State and Parameter Estimation of a HEV Li-ion Battery Pack Using Adaptive Kalman Filter with a New SOC-OCV Concept

被引:31
作者
Dai Haifeng [1 ]
Wei Xuezhe [1 ]
Sun Zechang [1 ]
机构
[1] Tongji Univ, Sch Automot Studies, Shanghai 200092, Peoples R China
来源
2009 INTERNATIONAL CONFERENCE ON MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION, VOL II | 2009年
关键词
new SOC-OCV Concept; State and parameter estimation; adaptive Kalman filter; model; HEV Li-ion battery;
D O I
10.1109/ICMTMA.2009.333
中图分类号
TP [自动化技术、计算机技术];
学科分类号
080201 [机械制造及其自动化];
摘要
A new methodology of defining the relationship between SOC (State of Charge) and OCV (Open Circuit Voltage) relationship of the Li-ion battery pack used on HEVs (Hybrid Electric Vehicles) which is independent of the battery condition was proposed. This methodology could avoid the problems resulting from the defects that the conventional SOC-OCV relationship differs between batteries and different working conditions. Based on the new definition, a state and parameter estimator of the Li-ion battery pack based on the Sage-Husa adaptive Kalman filter was proposed. This estimator recruited an equivalent circuit model to describe the dynamic characteristics of the battery pack. The estimator could estimate the SOC, the battery actual capacity and the inner resistance on-board. The implementation of the estimator on a FPGA platform was also introduced. Testing results show that the new definition and the estimator work very well in any specific working condition.
引用
收藏
页码:375 / 380
页数:6
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