Title: A comparative study of integral order and fractional order models for estimating state-of-charge of lithium-ion battery

Authors: Yifan Zhang; Tao Sun; Yuejiu Zheng; Xin Lai

Addresses: School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China ' School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China ' School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China ' School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China

Abstract: Battery state estimation is a key technology for battery management systems for electric vehicles, and state-of-charge (SOC) estimation of battery is the basis for numerous state estimations. In this paper, five fractional order equivalent circuit models are compared and evaluated based on a LiNMC cell. First of all, the particle swarm optimisation (PSO) is used to identify the parameters of the fractional order models, and the fractional Kalman filter algorithm is further adopted to estimate the SOC and compared with the SOC estimation obtained by the integral order models. The results indicate that the fractional battery model has higher accuracy, especially in the low SOC interval. Through comparative analysis of several fractional order models, it is found that the fractional order model with the Warburg component can be better describe the battery characteristics in the low SOC interval. From the perspective of model accuracy and computational cost, the addition of the Warburg element to the fractional second-order RC model is the best choice.

Keywords: lithium-ion battery; fractional order model; Kalman filter algorithm; state of charge.

DOI: 10.1504/IJPT.2020.108409

International Journal of Powertrains, 2020 Vol.9 No.1/2, pp.38 - 58

Received: 13 Jun 2018
Accepted: 12 Apr 2019
Published online: 13 Jul 2020 *

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