KR20220130366A - Method of Online Detection of Soft Internal Short Circuit in Lithium-Ion Batteries at Various Standard Charging Ranges and Apparatus thereof - Google Patents

Abstract

According to the present invention, an early detection method of an internal short fault generated in a lithium-ion battery in a constant-current charging situation is a method of estimating the open circuit voltage (OCV) and state of charge (SOC) of a lithium-ion battery by using the equivalent circuit model (ECM) of the battery and measured signals in an algorithm for detecting an internal short fault in an early stage by using current and voltage signals measured in the process of charging the battery at a constant current. The accuracy of estimation can be increased by using a fault index including information on the degree of a fault as well as whether an internal short fault exists.

Description

Method and apparatus for early detection of internal short circuit failures {Method of Online Detection of Soft Internal Short Circuit in Lithium-Ion Batteries at Various Standard Charging Ranges and Apparatus thereof}

The present invention relates to a method and apparatus for early detection of an internal short circuit failure, and a method for early detection of an internal short circuit failure using an algorithm for early detection of an internal short circuit failure using current and voltage signals measured in the process of charging a lithium ion battery with a constant current and devices.

Due to the importance of detecting a short circuit inside the battery, the demand for lithium ion batteries as an energy storage system (ESS) in electric vehicles and smart grid systems is expected to increase explosively due to high energy power and long lifespan. Recently reported incidents such as solar energy storage system (ESS) fire incidents, cell phone explosion incidents, and electric vehicle fire incidents reported at home and abroad have been an opportunity for consumers to pay great attention to the safety of batteries. The main cause of the mentioned accidents was investigated as battery thermal runaway, and in particular, a short circuit inside the battery is considered to be the main cause of thermal runaway. Therefore, a method for detecting a short circuit inside a battery is required to prevent damage to human and property in advance.

The concept of internal short circuit and the importance of early detection of internal short circuit, internal short circuit of a battery can occur in the battery due to manufacturing defects, changes in chemical composition during use, misuse such as overcharging and overdischarging the user's battery. It is a weak failure stage at the initial occurrence of an internal short circuit in the battery, which does not affect the operation of the battery, but the battery usage efficiency is lowered due to the continuous self-discharge current. If the battery in this state continues to be used or develops into a severe failure stage internal short circuit due to the physical collision of the battery, the battery will undergo thermal runaway accompanied by explosion and fire. So, not only to detect the internal short circuit in the severe failure stage, but also detect the internal short circuit in the weak failure stage (early detection of internal short circuit) to calculate the correct remaining usage time of the battery, and also reduce the time the user can replace the battery. Therefore, there is a need for a method for early detection of an internal short circuit.

The prior art is a performance limitation of the internal short-circuit detection method using the measured signal threshold, from the signal characteristics (voltage decrease, temperature increase) measured when a physical shock is given to the battery in advance and a severe internal short-circuit failure occurs in the battery. Threshold is calculated, and the presence or absence of internal short-circuit failure is determined based on the voltage and temperature measured in real time using this. However, it has a performance limitation of not detecting weak internal short-circuit failures along with the need for preliminary severe internal short-circuit failure testing.

In addition, as a performance limitation of the internal short circuit detection method using the real-time estimated equivalent circuit model parameter change, the battery is expressed as an electrical equivalent circuit model, and the model parameters are estimated using the battery current and voltage measured in real time. Based on the estimated model parameter of the normal battery, it is determined whether there is an internal short circuit failure using the degree of change in the model parameter estimated from the battery in which the internal short circuit has occurred. However, it has a performance limitation that it cannot be used as a failure index to classify failure stages because the degree of parameter change from a weak failure stage to a severe failure stage is not linear.

In addition, due to the performance limitations and detectable environment limitations of the internal short circuit detection method that estimates the internal short circuit resistance in real time in the equivalent circuit model expressing the internal short circuit, the internal short circuit occurred in the battery by connecting the short circuit resistance in parallel to the existing battery equivalent circuit model. was expressed and the degree of internal short circuit was described as the size of the short circuit resistance. By estimating the short-circuit resistance on the circuit directly using the load current applied to the battery and the output terminal voltage, a failure index that can distinguish the internal short-circuit failure stages was proposed. However, there is a limitation in performance that the accuracy of the estimated internal short-circuit resistance is low, and also the short-circuit resistance may not be estimated depending on the load current applied to the battery, so the battery usage environment in which the failure index can be detected is limited. .

An object of the present invention for solving the above problems is the open circuit voltage (OCV) and the state of charge of the battery using the measured signal and the battery equivalent circuit model (ECM) , we propose a method for estimating SOC). Early detection of internal short-circuit failures that occur in lithium-ion batteries under current charging conditions, which can suggest a failure index that includes information on the degree of failure as well as the presence or absence of an internal short-circuit failure and increase the estimation accuracy. A detection method and apparatus are provided.

In order to achieve the above object, an apparatus for early detection of an internal short circuit failure according to an embodiment of the present invention comprises: a processor; a memory in which at least one instruction executed by the processor is stored; Including, but at least one command, in the process of charging the lithium ion battery with a constant current, measuring a current and a voltage signal, and using the measured signal and a battery equivalent circuit model (ECM) to open circuit of the battery a command for estimating an Open circuit voltage (OCV) and a State of charge (SOC); may include.

The device, the internal short circuit resistance (R _ISCr ) and the cell (Cell) is built-in thermal chamber (Thermal chamber); a battery test device connected to the thermal chamber to perform a battery cell test; a data logger & computer connected to the thermal chamber to record experimental data including charging current and terminal voltage signals; Switch to trigger ISCr, which triggers an internal short circuit (ISCr) fault with a switch when standard charging current is applied to a cell with multiple initial states of charge (STATE OF CHARGE, SOC); may include.

The apparatus may include a failure index extraction unit using the failure index including information on the degree of failure as well as the presence or absence of an internal short circuit failure.

The failure index extraction unit may include: an internal short-circuit resistance estimation start time determination unit for variously determining a time point for estimating the internal short-circuit resistance; an internal short-circuit resistance estimator that directly estimates the internal short-circuit resistance using the current and voltage signals obtained from standard battery charging; a failure index representative value selection unit that obtains one failure index representative value from a plurality of internal short circuit resistances obtained from various points of view; may include.

The internal short-circuit resistance estimating unit includes a standard charging unit for charging the battery and measuring the charging constant current and the battery terminal voltage together; a characteristic curve extractor for extracting an OPEN CIRCUIT VOLTAGE (OCV)-STATE OF CHARGE (SOC) curve of the battery required to estimate the open circuit voltage and state of charge of the battery from the constant current; The open circuit voltage (OPEN CIRCUIT VOLTAGE, OCV) obtained from the signal measured in the standard charging part of the battery and the characteristic curve extraction part 302 - The open circuit voltage (OPEN) from the battery model equation using the state of charge (SOC) curve a real-time battery state estimator for estimating CIRCUIT VOLTAGE, OCV) and state of charge (STATE OF CHARGE, SOC); an internal short-circuit resistance extractor that calculates an internal short-circuit resistance using the estimated state of charge (SOC) of the battery; and a model update unit that updates the battery model using the estimated internal short-circuit resistance. may include.

In accordance with another aspect of the present invention, there is provided a method for early detection of internal short circuit failure, comprising the steps of: initiating a failure index extraction system for internal short circuit detection by a failure index extraction unit; determining, by the internal short-circuit resistance estimation start time determination unit, a time point for estimating internal short-circuit resistance in various ways; directly estimating the internal short-circuit resistance by the internal short-circuit resistance estimator using the current and voltage signals obtained from standard battery charging; and obtaining, by the failure index representative value selection unit, one representative failure index value from a plurality of internal short circuit resistances obtained from various time points. may include.

Standard charging the battery by the standard charging unit and measuring the charging constant current and the battery terminal voltage together; extracting an open circuit voltage (OCV)-STATE OF CHARGE (SOC) curve of the battery required for the characteristic curve extraction unit to estimate the open circuit voltage and the state of charge of the battery from the constant current; The open circuit voltage from the battery model equation using the OPEN CIRCUIT VOLTAGE (OCV)-STATE OF CHARGE (SOC) curve obtained from the signal measured in the standard charging part of the battery and the characteristic curve extraction part by the real-time battery state estimator estimating (OPEN CIRCUIT VOLTAGE, OCV) and a state of charge (STATE OF CHARGE, SOC); calculating, by an internal short-circuit resistance extractor, an internal short-circuit resistance using the estimated state of charge (STATE OF CHARGE, SOC) of the battery; and updating, by the model updater, the battery model using the estimated internal short-circuit resistance. may further include.

In the above method, a battery model in which an internal short circuit occurs may be defined by Equation (1).

)을 계산할 수 있다. In the above method, the internal short-circuit resistance extractor uses the state of charge (STATE OF CHARGE, SOC) estimated in real time by the real-time battery state estimator and the current and voltage values measured from Equation 2 to the internal short-circuit resistance (

) can be calculated.

It may be a computer-readable recording medium for implementing the program of the internal short-circuit failure early detection method according to any one of the internal short-circuit failure early detection methods for achieving another object of the present invention.

According to an embodiment of the present invention, the use of the method for estimating the internal short-circuit resistance in the prior art is limited to a battery operating environment (electric vehicle discharge situation, etc.) in which a battery load current that satisfies a specific condition is used,

In the method and apparatus for early detection of an internal short circuit failure of the present invention, an internal short circuit can be detected early in a general battery standard charging environment (constant current charging) in order to overcome a specific internal short circuit detectable environment.

In addition, it is possible to improve the estimation accuracy of the internal short-circuit resistance used as the failure index.

In addition, it is possible to propose an algorithm for early detection of a short circuit inside a battery in real time by using the current and voltage measured in a standard battery charging situation.

The algorithm of the method and apparatus for early detection of an internal short circuit failure of the present invention may include a method of estimating an open circuit voltage (OPEN CIRCUIT VOLTAGE, OCV) and a state of charge (STATE OF CHARGE, SOC) of a battery in a constant current environment.

A method for estimating the internal short circuit resistance at multiple points and extracting the final failure index to improve the estimation accuracy of the failure index may also be included.

In addition, by diagnosing an internal short circuit occurring in the battery at an early stage using the current and voltage signals obtained in the standard charging state of the battery, it is possible to overcome the limitation in that the diagnosis is possible only in a specific discharge condition of the prior art.

In addition, it is possible to detect internal short circuits in various charging ranges rather than full charge, and the estimation accuracy of internal short circuit resistance used as a failure index is greatly improved, which is a battery failure state far away from the period leading to thermal runaway in the severe failure phase. battery usage safety can be improved, and the accuracy of the battery model can be improved due to the internal short-circuit resistance estimated in the weak failure stage, thereby diagnosing the current battery condition more accurately, which can greatly contribute to improving the use efficiency.

1 is a schematic diagram showing a schematic configuration of a method for early detection of an internal short circuit failure according to the present invention.
2 is a block diagram illustrating an internal short circuit (ISCr) experiment bench of the device for early detection of an internal short circuit failure according to the present invention.
3 is a block diagram of the failure index extraction unit 100 of the device for early detection of an internal short circuit failure according to the present invention.
4 is a block diagram of the internal resistance estimator 300 of the device for early detection of an internal short circuit failure according to the present invention.
5 is a graph illustrating an example of an open circuit voltage (OPEN CIRCUIT VOLTAGE, OCV)-STATE OF CHARGE (SOC) curve at room temperature of the present invention.
6 is an exemplary histogram of estimated internal short-circuit resistance values (when the internal short-circuit resistance is 50Ω) according to the present invention.
7 (a) and (b) are graphs showing a plurality of internal short-circuit resistance values (R _ISCr ) estimated at a plurality of estimation points when ISCr is 50Ω in the method for early detection of an internal short circuit failure of the present invention, and an enlarged graph thereof to be.
8 is a flowchart of a failure index extraction algorithm of the method for early detection of an internal short circuit failure according to the present invention.
9 is a flowchart of an internal short circuit resistance estimation algorithm of the internal short circuit failure early detection method according to the present invention.

Since the present invention can have various changes and can have various embodiments, specific embodiments are illustrated in the drawings and described in detail in the detailed description. However, this is not intended to limit the present invention to specific embodiments, and should be understood to include all modifications, equivalents and substitutes included in the spirit and scope of the present invention. In describing each figure, like reference numerals have been used for like elements.

Terms such as first, second, A, B, etc. may be used to describe various elements, but the elements should not be limited by the terms. The above terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, a first component may be referred to as a second component, and similarly, a second component may also be referred to as a first component. The term "and/or" includes a combination of a plurality of related listed items or any of a plurality of related listed items.

When a component is referred to as being “connected” or “connected” to another component, it may be directly connected or connected to the other component, but it is understood that other components may exist in between. it should be On the other hand, when it is said that a certain element is "directly connected" or "directly connected" to another element, it should be understood that the other element does not exist in the middle.

The terms used in the present application are only used to describe specific embodiments, and are not intended to limit the present invention. The singular expression includes the plural expression unless the context clearly dictates otherwise. In the present application, terms such as “comprise” or “have” are intended to designate that a feature, number, step, operation, component, part, or combination thereof described in the specification exists, but one or more other features It is to be understood that this does not preclude the possibility of the presence or addition of numbers, steps, operations, components, parts, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in a commonly used dictionary should be interpreted as having a meaning consistent with the meaning in the context of the related art, and should not be interpreted in an ideal or excessively formal meaning unless explicitly defined in the present application. does not

Hereinafter, preferred embodiments according to the present invention will be described in detail with reference to the accompanying drawings.

1 is a schematic diagram showing a schematic configuration of a method for early detection of an internal short circuit failure according to the present invention.

Referring to Fig. 1, the overall structure of the proposed algorithm of the method for early detection of an internal short circuit failure of the present invention is shown.

Internal short circuit resistance (R _ISCr ) estimation process 100 is a standard charging internal short circuit resistance (R _ISCr ) (Internal short circuit resistance) standard for on-line detection of soft internal short circuit (R _ISCr ) (Internal short circuit) It is estimated with the measured terminal voltage and constant current for (110).

In order to improve the estimation accuracy of the internal short-circuit resistance (R _ISCr ) and obtain a reliable final fault index ( 200 ), various estimation points are used to estimate various internal short-circuit resistance (R _ISCr ).

The average value of this estimate is used as the final failure index after excluding outliers with the largest deviation.

In an embodiment of the present invention, an experiment on a soft internal short circuit (ISCr) was performed to verify the proposed method. Experimental data were obtained using two identical batteries (SAMSUNG INR 18650-29E) A and B, and the nominal capacity of the cell is 2.850 Ah. The charge and discharge cut-off voltages correspond to 4.2V and 2.5V, respectively, and the nominal voltage corresponds to 3.65V. Pre-tests were performed to obtain dose and OCV-SOC curves. The capacity test showed that the cell was charged with a constant current-constant voltage (CC-CV) protocol and then discharged to 0.2C (0.57A) with a CC discharge. The discharge capacity was defined as the actual capacity and the values correspond to 2.8374 Ah and 2.8340 Ah for cells A and B, respectively. Regarding the OCV-SOC curve test, a fully charged battery cell was rested for 4 hours to measure an OCV equal to the terminal voltage at 100% SOC. Then, a discharge current of 0.5C was applied to the cell for 720 s to set 90% SOC, and then the cell was rested for 4 h to obtain OCV. The process was repeated until 0% SOC was reached and an experimental OCV-SOC curve was obtained.

2 is a block diagram illustrating an internal short circuit (ISCr) experiment bench of the device for early detection of an internal short circuit failure according to the present invention.

Referring to Figure 2, the configuration of the battery test bench is shown. The internal short circuit failure early detection device of the present invention, the internal short circuit resistor (R _ISCr ) 11 and the cell (Cell) 15 is a built-in thermal chamber (Thermal chamber) 10, a battery test device (Battery test device, Chroma 17020) (20); Data logger & Computer (30), Internal Short Circuit (ISCr) Switch to trigger ISCr, national Instruments (40).

The battery cells were tested in a thermal chamber where the ambient temperature of the cells was maintained at 25 ± 1 °C. Battery cell experiments were performed using a battery test device (Regenerative Battery Pack Test System 17020, Chroma), with a sample duration of 0.1 s. Experimental data, including charging current and terminal voltage signals, were measured through a data logger and stored in a computer. To represent the various soft ISCr errors, a resistor with ±5% tolerance is connected in parallel with the battery and the actual values measured correspond to 99.83, 49.91, 29.98 and 20.00. When the resistance is 99.83, the battery's self-discharge current is C/67 and the values represent 3% of the standard charge current (1.375A and C/2). In the present invention, the resistance range was set from 20.00 to 99.83 because 99.83 is a large enough value to account for the weak defect. Validation of the proposed method with experimental data with a wide resistance range (R _ISCr > 100) remains a future work. The relative error of the final fault index (R _fi ) was calculated as the actual resistance value. A soft internal short circuit (ISCr) fault was triggered by a switch when a standard charge current was applied to a cell with various initial SOCs. Cell A applied 49.91, 29.98 and 20.00 to soft ISCr defects and cell B applied 99.83.

3 is a block diagram of the failure index extraction unit 100 of the device for early detection of an internal short circuit failure according to the present invention.

Referring to FIG. 3 , a flowchart of an overall algorithm for extracting a failure index to early detection of an internal short circuit in a standard battery state of charge in the present invention is disclosed.

The failure index extraction system 200 for detecting an internal short of the present invention includes a failure index extraction unit 100 .

The failure index extraction unit 100 includes an internal short-circuit resistance estimation start time determination unit 200 , an internal short-circuit resistance estimation unit 300 , and a failure index representative value selection unit 400 .

The internal short-circuit resistance estimation start time determination unit 200 variously determines the internal short-circuit resistance estimation timing ( 210 ).

The internal short-circuit resistance estimating unit 300 directly estimates the internal short-circuit resistance using the current and voltage signals obtained from standard battery charging ( 220 ).

The failure index representative value selection unit 400 obtains a single failure index representative value in consideration of deviations from a plurality of internal short circuit resistors 230 obtained from various time points (240).

4 is a block diagram of the internal resistance estimator 300 of the device for early detection of an internal short circuit failure according to the present invention.

Referring to FIG. 4 , the internal short-circuit resistance estimation unit 300 includes a battery standard charging unit 301 , a characteristic curve extraction unit 302 , a real-time battery state estimation unit 303 , an internal short-circuit resistance extraction unit 304 , and a model update. part 305 .

The standard battery charging unit 301 charges the battery and measures the charging constant current and the battery terminal voltage together.

The characteristic curve extraction unit 302 extracts an open circuit voltage (OCV)-STATE OF CHARGE (SOC) curve of the battery required to estimate the open circuit voltage and the state of charge of the battery from the constant current.

The real-time battery state estimating unit 303 includes a signal measured by the battery standard charging unit 301 and an open circuit voltage (OCV)-STATE OF CHARGE, SOC curve obtained by the characteristic curve extraction unit 302 . Estimate the open circuit voltage (OPEN CIRCUIT VOLTAGE, OCV) and the state of charge (STATE OF CHARGE, SOC) from the battery model equation using

The internal short-circuit resistance extractor 304 calculates the internal short-circuit resistance using the estimated state of charge (SOC) of the battery.

The model update unit 305 updates the battery model using the estimated internal short-circuit resistance.

5 is a graph showing an example of an open circuit voltage (OPEN CIRCUIT VOLTAGE, OCV)-STATE OF CHARGE (SOC) curve at room temperature of the present invention, and FIG. 6 is an estimated internal short-circuit resistance value of the present invention (When the internal short-circuit resistance is 50Ω) is an example of a histogram.

및 전압

을 배터리 표준 충전부(301)에서 측정한다. The device for early detection of internal short circuit failure of the present invention, the conventional method of estimating internal short circuit resistance operates only in a situation in which the battery is discharged with a load current that satisfies a specific condition (persistent excitation), and has a disadvantage in that it can detect an internal short circuit. In order to overcome this, the current measured when the standard charging 110 of the battery 120 having a different initial state of charge (STATE OF CHARGE, SOC) is charged with a constant current (current that does not satisfy a specific condition).

and voltage

is measured in the battery standard charging unit 301 .

A battery model in which an internal short circuit occurs is shown in Equation 1.

[Equation 1]

는 배터리의 화학적 특징에 의한 내부 저항을 나타내고,

는 내부 단락으로 유발된 자가방전 전류를 나타낸다. 즉, 배터리(120)를 표준 충전(110)시킬 때 충전 전류

에서 계속해서 누설되고 있는 자가 방전 전류

를 뺀 전류로 충전이 되는 것을 수학식 1은 설명하고 있다.here

represents the internal resistance by the chemical characteristics of the battery,

represents the self-discharge current induced by an internal short circuit. That is, the charging current when the battery 120 is standard-charged 110 .

self-discharge current continuously leaking from

Equation 1 explains that charging is performed by subtracting the current.

를 실시간으로 추정할 수 있었지만, 정전류 충전에서는 최소 순환 자승법을 동작하지 못하기 때문에 실시간 배터리 상태 추정부(303)에서 수학식 1로부터 배터리(120)의 개방 회로 전압(OPEN CIRCUIT VOLTAGE, OCV)를 구하게 되고 수식적으로 구해진 개방 회로 전압(OPEN CIRCUIT VOLTAGE, OCV)에 맞는 배터리의 개방 회로 전압(OPEN CIRCUIT VOLTAGE, OCV) - 충전 상태(STATE OF CHARGE, SOC) 곡선(140)을 이용하여 충전 상태(STATE OF CHARGE, SOC)를 추정하게 된다.In the prior art, the OPEN CIRCUIT VOLTAGE (OCV) of the battery is

could be estimated in real time, but the open circuit voltage (OPEN CIRCUIT VOLTAGE, OCV) of the battery 120 is obtained from Equation 1 in the real-time battery state estimator 303 because the least cyclic square method does not operate in constant current charging. The open circuit voltage (OPEN CIRCUIT VOLTAGE, OCV) of the battery corresponding to the mathematically obtained open circuit voltage (OPEN CIRCUIT VOLTAGE, OCV)-STATE OF CHARGE (SOC) curve 140 OF CHARGE, SOC) is estimated.

When the battery open circuit voltage (OPEN CIRCUIT VOLTAGE, OCV) in the first iteration is calculated from Equation 1, it is assumed that the battery 120 is normal and there is no self-discharge current. And the internal resistance is selected as a constant due to the experimental experience, and the battery open circuit voltage (OPEN CIRCUIT VOLTAGE, OCV) is calculated using only the measured voltage and current signals. If the internal short-circuit resistance is estimated later by the internal short-circuit resistance estimator 300 , the self-discharge current calculated from the model updater 305 is supplied using the estimated value.

The characteristic curve extracting unit 302 uses the current and voltage signals from full discharge to full charge of the normal battery 120 to draw an open circuit voltage (OPEN CIRCUIT VOLTAGE, OCV) from Equation 1 and the state of charge by the current integration method. (STATE OF CHARGE, SOC) is calculated respectively. By using these two values, the open circuit voltage (OPEN CIRCUIT VOLTAGE, OCV)-STATE OF CHARGE, SOC curve 140 of the normal battery 120 is extracted and provided to the real-time battery state estimation unit 303 and An example of an OPEN CIRCUIT VOLTAGE (OCV)-STATE OF CHARGE (SOC) curve of a battery is shown in FIG. 3 .

을 계산(170)하게 된다. The internal short-circuit resistance extraction unit 304 uses the state of charge (STATE OF CHARGE, SOC) 160 estimated in real time by the real-time battery state estimation unit 303 and the current and voltage values measured from Equation 2 to the internal short-circuit resistance

is calculated (170).

[Equation 2]

는 배터리 정격 용량을 나타내며,

는 배터리 표준 충전부(301)에서 신호를 측정할 때 샘플링 주기를 나타낸다.here,

indicates the rated capacity of the battery,

denotes a sampling period when a signal is measured in the battery standard charging unit 301 .

를 계산할 수 있으며 이를 활용해서 다음 반복(iteration)에서 개방 회로 전압(OPEN CIRCUIT VOLTAGE, OCV)를 계산할 때 사용되는 방식의 모델 업데이트(150)를 모델 업데이트부(305)에서 진행한다. 또한 매순간 추정되는 내부 단락 저항을 그대로 반영하기 보다는 순간적으로 튀는 추정값들의 영향을 줄이고자 추정되는 값들을 평균하여 평균값

을 모델 업데이트(150)에 사용한다. When the internal short-circuit resistance is estimated, the measured battery voltage is divided by the estimated internal short-circuit resistance to determine the self-discharge current caused by the short circuit.

can be calculated, and the model update unit 305 performs the model update 150 of the method used to calculate the open circuit voltage (OPEN CIRCUIT VOLTAGE, OCV) in the next iteration by using it. In addition, rather than reflecting the instantaneous internal short-circuit resistance as it is, to reduce the influence of instantaneous estimated values, the estimated values are averaged and averaged.

is used for model update 150 .

에서 하나의 내부 단락 저항을 얻기보다 다양한 시점에서 다수의 내부 단락 저항을 동시에 추정하기 위해서 내부 단락 저항 추정 시작 시점 결정부(200)에서 p시점을 추정된 충전 상태(STATE OF CHARGE, SOC)을 기준으로 특정 간격으로 다양하게 정하게 된다(210). 그리고 각 시점마다 평행하게 내부 단락 저항 추정부(300)는 동시에 작동이 되며, 배터리 충전이 종료되는 시점에서는 다수의 p시점과 같은 수의 내부 단락 저항의 추정 평균 값의 마지막 반복(iteration)에서의 값

을 얻게(230) 된다. 고장 인덱스 대표 값 선정부(400)에서는 다수의

에서 하나의 대표 값을 계산(250)하게 된다. 즉, 다수의

(230)을 도 4와 같이 추정 값들의 분산을 나타내는 히스토그램을 도시할 수 있으며, 히스토그램의 평균으로부터 가장 편차가 심한 몇 개의 추정 값들은 제거를 하고 비교적 평균에 가까운 값들을 평균하여 얻은 평균 값을 최종 내부 단락 고장을 검출하기 위한 최종 고장 인덱스(250)로 사용한다.In the failure index extraction unit 100, when estimating the internal short circuit resistance of the battery, one fixed time point

In order to simultaneously estimate a plurality of internal short-circuit resistances at various time points rather than obtaining one internal short-circuit resistance at is variously determined at a specific interval ( 210 ). And in parallel at each time point, the internal short-circuit resistance estimating unit 300 is simultaneously operated, and at the time when battery charging is finished, in the last iteration of the estimated average value of the same number of internal short-circuit resistance as a plurality of p time points. value

is obtained (230). In the failure index representative value selection unit 400, a plurality of

One representative value is calculated ( 250 ). That is, many

4, a histogram showing the variance of the estimated values can be shown. Some estimated values with the greatest deviation from the mean of the histogram are removed, and the average value obtained by averaging the values relatively close to the mean is finalized. It is used as the final failure index 250 for detecting an internal short-circuit failure.

7 (a) and (b) are graphs showing a plurality of internal short-circuit resistance values (R _ISCr ) estimated at a plurality of estimation points when ISCr is 50Ω in the method for early detection of an internal short circuit failure of the present invention, and an enlarged graph thereof to be.

Referring to (a) and (b) of FIG. 7 , as an exemplary experimental verification of the method devised in the present invention, a short-circuit resistance of 50Ω is connected in parallel to a SAMSUNG lithium-ion battery (INR 18650-29E) and charging is performed with a constant current. When set, a plurality of internal short-circuit resistance values estimated at a plurality of estimation points are disclosed. It can be seen that the resistance values estimated at multiple time points converge to a value similar to the actual value at the end of the estimation, and the calculated final failure index is 47.4032Ω, confirming that a fairly reliable value is derived.

In addition, the method devised in the present invention can operate in a variety of charging ranges, and not only internal short circuits in severe failure stages (failure of internal short circuit resistance of 5.5 Ω or less based on the battery) but also weak failure stages (5.5 Ω or more based on the battery standards). Internal short circuits (failures of internal short circuit resistors) can also be accurately detected. In other words, it is possible to diagnose the battery internal short circuit failure at a safer time (weak failure stage) and inform the user of the exact time to replace the battery. can also provide Further, the present invention is expected to improve battery management technology in the future in terms of safety and efficiency of battery use.

8 is a flowchart of a failure index extraction algorithm of the method for early detection of an internal short circuit failure according to the present invention.

Referring to FIG. 8 , a flowchart of an entire algorithm for extracting a failure index for early detection of an internal short circuit in a standard battery state of charge of the method for early detection of an internal short circuit failure of the present invention is shown.

The method for early detection of an internal short circuit failure of the present invention includes steps S1100 to S1400.

In step S1100, the failure index extraction unit 100 starts a failure index extraction system for detecting an internal short.

In step S1200, the internal short-circuit resistance estimation start time determination unit 200 determines variously the internal short-circuit resistance estimation time point.

In step S1300, the internal short-circuit resistance estimating unit 300 directly estimates the internal short-circuit resistance using the current and voltage signals obtained from standard charging of the battery.

In step S1400, the failure index representative value selection unit 400 obtains one representative failure index value from a plurality of internal short circuit resistances obtained from various time points.

9 is a flowchart of an internal short circuit resistance estimation algorithm of the internal short circuit failure early detection method according to the present invention.

Referring to FIG. 9 , the method for early detection of an internal short circuit failure according to the present invention includes steps S2100 to S2500.

In step S2100, the standard battery charging unit 301 charges the battery and measures the charging constant current and the battery terminal voltage together.

In step S2200, the open circuit voltage (OPEN CIRCUIT VOLTAGE, OCV)-STATE OF CHARGE (SOC) curve of the battery required for the characteristic curve extraction unit 302 to estimate the open circuit voltage and the state of charge of the battery from the constant current. extract

In step S2300, the real-time battery state estimating unit 303 obtains the signal measured by the battery standard charging unit 301 and the characteristic curve extracting unit 302 OPEN CIRCUIT VOLTAGE, OCV-STATE OF CHARGE, SOC) curves are used to estimate the open circuit voltage (OPEN CIRCUIT VOLTAGE, OCV) and the state of charge (STATE OF CHARGE, SOC) from the battery model equation.

In step S2400, the internal short-circuit resistance extracting unit 304 calculates the internal short-circuit resistance using the estimated state of charge (SOC) of the battery.

In step S2500, the model update unit 305 updates the battery model using the estimated internal short-circuit resistance.

According to an embodiment of the present invention, the use of the method for estimating the internal short-circuit resistance in the prior art is limited to a battery operating environment (electric vehicle discharge situation, etc.) in which a battery load current that satisfies a specific condition is used,

In the method and apparatus for early detection of an internal short circuit failure of the present invention, an internal short circuit can be detected early in a general battery standard charging environment (constant current charging) in order to overcome a specific internal short circuit detectable environment.

In addition, it is possible to improve the estimation accuracy of the internal short-circuit resistance used as the failure index.

In addition, it is possible to propose an algorithm for early detection of a short circuit inside a battery in real time by using the current and voltage measured in a standard battery charging situation.

The algorithm of the method and apparatus for early detection of an internal short circuit failure of the present invention may include a method of estimating an open circuit voltage (OPEN CIRCUIT VOLTAGE, OCV) and a state of charge (STATE OF CHARGE, SOC) of a battery in a constant current environment.

A method for estimating the internal short circuit resistance at multiple points and extracting the final failure index to improve the estimation accuracy of the failure index may also be included.

In addition, by diagnosing an internal short circuit occurring in the battery at an early stage using the current and voltage signals obtained in the standard charging state of the battery, it is possible to overcome the limitation in that the diagnosis is possible only in a specific discharge condition of the prior art.

In addition, it is possible to detect internal short circuits in various charging ranges rather than full charge, and the estimation accuracy of internal short circuit resistance used as a failure index is greatly improved, which is a battery failure state far away from the period leading to thermal runaway in the severe failure phase. battery usage safety can be improved, and the accuracy of the battery model can be improved due to the internal short-circuit resistance estimated in the weak failure stage, thereby diagnosing the current battery condition more accurately, which can greatly contribute to improving the use efficiency.

The operation of the method according to the embodiment of the present invention can be implemented as a computer-readable program or code on a computer-readable recording medium. The computer-readable recording medium includes all kinds of recording devices in which information readable by a computer system is stored. In addition, the computer-readable recording medium may be distributed in a network-connected computer system to store and execute computer-readable programs or codes in a distributed manner.

In addition, the computer-readable recording medium may include a hardware device specially configured to store and execute program instructions, such as ROM, RAM, and flash memory. The program instructions may include not only machine language codes such as those generated by a compiler, but also high-level language codes that can be executed by a computer using an interpreter or the like.

Although some aspects of the invention have been described in the context of an apparatus, it may also represent a description according to a corresponding method, wherein a block or apparatus corresponds to a method step or feature of a method step. Similarly, aspects described in the context of a method may also represent a corresponding block or item or a corresponding device feature. Some or all of the method steps may be performed by (or using) a hardware device such as, for example, a microprocessor, a programmable computer, or an electronic circuit. In some embodiments, one or more of the most important method steps may be performed by such an apparatus.

In embodiments, a programmable logic device (eg, a field programmable gate array) may be used to perform some or all of the functions of the methods described herein. In embodiments, the field programmable gate array may operate in conjunction with a microprocessor to perform one of the methods described herein. In general, the methods are preferably performed by some hardware device.

Although the above has been described with reference to the preferred embodiment of the present invention, those skilled in the art can variously modify and change the present invention within the scope without departing from the spirit and scope of the present invention described in the claims below. You will understand that you can.

10: heat chamber
11: internal short circuit resistance
15 : cell
20: battery test device
30: Data loggers and computers
40: ISCr trigger switching part
100: failure index extraction unit
200: internal short-circuit resistance estimation start time determining unit
300: internal short circuit resistance estimation unit
301: battery standard charging part
302: characteristic curve extraction unit
303: Real-time battery state estimation unit
304: internal short circuit resistance extraction part
305: model update unit
400: failure index representative value selection unit

Claims (10)

A device for early detection of an internal short circuit failure, comprising:
processor;
a memory in which at least one instruction executed by the processor is stored; including,
At least one command is
In the process of charging a lithium-ion battery with a constant current, the current and voltage signals are measured, and the open circuit voltage (OCV) and charging of the battery are measured using the measured signals and the battery equivalent circuit model (ECM). a command for estimating a state of charge (SOC); containing,
Internal short circuit failure early detection device. The method of claim 1, wherein the device comprises:
Internal short circuit resistance (R _ISCr ) (11) and a cell (Cell) (15) is a built-in thermal chamber (Thermal chamber) (10);
a battery test device 20 connected to the thermal chamber 10 to perform a battery cell experiment;
a data logger & computer 30 connected to the thermal chamber 10 to record experimental data including a charging current and a terminal voltage signal;
a Switch to trigger ISCr (40) that triggers an internal short circuit (ISCr) fault with a switch when a standard charge current is applied to a cell with multiple initial states of charge (STATE OF CHARGE, SOC); containing,
Internal short circuit failure early detection device. The method according to claim 1, wherein the device,
Including the failure index extraction unit 100 using the failure index containing information on the degree of failure as well as the presence or absence of an internal short circuit failure,
Internal short circuit failure early detection device. The method according to claim 3, The failure index extraction unit 100,
an internal short-circuit resistance estimation start time determination unit 200 for variously determining a time point for estimating the internal short-circuit resistance;
an internal short-circuit resistance estimating unit 300 for directly estimating internal short-circuit resistance using current and voltage signals obtained from standard battery charging;
a failure index representative value selection unit 400 that obtains one failure index representative value from a plurality of internal short circuit resistances obtained from various time points; containing,
Internal short circuit failure early detection device. 5. The method according to claim 4,
The internal short-circuit resistance estimation unit 300,
a standard charging unit 301 for charging the battery and measuring the charging constant current and the battery terminal voltage together;
a characteristic curve extraction unit 302 for extracting an OPEN CIRCUIT VOLTAGE (OCV)-STATE OF CHARGE (SOC) curve of the battery required to estimate the open circuit voltage and the state of charge of the battery from the constant current;
The open circuit voltage (OPEN CIRCUIT VOLTAGE, OCV)-STATE OF CHARGE (SOC) curve obtained from the signal measured by the battery standard charging unit 301 and the characteristic curve extraction unit 302 is used to calculate the open circuit from the battery model equation. a real-time battery state estimator 303 for estimating a voltage (OPEN CIRCUIT VOLTAGE, OCV) and a state of charge (STATE OF CHARGE, SOC);
an internal short-circuit resistance extraction unit 304 for calculating an internal short-circuit resistance using the estimated state of charge (SOC) of the battery; and
a model update unit 305 for updating the battery model using the estimated internal short-circuit resistance; containing,
Internal short circuit failure early detection device. The failure index extraction unit 100 starts the failure index extraction system for detecting an internal short circuit (S1100);
determining, by the internal short-circuit resistance estimation start time determination unit 200, various timing points for estimating the internal short-circuit resistance (S1200);
The internal short-circuit resistance estimating unit 300 directly estimating the internal short-circuit resistance using the current and voltage signals obtained from standard charging of the battery (S1300); and
The step of the failure index representative value selection unit 400 obtaining one representative failure index value from a plurality of internal short circuit resistances obtained from various time points (S1400); containing,
An early detection method for internal short circuit failure. 7. The method of claim 6,
The standard battery charging unit 301 charges the battery and measures the charging constant current and the battery terminal voltage together (S2100);
Step of extracting the open circuit voltage (OPEN CIRCUIT VOLTAGE, OCV)-STATE OF CHARGE (SOC) curve of the battery required for the characteristic curve extraction unit 302 to estimate the open circuit voltage and the state of charge of the battery from the constant current (S2200);
The real-time battery state estimating unit 303 obtains the signal measured by the battery standard charging unit 301 and the characteristic curve extracting unit 302 OPEN CIRCUIT VOLTAGE, OCV-STATE OF CHARGE, SOC curve estimating the open circuit voltage (OPEN CIRCUIT VOLTAGE, OCV) and the state of charge (STATE OF CHARGE, SOC) from the battery model equation by using (S2300);
calculating, by the internal short circuit resistance extraction unit 304, the internal short circuit resistance using the estimated state of charge (STATE OF CHARGE, SOC) of the battery (S2400); and
updating, by the model updater 305, the battery model using the estimated internal short-circuit resistance (S2500); further comprising,
An early detection method for internal short circuit failure. The method of claim 6, wherein the method comprises:
The battery model in which the internal short circuit occurred is defined by Equation 1,
An early detection method for internal short circuit failure.
(Equation 1)

here,

is the internal resistance of the battery,

is the self-discharge current caused by an internal short circuit The method of claim 6, wherein the method comprises:
The internal short-circuit resistance extraction unit 304 uses the state of charge (STATE OF CHARGE, SOC) 160 estimated in real time by the real-time battery state estimation unit 303 and the current and voltage values measured from Equation 2 to the internal short-circuit resistance (

) to calculate 170 ,
An early detection method for internal short circuit failure.
(Equation 2)

here,

is the rated capacity of the battery,

is the sampling period when measuring the signal in the battery standard charging unit 301 10. A computer-readable recording medium for implementing the program of the method for early detection of an internal short-circuit failure according to any one of claims 6 to 9.

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