DocumentCode :
2890155
Title :
Model-based electrochemical estimation of lithium-ion batteries
Author :
Smith, Kandler A. ; Rahn, Christopher D. ; Wang, Chao Yang
Author_Institution :
Pennsylvania State Univ., University Park, PA
fYear :
2008
fDate :
3-5 Sept. 2008
Firstpage :
714
Lastpage :
719
Abstract :
A linear Kalman filter based on a reduced order electrochemical model is designed to estimate internal battery potentials, concentration gradients, and state of charge (SOC) from external current and voltage measurements. The estimates are compared with results from an experimentally validated one-dimensional nonlinear finite volume model of a 6 Ah hybrid electric vehicle battery. The linear filter gives, to within ~2%, performance in the 30%-70% SOC range, except in the case of severe current pulses that draw electrode surface concentrations to near saturation and depletion; however, the estimates recover as concentration gradients relax. With 4 to 7 states, the filter has low order comparable to empirical equivalent circuit models but provides estimates of the batterypsilas internal electrochemical state.
Keywords :
Kalman filters; battery powered vehicles; electrochemistry; finite volume methods; hybrid electric vehicles; secondary cells; concentration gradients; hybrid electric vehicle battery; linear Kalman filter; lithium-ion batteries; model-based electrochemical estimation; one-dimensional nonlinear finite volume model; reduced order electrochemical model; state of charge; Batteries; Electrodes; Equivalent circuits; Hybrid electric vehicles; Nonlinear filters; Predictive models; Solid modeling; State estimation; Vehicle dynamics; Voltage control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Applications, 2008. CCA 2008. IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
978-1-4244-2222-7
Electronic_ISBN :
978-1-4244-2223-4
Type :
conf
DOI :
10.1109/CCA.2008.4629589
Filename :
4629589
Link To Document :
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