摘要
提出了一种多维输入的VRLA蓄电池专家诊断模型,该模型主要基于优化的支持向量机非线性回归(SVR)算法,同时应用蓄电池相关物理参数对目标参数进行补偿修正,预测蓄电池的健康状态(SOH)。文中所建立的模型结合相应的硬件设备,可实时地检测到蓄电池的特征数据,并且只需短时间放电,即可预估出蓄电池的健康状态。
This paper proposes a multi-dimensional battery professional diagnosing model based on optimizing support vector regression algorithm to predict the battery＇s SOH（State of Health,the ratio between actual capacity and rated capacity）.Battery parameters are used to adjust target parameters.This model can get battery data real-time combing with hardware.It also can predict the SOH of battery in a short time of discharge.
出处
《通信电源技术》
2010年第3期71-73,共3页
Telecom Power Technology
关键词
蓄电池
支持向量机
容量预测
蓄电池健康状态
battery
support vector
predict capacity of battery
healthy state of battery
