Online SOC Estimation Based on Simplified Electrochemical Model for Lithium-Ion Batteries Considering Current Bias

Longxing Wu, Kai Liu, Hui Pang and Jiamin Jin
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Longxing Wu: School of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an 710048, China
Kai Liu: School of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an 710048, China
Hui Pang: School of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an 710048, China
Jiamin Jin: School of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an 710048, China

Energies, 2021, vol. 14, issue 17, 1-12

Abstract: State of Charge (SOC) is essential for a smart Battery Management System (BMS). Traditional SOC estimation methods of lithium-ion batteries are usually conducted using battery equivalent circuit models (ECMs) and the impact of current sensor bias on SOC estimation is rarely considered. For this reason, this paper proposes an online SOC estimation based on a simplified electrochemical model (EM) for lithium-ion batteries considering sensor bias. In EM-based SOC estimation structure, the errors from the current sensor bias are addressed by proportional–integral observer. Then, the accuracy of the proposed EM-based SOC estimation is validated under different operating conditions. The results indicate that the proposed method has good performance and high accuracy in SOC estimation for lithium-ion batteries, which facilitates the on-board application in advanced BMS.

Keywords: lithium-ion batteries; simplified electrochemical model; state of charge; proportional–integral observer; sensor bias (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: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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