Design of Lithium Battery Intelligent Management System
Lithium batteries have the advantages of safe and reliable power supply, low maintenance costs, small footprint, often used as the preferred solution for power supply in data centers. To solve the problems of non-linear charging and discharging curves in lithium batteries, and uneven charging and discharging caused by multiple lithium batteries in series and parallel, we design an intelligent comprehensive management system for lithium power batteries used for data centers. This system includes a master control module and a slave control module. The latter is mainly responsible for collecting voltage, current, and temperature information of lithium batteries; The main control module will perform fault detection, estimate battery charge state estimation algorithm, display data on LCD screen, and communicate with the upper computer using CAN protocol based on the information collected from the control module, transmitting the battery data situation to the user in real-time. This system uses the Internet of Things communication technology to obtain the battery status information collected on the main control board, realize the information interaction between the computer and the lithium Battery management system, and design and optimize the state of charge estimation algorithm to improve the accuracy of lithium battery data so as to improve the security and stability of the lithium battery management box. Compared with existing technologies, the accuracy of the state of charge (SOC) estimation algorithm has been improved by using an improved ampere hour integration method combined with a neural network. At the same time, the system can transmit data to users in real time, further ensuring the security of the data center.
Authors
- Nan Xu (ORCID: https://orcid.org/0000-0001-6543-9055)
- Lei Jin (ORCID: https://orcid.org/0000-0002-9346-8117)
- Huadong Yang
Institutions
- Shenyang Ligong University (CN)
- Shenyang Jianzhu University (CN)
Publication Details
- Published
- 2024-09-20
- DOI
- https://doi.org/10.1109/spic62469.2024.10691525
- Primary Topic
- Wireless Sensor Networks and IoT
- Type
- article
- Field-Weighted Citation Impact
- 0.00