A Universal State-of-Charge Algorithm for Batteries
被引:0
作者:
Xiao, Bingjun
论文数: 0引用数: 0
h-index: 0
机构:
Univ Calif Los Angeles, Dept Elect Engn, Los Angeles, CA 90095 USAUniv Calif Los Angeles, Dept Elect Engn, Los Angeles, CA 90095 USA
Xiao, Bingjun
[1
]
Shi, Yiyu
论文数: 0引用数: 0
h-index: 0
机构:
Univ Calif Los Angeles, Dept Elect Engn, Los Angeles, CA 90095 USAUniv Calif Los Angeles, Dept Elect Engn, Los Angeles, CA 90095 USA
Shi, Yiyu
[1
]
He, Lei
论文数: 0引用数: 0
h-index: 0
机构:
Univ Calif Los Angeles, Dept Elect Engn, Los Angeles, CA 90095 USAUniv Calif Los Angeles, Dept Elect Engn, Los Angeles, CA 90095 USA
He, Lei
[1
]
机构:
[1] Univ Calif Los Angeles, Dept Elect Engn, Los Angeles, CA 90095 USA
来源:
PROCEEDINGS OF THE 47TH DESIGN AUTOMATION CONFERENCE
|
2010年
关键词:
Battery;
State of Charge;
Circuit Analysis;
D O I:
暂无
中图分类号:
TP301 [理论、方法];
学科分类号:
081202 ;
摘要:
State-of-charge (SOC) measures energy left in a battery, and it is critical for modeling and managing batteries. Developing efficient yet accurate SOC algorithms remains a challenging task. Most existing work uses regression based on a time-variant circuit model, which may be hard to converge and often does not apply to different types of batteries. Knowing open-circuit voltage (OCV) leads to SOC due to the well known mapping between OCV and SOC. In this paper, we propose an efficient yet accurate OCV algorithm that applies to all types of batteries. Using linear system analysis but without a circuit model, we calculate OCV based on the sampled terminal voltage and discharge current of the battery. Experiments show that our algorithm is numerically stable, robust to history dependent error, and obtains SOC with less than 4% error compared to a detailed battery simulation for a variety of batteries. Our OCV algorithm is also efficient, and can be used as a real-time electro-analytical tool revealing what is going on inside the battery.