摘要
动力电池的容量剩余表现称为荷电状态(SOC),是衡量电池管理系统好坏的重要参数之一,通常定义值是电池剩余的容量除以电池额定容量。使用最小二乘支持向量回归机(LSSVR),并对此学习机使用遗传算法优化执行,估算动力电池的 SOC,将结果误差控制在 3 % 以内。
State of charge(SOC)is one of the important parameters to measure the quality of battery management system.It is usually defined as the remaining capacity of battery divided by the rated capacity of battery.The least squares support vector machine(LSSVR)was used,and the learning machine was optimized by using genetic algorithm to estimate the SOC of the power battery,and the error of the result was controlled within 3%.
作者
容伟
佘世刚
魏新尧
刘爱琦
RONG Wei;SHE Shigang;WEI Xinyao;LIU Aiqi(School of Mechanical Engineering,Changzhou University,Changzhou Jiangsu 213146;Automatic Control Laboratory of Jiangsu Province,Changzhou University,Changzhou Jiangsu 213164,China)
出处
《蓄电池》
CAS
2021年第2期51-55,87,共6页
Chinese LABAT Man
关键词
锂离子
动力电池
荷电状态
最小二乘
支持向量机
遗传算法
电池管理系统
lithium-ion
power battery
SOC
least square
support vector machine
genetic algorithm
battery management system
