Fractional-order Modeling and Time Domain System Identification for Lithium-ion Battery on Electric Vehicle

被引:0
|
作者
Shao, Bing [1 ]
Zou, Yuan [1 ]
机构
[1] Beijing Inst Technol, Beijing, Peoples R China
来源
2015 INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS, MACHINERY AND MATERIALS (IIMM 2015) | 2015年
关键词
Lithium ion batteries; Constant phase element; Fractional-order model; Oustaloup recursive approximation; Multi-swarm particle swarm optimization; EQUIVALENT-CIRCUIT MODELS; CHARGE ESTIMATION; IMPEDANCE MODEL; STATE; OPTIMIZATION;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Battery technology is critical to the development of electric vehicles. This paper presents a fractional-order model (FOM) for Lithium ion batteries with a constant phase element (CPE) in order to accurately describe the battery dynamics. To solve the fractional-order system control problem, the Oustaloup recursive approximation method was selected to model the fractional differentiation operator in integer order state-space form. The multi-swarm particle swarm optimization (MPSO) algorithm was implemented to identify the model parameters using time-domain battery test data. The model accuracy was measured by the average root-mean-squared error (RMSE) between the test datasets and the output from the optimized model. The validation result suggested that the FOM has better accuracy with smaller RMSEs compared with 1-RC model. With good accuracy, the derived FOM can be used in SOC estimation, battery aging analysis, etc.
引用
收藏
页码:69 / 73
页数:5
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