current value list is a list of discharge current values for calculating the discharge capacity maintenance rate, and includes a plurality of current values from low current to high current.
  • the computing unit 80 calculates discharge characteristics, performs parameter fitting, extracts the effective active material amount ratio, Li stoichiometry ratio at the start of discharge, and film resistance, which are deterioration parameters of the secondary battery 10, and calculates the remaining life. To do.
  • the display unit 60 displays the remaining life calculated by the computing unit 80.
  • the secondary battery 10 is a battery formed by connecting one or a plurality of unit battery cells, and will be described as the secondary battery 10 in the present specification. In the following description, a lithium ion battery is taken as an example of the secondary battery 10.
  • FIG. 13 is a flowchart illustrating an example of a remaining life diagnosis method in which the arithmetic device 50 in FIG. 12 diagnoses the remaining life of the secondary battery 10.
  • the computing unit 80 After the use of the secondary battery 10 is started, the computing unit 80 reads the diagnosis time, the two discharge current values I 1 and I 2 , and the time increment ⁇ t from the ROM 100 in step S1.
  • step S10 it reads the elapsed time t 0 after the start of use from the timer 70.
  • step S20 the present time t 0 is determined whether diagnosis time, if not diagnosed time (S20-No), the process proceeds to step S80. If it is the diagnosis time (S20-Yes), the process proceeds to step S30.
  • step S30 according to a measurement instruction from the computing unit 80, the control unit 20 once charges the battery 10 at a constant current and a constant voltage to the upper limit voltage V high, and then discharges the low discharge current I 1 to the lower limit voltage V low , and then continues. Then, after charging with constant current and constant voltage again to the upper limit voltage V high , discharge with a higher current I 2 higher than that until the lower limit voltage V low is performed. Time, current, and voltage data are read from the timer 70, the current sensor 40, and the voltage sensor 30, respectively, and converted into measured discharge characteristic data.
  • step S40 the computing unit 80 calculates the discharge characteristics of the low current I 1 by simulation using the effective active material amount ratio x of the positive electrode and the negative electrode and the Li stoichiometric ratio y at the start of discharge as fitting parameters. Then, fitting with the measured discharge characteristic data is performed to extract the effective active material amount ratio x and the Li stoichiometry ratio y at the start of discharge for each of the positive electrode and the negative electrode. As the fitting method, an appropriate parameter search method that minimizes the difference between the calculated value and the actually measured value is used.
  • step S50 the computing unit 80 inputs the effective active material amount ratio x and the discharge start Li stoichiometric ratio y obtained in step S40, and performs high current I 2 by simulation using the film resistance as a fitting parameter.
  • the discharge characteristic is calculated, and fitting with the measured discharge characteristic data is performed to extract the film resistance Rf.
  • step S60 writes the deterioration parameter extracted at step S40 and S50 together with the time t 0 in the nonvolatile memory 90, reads the entire history.
  • step S70 the computing unit 80 first converts the above equation (15) into the set of the diagnosis times t and y read in step S60 by the least square method for the effective active material amount ratio y. Fitting is performed, and coefficients A and B are extracted.
  • the above equation (16) is fitted to the set of the diagnosis times t and x read in step S60 by the least square method, and the coefficients C and D are extracted.
  • the equation (17) is fitted to the set of the diagnosis times t and Rf read in step S60 by the least square method, and the coefficient E is extracted.
  • the function formula to be incorporated in advance may be a logarithmic expression, polynomial, etc. other than the above formulas (15) to (17).
  • the number of equations used in step S60 and the number of coefficients to be determined vary depending on the number of equations and coefficients to be incorporated.
  • step S80 If it is determined in step S20 that it is not the diagnosis time, it is determined in step S80 whether or not the user has requested a remaining life diagnosis. If not (S80-No), the process returns to the start. If the remaining life diagnosis is requested (S80-Yes), the coefficients A to E of the deterioration parameter function formula are read from the nonvolatile memory 90 in step S90.
  • the computing unit 80 calculates the lifetime in steps S100 to S140.
  • step S100 it sets the time t 1 to calculate the Delta] t.
  • step S110 the deterioration parameter at time t 1 is calculated based on the equation (15) to (17).
  • step S120 a discharge current value list used for life estimation is read from the ROM 100.
  • step S130 the discharge capacity and discharge DC resistance against current value included in the discharge current value list at time t 1 is calculated and the corresponding current value from the memory 100
  • the discharge capacity initial value and the direct current resistance initial value are read and converted into a capacity maintenance rate and a direct current resistance increase rate.
  • step S140 life determination is performed.
  • the process proceeds to step S150. If even one does not exceed the life criterion (S140-No), the time is updated by ⁇ t, the process returns to step S110, and the calculation is repeated.
  • step S150 the remaining life related to the discharge capacity maintenance rate and the remaining life related to the discharge DC resistance maintenance rate for each discharge current value are calculated.
  • the lifetime is obtained by interpolating data at two times before and after the lifetime criterion. If the time when the life is reached has already passed, the remaining life is a negative value.
  • step S160 the capacity maintenance rate remaining life and discharge DC resistance increase rate remaining life for each discharge current are displayed on the display unit 60, and the process returns to the start.
  • the deterioration parameter at an arbitrary time is estimated and estimated based on the battery usage time dependency of the deterioration parameter extracted from the discharge characteristics of two different discharge rates. It is possible to estimate the remaining life by calculating the discharge characteristics by simulation with the deterioration parameter as an input.
  • the remaining battery life diagnosis method and remaining life diagnosis apparatus according to the second embodiment will be described with reference to FIGS. In the following, differences from the first embodiment will be mainly described.
  • FIG. 14 is a block diagram illustrating an example of a schematic configuration of the calculation unit 50.
  • the computing unit 50 includes a computing unit 81, a history of degradation parameters, coefficients A to E of degradation parameter function formulas, and a non-volatile memory 91 for storing previous measurement current values, material parameters, structural parameters, degradation parameter function formulas,
  • a ROM 101 also simply referred to as “memory” that stores a deterioration parameter initial value, an output initial value, two charging current values, and time increments.
  • the deterioration parameter is extracted from the charging characteristics for two different currents.
  • the charging characteristics during charging can be used for parameter extraction. Since it is difficult to measure two charging characteristics with different charging currents during one charging, a set of deterioration parameters is obtained from the charging characteristics of two chargings with different charging currents.
  • FIG. 15 is a flowchart illustrating an example of a remaining life diagnosis method in which the calculation unit 50 diagnoses the remaining life of the secondary battery 10.
  • the computing unit 81 determines in step S2 whether there is a charge request, and if there is no charge request (S80-No), the process returns to the start. If there is a charge request (S80-Yes), the process proceeds to step 3.
  • step S3 the previous charging current value is read from the nonvolatile memory 91, and the two charging current values I 1 and I 2 (I 1 ⁇ I 2 ) are read from the ROM 101, and the charging current value different from the previous charging current value is read. This is determined as the current charging current value.
  • step S10 it reads the elapsed time t 0 after the start of use from the timer 70.
  • step S11 the control unit 20 discharges the battery 10 to the lower limit voltage V low once according to a measurement instruction from the computing unit 81.
  • step S21 it is determined whether the current charging current value is a small current I 1 (low current) or a large current I 2 (high current). If the current value is small (S21—Yes), the process proceeds to step S31. If the current is large (S21-No), the process proceeds to step S32.
  • step S31 the calculator 81, in step S31, to perform the charging of the charging current I 1, the timer 70, current sensor 40 and voltage sensor 30, respectively time, read current, the data voltage, charge characteristic Convert to data.
  • the arithmetic unit 81 in step S41, the material parameters from ROM 101, reads the structural parameters, an effective amount of the active material ratio x and charging starts Li stoichiometry y as fitting parameters, charging characteristics of the charging current I 1 And fitting with charging characteristic data to extract the effective active material amount ratio x and the Li start stoichiometric ratio y.
  • the calculator 81 writes the time t 0 , the effective active material amount ratio x, and the charging start Li stoichiometry ratio y in the nonvolatile memory 91 in step S 51.
  • step S61 the computing unit 81 obtains initial values of the degradation parameter function formulas (the above formulas (15) and (16)), the effective active material amount ratio x, and the charging start Li stoichiometric ratio y from the ROM 101. Read.
  • step S71 the computing unit 81 reads the time history of the effective active material amount ratio x and the Li stoichiometry ratio y at the start of charging from the nonvolatile memory 91, extracts parameters A to D by fitting, Write to memory 91 and return to start.
  • step S32 the calculator 81, in step S32, to perform the charging of the charging current I 2, from the timer 70, current sensor 40 and voltage sensor 30, respectively time, read current, the data voltage, charge Convert to characteristic data.
  • the calculator 81 reads the deterioration parameter function equation (the above equation (17)) and the initial value of the deterioration parameter Rf from the ROM 101 in step S42.
  • step S52 the calculator 81 reads the coefficients A to D of the deterioration parameter function equation from the nonvolatile memory 91, and calculates the effective active material amount ratio x and the charge start Li stoichiometry ratio y at the current time. .
  • step S72 the computing unit 81 reads the material parameter and the structural parameter from the ROM 101, and uses the effective active material amount ratio x and the charging start Li stoichiometric ratio y as input values of the simulator to the film resistance. the Rf as fitting parameters, calculates the charging characteristics of the charging current I 2, performed fitting the charge characteristic data, to extract the film resistor Rf.
  • the arithmetic unit 81 the step S81, and writes the time t 0 and the film resistor Rf in the nonvolatile memory 91.
  • step S91 the calculator 81 reads the history of the time t and the deterioration parameter Rf stored in the nonvolatile memory 91, reads the deterioration parameter function equation (the above equation (17)) from the ROM 101, and calculates the coefficient E. Extracted and written into the nonvolatile memory 91.
  • the computing unit 81 calculates the lifetime from step S100 to step S140.
  • step S100 it sets the time t 1 for predicting the characteristics Delta] t.
  • step S110 the deterioration parameter at time t 1 is calculated based on the equation (15) to (17).
  • step S121 the calculated deterioration parameter as input to the simulator to calculate the output at time t 1, reads the initial output value from the memory 101, converted into an output retention ratio.
  • step S130 the life is determined.
  • the process proceeds to step S140. If the service life criterion has not been exceeded (S130-No), the time is increased by ⁇ t, the process returns to step S110, and the calculation is repeated.
  • step S140 the lifetime is calculated.
  • the calculation method is obtained by interpolating data at two times before and after the life determination reference value. If the time when the life is reached has already passed, the remaining life is a negative value.
  • step S150 the difference between the current time and the life is displayed as the remaining life on the display unit 60, and the process returns to the start.
  • the deterioration parameter at an arbitrary time is estimated and estimated based on the battery usage time dependency of the deterioration parameter extracted from the charging characteristics of two different charging currents.
  • the remaining life can be estimated by calculating the output by simulation using the degradation parameter as an input value.
  • the secondary battery remaining life diagnosis apparatus will be described as an example. However, the following mainly describes differences from the first and second embodiments. explain.
  • the function expression may be anything such as an exponential function, a logarithmic function, a power function, or a polynomial.
  • 10 secondary battery
  • 20 control unit
  • 30 voltage sensor
  • 35 sensor
  • 40 current sensor
  • 50 calculation unit
  • 60 display unit
  • 70 timer
  • 80 calculation unit
  • 81 calculation unit
  • 90 Non-volatile memory
  • 91 non-volatile memory
  • 100 101: ROM.

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Abstract

A secondary battery remaining life diagnosis method in which the parameters of a secondary battery in an initial state are stored in memory and after a prescribed period of time has passed, the remaining life for the discharge capacity and direct current resistance of the secondary battery is calculated on the basis of the initial state parameters stored in memory, a discharge characteristic at a first current value, and a discharge characteristic at a second current value larger than the first current value. In the prediction of the remaining life of a secondary battery, this method makes it possible to calculate the remaining life for a discharge capacity maintenance rate, direct current resistance growth rate, and output maintenance rate, which are indicators used to determine the remaining life of a secondary battery, on the basis of discharge characteristics for two different discharge currents or charging characteristics for two different charging currents.

Description

二次電池の余寿命診断方法並びに余寿命診断装置及びこれを備えた電池システムSecondary battery remaining life diagnosis method, remaining life diagnosis apparatus, and battery system including the same
　本発明は、二次電池の余寿命を予測する技術に関し、具体的には、二次電池の放電容量維持率、直流抵抗増加率および出力維持率を推定する余寿命診断方法並びに余寿命診断装置及びこれを備えた電池システムに関する。 The present invention relates to a technique for predicting the remaining life of a secondary battery, and more specifically, a remaining life diagnosis method and a remaining life diagnosis apparatus for estimating a discharge capacity maintenance rate, a DC resistance increase rate, and an output maintenance rate of a secondary battery. And a battery system including the same.
　二次電池、たとえば、リチウムイオン二次電池は、保存あるいは使用とともに性能が劣化することが知られている。したがって、ノート型パーソナルコンピュータや携帯電話などの民生用途の携帯機器、あるいは、二次電池によって駆動される電動機を駆動力源として備えたハイブリッド自動車や電気自動車などでは、電源としての二次電池の劣化度をユーザに通知する必要がある。 Secondary batteries, such as lithium ion secondary batteries, are known to deteriorate in performance with storage or use. Therefore, in portable devices for consumer use such as notebook personal computers and mobile phones, or in hybrid vehicles and electric vehicles equipped with a motor driven by a secondary battery as a driving force source, the secondary battery as a power source deteriorates. It is necessary to notify the user of the degree.
　二次電池の劣化度を表す指標としては、満充電状態から放電した場合の放電容量と、ある指定した充電状態（ＳＯＣ：Ｓｔａｔｅ　ｏｆ　Ｃｈａｒｇｅ）における直流抵抗（ＤＣＲ：Ｄｉｒｅｃｔ　Ｃｕｒｒｅｎｔ　Ｒｅｓｉｓｔａｎｃｅ）との２つが一般に使われる。あるいは、駆動力源として使用する場合には、出力が指標となる。劣化が進むと、放電容量は減少し、直流抵抗は増加し、出力は減少する。通常、劣化診断には、それぞれの劣化前の値で規格化してパーセンテージ表示した放電容量維持率、直流抵抗増加率及び出力維持率が用いられる。 There are two indexes that indicate the degree of deterioration of the secondary battery: a discharge capacity when discharged from a fully charged state, and a direct current resistance (DCR) in a specified state of charge (SOC: State of Charge). Generally used. Alternatively, when used as a driving force source, the output is an index. As the deterioration progresses, the discharge capacity decreases, the DC resistance increases, and the output decreases. Usually, the deterioration diagnosis uses a discharge capacity maintenance rate, a direct current resistance increase rate, and an output maintenance rate that are normalized by the respective values before deterioration and displayed as percentages.
　これらの劣化指標を検出および推定する方法および装置は、従来、各種提案されている。 Various methods and apparatuses for detecting and estimating these deterioration indexes have been proposed in the past.
　たとえば、特許文献１には、電池動作中の電圧、電流、温度を検出し、新品時のパラメータ特性マップと電池モデル式を用いて、電池の充電率と直流抵抗変化率を推定し、直流抵抗変化率から劣化診断を行う方法が開示されている。 For example, in Patent Document 1, the voltage, current, and temperature during battery operation are detected, and the battery charge rate and DC resistance change rate are estimated using a parameter characteristic map and a battery model equation at the time of a new product. A method of performing a deterioration diagnosis from the rate of change is disclosed.
　また、特許文献２には、容量維持率が時間の平方根に比例することを仮定し、寿命予測を行う方法が開示されている。 Further, Patent Document 2 discloses a method for performing life prediction on the assumption that the capacity maintenance rate is proportional to the square root of time.
　非特許文献１には、リチウムイオン電池が充放電を繰り返す過程におけるイオンの移動現象について数値解析を行う方法が開示されている。 Non-Patent Document 1 discloses a method of performing a numerical analysis on an ion movement phenomenon in a process in which a lithium ion battery repeats charging and discharging.
特開２００８－２４１２４６号公報JP 2008-241246 A 特開２０１３－８９４２４号公報JP 2013-89424 A
　特許文献１においては、電池動作中の特性を用いて、微分方程式を含む複数の電池モデル式を連立して解くことにより、電池の現時点における容量維持率および直流抵抗増加率を計算するが、将来予測すなわち残寿命予測は行うことができない。 In Patent Document 1, the current capacity maintenance rate and the DC resistance increase rate of a battery are calculated by simultaneously solving a plurality of battery model equations including differential equations using characteristics during battery operation. Prediction, that is, remaining life cannot be predicted.
　また、特許文献２においては、低レートの放電容量に関する寿命予測を行うが、任意の放電レートに対する寿命予測、直流抵抗および出力に対する寿命予測は行うことができない。 In Patent Document 2, life prediction for a low rate discharge capacity is performed, but life prediction for an arbitrary discharge rate and life prediction for DC resistance and output cannot be performed.
　そこで、本発明は、このような問題点を解決するためになされたものであって、この発明の代表的な目的は、二次電池の余寿命の予測技術において、二次電池の寿命を判定する指標である放電容量維持率、直流抵抗増加率および出力維持率を、２つの異なる放電電流の放電特性、あるいは２つの異なる充電電流の充電特性から予測する余寿命予測方法および余寿命予測装置を提供することにある。 Accordingly, the present invention has been made to solve such problems, and a typical object of the present invention is to determine the life of a secondary battery in a technique for predicting the remaining life of a secondary battery. A remaining life prediction method and a remaining life prediction apparatus for predicting a discharge capacity maintenance rate, a direct current resistance increase rate, and an output maintenance rate, which are indices to be used, from discharge characteristics of two different discharge currents or charge characteristics of two different charge currents It is to provide.
　本発明の二次電池の余寿命診断方法は、二次電池の初期状態のパラメータをメモリに保存し、所定時間経過後に、メモリに保存された初期状態のパラメータと、第一の電流値における放電特性と、第一の電流値より大きい第二の電流値における放電特性とに基づいて、二次電池の放電容量及び直流抵抗に関する余寿命を算出することを特徴とする。 The method for diagnosing the remaining life of a secondary battery according to the present invention stores a parameter of an initial state of the secondary battery in a memory, and discharges at a first current value and the parameter of the initial state stored in the memory after a predetermined time has elapsed. The remaining life regarding the discharge capacity and DC resistance of the secondary battery is calculated based on the characteristics and the discharge characteristics at the second current value larger than the first current value.
　また、本発明の二次電池の余寿命診断装置は、上記の余寿命の算出を行う演算器を備えている。 The secondary battery remaining life diagnosis apparatus of the present invention includes an arithmetic unit for calculating the remaining life.
　さらに、本発明の電池システムは、二次電池と、制御部と、上記の余寿命診断装置と、を備えている。 Furthermore, the battery system of the present invention includes a secondary battery, a control unit, and the remaining life diagnosis apparatus.
　本発明によれば、二次電池の余寿命の予測技術において、二次電池の寿命を判定する指標である放電容量維持率、直流抵抗増加率及び出力維持率について、２つの異なる放電電流の放電特性、又は、２つの異なる充電電流の充電特性から予測し、余寿命を算出することができる。 According to the present invention, in the technique for predicting the remaining life of a secondary battery, discharge of two different discharge currents is performed with respect to a discharge capacity maintenance rate, a DC resistance increase rate, and an output maintenance rate, which are indices for determining the life of the secondary battery. The remaining life can be calculated by predicting from the characteristics or the charging characteristics of two different charging currents.
正極活物質単極の開回路電圧を示すグラフである。It is a graph which shows the open circuit voltage of a positive electrode active material single electrode. 負極活物質単極の開回路電圧を示すグラフである。It is a graph which shows the open circuit voltage of a negative electrode active material single electrode. 電池の低電流極限での放電時の電圧と容量との関係を示すグラフである。It is a graph which shows the relationship between the voltage at the time of discharge in the low-current limit of a battery, and a capacity | capacitance. 電池の低電流極限での放電時の電圧と容量との関係を示すグラフである。It is a graph which shows the relationship between the voltage at the time of discharge in the low-current limit of a battery, and a capacity | capacitance. 電池の高電流での放電時の電圧と容量との関係を示すグラフである。It is a graph which shows the relationship between the voltage at the time of discharge with the high current of a battery, and a capacity | capacitance. 電池が劣化する前（新品）の低電流極限での放電時の電圧と容量との関係を示すグラフである。It is a graph which shows the relationship between the voltage at the time of discharge in the low current limit before a battery deteriorates (new article), and a capacity | capacitance. 電池が劣化した後（中古品）の低電流極限での放電時の電圧と容量との関係を示すグラフである。It is a graph which shows the relationship between the voltage and the capacity | capacitance at the time of discharge in the low-current limit after a battery deteriorates (used article). 電池が劣化する前（新品）の０．１Ｃレート及び１０Ｃレートに対する放電特性の実測値にパラメータフィッティングした計算結果を示すグラフである。It is a graph which shows the calculation result which carried out parameter fitting to the measured value of the discharge characteristic with respect to 0.1C rate and 10C rate before a battery deteriorates (new article). 電池が劣化した後（中古品）の０．１Ｃレート及び１０Ｃレートに対する放電特性の実測値にパラメータフィッティングした計算結果を示すグラフである。It is a graph which shows the calculation result which carried out the parameter fitting to the measured value of the discharge characteristic with respect to the 0.1C rate and 10C rate after a battery deteriorates (used article). 放電特性のフィッティングにより抽出した有効活物質量比の履歴について式（１５）を用いてフィッティングした結果を示すグラフである。It is a graph which shows the result of fitting using Formula (15) about the log | history of the effective active material amount ratio extracted by fitting of the discharge characteristic. 放電特性のフィッティングにより抽出した放電開始時Ｌｉ化学量論比の履歴について式（１６）を用いてフィッティングした結果を示すグラフである。It is a graph which shows the result fitted using Formula (16) about the log | history of Li stoichiometry at the time of the start of discharge extracted by fitting of the discharge characteristic. 放電特性のフィッティングにより抽出した被膜抵抗の履歴について式（１７）によりフィッティングした結果を示すグラフである。It is a graph which shows the result of fitting by Formula (17) about the log | history of the film | membrane resistance extracted by fitting of the discharge characteristic. ０．１Ｃレート及び１０Ｃレートに対する放電容量維持率の実測値と計算結果との比較を示すグラフである。It is a graph which shows the comparison with the measured value and calculation result of the discharge capacity maintenance factor with respect to 0.1C rate and 10C rate. 放電直流抵抗増加率の実測値と計算結果との比較を示すグラフである。It is a graph which shows the comparison with the measured value and calculation result of discharge direct current | flow resistance increase rate. 出力維持率の実測値と計算結果との比較を示すグラフである。It is a graph which shows the comparison with the actual value of an output maintenance factor, and a calculation result. 二次電池の余寿命診断装置の概略構成を示すブロック図である。It is a block diagram which shows schematic structure of the remaining life diagnosis apparatus of a secondary battery. 実施例１の余寿命診断装置における演算部の詳細を示すブロック図である。It is a block diagram which shows the detail of the calculating part in the remaining life diagnostic apparatus of Example 1. FIG. 実施例１の演算部における演算の流れを示すフローチャートである。3 is a flowchart illustrating a flow of calculation in a calculation unit according to the first embodiment. 実施例２の余寿命診断装置における演算部の詳細を示すブロック図である。It is a block diagram which shows the detail of the calculating part in the remaining life diagnostic apparatus of Example 2. FIG. 実施例２の演算部における演算の流れを示すフローチャートである。6 is a flowchart illustrating a flow of calculation in a calculation unit according to the second embodiment.
　本発明のうち、代表的なものの概要を簡単に説明すれば、次のとおりである。 The outline of typical ones of the present invention will be briefly described as follows.
　（１）代表的な二次電池の余寿命診断方法は、検出器により、二次電池の電池電圧、電池電流を検出する検出ステップと、演算部により、検出器の検出に基づいた二次電池の異なる二種の電流に対する放電特性から、二次電池の劣化状態を表す劣化パラメータを所定の時刻において抽出する抽出ステップと、複数の時刻における前記パラメータの履歴から前記パラメータの時間依存性を推定し、所望の時刻における前記パラメータを求めることにより放電容量および放電直流抵抗を予測する予測ステップと、を有し、放電容量維持率および放電直流抵抗増加率から二次電池の余寿命を診断する。 (1) A representative secondary battery remaining life diagnosis method includes a detection step of detecting a battery voltage and a battery current of a secondary battery by a detector, and a secondary battery based on detection of the detector by a calculation unit. An extraction step for extracting a deterioration parameter representing a deterioration state of the secondary battery at a predetermined time from discharge characteristics with respect to two different types of currents, and estimating the time dependence of the parameter from the history of the parameter at a plurality of times A prediction step of predicting the discharge capacity and the discharge DC resistance by obtaining the parameters at a desired time, and diagnosing the remaining life of the secondary battery from the discharge capacity maintenance rate and the discharge DC resistance increase rate.
　（２）代表的な二次電池の余寿命診断方法は、検出器により、二次電池の電池電圧、電池電流を検出する検出ステップと、演算部により、検出器の検出に基づいた二次電池の二種の電流に対する充電特性から、二次電池の状態を表すパラメータを抽出する抽出ステップと、複数の時刻における前記パラメータの履歴から前記パラメータの時間依存性を推定し、所望の時刻における前記パラメータを求めることにより出力を予測する予測ステップと、を有し、出力維持率から二次電池の余寿命を診断する。 (2) A typical secondary battery remaining life diagnosis method includes a detection step of detecting a battery voltage and a battery current of a secondary battery by a detector, and a secondary battery based on detection of the detector by a calculation unit. An extraction step for extracting a parameter representing the state of the secondary battery from the charging characteristics for the two types of currents, and estimating the time dependence of the parameter from the history of the parameter at a plurality of times, and the parameter at a desired time A predicting step of predicting the output by determining the remaining life of the secondary battery from the output maintenance rate.
　より好ましくは、推定ステップにおいては、演算部により、劣化パラメータの履歴および時間依存性を表すモデル式を参照して劣化パラメータを推定し、放電容量、放電直流抵抗及び出力を計算する。 More preferably, in the estimation step, the calculation unit estimates the deterioration parameter with reference to a model expression representing the history and time dependency of the deterioration parameter, and calculates the discharge capacity, the discharge DC resistance, and the output.
　本願において開示される発明のうち、代表的なものによって得られる効果を簡単に説明すれば以下のとおりである。 Among the inventions disclosed in the present application, effects obtained by typical ones will be briefly described as follows.
　すなわち、代表的な効果は、二次電池の劣化状態を記述する劣化パラメータを、異なった二種の電流に対する放電あるいは充電特性から抽出し、劣化パラメータの将来の値を推定することにより、放電容量維持率および直流抵抗増加率あるいは出力維持率を計算することができ、二次電池の余寿命診断を行うことができる。 In other words, the representative effect is that the degradation parameter describing the degradation state of the secondary battery is extracted from the discharge or charge characteristics for two different types of currents, and the future value of the degradation parameter is estimated, thereby determining the discharge capacity. The maintenance rate and the DC resistance increase rate or the output maintenance rate can be calculated, and the remaining life diagnosis of the secondary battery can be performed.
　以下の実施の形態においては、便宜上その必要があるときは、複数のセクションまたは実施の形態に分割して説明するが、特に明示した場合を除き、それらは互いに無関係なものではなく、一方は他方の一部または全部の変形例、詳細、補足説明等の関係にある。また、以下の実施の形態において、要素の数等（個数、数値、量、範囲等を含む）に言及する場合、特に明示した場合および原理的に明らかに特定の数に限定される場合等を除き、その特定の数に限定されるものではなく、特定の数以上でも以下でもよい。 In the following embodiments, when it is necessary for the sake of convenience, the description will be divided into a plurality of sections or embodiments. However, unless otherwise specified, they are not irrelevant and one is the other. There are some or all of the modifications, details, supplementary explanations, and the like. Further, in the following embodiments, when referring to the number of elements (including the number, numerical value, quantity, range, etc.), especially when clearly indicated and when clearly limited to a specific number in principle, etc. Except, it is not limited to the specific number, and may be more or less than the specific number.
　さらに、以下の実施の形態において、その構成要素（要素ステップ等も含む。）は、特に明示した場合および原理的に明らかに必須であると考えられる場合等を除き、必ずしも必須のものではないことは言うまでもない。同様に、以下の実施の形態において、構成要素等の形状、位置関係等に言及するときは、特に明示した場合および原理的に明らかにそうでないと考えられる場合等を除き、実質的にその形状等に近似または類似するもの等を含むものとする。このことは、上記数値および範囲についても同様である。 Further, in the following embodiments, the constituent elements (including element steps and the like) are not necessarily indispensable unless otherwise specified and clearly considered essential in principle. Needless to say. Similarly, in the following embodiments, when referring to the shapes, positional relationships, etc. of the components, etc., the shapes are substantially the same unless otherwise specified, or otherwise apparent in principle. And the like are included. The same applies to the above numerical values and ranges.
　［実施の形態の前提］
　＜二次電池の劣化前の放電特性＞
　まず、本実施の形態の前提として、図１Ａ～図３Ｂを用いて、二次電池（以下、単に「電池」ともいう。）の劣化前（初期状態）の放電特性について説明する。 [Assumptions of the embodiment]
<Discharge characteristics of secondary battery before deterioration>
First, as a premise of the present embodiment, discharge characteristics before deterioration (initial state) of a secondary battery (hereinafter also simply referred to as “battery”) will be described with reference to FIGS. 1A to 3B.
　図１Ａ～１Ｃは、この二次電池の放電特性を説明するための図である。 1A to 1C are diagrams for explaining the discharge characteristics of the secondary battery.
　図１Ａ及び１Ｂは、正極及び負極の開回路電圧（ＯＣＶ：Ｏｐｅｎ　Ｃｉｒｃｕｉｔ　Ｖｏｌｔａｇｅ）特性を示したものである。図１Ｃは、電池の低電流極限での放電時の電圧と容量との関係を示したものである。図１Ａ～１Ｃは、二次電池、例えば、リチウムイオン電池の放電特性を模式的に示している。劣化前であり、かつ、放電電流が小さく、抵抗が無視できる低電流極限状態を想定している。 1A and 1B show the open circuit voltage (OCV) characteristics of the positive electrode and the negative electrode. FIG. 1C shows the relationship between voltage and capacity during discharge at the low current limit of the battery. 1A to 1C schematically show discharge characteristics of a secondary battery, for example, a lithium ion battery. It assumes a low current limit state before deterioration and with a small discharge current and negligible resistance.
　図１Ｃの放電特性（低放電電流）は、縦軸を電池の端子電圧、横軸を放電容量として示したものである。電池の端子電圧Ｖは放電とともに変化するが、電池の電圧は、正極の電位と負極の電位との差で与えられる。電圧がＶｈｉｇｈの充電状態から放電し、所定の下限電圧Ｖｌｏｗまで放電したときの放電容量の値を低放電電流の放電容量と呼ぶ。 The discharge characteristic (low discharge current) of FIG. 1C shows the battery terminal voltage on the vertical axis and the discharge capacity on the horizontal axis. The terminal voltage V of the battery changes with discharge, but the battery voltage is given by the difference between the positive electrode potential and the negative electrode potential. The value of the discharge capacity when the voltage is discharged from the charged state of V high and discharged to a predetermined lower limit voltage V low is called the discharge capacity of the low discharge current.
　放電中の正極の電位の変化及び負極の電位の変化は、図１Ａの正極活物質単極のＯＣＶ特性及び図１Ｂの負極活物質単極のＯＣＶ特性から決まる。図１Ａ及び１ＢのＯＣＶ特性は、縦軸を金属リチウムに対する電位（電圧）、横軸をＬｉ化学量論比、すなわち、Ｌｉの占有率として示したものである。 The change in the potential of the positive electrode and the change in the potential of the negative electrode during discharge are determined from the OCV characteristics of the single electrode of the positive electrode active material in FIG. 1A and the OCV characteristics of the single electrode of the negative electrode active material in FIG. 1B. In the OCV characteristics of FIGS. 1A and 1B, the vertical axis represents the potential (voltage) with respect to metallic lithium, and the horizontal axis represents the Li stoichiometric ratio, that is, the occupation ratio of Li.
　電池の放電開始時における正極のＬｉ化学量論比をｘｐとし、負極のＬｉ化学量論比をｘｎとする。放電開始後Δｔの時間において、正極のＬｉ化学量論比はｘｐから増加（ｘｐ＋Δｘｐ）し、負極の化学量論比はｘｎから減少（ｘｎ－Δｘｎ）するが、それぞれの変化量Δｘｐ及びΔｘｎには、下記式（１）で表される関係がある。 The Li stoichiometry of the positive electrode at the time of start of discharging the battery and x p, the Li stoichiometry of the negative electrode and x n. In time of the discharge after the start Delta] t, Li stoichiometry of the positive electrode increases from x p (x p + Δx p ), the stoichiometric ratio of the negative electrode decreases from x n (x n -Δx n) Suruga, respectively There is a relationship represented by the following formula (1) between the change amounts Δx p and Δx n of.
Figure JPOXMLDOC01-appb-M000001
Figure JPOXMLDOC01-appb-M000001
　ここで、ｍｐ、ｍｎはそれぞれ、実効的正極活物質量、実効的負極活物質量であり、Ｃｐ、Ｃｎはそれぞれ、正極比容量、負極比容量である。ここで、正極及び負極の活物質量の設計値をそれぞれ、ｍｐ０、ｍｎ０とすると、正極及び負極の有効活物質量比ｙｐ、ｙｎはそれぞれ、下記式（２）、（３）のように定義される。 Here, m p and mn are an effective positive electrode active material amount and an effective negative electrode active material amount, respectively, and C p and C n are a positive electrode specific capacity and a negative electrode specific capacity, respectively. Wherein each positive and negative active material of the design value, when m p0, m n0, positive and effective amount of the active material ratio y p of the negative electrode, respectively y n, the following equation (2), (3) Is defined as follows.
Figure JPOXMLDOC01-appb-M000002
Figure JPOXMLDOC01-appb-M000002
Figure JPOXMLDOC01-appb-M000003
 　これらは、充放電に関与する活物質量の設計値に対する割合を表す。
Figure JPOXMLDOC01-appb-M000003
 These represent the ratio with respect to the design value of the amount of active material involved in charge / discharge.
　放電開始後の時間Δｔにおける電池の放電容量Ｑの変化分は、Δｘｐ×ｍｐ×Ｃｐ及びΔｘｎ×ｍｎ×Ｃｎに等しい。従って、低放電電流の放電特性は、放電開始状態に対する以上の４つのパラメータｘｎ、ｘｐ、ｙｎ及びｙｐを指定すれば、正極及び負極それぞれのＯＣＶ特性のみから決定される。 The change in the discharge capacity Q of the battery at time Δt after the start of discharge is equal to Δx p × m p × C p and Δx n × m n × C n . Accordingly, the discharge characteristics of the low discharge current, four parameters x n or more with respect to the discharge start state, by specifying the x p, y n and y p, is determined only from the OCV characteristics of each positive and negative electrodes.
　図２Ａ及び２Ｂは、二次電池の放電特性を説明するための図である。図２Ａは電池の低電流極限での放電時の電圧と容量の関係、図２Ｂは高電流での放電時の電圧と容量の関係を示している。これらの図は、放電電流を大きくした場合の放電特性の変化を模式的に示したものである。これらの図において、縦軸は電池の端子電圧であり、横軸は放電容量である。 2A and 2B are diagrams for explaining the discharge characteristics of the secondary battery. FIG. 2A shows the relationship between voltage and capacity during discharging at the low current limit of the battery, and FIG. 2B shows the relationship between voltage and capacity during discharging at a high current. These drawings schematically show changes in discharge characteristics when the discharge current is increased. In these drawings, the vertical axis represents the battery terminal voltage, and the horizontal axis represents the discharge capacity.
　内部抵抗・外部抵抗（総和をＲとする。）による電圧降下が無視できないくらいに電流が大きい場合、放電特性は図２Ｂにおける低電流の場合（破線）から実線へと変化（正極電位は減少、負極電位は増加、電池電圧は減少）し、放電容量が減少する。従って、任意の放電電流に対する放電容量は、上記４つのパラメータに加えて抵抗Ｒにも依存している。抵抗Ｒは、電池の設計値、材料物性値、活物質表面被膜の抵抗などに依存している。このため、任意の放電電流に対する放電特性を求めるには、電池内部の電子・イオン伝導を記述する方程式を数値解法する計算プログラム、すなわち、電池シミュレータを用いる必要がある。 When the current is so large that the voltage drop due to the internal resistance / external resistance (the sum is R) cannot be ignored, the discharge characteristics change from the low current (broken line) to the solid line in FIG. 2B (the positive electrode potential decreases, The negative electrode potential increases and the battery voltage decreases), and the discharge capacity decreases. Accordingly, the discharge capacity for an arbitrary discharge current depends on the resistance R in addition to the above four parameters. The resistance R depends on the design value of the battery, the material property value, the resistance of the active material surface coating, and the like. For this reason, in order to obtain the discharge characteristics with respect to an arbitrary discharge current, it is necessary to use a calculation program that numerically solves an equation describing electron / ion conduction inside the battery, that is, a battery simulator.
　電池シミュレータに用いる方程式および入力パラメータ一覧は、例えば、非特許文献１に開示されている。当該方程式は、概略、下記のとおりである。 A list of equations and input parameters used in the battery simulator is disclosed in Non-Patent Document 1, for example. The equation is roughly as follows.
Figure JPOXMLDOC01-appb-M000004
Figure JPOXMLDOC01-appb-M000004
Figure JPOXMLDOC01-appb-M000005
Figure JPOXMLDOC01-appb-M000005
Figure JPOXMLDOC01-appb-M000006
Figure JPOXMLDOC01-appb-M000006
Figure JPOXMLDOC01-appb-M000007
Figure JPOXMLDOC01-appb-M000007
Figure JPOXMLDOC01-appb-M000008
Figure JPOXMLDOC01-appb-M000008
Figure JPOXMLDOC01-appb-M000009
Figure JPOXMLDOC01-appb-M000009
Figure JPOXMLDOC01-appb-M000010
Figure JPOXMLDOC01-appb-M000010
Figure JPOXMLDOC01-appb-M000011
Figure JPOXMLDOC01-appb-M000011
Figure JPOXMLDOC01-appb-M000012
Figure JPOXMLDOC01-appb-M000012
Figure JPOXMLDOC01-appb-M000013
Figure JPOXMLDOC01-appb-M000013
Figure JPOXMLDOC01-appb-M000014
Figure JPOXMLDOC01-appb-M000014
　これらの式において、εは電解液の体積分率、ｃは電解液濃度、ｔは時間、Ｄは電解液中のリチウムイオンの拡散係数、ｊｎは細孔壁流束、ｔ０ ＋は輸率、ｚ＋は電荷数、ν＋は解離した陽イオンの電解質１モル当たりの個数、Ｆはファラデー定数、Ｌは電池セルの厚さ、ａは活物質の比表面積、Ｉは全電流密度、ｉ１は電解液相の電流密度、ｉ２は固相の電流密度、Φ１は固相の電位、σは固相の伝導率、Φ２は電解液の電位、κは電解液の伝導率、Ｒは気体定数、Ｔは温度、ｆＡは塩の活量係数、ｓｉは電極反応における成分ｉの化学量論係数、ｒは活物質粒子における半径方向軸、ｃｓは固相におけるリチウムの濃度、Ｄｓは活物質粒子中のリチウムの拡散係数、Ｒｓは活物質粒子の半径、Ｕは開回路電圧、ｋは反応速度定数、αａ及びαｃは移動係数、Ｒｆは被膜抵抗である。有効活物質量比ｙは、比表面積ａをｙ倍することにより組み込まれる。 In these equations, ε is the volume fraction of the electrolyte, c is the electrolyte concentration, t is the time, D is the diffusion coefficient of lithium ions in the electrolyte, j n is the pore wall flux, and t 0 + is the transport. Rate, z + is the number of charges, ν + is the number of dissociated cations per mole of electrolyte, F is the Faraday constant, L is the battery cell thickness, a is the specific surface area of the active material, I is the total current density, i 1 is the current density of the electrolyte phase, i 2 is the current density of the solid phase, Φ 1 is the potential of the solid phase, σ is the conductivity of the solid phase, Φ 2 is the potential of the electrolyte, and κ is the conductivity of the electrolyte , R is the gas constant, T is the temperature, f A is the salt activity coefficient, s i is the stoichiometric coefficient of component i in the electrode reaction, r is the radial axis in the active material particle, c s is the lithium in the solid phase , D s is the diffusion coefficient of lithium in the active material particles, R s is the radius of the active material particles, U is the open circuit voltage, k is the reaction rate constant, α a and α c are transfer coefficients, and Rf is a film resistance. The effective active material amount ratio y is incorporated by multiplying the specific surface area a by y.
　＜二次電池の劣化後の放電特性と劣化パラメータ＞
　次に、劣化後の二次電池の放電特性を記述する劣化パラメータについて説明する。 <Discharge characteristics and deterioration parameters after secondary battery deterioration>
Next, deterioration parameters describing the discharge characteristics of the secondary battery after deterioration will be described.
　電池は、充電・放電の繰り返し使用に伴い、あるいは、使用せずに保存しておくだけでも、放電容量は減少し、放電直流抵抗は増加する。劣化の原因は、１つは充放電に利用できる実効的活物質量が減少することであり、もう１つは活物質表面の被膜が成長することにより充放電に利用できるリチウム量が減少すること及び被膜抵抗が増加することである。 電池 Batteries can be stored with repeated use of charge / discharge, or even if they are stored without being used, the discharge capacity decreases and the discharge DC resistance increases. One of the causes of deterioration is a decrease in the amount of effective active material that can be used for charging and discharging, and the other is that the amount of lithium that can be used for charging and discharging decreases due to the growth of the active material surface coating. And the film resistance is increased.
　図３Ａは劣化前の低放電電流における放電特性を示したものであり、図３Ｂは劣化後の低放電電流における放電特性を示したものである。従って、劣化による抵抗増加の効果は図では無視している。利用できる活物質量が減少することにより、放電中の正極電位特性及び負極電位特性が横軸の容量に関して縮小される。さらに、利用できるリチウム量が減少するため、電圧Ｖｈｉｇｈにおけるｘｐ及びｘｎが劣化前の値からずれる。図３Ｂでは、劣化によりｘｎが大きく増加した場合を示している。 FIG. 3A shows the discharge characteristics at a low discharge current before deterioration, and FIG. 3B shows the discharge characteristics at a low discharge current after deterioration. Therefore, the effect of increasing resistance due to deterioration is ignored in the figure. By reducing the amount of active material that can be used, the positive electrode potential characteristics and the negative electrode potential characteristics during discharge are reduced with respect to the capacity on the horizontal axis. Further, since the amount of lithium available is reduced, the x p and x n in the voltage V high deviates from the value before deterioration. FIG. 3B shows a case where xn greatly increases due to deterioration.
　劣化現象の１つ目の原因である活物質量の減少は、シミュレータの入力パラメータ中の有効活物質量比ｙｐ及びｙｎの減少により記述できる。２つ目の原因であるリチウム量減少と抵抗増大のうちリチウム量減少は、放電開始時電圧ＶｈｉｇｈにおけるＬｉ化学量論比ｘｐ及びｘｎが劣化前の値からずれることにより記述できる。抵抗増加は、被膜抵抗Ｒｆの増加で記述できる。あるいは、被膜の成長よりも電解液の劣化の方が顕著な場合、電解液抵抗を劣化パラメータとしても良い。 Reduction of first causes a is the amount of active material deterioration phenomenon can be described by a reduction in the effective amount of the active material ratio y p and y n in the input parameter of the simulator. The decrease in the amount of lithium among the decrease in the amount of lithium and the increase in resistance, which are the second cause, can be described by the deviation of the Li stoichiometric ratios x p and x n at the discharge start voltage V high from the values before deterioration. The increase in resistance can be described by an increase in the film resistance Rf. Alternatively, when the deterioration of the electrolytic solution is more significant than the growth of the coating, the electrolytic solution resistance may be used as the deterioration parameter.
　従って、これら５つのパラメータが電池の劣化状態を記述するために最低限必要なパラメータであり、劣化後の任意の放電電流に対する放電容量は、これら５つのパラメータをシミュレータに入力して放電特性を計算することによって予測できる。 Therefore, these five parameters are the minimum necessary parameters to describe the deterioration state of the battery, and the discharge capacity for any discharge current after deterioration is calculated by inputting these five parameters into the simulator. Can be predicted.
　図４Ａは、初期電池の低電流（０．１Ｃレート）及び高電流（１０Ｃレート）における放電特性のフィッティング結果を示したものである。低電流及び高電流の計算においては、放電電流以外のパラメータは共通である。 FIG. 4A shows the fitting results of the discharge characteristics of the initial battery at low current (0.1 C rate) and high current (10 C rate). In the calculation of the low current and the high current, parameters other than the discharge current are common.
　図４Ｂは、劣化後の電池の低電流及び高電流における放電特性のフィッティング結果を示したものである。 FIG. 4B shows the fitting results of the discharge characteristics at low current and high current of the battery after deterioration.
　放電初期特性及び劣化後の特性ともに、上記５つのパラメータをフィッティングパラメータとして用いることでフィッティング可能である。上記５つのパラメータのうち、被膜抵抗以外の４つは、抵抗成分の小さい低電流放電特性のフィッティングから抽出する。この際、計算結果は被膜抵抗にはほとんど依存しないので、入力パラメータのＲｆは適当な値あるいは０を入力しておく。次に、得られた４つのパラメータを固定して、高電流放電特性のフィッティングから被膜抵抗を抽出する。 Both the initial discharge characteristics and the characteristics after deterioration can be fitted by using the above five parameters as fitting parameters. Of the above five parameters, four other than the film resistance are extracted from the fitting of the low current discharge characteristic with a small resistance component. At this time, since the calculation result hardly depends on the film resistance, an appropriate value or 0 is input for the input parameter Rf. Next, the obtained four parameters are fixed, and the film resistance is extracted from the fitting of the high current discharge characteristics.
　なお、実測に用いた二次電池は、１８６５０型電池（リチウムイオン二次電池）であり、その負極は炭素系であり、正極は三元系（Ｎｉ、Ｍｎ、Ｃｏ）である。 The secondary battery used for the actual measurement is a 18650 type battery (lithium ion secondary battery), the negative electrode is carbon-based, and the positive electrode is ternary (Ni, Mn, Co).
　表１は、パラメータフィッティングにより抽出した劣化前電池と劣化後電池の５つの劣化パラメータの例を示したものである。同じ手順で、異なる劣化状態ごとに、それに対応した５つの劣化パラメータが１組得られる。 Table 1 shows an example of five deterioration parameters of the pre-deterioration battery and the post-deterioration battery extracted by parameter fitting. In the same procedure, a set of five deterioration parameters corresponding to different deterioration states is obtained.
Figure JPOXMLDOC01-appb-T000015
 　従って、現時点以降の劣化パラメータの時間変化を予測できれば、そのパラメータをシミュレータの入力値として用いることにより将来の放電特性が予測できることになる。
Figure JPOXMLDOC01-appb-T000015
 Therefore, if the time change of the deterioration parameter after the present time can be predicted, the future discharge characteristics can be predicted by using the parameter as an input value of the simulator.
　図５は、有効活物質量比ｙの時間変化を示す説明図である。横軸は電池使用時間ｔである。抽出値は単調な時間依存性を示しており、単純な関数式でフィッティングできる。 FIG. 5 is an explanatory diagram showing the change over time in the effective active material amount ratio y. The horizontal axis represents the battery usage time t. The extracted value shows a monotonous time dependence and can be fitted with a simple function expression.
　本図では、指数関数の時間依存性を持つ下記式（１５）を用いてフィッティングした例を示した。 This figure shows an example of fitting using the following formula (15) having time dependence of the exponential function.
Figure JPOXMLDOC01-appb-M000016
Figure JPOXMLDOC01-appb-M000016
　ここで、ｙ（０）は有効活物質量比の初期値である。係数ＡとＢが決まれば、（４）式を用いて長時間後の有効活物質量比を予測できる。 Here, y (0) is the initial value of the effective active material amount ratio. If the coefficients A and B are determined, the effective active material amount ratio after a long time can be predicted using the equation (4).
　図６は、放電開始時のＬｉ化学量論比ｘの時間変化を示す説明図である。抽出値は単調な時間依存性を示しており、単純な関数式でフィッティングできる。 FIG. 6 is an explanatory diagram showing the change over time in the Li stoichiometric ratio x at the start of discharge. The extracted value shows a monotonous time dependence and can be fitted with a simple function expression.
　本図では、指数関数の時間依存性を持つ下記式（１６）を用いてフィッティングした例を示した。 This figure shows an example of fitting using the following formula (16) having time dependence of the exponential function.
Figure JPOXMLDOC01-appb-M000017
Figure JPOXMLDOC01-appb-M000017
　ここで、ｘ（０）は放電開始時のＬｉ化学量論比の初期値である。係数Ｃ及びＤが決まれば、上記式（１６）を用いて長時間後のＬｉ化学量論比を予測できる。 Where x (0) is the initial value of the Li stoichiometry at the start of discharge. If the coefficients C and D are determined, the Li stoichiometry after a long time can be predicted using the above equation (16).
　図７は、被膜抵抗Ｒｆの時間変化を示す説明図である。抽出値は単調な時間依存性を示しており、単純な関数式でフィッティングできる。 FIG. 7 is an explanatory diagram showing the change over time of the film resistance Rf. The extracted value shows a monotonous time dependence and can be fitted with a simple function expression.
　本図では、線形の時間依存性を持つ下記式（１７）を用いてフィッティングした結果を示した。 This figure shows the result of fitting using the following equation (17) having linear time dependence.
Figure JPOXMLDOC01-appb-M000018
Figure JPOXMLDOC01-appb-M000018
　ここで、Ｒｆ（０）は劣化前の被膜抵抗である。係数Ｅが決まれば、上記式（１７）を用いて長時間後の被膜抵抗を予測できる。 Here, Rf (0) is the film resistance before deterioration. If the coefficient E is determined, the film resistance after a long time can be predicted using the above equation (17).
　図８は、上記式（１５）～（１７）を用いて劣化パラメータを計算し、得られた劣化パラメータを入力パラメータにして低電流（０．１Ｃレート）及び高電流（１０Ｃレート）の放電シミュレーションを行って求めた放電容量維持率について実測値と比較した結果を示す説明図である。予測精度の検証のため、劣化パラメータの抽出を行った使用期間以後の実測値もプロットしてある。 FIG. 8 shows a calculation of deterioration parameters using the above equations (15) to (17), and discharge simulation of low current (0.1 C rate) and high current (10 C rate) using the obtained deterioration parameters as input parameters. It is explanatory drawing which shows the result compared with the measured value about the discharge capacity maintenance factor calculated | required by performing. In order to verify the prediction accuracy, the measured values after the use period in which the deterioration parameters are extracted are also plotted.
　予測結果は実測値と良い一致を示している。容量維持率に関する寿命判定基準を、例えば６０％とすると、容量維持率が６０％を切る時刻が寿命であり、現時刻ｔ０との差ｔ０．１Ｃ、ｔ１０Ｃが、０．１Ｃ放電及び１０Ｃ放電に対する余寿命となる。 The prediction result shows a good agreement with the actual measurement value. Assuming that the life criterion for the capacity maintenance rate is 60%, for example, the time when the capacity maintenance rate falls below 60% is the life, and the differences t 0.1C and t 10C from the current time t 0 are 0.1C discharge and The remaining life for 10 C discharge is obtained.
　本図では、０．１Ｃ及び１０Ｃの放電容量維持率の例のみを示しているが、シミュレーションの入力値である放電電流を変えるだけで任意の放電レートに対する放電容量維持率及び余寿命を計算することができる。 In this figure, only examples of discharge capacity maintenance rates of 0.1 C and 10 C are shown, but the discharge capacity maintenance rate and remaining life for an arbitrary discharge rate are calculated simply by changing the discharge current that is the input value of the simulation. be able to.
　図９は、上記式（１５）～（１７）を用いて劣化パラメータを計算し、得られた劣化パラメータを入力パラメータにして求めたＳＯＣ５０％における直流抵抗増加率を、実測値と比較した結果を示したものである。予測精度の検証のため、劣化パラメータ抽出に用いた電池使用期間以降の実測値もプロットしてある。 FIG. 9 shows the results of calculating the degradation parameter using the above equations (15) to (17) and comparing the DC resistance increase rate at 50% SOC obtained using the obtained degradation parameter as an input parameter with the actual measurement value. It is shown. For verification of the prediction accuracy, the measured values after the battery use period used for extracting the deterioration parameters are also plotted.
　予測結果は実測値と良い一致を示している。直流抵抗増加率に関する寿命判定基準を、例えば１５０％とすると、直流抵抗増加率が１５０％を超える時刻が寿命であり、現時刻ｔ０との差ｔＤＣＲが余寿命となる。 The prediction result shows a good agreement with the actual measurement value. Life criteria for the DC resistance increase rate, for example, to 150%, the time that the DC resistance increase rate is more than 150% is the life, the difference t DCR between the current time t 0 is the remaining life.
　図１０は、上記式（１５）～（１７）を用いて劣化パラメータを計算し、得られた劣化パラメータを入力パラメータにして求めた出力維持率を、実測値と比較した結果である。ここでは、出力Ｐは、ＳＯＣ５０％に対して定義し、下記式（１８）で計算した。 FIG. 10 shows the result of calculating the degradation parameter using the above formulas (15) to (17), and comparing the output retention rate obtained using the obtained degradation parameter as the input parameter with the actual measurement value. Here, the output P was defined with respect to SOC 50%, and was calculated by the following formula (18).
Figure JPOXMLDOC01-appb-M000019
 　ここで、Ｖ５０％はＳＯＣ＝５０％におけるＯＣＶ、Ｖｌｏｗは設定下限電圧、ＲＤＣＲは直流抵抗である。出力維持率とは、劣化後の出力を劣化前の出力で規格化した値である。出力維持率に関する寿命の判定基準を、例えば６０％とすると、出力維持率が６０％を切る時刻が寿命であり、現時刻との差ｔｐｏｗｅｒが余寿命となる。
Figure JPOXMLDOC01-appb-M000019
 Here, V 50% is an OCV at SOC = 50%, V low is a set lower limit voltage, and R DCR is a direct current resistance. The output maintenance ratio is a value obtained by normalizing the output after deterioration with the output before deterioration. Assuming that the life criterion for the output maintenance ratio is 60%, for example, the time when the output maintenance ratio falls below 60% is the life, and the difference t power from the current time is the remaining life.
　本発明は、電池の劣化状態が上記５つの劣化パラメータにより記述できるということ、及びこれら５つの劣化パラメータは単調な時間依存性を示しており時間依存性を決めれば長時間後の値を予測できる結果に基づき、５つの劣化パラメータを入力パラメータとしたシミュレーションによって劣化後の任意の放電電流に対する放電特性を計算することによって、放電容量維持率、放電直流抵抗増加率又は出力維持率に関する余寿命を予測する方法及び装置を提供するものである。以下において、各実施の形態を具体的に説明する。 In the present invention, the deterioration state of the battery can be described by the above five deterioration parameters, and these five deterioration parameters show a monotonous time dependency, and the value after a long time can be predicted if the time dependency is determined. Based on the results, the remaining life related to the discharge capacity maintenance rate, discharge DC resistance increase rate, or output maintenance rate is predicted by calculating the discharge characteristics for any discharge current after deterioration by simulation using five deterioration parameters as input parameters. A method and apparatus are provided. Each embodiment will be specifically described below.
　［実施の形態１］
　本実施の形態１による二次電池の余寿命診断方法および余寿命診断装置について、図１１及び図１２を用いて説明する。 [Embodiment 1]
The remaining battery life diagnosis method and remaining life diagnosis apparatus according to the first embodiment will be described with reference to FIGS. 11 and 12.
　図１１は、本実施の形態による二次電池の余寿命診断装置の概略構成の一例を示すブロック図である。 FIG. 11 is a block diagram showing an example of a schematic configuration of a secondary battery remaining life diagnosis apparatus according to the present embodiment.
　装置は、二次電池１０、制御部２０、電圧センサ３０、電流センサ４０、演算部５０、表示部６０及びタイマ７０を備えた構成である。 The apparatus includes a secondary battery 10, a control unit 20, a voltage sensor 30, a current sensor 40, a calculation unit 50, a display unit 60, and a timer 70.
　電圧センサ３０は、二次電池１０から出力される電池電圧を測定する。電流センサ４０は、二次電池１０から出力される電池電流を測定する。これらの電圧センサ３０及び電流センサ４０は、検出器として機能する。以下では、電圧センサ３０による測定値をＶと表記し、電流センサ４０による測定値をＩと表記する。電圧センサ３０及び電流センサ４０によってそれぞれ測定された電池電圧Ｖ、電池電流Ｉは、演算部５０へ送出される。 The voltage sensor 30 measures the battery voltage output from the secondary battery 10. The current sensor 40 measures the battery current output from the secondary battery 10. These voltage sensor 30 and current sensor 40 function as a detector. Hereinafter, the measurement value obtained by the voltage sensor 30 is denoted as V, and the measurement value obtained by the current sensor 40 is denoted as I. The battery voltage V and the battery current I measured by the voltage sensor 30 and the current sensor 40 are sent to the calculation unit 50.
　図１２は、図１１の演算部５０の概略構成の一例を示すブロック図である。 FIG. 12 is a block diagram showing an example of a schematic configuration of the calculation unit 50 of FIG.
　演算部５０は、演算器８０と、劣化パラメータの履歴及び劣化パラメータ関数式の係数Ａ～Ｅを格納する不揮発メモリ９０と、材料パラメータ、構造パラメータ、劣化パラメータ関数式、劣化パラメータ初期値、２つの測定電流値Ｉ１、Ｉ２（Ｉ１＜Ｉ２）、寿命推定電流値リスト、寿命推定電流値リストに対応した放電容量初期値、直流抵抗初期値、診断時刻及び時間刻みΔｔを格納するＲＯＭ１００（単に「メモリ」ともいう。）とを備えた構成である。ここで、寿命推定電流値リストとは、放電容量維持率を計算する放電電流値のリストであり、低電流から高電流までの複数の電流値が含まれている。 The arithmetic unit 50 includes an arithmetic unit 80, a non-volatile memory 90 for storing deterioration parameter history and coefficients A to E of the deterioration parameter function, material parameters, structure parameters, deterioration parameter function expressions, deterioration parameter initial values, ROM 100 for storing measured current values I 1 , I 2 (I 1 <I 2 ), life estimation current value list, discharge capacity initial value corresponding to life estimation current value list, DC resistance initial value, diagnosis time, and time increment Δt (Also simply referred to as “memory”). Here, the life estimation current value list is a list of discharge current values for calculating the discharge capacity maintenance rate, and includes a plurality of current values from low current to high current.
　演算器８０は、放電特性を計算し、パラメータフィッティングを行い、二次電池１０の劣化パラメータである有効活物質量比、放電開始時Ｌｉ化学量論比及び被膜抵抗を抽出し、余寿命を計算する。 The computing unit 80 calculates discharge characteristics, performs parameter fitting, extracts the effective active material amount ratio, Li stoichiometry ratio at the start of discharge, and film resistance, which are deterioration parameters of the secondary battery 10, and calculates the remaining life. To do.
　表示部６０は、演算器８０で算出した余寿命を表示する。 The display unit 60 displays the remaining life calculated by the computing unit 80.
　二次電池１０は、単位電池セルを単数もしくは複数接続して電池としたものであり、以下、本明細書では、二次電池１０として説明する。また、以下の説明では、リチウムイオン電池を二次電池１０の例とする。 The secondary battery 10 is a battery formed by connecting one or a plurality of unit battery cells, and will be described as the secondary battery 10 in the present specification. In the following description, a lithium ion battery is taken as an example of the secondary battery 10.
　＜余寿命予測方法＞
　図１３は、図１２の演算装置５０が二次電池１０の余寿命を診断する余寿命診断方法の一例を示すフローチャートである。 <Remaining life prediction method>
FIG. 13 is a flowchart illustrating an example of a remaining life diagnosis method in which the arithmetic device 50 in FIG. 12 diagnoses the remaining life of the secondary battery 10.
　二次電池１０の使用開始後、演算器８０は、ステップＳ１により、ＲＯＭ１００から診断時刻、２つの放電電流値Ｉ１、Ｉ２、及び時間刻みΔｔを読み込む。 After the use of the secondary battery 10 is started, the computing unit 80 reads the diagnosis time, the two discharge current values I 1 and I 2 , and the time increment Δt from the ROM 100 in step S1.
　次に、ステップＳ１０により、タイマ７０から使用開始後の経過時間ｔ０を読み込む。 Next, in step S10, it reads the elapsed time t 0 after the start of use from the timer 70.
　次に、ステップＳ２０により、現在時刻ｔ０が診断時刻か否かを判定し、診断時刻でない場合（Ｓ２０－Ｎｏ）はステップＳ８０に進む。診断時間である場合（Ｓ２０－Ｙｅｓ）、ステップＳ３０に進む。このステップＳ３０において、演算器８０による計測指示により、制御部２０は、電池１０を一旦上限電圧Ｖｈｉｇｈまで定電流定電圧充電した後、下限電圧Ｖｌｏｗまでの低放電電流Ｉ１の放電、続いて再び上限電圧Ｖｈｉｇｈまで定電流定電圧充電した後、下限電圧Ｖｌｏｗまでのそれより大きい高電流Ｉ２での放電を行わせる。タイマ７０、電流センサ４０、電圧センサ３０から、それぞれ時間、電流、電圧のデータを読み込み、実測放電特性データに変換する。 Next, in step S20, the present time t 0 is determined whether diagnosis time, if not diagnosed time (S20-No), the process proceeds to step S80. If it is the diagnosis time (S20-Yes), the process proceeds to step S30. In this step S30, according to a measurement instruction from the computing unit 80, the control unit 20 once charges the battery 10 at a constant current and a constant voltage to the upper limit voltage V high, and then discharges the low discharge current I 1 to the lower limit voltage V low , and then continues. Then, after charging with constant current and constant voltage again to the upper limit voltage V high , discharge with a higher current I 2 higher than that until the lower limit voltage V low is performed. Time, current, and voltage data are read from the timer 70, the current sensor 40, and the voltage sensor 30, respectively, and converted into measured discharge characteristic data.
　次に、演算器８０は、ステップＳ４０により、正極と負極それぞれの有効活物質量比ｘ、放電開始時Ｌｉ化学量論比ｙをフィッティングパラメータとしたシミュレーションにより低電流Ｉ１の放電特性を計算し、実測放電特性データとのフィッティングを行って、正極及び負極それぞれの有効活物質量比ｘ、放電開始時Ｌｉ化学量論比ｙを抽出する。フィッティング方法は、計算値と実測値との差を最小化する適当なパラメータ探索法を用いる。 Next, in step S40, the computing unit 80 calculates the discharge characteristics of the low current I 1 by simulation using the effective active material amount ratio x of the positive electrode and the negative electrode and the Li stoichiometric ratio y at the start of discharge as fitting parameters. Then, fitting with the measured discharge characteristic data is performed to extract the effective active material amount ratio x and the Li stoichiometry ratio y at the start of discharge for each of the positive electrode and the negative electrode. As the fitting method, an appropriate parameter search method that minimizes the difference between the calculated value and the actually measured value is used.
　次に、演算器８０は、ステップＳ５０により、ステップＳ４０で求めた有効活物質量比ｘ、放電開始時Ｌｉ化学量論比ｙを入力し、被膜抵抗をフィッティングパラメータとしたシミュレーションにより高電流Ｉ２の放電特性を計算し、実測放電特性データとのフィッティングを行って、被膜抵抗Ｒｆを抽出する。 Next, in step S50, the computing unit 80 inputs the effective active material amount ratio x and the discharge start Li stoichiometric ratio y obtained in step S40, and performs high current I 2 by simulation using the film resistance as a fitting parameter. The discharge characteristic is calculated, and fitting with the measured discharge characteristic data is performed to extract the film resistance Rf.
　次に、演算器８０は、ステップＳ６０により、ステップＳ４０及びＳ５０で抽出した劣化パラメータを時刻ｔ０とともに不揮発メモリ９０に書き込むとともに、全履歴を読み込む。 Next, the arithmetic unit 80, in step S60, writes the deterioration parameter extracted at step S40 and S50 together with the time t 0 in the nonvolatile memory 90, reads the entire history.
　次に、演算器８０は、ステップＳ７０により、まず、有効活物質量比ｙに対しては、ステップＳ６０で読み込んだ診断時刻ｔとｙとの組に、上記式（１５）を最小二乗法によりフィッティングし、係数Ａ、Ｂを抽出する。 Next, in step S70, the computing unit 80 first converts the above equation (15) into the set of the diagnosis times t and y read in step S60 by the least square method for the effective active material amount ratio y. Fitting is performed, and coefficients A and B are extracted.
　放電開始時Ｌｉ化学量論比ｘに対しては、ステップＳ６０で読み込んだ診断時刻ｔとｘの組に、上記式（１６）を最小二乗法によりフィッティングし、係数Ｃ、Ｄを抽出する。 For the Li stoichiometric ratio x at the start of discharge, the above equation (16) is fitted to the set of the diagnosis times t and x read in step S60 by the least square method, and the coefficients C and D are extracted.
　被膜抵抗Ｒｆに対しては、ステップＳ６０で読み込んだ診断時刻ｔとＲｆの組に、上記式（１７）を最小二乗法によりフィッティングし、係数Ｅを抽出する。 For the film resistance Rf, the equation (17) is fitted to the set of the diagnosis times t and Rf read in step S60 by the least square method, and the coefficient E is extracted.
　あらかじめ組み込んでおく関数式は、上記式（１５）～（１７）以外の対数式、多項式などでも良い。組み込む式及び係数の個数に応じて、ステップＳ６０で用いる式及び決めるべき係数の個数は変わる。 The function formula to be incorporated in advance may be a logarithmic expression, polynomial, etc. other than the above formulas (15) to (17). The number of equations used in step S60 and the number of coefficients to be determined vary depending on the number of equations and coefficients to be incorporated.
　ステップＳ２０により、診断時刻ではないと判断した場合、ステップＳ８０により、ユーザが余寿命診断を要求しているか否かを判定し、要求していない場合（Ｓ８０－Ｎｏ）はスタートに戻る。余寿命診断を要求している場合（Ｓ８０－Ｙｅｓ）は、ステップＳ９０により、不揮発メモリ９０から劣化パラメータ関数式の係数Ａ～Ｅを読み込む。 If it is determined in step S20 that it is not the diagnosis time, it is determined in step S80 whether or not the user has requested a remaining life diagnosis. If not (S80-No), the process returns to the start. If the remaining life diagnosis is requested (S80-Yes), the coefficients A to E of the deterioration parameter function formula are read from the nonvolatile memory 90 in step S90.
　次に、演算器８０は、ステップＳ１００～ステップＳ１４０において寿命を計算する。 Next, the computing unit 80 calculates the lifetime in steps S100 to S140.
　まず、ステップＳ１００において、計算する時刻ｔ１をΔｔに設定する。 First, in step S100, it sets the time t 1 to calculate the Delta] t.
　次に、ステップＳ１１０において、時刻ｔ１における劣化パラメータを上記式（１５）～（１７）に基づいて計算する。 Next, in step S110, the deterioration parameter at time t 1 is calculated based on the equation (15) to (17).
　次に、ステップＳ１２０において、ＲＯＭ１００から、寿命推定に用いる放電電流値リストを読み込む。 Next, in step S120, a discharge current value list used for life estimation is read from the ROM 100.
　次に、計算した劣化パラメータをシミュレータの入力値として、ステップＳ１３０において、時刻ｔ１における放電電流値リストに含まれる電流値に対する放電容量及び放電直流抵抗を計算し、メモリ１００から対応する電流値の放電容量初期値と直流抵抗初期値を読み込んで、容量維持率及び直流抵抗増加率に換算する。 Then, the calculated deterioration parameter as input to the simulator, in step S130, the discharge capacity and discharge DC resistance against current value included in the discharge current value list at time t 1 is calculated and the corresponding current value from the memory 100 The discharge capacity initial value and the direct current resistance initial value are read and converted into a capacity maintenance rate and a direct current resistance increase rate.
　次に、ステップＳ１４０において、寿命判定を行う。寿命推定を行うすべての電流値に対する容量維持率および放電直流抵抗増加率が寿命判定基準を越えている場合（Ｓ１４０－Ｙｅｓ）、ステップＳ１５０に進む。１つでも寿命判定基準を越えていない場合（Ｓ１４０－Ｎｏ）、時刻をΔｔだけ更新し、ステップＳ１１０に戻り、計算を繰り返す。 Next, in step S140, life determination is performed. When the capacity maintenance rate and the discharge DC resistance increase rate for all current values for which the life estimation is performed exceed the life criterion, the process proceeds to step S150. If even one does not exceed the life criterion (S140-No), the time is updated by Δt, the process returns to step S110, and the calculation is repeated.
　次に、ステップＳ１５０において、各放電電流値に対する放電容量維持率に関する余寿命、及び放電直流抵抗維持率に関する余寿命を計算する。寿命は、寿命判定基準をまたぐ前後２つの時刻におけるデータを内挿補間して求める。寿命となる時刻をすでに過ぎている場合には、余寿命は負の値となる。 Next, in step S150, the remaining life related to the discharge capacity maintenance rate and the remaining life related to the discharge DC resistance maintenance rate for each discharge current value are calculated. The lifetime is obtained by interpolating data at two times before and after the lifetime criterion. If the time when the life is reached has already passed, the remaining life is a negative value.
　最後に、ステップＳ１６０において、放電電流ごとの容量維持率余寿命及び放電直流抵抗増加率余寿命を、表示部６０に表示し、スタートへ戻る。 Finally, in step S160, the capacity maintenance rate remaining life and discharge DC resistance increase rate remaining life for each discharge current are displayed on the display unit 60, and the process returns to the start.
　＜実施の形態１の効果＞
　以上のように、本実施の形態１によれば、二種の異なる放電レートの放電特性から抽出した劣化パラメータの電池使用時間依存性を元に、任意の時刻における劣化パラメータを推定し、推定した劣化パラメータを入力とするシミュレーションにより放電特性を計算し、余寿命を推定することができる。
［実施の形態２］
　本実施の形態２による二次電池の余寿命診断方法および余寿命診断装置について、図１４及び１５を用いて説明する。以下においては上記実施の形態１と異なる点を主に説明する。 <Effect of Embodiment 1>
As described above, according to the first embodiment, the deterioration parameter at an arbitrary time is estimated and estimated based on the battery usage time dependency of the deterioration parameter extracted from the discharge characteristics of two different discharge rates. It is possible to estimate the remaining life by calculating the discharge characteristics by simulation with the deterioration parameter as an input.
[Embodiment 2]
The remaining battery life diagnosis method and remaining life diagnosis apparatus according to the second embodiment will be described with reference to FIGS. In the following, differences from the first embodiment will be mainly described.
　図１４は、演算部５０の概略構成の一例を示すブロック図である。 FIG. 14 is a block diagram illustrating an example of a schematic configuration of the calculation unit 50.
　演算部５０は、演算器８１と、劣化パラメータの履歴、劣化パラメータ関数式の係数Ａ～Ｅ、及び前回の測定電流値を格納する不揮発メモリ９１と、材料パラメータ、構造パラメータ、劣化パラメータ関数式、劣化パラメータ初期値、出力初期値、２つの充電電流値、及び時間刻みを格納するＲＯＭ１０１（単に「メモリ」ともいう。）とを備えた構成である。 The computing unit 50 includes a computing unit 81, a history of degradation parameters, coefficients A to E of degradation parameter function formulas, and a non-volatile memory 91 for storing previous measurement current values, material parameters, structural parameters, degradation parameter function formulas, This is a configuration including a ROM 101 (also simply referred to as “memory”) that stores a deterioration parameter initial value, an output initial value, two charging current values, and time increments.
　＜余寿命予測方法＞
　本実施の形態２では、二つの異なった電流に対する充電特性から劣化パラメータを抽出する。電池の使用中に放電特性を測定することが困難な、電気自動車などに搭載された電池の場合、充電時の充電特性をパラメータ抽出に用いることができる。一回の充電の際に、充電電流を変えた二つの充電特性を測定することは困難であるため、充電電流の異なる二回の充電の充電特性から１組の劣化パラメータを得る。 <Remaining life prediction method>
In the second embodiment, the deterioration parameter is extracted from the charging characteristics for two different currents. In the case of a battery mounted on an electric vehicle or the like where it is difficult to measure the discharge characteristics during use of the battery, the charging characteristics during charging can be used for parameter extraction. Since it is difficult to measure two charging characteristics with different charging currents during one charging, a set of deterioration parameters is obtained from the charging characteristics of two chargings with different charging currents.
　図１５は、演算部５０が二次電池１０の余寿命を診断する余寿命診断方法の一例を示すフローチャートである。 FIG. 15 is a flowchart illustrating an example of a remaining life diagnosis method in which the calculation unit 50 diagnoses the remaining life of the secondary battery 10.
　演算器８１が、ステップＳ２により、充電要求があるかどうかを判定し、充電要求がない場合（Ｓ８０－Ｎｏ）、スタートに戻る。充電要求がある場合（Ｓ８０－Ｙｅｓ）、ステップ３に進む。 The computing unit 81 determines in step S2 whether there is a charge request, and if there is no charge request (S80-No), the process returns to the start. If there is a charge request (S80-Yes), the process proceeds to step 3.
　次に、ステップＳ３により、不揮発メモリ９１から前回の充電電流値を読み込むとともに、ＲＯＭ１０１から２つの充電電流値Ｉ１、Ｉ２（Ｉ１＜Ｉ２）を読み込み、前回とは異なる充電電流値を今回の充電電流値として決定する。 Next, in step S3, the previous charging current value is read from the nonvolatile memory 91, and the two charging current values I 1 and I 2 (I 1 <I 2 ) are read from the ROM 101, and the charging current value different from the previous charging current value is read. This is determined as the current charging current value.
　次に、ステップＳ１０により、タイマ７０から使用開始後の経過時間ｔ０を読み込む。 Next, in step S10, it reads the elapsed time t 0 after the start of use from the timer 70.
　次に、ステップＳ１１により、演算器８１による計測指示により、制御部２０は、電池１０を一旦下限電圧Ｖｌｏｗまで放電する。 Next, in step S11, the control unit 20 discharges the battery 10 to the lower limit voltage V low once according to a measurement instruction from the computing unit 81.
　次に、ステップＳ２１により、今回の充電電流値が小電流Ｉ１（低電流）か大電流Ｉ２（高電流）か判定し、小電流の場合（Ｓ２１－Ｙｅｓ）、ステップＳ３１に進む。大電流の場合（Ｓ２１－Ｎｏ）、ステップＳ３２に進む。 Next, in step S21, it is determined whether the current charging current value is a small current I 1 (low current) or a large current I 2 (high current). If the current value is small (S21—Yes), the process proceeds to step S31. If the current is large (S21-No), the process proceeds to step S32.
　ステップＳ３１に進む場合、演算器８１は、ステップＳ３１により、充電電流Ｉ１の充電を行わせ、タイマ７０、電流センサ４０及び電圧センサ３０から、それぞれ時間、電流、電圧のデータを読み込み、充電特性データに変換する。 The operation proceeds to step S31, the calculator 81, in step S31, to perform the charging of the charging current I 1, the timer 70, current sensor 40 and voltage sensor 30, respectively time, read current, the data voltage, charge characteristic Convert to data.
　次に、演算器８１は、ステップＳ４１により、ＲＯＭ１０１から材料パラメータ、構造パラメータを読み込み、有効活物質量比ｘ及び充電開始時Ｌｉ化学量論比ｙをフィッティングパラメータとして、充電電流Ｉ１の充電特性を計算し、充電特性データとのフィッティングを行って、有効活物質量比ｘ及び充電開始時Ｌｉ化学量論比ｙを抽出する。 Next, the arithmetic unit 81, in step S41, the material parameters from ROM 101, reads the structural parameters, an effective amount of the active material ratio x and charging starts Li stoichiometry y as fitting parameters, charging characteristics of the charging current I 1 And fitting with charging characteristic data to extract the effective active material amount ratio x and the Li start stoichiometric ratio y.
　次に、演算器８１は、ステップＳ５１により、時刻ｔ０、有効活物質量比ｘ及び充電開始時Ｌｉ化学量論比ｙを不揮発メモリ９１に書き込む。 Next, the calculator 81 writes the time t 0 , the effective active material amount ratio x, and the charging start Li stoichiometry ratio y in the nonvolatile memory 91 in step S 51.
　次に、演算器８１は、ステップＳ６１により、ＲＯＭ１０１から劣化パラメータ関数式（上記式（１５）及び（１６））並びに有効活物質量比ｘ及び充電開始時Ｌｉ化学量論比ｙの初期値を読み込む。 Next, in step S61, the computing unit 81 obtains initial values of the degradation parameter function formulas (the above formulas (15) and (16)), the effective active material amount ratio x, and the charging start Li stoichiometric ratio y from the ROM 101. Read.
　次に、演算器８１は、ステップＳ７１により、有効活物質量比ｘ及び充電開始時Ｌｉ化学量論比ｙの時間履歴を不揮発メモリ９１から読み込み、フィッティングによりパラメータＡ～Ｄを抽出して、不揮発メモリ９１に書き込み、スタートに戻る。 Next, in step S71, the computing unit 81 reads the time history of the effective active material amount ratio x and the Li stoichiometry ratio y at the start of charging from the nonvolatile memory 91, extracts parameters A to D by fitting, Write to memory 91 and return to start.
　ステップＳ３２に進んだ場合、演算器８１は、ステップＳ３２により、充電電流Ｉ２の充電を行わせ、タイマ７０、電流センサ４０及び電圧センサ３０から、それぞれ時間、電流、電圧のデータを読み込み、充電特性データに変換する。 When step S32, the calculator 81, in step S32, to perform the charging of the charging current I 2, from the timer 70, current sensor 40 and voltage sensor 30, respectively time, read current, the data voltage, charge Convert to characteristic data.
　次に、演算器８１は、ステップＳ４２により、ＲＯＭ１０１から劣化パラメータ関数式（上記式（１７））および劣化パラメータＲｆの初期値を読み込む。 Next, the calculator 81 reads the deterioration parameter function equation (the above equation (17)) and the initial value of the deterioration parameter Rf from the ROM 101 in step S42.
　次に、演算器８１は、ステップＳ５２により、不揮発メモリ９１から劣化パラメータ関数式の係数Ａ～Ｄを読み込み、現時刻の有効活物質量比ｘ及び充電開始時Ｌｉ化学量論比ｙを計算する。 Next, in step S52, the calculator 81 reads the coefficients A to D of the deterioration parameter function equation from the nonvolatile memory 91, and calculates the effective active material amount ratio x and the charge start Li stoichiometry ratio y at the current time. .
　次に、演算器８１は、ステップＳ７２により、ＲＯＭ１０１から材料パラメータ及び構造パラメータを読み込み、現時刻の有効活物質量比ｘ及び充電開始時Ｌｉ化学量論比ｙをシミュレータの入力値として、被膜抵抗Ｒｆをフィッティングパラメータとして、充電電流Ｉ２の充電特性を計算し、充電特性データとのフィッティングを行って、被膜抵抗Ｒｆを抽出する。 Next, in step S72, the computing unit 81 reads the material parameter and the structural parameter from the ROM 101, and uses the effective active material amount ratio x and the charging start Li stoichiometric ratio y as input values of the simulator to the film resistance. the Rf as fitting parameters, calculates the charging characteristics of the charging current I 2, performed fitting the charge characteristic data, to extract the film resistor Rf.
　次に、演算器８１は、ステップＳ８１により、時刻ｔ０と被膜抵抗Ｒｆを不揮発メモリ９１に書き込む。 Next, the arithmetic unit 81, the step S81, and writes the time t 0 and the film resistor Rf in the nonvolatile memory 91.
　次に、演算器８１は、ステップＳ９１により、不揮発メモリ９１に格納されている時刻ｔ及び劣化パラメータＲｆの履歴を読み込み、ＲＯＭ１０１から劣化パラメータ関数式（上記式（１７））を読み込み、係数Ｅを抽出して、不揮発メモリ９１に書き込む。 Next, in step S91, the calculator 81 reads the history of the time t and the deterioration parameter Rf stored in the nonvolatile memory 91, reads the deterioration parameter function equation (the above equation (17)) from the ROM 101, and calculates the coefficient E. Extracted and written into the nonvolatile memory 91.
　次に、演算器８１は、ステップＳ１００からステップＳ１４０において寿命を計算する。 Next, the computing unit 81 calculates the lifetime from step S100 to step S140.
　まず、ステップＳ１００において、特性を予測する時刻ｔ１をΔｔに設定する。 First, in step S100, it sets the time t 1 for predicting the characteristics Delta] t.
　次に、ステップＳ１１０において、時刻ｔ１における劣化パラメータを上記式（１５）～（１７）に基づいて計算する。 Next, in step S110, the deterioration parameter at time t 1 is calculated based on the equation (15) to (17).
　次に、ステップＳ１２１において、計算した劣化パラメータをシミュレータの入力値として、時刻ｔ１における出力を計算し、メモリ１０１から出力初期値を読み込んで、出力維持率に換算する。 Next, in step S121, the calculated deterioration parameter as input to the simulator to calculate the output at time t 1, reads the initial output value from the memory 101, converted into an output retention ratio.
　次に、ステップＳ１３０において、寿命判定を行う。寿命判定基準を越えている場合（Ｓ１３０－Ｙｅｓ）、ステップＳ１４０に進む。寿命判定基準を越えていない場合（Ｓ１３０－Ｎｏ）、時刻をΔｔだけ増やし、ステップＳ１１０に戻り、計算を繰り返す。 Next, in step S130, the life is determined. When the life criterion is exceeded (S130-Yes), the process proceeds to step S140. If the service life criterion has not been exceeded (S130-No), the time is increased by Δt, the process returns to step S110, and the calculation is repeated.
　次に、ステップＳ１４０において、寿命を計算する。計算方法は、寿命判定基準値をまたぐ前後２つの時刻におけるデータを内挿補間して求める。寿命となる時刻をすでに過ぎている場合には、余寿命は負の値となる。 Next, in step S140, the lifetime is calculated. The calculation method is obtained by interpolating data at two times before and after the life determination reference value. If the time when the life is reached has already passed, the remaining life is a negative value.
　最後に、ステップＳ１５０において、現時刻と寿命との差を余寿命として、表示部６０に表示し、スタートへ戻る。 Finally, in step S150, the difference between the current time and the life is displayed as the remaining life on the display unit 60, and the process returns to the start.
　＜実施の形態２の効果＞
　以上のように、本実施の形態２によれば、二種の異なる充電電流の充電特性から抽出した劣化パラメータの電池使用時間依存性を元に、任意の時刻における劣化パラメータを推定し、推定した劣化パラメータを入力値とするシミュレーションにより出力を計算し、余寿命を推定することができる。
［実施の形態３］
　本実施の形態３においても、上記実施の形態１及び２と同様に、二次電池の余寿命診断装置を例に説明するが、以下においては上記実施の形態１及び２と異なる点を主に説明する。 <Effect of Embodiment 2>
As described above, according to the second embodiment, the deterioration parameter at an arbitrary time is estimated and estimated based on the battery usage time dependency of the deterioration parameter extracted from the charging characteristics of two different charging currents. The remaining life can be estimated by calculating the output by simulation using the degradation parameter as an input value.
[Embodiment 3]
In the third embodiment, as in the first and second embodiments, the secondary battery remaining life diagnosis apparatus will be described as an example. However, the following mainly describes differences from the first and second embodiments. explain.
　実施の形態１及び２では、あらかじめＲＯＭに搭載されている各劣化パラメータに対する劣化パラメータ関数式は１種類であったが、劣化パラメータの時間依存性を事前に設定できない場合には、候補となる関数式を複数ＲＯＭに用意し、診断の都度、最もフィッティング精度の良い式を選択するようにすることもできる。関数式としては、指数関数、対数関数、ベキ関数、多項式など何でも良い。 In the first and second embodiments, there is only one type of deterioration parameter function expression for each deterioration parameter mounted in advance in the ROM. However, if the time dependency of the deterioration parameter cannot be set in advance, a candidate function is used. It is also possible to prepare a plurality of formulas in the ROM and select the formula with the best fitting accuracy for each diagnosis. The function expression may be anything such as an exponential function, a logarithmic function, a power function, or a polynomial.
　＜実施の形態３の効果＞
　以上のように、本実施の形態３によれば、最も適切な劣化パラメータ関数式を適宜選択して寿命を計算するので、更に精度良く余寿命を推定することができる。 <Effect of Embodiment 3>
As described above, according to the third embodiment, since the lifetime is calculated by appropriately selecting the most appropriate deterioration parameter function equation, the remaining lifetime can be estimated with higher accuracy.
　以上、本発明者によってなされた発明を実施の形態１～３に基づき具体的に説明したが、本発明は、上述の実施の形態に限定されるものではなく、その要旨を逸脱しない範囲で種々変更可能であることはいうまでもない。上述の実施の形態１～３は、本発明を分かり易く説明するために詳細に説明したものであり、必ずしも説明した全ての構成を備えるものに限定されるものではない。 As mentioned above, the invention made by the present inventor has been specifically described based on the first to third embodiments. However, the present invention is not limited to the above-described embodiments, and various modifications can be made without departing from the scope of the invention. Needless to say, it can be changed. The above-described first to third embodiments are described in detail for easy understanding of the present invention, and are not necessarily limited to those having all the configurations described.
　１０：二次電池、２０：制御部、３０：電圧センサ、３５：センサ、４０：電流センサ、５０：演算部、６０：表示部、７０：タイマ、８０：演算器、８１：演算器、９０：不揮発メモリ、９１：不揮発メモリ、１００、１０１：ＲＯＭ。 10: secondary battery, 20: control unit, 30: voltage sensor, 35: sensor, 40: current sensor, 50: calculation unit, 60: display unit, 70: timer, 80: calculation unit, 81: calculation unit, 90 : Non-volatile memory, 91: non-volatile memory, 100, 101: ROM.

Claims (10)

  1. 　二次電池の初期状態のパラメータをメモリに保存し、
    　所定時間経過後に、前記メモリに保存された前記初期状態のパラメータと、第一の電流値における放電特性と、前記第一の電流値より大きい第二の電流値における放電特性とに基づいて、前記二次電池の放電容量及び直流抵抗に関する余寿命を算出することを特徴とする二次電池の余寿命診断方法。     Save the initial parameters of the secondary battery in memory,
    After a predetermined time, based on the parameters of the initial state stored in the memory, the discharge characteristics at a first current value, and the discharge characteristics at a second current value greater than the first current value, A method for diagnosing the remaining life of a secondary battery, wherein the remaining life relating to the discharge capacity and DC resistance of the secondary battery is calculated.
  2. 　前記余寿命の算出は、
    　前記メモリに保存された前記初期状態のパラメータと、前記第一の電流値における放電特性と、前記第二の電流値における放電特性とに基づいて、前記二次電池の劣化状態を表す劣化パラメータを抽出し、保存することを繰り返して履歴を作成し、
    　作成した前記劣化パラメータの履歴から所望の時刻の劣化パラメータを推定し、
    　前記初期状態のパラメータを入力値とするシミュレータを用いて行う、請求項１記載の二次電池の余寿命診断方法。     The remaining life is calculated as follows:
    A deterioration parameter representing a deterioration state of the secondary battery based on the initial state parameter stored in the memory, the discharge characteristic at the first current value, and the discharge characteristic at the second current value. Extract and save it repeatedly to create a history,
    Estimating the degradation parameter at a desired time from the history of the created degradation parameter,
    The method for diagnosing the remaining life of a secondary battery according to claim 1, wherein the remaining life diagnosis method is performed using a simulator having the initial state parameters as input values.
  3. 　前記所望の時刻の劣化パラメータは、前記メモリに保存されている関数式を用いて推定する、請求項２記載の二次電池の余寿命診断方法。 3. The method for diagnosing the remaining life of a secondary battery according to claim 2, wherein the deterioration parameter at the desired time is estimated using a function equation stored in the memory.
  4. 　二次電池の初期状態のパラメータをメモリに保存し、
    　充電時に、前記メモリに保存された前記初期状態のパラメータと、第一の電流値における充電特性と、前記第一の電流値より大きい第二の電流値における充電特性とに基づいて、前記二次電池の出力維持率に関する余寿命を算出することを特徴とする二次電池の余寿命診断方法。     Save the initial parameters of the secondary battery in memory,
    At the time of charging, based on the parameters of the initial state stored in the memory, the charging characteristics at the first current value, and the charging characteristics at the second current value greater than the first current value, the secondary A method for diagnosing a remaining life of a secondary battery, comprising calculating a remaining life related to an output maintenance ratio of the battery.
  5. 　前記余寿命の算出は、
    　前記メモリに保存された前記初期状態のパラメータと、前記第一の電流値における充電特性と、前記第二の電流値における充電特性とに基づいて、前記二次電池の劣化状態を表す劣化パラメータを抽出し、保存することを繰り返して履歴を作成し、
    　作成した前記劣化パラメータの履歴から所望の時刻の劣化パラメータを推定し、
    前記初期状態のパラメータを入力値とするシミュレータを用いて行う、請求項４記載の二次電池の余寿命診断方法。     The remaining life is calculated as follows:
    A deterioration parameter representing a deterioration state of the secondary battery based on the initial state parameter stored in the memory, the charging characteristic at the first current value, and the charging characteristic at the second current value. Extract and save it repeatedly to create a history,
    Estimating the degradation parameter at a desired time from the history of the created degradation parameter,
    The method for diagnosing the remaining life of a secondary battery according to claim 4, wherein the remaining life diagnosis method is performed using a simulator having the initial state parameters as input values.
  6. 　前記所望の時刻の劣化パラメータは、前記メモリに保存されている関数式を用いて推定する、請求項５記載の二次電池の余寿命診断方法。 6. The secondary battery remaining life diagnosis method according to claim 5, wherein the deterioration parameter at the desired time is estimated using a function equation stored in the memory.
  7. 　二次電池の電池電圧及び電池電流を検出する検出器と、
    　前記検出器により検出した第一の電流値における放電特性、及び、前記第一の電流値より大きい第二の電流値における放電特性から前記二次電池の劣化状態を表す劣化パラメータを推定し、放電容量維持率及び直流抵抗増加率を計算する演算器と、
    　を有し、
    　前記演算器は、前記放電容量維持率及び直流抵抗増加率から前記二次電池の余寿命を算出することを特徴とする二次電池の余寿命診断装置。     A detector for detecting the battery voltage and battery current of the secondary battery;
    A deterioration parameter representing a deterioration state of the secondary battery is estimated from a discharge characteristic at a first current value detected by the detector and a discharge characteristic at a second current value larger than the first current value, and discharge An arithmetic unit for calculating the capacity maintenance rate and the DC resistance increase rate;
    Have
    The arithmetic unit calculates the remaining life of the secondary battery from the discharge capacity maintenance rate and the DC resistance increase rate, and the remaining life diagnosis apparatus for the secondary battery.
  8. 　二次電池の電池電圧及び電池電流を検出する検出器と、
    　前記検出器により検出した第一の電流値における充電特性、及び、前記第一の電流値より大きい第二の電流値における充電特性から前記二次電池の劣化状態を表す劣化パラメータを推定し、出力維持率を計算する演算器と、
    　を有し、
    　前記演算器は、前記出力維持率から前記二次電池の余寿命を算出することを特徴とする二次電池の余寿命診断装置。     A detector for detecting the battery voltage and battery current of the secondary battery;
    Estimating a deterioration parameter representing a deterioration state of the secondary battery from a charging characteristic at a first current value detected by the detector and a charging characteristic at a second current value larger than the first current value, and outputting An arithmetic unit for calculating the maintenance rate;
    Have
    The arithmetic unit calculates the remaining life of the secondary battery from the output maintenance rate, and the remaining life diagnosis apparatus for the secondary battery.
  9. 　前記二次電池と、制御部と、請求項７又は８に記載の二次電池の余寿命診断装置と、を備えたことを特徴とする電池システム。 A battery system comprising: the secondary battery; a control unit; and the secondary battery remaining life diagnosis device according to claim 7 or 8.
  10. 　さらに、表示部を備えたことを特徴とする請求項９記載の電池システム。 The battery system according to claim 9, further comprising a display unit.
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