Combined estimation of State-of-Charge and State-of-Health of Li-ion battery cells using SMO on electrochemical model

Satadru Dey; Beshah Ayalew; Pierluigi Pisu

doi:10.1109/VSS.2014.6881140

Combined estimation of State-of-Charge and State-of-Health of Li-ion battery cells using SMO on electrochemical model

Satadru Dey, Beshah Ayalew, Pierluigi Pisu

Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

25 Scopus citations

Abstract

Advanced battery management systems require accurate information of battery State-of-Charge (SOC) and State-of-Health (SOH) for diagnostics and prognostics as well as for efficient capacity utilization. In this paper, an integrated SOC and SOH estimation scheme is presented that applies sliding modes on an electrochemical model for Li-ion battery cell. The electrochemical model is selected and progressively reduced to sufficiently describe the relevant temporal and spatial evolution of Li-ion concentration in each electrode. The proposed estimation scheme is comprised of three sub-estimators which work jointly: two separate adaptive sliding mode observers (SMO) for estimation of Li-ion concentration and film resistance, and a separate parameter estimator for the solid state diffusion coefficient of negative electrode. Convergence of the observers has been proven using Lyapunov's stability theory. Simulation results are included to demonstrate the effectiveness of the overall scheme.

Original language	English (US)
Title of host publication	VSS 2014 - Proceedings of 13th International Workshop on Variable Structure Systems
Publisher	IEEE Computer Society
ISBN (Print)	9781479955664
DOIs	https://doi.org/10.1109/VSS.2014.6881140
State	Published - 2014
Event	13th International Workshop on Variable Structure Systems, VSS 2014 - Nantes, France Duration: Jun 29 2014 → Jul 2 2014

Publication series

Name	Proceedings of IEEE Workshop on Applications of Computer Vision
ISSN (Print)	2158-3978
ISSN (Electronic)	2158-3986

Conference

Conference	13th International Workshop on Variable Structure Systems, VSS 2014
Country	France
City	Nantes
Period	6/29/14 → 7/2/14

All Science Journal Classification (ASJC) codes

Computer Vision and Pattern Recognition
Computer Science Applications

Access to Document

10.1109/VSS.2014.6881140

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Dey, S., Ayalew, B., & Pisu, P. (2014). Combined estimation of State-of-Charge and State-of-Health of Li-ion battery cells using SMO on electrochemical model. In VSS 2014 - Proceedings of 13th International Workshop on Variable Structure Systems [6881140] (Proceedings of IEEE Workshop on Applications of Computer Vision). IEEE Computer Society. https://doi.org/10.1109/VSS.2014.6881140

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abstract = "Advanced battery management systems require accurate information of battery State-of-Charge (SOC) and State-of-Health (SOH) for diagnostics and prognostics as well as for efficient capacity utilization. In this paper, an integrated SOC and SOH estimation scheme is presented that applies sliding modes on an electrochemical model for Li-ion battery cell. The electrochemical model is selected and progressively reduced to sufficiently describe the relevant temporal and spatial evolution of Li-ion concentration in each electrode. The proposed estimation scheme is comprised of three sub-estimators which work jointly: two separate adaptive sliding mode observers (SMO) for estimation of Li-ion concentration and film resistance, and a separate parameter estimator for the solid state diffusion coefficient of negative electrode. Convergence of the observers has been proven using Lyapunov's stability theory. Simulation results are included to demonstrate the effectiveness of the overall scheme.",

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Dey, S, Ayalew, B & Pisu, P 2014, Combined estimation of State-of-Charge and State-of-Health of Li-ion battery cells using SMO on electrochemical model. in VSS 2014 - Proceedings of 13th International Workshop on Variable Structure Systems., 6881140, Proceedings of IEEE Workshop on Applications of Computer Vision, IEEE Computer Society, 13th International Workshop on Variable Structure Systems, VSS 2014, Nantes, France, 6/29/14. https://doi.org/10.1109/VSS.2014.6881140

Combined estimation of State-of-Charge and State-of-Health of Li-ion battery cells using SMO on electrochemical model. / Dey, Satadru; Ayalew, Beshah; Pisu, Pierluigi.

VSS 2014 - Proceedings of 13th International Workshop on Variable Structure Systems. IEEE Computer Society, 2014. 6881140 (Proceedings of IEEE Workshop on Applications of Computer Vision).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Dey S, Ayalew B, Pisu P. Combined estimation of State-of-Charge and State-of-Health of Li-ion battery cells using SMO on electrochemical model. In VSS 2014 - Proceedings of 13th International Workshop on Variable Structure Systems. IEEE Computer Society. 2014. 6881140. (Proceedings of IEEE Workshop on Applications of Computer Vision). https://doi.org/10.1109/VSS.2014.6881140