Title :
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
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, VOC, Rt, Rp, and Cp, 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;
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1507-4
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZ-IEEE.2012.6250837
