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

作　　者：陈晓辉 周骏[1] 蒋超[1] CHEN Xiaohui;ZHOU Jun;JIANG Chao(Air Force Logistics University,Xuzhou 221000,China)

机构地区：[1]空军勤务学院,江苏徐州221000

出　　处：《科技创新与生产力》2024年第6期135-137,141,共4页Sci-tech Innovation and Productivity

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。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 

分 类 号：TM911[电气工程—电力电子与电力传动] TP311.13[自动化与计算机技术—计算机软件与理论]