Joint estimation of model parameters and SOC for lithium-ion batteries in wireless charging systems

Abstract

Accurate prediction of model parameters and state of charge (SOC) is crucial for lithium-ion batteries, especially for those used in wireless charging systems. For example, estimation of the battery model parameters is beneficial to adjust the system operation frequency, improving the system efficiency. In addition, SOC prediction can guarantee the battery safety by preventing the battery from over-charging, and can be used as an indicator for limiting the battery's energy in an optimal range, which is helpful to extend the battery lifespan. This paper presents a joint estimation method for model parameters and SOC of the lithium-ion battery. Battery model parameters are estimated online by recursive least square algorithm with forgetting factor. Based on the online battery model, the battery SOC is predicted using a nonlinear observer algorithm. Validity of the presented method is verified by experiments based on both new and aged lithium-ion battery. Experimental results indicate that the proposed approach can accurately predict the battery SOC with errors less than 0.5%.