The fuzzy c-regression model of the lithium battery and its application to the estimation of the state of charge

Author

Kung, Chung-Chun ; Chang, Shuo-Chieh

Author_Institution

Dept. of Electr. Eng., Tatung Univ., Taipei, Taiwan

fYear

2012

fDate

10-15 June 2012

Firstpage

1

Lastpage

6

Abstract

In this paper, the fuzzy c-regression model of the lithium battery and its application to the estimation of the state of charge (SOC) is proposed. The equivalent circuit model (ECM) of the lithium battery as shown in fig. 1 is adopted. It is seen that all the parameters, V_OC, R_t, R_p, and C_p, in the ECM depend on the SOC of the lithium battery. Thus, we apply the fuzzy c-regression models (FCRM) to formulate these parametric dependence functions. Based on these fuzzy c-regression models, we can estimate the SOC of the given lithium battery. The direct current internal resistance (DCIR) test method under the room temperature is applied to measure the parameters of the ECM. Simulation results demonstrate the effectiveness of the proposed approach.

Keywords

battery charge measurement; battery testers; equivalent circuits; fuzzy set theory; regression analysis; secondary cells; DCIR; FCRM; SOC; direct current internal resistance test method; equivalent circuit model; fuzzy c-regression model; lithium battery; parametric dependence functions; state-of-charge estimation; Batteries; Clustering algorithms; Electronic countermeasures; Integrated circuit modeling; Lithium; Resistance; System-on-a-chip; direct current internal resistance; fuzzy c-regression model; state of charge;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on

Conference_Location

Brisbane, QLD

ISSN

1098-7584

Print_ISBN

978-1-4673-1507-4

Electronic_ISBN

1098-7584

Type

conf

DOI

10.1109/FUZZ-IEEE.2012.6250837

Filename

6250837