期刊
JOURNAL OF ENERGY STORAGE
卷 25, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.est.2019.100838
关键词
Lithium-ion battery; State of charge; Thermal coupling simplified first-principles model; Extended Kalman filter; Adaptive extended Kalman filter
资金
- program of Shenzhen knowledge innovation [JCYJ20180306171803050]
- National Natural Science Foundation of China [51477037]
- Fundamental Research Funds for the Central Universities [HIT.NSRIF.201705]
Accurate lithium-ion battery state of charge (SOC) estimation can enhance reliable and safe operation of electric vehicles. A thermal coupling simplified first-principles model has been adopted to achieve high SOC estimation accuracy. Extended Kalman filter and adaptive extended Kalman filter algorithms are separately combined with the model to estimate state of charge for a wide range of environmental temperatures (10-45 degrees C) and different charge/discharge rates. The SOC estimation method is validated with respect to the accuracy and convergence. The average absolute errors using the adaptive extended Kalman filter algorithm under conditions of dynamic stress tests and hybrid pulse power characteristics are less than 1%, which is 1.5% smaller than that of the EKF algorithm. Compared to the extended Kalman filter algorithm, the adaptive extended Kalman filter algorithm can achieve fast convergence after less than 10 s while maintaining the estimation accuracy given an initial SOC guess error of 50%. The effects of sampling frequency and battery aging states on estimation accuracy are also assessed. A sampling frequency of at least 1 Hz can ensure the accuracy is within 1%. The developed SOC estimation method is also fit for the degraded battery with about 1% estimation error.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据