摘要
满充蓄电池放电过程中,Coup de fouet(电压陡降复升)现象与电池健康状态(SOH)具有很强的相关性;不同放电条件(温度、放电率)会对Coup de fouet的谷底电压和峰值电压产生较大影响。利用该蓄电池特性,以谷底电压、峰值电压、放电率、温度为输入变量,电池SOH为输出变量,建立基于BP神经网络的蓄电池SOH估测模型。结果表明,网络模型识别精度较高,适用于蓄电池SOH在线估测。
The strong correlation between Coup de fouet and SOH(state of health)of the battery had been found in the discharge process of fully charged battery.The trough voltage and plateau voltage would be impacted much in different discharge conditions(temperature,discharge rate).According to the Coup de fouet characteristic of battery,the SOH is taken as the output variable with the trough voltage,plateau voltage,discharge rate and temperature as input variables,and a battery SOH estimation model based on BP neural network was built.The results showed that the network model could identify SOH precision and was very suitable for battery SOH online estimation.
作者
袁世魁
程力
YUAN Shikui;CHENG Li(School of Energy and Environment,Southeast University,Nanjing Jiangsu 210096,China)
出处
《蓄电池》
2018年第2期65-68,共4页
Chinese LABAT Man
