A Novel Methodology for Estimating State-Of-Charge of Li-Ion Batteries Using Advanced Parameters Estimation

Ibrahim M. Safwat, Weilin Li and Xiaohua Wu
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Ibrahim M. Safwat: Electrical Engineering Department, Northwestern Polytechnical University, Xi’an 710065, China
Weilin Li: Electrical Engineering Department, Northwestern Polytechnical University, Xi’an 710065, China
Xiaohua Wu: Electrical Engineering Department, Northwestern Polytechnical University, Xi’an 710065, China

Energies, 2017, vol. 10, issue 11, 1-16

Abstract: State-of-charge (SOC) estimations of Li-ion batteries have been the focus of many research studies in previous years. Many articles discussed the dynamic model’s parameters estimation of the Li-ion battery, where the fixed forgetting factor recursive least square estimation methodology is employed. However, the change rate of each parameter to reach the true value is not taken into consideration, which may tend to poor estimation. This article discusses this issue, and proposes two solutions to solve it. The first solution is the usage of a variable forgetting factor instead of a fixed one, while the second solution is defining a vector of forgetting factors, which means one factor for each parameter. After parameters estimation, a new idea is proposed to estimate state-of-charge (SOC) of the Li-ion battery based on Newton’s method. Also, the error percentage and computational cost are discussed and compared with that of nonlinear Kalman filters. This methodology is applied on a 36 V 30 A Li-ion pack to validate this idea.

Keywords: dynamic model of Li-ion battery; variable forgetting factor recursive least square (RLS) estimator; multiple forgetting factors RLS estimator; state-of-charge (SOC) estimation using Newton’s method (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: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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