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

Content Provider	IEEE Xplore Digital Library
Author	Haifeng Dai Xuezhe Wei Zechang Sun
Copyright Year	2006
Description	Author affiliation: Tongji Univ., Shanghai (Haifeng Dai)
Abstract	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.
Starting Page	342
Ending Page	347
File Size	4234355
Page Count	6
File Format	PDF
ISBN	1424407583
DOI	10.1109/ICVES.2006.371612
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-12-13
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Resistors SOC estimation Capacitors Battery charge measurement Hybrid electric vehicles Vehicle dynamics Extended Kalman filter Lithium-ion batteries Current measurement Battery management systems Voltage Model HEVs State estimation Equivalent circuits
Content Type	Text
Resource Type	Article

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