The estimation of the state of charge for lithium-ion battery by fuzzy c-regression model (FCRM) clustering algorithm

Chung-Chun Kung; Shuo-Chieh Chang

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https://doi.org/10.1109/icsmc....

Article . 2011 . Peer-reviewed

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https://dx.doi.org/10.1109/ics...

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The estimation of the state of charge for lithium-ion battery by fuzzy c-regression model (FCRM) clustering algorithm

descriptionPublicationkeyboard_double_arrow_right Article 01 Oct 2011Publisher:IEEEJournal:2011 IEEE International Conference on Systems, Man, and Cybernetics

Authors: Chung-Chun Kung; Shuo-Chieh Chang;

doi: 10.1109/icsmc.2011.6083894

The estimation of the state of charge for lithium-ion battery by fuzzy c-regression model (FCRM) clustering algorithm

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Abstract

In this paper, the estimation of the state of charge (SOC) of lithium-ion battery by fuzzy c-regression model (FCRM) clustering algorithm is proposed. Based on these experiment data, we apply the FCRM clustering algorithm with affine linear functional cluster representatives to build the dynamic behavior of all parameters for the RC model. Finally, the simulation results demonstrate the effectiveness of the proposed approach.

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Tatung University
Taiwan

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