摘要
以电池组的电压、充放电电流作为输入变量,SOC作为输出变量。在建模过程中,用人群搜索算法来优化随机给定的极限学习机的输入权值矩阵和偏差。
With the battery voltage,charge and discharge current as input variables,and state of current(SOC)as output variables.Seeker optimization algorithm is used to modify the input weightmatrix and bias of the extreme learning machine,when a random model is established.
出处
《长春工业大学学报》
CAS
2017年第5期468-471,共4页
Journal of Changchun University of Technology
关键词
荷电状态
极限学习机
人群搜索算法
预测
SOC
Extreme Learning Machine(ELM)
seeker optimization algorithm
prediction