A comparative study of integral order and fractional order models for estimating state-of-charge of lithium-ion battery. (3rd July 2020)

• Record Type: Journal Article
• Authors: Zhang, Yifan; Sun, Tao; Zheng, Yuejiu; Lai, Xin
• Is Part Of: International journal of powertrains. Volume 9:Number 1/2(2020)
• Page Start: 38
• Page End: 58
• Publication Date: 2020-07-03
• Subjects: lithium-ion battery -- fractional order model -- Kalman filter algorithm -- state of charge; Motor vehicles -- Power trains -- Periodicals; 629.25
• Languages: English
• ISSNs: 1742-4267

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.