NDLI: An EM approach for dynamic battery management systems

Content Provider	IEEE Xplore Digital Library
Author	Balasingam, B. Pattipati, B. Sankavaram, C. Pattipati, K. Bar-Shalom, Y.
Copyright Year	2012
Description	Author affiliation: Department of Electrical and Computer Engineering, University of Connecticut, Storrs, CT 06269, USA (Balasingam, B.; Pattipati, B.; Sankavaram, C.; Pattipati, K.; Bar-Shalom, Y.)
Abstract	In this paper we propose an expectation maximization (EM) type algorithm for online system identification and tracking of prognostic states as applied to battery management systems (BMS). The objective of BMS is to adaptively estimate state of charge (SOC) — a crucial battery state information. We find that the existing approaches in the literature need enhancement because (i) they lack battery equivalent models that accurately model the actual physical and chemical properties of the batteries, and (ii) they fail to utilize powerful state and parameter estimation techniques for system identification and tracking. It is often noticed throughout the literature that (ii) is a precursor to (i). In this paper, first we model the dynamic equivalent model of batteries as a series of m parallel RC circuits and derive the relationship between the time-varying battery states and the current, voltage output observations as a non-linear state space model. Then, we derive an expectation maximization (EM) type algorithm for identification of the so-derived statespace model and for the adaptive tracking of SOC. Finally we discuss the performance evaluation of the proposed algorithm through simulation and by testing them on experimental data obtained from Li-ion based cellphone batteries.
Starting Page	2110
Ending Page	2117
File Size	721795
Page Count	8
File Format	PDF
ISBN	9781467304177
e-ISBN	9780982443859
e-ISBN	9780982443842
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-09
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	ISIF ( Intl Society of Information Fusi
Subject Keyword	Batteries Integrated circuit modeling System-on-a-chip Voltage measurement Adaptation models Battery management systems Equivalent circuits EKF smoothing Battery management system (BMS) online system identification the expectation maximization (EM) algorithm non-linear filtering
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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