Online Parameter Estimation of the Ni-MH Batteries Based on Statistical Methods

Chang-hao Piao, Wen-li Fu, Gai-hui Lei and Chong-du Cho
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Chang-hao Piao: Key Laboratory of Network control & Intelligent Instrument, Ministry of Education, Chongqing University of Posts and Telecommunications, Chongqing 400065 China
Wen-li Fu: Research Center of Energy Electronics, College of Automation Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065 China
Gai-hui Lei: Research Center of Energy Electronics, College of Automation Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065 China
Chong-du Cho: Department of mechanical Engineering, INHA University of Korea, Incheon, 402751, Korea

Energies, 2010, vol. 3, issue 2, 1-10

Abstract: Based on the application of the power batteries, this paper uses a statistical method to estimate the internal resistance and open-circuit voltage of Ni-MH battery. Battery status is monitored and simulated by battery pack test bench. Through using ideal battery model and fitting the data of measured voltage and current, the battery internal resistance and open-circuit voltage are estimated. The average relative error between battery statistic internal resistance and pulse internal resistance is less than 15% in different state of charge. Relative error is influenced by dispersion and symmetry of charge or discharge current. Average of absolute error in open-circuit voltage is about 5% respectively. The results show that it is feasible and accurate to estimate the parameters of Ni-MH battery by using statistical method.

Keywords: dynamic batteries; statistical method; battery model; resistance; open-circuit voltage (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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