Online Estimation of Model Parameters and State of Charge of LiFePO 4 Batteries Using a Novel Open-Circuit Voltage at Various Ambient Temperatures

Fei Feng, Rengui Lu, Guo Wei and Chunbo Zhu
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Fei Feng: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Rengui Lu: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Guo Wei: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Chunbo Zhu: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China

Energies, 2015, vol. 8, issue 4, 1-27

Abstract: This study describes an online estimation of the model parameters and state of charge (SOC) of lithium iron phosphate batteries in electric vehicles. A widely used SOC estimator is based on the dynamic battery model with predeterminate parameters. However, model parameter variances that follow with their varied operation temperatures can result in errors in estimating battery SOC. To address this problem, a battery online parameter estimator is presented based on an equivalent circuit model using an adaptive joint extended Kalman filter algorithm. Simulations based on actual data are established to verify accuracy and stability in the regression of model parameters. Experiments are also performed to prove that the proposed estimator exhibits good reliability and adaptability under different loading profiles with various temperatures. In addition, open-circuit voltage (OCV) is used to estimate SOC in the proposed algorithm. However, the OCV based on the proposed online identification includes a part of concentration polarization and hysteresis, which is defined as parametric identification-based OCV (OCV PI ). Considering the temperature factor, a novel OCV–SOC relationship map is established by using OCV PI under various temperatures. Finally, a validating experiment is conducted based on the consecutive loading profiles. Results indicate that our method is effective and adaptable when a battery operates at different ambient temperatures.

Keywords: state of charge (SOC) estimation; online identification; open-circuit voltage; lithium-ion batteries; wide temperature range (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: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (19)

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