Noise-Immune Model Identification and State of Charge Estimation for Lithium-Ion Battery Using Bilinear Parameterization

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Author(s)

  • Zhongbao Wei
  • Guangzhong Dong
  • Xinan Zhang
  • Josep Pou
  • Zhongyi Quan
  • And 1 others
  • Hongwen He

Detail(s)

Original languageEnglish
Pages (from-to)312-323
Journal / PublicationIEEE Transactions on Industrial Electronics
Volume68
Issue number1
Online published7 Jan 2020
Publication statusPublished - Jan 2021
Externally publishedYes

Abstract

Accurate estimation of state of charge (SOC) is critical to the safe and efficient utilization of battery system. Model-based SOC observers have been widely used due to their high accuracy and robustness, but they rely on a well parameterized battery model. This paper scrutinizes the effect of measurement noises on model parameter identification and SOC estimation. A novel parameterization method combining instrumental variable (IV) estimation and bilinear principle is proposed to compensate for the noise-induced biases of model identification. Specifically, the IV estimator is used to reformulate an overdetermined system so as to allow co-estimating the model parameters and noise variances. The co-estimation problem is then decoupled into two linear sub-problems which are solved efficiently by a two-stage least squares algorithm in a recursive manner. The parameterization method is further combined with a Luenberger observer to estimate the SOC in real time. Simulations and experiments are performed to validate the proposed method. Results reveal that the proposed method is superior to existing method in terms of the immunity to noise corruption.

Research Area(s)

  • battery management, bias compensation, Model identification, noise, state of charge

Citation Format(s)

Noise-Immune Model Identification and State of Charge Estimation for Lithium-Ion Battery Using Bilinear Parameterization. / Wei, Zhongbao; Dong, Guangzhong; Zhang, Xinan; Pou, Josep; Quan, Zhongyi; He, Hongwen.

In: IEEE Transactions on Industrial Electronics, Vol. 68, No. 1, 01.2021, p. 312-323.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review