WO2023176028A1 - Battery state estimation device, battery system, and battery state estimation method - Google Patents

Battery state estimation device, battery system, and battery state estimation method Download PDF

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WO2023176028A1
WO2023176028A1 PCT/JP2022/038268 JP2022038268W WO2023176028A1 WO 2023176028 A1 WO2023176028 A1 WO 2023176028A1 JP 2022038268 W JP2022038268 W JP 2022038268W WO 2023176028 A1 WO2023176028 A1 WO 2023176028A1
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battery
calculation unit
difference
state
estimating
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PCT/JP2022/038268
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French (fr)
Japanese (ja)
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ラフル クマル
亨 河野
穣 植田
アキラ 藤本
博也 藤本
絵里 磯崎
慧土 秋月
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株式会社日立ハイテク
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Publication of WO2023176028A1 publication Critical patent/WO2023176028A1/en

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L3/00—Electric devices on electrically-propelled vehicles for safety purposes; Monitoring operating variables, e.g. speed, deceleration or energy consumption
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
    • B60L58/10—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries
    • B60L58/16—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries responding to battery ageing, e.g. to the number of charging cycles or the state of health [SoH]
    • 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]
    • G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
    • G01R31/3835—Arrangements for monitoring battery or accumulator variables, e.g. SoC involving only voltage measurements
    • 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]
    • G01R31/385—Arrangements for measuring battery or accumulator variables
    • G01R31/387—Determining ampere-hour charge capacity or SoC
    • G01R31/388—Determining ampere-hour charge capacity or SoC involving voltage measurements
    • 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
    • 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
    • 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 estimating the state of a battery.
  • SOH state of health
  • Patent Document 1 describes a technique for diagnosing the deterioration state of a battery.
  • the document states, ⁇ Evaluate the state of a storage battery system with high accuracy.
  • a storage battery condition evaluation system that evaluates the condition of a storage battery system consisting of a plurality of storage battery cells, which is a storage battery condition evaluation system that evaluates the condition of a storage battery system consisting of a plurality of storage battery cells, in which at least one of the voltages of the plurality of storage battery cells has different positions in the voltage distribution. It has a memory that holds the voltages of the two storage battery cells, and a deterioration state calculation unit that calculates the slope of the voltage with respect to time during the rest period after discharge of at least the two storage battery cells. ” (see summary).
  • the initial stage of the rest period due to the environment in which the measurement work is performed, it may not be possible to secure sufficient sampling points for the battery voltage in the period immediately after charging and discharging is completed (the initial stage of the rest period). Since it is not possible to sufficiently obtain the battery voltage at the initial stage of the rest period, it is difficult to accurately perform diagnosis within a short time after charging and discharging are completed. That is, in this case as well, as in the case where the sampling rate is low, the accuracy of the diagnosis using the temporal fluctuation of the battery voltage at the beginning of the rest period is not considered to be sufficient.
  • the present invention has been made in view of the above-mentioned problems, and is a technology for estimating the deterioration state of a battery using the voltage characteristics during the rest period after charging and discharging the battery.
  • the purpose is to accurately estimate the deterioration state of a battery even when a sufficient number of values cannot be obtained.
  • the battery state estimation device specifies the baseline voltage of the battery voltage in a period after a predetermined period of time has passed after the start of the rest period, and according to the difference between the baseline voltage and the battery voltage, A time differential of the battery voltage within the predetermined time is estimated, and a deterioration state of the battery is estimated using the time differential.
  • the battery condition estimating device in the technique of estimating the deterioration state of a battery using the voltage characteristics during the rest period after charging and discharging the battery, a sufficient number of battery voltage sampling values at the beginning of the rest period can be obtained. Even in cases where the deterioration state of the battery cannot be estimated, the deterioration state of the battery can be estimated with high accuracy.
  • FIG. 2 is a graph showing a change in battery voltage over time during a rest period after a secondary battery performs a discharging operation.
  • 1 shows various forms of battery state estimation devices that estimate the state of a secondary battery.
  • 1 shows a functional block diagram of a battery state estimation device 100 according to the first embodiment and a processing flow for estimating a deterioration state.
  • 3 shows a functional block diagram of a battery state estimating device according to a second embodiment and a processing flow for estimating a deterioration state.
  • FIG. This is an example of the first correspondence relationship.
  • This is an example of the third correspondence relationship.
  • This is an example of the second correspondence relationship.
  • An example of actual measurement of impedance of a battery cell measured using EIS is shown.
  • An example of an equivalent circuit diagram of a secondary battery is shown.
  • ⁇ Embodiment 1> As described above, existing techniques for quickly diagnosing the deterioration state of a secondary battery generally require a high sampling rate.
  • the present invention provides a technique that can estimate the SOH of a secondary battery at a low sampling rate without having to attach or detach the secondary battery to a device equipped with the secondary battery.
  • FIG. 1 is a graph showing temporal fluctuations in battery voltage during a rest period after a secondary battery performs a discharging operation.
  • the rest period can be divided into a period T1 in which the battery voltage fluctuates sharply and a subsequent period T2 in which it fluctuates slowly.
  • the SOH can be estimated within a short time.
  • the battery voltage fluctuates rapidly during the period T1
  • the present invention provides a technique for accurately estimating the SOH without using a high sampling rate (even if there are few sampling points in the period T1) using the battery voltage characteristics in the period T2.
  • the baseline voltage shown in FIG. 1 and its updating will be explained using a flowchart described later.
  • FIG. 2 shows various forms of battery state estimation devices that estimate the state of a secondary battery.
  • the battery voltage (as well as battery current, battery temperature, etc.) of a secondary battery installed in an electric vehicle (EV) is obtained using a charging/discharging device, a measuring device, an on-board diagnostic (OBD) device, etc. be able to.
  • OBD on-board diagnostic
  • a measuring device communicates with the battery system to obtain measured values such as battery voltage.
  • These measurement devices can transmit measured values and the like to the data acquisition unit 110 without being removed from a device equipped with a battery (an EV or a power storage system in this example).
  • Measured values such as battery voltage obtained by these devices can be used by the devices themselves to estimate the battery status, or once the measured values have been uploaded to the cloud platform, the server computer can use them to estimate the battery status. can be estimated. By accessing the cloud platform using a computer (PC) or mobile terminal, the estimation results can be viewed.
  • PC computer
  • These devices that estimate the battery state can be configured as a battery state estimation device according to the present invention.
  • FIG. 3 shows a functional block diagram of the battery state estimating device 100 according to the first embodiment and a processing flow for estimating the deterioration state.
  • the battery state estimation device 100 includes a data acquisition section 110 and a processor 120.
  • the data acquisition unit 110 acquires data such as the measured value of the battery voltage of the secondary battery, the start time and end time of T1 explained in FIG. 1, etc. from a measuring device, for example.
  • Processor 120 estimates the deterioration state of the secondary battery according to the flowchart shown in FIG. Each step in FIG. 3 will be explained below.
  • a controller for example, a battery management unit: BMU
  • BMU battery management unit
  • processor 120 determines whether the secondary battery has entered a rest period. If the system enters the suspension period, perform the following steps; otherwise, there is no need to perform this flowchart.
  • the controller may be configured as part of the battery state estimating device 100, or may be configured as part of a battery system including a secondary battery.
  • the processor 120 may determine by itself whether the secondary battery has entered a rest period. For example, it may be determined that the idle period has entered when the charging/discharging current becomes less than a threshold value (typically 0) or when this state continues for a threshold time or longer. Other appropriate criteria may also be used.
  • a threshold value typically 0
  • Other appropriate criteria may also be used.
  • the data acquisition unit 110 acquires data such as the measured value of the battery voltage of the secondary voltage, the start time and end time of T1 explained in FIG. 1, and the initial baseline voltage (B0). These values may be obtained, for example, from a charge/discharge controller, or may be obtained by accessing values once stored in a storage device such as cloud storage. Fixed values other than the measured values may be stored in advance in the storage device of the battery state estimating device as initial values.
  • the processor 120 acquires these from the data acquisition unit 110, and sets the periods T1 and T2 and the initial baseline voltage based on this.
  • Processor 120 calculates the difference ⁇ V between the current baseline voltage (initial baseline voltage B0 when performing this step for the first time) and the battery voltage.
  • the sampling point of the battery voltage it is desirable to use a point at which the temporal fluctuation of the battery voltage becomes stable. That is, it is desirable to set the difference between the sampling point and the baseline voltage at a point in time when the slope of the battery voltage is almost flat during period T2 to be ⁇ V.
  • the processor 120 uses the calculated ⁇ V to determine the tentative SOH by referring to data describing a first correspondence relationship (exampled later) between ⁇ V and the SOH.
  • the data acquisition unit 110 may acquire this correspondence data from a controller, cloud storage, etc., or it may be stored in advance in a storage device included in the battery state estimation device and the data acquisition unit 110 acquires the data. It's okay. The same applies to other correspondence data described later.
  • Step S303 Part 1
  • the processor 120 uses the SOH provisionally acquired in S302 to data describing a second correspondence relationship (exampled later) between the time rate of change (dV/dt) of the battery voltage in the period T1 and the SOH. By doing so, dV/dt in period T1 is estimated. This step has the significance of being able to obtain the dV/dt during the period T1 without obtaining the measured value of the battery voltage during the period T1.
  • Processor 120 uses the estimated dV/dt to update the baseline voltage. Specifically, for example, the changed dV/dt is multiplied by a minute time (if T1 is about several hundred ms, a minute time of about several ms). This allows an increase in battery voltage to be obtained.
  • the baseline voltage can be updated by adding the increment to the current baseline voltage. If the end of T1 is reached through the repetition described below, the baseline voltage is not updated any further.
  • Processor 120 recalculates ⁇ V using the updated baseline voltages (eg, B1, B2 in FIG. 1).
  • the processor 120 re-obtains the SOH by referring to the first correspondence using the recalculated ⁇ V.
  • the processor 120 repeats S303 to S304 until the SOH converges.
  • the SOH may be repeatedly acquired until the difference between the previous value and the current value of the SOH becomes less than a threshold value.
  • Embodiment 2 of the present invention in addition to the low sampling rate described in Embodiment 1, a method for estimating SOH in a case where charging/discharging current is performed at a low C rate will be described. That is, the data acquisition unit 110 acquires the measured value of the battery voltage during the rest period after being charged and discharged at the low C rate.
  • FIG. 4 shows a functional block diagram of a battery state estimating device according to the second embodiment and a processing flow for estimating a deterioration state.
  • S401 and S402 are performed instead of S303.
  • the other configurations are the same as in the first embodiment.
  • the processor 120 uses ⁇ V estimated by the conversion in S401 to refer to the first correspondence relationship to obtain the temporary SOH again.
  • Processor 120 estimates dV/dt in period T1 by referring to the second correspondence using the temporary SOH.
  • the processor 120 updates the baseline voltage similarly to S303: Part 2.
  • FIG. 5A is an example of the first correspondence.
  • the correspondence between ⁇ V and SOH can be obtained, for example, by actually measuring ⁇ V for each value of SOH of the secondary battery. If the values vary widely, the correspondence may be defined using an approximation function.
  • FIG. 5A shows an example of approximation using a linear function.
  • FIG. 5B is an example of the third correspondence relationship.
  • the correspondence between ⁇ V and C rate can be defined for each value of SOH.
  • This correspondence relationship can be obtained, for example, by actually measuring ⁇ V for each C rate value and SOH value of the secondary battery. It may be defined using an approximation function similarly to FIG. 5A.
  • FIG. 5B shows an example of approximation using a linear function.
  • the processor 120 uses the current ⁇ V and SOH to refer to the correspondence of FIG. 5B, thereby obtaining a ⁇ V of a higher C rate within the correspondence. This allows ⁇ V to be converted to a value at a higher C rate.
  • FIG. 5C is an example of the second correspondence relationship.
  • the correspondence between dV/dt and SOH can be defined for each value of the C rate (in the first embodiment, the C rate is a fixed value).
  • This correspondence relationship can be obtained, for example, by actually measuring dV/dt for each SOH value and C rate value. It may be defined using an approximation function similarly to FIG. 5A.
  • FIG. 5C shows an example of approximation using a high-order function (second-order or higher).
  • the processor 120 can estimate dV/dt by using the current C rate and SOH and referring to the correspondence in FIG. 5C.
  • Embodiment 3 of the present invention a method for determining the time length of period T1 will be described.
  • the other configurations are the same as those in Embodiments 1 and 2.
  • EIS electrochemical impedance spectroscopy
  • FIG. 6 shows an example of actual measurement of impedance of a battery cell measured using EIS.
  • impedance characteristics can be obtained for each battery and for each frequency band. From this impedance characteristic, a time domain that requires a high sampling rate (to the left of the vertical dotted line in FIG. 6) and a time domain that requires a low sampling rate (to the right of the vertical dotted line in FIG. 6) can be obtained.
  • the time length of the period T1 can be defined for each secondary battery.
  • the data acquisition unit 110 may acquire data describing the definition.
  • FIG. 7 shows an example of an equivalent circuit diagram of a secondary battery.
  • the upper part of FIG. 7 shows a second-order model, and the lower part of FIG. 7 shows a first-order model.
  • the present invention is not limited to the embodiments described above, and includes various modifications.
  • the above-described embodiments have been described in detail to explain the present invention in an easy-to-understand manner, and the present invention is not necessarily limited to having all the configurations described.
  • the SOH is estimated during the rest period after the battery discharge operation, but if a change over time in the output voltage corresponding to the SOH appears during the rest period after the charging operation, the above method can be used.
  • SOH can be estimated similarly to the embodiment. Whether a change with time that correlates with SOH appears in the rest period after the discharging operation, the rest period after the charging operation, or both of these depends on the characteristics of the battery. Therefore, it is sufficient to estimate the SOH in any one of these depending on the characteristics of the battery.
  • a measured value of battery voltage, etc. can be obtained via the data acquisition unit 110 from any measurement device built into a device equipped with a secondary battery or any measurement device externally attached to the device. By acquiring the information, the method according to the present invention can be implemented.
  • the processor 120 can be configured by hardware such as a circuit device implementing the function, or alternatively, the processor 120 can be configured by software implementing the function by an arithmetic device such as a CPU (Central Processing Unit). It can also be configured by running
  • the present invention is also applicable to other types of secondary batteries.
  • the present invention is applicable to secondary batteries such as lead acid batteries, nickel-cadmium batteries, electric double layer capacitors, and the like.

Abstract

The purpose of the present invention, in relation to technology for estimating the state of degradation of a battery using voltage characteristics during a rest period after charging/discharging of the battery, is to accurately estimate the state of degradation of the battery even when it is not possible to obtain a sufficient number of sampling values of the battery voltage in the initial period of the rest period. A battery state estimation device according to the present invention identifies a baseline voltage of a battery voltage during a period after a prescribed time has elapsed after the start of a rest period, estimates the time differential of the battery voltage within the prescribed time according to the difference between the baseline voltage and the battery voltage, and estimates the state of degradation of the battery using the time differential (refer to fig. 1).

Description

電池状態推定装置、電池システム、電池状態推定方法Battery condition estimation device, battery system, battery condition estimation method
　本発明は、電池の状態を推定する技術に関する。 The present invention relates to a technique for estimating the state of a battery.
　２次電池の劣化状態（Ｓｔａｔｅ　Ｏｆ　Ｈｅａｌｔｈ：ＳＯＨ）を高速に推定する診断技術は、需要が高まっている。この技術は、電気自動車や電力蓄積システムなどにおける２次電池のライフサイクルを管理するために重要である。使用済蓄電池を迅速に診断する技術に対する市場からのニーズが増加しており、蓄電池を搭載した機器に対して蓄電池を着脱することなる、蓄電池の劣化状態を高速に診断することが望まれている。このためには、電源負荷装置と電池測定装置の組み合わせごとに適切な診断方法を提供する必要がある。 There is an increasing demand for diagnostic technology that quickly estimates the state of health (SOH) of secondary batteries. This technology is important for managing the life cycle of secondary batteries in electric vehicles, power storage systems, and the like. There is an increasing need in the market for technology that quickly diagnoses used storage batteries, and it is desired to quickly diagnose the deterioration state of storage batteries, which involves attaching and removing batteries to devices equipped with storage batteries. . For this purpose, it is necessary to provide an appropriate diagnostic method for each combination of power supply load device and battery measuring device.
　特許文献１は、電池の劣化状態を診断する技術について記載している。同文献は、『蓄電池システムの状態を精度よく評価する。』ことを課題として、『複数の蓄電池セルからなる蓄電池システムの状態を評価する蓄電池状態評価システムであって、複数の蓄電池セルの電圧のうち、複数の蓄電池セルの電圧の分布における位置が異なる少なくとも二つの蓄電池セルの電圧を保持するメモリと、少なくとも二つの蓄電池セルの放電後の休止期間における電圧の時間に対する傾きを計算する劣化状態計算部と、を有する。』という技術を記載している（要約参照）。 Patent Document 1 describes a technique for diagnosing the deterioration state of a battery. The document states, ``Evaluate the state of a storage battery system with high accuracy. ``A storage battery condition evaluation system that evaluates the condition of a storage battery system consisting of a plurality of storage battery cells, which is a storage battery condition evaluation system that evaluates the condition of a storage battery system consisting of a plurality of storage battery cells, in which at least one of the voltages of the plurality of storage battery cells has different positions in the voltage distribution. It has a memory that holds the voltages of the two storage battery cells, and a deterioration state calculation unit that calculates the slope of the voltage with respect to time during the rest period after discharge of at least the two storage battery cells. ” (see summary).
特開２０２０－１６９９４３号公報JP2020-169943A
　特許文献１のように、休止期間における電圧特性を用いた高速診断は、電圧測定が高いサンプリングレートで実施される場合においては適している。短時間内に電池を診断するためには、その短時間内に多くの計測点を得る必要があるので、サンプリングレートが高いことが望ましいからである。換言するとこの技術は、サンプリングレートが低ければ、劣化状態の推定精度が下がる可能性がある。 As in Patent Document 1, high-speed diagnosis using voltage characteristics during the rest period is suitable when voltage measurement is performed at a high sampling rate. This is because in order to diagnose the battery within a short period of time, it is necessary to obtain many measurement points within that short period of time, so a high sampling rate is desirable. In other words, with this technique, if the sampling rate is low, the accuracy of estimating the state of deterioration may decrease.
　また、例えば計測作業を実施する環境に起因して、充放電が完了した直後の期間（休止期間の初期段階）における電池電圧のサンプリング点を十分に確保できない場合がある。休止期間の初期段階における電池電圧を十分に取得できないので、充放電完了後の短時間内に診断を精度よく実施するのは困難である。すなわちこの場合も、サンプリングレートが低い場合と同様に、休止期間初期の電池電圧の経時変動を用いた診断の精度は、十分ではないと考えられる。 Additionally, for example, due to the environment in which the measurement work is performed, it may not be possible to secure sufficient sampling points for the battery voltage in the period immediately after charging and discharging is completed (the initial stage of the rest period). Since it is not possible to sufficiently obtain the battery voltage at the initial stage of the rest period, it is difficult to accurately perform diagnosis within a short time after charging and discharging are completed. That is, in this case as well, as in the case where the sampling rate is low, the accuracy of the diagnosis using the temporal fluctuation of the battery voltage at the beginning of the rest period is not considered to be sufficient.
　本発明は、上記のような課題に鑑みてなされたものであり、電池の充放電後の休止期間における電圧特性を用いて電池の劣化状態を推定する技術において、休止期間初期における電池電圧のサンプリング値を十分な個数得られない場合であっても、電池の劣化状態を精度よく推定することを目的とする。 The present invention has been made in view of the above-mentioned problems, and is a technology for estimating the deterioration state of a battery using the voltage characteristics during the rest period after charging and discharging the battery. The purpose is to accurately estimate the deterioration state of a battery even when a sufficient number of values cannot be obtained.
　本発明に係る電池状態推定装置は、休止期間が開始してから所定時間経過後の期間における電池電圧のベースライン電圧を特定し、前記ベースライン電圧と前記電池電圧との間の差分にしたがって、前記所定時間内の前記電池電圧の時間微分を推定し、前記時間微分を用いて電池の劣化状態を推定する。 The battery state estimation device according to the present invention specifies the baseline voltage of the battery voltage in a period after a predetermined period of time has passed after the start of the rest period, and according to the difference between the baseline voltage and the battery voltage, A time differential of the battery voltage within the predetermined time is estimated, and a deterioration state of the battery is estimated using the time differential.
　本発明に係る電池状態推定装置によれば、電池の充放電後の休止期間における電圧特性を用いて電池の劣化状態を推定する技術において、休止期間初期における電池電圧のサンプリング値を十分な個数得られない場合であっても、電池の劣化状態を精度よく推定することができる。 According to the battery condition estimating device according to the present invention, in the technique of estimating the deterioration state of a battery using the voltage characteristics during the rest period after charging and discharging the battery, a sufficient number of battery voltage sampling values at the beginning of the rest period can be obtained. Even in cases where the deterioration state of the battery cannot be estimated, the deterioration state of the battery can be estimated with high accuracy.
２次電池が放電動作を実施した後の休止期間における電池電圧の経時変動を示すグラフである。2 is a graph showing a change in battery voltage over time during a rest period after a secondary battery performs a discharging operation. ２次電池の状態を推定する電池状態推定装置の様々な形態を示す。1 shows various forms of battery state estimation devices that estimate the state of a secondary battery. 実施形態１に係る電池状態推定装置１００の機能ブロック図および劣化状態を推定するための処理フローを示す。1 shows a functional block diagram of a battery state estimation device 100 according to the first embodiment and a processing flow for estimating a deterioration state. 実施形態２に係る電池状態推定装置の機能ブロック図および劣化状態を推定するための処理フローを示す。3 shows a functional block diagram of a battery state estimating device according to a second embodiment and a processing flow for estimating a deterioration state. FIG. 第１対応関係の例である。This is an example of the first correspondence relationship. 第３対応関係の例である。This is an example of the third correspondence relationship. 第２対応関係の例である。This is an example of the second correspondence relationship. ＥＩＳを用いて測定した電池セルのインピーダンスの実測例を示す。An example of actual measurement of impedance of a battery cell measured using EIS is shown. ２次電池の等価回路図の例を示す。An example of an equivalent circuit diagram of a secondary battery is shown.
＜実施の形態１＞
　先に説明したように、２次電池の劣化状態を高速に診断する既存技術は一般に、高いサンプリングレートを必要とする。本発明は、２次電池を搭載した機器に対して２次電池を着脱することなく、低サンプリングレートで２次電池のＳＯＨを推定することができる技術を提供する。 <Embodiment 1>
As described above, existing techniques for quickly diagnosing the deterioration state of a secondary battery generally require a high sampling rate. The present invention provides a technique that can estimate the SOH of a secondary battery at a low sampling rate without having to attach or detach the secondary battery to a device equipped with the secondary battery.
　図１は、２次電池が放電動作を実施した後の休止期間における電池電圧の経時変動を示すグラフである。図１に示すように、休止期間は、電池電圧が急峻に変動する期間Ｔ１とその後の緩やかに変動する期間Ｔ２に分けることができる。期間Ｔ１における電池電圧の時間変化率（ｄＶ／ｄｔ）を用いてＳＯＨを推定することにより、ＳＯＨを短時間内で推定することができる。他方で期間Ｔ１においては電池電圧が急峻に変動するので、正確な推定のためには、電池電圧のサンプリング点を短時間内に多くとる必要がある。すなわち高いサンプリングレートが必要である。したがって、例えば計測機器の制約などに起因して高サンプリングレートで電池電圧をサンプリングすることが難しい場合は、推定精度が低下する可能性がある。 FIG. 1 is a graph showing temporal fluctuations in battery voltage during a rest period after a secondary battery performs a discharging operation. As shown in FIG. 1, the rest period can be divided into a period T1 in which the battery voltage fluctuates sharply and a subsequent period T2 in which it fluctuates slowly. By estimating the SOH using the time rate of change (dV/dt) of the battery voltage during the period T1, the SOH can be estimated within a short time. On the other hand, since the battery voltage fluctuates rapidly during the period T1, for accurate estimation, it is necessary to take many sampling points of the battery voltage within a short period of time. That is, a high sampling rate is required. Therefore, if it is difficult to sample the battery voltage at a high sampling rate due to, for example, restrictions on measuring equipment, the estimation accuracy may decrease.
　例えば電池電圧を計測する環境に起因して、期間Ｔ１における電池電圧の経時変動を十分取得できない場合がある。この場合もサンプリングレートが低い場合と同様に、期間Ｔ１における電池電圧のサンプリング点を十分な個数とることができない。したがって同様に推定精度が低下する可能性がある。 For example, due to the environment in which the battery voltage is measured, it may not be possible to sufficiently acquire the temporal fluctuations in the battery voltage during the period T1. In this case as well, as in the case where the sampling rate is low, a sufficient number of battery voltage sampling points cannot be taken during the period T1. Therefore, estimation accuracy may similarly decrease.
　そこで本発明においては、期間Ｔ２における電池電圧特性を用いて、高いサンプリングレートを用いることなく（期間Ｔ１におけるサンプリング点が少ない場合であっても）ＳＯＨを精度よく推定する技術を提供する。図１に示すベースライン電圧とその更新については、後述のフローチャートを用いて説明する。 Therefore, the present invention provides a technique for accurately estimating the SOH without using a high sampling rate (even if there are few sampling points in the period T1) using the battery voltage characteristics in the period T2. The baseline voltage shown in FIG. 1 and its updating will be explained using a flowchart described later.
　図２は、２次電池の状態を推定する電池状態推定装置の様々な形態を示す。例えば電気自動車（Ｅｌｅｃｔｒｉｃ　Ｖｅｈｉｃｌｅ：ＥＶ）が搭載している２次電池の電池電圧（電池電流、電池温度なども同様）は、充放電機器、計測機器、オンボード診断（ＯＢＤ）装置などによって取得することができる。定置型蓄電システムなどのように大型の設備については、例えば計測機器が電池システムと通信することによって電池電圧などの計測値を取得する。これらの測定デバイスは、電池を搭載した機器（この例においてはＥＶや蓄電システム）から取り外すことなく、データ取得部１１０に対して測定値などを送信することができる。 FIG. 2 shows various forms of battery state estimation devices that estimate the state of a secondary battery. For example, the battery voltage (as well as battery current, battery temperature, etc.) of a secondary battery installed in an electric vehicle (EV) is obtained using a charging/discharging device, a measuring device, an on-board diagnostic (OBD) device, etc. be able to. For large equipment such as a stationary power storage system, for example, a measuring device communicates with the battery system to obtain measured values such as battery voltage. These measurement devices can transmit measured values and the like to the data acquisition unit 110 without being removed from a device equipped with a battery (an EV or a power storage system in this example).
　これらのデバイスが取得した電池電圧などの計測値は、デバイス自身が用いることによって電池状態を推定するか、または、いったんクラウドプラットフォームに対して計測値をアップロードした後にサーバコンピュータがこれを用いて電池状態を推定することができる。クラウドプラットフォームに対してコンピュータ（ＰＣ）や携帯端末を用いてアクセスすることにより、その推定結果を閲覧することができる。電池状態を推定するこれらの装置は、本発明に係る電池状態推定装置として構成することができる。 Measured values such as battery voltage obtained by these devices can be used by the devices themselves to estimate the battery status, or once the measured values have been uploaded to the cloud platform, the server computer can use them to estimate the battery status. can be estimated. By accessing the cloud platform using a computer (PC) or mobile terminal, the estimation results can be viewed. These devices that estimate the battery state can be configured as a battery state estimation device according to the present invention.
　図３は、実施形態１に係る電池状態推定装置１００の機能ブロック図および劣化状態を推定するための処理フローを示す。電池状態推定装置１００は、データ取得部１１０、プロセッサ１２０を備える。データ取得部１１０は、例えば計測装置などから、２次電池の電池電圧の計測値、図１で説明したＴ１の開始時刻と終了時刻、などのデータを取得する。プロセッサ１２０は、図３に示すフローチャートにしたがって、２次電池の劣化状態を推定する。以下図３の各ステップを説明する。 FIG. 3 shows a functional block diagram of the battery state estimating device 100 according to the first embodiment and a processing flow for estimating the deterioration state. The battery state estimation device 100 includes a data acquisition section 110 and a processor 120. The data acquisition unit 110 acquires data such as the measured value of the battery voltage of the secondary battery, the start time and end time of T1 explained in FIG. 1, etc. from a measuring device, for example. Processor 120 estimates the deterioration state of the secondary battery according to the flowchart shown in FIG. Each step in FIG. 3 will be explained below.
（図３：ステップＳ３０１）
　２次電池の充放電動作を制御するコントローラ（例えばバッテリ管理ユニット：ＢＭＵ）は、２次電池に対して充放電動作を指示するコマンドを送信する。プロセッサ１２０はそのコマンドにしたがって、２次電池が休止期間に入ったか否かを判定する。休止期間に入った場合は以下のステップを実施し、それ以外であれば本フローチャートを実施する必要はない。コントローラは電池状態推定装置１００の一部として構成してもよいし、２次電池を含む電池システムの一部として構成してもよい。 (Figure 3: Step S301)
A controller (for example, a battery management unit: BMU) that controls charging and discharging operations of a secondary battery transmits a command instructing a charging and discharging operation to the secondary battery. According to the command, processor 120 determines whether the secondary battery has entered a rest period. If the system enters the suspension period, perform the following steps; otherwise, there is no need to perform this flowchart. The controller may be configured as part of the battery state estimating device 100, or may be configured as part of a battery system including a secondary battery.
（図３：ステップＳ３０１：補足）
　プロセッサ１２０はこれに代えて、２次電池が休止期間に入ったか否かを自ら判断してもよい。例えば充放電電流が閾値未満（典型的には０）になったかあるいはその状態が閾値時間以上継続したことにより、休止期間に入ったと判断してもよい。その他適当な判断基準を用いてもよい。 (Figure 3: Step S301: Supplement)
Alternatively, the processor 120 may determine by itself whether the secondary battery has entered a rest period. For example, it may be determined that the idle period has entered when the charging/discharging current becomes less than a threshold value (typically 0) or when this state continues for a threshold time or longer. Other appropriate criteria may also be used.
（図３：ステップＳ３０２：その１）
　データ取得部１１０は、２次電圧の電池電圧の計測値、図１で説明したＴ１の開始時刻と終了時刻、初期ベースライン電圧（Ｂ０）、などのデータを取得する。これらの値は、例えば充放電コントローラから取得してもよいし、クラウドストレージなどの記憶装置にいったん格納された値に対してアクセスすることにより取得してもよい。計測値以外の固定値については、初期値としてあらかじめ電池状態推定装置の記憶装置内に格納しておいてもよい。プロセッサ１２０は、データ取得部１１０からこれらを取得し、これに基づき期間Ｔ１とＴ２および初期ベースライン電圧を設定する。 (Figure 3: Step S302: Part 1)
The data acquisition unit 110 acquires data such as the measured value of the battery voltage of the secondary voltage, the start time and end time of T1 explained in FIG. 1, and the initial baseline voltage (B0). These values may be obtained, for example, from a charge/discharge controller, or may be obtained by accessing values once stored in a storage device such as cloud storage. Fixed values other than the measured values may be stored in advance in the storage device of the battery state estimating device as initial values. The processor 120 acquires these from the data acquisition unit 110, and sets the periods T1 and T2 and the initial baseline voltage based on this.
（図３：ステップＳ３０２：その２）
　プロセッサ１２０は、現在のベースライン電圧（本ステップを最初に実施するときは初期ベースライン電圧Ｂ０）と、電池電圧との間の差分ΔＶを計算する。電池電圧のサンプリング点としては、電池電圧の経時変動が安定した時点におけるものを用いることが望ましい。すなわち、期間Ｔ２における電池電圧の傾きが平坦に近い時点のサンプリング点とベースライン電圧との間の差分を、ΔＶとすることが望ましい。 (Figure 3: Step S302: Part 2)
Processor 120 calculates the difference ΔV between the current baseline voltage (initial baseline voltage B0 when performing this step for the first time) and the battery voltage. As the sampling point of the battery voltage, it is desirable to use a point at which the temporal fluctuation of the battery voltage becomes stable. That is, it is desirable to set the difference between the sampling point and the baseline voltage at a point in time when the slope of the battery voltage is almost flat during period T2 to be ΔV.
（図３：ステップＳ３０２：補足）
　本ステップにおいて、電池電圧の計測値は、期間Ｔ２におけるものを取得すればよく、期間Ｔ１における計測値は必要ない。すなわち計測装置は、期間Ｔ１において高サンプリングレートで電池電圧を計測する必要はない。 (Figure 3: Step S302: Supplement)
In this step, it is sufficient to obtain the measured value of the battery voltage in the period T2, and the measured value in the period T1 is not necessary. That is, the measuring device does not need to measure the battery voltage at a high sampling rate during period T1.
（図３：ステップＳ３０２：その３）
　プロセッサ１２０は、計算したΔＶを用いて、ΔＶとＳＯＨとの間の第１対応関係（後に例示する）を記述したデータを参照することにより、仮ＳＯＨを判定する。この対応関係データは、データ取得部１１０がコントローラやクラウドストレージなどから取得してもよいし、電池状態推定装置が備える記憶装置内にあらかじめ格納しておいてデータ取得部１１０がそのデータを取得してもよい。後述するその他の対応関係データについても同様である。 (Figure 3: Step S302: Part 3)
The processor 120 uses the calculated ΔV to determine the tentative SOH by referring to data describing a first correspondence relationship (exampled later) between ΔV and the SOH. The data acquisition unit 110 may acquire this correspondence data from a controller, cloud storage, etc., or it may be stored in advance in a storage device included in the battery state estimation device and the data acquisition unit 110 acquires the data. It's okay. The same applies to other correspondence data described later.
（図３：ステップＳ３０３：その１）
　プロセッサ１２０は、Ｓ３０２において仮取得したＳＯＨを用いて、期間Ｔ１における電池電圧の時間変化率（ｄＶ／ｄｔ）とＳＯＨとの間の第２対応関係（後に例示する）を記述したデータを参照することにより、期間Ｔ１におけるｄＶ／ｄｔを推定する。本ステップは、期間Ｔ１における電池電圧の計測値を取得することなく、期間Ｔ１におけるｄＶ／ｄｔを得ることができる意義がある。 (Figure 3: Step S303: Part 1)
Using the SOH provisionally acquired in S302, the processor 120 refers to data describing a second correspondence relationship (exampled later) between the time rate of change (dV/dt) of the battery voltage in the period T1 and the SOH. By doing so, dV/dt in period T1 is estimated. This step has the significance of being able to obtain the dV/dt during the period T1 without obtaining the measured value of the battery voltage during the period T1.
（図３：ステップＳ３０３：その２）
　プロセッサ１２０は、推定したｄＶ／ｄｔを用いて、ベースライン電圧を更新する。具体的には例えば、推移したｄＶ／ｄｔに対して微小時間（Ｔ１が数百ｍｓ程度であれば数ｍｓ程度の微小時間）を乗算する。これにより電池電圧の増分を得ることができる。現在のベースライン電圧に対してその増分を加算することにより、ベースライン電圧を更新することができる。後述する繰り返しによってＴ１の終端に到達した場合は、ベースライン電圧をそれ以上更新しない。 (Figure 3: Step S303: Part 2)
Processor 120 uses the estimated dV/dt to update the baseline voltage. Specifically, for example, the changed dV/dt is multiplied by a minute time (if T1 is about several hundred ms, a minute time of about several ms). This allows an increase in battery voltage to be obtained. The baseline voltage can be updated by adding the increment to the current baseline voltage. If the end of T1 is reached through the repetition described below, the baseline voltage is not updated any further.
（図３：ステップＳ３０４）
　プロセッサ１２０は、更新したベースライン電圧（例：図１におけるＢ１、Ｂ２）を用いて、ΔＶを再計算する。プロセッサ１２０は、再計算したΔＶを用いて第１対応関係を参照することにより、ＳＯＨを再取得する。 (Figure 3: Step S304)
Processor 120 recalculates ΔV using the updated baseline voltages (eg, B1, B2 in FIG. 1). The processor 120 re-obtains the SOH by referring to the first correspondence using the recalculated ΔV.
（図３：ステップＳ３０５）
　プロセッサ１２０は、ＳＯＨが収束するまで、Ｓ３０３～Ｓ３０４を繰り返す。例えばＳＯＨの前回値と今回値との間の差分が閾値未満になるまで、ＳＯＨを繰り返し取得すればよい。 (Figure 3: Step S305)
The processor 120 repeats S303 to S304 until the SOH converges. For example, the SOH may be repeatedly acquired until the difference between the previous value and the current value of the SOH becomes less than a threshold value.
＜実施の形態２＞
　２次電池の劣化状態を高速に診断する既存技術においては一般に、高いＣレート（１時間で電池を満充電または完全放電できる電流値を１Ｃとする）を用いて２次電池を充放電するのが一般的である。高いＣレートを用いることにより、休止期間における電池電圧の変動が大きくなり、これにより電池電圧を用いた推定精度も向上するからである。 <Embodiment 2>
Existing technologies for quickly diagnosing the deterioration state of secondary batteries generally charge and discharge secondary batteries using a high C rate (1C is the current value that can fully charge or completely discharge a battery in 1 hour). is common. This is because by using a high C rate, fluctuations in battery voltage during the rest period become large, which also improves estimation accuracy using battery voltage.
　しかし２次電池を搭載した機器や計測装置などの制約により、高いＣレートを用いることが困難である場合もあり得る。そこで本発明の実施形態２では、実施形態１で説明した低サンプリングレートに加えて、充放電電流が低Ｃレートによって実施される場合におけるＳＯＨの推定手法を説明する。すなわちデータ取得部１１０は、低Ｃレートによって充放電された後の休止期間における電池電圧の計測値を取得する。 However, it may be difficult to use a high C rate due to restrictions on devices equipped with secondary batteries, measuring devices, etc. Therefore, in Embodiment 2 of the present invention, in addition to the low sampling rate described in Embodiment 1, a method for estimating SOH in a case where charging/discharging current is performed at a low C rate will be described. That is, the data acquisition unit 110 acquires the measured value of the battery voltage during the rest period after being charged and discharged at the low C rate.
　図４は、実施形態２に係る電池状態推定装置の機能ブロック図および劣化状態を推定するための処理フローを示す。本実施形態２においては、Ｓ３０３に代えてＳ４０１とＳ４０２を実施する。その他の構成は実施形態１と同様である。 FIG. 4 shows a functional block diagram of a battery state estimating device according to the second embodiment and a processing flow for estimating a deterioration state. In the second embodiment, S401 and S402 are performed instead of S303. The other configurations are the same as in the first embodiment.
（図４：ステップＳ４０１）
　プロセッサ１２０は、Ｓ３０２において計算したΔＶを用いて、ΔＶとＣレートとＳＯＨとの間の第３対応関係（後に例示する）を記述したデータを参照することにより、Ｓ３０２におけるΔＶを、実際の充放電Ｃレートよりも高いＣレートにおけるΔＶの値へ変換する。 (Figure 4: Step S401)
Using the ΔV calculated in S302, the processor 120 uses the ΔV in S302 to calculate the actual charge by referring to data describing the third correspondence relationship (exampled later) between ΔV, C rate, and SOH. It is converted into a value of ΔV at a C rate higher than the discharge C rate.
（図４：ステップＳ４０２）
　プロセッサ１２０は、Ｓ４０１における変換によって推定したΔＶを用いて、第１対応関係を参照することにより、改めて仮ＳＯＨを取得する。プロセッサ１２０は、その仮ＳＯＨを用いて第２対応関係を参照することにより、期間Ｔ１におけるｄＶ／ｄｔを推定する。プロセッサ１２０は、Ｓ３０３：その２と同様に、ベースライン電圧を更新する。 (Figure 4: Step S402)
The processor 120 uses ΔV estimated by the conversion in S401 to refer to the first correspondence relationship to obtain the temporary SOH again. Processor 120 estimates dV/dt in period T1 by referring to the second correspondence using the temporary SOH. The processor 120 updates the baseline voltage similarly to S303: Part 2.
　図５Ａは、第１対応関係の例である。ΔＶとＳＯＨとの間の対応関係は、例えば２次電池のＳＯＨの値ごとにΔＶを実測するなどによって取得することができる。値のばらつきが大きい場合は、近似関数を用いて対応関係を定義してもよい。図５Ａにおいては１次関数によって近似した例を示した。 FIG. 5A is an example of the first correspondence. The correspondence between ΔV and SOH can be obtained, for example, by actually measuring ΔV for each value of SOH of the secondary battery. If the values vary widely, the correspondence may be defined using an approximation function. FIG. 5A shows an example of approximation using a linear function.
　図５Ｂは、第３対応関係の例である。ΔＶとＣレートとの間の対応関係は、ＳＯＨの値ごとに定義することができる。この対応関係は、例えばＣレートの値および２次電池のＳＯＨの値ごとにΔＶを実測するなどによって取得することができる。図５Ａと同様に近似関数を用いて定義してもよい。図５Ｂにおいては１次関数によって近似した例を示した。プロセッサ１２０はＳ４０１において、現在のΔＶとＳＯＨを用いて図５Ｂの対応関係を参照することにより、その対応関係内においてより高いＣレートのΔＶを得ることができる。これにより、ΔＶをより高いＣレートにおける値へ変換できる。 FIG. 5B is an example of the third correspondence relationship. The correspondence between ΔV and C rate can be defined for each value of SOH. This correspondence relationship can be obtained, for example, by actually measuring ΔV for each C rate value and SOH value of the secondary battery. It may be defined using an approximation function similarly to FIG. 5A. FIG. 5B shows an example of approximation using a linear function. In S401, the processor 120 uses the current ΔV and SOH to refer to the correspondence of FIG. 5B, thereby obtaining a ΔV of a higher C rate within the correspondence. This allows ΔV to be converted to a value at a higher C rate.
　図５Ｃは、第２対応関係の例である。本実施形態２において、ｄＶ／ｄｔとＳＯＨとの間の対応関係は、Ｃレートの値ごとに定義することができる（実施形態１においてはＣレートは固定値である）。この対応関係は、例えばＳＯＨの値およびＣレートの値ごとにｄＶ／ｄｔを実測するなどによって取得することができる。図５Ａと同様に近似関数を用いて定義してもよい。図５Ｃにおいては高次関数（２次以上）によって近似した例を示した。プロセッサ１２０はＳ４０２において、現在のＣレートとＳＯＨを用いて図５Ｃの対応関係を参照することにより、ｄＶ／ｄｔを推定することができる。 FIG. 5C is an example of the second correspondence relationship. In the second embodiment, the correspondence between dV/dt and SOH can be defined for each value of the C rate (in the first embodiment, the C rate is a fixed value). This correspondence relationship can be obtained, for example, by actually measuring dV/dt for each SOH value and C rate value. It may be defined using an approximation function similarly to FIG. 5A. FIG. 5C shows an example of approximation using a high-order function (second-order or higher). At S402, the processor 120 can estimate dV/dt by using the current C rate and SOH and referring to the correspondence in FIG. 5C.
＜実施の形態３＞
　本発明の実施形態３では、期間Ｔ１の時間長を決定する手法について説明する。その他の構成は実施形態１～２と同様である。例えば複数の２次電池に対して電気化学インピーダンス分光法（ＥＩＳ）を用いて電池セルのインピーダンスを測定することにより、Ｔ１の時間長を実験的に決定することが考えられる。 <Embodiment 3>
In Embodiment 3 of the present invention, a method for determining the time length of period T1 will be described. The other configurations are the same as those in Embodiments 1 and 2. For example, it is possible to experimentally determine the time length of T1 by measuring the impedance of a plurality of secondary batteries using electrochemical impedance spectroscopy (EIS).
　図６は、ＥＩＳを用いて測定した電池セルのインピーダンスの実測例を示す。複数の２次電池の異なる周波数に対するインピーダンス特性を分析することにより、電池ごとにおよび周波数帯域ごとに、インピーダンス特性を得ることができる。このインピーダンス特性から、高サンプリングレートを必要とする時間領域（図６縦点線の左側）と低サンプリングレートで足りる時間領域（図６の縦点線の右側）を得ることができる。これに基づき２次電池ごとにルックアップテーブルなどを作成することにより、期間Ｔ１の時間長を２次電池ごとに定義することができる。データ取得部１１０はその定義を記述したデータを取得すればよい。 FIG. 6 shows an example of actual measurement of impedance of a battery cell measured using EIS. By analyzing the impedance characteristics of a plurality of secondary batteries at different frequencies, impedance characteristics can be obtained for each battery and for each frequency band. From this impedance characteristic, a time domain that requires a high sampling rate (to the left of the vertical dotted line in FIG. 6) and a time domain that requires a low sampling rate (to the right of the vertical dotted line in FIG. 6) can be obtained. By creating a lookup table or the like for each secondary battery based on this, the time length of the period T1 can be defined for each secondary battery. The data acquisition unit 110 may acquire data describing the definition.
＜実施の形態４＞
　図７は、２次電池の等価回路図の例を示す。図７上段は２次モデルを示し、図７下段は１次モデルを示す。図７に示すような回路モデルを用いて充放電後の電池電圧の経時変化をシミュレートすることにより、ＳＯＨを推定するために使用できる特定のパラメータを導出することが可能である。しかしこのようなシミュレート手法は、十分な推定精度を得るために長時間にわたる演算時間を必要とする場合がある。また低Ｃレートを用いて充放電する場合は、電池電圧の変動幅が小さいので、フィッティング処理などの精度が不十分となる可能性がある。 <Embodiment 4>
FIG. 7 shows an example of an equivalent circuit diagram of a secondary battery. The upper part of FIG. 7 shows a second-order model, and the lower part of FIG. 7 shows a first-order model. By simulating the change in battery voltage over time after charging and discharging using a circuit model as shown in FIG. 7, it is possible to derive specific parameters that can be used to estimate SOH. However, such a simulation method may require a long calculation time to obtain sufficient estimation accuracy. Furthermore, when charging and discharging using a low C rate, the fluctuation range of the battery voltage is small, so there is a possibility that the accuracy of fitting processing etc. will be insufficient.
　そこで、実施形態１～３で説明した手法と、図７に示す回路モデルによるシミュレーションとを組み合わせることが考えられる。これにより、図７に示すような回路モデル手法を単独で用いる場合よりも、ＳＯＨの推定精度を改善することができると考えられる。 Therefore, it is conceivable to combine the methods described in Embodiments 1 to 3 with the simulation using the circuit model shown in FIG. It is thought that this makes it possible to improve the SOH estimation accuracy compared to the case where the circuit model method shown in FIG. 7 is used alone.
＜本発明の変形例について＞
　本発明は、前述した実施形態に限定されるものではなく、様々な変形例が含まれる。例えば、上記した実施形態は本発明を分かりやす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。また、ある実施形態の構成の一部を他の実施形態の構成に置き換えることが可能であり、また、ある実施形態の構成に他の実施形態の構成を加えることも可能である。また、各実施形態の構成の一部について、他の構成の追加・削除・置換をすることが可能である。 <About modifications of the present invention>
The present invention is not limited to the embodiments described above, and includes various modifications. For example, the above-described embodiments have been described in detail to explain the present invention in an easy-to-understand manner, and the present invention is not necessarily limited to having all the configurations described. Furthermore, it is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. Furthermore, it is possible to add, delete, or replace some of the configurations of each embodiment with other configurations.
　以上の実施形態においては、電池の放電動作後の休止期間においてＳＯＨを推定することを説明したが、充電動作後の休止期間においてＳＯＨと対応する出力電圧の経時変化が現れるのであれば、以上の実施形態と同様にＳＯＨを推定することができる。放電動作後の休止期間、充電動作後の休止期間、またはこれら双方、いずれにおいてＳＯＨと相関を有する経時変化が現れるのか否かは、電池の特性に応じて異なる。したがって電池の特性に応じて、これらのいずれかにおいてＳＯＨを推定すればよい。 In the above embodiment, it has been explained that the SOH is estimated during the rest period after the battery discharge operation, but if a change over time in the output voltage corresponding to the SOH appears during the rest period after the charging operation, the above method can be used. SOH can be estimated similarly to the embodiment. Whether a change with time that correlates with SOH appears in the rest period after the discharging operation, the rest period after the charging operation, or both of these depends on the characteristics of the battery. Therefore, it is sufficient to estimate the SOH in any one of these depending on the characteristics of the battery.
　以上の実施形態（図２）において、電池状態推定装置の実装形態の例を説明したが、その他の実装形態も可能である。例えば、２次電池を搭載した機器内に組み込まれた任意の測定デバイスまたは同機器に対して外部的に取り付けられた任意の測定デバイスから、データ取得部１１０を介して電池電圧の測定値などを取得することにより、本発明に係る手法を実施できる。 In the above embodiment (FIG. 2), an example of the implementation of the battery state estimating device has been described, but other implementations are also possible. For example, a measured value of battery voltage, etc. can be obtained via the data acquisition unit 110 from any measurement device built into a device equipped with a secondary battery or any measurement device externally attached to the device. By acquiring the information, the method according to the present invention can be implemented.
　以上の実施形態において、プロセッサ１２０は、その機能を実装した回路デバイスなどのハードウェアによって構成することもできるし、これに代えてその機能を実装したソフトウェアをＣＰＵ（Ｃｅｎｔｒａｌ　Ｐｒｏｃｅｓｓｉｎｇ　Ｕｎｉｔ）などの演算装置が実行することによって構成することもできる。 In the above embodiments, the processor 120 can be configured by hardware such as a circuit device implementing the function, or alternatively, the processor 120 can be configured by software implementing the function by an arithmetic device such as a CPU (Central Processing Unit). It can also be configured by running
　以上の実施形態においては、２次電池がリチウムイオン電池であることを前提にしているが、その他タイプの２次電池であっても本発明を適用可能である。例えば鉛酸電池、ニッケル－カドミウム電池、電気２重層キャパシタ、などの２次電池であっても本発明を適用可能である。 Although the above embodiments are based on the assumption that the secondary battery is a lithium ion battery, the present invention is also applicable to other types of secondary batteries. For example, the present invention is applicable to secondary batteries such as lead acid batteries, nickel-cadmium batteries, electric double layer capacitors, and the like.
１００：電池状態推定装置
１１０：データ取得部
１２０：プロセッサ 100: Battery state estimation device 110: Data acquisition unit 120: Processor

Claims (13)

  1. 　電池の状態を推定する電池状態推定装置であって、
    　前記電池からの出力電圧を記述したデータを取得するデータ取得部、
    　前記データにしたがって前記電池の劣化状態を推定する演算部、
    　を備え、
    　前記演算部は、前記電池の充電後または放電後の休止期間内における前記データから電圧値を取得し、
    　前記演算部は、前記休止期間の開始時点から所定時間が経過した時点において開始する期間の前記電圧値から、前記電圧値のベースライン電圧を特定し、
    　前記演算部は、前記ベースライン電圧と前記電圧値との間の差分を計算し、
    　前記演算部は、前記差分にしたがって、前記所定時間内における前記出力電圧の時間微分を推定し、
    　前記演算部は、前記時間微分と前記劣化状態との間の関係にしたがって、前記劣化状態を推定する
    　ことを特徴とする電池状態推定装置。     A battery condition estimation device that estimates a battery condition,
    a data acquisition unit that acquires data describing the output voltage from the battery;
    a calculation unit that estimates the deterioration state of the battery according to the data;
    Equipped with
    The calculation unit obtains a voltage value from the data during a rest period after charging or discharging the battery,
    The calculation unit specifies a baseline voltage of the voltage value from the voltage value of a period starting when a predetermined time has elapsed from the start of the rest period,
    The calculation unit calculates a difference between the baseline voltage and the voltage value,
    The calculation unit estimates a time differential of the output voltage within the predetermined time according to the difference,
    The battery state estimating device, wherein the calculation unit estimates the deterioration state according to a relationship between the time differential and the deterioration state.
  2. 　前記演算部は、前記推定した時間微分にしたがって前記ベースライン電圧を更新し、
    　前記演算部は、前記更新したベースライン電圧にしたがって前記差分を再計算し、
    　前記演算部は、前記差分と前記劣化状態との間の第１関係にしたがって、前記劣化状態を推定する
    　ことを特徴とする請求項１記載の電池状態推定装置。     The calculation unit updates the baseline voltage according to the estimated time differential,
    The calculation unit recalculates the difference according to the updated baseline voltage,
    The battery state estimating device according to claim 1, wherein the calculation unit estimates the deterioration state according to a first relationship between the difference and the deterioration state.
  3. 　前記演算部は、前記時間微分と前記劣化状態との間の第２関係にしたがって、前記時間微分を推定し、
    　前記演算部は、前記第２関係にしたがって推定した前記時間微分にしたがって、前記ベースライン電圧を更新する 
    　ことを特徴とする請求項２記載の電池状態推定装置。     The calculation unit estimates the time differential according to a second relationship between the time differential and the deterioration state,
    The calculation unit updates the baseline voltage according to the time differential estimated according to the second relationship.
    The battery state estimation device according to claim 2, characterized in that:
  4. 　前記演算部は、前記劣化状態が収束するまで、
    　　前記第１関係にしたがって前記劣化状態を推定する処理、
    　　前記第２関係にしたがって前記時間微分を推定する処理、
    　　前記差分を再計算する処理、
    　を繰り返す
    　ことを特徴とする請求項３記載の電池状態推定装置。     The arithmetic unit operates until the deterioration state converges.
    a process of estimating the deterioration state according to the first relationship;
    a process of estimating the time differential according to the second relationship;
    a process of recalculating the difference;
    The battery state estimating device according to claim 3, wherein the battery state estimating device repeats the following steps.
  5. 　前記演算部は、前記差分と前記劣化状態との間の第１関係にしたがって、前記劣化状態を仮推定し、
    　前記演算部は、前記時間微分と前記劣化状態との間の第２関係にしたがって、前記時間微分を仮推定し、
    　前記演算部は、前記推定した時間微分にしたがって前記ベースライン電圧を更新し、
    　前記演算部は、前記更新したベースライン電圧にしたがって前記差分を再計算し、
    　前記演算部は、前記劣化状態が収束するまで、
    　　前記第１関係にしたがって前記劣化状態を推定する処理、
    　　前記第２関係にしたがって前記時間微分を推定する処理、
    　　前記差分を再計算する処理、
    　を繰り返す
    　ことを特徴とする請求項１記載の電池状態推定装置。     The calculation unit temporarily estimates the deterioration state according to a first relationship between the difference and the deterioration state,
    The calculation unit temporarily estimates the time differential according to a second relationship between the time differential and the deterioration state,
    The calculation unit updates the baseline voltage according to the estimated time differential,
    The calculation unit recalculates the difference according to the updated baseline voltage,
    The arithmetic unit operates until the deterioration state converges.
    a process of estimating the deterioration state according to the first relationship;
    a process of estimating the time differential according to the second relationship;
    a process of recalculating the difference;
    The battery state estimating device according to claim 1, wherein the battery state estimating device repeats the following steps.
  6. 　前記データ取得部は、前記電池が第１Ｃレートで充電または放電されるときの前記出力電圧を記述した前記データを取得し、
    　前記演算部は、前記差分を、前記電池が第２Ｃレートで充電または放電されるときにおける第２差分へ、
    　　前記差分、前記第２差分、前記第１Ｃレート、および前記第２Ｃレートの間の第３関係
    　にしたがって変換し、
    　前記演算部は、前記第２差分にしたがって前記時間微分を再推定する
    　ことを特徴とする請求項１記載の電池状態推定装置。     The data acquisition unit acquires the data describing the output voltage when the battery is charged or discharged at a first C rate,
    The calculation unit converts the difference into a second difference when the battery is charged or discharged at a second C rate;
    converting according to a third relationship between the difference, the second difference, the first C rate, and the second C rate;
    The battery state estimating device according to claim 1, wherein the calculation unit re-estimates the time differential according to the second difference.
  7. 　前記第３関係は、前記劣化状態の値ごとに定義されており、
    　前記演算部は、前記差分から前記劣化状態を仮推定し、
    　前記演算部は、前記仮推定した劣化状態に対応する前記第３関係を参照することにより、前記差分を前記第２差分へ変換する
    　ことを特徴とする請求項６記載の電池状態推定装置。     The third relationship is defined for each value of the deterioration state,
    The calculation unit tentatively estimates the deterioration state from the difference,
    The battery state estimating device according to claim 6, wherein the calculation unit converts the difference into the second difference by referring to the third relationship corresponding to the provisionally estimated deterioration state.
  8. 　前記時間微分と前記劣化状態との間の関係は、Ｃレートの値ごとに定義されており、
    　前記演算部は、前記第２Ｃレートに対応する前記関係を参照することにより、前記劣化状態を推定する 
    　ことを特徴とする請求項６記載の電池状態推定装置。     The relationship between the time differential and the deterioration state is defined for each value of C rate,
    The calculation unit estimates the deterioration state by referring to the relationship corresponding to the second C rate.
    7. The battery state estimating device according to claim 6.
  9. 　前記データ取得部は、前記電池を搭載した装置内に組み込まれた測定デバイスまたは前記電池を搭載した装置に対して外部的に取り付けられた測定デバイスから、前記データを取得する
    　ことを特徴とする請求項１記載の電池状態推定装置。     The data acquisition unit acquires the data from a measurement device built into the device equipped with the battery or a measurement device attached externally to the device equipped with the battery. Item 1. The battery state estimation device according to item 1.
  10. 　前記電池を搭載した装置は電気自動車であり、
    　前記測定デバイスは、前記電気自動車の充電器またはＯＢＤツールであり、
    　前記データ取得部は、前記電池を前記電気自動車から取り外すことなく、前記測定デバイスから前記データを取得する
    　ことを特徴とする請求項９記載の電池状態推定装置。     The device equipped with the battery is an electric vehicle,
    the measuring device is a charger or an OBD tool for the electric vehicle;
    The battery state estimation device according to claim 9, wherein the data acquisition unit acquires the data from the measurement device without removing the battery from the electric vehicle.
  11. 　請求項１記載の電池状態推定装置、
    　前記電池、
    　を有することを特徴とする電池システム。     The battery state estimation device according to claim 1,
    the battery;
    A battery system characterized by having:
  12. 　前記電池システムはさらに、前記電池の充放電を制御するコントローラを備え、
    　前記演算部は、前記コントローラから前記電池に対する指令にしたがって、前記休止期間の開始時点を判定する
    　ことを特徴とする請求項１１記載の電池システム。     The battery system further includes a controller that controls charging and discharging of the battery,
    The battery system according to claim 11, wherein the arithmetic unit determines the start time of the rest period according to a command from the controller to the battery.
  13. 　電池の状態を推定する電池状態推定方法であって、
    　前記電池からの出力電圧を記述したデータを取得するステップ、
    　前記データにしたがって前記電池の劣化状態を推定するステップ、
    　を有し、
    　前記推定するステップにおいては、前記電池の充電後または放電後の休止期間内における前記データから電圧値を取得し、
    　前記推定するステップにおいては、前記休止期間の開始時点から所定時間が経過した時点において開始する期間の前記電圧値から、前記電圧値のベースライン電圧を特定し、
    　前記推定するステップにおいては、前記ベースライン電圧と前記電圧値との間の差分を計算し、
    　前記推定するステップにおいては、前記差分にしたがって、前記所定時間内における前記出力電圧の時間微分を推定し、
    　前記推定するステップにおいては、前記時間微分と前記劣化状態との間の関係にしたがって、前記劣化状態を推定する
    　ことを特徴とする電池状態推定方法。     A battery condition estimation method for estimating a battery condition, the method comprising:
    obtaining data describing the output voltage from the battery;
    estimating the deterioration state of the battery according to the data;
    has
    In the estimating step, a voltage value is obtained from the data during a rest period after charging or discharging the battery,
    In the estimating step, a baseline voltage of the voltage value is specified from the voltage value of a period starting when a predetermined time has elapsed from the start of the rest period,
    In the estimating step, a difference between the baseline voltage and the voltage value is calculated,
    In the estimating step, a time differential of the output voltage within the predetermined time is estimated according to the difference;
    A battery state estimation method, wherein in the estimating step, the deterioration state is estimated according to a relationship between the time differential and the deterioration state.
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