Estimation of Electric Vehicle Battery Ohmic Resistance Using Dual Extend Kalman Filter

Article Preview

Abstract:

Using the traditional measurement analysis methods to estimate electric vehicle lithium ion battery ohmic resistance, it is difficult to realize on line. We in this paper use dual extend kalman filter (DEKF) based on thevenin model to solve this problem. DEKF is a kind of circulative iteration algorithm of two kalman filters, applied in the estimation which the systems state and parameter both are unknown. Using DEKF on the estimation of battery ohmic resistance only need the battery current and terminal voltage, therefore, it can be realized on line easily. This paper verified the effectiveness of DEKF through simulation and analysis of the test data.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

246-249

Citation:

Online since:

September 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] ABRAHAMA D P, LINA J, CHENA C H, et al. Diagnosis of power fade mechanisms in high-power lithium-ion cells[J]. Journal of Power Sources, 2003, 119-121: 511-516.

DOI: 10.1016/s0378-7753(03)00275-1

Google Scholar

[2] KHARE N, CHANDRA S, GOVIL R. Statistical modeling of SOH of an automotive battery for online Indication[C]/Proc of IEEE 34th International Telecommunications Energy Conference. P.O. Banasthali: IEEE Press, 2008: 1-7.

DOI: 10.1109/intlec.2008.4664086

Google Scholar

[3] SCHMIDTA A P, BITZERB M, IMRE A W, et al. Model-based distinction and quantification of capacity loss and rate capability fade in Li-ion batteries[J]. Journal of Power Sources, 2010, 195(22): 7634-7638.

DOI: 10.1016/j.jpowsour.2010.06.011

Google Scholar

[4] HUET F. A review of impedance measurements for determination of the state-of-charge or state-of-health of secondary batteries[J]. Journal of Power Sources, 1998, 70(1): 59-69.

DOI: 10.1016/s0378-7753(97)02665-7

Google Scholar

[5] REMMLINGER J, BUCHHOLZ M, MEILER M, et al. State-of-health monitoring of lithium-ion batteries in electric vehicles by on-board internal resistance estimation[J]. Journal of Power Sources, 2001, 196(12): 5357-5363.

DOI: 10.1016/j.jpowsour.2010.08.035

Google Scholar

[6] KIM I A. Technique for estimating the state of health of lithium batteries through a dual-sliding-mode observer[J]. IEEE Transactions on Power Electronics, 2010, 25(4): 1013-1022.

DOI: 10.1109/tpel.2009.2034966

Google Scholar

[7] ABRAHAMA D P, KNUTH J L, DEES D W, et al. Performance degradation of high-power lithium-ion cells-electrochemistry of harvested electrodes[J]. Journal of Power Sources, 2007, 170(2): 465-475.

DOI: 10.1016/j.jpowsour.2007.03.071

Google Scholar

[8] KARDEN E, BULLER S, DE DONCKER R D. A method for measurement and interpretation of impedance spectra for industrial batteries[J]. Journal of Power Sources, 2000, 85(1): 72–78.

DOI: 10.1016/s0378-7753(99)00385-7

Google Scholar

[9] SINGHA P, VINJAMURIA R, WANG X, et al. Fuzzy logic modeling of EIS measurements on lithium-ion batteries[J]. Electrochimica Acta, 2006, 51(8-9): 1673–1679.

DOI: 10.1016/j.electacta.2005.02.143

Google Scholar

[10] TAKENO K, ICHIMURA M, TAKANO K, et al. Quick testing of batteries in lithium-ion battery packs with impedance-measuring technology[J]. Journal of Power Sources, 2004, 128(1): 67–75.

DOI: 10.1016/j.jpowsour.2003.09.045

Google Scholar