WO2021039018A1 - Procédé d'estimation de température, procédé d'estimation d'état de détérioration et procédé de prédiction de durée de vie pour module de batterie secondaire, dispositif d'estimation de température, dispositif d'estimation d'état de détérioration et dispositif de prédiction de durée de vie pour module de batterie secondaire et dispositif de charge - Google Patents

Procédé d'estimation de température, procédé d'estimation d'état de détérioration et procédé de prédiction de durée de vie pour module de batterie secondaire, dispositif d'estimation de température, dispositif d'estimation d'état de détérioration et dispositif de prédiction de durée de vie pour module de batterie secondaire et dispositif de charge Download PDF

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WO2021039018A1
WO2021039018A1 PCT/JP2020/022639 JP2020022639W WO2021039018A1 WO 2021039018 A1 WO2021039018 A1 WO 2021039018A1 JP 2020022639 W JP2020022639 W JP 2020022639W WO 2021039018 A1 WO2021039018 A1 WO 2021039018A1
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Prior art keywords
secondary battery
temperature
battery module
charging
battery
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PCT/JP2020/022639
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English (en)
Japanese (ja)
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修子 山内
孝徳 山添
茂樹 牧野
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株式会社日立製作所
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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]
    • G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
    • 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
    • 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
    • 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

Definitions

  • the present invention relates to a secondary battery module temperature estimation method, a deterioration state estimation method and a life prediction method, a secondary battery module temperature estimation device, a deterioration state estimation device and a life prediction device, and a charging device.
  • the storage battery module constituting such a large secondary battery is generally configured by connecting a plurality of battery cells in series and parallel.
  • high-performance and lightweight lithium-ion batteries are generally used because the performance of the batteries affects driving. Therefore, the price of a driving battery is generally high, and the price of an electric vehicle is also higher than that of a gasoline vehicle of the same class. Therefore, there is a demand from users that they want to continue using and running electric vehicles for a longer period of time. Therefore, it is important to more appropriately diagnose the degree of deterioration of the battery and diagnose the remaining life.
  • Secondary batteries such as lithium-ion batteries deteriorate each time they are charged and discharged, and their capacity decreases and their internal resistance increases. As a result, the output of the secondary battery fluctuates.
  • the degree of deterioration of the secondary battery varies depending on the usage history of the secondary battery, such as the environment and method in which the secondary battery has been used so far. Therefore, there is a demand for a technique for accurately estimating the deterioration state according to the usage history of the secondary battery.
  • Patent Document 1 the amount of current flowing through the secondary battery is integrated to calculate a predetermined deterioration coefficient corresponding to each of a plurality of usage conditions that affect the capacity deterioration of the secondary battery, and the integrated current value is obtained.
  • a battery deterioration estimation method is disclosed in which the above is corrected by a deterioration coefficient and the level of capacity deterioration of the secondary battery is estimated.
  • Patent Document 2 describes the current and terminal voltage of a battery for the purpose of suppressing the cost of directly attaching a temperature detector for detecting the temperature of the secondary batteries constituting the assembled battery to each secondary battery.
  • Battery temperature estimation provided with a means for calculating the internal resistance value of the battery based on the above and estimating the battery temperature based on the ratio of the internal resistance value and the initial internal resistance value of the battery at the reference temperature. The system is disclosed.
  • Battery resistance increases significantly under low temperature conditions. At sub-zero temperatures, the resistance of the battery may be several times higher than at room temperature.
  • the deterioration rate of the battery varies depending on the temperature at which the battery is stored.
  • the deterioration of the battery using the resistance value as an index tends to progress.
  • the battery deterioration estimation method described in Patent Document 1 estimates the level of deterioration under specific usage conditions, and is limited to capacity estimation. When combining a plurality of used battery packs having different standards for each manufacturer, it is not always possible to make a sufficient estimation simply by correcting with the deterioration coefficient as in the battery deterioration estimation method described in Patent Document 1. There is room for improvement.
  • the battery temperature can be estimated, but when calculating the full charge capacity for continuous energization, an error may occur due to the temperature change accompanying energization. Conceivable.
  • An object of the present invention is to estimate the temperature of a secondary battery, determine the degree of deterioration of the battery, and estimate the life even when the temperature information of the secondary battery constituting the secondary battery module cannot be obtained. ..
  • the method for estimating the temperature of the secondary battery module of the present invention includes a step of acquiring charging characteristic data including the current and voltage supplied to the secondary battery module at the time of charging and charging time, charging characteristic data, and a database.
  • the temperature of the secondary battery can be estimated even when the temperature information of the secondary battery constituting the secondary battery module cannot be obtained.
  • the present invention estimates the temperature of the secondary battery constituting the secondary battery module, calculates the deterioration state of the secondary battery, and predicts the life of the secondary battery.
  • Battery resistance increases significantly under low temperature conditions. At sub-zero temperatures, the resistance of the battery may be several times higher than at room temperature.
  • FIG. 1 is a graph showing an example of the temperature dependence of the resistance of a lithium ion secondary battery.
  • the horizontal axis is the temperature, and the vertical axis is the standardized resistance value (DC resistance).
  • the resistance at 25 ° C. is 1.
  • the resistance becomes very large at a temperature of 0 ° C or lower. At -20 ° C, it is about 7 times higher than the value at 25 ° C.
  • FIG. 2 is a graph showing an example of the effect of the storage temperature of the battery on the resistance of the battery.
  • the horizontal axis represents the temperature set when the battery is stored, and the vertical axis represents the standardized resistance value (DC resistance). The ratio of the resistance value measured after storage under a constant storage voltage condition to the initial resistance is shown.
  • the higher the storage temperature the larger the resistance value, which increases by 20% at 60 ° C and 40% at 80 ° C.
  • the rate of resistance deterioration of the lithium ion secondary battery differs depending on the temperature, and the condition of the battery temperature is important for evaluating the degree of deterioration of the battery.
  • FIG. 3 is a diagram for explaining the temperature rise of the battery during charging.
  • the vertical axis represents the charging current I, the battery voltage V, the battery temperature T cell, and the temperature rise ⁇ T.
  • the curve a is the case of charging from a normal temperature state
  • the curve b is the case of charging with a constant current from a low temperature state.
  • the temperature rise ⁇ T of the battery is a curve a for charging from a normal temperature state
  • a curve b for charging from a low temperature state has a large internal resistance, so that the amount of heat generated is larger than the normal temperature. Therefore, it behaves like a curve b.
  • the temperature rises as shown by curves a'and b'.
  • Capacity measurement measures the amount of electricity between the upper limit voltage and the lower limit voltage. In the measurement at low temperature, the temperature state inside the battery changes, so the capacity also changes when the temperature changes. The degree of deterioration of a battery is indexed by capacity and resistance. In order to compare and evaluate the degree of deterioration of batteries, it is necessary to evaluate the capacity and resistance by measurement under the same conditions.
  • FIG. 4 is a schematic diagram showing a deterioration detection calculation in a conventional battery management system.
  • the SOH of the battery is calculated by the SOH calculation unit using the voltage V, the current I, and the temperature T of the battery. That is, the temperature T is also used for the calculation of SOH.
  • SOH is an index showing the degree of deterioration (deterioration state) of the battery, and is calculated based on resistance or capacity.
  • BMS is also called a battery controller.
  • FIG. 5 shows the overall configuration (life prediction device of the secondary battery module) of one embodiment of the present invention.
  • the secondary battery module 11 (storage battery module) installed in the vehicle 1 (battery system) is the target of the life diagnosis.
  • the charger 2 (charging device) transmits information such as the charging state (State of Charge: SOC) obtained from the communication protocol in the charging cable, the output current I from the charger, and the output voltage V to the server 4 when charging. It is configured so that it can be transmitted by wireless or wired communication.
  • SOC State of Charge
  • the server 4 is a life prediction device for the secondary battery module 11, and has a resistance / capacity calculation unit 5, a deterioration estimation unit 6, and a life calculation unit 7.
  • the resistance / capacitance calculation unit 5, the deterioration estimation unit 6, and the life calculation unit 7 can cooperate with each other and share information.
  • the server 4 may be outside the vehicle 1 and the charger 2, or may have a configuration in which a part thereof is built in the charger 2.
  • the present invention can be applied not only to a vehicle but also to a moving body such as a traveling robot or a flying robot powered by a secondary battery.
  • the secondary battery module 11 When the vehicle 1 is connected to the charger 2, the secondary battery module 11 is charged. That is, the current I is supplied to the secondary battery module 11 by the current command from the vehicle. The current I and voltage V at this time are notified to the vehicle, and the vehicle notifies the SOC according to the amount of charge. Corresponds to the arrow between the vehicle 1 and the charger 2 in the figure. At this time, the charger 2 acquires information (charging information) such as the SOC of the secondary battery constituting the secondary battery module 11, the output current I of the charger, and the output voltage V from the vehicle 1. The charger 2 transmits the acquired charging information to the resistance / capacity calculation unit 5. The output voltage of the charger is assumed to be equal to the closed circuit voltage (CCV) of the secondary battery module 11.
  • CCV closed circuit voltage
  • the resistance / capacity calculation unit 5 calculates the current capacity and resistance values of the secondary battery from the acquired information, and calculates the degree of deterioration by comparing with the initial values.
  • the deterioration estimation unit 6 has a deterioration prediction formula (also referred to simply as a “prediction formula”), and predicts future deterioration transitions.
  • the life calculation unit 7 calculates the life from the prediction result calculated by the deterioration estimation unit 6 using the standard values of the capacity and resistance of the life reference of the vehicle 1. Further, the life calculation unit 7 can transmit information such as the degree of deterioration and the remaining life to an arbitrary terminal (not shown).
  • the "current" capacitance and resistance data may be, for example, several days ago data, but it is desirable that it is the latest data (real-time data).
  • the server 4 may have at least the life calculation unit 7 of the resistance / capacitance calculation unit 5, the deterioration estimation unit 6, and the life calculation unit 7.
  • the resistance / capacitance calculation unit 5 and the deterioration estimation unit 6 may be arranged in the charger 2.
  • the server 4 has a deterioration estimation unit 6 and a life calculation unit 7 among the resistance / capacitance calculation unit 5, the deterioration estimation unit 6 and the life calculation unit 7, the resistance / capacity calculation unit 5 may be used. It may be arranged in the charger 2.
  • a plurality of vehicle information acquired from the charger 2 can be stored in one server 4.
  • the database can be enriched. Then, by referring to the deterioration information of the same model from the database, it becomes easy to create a deterioration estimation formula that refers to the initial battery characteristic value and the running method even when the new car starts to be used, and the battery deterioration and remaining life. It becomes possible to predict the estimation of the above more accurately in a short time.
  • the database is provided on the server 4. Further, it is desirable that the battery temperature estimation unit is provided in the resistance / capacity calculation unit 5.
  • FIG. 6 shows a configuration for performing an SOH calculation according to the present invention.
  • the configuration shown in FIG. 5 will be described with reference to the reference numerals.
  • the battery temperature estimation calculation unit 111 (battery temperature estimation unit), the SOH calculation unit 112, and the database 113 shown in FIG. 6 are built in the server 4 of FIG. In addition, all or a part of these configurations may be provided other than the server 4. For example, it may be provided in the charging device (charging device side database).
  • the battery temperature estimation calculation unit 111 is provided in the resistance / capacity calculation unit 5 shown in FIG. 5, and the SOH calculation unit 112 is provided in the deterioration estimation unit 6 shown in FIG.
  • the battery temperature estimation calculation unit 111 includes curve data (existing charging characteristic data stored in the database 113) indicating the relationship between the temperature (battery temperature or ambient temperature) stored in the database 113 and the charging voltage or charging current. (Correlation data between and temperature) is acquired, and the corresponding battery temperature T cell is estimated. In this case, if possible, it is desirable to obtain the initial temperature T 0 of the battery. As the initial temperature T 0 of the battery, the ambient temperature of the battery or the charger 2 may be substituted.
  • the SOH calculation unit 112 calculates the current SOH using the battery temperature T cell estimated by the battery temperature estimation calculation unit 111 and the input charging current and charging voltage. In this case, the calculation may be performed using the SOC obtained from the charger 2.
  • FIG. 7 shows a battery temperature estimation calculation unit according to the present invention.
  • the temperature estimation calculation unit 150 performs a primary search in the database 151 using the input voltage, current, SOC, initial temperature T 0, etc., and refers to the relationship between the corresponding voltage profile and temperature. Then, the estimated value of the battery temperature is output.
  • the initial temperature T 0 and SOC By inputting the initial temperature T 0 and SOC, the initial values of the search start area of the start SOC and the initial temperature can be determined, and the search time from a huge database can be shortened.
  • the temperature estimation calculation unit 150 corresponds to the battery temperature estimation calculation unit 111 of FIG.
  • the database 151 stores data on current, environmental temperature, SOC, voltage, and battery temperature change with respect to the time when the battery is energized for which the internal resistance is known in advance. Alternatively, it has a plurality of maps in which feature quantities are extracted from the current, environmental temperature, voltage, and battery temperature with respect to the above-mentioned energization time.
  • the battery temperature can be specified by adopting the temperature under the condition closest to the current and voltage changes of the stored data. Alternatively, the battery temperature is output in chronological order according to the initial temperature, SOC, current, and voltage input by the estimation module that has learned the feature amount of the accumulated data.
  • the temperature data output from the battery temperature estimation calculation block is used, and the SOH calculation block outputs the internal resistance value at this time from the internal resistance estimation module that has learned the feature amount or refers to the database.
  • the capacity is corrected from the measured resistance deterioration degree, estimated battery temperature, etc., and the full charge capacity value at the same temperature as the measured temperature in the specifications displayed in the catalog etc. is estimated. .. This makes it possible to detect capacity deterioration without being affected by the increase or decrease in capacity due to temperature.
  • catalog, etc. refers to materials provided by the manufacturer or distributor.
  • FIG. 8 shows an example of the life prediction method of the secondary battery module of the present invention.
  • the battery temperature with respect to time is estimated by collating with the previously acquired charge curve learned (S2).
  • S2 the data on the charging voltage or charging current and the temperature change with time stored in the database is acquired, and the battery temperature with respect to time is estimated.
  • the steps up to this point correspond to the processing in the temperature estimation calculation unit 150 of FIG. 7.
  • step S3 will be described later with reference to FIG.
  • a temperature coefficient is calculated using the correlation between the SOC, temperature, and internal resistance stored in the database and the battery temperature estimated in S2, and the resistance value R is calculated using this temperature coefficient. Correct (S6). The steps up to this point correspond to the processing in the resistance / capacitance calculation unit 5 of FIG.
  • the capacitance value calculated from the current and time and the resistance value R acquired in S6 are converted into the acquired values under the conditions such as the reference temperature (for example, 25 ° C.), current, time, etc. such as the measurement temperature in the catalog display specifications. Is corrected (S7).
  • the full charge capacity is calculated using the converted capacity value, the ratio of the corrected resistance value and capacity value to the initial value or the catalog value is calculated, and the deterioration degree SOHR and SOHQ are calculated (S8). Steps S7 to S8 correspond to the processing in the deterioration estimation unit 6 of FIG.
  • Step S9 corresponds to the process in the life calculation unit 7 of FIG.
  • the deterioration degree SOHQ and SOHR of the battery can be calculated in a shorter time.
  • the degree of deterioration is also referred to as "deterioration state”.
  • the deteriorated state of the battery is SOHR calculated using the internal resistance of the battery (hereinafter, also simply referred to as “resistance”) or SOHQ calculated using the full charge capacity of the battery.
  • SOHR is SOH obtained based on the internal resistance of the battery, represents the rate of increase in the internal resistance of the battery that increases with the deterioration of the battery, and is defined by the following equation (1).
  • R 1 (SOC, T) represents the current (after deterioration) internal resistance [ ⁇ ] of the cell.
  • R 0 (SOC, T) represents the internal resistance [ ⁇ ] of the cell when it is new.
  • the SOHQ calculated using the capacity is the current capacity divided by the initial capacity.
  • the SOHR of the above formula (1) is expressed as a percentage, but the current ratio to the initial stage is not necessarily limited to the percentage.
  • step S2 namely to calculate the temperature rise ⁇ T from aging temperature, the heat capacity C p of ⁇ T and the battery module, by using the cell, it calculates the calorific value Q. Then, the resistance value R'is back-calculated from the calorific value Q and the current.
  • q'(t) is the amount of heat radiated to the outside of the battery.
  • q '(t) can be calculated using radiation area A, the heat transfer coefficient h, and the surface temperature T cell and the refrigerant temperature T C. Compared with the resistance value R obtained in S6, if there is a gap, further correction is performed and the result is accumulated in the database. This makes it possible to obtain a more appropriate resistance value.
  • the battery temperature is corrected by the correction coefficient, and the capacity when a large current is energized at the current value I observed at the time of measurement, which is stored in the database, is calculated. Convert to the capacity under the same standard conditions as the nominal capacity acquired with the low current value in the catalog etc.
  • the deterioration degree SOHQ and SOHR of the reference values obtained as described above can be obtained with a fair standard for the battery modules of any vehicle, and can be compared. Utilizing the degree of deterioration of these standards, it is possible to set the residual value of used batteries and to use them stably in a system using multiple modules for other purposes. In particular, it is possible to shorten the time required for battery deterioration evaluation and performance measurement during reuse, which is effective in utilizing used batteries. Utilization of used batteries also leads to a reduction in the amount of waste batteries and can contribute to the realization of a sustainable society.
  • FIG. 9 shows an example of changes in voltage over time in quick charging and low-speed charging. Time is on the horizontal axis and voltage is on the vertical axis.
  • the curve (a) is for fast charging and the curve (b) is for OCV and slow charging.
  • the voltage curve during low-speed charging for example, when charging at a 0.2 C rate, almost matches the OCV curve when the internal resistance of the battery is low.
  • the discharge rate that matches the OCV differs depending on the battery.
  • the amount of electricity charged by the end of charging on the curve (a) is defined as Q ch .
  • the graph at the bottom of FIG. 9 is a conversion of the graph at the top of FIG. 9 into an SOC-V curve, and shows an example of a charging voltage curve (quick charging curve) and an OCV curve.
  • the horizontal axis is SOC and the vertical axis is voltage.
  • the curve (c) is for quick charging, and the curve (d) is the OCV of the battery.
  • the range of the electric energy Q ch corresponds.
  • the difference between the charging voltage curve and the OCV curve is ⁇ V (SOC).
  • the OCV of the battery is obtained by searching the database for the specifications of the battery used in the vehicle 1 from the information of the vehicle 1 in FIG.
  • the open circuit voltage (OCV) at the start of charging is converted into SOC ini , and the voltage OCV ini , which is the start OCV, is obtained.
  • the OCV ini which is the start OCV, is obtained by setting the notified SOC at the start of charging as the SOC ini.
  • the charging voltage for the SOC is calculated from the notified SOC ini to the SOC end, and the difference ⁇ V (SOC) between the charging voltage and the OCV at the same SOC is divided by the energizing current value.
  • the resistance value R can be obtained. In particular, immediately after the start of energization, before the SOC fluctuates, the influence of the reaction resistance is small and it is suitable.
  • the resistance value R calculated as described above is known to be dependent on SOC.
  • R and SOC shown in this figure can be expressed as a function or table.
  • the resistance value R can also be obtained by the following equation (5).
  • the resistance value R can be obtained from the coefficient A in the linear approximation formula Ax + C obtained by the relationship between the plurality of currents and the closed circuit voltage of the battery according to the current value x at a constant SOC.
  • the coefficient A becomes the internal resistance DCR.
  • the capacity Q can be obtained by the following equation (6) from the difference between the SOC ini which is the initial SOC and the SOC end which is the SOC at the end, that is, the fluctuation range of the SOC and the electric energy Q ch.
  • the obtained Q is a value at the battery temperature T cell , and the characteristics at the T cell are converted into the capacity obtained at the reference temperature.
  • the conversion method uses the coefficient of the ratio of the temperature T cell to the reference temperature (for example, 25 ° C.) capacity, or uses the obtained resistance value and the estimated temperature at that time, and uses the initial reference temperature and the resistance at each temperature.
  • the value ratio is applied, the obtained resistance value is converted to the resistance value at the reference temperature, the voltage curve is recalculated, and the value between the upper limit voltage and the lower limit voltage, which is the definition of the battery capacity, is set as the reference value capacity.
  • the data acquired during charging is sequentially accumulated in the database, improving the accuracy of temperature estimation.
  • SOH is also sequentially accumulated in the database (for estimation of deterioration), and the deterioration prediction formula is updated.
  • the database is sequentially updated and the deterioration prediction formula is also updated. Therefore, even after the prediction formula with a certain amount of data is created and implemented, the measured data increases and the deterioration prediction formula can be updated. it can. Therefore, the error can be reduced as the amount of measurement data increases.
  • the battery temperature can be estimated and converted into characteristic values (capacity, resistance) at the reference temperature to detect the degree of deterioration, it is possible to compare the performance of multiple modules acquired under different conditions with the same reference. , Battery value evaluation and used battery utilization will be easier.
  • the man-hours for model construction until mounting can be reduced.
  • the man-hours for the battery deterioration test for constructing the battery deterioration estimation formula can be reduced, and the remaining life diagnosis with high accuracy can be performed in a short time.
  • FIG. 10 shows the basic configuration of the battery system of the vehicle to be charged by the charger.
  • the system configuration includes a secondary battery module 11 (storage battery module) used in the vehicle and a measured value detection unit 21 installed in the vehicle.
  • the secondary battery module 11 is configured by connecting a plurality of cell cells 11a and 11b having a positive electrode and a negative electrode in series.
  • the secondary battery module 11 is connected to a load (not shown) and supplies electric power to the load.
  • the battery control unit 30, the upper control unit 60, and the load control unit 70 are also components of the system.
  • This system controls the secondary battery module 11 by the measured value detection unit 21, the battery control unit 30, the upper control unit 60, and the load control unit 70.
  • the measured value detection unit 21 detects various information (data) regarding the state of the secondary battery module 11. For example, data such as total current, total voltage, environmental temperature, maximum temperature, average temperature, minimum temperature of the secondary battery module 11, and temperature and voltage of each of the cells 11a and 11b are detected.
  • the data detected by the measured value detection unit 21 is input to the battery control unit 30. It is desirable to detect the type or model of each of the cells 11a and 11b, in other words, the individual characteristics of the cells 11a and 11b.
  • the battery control unit 30 calculates the current charge state (SOC) of the secondary battery module 11 based on the data input from the measured value detection unit 21, detects an abnormal state, and calculates the power that can be input / output. , Execute processing such as generation of temperature control command. These pieces of information obtained by the upper control unit 60 are output to the load control unit 70.
  • SOC current charge state
  • the load control unit 70 executes load control based on the control command input from the host control unit 60 and the information input from the battery control unit 30.
  • FIG. 11 shows an example of the life prediction device for the secondary battery module of the present invention.
  • the remaining life diagnosis unit 50 has each functional block of a data storage unit 41, a data selection unit 42, a deterioration calculation unit 43, a deterioration prediction unit 46 (deterioration state estimation unit), and a remaining life calculation unit 47.
  • the remaining life diagnosis unit 50 can realize each function corresponding to these functional blocks by, for example, executing a program stored in advance by the CPU.
  • the detection unit 20 detects data such as battery voltage and current together with time information such as date and time, and outputs the data to the remaining life diagnosis unit 50.
  • the SOC information notified to the charger and calculated is also input to the remaining life diagnosis unit 50.
  • the outside air temperature by the outside air temperature measurement sensor provided in the charger is also input.
  • the data selection unit 42 selects data that matches the preset conditions from the output information of the charger and the data output from the detection unit 20, and outputs the data to the data storage unit 41. It has a temperature estimation unit in the data selection unit and calculates the temperature by referring to the database. The calculated temperature and charge measurement acquisition data are stored in the database.
  • the data storage unit 41 has an SOC-OCV data storage unit 41a, an SOC-R data storage unit 41b (SOC-resistance data storage unit), and a database 44.
  • the data selection unit 42 refers to the database and selects the data required for temperature estimation by the temperature estimation calculation unit 150.
  • the SOC-OCV data storage unit 41a of the battery with respect to the temperature is provided.
  • the SOC-R data storage unit 41b stores the acquired resistance data for the number of seconds of each temperature with respect to the SOC. As a result, the existing charging characteristic data is accumulated.
  • the database 44 is provided with various data used for deterioration estimation. For example, a prediction formula for estimating deterioration, an initial value of a parameter, a change amount of a parameter, and the like.
  • a prediction formula for estimating deterioration For example, a prediction formula for estimating deterioration, an initial value of a parameter, a change amount of a parameter, and the like.
  • the SOC-OCV data storage unit 41a and the SOC-R data storage unit 41b also store the initial data of the battery in advance.
  • the current deterioration state is estimated by the deterioration calculation unit 43 and output to the deterioration prediction unit 46.
  • the calculated deterioration state is added to the database 44 as time series data and accumulated.
  • the calculated parameters are used by the deterioration prediction unit 46 for predicting deterioration in time series.
  • the remaining life calculation unit 47 calculates and outputs the predicted life or the remaining life using the database 44.
  • information on the deteriorated state of the secondary battery module can be appropriately detected without preparing a special discharging means, and the internal state of the secondary battery module and the secondary battery module can be detected.
  • the capacity and resistance of the system can be obtained, and the remaining life of the system can be calculated accurately.

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Abstract

La présente invention concerne un procédé d'estimation de la température d'un module de batterie secondaire comprenant : une étape consistant à acquérir des données de caractéristique de charge comprenant un courant et une tension fournie au module de batterie secondaire et un temps de charge pendant la charge ; et une étape consistant à estimer la température d'une batterie secondaire constituant le module de batterie secondaire en collationnant les données de caractéristique de charge avec des données de corrélation entre des données de caractéristique de charge existantes stockées dans une base de données et la température. Par conséquent, même lorsque des informations de température de la batterie secondaire constituant le module de batterie secondaire ne peuvent pas être obtenues, la température de la batterie secondaire peut être estimée.
PCT/JP2020/022639 2019-08-29 2020-06-09 Procédé d'estimation de température, procédé d'estimation d'état de détérioration et procédé de prédiction de durée de vie pour module de batterie secondaire, dispositif d'estimation de température, dispositif d'estimation d'état de détérioration et dispositif de prédiction de durée de vie pour module de batterie secondaire et dispositif de charge WO2021039018A1 (fr)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2022244008A1 (fr) * 2021-05-20 2022-11-24 Ariel Scientific Innovations Ltd. Outil de dimensionnement en temps réel utilisant la modélisation générique de système de stockage d'énergie

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2022250076A1 (fr) * 2021-05-28 2022-12-01 エナジーウィズ株式会社 Système de gestion de batterie, procédé de gestion de batterie et programme de gestion de batterie
CN114290959B (zh) * 2021-12-30 2023-05-23 重庆长安新能源汽车科技有限公司 一种动力电池主动寿命控制方法、系统及计算机可读存储介质

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH11162526A (ja) * 1997-11-29 1999-06-18 Sanyo Electric Co Ltd 電池状態検出装置
JP2001085071A (ja) * 1999-09-13 2001-03-30 Toyota Motor Corp 組電池の温度検出装置および温度検出方法
JP2010246320A (ja) * 2009-04-09 2010-10-28 Fujitsu Ten Ltd 制御装置及び制御方法
JP2011018532A (ja) * 2009-07-08 2011-01-27 Toyota Motor Corp 二次電池の温度推定装置
WO2019097664A1 (fr) * 2017-11-17 2019-05-23 三菱電機株式会社 Dispositif d'estimation de durée de vie de batterie
JP2019124612A (ja) * 2018-01-18 2019-07-25 日立オートモティブシステムズ株式会社 二次電池システム

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH11162526A (ja) * 1997-11-29 1999-06-18 Sanyo Electric Co Ltd 電池状態検出装置
JP2001085071A (ja) * 1999-09-13 2001-03-30 Toyota Motor Corp 組電池の温度検出装置および温度検出方法
JP2010246320A (ja) * 2009-04-09 2010-10-28 Fujitsu Ten Ltd 制御装置及び制御方法
JP2011018532A (ja) * 2009-07-08 2011-01-27 Toyota Motor Corp 二次電池の温度推定装置
WO2019097664A1 (fr) * 2017-11-17 2019-05-23 三菱電機株式会社 Dispositif d'estimation de durée de vie de batterie
JP2019124612A (ja) * 2018-01-18 2019-07-25 日立オートモティブシステムズ株式会社 二次電池システム

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2022244008A1 (fr) * 2021-05-20 2022-11-24 Ariel Scientific Innovations Ltd. Outil de dimensionnement en temps réel utilisant la modélisation générique de système de stockage d'énergie

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