摘要
为了准确估算动力锂离子电池的荷电状态(SOC),创新性地将双指数拟合的方法运用到参数辨识中,并设计了一种新型验证模型。首先,对新一代汽车协商会(PNGV)等效电路模型进行改进,利用改进PNGV模型来模拟电池的动静态工作特性;然后,利用混合动力脉冲能力特性(HPPC)试验数据对电池在改进PNGV模型下的动态参数进行辨识,并取SOC值为0.4时的状态,对参数辨识过程中单指数拟合与双指数拟合的误差作对比分析;最后,在Matlab/Simulink环境下,建立了一种新型的锂离子电池仿真模型,并利用该仿真模型对参数辨识的结果进行仿真分析与验证。验证结果表明,在温度固定和SOC已知的情况下,改进型PNGV模型的端电压仿真值与试验值最大误差不超过0.9%,模型精度较高。该试验可为锂离子电池内部状态变量的准确估算提供理论依据。
In order to accurately estimate the state of charge ( SOC ) of power lithium ion battery ,the method of double exponential fitting is innovatively applied to parameter identification, and a new verification model is proposed. Firstly, partnership for a new generation ( PNGV) equivalent circuit model is improved to simulate the dynamic and static working characteristics of the battery. Then ,the experimental data of hybrid pulse power characterization ( HPPC ) are used to identify the dynamic parameters of the battery in the improved PNGV model, and the state of SOC is taken to be 0. 4, and the errors of single exponential and double exponential fitting are compared and analyzed in the process of parameter identification. Finally, in the Matlab/Simulink environment, a new lithium ion battery simulation model is established, and the results of parameter identification are analyzed and verified by the simulation model. The verification results show that under the conditions of fixed temperature and known SOC ,the maximum error between the simulation value of terminal voltage and the experimental value of the improved PNGV model does not exceed 0. 9%, and the model has a high accuracy. This experiment can provide a theoretical basis for the accurate estimation of internal state variables of lithium ion batteries.
作者
时浩添
王顺利
任哲昆
于春梅
李小霞
王晨懿
SHI Haotian;WANG Shunli;REN Zhekun;YU Chunmei;LI Xiaoxia;WANG Chenyi(School of Information Engineering,Southwest University of Science and Technology,Mianyang 621010,China)
出处
《自动化仪表》
CAS
2019年第5期6-12,共7页
Process Automation Instrumentation
基金
国家自然科学基金资助项目(61801407)
国家级大学生创新训练计划基金资助项目(201810619028)
四川省科技厅重点研发基金资助项目(2018GZ0390
2019YFG0427)
四川省教育厅科研基金资助项目(17ZB0453)
关键词
锂离子电池
参数辨识
双指数拟合
改进型PNGV模型
HPPC试验
等效电路
荷电状态
电池管理系统
Lithium battery
Parameter identification
Double exponential fitting
Improved PNGV model
HPPC experiment
Equivalent circuit
State of charge ( SOC )
Battery management system
