CN110967639A - Technology for monitoring energy storage battery by utilizing big data - Google Patents
Technology for monitoring energy storage battery by utilizing big data Download PDFInfo
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- CN110967639A CN110967639A CN201911288368.1A CN201911288368A CN110967639A CN 110967639 A CN110967639 A CN 110967639A CN 201911288368 A CN201911288368 A CN 201911288368A CN 110967639 A CN110967639 A CN 110967639A
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- energy storage
- storage battery
- information
- battery
- big data
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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]
- G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
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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]
- G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
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- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Fuel Cell (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
- Secondary Cells (AREA)
Abstract
The invention discloses a technology for monitoring an energy storage battery by utilizing big data, which comprises the following steps: the energy storage battery pack 1 comprises an information acquisition module 2 for acquiring information of an energy storage battery, an information transmitting module 3 for transmitting information, a big data center 4 for analyzing the information, an information receiving module 5 for receiving the information of the big data center, and a control module 6 for controlling the energy storage battery. All networking energy storage battery group information all is controlled in a big data network, and each energy storage battery group information all is timely dynamic's demonstration, and the control of being convenient for deals with unusual information.
Description
The technical field is as follows: the invention relates to a technology for monitoring an energy storage battery by utilizing big data, belonging to the field of energy storage battery technology and big data application.
Background art:
the big data statistical data of the lithium battery shows that in 2020, the demand of the energy storage market of the lithium battery in China can reach 16.64 GWH. In the next five years, the cumulative requirement of the energy storage battery is 68.05GWH, and the cumulative requirement of the lithium battery in the next five years can reach 45.59GWH according to the current installed share measurement. The single battery management system of the energy storage battery monitors, is not networked, has few functions, can not comprehensively reflect the state of the energy storage battery during operation and can not feed back the state of the battery in real time, thereby bringing potential safety hazards.
Disclosure of Invention
In order to overcome the defects of data dispersion, incapability of long-term storage, low utilization rate and incomplete battery performance information reflection of the conventional energy storage battery, the invention provides a technology for monitoring the energy storage battery by utilizing big data and a technology for analyzing and monitoring the operation of the energy storage battery by utilizing the big data in real time, thereby improving the timeliness of monitoring the energy storage battery. Bad batteries are found in time in dynamic monitoring, potential safety hazards can be found in time by finding the high-temperature area of the battery compartment in time, the safety of the electric vehicle can be improved, and the safety of vehicles and personnel is guaranteed.
In order to achieve the purpose, the technical scheme of the invention is as follows:
one technique for monitoring energy storage cells using big data is to use all energy storage cells in an operator or across the country. The energy storage batteries of one city or the whole country are networked with the big data center 4, and the big data center 4 monitors all the energy storage batteries of one operator or the whole country in real time. The specific technology for monitoring the energy storage battery by utilizing big data comprises the following steps: the energy storage battery pack 1 comprises an information acquisition module 2 for acquiring information of an energy storage battery, an information transmitting module 3 for transmitting information, a big data center 4 for analyzing the information, an information receiving module 5 for receiving the information of the big data center, and a control module 6 for controlling the energy storage battery.
The information acquisition module 2 acquires battery information and includes: the energy storage battery pack 1 comprises charging capacity, discharging capacity, temperature, total voltage and internal resistance of the battery pack, charging and discharging curves of the battery pack, platform voltage, platform capacity, power and harmful gas concentration.
The big data center 4 analyzes and judges the health state of the energy storage battery, judges bad information, gives an alarm to the bad information and provides a treatment suggestion, and the information returns to the information receiving module 5 and the control module 6.
The energy storage battery pack 1 is an energy storage device, and includes a lead-acid battery, a lithium ion battery, a nickel-metal hydride battery, a fuel cell, a zinc-air battery, and a lithium-air battery. The energy storage battery pack 1 has an identification code, and the identification code content comprises: the position of the energy storage battery, the serial number of the container and the position code of the battery in the container.
Drawings
Fig. 1 is a flow chart of a technique for monitoring an energy storage battery using big data.
Detailed Description
In order that those skilled in the art will better understand the present invention, the following detailed description of the embodiments is provided in conjunction with fig. 1:
a technique for monitoring an energy storage battery using big data, comprising: the energy storage battery pack 1 comprises an information acquisition module 2 for acquiring information of an energy storage battery, an information transmitting module 3 for transmitting information, a big data center 4 for analyzing the information, an information receiving module 5 for receiving the information of the big data center, and a control module 6 for controlling the energy storage battery.
The battery pack 1 includes a lead-acid battery, a lithium ion battery, a nickel-metal hydride battery, a fuel cell, a zinc-air battery, and a lithium-air battery. The energy storage battery pack 1 has an identification code, and the identification code content comprises: the position of the energy storage battery, the serial number of the container and the position code of the battery in the container.
The information acquisition module 2 acquires battery information and includes: the system comprises an energy storage battery, a charging and discharging capacity, a temperature, a total voltage and an internal resistance of a battery pack, a charging and discharging curve of the battery pack, a platform voltage, a platform capacity, a power and a harmful gas concentration.
The big data center 4 analyzes and judges the health state of the energy storage battery, judges bad information, gives an alarm to the bad information and provides a treatment suggestion, and the information returns to the information receiving module 5.
Case one: in a company, a large data center monitors all the energy storage batteries 1 of the company in real time. The specific technology for monitoring the energy storage battery by utilizing big data comprises the following steps: the energy storage battery pack 1 comprises an information acquisition module 2 for acquiring information of an energy storage battery, an information transmitting module 3 for transmitting information, a big data center 4 for analyzing the information, an information receiving module 5 for receiving the information of the big data center, and a control module 6 for controlling the energy storage battery.
The information acquisition module 2 acquires battery information and includes: the energy storage battery pack 1 comprises charging capacity, discharging capacity, temperature, total voltage and internal resistance of the battery pack, charging and discharging curves of the battery pack, platform voltage, platform capacity, power and harmful gas concentration.
The big data center 4 analyzes and judges the health state of the energy storage battery, judges bad information, gives an alarm to the bad information and provides a treatment suggestion, and the information returns to the information receiving module 5 and the control module 6.
All energy storage battery information of a company is controlled in a large data network, and the information of each energy storage battery pack is timely and dynamically displayed, so that monitoring is facilitated, and abnormal information is dealt with.
Case two: when the system is applied to a city or a whole country, all the energy storage batteries are networked to the big data center, a plurality of big data sub-centers can be arranged, and the big data center monitors all the electric energy storage batteries in real time.
The specific technology for monitoring the energy storage battery by utilizing big data comprises the following steps: the system is used for the energy storage battery pack 1 and comprises an information acquisition module 2 used for acquiring information of an energy storage battery, an information transmitting module 3 used for transmitting information, a big data center 4 used for analyzing the information, an information receiving module 5 used for receiving the information of the big data center, and a control module 6 used for controlling the energy storage battery.
The information acquisition module 2 acquires battery information and includes: the energy storage battery pack 1 comprises charging capacity, discharging capacity, temperature, total voltage and internal resistance of the battery pack, charging and discharging curves of the battery pack, platform voltage, platform capacity, power and harmful gas concentration.
The big data center 4 analyzes and judges the health state of the energy storage battery, judges bad information, gives an alarm to the bad information and provides a treatment suggestion, and the information returns to the information receiving module 5 and the control module 6.
All energy storage battery information of a city or a country is controlled in a large data network, and the information of each energy storage battery pack is dynamically displayed in time, so that the monitoring is convenient, and abnormal information is dealt with.
The present invention is specifically described in the above, and those skilled in the art can make equivalent modifications or substitutions within the spirit of the present invention, and the scope of the present invention is defined by the claims.
Claims (4)
1. A technique for monitoring an energy storage battery using big data, comprising: the energy storage battery pack 1 comprises an information acquisition module 2 for acquiring information of an energy storage battery, an information transmitting module 3 for transmitting information, a big data center 4 for analyzing the information, an information receiving module 5 for receiving the information of the big data center, and a control module 6 for controlling the energy storage battery.
The battery pack 1 includes a lead-acid battery, a lithium ion battery, a nickel-metal hydride battery, a fuel cell, a zinc-air battery, and a lithium-air battery. The energy storage battery pack 1 has an identification code, and the identification code content comprises: the position of the energy storage battery, the serial number of the container and the position code of the battery in the container.
The information acquisition module 2 acquires battery information and includes: the system comprises an energy storage battery, a charging and discharging capacity, a temperature, a total voltage and an internal resistance of a battery pack, a charging and discharging curve of the battery pack, a platform voltage, a platform capacity, a power and a harmful gas concentration.
The big data center 4 analyzes and judges the health state of the energy storage battery, judges bad information, gives an alarm to the bad information and provides a treatment suggestion, and the information returns to the information receiving module 5.
2. The technology for monitoring the energy storage battery by utilizing the big data is characterized in that: the energy storage battery pack 1 has an identification code, and the identification code content comprises: the position of the energy storage battery, the serial number of the container and the position code of the battery in the container.
3. The technology for monitoring the energy storage battery by utilizing the big data is characterized in that: the energy storage battery pack 1 is a product of a company or an energy storage battery pack owned by a city or a country.
4. The technology for monitoring the energy storage battery by utilizing the big data is characterized in that: the energy storage battery pack 1 comprises a lead-acid battery, a lithium ion battery, a nickel-metal hydride battery, a fuel battery, a zinc-air battery and a lithium-air battery.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201911288368.1A CN110967639A (en) | 2019-12-10 | 2019-12-10 | Technology for monitoring energy storage battery by utilizing big data |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201911288368.1A CN110967639A (en) | 2019-12-10 | 2019-12-10 | Technology for monitoring energy storage battery by utilizing big data |
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| CN110967639A true CN110967639A (en) | 2020-04-07 |
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| CN201911288368.1A Pending CN110967639A (en) | 2019-12-10 | 2019-12-10 | Technology for monitoring energy storage battery by utilizing big data |
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Citations (6)
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| CN102749102A (en) * | 2012-07-10 | 2012-10-24 | 新源动力股份有限公司 | Data visualization method for high-power fuel cell |
| CN105116819A (en) * | 2015-07-29 | 2015-12-02 | 中国汽车技术研究中心 | Battery management main system suitable for new energy automobile and control method thereof |
| CN105911476A (en) * | 2016-04-13 | 2016-08-31 | 华北电力大学 | Battery energy storage system SOC predication method based on data mining |
| US20180181967A1 (en) * | 2016-12-22 | 2018-06-28 | Powin Energy Corporation | Battery pack monitoring and warranty tracking system |
| US20180264969A1 (en) * | 2017-03-17 | 2018-09-20 | Toyota Jidosha Kabushiki Kaisha | Battery control device and battery control system |
| CN110518300A (en) * | 2019-08-18 | 2019-11-29 | 浙江万马新能源有限公司 | It is a kind of to monitor power battery technology using big data |
-
2019
- 2019-12-10 CN CN201911288368.1A patent/CN110967639A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102749102A (en) * | 2012-07-10 | 2012-10-24 | 新源动力股份有限公司 | Data visualization method for high-power fuel cell |
| CN105116819A (en) * | 2015-07-29 | 2015-12-02 | 中国汽车技术研究中心 | Battery management main system suitable for new energy automobile and control method thereof |
| CN105911476A (en) * | 2016-04-13 | 2016-08-31 | 华北电力大学 | Battery energy storage system SOC predication method based on data mining |
| US20180181967A1 (en) * | 2016-12-22 | 2018-06-28 | Powin Energy Corporation | Battery pack monitoring and warranty tracking system |
| US20180264969A1 (en) * | 2017-03-17 | 2018-09-20 | Toyota Jidosha Kabushiki Kaisha | Battery control device and battery control system |
| CN110518300A (en) * | 2019-08-18 | 2019-11-29 | 浙江万马新能源有限公司 | It is a kind of to monitor power battery technology using big data |
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Address after: 311300 2nd floor, Wanma Innovation Park, 2159 Keji Avenue, Qingshanhu street, Lin'an District, Hangzhou City, Zhejiang Province Applicant after: ZHEJIANG WANMA NEW ENERGY Co.,Ltd. Address before: 310012 11th floor, Tianji building, 180 Tianmushan Road, Hangzhou City, Zhejiang Province Applicant before: ZHEJIANG WANMA NEW ENERGY Co.,Ltd. |
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Application publication date: 20200407 |
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