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Energies 2015, 8(8), 7854-7873; doi:10.3390/en8087854

State-of-Charge Estimation for Lithium-Ion Batteries Using a Kalman Filter Based on Local Linearization

1
College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao 266590, China
2
College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, China
*
Author to whom correspondence should be addressed.
Academic Editor: Sheng S. Zhang
Received: 29 April 2015 / Revised: 6 June 2015 / Accepted: 24 July 2015 / Published: 30 July 2015
(This article belongs to the Special Issue Electrochemical Energy Storage - 2015)
View Full-Text   |   Download PDF [634 KB, uploaded 30 July 2015]   |  

Abstract

State of charge (SOC) estimation is of great significance for the safe operation of lithium-ion battery (LIB) packs. Improving the accuracy of SOC estimation results and reducing the algorithm complexity are important for the state estimation. In this paper, a zeroaxial straight line, whose slope changes along with SOC, is used to map the predictive SOC to the predictive open circuit voltage (OCV), and thus only one parameter is used to linearize the SOC-OCV curve near the present working point. An equivalent circuit model is used to simulate the dynamic behavior of a LIB, updating the linearization parameter in the measurement equation according to the present value of the state variables, and then a standard Kalman filter is used to estimate the SOC based on the local linearization. This estimation method makes the output equation of the nonlinear battery model contain only one parameter related to its dynamic variables. This is beneficial to simplify the algorithm structure and to reduce the computation cost. The linearization method do not essentially lose the main information of the dynamic model, and its effectiveness is verified experimentally. Fully and a partially charged battery experiments indicate that the estimation error of SOC is better than 0.5%. View Full-Text
Keywords: state-of-charge; local linearization; equivalent circuit model; Kalman filter; Coulomb integral; open-circuit voltage state-of-charge; local linearization; equivalent circuit model; Kalman filter; Coulomb integral; open-circuit voltage
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Yu, Z.; Huai, R.; Xiao, L. State-of-Charge Estimation for Lithium-Ion Batteries Using a Kalman Filter Based on Local Linearization. Energies 2015, 8, 7854-7873.

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