SOC estimation of retired lithium-ion batteries for electric vehicle with improved particle filter by H-infinity filter

Abstract

The echelon utilization of retired lithium-ion battery with remaining capacity of 80%, is considered as one of the most promising ways to reduce battery cost by extending their service life. The accurate state of charge (SOC) estimation for retired lithium-ion batteries is of great significance for less-stressful demanding applications. The H-infinity filter (HIF) is widely used to identify the battery model parameters and correspondingly to estimate the SOC online assisted with the Thevenin model. But the estimation accuracy cannot be ensured due to the overly simple algorithm structure. In this paper, H-infinity particle filter (HIPF) is proposed to further improve the SOC estimation accuracy. It is a particle filter (PF) improved by HIF and can suppress the particle depletion during the execution of the standard particle filter. HIPF estimated the SOC after the weights of particles were compromised. The joint estimation of model parameters by HIF and the SOC by HIPF was simulated to verify the model accuracy. In the experiment, the retired lithium–iron phosphate battery in BAIC EV150 vehicle was tested under FUDS cycle and DST cycle. The verification result shows that the mean error of the estimated SOC by HIPF is 0.63% in FUDS cycle and 0.59% in DST cycle. And in FUDS cycle and DST cycle, respectively, the proposed method’s SOC estimation accuracy was increased by 65% and 63% compared with when particle weights were not compromised.

Keywords

• Electric vehicle
• Battery state estimation
• Retired lithium-ion battery
• H-infinity filter
• Particles’ weights compromised