TWI842331B - Battery state estimation device, battery system, and battery state estimation method - Google Patents
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Abstract
[課題] 本發明其目的在於，使用電池的充放電後的休止期間中的電壓特性來推定電池的劣化狀態之技術中，即便是在無法得到充分的個數之休止期間初始中的電池電壓的取樣值的情況下，也可以高精度推定電池的劣化狀態。 [解決手段] 有關本發明的電池狀態推定裝置係確定從休止期間開始到規定時間經過後的期間中的電池電壓的基線電壓，根據前述基線電壓與前述電池電壓之間的差值，推定前述規定時間內的前述電池電壓的時間微分，使用前述時間微分來推定電池的劣化狀態。 [Topic] The present invention aims to estimate the degradation state of a battery using the voltage characteristics during a rest period after charging and discharging of the battery, and to estimate the degradation state of the battery with high accuracy even when a sufficient number of sample values of the battery voltage during the initial rest period cannot be obtained. [Solution] The battery state estimation device of the present invention determines a baseline voltage of the battery voltage during the period from the start of the rest period to the lapse of a predetermined time, estimates the time differential of the battery voltage within the predetermined time based on the difference between the baseline voltage and the battery voltage, and estimates the degradation state of the battery using the time differential.
Description
本發明有關推定電池的狀態的技術。The present invention relates to a technique for estimating the state of a battery.
高速推定二次電池的劣化狀態(State Of Health：SOH)的診斷技術越發有其需求。該技術對於管理電動車或電力儲存系統等中的二次電池的生命週期是為重要。來自對迅速診斷使用完畢的蓄電池之技術的市場的需求增加，期望對搭載了蓄電池的機器裝卸蓄電池，高速診斷蓄電池的劣化狀態。為此，有必要提供一種對電源負載裝置與電池測定裝置的各種組合適切的診斷方法。There is an increasing demand for diagnostic technology that can estimate the state of health (SOH) of secondary batteries at high speed. This technology is important for managing the life cycle of secondary batteries in electric vehicles or power storage systems. The market demand for technology that can quickly diagnose used batteries is increasing, and it is expected that batteries can be loaded and unloaded from machines equipped with batteries and the degradation state of batteries can be diagnosed at high speed. To this end, it is necessary to provide a diagnostic method that is suitable for various combinations of power load devices and battery measuring devices.
專利文獻1記載有關診斷電池的劣化狀態之技術。同文獻係以『高精度評量蓄電池系統的狀態。』為課題，記載有一種技術，乃是一種『評量複數個蓄電池單元所構成的蓄電池系統的狀態之蓄電池狀態評量系統，具有：記憶體，其係保持複數個蓄電池單元的電壓中，複數個蓄電池單元的電壓的分布中位置為相異之至少二個蓄電池單元的電壓；以及劣化狀態計算部，其係計算至少二個蓄電池單元的放電後的休止期間中對電壓的時間之斜率。』(參閱摘要)。 [先前技術文獻] [專利文獻] Patent document 1 describes a technology for diagnosing the degradation state of a battery. The same document is titled "High-precision evaluation of the state of a battery system." It describes a technology, which is a "battery state evaluation system for evaluating the state of a battery system composed of a plurality of battery cells, having: a memory that stores the voltages of at least two battery cells whose positions are different in the distribution of the voltages of the plurality of battery cells; and a degradation state calculation unit that calculates the slope of the voltage with respect to time during the rest period after the discharge of at least two battery cells." (See abstract). [Prior technical document] [Patent document]
[專利文獻1] 日本特開2020-169943號專利公報[Patent Document 1] Japanese Patent Publication No. 2020-169943
[發明欲解決之課題][Problems to be solved by the invention]
如專利文獻1，使用了休止期間中的電壓特性之高速診斷，適合在以高的取樣率實施電壓測定的情況下。為了在短時間內診斷電池，必須在該短時間內得到多的計測點，所以期望取樣率高。換言之，該技術若取樣率低的話，是有劣化狀態的推定精度下降的可能性。As in Patent Document 1, high-speed diagnosis using voltage characteristics during the rest period is suitable for voltage measurement at a high sampling rate. In order to diagnose the battery in a short time, many measurement points must be obtained in the short time, so a high sampling rate is desired. In other words, if the sampling rate of this technology is low, there is a possibility that the accuracy of deterioration state estimation will decrease.
而且，例如起因於實施計測作業的環境，是有無法充分確保充放電完畢後不久的期間(休止期間的初始階段)中的電池電壓的取樣點的情況。因為無法充分取得休止期間的初始階段中的電池電壓，所以在充放電完畢後的短時間內高精度實施診斷是有困難。亦即也在該情況下，與取樣率低的情況同樣，使用了休止期間初始的電池電壓的經時變動之診斷的精度不充分。Furthermore, for example, due to the environment in which the measurement operation is performed, there is a case where the sampling point of the battery voltage in the period immediately after the charge and discharge is completed (the initial stage of the rest period) cannot be fully secured. Since the battery voltage in the initial stage of the rest period cannot be fully obtained, it is difficult to perform a diagnosis with high accuracy in a short period of time after the charge and discharge is completed. In other words, in this case, as in the case of a low sampling rate, the accuracy of the diagnosis using the time-dependent change of the battery voltage at the initial stage of the rest period is insufficient.
本發明為有鑑於上述般的課題而為之創作，其目的在於，在使用電池的充放電後的休止期間中的電壓特性來推定電池的劣化狀態之技術中，即便是在無法得到充分的個數之休止期間初始中的電池電壓的取樣值的情況下，也可以高精度推定電池的劣化狀態。 [解決課題之手段] The present invention was created in view of the above-mentioned problems, and its purpose is to estimate the degradation state of the battery with high accuracy even when a sufficient number of sample values of the battery voltage at the beginning of the rest period cannot be obtained in the technology of estimating the degradation state of the battery using the voltage characteristics during the rest period after the battery is charged or discharged. [Means for solving the problem]
有關本發明的電池狀態推定裝置係確定從休止期間開始到規定時間經過後的期間中的電池電壓的基線電壓，根據前述基線電壓與前述電池電壓之間的差值，推定前述規定時間內的前述電池電壓的時間微分，使用前述時間微分來推定電池的劣化狀態。 [發明效果] The battery state estimation device of the present invention determines the baseline voltage of the battery voltage during the period from the start of the rest period to the lapse of a specified time, estimates the time differential of the battery voltage within the specified time based on the difference between the baseline voltage and the battery voltage, and estimates the degradation state of the battery using the time differential. [Effect of the invention]
根據有關本發明的電池狀態推定裝置，可以在使用電池的充放電後的休止期間中的電壓特性來推定電池的劣化狀態之技術中，即便是在無法得到充分的個數之休止期間初始中的電池電壓的取樣值的情況下，也可以高精度推定電池的劣化狀態。According to the battery condition estimation device related to the present invention, in the technology of estimating the battery degradation state by using the voltage characteristics during the rest period after charging and discharging of the battery, the battery degradation state can be estimated with high accuracy even when a sufficient number of sample values of the battery voltage at the beginning of the rest period cannot be obtained.
＜實施方式1＞＜Implementation Method 1＞
如先前說明，有關高速診斷二次電池的劣化狀態之現有技術，一般，高的取樣率是為必要。本發明提供了一種對搭載了二次電池的機器不用裝卸二次電池，能夠以低取樣率推定二次電池的SOH之技術。As described above, conventional techniques for high-speed diagnosis of secondary battery degradation generally require a high sampling rate. The present invention provides a technique for estimating the SOH of a secondary battery at a low sampling rate without loading or unloading the secondary battery in a device equipped with the secondary battery.
圖1為表示二次電池實施了放電動作後的休止期間中的電池電壓的經時變動之圖表。如圖1表示，休止期間可以分成電池電壓陡峭變動之期間T1、以及之後和緩變動之期間T2。使用期間T1中的電池電壓的時間變化率(dV/dt)來推定SOH，經此，可以在短時間內推定SOH。另一方面，在期間T1中，電池電壓陡峭變動的緣故，為了正確的推定，必須在短時間內有較多的電池電壓的取樣點。亦即高的取樣率是為必要。因此，例如在起因於計測機器的限制等以高取樣率取樣電池電壓為困難的情況下，是有推定精度下降的可能性。FIG1 is a graph showing the time variation of the battery voltage during the rest period after the secondary battery has implemented a discharge operation. As shown in FIG1 , the rest period can be divided into a period T1 during which the battery voltage changes abruptly, and a period T2 during which the battery voltage changes slowly thereafter. The SOH can be estimated in a short time by using the time variation rate (dV/dt) of the battery voltage during the period T1. On the other hand, since the battery voltage changes abruptly during the period T1, more battery voltage sampling points must be taken in a short time in order to make an accurate estimate. That is, a high sampling rate is necessary. Therefore, in a case where it is difficult to sample the battery voltage at a high sampling rate, for example due to limitations of the measuring device, there is a possibility that the estimation accuracy will decrease.
例如是有起因於計測電池電壓的環境，無法充分取得期間T1中的電池電壓的經時變動的情況。該情況也與取樣率低的情況同樣，無法以充分的個數來取得期間T1中的電池電壓的取樣點。因此同樣是有推定精度下降的可能性。For example, due to the environment in which the battery voltage is measured, the temporal variation of the battery voltage during the period T1 may not be fully acquired. This is similar to the case where the sampling rate is low, and a sufficient number of sampling points of the battery voltage during the period T1 may not be acquired. Therefore, there is a possibility that the estimation accuracy may also decrease.
在此，本發明中，提供一種使用期間T2中的電池電壓特性，不使用高的取樣率(即便是在期間T1中的取樣點為較少的情況下)來高精度推定SOH之技術。有關圖1表示的基線電壓與其更新，使用後述的流程來說明。Here, the present invention provides a technique for estimating SOH with high accuracy using the battery voltage characteristics in period T2 without using a high sampling rate (even when the number of sampling points in period T1 is small). The baseline voltage shown in FIG1 and its update are explained using the flow described below.
圖2為表示推定二次電池的狀態的電池狀態推定裝置之各式各樣的型態。例如電動車(Electric Vehicle：EV)搭載的二次電池的電池電壓(電池電流、電池溫度等也同樣)，係可以藉由充放電機器、計測機器、車載診斷(OBD)裝置等來取得。有關如定置型蓄電系統等般的大型設備，例如藉由計測機器與電池系統通訊來取得電池電壓等的計測值。這些測定裝置係不用從搭載了電池的機器(該例中為EV或蓄電系統)取下，就可以對資料取得部110發送測定值等。FIG2 shows various types of battery status estimation devices for estimating the status of secondary batteries. For example, the battery voltage (battery current, battery temperature, etc.) of a secondary battery mounted on an electric vehicle (EV) can be obtained by a charging and discharging machine, a measuring machine, an on-board diagnostic (OBD) device, etc. For large equipment such as a stationary power storage system, for example, the measured value of the battery voltage, etc., can be obtained by communicating with the battery system through a measuring machine. These measuring devices can send measured values, etc. to the data acquisition unit 110 without being removed from the device (EV or power storage system in this example) equipped with the battery.
這些裝置所取得的電池電壓等的計測值，是可以藉由裝置本身所用的資料來推定電池狀態，或是，一旦對雲端平臺上傳了計測值後，伺服電腦可以使用這些資料來推定電池狀態。經由使用電腦(PC)或攜帶式終端來對雲端平臺做存取，可以閱覽其推定結果。推定電池狀態之這些個裝置，是可以構成作為有關本發明的電池狀態推定裝置。The measured values of battery voltage etc. obtained by these devices can be used to estimate the battery status through the data used by the device itself, or once the measured values are uploaded to the cloud platform, the server computer can use these data to estimate the battery status. By accessing the cloud platform using a computer (PC) or a portable terminal, the estimated results can be viewed. These devices that estimate the battery status can constitute the battery status estimation device related to the present invention.
圖3為表示用於推定有關實施方式1的電池狀態推定裝置100的功能方塊圖及劣化狀態之處理流程。電池狀態推定裝置100具備：資料取得部110、處理器120。資料取得部110例如從計測裝置等，取得二次電池的電池電壓的計測值、在圖1說明的T1的開始時間與結束時間等的資料。處理器120根據圖3表示的流程，推定二次電池的劣化狀態。以下說明圖3的各步驟。FIG3 is a functional block diagram of a battery state estimation device 100 for estimating a degradation state according to Embodiment 1 and a processing flow of the degradation state. The battery state estimation device 100 includes a data acquisition unit 110 and a processor 120. The data acquisition unit 110 acquires data such as a measured value of a battery voltage of a secondary battery, a start time and an end time of T1 described in FIG1 , etc. from a measuring device, etc. The processor 120 estimates the degradation state of the secondary battery according to the flow shown in FIG3 . The steps of FIG3 are described below.
(圖3：步驟S301) 控制二次電池的充放電動作的控制器(例如電池管理單元：BMU)對二次電池發送指示充放電動作的指令。處理器120根據該指令，判定二次電池是否已經進入到休止期間。在進入到了休止期間的情況下，實施以下的步驟，除此之外沒有必要實施本流程。控制器可以構成作為電池狀態推定裝置100的一部分，也可以構成作為包含二次電池的電池系統的一部分。 (Figure 3: Step S301) The controller (e.g., battery management unit: BMU) that controls the charging and discharging of the secondary battery sends instructions to the secondary battery to instruct the charging and discharging. The processor 120 determines whether the secondary battery has entered a rest period based on the instructions. When entering a rest period, the following steps are performed, and there is no need to perform this process otherwise. The controller can be configured as a part of the battery state estimation device 100, or as a part of a battery system including a secondary battery.
(圖3：步驟S301：補足) 取而代之，處理器120也可以自己判斷二次電池是否進入到了休止期間。例如也可以經由充放電電流是否未達閾值(典型為0)或者是其狀態持續在閾值時間以上，來判斷已進入到休止期間。也可以使用其他適當的判斷基準。 (Figure 3: Step S301: Replenishment) Alternatively, the processor 120 can also determine whether the secondary battery has entered the rest period. For example, it can also determine whether the charging and discharging current has not reached the threshold (typically 0) or its state has continued to exceed the threshold time to determine that it has entered the rest period. Other appropriate judgment criteria can also be used.
(圖3：步驟S302：其之1) 資料取得部110取得二次電壓的電池電壓的計測值、在圖1說明的T1的開始時間與結束時間、初始基線電壓(B0)等的資料。這些值例如可以從充放電控制器來取得，也可以對儲存在雲端儲存庫等的記憶裝置的值做存取來取得。有關計測值以外的固定值，也可以作為初始值預先儲存在電池狀態推定裝置的記憶裝置內。處理器120從資料取得部110取得這些，根據這些設定期間T1與T2及初始基線電壓。 (Figure 3: Step S302: 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 illustrated in Figure 1, and the initial baseline voltage (B0). These values can be acquired, for example, from a charge and discharge controller, or by accessing values stored in a memory device such as a cloud storage. Fixed values other than the measured values can also be pre-stored as initial values in the memory device of the battery state estimation device. The processor 120 acquires these from the data acquisition unit 110, and sets the time periods T1 and T2 and the initial baseline voltage based on these values.
(圖3：步驟S302：其之2) 處理器120計算現在的基線電壓(最初實施本步驟時的初始基線電壓B0)、以及電池電壓之間的差值ΔV。作為電池電壓的取樣點，希望使用電池電壓的經時變動為安定的時點中的點。亦即，希望把期間T2中的電池電壓的斜率近乎平坦的時點的取樣點與基線電壓之間的差值，作為ΔV。 (Figure 3: Step S302: 2) The processor 120 calculates the difference ΔV between the current baseline voltage (initial baseline voltage B0 when this step is first implemented) and the battery voltage. As the sampling point of the battery voltage, it is desirable to use a point at which the time variation of the battery voltage becomes stable. That is, it is desirable to use the difference between the sampling point at which the slope of the battery voltage in period T2 is almost flat and the baseline voltage as ΔV.
(圖3：步驟S302：補足) 本步驟中，電池電壓的計測值只要是取得期間T2中的值即可，期間T1中的計測值並無必要。亦即，計測裝置在期間T1中沒有必要用高取樣率來計測電池電壓。 (Figure 3: Step S302: Supplement) In this step, the measured value of the battery voltage only needs to be the value in period T2, and the measured value in period T1 is not necessary. In other words, the measuring device does not need to measure the battery voltage at a high sampling rate in period T1.
(圖3：步驟S302：其之3) 處理器120使用計算出的ΔV，參閱記述了ΔV與SOH之間的第1對應關係(之後例示)之資料，經此，來判定臨時SOH。關於該對應關係資料，資料取得部110可以從控制器或雲端儲存庫等來取得，資料取得部110也可以從預先儲存在電池狀態推定裝置所具備的記憶裝置內來取得該資料。後述之其他的對應關係資料也是同樣。 (Figure 3: Step S302: 3) The processor 120 uses the calculated ΔV to refer to the data describing the first correspondence between ΔV and SOH (an example will be shown later), and thereby determines the temporary SOH. The data acquisition unit 110 can obtain the correspondence data from the controller or cloud storage, etc., or the data acquisition unit 110 can obtain the data from a memory device pre-stored in the battery state estimation device. The same is true for other correspondence data described later.
(圖3：步驟S303：其之1) 處理器120在S302中使用臨時取得的SOH，參閱記述了期間T1中的電池電壓的時間變化率(dV/dt)與SOH之間的第2對應關係(如後例示)之資料，經此，來推定期間T1中的dV/dt。本步驟具有不用取得期間T1中的電池電壓的計測值，就可以得到期間T1中的dV/dt之意義。 (Figure 3: Step S303: 1) The processor 120 uses the temporarily acquired SOH in S302 to refer to the data describing the second correspondence between the time change rate (dV/dt) of the battery voltage in period T1 and the SOH (as exemplified below), and thereby estimates the dV/dt in period T1. This step has the meaning of obtaining the dV/dt in period T1 without acquiring the measured value of the battery voltage in period T1.
(圖3：步驟S303：其之2) 處理器120使用推定出的dV/dt，來更新基線電壓。具體方面例如，對已推移出的dV/dt乘上微小時間(T1為數百ms左右的話則為數ms左右的微小時間)。經此，可以得到電池電壓的增量。對現在的基線電壓加上其增量，經此，可以更新基線電壓。藉由後述的重覆而到達T1的終端的情況下，不把基線電壓更新到其之上。 (Figure 3: Step S303: 2) The processor 120 uses the estimated dV/dt to update the baseline voltage. Specifically, for example, the shifted dV/dt is multiplied by a small time (a small time of several ms if T1 is about several hundred ms). This can obtain the increment of the battery voltage. The increment is added to the current baseline voltage, and the baseline voltage can be updated. When the end of T1 is reached by the repetition described later, the baseline voltage is not updated above it.
(圖3：步驟S304) 處理器120使用更新過的基線電壓(例：圖1中的B1、B2)，再計算ΔV。處理器120使用再計算出的ΔV並參閱第1對應關係，經此，再取得SOH。 (Figure 3: Step S304) The processor 120 uses the updated baseline voltage (e.g., B1, B2 in Figure 1) to recalculate ΔV. The processor 120 uses the recalculated ΔV and refers to the first correspondence, thereby obtaining SOH again.
(圖3：步驟S305) 到SOH收斂為止，處理器120重覆S303～S304。例如一直到SOH的前次值與此次值之間的差值未達閾值為止，重覆取得SOH即可。 (Figure 3: Step S305) Until the SOH converges, the processor 120 repeats S303 to S304. For example, until the difference between the previous value and the current value of the SOH does not reach the threshold, the SOH can be obtained repeatedly.
＜實施方式2＞ 在高速診斷二次電池的劣化狀態之現有技術中，一般，使用高的充放電率(把在1小時電池可以充滿電或是完全放電之電流值稱為1C)來對二次電池充放電者為一般。這是因為經由使用高的充放電率，休止期間中的電池電壓的變動變大，經此使用了電池電壓的推定精度也提升。 <Implementation Method 2> In the prior art of high-speed diagnosis of the degradation state of secondary batteries, it is generally common to charge and discharge the secondary battery using a high charge and discharge rate (the current value at which the battery can be fully charged or completely discharged in 1 hour is called 1C). This is because by using a high charge and discharge rate, the change in battery voltage during the rest period becomes larger, and the estimation accuracy of the battery voltage is also improved.
但是因為搭載了二次電池的機器或計測裝置等的限制，也會有使用高的充放電率是有困難的情況。在此在本發明的實施方式2中，除了在實施方式1說明的低取樣率，還說明充放電電流藉由低充放電率而實施的情況下的SOH的推定手法。亦即，資料取得部110取得藉由低充放電率而充放電後的休止期間中的電池電壓的計測值。However, due to the limitations of the equipment or measuring devices equipped with the secondary battery, it may be difficult to use a high charge and discharge rate. Here, in the second embodiment of the present invention, in addition to the low sampling rate described in the first embodiment, the method of estimating the SOH when the charge and discharge current is implemented at a low charge and discharge rate is also described. That is, the data acquisition unit 110 acquires the measured value of the battery voltage during the rest period after charging and discharging at a low charge and discharge rate.
圖4為表示用於推定有關實施方式2的電池狀態推定裝置的功能方塊圖及劣化狀態之處理流程。本實施方式2中，實施S401與S402來取代S303。其他的構成與實施方式1同樣。Fig. 4 is a functional block diagram showing a processing flow for estimating a battery state according to Embodiment 2 and a deterioration state. In Embodiment 2, S401 and S402 are implemented instead of S303. The other structures are the same as those of Embodiment 1.
(圖4：步驟S401) 處理器120在S302中使用計算出的ΔV，參閱記述了ΔV與充放電率與SOH之間的第3對應關係(之後例示)的資料，經此，把S302中的ΔV，變換成比實際的充放電充放電率還高的充放電率中的ΔV的值。 (Figure 4: Step S401) The processor 120 uses the calculated ΔV in S302 to refer to the data describing the third correspondence between ΔV, charge and discharge rate, and SOH (to be illustrated later), thereby converting the ΔV in S302 into a ΔV value at a charge and discharge rate higher than the actual charge and discharge rate.
(圖4：步驟S402) 處理器120使用藉由S401中的變換所推定出的ΔV，參閱第1對應關係，經此，重新取得臨時SOH。處理器120經由使用該臨時SOH並參閱第2對應關係，推定期間T1中的dV/dt。處理器120與S303：其之2同樣，更新基線電壓。 (Figure 4: Step S402) The processor 120 uses the ΔV estimated by the transformation in S401 and refers to the first correspondence relationship to retrieve the temporary SOH. The processor 120 estimates the dV/dt in the period T1 by using the temporary SOH and referring to the second correspondence relationship. The processor 120 updates the baseline voltage in the same manner as S303: Part 2.
圖5A為第1對應關係之例。ΔV與SOH之間的對應關係例如可以藉由對各個二次電池的SOH的值實測ΔV等來取得。在值的偏差大的情況下，也可以使用近似函數來定義對應關係。圖5A中，表示藉由一次函數來近似之例。FIG5A is an example of the first correspondence relationship. The correspondence relationship between ΔV and SOH can be obtained by, for example, measuring ΔV for the SOH value of each secondary battery. When the value deviation is large, an approximate function can be used to define the correspondence relationship. FIG5A shows an example of approximation by a linear function.
圖5B為第3對應關係之例。ΔV與充放電率之間的對應關係可以定義在各個SOH的值。該對應關係，例如可以藉由對充放電率的值及各個二次電池的SOH的值實測ΔV等來取得。與圖5A同樣也可以使用近似函數來定義。圖5B中，表示藉由一次函數來近似之例。處理器120在S401中，使用現在的ΔV與SOH並參閱圖5B的對應關係，經此，可以在其對應關係內得到更高的充放電率的ΔV。經此，可以把ΔV變換成更高的充放電率的值。FIG5B is an example of the third correspondence. The correspondence between ΔV and the charge and discharge rate can be defined at each SOH value. The correspondence can be obtained, for example, by measuring ΔV for the charge and discharge rate value and the SOH value of each secondary battery. As with FIG5A, it can also be defined using an approximate function. FIG5B shows an example of approximation using a linear function. In S401, the processor 120 uses the current ΔV and SOH and refers to the correspondence of FIG5B, thereby obtaining a ΔV of a higher charge and discharge rate within the correspondence. Thus, ΔV can be converted into a higher charge and discharge rate value.
圖5C為第2對應關係之例。本實施方式2中，dV/dt與SOH之間的對應關係可以定義在各個充放電率的值(實施方式1中，充放電率為固定值)。該對應關係，例如可以藉由對SOH的值及各個充放電率的值實測dV/dt等來取得。與圖5A同樣也可以使用近似函數來定義。圖5C中，表示藉由高次函數(二次以上)來近似之例。處理器120在S402中，使用現在的充放電率與SOH並參閱圖5C的對應關係，經此，可以推定dV/dt。FIG5C is an example of the second correspondence. In the second embodiment, the correspondence between dV/dt and SOH can be defined at each charge and discharge rate value (in the first embodiment, the charge and discharge rate is a fixed value). The correspondence can be obtained, for example, by measuring dV/dt for the SOH value and each charge and discharge rate value. As with FIG5A, it can also be defined using an approximate function. FIG5C shows an example of approximation using a high-order function (secondary or higher). In S402, the processor 120 uses the current charge and discharge rate and SOH and refers to the correspondence of FIG5C, whereby dV/dt can be estimated.
＜實施方式3＞ 在本發明的實施方式3中，說明有關決定期間T1的時間長度之手法。其他的構成與實施方式1～2同樣。例如考慮到對複數個二次電池使用電化學阻抗光譜分析法(EIS)來測定電池單元的阻抗，經此，實驗性決定T1的時間長度。 <Implementation method 3> In implementation method 3 of the present invention, a method for determining the length of time T1 is described. The other structures are the same as those of implementation methods 1 to 2. For example, considering using electrochemical impedance spectroscopy (EIS) to measure the impedance of battery cells for a plurality of secondary batteries, the length of time T1 is experimentally determined.
圖6為表示使用EIS所測定出的電池單元的阻抗之實測例。經由分析複數個二次電池之不同頻率的阻抗特性，對各個電池及各個頻率帶域，可以得到阻抗特性。從該阻抗特性，可以得到高取樣率為必要的時間領域(圖6縱虛線的左側)與以低取樣率便足夠的時間領域(圖6的縱虛線的右側)。據此來對各個二次電池作成查找表等，經此，可以對各個二次電池定義期間T1的時間長度。資料取得部110只要是取得記述了該定義的資料即可。FIG6 shows an actual measurement example of the impedance of a battery cell measured using EIS. By analyzing the impedance characteristics of multiple secondary batteries at different frequencies, the impedance characteristics can be obtained for each battery and each frequency band. From the impedance characteristics, it is possible to obtain a time domain where a high sampling rate is necessary (the left side of the vertical dashed line in FIG6 ) and a time domain where a low sampling rate is sufficient (the right side of the vertical dashed line in FIG6 ). Based on this, a lookup table is created for each secondary battery, and the time length of the period T1 can be defined for each secondary battery. The data acquisition unit 110 only needs to obtain data that describes this definition.
＜實施方式4＞ 圖7為表示二次電池的等效電路圖之例。圖7上段表示二次模型，圖7下段表示一次模型。使用如圖7表示的電路模型來模擬充放電後的電池電壓的時程變化，經此，為了推定SOH，可以導出可以使用之確定的參數。但是這樣的模擬手法，是有為了得到充分的推定精度而長時間的演算時間為有必要的情況。在使用而且低充放電率來進行充放電的情況下，電池電壓的變動幅寬度小的緣故，是有配適處理等的精度變得不充分的可能性。 <Implementation Method 4> Figure 7 is an example of an equivalent circuit diagram of a secondary battery. The upper part of Figure 7 shows a secondary model, and the lower part of Figure 7 shows a primary model. By using the circuit model shown in Figure 7 to simulate the time course change of the battery voltage after charging and discharging, a certain parameter that can be used to estimate the SOH can be derived. However, such a simulation method may require a long calculation time in order to obtain sufficient estimation accuracy. When charging and discharging is performed at a low charge and discharge rate, the battery voltage has a small fluctuation range, so there is a possibility that the accuracy of the adaptation process, etc. may become insufficient.
在此，考慮到組合在實施方式1～3說明的手法、與圖7表示的電路模型所致之模擬。經此，比起單獨使用如圖7表示般的電路模型手法的情況，更可以改善SOH的推定精度。Here, it is considered to combine the methods described in the first to third embodiments with the simulation by the circuit model shown in Fig. 7. This can improve the estimation accuracy of SOH compared with the case where the circuit model method shown in Fig. 7 is used alone.
＜有關本發明的變形例＞ 本發明並不限定於前述的實施方式，是包含各式各樣的變形例。例如，上述的實施型態係為了容易理解地說明本發明而詳細說明，未必會限定在具備已說明之全部的構成。又，可以把某一實施方式的構成的一部分分分分置換到另一實施方式的構成，還有，亦可在某一實施方式的構成加上另一實施方式的構成。又，有關各實施型態的構成的一部分分分分，是可以追加，刪除，置換其他的構成。 <Variations of the present invention> The present invention is not limited to the aforementioned embodiments, but includes various variations. For example, the aforementioned embodiments are described in detail to explain the present invention in an easy-to-understand manner, and are not necessarily limited to having all the structures described. In addition, a part of the structure of a certain embodiment can be replaced with the structure of another embodiment, and a part of the structure of another embodiment can be added to the structure of a certain embodiment. In addition, a part of the structure of each embodiment can be added, deleted, or replaced with other structures.
在以上的實施方式中，說明了於電池的放電動作後的休止期間推定SOH，但是，於充電動作後的休止期間，出現了與SOH對應的輸出電壓的時程變化的話，是可以與以上的實施方式同樣來推定SOH。於放電動作後的休止期間、充電動作後的休止期間、或是這些雙方、任一中，是否出現具有與SOH相關的時程變化，是因電池的特性而異。因此配合電池的特性，在這些的任意一個中推定SOH即可。In the above embodiment, it is described that SOH is estimated during the rest period after the discharge operation of the battery. However, if a time course change of the output voltage corresponding to SOH occurs during the rest period after the charge operation, SOH can be estimated in the same way as in the above embodiment. Whether a time course change related to SOH occurs during the rest period after the discharge operation, the rest period after the charge operation, or both, depends on the characteristics of the battery. Therefore, SOH can be estimated in any of these according to the characteristics of the battery.
以上的實施方式(圖2)中，說明了電池狀態推定裝置的構裝型態之例，但是也可以是其他的構裝型態。例如，從相對於裝入到搭載了二次電池的機器內之任意的測定裝置或是同機器而安裝在外部之任意的測定裝置，透過資料取得部110取得電池電壓的測定值等，經此，可以實施與本發明有關的手法。In the above embodiment (FIG. 2), an example of the configuration of the battery state estimation device is described, but other configurations are also possible. For example, the method related to the present invention can be implemented by obtaining the measured value of the battery voltage through the data acquisition unit 110 from any measuring device installed in a device equipped with a secondary battery or any measuring device installed outside the same device.
以上的實施方式中，處理器120は，藉由構裝了該功能的電路裝置等的硬體而可以構成，取而代之，藉由執行CPU(Central Processing Unit)等的演算裝置來執行構裝了該功能的軟體。In the above embodiment, the processor 120 can be configured by hardware such as a circuit device that implements the function, but instead, a computing device such as a CPU (Central Processing Unit) can be used to execute software that implements the function.
以上的實施方式中，是以二次電池為鋰離子電池為前提，但是，即便是其他類型的二次電池，也可以適用本發明。例如鉛酸電池、鎳-鎘電池、電雙層電容等的二次電池也可以適用本發明。In the above embodiments, the secondary battery is a lithium-ion battery as a premise, but even other types of secondary batteries can also be applied to the present invention. For example, secondary batteries such as lead-acid batteries, nickel-cadmium batteries, and electric double-layer capacitors can also be applied to the present invention.
100:電池狀態推定裝置 110:資料取得部 120:處理器 100: Battery status estimation device 110: Data acquisition unit 120: Processor
[圖1]為表示二次電池實施了放電動作後的休止期間中的電池電壓的經時變動之圖表。 [圖2]為表示推定二次電池的狀態的電池狀態推定裝置之各式各樣的型態。 [圖3]為表示用於推定有關實施方式1的電池狀態推定裝置100的功能方塊圖及劣化狀態之處理流程。 [圖4]為表示用於推定有關實施方式2的電池狀態推定裝置的功能方塊圖及劣化狀態之處理流程。 [圖5A]為第1對應關係之例。 [圖5B]為第3對應關係之例。 [圖5C]為第2對應關係之例。 [圖6]為表示使用EIS所測定出的電池單元的阻抗之實測例。 [圖7]為表示二次電池的等效電路圖之例。 [FIG. 1] is a graph showing the change over time of the battery voltage during the rest period after the secondary battery has performed a discharge operation. [FIG. 2] shows various types of battery state estimation devices for estimating the state of the secondary battery. [FIG. 3] shows a functional block diagram of the battery state estimation device 100 for estimating the state of the first embodiment and a processing flow of the degradation state. [FIG. 4] shows a functional block diagram of the battery state estimation device for estimating the state of the second embodiment and a processing flow of the degradation state. [FIG. 5A] is an example of the first correspondence relationship. [FIG. 5B] is an example of the third correspondence relationship. [FIG. 5C] is an example of the second correspondence relationship. [FIG. 6] shows an actual measurement example of the impedance of a battery cell measured using EIS. [Figure 7] is an example of an equivalent circuit diagram of a secondary battery.
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