Title :
Estimation of internal states of 18650 lithium-ion batteries by Sigma-Point Kalman Filter
Author :
Liu, Yunfeng ; Zheng, Kun ; Xing, Zhilong
Author_Institution :
Sch. of Mechatron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
Abstract :
In this paper, Sigma-Point Kalman Filter(SPKF) has been adopted to estimate the internal states of 18650 lithium-ion battery. An equivalent circuit model of lithium-ion battery has been build. The initial parameters of the model can be calculated through the experimental data of the Hybrid Pulse Power Characterization (HPPC). In addition, the state space equation and output equation based on the circuit model have been defined. Then the algorithm of SPKF is been simulated by MATLAB software. The result proves that the computational internal states of battery is effective and estimation accuracy is relatively high.
Keywords :
Kalman filters; lithium; secondary cells; 18650 lithium-ion batteries; HPPC; Li; MATLAB software; SPKF; equivalent circuit model; hybrid pulse power characterization; internal state estimation; sigma-point Kalman filter; state space equation; Batteries; Estimation; Integrated circuit modeling; Kalman filters; MATLAB; Mathematical model; System-on-a-chip; 18650 lithium-ion battery; SOC; Sigma-Point Kalman Filter; battery model;
Conference_Titel :
Electrical and Control Engineering (ICECE), 2011 International Conference on
Conference_Location :
Yichang
Print_ISBN :
978-1-4244-8162-0
DOI :
10.1109/ICECENG.2011.6057800