KR102079038B1 - Intelligent Battery Sensor Apparatus and Method thereof - Google Patents

Intelligent Battery Sensor Apparatus and Method thereof Download PDF

Info

Publication number
KR102079038B1
KR102079038B1 KR1020130116455A KR20130116455A KR102079038B1 KR 102079038 B1 KR102079038 B1 KR 102079038B1 KR 1020130116455 A KR1020130116455 A KR 1020130116455A KR 20130116455 A KR20130116455 A KR 20130116455A KR 102079038 B1 KR102079038 B1 KR 102079038B1
Authority
KR
South Korea
Prior art keywords
battery
soc
capacity
ocv
specific error
Prior art date
Application number
KR1020130116455A
Other languages
Korean (ko)
Other versions
KR20150037144A (en
Inventor
김승현
Original Assignee
현대모비스 주식회사
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 현대모비스 주식회사 filed Critical 현대모비스 주식회사
Priority to KR1020130116455A priority Critical patent/KR102079038B1/en
Priority to CN201410424325.2A priority patent/CN104518247B/en
Publication of KR20150037144A publication Critical patent/KR20150037144A/en
Application granted granted Critical
Publication of KR102079038B1 publication Critical patent/KR102079038B1/en

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
    • B60L58/10—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries
    • B60L58/12—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries responding to state of charge [SoC]
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/3644—Constructional arrangements
    • G01R31/3648—Constructional arrangements comprising digital calculation means, e.g. for performing an algorithm
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
    • G01R31/52—Testing for short-circuits, leakage current or ground faults
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/48—Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/48—Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte
    • H01M10/486—Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte for measuring temperature
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M2220/00—Batteries for particular applications
    • H01M2220/20—Batteries in motive systems, e.g. vehicle, ship, plane
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/10—Energy storage using batteries

Abstract

본 발명은 지능형 배터리 센서 장치 및 그 동작 방법에 관한 것으로서, 본 발명에 따른 지능형 배터리 센서 장치는 차량의 배터리가 정격 용량이 아닌 배터리로 교체되더라도 교체된 배터리의 SOC를 정확하게 산출할 수 있는 것을 특징으로 한다. 본 발명에 따르면, 배터리가 교체되더라도 SOC를 정확하게 산출할 수 있는 효과가 있고, 특히 다른 용량, 다른 제조업체의 배터리로 교체되더라도 SOC를 정확하게 산출할 수 있는 이점이 있다.The present invention relates to an intelligent battery sensor device and an operation method thereof, wherein the intelligent battery sensor device according to the present invention can accurately calculate the SOC of the replaced battery even when the battery of the vehicle is replaced with a battery that is not rated. do. According to the present invention, there is an effect that can accurately calculate the SOC even if the battery is replaced, in particular, there is an advantage that can accurately calculate the SOC even if replaced with a battery of a different capacity, different manufacturers.

Description

지능형 배터리 센서 장치 및 그 동작 방법{Intelligent Battery Sensor Apparatus and Method thereof}Intelligent Battery Sensor Apparatus and Its Operation Method {Intelligent Battery Sensor Apparatus and Method}

본 발명은 지능형 배터리 센서 장치 및 그 동작 방법에 관한 것으로서, 보다 구체적으로는 교체된 배터리의 SOC를 정확하게 산출하는 장치 및 방법에 관한 것이다.The present invention relates to an intelligent battery sensor device and an operation method thereof, and more particularly, to an apparatus and method for accurately calculating the SOC of a replaced battery.

종래의 차량용 배터리 용량 측정방법은 도 1에 도시된 바와 같이, 교체된 배터리의 내부 저항이 아닌 기존 배터리의 용량을 기준으로 교체된 배터리의 충전이 완료된 이후에도 유입되는 전류량을 측정하여 교체된 배터리의 용량을 측정하였다.In the conventional method for measuring the battery capacity of a vehicle, as shown in FIG. 1, the capacity of the replaced battery is measured by measuring the amount of current flowing after the replacement of the battery is completed based on the capacity of the existing battery, not the internal resistance of the replaced battery. Was measured.

이러한 차량용 배터리 용량 측정 방법에 따르면, 차량용 배터리가 교체된 이후, 특히 차량용 배터리가 이전보다 큰 배터리로 교체된 이후에도 교체된 배터리의 용량을 정확하게 측정할 수 있으므로, 교체된 배터리의 SOC 등을 정확하게 산출할 수 있다.According to such a method of measuring the battery capacity of a vehicle, since the capacity of the replaced battery can be accurately measured after the vehicle battery is replaced, especially after the vehicle battery is replaced with a larger battery, the SOC of the replaced battery can be accurately calculated. Can be.

그러나, 종래 기술은 배터리가 기존 배터리보다 큰 용량으로 교체될 경우에만 교체된 배터리의 SOC 등을 정확하게 산출할 수 있다 라는 제약이 있다.However, the prior art has a limitation that the SOC of the replaced battery can be accurately calculated only when the battery is replaced with a larger capacity than the existing battery.

즉, (차량의 배터리가 항상 기존 용량보다 큰 용량의 배터리로만 교체되는 것이 아니기 때문에) 종래 기술은 배터리가 기존 용량보다 작은 용량의 배터리로 교체될 경우 SOC를 정확하게 산출할 수 없고, 기존 용량보다 큰 용량의 배터리로 교체되더라도, 교체된 배터리가 기존 배터리와 사양이 다르기 때문에 기입력된 SOC-OCV 맵을 이용할 수 없으므로, IBS가 Recalibration될 경우 SOC를 정확하게 산출할 수 없다 라는 문제점이 있다. That is, the prior art cannot accurately calculate the SOC when the battery is replaced with a smaller capacity battery (because the battery is not always replaced with a battery having a larger capacity than the existing capacity), Even if the battery is replaced with a battery having a capacity, the SOC-OCV map inputted cannot be used because the replaced battery has different specifications from the existing battery, and thus there is a problem in that the SOC cannot be accurately calculated when the IBS is recalibrated.

본 발명은 상기와 같은 문제점을 감안하여 창출한 것으로서, 차량의 배터리가 정격 용량이 아닌 배터리로 교체되더라도 교체된 배터리의 SOC를 정확하게 산출할 수 있는 지능형 배터리 센서 장치 및 그 동작 방법을 제공하는 데 그 목적이 있다.The present invention has been made in view of the above problems, and provides an intelligent battery sensor device and an operation method thereof capable of accurately calculating the SOC of the replaced battery even when the battery of the vehicle is replaced with a battery that is not rated. There is a purpose.

전술한 목적을 달성하기 위하여, 본 발명의 일면에 따른 지능형 배터리 센서 장치는 차량에 배터리가 장착되면 장착된 상기 배터리로부터 전압, 전류 및 온도 정보를 감지하는 센서부; 및 장착된 상기 배터리의 SOC 및 용량에 특정 오차가 반영된 상기 배터리의 SOC를 예측하고, 상기 배터리의 충전이 완료될 때까지 상기 센서부에 의해 감지된 전류의 적산 값을 산출하며, 예측된 각 SOC와, 상기 배터리의 충전 완료 후 산출된 전류의 적산 값을 토대로 산출된 상기 배터리의 SOC, 상기 용량에 특정 오차를 반영한 상기 배터리의 SOC를 각각 비교하며, 비교결과를 토대로 상기 배터리의 용량을 판단하며, 판단된 상기 배터리의 용량에 따라 상기 배터리의 SOC를 산출하는 제어부를 포함한다.In order to achieve the above object, an intelligent battery sensor device according to an aspect of the present invention comprises a sensor unit for detecting voltage, current and temperature information from the battery mounted when the battery is mounted on the vehicle; And predicting the SOC of the battery in which a specific error is reflected in the installed SOC and capacity of the battery, calculating an integrated value of the current sensed by the sensor unit until charging of the battery is completed, and predicting each SOC And comparing the SOC of the battery calculated on the basis of the integrated value of the current calculated after the completion of charging of the battery and the SOC of the battery reflecting a specific error in the capacity, and determining the capacity of the battery based on a comparison result. And a controller configured to calculate the SOC of the battery according to the determined capacity of the battery.

본 발명의 다른 면에 따른 지능형 배터리 센서 장치의 동작 방법은 차량에 장착된 배터리의 SOC 및 용량에 특정 오차가 반영된 상기 배터리의 SOC를 예측하는 단계; 상기 배터리의 충전이 완료될 때까지 전류 적산 값을 산출하는 단계; 예측된 각 SOC와, 상기 배터리의 충전 완료 후 산출된 전류 적산 값을 토대로 산출된 상기 배터리의 SOC, 상기 용량에 특정 오차를 반영한 상기 배터리의 SOC를 각각 비교하는 단계; 및 비교결과를 토대로 상기 배터리의 용량을 판단하여 판단된 상기 배터리의 용량에 따라 상기 배터리의 SOC를 산출하는 단계를 포함한다.According to another aspect of the present invention, there is provided a method of operating an intelligent battery sensor device, the method comprising: predicting an SOC of a battery in which a specific error is reflected in an SOC and a capacity of a battery mounted in a vehicle; Calculating a current integration value until the charging of the battery is completed; Comparing each predicted SOC with the SOC of the battery calculated on the basis of the current integration value calculated after the completion of charging of the battery, and the SOC of the battery reflecting a specific error in the capacity; And calculating SOC of the battery according to the capacity of the battery determined by determining the capacity of the battery based on a comparison result.

본 발명에 따르면, 배터리가 교체되더라도 SOC를 정확하게 산출할 수 있는 효과가 있다.According to the present invention, even if the battery is replaced, there is an effect that can accurately calculate the SOC.

특히 다른 용량, 다른 제조업체의 배터리로 교체되더라도 SOC를 정확하게 산출할 수 있는 이점이 있다.In particular, the SOC can be accurately calculated even if it is replaced by a battery of different capacity or from another manufacturer.

도 1은 종래의 기술을 설명하기 위한 도면.
도 2는 본 발명의 일 실시예에 따른 지능형 배터리 센서 장치를 설명하기 위한 도면.
도 3은 본 발명의 일 실시예에 따른 지능형 배터리 센서의 동작 방법을 설명하기 위한 흐름도.1 is a view for explaining a conventional technology.
2 is a view for explaining the intelligent battery sensor device according to an embodiment of the present invention.
3 is a flowchart illustrating a method of operating an intelligent battery sensor according to an embodiment of the present invention.

본 발명의 이점 및 특징, 그리고 그것들을 달성하는 방법은 첨부되는 도면과 함께 상세하게 후술되어 있는 실시예들을 참조하면 명확해질 것이다. 그러나 본 발명은 이하에서 개시되는 실시예들에 한정되는 것이 아니라 서로 다른 다양한 형태로 구현될 것이며, 단지 본 실시예들은 본 발명의 개시가 완전하도록 하며, 본 발명이 속하는 기술분야에서 통상의 지식을 가진 자에게 발명의 범주를 용이하게 이해할 수 있도록 제공되는 것이며, 본 발명은 청구항의 기재에 의해 정의된다. 한편, 본 명세서에서 사용된 용어는 실시예들을 설명하기 위한 것이며 본 발명을 제한하고자 하는 것은 아니다. 본 명세서에서, 단수형은 문구에서 특별히 언급하지 않는 한 복수형도 포함한다. 명세서에서 사용되는 "포함한다(comprises)" 또는 "포함하는(comprising)"은 언급된 구성요소, 단계, 동작 및/또는 소자 이외의 하나 이상의 다른 구성요소, 단계, 동작 및/또는 소자의 존재 또는 추가를 배제하지 않는다.Advantages and features of the present invention, and methods for achieving them will be apparent with reference to the embodiments described below in detail in conjunction with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but may be implemented in various forms, and only the embodiments of the present invention make the disclosure of the present invention complete, and those of ordinary skill in the art to which the present invention belongs. It is provided to those skilled in the art to easily understand the scope of the invention, which is defined by the description of the claims. Meanwhile, the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. In this specification, the singular also includes the plural unless specifically stated otherwise in the phrase. As used herein, "comprises" or "comprising" means the presence of one or more other components, steps, operations and / or elements other than the components, steps, operations and / or elements mentioned or Does not exclude additional

배터리 센서는 배터리 제조사로부터 제공된 SOC-OCV 맵을 이용하여 배터리가 최초 Power On Reset되고, 특정 시간(대략 3-4시간) 경과 후 획득된 OCV(Open Circuit Voltage)를 이용하여 최초 SOC를 획득한다.The battery sensor uses the SOC-OCV map provided by the battery manufacturer to acquire the initial SOC using the OCV (Open Circuit Voltage) obtained after the battery is initially powered on and after a specific time (about 3-4 hours).

즉, 배터리 센서는 차량에 배터리가 최초 장착된 후 일정 암전류 이하에서 특정 시간(대략 3-4시간)이 경과 되어야 최초 장착된 배터리가 안정된 것으로 판단한다.That is, the battery sensor determines that the first battery installed is stable only after a certain time (approximately 3-4 hours) has elapsed below a certain dark current after the battery is first installed in the vehicle.

그러나, 차량 출고시 장착된 배터리가 다른 사양의 배터리로 교체될 경우, 배터리 센서에 기입력된 SOC-OCV 맵과 교체된 배터리의 특성이 다르기 때문에 SOC 산출에 있어서 문제가 발생할 수도 있다.However, when the battery installed at the time of shipment of the vehicle is replaced with a battery having a different specification, there may be a problem in calculating the SOC because the characteristics of the replaced battery and the SOC-OCV map previously input to the battery sensor are different.

즉, 배터리 센서가 시판 중인 모든 사양의 배터리 SOC-OCV 맵을 기저장하는 것은 현실적으로 불가능하고, 또한 어떤 사양의 배터리로 교체되었는지 조차 판단할 수 없기 때문에 배터리가 교체될 경우 어떤 배터리로 교체되었는지 배터리 용량 판단 자기학습 알고리즘이 필요하다.That is, it is practically impossible for a battery sensor to store a battery SOC-OCV map of all the specifications on the market, and it is impossible to determine which battery has been replaced, so it is not possible to determine which battery has been replaced when the battery is replaced. Judgment self-learning algorithms are needed.

단 배터리 교체시 차량의 배터리 장착 레이아웃에 따른 한계 및 차량의 성능 저하를 막기 위해 배터리의 교체는 최초 장착된 차량의 배터리 대비 ±10Ah 내에서 교체되고, 배터리 타입(Flooded, AGM)은 동일하게 교체되어야 한다.However, when replacing the battery, the battery should be replaced within ± 10Ah of the battery of the first vehicle and the battery type (Flooded, AGM) should be replaced in order to prevent the performance limitation of the vehicle's battery installation layout and the performance degradation of the vehicle. do.

또한, 배터리의 SOC와 OCV는 선형관계에 있다.In addition, the SOC and OCV of the battery are linear.

즉, OCV를 slope이 a, offset 값이 b인 a*SOC + b의 일차 함수형태로 나타낼 수 있다.That is, OCV can be expressed as a linear function form of a * SOC + b with slope a and offset value b.

SOC와 OCV의 선형적 특성은 배터리의 제조사별, 용량별로 편차가 있어서, 배터리의 특성을 판단하는 하나의 대표 값(기준 값)으로 사용될 수 없다.Since the linear characteristics of SOC and OCV vary depending on the manufacturer and capacity of the battery, it cannot be used as a representative value (reference value) for determining the characteristics of the battery.

그러나, SOC-OCV 맵 상에서 Slope는 평균적으로 용량별 비슷한 특성을 나타내기 때문에 제조사별 배터리를 용량별로 나누고, 용량별로 나누어진 배터리들의 SOC와 OCV의 선형적 특성에 따른 Slope에 대해 평균 Slope를 산출하여 계산된 Offset값을 적용할 경우, 교체된 배터리의 SOC-OCV 맵을 결정할 수 있다.However, on the SOC-OCV map, the slope shows similar characteristics for each capacity, so the battery of each manufacturer is divided by capacity, and the average slope is calculated for the slope according to the linear characteristics of SOC and OCV of batteries divided by capacity. When applying the calculated offset value, it is possible to determine the SOC-OCV map of the replaced battery.

즉, 차량에 최초 장착된 배터리로부터 획득된 OCV값과, 다양한 제조사별 배터리의 SOC-OCV맵에 대한 평균 slope를 토대로 초기 예상 SOC를 산출할 수 있기 때문에, offset값을 계산하여 최종적으로 SOC-OCV맵을 결정할 수 있다.That is, since the initial estimated SOC can be calculated based on the OCV value obtained from the battery first installed in the vehicle and the average slope of the SOC-OCV map of the battery of various manufacturers, the SOC-OCV is finally calculated by calculating the offset value. The map can be determined.

배터리가 교체 후 교체된 배터리의 전압은 안정화된 전압 즉. OCV(Open Circuit Voltage)라고 볼 수 없기 때문에 배터리가 교체된 후 일정 조건하에 특정 시간(대략 3-4시간) 경과 후 획득된 전압을 OCV라 한다.After the battery is replaced, the voltage of the replaced battery is the stabilized voltage. Since it is not called OCV (Open Circuit Voltage), the voltage obtained after a certain time (approximately 3-4 hours) after a battery is replaced is called OCV.

이하에서는 배터리가 용량이 60Ah와 68Ah사이인 배터리로 교체된 것을 기준으로 설명한다.In the following description, the battery is replaced with a battery having a capacity between 60 Ah and 68 Ah.

이하, 도 2를 참조하여 본 발명의 일 실시예에 따른 지능형 배터리 센서 장치를 설명한다. 도 2는 본 발명의 일 실시예에 따른 지능형 배터리 센서 장치를 설명하기 위한 도면이다.Hereinafter, an intelligent battery sensor device according to an embodiment of the present invention will be described with reference to FIG. 2. 2 is a view for explaining an intelligent battery sensor device according to an embodiment of the present invention.

도 2에 도시된 바와 같이, 지능형 배터리 센서 장치(100)는 제어부(110), 센서부(120) 및 저장부(130)를 포함한다. As shown in FIG. 2, the intelligent battery sensor device 100 includes a control unit 110, a sensor unit 120, and a storage unit 130.

제어부(110)는 차량에 최초 장착된 배터리(200)의 OCV(Open Circuit Voltage)를 획득한 후 전류 적산을 시작한다.The controller 110 acquires an OCV (Open Circuit Voltage) of the battery 200 first installed in the vehicle and starts to integrate current.

예컨대, 차량의 배터리가 교체될 경우, 센서부(120)는 최초 장착된 배터리(200)로부터 전압, 전류, 온도 정보를 감지한다. For example, when the battery of the vehicle is replaced, the sensor unit 120 detects voltage, current, and temperature information from the battery 200 first installed.

제어부(110)는 얼터네이터를 제어하여 배터리(200)의 충전이 완료(배터리가 100% 충전)될 때까지 전류 적산 값을 산출한다.The controller 110 controls the alternator to calculate the current integration value until the charging of the battery 200 is completed (the battery is 100% charged).

한편, 차량에 최초 장착된 배터리(200)의 용량이 60Ah일 경우, 시판 중인 배터리의 용량을 기준으로 ±10Ah 사이의 배터리 용량은 68Ah이다.On the other hand, when the capacity of the battery 200 initially mounted on the vehicle is 60 Ah, the battery capacity between ± 10 Ah based on the capacity of the commercially available battery is 68 Ah.

제어부(110)는 기실험으로 획득된 전압 α, 전류 β값을 토대로 일정시간 동안 감지된 배터리(200)의 전압이 기실험으로 획득된 전압 α이상, 일정시간 동안 감지된 배터리(200)의 전류가 기실험으로 획득된 전류 β이하로 흐르면, 배터리(200)의 충전이 완료된 것으로 판단한다.The controller 110 determines that the voltage of the battery 200 sensed for a predetermined time is greater than or equal to the voltage α obtained for the experimental experiment and the current of the battery 200 sensed for a predetermined time, based on the voltage α and the current β values obtained by the experimental experiment. When the current flows below the value β obtained by the experiment, it is determined that the charging of the battery 200 is completed.

제어부(110)는 배터리(200)의 충전이 완료된 것으로 판단되면, 배터리(200)의 SOC를 100%으로 설정하고, 이후 센서부(120)가 Recalibration될 경우 사용할 SOC-OCV맵을 결정한다.When the controller 110 determines that the charging of the battery 200 is completed, the controller 110 sets the SOC of the battery 200 to 100%, and then determines the SOC-OCV map to be used when the sensor 120 is recalibrated.

예컨대, 제어부(110)는 차량에 배터리(200)가 장착된 후 일정 암전류 이하에서 특정 시간(3-4시간)이 경과되면, 저장부(130)에 저장된 배터리(200)의 SOC-OCV맵을 이용하여 배터리(200)의 SOC를 초기화하며, 센서부(120)를 Recalibration한다.For example, the controller 110 may determine the SOC-OCV map of the battery 200 stored in the storage unit 130 when a specific time (3-4 hours) elapses after a predetermined dark current after the battery 200 is installed in the vehicle. The SOC of the battery 200 is initialized by using the same, and the sensor unit 120 is recalibrated.

여기서 배터리(200)의 용량은 60Ah이고, 배터리(200)의 용량에 오차를 반영하여 오차가 반영된 배터리(200)의 용량은 68Ah이다.Herein, the capacity of the battery 200 is 60 Ah, and the capacity of the battery 200 in which the error is reflected by reflecting the error in the capacity of the battery 200 is 68 Ah.

제어부(110)는 획득된 배터리(200)의 OCV를 토대로 용량이 60Ah인 배터리(200) 및 용량이 68Ah인 배터리에 대한 평균 slope 및 평균 offset을 이용하여 배터리(200)와 용량에 오차를 반영한 배터리(200)의 SOC-OCV맵을 획득할 수 있다.The controller 110 reflects an error in the battery 200 and the capacity by using the average slope and the average offset of the battery 200 having a capacity of 60 Ah and the battery having a capacity of 68 Ah based on the obtained OCV of the battery 200. An SOC-OCV map of 200 may be obtained.

즉, 제어부(110)는 최초 장착된 배터리(200)의 SOC와, 용량에 오차를 반영한 배터리(200)의 SOC를 예측하고, 예측된 각 SOC와, 배터리(200)의 충전 완료 후 산출된 전류 적산 값을 토대로 산출된 최초 장착된 배터리(200)의 SOC, 용량에 오차를 반영한 배터리(200)의 SOC를 각각 비교하며, 비교결과를 토대로 최종 배터리(200)의 용량을 예측할 수 있다.That is, the controller 110 predicts the SOC of the battery 200 initially installed, and the SOC of the battery 200 reflecting an error in capacity, and calculates each of the predicted SOCs and the current calculated after completion of the charging of the battery 200. The SOC of the battery 200 initially calculated based on the integrated value and the SOC of the battery 200 reflecting an error in the capacity may be compared, and the capacity of the final battery 200 may be estimated based on the comparison result.

예컨대, 제어부(110)는 최초 획득된 배터리(200)의 OCV를 토대로 용량이 60Ah인 배터리(200)의 평균 SOC-OCV맵을 이용할 경우 SOC를 60%로 예측할 수 있고, 용량이 68Ah인 배터리의 평균 SOC-OCV맵을 이용할 경우 SOC를 67%로 예측할 수 있다.For example, the controller 110 may predict the SOC as 60% when the average SOC-OCV map of the battery 200 having a capacity of 60 Ah is based on the OCV of the battery 200 that is initially obtained, and the battery may have a capacity of 68 Ah. Using the average SOC-OCV map, the SOC can be estimated at 67%.

또한, 계산된 전류 적산 값이 20Ah일 경우, 용량 대비 SOC를 (적산량/CNOM)*100의 식에 의해 퍼센티지로 환산할 수 있으며, 퍼센티지로 환산할 경우, 최초 장착된 배터리(200)와, 용량에 오차를 반영한 배터리(200)의 용량 대비 SOC 퍼센티지 환산값은 100-(20/60)*100 = 66%, 100-(20/68)*100 = 70% (100%에서 빼는 이유는 배터리의 충전이 완료되었다고 판단되기 때문)이고, 이 결과를 토대로 배터리의 용량을 60Ah로 예상할 경우 오차가 |60-66|=6%, 68Ah로 예상할 경우의 오차가 |67-70|=3%가 되므로, 배터리(200)의 용량을 68Ah라고 판단할 수 있다.In addition, when the calculated current integration value is 20Ah, SOC can be converted into a percentage by the formula (accumulation amount / CNOM) * 100, and when converted into a percentage, the first installed battery 200 and, The SOC percentage conversion value compared to the capacity of the battery 200 reflecting the error in capacity is 100- (20/60) * 100 = 66%, 100- (20/68) * 100 = 70% (the reason for subtracting from 100% is Is estimated to be fully charged), and based on this result, when the battery capacity is estimated to be 60 Ah, the error is | 60-66 | = 6% and the error is expected to be 68Ah is | 67-70 | = 3 %, The capacity of the battery 200 can be determined as 68 Ah.

한편, 제어부(110)는 OCV = a*SOC + b에 의하여, 최초 OCV값, 선택된 배터리(200)의 용량에 따른 SOC-OCV맵의 slope값, 전류 적산에 의해 산출된 SOC값을 토대로 새로운 offset값을 산출할 수 있다.On the other hand, the control unit 110 by the OCV = a * SOC + b, the new offset based on the initial OCV value, the slope value of the SOC-OCV map according to the capacity of the selected battery 200, the SOC value calculated by the current integration The value can be calculated.

제어부(110)는 산출된 최종 배터리(200)의 용량과 SOC-OCV맵을 저장부(130)에 저장하고, 저장된 정보를 토대로 센서부(120)의 다음 Recalibration시부터 새롭게 교체된 배터리에 대해서 정확한 SOC를 판단할 수 있다.The controller 110 stores the calculated capacity of the final battery 200 and the SOC-OCV map in the storage unit 130, and corrects the newly replaced battery from the next recalibration of the sensor unit 120 based on the stored information. The SOC can be determined.

전술한 바와 같은 방식으로 60Ah와 68Ah 이외에도 다른 용량(ex. 기준용량이 90Ah일 경우 80Ah, 90Ah, 100Ah)도 CNOM값을 판단할 수 있다.In the same manner as described above, in addition to 60Ah and 68Ah, another capacity (eg, 80Ah, 90Ah, 100Ah when the reference capacity is 90Ah) may also determine the CNOM value.

이상, 도 2를 참조하여 본 발명의 일 실시예에 따른 지능형 배터리 센서 장치를 설명하였고, 이하에서는 도 3을 참조하여 본 발명의 일 실시예에 따른 지능형 배터리 센서의 동작 방법을 설명한다. 도 3은 본 발명의 일 실시예에 따른 지능형 배터리 센서의 동작 방법을 설명하기 위한 흐름도이다.The intelligent battery sensor device according to the exemplary embodiment of the present invention has been described above with reference to FIG. 2, and the operation method of the intelligent battery sensor according to the exemplary embodiment of the present invention will be described with reference to FIG. 3. 3 is a flowchart illustrating a method of operating an intelligent battery sensor according to an embodiment of the present invention.

도 3에 도시된 바와 같이, 최초 장착된 배터리(200)의 파워 온 리셋 여부를 확인하고(S300), 판단결과, 배터리(200)가 파워 온 리셋된 경우, 배터리(200)의 안정화 상태에서 센서부(120)의 Recalibration이후 배터리(200)의 OCV를 획득한다(S301).As shown in FIG. 3, when the battery 200 is initially turned on, the controller 200 checks whether the battery 200 is initially powered on. When the battery 200 is powered on, the sensor 200 is stabilized in the stabilized state of the battery 200. After recalibration of the unit 120, an OCV of the battery 200 is obtained (S301).

획득된 OCV를 토대로 Slope을 이용하여 Offest을 결정한다(S302).Based on the obtained OCV, Offest is determined using the slope (S302).

예컨대, 획득된 배터리(200)의 OCV를 토대로 배터리(200)의 용량과 배터리(200)의 용량에 오차를 반영한 값을 60Ah, 68Ah라하며, 용량이 60Ah인 배터리(200) 및 용량이 68Ah인 배터리에 대한 평균 slope와, 평균 offset을 산출하고, 배터리(200)의 SOC와 용량에 오차를 반영한 배터리의 SOC를 획득한다.For example, a value reflecting an error in the capacity of the battery 200 and the capacity of the battery 200 based on the obtained OCV of the battery 200 is 60 Ah, 68 Ah, and the battery 200 having a capacity of 60 Ah and the capacity of 68 Ah The average slope of the battery and the average offset are calculated, and the SOC of the battery reflecting the error in the SOC and the capacity of the battery 200 is obtained.

즉, 용량이 60Ah인 배터리의 예측 SOC(Expected_SOC_60Ah)와, 용량이 68Ah인 배터리의 예측 SOC(Expected_SOC_68Ah)를 산출한다.That is, a predicted SOC (Expected_SOC_60Ah) of a battery having a capacity of 60 Ah and a predicted SOC (Expected_SOC_68Ah) of a battery having a capacity of 68 Ah are calculated.

산출된 배터리(200)의 전류 적산 량을 토대로 배터리(200)로 인가된 전압 및 전류를 감지하고(S303), 기실험으로 획득된 전압 α, 전류 β값을 토대로 일정시간 동안 감지된 전압이 기실험으로 획득된 전압 α이상, 일정시간 동안 감지된 전류가 기실험으로 획득된 전류 β이하로 흐르는지 여부를 판단한다(S304).The voltage and current applied to the battery 200 are sensed based on the calculated current integration amount of the battery 200 (S303), and the voltage detected for a predetermined time is based on the voltage α and current β values obtained by the experimental experiment. It is determined whether the current obtained by the experiment is above the voltage α, the current sensed for a predetermined time flows below the current β obtained by the experimental experiment (S304).

판단결과, 기실험으로 획득된 전압 α, 전류 β값을 토대로 일정시간 동안 감지된 전압이 기실험으로 획득된 전압 α이상, 일정시간 동안 감지된 전류가 기실험으로 획득된 전류 β이하로 흐르면, 배터리(200)의 충전이 완료된 것으로 판단하여 배터리(200)의 충전 완료 판단 플래그를 온으로 설정하고, 배터리(200)의 SOC를 100%로 설정한다(S305).As a result of the determination, when the voltage sensed for a predetermined time flows above the voltage α acquired through the experimental experiment and the current sensed for the predetermined time falls below the current β acquired through the experimental experiment, After determining that the battery 200 is fully charged, the charging completion determination flag of the battery 200 is set to on, and the SOC of the battery 200 is set to 100% (S305).

용량 대비 SOC를 퍼센티지로 환산한다(S306).The SOC is converted into a percentage of the capacity (S306).

예컨대, 계산된 전류 적산 값이 20Ah일 경우 용량 대비 SOC를 (적산량/CNOM)*100의 식에 의해 퍼센티지로 환산할 수 있으며, 환산할 경우 100-(20/60)*100 = 66%, 100-(20/68)*100 = 70% (100%에서 빼는 이유는 배터리의 충전이 완료되었다고 판단되기 때문)이다.For example, when the calculated current integration value is 20 Ah, SOC can be converted into a percentage by the formula (Integration amount / CNOM) * 100, 100- (20/60) * 100 = 66%, 100- (20/68) * 100 = 70% (minus 100% is because the battery is determined to be fully charged).

최초 장착된 배터리(200)의 SOC와 용량에 오차를 반영한 배터리의 SOC를 획득하고, 획득된 예측 SOC값과, 배터리(200)의 충전 완료 후 산출된 전류 적산 값을 토대로 산출한 SOC값을 비교한다(S307).The SOC of the battery 200 first installed and the SOC of the battery reflecting the error in capacity are obtained, and the predicted SOC value obtained is compared with the SOC value calculated based on the current integration value calculated after the battery 200 is fully charged. (S307).

예컨대, |Expected_SOC_60Ah-[100-(적산전류량/60)*100]|이|Expected_SOC_68Ah-[100-(적산전류량/68)*100]|보다 작거나 같은지 여부를 판단한다.For example, it is determined whether | Expected_SOC_60Ah- [100- (accumulated current amount / 60) * 100] | is less than or equal to | Expected_SOC_68Ah- [100- (accumulated current amount / 68) * 100] |.

판단결과, |Expected_SOC_60Ah-[100-(적산전류량/60)*100]|이|Expected_SOC_68Ah-[100-(적산전류량/68)*100]|보다 작거나 같을 경우, 배터리(200)의 용량을 60으로 설정하고(S308), |Expected_SOC_60Ah-[100-(적산전류량/60)*100]|이|Expected_SOC_68Ah-[100-(적산전류량/68)*100]|보다 클 경우, 배터리의 용량을 68로 설정한다(S309). As a result, when | Expected_SOC_60Ah- [100- (accumulated current amount / 60) * 100] | is less than or equal to | Expected_SOC_68Ah- [100- (accumulated current amount / 68) * 100] |, the capacity of the battery 200 is increased by 60. (S308) and | Expected_SOC_60Ah- [100- (accumulated current / 60) * 100] | is greater than | Expected_SOC_68Ah- [100- (accumulated current / 68) * 100] |, the battery capacity is 68. It is set (S309).

배터리 용량인식 플래그를 온으로 설정하고(S310), 센서부(120)의 Recalibration시 산출된 Slope및 Offset을 이용하여 OCV맵을 적용한다(S311).The battery capacity recognition flag is set to ON (S310), and the OCV map is applied using the slope and offset calculated during the recalibration of the sensor unit 120 (S311).

이상 바람직한 실시예와 첨부도면을 참조하여 본 발명의 구성에 관해 구체적으로 설명하였으나, 이는 예시에 불과한 것으로 본 발명의 기술적 사상을 벗어나지 않는 범주내에서 여러 가지 변형이 가능함은 물론이다. 그러므로 본 발명의 범위는 설명된 실시예에 국한되어 정해져서는 안되며 후술하는 특허청구의 범위뿐만 아니라 이 특허청구의 범위와 균등한 것들에 의해 정해져야 한다.
Although the configuration of the present invention has been described in detail with reference to the preferred embodiments and the accompanying drawings, this is merely an example, and various modifications are possible within the scope without departing from the spirit of the present invention. Therefore, the scope of the present invention should not be limited to the described embodiments, but should be defined not only by the scope of the following claims, but also by the equivalents of the claims.

100 : 지능형 배터리 센서 장치 110 : 제어부
120 : 센서부 130 : 저장부
200 : 배터리100: intelligent battery sensor device 110: control unit
120: sensor unit 130: storage unit
200: battery

Claims (6)

차량에 배터리가 장착되면 장착된 상기 배터리로부터 전압, 전류 및 온도 정보를 감지하는 센서부; 및
상기 배터리의 예측 SOC와 상기 배터리의 충전이 완료될 때까지 상기 센서부에 의해 감지된 전류 적산값을 토대로 상기 배터리의 용량 대비 SOC를 퍼센티지로 환산한 SOC 사이의 차이에 대한 절대값과, 용량에 특정 오차를 반영한 상기 배터리의 예측 SOC와 상기 배터리의 충전이 완료될 때까지 상기 센서부에 의해 감지된 전류 적산값을 토대로 상기 용량에 특정 오차를 반영한 상기 배터리의 용량 대비 SOC를 퍼센티지로 환산한 SOC 사이의 차이에 대한 절대값을 비교하며, 비교결과를 토대로 상기 배터리의 용량을 판단하며, 판단된 상기 배터리의 용량에 따라 상기 배터리의 SOC를 산출하는 제어부
를 포함하는 지능형 배터리 센서 장치.A sensor unit configured to detect voltage, current, and temperature information from the battery when the battery is mounted in the vehicle; And
The absolute value and the capacity of the difference between the estimated SOC of the battery and the SOC converted into a percentage of the capacity of the battery based on the current integration value detected by the sensor until the battery is completed, the capacity SOC which converts the SOC to a percentage of the capacity of the battery reflecting a specific error in the capacity based on the estimated SOC of the battery reflecting a specific error and the current integration value sensed by the sensor unit until the battery is fully charged. A control unit for comparing the absolute value of the difference between, determining the capacity of the battery based on the comparison result, and calculates the SOC of the battery according to the determined capacity of the battery
Intelligent battery sensor device comprising a. 제1항에 있어서,
상기 제어부는 상기 배터리가 파워 온 리셋된 경우, 상기 배터리의 안정화 상태에서 상기 센서부의 Recalibration이후 상기 배터리의 OCV를 획득하고, 획득된 상기 배터리의 OCV를 토대로 상기 배터리의 예측 SOC 및 상기 용량에 특정 오차가 반영된 상기 배터리의 예측 SOC를 예측하는 것
인 지능형 배터리 센서 장치.The method of claim 1,
When the battery is powered on and reset, the controller acquires the OCV of the battery after the recalibration of the sensor unit in the stabilized state of the battery, and based on the acquired OCV of the battery, a specific error in the predicted SOC and the capacity of the battery. To predict the predicted SOC of the battery reflected
Intelligent battery sensor device. 삭제delete 차량에 장착된 배터리의 SOC 및 용량에 특정 오차가 반영된 상기 배터리의 SOC를 예측하는 단계;
상기 배터리의 충전이 완료될 때까지 전류 적산 값을 산출하는 단계;
상기 배터리의 예측 SOC와 상기 산출된 전류 적산 값을 토대로 상기 배터리의 용량 대비 SOC를 퍼센티지로 환산한 SOC 사이의 차이에 대한 절대값과, 용량에 특정 오차를 반영한 상기 배터리의 예측 SOC와 상기 산출된 전류 적산 값을 토대로 상기 용량에 특정 오차를 반영한 상기 배터리의 용량 대비 SOC를 퍼센티지로 환산한 SOC 사이의 차이에 대한 절대값을 비교하는 단계; 및
비교결과를 토대로 상기 배터리의 용량을 판단하여 판단된 상기 배터리의 용량에 따라 상기 배터리의 SOC를 산출하는 단계
를 포함하는 지능형 배터리 센서 장치의 동작 방법.Predicting the SOC of the battery in which a specific error is reflected in the SOC and the capacity of the battery mounted in the vehicle;
Calculating a current integration value until charging of the battery is completed;
The absolute value of the difference between the SOC of the battery and the SOC converted into a percentage of the capacity of the battery based on the calculated current integration value and the calculated current integration value, the estimated SOC of the battery reflecting a specific error in the capacity and the calculated Comparing an absolute value of a difference between the capacity of the battery which reflects a specific error in the capacity based on the current integration value and the difference between the SOC converted in percentages; And
Calculating the SOC of the battery according to the determined capacity of the battery based on the determination of the capacity of the battery based on a comparison result;
Method of operation of intelligent battery sensor device comprising a. 제4항에 있어서, 상기 예측하는 단계는,
상기 배터리가 파워 온 리셋된 경우, 상기 배터리의 안정화 상태에서 센서부의 Recalibration이후 상기 배터리의 OCV를 획득하는 단계; 및
획득된 상기 배터리의 OCV를 토대로 장착된 상기 배터리의 SOC 및 상기 용량에 특정 오차가 반영된 상기 배터리의 SOC를 예측하는 단계를 포함하는 것
인 지능형 배터리 센서 장치의 동작 방법.

The method of claim 4, wherein the predicting comprises:
Acquiring an OCV of the battery after recalibration of a sensor unit when the battery is powered on and reset; And
Predicting the SOC of the battery mounted on the basis of the obtained OCV of the battery and the SOC of the battery whose specific error is reflected in the capacity;
Operation method of intelligent battery sensor device.

삭제delete
KR1020130116455A 2013-09-30 2013-09-30 Intelligent Battery Sensor Apparatus and Method thereof KR102079038B1 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
KR1020130116455A KR102079038B1 (en) 2013-09-30 2013-09-30 Intelligent Battery Sensor Apparatus and Method thereof
CN201410424325.2A CN104518247B (en) 2013-09-30 2014-08-26 Intelligent battery sensor apparatus and working method thereof

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
KR1020130116455A KR102079038B1 (en) 2013-09-30 2013-09-30 Intelligent Battery Sensor Apparatus and Method thereof

Publications (2)

Publication Number Publication Date
KR20150037144A KR20150037144A (en) 2015-04-08
KR102079038B1 true KR102079038B1 (en) 2020-02-19

Family

ID=52793205

Family Applications (1)

Application Number Title Priority Date Filing Date
KR1020130116455A KR102079038B1 (en) 2013-09-30 2013-09-30 Intelligent Battery Sensor Apparatus and Method thereof

Country Status (2)

Country Link
KR (1) KR102079038B1 (en)
CN (1) CN104518247B (en)

Families Citing this family (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102016223154A1 (en) 2016-11-23 2018-05-24 Robert Bosch Gmbh battery unit
US20190308630A1 (en) * 2018-04-10 2019-10-10 GM Global Technology Operations LLC Battery state estimation based on open circuit voltage and calibrated data
DE102019219427A1 (en) * 2019-12-12 2021-06-17 Robert Bosch Gmbh Method for monitoring an energy store in a motor vehicle
CN113594560B (en) * 2020-04-30 2024-03-19 宁德时代新能源科技股份有限公司 Battery module, battery pack and device
CN112397798B (en) * 2020-11-13 2022-04-26 上汽大众汽车有限公司 Power battery management system and matching method

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2012058028A (en) 2010-09-07 2012-03-22 Calsonic Kansei Corp Battery capacity calculation apparatus and battery capacity calculation method

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR100804698B1 (en) * 2006-06-26 2008-02-18 삼성에스디아이 주식회사 The method of assuming the state of charge of the battery, battery management system using the method and the driving method of the battery management system using the method
KR100805116B1 (en) * 2006-09-08 2008-02-21 삼성에스디아이 주식회사 Battery management system and driving method thereof
US8264202B2 (en) * 2008-10-10 2012-09-11 Deeya Energy, Inc. Method and apparatus for determining state of charge of a battery using an open-circuit voltage
US8405356B2 (en) * 2010-03-05 2013-03-26 Panasonic Corporation Full charge capacity value correction circuit, battery pack, and charging system
KR20130017740A (en) * 2011-08-11 2013-02-20 현대자동차주식회사 Method for estimating state of charge in battery
KR101863036B1 (en) * 2011-11-30 2018-06-01 주식회사 실리콘웍스 Method for estimating the state of charge of battery and battery management system
KR101486470B1 (en) * 2012-03-16 2015-01-26 주식회사 엘지화학 Apparatus and method for estimating battery state

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2012058028A (en) 2010-09-07 2012-03-22 Calsonic Kansei Corp Battery capacity calculation apparatus and battery capacity calculation method

Also Published As

Publication number Publication date
KR20150037144A (en) 2015-04-08
CN104518247B (en) 2017-04-12
CN104518247A (en) 2015-04-15

Similar Documents

Publication Publication Date Title
US10386420B2 (en) Secondary battery degradation determination method and secondary battery degradation determination device
KR102066702B1 (en) Battery management apparatus and soc calibrating method using the same
JP6477733B2 (en) Charge state estimation device
KR102080632B1 (en) Battery management system and its operating method
KR101500128B1 (en) Degradation estimation method for high voltage battery
KR102079038B1 (en) Intelligent Battery Sensor Apparatus and Method thereof
CN103176135B (en) battery aging evaluation method
US8779729B2 (en) Electric storage device monitor
JP5282789B2 (en) Battery capacity detection device for lithium ion secondary battery
US10286806B2 (en) Electrical storage system
JP6234946B2 (en) Battery state estimation device
US10261136B2 (en) Battery degradation degree estimation device and battery degradation degree estimation method
KR102171096B1 (en) Method and device to estimate battery lifetime during driving of electrical vehicle
JP6183242B2 (en) Power storage system
US7880442B2 (en) Charging control device for a storage battery
KR20160004077A (en) Method and apparatus for estimating state of battery
US20150362557A1 (en) State detecting method and state detecting device of secondary battery
US9910100B2 (en) Battery characteristic determining device for a vehicle
US20090248334A1 (en) Method for estimating the charge of a motor vehicle battery
WO2010140233A1 (en) Battery state of charge calculation device
JP6525648B2 (en) Battery capacity estimation system, battery capacity estimation method and battery capacity estimation program
US20170227607A1 (en) Schemes capable of efficiently and accurately estimating and/or predicting available battery capacity and battery aging factor
JP5313215B2 (en) Battery charge rate estimation device
JP5928385B2 (en) Power storage system
KR102588928B1 (en) Method for estimating degradation of battery for vehicle

Legal Events

Date Code Title Description
A201 Request for examination
E902 Notification of reason for refusal
E701 Decision to grant or registration of patent right
GRNT Written decision to grant