韦海燕;陈孝杰;吕治强;王峥峥;潘海鸿;陈琳;

• 1:广西大学机械工程学院

摘要(Abstract)：

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%。

关键词(KeyWords)： 灰色神经网络;锂离子电池;SOH估算;健康因子

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(51267002,51667006);; 广西自然科学基金资助项目(2015GXNSFAA139287);; 广西制造系统与先进制造技术重点实验室项目(1514030S002);; 广西研究生教育创新计划项目(YCSW2017038)~~

作者(Author): 韦海燕;陈孝杰;吕治强;王峥峥;潘海鸿;陈琳;

Email:

DOI: 10.13335/j.1000-3673.pst.2017.0522

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