Article Details

Abstract

Nowadays, with the increase in energy consumption and demand, batteries are increasingly used as energy storage units for various devices. Therefore, accurately estimating the State of Charge (SOC) of each individual battery within a lithium-ion battery pack is a core part of the battery management system. This paper uses the Adaptive Genetic Algorithm (AGA) to identify the parameters of the fractional-order model. On this basis, the particle filter algorithm is applied to significantly improve the estimation accuracy of the SOC of lithium-ion power batteries, which provides important practical value for the power battery management system.

Keywords

battery fractional order model; AGA; particle filter; battery SOC

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About the authors

Liu Yiqi (1996-), male, Han ethnicity, from Xi'an, Shaanxi Province, assistant engineer, master's degree, research direction: battery health status prediction.