基于数据挖掘的锂电池剩余电量分析
Analysis of State of Charge of Lithium Battery Based on Data Mining
陈晓辉 1周骏 1蒋超1
作者信息
- 1. 空军勤务学院,江苏 徐州 221000
- 折叠
摘要
随着锂电池在各类电子设备中的广泛应用,对其剩余电量(State of Charge,SOC)的准确估计变得至关重要.本文提出了一种基于数据挖掘技术的锂电池SOC分析方法.通过收集锂电池充放电过程中的相关数据,利用数据挖掘算法对数据参数进行分析和处理,建立了锂电池SOC预测模型.实验结果表明,该模型能够有效地估计锂电池的SOC,为锂电池的使用和管理提供了重要依据.
Abstract
With the widespread application of lithium batteries in various electronic devices,accurate estimation of their State of Charge(SOC)has become crucial.This paper proposes a lithium battery SOC analysis method based on data mining technology.A lithium battery SOC prediction model is established by collecting relevant data during the charging and discharging process of lithium batteries,analyzing and processing data parameters using data mining algorithms.The experimental results indicate that the model can effectively estimate the SOC of lithium batteries,providing important basis for the use and management of lithium batteries.
关键词
数据挖掘/锂电池/SOC分析/预测模型Key words
data mining/lithium battery/SOC analysis/prediction models引用本文复制引用
出版年
2024
NETL
NSTL
万方数据