NDLI: Adaptive parameter identification and State-of-Charge estimation of lithium-ion batteries

Content Provider	IEEE Xplore Digital Library
Author	Rahimi-Eichi, H. Mo-Yuen Chow
Copyright Year	2012
Description	Author affiliation: Department of Electrical and Computer Engineering, North Carolina State University, USA (Rahimi-Eichi, H.; Mo-Yuen Chow)
Abstract	Estimation of the State of Charge (SOC) is a fundamental need for the battery, which is the most important energy storage in Electric Vehicles (EVs) and the Smart Grid. Regarding those applications, the SOC estimation algorithm is expected to be accurate and easy to implement. In this paper, after considering a resistor-capacitor (RC) circuit-equivalent model for the battery, the nonlinear relationship between the Open Circuit Voltage (VOC) and the SOC is described in a lookup table obtained from experimental tests. Assuming piecewise linearity for the VOC -SOC curve in small time steps, a parameter identification technique is applied to the real current and voltage data to estimate and update the parameters of the battery at each step. Subsequently, a reduced-order linear observer is designed for this continuously updating model to estimate the SOC as one of the states of the battery system. In designing the observer, a mixture of Coulomb counting and VOC algorithm is combined with the adaptive parameter-updating approach and increases the accuracy to less than 5% error. This paper also investigates the correlation between the SOC estimation error and the observability criterion for the battery model, which is directly related to the slope of the VOC- SOC curve.
Starting Page	4012
Ending Page	4017
File Size	1526517
Page Count	6
File Format	PDF
ISBN	9781467324199
ISSN	1553572X
e-ISBN	9781467324212
e-ISBN	9781467324205
DOI	10.1109/IECON.2012.6389248
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-25
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	System-on-a-chip Batteries Chemicals Impedance Adaptation models Data models Indexes VOC-Based SOC Estimation Battery Parameter Estimation Parameter Identification State Observer Design State-of-Charge
Content Type	Text
Resource Type	Article

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