KR20210155922A - ESS system having Energy storage method for storing electric energy using charge-discharge characteristics of battery - Google Patents

Abstract

Disclosed is an energy storage method for storing electrical energy in a battery by using charging/discharging characteristics of the battery. The method includes: measuring state information including a voltage, a current, a temperature, and an internal resistance of a battery; estimating a state-of-charge (SoC) and a state-of-health (SoH) of the battery from the measured state information, and equalizing charge amounts of cells constituting the battery based on the estimated SoC and the estimated SoH; and predicting a remaining lifespan of the battery based on the estimated SoC and the estimated SoH, and protecting the battery by preventing overcharging and overdischarging of the battery according to the predicted remaining lifespan. According to the present invention, a lifespan of a battery is predicted while excluding temperature and time components so that energy is stably stored.

Description

ESS system having Energy storage method for storing electric energy using charge-discharge characteristics of battery

The present invention relates to battery management, and more particularly, to a method of storing electrical energy in a chargeable/dischargeable battery using the charge/discharge characteristics of the battery in an ESS.

Lithium-ion batteries have the best performance among secondary batteries currently commercially available. Since they are relatively light in weight and have high energy density compared to other secondary batteries, they are widely used in various fields from portable products to large-scale energy storage systems. In particular, as electric vehicles are becoming more popular, lithium-sulfur, lithium-air, sodium-magnesium are used to solve the problem of battery storage capacity to improve mileage and stability, which is a fatal disadvantage. Next-generation batteries such as (Sodium-Magnesium) and solid-state batteries are being developed. However, these next-generation batteries still have many problems to be solved until they are commercialized. Therefore, the lithium-ion battery market is expected to expand continuously for the time being. In particular, with the growth of the mobile phone and personal mobility (electric kickboard, electric bicycle, etc.) markets, the efficient energy use and stability issues of lithium-ion batteries are becoming more prominent.

In general, lithium-ion batteries are initially stable for a while. However, as the frequency of use increases, the lifespan decreases, the electrolyte is decomposed by an oxidation-reduction reaction, and this forms the SEI (Solid Electrolyte Interface) layer, which has the effect of increasing the internal resistance, reducing the usable battery capacity. will decrease The SEI layer acts as a protective film that prevents the electrolyte from being continuously decomposed, but on the other hand, from an entropy point of view, it is a direct cause of a decrease in the reversible capacity.

If charging and discharging are repeated while the lifespan is shortened, problems such as overcharging, overdischarging, and overcurrent may occur depending on the situation. In particular, due to the growth of the personal mobility market, while charging electric kickboards and electric bicycles in each home without considering the lifespan, fire accidents due to overheating and ignition are also frequently occurring.

Lithium-ion batteries are considered to have reached the end of their lifespan when their capacity drops below 80% of their initial capacity. Predicting the lifespan of such a battery is very important for efficient resource utilization and stable management and use of energy storage devices.

Many studies are being conducted for life expectancy prediction.

Korean Patent Publication No. 10-2010-0019660 (2010.02.19.) "A device for predicting the lifespan of a secondary battery and a method for predicting a life using the same" includes the steps of primary charging in the operating voltage range of the secondary battery, the specific of the secondary battery The step of cut-off at the charging point of the capacity, when the cut-off voltage is reached, secondary charging up to a current of a specific capacity, measuring the time from the secondary charging until the current is reached; Predicting the lifespan of a battery through data mapping between the measurement time and a preset reference time, and a method of predicting the lifespan of a secondary battery through a constant voltage section during battery charging, comprising displaying the predicted lifespan, and the method A predictable device is disclosed. According to this prior art, the user can check the lifespan of the secondary battery, and as the secondary battery is discharged at an unexpected time, the inconvenience that the user cannot use the portable electric device can be eliminated, and in particular, despite the need for replacement of the secondary battery And it can solve the problem of unnecessary charging because the user is not aware of this before charging in the charger.

However, most of the methods of the prior art have a disadvantage in that they cannot cope with a use environment that may change frequently by using a parameter including a time function. In addition, the parameter and model estimation method based on the temperature (T) act as a factor that causes errors in the state analysis of the battery due to the error according to the boundary condition, the temperature measurement error, and the slow dynamic characteristics of the temperature change.

Therefore, there is an urgent need for a technology capable of storing energy in a battery by accurately predicting the remaining lifespan of the battery by excluding a factor in which such uncertainty exists.

Korean Patent Publication No. 10-2010-0019660 (2010.02.19.) "A device for predicting the lifespan of a secondary battery and a method for predicting the lifespan using the same"

It is an object of the present invention to predict a battery life in terms of entropy based on a voltage/SOC relationship rather than a time factor in configuring a battery management system, and to provide an energy storage method for storing electrical energy in a battery based on the predicted lifespan will do

를 사용하여 유도하는 것을 포함하고, 여기에서 Q₀는 배터리 최대 용량, α는 아레니우스 상수(Arrhenius rate constant)이고, E_C 및 E_D는 각각 충전시 및 방전시의 셀전압이다. 또한, 상기 배터리의 잔여 수명을 예측하는 단계는, 상기 배터리의 잔여 수명을 수학식

를 사용하여 예측하는 것을 포함하고, 여기에서 Q _{ir_m} 은 비가역적 에너지량의 사이클별 최대값, m은 최대 사이클 기간, N _a 및 N _p 는 각각 실제 사이클 횟수와 예측된 사이클 횟수이고, Q _{ir_k} 는 k번째 사이클 현재의 비가역적 에너지량이다. 특히, 상기 배터리의 잔여 수명을 예측하는 단계는, Q _{ir_m} 및 Q _{ir_k} 를, 상기 배터리에 대한 전압과 충전 상태(SOC)의 관계를 나타내는 그래프에서 사이클별 충방전 곡선이 차지하는 면적으로부터 구하고, 상기 사이클별 충방전 곡선의 면적은, 상기 충방전 곡선을 적어도 두 개 이상의 섹션으로 분할하고, 분할된 섹션별 면적을 합산하여 구해진다. 더 나아가, 상기 사이클별 충방전 곡선을 분할하는 것은, 상기 충방전 곡선에서, 연속하는 두 사이클에서의 충전 시작점(P_CS, P^* _CS), 충전 변곡점(P_CK, P^* _CK), 방전 시작점(P_DS, P^* _DS), 및 방전 변곡점(P_DK, P^* _DK)을 추출하는 것, 및 상기 충방전 곡선을: P_CS, P^* _CS, P_CK, 및 P^* _CK에 의해 형성되는 제 1 섹션; P^* _CS, P^* _CK, P^* _DS, 및 P^* _DK에 의해 형성되는 제 2 섹션; 및 P_DS, P^* _DS, P_DK, 및 P^* _DK에 의해 형성되는 제 3 섹션으로 분할하는 것을 포함한다. 또한, 상기 충전 시작점(P_CS) 및 방전 시작점(P_DS)은 전류의 방향 변동에 의해 추출되고, 상기 충전 변곡점(P_CK) 및 방전 변곡점(P_DK)은 충전 상태(SOC)에 대한 전압의 변화량에 기반하여 추출된다.One aspect of the present invention for achieving the above objects relates to an energy storage method for storing electrical energy in a battery using the charge/discharge characteristics of the battery. The energy storage method according to the present invention comprises the steps of measuring state information including voltage, current, temperature, and internal resistance of the battery; Estimate a state of charge (SOC) and a state of health (SOH) of the battery from the measured state information, and calculate the amount of charge of cells constituting the battery based on the estimated state of charge and health equalizing; and estimating the remaining lifespan of the battery based on the estimated estimated state of charge and health, and protecting the battery by preventing overcharging and overdischarging of the battery according to the predicted remaining lifespan. In particular, the step of protecting the battery includes charging and discharging the battery with a varying charging current and discharging current, while charging and discharging the battery with a voltage, a state of charge (SOC), and a depth of discharge (DOD) of the battery. ) to measure; deriving an irreversible amount of energy (Q _ir ) generated in the process of charging and discharging the battery from the voltage and the state of charge (SOC) using enthalpy and entropy laws; and predicting the remaining life of the battery from the induced irreversible amount of energy Q _{ir .} In particular, the steps of the irreversible amount of energy (Q _ir) of the ratio leads to irreversible energy amount (Q _ir) equation

, where Q ₀ is the maximum battery capacity, α is an Arrhenius rate constant, and E _C and E _D are cell voltages during charging and discharging, respectively. In addition, the step of predicting the remaining life of the battery,

In, and this involves the prediction using Q _{ir_m} is irreversible amount of energy of maximum value per cycle, m is the maximum cycle time period, N _a and N _p are each a number of actual cycles a number of times and the predicted cycle, Q _{ir_k} is It is the irreversible amount of energy present in the kth cycle. In particular, the predicting of the remaining life of the battery includes _obtaining Q ir_m and Q _{ir_k} from the area occupied by the charge/discharge curve for each cycle in a graph representing the relationship between the voltage and the state of charge (SOC) for the battery, and the cycle The area of each charge/discharge curve is obtained by dividing the charge/discharge curve into at least two or more sections and summing the divided areas for each section. Furthermore, dividing the charge/discharge curve for each cycle is, in the charge/discharge curve, a charge start point (P _CS , P ^* _CS ), a charge inflection point (P _CK , P ^* _CK ), a discharge start point in two consecutive cycles (P _DS , P ^* _DS ), and extracting the discharge inflection point (P _DK , P ^* _DK ), and the charge-discharge curve formed by: P _CS , P ^* _CS , P _CK , and P ^* _CK first section; a second section formed by P ^* _CS , P ^* _CK , P ^* _DS , and P ^* _{DK ;} and dividing into a third section formed by _{P DS} , P ^* _DS , P _DK , and P ^* _{DK .} In addition, the charge start point (P _CS ) and the discharge start point (P _DS ) are extracted by the change in the direction of the current, and the charge inflection point (P _CK ) and the discharge inflection point ( _PDK ) are the voltages for the state of charge (SOC). It is extracted based on the amount of change.

According to the present invention, the voltage/SOC relationship is identified in terms of entropy in order to remove the temporal factor, and the effect of temperature is summarized as the V/SOC result, thereby excluding temperature and time components and predicting the battery life. and energy can be stably stored in the battery based on the predicted lifespan.

1A is a block diagram schematically illustrating a battery management system (BMS), and FIG. 1B is a block diagram schematically illustrating an energy storage system (ESS).
FIG. 1C is a flowchart schematically illustrating a method for predicting battery life based on entropy-enthalpy, and FIG. 1D is a block diagram schematically illustrating a system for predicting battery life for executing the method for predicting battery life in FIG. 1C.
2 is a diagram showing a simplified configuration of a battery test system.
3A is a graph of the discharge characteristics when discharging at 1C for batteries of different states, and FIG. 3B shows the charging characteristics when charging at 0.5C.
Fig. 4A is a voltage curve for SOC in which the charging current is changed (discharge current is fixed at 1C), and Fig. 4B is a voltage curve for SOC in which the discharge current is changed (charge current is fixed at 0.5C).
FIG. 5A shows the change in Q value when only the charge/discharge current is different, and FIG. 5B shows the change in the Q value when the charge/discharge current and DOD are different.
6 shows irreversible energy in various situations.
7A and 7B show the charging/discharging operation for a smaller current.
8 illustrates the concept of a check-out method (PDM).
9 shows four cases of PDM according to charging and discharging states.
10 illustrates the concept of applying the section division method.
11 schematically shows pseudocode of an algorithm for predicting battery life.
12 shows a comparison of a voltage change according to time and a voltage change according to SOC when the discharge current is changed in real time.
13 is a comparison curve between the predicted lifetime and the actual lifetime.

In order to fully understand the present invention, the operational advantages of the present invention, and the objects achieved by the practice of the present invention, reference should be made to the accompanying drawings illustrating preferred embodiments of the present invention and the contents described in the accompanying drawings.

Hereinafter, the present invention will be described in detail by describing preferred embodiments of the present invention with reference to the accompanying drawings. However, the present invention may be embodied in various different forms, and is not limited to the described embodiments. In addition, in order to clearly explain the present invention, parts irrelevant to the description are omitted, and the same reference numerals in the drawings indicate the same members.

1A is a block diagram schematically illustrating a battery management system (BMS), and FIG. 1B is a block diagram schematically illustrating an energy storage system (ESS).

The battery management system (BMS) shown in FIG. 1A manages the battery by performing the following functions.

- Battery status monitoring function: Measures voltage, current, temperature, and internal resistance, the state of charge (SOC), the state of health (SOH), and the remaining battery life life; SOL) is monitored.

- Cell balancing: It performs a function of adjusting the charging and discharging degree between cells to be the same so that the voltage between the cells of the battery modules connected in series can be balanced.

- Battery protection: It performs a protection function to prevent overvoltage, overdischarge, and overcurrent, and is a very important function for battery life.

- Other functions: Performs functions such as battery diagnosis and data status transmission. That is, in conjunction with PMS and EMS, which will be described later, a function of transmitting and managing the actual battery state is performed.

To perform these operations, the battery management system illustrated in FIG. 1A may include a cell balancing unit and a battery protection unit.

The cell balancing unit receives state information from a sensor that measures voltage, current, temperature, and internal resistance of the battery, and the state of charge (SOC) and state of health (State of Health) of the battery from the received state information; SOH) is estimated. In addition, the cell balancing unit prevents overcharged or overdischarged cells from occurring by equalizing the charge amounts of cells constituting the battery based on the estimated state of charge and health.

In addition, the battery protector predicts the remaining lifespan of the battery based on the estimated estimated state of charge and health, and protects the battery by preventing overcharging and overdischarging of the battery according to the predicted remaining lifespan.

Such a battery management system is combined with a battery life prediction function using the charge/discharge characteristics of the battery to accurately predict the remaining life of the battery and manage the battery. A technique for predicting the lifespan of a battery by using the charging/discharging characteristics of the battery will be described in detail later in the corresponding part of the present specification.

FIG. 1B is a block diagram schematically illustrating an energy storage system (ESS) employing the battery management system of FIG. 1A . A brief introduction to each function of ESS is as follows.

- PMS (Power Management System): It plays a role of monitoring and controlling the status of the battery and PCS to be described later. In addition, the PMS is responsible for controlling power in conjunction with the EMS.

- PCS (Power Conversion System): Charges the battery with electrical energy and discharges the electrical energy from the battery.

- EMS (Energy Management System): It is a system that manages the total energy of the ESS and plays a role as a control tower for the PMS. In other words, the EMS manages the supply and demand of the power system and operates the energy system.

- BMS (Battery Management System): BMS as shown in FIG. 1a measures battery state information such as voltage, current, temperature, internal resistance, and estimates SOC and SOH based on this, protects the battery and protects the cell It plays a role in balancing.

A battery life prediction function using the charge/discharge characteristics of the battery is also employed in the energy storage system illustrated in FIG. 1B . Accordingly, the energy storage system shown in FIG. 1B accurately predicts the remaining life of the battery and manages the battery, so that energy can be efficiently stored and the battery life can be uniformly managed. It is possible to prevent unexpected accidents such as fires in advance. A technique for predicting the lifespan of a battery using the charge/discharge characteristics of the battery will be described in detail later in the corresponding part of the present specification.

FIG. 1C is a flowchart schematically illustrating a battery life prediction method S100 based on entropy-enthalpy, and FIG. 1D is a block diagram schematically illustrating a battery life prediction system 100 executing the battery life prediction method of FIG. 1C.

To establish optimal operating conditions for battery performance, such as battery life and safety, it is important to quantify heat generation and temperature changes based on the C-rate of charge/discharge. For convenience of understanding, a method of predicting battery life in which time parameters are reflected will be briefly described.

Based on the Shepherd model, the characteristic equation for the charge/discharge voltage of the battery can be expressed as follows with parameters related to the current item, temperature (T), and SOH.

는 온도와 SOH에 따라 다음 수학식들과 같이 나타낼 수 있는 함수이므로, 수학식 1과 2에 의해서만 배터리의 특성을 해석하는 것은 큰 무리가 있다.The above equation is a voltage characteristic equation for battery analysis, and many researchers have presented it as a basic model. However, even if the current is interpreted as a constant current operated by CC (Constant Current) mode,

Since is a function that can be expressed as in the following equations according to temperature and SOH, it is difficult to interpret battery characteristics only by equations 1 and 2.

In addition, since the above equations are calculated as a function of time, there is a high probability of causing many errors according to changes in the battery usage pattern or load environment, and thus may be an unrealistic analysis method. In addition, estimating internal resistance, polarization resistance, capacity, etc. reflecting thermal factors analyzed in many studies contains many error factors in reality, so there is a limit to the practical use method.

In order to prevent this problem, a method of analyzing the state by measuring the current '0' state, that is, OCV, is also proposed. difficult to do

First, the voltage, SOC, DOD, etc. of the battery are measured while charging and discharging the battery (S110). Such an operation may be performed by the battery state measuring unit 110 .

Considering the realistic usage environment, the actual measurable parameters are voltage, current, and temperature. Here, temperature must be an important parameter. In large-capacity applications such as ESS, a cooling facility is provided for stable battery operation, and a system is operated to control battery surface temperatures according to temperature. However, most small capacity systems do not have cooling facilities, maintain an appropriate I-rate, and limit the temperature and use only as a protection device.

Considering the internal and external heat transfer characteristics of temperature and the slow dynamic characteristics of temperature sensor measurement and response, reflecting in real-time calculation has a high probability of making an error in interpreting the state of the battery.

- Mathematical modeling for life prediction

Therefore, it is advantageous to predict the remaining lifespan of the battery by using the concept of entropy and enthalpy, excluding time elements such as Equations 1 to 6.

The concepts of enthalpy (ΔH) and entropy (ΔS) will be described in terms of Gibb's free energy (ΔG) as shown in Equation (7). Here, n is the number of electrons included in the reaction. In the case of lithium ions, n=1, and F is the Faraday constant. Here, x represents the concentration of lithium ions, and since this value is proportional to SOC, it can be expressed as in Equation 8.

Based on the above formula, it can be defined as irreversible Joule heat, reversible Joule heat, and heat due to terminal resistance as in Equation 9 based on the entropy law.

Here, attention should be paid to irreversible Joule fever. This is because, in the case of temperature-related functions or internal resistance, as mentioned above, there is a high probability of errors due to measurement or estimation errors and slow dynamic characteristics. Therefore, it is desirable to apply the irreversible amount of energy in terms of voltage and current that can be estimated in real time.

Here, E _C represents the cell voltage during charging, and E _D represents the cell voltage during discharge. The total amount of irreversible heat can be expressed as follows by integrating Equation (10) (S120).

In Equation 13, when V _b is multiplied by both sides and expressed as an integral expression, Equation 14 is obtained.

Here, when V _b is defined as αE _C -E _D , and the equation is rearranged, it is defined as in Equation 15.

By rearranging Equation 15 from Equation 11, it can be seen that the total amount of voltage change with respect to SOC can be induced in a way that can obtain irreversible energy as Equation 16 shows. Such an operation may be performed by the irreversible amount of energy inducing unit 150 .

During each charge-discharge cycle, compared to the product of the battery it is irreversible energy add (Q _{ir_k)} and irreversible energy maximum amount (Q _{ir_m)} and the maximum cycle duration (maximum cycle period), which may be generated during one cycle, this can be calculated by

Using Equation 17, the state of life (SOL) of the battery may be estimated. Accordingly, the battery life may be determined by calculating irreversible energy according to the corresponding charging and discharging.

In general, using Equation 17, it can be determined that the life of the battery has expired when the sum of irreversible energies due to charging and discharging is less than 80% of the initial battery capacity.

Since the charge/discharge cycle provided by the battery manufacturer means the number of times the DOD is 100%, the actual usable charge/discharge cycle can be calculated as follows. Such an operation may be performed by the remaining life prediction unit 190 .

In addition, after the irreversible amount of energy (Q _ir ) generated in the process of charging and discharging the battery is induced, in the charging/discharging curve, the charging start point (P _CS , P ^* _CS ) and the charging inflection point (P) in two successive cycles _CK , P ^* _CK ), discharge start point ( _PDS , P ^* _DS ), and discharge inflection point (P _DK , P ^* _DK ) are extracted (S130), and the charge/discharge curve is divided into three sections using the extracted points Divide (S140).

Then, by calculating the area of each section and summing (S150) Q _{ir_m} and Q _{ir_k} is calculated (S160). And, the calculated Q _{ir_m} and The remaining life of the battery is predicted from Q _{ir_k ( S170 ).} These processes are described below in detail in the corresponding parts of the specification.

- Configuration of test system

2 is a diagram showing a simplified configuration of a battery test system.

In order to verify the proposed method, the battery charge/discharge test system was configured as shown in Figure 1. Using a battery-only charger with constant current (CC) and constant voltage (CV) functions, it is possible to turn on/off according to the charging/discharging sequence in the main controller, but it is a more simplified configuration considering the transient state and loss of the switch. An experimental system is constructed. The CV operation was implemented using a power supply with a current limit function, and the switch was removed and configured to control the charge/discharge sequence using serial communication. The temperature T was configured to operate only in the role of protecting against abnormal conditions.

Table 1 lists the specifications of the batteries used in the tests. It should be noted that the specifications in Table 1 are merely exemplary and do not limit the present invention.

In order to find out the characteristics of the aging state of the battery, 100, 200, 300, 400, and 500 charging and discharging of a new battery, DOD 100, and rated charging current (0.5C) and discharging current (1C) were performed respectively. Charge-discharge characteristics were tested for 5 types.

3A is a graph of the discharge characteristics when discharging at 1C for batteries of different states, and FIG. 3B shows the charging characteristics when charging at 0.5C. As expected, it can be seen that the rate of charging and discharging changes rapidly as the battery undergoes many charge/discharge cycles. It can be seen that the characteristics according to each aging state show a very linear change because the charging and discharging were carried out according to the exact rules set for the battery characteristics.

Fig. 4A is a voltage curve for SOC in which the charging current is changed (discharge current is fixed at 1C), and Fig. 4B is a voltage curve for SOC in which the discharge current is changed (charge current is fixed at 0.5C).

That is, FIG. 4A is a graph of voltage versus SOC when the DOD is charged and discharged at 100% while the discharge current is fixed at 1C, which is the rated current, and the charging current is changed from 0.1C to 1C. It can be seen that the area of the curve that appears during charging and discharging changes according to the magnitude of the current. In the case of 1C having the largest current, the area is wide, and it can be seen that the area decreases as the charging current decreases. Figure 4b shows a graph of the voltage versus SOC while changing the discharge current to 100% DOD in a state where the charging current is fixed at 0.5C. In the case of 1C with the largest discharge current, you can see that the graph is drawn at the bottom of the lower part. It can be seen that as the current decreases, the area covered by the graph decreases. It can be seen that the basis for the above-described method becomes clear through FIGS. 4A and 4B. It can be seen that the area covered by the voltage curve for the SOC changes according to the magnitude of the current, and it can be seen that the area increases as the current increases. This amount can be converted into irreversible energy, and thus, life expectancy can be estimated by the method of calculating irreversible energy.

FIG. 5A shows the change in Q value when only the charging/discharging current is different, and FIG. 5B shows the change in the Q value when the charging/discharging current and the DOD are different. In particular, FIG. 5A shows a charging/discharging characteristic curve at 100% DOD for 0.5C Charging (0.5CC), 1C Discharging (1CD) and 0.1C Charging (0.1CC), 0.1C Discharging (0.1CD). The area of the curved surface surrounded by the black solid line in FIG. 5A _{is defined as Q ir_m} , and the rated charging current and rated discharge current are the maximum size of irreversible heat capacity when operated at DOD100% in one cycle. The area indicated by the red solid line is the magnitude of the irreversible heat capacity when the DOD is 100% for 0.1C Charging (0.1CC) and 0.1C Discharging (0.1CD), _{and is defined as Q ir_k} , and the battery has been attenuated in one specific cycle. means capacity. 5B shows the consumed capacity when the DOD is operated at 70%. In FIGS. 5A and 5B , Q _{ir_m} -Q _{ir_k} means a usable remaining capacity. Through this, we can calculate the remaining capacity and the remaining cycles through the proportional relationship.

6 shows irreversible energy in various situations.

6 is a graph of the result of changing the magnitude of the charge/discharge current and the DOD, and the black solid line region is the maximum value of irreversible energy Qir_m during one cycle. 5 shows variously changing shapes of irreversible heat capacity. If the charging rate of the current exceeds the rated range, the irreversible heat capacity exceeds the 1-cycle reference value, and consequently the life is shortened.

7A and 7B are graphs showing the charging/discharging operation for a smaller current, that is, compared to the reference, the result graph showing the size of the charging-discharging current and the DOD being changed. In this case, the irreversible energy is reduced and the remaining life is increased.

Specifically, FIG. 7A shows a case of 0.5C charging current and 1C discharge current (0 to 500 cycles), and FIG. 7B shows a case of 0.5C discharging current and 1C charging current (new battery, 500th battery). . That is, FIG. 7 shows a comparison of characteristic curves in the case of charging and discharging batteries having six different lifespans at 0.5CC, 1CD, and DOD=100%. When divided by area, the curved area of the new battery It is the smallest, and it can be seen that the area of the curve becomes wider as the lifespan is over. 7B shows characteristic curves of a new battery and a battery that has reached the end of its lifespan. In the case of an expired battery, it was confirmed that a voltage drop occurred when discharging until the SOC reached 0% during discharging. At this time, it is expected that the possibility of a battery problem is high due to a momentary transient.

- point detection method (PDM)

In general, a method using an integrator is used to find the area of a curve. However, the integrator has a disadvantage in that it has to be dealt with by applying a method for removing the accumulated error. Therefore, in the present invention, a method for calculating the area of a quadrangle by detecting four inflection points without using an integrator is applied. In the case of this method, the disadvantage of using an integrator can be eliminated, and the irreversible heat capacity can be obtained in a simpler and more effective way.

8 illustrates the concept of a check-out method (PDM).

The change of the point is consequently divided into a case where the discharged energy is less than the charged energy (FIG. 8A), and the case where the discharged energy is greater than the charged energy (FIG. 8B). Here, P _CS is a charging start point, P _CK is a charging knee point, P _DS is a discharging start point, and P _DK is a discharging knee point. This point change has a total of four cases, and it is shown schematically in FIG. 9 .

9 shows four cases of PDM according to charging and discharging states. Specifically, (a) is when DOD is widened; (b) when the DOD is narrowed; (c) when the DOD range is lowered; and (d) show a case where the DOD range is increased.

9 may be represented as a DOD. In case of (a), the range of DOD is wider than before, and in case of (b), the range of DOD is narrower. In the case of (c), the DOD range is shifted, that is, the depth of discharge becomes deeper and the depth of charge becomes shallower. Here, if the depth of charge is also deep, this is the case for (a). That is, contrary to (d), the discharge depth becomes thinner and the charge depth increases. Similarly, if the filling depth is also lowered, this is the case for (b). In general, almost all charge/discharge states of a battery are included in the above four cases. In FIG. 9 , P(P _CS , P _CK , P _DS , P _DK ) in blue indicates the current position and is equal to P(n-1) of the discrete signal processing component. ^{Green dots P *} (P ^* _CS , P ^* _CK , P ^* _DS , P ^* _DK ) denoted by superscripts (*) are the newly updated points, which is P(n) of the discrete signal processing component.

- Section Separation Method (SSM)

10 illustrates a concept of applying a section division method. Specifically, (a) shows the Q value by PDM when SSM is not applied, and (b) shows the Q value by PDM when SSM is applied.

Although the area can be calculated using the above PDM, when the DOD is large, the calculation error of the area becomes large as shown in FIG. 10( a ). Of course, considering that the actual battery usage period is mostly 20-80%, there is no big error because it is an almost constant area of the curve, but considering the entire area (0-100%) of the SOC, this method is an impractical method. work can be Therefore, a method (SSM) for dividing into three zones as shown in FIG. 10(b) is proposed. Table 2 shows the error rate between the area of the actual curve and the area calculated by PDM. When SSM is not applied, it can be seen that the error rate significantly increases in the section with a large DOD.

- algorithm

11 schematically shows pseudocode of an algorithm for predicting battery life.

First, _{in order to determine Q ir_m} , information provided by the manufacturer is used or Q _{ir_m} information is stored by executing a sample charge/discharge cycle. After that, voltage, current, and temperature information is acquired in real time, and this information is used to predict the lifetime. The temperature information is used as an emergency stop trigger for abnormal situations.

Using this information, it first checks whether it is in a charged state or a discharged state. If the current direction changes when looking at the current information, this is the information of the charging or discharging start point, so we store it as _{P CS} and P _{DS .} Then, during each of the charging and discharging, the SOC information is checked. If the SOC at the start of charging or discharging changes by more than 1%, the corresponding point is determined as an inflection point, and voltage information at the inflection point is stored in _PCK or _PDK. It should be noted that these variations are exemplary and not limiting of the present invention.

In this way, four points can be found, and the same operation is performed in three sections, which is used to calculate a value corresponding to the irreversible energy of one cycle, and the lifetime is estimated.

- Life cycle prediction results

12 shows a comparison of a voltage change according to time and a voltage change according to SOC when the discharge current is changed in real time. 12A shows that the voltage state changes when the discharge current magnitude is changed to 0.5C, 0.25C, and 1C during the time interval. However, in FIG. 12( b ) , although the discharge current changes for each time interval, the voltage change graph for SOC shows a constant cycle curve irrespective of the time change. From this, it can be seen that it is very effective to predict the lifespan using the voltage/SOC curve regardless of the change in the user's charging/discharging pattern.

Table 3 shows the results of comparative analysis of the predicted lifespan and the actual remaining capacity by applying the method proposed by the present invention while changing the size of the battery charge/discharge current and the DOD.

As a result, it can be seen that there is some difference in the estimation accuracy according to the DOD. The accuracy was rather low in the 0-100% range, and the smaller the DOD, the smaller the estimation error and the higher the accuracy. It can be seen that the estimated accuracy deviation in the 100% DOD section and the 50% DOD section differs by up to 2.7%, but with a deviation of about 1% depending on the magnitude of the charge/discharge current.

- conclusion

13 is a comparative curve between the predicted lifetime and the actual lifetime.

13 is a graphical representation of the data of Table 3; It can be seen that the remaining life is highly dependent on the charge/discharge C-rate and DOD. The predicted lifetime results were compared based on the actual remaining capacity, and the predicted lifetime was analyzed to obtain an average accuracy of 93% or more. In the high DOD section, the accuracy was somewhat poor, and the accuracy was 94% in the 20-80% section and 30-80% section, which is expected for the real-world section.

In light of these results, it can be seen that, above all, DOD and C-rate are important for lifespan. As can be seen from the analysis results of the curve for calculating the irreversible heat capacity herein, it can be seen that the area of the Q value clearly varies according to the DOD and the C-rate.

As a result, the higher the DOD, the higher the C-rate and the higher the Q value, which means shorter lifetime. Rather, under the same conditions (same DOD and C-rate), the irreversible zero capacity increases somewhat with the aging state of the battery, but the aging rate is relatively slower than the effect of DOD or C-rate.

As a result of the experiment, it can be seen that the temperature has little effect on the result. If the temperature is outside the suitable operating range, the calculated irreversible energy increases, which means that the lifetime is shortened. Similarly, the calculated irreversible energy increases as the battery ages. In the present invention, the average life expectancy is provided with an accuracy of 90% or more. In order to increase the accuracy, the Q _{ir_m} value should reflect the temperature and aging state.

According to the present invention, a method for predicting the lifespan of a widely used lithium ion battery is proposed according to the law of entropy and the result has been verified. Although this method is physical, it has the advantage of being intuitive and can be implemented relatively easily. As mentioned above, life estimation and analysis methods involving functions of temperature and time are error-prone. In fact, in the process of acquiring and processing the battery state in real time, it is more effective to estimate the lifespan from information about voltage and current, which is more reactive than temperature. The voltage reflects the internal state, temperature, and environmental factors of the battery, making analysis easier.

In addition, by using a voltage for SOC information rather than using a time-varying component, the influence on a time component varying according to a usage pattern is eliminated. And, as a result of the experiment according to the present invention, it was proved that the present invention is effective and accurate with an accuracy higher than 92%.

Although the present invention has been described with reference to the embodiment shown in the drawings, which is only exemplary, those skilled in the art will understand that various modifications and equivalent other embodiments are possible therefrom.

In addition, the method according to the present invention can be implemented as computer-readable codes on a computer-readable recording medium. The computer-readable recording medium may include any type of recording device in which data readable by a computer system is stored. Examples of the computer-readable recording medium include ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage device, etc., and may also be implemented in the form of a carrier wave (eg, transmission through the Internet) include In addition, the computer-readable recording medium may store computer-readable codes that can be executed in a distributed manner by a network-connected distributed computer system.

In terms of the terms used herein, the singular expression should be understood to include the plural expression unless the context clearly dictates otherwise, and terms such as "comprises" refer to the described feature, number, step, operation, element. , parts or combinations thereof are to be understood, but not to exclude the possibility of the presence or addition of one or more other features or numbers, step operation components, parts or combinations thereof. In addition, terms such as "...unit", "...group", "module", and "block" described in the specification mean a unit that processes at least one function or operation, which is hardware, software, or hardware. and a combination of software.

Accordingly, the present embodiment and the drawings attached to this specification only clearly show a part of the technical idea included in the present invention, and within the scope of the technical idea included in the specification and drawings of the present invention, those skilled in the art can easily It will be apparent that all inferred modified examples and specific embodiments are included in the scope of the present invention.

It can be applied to the battery management technology of the present invention.

Claims (7)

An energy storage method for storing electrical energy in a battery using the charge/discharge characteristics of the battery, comprising:
measuring state information including voltage, current, temperature, and internal resistance of the battery;
Estimate a state of charge (SOC) and a state of health (SOH) of the battery from the measured state information, and calculate the amount of charge of cells constituting the battery based on the estimated state of charge and health equalizing; and
Predicting the remaining life of the battery based on the estimated estimated state of charge and health, and protecting the battery by preventing overcharging and overdischarging of the battery according to the predicted remaining life,
The step of protecting the battery comprises:
measuring a voltage, a state of charge, and a depth of discharge (DOD) of the battery while charging and discharging the battery with varying charging and discharging currents;
deriving an irreversible amount of energy (Q _ir ) generated in the process of charging and discharging the battery from the voltage and the state of charge using the laws of enthalpy and entropy; and
An energy storage method using charge/discharge characteristics of a battery applied to an ESS system, comprising the step of predicting the remaining life of the battery from the induced irreversible amount of energy ( Q _{ir ).} According to claim 1,
Inducing the irreversible amount of energy ( Q _ir ) is,
The irreversible amount of energy ( Q _ir ) is expressed by the formula

Including derivation using
Here, Q ₀ is the maximum capacity of the battery, α is the Arrhenius rate constant, and E _C and E _D are the cell voltages during charging and discharging, respectively. A method of energy storage using discharge characteristics. 3. The method of claim 2,
Predicting the remaining life of the battery comprises:
Equation for the remaining life of the battery

Predicting using
Here Q _{ir_m} the ratio of maximum value per cycle of the irreversible amount of energy, m is the maximum cycle time period, N _a and N _p are each a real number and the expected number of cycles Cycles, Q _{ir_k} the amount of irreversible energy of the current k-th cycle, An energy storage method using the charge/discharge characteristics of a battery applied to an ESS system, characterized in that 4. The method of claim 3,
Predicting the remaining life of the battery comprises:
Q _{ir_m} and Q _{ir_k} are obtained from the area occupied by the charge/discharge curve for each cycle in the graph representing the relationship between the voltage and the state of charge (SOC) for the battery. energy storage method. 5. The method of claim 4,
The area of the charge/discharge curve for each cycle is obtained by dividing the charge/discharge curve into at least two or more sections, and summing the divided areas for each section. energy storage method. 6. The method of claim 5,
Splitting the charge/discharge curve for each cycle is,
In the charge/discharge curve, the charge start point (P _CS , P ^* _CS ), the charge inflection point (P _CK , P ^* _CK ), the discharge start point (P _DS , P ^* _DS ), and the discharge inflection point (P ) in two successive cycles _{extracting DK} , P ^* _DK ), and
The charge/discharge curve is:
a first section formed by P _CS , P ^* _CS , P _CK , and P ^* _{CK ;}
a second section formed by P ^* _CS , P ^* _CK , P ^* _DS , and P ^* _{DK ;} and
P _DS , P ^* _DS , P _DK , and an energy storage method using charge/discharge characteristics of a battery applied to an ESS system, comprising dividing into a third section formed by ^{P *} _{DK .} 7. The method of claim 6,
The charging starting point (P _CS ) and discharging starting point (P _DS ) are extracted by the change in the direction of the current,
The charge inflection point (P _CK ) and the discharge inflection point ( _PDK ) are extracted based on the amount of change in voltage with respect to the state of charge (SOC).

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