CN115443573A - 剩余容量推定装置、模型生成装置、剩余容量推定方法、模型生成方法以及程序 - Google Patents

剩余容量推定装置、模型生成装置、剩余容量推定方法、模型生成方法以及程序 Download PDF

Info

Publication number
CN115443573A
CN115443573A CN202180029104.3A CN202180029104A CN115443573A CN 115443573 A CN115443573 A CN 115443573A CN 202180029104 A CN202180029104 A CN 202180029104A CN 115443573 A CN115443573 A CN 115443573A
Authority
CN
China
Prior art keywords
data
remaining capacity
model
training
storage battery
Prior art date
Legal status (The legal status 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 status listed.)
Withdrawn
Application number
CN202180029104.3A
Other languages
English (en)
Chinese (zh)
Inventor
岛胁秀德
陈九廷
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
AESC Japan Ltd
Original Assignee
Envision AESC Japan Ltd
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 Envision AESC Japan Ltd filed Critical Envision AESC Japan Ltd
Publication of CN115443573A publication Critical patent/CN115443573A/zh
Withdrawn legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
    • 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]
    • G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
    • 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
    • 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]
    • G01R31/385—Arrangements for measuring battery or accumulator variables
    • G01R31/387—Determining ampere-hour charge capacity or SoC
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/09—Supervised learning
    • 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
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or discharging batteries or for supplying loads from batteries
    • H02J7/80—Circuit arrangements for charging or discharging batteries or for supplying loads from batteries including monitoring or indicating arrangements
    • 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
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or discharging batteries or for supplying loads from batteries
    • H02J7/80—Circuit arrangements for charging or discharging batteries or for supplying loads from batteries including monitoring or indicating arrangements
    • H02J7/82—Control of state of charge [SOC]
    • 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

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Artificial Intelligence (AREA)
  • Software Systems (AREA)
  • Health & Medical Sciences (AREA)
  • Evolutionary Computation (AREA)
  • Power Engineering (AREA)
  • Theoretical Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Medical Informatics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Biomedical Technology (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Mathematical Physics (AREA)
  • General Health & Medical Sciences (AREA)
  • Data Mining & Analysis (AREA)
  • Computational Linguistics (AREA)
  • Biophysics (AREA)
  • Molecular Biology (AREA)
  • Manufacturing & Machinery (AREA)
  • Chemical & Material Sciences (AREA)
  • Chemical Kinetics & Catalysis (AREA)
  • Electrochemistry (AREA)
  • General Chemical & Material Sciences (AREA)
  • Secondary Cells (AREA)
  • Tests Of Electric Status Of Batteries (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)
CN202180029104.3A 2020-04-17 2021-04-12 剩余容量推定装置、模型生成装置、剩余容量推定方法、模型生成方法以及程序 Withdrawn CN115443573A (zh)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
JP2020073844A JP2021170511A (ja) 2020-04-17 2020-04-17 残容量推定装置、モデル生成装置、残容量推定方法、モデル生成方法、及びプログラム
JP2020-073844 2020-04-17
PCT/JP2021/015145 WO2021210526A1 (ja) 2020-04-17 2021-04-12 残容量推定装置、モデル生成装置、残容量推定方法、モデル生成方法、及びプログラム

Publications (1)

Publication Number Publication Date
CN115443573A true CN115443573A (zh) 2022-12-06

Family

ID=78084785

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202180029104.3A Withdrawn CN115443573A (zh) 2020-04-17 2021-04-12 剩余容量推定装置、模型生成装置、剩余容量推定方法、模型生成方法以及程序

Country Status (5)

Country Link
US (1) US12443152B2 (cg-RX-API-DMAC10.html)
EP (1) EP4138173A4 (cg-RX-API-DMAC10.html)
JP (1) JP2021170511A (cg-RX-API-DMAC10.html)
CN (1) CN115443573A (cg-RX-API-DMAC10.html)
WO (1) WO2021210526A1 (cg-RX-API-DMAC10.html)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20240097469A1 (en) * 2022-09-21 2024-03-21 Hong Kong Applied Science And Technology Research Institute Co., Ltd. System and method for on-site determination of charging current for a battery
WO2024105837A1 (ja) * 2022-11-17 2024-05-23 恒林日本株式会社 機械学習モデル生成装置、及び蓄電池の特性値算出装置

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2010048759A (ja) * 2008-08-25 2010-03-04 Nippon Telegr & Teleph Corp <Ntt> 残容量推定方法および残容量推定装置
US20160202324A1 (en) * 2013-09-11 2016-07-14 Commissariat A L'energie Ato Mique Et Aux Energies Alternatives Method, device and system for estimating the charge state of a battery
US20180095140A1 (en) * 2016-10-05 2018-04-05 Samsung Electronics Co., Ltd. Battery state estimation apparatus and method
WO2019017991A1 (en) * 2017-07-21 2019-01-24 Quantumscape Corporation PREDICTIVE MODEL FOR ESTIMATING BATTERY CONDITIONS
US20190157891A1 (en) * 2017-11-20 2019-05-23 The Trustees Of Columbia University In The City Of New York Neural-network state-of-charge estimation

Family Cites Families (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP5366166B2 (ja) 2006-02-09 2013-12-11 株式会社デンソー 二次電池の状態量演算方式
JP2008232758A (ja) 2007-03-19 2008-10-02 Nippon Soken Inc 二次電池の内部状態検出装置及びニューラルネット式状態量推定装置
KR101617167B1 (ko) 2015-08-12 2016-05-03 한국수력원자력 주식회사 측면 배출게이트가 구비된 플라즈마 용융로
JP2019004388A (ja) * 2017-06-16 2019-01-10 株式会社半導体エネルギー研究所 情報処理装置、及び表示方法
CN111868540A (zh) 2018-03-20 2020-10-30 株式会社杰士汤浅国际 劣化估计装置、计算机程序以及劣化估计方法
EP3770619B1 (en) 2018-03-20 2023-10-25 GS Yuasa International Ltd. Degradation estimating device and degradation estimating method
TWI682325B (zh) * 2018-11-20 2020-01-11 新唐科技股份有限公司 辨識系統及辨識方法
CN111220921A (zh) * 2020-01-08 2020-06-02 重庆邮电大学 基于改进卷积-长短时记忆神经网络的锂电池容量估算方法

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2010048759A (ja) * 2008-08-25 2010-03-04 Nippon Telegr & Teleph Corp <Ntt> 残容量推定方法および残容量推定装置
US20160202324A1 (en) * 2013-09-11 2016-07-14 Commissariat A L'energie Ato Mique Et Aux Energies Alternatives Method, device and system for estimating the charge state of a battery
US20180095140A1 (en) * 2016-10-05 2018-04-05 Samsung Electronics Co., Ltd. Battery state estimation apparatus and method
WO2019017991A1 (en) * 2017-07-21 2019-01-24 Quantumscape Corporation PREDICTIVE MODEL FOR ESTIMATING BATTERY CONDITIONS
US20190157891A1 (en) * 2017-11-20 2019-05-23 The Trustees Of Columbia University In The City Of New York Neural-network state-of-charge estimation

Also Published As

Publication number Publication date
WO2021210526A1 (ja) 2021-10-21
US12443152B2 (en) 2025-10-14
EP4138173A4 (en) 2023-10-04
US20230221683A1 (en) 2023-07-13
JP2021170511A (ja) 2021-10-28
EP4138173A1 (en) 2023-02-22

Similar Documents

Publication Publication Date Title
CN115698738A (zh) 劣化推定装置、模型生成装置、劣化推定方法、模型生成方法及程序
EP3748380B1 (en) Battery capacity prediction system using charge and discharge cycles of a battery to predict capacity variations, and associated method
Ghanem Hybrid stochastic finite elements and generalized Monte Carlo simulation
US10146248B2 (en) Model calculation unit, control unit and method for calibrating a data-based function model
JP2016536605A (ja) 電池の充電状態を推定するための方法、装置およびシステム
CN102270302A (zh) 一种基于灰色支持向量机的多应力加速寿命试验预测方法
US20240086598A1 (en) Transforming a model in a first language to a surrogate in a second language for simulation
CN112733275A (zh) 基于半监督学习的卫星组件热布局温度场预测方法
CN105989421B (zh) 用于通过组合实验和数字数据预测时间相关现象的方法和系统
US12443152B2 (en) Remaining capacity estimation apparatus, model generation apparatus, and non-transitory computer-readable medium
CN119224623A (zh) 一种储能电池寿命评价方法及相关装置
JP2015224927A (ja) 蓄電残量推定装置、蓄電池の蓄電残量を推定する方法、及びコンピュータプログラム
CN114441969A (zh) 电池荷电状态估算方法及装置
CN118395802A (zh) 电机温度应力场代理模型构建方法、装置、设备及介质
US20150339419A1 (en) Efficient power grid analysis on multiple cpu cores with states elimination
WO2022102532A1 (ja) データ処理装置、モデル生成装置、データ処理方法、モデル生成方法、及びプログラム
JP2006133994A (ja) 解析装置、解析プログラム、および解析プログラムを記録したコンピュータ読取可能な記録媒体
CN105608237B (zh) 一种电路版图后仿真阶段的快速波形预测方法
JP2011237989A (ja) 半導体集積回路の設計装置、その設計方法、及びその設計プログラム
CN115116553B (zh) 分子的参数配置方法、装置、介质及电子装置
WO2020054599A1 (ja) モデル生成装置、予測装置、モデル生成方法、予測方法、及びプログラム
CN103837772A (zh) 一种基于加速寿命试验的低功耗采集系统寿命评估方法
WO2022075215A1 (ja) データ処理システム、モデル生成装置、データ処理方法、モデル生成方法、及びプログラム
EP4545990A1 (en) Method and system for predicting sohc for electric vehicle (ev)
JP2004102831A (ja) パラメータ推定方法、データ予測方法、パラメータ推定装置、データ予測装置、コンピュータプログラム、及び記録媒体

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
WW01 Invention patent application withdrawn after publication
WW01 Invention patent application withdrawn after publication

Application publication date: 20221206