KR102255914B1 - Method and Apparatus for State-of-Charge Prediction of Lithium Ion Battery for Precision Enhancement at Low Temperature - Google Patents

Abstract

In the present invention, in predicting the remaining capacity of a lithium secondary battery by adding or subtracting the current accumulated amount of the lithium secondary battery, the lithium secondary battery improves the prediction accuracy in a low-temperature environment by applying the corrected current accumulated amount according to the battery temperature and the battery current. A method and a device for predicting the remaining amount of secondary batteries, which are corrected by a temperature factor corresponding to the measured temperature based on a temperature factor calculation equation obtained by curve fitting the capacity utilization rate in environments at different temperatures. The remaining capacity is predicted by adding or subtracting the accumulated amount.

Description

[Method and Apparatus for State-of-Charge Prediction of Lithium Ion Battery for Precision Enhancement at Low Temperature]

In the present invention, in predicting the remaining capacity of a lithium secondary battery by adding or subtracting the current accumulated amount of the lithium secondary battery, the lithium secondary battery improves the prediction accuracy in a low-temperature environment by applying the corrected current accumulated amount according to the battery temperature and the battery current. It relates to a method and a prediction device for predicting the remaining amount of secondary batteries.

When charging a lithium secondary battery, the recommended ambient temperature is in the range of 0℃ to 45℃, which is relatively narrow compared to the actual use environment.

The reason for recommending this temperature range is that when charging in a low temperature environment of 0°C or lower, lithium precipitates on the electrode surface, reducing the usable capacity and reducing safety. In addition, charging in a high temperature environment results in excessive heat generation. This is because battery performance may be deteriorated due to side reactions.

Even when discharging, when discharging in a low-temperature environment, side reactions such as lithium precipitation do not occur, but the charge transfer rate or electrode reaction rate is lowered, thereby reducing the usable capacity (or capacity utilization rate) compared to room temperature. When discharging in a high-temperature environment, the charge transfer rate and electrode reaction rate slightly increase, but other unwanted reactions such as an increase in side reactions of the electrolyte occur, resulting in a decrease in the usable capacity and an increase in irreversible capacity. As the time accumulates, the lifespan can be drastically reduced. Accordingly, it is recommended to discharge the lithium secondary battery in the recommended temperature environment.

In addition, the charging current and the discharging current affect the usable capacity. In particular, as the temperature decreases, the electrode reaction speed and the charge transfer speed decrease, and the resistance size also fluctuates, so that the reaction efficiency sharply decreases compared to room temperature.

Therefore, it is necessary to predict the residual capacity of the lithium secondary battery by reflecting the effects of temperature and current. In particular, for the prediction of a low-temperature section outside the recommended temperature range, it is necessary to sufficiently reflect and predict the characteristic change according to temperature.

As a method of predicting the remaining capacity, a method of using a look-up table, an ampere-hour counting method, a method of using mathematical modeling, and a method of using an equivalent circuit model are mainly used. have.

Among these methods, the current integration method sets the capacity at full charge to 100, and calculates the remaining capacity by adding or subtracting the capacity change amount from the previous capacity by using the amount of charge or discharge obtained by accumulating current at the time of charging or discharging as the capacity change amount. As a method of doing so, the prediction accuracy is relatively high, it is advantageous for calculation, and it is less sensitive to external noise (or external environment), and thus, it is used relatively more than other methods.

However, the current integration method can predict relatively accurately in a room temperature and high temperature environment, but the prediction error tends to be large in a low temperature environment.

That is, in a low-temperature environment, as the charge transfer speed and electrode reaction speed rapidly decrease, the utilization rate of the remaining capacity based on the room temperature is significantly lowered, so if only the amount of change in capacity obtained by integrating the current is reflected as it is, an error in the remaining capacity occurs. There is also a problem of accumulating errors.

Accordingly, the utilization rate at a low temperature can be experimentally obtained and reflected, but in that case, the error at a low temperature temperature other than the experimental temperature cannot be corrected because it is limited to the experiment temperature. That is, there is a need for a technique for predicting the residual capacity reflecting the temperature change in real time when charging or discharging.

KR 10-0740099 B1 2007.07.10. KR 10-1946877 B1 2019.02.01.

Accordingly, an object of the present invention is to predict the capacity utilization rate by reflecting the temperature change during charging or discharging, and to accurately predict the remaining capacity in a low-temperature environment by reflecting the predicted capacity utilization rate to the current integration equation. It is to provide a method and a prediction device.

이되,

은 온도인자이고,

는 측정 온도이고, a, b 및 c는 커브 피팅(Curve Fitting)에 의해 얻은 기설정 상수로 한다.In order to achieve the above object, the present invention is a method for predicting the remaining capacity of a lithium secondary battery by adding or subtracting the accumulated current during charging and discharging, in the method for predicting the remaining capacity of the lithium secondary battery, by adding or subtracting the accumulated current. A method for predicting remaining amount of a lithium secondary battery, comprising: a measuring step of measuring a temperature and a current of a lithium secondary battery with a sensor; The temperature factor corresponding to the measured temperature is determined based on the preset temperature factor calculation formula that curve fitting the ratio of the discharge capacity of each temperature to the room temperature discharge capacity obtained by discharging each temperature to the discharge end voltage in different temperature environments. A performance prediction step of calculating; A residual amount prediction step of predicting the residual capacity of the lithium secondary battery by applying the corrected current accumulated amount according to the calculated temperature factor; And, in the performance prediction step, the temperature factor calculation equation is

This,

Is the temperature factor,

Is the measurement temperature, and a, b, and c are preset constants obtained by curve fitting.

According to an embodiment of the present invention, the temperature factor calculation equation in the performance prediction step is a curve fitting obtained by obtaining the ratio of the discharge capacity for each temperature to the room temperature discharge capacity for discharge rates including 0.2C and 0.5C, respectively. .

According to an embodiment of the present invention, the temperature factor calculation equation in the performance prediction step is a curve fitting obtained by obtaining a ratio of the discharge capacity for each temperature to the room temperature discharge capacity for different discharge rates, respectively.

According to an exemplary embodiment of the present invention, in the performance prediction step, the temperature factor calculation equation is obtained as a discharge capacity for each temperature obtained in an environment of different temperatures including -30°C and 50°C.

으로 산정하며,

는 온도인자로 하는 성능 예측인자이고,

는 성능 예측인자

에 의해 보정되어 적산하는 측정 전류로 한다.According to an embodiment of the present invention, the accumulated current amount corrected according to the temperature factor in the residual amount prediction step is

Is calculated as,

Is the performance predictor as a temperature factor,

Is the performance predictor

It is set as the measured current corrected by and accumulated by.

는 충방전율 구간별 용량 활용률로 정의한 전류인자를 설정하여 둔 룩업테이블에 근거하여, 측정 전류의 충방전율에 대응되는 전류인자를 선정한 후, 온도인자와 전류인자의 곱셈으로 얻는 값을 상기 성능 예측인자로 한다.According to an embodiment of the present invention, the performance predictor

Is a value obtained by multiplying the temperature factor and the current factor based on a lookup table in which the current factor defined as the capacity utilization rate for each charging/discharging rate section is set, and then selecting the current factor corresponding to the charging/discharging rate of the measured current is the performance prediction factor. It should be.

According to an exemplary embodiment of the present invention, in the performance prediction step, when the lithium secondary battery is less than 0°C and is in the idle period, a current factor is set to 1 and a performance predictor is applied as a value of the temperature factor.

이되,

은 온도인자이고,

는 측정 온도이고, a, b 및 c는 커브 피팅(Curve Fitting)에 의해 얻은 기설정 상수로 한다.In order to achieve the above object, the present invention is an apparatus for predicting the remaining capacity of a lithium secondary battery by adding or subtracting an accumulated amount of current during charging and discharging. A data storage unit 10 storing a parameter value of a preset temperature factor calculation formula obtained by curve fitting a ratio of the discharge capacity for each temperature to the room temperature discharge capacity obtained by performing a curve fitting; A measuring unit 20 for measuring the temperature and current of the lithium secondary battery with a sensor; And a residual amount prediction unit that obtains a temperature factor corresponding to the measured temperature by the above temperature factor calculation formula, corrects the accumulated current amount by applying the temperature factor, and predicts the remaining capacity of the lithium secondary battery by applying the corrected current accumulation amount. (30); Including, the temperature factor calculation formula is

This,

Is the temperature factor,

Is the measurement temperature, and a, b, and c are preset constants obtained by curve fitting.

In the present invention made as described above, the temperature factor calculation equation obtained by curve fitting after acquiring the capacity utilization rate according to temperature for each temperature was used, and the temperature factor calculation formula could well reflect the capacity utilization rate for each temperature. Accordingly, the temperature factor calculation By applying the officially calculated temperature factor and accumulating the current, it is possible to predict the residual capacity that offsets the effect of temperature. In particular, it more accurately predicts the residual capacity under a low-temperature environment, adapts to continuous temperature changes, and offsets the temperature effect. One can predict the remaining capacity.

1 is a block diagram of an apparatus for predicting remaining amount of a lithium secondary battery according to an embodiment of the present invention.
2 is a flow chart of a method for predicting a remaining amount of a lithium secondary battery according to an embodiment of the present invention.
3 shows the ratio of the discharge capacity by temperature to the discharge capacity at room temperature (25°C) obtained by discharging to the discharge end voltage in the environments of -30°C, -10°C, 0°C, 25°C and 50°C, respectively, 0.2C and 0.5C. A diagram showing a curve-fitting graph after each obtained by discharge rate.
FIG. 4 is a graph of temperature, voltage, and current measured while performing electric vehicle (EV) evaluation after a lithium secondary battery charged with approximately 61% at room temperature is allowed to stand at -10°C for 2 hours.
5 is a graph comparing residual capacity prediction results before and after applying a performance predictor.

Hereinafter, preferred embodiments of the present invention will be described with reference to the accompanying drawings so that those of ordinary skill in the art can easily implement them. In describing an embodiment of the present invention, if it is determined that a detailed description of a related known function or a known configuration may unnecessarily obscure the subject matter of the present invention, a detailed description thereof will be omitted.

Referring to the block diagram shown in FIG. 1, the apparatus for predicting the remaining amount of a lithium secondary battery according to an embodiment of the present invention is a device for predicting the remaining capacity of a lithium secondary battery by using an improved current integration method. Accordingly, the accumulated current amount is corrected, and the remaining capacity is predicted with the corrected accumulated current amount. To this end, a data storage unit 10, a measuring unit 20, and a residual amount predicting unit 30 are included.

According to the lithium secondary battery remaining amount prediction device configured as described above, the measurement unit 20 measures the current and voltage when charging or discharging the lithium secondary battery 1 and the temperature of the lithium secondary battery 1 in real time and stores data. It is stored in the unit 10, and the remaining capacity prediction unit 30 predicts the remaining capacity according to the current, temperature, and voltage of the lithium secondary battery 1, and the data storage unit 10 stores the data necessary for the remaining capacity prediction in advance. It is stored and used when predicting the remaining capacity, and a detailed description is as follows.

In the data storage unit 10, a parameter value of a temperature factor calculation equation using the battery temperature as a variable and a lookup table of current factors for each charge/discharge rate section are stored in advance, and the current and voltage measured by the measurement unit 20 And the temperature and the history of the predicted remaining capacity are recorded and stored.

First, the temperature factor calculation equation will be described in detail.

The remaining capacity of the lithium secondary battery is generally expressed by SOC (State of Charge) defined by Equation 1 below.

는 현재 보유하고 있는 잔여 용량이고,

는 상온에서 최대한 충전한 상태의 잔여 용량(즉, 만충전 용량)이며, 통상적으로 [Ah] 단위를 사용한다. 수학식 1에 따르면, 만충전 용량 대한 현재 잔여 용량의 비율로 정의한 SOC로 잔여 용량을 표현함으로써, 만충전 용량이 상이한 리튬이차전지에 대해 표준화된 잔여 용량으로 표현할 수 있다.In Equation 1,

Is the remaining capacity currently held,

Is the remaining capacity (ie, fully charged capacity) in the state of being fully charged at room temperature, and is usually used in units of [Ah]. According to Equation 1, by expressing the residual capacity in SOC defined as the ratio of the current remaining capacity to the full charging capacity, it can be expressed as the standardized residual capacity for lithium secondary batteries having different full charging capacity.

을 반영하여, 아래의 수학식 2로 잔여 용량 SOC를 산정한다. According to the present invention, the performance predictor when calculating the current integration amount according to the current integration method

In reflection, the remaining capacity SOC is calculated by Equation 2 below.

는 이전 시점

에서의 SOC이고,

는

이후의 시점

에 예측되는 SOC이고,

는 순시 전류이고,

는

부터

까지 측정한 전류의 적산량이며,

는 상수로서

의 단위를 [sec]로 하고

의 단위를 [A]로 하는 경우

이다.In Equation 2,

Is the previous point

Is the SOC at,

Is

A later point of view

Is the predicted SOC,

Is the instantaneous current,

Is

from

It is the cumulative amount of current measured to

Is a constant

And the unit of [sec]

When the unit of is [A]

to be.

는 전류 i 및 온도 T를 변수로 하는 함수로서, 아래의 수학식 3과 같이 정의하였다.Here, the performance predictor

Is a function using current i and temperature T as variables, and is defined as in Equation 3 below.

는 온도의 영향에 따른 용량 활용률로서 아래의 수학식 4로 정의한 온도인자 산정식으로 산정한다.In Equation 3,

Is the capacity utilization rate according to the influence of temperature and is calculated by the temperature factor calculation formula defined by Equation 4 below.

Here, a, b, and c are constants selected according to the experimentally obtained capacity utilization rate for each temperature. In other words, after charging the same, the batteries are discharged to the discharge end voltage in an environment at different temperatures to obtain the discharge capacity (or discharge amount) for each temperature, and then the ratio of the discharge capacity for each temperature to the room temperature discharge capacity is calculated as the capacity utilization rate. Get as. In addition, constants a, b, and c are obtained by curve fitting the capacity utilization rate using the temperature factor calculation equation of Equation 4 above. When fitting a curve, for example, the least squares method can be used.

For example, a fully charged lithium secondary battery can be discharged to the discharge end voltage under different temperature environments, and the discharge current is accumulated to obtain the discharge capacity for each temperature, and the temperature at which the maximum value is expressed among the discharge capacity for each temperature thus obtained. By setting (usually about 25°C) to room temperature, the ratio to the room temperature discharge capacity can be obtained. The ratio obtained at this time is a capacity utilization rate reflecting the effect of temperature T, and as defined by Equation 4 above, it was modeled as a function using a second-order polynomial with temperature T as a variable as an exponent.

However, since the discharge capacity is also affected by the discharge current, in the embodiment of the present invention, the ratio of the discharge capacity for each temperature to the room temperature discharge capacity is obtained for different discharge rates, and curve fitting ( Curve Fitting). The different discharge rates at this time were set to 0.2C and 0.5C, so that a temperature factor calculation formula was obtained that can reduce the error due to the influence of the discharge current as much as possible.

Meanwhile, different temperatures to be tested for curve fitting included at least -30°C and 50°C so that curve fitting from low temperature to high temperature, and temperatures dividing between -30°C and 50°C into multiple sections were included.

As described above, the temperature factor calculation equation defined by Equation 4 is programmatically coded to be used in the temperature factor selection unit 31a of the performance prediction factor calculation unit 31 of the residual amount estimating unit 30 to be described later. The constants a, b and c obtained by this are stored in the data storage unit 10 as parameter values of the temperature factor calculation equation.

는 충방전율에 따른 용량 활용률로서, 아래의 표 1로 보여주는 룩업테이블과 같이 정의하여, 상기 데이터 저장부(10)에 저장하여 두었다.Next, the current factor

Is a capacity utilization rate according to a charge/discharge rate, defined as a lookup table shown in Table 1 below, and stored in the data storage unit 10.

Charge rate or discharge rate

T <0.2C 1.0 0.2C ≤T <0.5C 0.9 0.5C ≤T <1.0C 0.85 1.0C ≤T 0.8

는 충방전율 구간별로 설정되어 있으므로, 측정 전류가 속한 구간의 값을 전류 영향을 반영한 용량 활용률로서 사용할 수 있게 한다. 예를 들어, 충방전율 구간별 전류인자

의 값은 구간별 대표 방전율에 대해 각각 측정한 용량 활용률로 선정할 수 있다. 아울러, 서로 다른 온도 환경에 각각 충방전율 구간별 용량 활용률을 얻은 후, 오차를 최소화할 수 있는 최적으로 값으로 선정할 수도 있다. 또한, 표 1의 충방전율 구간 수는 좀 더 많게 하여 구간을 세분화할 수도 있다.Referring to Table 1 above, the current factor

Since is set for each charge/discharge rate section, the value of the section to which the measured current belongs can be used as a capacity utilization rate reflecting the current effect. For example, the current factor for each charge/discharge rate section

The value of can be selected as the capacity utilization rate measured for each representative discharge rate for each section. In addition, after obtaining the capacity utilization rate for each charge/discharge rate section in different temperature environments, it may be selected as an optimal value that can minimize an error. In addition, the number of charge/discharge rate sections in Table 1 may be increased to further subdivide the sections.

의 룩업테이블을 상기 데이터 저장부(10)에 저장하여 둠으로써, 후술하는 바와 같이 충방전에 따른 잔여 용량을 예측할 시에 활용되게 한다.As described above, the values of the constants a, b and c of the temperature factor calculation equation defined by Equation 4 and the current factor defined in Table 1

The lookup table of is stored in the data storage unit 10 to be used when predicting the remaining capacity due to charging and discharging, as described later.

The measurement unit 20 includes a current sensor 21, a temperature sensor 22, and a voltage sensor 23 to measure the current, temperature, and voltage of the lithium secondary battery 1 in real time, and the data storage unit 10 ). Of course, current, temperature, and voltage are obtained and stored as digital data values of a preset sample period.

In describing the embodiment of the present invention, it is not described how the measured voltage is used, but it can be used as data for monitoring the state of the lithium secondary battery 1, and in addition, the remaining voltage according to the measured voltage is not described. By adopting a known technique for predicting capacity, it can be utilized to correct the remaining capacity. For example, even if the remaining capacity is predicted by integrating the current according to Equation 2, the remaining capacity corresponding to the voltage measured during the idle period when the lithium secondary battery 1 is not used is selected based on the voltage-capacity correlation. It is to correct.

The remaining amount prediction unit 30 is a performance prediction factor calculation unit 31 that calculates a performance prediction factor according to the temperature and current measured when charging and discharging a lithium secondary battery, and calculates an increase or decrease in capacity by applying the performance prediction factor. It includes a capacity increase/decrease operation unit 32 and a remaining capacity prediction unit 33 that corrects and predicts the remaining capacity according to the capacity increase/decrease.

The performance prediction factor calculation unit 31 includes a temperature factor selection unit 31a that calculates a temperature factor corresponding to the measured temperature based on the temperature factor calculation equation of Equation 4, and a current factor corresponding to the charge/discharge rate of the measured current. A current factor selection unit 31b is provided for selecting according to the lookup table of Table 1, and a temperature factor and a current factor are multiplied to obtain a performance prediction factor of Equation 3.

Of course, the constants a, b, and c of the temperature factor calculation equation apply the values stored in the data storage unit 10, and the lookup table applies what is stored in the data storage unit 10.

Here, as the temperature factor, a value corresponding to the temperature can be applied to a continuous temperature change by using the temperature factor calculation equation fitted with Equation 4 above.

을 얻는다. The capacity increase/decrease operation unit 32 is in Equation 2, the capacity increase/decrease

Get

That is, by applying a performance prediction factor including a temperature factor corresponding to the measured temperature, the integrated current amount corrected by reflecting the temperature effect is obtained.

Similarly, by applying a performance prediction factor including a current factor corresponding to the charge/discharge rate of the measured current, the accumulated current amount corrected by reflecting the current effect is obtained.

을 상기 수학식 2에 대입하여, SOC로 표현한 잔여 용량을 얻는다. 앞서 언급하였듯이, 최대 충전 용량에 따른 상수 k에 용량 증감분을 곱셈하여 얻는

는 SOC 증감분이 되므로, 이전 SOC에 SOC 증감분을 가감하여 현재의 SOC의 예측치를 얻게 된다.The remaining capacity prediction unit 33 increases or decreases the capacity

Substituting in Equation 2 above, a residual capacity expressed by SOC is obtained. As mentioned earlier, the constant k according to the maximum charging capacity is multiplied by the capacity increase or decrease.

Is the SOC increase or decrease, so by adding or subtracting the SOC increase or decrease to the previous SOC, the predicted value of the current SOC is obtained.

The predicted SOC is stored in the data storage unit 10 and recorded in the SOC history. Although not shown in the drawing, in order to utilize the predicted SOC, a known display means or BMS (Battery Management System) and may include a known means of linking. Of course, the apparatus for predicting the remaining amount of a lithium secondary battery according to the present invention may be configured to be built into the BMS.

FIG. 2 is a flow chart of a method for predicting remaining amount of a lithium secondary battery according to an embodiment of the present invention. Since it is made by the device for predicting remaining amount of remaining lithium secondary battery described with reference to FIG. 1, repeated descriptions will be omitted, and a description will be focused on the order of the method. .

간격마다 순차적으로 수행하여, 잔여 용량을

간격으로 갱신하는 것으로 설명한다. 여기서,

는 디지털 데이터 처리를 위한 시간 간격으로서, 디지털 데이터로 얻기 위한 샘플 주기의 배수로 할 수 있다.Since the remaining capacity is predicted by digital data processing, the method for predicting the remaining amount of a lithium secondary battery according to an embodiment of the present invention includes a measuring step (S10), a performance predicting step (S20, S21, S22), and a remaining amount predicting step (S30, S31). To

It is performed sequentially at intervals, and the remaining capacity is

It will be described as updating at intervals. here,

Is a time interval for digital data processing, and can be a multiple of the sample period for obtaining digital data.

When it is determined that charging or discharging is performed by monitoring the current measured by the measurement unit 20, the remaining amount predicting unit 30 monitors the current measured by the measurement unit 20, and if it is determined that the charging or discharging is performed, the measuring step S10, the performance predicting step S20, S21, S22 and the remaining amount predicting step The circular loop for sequentially performing (S30, S31) is repeatedly performed, and if an end condition occurs in the end confirmation step (S40), the circular loop is terminated.

간격으로 불러들인다(S10). 물론, 측정부(20)를 통해 측정되는 전류 및 온도 값을 잔량 예측부(30)에서 직접 받아도 좋다.In the measuring step (S10), the current and temperature measured through the measuring unit 20 and stored in the data storage unit 10 are measured.

Call at intervals (S10). Of course, the current and temperature values measured through the measurement unit 20 may be directly received from the residual amount prediction unit 30.

간격의 측정 온도에 대응되는 온도인자를 상기 수학식 4의 온도인자 산정식에 근거하여 산정하고(S20),

간격의 측정 전류의 충전율 또는 방전율에 대응되는 전류인자를 상기 표 1의 룩업테이블에 근거하여 선정한 후(S21), 온도인자에 전류인자를 곱셈하여 성능 예측인자를 얻는다(S22).Next, in the performance prediction step (S20, S21, S22)

A temperature factor corresponding to the measured temperature of the interval is calculated based on the temperature factor calculation formula of Equation 4 (S20),

After selecting a current factor corresponding to the charging rate or the discharge rate of the measured current in the interval based on the lookup table in Table 1 (S21), a performance predictor is obtained by multiplying the temperature factor by the current factor (S22).

시간 동안 변동한 후의 잔여 용량을 예측한다(S31). 여기서 얻는 잔여 용량은 상기 데이터 저장부(10)에 기록함은 물론이고 현재 잔여 용량을 갱신한다.Next, in the remaining amount prediction steps (S30, S31), after calculating the capacity increase/decrease reflecting the performance predictor (S30), the capacity increase/decrease is added or subtracted to the previous remaining capacity.

The remaining capacity after fluctuations over time is predicted (S31). The remaining capacity obtained here is recorded in the data storage unit 10 as well as the current remaining capacity is updated.

Since the remaining capacity is obtained by digital data processing, the remaining capacity is obtained by using Equation (5) below, which is modified from Equation (2).

를 샘플 주기의 2배수 이상으로 설정 사용한다면, 전류 평균치 및 온도 평균치에 따라 성능 예측인자

를 산정하여 상기 수학식 5에 적용한다.if,

If used by setting as more than twice the sample period, the performance predictor according to the current average value and the temperature average value

Is calculated and applied to Equation 5.

Next, by performing the termination confirmation step (S40), it is determined whether to perform the residual capacity update operation again consisting of the measurement step (S10), the performance prediction steps (S20, S21, S22), and the remaining amount prediction steps (S30, S31). do. For example, it is determined whether it is a pause period according to the stationary of the driving motor of an EV (Electric Vehicle) or HEV (Hybrid Electric Vehicle) in which the lithium secondary battery 1 is mounted and used, and if it is not the suspension period, the capacity update operation is repeated, If it is a period of rest, it ends. Of course, although not shown in the drawings, as a means for detecting the operation of a device in which the lithium secondary battery 1 is mounted and used, an interrupt signal related to a driving operation of the device may be input.

On the other hand, as a modified embodiment of the present invention, the remaining amount prediction unit 30 performs an operation of updating the remaining capacity even when the lithium secondary battery is less than 0°C and is in the idle period, but the temperature calculated according to the temperature of the lithium secondary battery The remaining capacity can be predicted by reflecting only the factor. That is, the value of the current factor in the performance prediction factor is set to a value of 0. The device equipped with the lithium secondary battery 1 can consume low power as well as self-discharge even when it is not driven, and its effect can be large at low temperatures. In this situation, a temperature factor is applied to reduce the fluctuating residual capacity. It is to predict.

In this case, in the termination confirmation step (S40), a determination criterion for determining whether to perform a residual capacity prediction operation based on current integration may be separately prepared. For example, the case of predicting the remaining capacity according to the voltage during the idle period may be used as a criterion.

<Specific Example: Curve fitting of temperature factor calculation formula>

In a state where a single cell of a lithium ion polymer battery with a nominal voltage of 3.7V and a nominal capacity of 50Ah is placed in a constant temperature chamber, the temperature of the constant temperature chamber is maintained at room temperature (25°C in the embodiment of the present invention) and fully charged, and then to the test temperature. After adjustment, it was allowed to stand for 2 hours, and then discharged to the discharge end voltage at a discharge rate of 0.2C to obtain a discharge capacity. Here, the discharge capacity was obtained for the case where the test temperatures were -30°C, -10°C, 0°C, 25°C, and 50°C, respectively.

Further, only the discharge rate was 0.5C, and the discharge capacities under the environment of -30°C, -10°C, 0°C, 25°C and 50°C were obtained again.

The table below is the result of arranging the discharge capacity by temperature obtained by discharging at the discharge rates of 0.2C and 0.5C as a ratio to the room temperature discharge capacity (that is, the capacity utilization rate according to temperature).

Temperature [℃] (Discharge capacity)/(Room temperature discharge capacity) Discharge rate 0.2C Discharge rate 0.5C -30 0.754 0.751 -10 0.873 0.861 0 0.921 0.903 25 One One 50 0.995 0.999

의 값을 온도인자 산정식

으로 커브 피팅한 결과, 상수 a는 -0.0807이고, b는 0.00477이고, c는 -0.0000648이었다. 여기서, 상온 방전용량은 특정 온도로 하지 아니하고 용량 활용률이 최대인 온도로 하는 것이 좋다.Next, the ratio representing the capacity utilization rate

The value of the temperature factor calculation formula

As a result of curve fitting with, the constant a was -0.0807, b was 0.00477, and c was -0.0000648. Here, it is preferable not to set the room temperature discharge capacity to a specific temperature, but to a temperature at which the capacity utilization rate is maximum.

과 커브 피팅한 그래프를 보여주는 그래프이다.Figure 3 shows 0.2C and 0.5C discharge rates and capacity utilization rates obtained under -30°C, -10°C, 0°C, 25°C and 50°C temperature environments.

This is a graph showing a graph with curve fitting and curve fitting.

의 차이가 나타남을 확인할 수 있다. 이에, 0.2C 및 0.5C 방전율을 얻은 결과에 따라 커브 피팅하여서, 어느 한 방전율에 편중되지 아니한 피팅 결과를 얻었다.Referring to Figure 3, the capacity utilization rate according to the difference in the discharge rate

It can be seen that the difference appears. Accordingly, curve fitting was performed according to the results obtained at 0.2C and 0.5C discharge rates, thereby obtaining a fitting result that was not biased against any one discharge rate.

<Specific Example: Performance Comparison>

The predicted performance before and after reflecting the temperature factor or the current factor was compared.

Here, the temperature factor was obtained by the temperature factor calculation equation in which the values of constants a, b, and c were determined according to the curve fitting result, and the lookup table of Table 1 was applied as the current factor.

In order to compare the predicted performance, the lithium secondary battery was charged with approximately 61% SOC at room temperature, left at -10°C for 2 hours, and then EV (Electric Vehicle) was evaluated for 1 hour. Temperature, voltage and current data were obtained.

Referring to the graph of FIG. 4, the current shows a pattern in which a discharge pattern according to driving of the EV electric motor and a charging pattern due to a regenerative current at stop are mixed. The maximum charging current is 44A, the maximum discharge current is -60A, and the average current is -3.73A.

The voltage is maintained at 3.85V during the initial idle period, and after the EV electric motor is started, the discharge pattern and the charging pattern are mixed like the current pattern. It is 4.14V in the section in which the maximum charging current flows, and 3.45V in the section in which the maximum discharge current is applied.

The temperature increased after starting of the EV and maintained at approximately -10.5°C, and reached a maximum value of -9.5°C when approximately 3000 seconds elapsed during the evaluation process.

As a result of measuring at room temperature before EV evaluation, the residual capacity (SOC) was approximately 61.2%, and by applying the current and temperature data obtained by EV evaluation, the residual capacity was predicted by the current integration method.

5 shows the residual capacity (A graph) predicted by not applying the performance predictor (temperature factor and current factor), the residual capacity (B graph) predicted by applying the temperature factor but the current factor as 1, and the temperature factor as the rest period. This is a diagram showing the estimated residual capacity (C graph) with the current factor as 1, and the estimated residual capacity (D graph) by applying both the temperature factor and the current factor but not during the rest period.

Referring to FIG. 5, the residual capacity (B, C, D graph) predicted by applying the performance predictor is lower than the residual capacity predicted without applying the performance predictor (A graph), and even if the performance predictor is applied, the temperature The residual capacity predicted by applying both the temperature factor and the current factor (D graph) was lower than the residual capacity predicted by applying only the factor (B, C graph). In addition, there was also a difference in the remaining capacity (B, C graph) before and after applying the temperature factor during the rest period.

As a result of predicting the residual capacity SOC after completing the EV evaluation, it is 53.8% (A graph) when the performance predictor is not applied, 52.7% (B graph) when only the temperature factor is applied, and the temperature factor is paused. When applied to also, it was 52.5% (C graph), and when both temperature and current factors were applied, it was 51.8% (D graph).

In order to obtain the actual remaining capacity after the EV evaluation was completed, the EV discharge test was conducted at -10°C, allowed to stand for 2 hours, and then discharged to the discharge end voltage to measure the discharge capacity. The discharge time took 2.6 hours, the discharge capacity was measured as 26Ah, and as a result of conversion to SOC, the actual remaining capacity was 52%.

As a result of comparing the actual residual capacity and the predicted residual capacity, the error was the least when both the temperature factor and the current factor were applied.

In addition, it was confirmed that even if only the temperature factor was applied, the predictive performance of the remaining capacity was greatly improved.

In addition, it was confirmed that the prediction performance was further improved when the temperature factor was applied to the rest period as well.

Here, the pause period includes before starting the EV and after starting and stopping the EV (i.e., the period in which the EV is stopped). To expand the meaning, devices such as EVs, HEVs, and devices in which lithium secondary batteries are mounted and used It can be viewed as a state in which the drive is stopped, that is, a state in which the power supply used for driving is cut off and not used. For example, in EV, when the driving motor is operated, the remaining capacity is predicted using the current integration method.Even when the driving motor is stopped, the remaining capacity is predicted by applying a temperature factor to reflect the change in the remaining capacity during the idle period. Is to predict in real time.

1: Lithium secondary battery
10: data storage unit
20: measurement unit
21: current sensor 22: temperature sensor 23: voltage sensor
30: remaining amount prediction unit
31: Calculation of performance predictors
31a: temperature factor selection unit 31b: current factor selection unit
32: capacity increase/decrease calculation unit
33: remaining capacity prediction unit

Claims (12)

In the lithium secondary battery remaining amount prediction method for predicting the remaining capacity of the lithium secondary battery by adding or subtracting the accumulated current amount,
A measuring step of measuring the temperature and current of the lithium secondary battery with a sensor;
Curve fitting by obtaining the ratio of the discharge capacity of each temperature to room temperature discharge capacity obtained by discharging to the discharge end voltage in different temperature environments including -30℃ and 50℃ for discharge rates including 0.2C and 0.5C, respectively. ) Based on a preset temperature factor calculation formula, calculate the temperature factor corresponding to the measured temperature, and respond to the charging/discharging rate of the measured current based on a lookup table in which the current factor defined as the capacity utilization rate for each charging/discharging rate section is set. After selecting the current factor to be used, the value obtained by multiplying the temperature factor and the current factor is obtained as the value of the performance prediction factor. A performance prediction step of obtaining a performance predictor as a value;
A residual amount predicting step of predicting a residual capacity of a lithium secondary battery by applying an accumulated current amount corrected according to a performance predictor;
Including,
In the performance prediction step, the temperature factor calculation equation is

This,

Is the temperature factor,

Is the measured temperature, a, b and c are preset constants obtained by curve fitting,
The accumulated current amount corrected according to the temperature factor in the remaining amount prediction step is

Is calculated as,

Is the performance predictor,

Is the performance predictor

It is corrected by and used as the measured current to be accumulated.
Method for predicting remaining amount of lithium secondary battery. delete delete delete delete delete delete Curve fitting by obtaining the ratio of the discharge capacity of each temperature to room temperature discharge capacity obtained by discharging to the discharge end voltage in different temperature environments including -30℃ and 50℃ for discharge rates including 0.2C and 0.5C, respectively. ) A data storage unit 10 storing a lookup table in which a parameter value of a preset temperature factor calculation equation and a current factor defined as a capacity utilization rate for each charge/discharge rate section are set;
A measuring unit 20 for measuring the temperature and current of the lithium secondary battery with a sensor; And
The temperature factor corresponding to the measured temperature is obtained by the above temperature factor calculation formula, and a current factor corresponding to the charging/discharging rate of the measured current is selected based on the lookup table, and then the performance prediction factor obtained by multiplying the temperature factor and the current factor is applied. , When the lithium secondary battery is less than 0℃ and is in the idle period, the current factor is set to 1 and a performance prediction factor that becomes the value of the temperature factor is applied to correct the accumulated current amount, and the corrected current accumulated amount is applied to the lithium battery. A residual amount predicting unit 30 for predicting a residual capacity of the secondary battery;
Including,
The above temperature factor calculation formula is

This,

Is the temperature factor,

Is the measured temperature, a, b and c are preset constants obtained by curve fitting,
The remaining amount prediction unit 30

Calculate the corrected current integration amount according to,

Is a performance predictor,

Is the performance predictor

It is corrected by and used as the measured current to be accumulated.
A device for predicting the remaining amount of lithium secondary batteries. delete delete delete delete

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