JP3965817B2 - Battery capacity prediction device - Google Patents
Battery capacity prediction device Download PDFInfo
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- JP3965817B2 JP3965817B2 JP02690399A JP2690399A JP3965817B2 JP 3965817 B2 JP3965817 B2 JP 3965817B2 JP 02690399 A JP02690399 A JP 02690399A JP 2690399 A JP2690399 A JP 2690399A JP 3965817 B2 JP3965817 B2 JP 3965817B2
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- battery capacity
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- 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
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- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Description
【0001】
【発明の属する技術分野】
本発明は、所定時点における電池の充電後の総容量である電池容量を予測するための電池容量予測装置に関する。
【0002】
【従来の技術】
ポリマー電池を含め、リチウム金属2次電池あるいはリチウムイオン2次電池を用いたアプリケーションを設計するためには、その電池の寿命すなわち電池の充電後の総容量である電池容量の低下を見込んでおくことが重要である。たとえば、特開平9−257890号公報には、ある時点における電池の総容量から、次回の充電時における電池温度に対応する一充電当たりの電池容量の劣化による容量減少量を減算して充電後の電池容量を検出する方法が開示されている。
【0003】
【発明が解決しようとする課題】
しかし、上記従来の電池容量の測定方法においては、次回充電時の電池の温度しか考慮されていない。たしかに、電池容量は電池の温度にも依存するが、電池の充電状態にも依存するため、電池の温度のみを考慮しただけでは、正確な電池容量の算出を行うことができないという問題がある。
【0004】
本発明は、上記従来の課題に鑑みなされたものであり、その目的は、電池容量を正確に予測することができる電池容量予測装置を提供することにある。
【0005】
【課題を解決するための手段】
上記目的を達成するために、本発明は、電池容量予測装置であって、リチウムイオン2次電池あるいはリチウム金属2次電池の満充電状態における容量とある時点における容量との比であるSOCと温度と、初期の時点から所定時点までの経過時間とにより、前記電池の所定時点における電池容量を算出する電池容量算出手段を有し、前記電池容量算出手段は、SOCと温度との2つの変数を含む関数により電池容量の劣化速度を算出する劣化速度算出手段と、前記劣化速度よりその時々の電池の容量劣化量を算出し、これを前記経過時間の間継続し、これらの容量劣化量に基づき前記所定時点における電池容量の劣化量を算出する劣化量算出手段と、を含み、前記劣化容量算出手段により算出される劣化量を、初期の電池容量から減算して前記所定時点における電池容量を算出することを特徴とする。
【0006】
また、上記電池容量予測装置において、前記劣化量算出手段は、一定期間における電池容量の劣化量を積算して所定時点における電池容量の劣化量を算出することを特徴とする。
【0010】
【発明の実施の形態】
以下、本発明の実施の形態(以下実施形態という)を、図面に従って説明する。
【0011】
本発明者らは、ポリマー電池を含むリチウムイオン2次電池あるいはリチウム金属2次電池の電池容量すなわち充電後の総容量の低下速度が、電池の温度とSOC(State Of Charge)によって決定されることを見いだした。この電池容量の劣化速度は、電池の温度が高くなるほど、またSOCが高いほど大きくなる。ここでSOCとは、満充電状態における容量と所定時点における容量との比をいう。
【0012】
さらに、本発明者らは、上記温度に対する電池容量の劣化速度が、アレニウス則に従うことも見いだした。
【0013】
図1には、電池の絶対温度(T)の逆数と電池容量の劣化速度との関係が示される。図1に示されるように、電池の各SOCに応じて、片対数グラフ上で本プロットが直線となっていることがわかる。このアレニウスプロットから電池の容量劣化速度を温度(T)とSOCの2つの変数を用いて数式化すると、以下のとおりとなる。
【0014】
【数1】
ここで、F(t,SOC)は、電池温度t及びその場合のSOCに応じた電池容量の劣化速度を示している。この電池温度tは、図1の℃単位の温度であり、絶対温度T=t+273の関係となる。また、AとBは、SOCに応じたy切片を規定するための、各電池の特性値である。したがって、使用する各電池毎に、図1に示されたアレニウスプロットを求め、これから上記式(1)を決定しておけば、いかなる温度、SOCの履歴を経ても、そのプロファイルがわかれば、電池の寿命予測を数値計算によって行うことができる。
【0015】
したがって、自動車用途等には、たとえば一日当たりの温度/SOCのプロファイルを、一定時間毎のデータとして記憶させ、順次電池容量の劣化量を計算し、積算することにより、正確な電池容量を把握することができる。
【0016】
図2には、本発明に係る電池容量予測装置により電池の容量劣化量を算出する工程が示される。
【0017】
まず、図1に示されたアレニウスプロットをSOC毎に求める(S1)。次に、上記アレニウスプロットから、容量劣化速度F(t,SOC)を、電池温度tとSOCの2つの変数を用いて数式化する。この数式が前述した式(1)となる(S2)。
【0018】
次に、電池の温度とSOCを上記式に代入し、その時々の電池の容量劣化量を計算する(S3)。この計算を目的の時間またはサイクルまで続行し、一定期間における電池容量の劣化量を算出し、その劣化量の積算値を初期の電池容量から減算することにより、所定時点における劣化後の電池容量を算出する。このように、本発明にかかる電池容量予測装置では、電池の充電状態と温度と経過時間とにより所定時点における電池容量を算出する手段を有する。この算出値は表示され、または電池制御のパラメータとして利用される(S4)。なお、S3及びS4のステップを繰り返すことにより、定期的に劣化後の電池容量を算出することができる。
【0019】
以上の説明では、電池の充電状態としてSOCを使用していたが、この代わりに充電後の電池の電圧値を用いることも可能である。
【0020】
図3(a),(b)には、電池の動作パターン毎に電池容量の維持率すなわち電池容量の変化を測定した結果が示される。図3(a)のパターンAに比べて、パターンBの場合の方が、図3(b)に示されるように容量維持率が高くなっている。すなわち、パターンBの方が電池容量の劣化速度が小さくなっている。これは、図3(a)に示されるように、パターンAの場合にはSOCの平均値が約70%であるのに対し、パターンBの場合にはSOCがほぼ60%であるが、図1に示されるように、低いSOCの方が容量劣化率が小さいためであると考えられる。
【0021】
なお、図3(b)では、パターンA、パターンBにおける容量維持率の実測値のほかに、本発明にかかる電池容量予測装置が前述の計算式によって電池温度とSOCの状態から算出した予測値も記載している。なお、この場合の温度は、ある加速劣化温度で実施した。いずれのパターンにおいても、予測値と実測値がほぼ一致しており、本発明にかかる電池容量予測装置が、正確に電池容量を予測できることがわかる。
【0022】
【発明の効果】
以上説明したように、本発明によれば、電池の温度のほかに、SOCも使用して電池容量を予測するので、電池容量を正確に予測することができ、電池寿命の管理を容易にすることができる。
【図面の簡単な説明】
【図1】 電池の温度と電池容量の劣化速度との関係を示すアレニウスプロット図である。
【図2】 本発明に係る電池容量予測装置により電池容量の劣化速度を算出する工程図である。
【図3】 電池動作のパターンに応じた容量維持率の実測値及び予測値を示す図である。[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a battery capacity prediction apparatus for predicting a battery capacity, which is a total capacity of a battery after charging at a predetermined time.
[0002]
[Prior art]
In order to design applications using lithium metal secondary batteries or lithium ion secondary batteries, including polymer batteries, it is necessary to expect a reduction in battery capacity, which is the battery life, that is, the total capacity after charging the battery. is important. For example, Japanese Patent Laid-Open No. 9-257890 discloses a method of subtracting the amount of decrease in capacity due to deterioration of the battery capacity per charge corresponding to the battery temperature at the next charge from the total capacity of the battery at a certain point in time. A method for detecting battery capacity is disclosed.
[0003]
[Problems to be solved by the invention]
However, in the conventional method for measuring battery capacity, only the temperature of the battery at the next charging is considered. Certainly, although the battery capacity depends on the battery temperature, it also depends on the state of charge of the battery. Therefore, there is a problem that the battery capacity cannot be accurately calculated only by considering only the battery temperature.
[0004]
The present invention has been made in view of the above-described conventional problems, and an object of the present invention is to provide a battery capacity prediction apparatus capable of accurately predicting battery capacity.
[0005]
[Means for Solving the Problems]
To achieve the above object, the present invention provides a battery capacity prediction apparatus, and SO C which is the ratio of the capacity at some point the capacity in the fully charged state of the lithium ion secondary battery or a lithium metal secondary battery and temperature, the elapsed time from the initial time point to a prescribed time point, have a battery capacity calculation means for calculating the battery capacity at a given time point of the battery, the battery capacity calculation means, two variables between the SOC and temperature A deterioration rate calculating means for calculating a deterioration rate of the battery capacity by a function including: a battery capacity deterioration amount at that time is calculated from the deterioration rate, and this is continued for the elapsed time, and these capacity deterioration amounts are calculated. A deterioration amount calculating means for calculating a deterioration amount of the battery capacity at the predetermined time based on, and subtracting the deterioration amount calculated by the deterioration capacity calculating means from an initial battery capacity. The battery capacity at the predetermined time is calculated .
[0006]
In the above battery capacity prediction apparatus, the deterioration amount calculating means is characterized and Turkey to calculate the deterioration amount of the battery capacity at a given point in time totalized deterioration of the battery capacity over a period of time.
[0010]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, embodiments of the present invention (hereinafter referred to as embodiments) will be described with reference to the drawings.
[0011]
The present inventors have determined that the battery capacity of a lithium ion secondary battery or a lithium metal secondary battery including a polymer battery, that is, the rate of decrease in the total capacity after charging is determined by the battery temperature and SOC (State Of Charge). I found. The deterioration rate of the battery capacity increases as the temperature of the battery increases and as the SOC increases. Here, the SOC means a ratio between the capacity in a fully charged state and the capacity at a predetermined time.
[0012]
Furthermore, the present inventors have also found that the deterioration rate of the battery capacity with respect to the temperature follows the Arrhenius law.
[0013]
FIG. 1 shows the relationship between the reciprocal of the absolute battery temperature (T) and the deterioration rate of the battery capacity. As shown in FIG. 1, it can be seen that the plot is a straight line on the semilogarithmic graph according to each SOC of the battery. From the Arrhenius plot, the battery capacity degradation rate is expressed as follows using two variables of temperature (T) and SOC.
[0014]
[Expression 1]
Here, F (t, SOC) represents the battery capacity deterioration rate according to the battery temperature t and the SOC in that case. The battery temperature t is a temperature in ° C. in FIG. 1 and has an absolute temperature T = t + 273. A and B are characteristic values of each battery for defining the y-intercept according to the SOC. Accordingly, the Arrhenius plot shown in FIG. 1 is obtained for each battery to be used, and if the above equation (1) is determined from this, the battery can be obtained if the profile is known regardless of the temperature and SOC history. Life prediction can be performed by numerical calculation.
[0015]
Therefore, for automobile applications, for example, the temperature / SOC profile per day is stored as data for every fixed time, and the battery capacity deterioration amount is sequentially calculated and integrated to obtain an accurate battery capacity. be able to.
[0016]
FIG. 2 shows a step of calculating the battery capacity deterioration amount by the battery capacity prediction apparatus according to the present invention.
[0017]
First, the Arrhenius plot shown in FIG. 1 is obtained for each SOC (S1). Next, from the Arrhenius plot, the capacity deterioration rate F (t, SOC) is formulated using two variables of the battery temperature t and the SOC. This mathematical formula becomes the above-described formula (1) (S2).
[0018]
Next, the battery temperature and SOC are substituted into the above formula, and the battery capacity deterioration amount at that time is calculated (S3). Continue this calculation until the target time or cycle, calculate the amount of battery capacity deterioration over a fixed period, and subtract the integrated value of the amount of deterioration from the initial battery capacity to obtain the battery capacity after deterioration at a given point in time. calculate. As described above, the battery capacity prediction apparatus according to the present invention includes means for calculating the battery capacity at a predetermined time point based on the state of charge of the battery, the temperature, and the elapsed time. This calculated value is displayed or used as a parameter for battery control (S4). It should be noted that the battery capacity after deterioration can be calculated periodically by repeating the steps of S3 and S4.
[0019]
In the above description, the SOC is used as the state of charge of the battery, but the voltage value of the battery after charging can be used instead.
[0020]
FIGS. 3A and 3B show the results of measuring the maintenance rate of the battery capacity, that is, the change in the battery capacity, for each operation pattern of the battery. Compared to the pattern A in FIG. 3A, the capacity retention rate in the pattern B is higher as shown in FIG. 3B. That is, the deterioration rate of the battery capacity is smaller in the pattern B. As shown in FIG. 3A, the average value of the SOC is about 70% in the case of the pattern A, whereas the SOC is almost 60% in the case of the pattern B. As shown in FIG. 1, it is considered that the lower SOC has a smaller capacity deterioration rate.
[0021]
In FIG. 3B, in addition to the actually measured values of the capacity retention rates in the patterns A and B, the predicted values calculated by the battery capacity prediction apparatus according to the present invention from the battery temperature and the SOC state by the above-described calculation formula. Is also described. In this case, the temperature was a certain accelerated deterioration temperature. In any of the patterns, the predicted value and the actually measured value are substantially the same, and it can be seen that the battery capacity prediction apparatus according to the present invention can accurately predict the battery capacity.
[0022]
【The invention's effect】
As described above, according to the present invention, the battery capacity is predicted using not only the battery temperature but also the SOC, so that the battery capacity can be accurately predicted and the battery life can be easily managed. be able to.
[Brief description of the drawings]
FIG. 1 is an Arrhenius plot showing the relationship between battery temperature and battery capacity deterioration rate.
FIG. 2 is a process diagram for calculating a battery capacity deterioration rate by a battery capacity prediction apparatus according to the present invention;
FIG. 3 is a diagram showing an actual measurement value and a predicted value of a capacity maintenance rate according to a battery operation pattern.
Claims (2)
前記電池容量算出手段は、
SOCと温度との2つの変数を含む関数により電池容量の劣化速度を算出する劣化速度算出手段と、
前記劣化速度よりその時々の電池の容量劣化量を算出し、これを前記経過時間の間継続し、これらの容量劣化量に基づき前記所定時点における電池容量の劣化量を算出する劣化量算出手段と、
を含み、
前記劣化容量算出手段により算出される劣化量を、初期の電池容量から減算して前記所定時点における電池容量を算出する、
ことを特徴とする電池容量予測装置。The SOC of the lithium ion secondary battery or the lithium metal secondary battery in the fully charged state and the SOC, which is the ratio of the capacity at a certain point in time , the temperature, and the elapsed time from the initial point to the predetermined point , have a battery capacity calculation means for calculating the battery capacity at the time,
The battery capacity calculation means includes
A deterioration rate calculating means for calculating a deterioration rate of the battery capacity by a function including two variables of SOC and temperature;
A deterioration amount calculating means for calculating the amount of battery capacity deterioration at that time from the deterioration speed, continuing this during the elapsed time, and calculating the amount of battery capacity deterioration at the predetermined time based on the capacity deterioration amount; ,
Including
Subtracting the deterioration amount calculated by the deterioration capacity calculation means from the initial battery capacity to calculate the battery capacity at the predetermined time point;
The battery capacity prediction apparatus characterized by the above-mentioned.
前記劣化量算出手段は、一定期間における電池容量の劣化量を積算して所定時点における電池容量の劣化量を算出する、
ことを特徴とする電池容量予測装置。The battery capacity prediction apparatus according to claim 1,
The deterioration amount calculating means calculates a deterioration amount of the battery capacity at a given point in time totalized deterioration of the battery capacity over a period of time,
The battery capacity prediction apparatus characterized by the above-mentioned.
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JP02690399A JP3965817B2 (en) | 1999-02-04 | 1999-02-04 | Battery capacity prediction device |
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Families Citing this family (14)
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CN102859377B (en) | 2010-04-26 | 2014-11-05 | 丰田自动车株式会社 | Degradation estimation device and degradation estimation method for storage battery device |
WO2012095894A1 (en) * | 2011-01-14 | 2012-07-19 | トヨタ自動車株式会社 | Degradation speed estimation method, and degradation speed estimation device, of lithium-ion battery |
US9077184B2 (en) * | 2011-01-18 | 2015-07-07 | Nissan Motor Co., Ltd. | Control device to control deterioration of batteries in a battery stack |
JP5852399B2 (en) * | 2011-10-17 | 2016-02-03 | インターナショナル・ビジネス・マシーンズ・コーポレーションInternational Business Machines Corporation | Battery state prediction system, method and program |
JP2013253991A (en) | 2012-11-30 | 2013-12-19 | Gs Yuasa Corp | Deteriorated capacity estimating device and deteriorated capacity estimating method for electricity storage elements, and electricity storage system |
JP6546452B2 (en) | 2015-06-02 | 2019-07-17 | ローム株式会社 | Battery remaining amount estimating device, battery remaining amount estimating system, and battery pack |
CN107179505B (en) * | 2016-03-09 | 2020-07-07 | 华为技术有限公司 | Battery health state detection device and method |
JP6624012B2 (en) * | 2016-11-04 | 2019-12-25 | トヨタ自動車株式会社 | Control system for lithium ion secondary battery |
JP2020038146A (en) * | 2018-09-05 | 2020-03-12 | トヨタ自動車株式会社 | Secondary battery system and soc estimation method for secondary battery |
JP2020038138A (en) * | 2018-09-05 | 2020-03-12 | 富士電機株式会社 | Storage battery diagnostic device, system, program, and method |
CN109342955A (en) * | 2018-11-19 | 2019-02-15 | 台州钱江新能源研究院有限公司 | A kind of projectional technique and system of capacity of lithium ion battery |
CN112014735B (en) * | 2019-05-30 | 2023-09-22 | 上海汽车集团股份有限公司 | Battery cell aging life prediction method and device based on full life cycle |
CN112415409B (en) * | 2019-08-23 | 2022-04-15 | 比亚迪股份有限公司 | Method and device for estimating battery capacity, storage medium and vehicle |
CN113030742B (en) * | 2019-12-24 | 2023-02-07 | 比亚迪股份有限公司 | Method, device and equipment for estimating battery capacity |
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