Title: SOC estimation method of SiO₂ aerogel power battery pack based on improved Kalman filter

Authors: Xueke Li; Yanjie Wu; Yanfen Li

Addresses: School of Automotive Engineering, Huanghe Jiaotong University, Jiaozuo, 454950, China ' School of Automotive Engineering, Huanghe Jiaotong University, Jiaozuo, 454950, China ' School of Automotive Engineering, Huanghe Jiaotong University, Jiaozuo, 454950, China

Abstract: In order to reduce the SOC estimation error of SiO₂ aerogel power battery pack and shorten the estimation time, this study proposes a SOC estimation method of SiO₂ aerogel power battery pack based on improved Kalman filter. This method first describes the working principle of SiO₂ aerogel power battery pack, and analyses the factors that can affect the SOC estimation of the battery, such as charge discharge ratio, aging degree, self-discharge and operating temperature. Then, the first-order RC equivalent circuit is selected as the basic model, and FFRLS technology is used to identify the relevant parameters of the battery to establish a simulation model of battery dynamic changes. Finally, through the improved Kalman filter algorithm, the SOC state of SiO₂ aerogel power battery can be accurately estimated. The experimental results show that this method has lower SOC estimation error, shorter estimation time, and good application performance.

Keywords: Kalman filtering; SiO₂ aerogel power battery pack; SOC estimation.

DOI: 10.1504/IJMMP.2024.142801

International Journal of Microstructure and Materials Properties, 2024 Vol.17 No.4, pp.349 - 363

Received: 18 Aug 2023
Accepted: 07 Feb 2024
Published online: 22 Nov 2024 *

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