Estimation of the Charge State in Lithium-ion Batteries Based on an Adaptive Particle Filter

Abstract

Lithium-ion batteries have the advantages of high energy density, long life, and environmental friendliness, and are widely used as sources of energy in new energy vehicles. The charge state (SOC) of lithium-ion battery greatly represents the remaining service time of the battery, and in electric vehicles, it greatly determines the range of the electric vehicle. Therefore, how to estimate SOC from physical quantities such as end voltage and end current is crucial. This paper introduces the common lithium-ion battery charge state estimation method and its state model, and estimates the charge state based on the adaptive particle filter algorithm.