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A variable-length window-wise parameter-dependent state of charge estimation by Kalman filters

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posted on 30.03.2021, 13:41 by Bataa LkhagvasurenBataa Lkhagvasuren, Minkyu Kwak, Hong Sung Jin, Gyuwon Seo, Sungyool Bong, Jaeyoung Lee
This paper proposes a new window-wise state of charge (SOC) estimation algorithm based on Kalman filters (KF). In the first stage, the equivalent circuit model's parameters are estimated by a least square estimation window-wise, assuming a linear SOC and open-circuit voltage (OCV) relation. The algorithm accurately estimates the parameters and observes the changes that depend on SOC. Moreover, based on the estimated parameters, the OCV values are identified. In the next stage, window-wise linear Kalman filter(ES-LKF) without hysteresis and extended Kalman filter (ES-EKF) and sigma-point Kalman filter (ES-SPKF) algorithm with hysteresis are executed to estimate SOC. Having fewer state equations and hysteresis parameters tuned up in an off-line way, the ES-EKF and ES-SPKF perform better than the algorithms considered in previous works. The algorithms are validated by experiments with real data obtained from lab tests.

Funding

NRF 2017R1E1A1A03070061

NRF 2020R1I1A3071769

History

Email Address of Submitting Author

bat120@gmail.com

ORCID of Submitting Author

https://orcid.org/0000-0003-0285-1151

Submitting Author's Institution

Chonnam National University

Submitting Author's Country

Korea