WO2015041093A1 - Dispositif et procédé permettant d'évaluer les performances d'un accumulateur - Google Patents

Dispositif et procédé permettant d'évaluer les performances d'un accumulateur Download PDF

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Publication number
WO2015041093A1
WO2015041093A1 PCT/JP2014/073707 JP2014073707W WO2015041093A1 WO 2015041093 A1 WO2015041093 A1 WO 2015041093A1 JP 2014073707 W JP2014073707 W JP 2014073707W WO 2015041093 A1 WO2015041093 A1 WO 2015041093A1
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Prior art keywords
storage battery
state quantity
battery
deterioration
performance evaluation
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PCT/JP2014/073707
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English (en)
Japanese (ja)
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板倉　昭宏
徹 江澤
山本　幸洋
雄毅 羽生
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株式会社 東芝
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    • 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
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/0047—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries with monitoring or indicating devices or circuits
    • H02J7/005—Detection of state of health [SOH]
    • 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
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/0047—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries with monitoring or indicating devices or circuits
    • H02J7/0048—Detection of remaining charge capacity or state of charge [SOC]
    • 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

  • Embodiments of the present invention relate to a storage battery performance evaluation apparatus and method.
  • Embodiment of this invention estimates the future performance of a storage battery in consideration of a future user's use condition.
  • the storage battery performance evaluation apparatus as one aspect of the present invention includes an estimation unit, a prediction unit, and a performance evaluation unit.
  • the estimation unit estimates the use history of the storage battery based on the state quantity representing the internal state of the storage battery to be evaluated.
  • the prediction unit calculates the progress of deterioration of the internal state of the storage battery when the storage battery is used in the future according to a user-set usage condition given in advance, and calculates the state quantity of the storage battery in the future. Predict.
  • the performance evaluation unit evaluates the performance of the storage battery based on the state quantity predicted by the prediction unit.
  • FIG. 1 shows a block diagram of a storage battery residual value evaluation apparatus according to an embodiment of the present invention.
  • the storage battery residual value evaluation apparatus includes a battery state quantity detection unit 102, a deterioration characteristic database (DB) 103, a current state estimation unit 104, a battery usage pattern database 106, a battery usage pattern conversion unit 107, and a future performance prediction unit. 120, a residual value calculation unit (performance evaluation unit) 111, and a residual value display unit 112.
  • the storage battery state quantity detection unit 102 detects one or more state quantities representing the internal state from the storage battery 101 to be evaluated.
  • the state quantity is a parameter corresponding to the capacity of each active material constituting the battery, the resistance of the battery, the resistance of each active material, and the like.
  • capacitance for every active material instead of every active material as a state quantity is also possible. For example, when there are not a plurality of types of active materials but a single type, the battery capacity itself may be detected.
  • the deterioration characteristic database 103 stores data of deterioration characteristics corresponding to the usage status of the storage battery.
  • the format of the deterioration characteristic data may be arbitrary.
  • the battery state quantity detection unit 102 may be used to process storage battery test data to measure deterioration characteristics, and store the measurement results in a storage battery deterioration characteristic database.
  • the capacity (for each active material or battery capacity) and resistance may be measured by changing temperature conditions, charge / discharge conditions, storage conditions, and the like, and the measured data may be recorded in association with the test data.
  • the deterioration characteristic database 103 may store a deterioration model formula described later.
  • the current state estimation unit 104 estimates the current state of the storage battery as a storage battery usage history based on the one or more state amounts detected by the battery state amount detection unit 102 and the deterioration characteristic database 103 (step 2). ).
  • the estimated current state (usage history) is the equivalent usage condition and usage period of the storage battery so far, and is defined as equivalent history and equivalent age, respectively.
  • the equivalent history and equivalent age are examples of storage battery usage history estimated in the present embodiment.
  • Fig. 3 shows the identification method of equivalent history and equivalent age.
  • active material A capacity state quantity 1
  • active material B capacity state quantity 2
  • battery resistance state quantity 3
  • state quantities 1 and 2 a graph of deterioration characteristics according to use conditions is shown according to use periods.
  • the use temperature environment temperature
  • the capacity value decreases as the use period proceeds (deterioration progresses).
  • the state quantity 3 as the deterioration progresses, the resistance value increases.
  • the progress of deterioration varies depending on the use conditions.
  • the number of charge / discharge cycles may be used.
  • the charge / discharge current may be used in addition to or in place of the use temperature.
  • use conditions other than these may be used.
  • the values detected by the battery state quantity detection unit 102 are shown as detection results 1, 2, and 3 in FIG.
  • the usage periods corresponding to the detection results 1, 2, and 3 are obtained as N1, N2, and N3.
  • the usage period corresponding to each usage condition is obtained for each state quantity, and the same usage condition with the smallest variation in the calculated usage period is specified as the equivalent history of the storage battery.
  • Use periods corresponding to the specified use conditions are N1, N2, and N3, and among these, for example, the one closest to the center of the distribution (median value) is selected, and this is set as the equivalent age (Neq) of the storage battery.
  • the average of N1, N2, and N3 may be set as the equivalent age.
  • the method for determining the equivalent history and equivalent age described here is an example, and any method can be used as long as the usage condition and the usage period are specified so that the errors with respect to the state quantities 1, 2, and 3 are reduced. Can do.
  • the usage conditions 105 input to the battery usage pattern conversion unit 107 are conditions that can be set by the user, and are future planned usage conditions. If the storage battery is used in an EV (electric vehicle), the future usage period, frequency of use, area of use, use / non-use of quick charge, etc. are set.
  • EV electric vehicle
  • the usage period includes a period up to a time when it is desired to predict, for example, a period up to the next vehicle inspection time.
  • the use frequency may be a typical use condition such as leisure use or business use, or more specifically, a numerical setting such as a daily travel distance or the number of use days in a week may be used.
  • the presence or absence of quick charging is whether or not there is a plan to perform quick charging, and in the case of performing charging, the frequency of use may be included.
  • the setting of a vehicle type may be included.
  • the battery usage pattern DB 106 stores storage battery usage patterns according to usage conditions that can be set by the user.
  • the usage pattern represents a change in parameters related to the storage battery according to time. For example, according to the period of use and the frequency of use, the change pattern according to the time of the parameter regarding the storage battery considering the cycle deterioration characteristic and the calendar deterioration characteristic. Furthermore, the change pattern according to the time of the battery temperature based on the temperature information for every area may be stored. Cycle deterioration is deterioration that progresses by repeating charging and discharging, and calendar deterioration is deterioration that progresses with time even in a state where charging and discharging are not performed.
  • Fig. 5 shows an example of battery usage patterns.
  • L1 in the figure represents an elapsed time that is desired to be predicted from the present time.
  • FIG. 5A shows a pattern for one cycle period
  • FIG. 5B shows an overall pattern (until the end of the use period).
  • the example is based on the assumption that the EV is used regularly and the rest is stopped, and the SOC, temperature, and current (charge / discharge current) patterns at that time are shown.
  • the SOC, battery temperature, and current (charge / discharge current) are examples of parameters related to the storage battery.
  • Battery usage pattern conversion unit 107 acquires a battery usage pattern according to usage conditions 105 set by the user from battery usage pattern DB 106.
  • the future performance prediction unit 120 is a predetermined value when the storage battery is used in the future with the battery usage pattern obtained by the battery usage pattern conversion unit 107 based on the current state (equivalent age) estimated by the current state estimation unit 104.
  • the performance after the period is predicted based on the deterioration model 108 (first future performance prediction). For example, the performance after a predetermined period can be expressed by a probability distribution.
  • the future performance prediction unit 120 uses the storage battery in the future with the same history as the equivalent history estimated by the current state estimation unit 104 based on the current state (equivalent age) estimated by the current state estimation unit 104. It also has a function of predicting performance after a predetermined period of time (second future performance prediction).
  • the storage battery is used with the battery usage pattern obtained by the battery usage pattern conversion unit based on the current state (equivalent age) estimated by the current state estimation unit 104.
  • the state quantity after a predetermined period is predicted based on the deterioration model 108.
  • the deterioration model 108 will be described.
  • deterioration of storage batteries There are two main reasons for the deterioration of storage batteries. One is cycle deterioration that progresses by repeating charging and discharging, and the other is calendar deterioration that progresses with time even in a state where charging and discharging are not performed.
  • the deterioration of the storage battery is considered to occur in a combination of both, and as an example, the deterioration model can be expressed by the sum of both.
  • a deterioration model is created based on cycle and calendar deterioration test data.
  • cycle deterioration test a deterioration test is performed using temperature (battery temperature), current, and SOC as variables.
  • calendar deterioration test a deterioration test is performed with SOC and temperature as variables.
  • SOC battery temperature
  • FIG. 9 shows an example of the deterioration model equation.
  • the deterioration is advanced according to the usage pattern of the battery, and the future battery state (battery performance) is calculated.
  • FIG. 9 shows an example of a capacity degradation model formula and a resistance degradation model formula.
  • Capacity deterioration and resistance deterioration are expressed based on calendar deterioration and cycle deterioration, respectively.
  • Each model formula also includes variables representing the current state as initial values (for example, the use time and the use temperature so far), so that the capacity or resistance after a predetermined period can be estimated from the current state.
  • a specific model creation method may be a known method, and a specific creation method is not described in the present embodiment.
  • an equation for capacity degradation an equation for each active material capacity can be created, or it can be created for the battery capacity.
  • the future state quantity calculation unit 109 receives the usage pattern obtained by the battery usage pattern conversion unit 107, calculates the deterioration of the storage battery according to the deterioration model 108, and calculates the state quantity after a predetermined period. If the usage period is specified in the usage conditions, the predetermined period matches the specified period.
  • a graph may be created by sequentially calculating the state quantities at each point in time until a predetermined period.
  • the future state quantity calculation unit 109 of the future performance prediction unit 120 extends the equivalent history identified by the current state estimation unit 104 to a state after a predetermined period, thereby extending the state after the predetermined period. Calculate the amount.
  • FIG. 4 shows the capacity deterioration tendency. For example, consider the capacity of the active material A shown in FIG.
  • the graph of the equivalent history of the capacity of the active material A estimated by the current state estimation unit 104 corresponds to the deterioration tendency graph of continuous use shown in the drawing. This is stored in the deterioration characteristic database 103.
  • a position on the graph corresponding to the equivalent age estimated by the current state estimation unit 104 is indicated by a circle.
  • a value on the graph after a predetermined period is obtained from this position, and this is defined as the capacity of the active material A after the predetermined period. It is possible to externally set a use condition that is stricter use or gentle use than continuous use, and evaluate the capacity of the active material A after a predetermined period according to each condition. In this case, the capacity after a predetermined period of time may be calculated in the same manner according to the graph of the deterioration characteristic of gentle use and the graph of deterioration characteristic of severe use. “Severe” and “gentle” may be the case where the number of cycles is high and low, respectively, and the case where the environmental temperature is high and low. These graphs may be prepared in advance in the same manner as the deterioration characteristic graph of FIG. Alternatively, the above-described deterioration model 108 may be used to calculate a parameter set with a stricter or gentler value than “continuous use” as an input to the deterioration model 108.
  • the performance index conversion unit 110 obtains a battery performance index corresponding to the battery capacity or internal resistance from the state quantity of the battery after a predetermined period calculated in the first or second future performance prediction.
  • the battery performance index may be calculated as a probability distribution, and a case where it is obtained as a probability distribution will be described below.
  • the description will be made on the assumption that the first future performance prediction is performed, but the same can be done when the second future performance prediction is performed.
  • FIG. 6 shows a calculation example of the battery performance index when the representative performance index is the battery capacity of the storage battery.
  • the deterioration characteristic DB 103 stores the deterioration characteristic of the representative performance index corresponding to the battery use condition (see FIG. 3).
  • the performance index conversion unit 110 reads deterioration characteristic data corresponding to the equivalent history calculated by the current state estimation unit 104 from the deterioration characteristic DB 103.
  • the graph of the portion before the equivalent age Neq in the thick line graph shown in FIG. 6 corresponds to the portion of the read graph before the equivalent age Neq.
  • the graph after the point A is calculated according to the above-mentioned deterioration model.
  • the value of the point B after a predetermined period (after the use period) corresponds to the sum of the capacities of the two active materials calculated by the future state quantity calculation unit 109. That is, the battery capacity of the storage battery can be expressed as the sum of the state quantity 1 and the state quantity 2 when the state quantity 1 and the state quantity 2 are the capacities of the two main active materials of the storage battery electrode.
  • the deterioration characteristic DB 103 also stores battery capacity variation data according to the period of use (age) and the type of battery.
  • the variation data may be an arbitrary index such as standard deviation ⁇ c or variance.
  • a standard deviation ⁇ c is assumed.
  • a normal distribution centered on the value of the battery capacity (representative performance index) at the age after the specified period from the equivalent age Neq, that is, the value of the point B is calculated, and this is present in the future Find as a probability.
  • the white circle in the figure indicates a value that is separated from the point B by the standard deviation.
  • the dotted line graph is a smooth connection of this white circle and the graph before point A.
  • the predetermined use limit level shown in the figure is the use limit level of the storage battery, and when this level is exceeded, it is a standard for determining that the use suitability of the storage battery is not present.
  • the area below the use limit level line is the area that exceeds the use limit level.
  • the sample is randomly sampled multiple times for each normal distribution with the mean (for each of the active materials A and B) at the equivalent age Neq and the standard deviation as ⁇ c, and the future state quantity after a predetermined period according to the deterioration model Are estimated and summed to calculate a battery performance index (battery capacity).
  • a distribution of the calculated battery performance index or a normal distribution that most closely matches the distribution (having a shape close to the distribution) is obtained as a future existence probability.
  • the future state quantity calculation unit 109 predicts the future state quantity for each capacity (state quantity) of the active material by the deterioration model, but the battery capacity that is the sum of the two at the present time is deteriorated according to the deterioration model. By doing so, it is possible to directly predict the future battery capacity. This method may be combined with the above-described Monte Carlo method.
  • the graph of the part before the point A is the part of the deterioration characteristic data corresponding to the equivalent history read from the deterioration characteristic DB 103.
  • the graph is detected by the battery state quantity detection unit 102.
  • the total capacity for each active material may be the value of point A, and the graph before A may be omitted.
  • the value of the point A is not necessarily exactly the same in both cases, but the present invention can be implemented with either.
  • FIG. 7 shows a calculation example of the battery performance index when the representative performance index is internal resistance.
  • the state quantity 3 (resistance) of the storage battery shown in FIG. 3 is directly used as a battery performance index.
  • the region above the use limit level line shown in the figure is the region exceeding the use limit level. The rest is the same as in FIG.
  • Fig. 8 shows a two-dimensional display of battery capacity and resistance as representative performance indicators.
  • the horizontal axis is the battery capacity and the vertical axis is the internal resistance.
  • the white circle in the figure indicates the value (battery capacity, resistance) at the time of evaluation (current), and the range indicated by the dotted line means the existence probability of the value (battery capacity, resistance) after a predetermined period, Each dotted line corresponds to a probability contour line.
  • the black circle in the figure is the center of the distribution. In this way, a multivariate probability distribution regarding a plurality of representative performance indexes can also be calculated.
  • the hatched area in the figure is an area that exceeds the use limit level.
  • the residual value calculation unit (performance evaluation unit) 111 compares the performance index calculated as the probability distribution by the performance index conversion unit 110 with a predetermined usage limit level (see FIGS. 6 to 8), and out of the entire probability distribution.
  • the use nonconformity rate that is the ratio of the area of the part exceeding the level is calculated as the residual value.
  • the hatched area shown in FIGS. 6 and 7 indicates a portion exceeding a predetermined use limit level. In FIG. 8, the intersection area between the dashed elliptical area and the hatched area corresponds to a portion exceeding a predetermined use limit level.
  • the residual value display unit 112 displays the residual value calculated by the residual value calculation unit (performance evaluation unit) 111 as a residual value evaluation result of the storage battery to be evaluated.
  • one battery usage pattern is acquired from the user-set use condition 105.
  • a configuration in which a probability distribution of the battery use pattern is acquired for the user-set use condition 105 is also possible. This will be described below.
  • the usage pattern database 106 may store a probability distribution of usage patterns based on usage conditions.
  • usage patterns are generated according to the probability distribution, and for each usage pattern, the standard deviation of the representative performance index value (battery capacity or resistance) at the equivalent age is considered, and the above-described Monte Carlo method is used.
  • the distribution of representative performance index values in the future is acquired. That is, the distribution in the case of using one usage pattern as described above is obtained for the number of usage patterns. Then, a probability distribution (for example, a normal distribution) that approximates the composition of these distributions is obtained as a future existence probability. Other methods may be used to determine the future existence probability.
  • FIG. 2 shows a flowchart of the storage battery performance evaluation apparatus according to this embodiment.
  • the storage battery state quantity detection unit 102 detects one or more state quantities representing the internal state of the battery from the storage battery 101 to be evaluated (step 1).
  • the current state estimation unit 104 estimates the current state of the storage battery (storage battery usage history) based on the one or more state quantities detected by the battery state quantity detection unit 102 and the deterioration characteristic database 103 (step 2). ).
  • step 3 If the user's usage conditions are set (“Yes” in step 3), the first future performance prediction is performed (steps 4 and 5). If not set (no in step 3), the first 2 predicts the future (step 6).
  • the future state quantity calculation unit 109 of the future performance prediction unit 120 extends the equivalent history identified by the current state estimation unit 104 until after a predetermined period, whereby the state after the predetermined period The amount is calculated (step 6).
  • the battery usage pattern conversion unit 107 acquires a battery usage pattern corresponding to the usage condition 105 set by the user from the battery usage pattern DB 106.
  • the future state quantity calculation unit 109 uses the storage battery with the battery usage pattern obtained by the battery usage pattern conversion unit based on the current state estimated by the current state estimation unit 104 Are estimated based on the deterioration model 108.
  • the performance index conversion unit 110 performs the following operation after the predetermined period calculated by the first or second future performance prediction.
  • a battery performance index corresponding to the battery capacity or internal resistance is calculated as a probability distribution such as a normal distribution (step 7).
  • the residual value calculation unit (performance evaluation unit) 111 compares the performance index calculated as a probability distribution by the performance index conversion unit 110 with a predetermined usage limit level, and the usage is a probability exceeding that level. Calculate the nonconformity rate as the residual value.
  • the residual value display unit 112 displays the residual value calculated by the residual value calculation unit (performance evaluation unit) 111 as a residual value evaluation result of the storage battery to be evaluated.
  • the storage battery performance evaluation apparatus of this embodiment can be realized by using, for example, a general-purpose computer apparatus as basic hardware.
  • Each processing block in the scheduling device can be realized by causing a processor mounted on the computer device to execute a program.
  • the storage battery performance evaluation device may be realized by installing the above program in a computer device in advance, or may be stored in a storage medium such as a CD-ROM or distributed through the network. Then, this program may be realized by appropriately installing it in a computer device.
  • each database in the storage battery performance evaluation apparatus appropriately uses a memory, a hard disk or a storage medium such as a CD-R, CD-RW, DVD-RAM, DVD-R, etc. incorporated in or externally attached to the above-described computer apparatus. Can be realized.

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Abstract

[Problème] Prédire les performances futures d'un accumulateur tout en prenant en compte l'utilisation future par un utilisateur. [Solution] Le dispositif d'évaluation des performances d'un accumulateur selon un mode de réalisation de la présente invention est doté d'une unité d'estimation, d'une unité de prédiction et d'une unité d'évaluation des performances. L'unité d'estimation estime un historique d'utilisation de l'accumulateur sur la base d'une grandeur d'état représentant un état interne de l'accumulateur à évaluer. L'unité de prédiction calcule, sur la base de l'historique d'utilisation, l'évolution de la dégradation de l'état interne de l'accumulateur pour une situation dans laquelle l'accumulateur doit être utilisé à partir du moment présent selon une condition d'utilisation d'un réglage utilisateur donné à l'avance, et prédit la grandeur d'état de l'accumulateur pour le futur. L'unité d'évaluation des performances évalue les performances de l'accumulateur sur la base de la grandeur d'état prédite par l'unité de prédiction.
PCT/JP2014/073707 2013-09-20 2014-09-08 Dispositif et procédé permettant d'évaluer les performances d'un accumulateur WO2015041093A1 (fr)

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