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Online SOC Estimation of High-power Lithium-ion Batteries Used on HEVs

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3 Author(s)
Haifeng Dai ; Department of Automotive Engineering, Tongji University, Shanghai. 201804 China P.R. fax: 086-021-6958-9121; E-mail address: ; Zechang Sun ; Xuezhe Wei

Battery management systems (BMS) in hybrid electric vehicles (HEVs) should be able to online estimate the present state of charge (SOC) of the battery pack accurately. In this paper, we proposed a SOC estimating method for battery packs based on the well-known extended Kalman filter (EKF). The underlying dynamic behavior of the battey pack was described by a model which was based on an equivalent circuit comprising of two capacitors and three resistors. Measurements of current and voltage in two different tests were applied to validate the proposed method. By comparing the SOC estimated by model based EKF to the SOC estimated by coulomb counting, we got the results showing that the methodologies we proposed were able to perform a good estimation of SOC of the battery pack. Moreover, a corresponding BMS including hardware and software based on our estimating method was designed.

Published in:

Vehicular Electronics and Safety, 2006. ICVES 2006. IEEE International Conference on

Date of Conference:

13-15 Dec. 2006