KR102210716B1 - Energy storage system for storing electric energy using charge-discharge characteristics of battery - Google Patents

Abstract

Disclosed is an energy storage system (ESS) for storing electric energy using charge/discharge characteristics of a battery. The ESS comprises: a power conversion system (PCS) to charge/discharge electric energy in the battery; a power management system (PMS) to monitor and control state information including voltages, currents, temperatures, and internal resistances of the battery and the PCS; and a battery management system (BMS) to estimate a state of charge (SOC) and a state of health (SOH) of the battery from the state information of the battery, and to manage the battery based on the estimated SOC and SOH. The BMS includes a cell balancing unit to equalize an amount of charge of configured cells; and a battery protecting unit to predict a remaining life of the battery based on the estimated SOC and SOH, and for preventing overcharge and over discharge of the battery according to the predicted remaining life to protect the battery. The present invention may exclude temperature and time components and predict the life of the battery to stably store the battery.

Description

ESS system for storing electric energy using charge-discharge characteristics of battery

The present invention relates to battery management, and in particular, to an energy storage system for storing electric energy in a battery that can be charged and discharged using the charge/discharge characteristics of the battery.

Lithium-ion batteries have the best performance among secondary batteries currently commercially available. Compared to other secondary batteries, since it is relatively light in weight and has high energy density, it is widely used in various fields ranging from portable products to large energy storage systems. In particular, with the spread of electric vehicles, lithium-sulfur, lithium-air, sodium-magnesium in order to solve the storage capacity problem of the battery for improving the mileage and the stability problem, which is a fatal disadvantage. (Sodium-Magnesium) and solid-state batteries, such as next-generation batteries are being developed. However, these next-generation batteries have many problems to be solved until commercialization. Therefore, the lithium-ion battery market is expected to continue expanding for the time being. In particular, with the growth of the mobile phone and personal mobility (electric kickboard, electric bicycle, etc.) market, 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, and the electrolyte is decomposed by an oxidation-reduction reaction, which forms a SEI (Solid Electrolyte Interface) layer, resulting in an effect of increasing internal resistance, thereby reducing the usable battery capacity. Will decrease. The SEI layer acts as a protective film to prevent the electrolyte from decomposing continuously, but on the other hand, it is a direct cause of a decrease in reversible capacity when viewed from an entropy perspective.

If charging/discharging is 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, fire accidents due to overheating and ignition frequently occur while charging electric kickboards and electric bicycles in each home while charging without considering the life condition.

When the capacity of a lithium-ion battery falls below 80% of the initial capacity, it is considered to have reached the end of its life. 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.

Republic of Korea Patent Publication No. 10-2010-0019660 (2010.02.19.) "A system for predicting a life of a secondary battery and a device for predicting a life using the same", the step of primary charging in the operating voltage category of the secondary battery, the specification of the secondary battery Cut-off at the charging point of capacity, when the cut-off voltage is reached, secondary charging to a current of a specific capacity, measuring the time from the secondary charging to reaching the current, Predicting the life of the battery through data mapping between the measurement time and a preset reference time, and displaying the predicted life span. A predictable device is disclosed. According to this prior art, since the user can check the life of the secondary battery, it is possible to eliminate the inconvenience that the user cannot use the portable electric device as the secondary battery is discharged at an unexpected time. In particular, although the secondary battery needs to be replaced. And it can solve the problem of unnecessary charging because the user does not know this before charging in the charger.

However, most of the devices of the prior art have a disadvantage in that they cannot cope with a use environment that can change from time to time by using a parameter including a time function. In addition, the parameter and model estimation device based on the temperature (T) acts as a factor that causes an error in the state analysis of the battery due to the error according to the boundary condition, the temperature measurement error, and the slow dynamic characteristic of temperature change.

Accordingly, there is an urgent need for a technology capable of storing energy in a battery by excluding such an element of uncertainty and accurately predicting the remaining life of the battery.

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

It is an object of the present invention to provide an energy storage system for predicting battery life from an entropy perspective based on a voltage/SOC relationship rather than a temporal factor, and storing electrical energy in a battery based on the predicted lifespan.

를 사용하여 유도하고, 여기에서 Q₀는 배터리 최대 용량, α는 아레니우스 상수(Arrhenius rate constant)이고, E_C 및 E_D는 각각 충전시 및 방전시의 셀전압이다. 또한, 상기 잔여 수명 예측부는, 상기 배터리의 잔여 수명을 수학식

를 사용하여 예측하고, 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 잔여 수명 예측부는, 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 구한다. 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.The present invention for achieving the above objects relates to an energy storage system for storing electric energy in a battery using the charge/discharge characteristics of the battery. The energy storage system according to the present invention includes: a power conversion system (PCS) for charging and discharging electrical energy in the battery; A power management system (PMS) for monitoring and controlling status information including voltage, current, temperature, and internal resistance of the battery and the power conversion unit; And a battery management unit that estimates a state of charge (SOC) and a state of health (SOH) of the battery from the state information of the battery, and manages the battery based on the estimated state of charge and health. (battery management system; BMS), wherein the battery management unit includes: a cell balancing unit for equalizing charge amounts of constituting cells; And a battery protection unit that predicts the remaining life 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 estimated remaining life, The battery protection unit charges and discharges the battery with varying charging and discharging currents, while measuring a voltage, a state of charge (SOC), and a depth of discharge (DOD) of the battery. State measurement unit; An irreversible energy amount inducing unit for inducing an irreversible amount of energy Q _ir generated in a process of charging and discharging the battery from the voltage and the state of charge (SOC) using the law of enthalpy and entropy; And a remaining life prediction unit that predicts the remaining life of the battery from the induced irreversible energy Q _ir . In particular, the irreversible energy amount inducing unit, the irreversible energy amount ( Q _ir ) by the equation

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

To predict and, where Q _{ir _m} use is 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 is the number of the prediction and the respective actual number of cycles Cycles, Q _{ir_k} the k th This is the irreversible amount of energy in the current cycle. In particular, the remaining life prediction unit obtains Q _{ir_m} and Q _{ir_k} from an area occupied by a charge/discharge curve for each cycle in a graph representing a relationship between a voltage and a state of charge (SOC) for the battery, and the charge/discharge curve for each cycle The area is obtained by dividing the charge/discharge curve into at least two or more sections and summing the divided areas for each section. Further, dividing the cycle-by-cycle charge/discharge curve includes, in the charge/discharge curve, a charge start point (P _CS , P ^* _CS ), a charge inflection point (P _CK , P ^* _CK ), and a discharge start point in two consecutive cycles. (P _DS , P ^* _DS ), and extracting the discharge inflection points (P _DK , P ^* _DK ), and the charge/discharge curves 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 charging starting point (P _CS ) and the discharging starting point (P _DS ) are extracted by the change in the direction of the current, and the charging inflection point (P _CK ) and the discharging inflection point (P _DK ) are the voltage for the state of charge (SOC). It is extracted based on the amount of change.

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

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 of predicting battery life based on entropy-enthalpy, and FIG. 1D is a block diagram schematically illustrating a battery life prediction system executing the method of predicting battery life of FIG. 1C.
2 is a diagram showing a simplified configuration of a battery test system.
3A is a graph of discharge characteristics when discharged at 1C for batteries in different states, and FIG. 3B is a graph showing charging characteristics when charged at 0.5C.
FIG. 4A is a voltage curve for SOC with varying charging current (discharge current is fixed at 1C), and FIG. 4B is a voltage curve for SOC with varying discharge current (charging current is fixed at 0.5C).
FIG. 5A shows a change in Q value when only the charge/discharge current is different, and FIG. 5B shows a change in Q value when the charge/discharge current and DOD are different.
6 shows the irreversible energy in various situations.
7A and 7B show charging and discharging operations for less current.
8 illustrates the concept of a checkout device (PDM).
9 shows four cases of PDM according to the state of charge and discharge.
10 illustrates a concept of applying a section dividing device.
11 schematically shows a pseudocode of an algorithm for predicting battery life.
12 shows a comparison of a voltage change over time and a voltage change over SOC when the discharge current changes in real time.
13 is a comparison curve between the predicted life and the actual life.

In order to fully understand the present invention, the operational advantages of the present invention, and the objects achieved by the implementation 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 a preferred embodiment of the present invention with reference to the accompanying drawings. However, the present invention may be implemented in various different forms, and is not limited to the described embodiments. In addition, in order to clearly describe 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, and measures the state of charge (SOC) of the battery, the state of health (SOH), and the state of the battery. life; SOL).

-Cell balancing: It performs a function of adjusting the charge/discharge degree between cells to be the same so that the voltage between 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: It performs functions such as battery diagnosis and data status transmission. That is, it performs a function of transmitting and managing the actual state of the battery in connection with the PMS and EMS described later.

In order 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 includes a state of charge (SOC) and a state of health of the battery from the received state information; SOH) is estimated. In addition, the cell balancing unit equalizes the amount of charge of the cells constituting the battery based on the estimated state of charge and the state of health to prevent overcharged or overdischarged cells from occurring.

In addition, the battery protection unit predicts the remaining life of the battery based on the estimated state of charge and the state of health, and protects the battery by preventing overcharging and overdischarging of the battery according to the estimated remaining life.

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 to manage the battery. A technology for predicting the life of the battery using the charge/discharge characteristics of the battery will be described in detail later in the relevant part of this specification.

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

-PMS (Power Management System): It monitors and controls the state of the battery and PCS to be described later. In addition, PMS is in charge of controlling power in connection with EMS.

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

-EMS (Energy Management System): It is a system that manages the total energy of ESS, and plays a role as a control tower for PMS. In other words, 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, and internal resistance, estimates SOC and SOH based on this, protects the battery and protects the cell. It plays a role in balancing.

The energy storage system shown in FIG. 1B also employs a battery life prediction function using charge/discharge characteristics of a battery. Therefore, the energy storage system shown in FIG. 1B can accurately predict the remaining life of the battery to manage the battery, thereby efficiently storing energy, and uniformly managing the battery life. It is possible to prevent unexpected accidents such as fire in advance. A technology for predicting the life of the battery using the charge/discharge characteristics of the battery will be described in detail later in the relevant part of this specification.

1C is a flowchart schematically showing a battery life prediction method S100 based on entropy-enthalpy, and FIG. 1D is a block diagram schematically showing 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 brief description will be given of a battery life prediction method reflecting the time parameter.

The characteristic equation for the charge/discharge voltage of a battery is based on the Shepherd model, and can be expressed as the following as parameters related to current items, 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, which many researchers have suggested 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 the following equations depending on temperature and SOH, it is very unreasonable to analyze the characteristics of the battery 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 bringing about a large number of errors according to changes in the use pattern of the battery or the load environment, and thus can be an unrealistic analysis device. In addition, estimating internal resistance, polarization resistance, capacity, etc. that reflect thermal factors that have been analyzed in many studies actually includes many error factors, so there is a limit to the actual device used.

To prevent this problem, a method of analyzing the state by measuring the current '0', that is, OCV, but it takes some time to stabilize to measure OCV, so it is applied to the real-time prediction method. It is difficult to do.

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

Considering the realistic environment, the parameters that can be measured are voltage, current, and temperature. Temperature must be an important parameter here. In large-capacity applications such as ESS, a cooling facility is provided for the stable operation of the battery, and a system is operated to control the surface temperatures of the battery according to the temperature. However, most small-capacity systems do not have a cooling facility, keep an appropriate I-rate, and limit the temperature to use only as a protective device.

Considering the heat transfer characteristics inside and outside of the temperature and the slow dynamics of the temperature sensor measurement and response, reflecting it in real-time calculations 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 exclude the time factor as in Equations 1 to 6 and predict the remaining life of the battery using the concept of entropy and enthalpy.

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

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

Here one should pay attention to the irreversible Joule. This is because, in the case of a function or internal resistance related to temperature, as mentioned above, there is a high probability of errors due to measurement or estimation errors or slow dynamics. Therefore, it is desirable to apply an 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 calories can be expressed as follows by integrating Equation 10 (S120).

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

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

Reorganizing Equation 15 from Equation 11, it can be seen that as shown in Equation 16, the total amount of voltage change for the SOC can be derived in an equation that can obtain the irreversible energy. This operation may be performed by the irreversible energy amount 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 can be estimated. Accordingly, the battery life can be determined by calculating irreversible energy according to the charge/discharge.

In general, by using Equation 17, the life of the battery may be determined to have reached the end of the life when the sum of irreversible energy due to charging and discharging becomes 80% or less of the initial battery capacity.

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

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

And, by _obtaining and summing the area of each section (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 in detail later in the corresponding part of the specification.

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

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

To find out the characteristics of the aging state of the battery, a new battery and a battery that has been charged and discharged 100, 200, 300, 400, 500 times with a rated charging current (0.5C) and a discharge current (1C), respectively. Charge and discharge characteristics were tested for five types.

3A is a graph of discharge characteristics when discharged at 1C for batteries in different states, and FIG. 3B is a graph showing charging characteristics when charged at 0.5C. As expected, it can be seen that the faster the charging and discharging speeds change, the more battery charging and discharging cycles have been performed. It can be seen that since charging and discharging were performed according to the exact rules determined for the battery characteristics, the characteristics according to each aging state showed a very linear change.

FIG. 4A is a voltage curve for SOC with varying charging current (discharge current is fixed at 1C), and FIG. 4B is a voltage curve for SOC with varying discharge current (charging current is fixed at 0.5C).

That is, FIG. 4A is a graph of the voltage against SOC when the discharge current is fixed at 1C, which is the rated current, and the DOD is charged and discharged at 100% while changing the charging current from 0.1C to 1C. It can be seen that the area of the curve that appears while charging and discharging changes according to the magnitude of the current. In the case of 1C, where the current is the largest, the area is wide, and as the charging current decreases, the area decreases. 4B shows a graph of the voltage against SOC while changing the discharge current with 100% DOD while the charging current is fixed at 0.5C. In the case of 1C with the largest discharge current, it can be seen that a 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 technology becomes clear through FIGS. 4A and 4B. It can be seen that the area covered by the voltage curve for 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, it is possible to estimate the lifetime by calculating the irreversible energy.

FIG. 5A shows a change in Q value when only the charge/discharge current is different, and FIG. 5B shows a change in Q value when the charge/discharge current and DOD are different. In particular, FIG. 5A shows the charge/discharge characteristic curves at 100% DOD for 0.5C Charging (0.5CC), 1C Discharging (1CD), 0.1C Charging (0.1CC), and 0.1C Discharging (0.1CD). When the area of the curved surface surrounded by the solid black line in FIG. 5A is defined as Q _{ir_m} , and the rated charging current and rated discharge current in one cycle are operated at DOD 100%, the maximum irreversible heat capacity is. The area indicated by the red solid line is the size of the irreversible heat capacity at 100% DOD for 0.1C Charging (0.1CC) and 0.1C Discharging (0.1CD), defined as Q _{ir_k} , and attenuated in a 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} denotes a usable remaining capacity. This allows us to calculate the remaining capacity and remaining cycles through the proportional relationship.

6 shows the 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 area is the maximum value Qir_m of the irreversible energy during one cycle. 5 shows the shape of the irreversible heat capacity that varies in various ways. If the charging rate of the current exceeds the rated range, the irreversible heat capacity will exceed the 1-cycle reference value, resulting in a shortened life.

7A and 7B are graphs showing the charging/discharging operation for a smaller current, that is, by changing the magnitude of the charge-discharge current and the DOD compared to the reference. 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 discharge current and 1C charging current (new battery, 500th battery). . That is, FIG. 7 shows a comparison of characteristic curves when 6 batteries with different lifetimes are charged and discharged at 0.5CC, 1CD, and DOD = 100%, and when divided by area, the area of the curved surface of the new battery This 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 life. In the case of the exhausted battery, it was confirmed that a voltage drop occurs when the battery is discharged until the SOC reaches 0% during discharge. At this time, it is expected that a battery problem will occur due to an instantaneous transient phenomenon.

-Point detection method (PDM)

In general, we use an integrator to find the area of the curve. However, the integrator has a drawback that it must be processed by applying a method for removing accumulated errors. Therefore, in the present invention, a method of obtaining the area of a square by detecting four inflection points is applied without using an integrator. In this method, the disadvantages of using the integrator can be eliminated, and the irreversible heat capacity can be obtained in a more convenient and effective method.

8 illustrates the concept of an inspection method (PDM).

The change in point is conclusively divided into cases 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 defined as a charging start point, P _CK is a charging knee point, P _DS is a discharging start point, and P _DK is a discharge knee point. The change of these points has a total of 4 cases, and schematically, as shown in FIG. 9.

9 shows four cases of PDM according to the state of charge and discharge. Specifically, (a) when the DOD widens; (b) when DOD becomes narrower; (c) when the DOD range is lowered; And (d) shows a case where the DOD range is increased.

9 can be represented as DOD. In the case of (a), the range of the DOD is wider than before, and in the case of (b), the range of the DOD is narrowed. In case (c), the DOD range is shifted, that is, the discharge depth becomes deeper and the filling depth becomes shallower. Here, if the depth of charge is also deep, this is the case in (a). That is, contrary to (d), the discharge depth becomes thinner and the filling depth increases. Similarly, if the filling depth is also lowered, this is the case in (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. The green dots P ^* (P ^* _CS , P ^* _CK , P ^* _DS , P ^* _DK ) denoted by superscripts (*) are newly updated points, and this is the P(n) of the discrete signal processing component.

-Section Separation Method (SSM)

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

The area can be obtained using the above PDM, but looking at the shape of the curve, 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 total area of SOC (0-100%), this method is an impractical method. Can be Therefore, a method (SSM) of dividing into three zones as shown in FIG. 10(b) is proposed. Table 2 shows the area of the actual curve and the error rate of the area calculated by PDM. If SSM is not applied, it can be seen that the error rate increases significantly in the section with a large DOD.

- algorithm

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

First, in order to determine Q _{ir_m} , information provided by the manufacturer is used or a sample charge/discharge cycle is executed to store Q _{ir_m} information. After that, voltage, current, and temperature information is obtained 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 or discharged state. When looking at the current information, if the current direction is hard, this is the information of the starting point of charging or discharging, so it is stored as P _CS and P _DS . Then, SOC information is checked during each of charging and discharging. 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 P _CK or P _DK . It should be noted that these variations are exemplary and do not limit the present invention.

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

-Life cycle prediction result

12 shows a comparison of a voltage change over time and a voltage change over SOC when the discharge current changes in real time. 12A shows that the voltage state changes when the magnitude of the discharge current changes to 0.5C, 0.25C, and 1C during the time interval. However, in Fig. 12(b), although the discharge current changes at every time interval, the voltage change graph for SOC shows a constant cycle curve regardless of the time change. From this, it can be seen that it is very efficient to predict the lifetime using the voltage/SOC curve regardless of the change in the user's charge/discharge pattern.

Table 3 shows the results of comparing and analyzing the predicted lifespan and the actual remaining capacity by applying the method proposed by the present invention while changing the size and DOD of the battery charging/discharging current.

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

- conclusion

13 is a comparison curve between the predicted life and the actual life.

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

In light of these results, it can be seen that, above all, DOD and C-rate are important for longevity. As can be seen from the analysis result of the curve for calculating the irreversible heat capacity in the present specification, it can be seen that the area of the Q value is clearly different depending on the DOD and the C-rate.

As a result, the larger the DOD, the larger the C-rate and the larger the Q value, which means a 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 results. If the temperature is outside the suitable operating range, the calculated irreversible energy increases, which means that the lifespan is shortened. Similarly, as the battery ages, the calculated irreversible energy increases. 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, an apparatus for predicting the life of a widely used lithium ion battery is proposed according to the law of entropy, and the result is verified. Such a device has the advantage that it is physical, but intuitive and can be implemented relatively easily. As described above, there are many errors in the life estimation and analysis method involving a function of temperature and time. In fact, in the process of acquiring and processing battery status in real time, it is more effective to estimate the lifetime from information about voltage and current, which is more responsive 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 without using a component that changes over time, the influence on the time component that changes 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%.

The present invention has been described with reference to the embodiments shown in the drawings, but these are merely exemplary, and those of ordinary skill in the art will appreciate that various modifications and other equivalent embodiments are possible therefrom.

Further, the apparatus according to the present invention can be implemented as a computer-readable code on a computer-readable recording medium. The computer-readable recording medium may include any type of recording device storing data that can be read by a computer system. Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tapes, floppy disks, optical data storage devices, etc., and also implemented in the form of carrier waves (for example, transmission over 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 distributed computer system connected through a network.

In terms of the terms used in the present specification, expressions in the singular should be understood as including plural expressions unless clearly interpreted differently in context, and terms such as "includes" are specified features, numbers, steps, actions, and components. It is to be understood that the presence or addition of one or more other features or numbers, step-acting components, parts or combinations thereof is not meant to imply the presence of, 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 software.

Accordingly, the present embodiment and the accompanying drawings are merely illustrative of some of the technical ideas included in the present invention, and those skilled in the art within the scope of the technical ideas included in the specification and drawings of the present invention can be easily It will be apparent that all of the modified examples and specific embodiments that can be inferred are included in the scope of the present invention.

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

Claims (7)

As an energy storage system for storing electrical energy in a battery by using the charge/discharge characteristics of the battery,
A power conversion system (PCS) for charging and discharging electrical energy in the battery;
A power management system (PMS) for monitoring and controlling status information including voltage, current, temperature, and internal resistance of the battery and the power conversion unit; And
And a battery management system (BMS) that measures a state of charge (SOC) of the battery from the state information of the battery and manages the battery based on the state of charge,
The battery management unit,
A cell balancing unit that equalizes the charge amount of the constituting cells; And
And a battery protection unit that predicts the remaining life of the battery based on the state of charge and protects the battery by preventing overcharging and overdischarging of the battery according to the predicted remaining life,
The battery protection unit,
A battery state measurement unit that measures a voltage, a state of charge (SOC), and a depth of discharge (DOD) of the battery while charging and discharging the battery with varying charging and discharging currents;
An irreversible energy amount inducing unit for inducing an irreversible amount of energy Q _ir generated in a process of charging and discharging the battery from the voltage and the state of charge (SOC) using the law of enthalpy and entropy; And
And a remaining life predicting unit that predicts the remaining life of the battery from the induced irreversible energy amount Q _ir ,
The irreversible energy amount inducing unit,
Equation of the irreversible energy amount ( Q _ir )

Is derived using
Where Q ₀ is the maximum capacity of the battery, α is the Arrhenius rate constant, E _C and E _D are the cell voltages during charging and discharging, respectively,
The remaining life prediction unit,
Equation of the remaining life of the battery

Is used to predict,
Where Q _{ir_m} is the maximum value for each cycle of the irreversible energy amount, m is the maximum cycle period, N _a and N _p are the actual and predicted cycles, respectively, and Q _{ir_k} is the current irreversible energy amount of the kth cycle ESS system using the charging and discharging characteristics of the battery, characterized in that. delete delete The method of claim 1,
The remaining life prediction unit,
ESS system using charge/discharge characteristics of a battery, characterized in that Q _{ir_m} and Q _{ir_k} are obtained from an area occupied by a cycle-by-cycle charge/discharge curve in a graph showing a relationship between a voltage and a state of charge (SOC) for the battery. 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. The ESS system using charge/discharge characteristics of a battery. The method of claim 5,
Dividing the charge/discharge curve for each cycle,
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 (P _DS , P ^* _DS ), and a discharge inflection point (P) in two consecutive cycles Extracting _DK , P ^* _DK ), and
The charge/discharge curve:
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
An ESS system using charge/discharge characteristics of a battery, comprising dividing into a third section formed by P _DS , P ^* _DS , P _DK , and P ^* _DK . The method of claim 6,
The charging start point (P _CS ) and the discharge start point (P _DS ) are extracted by the change in the direction of current,
The charging inflection point (P _CK ) and the discharge inflection point (P _DK ) are extracted based on a change in voltage with respect to a state of charge (SOC).

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