Remaining charge estimation of LiFePO4 power battery using an Unscented Kalman Filter

2013 ◽  
Vol 303-306 ◽  
pp. 975-978
Author(s):  
Hong Yu Zheng ◽  
Chang Fu Zong

The power battery state of charge (SOC) in electric vehicles is not easy to measure accurately or apply a sensor but the expense is increased. However the variable of SOC is great importance to control of electric vehicles. A power battery model is built by the Partnership for a New Generation of Vehicles (PNGV) model to estimate the state of SOC. In order to make a high accurate estimate for SOC value, an information fusion algorithm based on unscented kalman filter (UKF) is introduced to design an observer. The test results show that the observer based information fusion and UKF are effective and accuracy, so it is may apply it the electric vehicle control and observation.


Sign in / Sign up

Export Citation Format

Share Document