KR102422376B1 - System and method for extracting the ocv table of electric vehicle batteries - Google Patents

Abstract

The present invention relates to a system and method for extracting an OCV table of an electric vehicle battery, and more specifically, to a system and method for extracting an OCV table of an electric vehicle battery, the system including a terminal and a server. Since one embodiment of the present invention uses updated map data based on information brought from other external transportation means as well as map data in an existing battery management system (BMS), it is possible to accurately estimate state of health (SOH).

Description

SYSTEM AND METHOD FOR EXTRACTING THE OCV TABLE OF ELECTRIC VEHICLE BATTERIES

The present invention relates to an electric vehicle battery OCV table extraction system and method, and more particularly, to an electric vehicle battery OCV table extraction system and method including a terminal and a server for extracting an OCV table.

An electric vehicle uses electric energy stored in a battery as an energy source. A lithium-ion polymer battery is widely used as a battery for such an electric vehicle, and research on the battery is being actively conducted.

On the other hand, in the case of a gasoline vehicle, since the engine is driven using fuel, there is no difficulty in measuring the amount of fuel. However, for the driver of an electric vehicle, information on how much energy is left and how much more can be driven in the future is very important.

In other words, since an electric vehicle is a vehicle that runs by the energy charged in the battery, it is very important to know the remaining capacity charged in the battery. Several technologies are being developed to inform you.

In addition, many attempts have been made to properly set the initial value of the remaining capacity of the battery prior to driving the vehicle. At this time, the initial value of the residual capacity is usually set with reference to the open circuit voltage (OCV). In this way, the premise is that the OCV does not change with the environment and is an absolute reference value of the remaining capacity.

Accordingly, it is important to use and manage EV batteries more efficiently by extracting OCV and estimating the lifespan of EV batteries.

In this regard, Korean Patent Application No. 10-2018-0060972 discloses an apparatus and method for diagnosing a lifespan by a phase change measured by applying a signal having a preset frequency to each battery cell, but the technology is not related to the battery cell There is a hassle of having to apply a frequency signal set to .

Therefore, there is a need for a technique for solving the above-mentioned problems.

On the other hand, the above-mentioned background art is technical information possessed by the inventor for the derivation of the present invention or acquired in the process of derivation of the present invention, and cannot necessarily be said to be a known technique disclosed to the general public prior to the filing of the present invention.

An embodiment of the present invention aims to provide an electric vehicle battery OCV table extraction system and method.

에 기초하여 연산하는 셀 밸런싱 인덱스 연산부;를 더 포함하고, 상기

는 충전이 완료된 배터리 셀 중에서 가장 큰 SOC(배터리 충전 상태)값을 가지는 배터리 셀의 SOC값을, 상기

는 충전 시작 시 배터리 셀 중에서 가장 작은 SOC값을 가지는 배터리 셀의 SOC값, 상기

과 상기

[01] 는 각각 충전 완료 시, 시작 시 배터리 팩의 SOC인 전기자동차 배터리 OCV테이블 추출시스템을 포함할 수 있다.In order to solve the above object, an embodiment of the present invention relates to an electric vehicle battery OCV table extraction system using battery state information, comprising: a terminal for receiving the battery state information from OBD and filtering only necessary information; and a server for estimating a state of health (SOH) of the battery based on the filtered information, wherein the terminal determines whether the mobile means including the OBD is a battery charging state or a dynamic state wealth; and when the battery condition determination unit determines that the battery is in a charged state, the cell balancing index BI

Further comprising; a cell balancing index operator that calculates based on

is the SOC value of the battery cell having the largest SOC (state of charge) value among the charged battery cells,

is the SOC value of the battery cell having the smallest SOC value among the battery cells at the start of charging,

and above

[01] may include an electric vehicle battery OCV table extraction system that is the SOC of the battery pack at the start of each charging completion.

에 기초하여 셀 편차 인덱스

를 연산하는 셀 편차 인덱스 연산부를 포함하고, 상기

는 k번째 셀 전압을, 상기

는 전체 셀 평균 전압인 전기자동차 배터리 OCV테이블 추출시스템을 포함할 수 있다.In addition, the terminal,

Based on the cell deviation index

Including a cell deviation index operator to calculate,

is the k-th cell voltage,

may include an electric vehicle battery OCV table extraction system that is the total cell average voltage.

In addition, when the battery condition determination unit determines that the mobile means is in a dynamic driving condition, the terminal has a special cell determination unit that determines a battery cell whose voltage has been lowered by 1% or more based on the voltage of a normal battery cell as a special cell electric vehicle battery OCV It may include a table extraction system.

In addition, the server receives and stores the processed battery state information including the voltage, current, temperature, the balancing index and the cell deviation index from the terminal in a database, and uses the processed battery state information to an OCV table OCV table extraction system for an electric vehicle battery that additionally extracts and receives from another terminal and estimates SOH (State Of Health) included in battery information corresponding to the battery state information received from the terminal among the battery information pre-stored in the database may include

에 기초하여 연산하는 셀 밸런싱 인덱스를 연산하는 단계를 더 포함하고, 상기

는 충전이 완료된 배터리 셀 중에서 가장 큰 SOC(배터리 충전 상태)값을 가지는 배터리 셀의 SOC값을, 상기

는 충전 시작 시 배터리 셀 중에서 가장 작은 SOC값을 가지는 배터리 셀의 SOC값, 상기

과 상기

는 각각 충전 완료 시, 시작 시 배터리 팩의 SOC인 전기자동차 배터리 OCV테이블 추출방법을 포함할 수 있다.In order to solve the above object, an embodiment of the present invention provides a method for extracting an OCV table for an electric vehicle battery using battery state information, comprising: a first step of receiving and filtering the battery state information; and a second step of estimating a state of health (SOH) based on the filtered information, wherein the first step includes determining whether the moving means is a battery charging state or a dynamic driving state, and charging If the status is the cell balancing index BI

Further comprising the step of calculating a cell balancing index calculated based on the

is the SOC value of the battery cell having the largest SOC (state of charge) value among the charged battery cells,

is the SOC value of the battery cell having the smallest SOC value among the battery cells at the start of charging,

and above

may include a method of extracting an electric vehicle battery OCV table that is the SOC of the battery pack at the time of completion of charging, respectively.

에 기초하여 연산하는 단계를 포함하고, 상기

는 k번째 셀 전압을, 상기

는 전체 셀 평균 전압인 전기자동차 배터리 OCV테이블 추출방법을 포함할 수 있다.In addition, in the first step, the cell deviation index I(t)

Comprising the step of calculating based on the

is the k-th cell voltage,

may include an electric vehicle battery OCV table extraction method that is the average voltage of all cells.

In addition, the first step includes a specific cell discrimination step of discriminating a battery cell in which the voltage of the normal battery cell has decreased by 1% or more as a specific cell as a specific cell when the dynamic driving situation occurs. An OCV table extraction method may be included.

In addition, the second step receives and stores battery state information including the voltage, current, temperature, the cell balancing index and the cell deviation index, and additionally extracts an OCV table using the processed battery state information, It may include a method of extracting an electric vehicle battery OCV table for estimating a state of health (SOH) included in battery information corresponding to the battery state information among previously stored battery information.

According to an embodiment of the present invention, since accurate battery life estimation is possible, users can easily determine the battery replacement cycle.

In addition, since an embodiment of the present invention uses updated map data based on information brought from other external means of transportation as well as map data in the existing BMS (Battery Management System), it is possible to accurately estimate SOH (State Of Health). do.

In addition, according to an embodiment of the present invention, state of health (SOH) updates are possible for various situations as well as special situations such as rapid charging.

In addition, according to an embodiment of the present invention, when implementing an algorithm for modeling time-varying characteristics by indexing information on cell voltage deviation by applying a cell deviation index, it is possible with relatively little data when estimating a state of health (SOH).

In addition, since an embodiment of the present invention uses a cell deviation index value, it is possible to diagnose battery deterioration due to a cell voltage deviation.

In addition, the OCV (Open Circuit Voltage) table according to the SOC extracted in an embodiment of the present invention is key information used for estimating various parameters (SOH, SOP, etc.) of the battery, in particular, the lifespan of the battery using the OCV table. The State of Health (SOH) is easier to understand.

The effects obtainable in the present invention are not limited to the above-mentioned effects, and other effects not mentioned will be clearly understood by those of ordinary skill in the art from the following description. .

1 is a diagram specifically illustrating the configuration of an electric vehicle battery OCV table extraction system according to an embodiment of the present invention.
2 is a diagram specifically illustrating the configuration of a terminal according to an embodiment of the present invention.
3 is a diagram specifically illustrating the configuration of a server, which is an embodiment of the present invention.
4 is a diagram illustrating a method for extracting an OCV table for an electric vehicle battery according to an embodiment of the present invention.
5 is a diagram illustrating a step of extracting an OCV (Open Circuit Voltage) table in an electric vehicle battery OCV table extraction method according to an embodiment of the present invention.
6 is a diagram illustrating a step of estimating a state of health (SOH) in an OCV table extraction method for an electric vehicle battery according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those of ordinary skill in the art can easily carry out the present invention. However, the present invention may be embodied in various different forms and is not limited to the embodiments described herein. And in order to clearly explain the present invention in the drawings, parts irrelevant to the description are omitted, and similar reference numerals are attached to similar parts throughout the specification.

Throughout the specification, when a part is "connected" with another part, it includes not only the case of being "directly connected" but also the case of being "electrically connected" with another element in the middle. In addition, when a part "includes" a certain component, this means that other components may be further included, rather than excluding other components, unless otherwise stated.

In the present invention, the means of transportation is a device for transporting people and/or cargo, and examples thereof include land vehicles, water vehicles, railroad vehicles and air vehicles, particularly aircraft, ships and automobiles. As an example, we will focus on electric vehicles.

In the present invention, the state of charge (SOC) is information indicating the state of charge of the battery, and is a measure of how much time the user can use the battery in the future, and in general, the remaining charge for the full charge capacity. It can be expressed as a percentage of the capacity (Remain Capacity). In this case, the full charge capacity represents the maximum amount of charge that the battery can actually accommodate, and is distinguished from the design capacity of a fixed value in that it gradually decreases as the number of times of charging and discharging of the battery increases. The residual capacity may be an amount of electric charge remaining in the battery at a specific point in time after the battery is manufactured.

In the present invention, the state of health (SOH) refers to the aging and performance index of the battery expressed by comparing the ideal state of the battery with the current state of the battery. Like SOC (State Of Charge), the unit uses percentage (%), and in general, the ideal initial battery SOH (State Of Health) is 100%, but as the period or frequency of use increases, the SOH (State Of Health) decreases. do. SOH (State Of Health) measures SOH (State Of Health) for the initial battery state in BMS (Battery Management System) and stores the value The current battery's state of health (SOH) is determined by comparing it with the health) value.

Also, in the present invention, a battery cell refers to a configuration capable of storing energy in a chemical form and transmitting it to a consuming device in the form of electricity, that is, a minimum unit capable of repeatedly charging and discharging. For example, the battery cell may be a pouch-type lithium ion battery. In addition, a voltage applied to both ends of each battery cell is referred to as a battery cell voltage, and a current applied to both ends of each battery cell is referred to as a battery cell current.

In addition, in the present invention, the vehicle state information includes voltage, current, temperature, state of charge (SOC) value, cell balancing index, cell deviation index, and state of health (SOH) value of battery cells and packs.

In addition, the battery state information includes voltage, current, temperature, and state of charge (SOC) values of battery cells and packs.

In addition, the processed battery state information includes voltage, current, temperature, cell balancing index, and cell deviation index of battery cells and packs, and the battery life information includes a state of health (SOH) value.

In this case, the moving means includes an Electronic Control Unit (ECU) and a Battery Management System (BMS).

The ECU (Electronic Control Unit) of the transportation means can call the presence and extent of movement and speed changes of these components from sensors connected to the wheels, handles, and gears of the transportation means.

The BMS (Battery Management System) of the mobile means is connected to the battery pack of the mobile means and the sensors of each cell, so that the voltage, current, temperature, voltage, current and temperature of each cell can be called.

Battery cell balancing refers to a mechanism in which the BMS (Battery Management System) of a vehicle detects and automatically performs a battery cell that has a voltage difference of 1% or more from other cells among the battery cells. There is a method of lowering the voltage by connecting high cells to a resistor and flowing a current (passive cell balancing) or flowing a current from a cell with a high voltage to a cell with a low voltage (active cell balancing).

At this time,

로 정의된다.In this case, the cell balancing index indicates the degree of cell balancing as an index. cell balancing index

is defined as

는 충전이 완료된 배터리 셀 중에서 가장 큰 SOC(배터리 충전 상태)값을 가지는 배터리 셀의 SOC값을,

는 충전 시작 시 배터리 셀 중에서 가장 작은 SOC값을 가지는 배터리 셀의 SOC값,

과

는 각각 충전 완료시, 시작 시 배터리 팩의 SOC을 말한다.At this time,

is the SOC value of the battery cell having the largest SOC (state of charge) value among the battery cells that have been charged,

is the SOC value of the battery cell having the smallest SOC value among the battery cells at the start of charging,

class

is the SOC of the battery pack when charging is completed and when starting, respectively.

가 94%이고,

가 92%이고,

가 97%이고,

가 42%라고 가정하자.for example,

is 94%,

is 92%,

is 97%,

Assume that is 42%.

At this time, the cell balancing index value is 3.63%. If so, it is assumed that 3.63% of cell balancing has been performed with respect to the battery capacity in this battery cell.

로 정의된다. 이때,

는 k번째 셀 전압을,

는 전체 셀 평균 전압을 뜻한다.The cell deviation index is

is defined as At this time,

is the k-th cell voltage,

is the average voltage of all cells.

For example, 8 modules are mounted in one battery pack, and each module consists of 12 cells, so a total of 96 cells can be configured.

는 3.52v일 때, 셀 편차 인덱스 수식에 의해 0.1179이다. When calculating the cell deviation index from the 1st battery cell to the 5th battery cell among these 96 battery cells, the voltages of the 1st to 5th cells are 3.28v, 3.31v, 3.48v, 3.63v, and 3.57v, respectively. do

When is 3.52v, it is 0.1179 by the cell deviation index formula.

In the present invention, hysteresis, that is, hysteresis may mean hysteresis.

It does not mean the limited hysteresis of the magnetic flux density-magnetic field strength graph, and hysteresis is not determined only by the physical conditions at that time in any physical state or physical quantity, but it refers to the phenomenon.

Hereinafter, an electric vehicle battery OCV table extraction system will be described based on FIGS. 1 to 3 .

1 is a diagram specifically illustrating the configuration of an electric vehicle battery OCV table extraction system according to an embodiment of the present invention, FIG. 2 is a diagram specifically illustrating the configuration of a terminal according to an embodiment of the present invention, and FIG. 3 is this It is a diagram specifically illustrating the configuration of a server, which is an embodiment of the invention.

An electric vehicle battery OCV table extraction system according to an embodiment of the present invention is a system for extracting an OCV table according to SOC using battery information of a moving means and estimating the state of health (SOH) of a battery.

The electric vehicle battery OCV table extraction system according to an embodiment of the present invention may include an OBD 100 , a terminal 200 , a server 300 , and a user terminal 400 .

The OBD 100 is a device in which a communication protocol or communication protocol for transmitting information such as an ECU (Electronic Control Unit) to other devices or components is embedded, and may include OBD-1 and OBD-2, OBD-1 and OBD. -2 is just one example, and any configuration or protocol that transmits ECU information to a configuration or device other than the ECU may correspond to the OBD 100 .

The battery status information and control signals of the ECU (Electronic Control Unit) and the BMS (Battery Management System) of the mobile means are transmitted through the OBD (100) protocol using CAN (controller area network) communication, etc. Battery status information and control signals of the mobile means may be transmitted to the terminal 200 .

Hereinafter, the configuration of the terminal 200 will be described in detail based on FIG. 2 . 2 is a schematic diagram of an embodiment of the invention, in which the terminal 200 includes a terminal transceiver unit 210, a battery condition determination unit 220, a unique cell determination unit 230, a balancing determination unit 240, a balancing index operation unit 250 and a cell deviation index calculator 260 .

The terminal 200 may filter only necessary information based on the battery state information received through the OBD 100 .

The terminal transceiver 210 and the server transceiver 310 to be described later include DMR and WiFi, Bluetooth Low Energy (BLE), Bluetooth, 3rd Generation (3G), 3rd Generation Partnership Project (3GPP), Long Term Evolution (LTE). , LTE-A, 4G (4th Generation), and 5G (5th Generation) may communicate with an external device through at least one communication module. The communication module is only an example, and any communication module capable of communicating with the outside may be used for the terminal transceiver 210 and the server transceiver 310 to be described later.

The terminal transceiver 210 and the server transceiver 310 to be described later may receive battery state information from the OBD 100 .

The terminal transceiver unit 210 transmits information processed by the battery condition determination unit 220, the balancing determination unit 230, the balancing index operation unit 240, the specific cell determination unit 250, and the cell deviation index operation unit 260 to the server It can be sent to (300).

The information processed at this time will be described later.

The battery condition determination unit 220 determines whether the vehicle is driving or stopped based on the wheel rotation information and the wheel rotation information of the moving means received from the ECU (Electronic Control Unit). When accelerating, a large current is applied to the battery because a large amount of energy is required.

In addition, when a sensor connected to the battery detects a state in which current is being applied to the battery in a stopped state, it is recognized as the battery charge state.

When the battery condition determining unit 220 determines that the moving means is in a charged state, the balancing determining unit 230 periodically monitors the battery cell voltage to determine whether cell balancing has been performed.

에 의해 연산한다.When the balancing index calculating unit 240 determines that cell balancing is performed in the battery cells in the balancing determining unit 230, the degree of

calculated by

For example, at this time, when there is no movement in the wheel of the electric vehicle and the current of the battery is applied in a state in which the steering wheel does not move, it is determined that charging is being performed.

The battery management system (BMS) of an electric vehicle monitors the voltage value of the cells of each battery while the battery is being charged. At this time, when it is sensed that a voltage of one battery cell is higher than that of another cell, cell balancing is performed.

When it is detected that cell balancing is being performed, the degree is calculated as an index value.

When the battery condition determining unit 220 determines that the moving means is dynamic driving, the unusual cell determination unit 250 determines a battery cell whose voltage is lowered by 1% or more based on the normal battery cell voltage as the unusual cell.

For example, it is a situation in which the wheel of an electric vehicle continues to move for more than a predetermined time. When the driver presses the brake for sudden braking, a large current is required. At this time, since a large voltage is required for braking in an electric vehicle in a sudden braking situation, a large current is applied to the battery in a short time.

When the sensor detects that a large current is applied, it is determined that this situation is a dynamic driving situation.

And in this dynamic driving situation, as a large current is applied, the voltage stored in the battery cell drops. At this time, when the voltage falls to 1% or more of the normal battery cell voltage, this battery cell is identified as a special cell.

에 기초하여 셀 편차 인덱스를 연산한다.The cell deviation index operation unit 260 is

Calculate the cell deviation index based on

Specifically, the cell deviation index calculator 260 calculates the cell deviation index based on the battery state information.

In addition, when the cell deviation index is applied in an embodiment of the present invention, it is possible with relatively little data when estimating the state of health (SOH) in the server 300 to index information on the cell voltage deviation.

Hereinafter, the configuration of the server 300 will be described in detail based on FIG. 3 . 3 is a schematic diagram of an embodiment of the invention, and the server 300 may include a server transceiver 310 , a database 320 , an OCV extractor 330 , and an SOH estimator 340 .

The server 300 receives battery state information including the voltage, current, temperature, the cell balancing index, and the cell deviation index from the terminal 200 and stores it in the database 320 .

The server 300 estimates the state of health (SOH) included in battery information corresponding to the processed battery state information received from the terminal among the battery information previously stored in the database 320 received from another terminal.

The server transceiver 310 receives battery state information from the terminal 200 .

The database 320 may store battery state information received from other terminals.

The OCV extractor 330 may extract the OCV table based on the battery state information received from the terminal. At this time, the OCV (Open Circuit Voltage) table means a change in OCV according to the SOC having all of the battery pack voltage, current, temperature, and SOC information of the mobile means while the mobile means is driving or charging.

However, the battery pack voltage, current, temperature, and SOC are not all extracted when the vehicle is driving or charging. At this time, there is a preset condition, and the OCV table according to the SOC is extracted by using the voltage, current, temperature, and SOC that satisfy the preset conditions.

At this time, there are two preset conditions: 1) whether the battery current value is less than the threshold value, or 2) whether the time during which the battery current value is maintained below the threshold value is longer than a specific time.

1) The condition is that the battery current value is less than the threshold while driving or charging, 1) meets the condition, and 2) if the current value continues for more than a specific time, it will be possible to measure the stable voltage of the battery pack that is below the threshold. . At this time, the voltage remaining after the battery has been used is a stable voltage, and to measure it, it is in the open circuit situation, that is, when the battery current value is close to 0. Accordingly, the OCV table according to the SOC is extracted by using the voltage, current, temperature, and SOC information of the battery pack satisfying both conditions 1) and 2).

In addition, since the OCV table has nothing to do with the aging of the battery, it is okay to update the OCV table into a single OCV table using battery information acquired from various transportation means.

However, a subtle difference (hysteresis) may occur in the graph of the OCV table according to the SOC of charging and discharging according to the difference in the time during which the moving means is stopped. For such hysteresis, when updating the OCV table of the moving means that satisfies both condition 1) and condition 2), the OCV according to the SOC after acquiring the information (voltage, current, temperature, SOC, etc.) Because the table is updated, distortion of OCV information due to hysteresis can be limited.

The SOH estimator 330 may estimate the state of health (SOH) of the mobile means based on the state information of the mobile means pre-stored in the database and the battery state information received from the terminal 200 , and in the OCV extractor 330 , The State of Health (SOH) can be estimated using the extracted OCV table.

Specifically, the database has the state information of the transportation means received from dozens of other means of transportation, and this information is stored through deep learning.

This deep learning process uses time-dependent sequence algorithms such as RNN (Recurrent Neural Network) and LSTM (Long Short-Term Memory).

At this time, the sequence algorithm according to time used in an embodiment of the present invention is not limited to Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM).

The SOH estimator 330 estimates the state of health (SOH) corresponding to the battery state information received from the terminal and the mobile means state information stored in the database 320 .

Specifically, information about the state of transportation means of about 100,000 or more other electric vehicles is stored in the database. The stored transportation means state information may be expressed as a parameter index value according to time. The state of health (SOH) is estimated by comparing the stored state of transportation information with the battery state information of the electric vehicle to be estimated.

The terminal 200 and the user terminal 400 may be implemented on an electronic terminal including an interface that enables interaction with a user.

Here, the electronic terminal, for example, may be implemented as a computer or portable terminal, television, wearable device, contactless control device, etc. that can be connected to a remote server through a network or connectable to other terminals and servers. . Here, the computer includes, for example, a laptop, a desktop, and a laptop equipped with a web browser, and the portable terminal is, for example, a wireless communication device that ensures portability and mobility. , PCS (Personal Communication System), PDC (Personal Digital Cellular), PHS (Personal Handyphone System), PDA (Personal Digital Assistant), GSM (Global System for Mobile communications), IMT (International Mobile Telecommunication)-2000, CDMA (Code) All kinds of Handheld, such as Division Multiple Access)-2000, WCode Division Multiple Access (W-CDMA), Wireless Broadband Internet (Wibro), Smart Phone, Mobile Worldwide Interoperability for Microwave Access (WiMAX), etc. ) based wireless communication device. In addition, the television may include IPTV (Internet Protocol Television), Internet TV (Internet Television), terrestrial TV, cable TV, and the like. Furthermore, the wearable device is, for example, a type of information processing device that can be worn directly on the human body, such as watches, glasses, accessories, clothes, shoes, etc. can be connected with

Hereinafter, a method of extracting an electric vehicle battery OCV table will be described based on FIGS. 4 and 6 .

4 is a diagram illustrating an electric vehicle battery OCV table extraction method according to an embodiment of the present invention, and FIG. 5 is a step of extracting an OCV (Open Circuit Voltage) table among the electric vehicle battery OCV table extraction method according to an embodiment of the present invention. FIG. 5 is a diagram illustrating a step of estimating a State of Health (SOH) in an OCV table extraction method for an electric vehicle battery according to an embodiment of the present invention.

An embodiment of the present invention can be started by calling information to the terminal (s100).

Specifically, the information received by the terminal may include battery state information.

As described above, the battery state information may include voltage, current, temperature, and state of charge (SOC) values of battery cells and packs.

According to an embodiment of the present invention, only necessary information can be filtered based on the battery state information retrieved from the terminal (s200).

Since unnecessary information is included in the information retrieved from the terminal, filtering is required to estimate the SOH.

In the process of filtering, a cell deviation index may be calculated (s210).

에 기초하여 연산한다.The cell deviation index is

calculated based on

In the filtering process, it may be determined whether the mobile means is in a battery charging state or a dynamic driving state (s220).

Specifically, it is determined that the vehicle is temporarily running when the speed of the vehicle exceeds 0 km/h, and when it is not, it is determined that the vehicle is stopped.

If the means of transportation is braked and accelerated rapidly while driving, a large current is applied to the battery because a large amount of energy is required. will be.

In addition, if a current is being applied to the battery while the vehicle is stopped, when a sensor connected to the battery detects it, it is identified as the battery charging state.

If it is determined that the mobile means is in a charged state during the filtering process, a cell balancing index can be calculated (s230).

식에 기초하여 연산한다. 셀 밸런싱이 다 수행이 된 후, 충전이 완료된다.Specifically, in the charging situation, cell balancing is performed.

It is calculated based on the formula. After cell balancing is completed, charging is completed.

In the filtering process, if it is determined that the moving means is in a dynamic driving situation, a battery cell whose voltage is lowered by 1% or more based on the voltage reference of the battery cell may be determined as a specific cell (s240).

The second step (s300, s400) is a step of extracting an OCV table and a step of estimating a State of Health (SOH), which will be described later with FIGS. 5 and 6 .

Hereinafter, the step (s300) of extracting the OCV table among the OCV table extraction method of the electric vehicle battery will be described in detail based on FIG. 5 .

The step of extracting the OCV table (s300) may extract the OCV table based on the battery state information received from the terminal (s100). At this time, the OCV (Open Circuit Voltage) table means a change in OCV according to the SOC having all of the battery pack voltage, current, temperature, and SOC information of the mobile means while the mobile means is driving or charging.

However, the battery pack voltage, current, temperature, and SOC are not all extracted when the vehicle is driving or charging. At this time, there is a preset condition, and the OCV table according to the SOC is extracted by using the voltage, current, temperature, and SOC that satisfy the preset conditions.

At this time, there are two preset conditions: 1) whether the battery current value is less than the threshold value (s310), and 2) whether the time for which the battery current value is maintained below the threshold value is longer than a specific time (s320).

1) In condition (s310), the battery current value is less than the threshold value in a driving or charging situation, 1) meets the condition, and 2) if the current value continues for more than a specific time in condition (s320), the battery pack that is less than the threshold is stable. You will be able to measure the voltage. At this time, the voltage remaining after the battery has been used is a stable voltage, and to measure it, it is in the open circuit situation, that is, when the battery current value is close to 0. Accordingly, the OCV table according to the SOC is extracted using the voltage, current, temperature, and SOC information of the battery pack satisfying both conditions 1) and 2) ( s330 ).

In addition, the OCV table extracted in the step (s300) of extracting the OCV table has no relation to the aging ditch of the battery, so it is okay to update it as one OCV table using battery information acquired from various means of transportation.

However, a subtle difference (hysteresis) may occur in the graph of the OCV table according to the SOC of charging and discharging according to the difference in the time during which the moving means is stopped. When updating (s330) the OCV table of a moving means that satisfies both condition 1) (s310) and condition 2) (s320) with respect to such hysteresis, information (voltage, current, temperature, SOC of various moving means described above) etc.), the OCV information distortion due to hysteresis can be limited because the OCV table is updated according to the SOC.

Hereinafter, the step of estimating the state of health (SOH) among the OCV table extraction method of the electric vehicle battery will be described in detail based on FIG. 6 .

The second step (s400) may include a step (s410) of deep learning by receiving information from the outside.

Specifically, it is a step of deep learning by getting information about the state of transportation means from other means of transportation other than the means of transportation for which SOH (State Of Health) needs to be estimated.

This deep learning process uses an algorithm that can process sequence information, and the algorithms used at this time include RNN (Recurrent Neural Network) and LSTM (Long Short-Term Memory).

However, any algorithm capable of processing sequence information is not limited thereto.

Specifically, the step (s420) of estimating the State of Health (SOH) corresponds to the battery state information for estimating the state of health (SOH) and the state of the transportation means of the step (s410) of deep learning by receiving information from the outside. You can call the SOH (State Of Health) value.

The program analysis method according to the embodiment described with reference to FIGS. 4 and 5 may also be implemented in the form of a recording medium including instructions executable by a computer, such as a program module executed by a computer. Computer-readable media can be any available media that can be accessed by a computer and includes both volatile and nonvolatile media, removable and non-removable media. In addition, computer-readable media may include both computer storage media and communication media. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Communication media typically includes computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave, or other transport mechanism, and includes any information delivery media. In addition, the program analysis method according to an embodiment of the present invention may be implemented as a computer program (or computer program product) including instructions executable by a computer. The computer program includes programmable machine instructions processed by a processor, and may be implemented in a high-level programming language, an object-oriented programming language, an assembly language, or a machine language. . In addition, the computer program may be recorded in a tangible computer-readable recording medium (eg, a memory, a hard disk, a magnetic/optical medium, or a solid-state drive (SSD), etc.). Therefore, the program analysis method according to an embodiment of the present invention may be implemented by executing the computer program as described above by a computing device. The computing device may include at least a portion of a processor, a memory, a storage device, a high-speed interface connected to the memory and the high-speed expansion port, and a low-speed interface connected to the low-speed bus and the storage device. Each of these components is connected to each other using various buses, and may be mounted on a common motherboard or in any other suitable manner. Here, the processor may process a command within the computing device, such as for displaying graphic information for providing a Graphical User Interface (GUI) on an external input or output device, such as a display connected to a high-speed interface, for example. For example, instructions stored in memory or a storage device. In other embodiments, multiple processors and/or multiple buses may be used with multiple memories and types of memory as appropriate. In addition, the processor may be implemented as a chipset formed by chips including a plurality of independent analog and/or digital processors.

Memory also stores information within the computing device. As an example, the memory may be configured as a volatile memory unit or a set thereof. As another example, the memory may be configured as a non-volatile memory unit or a set thereof. The memory may also be another form of computer readable medium such as, for example, a magnetic or optical disk.

In addition, the storage device may provide a large-capacity storage space to the computing device. The storage device may be a computer-readable medium or a component comprising such a medium, and may include, for example, devices or other components within a storage area network (SAN), a floppy disk device, a hard disk device, an optical disk device, Alternatively, it may be a tape device, a flash memory, or other semiconductor memory device or device array similar thereto.

The above description of the present invention is for illustration, and those of ordinary skill in the art to which the present invention pertains can understand that it can be easily modified into other specific forms without changing the technical spirit or essential features of the present invention. will be. Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive. For example, each component described as a single type may be implemented in a distributed manner, and likewise components described as distributed may be implemented in a combined form.

The scope of the present invention is indicated by the following claims rather than the above detailed description, and all changes or modifications derived from the meaning and scope of the claims and their equivalents should be interpreted as being included in the scope of the present invention. do.

100: OBD
200: terminal
210: terminal transceiver unit
220: battery status determination unit
230: balancing determination unit
240: balancing index operation unit
250: specific cell discrimination unit
260: cell deviation index operation unit
300: server
310: server transceiver
320: database
330: OCV extraction unit
340: SOH estimator
400: user terminal

Claims (8)

Regarding the electric vehicle battery OCV table extraction system using battery state information,
a terminal receiving the battery state information from the OBD and filtering only necessary information; and
a server for estimating a state of health (SOH) of a battery based on the filtered information; including,
The terminal is
a battery condition determining unit for determining whether the moving means including the OBD is a battery charging condition or a dynamic condition; and when the battery condition determination unit determines that the battery is in a charged state, the cell balancing index BI

a cell balancing index calculator that calculates based on ; includes,
remind

is the SOC value of the battery cell having the largest SOC (state of charge) value among the battery cells that have been fully charged,

is the SOC value of the battery cell having the smallest SOC value among the battery cells at the start of charging,

and above

is the SOC of the battery pack when charging is completed and starting, respectively,
The server is
An OCV extraction unit for extracting an OCV table representing a change in OCV (Open Circuit Voltage) according to the SOC of the battery pack based on the battery state information received from the terminal,
The OCV extraction unit 1) the battery current value is less than the threshold value, 2) the electric vehicle battery OCV table extraction system for extracting the OCV table when the time for maintaining the battery current value less than the threshold value is longer than a specific time.
delete According to claim 1,
The terminal is
Electric vehicle battery OCV table extraction system including a special cell determining unit that determines that the battery condition determination unit determines that the moving means is a dynamic driving condition, a battery cell whose voltage has been lowered by 1% or more based on the voltage reference of the normal battery cell as a unique cell . 4. The method of claim 3,
The server is
Receive and store the processing battery state information including the voltage, current, temperature and the balancing index from the terminal in a database,
The OCV table is additionally extracted using the processed battery state information, and SOH (State Of Health) included in battery information corresponding to the battery state information received from the terminal among the battery information received from another terminal and stored in the database in advance. Electric vehicle battery OCV table extraction system for estimating . Regarding the method of extracting the electric vehicle battery OCV table using battery state information,
a first step of receiving and filtering battery state information; and
a second step of estimating a State of Health (SOH) based on the filtered information; including,
The first step is
Including the step of determining whether the means of transportation is in a battery charging state or a dynamic driving state, and in the case of a charging state, the cell balancing index BI

Comprising the step of calculating a cell balancing index to calculate based on,
remind

is the SOC value of the battery cell having the largest SOC (state of charge) value among the charged battery cells,

is the SOC value of the battery cell having the smallest SOC value among the battery cells at the start of charging,

and above

is the SOC of the battery pack when charging is completed and starting, respectively,
The second step is
and extracting an OCV table representing a change in OCV (Open Circuit Voltage) according to the SOC of the battery pack based on the battery state information,
1) The battery current value is less than the threshold value, 2) the electric vehicle battery OCV table extraction method for extracting the OCV table when the time for maintaining the battery current value less than the threshold value is greater than a specific time.
delete 6. The method of claim 5,
The first step is
Electric vehicle battery OCV table extraction method comprising the step of discriminating a battery cell in which the voltage of the normal battery cell has been lowered by 1% or more when the dynamic driving situation occurs 8. The method of claim 7,
The second step is
Receive and store battery state information including the voltage, current, temperature and the cell balancing index,
An electric vehicle battery OCV table extraction method for estimating a state of health (SOH) included in battery information corresponding to the battery state information among previously stored battery information and additionally extracting an OCV table using the battery state information

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