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1. WO2021040236 - ESS BATTERY STATE DIAGNOSIS AND LIFESPAN PREDICTION DEVICE AND METHOD

Publication Number WO/2021/040236
Publication Date 04.03.2021
International Application No. PCT/KR2020/009624
International Filing Date 22.07.2020
IPC
G01R 31/392 2019.01
GPHYSICS
01MEASURING; TESTING
RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
31Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
36Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge
392Determining battery ageing or deterioration, e.g. state of health
G01R 31/3842 2019.01
GPHYSICS
01MEASURING; TESTING
RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
31Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
36Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge
382Arrangements for monitoring battery or accumulator variables, e.g. SoC
3842combining voltage and current measurements
G01R 31/396 2019.01
GPHYSICS
01MEASURING; TESTING
RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
31Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
36Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge
396Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
G06N 3/08 2006.01
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
08Learning methods
CPC
G01R 31/3842
GPHYSICS
01MEASURING; TESTING
RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
31Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
36Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
382Arrangements for monitoring battery or accumulator variables, e.g. SoC
3842combining voltage and current measurements
G01R 31/392
GPHYSICS
01MEASURING; TESTING
RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
31Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
36Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
392Determining battery ageing or deterioration, e.g. state of health
G01R 31/396
GPHYSICS
01MEASURING; TESTING
RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
31Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
36Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
396Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
G06N 3/08
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
08Learning methods
Applicants
  • 오토시맨틱스 주식회사 AUTOSEMANTICS, INC. [KR]/[KR]
Inventors
  • 정병철 CHONG, Byong Chol
  • 오상엽 OH, Sang Yeop
  • 정태호 JUNG, Tae Ho
Agents
  • 이철희 LEE, Chulhee
Priority Data
10-2019-010460626.08.2019KR
10-2020-008936620.07.2020KR
Publication Language Korean (KO)
Filing Language Korean (KO)
Designated States
Title
(EN) ESS BATTERY STATE DIAGNOSIS AND LIFESPAN PREDICTION DEVICE AND METHOD
(FR) DISPOSITIF ET PROCÉDÉ DE PRÉDICTION DE DURÉE DE VIE ET DE DIAGNOSTIC D'ÉTAT DE BATTERIE DE SYSTEME ESS
(KO) ESS 배터리의 상태진단 및 수명예측을 위한 장치 및 방법
Abstract
(EN)
The purpose of the present embodiment is to provide a battery state diagnosis and lifespan prediction device and method, capable of helping in the stable operation of an energy storage system (ESS) by carrying out state diagnosis and lifespan prediction of a battery contained in the ESS by using a diagnosis prediction model on the basis of data on the state of the battery. Here, the diagnosis prediction model is implemented by a deep learning-based neural network, and parameters of the diagnosis prediction model are updated using parameters received from a server.
(FR)
La présente invention a pour objet, selon le mode de réalisation, de fournir un dispositif et un procédé de prédiction de durée de vie et de diagnostic d'état de batterie, qui peuvent aider à l'opération stable d'un système de stockage d'énergie (ESS) en effectuant un diagnostic d'état et une prédiction de durée de vie d'une batterie contenue dans le système ESS en utilisant un modèle de prédiction de diagnostic sur la base de données sur l'état de la batterie. Ici, le modèle de prédiction de diagnostic est mis en œuvre par un réseau neuronal basé sur un apprentissage profond et des paramètres du modèle de prédiction de diagnostic sont mis à jour à l'aide de paramètres reçus d'un serveur.
(KO)
본 실시예는, ESS(Energy Storage System)에 포함된 배터리의 상태에 대한 데이터를 기반으로 진단예측 모델을 이용하여 배터리의 상태진단 및 수명예측을 수행함으로써 ESS의 안정적인 동작에 도움을 줄 수 있는 배터리 상태진단 및 수명예측을 위한 장치와 방법을 제공하는 데 목적이 있다. 여기서, 진단예측 모델은 딥러닝 기반의 신경망으로 구현되며, 서버로부터 전달받은 파라미터를 이용하여 진단예측 모델의 파라미터가 업데이트된다.
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