WO2023155220A1 - Procédé et appareil d'optimisation de sop de système de stockage d'énergie basés sur des données en nuage - Google Patents

Procédé et appareil d'optimisation de sop de système de stockage d'énergie basés sur des données en nuage Download PDF

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WO2023155220A1
WO2023155220A1 PCT/CN2022/077418 CN2022077418W WO2023155220A1 WO 2023155220 A1 WO2023155220 A1 WO 2023155220A1 CN 2022077418 W CN2022077418 W CN 2022077418W WO 2023155220 A1 WO2023155220 A1 WO 2023155220A1
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sop
value
single cell
management system
battery management
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PCT/CN2022/077418
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English (en)
Chinese (zh)
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张昉昀
张清芳
宋超
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福建时代星云科技有限公司
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Publication of WO2023155220A1 publication Critical patent/WO2023155220A1/fr

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H04L67/1097—Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks

Definitions

  • the invention relates to the technical field of high-speed communication and cloud storage, in particular to a cloud data-based SOP optimization method and device for an energy storage system.
  • the SOP of the existing energy storage system is calculated based on the temperature, cell voltage and SOH collected in real time by the BMS, combined with the ex-factory SOP map table (factory SOP value record table) provided by the cell factory.
  • the main defect is: on-board storage
  • the onboard BMS data on the main control board of the energy system is limited, and it is impossible to accurately predict the aging difference caused by the individual differences of the batteries, which will lead to deviations in the calculation of SOP, potential overcharge and overdischarge failure conditions, and affect the life of the batteries. and other security risks.
  • the technical problem to be solved by the present invention is to provide an energy storage system SOP optimization method and device based on cloud data, which can optimize the SOP differential calculation of each battery cell.
  • the technical solution adopted by the present invention is: a SOP optimization method for an energy storage system based on cloud data, comprising steps:
  • the battery management system collects real-time data of each single battery cell in the battery pack in real time and uploads it to the cloud platform.
  • the real-time data includes the current current, voltage, static pressure difference, temperature, and SOC value of the single battery cell and SOH value;
  • the battery management system calculates the SOP value of the single cell according to the real-time data
  • the cloud platform judges whether to optimize the SOP value of the single cell based on the historical data of the single cell uploaded by the battery management system.
  • An energy storage system SOP optimization device based on cloud data including a battery management system and a cloud platform;
  • the battery management system is used to collect real-time data of each single cell in the battery pack in real time, calculate the SOP value of the single cell according to the real-time data, and upload the real-time data to the cloud platform, the
  • the real-time data includes the current current, voltage, static pressure difference, temperature, SOC value and SOH value of the single cell;
  • the cloud platform is used to determine whether to optimize the SOP value of the single battery based on the historical data of the single battery uploaded by the battery management system.
  • the beneficial effect of the present invention is that: the present invention provides an energy storage system SOP optimization method and device based on cloud data, and the battery management system of the energy storage system collects the current, voltage, static voltage Calculate the SOP value of each single cell based on real-time data such as difference, temperature, SOC value, and SOH value, and evaluate whether it is necessary to optimize the calculation of the SOP value based on the historical data of the single cell stored in the cloud, so as to realize the The SOP differential calculation of the battery can accurately evaluate the aging difference of each single battery in the energy storage system.
  • FIG. 1 is an overall flow chart of an energy storage system SOP optimization method based on cloud data according to an embodiment of the present invention
  • Fig. 2 is a schematic block diagram of an energy storage system in an energy storage system SOP optimization method based on cloud data according to an embodiment of the present invention
  • FIG. 3 is a specific flow chart of an energy storage system SOP optimization method based on cloud data according to an embodiment of the present invention
  • Fig. 4 is a SOP optimization calculation judgment process in a cloud data-based energy storage system SOP optimization method according to an embodiment of the present invention
  • Fig. 5 is another SOP optimization calculation judgment process in another energy storage system SOP optimization method based on cloud data according to an embodiment of the present invention
  • FIG. 6 is a schematic structural diagram of an energy storage system SOP optimization device based on cloud data according to an embodiment of the present invention.
  • An energy storage system SOP optimization device based on cloud data 2. Battery management system; 3. Cloud platform.
  • BMS Battery Management System, battery management system
  • SOC State Of Charge, state of charge
  • SOH State Of Health, battery health status
  • SOP State Of Power, charge and discharge power state
  • MQTT Message Queuing Telemetry Transport, Message Queuing Telemetry Transport Protocol
  • TCP/IP Transmission Control Protocol/Internet Protocol, Transmission Control Protocol/Internet Protocol.
  • a cloud data-based energy storage system SOP optimization method including steps:
  • the battery management system collects real-time data of each single battery cell in the battery pack in real time and uploads it to the cloud platform.
  • the real-time data includes the current current, voltage, static pressure difference, temperature, and SOC value of the single battery cell and SOH value;
  • the battery management system calculates the SOP value of the single cell according to the real-time data
  • the cloud platform judges whether to optimize the SOP value of the single cell based on the historical data of the single cell uploaded by the battery management system.
  • the beneficial effect of the present invention is that the battery management system of the energy storage system collects real-time data such as current, voltage, static pressure difference, temperature, SOC value and SOH value of each single cell in the battery pack in real time, Calculate the SOP value of each single cell, and evaluate whether it is necessary to optimize the calculation of the SOP value based on the historical data of the single cell stored in the cloud, so as to realize the differential calculation of the SOP of each single cell and achieve an accurate evaluation of energy storage The aging difference of each single cell in the system.
  • step S1 also includes the steps before:
  • the cloud platform can modify the factory SOP by remotely modifying the flag bit The corresponding SOP value in the map table, update the factory SOP map table.
  • step S2 is specifically:
  • the battery management system queries the factory SOP according to the current temperature and SOC value of the single cell According to the charging and discharging power corresponding to the single cell in the map table, query the SOP attenuation coefficient corresponding to the single cell in the factory SOP map table according to the current SOH value of the single cell, and calculate the charging and discharging power
  • the SOP value is obtained after multiplying by the SOP attenuation coefficient.
  • the SOP value (that is, the charge and discharge power) can be directly obtained from the SOC value/temperature gauge of the battery cell, but because the health state of the battery cell will be attenuated during use, that is, there is an SOP attenuation coefficient, so it is necessary to check it.
  • the charging and discharging power obtained in the table is multiplied by the SOP attenuation coefficient to ensure the accuracy of the calculated SOP value.
  • step S3 is specifically:
  • the cloud platform invokes the historical data of each single cell within a preset time period, and captures the static data within the preset time period;
  • the cloud platform calculates the change rate of the static pressure difference of each single cell in each static time period according to the static time period corresponding to the static data. If the static pressure difference changes rate is greater than the calibration threshold, the cloud platform sends an SOP remote optimization calculation command to the battery management system, otherwise there is no need to perform SOP optimization calculation on the single battery cell, and the calibration threshold is each Monthly self-discharge rate.
  • the difference of each single battery cell is judged by the change rate of static pressure difference, so as to decide whether to optimize the calculation of the SOP value of the battery cell calculated by the look-up table according to the difference, so as to ensure the accuracy of the battery cell.
  • the accuracy of the SOP optimization assessment is considered by the change rate of static pressure difference, so as to decide whether to optimize the calculation of the SOP value of the battery cell calculated by the look-up table according to the difference, so as to ensure the accuracy of the battery cell.
  • step S31 also includes:
  • the static judgment method of the static data is:
  • this time period is the resting time period.
  • the static data needs to be powered off for at least half an hour and the current is less than 1A to ensure the rationality of the static data and further ensure the accuracy of the SOP optimization evaluation of the battery.
  • step S3 is specifically:
  • the battery management system uploads the calculated SOP value of the single cell to the cloud platform;
  • the cloud platform calculates another SOP value based on the stored historical data, and compares it with the SOP value uploaded by the battery management system. If the difference between the two is greater than the 5% of the SOP value calculated by the cloud platform, the cloud platform sends an SOP remote optimization calculation instruction to the battery management system, and the battery management system will deliver the SOP
  • the corresponding SOP value on the map table is modified to the SOP value calculated by the cloud platform, otherwise there is no need to perform SOP optimization calculation on the single cell.
  • the SOP of the stored batteries is less, and the SOP can only be calculated by checking the value of the currently stored factory SOP map, and the SOP differential calculation for each battery cannot be achieved. Therefore, Through a large amount of historical data stored on the cloud platform, the SOP of each cell can also be calculated to obtain a more accurate SOP value. By comparing the SOP values calculated by the on-board battery management system and the cloud platform, according to the two sets of data The difference between them determines whether to optimize the SOP value calculated onboard, which further ensures the accuracy of the SOP optimization evaluation of the battery cell.
  • step S3 it also includes the steps of:
  • the battery management system If the battery management system receives the SOP remote optimization calculation instruction sent by the cloud platform, the battery management system performs a second confirmation on the state of the single battery cell, specifically:
  • the battery management system does not receive the SOP remote optimization calculation instruction sent by the cloud platform, it directly uses the SOP value calculated in step S2 as the optimized SOP value of the single battery cell.
  • step S4 it is judged whether the current static pressure difference of the single cell is greater than the factory SOP
  • the static pressure difference corresponding to 8%SOC in the map table also includes:
  • the static pressure difference change rate of the two groups is calculated according to the two sets of static data of the single cell. If the static pressure difference change rate of the two groups is When the difference exceeds the preset monthly self-discharge rate of the single cell, perform SOP optimization calculation to obtain the optimized SOP value; otherwise, directly use the SOP value calculated in step S2 as the single cell
  • the optimized SOP value of the cell, the preset monthly self-discharge rate of the single cell is 2 ⁇ 5%.
  • the SOP power limit is to reduce the entire SOP value
  • the recalibration of the charging and discharging is that the cloud platform recalculates based on the stored historical data to obtain a new SOP value, replaces the corresponding SOP value in the factory SOP map table, regenerates a new SOP map table and sends it to the battery management system;
  • the lowering of the charge cut-off voltage is to adjust the cut-off point of the full charge voltage of the single cell
  • an energy storage system SOP optimization device based on cloud data including a battery management system and a cloud platform;
  • the battery management system is used to collect real-time data of each single cell in the battery pack in real time, calculate the SOP value of the single cell according to the real-time data, and upload the real-time data to the cloud platform, the
  • the real-time data includes the current current, voltage, static pressure difference, temperature, SOC value and SOH value of the single cell;
  • the cloud platform is used to determine whether to optimize the SOP value of the single battery based on the historical data of the single battery uploaded by the battery management system.
  • a SOP optimization device for an energy storage system based on cloud data is provided.
  • the battery management system of the system collects real-time data such as current, voltage, static pressure difference, temperature, SOC value and SOH value of each single cell in the battery pack in real time, calculates the SOP value of each single cell, and based on the cloud storage Whether it is necessary to optimize the calculation of the SOP value for the historical data evaluation of the single cell, so as to realize the differential calculation of the SOP of each single cell, and accurately evaluate the aging difference of each single cell in the energy storage system.
  • the SOP optimization method and device of an energy storage system based on cloud data provided by the present invention are suitable for evaluating the aging difference of each battery cell in the energy storage system and realizing the differential calculation of the SOP of each battery cell. The following is carried out in conjunction with specific embodiments illustrate.
  • embodiment one of the present invention is:
  • An energy storage system SOP optimization method based on cloud data includes steps:
  • the battery management system collects the real-time data of each single cell in the battery pack in real time and uploads it to the cloud platform.
  • the real-time data includes the current, voltage, static pressure difference, temperature, SOC value and SOH value of the single cell;
  • the battery management system calculates the SOP value of the single cell according to the real-time data
  • the cloud platform judges whether it is necessary to optimize the calculation of the SOP value of the single cell based on the historical data of the single cell uploaded by the battery management system.
  • the battery management system of the energy storage system collects real-time data such as the current, voltage, static pressure difference, temperature, SOC value, and SOH value of each single cell in the battery pack in real time, and calculates the current and voltage of each single cell. Based on the SOP value of the cell, and based on the historical data of the single cell stored in the cloud, it is evaluated whether it is necessary to optimize the calculation of the SOP value, so as to realize the differential calculation of the SOP of each single cell, and accurately evaluate the individual cells of the energy storage system. Core aging differences.
  • embodiment two of the present invention is:
  • the battery management system BMS and cloud platform also include a battery pack composed of individual cells, an energy management system EMS, a main control board, an AC/DC inverter PCS, a charging source and a load. Among them, the battery pack is the controlled object of this embodiment.
  • each individual cell there are also temperature sensors, current/voltage sensors, relays, and wiring harnesses set on each individual cell; the battery management system BMS According to the real-time data of the voltage, current, temperature and other real-time data collected by various sensors and other signal acquisition equipment installed on each single cell, the relevant state of the single cell, such as SOC value, SOH value, etc., will be estimated. And control each single cell to perform charging and discharging operations, and also transmit the collected real-time data to the cloud platform and the energy management system EMS through CAN or RS485 communication.
  • the former is used to store various histories of the single cell in the cloud
  • the latter is used to realize real-time monitoring of single cells;
  • the main control board is the core controller set in the energy storage system, and it is not limited to this name.
  • the main control board can receive data from each device in the energy storage system.
  • the cloud platform includes the medium for storing data, data processing, and communication protocols for communicating with the energy management system and battery management system (including but not limited to MQTT, TCP/IP protocol etc.), to realize data transmission, including uploading and sending, through sending, OTA (Over-the-Air Technology, over-the-air technology) remote refresh of each device can be realized.
  • OTA Over-the-Air Technology, over-the-air technology
  • steps before step S1 include:
  • the CAN bus is used for communication between the main control board and the battery management system BMS, then the CAN ID of the battery management system BMS is set to 0x100, and the CAN ID of the main control board is 0x200, then the BMS and the main control board Refer to Table 1 for the handshake protocol of multi-frame messages between boards:
  • the source code of the communication between the battery management system and the main control board is as follows:
  • the map table queries and calculates the SOP value, and at the same time sets the remote modification flag bit. After the SOP optimization calculation is performed, the cloud platform can modify the corresponding SOP value in the factory SOP map table through the remote modification flag bit, and update the factory SOP map table.
  • step S2 is specifically:
  • the battery management system queries the factory SOP according to the current temperature and SOC value of the single battery cell
  • the charging and discharging power corresponding to the single cell in the map table query the SOP attenuation coefficient corresponding to the single cell in the factory SOP map table according to the current SOH value of the single cell, and multiply the charging and discharging power by the SOP attenuation coefficient to get the SOP value.
  • the following table 2 is the SOP form of a certain battery based on SOC value and temperature provided by the battery factory:
  • Table 3 is the relationship table between the SOP and SOH of a certain battery provided by the battery factory:
  • the SOP value charge and discharge power
  • the SOP value can be directly obtained from the SOC value/temperature gauge of the battery cell, but because the health state of the battery cell will be attenuated during use, that is, there is an SOP attenuation coefficient, so it is necessary to The charge and discharge power obtained from the table lookup is multiplied by the SOP attenuation coefficient to ensure the accuracy of the calculated SOP value.
  • step S3 is specifically:
  • the cloud platform invokes the historical data of each single cell within a preset time period, and captures the static data within the preset time period, wherein the static judgment method of the static data is:
  • this time period is the rest period.
  • the cloud platform calculates the change rate of the static differential pressure of each single cell in each static period according to the static time period corresponding to the static data. If the static differential pressure change rate is greater than the calibration threshold, the cloud platform Send the SOP remote optimization calculation command to the battery management system, otherwise there is no need to perform SOP optimization calculation on the single cell, and the calibration threshold is the monthly self-discharge rate of the single cell.
  • the period from t1 to t2 is a static time period, if the calibration threshold is set to A according to the monthly self-discharge rate, during the period from t1 to t2 ,
  • the self-discharge rate of the battery is 2-5% per month, and the calibration threshold can be set at 3%, for example.
  • the difference of each single battery cell is judged by the change rate of the static pressure difference, so as to determine whether to optimize the SOP value of the battery cell calculated by looking up the table according to the difference, so as to ensure the optimal evaluation of the SOP of the battery cell
  • the static data needs to be powered off for at least half an hour and the current is less than 1A to ensure the rationality of the static data and further ensure the accuracy of the SOP optimization evaluation of the battery.
  • step S3 also adopts another method, as shown in Figure 5:
  • the battery management system BMS uploads the calculated SOP value of the single battery cell to the cloud platform.
  • the cloud platform calculates another SOP value based on the stored historical data, and compares it with the SOP value uploaded by the battery management system. If the difference between the two is greater than 5% of the SOP value calculated by the cloud platform , the cloud platform sends SOP remote optimization calculation instructions to the battery management system, and the battery management system will deliver the SOP The corresponding SOP value on the map table is changed to the SOP value calculated in the cloud, otherwise there is no need to perform SOP value optimization calculation for the single cell.
  • the SOP can only be calculated by checking the value of the currently stored factory SOP map, and the SOP differential calculation for each battery cell cannot be achieved. Therefore, through a large amount of historical data stored on the cloud platform, the SOP of each battery cell can also be calculated to obtain a more accurate SOP value.
  • step S3 the steps are also included:
  • the battery management system If the battery management system receives the SOP remote optimization calculation instruction sent by the cloud platform, the battery management system will perform a second confirmation on the status of the single battery cell, specifically:
  • the battery management system does not receive the SOP remote optimization calculation command sent by the cloud platform, it will directly use the SOP value calculated in step S2 as the optimized SOP value of the single battery cell.
  • the battery management system when the battery management system receives the SOP remote optimization calculation instruction issued by the cloud platform, it can first set the factory SOP The data in the map table is backed up, and the single battery cell is confirmed twice through the static pressure difference to finally decide whether to optimize the calculation of the SOP value to prevent false triggering of the SOP optimization calculation and further ensure the accuracy of the SOP optimization evaluation of the battery cell.
  • step S4 it is judged whether the current static pressure difference of the single cell is greater than the factory SOP
  • the static pressure difference corresponding to 8%SOC in the map table also includes:
  • the two sets of static pressure difference change rates are calculated according to the two sets of static data of the single cell. If the difference between the two sets of static pressure differential change rates exceeds the preset When the monthly self-discharge rate of the single cell is calculated, the SOP optimization calculation is performed to obtain the optimized SOP value; otherwise, the SOP value calculated in step S2 is directly used as the optimized SOP value of the single cell, and the preset single cell
  • the monthly self-discharge rate of the core is 2 ⁇ 5%.
  • the SOP optimization calculation is performed in the above step S4 to obtain an optimized SOP value, specifically:
  • the SOP limit power is to reduce the entire SOP value, such as setting a variable coefficient K that can be calibrated
  • the purpose is to prevent the battery from over-discharging and over-charging
  • re-calibration of charging and discharging is recalculated based on the stored historical data on the cloud platform to obtain a new SOP value, replace the corresponding SOP value in the factory SOP map table, regenerate a new SOP map table and send it to the battery management system, similar to the SOP power limit
  • step S4 it also includes:
  • the optimal calculation of the SOP value is realized through SOP power limit, charging and discharging recalibration, or lowering the charging cut-off voltage.
  • the single cells that have been optimized for the SOP value calculation are marked to ensure that the follow-up can be accurately traced. .
  • an energy storage system SOP optimization device 1 based on cloud data is provided, as shown in FIG. 6 , including a battery management system 2 and a cloud platform 3 .
  • the battery management system 2 is used to collect real-time data of each single cell in the battery pack in real time, calculate the SOP value of the single cell according to the real-time data, and upload the real-time data to the cloud platform 3.
  • the real-time data includes the single cell The current current, voltage, static pressure difference, temperature, SOC value and SOH value of the cell; the cloud platform 3 is used to judge whether the SOP of the single cell is required based on the historical data of the single cell uploaded by the battery management system 2 Values are optimized.
  • an energy storage system SOP optimization device based on cloud data is provided, and the battery of the energy storage system
  • the management system collects real-time data such as current, voltage, static pressure difference, temperature, SOC value, and SOH value of each single cell in the battery pack in real time, calculates the SOP value of each single cell, and calculates the SOP value of each single cell based on the single cell stored in the cloud. Whether it is necessary to optimize the calculation of the SOP value based on the historical data of the cell, so as to realize the differential calculation of the SOP of each single cell, and accurately evaluate the aging difference of each single cell in the energy storage system.
  • the SOP optimization method of energy storage system based on cloud data provided by the present invention has the following beneficial effects:
  • the SOP calculation logic of the onboard battery management system has completed various failure mode evaluations and response measures. Adding the SOP remote optimization calculation of the cloud platform can further protect the battery cells and reduce the chance of loss of control. ;

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  • Signal Processing (AREA)
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Abstract

Procédé et appareil d'optimisation de SOP de système de stockage d'énergie basés sur des données en nuage. Le procédé comprend les étapes suivantes : un système de gestion de batterie collecte des données en temps réel de chaque cellule unique dans un bloc-batterie en temps réel et télécharge en amont les données en temps réel vers une plateforme en nuage, les données en temps réel comprenant le courant, la tension, la différence de tension statique, la température, la valeur SOC et la valeur SOH de la cellule unique présents ; le système de gestion de batterie calcule une valeur SOP de la cellule unique selon les données en temps réel ; et sur la base de données historiques de la cellule unique qui sont téléchargées historiquement en amont par le système de gestion de batterie, la plateforme en nuage détermine si la valeur SOP de la cellule unique doit être soumise à un calcul d'optimisation. Dans le procédé, un système de gestion de batterie collecte des données en temps réel telles que le courant, la tension, la différence de tension statique, la température, une valeur SOC et une valeur SOH de chaque cellule unique dans un bloc-batterie en temps réel, et calcule une valeur SOP de chaque cellule unique, et le fait que la valeur SOP doit être soumise ou non à un calcul d'optimisation est évalué sur la base de données historiques de la cellule unique, qui sont stockées dans un nuage, de sorte que le calcul différentiel SOP de chaque cellule unique soit réalisé, ce qui permet l'évaluation précise des différences de vieillissement entre des cellules uniques d'un système de stockage d'énergie.
PCT/CN2022/077418 2022-02-16 2022-02-23 Procédé et appareil d'optimisation de sop de système de stockage d'énergie basés sur des données en nuage WO2023155220A1 (fr)

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Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115514063B (zh) * 2022-10-31 2023-09-29 淮阴工学院 一种储能电池充放电功率调节设备
CN116470623B (zh) * 2023-06-01 2023-08-29 苏州精控能源科技有限公司 大型储能系统充放电功率状态预测方法、电子设备及介质

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108258338A (zh) * 2017-12-29 2018-07-06 江苏博强新能源科技股份有限公司 电池的管理系统和方法
CN110749827A (zh) * 2019-12-02 2020-02-04 山东大学 基于云平台的智能化电池soc管理系统及方法
US20200176829A1 (en) * 2017-09-11 2020-06-04 Panasonic Intellectual Property Management Co., Ltd. Electricity storage system and management device
CN113625175A (zh) * 2021-10-11 2021-11-09 北京理工大学深圳汽车研究院(电动车辆国家工程实验室深圳研究院) 一种基于云端大数据平台的soc估算方法和系统

Family Cites Families (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110324383B (zh) * 2018-03-30 2021-09-03 比亚迪股份有限公司 云服务器、电动汽车及其中动力电池的管理系统、方法
CN108544925B (zh) * 2018-04-02 2019-10-01 北京理工大学 电池管理系统
CN109284563B (zh) * 2018-09-30 2023-06-13 桑顿新能源科技(长沙)有限公司 一种关于峰值与持续功率切换的bms对电池系统sop估算方法
CN110031767B (zh) * 2019-01-16 2021-12-14 上海理工大学 一种测试sop功率的方法
CN111257764A (zh) * 2020-02-24 2020-06-09 上海蔚来汽车有限公司 监控电池短路的方法、系统以及装置
CN111579998B (zh) * 2020-04-14 2022-05-06 浙江零跑科技股份有限公司 一种电池soc校准方法、装置及存储介质
CN115702533B (zh) * 2020-06-18 2023-12-15 沃尔沃卡车集团 用于预测多电池电能存储系统的功率状态的方法
US20220037892A1 (en) * 2020-07-31 2022-02-03 GM Global Technology Operations LLC Electrical energy storage system module level diagnostics
CN112305426B (zh) * 2020-10-27 2022-07-29 上海交通大学 一种多约束条件下的锂离子电池功率状态估计系统
CN114050633B (zh) * 2021-06-11 2023-11-10 上海玫克生储能科技有限公司 一种锂电池储能系统的动态管控方法、装置和电子设备

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20200176829A1 (en) * 2017-09-11 2020-06-04 Panasonic Intellectual Property Management Co., Ltd. Electricity storage system and management device
CN108258338A (zh) * 2017-12-29 2018-07-06 江苏博强新能源科技股份有限公司 电池的管理系统和方法
CN110749827A (zh) * 2019-12-02 2020-02-04 山东大学 基于云平台的智能化电池soc管理系统及方法
CN113625175A (zh) * 2021-10-11 2021-11-09 北京理工大学深圳汽车研究院(电动车辆国家工程实验室深圳研究院) 一种基于云端大数据平台的soc估算方法和系统

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