SOC Estimation of Ni-MH Battery Pack based on Approved HPPC Test and EKF Algorithm for HEV

被引:4
作者
Sun, Bingxiang [1 ]
Jiang, Jiuchun [1 ]
Wang, Zhanguo [1 ]
机构
[1] Beijing Jiaotong Univ, Sch Elect Engn, Beijing, Peoples R China
来源
MEMS, NANO AND SMART SYSTEMS, PTS 1-6 | 2012年 / 403-408卷
关键词
Hybrid electric vehicle(HEV); Nickel-metal hydride battery pack(NiMH battery pack); State of charge(SOC); Improved hybrid pulse power characterization test (Improved HPPC test); Extended Kalman Filter(EKF); MANAGEMENT-SYSTEMS; CHARGE; STATE;
D O I
10.4028/www.scientific.net/AMR.403-408.4398
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, Methods of SOC estimation of Extended Kalman Filter (EKF) is studied based on the characteristics of Nickel-Metal Hydride (Ni-MH) battery pack with 120 cells in series and 8Ah capacity for HEV. In the study of EKF-based SOC estimation, the improved Thevenin circuit model is adopted, and a new hybrid pulse power characterization (HPPC) test is designed to identify the model parameters by using piecewise linear regression method. In this way, the precision of the circuit model is improved. In addition, The Kalman gain matrix is optimized for EKF iterative algorithm by two ways: a constant gain is increased taking into account the entire process; a dynamic gain which increases at the beginning of abrupt change and decreases rapidly after abrupt change is set up. The improvement achieves a good tracing prediction.
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收藏
页码:4398 / 4402
页数:5
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