Lithium-ion Battery Modeling and Parameter Identification Based on Decentralized Least Squares Method

doi:10.3901/JME.2019.20.085

Abstract

Abstract: An accurate lithium-ion battery model is of critical importance for the estimation of the battery states, and the simulation, design and optimization of electric vehicles(EVs). Low accuracy of model parameters and poor modeling performance occur when the conventional recursive least squares method(RLS) is used to estimate model parameters of lithium-ion batteries which show the multi-time scale characteristics. Therefore, a decentralized least squares method(DLS) is proposed and used to identify model parameters of the second-order RC equivalent circuit. The underlying principle of the proposed method is estimating model parameters of two sub-models separately by using the information that different time scales of batteries can be separated, and the estimated parameters can be obtained accurately because of the elimination of the mutual interference. The experimental results under UDDS and FUDS tests show that compared to RLS, the mean absolute error and the root mean square error of the proposed method can be reduced by about 50.0% and 28.57%, 46.43% and 29.17%, respectively. The effectiveness and feasibility of the proposed method are validated.

Key words: lithium-ion battery, parameter identification, decentralized least squares, time scale, equivalent circuit model

CLC Number:

TM912

ZHU Rui, DUAN Bin, WEN Fazheng, ZHANG Junming, ZHANG Chenghui. Lithium-ion Battery Modeling and Parameter Identification Based on Decentralized Least Squares Method[J]. Journal of Mechanical Engineering, 2019, 55(20): 85-93.

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