TY - GEN
T1 - Identification of battery parameters via symbolic input-output analysis
T2 - 2015 American Control Conference, ACC 2015
AU - Li, Yue
AU - Ray, Asok
AU - Chattopadhyay, Pritthi
AU - Rahn, Christopher D.
N1 - Publisher Copyright:
© 2015 American Automatic Control Council.
PY - 2015/7/28
Y1 - 2015/7/28
N2 - This paper presents real-time parameter identification in battery systems as a paradigm of dynamic data-driven application systems (DDDAS). In the proposed method, symbol sequences are generated by partitioning (finite-length) time series data of synchronized input-output (i.e., current-voltage) pairs in the respective two-dimensional space. Then, a special class of probabilistic finite state automata (PFSA), called D-Markov machine, is constructed to extract pertinent features from the statistics of time series as state probability vectors. The proposed method has been validated on (approximately periodic) experimental data of a lead-acid battery for real-time identification of its pertinent parameters: State-of-Charge (SOC) and State-of-Health (SOH). The results of experimentation show that the analysis of input-output-pair data exceeds the performance of output-only data analysis.
AB - This paper presents real-time parameter identification in battery systems as a paradigm of dynamic data-driven application systems (DDDAS). In the proposed method, symbol sequences are generated by partitioning (finite-length) time series data of synchronized input-output (i.e., current-voltage) pairs in the respective two-dimensional space. Then, a special class of probabilistic finite state automata (PFSA), called D-Markov machine, is constructed to extract pertinent features from the statistics of time series as state probability vectors. The proposed method has been validated on (approximately periodic) experimental data of a lead-acid battery for real-time identification of its pertinent parameters: State-of-Charge (SOC) and State-of-Health (SOH). The results of experimentation show that the analysis of input-output-pair data exceeds the performance of output-only data analysis.
UR - http://www.scopus.com/inward/record.url?scp=84940905719&partnerID=8YFLogxK
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U2 - 10.1109/ACC.2015.7172151
DO - 10.1109/ACC.2015.7172151
M3 - Conference contribution
AN - SCOPUS:84940905719
T3 - Proceedings of the American Control Conference
SP - 5200
EP - 5205
BT - ACC 2015 - 2015 American Control Conference
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 1 July 2015 through 3 July 2015
ER -