灰色神经网络模型在线估算锂离子电池SOH

被引：67

作者：

韦海燕

陈孝杰

吕治强

王峥峥

潘海鸿

陈琳

机构：

[1] 广西大学机械工程学院

来源：

电网技术 | 2017年 / 41卷 / 12期

关键词：

灰色神经网络; 锂离子电池; SOH估算; 健康因子;

D O I：

暂无

中图分类号：

TM912 [蓄电池];

学科分类号：

080802 [电力系统及其自动化];

摘要：

锂离子电池是一个复杂的电化学动态系统,难以通过单一的监测电池内部的物理和化学特性实现健康状态(state of health,SOH)在线估算。为此提出以欧姆内阻增加量、极化内阻增加量和极化电容减少量作为电池的健康因子(health indicator,HI),并引入灰色神经网络离线训练以HI为输入,电池容量退化量为输出的灰色神经网络模型,最后通过在线构建电池HI实现电池SOH估算。实验结果表明所提出的HI能够有效表征电池健康状态,灰色神经网络模型与BP神经网络模型相比,具有更高的SOH在线估算精度,估算误差不超过2%。

引用

页码：4038 / 4044

页数：7

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