Dual EKF-based state and parameter estimator for a LiFePO4 battery cell

Pavković, Danijel and Krznar, Matija and Komljenović, Ante and Hrgetić, Mario and Zorc, Davor (2017) Dual EKF-based state and parameter estimator for a LiFePO4 battery cell. = Dual EKF-based state and parameter estimator for a LiFePO4 battery cell. Journal of Power Electronics, 17 (2). pp. 398-410. ISSN 1598-2092. Vrsta rada: ["eprint_fieldopt_article_type_article" not defined]. Kvartili JCR: Q4 (2017). Točan broj autora: 5.

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This paper presents the design of a dual Extended Kalman Filter (EKF) as a state/parameter estimator suitable for adaptive state-of-charge (SoC) estimation of an automotive lithium-iron-phosphate (LiFePO4) cell. An experimentally- identified lumped-parameter equivalent battery electrical circuit model has been used as a basis for the design of both estimators. In the proposed estimation scheme, the parameter estimator has been used for the adaptation of the state (SoC) EKF-based estimator, which may be sensitive to nonlinear battery parameter map errors. In order to achieve smooth transition between the parameter estimator-based adaptation and internal model within the SoC estimator, a suitable weighting scheme has also been proposed. The effectiveness of the proposed SoC and parameter estimators, as well as the combined dual estimator has been verified by means of computer simulations on the developed battery model subject to NEDC driving cycle-related operating regimes.

Item Type: Article (["eprint_fieldopt_article_type_article" not defined])
Keywords (Croatian): battery modeling, Kalman filter, estimation, electric vehicles
Subjects: TECHNICAL SCIENCE > Mechanical Engineering
Divisions: 900 Department of Robotics and Production System Automation > 910 Chair of Engineering Automation
Indexed in Web of Science: Yes
Indexed in Current Contents: No
Quartiles: Q4 (2017)
Date Deposited: 16 May 2017 14:08
Last Modified: 13 Sep 2018 09:21
URI: http://repozitorij.fsb.hr/id/eprint/7762

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