WO2019006995A1 - Système de prédiction intelligent du soc d'une batterie d'alimentation de véhicule électrique - Google Patents

Système de prédiction intelligent du soc d'une batterie d'alimentation de véhicule électrique Download PDF

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Publication number
WO2019006995A1
WO2019006995A1 PCT/CN2017/116819 CN2017116819W WO2019006995A1 WO 2019006995 A1 WO2019006995 A1 WO 2019006995A1 CN 2017116819 W CN2017116819 W CN 2017116819W WO 2019006995 A1 WO2019006995 A1 WO 2019006995A1
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WO
WIPO (PCT)
Prior art keywords
battery
prediction
model
neural network
soc
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PCT/CN2017/116819
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English (en)
Chinese (zh)
Inventor
马从国
王业琴
王建国
陈亚娟
杨玉东
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淮阴工学院
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Application filed by 淮阴工学院 filed Critical 淮阴工学院
Publication of WO2019006995A1 publication Critical patent/WO2019006995A1/fr

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    • 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
    • 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
    • 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
    • G01R31/36—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
    • G01R31/388—Determining ampere-hour charge capacity or SoC involving voltage measurements
    • 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
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/70—Energy storage systems for electromobility, e.g. batteries

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Sustainable Development (AREA)
  • Sustainable Energy (AREA)
  • Power Engineering (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Secondary Cells (AREA)

Abstract

La présente invention concerne un système de prédiction intelligent du SOC d'une batterie d'alimentation d'un véhicule électrique, le système de prédiction intelligent comprenant une plateforme de collecte de paramètres de batterie et un système de prédiction de SOC de batterie, la plateforme de collecte de paramètres de batterie étant utilisée pour collecter des paramètres en temps réel, tels que la tension, le courant et la température, d'un bloc-batterie d'alimentation de véhicule et une température ambiante; et le système de prédiction de SOC de batterie prédit, grâce aux paramètres collectés en temps réel, une valeur de SOC de batterie. Le SOC d'une batterie est un système en temps réel qui est non linéaire, retardé dans le temps, couplé à plusieurs variables et complexe, avec des demandes élevées en performances en temps réel. Le système de prédiction intelligent résout efficacement le problème selon lequel il est difficile pour un dispositif de prédiction classique d'obtenir un effet idéal de précision de prédiction de SOC d'une batterie.
PCT/CN2017/116819 2017-07-07 2017-12-18 Système de prédiction intelligent du soc d'une batterie d'alimentation de véhicule électrique WO2019006995A1 (fr)

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Application Number Priority Date Filing Date Title
CN201710548650.3A CN107436409B (zh) 2017-07-07 2017-07-07 一种电动汽车动力电池soc智能预测装置
CN201710548650.3 2017-07-07

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WO2019006995A1 true WO2019006995A1 (fr) 2019-01-10

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WO (1) WO2019006995A1 (fr)

Cited By (1)

* Cited by examiner, † Cited by third party
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US11498450B2 (en) * 2019-05-21 2022-11-15 Rolls-Royce Plc Forecast of electric vehicle state of charge and energy storage capacity

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CN107436409B (zh) * 2017-07-07 2019-12-31 淮阴工学院 一种电动汽车动力电池soc智能预测装置
CN108445410B (zh) * 2018-04-02 2021-02-26 国家计算机网络与信息安全管理中心 一种监测蓄电池组运行状态的方法及装置
CN108226809A (zh) * 2018-04-13 2018-06-29 淮阴工学院 一种多模型并用的电池soc估算方法
CN111301222B (zh) * 2020-02-17 2021-07-16 北京嘀嘀无限科技发展有限公司 车辆电芯电压下降预警方法、电子设备及存储介质
CN111695301A (zh) * 2020-06-16 2020-09-22 中国科学院深圳先进技术研究院 电池电荷状态的预测方法及预测装置、存储介质、设备
CN112083346B (zh) * 2020-08-03 2021-11-09 山东大学 基于lstm的并联电池组内部电流分布估计方法及系统
CN114692494A (zh) * 2022-03-17 2022-07-01 广东工业大学 一种锂电池温度场在线建模方法及系统

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